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Development of urban wind estimation method based on sparse sensor network

Research Project

Project/Area Number 20H02308
Research Category

Grant-in-Aid for Scientific Research (B)

Allocation TypeSingle-year Grants
Section一般
Review Section Basic Section 23020:Architectural environment and building equipment-related
Research InstitutionThe University of Tokyo

Principal Investigator

Kikumoto Hideki  東京大学, 生産技術研究所, 准教授 (80708082)

Co-Investigator(Kenkyū-buntansha) 大岡 龍三  東京大学, 生産技術研究所, 教授 (90251470)
崔 元準  東京大学, 生産技術研究所, 助教 (30817458)
Project Period (FY) 2020-04-01 – 2023-03-31
Project Status Completed (Fiscal Year 2023)
Budget Amount *help
¥17,680,000 (Direct Cost: ¥13,600,000、Indirect Cost: ¥4,080,000)
Fiscal Year 2022: ¥5,460,000 (Direct Cost: ¥4,200,000、Indirect Cost: ¥1,260,000)
Fiscal Year 2021: ¥5,980,000 (Direct Cost: ¥4,600,000、Indirect Cost: ¥1,380,000)
Fiscal Year 2020: ¥6,240,000 (Direct Cost: ¥4,800,000、Indirect Cost: ¥1,440,000)
Keywords建築環境・設備 / 都市防災 / 風工学 / 流体工学 / シミュレーション工学 / スパースセンシング / 機械学習 / データ駆動型手法
Outline of Research at the Start

本研究では、市街地(マイクロ)および都市(メソ)スケールにおける風況(風速・風向)に関して、スパース(疎)に配置されたセンサーによる計測データを入力値とした空間解像度およびリアルタイム性の高い推定システムの開発を行う。そのため、風況に関する計測および数値予測技術、ならびにそれらを束ねる観測理論・統計分析技術を統合的に開発・活用していく。そして、IoTなどによるセンサー情報の充実による可能性とともに計測システムとしてのその限界を見据えた技術開発を行い、安全・快適かつスマートな都市空間の創出に資する都市風況データ基盤を構築する。

Outline of Final Research Achievements

This study developed a high spatial resolution and real-time distribution estimation method for wind conditions (wind speed and direction) in urban and city scales, using measurement data from sparsely placed sensors as input values. The results of this study are expected to contribute to the creation of a safe and comfortable urban environment by enabling the accurate capture of changes in wind speed and direction through the combination of machine learning models and sensor data.

Academic Significance and Societal Importance of the Research Achievements

本研究では、安全で快適なスマートな都市空間を創造することを目指し、市街地や都市における風況をリアルタイムで把握する新しい技術を開発した。限られた数のセンサーから得られる情報を利用して都市の風速と風向の分布を高精度に推定する手法や、風速センサーのデータ駆動型校正に基づく精度向上手法、センサー配置の最適化手法などを開発した。これら技術は、風による影響を受けやすい市街地での災害リスク管理や建物運用の効率向上に寄与する。

Report

(4 results)
  • 2023 Final Research Report ( PDF )
  • 2022 Annual Research Report
  • 2021 Annual Research Report
  • 2020 Annual Research Report
  • Research Products

    (32 results)

All 2024 2023 2022 2021 2020 Other

All Int'l Joint Research (1 results) Journal Article (11 results) (of which Int'l Joint Research: 2 results,  Peer Reviewed: 10 results,  Open Access: 2 results) Presentation (20 results) (of which Int'l Joint Research: 3 results)

  • [Int'l Joint Research] 香港科技大学(中国)

    • Related Report
      2022 Annual Research Report
  • [Journal Article] Fast estimation of airflow distribution in an urban model using generative adversarial networks with limited sensing data☆2024

    • Author(s)
      Hu Chaoyi、Kikumoto Hideki、Zhang Bingchao、Jia Hongyuan
    • Journal Title

      Building and Environment

      Volume: 249 Pages: 111120-111120

    • DOI

      10.1016/j.buildenv.2023.111120

    • Related Report
      2022 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Transfer learning strategy for data-driven correction of wind measurement around buildings using cup anemometers2023

    • Author(s)
      Li Rongmao、Kikumoto Hideki、Jia Hongyuan、Okaze Tsubasa
    • Journal Title

      Building and Environment

      Volume: 241 Pages: 110499-110499

    • DOI

      10.1016/j.buildenv.2023.110499

    • Related Report
      2022 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Investigation of spatial variability in power law index of wind profiles above the urban area around Tokyo Bay based on local objective analysis data2023

    • Author(s)
      Wang Xiang、Kikumoto Hideki、Jia Hongyuan、Lin Chao、Nakao Keisuke
    • Journal Title

      Journal of Wind Engineering and Industrial Aerodynamics

      Volume: 240 Pages: 105471-105471

    • DOI

      10.1016/j.jweia.2023.105471

    • Related Report
      2022 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] Estimation of instantaneous airflow distribution in cubic building group model using multi-time-delay LSE-POD2023

    • Author(s)
      Hu Chaoyi、Jia Hongyuan、Kikumoto Hideki
    • Journal Title

      Building and Environment

      Volume: 243 Pages: 110642-110642

    • DOI

      10.1016/j.buildenv.2023.110642

    • Related Report
      2022 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Effects of sensor configuration optimization on airflow estimation in urban environment: A case study with a building group model2023

    • Author(s)
      Jia Hongyuan、Hu Chaoyi、Kikumoto Hideki
    • Journal Title

      Sustainable Cities and Society

      Volume: 98 Pages: 104840-104840

    • DOI

      10.1016/j.scs.2023.104840

    • Related Report
      2022 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Sensor configuration optimization for statistical source estimation: method based on the entropy of adjoint equations and its application to building group model2022

    • Author(s)
      賈 鴻源、菊本 英紀
    • Journal Title

      SEISAN KENKYU

      Volume: 74 Issue: 1 Pages: 65-71

    • DOI

      10.11188/seisankenkyu.74.65

    • NAID

      130008163651

    • ISSN
      0037-105X, 1881-2058
    • Year and Date
      2022-02-01
    • Related Report
      2021 Annual Research Report
    • Open Access
  • [Journal Article] Sensor configuration optimization based on the entropy of adjoint concentration distribution for stochastic source term estimation in urban environment2022

    • Author(s)
      Jia Hongyuan、Kikumoto Hideki
    • Journal Title

      Sustainable Cities and Society

      Volume: 79 Pages: 103726-103726

    • DOI

      10.1016/j.scs.2022.103726

    • Related Report
      2022 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Estimation of airflow distribution in cubic building group model using POD-LSE and limited sensors2022

    • Author(s)
      Hu Chaoyi、Jia Hongyuan、Kikumoto Hideki
    • Journal Title

      Building and Environment

      Volume: 221 Pages: 109324-109324

    • DOI

      10.1016/j.buildenv.2022.109324

    • Related Report
      2022 Annual Research Report
    • Peer Reviewed
  • [Journal Article] DATA-DRIVEN CALIBRATION OF ANEMOMETER IN DIFFERENT OBSERVATION PERIODS USING TRANSFER LEARNING BASED ON DOMAIN ADAPTATION2022

    • Author(s)
      李 栄茂、菊本 英紀、賈 鴻源
    • Journal Title

      Wind Engineering Research

      Volume: 27 Issue: 0 Pages: 227-236

    • DOI

      10.14887/windengresearch.27.0_227

    • ISSN
      2435-4384, 2435-5429
    • Related Report
      2022 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Data-driven calibration of cup anemometer based on field measurements and artificial neural network for wind measurement around buildings2022

    • Author(s)
      Li Rongmao、Kikumoto Hideki
    • Journal Title

      Journal of Wind Engineering and Industrial Aerodynamics

      Volume: 231 Pages: 105239-105239

    • DOI

      10.1016/j.jweia.2022.105239

    • Related Report
      2022 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Towards real-time prediction of velocity field around a building using generative adversarial networks based on the surface pressure from sparse sensor networks2022

    • Author(s)
      Zhang Bingchao、Ooka Ryozo、Kikumoto Hideki、Hu Chaoyi、Tse Tim K.T.
    • Journal Title

      Journal of Wind Engineering and Industrial Aerodynamics

      Volume: 231 Pages: 105243-105243

    • DOI

      10.1016/j.jweia.2022.105243

    • Related Report
      2022 Annual Research Report
    • Peer Reviewed / Int'l Joint Research
  • [Presentation] Extension and analysis of high-resolution wind velocity data by fusing meteorological observations and local objective analysis data in the Tokyo Bay area using POD-LSE2024

    • Author(s)
      Xiang Wang, Hideki Kikumoto, Chaoyi Hu, Hongyuan Jia, Keisuke Nakao, Ryozo Ooka
    • Organizer
      第39回生研TSFDシンポジウム
    • Related Report
      2022 Annual Research Report
  • [Presentation] センサーネットワークを用いた市街地気流の分布推定に関する研究 (その5)QR分解に基づくセンサー配置最適化による推定精度の改善2023

    • Author(s)
      賈鴻源, 菊本英紀, 胡超億
    • Organizer
      日本建築学会大会(近畿)
    • Related Report
      2022 Annual Research Report
  • [Presentation] センサーネットワークを用いた市街地気流の分布推定に関する研究 (その6)CWGANによる市街地モデル内の気流分布の推定2023

    • Author(s)
      胡超億, 菊本英紀, 賈鴻源, 張秉超
    • Organizer
      日本建築学会大会(近畿)
    • Related Report
      2022 Annual Research Report
  • [Presentation] 機械学習による建物周辺気流計測の高精度化に関する研究 (その3)経験的モード分解に基づく前処理を用いた複数の風速計校正2023

    • Author(s)
      李栄茂, 菊本英紀, 賈鴻源
    • Organizer
      日本建築学会大会(近畿)
    • Related Report
      2022 Annual Research Report
  • [Presentation] Study on utilization of local objective analysis data for microclimate prediction (Part 2) Reproduction of long-term high-resolution data in urban areas by POD-LSE method2023

    • Author(s)
      Xiang Wang, Hideki Kikumoto, Chaoyi Hu, Hongyuan Jia, Keisuke Nakao
    • Organizer
      日本建築学会大会(近畿)
    • Related Report
      2022 Annual Research Report
  • [Presentation] Fast estimation of airflow distribution in the urban model using generative adversarial network and limited sensors2023

    • Author(s)
      Chaoyi Hu, Hideki Kikumoto, Bingchao Zhang, Hongyuan Jia
    • Organizer
      IAQVEC 2023
    • Related Report
      2022 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Data-driven calibration for cup anemometer at different measurement locations around buildings using transfer learning based on domain adaptation2023

    • Author(s)
      Rongmao Li, Hideki Kikumoto, Hongyuan Jia
    • Organizer
      IAQVEC 2023
    • Related Report
      2022 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Estimation of near-ground wind velocity and temperature in the urban area around Tokyo Bay using local objective analysis data and the POD-LSE method2023

    • Author(s)
      Xiang Wang, Hideki Kikumoto, Chaoyi Hu, Hongyuan Jia, Keisuke Nakao
    • Organizer
      16th International Conference on Wind Engineering
    • Related Report
      2022 Annual Research Report
    • Int'l Joint Research
  • [Presentation] 機械学習による建物周辺気流計測の高精度化に関する研究 (その2)ドメイン適応に基づく転移学習による異なる場所でのデータ駆動型風速計校正2022

    • Author(s)
      李栄茂, 菊本英紀, 大風翼
    • Organizer
      日本建築学会大会(北海道)
    • Related Report
      2022 Annual Research Report
  • [Presentation] センサーネットワークを用いた市街地気流の分布推定に関する研究 (その4) 人工ニューラルネットワークによる市街地モデル内の気流分布の推定2022

    • Author(s)
      胡超億, 菊本英紀, 賈鴻源
    • Organizer
      日本建築学会大会(北海道)
    • Related Report
      2022 Annual Research Report
  • [Presentation] Study on utilization of local objective analysis data for microclimate prediction (Part 1) Comparison of local objective analysis and near-surface meteorological observation data2022

    • Author(s)
      Xiang Wang, Hideki Kikumoto
    • Organizer
      日本建築学会大会(北海道)
    • Related Report
      2022 Annual Research Report
  • [Presentation] Generative Adversarial Network による市街地モデル内の瞬時気流分布推定2022

    • Author(s)
      胡超億, 菊本英紀, 張秉超, 賈鴻源
    • Organizer
      風工学シンポジウム
    • Related Report
      2022 Annual Research Report
  • [Presentation] 確率的発生源同定における随伴濃度分布のエントロピーに基づくセンサー配置の最適化2022

    • Author(s)
      賈鴻源, 菊本英紀
    • Organizer
      第37回生研TSFDシンポジウム
    • Related Report
      2021 Annual Research Report
  • [Presentation] センサーネットワークを用いた市街地気流の分布推定に関する研究 (その3) 複数時点を考慮したLSE-PODの立方体建物群モデル内気流への応用2021

    • Author(s)
      胡超億, 菊本英紀, 賈鴻源
    • Organizer
      日本建築学会大会
    • Related Report
      2021 Annual Research Report
  • [Presentation] 確率的発生源同定におけるセンサー配置最適化手法に関する研究 (その1)随伴濃度分布のエントロピーに基づく最適化アルゴリズム2021

    • Author(s)
      賈鴻源, 菊本英紀
    • Organizer
      日本建築学会大会
    • Related Report
      2021 Annual Research Report
  • [Presentation] 機械学習による建物周辺気流計測の高精度化に関する研究 (第1報)ANNを用いた風杯型風速計による瞬間風速計測の校正2021

    • Author(s)
      李栄茂, 菊本英紀
    • Organizer
      空気調和・衛生工学会大会
    • Related Report
      2021 Annual Research Report
  • [Presentation] POD-LSEによる市街地瞬時気流分布推定に関する研究:立方体建物群モデル内の乱流への適用2021

    • Author(s)
      胡 超億, 菊本 英紀, 賈 鴻源
    • Organizer
      第36回生研TSFDシンポジウム
    • Related Report
      2020 Annual Research Report
  • [Presentation] センサーネットワークを用いた市街地気流の分布推定に関する研究 (その1)POD-LSEを用いた推定手法の概要と1次元拡散問題への適用2020

    • Author(s)
      菊本 英紀, 胡 超億, 賈 鴻源
    • Organizer
      日本建築学会大会
    • Related Report
      2020 Annual Research Report
  • [Presentation] センサーネットワークを用いた市街地気流の分布推定に関する研究 (その2)POD-LSEを用いた立方体建物群モデル内の気流推定2020

    • Author(s)
      胡 超億, 菊本 英紀, 賈 鴻源
    • Organizer
      日本建築学会大会
    • Related Report
      2020 Annual Research Report
  • [Presentation] POD-LSEを用いた立方体建物群モデル内の瞬時気流分布推定に関する研究2020

    • Author(s)
      胡 超億, 菊本 英紀, 賈 鴻源
    • Organizer
      風工学シンポジウム
    • Related Report
      2020 Annual Research Report

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Published: 2020-04-28   Modified: 2025-01-30  

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