This paper presents a framework for constructing surrogate models for sensitivity analysis of structural dynamics behavior.Physical models involving deformation,such as collisions,vibrations,and penetration,are devel-...This paper presents a framework for constructing surrogate models for sensitivity analysis of structural dynamics behavior.Physical models involving deformation,such as collisions,vibrations,and penetration,are devel-oped using the material point method.To reduce the computational cost of Monte Carlo simulations,response surface models are created as surrogate models for the material point system to approximate its dynamic behavior.An adaptive randomized greedy algorithm is employed to construct a sparse polynomial chaos expansion model with a fixed order,effectively balancing the accuracy and computational efficiency of the surrogate model.Based on the sparse polynomial chaos expansion,sensitivity analysis is conducted using the global finite difference and Sobol methods.Several examples of structural dynamics are provided to demonstrate the effectiveness of the proposed method in addressing structural dynamics problems.展开更多
An efficient and accurate uncertainty propagation methodology for mechanics problems with random fields is developed in this paper. This methodology is based on the stochastic response surface method （SRSM） which ha...An efficient and accurate uncertainty propagation methodology for mechanics problems with random fields is developed in this paper. This methodology is based on the stochastic response surface method （SRSM） which has been previously proposed for problems dealing with random variables only. This paper extends SRSM to problems involving random fields or random processes fields. The favorable property of SRSM lies in that the deterministic computational model can be treated as a black box, as in the case of commercial finite element codes. Numerical examples are used to highlight the features of this technique and to demonstrate the accuracy and efficiency of the proposed method. A comparison with Monte Carlo simulation shows that the proposed method can achieve numerical results close to those from Monte Carlo simulation while dramatically reducing the number of deterministic finite element runs.展开更多
This paper presents a compact and low-power-based discrete-time chaotic oscillator based on a carbon nanotube field-effect transistor implemented using Wong and Deng＇s well-known model. The chaotic circuit is compose...This paper presents a compact and low-power-based discrete-time chaotic oscillator based on a carbon nanotube field-effect transistor implemented using Wong and Deng＇s well-known model. The chaotic circuit is composed of a nonlinear circuit that creates an adjustable chaos map, two sample and hold cells for capture and delay functions, and a voltage shifter that works as a buffer and adjusts the output voltage for feedback. The operation of the chaotic circuit is verified with the SPICE software package, which uses a supply voltage of 0.9 V at a frequency of 20 kHz. The time series, frequency spectra, transitions in phase space, sensitivity with the initial condition diagrams, and bifurcation phenomena are presented. The main advantage of this circuit is that its chaotic signal can be generated while dissipating approximately 7.8 μW of power, making it suitable for embedded systems where many chaos-signal generators are required on a single chip.展开更多
Understanding the probabilistic nature of brittle materials due to inherent dispersions in their mechanical properties is important to assess their reliability and safety for sensitive engineering applications.This is...Understanding the probabilistic nature of brittle materials due to inherent dispersions in their mechanical properties is important to assess their reliability and safety for sensitive engineering applications.This is all the more important when elements composed of brittle materials are exposed to dynamic environments,resulting in catastrophic fatigue failures.The authors propose the application of a non-intrusive polynomial chaos expansion method for probabilistic studies on brittle materials undergoing fatigue fracture when geometrical parameters and material properties are random independent variables.Understanding the probabilistic nature of fatigue fracture in brittle materials is crucial for ensuring the reliability and safety of engineering structures subjected to cyclic loading.Crack growth is modelled using a phase-field approach within a finite element framework.For modelling fatigue,fracture resistance is progressively degraded by modifying the regularised free energy functional using a fatigue degradation function.Number of cycles to failure is treated as the dependent variable of interest and is estimated within acceptable limits due to the randomness in independent properties.Multiple 2D benchmark problems are solved to demonstrate the ability of this approach to predict the dependent variable responses with significantly fewer simulations than the Monte Carlo method.This proposed approach can accurately predict results typically obtained through 105 or more runs in Monte Carlo simulations with a reduction of up to three orders of magnitude in required runs.The independent random variables’sensitivity to the system response is determined using Sobol’indices.The proposed approach has low computational overhead and can be useful for computationally intensive problems requiring rapid decision-making in sensitive applications like aerospace,nuclear and biomedical engineering.The technique does not require reformulating existing finite element code and can perform the stochastic study by direct pre/post-processing.展开更多
To obtain a universal model solving the uncertain acoustic field in shallow water, a non-intrusive model coupled polynomial chaos expansion （PCE） method with Helmholtz equa- tion is established, in which the polynom...To obtain a universal model solving the uncertain acoustic field in shallow water, a non-intrusive model coupled polynomial chaos expansion （PCE） method with Helmholtz equa- tion is established, in which the polynomial coefficients are solved by probabilistic collocation method （PCM）. For the cases of Pekeris waveguide which have uncertainties in depth of water column, in both sound speed profile and depth of water column, and for the case of thermocline with lower limit depth uncertain, probability density functions （PDF） of transmission loss （TL） are calculated. The results show that the proposed model is universal for the acoustic propa- gation codes with high computational efficiency and accuracy, and can be applied to study the uncertainty of acoustic propagation in the shallow water en^-ironment with multiple parameters uncertain.展开更多
This paper is concerned with the application of generalized polynomial chaos （gPC） method to nonlinear random pantograph equations. An error estimation of gPC method is derived. The global error analysis is given fo...This paper is concerned with the application of generalized polynomial chaos （gPC） method to nonlinear random pantograph equations. An error estimation of gPC method is derived. The global error analysis is given for the error arising from finite-dimensional noise （FDN） assumption, projection error, aliasing error and discretization error. In the end, with several numerical experiments, the theoretical results are further illustrated.展开更多
To weaken the influence of profile error on compressor aerodynamic performance, especially on pressure ratio and efficiency, a robust design method considering profile error is built to improve the robustness of aerod...To weaken the influence of profile error on compressor aerodynamic performance, especially on pressure ratio and efficiency, a robust design method considering profile error is built to improve the robustness of aerodynamic performance of the blade. The characteristics of profile error are random and small-scaled, which means that to evaluate the influence of profile error on blade aerodynamic performance is a time-intensive and high-precision work. For this reason, non-intrusive polynomial chaos(NIPC) and Kriging surrogate model are introduced in this robust design method to improve the efficiency of uncertainty quantification(UQ) and ensure the evaluate accuracy. The profile error satisfies the Gaussian distribution, and NIPC is carried out to do uncertainty quantification since it has advantages in prediction accuracy and efficiency to get statistical behavior of random profile error. In the integrand points of NIPC, several surrogate models are established based on Latin hypercube sampling(LHS)+ Kriging, which further reduces the costs of optimization design by replacing calling computational fluid dynamic(CFD) repeatedly. The results show that this robust design method can significantly improve the performance robustness in shorter time(40 times faster) without losing accuracy, which is meaningful in engineering application to reduce manufacturing cost in the premise of ensuring the aerodynamic performance. Mechanism analysis of the robustness improvement samples carried out in current work can help find out the key parameter dominating the robustness under the disturbance of profile error, which is meaningful to further improvement of compressor robustness.展开更多
In this paper we study the integral curve in a random vector field perturbed by white noise. It is related to a stochastic transport-diffusion equation. Under some conditions on the covariance function of the vector f...In this paper we study the integral curve in a random vector field perturbed by white noise. It is related to a stochastic transport-diffusion equation. Under some conditions on the covariance function of the vector field, the solution of this stochastic partial differential equation is proved to have moments. The exact p-th moment is represented through integrals with respect to Brownian motions. The basic tool is Girsanov formula.展开更多
基金support from the National Natural Science Foundation of China(Grant Nos.52174123&52274222).
文摘This paper presents a framework for constructing surrogate models for sensitivity analysis of structural dynamics behavior.Physical models involving deformation,such as collisions,vibrations,and penetration,are devel-oped using the material point method.To reduce the computational cost of Monte Carlo simulations,response surface models are created as surrogate models for the material point system to approximate its dynamic behavior.An adaptive randomized greedy algorithm is employed to construct a sparse polynomial chaos expansion model with a fixed order,effectively balancing the accuracy and computational efficiency of the surrogate model.Based on the sparse polynomial chaos expansion,sensitivity analysis is conducted using the global finite difference and Sobol methods.Several examples of structural dynamics are provided to demonstrate the effectiveness of the proposed method in addressing structural dynamics problems.
基金The project supported by the National Natural Science Foundation of China(10602036)
文摘An efficient and accurate uncertainty propagation methodology for mechanics problems with random fields is developed in this paper. This methodology is based on the stochastic response surface method （SRSM） which has been previously proposed for problems dealing with random variables only. This paper extends SRSM to problems involving random fields or random processes fields. The favorable property of SRSM lies in that the deterministic computational model can be treated as a black box, as in the case of commercial finite element codes. Numerical examples are used to highlight the features of this technique and to demonstrate the accuracy and efficiency of the proposed method. A comparison with Monte Carlo simulation shows that the proposed method can achieve numerical results close to those from Monte Carlo simulation while dramatically reducing the number of deterministic finite element runs.
基金Project supported by the Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(Grant No.2011-0011698)
文摘This paper presents a compact and low-power-based discrete-time chaotic oscillator based on a carbon nanotube field-effect transistor implemented using Wong and Deng＇s well-known model. The chaotic circuit is composed of a nonlinear circuit that creates an adjustable chaos map, two sample and hold cells for capture and delay functions, and a voltage shifter that works as a buffer and adjusts the output voltage for feedback. The operation of the chaotic circuit is verified with the SPICE software package, which uses a supply voltage of 0.9 V at a frequency of 20 kHz. The time series, frequency spectra, transitions in phase space, sensitivity with the initial condition diagrams, and bifurcation phenomena are presented. The main advantage of this circuit is that its chaotic signal can be generated while dissipating approximately 7.8 μW of power, making it suitable for embedded systems where many chaos-signal generators are required on a single chip.
文摘Understanding the probabilistic nature of brittle materials due to inherent dispersions in their mechanical properties is important to assess their reliability and safety for sensitive engineering applications.This is all the more important when elements composed of brittle materials are exposed to dynamic environments,resulting in catastrophic fatigue failures.The authors propose the application of a non-intrusive polynomial chaos expansion method for probabilistic studies on brittle materials undergoing fatigue fracture when geometrical parameters and material properties are random independent variables.Understanding the probabilistic nature of fatigue fracture in brittle materials is crucial for ensuring the reliability and safety of engineering structures subjected to cyclic loading.Crack growth is modelled using a phase-field approach within a finite element framework.For modelling fatigue,fracture resistance is progressively degraded by modifying the regularised free energy functional using a fatigue degradation function.Number of cycles to failure is treated as the dependent variable of interest and is estimated within acceptable limits due to the randomness in independent properties.Multiple 2D benchmark problems are solved to demonstrate the ability of this approach to predict the dependent variable responses with significantly fewer simulations than the Monte Carlo method.This proposed approach can accurately predict results typically obtained through 105 or more runs in Monte Carlo simulations with a reduction of up to three orders of magnitude in required runs.The independent random variables’sensitivity to the system response is determined using Sobol’indices.The proposed approach has low computational overhead and can be useful for computationally intensive problems requiring rapid decision-making in sensitive applications like aerospace,nuclear and biomedical engineering.The technique does not require reformulating existing finite element code and can perform the stochastic study by direct pre/post-processing.
文摘To obtain a universal model solving the uncertain acoustic field in shallow water, a non-intrusive model coupled polynomial chaos expansion （PCE） method with Helmholtz equa- tion is established, in which the polynomial coefficients are solved by probabilistic collocation method （PCM）. For the cases of Pekeris waveguide which have uncertainties in depth of water column, in both sound speed profile and depth of water column, and for the case of thermocline with lower limit depth uncertain, probability density functions （PDF） of transmission loss （TL） are calculated. The results show that the proposed model is universal for the acoustic propa- gation codes with high computational efficiency and accuracy, and can be applied to study the uncertainty of acoustic propagation in the shallow water en^-ironment with multiple parameters uncertain.
基金Supported by the National Natural Science Foundation of China(No.11501427,11571128)
文摘This paper is concerned with the application of generalized polynomial chaos （gPC） method to nonlinear random pantograph equations. An error estimation of gPC method is derived. The global error analysis is given for the error arising from finite-dimensional noise （FDN） assumption, projection error, aliasing error and discretization error. In the end, with several numerical experiments, the theoretical results are further illustrated.
基金support of the National Natural Science Foundation of China (NSFC) under the Grant No. 51790512the Overseas Expertise Introduction Project for Discipline Innovation (111 Project) under Grant No. B17037Industry-University-Research Cooperation Project of Aero Engine Corporation of China (AECC) under Grant No. HFZL2018CXY011-1 and MIIT
文摘To weaken the influence of profile error on compressor aerodynamic performance, especially on pressure ratio and efficiency, a robust design method considering profile error is built to improve the robustness of aerodynamic performance of the blade. The characteristics of profile error are random and small-scaled, which means that to evaluate the influence of profile error on blade aerodynamic performance is a time-intensive and high-precision work. For this reason, non-intrusive polynomial chaos(NIPC) and Kriging surrogate model are introduced in this robust design method to improve the efficiency of uncertainty quantification(UQ) and ensure the evaluate accuracy. The profile error satisfies the Gaussian distribution, and NIPC is carried out to do uncertainty quantification since it has advantages in prediction accuracy and efficiency to get statistical behavior of random profile error. In the integrand points of NIPC, several surrogate models are established based on Latin hypercube sampling(LHS)+ Kriging, which further reduces the costs of optimization design by replacing calling computational fluid dynamic(CFD) repeatedly. The results show that this robust design method can significantly improve the performance robustness in shorter time(40 times faster) without losing accuracy, which is meaningful in engineering application to reduce manufacturing cost in the premise of ensuring the aerodynamic performance. Mechanism analysis of the robustness improvement samples carried out in current work can help find out the key parameter dominating the robustness under the disturbance of profile error, which is meaningful to further improvement of compressor robustness.
文摘In this paper we study the integral curve in a random vector field perturbed by white noise. It is related to a stochastic transport-diffusion equation. Under some conditions on the covariance function of the vector field, the solution of this stochastic partial differential equation is proved to have moments. The exact p-th moment is represented through integrals with respect to Brownian motions. The basic tool is Girsanov formula.
