Risk-based Fatigue Estimate of Deep Water Risers -- Course Project for EM388F: Fracture Mechanics, Spring 2008

Size: px
Start display at page:

Download "Risk-based Fatigue Estimate of Deep Water Risers -- Course Project for EM388F: Fracture Mechanics, Spring 2008"

Transcription

1 Rsk-based Fatgue Estmate of Deep Water Rsers -- Course Project for EM388F: Fracture Mechancs, Sprng 2008 Chen Sh Department of Cvl, Archtectural, and Envronmental Engneerng The Unversty of Texas at Austn Abstract Marne rser s an mportant component for the offshore ol platforms. Rser falure results n cessaton of producton and may lead to spllage and polluton. The deepwater rsers under cyclc load due to ocean current experence sgnfcant gue damage. Ths paper focuses on the fundamental gue analyss phlosophy of the deepwater rsers, coverng the dscusson of dfferent sources of cyclc load, S-N curves and combnaton of gue damages. Besdes the determnstc approach, the rsk based gue analyss s also studed n the probablstc feld. 1. Introducton Ol and natural gas have been produced from offshore locatons snce 1950s. At that tme all the platforms were fxed platforms whch were sttng on the seabed. Wth the ol exploraton and producton move to the deeper water, the other types of ol platform, such as tenson-leg platforms, floatng producton system (FPS) become more popular (See Fgure 1). Fgure 1 Fxed platform and Floatng producton system Rsers are the structure systems whch connect the platforms at the ocean surface and the structures on the seabed. The man functon of the rser system s to convey flud (crude 1

2 ol or the natural gas) between wells and platforms. Typcally the rsers are made of steel or ttanum ppe wth an outer dameter less than 30 nches and a wall thckness less than 1 nch (See Fgure 2). Wth the producton movng nto deeper water, the rsers become longer and longer, usually are about 3,000 ~ 6000 feet, and the longest ones are over 10,000 feet. The rsers are prone to be vbrated under the exctaton of current flow due to ther slenderness and low-dampng ratos. The sustan vbraton may cause gue damage whch may lead to cessaton of producton or spllage and polluton to the ocean. In ths paper, the basc steps of rser gue analyss were outlned. The procedures to estmate the probablty of gue falure usng Monte Carlo smulaton were ntroduced also. Fgure 2 Rsers 2 Rser Fatgue Analyss 2.1 Two types of components Generally the gue lfe conssts of two phases: crack ntaton and crack propagaton. For the un-welded components, such as the seamless ppes, the crack ntaton perod takes over 95% of the total gue lfe. And the gue strength ncreases wth materal tensle strength. For the welded jonts, the ntal cracks, such as the welded toes, always present. The crack propagaton perod represents the bulk of the total gue lfe. The crack propagaton rate s dependent on the propertes of base materal, envronment and other factors, so there s no consstent trend between gue strength and materal tensle strength. 2.2 Fatgue crteron and S-N curves The gue crteron s represented by D DFF 1 where D = Accumulated gue damage, estmated by Palmgren-Mner rule DFF = Desgn gue factor, whch depends on the safety classes, see Table 1. 2

3 Table 1 Classfcaton of Safety class and DFF values Safety class Defnton DFF Low Where falure mples low rsk of human njury and mnor 3.0 envronmental and economc consequences Normal Where falure mples rsk of human njury, sgnfcant 6.0 envronmental polluton or very hgh economc or poltcal consequences Hgh Where falure mples hgh rsk of human njury, sgnfcant envronmental polluton or very hgh economc or poltcal consequences 10.0 If approprate, fracture mechancs may be used to analyze the rser gue. However, the S-N curves based approach s commonly used whch correlates the number of stress cycles to falure and a constant stress range. N = a S m log( N ) = log( a) m log( S ) N: Number of stress cycles to falure S: Constant stress range a, m : Emprcal constants obtaned from experments 2.3 Fatgue loads Rser gue analyss should consder all relevant cyclc load effects, such as (a) Frst order wave effects (b) Second order floater moton (c) Vortex nduced vbraton (d) Thermal and pressure nduced stress cycles (e) Collsons (f) Fabrcaton and nstallaton loads (g) Others cyclc loads. Typcally, frst order wave effects, second order floater moton, and vortex nduced vbraton have relatvely larger contrbuton to rser gue. Ths paper wll focus on the analyss of gue due to the frst order wave effects and second order floater moton. The frst order wave effects s also called wave frequency effects, whch ncludes wave frequency floater motons and drect wave loadng on rsers. Second order floater moton means low frequency (the frequency s much lower than the natural frequency) response of floater motons, so also called low frequency effects. 3 Long-term gue damage due to wave frequency and low frequency effects The general approach for estmate the wave frequency and low frequency gue damage takes the followng procedures. 3

4 (a) Dvde all sea current state data nto a number of representatve blocks; (b) Use a sngle sea state to represent all the sea-state wthn one block. The probabltes of occurrence for all sea-states wthn the block are lumped to the selected sea-state. Here should be noted that, the selected sea-state should gve equal or greater damage than all the orgnal sea-state wth the block. (c) The long-term gue damage s equal to the weghted summaton of all short-term gue damage, expressed as D N = s = 1 D P n whch D : Long-term gue damage N S : Number of sngle sea-state, number of blocks of sea-state D : Short-term gue damage P : Sea-state probablty Table 2 and Table 3 gve an example of the scattered sea states and the lumped sea states. Table 2 shows the probablty of scatted sea states whch are grouped by wave heght ( H s ) and wave perod ( T p ). For example the sea state havng wave perod Tp = 8 ~ 10 sec. and wave heght H s = 1.00 ~ meters accounts for 4.74% of total occurrence. Note that ths table s uncompleted. It does not nclude the sea states havng perod 4~6 sec. All the scattered sea states were lumped and represented by 7 representatve sea states, whch are summarzed n Table 3. H se s the effectve wave heght for each representatve sea state, whch wll gve equvalent gue damage compared to all the scattered sea state n that bn. Calculate the short term gue damage for each lumped sea state, weghed by the sea state probablty and the fnal summaton wll gve the long term gue damage. 4

5 Table 2 Scattered sea states (uncompleted) Table 3 Lumped sea states 4 Short Term Fatgue -S-N Curves Approach The S-N curves approach s the general practce to calculate the short term gue n the rser ndustry. Besdes the lnear S-N curves, the blnear S-N curves represent the expermental data better and are frequently used. So here the method of usng the blnear S-N curves and the Mner-Palmgren rule to estmate the accumulated gue damage are ntroduced. 4.1 Blnear S-N curves N a1 S = a2 S m1 m2 S > S S S sw sw As same as the lnear S-N curves, N s the number of stress cycles to falure, for a constant stress range S. a, a and m, m are emprcal constants obtaned from experments. The basc defnton of blnear S-N curves s showed n a log-log scaled plot, see Fgure 3. 5

6 Fgure 3 Defnton of Blnear S-N curves (log-log scales) 4.2 Mner-Palmgren rule Palmgren-Mner rule s used for accumulaton of gue damage caused by varable stress ampltudes. The basc equaton s D = n( S ) N( S ) When n ( S ) s the number of stress cycles wth stress range S ; and N ( S ) s the number of stress cycles to falure wth stress range S. For a gven tme T, the accumulated gue damage can be obtaned from the followng equaton, Tf S sw V m Tf 2 D = S f fs( s) ds a 0 2 V m1 s( s) ds + S a S sw 1 In whch, f = Mean frequency of stress cycles V f s (s) = Probablty densty functon for stress cycles The above equatons consttute the basc formulatons for accumulated gue damage under statonary envronmental condtons 6

7 5 Fatgue Stress The gue stress consdered for rsers s the prncple stress wth a thckness correcton factor. 5.1 Thckness correcton factor S S = 0 t SCF t ref k Where: S 0 = Nomnal stress range SCF = Stress concentraton factor k t t ref than a reference wall thckness t t = t = Thckness correcton factor. Apples for ppes wth a wall thckness t greater norm norm 0.5 t corr before after t ref = 25mm nstallaton nstallaton t norm = Nomnal ppe wall thckness t = Corroson allowance, assumng lnear corroson loss corr 5.2 Nomnal stress The nomnal stress component of ppes s a lnear combnaton of the axal and bendng stresses gven by σ ( t) = σ ( t) + σ ( θ, t) a Te ( t) Axal stress: σ a ( t) = π ( D t ) t M D t Bendng stress: σ ( ) M ( θ, t) = M y ( t)sn( θ ) + M Z ( t)cos( θ ) 2I In whch, D s the outer dameter. T e s the effectve tenson. M y and M Z are the bendng moments about the local y and z axes, I s the moment of nerta. See Fgure 4. The stress vares along the crcumference, so at least 8 ponts along the crcumference needs to be analyzed to dentfy the most crtcal locaton. 7

8 Fgure 4 Cross-secton of rsers 6. Uncertantes of Fatgue Estmate and Monte Carlo Smulaton Many factors assocate wth rser gue analyss, ncludng the nput varables (such as drag coeffcent, ppe wall thckness, etc.), are stochastc n nature. These uncertantes need to be studed and the probablstc models for all stochastc varables should be set up based on lterature, experence and data analyss. If lackng of nformaton, the values n Table 4 may be used. Table 4 Stochastc varables After approprate probablstc models obtaned for all the stochastc varables, Monte Carlo smulaton can be used to get the rsk based gue estmaton. The advantage of Monte Carlo smulaton s that gven accurate probablstc models any desred level of accuracy can be acheved by ncreasng the number of teraton. The basc steps of the Monte Carlo smulatons are outlned as followng, (1) Establsh the probablstc model (mode type, mean and standard devaton) for each ndependent basc nput varables; 8

9 (2) Samplng probablty dstrbuton to obtan pont estmate for each ndependent nput varable; (3) Calculate dependent and then output varables; (4) Do loop for sets 2-3 (typcally more than 100,000 tmes for satsfed accuracy); (5) Post-process results to obtan probablstc dstrbuton of the output. 7. Summary (1) Fatgue damage estmaton s crtcal mportant for rser desgn and analyss. Unfortunately, the procedures and consderatons are very complex. (2) Blnear S-N curves and Mner rule are the typcal approach. (3) Fatgue damage and gue lfe can be estmated by usng the mean value of the nput varables. (4) Probablty of gue falure can be estmated by the stochastc model of the nput varables and Monte Carlo smulaton. 8. Reference DNV, 2005, Rser gue, DNV-RP-F204 Sen, T.K., Probablty of gue falure n steel catenary rsers n Deep Water, Journal of Engneerng Mechancs, Sep

SPEE Recommended Evaluation Practice #6 Definition of Decline Curve Parameters Background:

SPEE Recommended Evaluation Practice #6 Definition of Decline Curve Parameters Background: SPEE Recommended Evaluaton Practce #6 efnton of eclne Curve Parameters Background: The producton hstores of ol and gas wells can be analyzed to estmate reserves and future ol and gas producton rates and

More information

FORCED CONVECTION HEAT TRANSFER IN A DOUBLE PIPE HEAT EXCHANGER

FORCED CONVECTION HEAT TRANSFER IN A DOUBLE PIPE HEAT EXCHANGER FORCED CONVECION HEA RANSFER IN A DOUBLE PIPE HEA EXCHANGER Dr. J. Mchael Doster Department of Nuclear Engneerng Box 7909 North Carolna State Unversty Ralegh, NC 27695-7909 Introducton he convectve heat

More information

Risk Model of Long-Term Production Scheduling in Open Pit Gold Mining

Risk Model of Long-Term Production Scheduling in Open Pit Gold Mining Rsk Model of Long-Term Producton Schedulng n Open Pt Gold Mnng R Halatchev 1 and P Lever 2 ABSTRACT Open pt gold mnng s an mportant sector of the Australan mnng ndustry. It uses large amounts of nvestments,

More information

The Development of Web Log Mining Based on Improve-K-Means Clustering Analysis

The Development of Web Log Mining Based on Improve-K-Means Clustering Analysis The Development of Web Log Mnng Based on Improve-K-Means Clusterng Analyss TngZhong Wang * College of Informaton Technology, Luoyang Normal Unversty, Luoyang, 471022, Chna wangtngzhong2@sna.cn Abstract.

More information

Fatigue Assessment of Concrete Foundations for Wind Power Plants

Fatigue Assessment of Concrete Foundations for Wind Power Plants Fatgue Assessment of Concrete Foundatons for Wnd Power Plants Master of Scence Thess n the Master s Programme Structural Engneerng and Buldng Performance Desgn FRIDA GÖRANSSON, ANNA NORDENMARK Department

More information

Communication Networks II Contents

Communication Networks II Contents 8 / 1 -- Communcaton Networs II (Görg) -- www.comnets.un-bremen.de Communcaton Networs II Contents 1 Fundamentals of probablty theory 2 Traffc n communcaton networs 3 Stochastc & Marovan Processes (SP

More information

IMPACT ANALYSIS OF A CELLULAR PHONE

IMPACT ANALYSIS OF A CELLULAR PHONE 4 th ASA & μeta Internatonal Conference IMPACT AALYSIS OF A CELLULAR PHOE We Lu, 2 Hongy L Bejng FEAonlne Engneerng Co.,Ltd. Bejng, Chna ABSTRACT Drop test smulaton plays an mportant role n nvestgatng

More information

benefit is 2, paid if the policyholder dies within the year, and probability of death within the year is ).

benefit is 2, paid if the policyholder dies within the year, and probability of death within the year is ). REVIEW OF RISK MANAGEMENT CONCEPTS LOSS DISTRIBUTIONS AND INSURANCE Loss and nsurance: When someone s subject to the rsk of ncurrng a fnancal loss, the loss s generally modeled usng a random varable or

More information

HYPOTHESIS TESTING OF PARAMETERS FOR ORDINARY LINEAR CIRCULAR REGRESSION

HYPOTHESIS TESTING OF PARAMETERS FOR ORDINARY LINEAR CIRCULAR REGRESSION HYPOTHESIS TESTING OF PARAMETERS FOR ORDINARY LINEAR CIRCULAR REGRESSION Abdul Ghapor Hussn Centre for Foundaton Studes n Scence Unversty of Malaya 563 KUALA LUMPUR E-mal: ghapor@umedumy Abstract Ths paper

More information

Calculation of Sampling Weights

Calculation of Sampling Weights Perre Foy Statstcs Canada 4 Calculaton of Samplng Weghts 4.1 OVERVIEW The basc sample desgn used n TIMSS Populatons 1 and 2 was a two-stage stratfed cluster desgn. 1 The frst stage conssted of a sample

More information

Multivariate EWMA Control Chart

Multivariate EWMA Control Chart Multvarate EWMA Control Chart Summary The Multvarate EWMA Control Chart procedure creates control charts for two or more numerc varables. Examnng the varables n a multvarate sense s extremely mportant

More information

RESEARCH ON DUAL-SHAKER SINE VIBRATION CONTROL. Yaoqi FENG 1, Hanping QIU 1. China Academy of Space Technology (CAST) yaoqi.feng@yahoo.

RESEARCH ON DUAL-SHAKER SINE VIBRATION CONTROL. Yaoqi FENG 1, Hanping QIU 1. China Academy of Space Technology (CAST) yaoqi.feng@yahoo. ICSV4 Carns Australa 9- July, 007 RESEARCH ON DUAL-SHAKER SINE VIBRATION CONTROL Yaoq FENG, Hanpng QIU Dynamc Test Laboratory, BISEE Chna Academy of Space Technology (CAST) yaoq.feng@yahoo.com Abstract

More information

9.1 The Cumulative Sum Control Chart

9.1 The Cumulative Sum Control Chart Learnng Objectves 9.1 The Cumulatve Sum Control Chart 9.1.1 Basc Prncples: Cusum Control Chart for Montorng the Process Mean If s the target for the process mean, then the cumulatve sum control chart s

More information

Damage detection in composite laminates using coin-tap method

Damage detection in composite laminates using coin-tap method Damage detecton n composte lamnates usng con-tap method S.J. Km Korea Aerospace Research Insttute, 45 Eoeun-Dong, Youseong-Gu, 35-333 Daejeon, Republc of Korea yaeln@kar.re.kr 45 The con-tap test has the

More information

The Effect of Mean Stress on Damage Predictions for Spectral Loading of Fiberglass Composite Coupons 1

The Effect of Mean Stress on Damage Predictions for Spectral Loading of Fiberglass Composite Coupons 1 EWEA, Specal Topc Conference 24: The Scence of Makng Torque from the Wnd, Delft, Aprl 9-2, 24, pp. 546-555. The Effect of Mean Stress on Damage Predctons for Spectral Loadng of Fberglass Composte Coupons

More information

Study on CET4 Marks in China s Graded English Teaching

Study on CET4 Marks in China s Graded English Teaching Study on CET4 Marks n Chna s Graded Englsh Teachng CHE We College of Foregn Studes, Shandong Insttute of Busness and Technology, P.R.Chna, 264005 Abstract: Ths paper deploys Logt model, and decomposes

More information

Recurrence. 1 Definitions and main statements

Recurrence. 1 Definitions and main statements Recurrence 1 Defntons and man statements Let X n, n = 0, 1, 2,... be a MC wth the state space S = (1, 2,...), transton probabltes p j = P {X n+1 = j X n = }, and the transton matrx P = (p j ),j S def.

More information

Causal, Explanatory Forecasting. Analysis. Regression Analysis. Simple Linear Regression. Which is Independent? Forecasting

Causal, Explanatory Forecasting. Analysis. Regression Analysis. Simple Linear Regression. Which is Independent? Forecasting Causal, Explanatory Forecastng Assumes cause-and-effect relatonshp between system nputs and ts output Forecastng wth Regresson Analyss Rchard S. Barr Inputs System Cause + Effect Relatonshp The job of

More information

The Analysis of Outliers in Statistical Data

The Analysis of Outliers in Statistical Data THALES Project No. xxxx The Analyss of Outlers n Statstcal Data Research Team Chrysses Caron, Assocate Professor (P.I.) Vaslk Karot, Doctoral canddate Polychrons Economou, Chrstna Perrakou, Postgraduate

More information

x f(x) 1 0.25 1 0.75 x 1 0 1 1 0.04 0.01 0.20 1 0.12 0.03 0.60

x f(x) 1 0.25 1 0.75 x 1 0 1 1 0.04 0.01 0.20 1 0.12 0.03 0.60 BIVARIATE DISTRIBUTIONS Let be a varable that assumes the values { 1,,..., n }. Then, a functon that epresses the relatve frequenc of these values s called a unvarate frequenc functon. It must be true

More information

SIX WAYS TO SOLVE A SIMPLE PROBLEM: FITTING A STRAIGHT LINE TO MEASUREMENT DATA

SIX WAYS TO SOLVE A SIMPLE PROBLEM: FITTING A STRAIGHT LINE TO MEASUREMENT DATA SIX WAYS TO SOLVE A SIMPLE PROBLEM: FITTING A STRAIGHT LINE TO MEASUREMENT DATA E. LAGENDIJK Department of Appled Physcs, Delft Unversty of Technology Lorentzweg 1, 68 CJ, The Netherlands E-mal: e.lagendjk@tnw.tudelft.nl

More information

Portfolio Loss Distribution

Portfolio Loss Distribution Portfolo Loss Dstrbuton Rsky assets n loan ortfolo hghly llqud assets hold-to-maturty n the bank s balance sheet Outstandngs The orton of the bank asset that has already been extended to borrowers. Commtment

More information

Can Auto Liability Insurance Purchases Signal Risk Attitude?

Can Auto Liability Insurance Purchases Signal Risk Attitude? Internatonal Journal of Busness and Economcs, 2011, Vol. 10, No. 2, 159-164 Can Auto Lablty Insurance Purchases Sgnal Rsk Atttude? Chu-Shu L Department of Internatonal Busness, Asa Unversty, Tawan Sheng-Chang

More information

Fragility Based Rehabilitation Decision Analysis

Fragility Based Rehabilitation Decision Analysis .171. Fraglty Based Rehabltaton Decson Analyss Cagdas Kafal Graduate Student, School of Cvl and Envronmental Engneerng, Cornell Unversty Research Supervsor: rcea Grgoru, Professor Summary A method s presented

More information

Characterization of Assembly. Variation Analysis Methods. A Thesis. Presented to the. Department of Mechanical Engineering. Brigham Young University

Characterization of Assembly. Variation Analysis Methods. A Thesis. Presented to the. Department of Mechanical Engineering. Brigham Young University Characterzaton of Assembly Varaton Analyss Methods A Thess Presented to the Department of Mechancal Engneerng Brgham Young Unversty In Partal Fulfllment of the Requrements for the Degree Master of Scence

More information

State function: eigenfunctions of hermitian operators-> normalization, orthogonality completeness

State function: eigenfunctions of hermitian operators-> normalization, orthogonality completeness Schroednger equaton Basc postulates of quantum mechancs. Operators: Hermtan operators, commutators State functon: egenfunctons of hermtan operators-> normalzaton, orthogonalty completeness egenvalues and

More information

SIMPLE LINEAR CORRELATION

SIMPLE LINEAR CORRELATION SIMPLE LINEAR CORRELATION Smple lnear correlaton s a measure of the degree to whch two varables vary together, or a measure of the ntensty of the assocaton between two varables. Correlaton often s abused.

More information

CHAPTER EVALUATING EARTHQUAKE RETROFITTING MEASURES FOR SCHOOLS: A COST-BENEFIT ANALYSIS

CHAPTER EVALUATING EARTHQUAKE RETROFITTING MEASURES FOR SCHOOLS: A COST-BENEFIT ANALYSIS CHAPTER 17 EVALUATING EARTHQUAKE RETROFITTING MEASURES FOR SCHOOLS: A COST-BENEFIT ANALYSIS A.W. Smyth, G. Deodats, G. Franco, Y. He and T. Gurvch Department of Cvl Engneerng and Engneerng Mechancs, Columba

More information

CHOLESTEROL REFERENCE METHOD LABORATORY NETWORK. Sample Stability Protocol

CHOLESTEROL REFERENCE METHOD LABORATORY NETWORK. Sample Stability Protocol CHOLESTEROL REFERENCE METHOD LABORATORY NETWORK Sample Stablty Protocol Background The Cholesterol Reference Method Laboratory Network (CRMLN) developed certfcaton protocols for total cholesterol, HDL

More information

An Alternative Way to Measure Private Equity Performance

An Alternative Way to Measure Private Equity Performance An Alternatve Way to Measure Prvate Equty Performance Peter Todd Parlux Investment Technology LLC Summary Internal Rate of Return (IRR) s probably the most common way to measure the performance of prvate

More information

Faraday's Law of Induction

Faraday's Law of Induction Introducton Faraday's Law o Inducton In ths lab, you wll study Faraday's Law o nducton usng a wand wth col whch swngs through a magnetc eld. You wll also examne converson o mechanc energy nto electrc energy

More information

Forecasting the Demand of Emergency Supplies: Based on the CBR Theory and BP Neural Network

Forecasting the Demand of Emergency Supplies: Based on the CBR Theory and BP Neural Network 700 Proceedngs of the 8th Internatonal Conference on Innovaton & Management Forecastng the Demand of Emergency Supples: Based on the CBR Theory and BP Neural Network Fu Deqang, Lu Yun, L Changbng School

More information

Time Series Analysis in Studies of AGN Variability. Bradley M. Peterson The Ohio State University

Time Series Analysis in Studies of AGN Variability. Bradley M. Peterson The Ohio State University Tme Seres Analyss n Studes of AGN Varablty Bradley M. Peterson The Oho State Unversty 1 Lnear Correlaton Degree to whch two parameters are lnearly correlated can be expressed n terms of the lnear correlaton

More information

Optimal Bidding Strategies for Generation Companies in a Day-Ahead Electricity Market with Risk Management Taken into Account

Optimal Bidding Strategies for Generation Companies in a Day-Ahead Electricity Market with Risk Management Taken into Account Amercan J. of Engneerng and Appled Scences (): 8-6, 009 ISSN 94-700 009 Scence Publcatons Optmal Bddng Strateges for Generaton Companes n a Day-Ahead Electrcty Market wth Rsk Management Taken nto Account

More information

) of the Cell class is created containing information about events associated with the cell. Events are added to the Cell instance

) of the Cell class is created containing information about events associated with the cell. Events are added to the Cell instance Calbraton Method Instances of the Cell class (one nstance for each FMS cell) contan ADC raw data and methods assocated wth each partcular FMS cell. The calbraton method ncludes event selecton (Class Cell

More information

Nonlinear data mapping by neural networks

Nonlinear data mapping by neural networks Nonlnear data mappng by neural networks R.P.W. Dun Delft Unversty of Technology, Netherlands Abstract A revew s gven of the use of neural networks for nonlnear mappng of hgh dmensonal data on lower dmensonal

More information

The OC Curve of Attribute Acceptance Plans

The OC Curve of Attribute Acceptance Plans The OC Curve of Attrbute Acceptance Plans The Operatng Characterstc (OC) curve descrbes the probablty of acceptng a lot as a functon of the lot s qualty. Fgure 1 shows a typcal OC Curve. 10 8 6 4 1 3 4

More information

Application of Quasi Monte Carlo methods and Global Sensitivity Analysis in finance

Application of Quasi Monte Carlo methods and Global Sensitivity Analysis in finance Applcaton of Quas Monte Carlo methods and Global Senstvty Analyss n fnance Serge Kucherenko, Nlay Shah Imperal College London, UK skucherenko@mperalacuk Daro Czraky Barclays Captal DaroCzraky@barclayscaptalcom

More information

PROCESS CHANGING MODEL of STRIP CONTINUOUS HEAT TREATMENT FURNACE and its APPLICATION

PROCESS CHANGING MODEL of STRIP CONTINUOUS HEAT TREATMENT FURNACE and its APPLICATION Proceedngs of the 1st Internatonal Conference on Computers & Industral Engneerng PROCE CHANGING MODEL of RIP CONINUOU HEA REAMEN FURNACE and ts APPLICAION Dou Rufeng, Wen Zh, Zhou Gang, Lu Xunlang, Lou

More information

The Application of Fractional Brownian Motion in Option Pricing

The Application of Fractional Brownian Motion in Option Pricing Vol. 0, No. (05), pp. 73-8 http://dx.do.org/0.457/jmue.05.0..6 The Applcaton of Fractonal Brownan Moton n Opton Prcng Qng-xn Zhou School of Basc Scence,arbn Unversty of Commerce,arbn zhouqngxn98@6.com

More information

Monte Carlo Simulation

Monte Carlo Simulation Chapter 8 Monte Carlo Smulaton Chapter 8 Monte Carlo Smulaton 8. Introducton Monte Carlo smulaton s named ater the cty o Monte Carlo n Monaco, whch s amous or gamblng such as roulette, dce, and slot machnes.

More information

On-Line Fault Detection in Wind Turbine Transmission System using Adaptive Filter and Robust Statistical Features

On-Line Fault Detection in Wind Turbine Transmission System using Adaptive Filter and Robust Statistical Features On-Lne Fault Detecton n Wnd Turbne Transmsson System usng Adaptve Flter and Robust Statstcal Features Ruoyu L Remote Dagnostcs Center SKF USA Inc. 3443 N. Sam Houston Pkwy., Houston TX 77086 Emal: ruoyu.l@skf.com

More information

Reliability Assessment Using Modified Monte Carlo Simulation

Reliability Assessment Using Modified Monte Carlo Simulation Relablty Assessment Usng Moded Monte Carlo Smulaton 3.1 INTRODUCTION In ths chapter, the method o assessng the relablty or probablty o racture mechancs assessment methods wll be dscussed n depth. In secton

More information

Shielding Equations and Buildup Factors Explained

Shielding Equations and Buildup Factors Explained Sheldng Equatons and uldup Factors Explaned Gamma Exposure Fluence Rate Equatons For an explanaton of the fluence rate equatons used n the unshelded and shelded calculatons, vst ths US Health Physcs Socety

More information

1 Approximation Algorithms

1 Approximation Algorithms CME 305: Dscrete Mathematcs and Algorthms 1 Approxmaton Algorthms In lght of the apparent ntractablty of the problems we beleve not to le n P, t makes sense to pursue deas other than complete solutons

More information

Fatigue damage calculation of ULCS due to quasi-static wave response and springing response

Fatigue damage calculation of ULCS due to quasi-static wave response and springing response Fatgue damage calculaton of ULCS due to quas-statc wave response and sprngng response V. Boutller 1), S. Maherault 1), M. Huther 1), J. Henry 1), G. Parmenter 1) 1) Bureau Vertas, Marne Dvson, 67/71 Boulevard

More information

Chapter 7. Random-Variate Generation 7.1. Prof. Dr. Mesut Güneş Ch. 7 Random-Variate Generation

Chapter 7. Random-Variate Generation 7.1. Prof. Dr. Mesut Güneş Ch. 7 Random-Variate Generation Chapter 7 Random-Varate Generaton 7. Contents Inverse-transform Technque Acceptance-Rejecton Technque Specal Propertes 7. Purpose & Overvew Develop understandng of generatng samples from a specfed dstrbuton

More information

A Novel Methodology of Working Capital Management for Large. Public Constructions by Using Fuzzy S-curve Regression

A Novel Methodology of Working Capital Management for Large. Public Constructions by Using Fuzzy S-curve Regression Novel Methodology of Workng Captal Management for Large Publc Constructons by Usng Fuzzy S-curve Regresson Cheng-Wu Chen, Morrs H. L. Wang and Tng-Ya Hseh Department of Cvl Engneerng, Natonal Central Unversty,

More information

Calculating the high frequency transmission line parameters of power cables

Calculating the high frequency transmission line parameters of power cables < ' Calculatng the hgh frequency transmsson lne parameters of power cables Authors: Dr. John Dcknson, Laboratory Servces Manager, N 0 RW E B Communcatons Mr. Peter J. Ncholson, Project Assgnment Manager,

More information

Damage Tolerance Analysis of Aero Structural Components

Damage Tolerance Analysis of Aero Structural Components Damage Tolerance Analyss of Aero Structural Components In today s structural desgn, fatgue and damage tolerance analyss have become most mportant and challengng task for the desgners because of falure

More information

Description of the Force Method Procedure. Indeterminate Analysis Force Method 1. Force Method con t. Force Method con t

Description of the Force Method Procedure. Indeterminate Analysis Force Method 1. Force Method con t. Force Method con t Indeternate Analyss Force Method The force (flexblty) ethod expresses the relatonshps between dsplaceents and forces that exst n a structure. Prary objectve of the force ethod s to deterne the chosen set

More information

A Simple Economic Model about the Teamwork Pedagogy

A Simple Economic Model about the Teamwork Pedagogy Appled Mathematcal Scences, Vol. 6, 01, no. 1, 13-0 A Smple Economc Model about the Teamwork Pedagog Gregor L. Lght Department of Management, Provdence College Provdence, Rhode Island 0918, USA glght@provdence.edu

More information

THE DISTRIBUTION OF LOAN PORTFOLIO VALUE * Oldrich Alfons Vasicek

THE DISTRIBUTION OF LOAN PORTFOLIO VALUE * Oldrich Alfons Vasicek HE DISRIBUION OF LOAN PORFOLIO VALUE * Oldrch Alfons Vascek he amount of captal necessary to support a portfolo of debt securtes depends on the probablty dstrbuton of the portfolo loss. Consder a portfolo

More information

Analysis of Premium Liabilities for Australian Lines of Business

Analysis of Premium Liabilities for Australian Lines of Business Summary of Analyss of Premum Labltes for Australan Lnes of Busness Emly Tao Honours Research Paper, The Unversty of Melbourne Emly Tao Acknowledgements I am grateful to the Australan Prudental Regulaton

More information

A PROBABILISTIC DESIGN APPROACH TO LIFETIME PREDICTION FOR TURBINE BLADES

A PROBABILISTIC DESIGN APPROACH TO LIFETIME PREDICTION FOR TURBINE BLADES European Congress on Computatonal Methods n Appled Scences and Engneerng ECCOMAS 000 Barcelona, -4 September 000 ECCOMAS A PROBABILISTIC DESIGN APPROACH TO LIFETIME PREDICTION FOR TURBINE BLADES Roland

More information

Multicomponent Distillation

Multicomponent Distillation Multcomponent Dstllaton need more than one dstllaton tower, for n components, n-1 fractonators are requred Specfcaton Lmtatons The followng are establshed at the begnnng 1. Temperature, pressure, composton,

More information

Experiment 8 Two Types of Pendulum

Experiment 8 Two Types of Pendulum Experment 8 Two Types of Pendulum Preparaton For ths week's quz revew past experments and read about pendulums and harmonc moton Prncples Any object that swngs back and forth can be consdered a pendulum

More information

Robust Design of Public Storage Warehouses. Yeming (Yale) Gong EMLYON Business School

Robust Design of Public Storage Warehouses. Yeming (Yale) Gong EMLYON Business School Robust Desgn of Publc Storage Warehouses Yemng (Yale) Gong EMLYON Busness School Rene de Koster Rotterdam school of management, Erasmus Unversty Abstract We apply robust optmzaton and revenue management

More information

Section B9: Zener Diodes

Section B9: Zener Diodes Secton B9: Zener Dodes When we frst talked about practcal dodes, t was mentoned that a parameter assocated wth the dode n the reverse bas regon was the breakdown voltage, BR, also known as the peak-nverse

More information

The circuit shown on Figure 1 is called the common emitter amplifier circuit. The important subsystems of this circuit are:

The circuit shown on Figure 1 is called the common emitter amplifier circuit. The important subsystems of this circuit are: polar Juncton Transstor rcuts Voltage and Power Amplfer rcuts ommon mtter Amplfer The crcut shown on Fgure 1 s called the common emtter amplfer crcut. The mportant subsystems of ths crcut are: 1. The basng

More information

The Probit Model. Alexander Spermann. SoSe 2009

The Probit Model. Alexander Spermann. SoSe 2009 The Probt Model Aleander Spermann Unversty of Freburg SoSe 009 Course outlne. Notaton and statstcal foundatons. Introducton to the Probt model 3. Applcaton 4. Coeffcents and margnal effects 5. Goodness-of-ft

More information

Sensitivity based attribution of flood risk

Sensitivity based attribution of flood risk Senstvty based attrbuton of flood rsk Attrbuton du rsque d'nondaton basé sur la sensblté Jm Hall, Rchard Dawson, Lnda Speght, Slobodan Djordjevć, Dragan Savć and Jorge Leandro School of Cvl Engneerng and

More information

MAPP. MERIS level 3 cloud and water vapour products. Issue: 1. Revision: 0. Date: 9.12.1998. Function Name Organisation Signature Date

MAPP. MERIS level 3 cloud and water vapour products. Issue: 1. Revision: 0. Date: 9.12.1998. Function Name Organisation Signature Date Ttel: Project: Doc. No.: MERIS level 3 cloud and water vapour products MAPP MAPP-ATBD-ClWVL3 Issue: 1 Revson: 0 Date: 9.12.1998 Functon Name Organsaton Sgnature Date Author: Bennartz FUB Preusker FUB Schüller

More information

A Probabilistic Theory of Coherence

A Probabilistic Theory of Coherence A Probablstc Theory of Coherence BRANDEN FITELSON. The Coherence Measure C Let E be a set of n propostons E,..., E n. We seek a probablstc measure C(E) of the degree of coherence of E. Intutvely, we want

More information

Brigid Mullany, Ph.D University of North Carolina, Charlotte

Brigid Mullany, Ph.D University of North Carolina, Charlotte Evaluaton And Comparson Of The Dfferent Standards Used To Defne The Postonal Accuracy And Repeatablty Of Numercally Controlled Machnng Center Axes Brgd Mullany, Ph.D Unversty of North Carolna, Charlotte

More information

2.4 Bivariate distributions

2.4 Bivariate distributions page 28 2.4 Bvarate dstrbutons 2.4.1 Defntons Let X and Y be dscrete r.v.s defned on the same probablty space (S, F, P). Instead of treatng them separately, t s often necessary to thnk of them actng together

More information

The eigenvalue derivatives of linear damped systems

The eigenvalue derivatives of linear damped systems Control and Cybernetcs vol. 32 (2003) No. 4 The egenvalue dervatves of lnear damped systems by Yeong-Jeu Sun Department of Electrcal Engneerng I-Shou Unversty Kaohsung, Tawan 840, R.O.C e-mal: yjsun@su.edu.tw

More information

Institute of Informatics, Faculty of Business and Management, Brno University of Technology,Czech Republic

Institute of Informatics, Faculty of Business and Management, Brno University of Technology,Czech Republic Lagrange Multplers as Quanttatve Indcators n Economcs Ivan Mezník Insttute of Informatcs, Faculty of Busness and Management, Brno Unversty of TechnologCzech Republc Abstract The quanttatve role of Lagrange

More information

Mooring Pattern Optimization using Genetic Algorithms

Mooring Pattern Optimization using Genetic Algorithms 6th World Congresses of Structural and Multdscplnary Optmzaton Ro de Janero, 30 May - 03 June 005, Brazl Moorng Pattern Optmzaton usng Genetc Algorthms Alonso J. Juvnao Carbono, Ivan F. M. Menezes Luz

More information

Exhaustive Regression. An Exploration of Regression-Based Data Mining Techniques Using Super Computation

Exhaustive Regression. An Exploration of Regression-Based Data Mining Techniques Using Super Computation Exhaustve Regresson An Exploraton of Regresson-Based Data Mnng Technques Usng Super Computaton Antony Daves, Ph.D. Assocate Professor of Economcs Duquesne Unversty Pttsburgh, PA 58 Research Fellow The

More information

Realistic Image Synthesis

Realistic Image Synthesis Realstc Image Synthess - Combned Samplng and Path Tracng - Phlpp Slusallek Karol Myszkowsk Vncent Pegoraro Overvew: Today Combned Samplng (Multple Importance Samplng) Renderng and Measurng Equaton Random

More information

1.1 The University may award Higher Doctorate degrees as specified from time-to-time in UPR AS11 1.

1.1 The University may award Higher Doctorate degrees as specified from time-to-time in UPR AS11 1. HIGHER DOCTORATE DEGREES SUMMARY OF PRINCIPAL CHANGES General changes None Secton 3.2 Refer to text (Amendments to verson 03.0, UPR AS02 are shown n talcs.) 1 INTRODUCTION 1.1 The Unversty may award Hgher

More information

"Research Note" APPLICATION OF CHARGE SIMULATION METHOD TO ELECTRIC FIELD CALCULATION IN THE POWER CABLES *

Research Note APPLICATION OF CHARGE SIMULATION METHOD TO ELECTRIC FIELD CALCULATION IN THE POWER CABLES * Iranan Journal of Scence & Technology, Transacton B, Engneerng, ol. 30, No. B6, 789-794 rnted n The Islamc Republc of Iran, 006 Shraz Unversty "Research Note" ALICATION OF CHARGE SIMULATION METHOD TO ELECTRIC

More information

Generator Warm-Up Characteristics

Generator Warm-Up Characteristics NO. REV. NO. : ; ~ Generator Warm-Up Characterstcs PAGE OF Ths document descrbes the warm-up process of the SNAP-27 Generator Assembly after the sotope capsule s nserted. Several nqures have recently been

More information

What is Candidate Sampling

What is Candidate Sampling What s Canddate Samplng Say we have a multclass or mult label problem where each tranng example ( x, T ) conssts of a context x a small (mult)set of target classes T out of a large unverse L of possble

More information

8.5 UNITARY AND HERMITIAN MATRICES. The conjugate transpose of a complex matrix A, denoted by A*, is given by

8.5 UNITARY AND HERMITIAN MATRICES. The conjugate transpose of a complex matrix A, denoted by A*, is given by 6 CHAPTER 8 COMPLEX VECTOR SPACES 5. Fnd the kernel of the lnear transformaton gven n Exercse 5. In Exercses 55 and 56, fnd the mage of v, for the ndcated composton, where and are gven by the followng

More information

Aryabhata s Root Extraction Methods. Abhishek Parakh Louisiana State University Aug 31 st 2006

Aryabhata s Root Extraction Methods. Abhishek Parakh Louisiana State University Aug 31 st 2006 Aryabhata s Root Extracton Methods Abhshek Parakh Lousana State Unversty Aug 1 st 1 Introducton Ths artcle presents an analyss of the root extracton algorthms of Aryabhata gven n hs book Āryabhatīya [1,

More information

I. SCOPE, APPLICABILITY AND PARAMETERS Scope

I. SCOPE, APPLICABILITY AND PARAMETERS Scope D Executve Board Annex 9 Page A/R ethodologcal Tool alculaton of the number of sample plots for measurements wthn A/R D project actvtes (Verson 0) I. SOPE, PIABIITY AD PARAETERS Scope. Ths tool s applcable

More information

S. Malasri, D.A.Halijan and M.L.Keough Department of Civil Engineering Christian Brothers University Memphis, TN 38104. Abstract

S. Malasri, D.A.Halijan and M.L.Keough Department of Civil Engineering Christian Brothers University Memphis, TN 38104. Abstract S. Malasr, D.A.Haljan and M.L.Keough Department of Cvl Engneerng Chrstan Brothers Unversty Memphs, TN 38104 Abstract Ths paper demonstrates an applcaton of the natural selecton process to the desgn of

More information

Forecasting the Direction and Strength of Stock Market Movement

Forecasting the Direction and Strength of Stock Market Movement Forecastng the Drecton and Strength of Stock Market Movement Jngwe Chen Mng Chen Nan Ye cjngwe@stanford.edu mchen5@stanford.edu nanye@stanford.edu Abstract - Stock market s one of the most complcated systems

More information

A statistical approach to determine Microbiologically Influenced Corrosion (MIC) Rates of underground gas pipelines.

A statistical approach to determine Microbiologically Influenced Corrosion (MIC) Rates of underground gas pipelines. A statstcal approach to determne Mcrobologcally Influenced Corroson (MIC) Rates of underground gas ppelnes. by Lech A. Grzelak A thess submtted to the Delft Unversty of Technology n conformty wth the requrements

More information

Nasdaq Iceland Bond Indices 01 April 2015

Nasdaq Iceland Bond Indices 01 April 2015 Nasdaq Iceland Bond Indces 01 Aprl 2015 -Fxed duraton Indces Introducton Nasdaq Iceland (the Exchange) began calculatng ts current bond ndces n the begnnng of 2005. They were a response to recent changes

More information

FINAL REPORT. City of Toronto. Contract 47016555. Project No: B000203-3

FINAL REPORT. City of Toronto. Contract 47016555. Project No: B000203-3 Cty of Toronto SAFETY IMPACTS AD REGULATIOS OF ELECTROIC STATIC ROADSIDE ADVERTISIG SIGS TECHICAL MEMORADUM #2C BEFORE/AFTER COLLISIO AALYSIS AT SIGALIZED ITERSECTIO FIAL REPORT 3027 Harvester Road, Sute

More information

1. Fundamentals of probability theory 2. Emergence of communication traffic 3. Stochastic & Markovian Processes (SP & MP)

1. Fundamentals of probability theory 2. Emergence of communication traffic 3. Stochastic & Markovian Processes (SP & MP) 6.3 / -- Communcaton Networks II (Görg) SS20 -- www.comnets.un-bremen.de Communcaton Networks II Contents. Fundamentals of probablty theory 2. Emergence of communcaton traffc 3. Stochastc & Markovan Processes

More information

Naïve Bayes classifier & Evaluation framework

Naïve Bayes classifier & Evaluation framework Lecture aïve Bayes classfer & Evaluaton framework Mlos Hauskrecht mlos@cs.ptt.edu 539 Sennott Square Generatve approach to classfcaton Idea:. Represent and learn the dstrbuton p x, y. Use t to defne probablstc

More information

Numerical Study of Wave Run-up around Offshore Structure in Waves

Numerical Study of Wave Run-up around Offshore Structure in Waves Journal of Advanced Research n Ocean Engneerng Journal of Advanced Research n Ocean Engneerng 2(2) (2016) 061-066 http://dx.do.org/10.5574/jaroe.2016.2.2.061 Numercal Study of Wave Run-up around Offshore

More information

A Note on the Decomposition of a Random Sample Size

A Note on the Decomposition of a Random Sample Size A Note on the Decomposton of a Random Sample Sze Klaus Th. Hess Insttut für Mathematsche Stochastk Technsche Unverstät Dresden Abstract Ths note addresses some results of Hess 2000) on the decomposton

More information

Passive Filters. References: Barbow (pp 265-275), Hayes & Horowitz (pp 32-60), Rizzoni (Chap. 6)

Passive Filters. References: Barbow (pp 265-275), Hayes & Horowitz (pp 32-60), Rizzoni (Chap. 6) Passve Flters eferences: Barbow (pp 6575), Hayes & Horowtz (pp 360), zzon (Chap. 6) Frequencyselectve or flter crcuts pass to the output only those nput sgnals that are n a desred range of frequences (called

More information

Latent Class Regression. Statistics for Psychosocial Research II: Structural Models December 4 and 6, 2006

Latent Class Regression. Statistics for Psychosocial Research II: Structural Models December 4 and 6, 2006 Latent Class Regresson Statstcs for Psychosocal Research II: Structural Models December 4 and 6, 2006 Latent Class Regresson (LCR) What s t and when do we use t? Recall the standard latent class model

More information

A hybrid global optimization algorithm based on parallel chaos optimization and outlook algorithm

A hybrid global optimization algorithm based on parallel chaos optimization and outlook algorithm Avalable onlne www.ocpr.com Journal of Chemcal and Pharmaceutcal Research, 2014, 6(7):1884-1889 Research Artcle ISSN : 0975-7384 CODEN(USA) : JCPRC5 A hybrd global optmzaton algorthm based on parallel

More information

Inequality and The Accounting Period. Quentin Wodon and Shlomo Yitzhaki. World Bank and Hebrew University. September 2001.

Inequality and The Accounting Period. Quentin Wodon and Shlomo Yitzhaki. World Bank and Hebrew University. September 2001. Inequalty and The Accountng Perod Quentn Wodon and Shlomo Ytzha World Ban and Hebrew Unversty September Abstract Income nequalty typcally declnes wth the length of tme taen nto account for measurement.

More information

Evaluating Earthquake Retrofitting Measures for Schools: A Demonstration Cost-Benefit Analysis

Evaluating Earthquake Retrofitting Measures for Schools: A Demonstration Cost-Benefit Analysis Evaluatng Earthquake Retrofttng easures for Schools: A emonstraton Cost-Beneft Analyss A.W. Smyth, G. eodats 2, G. Franco 3, Y. He 4, and T. Gurvch 4 ept. of Cvl Engneerng & Engneerng echancs Columba Unversty,

More information

TECHNICAL NOTES 8 GRINDING. R. P. King

TECHNICAL NOTES 8 GRINDING. R. P. King TECHNICAL NOTES 8 GRINDING R. P. Kng Copyrght R P kng 000 8. Grndng 8.. Grndng acton Industral grndng machnes used n the mneral processng ndustres are mostly of the tumblng mll type. These mlls exst n

More information

Study on Model of Risks Assessment of Standard Operation in Rural Power Network

Study on Model of Risks Assessment of Standard Operation in Rural Power Network Study on Model of Rsks Assessment of Standard Operaton n Rural Power Network Qngj L 1, Tao Yang 2 1 Qngj L, College of Informaton and Electrcal Engneerng, Shenyang Agrculture Unversty, Shenyang 110866,

More information

DEFINING %COMPLETE IN MICROSOFT PROJECT

DEFINING %COMPLETE IN MICROSOFT PROJECT CelersSystems DEFINING %COMPLETE IN MICROSOFT PROJECT PREPARED BY James E Aksel, PMP, PMI-SP, MVP For Addtonal Informaton about Earned Value Management Systems and reportng, please contact: CelersSystems,

More information

PSYCHOLOGICAL RESEARCH (PYC 304-C) Lecture 12

PSYCHOLOGICAL RESEARCH (PYC 304-C) Lecture 12 14 The Ch-squared dstrbuton PSYCHOLOGICAL RESEARCH (PYC 304-C) Lecture 1 If a normal varable X, havng mean µ and varance σ, s standardsed, the new varable Z has a mean 0 and varance 1. When ths standardsed

More information

ErrorPropagation.nb 1. Error Propagation

ErrorPropagation.nb 1. Error Propagation ErrorPropagaton.nb Error Propagaton Suppose that we make observatons of a quantty x that s subject to random fluctuatons or measurement errors. Our best estmate of the true value for ths quantty s then

More information

Daily O-D Matrix Estimation using Cellular Probe Data

Daily O-D Matrix Estimation using Cellular Probe Data Zhang, Qn, Dong and Ran Daly O-D Matrx Estmaton usng Cellular Probe Data 0 0 Y Zhang* Department of Cvl and Envronmental Engneerng, Unversty of Wsconsn-Madson, Madson, WI 0 Phone: -0-- E-mal: zhang@wsc.edu

More information

PROFIT RATIO AND MARKET STRUCTURE

PROFIT RATIO AND MARKET STRUCTURE POFIT ATIO AND MAKET STUCTUE By Yong Yun Introducton: Industral economsts followng from Mason and Ban have run nnumerable tests of the relaton between varous market structural varables and varous dmensons

More information

BERNSTEIN POLYNOMIALS

BERNSTEIN POLYNOMIALS On-Lne Geometrc Modelng Notes BERNSTEIN POLYNOMIALS Kenneth I. Joy Vsualzaton and Graphcs Research Group Department of Computer Scence Unversty of Calforna, Davs Overvew Polynomals are ncredbly useful

More information