The optimization of two-scale structures can adapt to the different needs of materials in various regions by reasonably arranging different microstructures at the macro scale,thereby considerably improving structural ...The optimization of two-scale structures can adapt to the different needs of materials in various regions by reasonably arranging different microstructures at the macro scale,thereby considerably improving structural performance.Here,a multiple variable cutting(M-VCUT)level set-based data-driven model of microstructures is presented,and a method based on this model is proposed for the optimal design of two-scale structures.The geometry of the microstructure is described using the M-VCUT level set method,and the effective mechanical properties of microstructures are computed by the homogenization method.Then,a database of microstructures containing their geometric and mechanical parameters is constructed.The two sets of parameters are adopted as input and output datasets,and a mapping relationship between the two datasets is established to build the data-driven model of microstructures.During the optimization of two-scale structures,the data-driven model is used for macroscale finite element and sensitivity analyses.The efficiency of the analysis and optimization of two-scale structures is improved because the computational costs of invoking such a data-driven model are much smaller than those of homogenization.展开更多
In the current paper,the best linear unbiased estimators(BLUEs)of location and scale parameters from location-scale family will be respectively proposed in cases when one parameter is known and when both are unknown u...In the current paper,the best linear unbiased estimators(BLUEs)of location and scale parameters from location-scale family will be respectively proposed in cases when one parameter is known and when both are unknown under moving extremes ranked set sampling(MERSS).Explicit mathematical expressions of these estimators and their variances are derived.Their relative efficiencies with respect to the minimum variance unbiased estimators(MVUEs)under simple random sampling(SRS)are compared for the cases of some usual distributions.The numerical results show that the BLUEs under MERSS are significantly more efficient than the MVUEs under SRS.展开更多
Previous studies on river health evaluation mainly focused on characterizations at a river-corridor scale and ignored the complex interactions between the river ecosystem and other components of the river basin.Based ...Previous studies on river health evaluation mainly focused on characterizations at a river-corridor scale and ignored the complex interactions between the river ecosystem and other components of the river basin.Based on the consideration of the interactions among rivers,associated river basin and habitats,an assessment framework with multi-scale indicators was developed.An index system divided among these three scales to characterize the health of river ecosystems in China’s Liao River Basin was established.Set pair analysis was applied to integrate the multi-scale indicators and determine the health classes.The evaluation results indicated that the rivers in the western and eastern zones of the Liao River were classified as sick,and rivers in the main stream of the Liao and Huntai rivers were classified as unhealthy.An excessive level of disturbances,such as large pollution loads and dense construction of water conservation projects within the river basin,were the main causes of the river health deterioration.展开更多
In this paper Nottale’s acclaimed scale relativity theory is given a transfinite Occam’s razor leading to exact predictions of the missing dark energy [1,2] of the cosmos. It is found that 95.4915% of the energy in ...In this paper Nottale’s acclaimed scale relativity theory is given a transfinite Occam’s razor leading to exact predictions of the missing dark energy [1,2] of the cosmos. It is found that 95.4915% of the energy in the cosmos according to Einstein’s prediction must be dark energy or not there at all. This percentage is in almost complete agreement with actual measurements.展开更多
A new algorithm based on rough core was proposed to extract all relative-attribute reducts in decision information systems of large-scale records. In the algorithm, the rough core of the decision-making information sy...A new algorithm based on rough core was proposed to extract all relative-attribute reducts in decision information systems of large-scale records. In the algorithm, the rough core of the decision-making information system is first calculated. Then, an approach based on a top-down strategy is adopted to select the non-core condition attributes and generate candidate relative-attribute reducts. Finally, the set of all relative-attribute reducts is obtained by pruning the candidate relative-attribute reducts. Experimental results show that the proposed algorithm is superior to the other methods such as the algorithm without computing core, the exhaustive method and the discernibility matrix method in extracting all relative-attribute reducts for large-scale data sets.展开更多
In statistical parameter estimation problems,how well the parameters are estimated largely depends on the sampling design used.In the current paper,a modification of ranked set sampling called moving extremes ranked s...In statistical parameter estimation problems,how well the parameters are estimated largely depends on the sampling design used.In the current paper,a modification of ranked set sampling called moving extremes ranked set sampling(MERSS)is considered for the Fisher information matrix for the location-scale family.The Fisher information matrix for this model are respectively derived under simple random sampling and MERSS.In order to give more insight into the performance of MERSS with respect to simple random sampling,the Fisher information matrix for usual locationscale distributions are respectively computed under the two sampling.The numerical results show that MERSS provides more information than simple random sampling in parametric inference.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.12272144).
文摘The optimization of two-scale structures can adapt to the different needs of materials in various regions by reasonably arranging different microstructures at the macro scale,thereby considerably improving structural performance.Here,a multiple variable cutting(M-VCUT)level set-based data-driven model of microstructures is presented,and a method based on this model is proposed for the optimal design of two-scale structures.The geometry of the microstructure is described using the M-VCUT level set method,and the effective mechanical properties of microstructures are computed by the homogenization method.Then,a database of microstructures containing their geometric and mechanical parameters is constructed.The two sets of parameters are adopted as input and output datasets,and a mapping relationship between the two datasets is established to build the data-driven model of microstructures.During the optimization of two-scale structures,the data-driven model is used for macroscale finite element and sensitivity analyses.The efficiency of the analysis and optimization of two-scale structures is improved because the computational costs of invoking such a data-driven model are much smaller than those of homogenization.
基金supported by National Science Foundation of China (Grant Nos.12261036 and 11901236)Scientific Research Fund of Hunan Provincial Education Department (Grant No.21A0328)+1 种基金Provincial Natural Science Foundation of Hunan (Grant No.2022JJ30469)Young Core Teacher Foundation of Hunan Province (Grant No.[2020]43)。
文摘In the current paper,the best linear unbiased estimators(BLUEs)of location and scale parameters from location-scale family will be respectively proposed in cases when one parameter is known and when both are unknown under moving extremes ranked set sampling(MERSS).Explicit mathematical expressions of these estimators and their variances are derived.Their relative efficiencies with respect to the minimum variance unbiased estimators(MVUEs)under simple random sampling(SRS)are compared for the cases of some usual distributions.The numerical results show that the BLUEs under MERSS are significantly more efficient than the MVUEs under SRS.
基金This research was supported by the National Natural Science Foundation of China(Grant Nos.50979006 and 50939001)National Water Pollution Control Technology Major Projects(Grant No.2008ZX07526-001 and 2008ZX07209-009).
文摘Previous studies on river health evaluation mainly focused on characterizations at a river-corridor scale and ignored the complex interactions between the river ecosystem and other components of the river basin.Based on the consideration of the interactions among rivers,associated river basin and habitats,an assessment framework with multi-scale indicators was developed.An index system divided among these three scales to characterize the health of river ecosystems in China’s Liao River Basin was established.Set pair analysis was applied to integrate the multi-scale indicators and determine the health classes.The evaluation results indicated that the rivers in the western and eastern zones of the Liao River were classified as sick,and rivers in the main stream of the Liao and Huntai rivers were classified as unhealthy.An excessive level of disturbances,such as large pollution loads and dense construction of water conservation projects within the river basin,were the main causes of the river health deterioration.
文摘In this paper Nottale’s acclaimed scale relativity theory is given a transfinite Occam’s razor leading to exact predictions of the missing dark energy [1,2] of the cosmos. It is found that 95.4915% of the energy in the cosmos according to Einstein’s prediction must be dark energy or not there at all. This percentage is in almost complete agreement with actual measurements.
文摘A new algorithm based on rough core was proposed to extract all relative-attribute reducts in decision information systems of large-scale records. In the algorithm, the rough core of the decision-making information system is first calculated. Then, an approach based on a top-down strategy is adopted to select the non-core condition attributes and generate candidate relative-attribute reducts. Finally, the set of all relative-attribute reducts is obtained by pruning the candidate relative-attribute reducts. Experimental results show that the proposed algorithm is superior to the other methods such as the algorithm without computing core, the exhaustive method and the discernibility matrix method in extracting all relative-attribute reducts for large-scale data sets.
基金supported by the National Natural Science Foundation of China under Grant No.11901236Fund of Hunan Provincial Science and Technology Department under Grant No.2019JJ50479+1 种基金Fund of Hunan Provincial Education Department under Grant No.18B322Young Core Teacher Foundation of Hunan Province under Grant No.[2020]43。
文摘In statistical parameter estimation problems,how well the parameters are estimated largely depends on the sampling design used.In the current paper,a modification of ranked set sampling called moving extremes ranked set sampling(MERSS)is considered for the Fisher information matrix for the location-scale family.The Fisher information matrix for this model are respectively derived under simple random sampling and MERSS.In order to give more insight into the performance of MERSS with respect to simple random sampling,the Fisher information matrix for usual locationscale distributions are respectively computed under the two sampling.The numerical results show that MERSS provides more information than simple random sampling in parametric inference.
