IFCを活用した建物全体の意味的最適化とクエリ駆動型意思決定支援ワークフロー：低炭素・循環型スマート建設に向けて
Industry Foundation Classes (IFC)‑enabled whole‑building semantic optimisation and query‑driven decision‑support workflow for low‑carbon and circular smart construction (原題)
Yiping Meng, Yiming Sun, Haoyu Huang, Cong Zhang
🤖 gxceed AI 要約
日本語
IFCデータを読み込み、建物全体の資材シナリオを列挙し、パレート支配で絞り込み、意味的クエリに応答する決定論的ワークフローを実装。150の壁・床・屋根構成を評価し、12の非支配解（低炭素志向6・循環志向6）を同定した。BCS重み付けや閾値変更でも分類は安定し、モンテカルロ検証でも頑健性を確認。約0.79秒で完結する試作段階の意思決定支援ツール。
English
A deterministic workflow reads IFC data, enumerates whole-building material scenarios, filters by Pareto dominance, and answers semantic queries. Evaluating 150 wall-floor-roof configurations yielded 12 non-dominated solutions (6 low-carbon, 6 circularity-oriented), stable across BCS weightings and thresholds and robust in Monte Carlo checks. The prototype runs in ~0.79s, offering candidate scenarios for early-stage low-carbon and circular design decisions.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
建設業のScope 3上流（資材）排出と循環性評価は、SSBJ・有報でのサプライチェーン開示要求が強まる中で日本企業にも直接関係する。IFCベースの自動評価は、設計初期段階での低炭素資材選定と循環性指標の統合に道を開く。
In the global GX context
As ISSB and CSRD push embodied carbon and circularity into disclosure, IFC-based automated ranking offers a reproducible way to link BIM data to environmental metrics. This supports the growing demand for verifiable, data-driven embodied-carbon accounting in construction value chains.
👥 読者別の含意
🔬研究者:IFCデータから資材シナリオを自動評価する決定論的枠組みと、パレート支配・意味的クエリを組み合わせた手法の実装例。
🏢実務担当者:設計初期に低炭素・循環性のトレードオフを定量化し、資材選定の根拠をBIMデータから自動生成するヒント。
🏛政策担当者:建設分野の embodied carbon 規制や循環性評価基準を検討する際、IFCベースの自動評価が監査可能性向上に寄与しうる。
📄 Abstract（原文）
Material choices fixed early in design determine much of a building’s embodied carbon and how much of its material can later be recovered, but the data needed to weigh the two are usually held in separate tools. To bring them together, a deterministic process was implemented that reads Industry Foundation Classes (IFC) data, enumerates whole-building material scenarios, filters them for Pareto dominance, answers controlled semantic queries, and packages the results as prompt text for optional downstream interpretation. One buildingSMART reference IFC model yielded seven valid components, and 150 wall-floor-roof material configurations were evaluated on that basis. Twelve configurations were non-dominated: six low-carbon-oriented configurations, in which timber systems predominate, and six circularity-oriented configurations built on aluminium-roof systems. The same candidates were returned under all five Building Circularity Score (BCS) weighting schemes (12/12 overlap with the equal-weight baseline), and the classification of 0 balanced, 6 low-carbon-oriented, and 6 circularity-oriented scenarios held across nine threshold combinations. In a scenario-based Monte Carlo check, every one of the 12 baseline candidates stayed non-dominated in at least 83.2% of 1000 sampled runs under the stated assumptions. The full 150-configuration case took approximately 0.79 s, of which pairwise Pareto filtering accounted for approximately 0.023 s. Within this single test case, IFC-derived quantities were sufficient for a reproducible environmental ranking, and the outputs are candidate scenarios for prototype-stage decision support, not complete design prescriptions. External validation, additional IFC models, engineering feasibility checks, and deployment beyond the prototype are left to future work.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.55092/sc20260019first seen 2026-10-03 04:55:31
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