| 引用本文: | 姜春萌,宫经伟,唐新军,蒋林华,郑祖国.基于PPR的低热水泥胶凝体系综合性能优化方法[J].建筑材料学报,2019,22(3):333-340 |
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| 基于PPR的低热水泥胶凝体系综合性能优化方法 |
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姜春萌1, 宫经伟1, 唐新军1, 蒋林华2, 郑祖国3
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1.新疆农业大学水利与土木工程学院，新疆乌鲁木齐830052;2.河海大学力学与材料学院，江苏南京211100;3.浙江水利水电学院水利与环境工程学院，浙江杭州310018
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| 摘要: |
| 以低热水泥胶凝体系为研究对象，分析矿物掺和料种类及其掺量对该体系抗压强度和水化热的影响.提出建立基于投影寻踪回归(PPR)方法的低热水泥胶凝体系力学、热学综合性能预测模型，确立PPR模型精度判别准则及建模样本选取准则，通过仿真计算绘制综合性能等值线图，将其多目标性能优化问题转化为力学、热学单目标性能优化问题，避免了主观赋权和假定建模，可直接确定力学、热学最优性能指标及胶凝材料组成.所得结果可为低热水泥胶凝体系在大体积混凝土中的应用提供指导，并为混凝土材料的综合性能优化研究提供参考. |
| 关键词: 综合性能优化 投影寻踪回归 精度判别准则 样本选取准则 低热水泥胶凝体系 |
| DOI：103969/j.issn.1007 9629201903002 |
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| 基金项目:国家自然科学基金资助项目(51641906，51869031)；新疆维吾尔自治区研究生科研创新项目(XJGRI2018) |
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| Optimization Method of Comprehensive Properties of Low Heat Cement Cementitious System Based on Projection Pursuit Regression |
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JIANG Chunmeng1, GONG Jingwei1, TANG Xinjun1, JIANG Linhua2, ZHENG Zuguo3
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1.College of Hydraulic and Civil Engineering, Xinjiang Agricultural University, Urumqi 830052, China;2.College of Mechanics and Materials, Hohai University, Nanjing 211100, China;3.College of Water Resources and Environmental Engineering, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China
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| Abstract: |
| Taking low heat cement cementitious system as research object, the effect of types and content of mineral admixture on its compressive strength and hydration heat was studied. A prediction model of mechanical and thermal properties of low heat cement cementitious system based on projection pursuit regression(PPR) was proposed, accuracy discrimination criterion was summarized, and the sample selection criteria of PPR was established. Through simulation calculation and comprehensive performance contour map, comprehensive performance optimization of cementitious material system could be transformed into the optimization of its mechanical and thermal single target properties. The comprehensive performance optimization method based on PPR model could directly determine the mechanical and thermal index and their mix proportion without subjective weighting and assumed modeling, which provides guidance for the application of low heat cement cementitious system in large volume concrete. |
| Key words: comprehensive performance optimization projection pursuit regression(PPR) accuracy discrimination criterion sample selection criterion low heat cement cementitious system |
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