运用SPSS软件对试验数据回归建模开发高强高导热压铸铝合金材料
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摘要
为同时满足铝合金材料的多项特定性能,如压铸抗拉强度≥270 MPa、屈服强度≥160 MPa、伸长率≥1.8%、硬度≥78 HBW及材料导热系数≥172 W/mk,制定出所研发的高强高导热压铸铝合金材料的主要成分和变质方案.以23组试验数据为基础,运用SPSS软件对压铸抗拉强度、屈服强度、伸长率、硬度和材料导热系数5个性能指标进行线性回归分析,建立数学模型,并通过对5个模型的组合及其运算,进行工况条件下的模型预测,再通过试验验证主要成分和变质方案对实现高强高导热性能的效果.根据建立的数学模型,当w(Si)=12.83%,w(Cu)=0.55%,w(Mg)=0.265%,w(1号纳米材料)=2%,w(二元变质剂)=0.030%时,铝合金材料的性能为压铸抗拉强度287.81 MPa、屈服强度166.24 MPa、伸长率2.34%、硬度79.60HBW和材料导热系数174.458 W/mk.SPSS软件的回归建模和模型组合,对于特定性能铝合金新材料的开发,在数学模拟上可以起到方案设计的辅助作用.
The purpose of this work is to simultaneously satisfy with the specific properties of aluminium alloy materials, such as die casting tensile strength(≥270 MPa), yield strength(≥160 MPa), elongation(≥1.8%), hardness(≥78 HBW) and thermal conductivity of materials(≥172 W/mk). The main components and modification schemes of high strength and high thermal conductivity die casting aluminium alloy materials to be developed are formulated. Based on 23 sets of test data, the linear regression analysis of five performance indices of die casting, including tensile strength, yield strength, elongation, hardness and thermal conductivity of materials was carried out by using SPSS software. The mathematical model was established, and the model under working conditions was predicted by combining and calculating the five models. The effects of main components and modification schemes on high strength and high thermal conductivity are verified by experiments. According to the scheme established by the mathematical model, when w(Si)=12.83%, w(Cu)=0.55%, w(Mg)=0.265%, w(No. 1 nanomaterial)=2% and w(binary modifier)=0.030%, the properties of aluminium alloy materials are: die casting tensile strength 287.81 MPa, yield strength 166.24 MPa, elongation 2.34%, hardness 79.60 HBW and thermal conductivity of materials 174.458 W/mk. The regression modeling and model combination of SPSS software can play an assistant role in the mathematical simulation for the development of new aluminium alloy materials with specific properties.
The purpose of this work is to simultaneously satisfy with the specific properties of aluminium alloy materials, such as die casting tensile strength(≥270 MPa), yield strength(≥160 MPa), elongation(≥1.8%), hardness(≥78 HBW) and thermal conductivity of materials(≥172 W/mk). The main components and modification schemes of high strength and high thermal conductivity die casting aluminium alloy materials to be developed are formulated. Based on 23 sets of test data, the linear regression analysis of five performance indices of die casting, including tensile strength, yield strength, elongation, hardness and thermal conductivity of materials was carried out by using SPSS software. The mathematical model was established, and the model under working conditions was predicted by combining and calculating the five models. The effects of main components and modification schemes on high strength and high thermal conductivity are verified by experiments. According to the scheme established by the mathematical model, when w(Si)=12.83%, w(Cu)=0.55%, w(Mg)=0.265%, w(No. 1 nanomaterial)=2% and w(binary modifier)=0.030%, the properties of aluminium alloy materials are: die casting tensile strength 287.81 MPa, yield strength 166.24 MPa, elongation 2.34%, hardness 79.60 HBW and thermal conductivity of materials 174.458 W/mk. The regression modeling and model combination of SPSS software can play an assistant role in the mathematical simulation for the development of new aluminium alloy materials with specific properties.
引文
[1] 周静.SPSS在数学建模中的应用实例[J].天津职业院校联合学报,2012,14(11):93-96.
[2]常盛,朱亚玲.基于spss的多元线性回归算法建模的实例研究[J].数字技术与应用,2011(10):120.
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[2]常盛,朱亚玲.基于spss的多元线性回归算法建模的实例研究[J].数字技术与应用,2011(10):120.
[3]张文霖.主成分分析在SPSS中的操作应用[J].市场研究,2005(12):31-34.