A transformation-based framework for modeling and simulation of multivariate non-Gaussian random fields

Autor/innen

Meng-Ze Lyu
Institute for Risk & Reliability, Leibniz University Hannover, Hannover 30167, Germany
https://orcid.org/0000-0002-8932-2617
Yang-Yi Liu
Department of Civil, Environmental & Geo-Engineering, University of Minnesota Twin Cities, Minneapolis 55455, USA
Jian-Bing Chen
College of Civil Engineering, Tongji University, Shanghai 200092, China
https://orcid.org/0000-0001-8520-0383
Michael Beer
Institute for Risk and Reliability, Leibniz Universität Hannover, Hannover, Germany / Institute for Risk and Uncertainty, University of Liverpool, Liverpool, UK / Shanghai Institute of Disaster Prevention and Relief, Tongji University, Shanghai, China
https://orcid.org/0000-0002-0611-0345
DOI: https://doi.org/10.17877/tudobooks-11.194

Über dieses Buch

Accurate modeling of multivariate non-Gaussian random fields remains a fundamental challenge in reliable engineering computation, particularly when nonlinear dependencies coexist with spatial correlation. This study introduces a new framework in which the probabilistic model is defined by the original marginal distributions together with linear correlations of Gaussianized transformed variables. This leads to a transformed correlation function that preserves non-Gaussian marginals while consistently characterizing spatial variability. The bridge function, originally developed for Gaussian fields, is extended to reconcile spatial correlation with nonlinear dependencies such as those captured by vine copulas. Based on this model, an efficient non-iterative simulation algorithm is developed. Numerical results show that the method accurately reproduces marginal distributions, nonlinear dependence, and spatial correlation in complex engineering fields.

REC 2026 Reliability Computations in a Data and Model-Driven World

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REC 2026 - 11th International Workshop on Reliable Engineering Computing: Reliability Computations in a Data and Model-Driven World

Seiten

244-254

Veröffentlicht

21.08.2026
Copyright (c) 2026 Matthias Faes, Michael Beer, Julian Behrend, Marco Broccardo, Guohai Chen, Hanshu Chen, Jieyu Chen, Fang Cong, Henrik Ebel, Peter Eberhard, Andrea Franchini, Zhuojia Fu, Yanzhao Gu, Michael Hanss, Hui Huang, Md Maidul Islam, Jafar Jafari-Asl, Balsa Jovanovic, Tom Könecke, Olga Kosheleva, Vladik Kreinovich, Hao-Ming Li, Pei-Pei Li, Qinghe Li, Ruikun Li, Stefano Marelli, Rafi L. Muhanna, Robert L. Mullen, Chiara Nardin, Lukáš Novák, Shenghao Piao, Mario Rosenfelder, Styfen Schär, Jan Schneider, Wei Shi, Panagiotis Spyridis, Bruno Sudret, Ruben Van Coile, Bo-Yu Wang, Dixiong Yang, Xuan-Yi Zhang, Zi-Xin Zhang, Bo-Qi Zhao, Yan-Gang Zhao, Zhibao Zheng, Baihong Zhong, Zhaowei Zhou, Marcos A. Valdebenito, Chao Dang, Lan-Xin Li, Marius Bittner, Parth Tambat, Marco Behrendt, Zhao Liu, Ping Zhu, Zlatan Dimitrov, Petar O. Hristov, Meng-Ze Lyu, Yang-Yi Liu, Jian-Bing Chen, Qitian Lu, Miroslav Vořechovský, Ekaterina Auer, Lorenz Gillner, Julien Alexandre dit Sandretto, Binod K. Yadav, Ghifari Adam Faza, Hans Hallez, David Moens, Reza Naeimaei, Steffen Schön, Elisabeth Ötsch, Hans Neuner, Zhanhua Liang, Jingwen Song, Michael Desch, Mehdi Modares, Valentin Nikolov, Paulo Lucas Figueiredo, José Torres Farinha, Hugo Raposo, António J. Marques Cardoso, Alice do Carmo Duarte Rodrigues, Paula Gonçalves, Peihan Chen, Xinyu Zhu, Pengfei Wei, Kaiwen Li, Mansoureh Shahabi, Y. F. Cui, Johannes O. Royset, Salvatore Russotto, Mario Di Paola, Antonina Pirrotta, Til Lux, Johannes Sundheim, Tania Feiri, Udo Wiens, Marcus Ricker, F. Niklas Schietzold, Felix Harazin, Yoshi Diepelt, Wolfgang Graf, Michael Kaliske, Rongyao Song, Changcong Zhou, Xuanyi Zhao, Weiping Zhang, Juntao Hu, Yu Chen, Edoardo Patelli, Tingting Sun, Jianbing Chen, Bouwe Verkens, L. Bogaerts, Patrick Van Rymenant, Maximilian Schweizer, Marc Fina, Werner Wagner, Steffen Freitag, George Stefanou, Dimitros Savvas, Panagiotis Gavalas, Luigi Schiano, Razhan S. Ahmed, Oleksandr Al-Shboul, David Ringeloth, Vladislav Gudžulić, Stefanie Schoen, Jelena Bijeljić, Ernst Niederleithinger, Iurie Curoşu, Gerrit E. Neu, Jia-Hui Fu, Yi Luo, De-Cheng Feng, Xiao-Qiu Ai, Luyi Li, Hao Wang, Tairan Wang, Sifeng Bi, Emily Zeller (Kapitelautor/in)

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Creative Commons License

Dieses Werk steht unter der Lizenz Creative Commons Namensnennung 4.0 International.

Zitationsvorschlag

A transformation-based framework for modeling and simulation of multivariate non-Gaussian random fields. (2026). In REC 2026 - 11th International Workshop on Reliable Engineering Computing: Reliability Computations in a Data and Model-Driven World (pp. 244-254). TUDObooks. https://doi.org/10.17877/tudobooks-11.194