Search Results - "Probabilistic engineering mechanics" :: K.UTB vyhledávací portál

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Monte Carlo and variance reduction methods for structural reliability analysis: A comprehensive review

by Song, Chenxiao, Kawai, Reiichiro
Published in Probabilistic engineering mechanics (01.07.2023)

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Optimal design of a novel tuned mass-damper–inerter (TMDI) passive vibration control configuration for stochastically support-excited structural systems

by Marian, Laurentiu, Giaralis, Agathoklis
Published in Probabilistic engineering mechanics (01.10.2014)

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Random function based spectral representation of stationary and non-stationary stochastic processes

by Liu, Zhangjun, Liu, Wei, Peng, Yongbo
Published in Probabilistic engineering mechanics (01.07.2016)

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MCMC algorithms for Subset Simulation

by Papaioannou, Iason, Betz, Wolfgang, Zwirglmaier, Kilian, Straub, Daniel
Published in Probabilistic engineering mechanics (01.07.2015)

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Probabilistic method for wind speed prediction and statistics distribution inference based on SHM data-driven

by Ding, Yang, Ye, Xiao-Wei, Guo, Yong, Zhang, Ru, Ma, Zhi
Published in Probabilistic engineering mechanics (01.07.2023)

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Offshore renewable energy site correlated wind-wave statistics

by Gaidai, Oleg, Wang, Fang, Wu, Yu, Xing, Yihan, Medina, Ausberto Rivera, Wang, Junlei
Published in Probabilistic engineering mechanics (01.04.2022)

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Metamodel-based importance sampling for structural reliability analysis

by Dubourg, V., Sudret, B., Deheeger, F.
Published in Probabilistic engineering mechanics (01.07.2013)

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Copula-based JPDF of wind speed, wind direction, wind angle, and temperature with SHM data

by Ding, Yang, Ye, Xiao-Wei, Guo, Yong
Published in Probabilistic engineering mechanics (01.07.2023)

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A deep learning solution approach for high-dimensional random differential equations

by Nabian, Mohammad Amin, Meidani, Hadi
Published in Probabilistic engineering mechanics (01.07.2019)

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Sparse representations and compressive sampling approaches in engineering mechanics: A review of theoretical concepts and diverse applications

by Kougioumtzoglou, Ioannis A., Petromichelakis, Ioannis, Psaros, Apostolos F.
Published in Probabilistic engineering mechanics (01.07.2020)

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A general framework for data-driven uncertainty quantification under complex input dependencies using vine copulas

by Torre, Emiliano, Marelli, Stefano, Embrechts, Paul, Sudret, Bruno
Published in Probabilistic engineering mechanics (01.01.2019)

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Support vector regression based metamodeling for structural reliability analysis

by Roy, Atin, Manna, Ramkrishna, Chakraborty, Subrata
Published in Probabilistic engineering mechanics (01.01.2019)

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An enhanced PDEM-based framework for reliability analysis of structures considering multiple failure modes and limit states

by Feng, De-Cheng, Cao, Xu-Yang, Beer, Michael
Published in Probabilistic engineering mechanics (01.10.2022)

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A long short-term memory based deep learning algorithm for seismic response uncertainty quantification

by Kundu, Anirban, Ghosh, Swarup, Chakraborty, Subrata
Published in Probabilistic engineering mechanics (01.01.2022)

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Comparison of PDEM and MCS: Accuracy and efficiency

by Li, Jie, Wang, Dan
Published in Probabilistic engineering mechanics (01.01.2023)

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Probabilistic reconstruction for spatiotemporal sensor data integrated with Gaussian process regression

by Ma, Yafei, He, Yu, Wang, Lei, Zhang, Jianren
Published in Probabilistic engineering mechanics (01.07.2022)

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Probability density evolution method: Background, significance and recent developments

by Li, Jie
Published in Probabilistic engineering mechanics (01.04.2016)

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A refined analysis of thunderstorm outflow characteristics relevant to the wind loading of structures

by Zhang, Shi, Solari, Giovanni, De Gaetano, Patrizia, Burlando, Massimiliano, Repetto, Maria Pia
Published in Probabilistic engineering mechanics (01.10.2018)

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An adaptive algorithm to build up sparse polynomial chaos expansions for stochastic finite element analysis

by Blatman, Géraud, Sudret, Bruno
Published in Probabilistic engineering mechanics (01.04.2010)

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Elucidating appealing features of differentiable auto-correlation functions: A study on the modified exponential kernel

by Faes, Matthias G.R., Broggi, Matteo, Spanos, Pol D., Beer, Michael
Published in Probabilistic engineering mechanics (01.07.2022)

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