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

Research Project

Project/Area Number 18K04330
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Review Section Basic Section 22020:Structure engineering and earthquake engineering-related
Research InstitutionTokyo 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
Project Status Completed (Fiscal Year 2022)
Budget Amount *help
¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
Fiscal Year 2020: ¥390,000 (Direct Cost: ¥300,000、Indirect Cost: ¥90,000)
Fiscal Year 2019: ¥390,000 (Direct Cost: ¥300,000、Indirect Cost: ¥90,000)
Fiscal Year 2018: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Keywordsstructural deterioration / network structure / repair strategy / asset management / 維持管理 / アセットマネジメント / 確率論的最大損失評価 / 機械学習 / 劣化予測 / ライフライン維持管理 / 確率微分方程式 / 確率場情報更新 / カーネル補間 / 構造物維持管理 / 人工知能 / 道路交通網
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.

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.

Report

(6 results)
  • 2022 Annual Research Report   Final Research Report ( PDF )
  • 2021 Research-status Report
  • 2020 Research-status Report
  • 2019 Research-status Report
  • 2018 Research-status Report
  • Research Products

    (6 results)

All 2022 2020 2019

All Journal Article (3 results) (of which Peer Reviewed: 3 results) Presentation (3 results) (of which Int'l Joint Research: 2 results)

  • [Journal Article] Probable maximum loss of a pipe network due to earthquakes: a case study in Iloilo city, Philippines2020

    • Author(s)
      Samantha Louise N. Jarder, Lessandro Estelito O. Garciano, Osamu Maruyama
    • Journal Title

      International Journal of Disaster Resilience in the Built Environment

      Volume: Vol.12 Issue: 2 Pages: 223-237

    • DOI

      10.1108/ijdrbe-03-2020-0017

    • Related Report
      2020 Research-status Report
    • Peer Reviewed
  • [Journal Article] Proposed resilience index of water lifeline systems2020

    • Author(s)
      Carandang, A.M.S., Garciano, L.E.O., Maruyama, O. and De Jesus, R.
    • Journal Title

      International Journal of Disaster Resilience in the Built Environment

      Volume: Vol.11 Issue: 3 Pages: 253-264

    • DOI

      10.1108/ijdrbe-04-2020-0030

    • Related Report
      2020 Research-status Report
    • Peer Reviewed
  • [Journal Article] リスク最適制御の数値解法に対する重点サンプリング法の適用2019

    • Author(s)
      兼清泰明,東平蔵,檀寛成,須藤敦史,丸山收,佐藤京
    • Journal Title

      The Ninth Japan Conference on Structural Safety and Reliability

      Volume: Vol.9 Pages: 15-22

    • Related Report
      2019 Research-status Report
    • Peer Reviewed
  • [Presentation] implified Probable Maximum Loss Model from Generated Correlated Seismic Damaged Ratio2022

    • Author(s)
      Samantha Louise Jarder
    • Organizer
      令和4年度 土木学会全国大会
    • Related Report
      2022 Annual Research Report
  • [Presentation] Kernal Regression Estimator for Damage States of Tunnel Lining Concrete2019

    • Author(s)
      Osamu Maruyama
    • Organizer
      The 13th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP13)
    • Related Report
      2019 Research-status Report
    • Int'l Joint Research
  • [Presentation] Kernel Regression Estimator for Damage States of Tunnel Lining Concrete2019

    • Author(s)
      OSAMU MARUYAMA
    • Organizer
      13th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP13)
    • Related Report
      2018 Research-status Report
    • Int'l Joint Research

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Published: 2018-04-23   Modified: 2024-01-30  

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