以聚丙烯腈为聚合物,磷酸或聚乙二醇-600为添加剂,N-甲基吡咯烷酮为溶剂,采用 L-S 相转换法制备 PAN 超滤膜。利用计算机直接实验设计方法设计制膜的配方,用 Statistic Analytic System(sAS)统计软件对膜的水通量、牛血清蛋白截留率和...以聚丙烯腈为聚合物,磷酸或聚乙二醇-600为添加剂,N-甲基吡咯烷酮为溶剂,采用 L-S 相转换法制备 PAN 超滤膜。利用计算机直接实验设计方法设计制膜的配方,用 Statistic Analytic System(sAS)统计软件对膜的水通量、牛血清蛋白截留率和平均孔径进行回归分析,得出影响 PAN 基底膜性能的主要因素,并且优化了 PAN 基膜制备的工艺条件。实验结果表明,PAN浓度、添加剂种类和添加剂浓度是 PAN 基膜性能的主要影响因素;在一定的浓度范围内,以适当的 PAN 浓度和添加剂浓度均可制备出渗透性能较好的 PAN 超滤膜;SAS 统计软件对 PAN 基膜的截留率和平均孔径的预测值与实验值吻合较好。展开更多
This paper describes the construction and enumeration of mixed orthogonal arrays (MOA) to produce optimal experimental designs. A MOA is a multiset whose rows are the different combinations of factor levels, discrete ...This paper describes the construction and enumeration of mixed orthogonal arrays (MOA) to produce optimal experimental designs. A MOA is a multiset whose rows are the different combinations of factor levels, discrete values of the variable under study, having very well defined features such as symmetry and strength three (all main interactions are taken in consideration). The applied methodology blends the fields of combinatorics and group theory by applying the ideas of orbits, stabilizers and isomorphisms to array generation and enumeration. Integer linear programming was used in order to exploit the symmetry property of the arrays under study. The backtrack search algorithm was used to find suitable arrays in the underlying space of possible solutions. To test the performance of the MOAs, an engineered system was used as a case study within the stage of parameter design. The analysis showed how the MOAs were capable of meeting the fundamental engineering design axioms and principles, creating optimal experimental designs within the desired context.展开更多
文摘以聚丙烯腈为聚合物,磷酸或聚乙二醇-600为添加剂,N-甲基吡咯烷酮为溶剂,采用 L-S 相转换法制备 PAN 超滤膜。利用计算机直接实验设计方法设计制膜的配方,用 Statistic Analytic System(sAS)统计软件对膜的水通量、牛血清蛋白截留率和平均孔径进行回归分析,得出影响 PAN 基底膜性能的主要因素,并且优化了 PAN 基膜制备的工艺条件。实验结果表明,PAN浓度、添加剂种类和添加剂浓度是 PAN 基膜性能的主要影响因素;在一定的浓度范围内,以适当的 PAN 浓度和添加剂浓度均可制备出渗透性能较好的 PAN 超滤膜;SAS 统计软件对 PAN 基膜的截留率和平均孔径的预测值与实验值吻合较好。
文摘This paper describes the construction and enumeration of mixed orthogonal arrays (MOA) to produce optimal experimental designs. A MOA is a multiset whose rows are the different combinations of factor levels, discrete values of the variable under study, having very well defined features such as symmetry and strength three (all main interactions are taken in consideration). The applied methodology blends the fields of combinatorics and group theory by applying the ideas of orbits, stabilizers and isomorphisms to array generation and enumeration. Integer linear programming was used in order to exploit the symmetry property of the arrays under study. The backtrack search algorithm was used to find suitable arrays in the underlying space of possible solutions. To test the performance of the MOAs, an engineered system was used as a case study within the stage of parameter design. The analysis showed how the MOAs were capable of meeting the fundamental engineering design axioms and principles, creating optimal experimental designs within the desired context.
