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  • Open Access

    ARTICLE

    Recycled Aggregate Pervious Concrete: Analysis of Influence of Water-Cement Ratio and Fly Ash under Single Action and Optimal Design of Mix Proportion

    Shoukai Chen1,4,5, Chunpeng Xing1, Mengdie Zhao2,*, Junfeng Zhang3, Lunyan Wang1,4,5,*, Qidong He6

    Journal of Renewable Materials, Vol.10, No.3, pp. 799-819, 2022, DOI:10.32604/jrm.2022.017285

    Abstract

    Pervious concrete is recommended, which is of great benefit to the ecological environment and human living environment. In this paper, the influences of five water-cement ratios and four fly ash contents to replace the cement by mass with a water-cement ratio of 0.30 on the properties of Recycled Aggregate Pervious Concrete (RAPC) were studied. Following this, based on the Grey relational-Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) optimization method, the strength, permeability, abrasion loss rate, and material costs of RAPC were adopted as evaluation indices to establish a mix proportion optimization model. The results show that… More >

  • Open Access

    ARTICLE

    Optimal Model of Continuous Knowledge Transfer in the Big Data Environment

    Chuanrong Wu1, *, Evgeniya Zapevalova1, Yingwu Chen2, Deming Zeng3, Francis Liu4

    CMES-Computer Modeling in Engineering & Sciences, Vol.116, No.1, pp. 89-107, 2018, DOI:10.31614/cmes.2018.04041

    Abstract With market competition becoming fiercer, enterprises must update their products by constantly assimilating new big data knowledge and private knowledge to maintain their market shares at different time points in the big data environment. Typically, there is mutual influence between each knowledge transfer if the time interval is not too long. It is necessary to study the problem of continuous knowledge transfer in the big data environment. Based on research on one-time knowledge transfer, a model of continuous knowledge transfer is presented, which can consider the interaction between knowledge transfer and determine the optimal knowledge transfer time at different time… More >

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