Results 241 to 250 of about 4,977,477 (349)

High embankment slope stability prediction using data augmentation and explainable ensemble learning

open access: yesComputer-Aided Civil and Infrastructure Engineering, Volume 40, Issue 19, Page 2833-2858, 5 August 2025.
Abstract The stability of embankment slopes for heavy‐haul railway foundations is essential for safe railway operations. Railway embankment slope stability datasets often rely on engineering judgment for analysis. The labor‐ and resource‐intensive processes of data preparation result in small dataset sizes.
Zongyu Zhang   +8 more
wiley   +1 more source

Parameter identification in prestressed concrete beams by incremental beam–column equation and physics‐informed neural networks

open access: yesComputer-Aided Civil and Infrastructure Engineering, Volume 40, Issue 19, Page 2876-2899, 5 August 2025.
Abstract This paper explores a novel methodology for identifying prestress force (and bending rigidity) from the perspective of static deflection methods and derives an incremental beam–column equation (iBCE) by elucidating the mechanisms underlying the long‐ and short‐term behaviors, with particular emphasis on a physical system that disregards long ...
Yifan Yang, Zengwei Guo, Zhiyuan Liu
wiley   +1 more source

Early detection and location of unexpected events in buried pipelines under unseen conditions using the two‐stream global fusion classifier model

open access: yesComputer-Aided Civil and Infrastructure Engineering, EarlyView.
Abstract Failure of buried pipelines can result in serious impacts, such as explosions, environmental contamination, and economic losses. Early detection and location of unexpected events is crucial to prevent such events. However, conventional monitoring methods exhibit limited generalization performance under varying environmental and operational ...
Sun‐Ho Lee   +2 more
wiley   +1 more source

The Subgradient Extragradient Method for Solving Variational Inequalities in Hilbert Space

open access: yesJournal of Optimization Theory and Applications, 2011
Y. Censor, A. Gibali, S. Reich
semanticscholar   +1 more source

Deep learning for computer vision in pulse‐like ground motion identification

open access: yesComputer-Aided Civil and Infrastructure Engineering, EarlyView.
Abstract Near‐fault pulse‐like ground motions can cause severe damage to long‐period engineering structures. A rapid and accurate identification method is essential for seismic design. Deep learning offers a solution by framing pulse‐like motion identification as an image classification task.
Lu Han, Zhengru Tao
wiley   +1 more source

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