Beyond p-y method: A review of artificial intelligence approaches for predicting lateral capacity of drilled shafts in clayey soils

IF 11.3 1区化学 Q1 CHEMISTRY, PHYSICAL

ACS Catalysis Pub Date : 2024-05-01 DOI:10.1016/j.jrmge.2024.03.017

M.E. Al-Atroush, A.E. Aboelela, Ezz El-Din Hemdan

引用次数: 0

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超越 P-Y 法：预测粘性土中钻井横向承载力的人工智能方法综述

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

ACS Catalysis CHEMISTRY, PHYSICAL-

CiteScore

20.80

自引率

6.20%

发文量

1253

审稿时长

1.5 months

期刊介绍： ACS Catalysis is an esteemed journal that publishes original research in the fields of heterogeneous catalysis, molecular catalysis, and biocatalysis. It offers broad coverage across diverse areas such as life sciences, organometallics and synthesis, photochemistry and electrochemistry, drug discovery and synthesis, materials science, environmental protection, polymer discovery and synthesis, and energy and fuels. The scope of the journal is to showcase innovative work in various aspects of catalysis. This includes new reactions and novel synthetic approaches utilizing known catalysts, the discovery or modification of new catalysts, elucidation of catalytic mechanisms through cutting-edge investigations, practical enhancements of existing processes, as well as conceptual advances in the field. Contributions to ACS Catalysis can encompass both experimental and theoretical research focused on catalytic molecules, macromolecules, and materials that exhibit catalytic turnover.