Artificial Intelligence-Based Design and Analysis of Passive Control Structures: An Overview

Abstract

Recently, artificial intelligence (AI) has been widely adopted in the design and analysis of passively controlled structures. This study provides a comprehensive overview of AI-based methodologies aimed at enhancing the resilience and efficiency of buildings and infrastructures against environmental stresses and natural disasters. Despite extensive research on passive control systems like base isolators and energy dissipators, a detailed review focusing on AI's application in optimizing these systems is still lacking. This research addresses this gap by exploring the potential of AI to improve the design and performance of passive control systems. Traditional design methods often fail to adequately address the complex interactions between environmental forces and passive control systems, resulting in suboptimal safety and performance. By leveraging AI's predictive and analytical capabilities, this study highlights insights and strategies for enhancing the effectiveness and reliability of passively controlled structures. The findings show the AI's role in advancing structural engineering, promoting the development of smarter, adaptive building infrastructure, and ultimately contributing to safer, more resilient communities in the face of environmental challenges.

Keywords

• artificial intelligence
• structural engineering
• passive control systems
• seismic mitigation
• design optimization