A novel machine learning method to investigate the web crippling behaviour of perforated roll-formed aluminium alloy unlipped channels under interior-two flange …

Z Fang, K Roy, J Xu, Y Dai, B Paul, JBP Lim - Journal of Building …, 2022 - Elsevier
This study presents a novel machine-learning model using the eXtreme Gradient Boosting
(XGBoost) tool, for assessing the web crippling behaviour of perforated roll-formed …

Web crippling investigation of perforated aluminium lipped channels under interior-two-flange loading condition

H Alsanat, S Gunalan, P Gatheeshgar, M Alrsai… - Thin-Walled …, 2023 - Elsevier
Roll-formed aluminium members fabricated using 5052-H36 aluminium alloy grade have
been recently employed as structural members in construction. Their web crippling …

Optimal design of cold-formed steel face-to-face built-up columns through deep belief network and genetic algorithm

Y Dai, Z Fang, K Roy, GM Raftery, JBP Lim - Structures, 2023 - Elsevier
In this paper, a machine-learning optimisation framework for cold-formed steel (CFS) face-to-
face built-up columns was proposed using Deep Belief Network (DBN) and Genetic …

Bonobo optimizer algorithm for optimum design of truss structures with static constraints

V Goodarzimehr, U Topal, AK Das, T Vo-Duy - Structures, 2023 - Elsevier
In this study, a very recently developed intelligent algorithm called Bonobo Optimizer (BO)
algorithm is implemented for the sizing optimization of the truss structures with discrete and …

Optimizing the material and printing parameters of the additively manufactured fiber-reinforced polymer composites using an artificial neural network model and …

W Alhaddad, M He, Y Halabi, KYM Almajhali - Structures, 2022 - Elsevier
Fiber-reinforced polymer composite (FRP) has always been attracting the attention of
researchers due to its multiple applications as a primary material for manufacturing structural …

Assessment of end-two-flange web crippling strength of roll-formed aluminium alloy perforated channels by experimental testing, numerical simulation, and deep …

Z Fang, K Roy, JM Ingham, JBP Lim - Engineering Structures, 2022 - Elsevier
This work presents a deep-learning model referred to as a deep belief network (DBN) to
investigate the end-two-flange (ETF) web crippling behaviour of roll-formed aluminium alloy …

Bond prediction of stainless-steel reinforcement using artificial neural networks

M Rabi - Proceedings of the Institution of Civil Engineers …, 2023 - icevirtuallibrary.com
Stainless-steel reinforcement has become increasingly popular in the construction industry
in recent years, mainly due to its distinctive characteristics and excellent mechanical …

Experimental and numerical study of a novel cold-formed steel T-Stub connection subjected to tension force

K Roy, H Rezaeian, Z Fang, GM Raftery… - Journal of Constructional …, 2022 - Elsevier
Cold-formed steel (CFS) is a popular form of construction in New Zealand and the
developed world because it can be cost-effective, durable, sustainable, resilient to extreme …

Prediction of aerodynamic forces at the tip of the compressor blades based on multi-scale 1DCNN combined with CBAM

M Yao, S Wu, Y Niu, Q Wu, R Song, B Bai - Thin-Walled Structures, 2024 - Elsevier
The compressor is a crucial component of aircraft engines, and the blades are the critical
factor affecting the performance of the compressor. Based on multi-scale one-dimensional …

Auxetic pattern design for concentric-tube robots using an active DNN-metaheuristics optimization

J Park, JM Hur, S Park, DN Kim, G Noh - Thin-Walled Structures, 2024 - Elsevier
We optimized the design parameters of three auxetic patterns to minimize the bending
stiffness-to-torsional stiffness ratios (EI/GJ) in concentric-tube robots while maintaining …