Structural Design and Optimization of Lifting Self-forming GFRP Elastic Gridshells based on Machine Learning

Soheila Kookalani, Hamidreza Alavi, Farzad Pour Rahimian

• Publisher: CRC Press
• Year: 2025
• eBook ISBN: 9781040406328
• Topic: Computer Science
• Subtopic: Architecture General
• Index: Computer Science

Structural Design and Optimization of Lifting Self-forming GFRP Elastic Gridshells Based on Machine Learning presents the algorithms of machine learning (ML) that can be used for the structural design and optimization of glass fiber reinforced polymer (GFRP) elastic gridshells, including linear regression, ridge regression, K-nearest neighbors, decision tree, random forest, AdaBoost, XGBoost, artificial neural network, support vector machine (SVM), and six enhanced forms of SVM. It also introduces interpretable ML approaches, including partial dependence plot, accumulated local effects, and SHaply additive exPlanations (SHAP). Also, several methods for developing ML algorithms, including K-fold cross-validation (CV), Taguchi, a technique for order preference by similarity to ideal solution (TOPSIS), and multi-objective particle swarm optimization (MOPSO), are proposed. These algorithms are implemented to improve the applications of gridshell structures using a comprehensive representation of ML models. This research introduces novel frameworks for shape prediction, form-finding, structural performance assessment, and shape optimization of lifting self-forming GFRP elastic gridshells using ML methods. This book will be of interest to researchers and academics interested in advanced design methods and ML technology in architecture, engineering, and construction fields.

Table of contents

• Cover Page
• Half-Title Page
• Series Page
• Title Page
• Copyright Page
• Contents
• Preface
• List of Acronyms and Abbreviations
• Chapter 1 Introduction of GFRP Elastic Gridshell Structures and Machine Learning
• Chapter 2 A Review of GFRP Elastic Gridshell Structures and Machine Learning Algorithms
• Chapter 3 Shape Prediction of Slender Bars Based on Discrete Elements
• Chapter 4 Shape Prediction of GFRP Elastic Gridshells During Lifting Construction
• Chapter 5 Form-Finding of GFRP Elastic Gridshells During Lifting Construction Process
• Chapter 6 Structural Performance Assessment of GFRP Elastic Gridshells
• Chapter 7 Structural Optimization of GFRP Elastic Gridshells
• Chapter 8 Conclusions and Recommendations for Structural Design and Optimizations of Gridshell Structures
• Index