デジタルツインによる“生きた”建築モデル研究((Digital) Twin Studies)

2026-05-21 ピッツバーグ大学

米国のUniversity of Pittsburghの研究チームは、工学・医療分野における「デジタルツイン」研究を推進し、現実世界のシステムや人体状態を仮想空間上で高精度に再現・解析する取り組みを進めている。デジタルツインは、センサーやシミュレーション、AI解析を組み合わせ、物理対象の状態変化をリアルタイムに反映する技術であり、設備保守、製造最適化、医療診断、個別化治療など幅広い応用が期待される。Pittsburgh大学では、人体組織や疾患進行を模擬する医療デジタルツインや、工学システムの予測制御研究などが進められており、複雑システムの理解と最適化に貢献している。研究者らは、AIと高性能計算の進展により、将来的には患者ごとの精密医療や高度な自律制御システム実現につながると説明している。

<関連情報>

持続可能な建築のためのデジタルツイン:フレームワークから戦略ガイドライン、そして応用まで Digital twins for sustainable buildings: From framework to strategy guidelines and application

F. Geremicca, A. Fascetti, J.C. Brigham, M.M. Bilec

Energy And Buildings  Available online :18 March 2026

DOI:https://doi.org/10.1016/j.enbuild.2026.117332

Graphical abstract

デジタルツインによる“生きた”建築モデル研究((Digital) Twin Studies)

Highlights

  • Developed new DT Strategy Schedule & Document to provide pragmatic development guidance.
  • Developed a unified DT architecture to integrate sustainability assessments.
  • Demonstrated through a case study of a university building.
  • Created an immersive 3D visualization to enable actionable decision support.

Abstract

This paper investigates the application of Digital Twin (DT) technology to support sustainability assessments in the built environment. While DTs are increasingly adopted in building contexts, three key fundamental challenges persist: (1) lack of pragmatic guidance for DT development, (2) limited integration of multiple sustainability assessments, and (3) insufficient support for decision-making through contextualized visualization. To address the scientific gaps, this study introduced the Digital Twin Strategy Schedule and Digital Twin Strategy Document, which provide guidance for defining DT objectives, analytical scope, and data requirements. These instruments were derived by interpreting and adapting general DT strategy guidelines to the specific needs of sustainability-oriented DTs for buildings and are iteratively refined through application to a real-world case study. The proposed framework integrated energy modeling, Material Flow Analysis, and Life Cycle Assessment within a unified architecture. An automated workflow was developed to link Building Information Modeling, the analytical models, and Building Automation System data, enabling consistent data exchange, validation, and traceability. The proposed approach was demonstrated through a case study of a university building equipped with smart sensors. Sustainability indicators and operational performance metrics were visualized within an immersive, interactive 3D environment, supporting anomaly detection and alert-based communication. Results highlighted the potential of DTs to enhance sustainability-informed decision-making and challenges associated with data completeness, semantic alignment, and geometric interoperability. Overall, this work formalizes and demonstrates a DT architecture to connect sustainability analytics with spatially contextualized visualization, moving beyond static dashboards toward actionable decision support for building operation and maintenance.

1603情報システム・データ工学
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