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Hydrosystems engineering reliability assessment and risk analysis
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Series:
McGraw-Hill civil engineering series
Publication Information:
New York, NY : McGraw-Hill, 2006
ISBN:
9780071451581

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30000004715359 TD353 T86 2006 Open Access Book Book
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30000010107898 TD353 T86 2006 Open Access Book Book
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INTEGRATE RELIABILITY ASSESSMENT AND RISK ANALYSISINTO PLANNING, DESIGN, AND MANAGEMENT

This comprehensive text is the first to integrate reliability analysis and risk assessment into the planning, design, and management of hydrosystems. Written by internationally respected authorities, Hydrosystems Engineering Reliability Assessment and Risk Analysis provides the tools for designing safer, more reliable dams, storm sewer networks, water treatment plants, and pollution control systems.

Offering example problems that demonstrate the prediction of safety and reliability under different design scenarios, the authors illustrate the application of mathematical tools that quantify reliability and risk. With this book readers can improve the performance, durability (through maintenance scheduling/time to failure analysis), and predictability of hydrosystem designs.

Hydrosystems Engineering Reliability Assessment and Risk Analysis:

Brings together in a single resource mathematical risk and reliability analysis methods needed to improve planning, design, and performance of hydrosystems Demonstrates statistical and probability tools for solving a broad range of hydrosystem engineering problems Provides the tools needed to predict hydrosystem project behavior and lifespan under various risk scenarios Shows engineers and students how to conduct risk and reliability assessments Offers examples of each application, in both U.S. and international units Provides sets of Q & A's for self-testing after every chapter


Author Notes

Yeou-Koung Tung, Ph.D., is a Professor of Civil Engineering at Hong Kong University of Science and Technology. The author of numerous technical papers on hydrology and risk analysis, he has won several awards for his research on these topics including the Walter L. Huber Research Prize, ASCE; the Arthur T. Ippen Award, IAHR; and the Collingwood Prize, ASCE. Dr. Tung received his B.S. in Hydraulic Engineering from Tamkang University, Taiwan and his M.S. and Ph.D. in civil engineering from the University of Texas at Austin.

Ben-Chie Yen, Ph.D., (deceased) was a Professor of Civil and Environmental Engineering at the University of Illinois at Champaign-Urbana. He worked with surface water and urban hydrology problems, risk and reliability analysis, and open channel and river hydraulics for more than 30 years, and was author of over 200 published technical papers and co-author of eight books. He won a number of lifetime achievement awards from various professional societies focusing on hydraulics and civil engineering including the Hunter Rouse Hydraulic Engineering Lecture, ASCE; the Ven Te Chow Memorial Lecture Award, IWRA; and Honorary Membership in IAHR. He held a B.S. in civil engineering from National Taiwan University and M.S. and Ph.D. degrees in civil engineering from the University of Iowa.

Charles Steve Melching, Ph.D., P.E., is an Associate Professor of Civil and Environmental Engineering at Marquette University, Milwaukee, Wisconsin. He worked for the U.S. Geological Survey, Water Resources Division, for seven years prior to joining the Marquette faculty in 1999. Much of his research has been centered on the application of reliability and uncertainty analysis to water resources modeling and design. He has been honored for his research with the Walter L. Huber Research Prize, ASCE. He received his B.S. in civil engineering from Arizona State University and his M.S. and Ph.D. in civil engineering from the University of Illinois at Urbana-Champaign.


Table of Contents

Prefacep. xi
Acknowledgmentsp. xv
Chapter 1 Reliability in Hydrosystems Engineeringp. 1
1.1 Reliability Engineeringp. 1
1.2 Reliability of Hydrosystem Engineering Infrastructurep. 2
1.3 Brief History of Engineering Reliability Analysisp. 6
1.4 Concept of Reliability Engineeringp. 7
1.5 Definitions of Reliability and Riskp. 10
1.6 Measures of Reliabilityp. 13
1.7 Overall View of Reliability Analysis Methodsp. 15
Referencesp. 16
Chapter 2 Fundamentals of Probability and Statistics for Reliability Analysisp. 19
2.1 Terminologyp. 19
2.2 Fundamental Rules of Probability Computationsp. 21
2.2.1 Basic axioms of probabilityp. 21
2.2.2 Statistical independencep. 22
2.2.3 Conditional probabilityp. 23
2.2.4 Total probability theorem and Bayes' theoremp. 24
2.3 Random Variables and their Distributionsp. 27
2.3.1 Cumulative distribution function and probability density functionp. 27
2.3.2 Joint, conditional, and marginal distributionsp. 31
2.4 Statistical Properties of Random Variablesp. 35
2.4.1 Statistical moments of random variablesp. 35
2.4.2 Mean, mode, median, and quantilesp. 40
2.4.3 Variance, standard deviation, and coefficient of variationp. 43
2.4.4 Skewness coefficient and kurtosisp. 44
2.4.5 Covariance and correlation coefficientp. 47
2.5 Discrete Univariate Probability Distributionsp. 49
2.5.1 Binomial distributionp. 51
2.5.2 Poisson distributionp. 53
2.6 Some Continuous Univariate Probability Distributionsp. 55
2.6.1 Normal (Gaussian) distributionp. 56
2.6.2 Lognormal distributionp. 60
2.6.3 Gamma distribution and variationsp. 63
2.6.4 Extreme-value distributionsp. 66
2.6.5 Beta distributionsp. 71
2.6.6 Distributions related to normal random variablesp. 72
2.7 Multivariate Probability Distributionsp. 75
2.7.1 Multivariate normal distributionsp. 77
2.7.2 Computation of multivariate normal probabilityp. 81
2.7.3 Determination of bounds on multivariate normal probabilityp. 88
2.7.4 Multivariate lognormal distributionsp. 91
Problemsp. 92
Referencesp. 101
Chapter 3 Hydrologic Frequency Analysisp. 103
3.1 Types of Geophysical Data Seriesp. 104
3.2 Return Periodp. 108
3.3 Probability Estimates for Data Series: Plotting Positions (Rank-order Probability)p. 109
3.4 Graphic Approachp. 111
3.5 Analytical Approachesp. 114
3.6 Estimation of Distributional Parametersp. 119
3.6.1 Maximum-likelihood (ML) methodp. 119
3.6.2 Product-moments-based methodp. 121
3.6.3 L-moments-based methodp. 122
3.7 Selection of Distribution Modelp. 125
3.7.1 Probability plot correlation coefficientsp. 125
3.7.2 Model reliability indicesp. 126
3.7.3 Moment-ratio diagramsp. 126
3.7.4 Summaryp. 129
3.8 Uncertainty Associated with a Frequency Relationp. 129
3.9 Limitations of Hydrologic Frequency Analysisp. 135
3.9.1 Distribution selection: practical considerationsp. 135
3.9.2 Extrapolation problemsp. 136
3.9.3 The stationarity assumptionp. 139
3.9.4 Summary commentsp. 139
Problemsp. 140
Referencesp. 142
Chapter 4 Reliability Analysis Considering Load-Resistance Interferencep. 145
4.1 Basic Conceptp. 145
4.2 Performance Functions and Reliability Indexp. 147
4.3 Direct Integration Methodp. 149
4.4 Mean-Value First-Order Second-Moment (MFOSM) Methodp. 156
4.5 Advanced First-Order Second-Moment (AFOSM) Methodp. 164
4.5.1 Definitions of stochastic parameter spacesp. 164
4.5.2 Determination of design point (most probable failure point)p. 165
4.5.3 First-order approximation of performance function at the design pointp. 169
4.5.4 Algorithms of AFOSM for independent normal parametersp. 173
4.5.5 Treatment of nonnormal stochastic variablesp. 180
4.5.6 Treatment of correlated normal stochastic variablesp. 185
4.5.7 AFOSM reliability analysis for nonnormal correlated stochastic variablesp. 190
4.5.8 Overall summary of AFOSM reliability methodp. 200
4.6 Second-Order Reliability Methodsp. 203
4.6.1 Quadratic approximations of the performance functionp. 204
4.6.2 Breitung's formulap. 208
4.7 Time-Dependent Reliability Modelsp. 211
4.7.1 Time-dependent resistancep. 213
4.7.2 Time-dependent loadp. 214
4.7.3 Classification of time-dependent reliability modelsp. 214
4.7.4 Modeling intensity and occurrence of loadsp. 215
4.7.5 Time-dependent reliability modelsp. 217
4.7.6 Time-dependent reliability models for hydrosystemsp. 218
Appendix 4A Some One-Dimensional Numerical Integration Formulasp. 221
Appendix 4B Cholesky Decompositionp. 223
Appendix 4C Orthogonal Transformation Techniquesp. 224
Appendix 4D Gram-Schmid Ortho Normalizationp. 229
Problemsp. 231
Referencesp. 240
Chapter 5 Time-to-Failure Analysisp. 245
5.1 Basic Conceptp. 245
5.2 Failure Characteristicsp. 246
5.2.1 Failure density functionp. 246
5.2.2 Failure rate and hazard functionp. 247
5.2.3 Cumulative hazard function and average failure ratep. 251
5.2.5 Typical hazard functionsp. 254
5.2.6 Relationships among failure density function, failure rate, and reliabilityp. 255
5.2.7 Effect of age on reliabilityp. 257
5.2.8 Mean time to failurep. 259
5.3 Repairable Systemsp. 259
5.3.1 Repair density and repair probabilityp. 261
5.3.2 Repair rate and its relationship with repair density and repair probabilityp. 263
5.3.3 Mean time to repair, mean time between failures, and mean time between repairsp. 263
5.3.4 Preventive maintenancep. 264
5.3.5 Supportabilityp. 272
5.4 Determinations of Availability and Unavailabilityp. 272
5.4.1 Terminologyp. 272
5.4.2 Determinations of availability and unavailabilityp. 275
Appendix 5A Laplace Transformp. 282
Problemsp. 283
Referencesp. 286
Chapter 6 Monte Carlo Simulationp. 289
6.1 Introductionp. 289
6.2 Generation of Random Numbersp. 291
6.3 Classifications of Random Variates Generation Algorithmsp. 294
6.3.1 CDF-inverse methodp. 294
6.3.2 Acceptance-rejection methodsp. 296
6.3.3 Variable transformation methodp. 298
6.4 Generation of Univariate Random Numbers for Some Distributionsp. 299
6.4.1 Normal distributionp. 299
6.4.2 Lognormal distributionp. 301
6.4.3 Exponential distributionp. 301
6.4.4 Gamma distributionp. 302
6.4.5 Poisson distributionp. 302
6.4.6 Other univariate distributions and computer programsp. 303
6.5 Generation of Vectors of Multivariate Random Variablesp. 303
6.5.1 CDF-inverse methodp. 304
6.5.2 Generating multivariate normal random variatesp. 307
6.5.3 Generating multivariate random variates with known marginal PDFs and correlationsp. 311
6.5.4 Generating multivariate random variates subject to linear constraintsp. 312
6.6 Monte Carlo Integrationp. 314
6.6.1 The hit-and-miss methodp. 316
6.6.2 The sample-mean methodp. 319
6.6.3 Directional Monte Carlo simulation algorithmp. 321
6.6.4 Efficiency of the Monte Carlo algorithmp. 327
6.7 Variance-Reduction Techniquesp. 327
6.7.1 Importance sampling techniquep. 328
6.7.2 Antithetic-variates techniquep. 330
6.7.3 Correlated-sampling techniquesp. 333
6.7.4 Stratified sampling techniquep. 335
6.7.5 Latin hypercube sampling techniquep. 338
6.7.6 Control-variate methodp. 342
6.8 Resampling Techniquesp. 344
Problemsp. 348
Referencesp. 352
Chapter 7 Reliability of Systemsp. 357
7.1 Introductionp. 357
7.2 General View of System Reliability Computationp. 358
7.2.1 Classification of systemsp. 359
7.2.2 Basic probability rules for system reliabilityp. 360
7.2.3 Bounds for system reliabilityp. 363
7.3 Reliability of Simple Systemsp. 371
7.3.1 Series systemsp. 371
7.3.2 Parallel systemsp. 376
7.3.3 K-out-of-M parallel systemsp. 379
7.3.4 Standby redundant systemsp. 380
7.4 Methods for Computing Reliability of Complex Systemsp. 381
7.4.1 State enumeration methodp. 381
7.4.2 Path enumeration methodp. 385
7.4.3 Conditional probability approachp. 389
7.4.4 Fault-tree analysisp. 391
7.5 Summary and Conclusionsp. 398
Appendix 7A Derivation of Bounds for Bivariate Normal Probabilityp. 399
Problemsp. 402
Referencesp. 404
Chapter 8 Integration of Reliability in Optimal Hydrosystems Designp. 407
8.1 Introductionp. 407
8.1.1 General framework of optimization modelsp. 408
8.1.2 Single-objective versus multiobjective programmingp. 409
8.1.3 Optimization techniquesp. 411
8.2 Optimization of System Reliabilityp. 422
8.2.1 Reliability design with redundancyp. 422
8.2.2 Determination of optimal maintenance schedulep. 425
8.3 Optimal Risk-Based Design of Hydrosystem Infrastructuresp. 427
8.3.1 Basic conceptp. 428
8.3.2 Historical development of hydraulic design methodsp. 429
8.3.3 Tangible costs in risk-based designp. 431
8.3.4 Evaluations of annual expected flood damage costp. 433
8.3.5 Risk-based design without flood damage informationp. 436
8.3.6 Risk-based design considering intangible factorsp. 438
8.4 Applications of Risk-Based Hydrosystem Designp. 439
8.4.1 Optimal risk-based pipe culvert for roadway drainagep. 440
8.4.2 Risk-based analysis for flood-damage-reduction projectsp. 445
8.5 Optimization of Hydrosystems by Chance-Constrained Methodsp. 449
8.6 Chance-Constrained Method to ASSESS Water-Quality Managementp. 454
8.6.1 Optimal stochastic waste-load allocationp. 455
8.6.2 Multiobjective stochastic waste-load allocationp. 465
Appendix 8A Derivation of Water-Quality Constraintsp. 470
Problemsp. 472
Referencesp. 477
Indexp. 483