Axial resistant behavior of stub fold-fastened multi-cellular steel walls: Tests and simulations DOI

Shengjie Duan,

Jing‐Zhong Tong, Chao-Qun Yu

и другие.

Journal of Building Engineering, Год журнала: 2025, Номер unknown, С. 112913 - 112913

Опубликована: Май 1, 2025

Язык: Английский

Unified machine-learning-based design method for cold-formed steel multi-limbs built-up open section columns DOI
Yan Lu,

Bin Wu,

Tianhua Zhou

и другие.

Structures, Год журнала: 2025, Номер 73, С. 108398 - 108398

Опубликована: Фев. 14, 2025

Язык: Английский

Процитировано

1

Application of Artificial Intelligence to Support Design and Analysis of Steel Structures DOI Creative Commons
Sina Sarfarazi, Ida Mascolo, Mariano Modano

и другие.

Metals, Год журнала: 2025, Номер 15(4), С. 408 - 408

Опубликована: Апрель 4, 2025

In steel structural engineering, artificial intelligence (AI) and machine learning (ML) are improving accuracy, efficiency, automation. This review explores AI-driven approaches, emphasizing how AI models improve predictive capabilities, optimize performance, reduce computational costs compared to traditional methods. Inverse Machine Learning (IML) is a major focus since it helps engineers minimize reliance on iterative trial-and-error by allowing them identify ideal material properties geometric configurations depending predefined performance targets. Unlike conventional ML that mostly forward predictions, IML data-driven design generation, enabling more adaptive engineering solutions. Furthermore, underlined Explainable Artificial Intelligence (XAI), which enhances model transparency, interpretability, trust of AI. The paper categorizes applications in construction based their impact automation, health monitoring, failure prediction evaluation throughout research from 1990 2025. challenges such as data limitations, generalization, reliability, the need for physics-informed while examining AI’s role bridging real-world applications. By integrating into this work supports adoption ML, IML, XAI analysis design, paving way reliable interpretable practices.

Язык: Английский

Процитировано

1

An explainable machine learning method for predicting and designing crashworthiness of multi-cell tubes under oblique load DOI

Jian Xie,

Junyuan Zhang, Zheng Dou

и другие.

Engineering Applications of Artificial Intelligence, Год журнала: 2025, Номер 147, С. 110396 - 110396

Опубликована: Фев. 26, 2025

Язык: Английский

Процитировано

0

Deep Rayleigh-Ritz method for elastic local buckling analysis of cold-formed steel columns DOI
Yan Lu, Bo Ren,

Bin Wu

и другие.

Structures, Год журнала: 2025, Номер 76, С. 109016 - 109016

Опубликована: Апрель 28, 2025

Язык: Английский

Процитировано

0

Axial resistant behavior of stub fold-fastened multi-cellular steel walls: Tests and simulations DOI

Shengjie Duan,

Jing‐Zhong Tong, Chao-Qun Yu

и другие.

Journal of Building Engineering, Год журнала: 2025, Номер unknown, С. 112913 - 112913

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

0