Development of maintenance management technology for road network structures using artificial intelligence technology

2022 Fiscal Year Final Research Report

• Project/Area Number: 18K04330
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Review Section: Basic Section 22020:Structure engineering and earthquake engineering-related
• Research Institution: Tokyo City University
• Principal Investigator: Maruyama Osamu 東京都市大学, 建築都市デザイン学部, 教授 (50209699)
• Project Period (FY): 2018-04-01 – 2023-03-31
• Keywords: structural deterioration / network structure / repair strategy / asset management

Outline of Final Research Achievements

The purpose of this research is to examine strategies for comprehensively maintaining and managing social infrastructure facilities, with a focus on network structures. Predicting the soundness and future deterioration of individual social infrastructure facilities, treating a group of facilities as a portfolio, considering physical loss and functional loss for the functions that should be fulfilled, and considering budget constraints and other conditions. construct a practical strategy for efficient budget allocation in
Using stochastic differential equations for inspection data, theoretical development was carried out for prediction of deterioration of tunnel structures in the near future and formulation of repair strategies. We developed a method that considers correlation when evaluating the portfolio risk of a spatially spread structural system.

Free Research Field

構造信頼性

Academic Significance and Societal Importance of the Research Achievements

本研究は，構造物点検データの有効活用を目的として，1)点検データを基に確率微分方程式による予測式により構造物の近未来の状態把握を行うこと，2）最適な点検・補修時期を理論的に求めること，更に3）道路，トンネル，橋梁などの構造物群で構成される道路ネットワークの維持管理補修戦略の構築を行った．膨大な社会資本の点検データは，いわゆる「ビック・データ」である．与えられたデータから有益な情報を見出し，社会資本の維持管理に必要な知見を与えることの学術的な意義は大きいと考えられる．