This paper proposes a non-intrusive uncertainty analysis method for artillery dynamics involving hybrid uncertainty using polynomial chaos expansion(PCE).The uncertainty parameters with sufficient information are rega...This paper proposes a non-intrusive uncertainty analysis method for artillery dynamics involving hybrid uncertainty using polynomial chaos expansion(PCE).The uncertainty parameters with sufficient information are regarded as stochastic variables,whereas the interval variables are used to treat the uncertainty parameters with limited stochastic knowledge.In this method,the PCE model is constructed through the Galerkin projection method,in which the sparse grid strategy is used to generate the integral points and the corresponding integral weights.Through the sampling in PCE,the original dynamic systems with hybrid stochastic and interval parameters can be transformed into deterministic dynamic systems,without changing their expressions.The yielded PCE model is utilized as a computationally efficient,surrogate model,and the supremum and infimum of the dynamic responses over all time iteration steps can be easily approximated through Monte Carlo simulation and percentile difference.A numerical example and an artillery exterior ballistic dynamics model are used to illustrate the feasibility and efficiency of this approach.The numerical results indicate that the dynamic response bounds obtained by the PCE approach almost match the results of the direct Monte Carlo simulation,but the computational efficiency of the PCE approach is much higher than direct Monte Carlo simulation.Moreover,the proposed method also exhibits fine precision even in high-dimensional uncertainty analysis problems.展开更多
Recognizing target intent is crucial for making decisions on the battlefield.However,the imperfect and ambiguous character of battlefield situations challenges the validity and causation analysis of classical intent r...Recognizing target intent is crucial for making decisions on the battlefield.However,the imperfect and ambiguous character of battlefield situations challenges the validity and causation analysis of classical intent recognition techniques.Facing with the challenge,a target intention causal analysis paradigm is proposed by combining with an Intervention Retrieval(IR)model and a Hybrid Intention Recognition(HIR)model.The target data acquired by the sensors are modelled as Basic Probability Assignments(BPAs)based on evidence theory to create uncertain datasets.Then,the HIR model is utilized to recognize intent for a tested sample from uncertain datasets.Finally,the intervention operator under the evidence structure is utilized to perform attribute intervention on the tested sample.Data retrieval is performed in the sample database based on the IR model to generate the intention distribution of the pseudo-intervention samples to analyze the causal effects of individual sample attributes.The simulation results demonstrate that our framework successfully identifies the target intention under the evidence structure and goes further to analyze the causal impact of sample attributes on the target intention.展开更多
Abstract In this paper, we propose an uncertainty analysis and design optimization method and its applications on a hybrid rocket motor (HRM) powered vehicle. The multidisciplinary design model of the rocket system ...Abstract In this paper, we propose an uncertainty analysis and design optimization method and its applications on a hybrid rocket motor (HRM) powered vehicle. The multidisciplinary design model of the rocket system is established and the design uncertainties are quantified. The sensitivity anal- ysis of the uncertainties shows that the uncertainty generated from the error of fuel regression rate model has the most significant effect on the system performances. Then the differences between deterministic design optimization (DDO) and uncertainty-based design optimization (UDO) are discussed. Two newly formed uncertainty analysis methods, including the Kriging-based Monte Carlo simulation (KMCS) and Kriging-based Taylor series approximation (KTSA), are carried out using a global approximation Kriging modeling method. Based on the system design model and the results of design uncertainty analysis, the design optimization of an HRM powered vehicle for suborbital flight is implemented using three design optimization methods: DDO, KMCS and KTSA. The comparisons indicate that the two UDO methods can enhance the design reliability and robustness. The researches and methods proposed in this paper can provide a better way for the general design of HRM powered vehicles.展开更多
In this study,a hybrid uncertainties-based analysis and optimization method is presented for the designs of the powertrain mounting system(PMS)involving mixed uncertainties.In the presented method,the PMS parameters w...In this study,a hybrid uncertainties-based analysis and optimization method is presented for the designs of the powertrain mounting system(PMS)involving mixed uncertainties.In the presented method,the PMS parameters with sufficient data are treated as random variables,while those with limited information are defined as interval variables.Then,an uncertainty-based analysis method called as hybrid interval-random perturbation-central difference method(HIRP-CDM),is proposed to compute the hybrid interval-random outputs of the inherent characteristics of the PMS in concerned directions.In addition,the hybrid interval-random-Monte Carlo method(HIR-MCM)is developed to verify the computational accuracy of HIRP-CDM.Next,an optimization model mixed uncertainties is built up for the PMS design based on HIRP-CDM,in which the hybrid intervalrandom outputs of the concerned inherent characteristics are adopted to construct the design objective and constrains.The complex optimization problem can be effectively settled by means of HIRP-CDM.The effectiveness of the presented method is verified by a numerical example.展开更多
To obtain a conceptual design for a hybrid rocket motor(HRM)to be used as the Ascent Propulsion System in the Apollo lunar module,the deterministic design optimization(DDO)method is applied to the HRM design.Based on ...To obtain a conceptual design for a hybrid rocket motor(HRM)to be used as the Ascent Propulsion System in the Apollo lunar module,the deterministic design optimization(DDO)method is applied to the HRM design.Based on the results of an uncertainty analysis of HRMs,an uncertainty-based design optimization(UDO)method is also adopted to improve the design reliability.The HRM design process,which is a multidisciplinary system,is analyzed,and a mathematical model for the system design is established to compute the motor performance from the input parameters,including the input variables and model parameters.The input parameter uncertainties are quantified,and a sensitivity analysis of the model parameter uncertainties is conducted to identify the most important model parameter uncertainties for HRMs.The DDO and probabilistic UDO methods are applied to conceptual designs for an HRM to be used as a substitute for the liquid rocket motor(LRM)of the Ascent Propulsion System.The conceptual design results show that HRMs have several advantages as an alternative to the LRM of the Ascent Propulsion System,including nontoxic propellant combination,small motor volume,and comparable functions,such as restarting and throating.Comparisons of the DDO and UDO results indicate that the UDO method achieves more robust and reliable optimal designs than the DDO method.The probabilistic UDO method can be used to develop better conceptual designs for HRMs.展开更多
在风/柴/储混合供电系统中,风力发电的不确定性和用户负载的波动性对混合供电系统及其储能电池系统的优化设计和运行具有重要影响。针对混合供电系统,采用k-均值周期划分法考虑风力发电和用户负载的波动性,建立了混合供电系统及其储能...在风/柴/储混合供电系统中,风力发电的不确定性和用户负载的波动性对混合供电系统及其储能电池系统的优化设计和运行具有重要影响。针对混合供电系统,采用k-均值周期划分法考虑风力发电和用户负载的波动性,建立了混合供电系统及其储能电池系统的优化模型。在优化模型中将储能电池生命周期费用作为惩罚函数,将循环次数作为约束,以标准化能源费用为目标对混合供电系统进行优化,分析了风力发电不确定性对混合供电系统优化设计的影响。以能量需求为793 k W·h·d^(-1)的风/柴/储混合供电系统为例,研究了混合供电系统优化设计方法。研究表明,考虑风力发电和用户负载的周期划分后,储能电池系统循环次数显著降低,有利于储能电池使用寿命的延长。按风速特性划分周期时,储能电池系统的年循环次数最少,混合供电系统的标准化能源费用最低。当储能电池在其生命周期内的最大循环次数由2000次提升到10000次时,混合供电系统的标准化能源费用降低幅度可达8.3%~16.6%。展开更多
Design reliability and robustness are getting increasingly important for the general design of aerospace systems with many inherently uncertain design parameters.This paper presents a hybrid uncertainty-based design o...Design reliability and robustness are getting increasingly important for the general design of aerospace systems with many inherently uncertain design parameters.This paper presents a hybrid uncertainty-based design optimization(UDO) method developed from probability theory and interval theory.Most of the uncertain design parameters which have sufficient information or experimental data are classified as random variables using probability theory,while the others are defined as interval variables with interval theory.Then a hybrid uncertainty analysis method based on Monte Carlo simulation and Taylor series interval analysis is developed to obtain the uncertainty propagation from the design parameters to system responses.Three design optimization strategies,including deterministic design optimization(DDO),probabilistic UDO and hybrid UDO,are applied to the conceptual design of a hybrid rocket motor(HRM) used as the ascent propulsion system in Apollo lunar module.By comparison,the hybrid UDO is a feasible method and can be effectively applied to the general design of aerospace systems.展开更多
基金financially supported by the National Natural Science Foun-dation of China[Grant Nos.301070603,11572158]。
文摘This paper proposes a non-intrusive uncertainty analysis method for artillery dynamics involving hybrid uncertainty using polynomial chaos expansion(PCE).The uncertainty parameters with sufficient information are regarded as stochastic variables,whereas the interval variables are used to treat the uncertainty parameters with limited stochastic knowledge.In this method,the PCE model is constructed through the Galerkin projection method,in which the sparse grid strategy is used to generate the integral points and the corresponding integral weights.Through the sampling in PCE,the original dynamic systems with hybrid stochastic and interval parameters can be transformed into deterministic dynamic systems,without changing their expressions.The yielded PCE model is utilized as a computationally efficient,surrogate model,and the supremum and infimum of the dynamic responses over all time iteration steps can be easily approximated through Monte Carlo simulation and percentile difference.A numerical example and an artillery exterior ballistic dynamics model are used to illustrate the feasibility and efficiency of this approach.The numerical results indicate that the dynamic response bounds obtained by the PCE approach almost match the results of the direct Monte Carlo simulation,but the computational efficiency of the PCE approach is much higher than direct Monte Carlo simulation.Moreover,the proposed method also exhibits fine precision even in high-dimensional uncertainty analysis problems.
基金partially supported by the National Natural Science Foundation of China(No.62173272)。
文摘Recognizing target intent is crucial for making decisions on the battlefield.However,the imperfect and ambiguous character of battlefield situations challenges the validity and causation analysis of classical intent recognition techniques.Facing with the challenge,a target intention causal analysis paradigm is proposed by combining with an Intervention Retrieval(IR)model and a Hybrid Intention Recognition(HIR)model.The target data acquired by the sensors are modelled as Basic Probability Assignments(BPAs)based on evidence theory to create uncertain datasets.Then,the HIR model is utilized to recognize intent for a tested sample from uncertain datasets.Finally,the intervention operator under the evidence structure is utilized to perform attribute intervention on the tested sample.Data retrieval is performed in the sample database based on the IR model to generate the intention distribution of the pseudo-intervention samples to analyze the causal effects of individual sample attributes.The simulation results demonstrate that our framework successfully identifies the target intention under the evidence structure and goes further to analyze the causal impact of sample attributes on the target intention.
基金supported by the National Natural Science Foundation of China(No.51305014)China Postdoctoral Science Foundation(No.2013M540842)
文摘Abstract In this paper, we propose an uncertainty analysis and design optimization method and its applications on a hybrid rocket motor (HRM) powered vehicle. The multidisciplinary design model of the rocket system is established and the design uncertainties are quantified. The sensitivity anal- ysis of the uncertainties shows that the uncertainty generated from the error of fuel regression rate model has the most significant effect on the system performances. Then the differences between deterministic design optimization (DDO) and uncertainty-based design optimization (UDO) are discussed. Two newly formed uncertainty analysis methods, including the Kriging-based Monte Carlo simulation (KMCS) and Kriging-based Taylor series approximation (KTSA), are carried out using a global approximation Kriging modeling method. Based on the system design model and the results of design uncertainty analysis, the design optimization of an HRM powered vehicle for suborbital flight is implemented using three design optimization methods: DDO, KMCS and KTSA. The comparisons indicate that the two UDO methods can enhance the design reliability and robustness. The researches and methods proposed in this paper can provide a better way for the general design of HRM powered vehicles.
基金supported by the National Natural Science Foundation of China(Grant Nos.51605167,51975217)the Science and Technology Program of Guangzhou,China(Grant No.201804010092)the Fundamental Research Funds for the Central Universities,SCUT(Grant No.2019MS058).
文摘In this study,a hybrid uncertainties-based analysis and optimization method is presented for the designs of the powertrain mounting system(PMS)involving mixed uncertainties.In the presented method,the PMS parameters with sufficient data are treated as random variables,while those with limited information are defined as interval variables.Then,an uncertainty-based analysis method called as hybrid interval-random perturbation-central difference method(HIRP-CDM),is proposed to compute the hybrid interval-random outputs of the inherent characteristics of the PMS in concerned directions.In addition,the hybrid interval-random-Monte Carlo method(HIR-MCM)is developed to verify the computational accuracy of HIRP-CDM.Next,an optimization model mixed uncertainties is built up for the PMS design based on HIRP-CDM,in which the hybrid intervalrandom outputs of the concerned inherent characteristics are adopted to construct the design objective and constrains.The complex optimization problem can be effectively settled by means of HIRP-CDM.The effectiveness of the presented method is verified by a numerical example.
基金supported by the National Natural Science Foundation of China(Grant No.51305014)the China Postdoctoral Science Foundation(Grant No.2013M540842)
文摘To obtain a conceptual design for a hybrid rocket motor(HRM)to be used as the Ascent Propulsion System in the Apollo lunar module,the deterministic design optimization(DDO)method is applied to the HRM design.Based on the results of an uncertainty analysis of HRMs,an uncertainty-based design optimization(UDO)method is also adopted to improve the design reliability.The HRM design process,which is a multidisciplinary system,is analyzed,and a mathematical model for the system design is established to compute the motor performance from the input parameters,including the input variables and model parameters.The input parameter uncertainties are quantified,and a sensitivity analysis of the model parameter uncertainties is conducted to identify the most important model parameter uncertainties for HRMs.The DDO and probabilistic UDO methods are applied to conceptual designs for an HRM to be used as a substitute for the liquid rocket motor(LRM)of the Ascent Propulsion System.The conceptual design results show that HRMs have several advantages as an alternative to the LRM of the Ascent Propulsion System,including nontoxic propellant combination,small motor volume,and comparable functions,such as restarting and throating.Comparisons of the DDO and UDO results indicate that the UDO method achieves more robust and reliable optimal designs than the DDO method.The probabilistic UDO method can be used to develop better conceptual designs for HRMs.
基金Science and Technology Support Planning of Jiangsu Province(No.BE2014133)the Open Foundation of Key Laboratory of Underw ater Acoustic Signal Processing(No.UASP1301)the Prospective Joint Research Project of Jiangsu province(No.BY2014127-01)
文摘在风/柴/储混合供电系统中,风力发电的不确定性和用户负载的波动性对混合供电系统及其储能电池系统的优化设计和运行具有重要影响。针对混合供电系统,采用k-均值周期划分法考虑风力发电和用户负载的波动性,建立了混合供电系统及其储能电池系统的优化模型。在优化模型中将储能电池生命周期费用作为惩罚函数,将循环次数作为约束,以标准化能源费用为目标对混合供电系统进行优化,分析了风力发电不确定性对混合供电系统优化设计的影响。以能量需求为793 k W·h·d^(-1)的风/柴/储混合供电系统为例,研究了混合供电系统优化设计方法。研究表明,考虑风力发电和用户负载的周期划分后,储能电池系统循环次数显著降低,有利于储能电池使用寿命的延长。按风速特性划分周期时,储能电池系统的年循环次数最少,混合供电系统的标准化能源费用最低。当储能电池在其生命周期内的最大循环次数由2000次提升到10000次时,混合供电系统的标准化能源费用降低幅度可达8.3%~16.6%。
基金supported by the National Natural Science Foundation of China(No.51305014)
文摘Design reliability and robustness are getting increasingly important for the general design of aerospace systems with many inherently uncertain design parameters.This paper presents a hybrid uncertainty-based design optimization(UDO) method developed from probability theory and interval theory.Most of the uncertain design parameters which have sufficient information or experimental data are classified as random variables using probability theory,while the others are defined as interval variables with interval theory.Then a hybrid uncertainty analysis method based on Monte Carlo simulation and Taylor series interval analysis is developed to obtain the uncertainty propagation from the design parameters to system responses.Three design optimization strategies,including deterministic design optimization(DDO),probabilistic UDO and hybrid UDO,are applied to the conceptual design of a hybrid rocket motor(HRM) used as the ascent propulsion system in Apollo lunar module.By comparison,the hybrid UDO is a feasible method and can be effectively applied to the general design of aerospace systems.