Lifecycle Assessment of Sustainable Construction Materials in Green Buildings: A Multi-Objective Optimization Model
グリーンビルディングにおける持続可能な建設資材のライフサイクル評価：多目的最適化モデル (AI 翻訳)
Arthur J. Sterling, Marcus P. Thorne, Julian T. Harrow
🤖 gxceed AI 要約
日本語
本研究は、建設資材選定におけるコストと環境影響のトレードオフを解決するため、ライフサイクル評価と多目的最適化を統合したフレームワークを提案。遺伝的アルゴリズムを用いて、中規模商業ビルを対象に、初期コストとライフサイクル環境負荷（体積炭素、運用エネルギー）を同時に最小化するパレート最適解を導出。持続可能な資材は初期費用が高い場合でも、最適化により経済的負担を抑えつつ環境負荷を大幅削減できることを示した。
English
This paper integrates Lifecycle Assessment with a Multi-Objective Optimization model using a genetic algorithm to select sustainable construction materials. Applied to a mid-rise commercial building, it simultaneously minimizes lifecycle cost and environmental impact (embodied carbon and operational energy). The results show that optimization can identify Pareto-optimal solutions achieving significant emission reductions with modest cost premiums, bridging economic constraints and environmental goals.
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
日本では、CASBEEや建築物省エネ法により建物の環境性能評価が進んでいるが、ライフサイクル全体の炭素排出を考慮した資材選定はまだ普及途上。本モデルは、初期費用増加を抑えつつ環境負荷を低減する具体的な手法を提供し、SSBJのスコープ3対応やグリーンビルディング認証取得に有用。
In the global GX context
Global frameworks like the EU Taxonomy and ISSB standards increasingly demand whole-life carbon accounting for buildings. This optimization model provides a practical tool for balancing cost and carbon in material selection, supporting green building certification (LEED, BREEAM) and net-zero pathways in the built environment.
👥 読者別の含意
🔬研究者:Offers a multi-objective optimization framework integrating LCA with genetic algorithms for sustainable material selection.
🏢実務担当者:Provides a decision-support tool for construction firms and architects to select cost-effective low-carbon materials.
🏛政策担当者:Can inform building codes and incentives that promote lifecycle carbon reduction without disproportionate cost burdens.
📄 Abstract（原文）
The construction sector remains one of the largest contributors to global energy consumption and greenhouse gas emissions, precipitating an urgent shift toward sustainable development practices. Green buildings aim to mitigate these environmental impacts through the adoption of eco-friendly materials and energy-efficient designs. However, the selection of sustainable materials often presents a complex decision-making problem characterized by conflicting criteria, primarily the trade-off between initial construction costs and long-term environmental benefits. This paper presents a comprehensive framework that integrates Lifecycle Assessment with a Multi-Objective Optimization model to assist decision-makers in selecting optimal construction materials. By utilizing a non-dominated sorting genetic algorithm, the study simultaneously minimizes lifecycle cost and lifecycle environmental impact, specifically embodied carbon and operational energy. The proposed model is applied to a mid-rise commercial building case study, evaluating a wide range of material alternatives for structural and envelope systems. The results demonstrate that while sustainable materials may incur a higher upfront cost, optimization can identify Pareto-optimal solutions that significantly reduce environmental footprints with marginal economic premiums. This research contributes to the body of knowledge by providing a quantitative tool that bridges the gap between economic constraints and environmental stewardship in the built environment.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.71465/fess605first seen 2026-06-29 07:00:31
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