APPLICATION OF KNOWLEDGE-BASED SYSTEM (KBS) AND ARTIFICIAL INTELLIGENCE IN THE DESIGN OF REINFORCEMENT BARS FOR RECTANGULAR REINFORCED CONCRETE BEAMS ACCORDING TO TCVN 5574:2018

APPLICATION OF KNOWLEDGE-BASED SYSTEMS (KBS) AND ARTIFICIAL INTELLIGENCE IN DESIGNING LONGITUDINAL REINFORCEMENT FOR RECTANGULAR REINFORCED CONCRETE BEAMS ACCORDING TO TCVN 5574:2018

Abstract

In the era of Industry 4.0, automating structural design is essential for enhancing efficiency. This study proposes an AI-integrated Knowledge-Based System (KBS) to streamline the complex process of RC beam reinforcement design. By encoding TCVN 5574:2018 provisions into a logic-based framework, the system provides optimal detailing solutions that traditional software often overlooks. Current commercial structural analysis software mainly focuses on calculating internal forces and required steel area (A_s​), but lacks the capability to automate the detailed selection and optimal arrangement of longitudinal reinforcement that fully complies with the restrictive conditions of the Vietnamese standard. This study proposes the development of a Knowledge-Based System (KBS) integrated with artificial intelligence (AI) to address this problem. The KBS models the provisions of TCVN 5574:2018 into a Knowledge Base and utilizes an intelligent Search/Filter Algorithm (AI Module) to automatically find the most optimal longitudinal reinforcement layout (minimizing material cost) for rectangular RC beams. Validation results demonstrate that the system significantly reduces design time, eliminates errors caused by manual calculation, and ensures absolute compliance with the standard, presenting substantial application potential in structural design practice in Vietnam.