The stochastic simulation method, based on the concept of control window and the numerical solution of the Langevin equation, is applied to solve the deposition problem of particles from the flowing suspensions onto a...The stochastic simulation method, based on the concept of control window and the numerical solution of the Langevin equation, is applied to solve the deposition problem of particles from the flowing suspensions onto a fiber collector. Using the Kuwabara model to characterize the flow field, the effects of Stokes number, interception parameter, packing density, particle size distribution on the collection efficioncy, and the deposition morphology of particles onto a collector are i examined. The morphology of deposit obtained in the simulated results agrees Well with experimental observations. The estimation of the initial coUection efficiency through the simulations considers that the deposited particles are in good agreement with published experimental data. In addition, the collection efficiency of particles increases in a wider particle size distribution region.展开更多
For the structure system with epistemic and aleatory uncertainties,a new state dependent parameter(SDP) based method is presented for obtaining the importance measures of the epistemic uncertainties.By use of the marg...For the structure system with epistemic and aleatory uncertainties,a new state dependent parameter(SDP) based method is presented for obtaining the importance measures of the epistemic uncertainties.By use of the marginal probability density function(PDF) of the epistemic variable and the conditional PDF of the aleatory one at the fixed epistemic variable,the epistemic and aleatory uncertainties are propagated to the response of the structure firstly in the presented method.And the computational model for calculating the importance measures of the epistemic variables is established.For solving the computational model,the high efficient SDP method is applied to estimating the first order high dimensional model representation(HDMR) to obtain the importance measures.Compared with the direct Monte Carlo method,the presented method can considerably improve computational efficiency with acceptable precision.The presented method has wider applicability compared with the existing approximation method,because it is suitable not only for the linear response functions,but also for nonlinear response functions.Several examples are used to demonstrate the advantages of the presented method.展开更多
基金Shanghai Leading Academic Discipline Project,China(No.B604)
文摘The stochastic simulation method, based on the concept of control window and the numerical solution of the Langevin equation, is applied to solve the deposition problem of particles from the flowing suspensions onto a fiber collector. Using the Kuwabara model to characterize the flow field, the effects of Stokes number, interception parameter, packing density, particle size distribution on the collection efficioncy, and the deposition morphology of particles onto a collector are i examined. The morphology of deposit obtained in the simulated results agrees Well with experimental observations. The estimation of the initial coUection efficiency through the simulations considers that the deposited particles are in good agreement with published experimental data. In addition, the collection efficiency of particles increases in a wider particle size distribution region.
基金supported by the National Natural Science Foundation of China (Grant No. 51175425)the Aviation Science Foundation (Grant No.2011ZA53015)the Doctorate Foundation of Northwestern Polytechnical University (Grant No. CX201205)
文摘For the structure system with epistemic and aleatory uncertainties,a new state dependent parameter(SDP) based method is presented for obtaining the importance measures of the epistemic uncertainties.By use of the marginal probability density function(PDF) of the epistemic variable and the conditional PDF of the aleatory one at the fixed epistemic variable,the epistemic and aleatory uncertainties are propagated to the response of the structure firstly in the presented method.And the computational model for calculating the importance measures of the epistemic variables is established.For solving the computational model,the high efficient SDP method is applied to estimating the first order high dimensional model representation(HDMR) to obtain the importance measures.Compared with the direct Monte Carlo method,the presented method can considerably improve computational efficiency with acceptable precision.The presented method has wider applicability compared with the existing approximation method,because it is suitable not only for the linear response functions,but also for nonlinear response functions.Several examples are used to demonstrate the advantages of the presented method.
