A generalized autoregressive model for time-variant dynamical systems

Autor/innen

Styfen Schär
Chair of Risk, Safety and Uncertainty Quantification, ETH Zurich, 8093 Zurich, Switzerland
https://orcid.org/0000-0001-6715-220X
Chiara Nardin
Chair of Risk, Safety and Uncertainty Quantification, ETH Zurich, 8093 Zurich, Switzerland; Department of Civil, Environmental and Mechanical Engineering, University of Trento, 38132 Trento, Italy
https://orcid.org/0000-0001-5860-0314
Stefano Marelli
Chair of Risk, Safety and Uncertainty Quantification, ETH Zurich, 8093 Zurich, Switzerland
https://orcid.org/0000-0002-9268-9014
Bruno Sudret
Chair of Risk, Safety and Uncertainty Quantification, ETH Zurich, 8093 Zurich, Switzerland
https://orcid.org/0000-0002-9501-7395
DOI: https://doi.org/10.17877/tudobooks-11.153

Über dieses Buch

Surrogate models are a staple tool for the reliability analysis of complex engineering systems, because they enable the use of otherwise computationally prohibitive algorithms, such as Monte-Carlo simulation. Their prevalence in the context of nonlinear dynamic engineering systems, however, is significantly lower, because approximating their time-dependent response is generally considered more challenging than for their static counterparts. A powerful class of surrogate models is provided by autoregressive with exogenous input models, but their use is mostly limited to system identification tasks, as they tend to underperform in pure prediction tasks. Recent advances in data-driven autoregressive modeling, have vastly improved their prediction capabilities for engineering applications, but they still rely on the assumption of time-invariant dynamics at the core of NARX. In this contribution we demonstrate how the mNARX+ framework can efficiently handle time-variant dynamical systems, such as, e.g., civil or mechanical structures subject to plastic damage or fatigue accumulation, making it an ideal tool for their reliability assessment.

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

473-485

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 generalized autoregressive model for time-variant dynamical systems. (2026). In REC 2026 - 11th International Workshop on Reliable Engineering Computing: Reliability Computations in a Data and Model-Driven World (pp. 473-485). TUDObooks. https://doi.org/10.17877/tudobooks-11.153