炭素排出とクリープ挙動を考慮した低炭素コンクリート配合の多目的最適化

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:物理事前分布と機械学習のハイブリッドによる材料特性予測と多目的最適化の統合手法が参考になる。

🏢実務担当者:低炭素配合の候補設計と炭素・耐久性トレードオフの定量化に活用できるが、実施工前の実験検証が前提。

This study proposes a physical-prior and residual-learning method for creep prediction of low-carbon concrete and integrates it into a multi-objective optimization framework for mix proportion design. After cleaning and normalizing 1066 creep test records, the B4 model served as the physical prior backbone, and a sparse variational Gaussian process (SVGP) was used to fit the residuals between measured and theoretical values. Global linear calibration, a Matérn-5/2 kernel with automatic relevance determination, and length-scale regularization were used to suppress kernel collapse and overfitting. The B4+SVGP model was compared with random forest, extreme gradient boosting, and a backpropagation neural network under a unified dataset, feature set, and training protocol, and Shapley additive explanations (SHAP) were used to analyze mixture effects on creep compliance. The B4+SVGP model that performed best under record-level validation was then embedded in NSGA-II to optimize net carbon emissions and 1000-day creep compliance simultaneously; TOPSIS was used to derive mix proportions under carbon-emission-oriented, balanced, and creep-oriented weight preferences. Under a unified record-level 10-fold cross-validation protocol, B4+SVGP achieved favorable prediction accuracy (R2 = 0.9660) and retained a relative advantage in the target mix proportion region. Loading duration, age at loading, and 28-day compressive strength were the most influential factors, consistent with the physical mechanisms of the B4 model. Under strength and mix-feasibility constraints, the Pareto front exhibited an L shape with an inflection at approximately 205 kg/m3 net carbon emissions. The balanced (5:5) scenario yielded a candidate with a water-to-binder ratio of 0.4227, a binder content of 300.03 kg/m3, and fly ash/slag/silica fume replacements of 6.76%/6.70%/14.82%; it reduced net carbon emissions by approximately 18.7% while increasing creep compliance by only approximately 2.1%. The resulting mixtures are computational candidates whose fresh-state properties, compressive strength, and long-term creep behavior require experimental verification before engineering recommendation.

• openalex https://doi.org/10.3390/ma19214570first seen 2026-10-31 04:57:11 · last seen 2026-11-06 04:49:03