Results 121 to 130 of about 1,498,610 (256)

Generative adversarial network based on domain adaptation for crack segmentation in shadow environments

Computer-Aided Civil and Infrastructure Engineering, EarlyView.
Abstract Precision segmentation of cracks is important in industrial non‐destructive testing, but the presence of shadows in the actual environment can interfere with the segmentation results of cracks. To solve this problem, this study proposes a two‐stage domain adaptation framework called GAN‐DANet for crack segmentation in shadowed environments. In
Yingchao Zhang, Cheng Liu
wiley   +1 more source

Interpretable physics‐informed graph neural networks for flood forecasting

Computer-Aided Civil and Infrastructure Engineering, EarlyView.
Abstract Climate change has intensified extreme weather events, with floods causing significant socioeconomic and environmental damage. Accurate flood forecasting is crucial for disaster preparedness and risk mitigation, yet traditional hydrodynamic models, while precise, are computationally prohibitive for real‐time applications.
Mehdi Taghizadeh, Zanko Zandsalimi, Mohammad Amin Nabian, Majid Shafiee‐Jood, Negin Alemazkoor   +4 more
wiley   +1 more source

Self‐supervised domain adaptive approach for extrapolated crack segmentation with fine‐tuned inpainting generative model

Computer-Aided Civil and Infrastructure Engineering, EarlyView.
Abstract The number and proportion of aging infrastructures are increasing, thereby necessitating accurate inspection to ensure safety and structural stability. While computer vision and deep learning have been widely applied to concrete cracks, domain shift issues often result in the poor performance of pretrained models at new sites. To address this,
Seungbo Shim
wiley   +1 more source

End‐to‐end frequency enhancement framework for GPR images using domain‐adaptive generative adversarial networks

Computer-Aided Civil and Infrastructure Engineering, EarlyView.
Abstract Ground‐penetrating radar (GPR) offers nondestructive subsurface imaging but suffers from a trade‐off between frequency and penetration depth: High frequencies yield better resolution with limited depth, while low frequencies penetrate deeper with reduced detail.
Hancheng Zhang, Yuanyuan Hu, Qiang Wang, Zhendong Qian, Pengfei Liu   +4 more
wiley   +1 more source

Multiscale Analysis of Composite Structures with Artificial Neural Network Support for Micromodel Stress Determination. [PDF]

Materials (Basel), 2023
Kuś W, Mucha W, Jiregna IT.
europepmc   +1 more source

On Multiscale Methods in Petrov-Galerkin formulation [PDF]

arXiv, 2014
In this work we investigate the advantages of multiscale methods in Petrov-Galerkin (PG) formulation in a general framework. The framework is based on a localized orthogonal decomposition of a high dimensional solution space into a low dimensional multiscale space with good approximation properties and a high dimensional remainder space{, which only ...
arxiv  

Prediction of the most fire‐sensitive point in building structures with differentiable agents for thermal simulators

Computer-Aided Civil and Infrastructure Engineering, EarlyView.
Abstract Fire safety is crucial for ensuring the stability of building structures, yet evaluating whether a structure meets fire safety requirements is challenging. Fires can originate at any point within a structure, and simulating every potential fire scenario is both expensive and time‐consuming.
Yuan Xinjie, Khalid M. Mosalam
wiley   +1 more source

A Novel Methodology for the Automatic Decomposition of HAWT Wakes With K‐Means Clustering

Wind Energy, Volume 28, Issue 7, July 2025.
ABSTRACT This work presents a novel and automatic approach to process data from computational fluid dynamics at runtime, to identify and separate different regions of wind turbine wakes. The methodology is based on partitional clustering, in particular k‐Means, and applied to large eddy simulation (LES) computations of the wake of a DTU‐10‐MW wind ...
Lorenzo Tieghi, Davide Cerbarano, Filippo De Girolamo, Valerio Francesco Barnabei, Giovanni Delibra   +4 more
wiley   +1 more source

Fatigue Prediction of 50% Short Fiber‐Reinforced Polyphthalamide Using Equivalent Stress Criteria and Critical Distance Methods

Fatigue &Fracture of Engineering Materials &Structures, Volume 48, Issue 7, Page 2949-2964, July 2025.
Abstract Accurately predicting the fatigue lifetime of short fiber‐reinforced polymers (SFRPs) remains a significant challenge in the automotive industry, especially in the presence of sharp geometric discontinuities. This study presents a practical approach for estimating the fatigue life of injection‐molded notched SFRP specimens, considering ...
Francesco Emanuele Fiorini, Andrea Canegrati, Luca Michele Martulli, Philippe Steck, Andrea Bernasconi   +4 more
wiley   +1 more source

Subcycling Strategy for Finite‐Volume Updated‐Lagrangian Methods Applied to Fluid–Structure Interaction

International Journal for Numerical Methods in Engineering, Volume 126, Issue 11, 15 June 2025.
ABSTRACT In this article, we propose and investigate an explicit partitioned method for solving shock dynamics in fluid–structure interaction (FSI) problems. The method is fully conservative, ensuring the local conservation of mass, momentum, and energy, which is crucial for accurately capturing strong shock interactions.
Teddy Chantrait, Nicolas Chevaugeon, Stéphane Del Pino, Alexandre Gangloff, Emmanuel Labourasse   +4 more
wiley   +1 more source