This paper is dedicated to applying the Fourier amplitude sensitivity test(FAST)method to the problem of mixed extension and inflation of a circular cylindrical tube in the presence of residual stresses.The metafuncti...This paper is dedicated to applying the Fourier amplitude sensitivity test(FAST)method to the problem of mixed extension and inflation of a circular cylindrical tube in the presence of residual stresses.The metafunctions and the Ishigami function are considered in the sensitivity analysis(SA).The effects of the input variables on the output variables are investigated,and the most important parameters of the system under the applied pressure and axial force such as the axial stretch and the azimuthal stretch are determined.展开更多
敏感性分析(SA)是用于识别模型重要参数的最具有影响力的方式。以富士川流域作为研究区,对包含5个具有明确物理意义的参数的分布式水文物理模型BTOPMC进行敏感参数筛选。利用Morris One At A Time(MOAT)方法,在适当的采样设计和有效筛...敏感性分析(SA)是用于识别模型重要参数的最具有影响力的方式。以富士川流域作为研究区,对包含5个具有明确物理意义的参数的分布式水文物理模型BTOPMC进行敏感参数筛选。利用Morris One At A Time(MOAT)方法,在适当的采样设计和有效筛选敏感参数所需的足够样本大小条件下定性分析BTOPMC模型参数敏感性。根据输出结果发现,该模型中的敏感变量有9~12个,涉及到的参数有Srmax(m)、m(m)和n0。此外,采用基于导数的全局敏感度量(DGSM)这一定量方法验证定性分析的结果并量化所有参数的重要性,该方法所得结果与定性分析结果基本一致。展开更多
Evaluating the in situ concrete compressive strength by means of cores cut from hardened concrete is acknowledged as the most ordinary method, however, it is very difficult to predict the compressive strength of concr...Evaluating the in situ concrete compressive strength by means of cores cut from hardened concrete is acknowledged as the most ordinary method, however, it is very difficult to predict the compressive strength of concrete since it is affected by many factors such as different mix designs, methods of mixing, curing conditions, compaction, etc. In this paper, considering the experimental results, three different models of multiple linear regression model （MLR）, artificial neural network （ANN）, and adaptive neuro-fuzzy inference system （ANFIS） are established, trained, and tested within the Matlab programming environment for predicting the 28 days compressive strength of concrete with 173 different mix designs. Finally, these three models are compared with each other and resulted in the fact that ANN and ANFIS models enables us to reliably evaluate the compressive strength of concrete with different mix designs, however, multiple linear regression model is not feasible enough in this area because of nonlinear relationship between the concrete mix parameters. Finally, the sensitivity analysis （SA） for two different sets of parameters on the concrete compressive strength prediction are carried out.展开更多
In this paper,an Uncertainty-based Multi-disciplinary Design Optimization (UMDO)method combining with fuzzy theory and Multi-Discipline Feasible (MDF) method is developed for the conceptual design of a Hybrid Rocket M...In this paper,an Uncertainty-based Multi-disciplinary Design Optimization (UMDO)method combining with fuzzy theory and Multi-Discipline Feasible (MDF) method is developed for the conceptual design of a Hybrid Rocket Motor (HRM) powered Launch Vehicle (LV).In the method proposed,membership functions are used to represent the uncertain factors,the fuzzy statistical experiment is introduced to analyze the propagation of uncertainties,and means,standard deviations and credibility measures are used to delineate uncertain responses.A geometric programming problem is solved to verify the feasibility of the Fuzzy-based Multi-Discipline Feasible(F-MDF) method.A multi-disciplinary analysis of a three-stage HRM powered LV involving the disciplines of propulsion,structure,aerodynamics and trajectory is implemented,and the mathematical models corresponding to the F-MDF method and the MDF method are established.A two-phase optimization method is proposed for multi-disciplinary design optimization of the LV,including the orbital capacity optimization phase based on the Ziolkowski formula,and the scheme trajectory verification phase based on the 3-degree-of-freedom point trajectory simulation.The correlation coefficients and the quadratic Response Surface Method (RSM) based on Latin Hypercube Sampling (LHS) are adopted for sensitive analysis of uncertain factors,and the Multi-Island Genetic Algorithm (MIGA) is adopted as the optimization algorithm.The results show that the F-MDF method is applicable in LV conceptual design,and the design with the F-MDF method is more reliable and robust than that with the MDF method.展开更多
文摘This paper is dedicated to applying the Fourier amplitude sensitivity test(FAST)method to the problem of mixed extension and inflation of a circular cylindrical tube in the presence of residual stresses.The metafunctions and the Ishigami function are considered in the sensitivity analysis(SA).The effects of the input variables on the output variables are investigated,and the most important parameters of the system under the applied pressure and axial force such as the axial stretch and the azimuthal stretch are determined.
文摘敏感性分析(SA)是用于识别模型重要参数的最具有影响力的方式。以富士川流域作为研究区,对包含5个具有明确物理意义的参数的分布式水文物理模型BTOPMC进行敏感参数筛选。利用Morris One At A Time(MOAT)方法,在适当的采样设计和有效筛选敏感参数所需的足够样本大小条件下定性分析BTOPMC模型参数敏感性。根据输出结果发现,该模型中的敏感变量有9~12个,涉及到的参数有Srmax(m)、m(m)和n0。此外,采用基于导数的全局敏感度量(DGSM)这一定量方法验证定性分析的结果并量化所有参数的重要性,该方法所得结果与定性分析结果基本一致。
文摘Evaluating the in situ concrete compressive strength by means of cores cut from hardened concrete is acknowledged as the most ordinary method, however, it is very difficult to predict the compressive strength of concrete since it is affected by many factors such as different mix designs, methods of mixing, curing conditions, compaction, etc. In this paper, considering the experimental results, three different models of multiple linear regression model （MLR）, artificial neural network （ANN）, and adaptive neuro-fuzzy inference system （ANFIS） are established, trained, and tested within the Matlab programming environment for predicting the 28 days compressive strength of concrete with 173 different mix designs. Finally, these three models are compared with each other and resulted in the fact that ANN and ANFIS models enables us to reliably evaluate the compressive strength of concrete with different mix designs, however, multiple linear regression model is not feasible enough in this area because of nonlinear relationship between the concrete mix parameters. Finally, the sensitivity analysis （SA） for two different sets of parameters on the concrete compressive strength prediction are carried out.
基金supported by National Natural Science Foundation of China (No. 51305014)
文摘In this paper,an Uncertainty-based Multi-disciplinary Design Optimization (UMDO)method combining with fuzzy theory and Multi-Discipline Feasible (MDF) method is developed for the conceptual design of a Hybrid Rocket Motor (HRM) powered Launch Vehicle (LV).In the method proposed,membership functions are used to represent the uncertain factors,the fuzzy statistical experiment is introduced to analyze the propagation of uncertainties,and means,standard deviations and credibility measures are used to delineate uncertain responses.A geometric programming problem is solved to verify the feasibility of the Fuzzy-based Multi-Discipline Feasible(F-MDF) method.A multi-disciplinary analysis of a three-stage HRM powered LV involving the disciplines of propulsion,structure,aerodynamics and trajectory is implemented,and the mathematical models corresponding to the F-MDF method and the MDF method are established.A two-phase optimization method is proposed for multi-disciplinary design optimization of the LV,including the orbital capacity optimization phase based on the Ziolkowski formula,and the scheme trajectory verification phase based on the 3-degree-of-freedom point trajectory simulation.The correlation coefficients and the quadratic Response Surface Method (RSM) based on Latin Hypercube Sampling (LHS) are adopted for sensitive analysis of uncertain factors,and the Multi-Island Genetic Algorithm (MIGA) is adopted as the optimization algorithm.The results show that the F-MDF method is applicable in LV conceptual design,and the design with the F-MDF method is more reliable and robust than that with the MDF method.
基金Project supported by the National Natural Science Foundation of China(No.51478039)the Fundamental Research Funds for the Central Universities of China(Nos.FRF-TP-14-063A2 and FRF-TP-15-001C1)+2 种基金the Beijing Nova Program(No.Z151100000315053)the 111 Project(No.B12012)the Ningbo Science and Technology Project(No.2015C110020),China
