在国内外众多专家和朋友的支持下,Earthquake Engineering & Structural Dynamics AI特刊(EESD special issue: AI and data-driven methods in earthquake engineering)已经正式出版。本次特刊分为Part1和Part2两卷,详细信息请参见以下链接。
Part 1
Part 2
为更好的分享和传播地震工程领域与AI交叉的最新学科成果,EESD主编Masayoshi Nakashima教授与Wiley出版社商议后,本次特刊到2023年11月中旬前提供免费下载服务,欢迎大家阅读和交流。
Part 1论文目录
A hybrid non-parametric ground motion model for shallow crustal earthquakes in Europe. Vemula Sreenath, Bhargavi Podili, S. T. G. Raghukanth
Site classification using deep-learning-based image recognition techniques. Kun Ji, Chuanbin Zhu, Saman Yaghmaei-Sabegh, Jianqi Lu, Yefei Ren, Ruizhi Wen
Assessment of ground motion amplitude scaling using interpretable Gaussian process regression: Application to steel moment frames. Jawad Fayaz, Pablo Torres-Rodas, Miguel Medalla, Farzad Naeim
An unsupervised machine learning based ground motion selection method for computationally efficient estimation of seismic fragility. Jinjun Hu, Bali Liu, Lili Xie
Deep learning based seismic response prediction of hysteretic systems having degradation and pinching. Taeyong Kim, Oh-Sung Kwon, Junho Song
Surrogate modeling of structural seismic response using probabilistic learning on manifolds. Kuanshi Zhong, Javier G. Navarro, Sanjay Govindjee, Gregory G. Deierlein
Combination of physics-based and data-driven modeling for nonlinear structural seismic response prediction through deep residual learning. Jia Guo, Ryuta Enokida, Dawei Li, Kohju Ikago
The automated collapse data constructor technique and the data-driven methodology for seismic collapse risk assessment. Nenad Bijelić, Dimitrios G. Lignos, Alexandre Alahi
Reliability analysis of structures using probability density evolution method and stochastic spectral embedding surrogate model. Sourav Das, Solomon Tesfamariam
Deep learning-based evaluation for mechanical property degradation of seismically damaged RC columns. Zenghui Miao, Xiaodong Ji, Minghui Wu, Xiang Gao
Instance segmentation of soft-story buildings from street-view images with semiautomatic annotation. Chaofeng Wang, Sascha Hornauer, Stella X. Yu, Frank McKenna, Kincho H. Law
Three-dimensional fragility surface for reinforced concrete shear walls using image-based damage features. Amir Hossein Asjodi, Kiarash M. Dolatshahi, Henry V. Burton
Story drift and damage level estimation of buildings using relative acceleration responses with multi-target deep learning models under seismic excitation. Jau-Yu Chou, Chieh-Yu Liu, Chia-Ming Chang
Part 2论文目录
Unsupervised machine learning for detecting soil layer boundaries from cone penetration test data. Kenneth S. Hudson, Kristin J. Ulmer, Paolo Zimmaro, Steven L. Kramer, Jonathan P. Stewart, Scott J. Brandenberg
A continuous Bayesian network regression model for estimating seismic liquefaction-induced settlement of the free-field ground. Jilei Hu, Bin Xiong, Zheng Zhang, Jing Wang
Machine learning-based prediction of the seismic response of fault-crossing natural gas pipelines. Wenyang Zhang, Francois Ayello, Doug Honegger, Yousef Bozorgnia, Ertugrul Taciroglu
Machine-learning-based optimization framework to support recovery-based design. Omar Issa, Rodrigo Silva-Lopez, Jack W. Baker, Henry V. Burton
Base-isolation design of shear wall structures using physics-rule-co-guided self-supervised generative adversarial networks. Wenjie Liao, Xinyu Wang, Yifan Fei, Yuli Huang, Linlin Xie, Xinzheng Lu
A deep learning method to monitor axial pressure and shear deformation of rubber bearings under coupled compression and shear loading. Yi Zeng, Zhizhou He, Peng Pan
Collaborative filtering-based collapse fragility assessment. Xingquan Guan, Henry V. Burton
Uncertainty-aware structural damage warning system using deep variational composite neural networks. Kareem A. Eltouny, Xiao Liang
Multi-channel response reconstruction using transformer based generative adversarial network. Wenhao Zheng, Jun Li, Qilin Li, Hong Hao
Geometry-guided semantic segmentation for post-earthquake buildings using optical remote sensing images. Yu Wang, Xin Jing, Yang Xu, Liangyi Cui, Qiangqiang Zhang, Hui Li
Deep neural network-based regional seismic loss assessment considering correlation between EDP residuals of building structures. Chulyoung Kang, Taeyong Kim, Oh-Sung Kwon, Junho Song
Efficient regional seismic risk assessment via deep generative learning of surrogate models. Shanwu Li, Charles Farrar, Yongchao Yang.
Simulation-based methodology to identify damage indicators and safety thresholds for post-earthquake evaluation of structures. Francisco A. Galvis, Anne M. Hulsey, Jack W. Baker, Gregory G. Deierlein
Generalized stacked LSTM for the seismic damage evaluation of ductile reinforced concrete buildings. Bilal Ahmed, Sujith Mangalathu, Jong-Su Jeon
Seismic damage prediction of RC buildings using machine learning. Sanjeev Bhatta, Ji Dang
Guest Editors
陆新征
清华大学土木工程系教授
Henry Burton
加州大学洛杉矶分校(UCLA)
土木与环境工程学院副教授
EESD简介
Earthquake Engineering & Structural Dynamics是世界地震工程学会会刊、土木工程领域JCR Q1期刊(最新影响因子4.500),主编为中岛正爱(Masayoshi Nakashima)教授。该刊在地震工程领域享有盛誉。主要发表与地震工程和结构动力学相关的研究工作,包括以下方向:
1. Ground motions for analysis and design
2. Geotechnical earthquake engineering, including wave propagation, dynamic interaction, and underground structures
3. Probabilistic and deterministic methods of dynamic analysis
4. Experimental and computational simulation of dynamic effects on structures, including validation and verification in seismic simulation
5. Seismic protective systems, including seismic isolation systems, damping systems, new structural systems, adaptive and active systems
6. Earthquake health monitoring and sensors
7. Seismic code requirements, development, and evaluation
8. Methods for earthquake‐resistant design and retrofit of structures
9. Seismic risk assessment, quantification of resilience, and lifetime considerations for buildings, other structures, and community systems
10. Multi-hazard engineering that includes earthquakes and other hazards (wind, tsunami, storm surge, fire, blast, impact, etc.)
11. Enhanced seismic design emphasizing damage minimization, repairability, functional recovery, etc.
12. Seismic behavior, modelling and dynamic analysis of non-structural elements
13. Data-driven methods in earthquake engineering
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