000778078 000__ 05659cam\a2200541M\\4500 000778078 001__ 778078 000778078 005__ 20230306142750.0 000778078 006__ m\\\\\o\\d\\\\\\\\ 000778078 007__ cr\nn\nnnunnun 000778078 008__ 161125t20162017sz\\\\\\o\\\\\101\0\eng\d 000778078 019__ $$a963932467$$a967813256 000778078 020__ $$a9783319478869$$q(electronic book) 000778078 020__ $$a3319478869$$q(electronic book) 000778078 020__ $$z9783319478852 000778078 020__ $$z3319478850 000778078 035__ $$aSP(OCoLC)ocn964327741 000778078 035__ $$aSP(OCoLC)964327741$$z(OCoLC)963932467$$z(OCoLC)967813256 000778078 040__ $$aYDX$$beng$$epn$$cYDX$$dN$T$$dEBLCP$$dIDEBK$$dOCLCQ$$dGW5XE$$dOCLCF$$dN$T$$dAZU$$dUAB$$dIOG 000778078 049__ $$aISEA 000778078 050_4 $$aTA645 000778078 050_4 $$aTA1-2040 000778078 08204 $$a624.1/7$$223 000778078 08204 $$a620 000778078 1112_ $$aInternational Probabilistic Workshop$$n(14th :$$d2016 :$$cGhent, Belgium) 000778078 24510 $$a14th International Probabilistic Workshop /$$cRobby Caspeele, Luc Taerwe, Dirk Proske, editors. 000778078 260__ $$aCham, Switzerland :$$bSpringer,$$c2016, c2017. 000778078 300__ $$a1 online resource 000778078 336__ $$atext$$btxt$$2rdacontent 000778078 337__ $$acomputer$$bc$$2rdamedia 000778078 338__ $$aonline resource$$bcr$$2rdacarrier 000778078 500__ $$aIncludes author index. 000778078 5050_ $$aPreface; Organization; Chair of IPW2016; Scientific Committee; Contents; Keynotes; 1 Optimizing Adaptable Systems for Future Uncertainty; Abstract; 1 Introduction; 2 Adaptable or Flexible Engineering Systems; 2.1 A Measure of Flexibility; 3 Sequential Decision Analysis; 4 Numerical Illustrations; 4.1 Case 1: Infrastructure Capacity; 4.2 Case 2: Disaster Risk Management; 5 Concluding Remarks; References; 2 Freak Events, Black Swans, and Unknowable Unknowns: Impact on Risk-Based Design; Abstract; 1 Introduction; 2 Infrastructure: Evolving Expectations. 000778078 5058_ $$a3 What We Know, What We Should Know, What We Don't Know4 Black Swans and Perfect Storms; 5 The "Very" Extreme; 6 The Carlsbad Black Swan: El Paso Natural Gas Pipeline Rupture, 19 August, 2000; 7 The Fukushima Daiichi Perfect Storm, 11 March 2011; 8 Conclusions: Demystifying the Extraordinary; References; Structural Reliability Methods and Statistical Approaches; Extrapolation, Invariance, Geometry and Subset Sampling; 1 Introduction; 2 The Subset Sampling Method; 3 SuS and Asymptotic Approximations; 4 Extrapolation; 5 Invariance; 6 Changing Topological Structure of Domains. 000778078 5058_ $$a7 Several Beta Points8 Bias and Variance of SuS Estimates; 9 Conclusions; References; 4 Performance of Various Sampling Schemes in Asymptotic Sampling; Abstract; 1 Introduction; 2 Testing Limit-State Functions; 2.1 Limit-State Function Sum1D; 2.2 Limit-State Function Sum2D; 2.3 Limit-State Function Sin2D; 3 Asymptotic Sampling (AS); 4 Design of Experiment; 4.1 Monte Carlo (MC) Sampling; 4.2 Latin Hypercube Sampling (LHS); 4.3 LHS Optimized-Periodic Audze-Eglājs (PAE) Criterion; 4.4 Quasi-Monte Carlo (QMC) Sequences; 4.5 The Sobol Sequence; 5 Results; 5.1 Limit-State Function Sum1D. 000778078 5058_ $$a5.2 Limit-State Function Sum2D5.3 Limit-State Function Sin2D; 6 Concluding Remarks; Acknowledgments; References; Moving Least Squares Metamodels -- Hyperparameter, Variable Reduction and Model Selection; 1 Introduction; 2 From Least Squares to Moving Least Squares; 2.1 Linear Regression Model; 2.2 Least Squares; 2.3 Weighted Least Squares; 2.4 Moving Least Squares; 3 Settings of WLS and MLS; 3.1 Model Function f (b(x1, #x83;, xnk)); 3.2 Weighting Matrix; 4 MLS Model Tuning; 4.1 Tuning of Hyperparameters; 4.2 Variable Reduction; 5 Framework of Deterministic Models; 5.1 Implemented Models. 000778078 5058_ $$a5.2 Design of Experiments (DOE)6 Evaluation of LS and MLS Metamodels; 7 Summary and Outlook; References; 6 Comparing Three Methodologies for System Identification and Prediction; Abstract; 1 Introduction; 2 Structural Identification Methodologies; 2.1 Traditional Bayesian Model Updating; 2.2 Error-Domain Model Falsification; 2.3 Modified Bayesian Model Updating; 3 Numerical Example; 4 Conclusion; References; 7 Global Sensitivity Analysis of Reinforced Concrete Walls Subjected to Standard Fire-A Comparison of Methods; Abstract; 1 Introduction; 2 Applied Methods. 000778078 506__ $$aAccess limited to authorized users. 000778078 520__ $$aThis book presents the proceedings of the 14th International Probabilistic Workshop that was held in Ghent, Belgium in December 2016. Probabilistic methods are currently of crucial importance for research and developments in the field of engineering, which face challenges presented by new materials and technologies and rapidly changing societal needs and values. Contemporary needs related to, for example, performance-based design, service-life design, life-cycle analysis, product optimization, assessment of existing structures and structural robustness give rise to new developments as well as accurate and practically applicable probabilistic and statistical engineering methods to support these developments. These proceedings are a valuable resource for anyone interested in contemporary developments in the field of probabilistic engineering applications. 000778078 650_0 $$aStructural analysis (Engineering)$$vCongresses. 000778078 650_0 $$aProbabilities$$vCongresses. 000778078 7001_ $$aCaspeele, Robby,$$eeditor. 000778078 7001_ $$aTaerwe, Luc,$$eeditor. 000778078 7001_ $$aProske, Dirk,$$eeditor. 000778078 77608 $$iPrint version:$$t14TH INTERNATIONAL PROBABILISTIC WORKSHOP.$$d[Place of publication not identified] : SPRINGER, 2016$$z3319478850$$z9783319478852$$w(OCoLC)959035153 000778078 852__ $$bebk 000778078 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-47886-9$$zOnline Access$$91397441.1 000778078 909CO $$ooai:library.usi.edu:778078$$pGLOBAL_SET 000778078 980__ $$aEBOOK 000778078 980__ $$aBIB 000778078 982__ $$aEbook 000778078 983__ $$aOnline 000778078 994__ $$a92$$bISE