In this paper,the convergence of the split-step theta method for stochastic differential equations is analyzed using stochastic C-stability and stochastic B-consistency.The fact that the numerical scheme,which is both...In this paper,the convergence of the split-step theta method for stochastic differential equations is analyzed using stochastic C-stability and stochastic B-consistency.The fact that the numerical scheme,which is both stochastically C-stable and stochastically B-consistent,is convergent has been proved in a previous paper.In order to analyze the convergence of the split-step theta method(θ∈[1/2,1]),the stochastic C-stability and stochastic B-consistency under the condition of global monotonicity have been researched,and the rate of convergence 1/2 has been explored in this paper.It can be seen that the convergence does not require the drift function should satisfy the linear growth condition whenθ=1/2 Furthermore,the rate of the convergence of the split-step scheme for stochastic differential equations with additive noise has been researched and found to be 1.Finally,an example is given to illustrate the convergence with the theoretical results.展开更多
The March 28,2025 Myanmar earthquake generated ground shaking that was perceptible throughout Myanmar and adjacent regions.This study simulated three-component ground motions across the affected region using an improv...The March 28,2025 Myanmar earthquake generated ground shaking that was perceptible throughout Myanmar and adjacent regions.This study simulated three-component ground motions across the affected region using an improved stochastic finite-fault method to systematically assess seismic impacts.Observed near-field recordings at MM.NGU station was used to determine the reliability of the theoretically derived stress drop as input for simulation.Far-field recordings constrained the frequency-dependent S-wave quality factors(Q(f)=283.305f^(0.588))for anelastic attenuation modeling.Comparisons of peak accelerations between simulation and empirical ground-motion models showed good agreement at moderate-to-large distances.However,lower near-fault simulations indicate a weaker-than-average source effect.Analysis of simulated instrumental seismic intensity revealed key patterns.Maximum intensity(Ⅹ)occurred in isolated patches within the ruptured fault projection,correlating with shallow high-slip areas.TheⅨ-intensity zone formed a north-south elongated band centered on fault projection.Significant asymmetry inⅧ-intensity distribution perpendicular to the fault strike was observed,with a wider western extension attributed to lower shear-wave velocities west of the fault.Supershear rupture behavior enhanced ground motions,expanding intensity ranges by~20%compared to sub-shear rupture.This study reveals the integrated effects of fault geometry,slip spatial distribution,rupture velocity,and site condition in governing ground motion patterns.展开更多
In this work, we first derive the one-point large deviations principle (LDP) for both the stochastic Cahn–Hilliard equation with small noise and its spatial finite difference method (FDM). Then, we focus on giving th...In this work, we first derive the one-point large deviations principle (LDP) for both the stochastic Cahn–Hilliard equation with small noise and its spatial finite difference method (FDM). Then, we focus on giving the convergence of the one-point large deviations rate function (LDRF) of the spatial FDM, which is about the asymptotical limit of a parametric variational problem. The main idea for proving the convergence of the LDRF of the spatial FDM is via the Γ-convergence of objective functions. This relies on the qualitative analysis of skeleton equations of the original equation and the numerical method. In order to overcome the difficulty that the drift coefficient is not one-sided Lipschitz continuous, we derive the equivalent characterization of the skeleton equation of the spatial FDM and the discrete interpolation inequality to obtain the uniform boundedness of the solution to the underlying skeleton equation. These play important roles in deriving the T-convergence of objective functions.展开更多
Skin panels on supersonic vehicles are subjected to aero-thermo-acoustic loads,resulting in a well-known multi-physics dynamic problem.The high-frequency dynamic response of these panels significantly impacts the stru...Skin panels on supersonic vehicles are subjected to aero-thermo-acoustic loads,resulting in a well-known multi-physics dynamic problem.The high-frequency dynamic response of these panels significantly impacts the structural safety of supersonic vehicles,but it has been rarely investigated.Given that existing methods are inefficient for high-frequency dynamic analysis in multi-physics fields,the present work addresses this challenge by proposing a Stochastic Energy Finite Element Method(SEFEM).SEFEM uses energy density instead of displacement to describe the dynamic response,thereby significantly enhancing its efficiency.In SEFEM,the effects of aerodynamic and thermal loads on the energy propagation characteristics are studied analytically and incorporated into the energy density governing equation.These effects are also considered when calculating the input power generated by the acoustic load,and two effective approaches named Frequency Response Function Method(FRFM)and Mechanical Impedance Method(MIM)are developed accordingly and integrated into SEFEM.The good accuracy,applicability,and high efficiency of the proposed SEFEM are demonstrated through numerical simulations performed on a two-dimensional panel under aero-thermoacoustic loads.Additionally,the effects and underlying mechanisms of aero-thermo-acoustic loads on the high-frequency response are explored.This work not only presents an efficient approach for predicting high-frequency dynamic response of panels subjected to aero-thermo-acoustic loads,but also provides insights into the high-frequency dynamic characteristics in multi-physics fields.展开更多
This paper aims to evaluate the stochastic response of steel columns subjected to blast loads using the modified single degree of freedom(MSDOF)method,which assessed towards the conventional single degree of freedom(S...This paper aims to evaluate the stochastic response of steel columns subjected to blast loads using the modified single degree of freedom(MSDOF)method,which assessed towards the conventional single degree of freedom(SDOF)and the experimentally validated Finite Element(FE)methods(LSDYNA).For this purpose,special atten-tion is given to calculating the response of H-shaped steel columns under blast.The damage amount is determined based on the support rotation criterion,which is expressed as a function of their maximum lateral mid-span dis-placement.To account for uncertainties in input parameters and obtain the failure probability,the Monte Carlo simulation(MCS)method is employed,complemented by the Latin Hypercube Sampling(LHS)method to reduce the number of simulations.A parametric analysis is hence performed to examine the effect of several input pa-rameters(including both deterministic and probabilistic parameters)on the probability of column damage as a function of support rotation.First,the MSDOF method confirms its higher accuracy in estimating the probability of column damage due to blast,compared to the conventional SDOF.The collected results also show that un-certainties of several input parameters have significant effects on the column behavior.In particular,geometric parameters(including cross-sectional characteristics,boundary conditions and column length)have major effect on the corresponding column response,in the same way of input blast load parameters and material properties.展开更多
The stochastic boundary element method(SBEM)is developed in this paper for 3D problems with body forces and reliability analysis of engineering structures.The integral equations of SBEM are established by the approach...The stochastic boundary element method(SBEM)is developed in this paper for 3D problems with body forces and reliability analysis of engineering structures.The integral equations of SBEM are established by the approach of partial derivation with respect to stochastic variables,considering the yield limit,rotation speeds and material density to be the fundamental stochastic variables.Through analyzing a numerical example and a turbo-disk of an aeroengine,the results show that the method developed is successful.展开更多
A new fuzzy stochastic finite element method based on the fuzzy factor method and random factor method is given and the analysis of structural dynamic characteristic for fuzzy stochastic truss structures is presented....A new fuzzy stochastic finite element method based on the fuzzy factor method and random factor method is given and the analysis of structural dynamic characteristic for fuzzy stochastic truss structures is presented. Considering the fuzzy randomness of the structural physical parameters and geometric dimensions simultaneously, the structural stiffness and mass matrices axe constructed based on the fuzzy factor method and random factor method; from the Rayleigh＇s quotient of structural vibration, the structural fuzzy random dynamic characteristic is obtained by means of the interval arithmetic; the fuzzy numeric characteristics of dynamic characteristic axe then derived by using the random variable＇s moment function method and algebra synthesis method. Two examples axe used to illustrate the validity and rationality of the method given. The advantage of this method is that the effect of the fuzzy randomness of one of the structural parameters on the fuzzy randomness of the dynamic characteristic can be reflected expediently and objectively.展开更多
To study the effect of uncertain factors on the temperature field of frozen soil, we propose a method to calculate the spatial average variance from just the point variance based on the local average theory of random ...To study the effect of uncertain factors on the temperature field of frozen soil, we propose a method to calculate the spatial average variance from just the point variance based on the local average theory of random fields. We model the heat transfer coefficient and specific heat capacity as spatially random fields instead of traditional random variables. An analysis for calculating the random temperature field of seasonal frozen soil is suggested by the Neumann stochastic finite element method, and here we provide the computational formulae of mathematical expectation, variance and variable coefficient. As shown in the calculation flow chart, the stochastic finite element calculation program for solving the random temperature field, as compiled by Matrix Laboratory （MATLAB） sottware, can directly output the statistical results of the temperature field of frozen soil. An example is presented to demonstrate the random effects from random field parameters, and the feasibility of the proposed approach is proven by compar- ing these results with the results derived when the random parameters are only modeled as random variables. The results show that the Neumann stochastic finite element method can efficiently solve the problem of random temperature fields of frozen soil based on random field theory, and it can reduce the variability of calculation results when the random parameters are modeled as spatial- ly random fields.展开更多
The traditional voltage stability analysis method is mostly based on the deterministic mode1.and ignores the uncertainties of bus loads,power supplies,changes in network configuration and so on.However,the great expan...The traditional voltage stability analysis method is mostly based on the deterministic mode1.and ignores the uncertainties of bus loads,power supplies,changes in network configuration and so on.However,the great expansion of renewable power generations such as wind and solar energy in a power system has increased their uncertainty,and仃aditional techniques are limited in capturing their variable behavior.This leads to greater needs of new techniques and methodologies to properly quan tify the voltage stability of power systems.展开更多
With the development of computational power, there has been an increased focus on data-fitting related seismic inversion techniques for high fidelity seismic velocity model and image, such as full-waveform inversion a...With the development of computational power, there has been an increased focus on data-fitting related seismic inversion techniques for high fidelity seismic velocity model and image, such as full-waveform inversion and least squares migration. However, though more advanced than conventional methods, these data fitting methods can be very expensive in terms of computational cost. Recently, various techniques to optimize these data-fitting seismic inversion problems have been implemented to cater for the industrial need for much improved efficiency. In this study, we propose a general stochastic conjugate gradient method for these data-fitting related inverse problems. We first prescribe the basic theory of our method and then give synthetic examples. Our numerical experiments illustrate the potential of this method for large-size seismic inversion application.展开更多
The paper studies the parametric stochastic roll motion in the random waves.The differential equation of the ship parametric roll under random wave is established with considering the nonlinear damping and ship speed....The paper studies the parametric stochastic roll motion in the random waves.The differential equation of the ship parametric roll under random wave is established with considering the nonlinear damping and ship speed.Random sea surface is treated as a narrow-band stochastic process,and the stochastic parametric excitation is studied based on the effective wave theory.The nonlinear restored arm function obtained from the numerical simulation is expressed as the approximate analytic function.By using the stochastic averaging method,the differential equation of motion is transformed into Ito’s stochastic differential equation.The steady-state probability density function of roll motion is obtained,and the results are validated with the numerical simulation and model test.展开更多
The difficulty in solving stochastic dynamics problems lies in the need for a large number of repeated computations of deterministic dynamic equations,which has been a challenge in stochastic dynamics analysis and was...The difficulty in solving stochastic dynamics problems lies in the need for a large number of repeated computations of deterministic dynamic equations,which has been a challenge in stochastic dynamics analysis and was discussed in this study.To efficiently and accurately compute the exponential of the dynamics state matrix and the matrix functions due to external loads,an adaptively filtered precise integration method was proposed,which inherits the high precision of the precise integrationmethod,improves the computational efficiency and saves the memory required.Moreover,the perturbation method was introduced to avoid repeated computations of matrix exponential and terms due to external loads.Based on the filtering and perturbation techniques,an adaptively filtered precise integration method considering perturbation for stochastic dynamics problems was developed.Two numerical experiments,including a model of phononic crystal and a bridge model considering random parameters,were performed to test the performance of the proposed method in terms of accuracy and efficiency.Numerical results show that the accuracy and efficiency of the proposed method are better than those of the existing precise integration method,the Newmark-βmethod and the Wilson-θmethod.展开更多
The stochastic boundary element method is developed to analyze elasticity problems with random material and/or geometrical parameters and ran- domly perturbed boundaries. Based on the first-order Taylor series expansi...The stochastic boundary element method is developed to analyze elasticity problems with random material and/or geometrical parameters and ran- domly perturbed boundaries. Based on the first-order Taylor series expansion, the boundary integration equations concerning the mean and deviation of the displace- ments are derived, respectively. It is found that the randomness of material param- eters is equivalent to a random body force, so the mean and covariance matrices of unknown boundary displacements and tractions can be obtained. Furthermore, the mean and covariance of displacements and stresses at inner points can also be obtained. Numerical examples show that the proposed stochastic boundary element method gives satisfactory solutions, as compared with those obtained by theoretical analysis or other numerical methods.展开更多
Stochastic heat conduction and thermal stress analysis of structures has received considerable attention in recent years.The propagation of uncertain thermal environments will lead to stochastic variations in temperat...Stochastic heat conduction and thermal stress analysis of structures has received considerable attention in recent years.The propagation of uncertain thermal environments will lead to stochastic variations in temperature fields and thermal stresses.Therefore,it is reasonable to consider the variability of thermal environments while conducting thermal analysis.However,for ambient thermal excitations,only stationary random processes have been investigated thus far.In this study,the highly efficient explicit time-domain method(ETDM)is proposed for the analysis of non-stationary stochastic transient heat conduction and thermal stress problems.The explicit time-domain expressions of thermal responses are first constructed for a thermoelastic body.Then the statistical moments of thermal displacements and stresses can be directly obtained based on the explicit expressions of thermal responses.A numerical example involving non-stationary stochastic internal heat generation rate is investigated.The accuracy and efficiency of the proposed method are validated by comparison with the Monte-Carlo simulation.展开更多
This paper develops the mean-square exponential input-to-state stability（exp-ISS） of the Euler-Maruyama（EM） method for stochastic delay control systems（SDCSs）.The definition of mean-square exp-ISS of numerical m...This paper develops the mean-square exponential input-to-state stability（exp-ISS） of the Euler-Maruyama（EM） method for stochastic delay control systems（SDCSs）.The definition of mean-square exp-ISS of numerical methods is established.The conditions of the exact and EM method for an SDCS with the property of mean-square exp-ISS are obtained without involving control Lyapunov functions or functional.Under the global Lipschitz coefficients and mean-square continuous measurable inputs,it is proved that the mean-square exp-ISS of an SDCS holds if and only if that of the EM method is preserved for a sufficiently small step size.The proposed results are evaluated by using numerical experiments to show their effectiveness.展开更多
In this paper, the cubic and quintic diffusion equation under stochastic non homogeneity is solved using Wiener- Hermite expansion and perturbation (WHEP) technique, Homotopy perturbation method (HPM) and Pickard appr...In this paper, the cubic and quintic diffusion equation under stochastic non homogeneity is solved using Wiener- Hermite expansion and perturbation (WHEP) technique, Homotopy perturbation method (HPM) and Pickard approximation technique. The analytic solution of the linear case is obtained using Eigenfunction expansion .The Picard approximation method is used to introduce the first and second order approximate solution for the non linear case. The WHEP technique is also used to obtain approximate solution under different orders and different corrections. The Homotopy perturbation method (HPM) is also used to obtain some approximation orders for mean and variance. Using mathematica-5, the methods of solution are illustrated through figures, comparisons among different methods and some parametric studies.展开更多
Nonlinear stochastic modeling plays a significant role in disciplines such as psychology,finance,physical sciences,engineering,econometrics,and biological sciences.Dynamical consistency,positivity,and boundedness are ...Nonlinear stochastic modeling plays a significant role in disciplines such as psychology,finance,physical sciences,engineering,econometrics,and biological sciences.Dynamical consistency,positivity,and boundedness are fundamental properties of stochastic modeling.A stochastic coronavirus model is studied with techniques of transition probabilities and parametric perturbation.Well-known explicit methods such as Euler Maruyama,stochastic Euler,and stochastic Runge–Kutta are investigated for the stochastic model.Regrettably,the above essential properties are not restored by existing methods.Hence,there is a need to construct essential properties preserving the computational method.The non-standard approach of finite difference is examined to maintain the above basic features of the stochastic model.The comparison of the results of deterministic and stochastic models is also presented.Our proposed efficient computational method well preserves the essential properties of the model.Comparison and convergence analyses of the method are presented.展开更多
Owing to the fact that the conventional deterministic back analysis of the permeability coefficient cannot reflect the uncertainties of parameters, including the hydraulic head at the boundary, the permeability coeffi...Owing to the fact that the conventional deterministic back analysis of the permeability coefficient cannot reflect the uncertainties of parameters, including the hydraulic head at the boundary, the permeability coefficient and measured hydraulic head, a stochastic back analysis taking consideration of uncertainties of parameters was performed using the generalized Bayesian method. Based on the stochastic finite element method （SFEM） for a seepage field, the variable metric algorithm and the generalized Bayesian method, formulas for stochastic back analysis of the permeability coefficient were derived. A case study of seepage analysis of a sluice foundation was performed to illustrate the proposed method. The results indicate that, with the generalized Bayesian method that considers the uncertainties of measured hydraulic head, the permeability coefficient and the hydraulic head at the boundary, both the mean and standard deviation of the permeability coefficient can be obtained and the standard deviation is less than that obtained by the conventional Bayesian method. Therefore, the present method is valid and applicable.展开更多
This paper deals with the mean-square exponential input-to-state stability(exp-ISS)of Euler-Maruyama(EM)method applied to stochastic control systems(SCSs).The aim is to find out the conditions of the exact and EM meth...This paper deals with the mean-square exponential input-to-state stability(exp-ISS)of Euler-Maruyama(EM)method applied to stochastic control systems(SCSs).The aim is to find out the conditions of the exact and EM method solutions to an SCS having the property of mean-square exp-ISS without involving control Lyapunov functions.Second moment boundedness and an appropriate form of strong convergence are achieved under global Lipschitz coeffcients and mean-square continuous random inputs.Under the strong convergent condition,it is shown that the mean-square exp-ISS of an SCS holds if and only if that of the EM method is preserved for suffciently small step size.展开更多
Positive results are proved here about the ability of balanced methods to reproduce the mean square stability of the impulsive stochastic differential equations. It is shown that the balanced methods with strong conve...Positive results are proved here about the ability of balanced methods to reproduce the mean square stability of the impulsive stochastic differential equations. It is shown that the balanced methods with strong convergence can preserve the mean square stability with the sufficiently small stepsize. Weak variants and their mean square stability are also considered. Several numerical experiments are given for illustration and show that the fully implicit methods are superior to those of the explicit methods in terms of mean-square stabilities for relatively large stepsizes especially.展开更多
基金Supported by the National Natural Science Foundation of China (Grant No. 12301521)the Natural Science Foundation of Shanxi Province (Grant No. 20210302124081)。
文摘In this paper,the convergence of the split-step theta method for stochastic differential equations is analyzed using stochastic C-stability and stochastic B-consistency.The fact that the numerical scheme,which is both stochastically C-stable and stochastically B-consistent,is convergent has been proved in a previous paper.In order to analyze the convergence of the split-step theta method(θ∈[1/2,1]),the stochastic C-stability and stochastic B-consistency under the condition of global monotonicity have been researched,and the rate of convergence 1/2 has been explored in this paper.It can be seen that the convergence does not require the drift function should satisfy the linear growth condition whenθ=1/2 Furthermore,the rate of the convergence of the split-step scheme for stochastic differential equations with additive noise has been researched and found to be 1.Finally,an example is given to illustrate the convergence with the theoretical results.
基金National Key R&D Program of China under Grant No.2022YFC3003601。
文摘The March 28,2025 Myanmar earthquake generated ground shaking that was perceptible throughout Myanmar and adjacent regions.This study simulated three-component ground motions across the affected region using an improved stochastic finite-fault method to systematically assess seismic impacts.Observed near-field recordings at MM.NGU station was used to determine the reliability of the theoretically derived stress drop as input for simulation.Far-field recordings constrained the frequency-dependent S-wave quality factors(Q(f)=283.305f^(0.588))for anelastic attenuation modeling.Comparisons of peak accelerations between simulation and empirical ground-motion models showed good agreement at moderate-to-large distances.However,lower near-fault simulations indicate a weaker-than-average source effect.Analysis of simulated instrumental seismic intensity revealed key patterns.Maximum intensity(Ⅹ)occurred in isolated patches within the ruptured fault projection,correlating with shallow high-slip areas.TheⅨ-intensity zone formed a north-south elongated band centered on fault projection.Significant asymmetry inⅧ-intensity distribution perpendicular to the fault strike was observed,with a wider western extension attributed to lower shear-wave velocities west of the fault.Supershear rupture behavior enhanced ground motions,expanding intensity ranges by~20%compared to sub-shear rupture.This study reveals the integrated effects of fault geometry,slip spatial distribution,rupture velocity,and site condition in governing ground motion patterns.
基金supported by the National Natural Science Foundation of China(12201228,12171047)the Fundamental Research Funds for the Central Universities(3034011102)supported by National Key R&D Program of China(2020YFA0713701).
文摘In this work, we first derive the one-point large deviations principle (LDP) for both the stochastic Cahn–Hilliard equation with small noise and its spatial finite difference method (FDM). Then, we focus on giving the convergence of the one-point large deviations rate function (LDRF) of the spatial FDM, which is about the asymptotical limit of a parametric variational problem. The main idea for proving the convergence of the LDRF of the spatial FDM is via the Γ-convergence of objective functions. This relies on the qualitative analysis of skeleton equations of the original equation and the numerical method. In order to overcome the difficulty that the drift coefficient is not one-sided Lipschitz continuous, we derive the equivalent characterization of the skeleton equation of the spatial FDM and the discrete interpolation inequality to obtain the uniform boundedness of the solution to the underlying skeleton equation. These play important roles in deriving the T-convergence of objective functions.
基金financially supported by the National Natural Science Foundation of China(Nos.12302228 and 12372170)。
文摘Skin panels on supersonic vehicles are subjected to aero-thermo-acoustic loads,resulting in a well-known multi-physics dynamic problem.The high-frequency dynamic response of these panels significantly impacts the structural safety of supersonic vehicles,but it has been rarely investigated.Given that existing methods are inefficient for high-frequency dynamic analysis in multi-physics fields,the present work addresses this challenge by proposing a Stochastic Energy Finite Element Method(SEFEM).SEFEM uses energy density instead of displacement to describe the dynamic response,thereby significantly enhancing its efficiency.In SEFEM,the effects of aerodynamic and thermal loads on the energy propagation characteristics are studied analytically and incorporated into the energy density governing equation.These effects are also considered when calculating the input power generated by the acoustic load,and two effective approaches named Frequency Response Function Method(FRFM)and Mechanical Impedance Method(MIM)are developed accordingly and integrated into SEFEM.The good accuracy,applicability,and high efficiency of the proposed SEFEM are demonstrated through numerical simulations performed on a two-dimensional panel under aero-thermoacoustic loads.Additionally,the effects and underlying mechanisms of aero-thermo-acoustic loads on the high-frequency response are explored.This work not only presents an efficient approach for predicting high-frequency dynamic response of panels subjected to aero-thermo-acoustic loads,but also provides insights into the high-frequency dynamic characteristics in multi-physics fields.
文摘This paper aims to evaluate the stochastic response of steel columns subjected to blast loads using the modified single degree of freedom(MSDOF)method,which assessed towards the conventional single degree of freedom(SDOF)and the experimentally validated Finite Element(FE)methods(LSDYNA).For this purpose,special atten-tion is given to calculating the response of H-shaped steel columns under blast.The damage amount is determined based on the support rotation criterion,which is expressed as a function of their maximum lateral mid-span dis-placement.To account for uncertainties in input parameters and obtain the failure probability,the Monte Carlo simulation(MCS)method is employed,complemented by the Latin Hypercube Sampling(LHS)method to reduce the number of simulations.A parametric analysis is hence performed to examine the effect of several input pa-rameters(including both deterministic and probabilistic parameters)on the probability of column damage as a function of support rotation.First,the MSDOF method confirms its higher accuracy in estimating the probability of column damage due to blast,compared to the conventional SDOF.The collected results also show that un-certainties of several input parameters have significant effects on the column behavior.In particular,geometric parameters(including cross-sectional characteristics,boundary conditions and column length)have major effect on the corresponding column response,in the same way of input blast load parameters and material properties.
文摘The stochastic boundary element method(SBEM)is developed in this paper for 3D problems with body forces and reliability analysis of engineering structures.The integral equations of SBEM are established by the approach of partial derivation with respect to stochastic variables,considering the yield limit,rotation speeds and material density to be the fundamental stochastic variables.Through analyzing a numerical example and a turbo-disk of an aeroengine,the results show that the method developed is successful.
基金Project supported by the Natural Science Foundation of Shaanxi Province of China (No,A200214)
文摘A new fuzzy stochastic finite element method based on the fuzzy factor method and random factor method is given and the analysis of structural dynamic characteristic for fuzzy stochastic truss structures is presented. Considering the fuzzy randomness of the structural physical parameters and geometric dimensions simultaneously, the structural stiffness and mass matrices axe constructed based on the fuzzy factor method and random factor method; from the Rayleigh＇s quotient of structural vibration, the structural fuzzy random dynamic characteristic is obtained by means of the interval arithmetic; the fuzzy numeric characteristics of dynamic characteristic axe then derived by using the random variable＇s moment function method and algebra synthesis method. Two examples axe used to illustrate the validity and rationality of the method given. The advantage of this method is that the effect of the fuzzy randomness of one of the structural parameters on the fuzzy randomness of the dynamic characteristic can be reflected expediently and objectively.
基金funded by the National Basic Research Program of China (No. 2012CB026103)the National High Technology Research and Development Program of China (No. 2012AA06A401)the National Natural Science Foundation of China (No. 41271096)
文摘To study the effect of uncertain factors on the temperature field of frozen soil, we propose a method to calculate the spatial average variance from just the point variance based on the local average theory of random fields. We model the heat transfer coefficient and specific heat capacity as spatially random fields instead of traditional random variables. An analysis for calculating the random temperature field of seasonal frozen soil is suggested by the Neumann stochastic finite element method, and here we provide the computational formulae of mathematical expectation, variance and variable coefficient. As shown in the calculation flow chart, the stochastic finite element calculation program for solving the random temperature field, as compiled by Matrix Laboratory （MATLAB） sottware, can directly output the statistical results of the temperature field of frozen soil. An example is presented to demonstrate the random effects from random field parameters, and the feasibility of the proposed approach is proven by compar- ing these results with the results derived when the random parameters are only modeled as random variables. The results show that the Neumann stochastic finite element method can efficiently solve the problem of random temperature fields of frozen soil based on random field theory, and it can reduce the variability of calculation results when the random parameters are modeled as spatial- ly random fields.
文摘The traditional voltage stability analysis method is mostly based on the deterministic mode1.and ignores the uncertainties of bus loads,power supplies,changes in network configuration and so on.However,the great expansion of renewable power generations such as wind and solar energy in a power system has increased their uncertainty,and仃aditional techniques are limited in capturing their variable behavior.This leads to greater needs of new techniques and methodologies to properly quan tify the voltage stability of power systems.
基金partially supported by the National Natural Science Foundation of China (No.41230318)
文摘With the development of computational power, there has been an increased focus on data-fitting related seismic inversion techniques for high fidelity seismic velocity model and image, such as full-waveform inversion and least squares migration. However, though more advanced than conventional methods, these data fitting methods can be very expensive in terms of computational cost. Recently, various techniques to optimize these data-fitting seismic inversion problems have been implemented to cater for the industrial need for much improved efficiency. In this study, we propose a general stochastic conjugate gradient method for these data-fitting related inverse problems. We first prescribe the basic theory of our method and then give synthetic examples. Our numerical experiments illustrate the potential of this method for large-size seismic inversion application.
基金the State Administration of Science,Technology and Industry for National Defense of China(Grant No.B2420132001).
文摘The paper studies the parametric stochastic roll motion in the random waves.The differential equation of the ship parametric roll under random wave is established with considering the nonlinear damping and ship speed.Random sea surface is treated as a narrow-band stochastic process,and the stochastic parametric excitation is studied based on the effective wave theory.The nonlinear restored arm function obtained from the numerical simulation is expressed as the approximate analytic function.By using the stochastic averaging method,the differential equation of motion is transformed into Ito’s stochastic differential equation.The steady-state probability density function of roll motion is obtained,and the results are validated with the numerical simulation and model test.
基金the support of the National Natural Science Foundation of China(Grant Nos.11472067 and 51609034)the Science Foundation of Liaoning Province of China(No.2021-MS-119)+1 种基金the Dalian Youth Science and Technology Star Project(No.2018RQ06)the Fundamental Research Funds for the Central Universities(Grant No.DUT20GJ216).
文摘The difficulty in solving stochastic dynamics problems lies in the need for a large number of repeated computations of deterministic dynamic equations,which has been a challenge in stochastic dynamics analysis and was discussed in this study.To efficiently and accurately compute the exponential of the dynamics state matrix and the matrix functions due to external loads,an adaptively filtered precise integration method was proposed,which inherits the high precision of the precise integrationmethod,improves the computational efficiency and saves the memory required.Moreover,the perturbation method was introduced to avoid repeated computations of matrix exponential and terms due to external loads.Based on the filtering and perturbation techniques,an adaptively filtered precise integration method considering perturbation for stochastic dynamics problems was developed.Two numerical experiments,including a model of phononic crystal and a bridge model considering random parameters,were performed to test the performance of the proposed method in terms of accuracy and efficiency.Numerical results show that the accuracy and efficiency of the proposed method are better than those of the existing precise integration method,the Newmark-βmethod and the Wilson-θmethod.
文摘The stochastic boundary element method is developed to analyze elasticity problems with random material and/or geometrical parameters and ran- domly perturbed boundaries. Based on the first-order Taylor series expansion, the boundary integration equations concerning the mean and deviation of the displace- ments are derived, respectively. It is found that the randomness of material param- eters is equivalent to a random body force, so the mean and covariance matrices of unknown boundary displacements and tractions can be obtained. Furthermore, the mean and covariance of displacements and stresses at inner points can also be obtained. Numerical examples show that the proposed stochastic boundary element method gives satisfactory solutions, as compared with those obtained by theoretical analysis or other numerical methods.
基金funded by the National Natural Science Foundation of China (51678252)the Guangzhou Science and Technology Project (201804020069)
文摘Stochastic heat conduction and thermal stress analysis of structures has received considerable attention in recent years.The propagation of uncertain thermal environments will lead to stochastic variations in temperature fields and thermal stresses.Therefore,it is reasonable to consider the variability of thermal environments while conducting thermal analysis.However,for ambient thermal excitations,only stationary random processes have been investigated thus far.In this study,the highly efficient explicit time-domain method(ETDM)is proposed for the analysis of non-stationary stochastic transient heat conduction and thermal stress problems.The explicit time-domain expressions of thermal responses are first constructed for a thermoelastic body.Then the statistical moments of thermal displacements and stresses can be directly obtained based on the explicit expressions of thermal responses.A numerical example involving non-stationary stochastic internal heat generation rate is investigated.The accuracy and efficiency of the proposed method are validated by comparison with the Monte-Carlo simulation.
基金supported by the National Natural Science Foundation of China(6127312660904032)the Natural Science Foundation of Guangdong Province(10251064101000008)
文摘This paper develops the mean-square exponential input-to-state stability（exp-ISS） of the Euler-Maruyama（EM） method for stochastic delay control systems（SDCSs）.The definition of mean-square exp-ISS of numerical methods is established.The conditions of the exact and EM method for an SDCS with the property of mean-square exp-ISS are obtained without involving control Lyapunov functions or functional.Under the global Lipschitz coefficients and mean-square continuous measurable inputs,it is proved that the mean-square exp-ISS of an SDCS holds if and only if that of the EM method is preserved for a sufficiently small step size.The proposed results are evaluated by using numerical experiments to show their effectiveness.
文摘In this paper, the cubic and quintic diffusion equation under stochastic non homogeneity is solved using Wiener- Hermite expansion and perturbation (WHEP) technique, Homotopy perturbation method (HPM) and Pickard approximation technique. The analytic solution of the linear case is obtained using Eigenfunction expansion .The Picard approximation method is used to introduce the first and second order approximate solution for the non linear case. The WHEP technique is also used to obtain approximate solution under different orders and different corrections. The Homotopy perturbation method (HPM) is also used to obtain some approximation orders for mean and variance. Using mathematica-5, the methods of solution are illustrated through figures, comparisons among different methods and some parametric studies.
基金the Research and initiative center COVID-19-DES-2020-65,Prince Sultan University.
文摘Nonlinear stochastic modeling plays a significant role in disciplines such as psychology,finance,physical sciences,engineering,econometrics,and biological sciences.Dynamical consistency,positivity,and boundedness are fundamental properties of stochastic modeling.A stochastic coronavirus model is studied with techniques of transition probabilities and parametric perturbation.Well-known explicit methods such as Euler Maruyama,stochastic Euler,and stochastic Runge–Kutta are investigated for the stochastic model.Regrettably,the above essential properties are not restored by existing methods.Hence,there is a need to construct essential properties preserving the computational method.The non-standard approach of finite difference is examined to maintain the above basic features of the stochastic model.The comparison of the results of deterministic and stochastic models is also presented.Our proposed efficient computational method well preserves the essential properties of the model.Comparison and convergence analyses of the method are presented.
基金supported by the National Natural Science Foundation of China (Grant No. 50579090)the National Basic Research Program of China (973 Program, Grant No. 2007CB714102)National Science and Technology Support Program of China (Program for the Eleventh Five-Year Plan, Grant No. 2006BAB04A06)
文摘Owing to the fact that the conventional deterministic back analysis of the permeability coefficient cannot reflect the uncertainties of parameters, including the hydraulic head at the boundary, the permeability coefficient and measured hydraulic head, a stochastic back analysis taking consideration of uncertainties of parameters was performed using the generalized Bayesian method. Based on the stochastic finite element method （SFEM） for a seepage field, the variable metric algorithm and the generalized Bayesian method, formulas for stochastic back analysis of the permeability coefficient were derived. A case study of seepage analysis of a sluice foundation was performed to illustrate the proposed method. The results indicate that, with the generalized Bayesian method that considers the uncertainties of measured hydraulic head, the permeability coefficient and the hydraulic head at the boundary, both the mean and standard deviation of the permeability coefficient can be obtained and the standard deviation is less than that obtained by the conventional Bayesian method. Therefore, the present method is valid and applicable.
基金Supported by National Natural Science Foundation of China(10571036)the Key Discipline Development Program of Beijing Municipal Commission(XK100080537)
文摘This paper deals with the mean-square exponential input-to-state stability(exp-ISS)of Euler-Maruyama(EM)method applied to stochastic control systems(SCSs).The aim is to find out the conditions of the exact and EM method solutions to an SCS having the property of mean-square exp-ISS without involving control Lyapunov functions.Second moment boundedness and an appropriate form of strong convergence are achieved under global Lipschitz coeffcients and mean-square continuous random inputs.Under the strong convergent condition,it is shown that the mean-square exp-ISS of an SCS holds if and only if that of the EM method is preserved for suffciently small step size.
基金National Natural Science Foundations of China(Nos.11561028,11101101,11461032,11401267)Natural Science Foundations of Jiangxi Province,China(Nos.20151BAB201013,20151BAB201010,20151BAB201015)
文摘Positive results are proved here about the ability of balanced methods to reproduce the mean square stability of the impulsive stochastic differential equations. It is shown that the balanced methods with strong convergence can preserve the mean square stability with the sufficiently small stepsize. Weak variants and their mean square stability are also considered. Several numerical experiments are given for illustration and show that the fully implicit methods are superior to those of the explicit methods in terms of mean-square stabilities for relatively large stepsizes especially.
