熱橋分析のためのAIベースのアプローチ
Marta Pomada1, Krzysztof Cpałka1, Piotr Lacki1
1Czestochowa University of Technology, 69 Dabrowskiego St., Czestochowa, 42-201, Poland.
Scientific reports
|August 25, 2025
まとめ
この研究では,建物内の熱ブリッジを分析するためにフージーシステム (FS) を使用した人工知能 (AI) のアプローチを紹介しています. AIモデルは熱損失係数を正確に推定し,複雑な伝統的な分析の必要性を軽減します.
科学分野:
- 建築科学
- 人工知能
- エネルギー効率
背景:
- 建物は世界のエネルギー消費とCO2排出に大きく貢献しています
- 建物のエネルギー効率化に取り組むことは 気候変動の緩和に不可欠です
- 窓から壁への接続のように 建物内の熱ブリッジは 熱の損失の重要な経路を表しています
研究 の 目的:
- 窓から壁への接続における熱ブリッジを分析するための人工知能 (AI) ベースの方法を提案し評価する.
- 線形熱伝導系数 (Ψ) を推定するための普遍的な近似値としてフージーシステム (FS) を利用する.
- 新しいケースの Ψ 値を一般化し予測する AI アプローチの能力を実証する.
主な方法:
- TRISCOプログラムを使用して従来の熱橋分析から得られたデータで訓練されたフージーシステム (FS) の開発.
- 線形熱伝達係数 (Ψ) を推定するために訓練されたFSを適用する.
- FSモデルの性能と未確認データに対する一般化能力の検証.
主要な成果:
- AI駆動のフージーシステムは,線形熱伝達係数を推定する上で優れた性能を達成しました.
- 訓練されたFSは,最初のトレーニングデータセットに含まれていない窓から壁への接続のPz値を正確に予測しました.
- AIアプローチは他のAIモデルと比較して優れた解釈性を示しました.
結論:
- 提案されたAIアプローチは,建物における熱橋分析の効率的で正確な方法を提供します.
- このAI技術により 時間がかかる従来の計算や実験への依存を 大幅に減らすことができます
- このAIのアプローチを実装することで 設計者がエネルギー効率に最適な 建物のソリューションを選択するプロセスを 簡素化できます
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