14th International Probabilistic Workshop

This 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...

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Corporate Author: International Probabilistic Workshop Ghent, Belgium)
Other Authors: Caspeele, Robby, (Editor), Taerwe, Luc, (Editor), Proske, Dirk, (Editor)
Format: eBook
Language: English
Published: Cham, Switzerland : Springer, 2016, ©2017.
Subjects:
ISBN: 9783319478869
9783319478852
Physical Description: 1 online resource

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008 161125t20162017sz o 101 0 eng d
040 |a YDX  |b eng  |e pn  |c YDX  |d N$T  |d EBLCP  |d IDEBK  |d OCLCQ  |d GW5XE  |d OCLCF  |d N$T  |d AZU  |d UAB  |d IOG  |d MERER  |d ESU  |d Z5A  |d OCLCQ  |d JBG  |d IAD  |d ICW  |d ICN  |d OTZ  |d OCLCQ  |d U3W  |d CAUOI  |d KSU  |d UKMGB  |d AUD  |d UKAHL  |d OCLCQ 
020 |a 9783319478869  |q (electronic bk.) 
020 |z 9783319478852 
035 |a (OCoLC)964327741  |z (OCoLC)963932467  |z (OCoLC)967813256 
111 2 |a International Probabilistic Workshop  |n (14th :  |d 2016 :  |c Ghent, Belgium) 
245 1 0 |a 14th International Probabilistic Workshop /  |c Robby Caspeele, Luc Taerwe, Dirk Proske, editors. 
260 |a Cham, Switzerland :  |b Springer,  |c 2016, ©2017. 
300 |a 1 online resource 
336 |a text  |b txt  |2 rdacontent 
337 |a počítač  |b c  |2 rdamedia 
338 |a online zdroj  |b cr  |2 rdacarrier 
505 0 |a Preface; 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. 
505 8 |a 3 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. 
505 8 |a 7 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. 
505 8 |a 5.2 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. 
505 8 |a 5.2 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. 
500 |a Includes author index. 
506 |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty 
520 |a This 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. 
590 |a SpringerLink  |b Springer Complete eBooks 
650 0 |a Structural analysis (Engineering)  |v Congresses. 
650 0 |a Probabilities  |v Congresses. 
655 7 |a elektronické knihy  |7 fd186907  |2 czenas 
655 9 |a electronic books  |2 eczenas 
700 1 |a Caspeele, Robby,  |e editor. 
700 1 |a Taerwe, Luc,  |e editor. 
700 1 |a Proske, Dirk,  |e editor. 
776 0 8 |i Print version:  |t 14TH INTERNATIONAL PROBABILISTIC WORKSHOP.  |d [Place of publication not identified] : SPRINGER, 2016  |z 3319478850  |z 9783319478852  |w (OCoLC)959035153 
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