Interface Establishment between Reinforcement Learning Algorithm and External Analysis Program for AI-based Automation of Bridge Design Process

Minsu Kim; Sanghyun Choi

doi:10.7734/COSEIK.2021.34.6.403

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2021 Vol.34, Issue 6 Preview Page Next Page

Research Paper

Interface Establishment between Reinforcement Learning Algorithm and External Analysis Program for AI-based Automation of Bridge Design Process AI기반 교량설계 프로세스 자동화를 위한 강화학습 알고리즘과 외부 해석프로그램 간 인터페이스 구축

31 December 2021. pp. 403-408

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Abstract

Currently, in the design process of civil structures such as bridges, it is common to make final products by repeating the process of redesigning, if the initial design is found to not meet the standards after a structural review. This iterative process extends the design time, and causes inefficient consumption of engineering manpower, which should be put into higher-level design, on simple repetitive mechanical work. This problem can be resolved by automating the design process, but the external analysis program used in the design process has been the biggest obstacle to such automation. In this study, we constructed an AI-based automation system for the bridge design process, including an interface that could control both a reinforcement learning algorithm, and an external analysis program, to replace the repetitive tasks in the current design process. The prototype of the system built in this study was developed for a 2-span RC Rahmen bridge, which is one of the simplest bridge systems. In the future, it is expected that the developed interface system can be utilized as a basic technology for linking the latest AI with other types of bridge designs.

Keywords

reinforcement learning

deep q-learning

bridge design

structural analysis

현재 교량과 같은 토목구조물의 설계프로세스는 1차 설계 후 구조 검토를 수행하여 기준에 부적합할 경우 재설계하는 과정을 반복하여 최종적인 성과품을 만드는 것이 일반적이다. 이러한 반복 과정은 설계에 소요되는 기간을 연장시키는 원인이 되며, 보다 수준 높은 설계를 위해 투입되어야 할 고급 엔지니어링 인력을 기계적인 단순 반복 작업에 소모하고 있다. 이러한 문제는 설계 과정 자동화를 통하여 해결할 수 있으나, 설계 과정에서 사용되는 해석프로그램은 이러한 자동화에 가장 큰 장애요인이 되어 왔다. 본 연구에서는 기존 설계 과정 중 반복작업을 대체하고자 강화학습 알고리즘과 외부 해석프로그램을 함께 제어할 수 있는 인터페이스를 포함한 교량설계 프로세스에 대한 AI기반 자동화 시스템을 구축하였다. 이 연구를 통하여 구축된 시스템의 프로토타입은 2경간 RC라멘교를 대상으로 제작하였다. 개발된 인터페이스 체계는 향후 최신 AI 및 타 형식의 교량설계 간 연계를 위한 기초기술로써 활용될 수 있을 것으로 판단된다.

키워드

강화학습

심층 큐러닝

교량설계

구조해석

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Information

Publisher :Computational Structural Engineering Institute of Korea
Publisher(Ko) :한국전산구조공학회
Journal Title :Journal of the Computational Structural Engineering Institute of Korea
Journal Title(Ko) :한국전산구조공학회 논문집
Volume : 34
No :6
Pages :403-408
Received Date : 2021-10-27
Revised Date : 2021-10-31
Accepted Date : 2021-11-02
DOI :https://doi.org/10.7734/COSEIK.2021.34.6.403

Journal of the Computational Structural Engineering Institute of Korea ISSN:1229-3059(Print) 2287-2302(Online) 한국전산구조공학회 논문집

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