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BIM技术开创混凝土算量工作新模式 被引量:5
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作者 杨震卿 潘朝辉 +2 位作者 田丰 张晓玲 赵巍 《建筑技术》 北大核心 2015年第2期129-131,共3页
混凝土算量是施工现场一项至关重要的工作,其精准度直接影响到现场浇筑混凝土的工作效率和成本控制。传统混凝土算量工作繁琐且无法保证计算精度。通过利用BIM技术辅助进行混凝土算量工作,有效提取BIM模型中的工程量信息,为混凝土算量... 混凝土算量是施工现场一项至关重要的工作,其精准度直接影响到现场浇筑混凝土的工作效率和成本控制。传统混凝土算量工作繁琐且无法保证计算精度。通过利用BIM技术辅助进行混凝土算量工作,有效提取BIM模型中的工程量信息,为混凝土算量提供了新的工作模式,一定程度上控制了人力和资源的浪费。 展开更多
关键词 建筑信息模型 混凝土算量 成本控制
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Calculation Model of Equivalent Strength for Induced Crack Based on Double-K Fracture Theory and Its Optimizing Setting in RCC Arch Dam 被引量:8
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作者 张小刚 宋玉普 吴智敏 《Transactions of Tianjin University》 EI CAS 2005年第1期59-65,共7页
By means of fracture testing on roller-compacted concrete (RCC) three-point bending beams with two different specimen sizes, the P-CMOD complete curve for RCC was gained. Furthermore, by applying double-K fracture t... By means of fracture testing on roller-compacted concrete (RCC) three-point bending beams with two different specimen sizes, the P-CMOD complete curve for RCC was gained. Furthermore, by applying double-K fracture theory, KiniⅠC,KunⅠC, as well as the critical effective crack length and the critical crack tip opening displacement, were evaluated. Based on the double-K fracture parameters above, the calculation model of equivalent strength for induced crack was established, thus the calculation method on its initiation, stable propagation and unstable fracture was ascertained. Moreover, the finite element simulation analysis of stress field in ShaPai arch dam and the on-site observational splaying points of induced crack at different altitudes validated the reliability of the model. Finally, crack inducer′s optimal setting in RCC arch dam was studied. It improves the design level of induced crack in RCC arch dam and satisfies the necessity of engineering practice. 展开更多
关键词 roller-compacted concrete (RCC) arch dam induced crack double-K fracture parameters equivalent strength calculation model optimizing setting
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Computer-aided design of the effects of Cr_2O_3 nanoparticles on split tensile strength and water permeability of high strength concrete 被引量:7
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作者 Ali NAZARI Shadi RIAHI 《Science China(Technological Sciences)》 SCIE EI CAS 2011年第3期663-675,共13页
In the present paper, two models based on artificial neural networks and genetic programming for predicting split tensile strength and percentage of water absorption of concretes containing Cr2O3 nanoparticles have be... In the present paper, two models based on artificial neural networks and genetic programming for predicting split tensile strength and percentage of water absorption of concretes containing Cr2O3 nanoparticles have been developed at different ages of curing. For purpose of building these models, training and testing using experimental results for 144 specimens produced with 16 different mixture proportions were conducted. The data used in the multilayer feed forward neural networks models and input variables of genetic programming models are arranged in a format of 8 input parameters that cover the cement content, nanoparticle content, aggregate type, water content, the amount of superplasticizer, the type of curing medium, age of curing and number of testing try. According to these input parameters, in the neural networks and genetic programming models the split tensile strength and percentage of water absorption values of concretes containing Cr2O3 nanoparticles were predicted. The training and testing results in the neural network and genetic programming models have shown that every two models have strong potential for predicting the split tensile strength and percentage of water absorption values of concretes containing Cr2O3 nanoparticles. It has been found that NN and GEP models will be valid within the ranges of variables. In neural networks model, as the training and testing ended when minimum error norm of network was gained, the best results were obtained and in genetic programming model, when 4 genes were selected to construct the model, the best results were acquired. Although neural network has predicted better results, genetic programming is able to predict reasonable values with a simpler method rather than neural network. 展开更多
关键词 concrete curing medium Cr2O3 nanoparticles artificial neural network genetic programming split tensile strength percentage of water absorption
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