竹およびココナッツ殻バイオ炭の低炭素セメント代替材としての性能評価：実験と機械学習アプローチ
Performance evaluation of bamboo and coconut shell biochar as low-carbon cement replacements: experimental and machine learning approaches (原題)
Pallavi H J, Shiva Kumar G, R. Shanthi Vengadeshwari, ujwal m s, Arun Kumar Y M, Poornachandra Pandit, R. Mahesh
🤖 gxceed AI 要約
日本語
本研究は、竹およびココナッツ殻バイオ炭をセメント代替材として2%、4%、6%添加したコンクリートの性能を実験的に評価し、4%添加が強度・耐久性・施工性のバランスに優れることを示した。さらに、360サンプルのデータセットを用いて機械学習モデルで圧縮強度を予測し、ランダムフォレストが最高精度（R2=0.98）を達成した。低炭素建材としての可能性を示す一方、LCAによる環境便益の定量化が今後の課題とされた。
English
This study experimentally evaluated concrete with bamboo and coconut shell biochar as cement replacements at 2%, 4%, and 6%, finding 4% optimal for strength, durability, and workability. Machine learning models predicted compressive strength from 360 samples, with Random Forest achieving highest accuracy (R2=0.98). Highlights biochar concrete as sustainable material, but calls for LCA to quantify environmental benefits.
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
日本の建設業界では、カーボンニュートラル達成に向けてセメント産業のCO2削減が急務であり、バイオ炭の活用は低炭素コンクリートとして注目される。SSBJ開示やグリーン調達に対応するため、建材の環境性能データの蓄積が求められており、本研究成果はその基盤となり得る。
In the global GX context
Globally, the cement industry faces pressure to decarbonize under frameworks like TCFD and ISSB. Biochar as a cement replacement offers a circular economy solution, and this study provides empirical data on performance and ML-based prediction, supporting sustainable construction practices and disclosure of environmental metrics.
👥 読者別の含意
🔬研究者:Provides experimental data and ML models for predicting compressive strength of biochar concrete, useful for further research on sustainable materials.
🏢実務担当者:Offers guidance on optimal biochar replacement levels (4%) for concrete mix design, aiding in low-carbon product development and sustainability reporting.
🏛政策担当者:Supports policy on low-carbon construction materials by providing evidence of biochar's viability, potentially informing building codes and green procurement standards.
📄 Abstract（原文）
The growing demand for sustainable construction materials has accelerated the use of biochar as a partial cement replacement to enhance concrete performance while reducing environmental impacts. This study experimentally evaluated the influence of bamboo biochar (BB) and coconut shell biochar (CC) at replacement levels of 2%, 4%, and 6% on the fresh, mechanical, durability, and microstructural properties of concrete. Workability, compressive strength, split tensile strength, flexural strength, rapid chloride permeability (RCPT), sorptivity, and microstructural characteristics were investigated using SEM and EDS analyses. A machine learning dataset comprising 360 samples, compiled from experimental results and published literature, was used to develop Decision Tree, Random Forest, and XGBoost models for compressive strength prediction. The results demonstrated that 4% biochar provided the most favorable overall balance between compressive strength, durability, workability, and microstructural performance. Among the evaluated machine learning algorithms, Random Forest achieved the highest predictive accuracy for the bamboo biochar dataset (R2 = 0.98), whereas the coconut shell biochar dataset attained a maximum R2 = 0.91. These findings demonstrate the potential of biochar-modified concrete as a sustainable construction material while highlighting the need for larger datasets, comprehensive biochar characterization, and life-cycle assessment to improve model generalizability and quantify long-term environmental benefits.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1080/13467581.2026.2715926first seen 2026-08-20 04:42:34
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