Assessment of gas detection strategies for offshore HVAC ducts based on CFD modelling

Transcription

1 Health and Safety Executive Assessment of gas detection strategies for offshore HVAC ducts based on CFD modelling Prepared by the Health and Safety Laboratory for the Health and Safety Executive 2007 RR602 Research Report

2 Health and Safety Executive Assessment of gas detection strategies for offshore HVAC ducts based on CFD modelling Dr C J Lea & Dr M Deevy Health and Safety Laboratory Harpur Hill Buxton SK17 9JN The aim of this study has been to undertake CFD modelling to provide a basis for advice to inspectors and the industry on the effectiveness of flammable gas detection strategies for offshore HVAC ducts. CFD simulations of a high and low pressure gas release have been undertaken for idealised representations of an offshore platform, as well as a high pressure release for a more realistic geometry based on the Brae Alpha platform. In parallel with this modelling work a literature review has been carried out to build on a scoping study by Walsh et al (2005). This report and the work it describes were funded by the Health and Safety Executive (HSE). Its contents, including any opinions and/or conclusions expressed, are those of the author alone and do not necessarily reflect HSE policy. HSE Books

3 Crown copyright 2007 First published 2007 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means (electronic, mechanical, photocopying, recording or otherwise) without the prior written permission of the copyright owner. Applications for reproduction should be made in writing to: Licensing Division, Her Majesty s Stationery Office, St Clements House, 2-16 Colegate, Norwich NR3 1BQ or by to [email protected] Acknowledgements The authors would like to thank Marathon Oil UK Ltd, Flamgard Engineering Ltd, Integrated Engineering Services Ltd, Groveley Detection Ltd and Honeywell Analytics for providing information and assistance during the course of this project. Dr Peter Walsh, HSL, has also provided helpful guidance. ii

4 CONTENTS 1 INTRODUCTION 1 2 FLOW AND DISPERSION OF GAS IN A DUCT Turbulent flow in pipes and ducts Dispersion in pipes and ducts Summary 8 3 INGESTION OF GAS INTO HVAC INLETS Introduction Scenario Scenario DISTRIBUTION OF GAS INSIDE AN HVAC DUCT Overview Results 33 5 GAS RELEASE AND INGESTION INTO HVAC DUCTS FOR A 37 REALISTIC SCENARIO 5.1 Introduction Model geometry and computational domain Boundary conditions and flow physics Mesh, solution numerics and convergence Results 45 6 DISCUSSION Review and discussion of results Initial recommendations for gas detection strategies in HVAC ducts 56 7 CONCLUSIONS Recommendations for further work 59 8 APPENDIX 1: EXAMPLES OF COEFFICIENT OF VARIATION 60 9 REFERENCES 61 iii

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6 EXECUTIVE SUMMARY Objectives The aim of this study has been to undertake CFD modelling to provide a basis for advice to inspectors and the industry on the effectiveness of flammable gas detection strategies for offshore HVAC ducts. CFD simulations of a high and low pressure gas release have been undertaken for idealised representations of an offshore platform, as well as a high pressure release for a more realistic geometry based on the Brae Alpha platform. In parallel with this modelling work a literature review has been carried out to build on a scoping study by Walsh et al (2005). Main Findings The most significant finding is that in all of the CFD simulations the distribution of gas at HVAC inlets is non-uniform: large variations in gas concentration are present over the crosssection of the modelled HVAC inlets. This result is consistent with the theoretical behaviour of a high pressure gas release. Neither is there a substantial reason to believe that it is not also consistent with the behaviour of a low pressure gas release. It means that there is the potential for a gas release to be missed by detection systems unless this non-uniformity in gas concentration is anticipated in the selection and siting of gas detectors at HVAC inlets. The CFD results also show that a variation in gas concentration over a duct cross-section only reduces slowly with distance along a straight duct. This finding is consistent with a body of relevant literature stemming from the sampling of gas distributions in the exhaust ducts of nuclear stacks. This literature highlights that purpose-designed mixing elements and bends in a duct can be effective in creating well-mixed conditions in a duct, but at the cost of increased pressure drop. It also suggests that relatively small-scale obstructions such as louvres and fire dampers are unlikely to significantly enhance mixing. This is borne out by CFD modelling of such obstructions in this study. The implications of the modelling work, substantiated by the literature, are that in the absence of purpose-designed mixing elements or a series of bends upstream from gas detectors no significant benefit would be gained from siting detectors a significant distance downstream from an HVAC inlet. Also, no significant benefit can be expected to be gained from siting detectors inside an HVAC duct compared to locating them immediately outside the HVAC inlet. The CFD results have been post-processed to gain further insight into the likely effectiveness of point and infra-red beam or aspirated detector systems for HVAC ducts. The resulting output has been combined with the findings of the scoping study by Walsh et al (2005), and the outcomes of the literature review and CFD modelling as reported above, to provide a basis for the following initial recommendations on flammable gas detection strategies: x Detector alarm levels should be set as low as reasonably practical: 10% LEL or less. x Point catalytic, point infra-red, extended path point infra-red, cross-duct beam infra-red and aspirated point detector systems all have the potential to be effective in detecting non-uniform distributions of flammable gas in and around HVAC ducts provided that their sensitivity is sufficiently high (low detection limit) and that due regard is given to the possibility that gas will be distributed non-uniformly. v

7 x Extended path point infra-red detector systems currently appear to offer the greatest sensitivity, but multiple detectors should be used and sited so as to anticipate nonuniform mixing. x Cross-duct beam infra-red, extended path or aspirated point detector systems should be based on two approximately orthogonal beams or lines of aspirated point probes. x No significant benefit can be expected to be gained from siting detectors inside an HVAC duct compared to locating them immediately outside the HVAC inlet. x In the absence of purpose-designed mixing elements or a series of bends upstream from gas detectors no significant benefit is to be gained from siting detectors a significant distance downstream from an HVAC inlet. x Mixing elements have the potential to reduce any non-uniformity in the distribution of gas in a duct but their effectiveness should be proven by physical tests. Recommendations It is recommended that large-scale physical tests using commercial detectors are undertaken to validate the findings of this study and to support and refine the initial recommendations above. It is also recommended that the minimum practical alarm levels for a range of commercial detector types, especially cross-duct beam infra-red systems, are clarified. Reference Walsh P, Johnson A, Ivings M (2005) Effectiveness of gas detection in HVAC ducts: Scoping study. Health and Safety Laboratory Report FM/04/11. vi

8 1 INTRODUCTION The accidental release of flammable gas on offshore installations can potentially lead to the build-up of an explosive mixture. Natural or forced ventilation can help to mitigate such incidents and gas detection systems play a key role in reducing the risks from releases by enabling early detection and subsequent interventions. The provision and siting of gas detectors for open areas and gas turbine enclosures has been studied over a number of years and is comparatively well documented (HSE 1993, Kelsey et al 2000, Ivings et al 2002, HSE 2003, Kelsey et al 2005). However there is much less information available on gas detection systems for HVAC ducts supplying air to accommodation modules, temporary refuges or process areas on an installation. The information which is available on offshore HVAC ducts tends to address other aspects such as mechanical design with minimal information on gas detection systems (BS EN ISO 15138:2001, Chin & Lam 2004). Following an incident on the Brae Alpha platform in November 2004 in which there was a delay in confirmed detection and shutdown of the HVAC system, despite gas being ingested into the HVAC inlets, it became clear that there was a need for a study to establish the current state of the art. This led to the initiation of the scoping study by Walsh et al (2005) into the effectiveness of gas detection systems for HVAC ducts on offshore installations. This was carried out in response to concerns raised by HSE offshore safety inspectors on the positioning of flammable gas detectors in or around HVAC inlets. Walsh et al (2005) reviewed national standards, industry guidance, published papers and reports to obtain information on the siting of flammable gas detection systems for offshore HVAC inlets. Some industry guidance was obtained on performance targets for HVAC gas detection systems specific to a particular platform, stating that flammable gas at concentrations above 20% LEL (Lower Explosive Limit) at ventilation intake ducts should lead to an alarm and that concentrations above 60% should lead to isolation of the intake by stopping fans and closing dampers (Micropack, 2000). Other industry guidance advised that either point or beam detectors may be installed inside or outside of HVAC ducts and that for point detectors three should normally be installed to maintain voting logic (Shell UK, 1995). Guidance has also been obtained from a gas detector company advising on the appropriate proximity of point detectors to features such as bends or diffusers in gas turbine ductwork. Walsh et al (2005) surveyed commercial gas detector systems for HVAC applications. They found that a number of differing systems are available: point catalytic, point infra-red, beam infra-red or aspirated systems. In general the operating range of such systems was found to be up to 100% LEL, with a minimum alarm level of 20% LEL. However, Walsh et al noted that recent developments in HVAC gas detection technology have led to the availability of extended closed path infrared point detectors which measure an average concentration over a path length of typically around 1 m. Such systems have increased sensitivity and typically allow for minimum alarm levels of 5% LEL. Recent developments in catalytic point sensors for the industrial gas turbine industry also apparently allow for minimum alarm levels of 5% LEL. However, Walsh et al (2005) found essentially no guidance specific to the siting of gas detectors in and around HVAC inlets or on the effectiveness of differing siting strategies. They recommended that further work be undertaken to remedy this situation. In consultation with the Offshore Safety Division (OSD) in HSE they proposed that this further work should initially be based on Computational Fluid Dynamics (CFD) modelling, recognising that CFD can guide any potential future experimental work by helping identify effective and ineffective gas detection systems. This provides the basis and motivation for the project which is documented in the present report. 1

9 The overall aim of this project is therefore to apply CFD modelling to provide a basis for advice to inspectors and the industry on the effectiveness of flammable gas detection strategies for offshore HVAC ducts. It builds upon the scoping study of Walsh et al (2005). The primary focus of the project is on siting strategies for gas detectors located in or around HVAC inlets for circumstances in which gas is not ingested uniformly over the entire inlet. The present project and the earlier scoping study have both been funded by OSD. In Section 2 of this report the behaviour of flow and dispersion of gas in a duct is discussed. This discussion is supported by a literature review that encompasses sources of information which compliment that from the field of gas detection in offshore HVAC ducts. Section 3 addresses circumstances by which a non-uniform distribution of gas could be present immediately outside or inside of an HVAC inlet. This is of particular relevance to the present project. Thus, if a well-mixed and uniform distribution of gas and air is present then the positioning of detectors should have little impact on the performance of a system in detecting gas; instead the performance will be governed by other factors such as the sensitivity, speed of response and reliability of the detector. Such information is available from gas detector companies supported by experience of use. Therefore in this section the outcome of CFD modelling of gas releases is presented for two differing idealised scenarios showing how a nonuniform distribution of gas and air may be present in and around an HVAC inlet. Section 4 reports the mixing and distribution of gas inside an HVAC duct as simulated using CFD. The modelling extends that presented in Section 3 by focusing on the detail of the geometry and associated flow features likely to be found in an actual HVAC inlet. Section 5 presents CFD results for a more realistic scenario based on the release from the Brae Alpha platform in November Although the most significant elements of this incident are represented, the scenario is not a detailed replication of the incident; this would be very timeconsuming to undertake and may not be practical. The value of these results instead lies in the more general lessons which they provide on the behaviour of a release in a complex geometrical environment and which is subsequently ingested into HVAC ducts of varying size. The results from the CFD modelling are discussed in Section 6. Their implications for gas detection strategies for HVAC ducts are highlighted. Initial recommendations on the effective siting of flammable gas detectors in and around HVAC inlets are also provided. Conclusions and recommendations for further experimentally-based work are given in Section 7. Appendix 1 provides illustrative values of a parameter which can be used to characterise the degree of mixing in a duct. References are provided in Section 9. All of the CFD modelling has been undertaken using ANSYS CFX 10, a commercial software package. 2

10 2 FLOW AND DISPERSION OF GAS IN A DUCT 2.1 TURBULENT FLOW IN PIPES AND DUCTS An introduction to the flow regime in HVAC ducts is provided by Walsh et al (2005). They show that for offshore HVAC ducts the Reynolds number will be sufficiently high that the flow will be fully turbulent. This is based on a typical duct velocity of 5 m/s as outlined in BS EN ISO and a range of duct hydraulic diameters from 0.5 to 5 m, giving Reynolds numbers 6 in the range of approximately 10 5 to 10. Turbulence is often assumed to be synonymous with good mixing. Although this is generally the case, turbulent mixing does not occur instantaneously. It would be wrong to assume that because the flow in HVAC ducts is turbulent any non-uniformity in a distribution of gas at an HVAC inlet will very quickly be dispersed to give well-mixed uniform conditions. This has a significant impact on the siting of gas detectors in HVAC ducts. An indication that this is the case is given by experimental data on turbulent developing flow in a pipe. Sufficiently far downstream from the entrance to a long straight pipe the flow eventually reaches a condition in which it no longer changes. It is then said to be fully-developed. For turbulent flow in a smooth pipe the fully-developed mean velocity profile approximately follows a 1/n power law (Hinze, 1975): 1 / n U 2x U d ¹ max where U is the velocity at distance x from the wall of a pipe of diameter d and U max is the peak 5 velocity on the axis of the pipe. The constant, n, is 7 for a Reynolds number of 10 and approximately 9 for a Reynolds number of For rough pipes, n increases to between 4 and 5. The turbulent mean velocity profile is therefore rather flat across much of the cross-section of a pipe, dropping away steeply at the walls. Turbulent flow in a pipe is therefore often characterised as consisting of a relatively thin near-wall region and a central core. The distance before fully-developed conditions are established in a pipe is known as the development length. The development length depends on a number of factors: the Reynolds number, geometry of the inlet and flow conditions upstream of the inlet. For flow from quiescent surroundings into a straight pipe with rounded edges at its inlet the development length for fully-developed turbulent flow is given by White (1987): L e d 4.4Re 1/ 6 where L e is the development length and d is the pipe diameter. The development length is 6 approximately 30 d to 40 d for Reynolds numbers in the range of interest, i.e to 10. For laminar flow (Reynolds number below about 2000 to 4000) the development lengths are much greater. The above expression applies to idealised conditions in which the flow is from quiescent surroundings and the pipe is straight and rounded at its inlet. In these circumstances the flow which enters the pipe is initially uniform and laminar. A laminar boundary layer grows on the surface of the pipe and then rapidly becomes turbulent. The turbulent boundary layer grows in 3

11 thickness until eventually it extends to the axis of the pipe. Fully-developed flow conditions are reached shortly afterwards. Klein (1981) correlates data on developing flow in pipes from a range of sources, which include sharp-edged inlets. These data show that fully-developed flow is not established until greater than about 50 d downstream from the inlet. Other workers (Laws et al, 1979) have indicated that in the presence of significant obstructions at the inlet to a pipe, fully-developed flow is not established until significantly further downstream, possibly greater than 100 d. It should be noted that these studies are seeking flow profiles which are exactly the same with distance from the pipe inlet and so are rather rigorous in their requirements. As a practical rule of thumb Hinze (1975) recommends that turbulent fully developed flow can be assumed to occur in straight pipes after a minimum development length of 40 d. The turbulent developing flow in a straight square or rectangular duct behaves in a broadly similar manner, in that the distance to fully-developed flow is not short. Melling & Whitelaw (1976) present data which show that turbulent fully-developed flow in a square duct is reached at about 25 duct widths from the inlet. Other measurements, by Gessner et al (1977), show that fully-developed flow is not reached until much further downstream, at between 40 to 84 duct widths downstream from a rounded inlet. The development of the flow occurs in much the same manner as that for a circular pipe, with the gradual growth of boundary layers on the duct walls until they occupy the entire section of the duct. There is a further feature of flow in straight square or rectangular ducts which should be mentioned. This is the existence of a turbulence-driven secondary flow in the cross-stream direction. The secondary flow is of a very much smaller magnitude than the primary flow along the axis of the duct (Demuren & Rodi, 1984). Its effect is to slowly transport material from the centre of the duct towards the walls and back again. Overall this leads to an enhancement in turbulent mixing. This secondary flow presents a difficulty for CFD models. Simulations based on the commonlyused k-h turbulence model (Launder & Spalding, 1972) completely fail to capture this secondary flow (Speziale, 1996). More advanced turbulence models are available (Gatski & Speziale 1993, Gatski & Rumsey 2002) which do capture the secondary flow but they often tend to be more problematic to apply and require more computational resources. However, the secondary flow is not fully established immediately the flow enters a duct; in fact it is only completely established when fully developed conditions are met far downstream. In practice, offshore gas detectors for HVAC ducts are nearly always located close to the inlets. This is partly to minimise the volume of gas ingested following action to isolate an HVAC system upon detection of gas, and partly to provide access for maintenance and calibration. Therefore, although a standard k-h turbulence model cannot capture these secondary flows, the resulting error is unlikely to be significant in the few duct widths immediately downstream from an HVAC inlet, i.e. the region in which gas detectors are commonly found. The literature on developing and fully-developed flow in pipes and ducts gives a useful indication that equilibrium in the turbulent diffusion of momentum responsible for the creation of fully-developed flow profiles only occurs at a considerable distance downstream from the inlet to a straight pipe or duct. Of course, the offshore environment is somewhat different from the idealised experiments upon which this literature is based: offshore HVAC inlets do not have rounded edges; often they are sharp-edged and have obstructions such as grilles or weather louvres across their entire face. Figure 1 shows some examples of such features. 4

12 Figure 1: Examples of HVAC inlets Usually, dampers will be encountered a short distance inside an HVAC duct; to provide isolation from fire and gas in the event of an incident. The dampers will normally be open and parallel to the main flow direction, but they still present an obstruction to the flow, as does their supporting structure. Overall, the gross effect of obstructions such as grilles, louvres and dampers will be to generate turbulence which will lead to enhanced mixing. 2.2 DISPERSION IN PIPES AND DUCTS The above discussion has concentrated on the characteristics of turbulent flow in straight pipes and ducts. Our main interest is in the turbulent transfer of mass, or more specifically, in the turbulent diffusion of a contaminant such as natural gas at a relatively low concentration. It should be noted that at low concentrations in the flammable range and for the velocities typically encountered in offshore HVAC ducts, a natural gas mixture can be regarded as a passive contaminant, i.e. it is transported by, but does not directly influence the flow. This is because the Richardson number (Simpson, 1997) is likely to be at least an order of magnitude too low for any turbulence-modifying effects of a slightly buoyant gas to dominate over shearinduced turbulence. The turbulent diffusion of a contaminant which is essentially passive takes place in an analogous manner to that of the turbulent diffusion of momentum. Both are the result of the same turbulent flow-field. It can therefore be expected that the dispersion of a passive contaminant in a duct will follow roughly the same behaviour as that of the development of the velocity profile: if the development length is long then the distance to uniformly mixed conditions will also be long. A review of the literature was undertaken to obtain more information on the development of an initially non-uniform distribution of passive gas in a duct or pipe, in the presence or absence of obstructions. Initially this review focused on a search for papers in the field of gas dispersion, or detection, in ducts or HVAC systems. This produced little useful information on the distribution and mixing of gas in ducts. A search for papers in the field of sampling, rather than detection or dispersion, proved much more fruitful. Hence a number of papers were obtained on the sampling of exhaust duct stacks in the nuclear industry (Hampl et al 1986, Rodgers et al 1996, McFarland et al 1999a & 1999b, Anand et al 2003 and Seo et al 2006). These papers report research into the mixing of a passive tracer in circular, square and rectangular ducts in the presence or absence of bends and mixing elements. 5

13 In most cases the tracer was released from a single location on the axis of a duct. Multiple point concentration measurements were then made across the entire cross-section of the duct at a number of axial locations. This body of research was largely undertaken to support an improvement and updating of American standards on the sampling of gaseous radionuclide emissions from stacks. Sampling had historically been required at multiple points over the cross-section of a duct, with as many as 20 points being required for large ducts (Rodgers et al, 1996) to ensure that peaks in the concentration distribution were not missed. The sample plane was required to be no closer than eight duct diameters from the nearest upstream flow disturbance and two duct diameters from the nearest downstream disturbance. However, Hampl (1986) suggested that up to 50 duct diameters may be needed for near-uniform mixing of a passive tracer in a straight pipe, but less than two duct diameters for acceptable mixing downstream of two elbows. Proposals for a new approach were therefore made, based on a single point sample taken at a location where acceptable well-mixed conditions could be assured. To characterise the degree of mixing, a parameter known as the Coefficient of Variation (COV) was introduced. This is defined as: COV 1 N N ( C i C mean 1 i 1 C mean ) 2 where N is the number of samples at a particular downstream location, C i is the concentration of the ith sample and C mean is the mean concentration over all samples at that location, defined as: 1 N C C mean N i 1 i As an example, if the concentration distribution is such that across one half of a duct the concentration is a uniform 30% LEL whilst across the other half the concentration is a uniform 10% LEL, then the COV would be 50%. Appendix 1 provides examples of concentration distributions for a range of COV between 10% and 150%. The updated American standards (ANSI/HPS N ) allow for single point sampling of gaseous contaminants in a duct if the COV for both velocity and concentration of a tracer gas are less than 20% over the central two-thirds of a duct. We do not suggest or comment on the practicality or appropriateness of these criteria for offshore HVAC ducts. However, the notion of a COV is helpful in quantifying the uniformity of mixing in a duct: it is readily computed from CFD results. In addition, this body of research on stack sampling provides much useful data on how the COV is affected by a range of configurations; this can be used to inform the present research. Thus McFarland et al (1999a) showed that for a tracer released at a single point on the axis of a duct the COV can readily be reduced to ~5% following passage through a compact mixing chamber installed in the path of a duct. However, the pressure loss for this mixing chamber was not small (non-dimensional pressure coefficient of approximately 4.5, equivalent to a head loss of about 70 Pa for an average velocity of 5 m/s) and, more significantly, it would require reengineering of existing HVAC installations. Measurements of the COV in straight circular pipes by Anand et al (2003) show that the distance from a point release of a tracer to that at which the COV is less than 20% depends on the upstream turbulence intensity. For a low turbulence intensity of 1.5% the COV falls very slowly with distance and is still over 100% at 30 duct diameters downstream from the point of 6

14 release. Even with a high turbulence intensity of 10% - generated by passing the flow through an array of thick rods a COV of 20% was still not reached after 25 duct diameters downstream. McFarland et al (1999b) investigated the effect of bends and static mixing elements on the COV. They show that a single smooth 90 o bend in a circular duct still requires a distance of nine diameters downstream from the bend before the 20% COV criterion is met. The performance of the static mixing elements was very variable: all resulted in the 20% COV criterion being met within nine diameters downstream, but the most effective mixers were able to meet the criterion within three duct diameters of the mixing element. The most simple and effective mixing elements consisted of two large flow deflectors attached to opposite walls of a duct, leading to a slot-like opening in the centre of the duct. Two or more of these mixing elements were used in series. The common characteristic of the most effective mixing elements appears to be the introduction of cross-stream mixing from one side of a duct to another due to the introduction of large turbulent eddies (Seo et al, 2006). Mixing elements which only introduced flow swirl were less effective. One disadvantage of these simple deflector mixing elements is a relatively large non-dimensional pressure coefficient (5.0) for two elements in series. Seo et al (2006) examine the behaviour of the COV in square and rectangular ducts (aspect ratio of 3:1) with and without bends. They report that the COV is similar for circular and squaresection ducts at large distances downstream from the tracer release point, both with and without bends. This implies that the main findings of the previous work on circular-section ducts, discussed above, are likely to largely carry over to square-section ducts. However, a significant difference was found when the COV for the square and rectangular-section ducts were compared: typically the COV was much higher for the rectangular duct at any given distance downstream from the point of release, by about a factor of four. The COV for rectangular ducts with bends are also consistently higher than the same flow configuration in a square duct. Seo et al speculate that this is because turbulent eddies in a wide duct have less opportunity to effectively transfer mass and momentum from one side of a duct to another. The effect of grilles on the turbulence in a duct is relatively well understood. Laws & Livesey (1978) explain that the effect is either to suppress, or enhance turbulence, and this depends on the geometry of the grille. Thus a very fine grille, or mesh, will tend to suppress turbulence. Any turbulence which is introduced by the mesh decays quickly due to its small scale. A grid of relatively large diameter rods will enhance turbulence, although Laws & Livesey state that it is difficult to achieve a turbulence intensity of much higher than 10%. It is not clear whether grilles typically used to cover HVAC inlets will suppress or enhance turbulence. However, even if turbulence is significantly enhanced, Anand et al (2003) show that the COV will remain high for long distances downstream. For an inlet turbulence intensity of 10% created by an array of rods they found that the COV was still over 50% at 15 duct diameters downstream from the rod array. The reason for the relative ineffectiveness of such devices on mixing is that they introduce turbulence on too small a length-scale. Much of the above work is based on a flow which is well-controlled at the inlet to a duct, for example by use of a rounded entrance or other flow control devices. In the case of offshore HVAC installations this will not be the case: turbulence can be generated by large-scale flow separation at the sharp-edged entrance to a duct or is already present in the ambient flow outside of the duct. McFarland et al (1999b) note that the earlier work of Hampl et al (1986) was based on a sharp-edged inlet and in comparison to their later research with a well-controlled approach flow the COV were found to be reduced by between a factor of two to three: flow separation at the inlet enhances mixing inside a duct. Nevertheless, it should be recalled that Hampl et al still suggest that up to 50 duct diameters may be needed for near-uniform mixing of a passive tracer in a straight pipe, even with a sharp-edged inlet. It is difficult to know to what extent the effect 7

15 of turbulence which is present in the ambient flow affects the mixing inside a duct. However, the gross effects of pre-existing turbulence in the outside ambient flow on mixing in a duct should be represented, albeit crudely, by the CFD modelling which follows in Sections 3, 4, and 5. It is also significant that both Anand et al (2003) and Seo et al (2006) note that the COV is littleaffected by the Reynolds number. Seo et al state that for a square duct there is only a small effect of the Reynolds number on COV over a range from 25,000 to 150,000. For a rectangular duct with a 3:1 aspect ratio there is a significant dependence on the COV for a Reynolds number below 50,000, but relatively little effect at higher Reynolds number. Both Anand et al (2003) and Seo et al (2006) conclude that, for fully turbulent flow, mixing is primarily dependent on geometry. 2.3 SUMMARY The main findings of relevance to the present project from the above literature review are as follows: x The Reynolds number for offshore HVAC ducts is sufficiently high that the flow will be fully turbulent. x A flow development region exists downstream from the inlet to a duct; in the absence of obstructions and for a smoothly rounded inlet the length of this region can be assumed to be a minimum of 40 duct diameters for a straight duct whereupon the flow is said to be fully-developed and does not change further downstream. x In the development region the flow may not be turbulent across the entire section of a duct: in this region it is more likely to be turbulent in the presence of a sharp-edged entrance to the duct and where the duct contains obstructions such as louvres. x A weak secondary flow exists in square and rectangular ducts which will enhance mixing. In CFD modelling this secondary flow is not captured by the most commonlyused k-h turbulence model. However, the secondary flow is not completely established until the flow is fully developed, so associated errors from use of the k-h model are unlikely to be significant close to an HVAC inlet. x A natural gas mixture which is ingested into offshore HVAC ducts at concentrations in the flammable range can generally be treated as a passive contaminant. x The turbulent diffusion of a passive contaminant in a duct will take place in a broadly analogous manner to that of the turbulent diffusion of momentum; long development lengths imply similarly long distances before well-mixed conditions are obtained. x The degree of mixing in a duct can be quantified by a Coefficient of Variation, COV. x Uniform mixing of a point release of a passive tracer in a duct typically requires 50 duct diameters downstream from the release for a straight circular duct. The presence of bends and mixing elements can significantly reduce this distance. x The turbulent mixing in a rectangular duct with a large aspect ratio (3:1 and above) is significantly less effective than that in a square or circular duct. x Effective mixing in a duct is driven by large-scale turbulent eddies which are able to transfer mass and momentum across the duct. x The most effective mixing elements are those which introduce large turbulent eddies. x Grilles at the entrance to HVAC ducts are likely to be ineffective in introducing largescale turbulent eddies and so will do little to enhance mixing. x For fully turbulent flow, mixing in a duct is primarily dependent on geometry. 8

16 3 INGESTION OF GAS INTO HVAC INLETS 3.1 INTRODUCTION The circumstances by which a non-uniform distribution of gas could be present immediately inside or outside of an HVAC inlet are of particular interest in the present project. If an HVAC inlet ingests a non-uniform distribution of gas then there is the possibility that this could be missed by the detection system. To understand how it might be possible that a non-uniform distribution of gas could be present at an HVAC inlet, it is useful to briefly examine the characteristics of a gas jet. For simplicity we examine a free round jet, although in practice a release is likely to be more complex. Nevertheless, this simple case does give a broad indication of the flow behaviour which might be expected of some more complex releases. Far downstream from a high pressure release from a round hole, in the region where the Mach number is low enough for the flow to be treated as incompressible (Ma < 0.3), the concentration on the centre-line of the resulting jet is inversely proportional to distance (Rodi, 1982): T m D T o z where T m is the concentration on the centre-line at distance z from a release of diameter D with an initial uniform concentration T R. Far downstream, the concentration varies continuously across the radius of a round jet and can be described by the following function (Rodi, 1982): T T e m r z where T is the concentration at radius r. An example is helpful to indicate the radial variation in concentration which is implied by the expression immediately above. Consider a release of pure methane such that the centre-line concentration of the resulting jet is equal to LEL 10 m downstream from an initial diameter D (to be defined). Concentrations of 100%, 50%, 20% and 10% LEL would be obtained at radii of 0 m, 1.05 m, 1.6 m and 1.9 m. In fact a jet of these dimensions could be expected from a high pressure release of methane at a stagnation pressure and temperature of 100 bar and 40 o C, from a hole of approximately 12 mm diameter, respectively. This is a large, but credible, release. Note that the hole diameter of 12 mm is not D in the expression above. D is the diameter of the jet when it has expanded to atmospheric pressure, 85 mm in this instance - considerably larger than the release hole. The expressions by which this fully expanded diameter has been calculated are given in Section 5. This example shows that for a large, but credible, high pressure jet release the radial concentration at 10 m downstream can vary from a maximum of 100% LEL at the jet centre-line to just 10% LEL at a radius of 1.9 m. This distance, over which concentration varies by a factor of ten, is broadly comparable to the dimensions of typical offshore HVAC inlets. If such a release were ingested into an HVAC inlet, then significant non-uniformity in gas concentration could be expected outside and inside of the HVAC duct. 9

17 In practice a release could be affected by many factors such as the wind flow in and around a module, the presence of obstructions, impingement on nearby objects, etc. The release could also be at lower pressure and more significantly influenced by buoyancy. The effects of these factors, and others, are difficult or impossible to predict from theory alone, but in principle can be captured by CFD modelling. Therefore two scenarios have been simulated using ANSYS CFX 10 to illustrate and examine circumstances in which a non-uniform distribution of gas and air may be ingested into HVAC inlets. The scenarios are idealised but still include many of the complicating factors mentioned above. Scenario 1 is a high pressure release from a riser on the underside of a platform. The release is directed horizontally underneath the platform towards an HVAC duct which faces vertically down and whose inlet protrudes from the underside of the platform. Scenario 2 is a low pressure release from within a module. The release is directed upwards and out of the module to pass up the downstream face of a platform. A horizontal HVAC duct protrudes from this downstream face of the platform and is intersected by the release. Full details of these idealised scenarios, including a description of the CFD modelling and results, are given below 3.2 SCENARIO Model geometry and computational domain The model geometry is shown in Figures 2 and 3. Although it is a very simplified representation of an offshore platform this geometry presents approximately the same obstruction to the approaching wind-field as a real platform, but without the inclusion of any platform-specific geometrical elements such as flare-stacks, helipad, etc. The modelled geometry consists of a cube of side 30 m whose base is located 25 m above sea level. The release is located 3 m below the platform, 6 m inboard from the platform edges, and is initially angled at 30 o across the underside of the platform towards its downstream edge. The release is also oriented at a very shallow angle upwards such that its axis as it exits from the underside of the platform is approximately 2 m below the base of the platform. The location and initial direction of the release are indicated in Figures 2 and 3. A single HVAC duct of external dimensions 3 m x 1.5 m and internal dimensions 2.84 m x 1.34 m is located 4 m from the downstream face of the platform and 12 m from the nearest edge of the platform. The size of the duct was guided by information supplied by Integrated Engineering Services Ltd (specialist designer and supplier of offshore HVAC systems). The axis of the duct is vertical, 20.9 m long and protrudes 2 m below the underside of the platform. The HVAC duct can be seen in Figures 2 and 3. Figure 2: Scenario 1, geometry (HVAC duct in blue, gas release in red) 10

18 a) Plan view b) Vertical elevation Figure 3: Scenario 1, dimensions (m) An extensive region of the atmosphere that surrounds the platform is included in the CFD model. This is to ensure that the simulated flow around the platform is not constrained by the presence of the nearby boundaries of the computational domain. In particular it allows for the presence of large-scale time-dependent flow features to develop naturally as a consequence of flow over the bluff body of the platform. The resulting computational domain is 120 m wide, 11

19 115 m high, 240 m long and is illustrated in Figure 4. It includes the entire length of the HVAC duct. Note that the platform has been oriented at 20 o to the oncoming wind direction. Figure 4: Scenario 1, computational domain Boundary conditions The platform is located in the atmospheric boundary layer. Therefore at the upwind face of the computational domain a neutral stability atmospheric boundary layer profile was prescribed (Hargreaves & Wright, 2007). The wind speed was specified to be 1.5 m/s at 25 m above sea level. Although this is a low wind speed the results show that it is still sufficient to deflect the trajectory of the jet towards the HVAC duct. At the upper boundary of the computational domain a constant shear stress was applied by imposing a boundary velocity equal to that which would be expected at 115 m above sea level. At the downwind and two side boundaries in the atmosphere a condition was applied which allows for flow to leave or enter the domain. At sea level a rough wall boundary condition was applied. The sides, base and top of the platform were also specified as rough walls, with a surface roughness appropriate for corrugated metal (White, 1987). A mass flow rate of 19.2 kg/s was imposed at the upper end of the HVAC duct. This type of boundary condition allows the simulation to calculate an appropriate flow profile, rather than requiring a flow profile to be prescribed. The mass flow rate is equivalent to a uniform velocity of 4 m/s. Simulations have also been undertaken with a mass flow rate which is equivalent to a uniform velocity of 6 m/s and the results are qualitatively very similar. The release was assumed to be from a high pressure riser. Note that the riser is not explicitly included in the model since it will have negligible effect on the flow. In reality a gas release from a high pressure riser will initially be under-expanded and supersonic, i.e. it exhausts from the riser, accelerates to high Mach number then relaxes to atmospheric pressure by expansion through a complex shock structure. It is not practical or necessary to explicitly simulate this phase of a release. Instead, it is appropriate for such a release to be modelled from a location at 12

20 which expansion to atmospheric pressure has occurred and the flow is just sonic (Ivings et al, 2003). This has two advantages: it avoids the need to model the high Mach number region which can be problematic; and the dimension of the jet after expansion is much greater than that of the release hole and so is more readily resolved by the CFD mesh. In this scenario the release is modelled from the point at which expansion to atmospheric pressure has occurred. The release is sized and specified using the expressions in Section 3.1 for a free round jet as a rough guide. In this case the release is fixed at approximately 23 m from the HVAC duct. A peak concentration of 50% LEL was decided upon as a target concentration at this location since this is comparable to current action levels upon detection of gas at 50% to 60% LEL (Walsh et al, 2005). Using the expressions in Section 3.1 implies that after expansion to atmospheric pressure a jet which meets these target conditions should be specified as being 0.1 m in diameter. Note that for a high pressure release this actually corresponds to a much smaller hole size. For example, if the riser pressure and temperature were 100 bar and 40 o C, then the hole size would be approximately 14 mm diameter for a release of 100% methane. Section 5 provides expressions by which this effective hole size can be calculated. The release was therefore modelled as a sonic source of 100% methane over a nominal diameter of 0.1 m. The temperature of gas in the riser was assumed to be 40 o C which gives a sonic velocity of 428 m/s. The release rate is approximately 2.5 kg/s Flow physics The flow over a bluff body such as an offshore platform is known to be inherently transient. Large vortices are typically shed from a bluff body to form an oscillating wake. In fact initial attempts to compute this scenario as steady-state failed to converge. Therefore, all the simulations undertaken and presented in this report are time-dependent. The flow around the platform and in the HVAC duct will be turbulent. The commonly-used k-h turbulence model (Launder & Spalding, 1972) has been used throughout this work. Wall functions were used at all solid boundaries, appropriately modified to account for surface roughness. The physical properties for methane were taken from Santon et al (2002), including its LEL of 4.4% by volume Mesh An unstructured mesh was used to resolve the geometry. The mesh was refined in regions where high gradients of velocity and concentration were expected; across the methane jet, the HVAC inlet and duct. A total of 22 mesh elements were used to resolve the release source. On the walls of the platform four layers of prismatic mesh elements were used to aid resolution of the nearwall flow and help ensure that the first mesh node correctly falls within the log-law region for a turbulent boundary layer. A mesh with a total of 317,000 nodes (control volumes) was generated, constructed from 1.7 million mesh elements. The mesh is illustrated in Figures 5 to 7, overleaf. 13

21 Figure 5: Scenario 1, mesh - vertical elevation coincident with the release Figure 6: Scenario 1, mesh plan view coincident with the release 14

22 Figure 7: Scenario 1, mesh detail near the HVAC inlet Solution numerics and convergence All simulations in this work have been undertaken using high-order-accuracy spatial and temporal discretisation schemes in an effort to reduce numerical errors. Time-dependent simulations were undertaken with a short time-step of 1 s to aid convergence and also to help resolve the main time-dependent flow features. A non-dimensional frequency known as the Strouhal number, S, can be identified for the time-dependent flow over a sharpedged building: S fw /U where f is frequency, W is width in the cross-wind direction and U is mean velocity. For a cube of side 30 m in a 1.5 m/s flow the Strouhal number has a value of approximately 0.1 (Schetz and Fuhs, 1996), giving a frequency of Hz, equivalent to a time-period of 200 s. Hence, a time-step of 1 s is short in comparison to this long time-period. The transient simulation was run until the flow appeared periodic. A total of 1600 time-steps were computed. The residuals for all transport equations decreased by between at least two and usually three orders of magnitude, to very small rms values, and the global imbalances of mass, momentum, energy and gas mass fraction all reduced to very much less than 0.05% of reference values. This indicates that the solution is well-converged. 15

23 3.2.6 Results The flow-field around the platform is shown in Figure 8 for two time-steps separated by 60 s. Although the gross flow is similar consisting of massive flow separation in the wake of the platform the detail of the flow in the wake region is dissimilar. a) time t b) time t + 60 s Figure 8: Scenario 1, velocity field in plan view at mid-height of the platform 16

24 The flow-field in a vertical elevation is shown in Figure 9. Again, the separated region in the wake of the platform can be seen. Figure 9: Scenario 1, velocity field shown on a vertical plane The time-dependent wake flow has a minor effect on the trajectory of the gas jet, but sufficient to affect the concentration distribution at the HVAC inlet and inside the duct. An iso-surface of gas concentration at 50% of LEL is shown at two times in Figures 10 and 11. These times represent the two extreme states in the quasi-periodic time-dependent flow. a) time t b) time t + 60s Figure 10: Scenario 1, iso-surface at 50% LEL, plan view 17

25 a) time t b) time t + 60s Figure 11: Scenario 1, iso-surface at 50% LEL, iso-metric view The very small difference in the trajectory of the jet at these two time-steps can be seen to result in a more significant influence on the flow within the HVAC duct. This is especially evident in Figure 11, in which a more prominent tongue of gas can be seen in the duct at t + 60 s. The full extent of the gas jet is shown in Figure 12, below. Gas concentrations of 10% LEL and above are evident a significant way downstream from the platform. Figure 12: Scenario 1, gas concentration in % LEL, plan view 0.5 m below the HVAC inlet The distribution of gas at 0.5 m below the HVAC inlet, 1 m and 3 m inside the HVAC duct, is shown in Figure 13 at time t and t + 60 s. There is a large gradient in concentration across the duct in each case, with concentration differing by a factor of approximately five or six across the breadth of the duct. However, there is only a small difference in the concentration distribution between planes located immediately outside and inside of the duct. Although gas concentration is somewhat higher in the HVAC duct at time t + 60 s, the overall flow behaviour 18

26 in the duct remains the same for both time-steps. Hence, the results in Figures 14 to 17, which follow below, are all presented at time t. a) time t b) time t + 60s Figure 13: Scenario 1, gas concentration in % LEL at the HVAC inlet The flow behaviour at the HVAC inlet is shown in Figure 14. The jet impacts one side of the HVAC duct and creates a high velocity flow up one side. At the other side of the duct the flow separates and recirculates. This recirculation region probably contributes to the somewhat better mixed conditions at this side of the duct. Figure 14: Scenario 1, flow-field at the HVAC inlet, velocity vectors shown on a vertical plane which intersects the HVAC duct 19

27 The distribution of gas around and inside the HVAC duct is shown in Figure 15. The location of the gas jet just outside of the duct is clearly seen, with peak concentrations greater than 100% LEL. This is higher than the target concentration of 50% obtained from the round jet expressions in Section 3.1. The difference is no doubt a result of the additional complexity which occurs for a release in a cross-flow and whose spreading is constrained by the under-side of the platform. Figure 15 indicates that well-mixed conditions are not achieved at the duct outlet, almost 21 m distant from the inlet. The presence of a weak swirling flow in the duct is implied by the concentration distribution in Figure 15, as the location of the peak gas concentration at a cross-section is gradually shifted to the upwind face of the duct. The distribution of gas at two sample lines across the breadth and width of the HVAC duct, 1 m above the inlet is shown overleaf; Figures 16 and Figure 17. Figure 15: Scenario 1, gas concentration in % LEL in the HVAC duct 20

28 Figure 16: Scenario 1, location of sample lines 1 m inside the HVAC inlet % LEL 50 % LEL Distance across breadth of duct, m Distance across width of duct, m a) Across the breadth of the duct b) Across the width of the duct Figure 17: Scenario 1, distribution of gas 1 m inside the HVAC inlet Line integrals of gas concentration have been calculated at the locations shown in Figure 16 to model the output of cross-duct beam infra-red detectors. Values of these line integrals are shown in Table 1. The average concentration of gas in the duct is 27% LEL. Table 1: Scenario 1, Line integrals of gas concentration inside the HVAC duct Location of line integral Length of Concentration Orientation Distance inside line LEL.m %LEL inlet (m) integral (m) (m) per m Mid-plane across breadth Mid-plane across width An indication of the effectiveness of mixing in the HVAC duct can be given by post-processing the CFD results to obtain the Coefficient of Variation (COV) as defined in Section at a number of cross-sections. The COV falls very slowly over the first three metres of the duct: 57%, 56% and 52% immediately outside, at 1 m and 3 m inside, respectively. 10 m inside the duct it has only fallen to 39%. At the outlet of the duct the COV falls to 19%. It can be seen from the examples in Appendix 1 that COV values of 50% and greater imply a very high degree of non-uniformity in concentration distribution, whilst even at a COV of 20% there is still a significant difference between maximum and minimum values of concentration. 21

29 3.3 SCENARIO Model geometry and computational domain The model geometry is shown in Figures 18 and 19. Again, this is a simplified representation of an offshore platform. The modelled geometry is retained as a cube of side 30 m whose base is located 25 m above sea level. A horizontal HVAC duct of internal dimensions 2.8 m x 1.8 m is located 23 m above the base of the platform. It is offset to one side of the platform and opens onto its downstream face, i.e. the wake region. The duct protrudes 0.5 m from the face of the platform. The size of this duct was also guided by information supplied by Integrated Engineering Services Ltd. The duct is 23 m long and is shown in Figures 18 and 19. The release is located towards the downstream end of a module which is located at low level in the platform. The module is assumed to be 5 m high and its floor is 5 m above the base of the platform. The module has two solid walls and is open at its upwind and downwind faces. A congested region occupies the upwind half of the module. The release is sited 0.46 m inside the module, 2 m below its roof and is directed upwards at an angle of 70 o to the horizontal. The release is not directly below the HVAC duct, but is offset towards the centre of the module. The location and initial direction of the release are indicated in Figures 18 and 19. Figure 18: Scenario 2, geometry (HVAC duct in blue, gas release in red) 22

30 a) Plan view b) Vertical elevation Figure 19: Scenario 2, dimensions (m) Once again an extensive region of the atmosphere that surrounds the platform is included in the CFD model. The computational domain is as per Scenario 1: 120 m wide, 115 m high, 240 m long. It includes the entire length of the HVAC duct. Note that, as per Scenario 1, the platform has been oriented at 20 o to the oncoming wind direction Boundary conditions The boundary conditions at the six outer faces of the computational domain were prescribed to be the same as those of Scenario 1, except that the wind speed was slightly higher; 2 m/s at 25 m above sea level. A mass flow rate of 37.7 kg/s was imposed at the end of the HVAC duct, equivalent to a uniform velocity of 6 m/s. In this scenario the gas release was assumed to be at low pressure and velocity, but input over a larger area than that of scenario 1. Hence, the release was specified to be 100% methane at 23

31 ambient temperature of 10 o C and an initial velocity of 12.3 m/s over a circular area of nominal diameter 0.29 m. The mass release rate is 22% that of scenario 1, being 0.55 kg/s. It is postulated that a release of this type and magnitude could possibly result from a break in a pressurised line or vessel which is surrounded by sufficient lagging or insulation to significantly reduce but not entirely destroy its initial momentum Flow physics The flow was again modelled as time-dependent. A standard k-h turbulence model (Launder & Spalding, 1972) was also used. Wall functions were employed at all solid boundaries, modified to account for surface roughness. Physical properties were as per Scenario 1. The congested region which occupies the upwind half of the open module was modelled as a region of isotropic resistance with a volume porosity of approximately 0.8. It has the effect of reducing, but not eliminating, the cross-flow through the module Mesh An unstructured mesh was generated. The mesh was again refined in regions where high gradients of velocity and concentration were expected. On the walls of the platform and inside the module four layers of prismatic mesh elements were used to aid resolution of the near-wall flow and help ensure that the first mesh node correctly falls within the log-law region for a turbulent boundary layer. A mesh with a total of 378,000 nodes was generated, constructed from 2.0 million mesh elements. The mesh is illustrated in Figures 20 to 22. Figure 20: Scenario 2, mesh - vertical elevation coincident with the release 24

32 Figure 21: Scenario 2, mesh plan view through the HVAC duct Figure 22: Scenario 2, mesh detail near the HVAC inlet Solution numerics and convergence Transient simulations were undertaken using high-order-accuracy spatial and temporal discretisation schemes with a time-step of 1 s. The simulations were carried out until the flow appeared quasi-periodic. Over 1300 time-steps were computed. The residuals for all transport equations decreased by three or more orders of magnitude, to very small rms values, and the 25

33 global imbalances of mass, momentum, energy and gas mass fraction all reduced to very much less than 0.05% of reference values. This indicates that the solution is well-converged Results The flow-field around the platform is very similar to that of Scenario 1, shown in Figures 8 and 9, except for the existence of a weak flow through the open module. The gross flow again consists of massive flow separation in the wake of the platform. In this scenario the gas release has far lower momentum than the high pressure release of Scenario 1. Thus, it is more influenced by the time-dependent flow in the wake of the platform. In addition, the release is also partly driven by its buoyancy. These effects interact in a complex manner and their net result is that the gas plume meanders significantly in the platform wake. This can be seen in Figure 23, overleaf, which shows iso-surfaces at 50% LEL at 40 s time intervals. Essentially the plume oscillates from side to side. At the extremity of this oscillation it encounters the HVAC duct and gas is ingested, see Figures 23e and 23f. 26

34 a) time t b) time t + 40s c) time t + 80s d) time t + 120s e) time t + 160s f) time t + 200s Figure 23: Scenario 2, iso-surface at 50% LEL, iso-metric view, at 40 s intervals 27

35 All of the results which follow are presented at the extremity of the meandering motion of the plume at time t s, when gas is being ingested into the HVAC duct as per Figure 23f. Figure 24 shows that the plume attaches to the sheltered face of the platform towards its upper end. The distribution of gas on cross-sections at 0.5 m outside the HVAC inlet, 0.5 m, 2 m and 10 m inside the HVAC duct, as well as at the end of the duct, is shown in Figure 25, together with the concentration on a horizontal plane down the middle of the duct. Figure 26, overleaf provides a close-up view of concentration at the HVAC inlet. Figure 24: Scenario 2, gas concentration in % LEL, elevation through the gas plume Figure 25: Scenario 2, gas concentration in % LEL in the HVAC duct 28

36 Figure 26: Scenario 2, gas concentration in % LEL at 0.5 m outside, 0.5 m and 2.0 m inside the HVAC inlet Figures 25 and 26 can be compared to Figures 13 and 15, showing that there is an even more pronounced concentration gradient across the duct than in Scenario 1. In one corner of the duct, gas which is very close to its LEL is being ingested. However, in the opposite corner the concentration is close to zero. Again, well-mixed conditions are not achieved at the duct outlet. Also, the presence of a weak swirling flow in the duct is again implied by the gradual shift in location of the peak gas concentration at a cross-section. Figure 27 shows that the flow stays largely attached to the walls of the duct as it enters the HVAC inlet, with little sign of any significant flow separation. Figure 27: Scenario 2, flow-field at the HVAC inlet, velocity vectors shown on a vertical plane which intersects the HVAC duct 29

37 The distribution of gas at four sample lines across the breadth and height of the HVAC duct, 0.5 m and 2 m inside the inlet see Figure 28 below - is shown in Figure 29. Figure 28: Scenario 2, location of sample lines 0.5 m and 2 m inside the HVAC inlet % LEL m inside % LEL m inside m inside 2.0m inside Distance across breadth of duct, m Distance across height of duct, m a) Across the breadth of the duct b) Across the height of the duct Figure 29: Scenario 2, distribution of gas 0.5 m and 2 m inside the HVAC inlet Line integrals of gas concentration have again been calculated, at the locations shown in Figure 28, to model the output of cross-duct beam infra-red detectors. Values of these line integrals are shown in Table 2. The average concentration of gas in the duct is 22% LEL. Table 2: Scenario 2, Line integrals of gas concentration inside the HVAC duct Location of line integral Length of Concentration Orientation Distance inside line LEL.m %LEL inlet (m) integral (m) (m) per m Mid-plane across breadth Mid-plane across breadth Mid-plane across height Mid-plane across height The COV is given in Table 3, overleaf, showing that there is a very high degree of nonuniformity in concentration distribution throughout the entire length of the duct. 30

38 Table 3: Scenario 2, COV at various distances inside the HVAC duct Distance inside the HVAC duct, m COV, %

39 4 DISTRIBUTION OF GAS INSIDE AN HVAC DUCT 4.1 OVERVIEW The model geometry of Scenario 2 has been refined to include obstructions which represent louvres and fire dampers at the HVAC inlet. All other aspects of the modelling are identical to Scenario 2. This approach allows the effect of these obstructions on flow and dispersion in the duct to be isolated and examined. This case is referred to as Scenario 3. A set of 24 louvres is represented at the inlet plane of the duct. The geometry of these louvres was based on a GDL Ltd datasheet. GDL are manufacturers and suppliers of air distribution products. The complex ribbed geometry of the louvres has been simplified for modelling purposes, whilst retaining their overall dimensions. Each modelled louvre is 10 mm thick, inclined at approximately 45 o, with a centre-to-centre spacing of 75 mm. The louvres occupy the first 80 mm of the duct. Fire dampers, assumed to be fully open, are simply represented as an array of rectangular obstructions located 1 m inside the duct. Again, the complex geometry of each damper has been simplified, but their overall dimensions and position has been retained. Data on fire dampers was obtained from Flamgard Engineering Ltd, upon which this modelled geometry has been based. The dampers are represented as being 50 mm thick and 300 mm wide, with partial-width dampers of 195 mm being included at locations nearest to the duct wall and supporting assembly. This supporting assembly has also been included in the modelled geometry. The modelled geometry and mesh at the HVAC inlet is shown in Figure 30. Figure 30: Scenario 3, detail of the geometry and mesh at the HVAC inlet 32

40 The mesh is as used in Scenario 2 except that it was selectively refined at the HVAC inlet and in the HVAC duct. Layers of prismatic mesh elements were added at all of the duct walls, to better represent the near-wall flow. The mesh refinement and the layers of inflated mesh elements can be seen in Figure 30. An additional 186,000 mesh nodes were added at the HVAC inlet and inside the duct, to give a mesh with a total of 564,000 nodes constructed from 2.9 million mesh elements. Transient simulations were again undertaken using high-order-accuracy spatial and temporal discretisation schemes, with a time-step of 1 s. The simulations were started from an initial solution obtained for Scenario 2 at time t + 20 s, i.e. intermediate between that shown in Figures 23a and 23b. The simulation was then advanced for a total of 180 s, at which time the trajectory of the gas plume had reached the extremity of its oscillation and was being ingested into the HVAC duct in just the same manner as Scenario 2 at the equivalent time of t s. Results presented below are for time t s and can be compared directly with those for Scenario 2. The flow outside of the HVAC inlet is essentially identical at this time for both Scenarios. The convergence history was near-identical to that of Scenario 2, i.e. the solution is wellconverged. 4.2 RESULTS The overall flow-field around the platform, as well as the trajectory of the gas plume, are indistinguishable from Scenario 2 and therefore are not presented. The distribution of gas on cross-sections at 0.5 m outside the HVAC inlet, 0.5 m, 2 m and 10 m inside the HVAC duct, as well as at the end of the duct, is shown in Figure 31, together with the concentration on a horizontal plane down the middle of the duct. This can be compared against Figure 25, for Scenario 2. Close to the HVAC inlet the gas distribution is qualitatively similar in both scenarios, with a very marked non-uniformity in concentration over duct cross-sections, which occurs because gas is essentially ingested at just one side of the duct. However, further down the duct the region of highest gas concentration occurs at this same side of the duct, in contrast to that of Scenario 2 in which the highest concentrations occur on the opposite side of the duct. This suggests that the louvres and dampers have all but eliminated the weakly swirling flow implied in the results of Scenario 2. In both scenarios, well-mixed conditions are not achieved at the duct outlet. A more detailed view of the gas concentration distribution at the HVAC inlet is shown in Figure 32. Again, this can be compared to Scenario 2, Figure 26. Although the distributions are qualitatively similar it would appear that the flow is no better mixed by the presence of the louvres and dampers. In fact, somewhat higher concentrations are evident at 2 m inside the inlet in Scenario 3, than in Scenario 2. Examination of the velocity field in the duct, Figures 33 and 34, reveals that this behaviour is caused by the louvres. These have the effect of deflecting the flow towards the upper part of the duct, leading to an extensive region of separated recirculating flow in the lower region of the duct. Gas is transported with the deflected flow, resulting in higher concentrations at the roof of the duct compared to Scenario 2. Whilst it may initially appear surprising that the louvres and dampers have had no substantial effect on mixing, this result is consistent with the findings of the literature review: it is only when large obstructions are present which are capable of generating turbulence at large lengthscales of the order of the duct size that mixing is likely to be significantly enhanced. 33

41 Figure 31: Scenario 3, gas concentration in % LEL in the HVAC duct Figure 32: Scenario 3, gas concentration in % LEL at 0.5 m outside, 0.5 m and 2.0 m inside the HVAC inlet 34

42 Figure 33: Scenario 3, flow-field at the HVAC inlet, velocity vectors shown on a vertical plane which intersects the HVAC duct Figure 34: Scenario 3, details of flow-field at the HVAC inlet, velocity vectors shown on a vertical plane which intersects the HVAC duct The distribution of gas at four sample lines across the breadth and height of the HVAC duct, 0.5m and 2 m inside the inlet see Figure 28 - is shown in Figure 35. There are no very substantial differences from Scenario 2, see Figure 29, although in general the concentration distributions are slightly skewed towards the gas plume side and upper face of the HVAC duct. 35

43 % LEL m inside % LEL m inside m inside 2.0m inside Distance across breadth of duct, m Distance across height of duct, m a) Across the breadth of the duct b) Across the height of the duct Figure 35: Scenario 3, distribution of gas 0.5 m and 2m inside the HVAC inlet Line integrals of gas concentration have also been calculated, at the locations shown in Figure 28, to model the output of cross-duct beam infra-red detectors. Values of these line integrals are shown in Table 4. The average concentration of gas in the duct is 21% LEL. Table 4: Scenario 3, Line integrals of gas concentration inside the HVAC duct Location of line integral Length of Concentration Orientation Distance inside line LEL.m %LEL inlet (m) integral (m) (m) per m Mid-plane across breadth Mid-plane across breadth Mid-plane across height Mid-plane across height The COV is given in Table 5 which shows that, as per Scenario 2, there is still a very high degree of non-uniformity in concentration distribution throughout the entire length of the duct. Indeed, the COV is generally slightly higher than in Scenario 2. Table 5: Scenario 3, COV at various distances inside the HVAC duct Distance inside the HVAC duct, m COV, % Although not shown, the computed non-dimensional near-wall distance in the duct, y+, is well within acceptable bounds throughout almost the entire length of the HVAC duct. This indicates that the wall boundary condition in the duct is being appropriately applied. 36

44 5 GAS RELEASE AND INGESTION INTO HVAC DUCTS FOR A REALISTIC SCENARIO 5.1 INTRODUCTION Sections 3 and 4 strongly indicate that both high and low pressure releases can result in nonuniform gas distributions at HVAC inlets. However, these scenarios are geometrically rather idealised. Whilst simplified geometrical arrangements are very useful in indicating how a nonuniform gas distribution could be present at an HVAC inlet, the increased mixing and channelling due to the passage of a gas release through congested areas is not represented. It is therefore important to model a more realistic scenario, based on a gas release from an existing offshore platform, to establish whether similar behaviour occurs with increased geometrical complexity. Here, the scenario considered is a high pressure release resulting from the failure of a riser on the Brae Alpha platform, operated by Marathon Oil UK Ltd. th In fact on November a riser did fail on Brae Alpha, resulting in a high pressure gas release and subsequent ingestion of gas into Hazardous Modules via the Hazardous HVAC inlet duct. A subsequent investigation (OSD, 2006) reports that gas appeared to pass across only part of the duct for several minutes, leading to a delay in confirmed detection and shutdown of the HVAC system. There is no suggestion that the detectors were not operating correctly. The aim of the present scenario is not to replicate this incident. This would be very timeconsuming, would require the collation of much detailed information and may be impractical. The aim is instead to draw upon some elements of this platform and incident to devise a more realistic scenario than the idealised configurations presented in Sections 3 and 4, so enabling more general conclusions on the interaction of gas and HVAC inlets and ducts. 5.2 MODEL GEOMETRY AND COMPUTATIONAL DOMAIN Figure 36 shows the modelled geometry and indicates the location of the release. Figure 36: Modelled geometry 37

45 A very simplified representation of the Brae Alpha platform has been used as the basis of this more realistic scenario. The overall dimensions of the platform and plans of the most significant geometrical features at the module support frame (MSF) level were provided by Marathon Oil. These were used to guide the size, shape and location of major obstructions to the wind field and gas dispersion at MSF level. Note, that during the 2004 incident gas was released from the top of a riser caisson and subsequently passed below and through the MSF level. Only those platform support legs closest to the release have been modelled. There are three HVAC ducts which penetrate the floor of the MSF: Hazardous Supply Plant Room duct, Safe Supply Plant Room duct, Permanent Living Quarters (PLQ) duct. Figure 37 shows these ducts. The Hazardous Supply duct is essentially open and free from major obstructions, apart from a walkway (not represented) at approximately mid-height of the duct. The other two ducts have also been modelled as being free from obstructions. More detail on the modelling of the HVAC ducts and the release geometry is given in Section 5.3. Figure 37: Modelled geometry showing HVAC ducts 5.3 BOUNDARY CONDITIONS AND FLOW PHYSICS As with the idealised scenarios, a large region of the atmosphere surrounding the platform was modelled. Identical boundary conditions to those imposed in Scenario 1 were applied, except that the wind speed is much higher; 12.3 m/s at the top of the platform (65 m above sea-level). This appears to be a plausible value for wind speeds on the day of the release in The wind direction was reported as being from 45q East of platform North (OSD, 2006). However, initial CFD simulations with this wind direction showed that the gas cloud would disperse away from the platform and that the gas concentration in the HVAC ducts would be negligible. Hence, an alternative wind direction was chosen, 5q West of platform North, such that the gas cloud would be directed across the three HVAC ducts. This wind direction was set by fixing the platform at 5q to the main axis of the computational domain. The majority of the results presented in Section 5.5 relate to this wind direction. The computational domain is illustrated in Figure

46 Figure 38: CFD domain and boundary conditions The size and location of the HVAC ducts is illustrated in Figure 39. Volume flow rates through the HVAC ducts were based on information provided by Marathon Oil: x Hazardous supply HVAC: 148 m 3 /s. x Safe supply HVAC: 63 m 3 /s. x PLQ HVAC: 32 m 3 /s. 39

47 a.) Plan view of MSF b.) Source location c.) Source dimensions Figure 39: Plan view of the modelled MSF, also showing the modelled release source 40

48 These volume flow-rates were imposed as a uniform out-flow velocity on a downstream face within the ducts. The out-flow boundary condition was artificially located at the ends of the HVAC supply rooms in an attempt to reduce the influence of this assumed boundary condition on the flow detail in the HVAC ducts. No attempt was made to model features such as fire dampers which exist between the HVAC ducts and supply plant rooms. Figure 40 shows the position of the out-flow boundary conditions. Figure 40: Position of HVAC duct outlet boundary conditions th The November gas release on Brae Alpha resulted from the failure of a riser inside a caisson. The pressurisation of the caisson resulted in the vertical displacement of one-half of a two-part seal around an oil production riser. The resulting gas release from the caisson occurred over the gap between the oil production riser and the caisson top on its South side, extending over half its circumference. The oil production riser extends 1.5 m vertically above the caisson top before bending 90 such that it is horizontal and oriented in a Southerly direction. The release would probably be directed up this short vertical section of the riser before impinging on the horizontal section above. The modelling of this flow is likely to be very difficult since an extremely fine mesh would be required to resolve the resulting boundary layer that would form along the riser. In addition, such an approach might result in numerical instabilities due to the very high near-wall velocity gradients in that region. Instead, a simplified geometry was used to capture the main features of the jet impingement on the horizontal section of the pipe. This simplified geometry is shown in Figure

49 Figure 41: Simplified geometry at the release source The location of the top of the caisson was very approximately 4 metres below the MSF level, 6.5 m from the Western perimeter and 5 m from the Northern perimeter of the platform. A plan view in Figure 39 shows the overall dimensions of the modelled MSF - including the location and dimensions of the HVAC ducts together with the location of the release relative to the North and West faces of the platform. During the November 2004 incident the release from the top of the caisson occurred over an approximately semi-circular slot, 1 mm wide and 480 mm long (OSD, 2006). The stagnation conditions of gas in the caisson (assumed to be pure methane) are prescribed as follows: P 0 = 20 barg, T 0 = 273K Under these conditions the flow would be choked and the resulting jet under-expanded. As explained in Section 3.2.2, it is not practical or necessary to model such an under-expanded release from the immediate top of the caisson. Instead, an effective source is prescribed, at the point at which the release has expanded to atmospheric pressure but is still at sonic velocity (Mach 1). The methodology by which this effective sonic source can be obtained is provided in Ivings et al (2003) and is reproduced here in summary form. It is based on an assumption of isentropic flow through the release slot, followed by expansion to sonic velocity but with the same mass flow rate and static temperature as the original under-expanded release. 42

50 The following isentropic flow expressions relate conditions at the release point (subscript 1 ) to those from the known stagnation conditions (subscript 0 ): J 2 T 1 J T0 T T J 1, P P, V 1 JRT 1 the mass release rate, m, is given by; m U1A 1V 1 in which a discharge coefficient of unity has been assumed. U 1 is given by: U P / RT Ewan & Moodie (1986) have shown that an under-expanded jet can be represented by an equivalent jet at atmospheric pressure. The equivalent, or effective, jet is assumed to be sonic with a mass flow rate and temperature the same as the original jet, but with a new area based on expansion of the jet to atmospheric pressure. The following effective source expressions apply: V V 1, P T T 1, A A P / P 2 2 P ambient, ambient where subscript 2 refers to the effective sonic source. The expressions above can be used to obtain the following boundary conditions for the effective sonic source, assuming that the rupture in the caisson top is shaped as a semi-circular slot 1 mm wide and 480 mm long: V 2 = 400 m/s, T 2 = 237K, P 2 = Pa, A 2 = mm 2 Figure 41 shows the shape and dimensions of the effective sonic source, modelled as a semicircular slot with the same inner radius as the release source but with a width of 10.1 mm rather than 1 mm. All other aspects of the modelling of the flow physics are the same as that for Scenario 1, Section MESH, SOLUTION NUMERICS AND CONVERGENCE An unstructured mesh was generated which was refined near the source and in other regions where high gradients of velocity and mass fraction were expected. A total of 665,000 mesh nodes were used. Figure 42 shows the mesh on the surface of the caisson and Figure 43 shows the mesh in a plane through the expected trajectory of the cloud. 43

51 a) Caisson top and source b) Close up of source Figure 42: Mesh resolution at the source Figure 43: Mesh resolution in a plane through the expected trajectory of the cloud Time-dependent simulations were undertaken with a time-step of 1 s. High-order-accuracy spatial and temporal discretisation schemes were used. The results in the region of the HVAC ducts were essentially steady in time, although the flow over the platform was unsteady. Equation residuals reduced by two orders of magnitude to very small rms values and the global imbalances of transported variables were less than 0.1% of reference values, indicating good convergence. 44

52 5.5 RESULTS Overall flow field and dispersion Figure 44 shows an iso-surface of 10% LEL for an initial wind direction of 45q East of platform North. The figure shows that the gas cloud disperses away from the platform. Figure 44: Iso-surface of 10% LEL for a wind direction of 45q East of platform North Figure 45 shows an iso-surface of 10% LEL for a wind direction of 5q West of platform North. All of the results which follow correspond to this wind direction. Gas can be seen to disperse through the western half of the platform at the MSF level. In this figure, velocity vectors in a vertical plane are also shown to give an indication of the flow around the platform (the maximum speed shown is 15m/s). As with the more idealised scenarios in Sections 3 and 4, there is a large wake region in the lee of the platform. A more detailed view of the 10% LEL iso-surface is shown in Figure 46. The gas jet is very quickly deflected in the direction of the prevailing wind, meaning that there is no impingement on the underside of the module which is located immediately above the MSF level. As the gas travels through the MSF it is channelled around obstructions which generate turbulence in their wake. Qualitatively it would appear that gas dispersion is enhanced by the presence of congestion in the MSF. Figure 46 also indicates that gas spreads underneath the MSF level and is ingested by the HVAC ducts. This is confirmed in Figure 47, which shows contours of gas concentration in a horizontal plane 23.5 m above sea level (just above the MSF floor). Gas is visible in all of the HVAC ducts, although at low concentrations in the Hazardous and Safe Supply ducts. However, in the PLQ HVAC duct, gas at a concentration of greater than 10% LEL is visible along its entire length. Velocity vectors on this plane are also shown to indicate the flow speed through the MSF (the maximum speed shown is 15 m/s). 45

53 Figure 45: Iso-surface of 10% LEL for a wind direction of 5q West of platform North Figure 46: Detail of 10% LEL iso-surface Figure 47: Gas concentration contours in % LEL on a horizontal plane at 23.5 m above sea-level just above the MSF floor. 46

54 5.5.2 Gas distribution in the Hazardous supply HVAC duct Figure 48 shows contours of gas concentration across the Hazardous supply HVAC duct at approximately the height at which gas detectors were located during the 2004 incident on Brae Alpha. The average concentration of gas in the duct is 5.4% LEL. Whilst this is a relatively low average concentration, gas is distributed very non-uniformly: peak concentrations are close to 10%, but with a concentration minimum of less than 1%. The COV for gas at this plane is 39%, which as indicated in Appendix 1 represents a significant variation in values over the crosssection. Figure 48: Gas concentration contours (% LEL) across the hazardous HVAC duct, 23.5 m above sea-level and just above the MSF floor Figure 49 shows locations at which point and line integrals of gas concentration in the Hazardous supply duct have been obtained from post-processing of the CFD results. In effect, point detectors have been located 0.6 m and 0.4 m from the sides of the duct (as shown in the diagram), and placed at 23.5 m above sea level. In addition, horizontal lines along each diagonal at 23.5 m are shown, along which integrals of gas concentration have been computed to replicate the output of cross-duct beam infra-red detectors. a) Plan view b) View from south east Figure 49: Locations of gas detectors in Hazardous supply HVAC duct and gas concentrations at selected points 47

55 The gas distribution along lines 1 and 2 (Figure 49) is shown in Figure 50. Values of the line integrals along lines 1 and 2 are shown in Table % LEL 5 4 Line 1 Line Distance along line (m) Figure 50: Gas concentration (% LEL) in Hazardous supply HVAC duct, along lines 1 and 2 Table 6: Realistic scenario, line integrals of gas concentration inside the Hazardous supply HVAC duct Concentration Location of line integral Length of line integral (m) LEL.m (m) %LEL per m Line Line The values of gas concentration at the four point detectors (Figure 49) range from 3.1% to 8.1% LEL, i.e. approximately a factor of 2.5 variation between minimum and maximum values. The two line integrals, replicating the effect of cross-duct beam detectors, show much less difference in their values and both are close to the actual average concentration of gas in the duct (5.4% LEL). Also of interest is the flow-field in the Hazardous supply HVAC duct, Figure 51. Regions of flow separation and recirculation are evident close to the HVAC inlet. Figure 51: Flow-field in the Hazardous supply HVAC duct 48

56 During the course of this work an alternative slightly simpler geometry was used, in which certain blockages which represent plenums connecting the HVAC supply rooms to the module above were not included. The results of these simulations were somewhat different from those presented above and give an indication of the effect of relatively small changes to the modelled geometry. Figure 52 shows the two model geometries, highlighting the plenums above the HVAC supply rooms. a) Geometry 1 b) Geometry 2 (as described in Section 5.2) (not including blockage due to plenums) Figure 52: Alternative model geometry The results for Geometry 2 showed more transient behaviour in the duct than those for Geometry 1. Gas concentrations monitored at a number of locations in the duct suggest that the flow in this region is time-dependent with a time period of approximately 10 s. Figure 53 shows contours of concentration across the Hazardous supply HVAC duct for Geometry 2 at different times. a) t b) t + 5 s c) t + 10 s Figure 53: Gas concentration contours (% LEL) across the hazardous HVAC duct for Geometry 2, at various times. At time t, the average concentration across the duct at the detector height is 7.8% LEL, whilst the COV for gas is 37%. Very similar values are obtained at later times. 49

57 Figure 54 shows the gas concentration along lines 1 and 2, for both Geometry 1 and 2 (at time t). Values of the line integrals along lines 1 and 2 for Geometry 2 are shown in Table % LEL 6 Geometry 1 - Line 1 Geometry 1 - Line 2 Geometry 2 - Line 1 Geometry 2 - Line Distance along line (m) Figure 54: Gas concentration (% LEL) in Hazardous supply HVAC duct, along lines 1 and 2 Table 7: Realistic scenario, Geometry 2, line integrals of gas concentration inside the Hazardous supply HVAC duct Location of line integral Length of line integral (m) Concentration LEL.m (m) %LEL per m Line Line Again, the two line integrals are both close to the actual average concentration of gas in the duct (7.8% LEL) Gas distribution in the PLQ HVAC duct The PLQ HVAC duct is far smaller than the Hazardous supply HVAC duct, just 1.5 m square, compared to 6.25 m x 4 m. It might initially be expected that, since the PLQ duct is smaller, more uniformity in the gas concentration would be seen across the duct. In fact this is not the case. Figure 55, overleaf, shows contours of gas concentration across the PLQ HVAC duct for Geometry 1. There is a very marked variation in gas concentration across the duct, which persists up the duct. The COV 2 m inside the duct, is 43%. The peak gas concentration is greater than in the Hazardous supply duct, with an average value of 16.4% LEL. For Geometry 2, the situation is qualitatively similar, except that the gas concentration is overall of lower magnitude; an average of 4.1%. However, the COV at 2 m inside the duct remains high, 56%, indicating that the flow is far from being well-mixed. 50

58 a) 2 m inside the duct b) 4 m inside the duct c) 6 m inside the duct Figure 55: Gas concentration contours (% LEL) across the PLQ duct, Geometry 1. Note that platform North is to the left, East to the top of the figures, etc. Figure 56 shows the location of horizontal sample lines across the PLQ duct, 2 m inside the duct inlet. The concentration distribution along these sample lines is shown overleaf, in Figure 57. Figure 56: Locations of sample lines 2 m inside the PLQ duct 51

59 Gas concentrations in PLQ HVAC duct % LEL 15 With plenums - Line 1 With plenums - Line 2 No plenums - Line 1 No plenums - Line Distance along line (m) Figure 54: Gas concentration (% LEL) in PLQ HVAC duct, along lines 1 and 2 Line integrals of gas concentration have been computed along lines 1 and 2 in the PLQ HVAC duct, for Geometry 1 and 2. The results are given in Table 8. Table 8: Realistic scenario, line integrals of gas concentration inside the PLQ HVAC duct Geometry Concentration Location of line Length of line LEL.m %LEL integral integral (m) (m) per m 1 Line Line Line Line The two line integrals (replicating the effect of cross-duct beam detectors) for each geometry give values which are very close to the actual average concentration of gas in the duct: 16.4% and 4.1% LEL for Geometry 1 & 2, respectively. The line-integrated concentration is almost the same for lines 1 and 2, which simply reflects the fact that the peak concentration gradient is along a diagonal of the duct (the sample lines are across the width of the duct). 52

60 6 DISCUSSION 6.1 REVIEW AND DISCUSSION OF RESULTS In every Scenario the most significant feature of the CFD results is the presence of a large variation in gas concentration across HVAC inlets. This characteristic of the flow is consistent with the concentration field expected of a jet release at a large distance from the release source (as described in Section 3.1). Whilst the behaviour of a buoyant plume is different in detail it is similar in essence, therefore the low momentum release of Scenarios 2 and 3 would also be expected to show a significant variation in concentration across the plume at a large distance from the gas source. In this respect the CFD results are unsurprising and broadly consistent with the established fluid mechanics of jets and plumes. In every Scenario in which gas enters a straight HVAC duct, the rate at which the variation in gas concentration over the duct cross-section reduces with distance along the duct is very slow. This outcome of the CFD modelling is consistent with the body of literature reviewed in Section 2.2. The variation in gas concentration over a duct cross-section can be expressed as a Coefficient of Variation (COV). The computed rate of decay of COV with distance along a straight duct is qualitatively similar to that from this same body of literature, in that the COV reduces slowly with distance along a straight duct. Furthermore, the computed effect of louvres and fire dampers on mixing over a duct crosssection is seen to be very small. This is evident if the values for COV are compared in Tables 3 and 4. Again, the literature reviewed in Section 2.2 strongly suggests that only purposedesigned mixing elements, or bends in a duct, are effective in substantially enhancing mixing. So, whilst there necessarily remains some uncertainty in the ability of the CFD modelling to reproduce the fine details of turbulent mixing in the wake of obstacles such as louvres and grilles (discussed in more detail at the end of this Section), overall this aspect of the CFD results is again consistent with the findings of the literature review. In summary, there is no substantial reason to doubt that the CFD results broadly reflect the gross flow behaviour in and around HVAC ducts, at least for the simplified release sources and geometries considered in this study. One further aspect of the CFD results should be mentioned: that the presence of a large variation in gas concentration across a HVAC duct appears to occur not only for very large duct crosssections with a high aspect ratio (width:breadth), but also for more modestly-sized square ducts. The range of duct sizes examined in this study varies from a maximum of 6.25 m x 4 m, through 2.8 m x 1.8 m and 2.84 m x 1.34 m, to a minimum of 1.5 m x 1.5 m. In every case the COV at, or close to, the duct inlet is quite large, although smaller values of COV are seen for the realistic scenario than for the simplified cases. However, with ducts of smaller dimensions than those examined here it can be expected that the variation in gas concentration would also be smaller, although possibly still significant. In principle the CFD results in this study can be used to draw some general conclusions on the likely effectiveness of differing flammable gas detection strategies for HVAC inlets and ducts. However, it should not be forgotten that CFD modelling is an approximation to reality. Also there are other factors, in addition to the findings of this report, that are likely to influence the choice of gas detection strategy such as cost, maintenance, reliability, etc. Nevertheless, with these caveats in mind, it is possible to draw some conclusions. In due course, experimental validation via large-scale physical tests using commercial detectors would be very useful in reducing remaining uncertainties. 53

61 Hence, for large ducts (major dimension >> 1 m), it will be difficult to always ensure that peaks in gas concentration are not missed by point-based detection systems, especially if standard catalytic or infra-red point detectors are used and typically set to alarm at 20% LEL. For example, examination of the results of Scenario 1, Figure 13a, at a location 1 m inside the duct, shows that gas concentrations are less than 20% LEL over about half of the cross-section of the duct, even though the average concentration of gas in the duct is 27% LEL, i.e. well-above a 20% alarm level. For Scenario 3, Figure 32, at 0.5 m or 2 m inside the duct, gas concentrations are below 20% LEL over the vast majority of the duct cross-section, although the average concentration of gas in the duct is just greater than 20% LEL. If using a point-based detection system some mitigation for this situation would be possible if multiple detectors were used and located towards the extremities of the duct cross-section. However, the CFD results indicate that for a large duct up to four point detectors could be needed for systems which alarm upon two positive detections. Additional mitigation could be gained by the use of lower alarm settings. HSE (2006) recommend that the feasibility of alarm levels of ~10% be explored. The use of extended path point infra red detectors could also be beneficial, since these appear to have much higher sensitivity - with quoted minimum alarm levels of 5% - although whether they operate reliably in an offshore environment is currently uncertain. These detector types also have the benefit that they cover a path length of the order of 1 m, so providing greater coverage than standard point detectors. For these reasons extended path point infra-red detectors could also be well-suited to the monitoring of small ducts. For large ducts, cross-duct beam infra-red detector systems could potentially be beneficial. This is partly because the path length is relatively long - thereby maximising absorption of the beam - and partly because they are less likely than a point detector to miss a peak in concentration due to their coverage of a duct. However, there is some uncertainty as to whether they have sufficiently high sensitivity. Line integrals of gas concentration have been computed from the CFD results in this study to replicate the output of cross-duct beam infra-red detectors. For Scenarios 1 to 3, in which the average concentration of gas in the duct was always greater than 20%, line integrals which were equivalent to maximum and minimum output of 0.78 LEL.m to 0.17 LEL.m were obtained. It is questionable whether output as low as 0.17 LEL.m would meet minimum alarm levels for cross-duct beam infra-red systems. The CFD results in the present study indicate that the variation of gas concentration over a duct cross-section can occur in a simple fashion as a gradient along the major axis of a duct (Scenario 1, Figure 13) or along its diagonal (realistic scenario PLQ duct, Figure 55), or, in a more complex manner (Scenario 3, Figure 32; realistic scenario hazardous supply duct, Figures 48 & 53). Hence, where cross-duct beam infra-red detector systems are employed, two beams would be recommended to reduce the likelihood that a peak in gas concentration could be missed. The beams would probably best be arranged so as to be approximately orthogonal, either along the diagonals of a duct, or across the width & breadth of a duct. Aspirated systems could also potentially be beneficial for gas detection in a large duct, since in principle they could also provide good coverage of a duct. If such systems are configured as a line of sample holes, then two lines would be recommended, arranged approximately orthogonally, for the same reasons as given above. There is again some uncertainty as to whether the sensitivity of the detector at the end of an aspirated probe system would be sufficiently high. The CFD modelling in this study indicates that detector types which are based on sampling along a line (either cross-duct beam infra-red, extended path point infra-red, or aspirated line sample probes) tend to give an average concentration which is more approximately representative of the average concentration of gas in a duct (see Table 1, Scenario 1; Tables 6, 7 54

62 and 8, realistic scenario) than might be obtained with a limited number of point detectors. However, this is not always the case (see Table 4, Scenario 3). On the basis of the present CFD results, and the findings of the literature review, there would appear to be no significant increase to be gained in the likelihood of gas detection as a consequence of siting detectors a long way down an HVAC duct - in the expectation that wellmixed conditions will exist. Any non-uniform distribution of gas at the inlet to an HVAC duct is very likely to persist a long way downstream inside the duct, at least as far as any fans, unless purpose-designed mixing elements or bends are also present in the duct. This behaviour is illustrated in Figures 15 and 31. In addition, there are other practical considerations raised by such a strategy, such as the fact that a larger volume of gas would be ingested prior to closure of dampers. The CFD results indicate that the distribution of gas immediately outside of an HVAC inlet is quite similar to that which exists a short distance inside the inlet. See Figures 13 and 32. The literature review also suggests that unless purpose-designed mixing elements or bends are present close to an HVAC inlet then the COV reduces slowly with distance along a duct. Therefore, there would appear to be no significant benefit to be gained from siting detectors inside an HVAC duct compared to locating detectors immediately outside the duct. Practical considerations, such as ease of access to detectors for maintenance purposes, or sheltering of detectors from the weather, could be of more importance. The CFD results, supported by the fluid mechanics of flow around a bluff body, show that the flow around an offshore platform is likely to be time-dependent as a consequence of flow separation in the wake of the platform. In addition, the flow around other bluff objects on a platform can lead to transient flow in their wake. The time-scales for such transient flow features can cover a large range; from minutes for flow over the entire platform (see Section 3.2.5) to possibly tens of seconds or less (an indication of time-scales of the order of 10 s is evident in the simulation of the realistic scenario, see Section 5.5.2, Figure 53). The timedependency of the flow and gas dispersion, and its implications on gas detector response, is not investigated further in this study. This is in part because the simulations would probably need to be repeated using a much more sophisticated approach to the modelling of turbulence before firm conclusions could be reached. This would be very time-consuming and possibly impractical. However, the likely existence of time-dependency of flow and gas dispersion on a range of time-scales adds weight to recommendations that detection limits should be as low as reasonably practical. As mentioned above, it should not be forgotten that CFD modelling is an approximation to reality. Uncertainty in the CFD results will arise primarily as a consequence of approximations and assumptions which are implicit in the turbulence modelling. Errors in the CFD results will arise primarily as a result of mesh resolution, although the meshes used in this study are refined in regions of steep gradients. Also, high-order-accuracy numerical discretisation schemes are employed. Nevertheless, numerically-generated diffusion is likely to be present. However, this artificial diffusion will generally lead to a reduction in gas concentration gradients, such that in reality even more significant variations in gas concentration could be expected. Perhaps of more significance is the fact that only a few scenarios have been investigated, for a limited range of conditions, and that these scenarios are all somewhat idealised. Even so, the CFD results are consistent with the outcomes of the literature review and the known behaviour of flow and gas dispersion in and around ducts. Nevertheless, the recommendations which follow in Section 6.2, on gas detection strategies, are necessarily labelled as initial recommendations. Experimental validation, via large-scale physical tests using commercial detectors, is therefore recommended as a next step to reduce remaining uncertainties. 55

63 6.2 INITIAL RECOMMENDATIONS FOR GAS DETECTION STRATEGIES Initial recommendations on flammable gas detection strategies for HVAC ducts are listed below. These initial recommendations are based on the findings of the scoping study by Walsh et al (2005), a review of the literature on flow and dispersion in ducts which is presented in Section 2, as well as the outcomes of the CFD modelling reported in Sections 3 to 5. (1) Detector alarm levels should be set as low as reasonably practical: 10% LEL or less. Justification: The possibility of significant non-uniformity in the distribution of gas which is ingested into an HVAC duct has been demonstrated by CFD modelling and is also indicated by theoretical considerations. The literature review has highlighted that, in the absence of purposedesigned mixing elements, an initial non-uniform distribution of gas in a duct requires a very long downstream distance before uniformity is approached. HVAC detectors are now available with a concentration range of 0 to 20% LEL and quoted minimum alarm levels of 5% LEL (Walsh et al, 2005). To reduce the likelihood that detectors will miss a non-uniform distribution of gas ingested into an HVAC duct, it is recommended that alarm levels be set no greater than 10% LEL. HSE have already provided information which states that although it is common practice for gas detector alarm levels to be set at 20% LEL, duty holders should explore the feasibility of reducing this alarm level to ~ 10% LEL (HSE, 2006). The low alarm levels have to be balanced with the minimisation of false alarms, which arise from detector drift and transient operational activities. (2) Point catalytic, point infra-red, extended path point infra-red, cross-duct beam infrared and aspirated point detector systems all have the potential to be effective in detecting non-uniform distributions of flammable gas in and around HVAC ducts provided that their sensitivity is sufficiently high (low detection limit) and that due regard is given to the possibility that gas will be distributed non-uniformly. Justification: Walsh et al (2005) reviewed a number of different detector types. A range of detector types are available with high sensitivity, although there is some question as to whether all of the point and cross-duct beam infra-red systems have sufficiently-high sensitivity. Each detector type has its benefits and limitations, demanding differing siting requirements to ensure that a non-uniform distribution of gas is not missed. (3) Extended path point infra-red detector systems currently appear to offer the greatest sensitivity, but multiple detectors should be used and sited so as to anticipate non-uniform mixing. Justification: Walsh et al (2005) show that extended path point infra-red detector systems are available with a concentration range of 0 to 20% LEL and quoted minimum alarm levels of 5% LEL. In addition, specially designed point catalytic (e.g. for gas turbine enclosures) detectors are available with a similar sensitivity (typical catalytic detectors are usually not as sensitive or as reliable as infra-red types). However, whether either type operate reliably in the field with minimum false alarms is currently uncertain. The CFD modelling demonstrates that there is a possibility of significant non-uniformity in the distribution of gas inside and around an HVAC inlet. The literature review indicates that this non-uniformity will reduce slowly with distance downstream in a duct. It is difficult to provide firm guidance on how many point or extended path detectors should be used since this depends on the size and shape of a duct. However, there should be good coverage of the cross-section of the duct. For large ducts this may mean that four detectors would be needed for systems which alarm upon two positive detections. 56

64 (4) Cross-duct beam infra-red, extended path or aspirated point detector systems should be based on two approximately orthogonal beams or lines of aspirated point probes. Justification: As stated above, the CFD modelling demonstrates that there is a possibility of significant non-uniformity in the distribution of gas inside and around an HVAC inlet whilst the literature review indicates that this non-uniformity will reduce slowly with distance downstream in a duct. For these reasons there should be good coverage of the cross-section of a duct. This can be achieved by two infra-red beams, either as open-path cross duct or extended path point infra-red, or lines of aspirated point probes, arranged approximately orthogonally. (5) No significant benefit can be expected to be gained from siting detectors inside an HVAC duct compared to locating them immediately outside the HVAC inlet. Justification: The literature review indicates that effective mixing in a duct is only achieved if large-scale turbulent eddies are introduced via purpose-designed mixing elements or bends. The CFD modelling indicates that louvres at the inlet to a duct or fire/gas dampers inside a duct will not, in themselves, be sufficient to rapidly ensure that well-mixed conditions exist in a duct. In fact CFD simulations indicate that a non-uniform distribution of gas immediately outside of an HVAC inlet persists downstream from these geometrical elements. The literature review also indicates that grilles at the entrance to HVAC ducts are unlikely to significantly enhance mixing. (6) In the absence of purpose-designed mixing elements or a series of bends upstream from gas detectors no significant benefit is to be gained from siting detectors a significant distance downstream from an HVAC inlet. Justification: The literature review and the CFD modelling strongly indicate that, for a straight duct, well-mixed conditions are only achieved a very long way downstream from an HVAC inlet. (7) Mixing elements have the potential to reduce any non-uniformity in the distribution of gas in a duct but their effectiveness should be proven by physical tests. Justification: This is supported by the literature review. It should also be noted that mixing elements will result in an additional resistance to flow in a duct and that the resulting pressure drop may be significant. The above recommendations are based on evidence from CFD modelling and the published literature. However, CFD modelling has inherent uncertainties and it is not certain that the findings from the literature are always directly relevant. Therefore it is strongly recommended that the above initial recommendations are substantiated by physical trials, using real detectors. 57

65 7 CONCLUSIONS The aim of this study has been to undertake CFD modelling to provide a basis for advice to inspectors and the industry on the effectiveness of flammable gas detection strategies for offshore HVAC ducts. CFD simulations of a high and low pressure gas release have been undertaken for idealised representations of an offshore platform, as well as a high pressure release for a more realistic geometry based on the Brae Alpha platform. In parallel with this modelling work a literature review has been carried out to build on the scoping study of Walsh et al (2005). The most significant feature of the CFD results is that in all cases the distribution of gas at HVAC inlets was non-uniform: large variations in gas concentration were present over the cross-section of the modelled HVAC inlets. This result was found to be consistent with the theoretical behaviour of a high pressure gas release. Neither is there a substantial reason to believe that it is not also consistent with the behaviour of a low pressure gas release. It means that there is the potential for a gas release to be missed by detection systems unless this nonuniformity in gas concentration is anticipated in the selection and siting of gas detectors at HVAC inlets. The CFD results also show that a variation in gas concentration over a duct cross-section only reduces slowly with distance along a straight duct. This finding was found to be consistent with a body of relevant literature stemming from the sampling of gas distributions in the exhaust ducts of nuclear stacks. This literature highlights that purpose-designed mixing elements and bends in a duct can be effective in creating well-mixed conditions in a duct, but at the cost of increased pressure drop. It also suggests that relatively small-scale obstructions such as louvres and fire dampers are unlikely to significantly enhance mixing. This was borne out by CFD modelling of such obstructions. The implications of the modelling work, substantiated by the literature, are that in the absence of purpose-designed mixing elements or a series of bends upstream from gas detectors no significant benefit would be gained from siting detectors a significant distance downstream from an HVAC inlet. Also, no significant benefit can be expected to be gained from siting detectors inside an HVAC duct compared to locating them immediately outside the HVAC inlet. The CFD results were post-processed to gain some further insight into the likely effectiveness of point and infra-red beam or aspirated detector systems for HVAC ducts. The resulting output has been combined with the findings of the scoping study by Walsh et al (2005), and the outcomes of the literature review and CFD modelling as reported above, to provide a basis for the following initial recommendations on flammable gas detection strategies: x Detector alarm levels should be set as low as reasonably practical: 10% LEL or less. x Point catalytic, point infra-red, extended path point infra-red, cross-duct beam infra-red and aspirated point detector systems all have the potential to be effective in detecting non-uniform distributions of flammable gas in and around HVAC ducts provided that their sensitivity is sufficiently high (low detection limit) and that due regard is given to the possibility that gas will be distributed non-uniformly. x Extended path point infra-red detector systems currently appear to offer the greatest sensitivity, but multiple detectors should be used and sited so as to anticipate nonuniform mixing. 58

66 x Cross-duct beam infra-red, extended path or aspirated point detector systems should be based on two approximately orthogonal beams or lines of aspirated point probes. x No significant benefit can be expected to be gained from siting detectors inside an HVAC duct compared to locating them immediately outside the HVAC inlet. x In the absence of purpose-designed mixing elements or a series of bends upstream from gas detectors no significant benefit is to be gained from siting detectors a significant distance downstream from an HVAC inlet. x Mixing elements have the potential to reduce any non-uniformity in the distribution of gas in a duct but their effectiveness should be proven by physical tests. 7.1 RECOMMENDATIONS FOR FURTHER WORK The CFD modelling in this study is consistent with the findings of the literature review and the theoretical behaviour of high and low pressure gas releases. However, CFD modelling is an approximation to reality. Also, the range of scenarios which have been investigated using CFD are relatively small, as well as being somewhat idealised. In addition there are other factors, such as the reliability of detectors, which have not been addressed in this study. Therefore it is recommended that large-scale physical tests, using commercial detectors, are undertaken to validate the findings of this study and to support and refine the initial recommendations above. It would also be useful to clarify the minimum practical alarm levels for a range of commercial detector types, especially cross-duct beam infra-red systems. 59

67 8 APPENDIX 1: EXAMPLES OF COEFFICIENT OF VARIATION a) 10% b) 10% c) 20% d) 20% e) 50% f) 50% g) 100% h) 100% Figure A1: Example distributions of a scalar on a regular 10 x 10 grid with Coefficient of Variation ranging from 10% to 100%. 60

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73 Published by the Health and Safety Executive 12/07

74 Health and Safety Executive Assessment of gas detection strategies for offshore HVAC ducts based on CFD modelling The aim of this study has been to undertake CFD modelling to provide a basis for advice to inspectors and the industry on the effectiveness of flammable gas detection strategies for offshore HVAC ducts. CFD simulations of a high and low pressure gas release have been undertaken for idealised representations of an offshore platform, as well as a high pressure release for a more realistic geometry based on the Brae Alpha platform. In parallel with this modelling work a literature review has been carried out to build on a scoping study by Walsh et al (2005). This report and the work it describes were funded by the Health and Safety Executive (HSE). Its contents, including any opinions and/or conclusions expressed, are those of the author alone and do not necessarily reflect HSE policy. RR602