WHITE PAPER: Concurrent CFD: Mission Critical for Next-Generation Aerospace Design

Transcription

1 WHITE PAPER: Concurrent CFD: Mission Critical for Next-Generation Aerospace Design

2 Concurrent CFD: Mission Critical for Next-Generation Aerospace Design Aerospace manufacturers, like most other industries, are urgently pursuing cost-saving measures to deal with today s economic and market realities. But due to the complexity of aerospace products plus the safety and regulatory issues that uniquely affect them, it is not possible simply to use cheaper materials or lighter packaging. Cost savings (and their synonym, time savings) must be found elsewhere. Terms like lean engineering have joined the lexicon of efficiency as aerospace producers seek ways to do more with less. The discipline of software-based modeling in its many forms is proving to be the salvation of manufacturers working under pressure to deliver end products of proven quality at lower cost, and in less time. Almost every aspect of product design, from mechanical housings to printed circuit boards, has its own dedicated modeling toolset to aid engineers with basic layout, whatif trials and more. Not surprisingly, modeling is an enabling tool for today s aggressive efficiency strategies. Fluid Dynamics the study of the flow of gases, liquids, or heat within a system is one challenging area that has been tamed by modeling technology. Computational Fluid Dynamics (CFD) is a technology that has become a cornerstone of aerospace mechanical design, supporting the development of components as diverse as hydraulic valves and cockpit ventilation ducts. Within the larger arc of CFD there are variants and derivatives, including easy-to-use tools aimed at Mechanical (M) users who need to incorporate fluid analysis into their design flow. The Mentor Graphics Mechanical Analysis Division is a leading supplier of fluid analysis solutions in this category. Modeling, Simulation, and M Modeling and simulation processes are used almost universally in the aerospace industry s mechanical design establishment. The tools are indispensable for designing large-scale systems and structures, and have helped engineering organizations compress their development schedules while improving the quality of their finished products. These M tools have also reduced the need for over-design, saving weight and cost on critical parts without sacrificing strength or reliability. Engineers can cost-effectively test numerous concepts and alternatives in virtual form to arrive at designs that are stable and proven. An important step in aircraft design is of course fluid flow analysis, which studies the aerodynamics of structures including the body, wings, engine nacelles and thrust chambers under both subsonic and supersonic flow conditions. This is the obvious application, but there is much more. Today designers perform flow analysis on a broad range of components and subsystems, from engine intakes and exhaust systems to valves and ventilation. Almost any aircraft element that comes into contact with liquids or gases, or conducts heat from a device or process, is a candidate for fluid flow analysis. Flow analysis, like M itself, can help engineers save cost, time, and weight in their aerospace system designs. And like M, design-centric flow analysis minimizes over-design and reveals hidden weaknesses. 2

3 Doing the Financial Math The technical rationale for using modeling and simulation (whether fluid or mechanical) for aerospace design is well understood. But this is only the beginning. Cost matters. Irrespective of the ups and downs of a fickle economy, the bottom line for the procurement of almost any engineering development tool hardware or software is the universal cost/benefit equation: can the solution save time and money? This is not an issue whose importance is limited to the aerospace community, but it has special urgency because that industry builds some of the world s most complex products. Consequently it must deal with some of the longest product development cycles and highest engineering costs of any business enterprise. Producers of aerospace systems and components are constantly seeking new and improved design tools, often with the objective of reducing the cost of prototype development. Both M and CFD tools minimize the need for costly physical prototypes. The object of simulation and modeling is to inform and confirm important decisions about an emerging product, and to do so as early as possible in the design process. These benefits are especially critical when the product in question is complex. Most aerospace-related products are considered to have either high or very high complexity levels. The latter category encompasses systems containing up to 100,000 individual parts, or more. The development process can span weeks or years, depending on the complexity of the end product. And with each passing day, costs mount up. Figure 1 depicts the time and dollar cost of prototypes at various complexity levels. It is important to note that this is not the whole project timeline, but only the portion devoted to building a prototype. The conclusion after examining Figure 1 is that it pays, literally, to avoid physical prototypes. Not surprisingly, best-in-class companies (ie. Top Tier) strive to substitute virtual prototypes for physical ones as much as possible. This is a fact that has been verified by pragmatic market research. A 2007 study 1 compared 190 companies and rated them by their key performance metrics including hitting cost/revenue targets, achieving planned product launch dates and more. Using these criteria the researchers categorized the organizations into three tiers of performance and then mapped the companies use of simulation and modeling into this hierarchy. The results were enlightening: the top-tier enterprises relied most heavily on virtual prototyping and performed 2.8 rounds of testing while Build Time (Days) Figure 1: The cost of building physical prototypes. Source: Aberdeen Group study the lowest-tier companies used 40% more physical prototypes and performed 4.7 rounds 2 of testing. 0 Physical Prototype Costs 13 Days $7.6K 24 Days $58K 46 Days $130K 99 Days $1.2M Low Moderate High Very High Complexity 1 Engineering Decision Support: Driving Better Product Decisions and Speed to Market. Aberdeen Group study, September, All of the findings reflect mean values 3

4 Table 1 summarizes the savings that can be gleaned by following the example of the top-tier companies as opposed to the lower-tier performers. The latter used a mean of 1.1 more physical prototypes over the course of a project, and both the time and cost entries in Table 1 reflect this. Product Complexity Time Saved by Simulation Cost Saved by Simulation Low Moderate High Very high 14 days 26 days 51 days 109 days $8,360 $63,800 $143,000 $1,320,000 Table 1: Simulation saves cost and time in projects of every scale and scope. These figures reflect the savings achieved by best-in-class companies using M-based design processes when compared with companies that worked with physical prototypes exclusively. Source: Aberdeen Group study Fluid Analysis: Theme and Variations In the past, CFD was the province of highly-trained fluid analysis specialists whose rarified tools were by no means optimized for -based design processes. The technology underlying CFD is quite convoluted and traditional tools required experts to fine-tune the mesh and solver settings before converging on a solution. Today companies such as Mentor Graphics have brought CFD processing into the mainstream in the form of powerful tools that can be deployed without disrupting the process or methods of products design. As a result, CFD benefits are now easily accessible to small- and mid-sized enterprises. Mechanical design engineers not just CFD gurus can use their existing engineering skills to successfully perform flow and heat analyses. Importantly, these CFD packages accept M data, typically through a conversion tool that bridges the two environments and simplifies data transfer. Concurrent CFD is a new approach to CFD which uses the same mathematical foundation as CFD. Concurrent CFD simplifies the process by allowing the designer to analyze and optimize designs directly in the M environment; saving up to 75% of the time historically required for conventional CFD development (see Sidebar). Concurrent CFD is embedded in industry-standard tools such as ProENGINEER/Wildfire and CATIA. Analysis menus and displays are available from the M toolbar, just like the native design functions. In effect, fluid analysis becomes an M plug-in. These breakthrough solutions for fluid flow analysis have implications well beyond their purely technical features. More engineers will do more modeling and analysis up front simply because Concurrent CFD tools are easy to use and accessible, unlike some of the CFD solutions that preceded them. Because thoroughly analyzed designs tend to go through validation quickly and with fewer issues, end products can come to market sooner, with well-proven reliability. These are exactly the business benefits that most enterprises are looking for these days. The trend among design tools is toward democratization of once-rarified applications such as CFD. Now the same engineer who designs a valve or housing can quickly check its air, heat, or 4

5 fluid flow characteristics. It is a formula for fast, error-free generation of production-ready aerospace product designs. Concurrent CFD: Tools That Empower Mechanical Engineers to Excel at Design Concurrent CFD is a tool designed for mechanical engineers; a solution designed to be used routinely as part of everyday M design activities. Mentor Graphics FloEFD is a leading example of this innovative technology. Is features are aimed at the vast population of design engineers who are not CFD specialists. FloEFD features an extremely easy-to-use user interface that is tightly integrated with M applications and invoked by menus therein. Gone is the esoteric jargon of fluid analysis, replaced with self-explanatory variable such as walls, inlets and outlets. A powerful analysis wizard guides the set-up process. What-if analysis is simple because Concurrent CFD accepts new variations in the solid model without the need to reapply loads, boundary conditions and material properties. It all adds up to more expedient analysis, which encourages more thorough design evaluation earlier in the process. Features such as real-time automatic convergence monitoring help mechanical engineers achieve good usable fluid analysis results without numerical convergence problems. And when the flow within a model changes from laminar to turbulent, for example, Concurrent CFD recognizes the change and handles it automatically. An embedded Concurrent CFD tool can use newly-created or existing 3D geometry and solid model information t0 simulate designs in real-world conditions. It automates tedious operations such as creating phantom objects to represent the fluid (hollow) regions within solid objects. Fluid analysis is based on meshes that evaluate localized fluid effects on a cell-by-cell basis. Developing a mesh is one of those skills that has always separated CFD specialists from mechanical engineers. No more. With Concurrent CFD tools, meshes are created automatically. In fact, FloEFD actually creates an adaptive mesh that reduces the cell size (increasing the resolution of the analysis) to ensure more accurate simulation results in complex areas of the model, as shown in Figure 2. Figure 2: Using a rectangular adaptive mesh, Concurrent CFD tool FloEFD can automatically adjust cell size to deliver better resolution anywhere it is needed. 5

6 Why Concurrent CFD Speeds Up a Designers Workflow, and a Company s Profits Conventional CFD Concept Detailing Prototyping Traditional CFD Traditional CFD Testing Manufacture Comparison of Flow Simulation Design Processes Traditional Trra CFD Concept Detailing Upfront CFD Upfront CFD Tessting Testing Prototyping Manufacture Upfront CFD Upfront CFD Concept ept Detailing ailing g Prototyping Prototy ototy yping Testing Te g CFD CFD CFD Manufacture Concurrent CFD Figure 3: Diagram shows both Conventional and Upfront CFD need to Import/Export users M geometry to Third Party software for analysis during the design process. By comparison, Concurrent CFD is embedded into the users existing M design software. Figure 3 shows that in conventional CFD or as it is sometimes known, traditional CFD, the model geometry is first captured and then exported from the users M system. The geometry then needs to be imported into the users CFD tool, cleaned, meshed, solved, the results postprocessed and then reported back to the design team. This work is usually done by a specialist analysis group, or outsourced to a consultancy, so it s necessary for the design team to communicate accurately just what needs to be analyzed and how. However, by the time the results are captured and reported on, the analysis model has become stale, as the design due to time restrictions, has progressed, often making it difficult to act on the results. Any significant changes to the models geometry then need re-analyzing. The penalties of conventional/traditional CFD are increased manpower, time and cost. Upfront CFD attempts to improve this situation by aiming to streamline the interfacing between the M tool to the CFD tool. Usually this is done by incorporating a solid modeler within the analysis suite. The result are a cleaner import of the geometry; However, the actual CFD analysis process is still performed outside of the users M system, so a user needs to learn a separate and often complex piece of software, increasing a users learning curve and the products eventual time-to-market. It still carries the penalty of time, and the need to repeatedly export the geometry from the M software and re-import it into the CFD software. 6

7 Concurrent CFD operates very differently. Its M embedded CFD, so the work is performed within the M environment in an interface the user is already familiar with. Embedding CFD inside an M tool delivers very significant benefits. Design changes necessary to achieve the desired product performance are made directly on the M model, so the design is always upto-date with the analysis. Comparison of Flow Simulation Design Processes Conventional CFD Transfer Geometry Clean Geometry Create Cavity Meshing Boundary Conditions Sove (Batch) Post Processing Report Generation 100% Time Upfront CFD Transfer Geometry Clean Geometry Create Cavity Meshing Boundary Conditions Sove (Batch) Post Processing Report Generation 50%~70% Time x x x Create Cavity Transfer Geometry es M Clean Geometry h Concurrent CFD Meshing Boundary Conditions Sove (Batch) Post Report Processing Generation 25%~35% Time Figure 4: Diagram shows how both Conventional and Upfront CFD require extra workflow processes to perform their analysis programs. Embedded Concurrent CFD uses the live M geometry. This saves time and effort allowing the design to perform more iterations of a design in less time. In Figure 4 it becomes apparent why concurrent CFD is different to conventional and upfront CFD. By expanding the CFD workflow procedures, we can see they involve a number of process steps to obtain a full analysis report on a design. Both conventional and upfront CFD require geometry transferring from the M system and cleaning it up so it s suitable for analysis. This process has to be repeated each time a design change occurs, to keep the M geometry and CFD analysis synchronized. Typically this approach will require the geometry s fluid spaces to be watertight for the analysis. In M terms this is referred to as healing the geometry to make it manifold, whereas analysts often refer to it as cleaning the M model. This is a generic requirement for CFD analysis, so it appears in all three approaches. Another process in both conventional and upfront CFD is the Create Cavity step. Most conventional CFD meshing tools work by meshing a solid, so they require a solid object to mesh. For a CFD simulation the solid object is the flow space, which for conventional and upfront CFD tools has to be created as a dummy part within the M system by Boolean subtraction of the entire model from an encapsulating solid. This is usually done in the M system and it s this inverted flow space that is transferred to the external third party CFD software for meshing and analysis. 7

8 By comparison, M embedded concurrent CFD works rather differently. The geometry used for the analysis is native to the M system. This means that there is no geometry transfer step because the designer never has to leave his/her M software. Concurrent CFD therefore eliminates the transfer geometry and create cavity steps, and effectively meshes in one step. Meshing still takes place, but only takes minutes rather than hours of iterating back and forth. This speeds up a user s workflow, allowing them time to explore what if optimization changes which could enhance still further a designs reliability and overall manufacturing costs. Concurrent CFD provides one final benefit that s not shown in the diagram. As mechanical designers undertake their own analyses they quickly learn how to build analysis-friendly geometry within their M software, further eliminating the clean geometry step, so the time savings can be even greater than those indicated! CFD Fluid Flow Analysis is Shaping the Next Generation of Aircraft M modeling is standard operating procedure in the aerospace industry and now flexible CFD tools are opening the door to similar benefits when fluid analysis is needed. Aerospace requirements encompass hundreds of applications for fluid dynamics modeling and simulation during the development process, including: Engine intake, bypass and exhaust systems Air ducts, manifolds, filters, valves, nozzles and pumps Hydraulic systems of all kinds Fuel systems and tanks (including cryogenic cooling, fuel storage and fuel cells) Cooling systems for electronics Heat exchangers and heat sinks Fuel and air filtration systems Cabin/cockpit ventilation and thermal management for passenger comfort Environmental control systems Anti-icing systems Emission control and noise-reduction systems Aerodynamics and heat transfer in and around missiles and rockets Film cooling and kinetic heating effects Braking and thrust-reversal systems Subsonic and supersonic flows over surfaces or structures Aerodynamics of discrete components such as wing/fuselage pods, engine nacelles and thrust chambers, external antennas and windshield wipers Aerodynamics of an entire aircraft How Real-World Designers are Using CFD Solutions The foregoing sections in this document emphasize the numbers and confirm that modeling offers a wealth of advantages compared to building physical prototypes, most importantly the savings in time and cost. Now it is time to look at some real-world examples for proof of CFD effectiveness when development deadlines are tight, quality is critical, and costs must be kept to a minimum. Bell Helicopter Improves Safety, Saves Cost on Fuel Tank Design Requirements Bell Helicopter manufactures helicopters designed for a broad range of commercial and military applications. The latter class of aircraft includes defensive features designed to protect the helicopter and its occupants in the most adverse situations. Bell Helicopter needed a cost-effective 8

9 evaluation solution that would give reliable results and guide the design of these and other complex features. Bell engineers were tasked with reviewing and refining a system that injects nitrogen gas into the helicopter s fuel tank to displace oxygen as the fuel is consumed. This makes the tank less likely to ignite if it is hit by an incendiary projectile. The incoming nitrogen must fill the tank s recesses rapidly since, after all, the assumption is that the helicopter is under hostile fire and needs to escape as quickly as possible. How long must the pilot wait before taking off from the hot landing zone? When can he or she be confident that air in the fuel tank won t jeopardize the aircraft s safety? It is a question of time, and seconds matter. Historically the question has been answered by running physical tests with actual hardware components pumps, valves, and the tank itself. This method of testing is very expensive and time-consuming. And in Bell s case the costs are multiplied because the venting system is built by a subcontractor in Europe, and personnel from the other companies involved must travel to the test site with expensive equipment to set up and run the test. Solution The engineer responsible for the evaluation chose the Mentor Graphics FloEFD Concurrent CFD Analysis tools to examine the internal flow characteristics of the gases in the helicopter s fuel tank. She referred to Bell s own detailed work procedures and best practices in examining the tank s geometry. She obtained the initial conditions from Bell s integrated product team and used them as boundary conditions for the solid model. After creating the mesh in FloEFD (Figure 5) she performed a sensitivity analysis to verify that the solution was not mesh-dependent. This extra degree of care is important in critical applications such as characterizing the fuel tank behavior. The mesh must be built with sufficient resolution to reveal small imperfections in the fluid flow. Figure 5: The Bell engineer built a mesh using embedded FloEFD tools. This mesh guided the analysis of the fuel tank s interior flow characteristics. The localized response of each cell in the mesh contributes to the calculation of the overall results, and the size (resolution) of the cells can be optimized for any particular simulation. 9

10 With the mesh defined and analyzed, the engineer solved the model and generated the visualized output diagram (Figure 6). The tool also produced a chart that shows oxygen concentration in the tank over time. Results The isosurfaces of oxygen concentration resulting from the simulation revealed that several areas in the tank were not being adequately vented. Consequently a potential problem was identified and solved at very low cost compared to physical testing. Among the design changes included were adding a second redistribution nozzle. Had this issue remained undetected until the prototype phase, it would have been far more expensive to correct the problem and moreover, might have delayed the project. Here FloEFD made it possible for a Figure 6: FloEFD tools produced a visualization of the flow staff-level engineer to evaluate and of gases within the helicopter fuel tank. The study revealed correct a suspected problem without the intervention of a specialized fluid several areas that were not adequately vented. dynamics analyst. Concurrent CFD is perfect for situations such as this. The timely and accurate FloEFD analysis saved the cost of late-cycle hardware revisions. Equally important, the simple fact that a design engineer was able to solve the problem spared the expense and time of calling in a specialist with dedicated analysis tools. Liebherr-Aerospace Toulouse SAS Turns to Simulation to Ensure Passenger Comfort Requirement Liebherr-Aerospace Toulouse SAS in Toulouse, France is one of Europe s leading manufacturers of on-board aircraft ventilation systems. The company, recognizing that design automation tools can provide key cost and quality advantages in its very competitive field, set out to compare the results of fluid flow modeling and simulation with the real-world behavior of a ventilation system currently in service. After conducting research in cooperation with CERFACS3, Liebherr-Aerospace approached the Mentor Graphics Mechanical Analysis Division to verify the performance of its FloVENT 3D Airflow Modeling application when modeling air circulation in an aircraft cabin. FloVENT is a powerful CFD software tool that predicts airflow, heat transfer and contamination distribution in and around structures of all types and sizes. Commonly used to assess flows in buildings and even shopping malls, FloVENT is equally capable of modeling the smaller volumes in vehicles and aircraft. Because the Liebherr-Aerospace evaluation project used an existing, installed ventilation system as a point of reference, there was plenty of experimental data available to compare with the simulation results. To ensure impartiality, the Mentor Graphics team carried out a blind study without 3 10 The European Centre for Research and Advanced Training in Scientific Computation

11 access to the experimental data. Solution The first challenge in the project was to confirm that the 3D files from Liebherr-Aerospace Toulouse could be efficiently imported for use in FloVENT. These files, which contained the designs of seats and the cockpit, were produced in the CATIA M environment. CATIA output is just one of the formats that FloVENT accepts, and the supplied content ported easily into FloVENT. This gave the Mentor Graphics engineers the raw material they needed to model a section of the aircraft (Figure 7). They chose this approach because it produces simple models with short calculation times. The result is a valid microcosm of the full-size cabin. Had it been desirable to model an entire aircraft cabin, this too would be possible and in fact is common practice when designing railway cars, to cite one example. Results The evaluation project took about three weeks to complete, during which several models were generated. The outcome was as expected: the FloVENT modeling process successfully simulated the performance of the Liebherr-Aerospace Toulouse aircraft ventilation system hardware. The French manufacturer s engineers confirmed that the simulation results closely matched the physical phenomena in the airliner cabin. Fanger thermal comfort calculations, a component of the FloVENT toolset, can be used to reliably quantify the level of the ventilation performance. Working together, Mentor Graphics and Liebherr-Aerospace Toulouse SAS have confirmed that an accurate digital model of the aircraft cabin offers the same level of design assurance as a prototype built from aluminum and composites. Importantly, the three-week time-to-results of the experiment implies that FloVENT users can look forward to reduced prototyping costs and shorter design schedules. Figure 7: The FloVENT thermal solution modeled a section of an aircraft cabin and successfully duplicated the performance of installed ventilation system hardware. 11

12 Shaw Aero Devices Engineer Uses CFD to Boost Fuel Valve Performance Requirement Shaw Aero Devices, Inc. (Naples, Florida) manufactures valves for aerospace applications. A Shaw customer was poised to order a large quantity of a solenoid valve that appeared to be very similar to one of Shaw s off-the-shelf products. But first Shaw had to meet some conditions. The order was for fuel control valves for an unmanned aerial vehicle (UAV). Six of these valves operate in a manifold to route fuel to distributed tanks and keep the aircraft in balance as fuel is consumed. The UAV s manufacturer wanted to increase the aircraft s payload by using a smaller fuel pump a pump too light to overcome the pressure drop of the standard Shaw valves. To earn the order, Shaw Aero Devices would need to characterize and redesign the valve to eliminate constrictions that were causing the excessive drop in pressure through the valve. And the whole project had to meet a very aggressive customer timeline. In the past we would have had to make an educated guess on what was raising the pressure drop in the valve said Preble. For each guess we would build a prototype to see if we were right or not. Each prototype would cost about $3000 and would t ake about a month to machine, assemble and test. One of the weaknesses of this build-and-test approach is that physical tests determine the pressure drop in each new design iteration but provide very little additional information to help us diagnose problems such as determining which areas of the valve are constricting fluid flow. Shaw project engineer Rob Preble explains the challenge Shaw engineers knew that the redesign would require at least three expensive prototypes. After all, they were being asked to reduce the pressure drop by almost 88%. Would three prototypes be enough? There was no guarantee of success. Solution In this case, Preble simulated the original valve s design using the Mentor Graphics FloEFD Concurrent CFD Analysis tool. FloEFD represents a new generation of easy-to-use CFD software, affordable and accessible to small- and medium-sized manufacturers whose products involve fluid flow. Preble completed the first software prototype in just one day. Although he had prior CFD experience, the M-integrated FloEFD tools sped his work by allowing him to build and test virtual prototypes without translating and retranslating data as it moved from to CFD and back repeatedly. The results from FloEFD revealed areas in which the old design could be improved and by repeating a series of simulations at various flow rates, Preble was able to locate and correct the problem areas in the valve. FloEFD reduced the time required to simulate flow by analyzing each evolving model and automatically identifying fluid and solid regions without user interaction. Results The product knowledge gained from the first valve model was crucial to the project. First, it established that the modeling tool s output closely matched the behavior of the existing valve. Then it enabled astute decisions about the changes that needed to be made. Viewing the cut plot of the pressure gradient of the first design run, Preble noticed that the valve s We had complete confidence in the results because FloEFD provided such an accurate simulation of the original design. We took our simulation results to the customer and were awarded the contract to build the valve. Rob Preble, project engineer, Shaw Aero Devices 12

13 angled wing seat was a key source of the pressure drop. He modeled a new valve with a larger opening and without the angled valve seat (Figure 8). After several prototypes and revisions on a similar scale, the final design emerged. Figure 8: The original Shaw Aero Devices solenoid valve shown here exhibited a pressure drop of more than 6 psi and was unable to meet the customer s requirements. The Cut Plot shows the results of two design revisions that reduced the drop to about 1 psi. Subsequent revisions reduced the drop all the way to.71 psi, well within the customer s specifications. The entire redesign was completed without building a single hardware prototype of the valve. Ultimately the new design reduced the pressure drop from 6.09 psi (at a flow rate of 4.45 gal/min) to 0.71 psi, meeting the customer s exacting specifications. Equally important, the project met the purchaser s urgent schedule requirements. Instead of a month-long development cycle for each of several hardware prototypes, Shaw engineers were able to complete virtual prototypes in as little as one day. Crane Aerospace & Electronics Simulates Six Heat Sinks in Record Time Requirement Crane Aerospace & Electronics manufactures a diverse range of aerospace systems and components, including DC power elements. Commissioned to develop such a subsystem for a commercial airliner, Crane s engineers had to meet a challenging requirement: to design a power supply that could work in either the vertical or horizontal position. Most conventional units work in one orientation or the other but not both; heat sinks tend to disperse heat efficiently in one axis (say, the vertical) but allow heat to build up when rotated 90 away from that axis, that is, horizontal. Crane engineers brainstormed and came up with six possible designs for the new device. Unfortunately the development schedule imposed by the client didn t allow enough time to physically prototype and test all six variations. 13

14 Solution The Crane engineers used FloTHERM 3D thermal simulation software to evaluate the various designs, and they did so twice for each test once horizontally and once vertically. FloTHERM was chosen because it generates models quickly and makes it easy to change boundary conditions, environmental conditions and gravitational direction. Crane s designers used these capabilities to model all six geometries at various altitudes and ambient temperatures. Results The simulation results showed that a heat sink design combining a plate and Not only were we able to quickly find and then optimize the standoffs provided the best overall best design for the heat sink, thermal simulation also enabled us to optimize its performance to a level that would have been performance for both orientations. impossible to achieve with the build-and-test method within The engineers then turned to the s our schedule constraints. oftware again to help them find the optimal length of the standoff. Mark Resler, Mechanical Engineer Significantly, FloTHERM simulation (Figure 9) enabled the engineers to fine-tune the design beyond what would have been possible with hardware prototypes in the allotted time. Figure 9: Six virtual prototypes were modeled and ultimately produced a successful heat sink solution, eliminating the need for costly hardware prototyping. 14

15 Tecnobit Finds a Cool Way to Package Avionics Requirement Tecnobit, an industrial and defense electronics company based in Madrid, Spain, designed a special chassis to house cockpit avionics in an enclosure whose maximum dimension was approximately 10 cm. The enclosure is shown in Figure 10. By design, the system was totally sealed, without ventilation slots. This made it necessary to achieve the necessary heat transfer through the outside surface by conduction, radiation and natural convection. Unfortunately this design ideal is in conflict with the trend toward higher power and heat dissipation in avionics systems. Minimizing weight and optimizing space are always key design goals but an effective cooling solution is essential to reliability. Thermal management can be a significant design bottleneck. An obvious approach is a cooling fan, but system designers typically avoid using fans to minimize the potential for failures. All in all, thermal management is a major challenge from the very first design phase. Tecnobit s preliminary design did not meet the design requirements; it was clearly unacceptable from a thermal standpoint. The company s engineers modified the internal chassis structure to increase heat conduction from the components to the chassis walls. At the same time, the Tecnobit design team added special heat-dissipating fins to the chassis outer surface to transport the heat away from the box. Sand-blasting treatment and electrostatic painting further enhanced convection and radiation exchange with the external ambient air. Solution Tecnobit engineers used FloTHERM 3D thermal simulation to perform steady-state and transient thermo-fluid simulations and predict system thermal behavior as the various heat-conduction refinements were added (Figure 11). Virtual prototypes supplanted Tecnobit s traditional design approach, which involved building or refining a hardware prototype to test each new improvement in the evolving design. Results All of the design options for the avionics chassis were evaluated with no need for hardware prototypes. The simulations enabled the Tecnobit engineers to optimize the thermal design rapidly while observing the effects of their design changes. They found FloTHERM s method of representing electronic components to be particularly useful, since it enabled engineers to either use simple thermal data from component datasheets in many instances, or switch to detailed 3D models for critical components. Ultimately the team reduced component junction temperatures by 40 C compared with the initial design. Today FloTHERM is the standard thermal design tool at Tecnobit, recognized by the company s thermal electronic engineers for its powerful prototyping tools and its ease of use. Figure 10: The thermal design studies for this compact, fully-enclosed Technobit avionics package were completed by FloTHERM, eliminating the need for hardware prototypes. 15

16 Conclusion Powerful and flexible CFD simulation tools have joined M modeling solutions in supporting the fast, efficient design processes today s aerospace market demands. Many if not most aircraft assemblies can benefit from some level of flow analysis, whether the fluid is aviation fuel, supersonic airflow, or the heat from a radiator. With easy-to-use and affordable tools such as Mentor Graphics FloEFD, FloVENT, and FloTHERM, aerospace engineers can make informed design decisions during the early phases of a project. Fluid dynamics modeling and simulation tools like these are the solution of choice when costs must be contained and deadlines met. Simulation Delivers Answers When They are Most Needed The value of simulation has been demonstrated time and again. One important facet of simulation s cost benefit is easy to summarize with a simple statement: The cost of a design error increases by an order of magnitude with each advancing step in the development and distribution of a product. This axiom holds true whether the technology in question is an integrated circuit or an avionics subsystem. Simulation reduces the risk of perpetuating errors. Figure 11: Natural convection view of the Tecnobit product showing temperature and air speed planes. Design errors are the result of human fallibility and/or miscommunication. When an engineer detects his own error and corrects it before handing off the design, it may cost just a few minutes, equivalent to a few dollars, to solve the problem. Very likely he has all the information he needs to make the necessary changes, and can rectify the mistake with just a few keystrokes. Even if the error persists into the validation phase, the cost of correcting it may be relatively low. But suppose the error escapes the designer s notice and finds its way into the first prototype. This amplifies the cost of correcting the problem by a factor of 10 (an order of magnitude) at the very least. The prototype will need revisions, or might even have to be scrapped. Suddenly an issue that could have been resolved for a few dollars costs ten times as much to repair and that doesn t count the cost in project delays. If, somehow, the error persists into production the cost multiplies by another factor of 10 (at least). Finished products not just prototypes might need to be scrapped or modified at great cost. Now the same problem that could have been solved for just a few dollars costs hundreds of dollars to fix. In addition, the schedule delays are painful, especially if the product is aimed at a market opportunity whose duration is brief. Market share can be seriously diminished if a product misses its market window. And finally, the unthinkable: the error goes undetected all the way through manufacturing and products get into the hands of end users. Following the magnitude curve, costs increase by another factor of 10 into the thousands of dollars. It may be necessary to issue a recall whose massive costs are made even worse by the damage to the company s reputation. A design problem that reaches the end-product stage is almost certain to diminish the profitability of that product, and perhaps the company itself. 16

17 Figure 13 illustrates the cost progression. While the exact cost figures will vary from one project to the next, the frames highlight the importance of catching design errors as early as possible Figure 13: The cost of correcting design errors increases by approximately an order of magnitude for each step in a design s progress from the engineering lab to the end-user. The cost of making a field repair can be thousands of times higher than that of fixing the error at the beginning. Simulation helps designers avoid these multiplying costs by giving them the information needed to make the right design decisions at the right time. Simulation applies rules that prevent design errors in the first place, and can detect errors before they ripple through a series of costly prototypes and into production. It provides an in-depth understanding of the product when it is least expensive to address problems. Getting simulation and modeling involved at the beginning of the design process means getting crucial answers about the emerging product as early as possible, and having that information ready to use when it is most needed. 上海坤道信息技术有限公司 ｗｗｗ ｓｉｍｕ ｃａｄ ｃｏｍ ０２１ ６２１５７１００ 17