Probabilistic resilience analysis of urban road network considering wind damage to street trees via dimension-reduced probability density evolution equation (DR-PDEE)

Autor/innen

Yi Luo
Institute for Risk & Reliability, Leibniz University Hannover, Hannover 30167, Germany
https://orcid.org/0000-0002-6266-6700
De-Cheng Feng
School of Civil Engineering, Southeast University, Nanjing 211189, China
Xiao-Qiu Ai
Shanghai Institute of Disaster Prevention and Relief, Shanghai 200092, China
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-11.162

Über dieses Buch

A probabilistic framework to quantify the resilience of urban road networks considering the wind blowdown of urban trees is proposed. Various properties of street patterns, including length, speed class, and width, as well as the failure probability due to tree-blowdown are considered. The resilience is considered as the mean normalized efficiency during the reconstruction period, and a reconstruction strategy based on the edge betweenness and estimated edge recovering time is employed. The probability density function (PDF) of the estimated resilience under different wind speed is computed by using the dimension-reduced probability density evolution equation (DR-PDEE). The road network of the Inner-Ring area of Yangpu district, Shanghai, China is considered as an example.

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

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560-569

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

Zitationsvorschlag

Probabilistic resilience analysis of urban road network considering wind damage to street trees via dimension-reduced probability density evolution equation (DR-PDEE). (2026). In REC 2026 - 11th International Workshop on Reliable Engineering Computing: Reliability Computations in a Data and Model-Driven World (pp. 560-569). TUDObooks. https://doi.org/10.17877/tudobooks-11.162