Hongzhang Wang¹, Jing Guo¹, Shanjun Yang¹, Chaoheng Cheng², Jing Chen^3,*, Zhihao Chen³

Structural Durability & Health Monitoring, Vol.18, No.2, pp. 181-196, 2024, DOI:10.32604/sdhm.2024.044628

Abstract Pitting corrosion is harmful during bridge construction, which will lead to uneven roughness of steel surfaces and reduce the thickness of steel. Hence, the effect of pitting corrosion on the mechanical properties of cold-formed thin-walled steel stub columns is studied, and the empirical formulas are established through regression fitting to predict the ultimate load of web and flange under pitting corrosion. In detail, the failure modes and load-displacement curves of specimens with different locations, area ratios, and depths are obtained through a large number of non-linear finite element analysis. As for the specimens with pitting corrosion on the web, all… More > Graphic Abstract

Vishal Shreyans Shah¹, Henyl Rakesh Shah², Pijush Samui³, A. Ramachra Murthy⁴

CMC-Computers, Materials & Continua, Vol.44, No.2, pp. 73-84, 2014, DOI:10.3970/cmc.2014.044.073

Abstract This paper deals with the development of models for prediction of facture parameters, namely, fracture energy and ultimate load of high strength and ultra high strength concrete based on Minimax Probability Machine Regression (MPMR) and Extreme Learning Machine (ELM). MPMR is developed based on Minimax Probability Machine Classification (MPMC). ELM is the modified version of Single Hidden Layer Feed Foreword Network (SLFN). MPMR and ELM has been used as regression techniques. Mathematical models have been developed in the form of relation between several input variables such as beam dimensions, water cement ratio, compressive strength, split tensile strength, notch depth, and… More >