For costly and/or destructive tests,the sequential method with a proper maximum sample size is needed.Based on Koopman-Darmois distributions,this paper proposes the method of sequential mesh,which has an acceptable ma...For costly and/or destructive tests,the sequential method with a proper maximum sample size is needed.Based on Koopman-Darmois distributions,this paper proposes the method of sequential mesh,which has an acceptable maximum sample size.In comparison with the popular truncated sequential probability ratio test,our method has the advantage of a smaller maximum sample size and is especially applicable for costly and/or destructive tests.展开更多
The soil-rock mixture(SRM) is highly heterogeneous. Before carrying out numerical analysis,a structure model should be generated. A reliable way to obtain such structure is by generating random aggregate structure bas...The soil-rock mixture(SRM) is highly heterogeneous. Before carrying out numerical analysis,a structure model should be generated. A reliable way to obtain such structure is by generating random aggregate structure based on random sequential addition(RSA). The classical RSA is neither efficient nor robust since valid positions to place new inclusions are formulated by trial, which involves repetitive overlapping tests. In this paper, the algorithm of Entrance block between block A and B(EAB)is synergized with background mesh to redesign RSA so that permissible positions to place new inclusions can be predicted,resulting in dramatic improvement in efficiency and robustness.展开更多
文摘For costly and/or destructive tests,the sequential method with a proper maximum sample size is needed.Based on Koopman-Darmois distributions,this paper proposes the method of sequential mesh,which has an acceptable maximum sample size.In comparison with the popular truncated sequential probability ratio test,our method has the advantage of a smaller maximum sample size and is especially applicable for costly and/or destructive tests.
基金supported by the National Basic Research Program of China(973 Program)(Grant No.2014CB047100)the National Natural Science Foundation of China(Grant Nos.11572009,51538001 and 51609240)
文摘The soil-rock mixture(SRM) is highly heterogeneous. Before carrying out numerical analysis,a structure model should be generated. A reliable way to obtain such structure is by generating random aggregate structure based on random sequential addition(RSA). The classical RSA is neither efficient nor robust since valid positions to place new inclusions are formulated by trial, which involves repetitive overlapping tests. In this paper, the algorithm of Entrance block between block A and B(EAB)is synergized with background mesh to redesign RSA so that permissible positions to place new inclusions can be predicted,resulting in dramatic improvement in efficiency and robustness.
