Adaptive mesh refinement using piecewise-linear shape functions based on the blending function method

Use of quadrilateral elements for finite element mesh refinement can lead either to so-called irregular meshes or the necessity of adjustments between finer and coarser parts of the mesh necessary. In the case of irregular meshes, constraints have to be introduced in order to maintain continuity of the displacements. Introduction of finite elements based on blending function interpolation shape functions using piecewise boundary interpolation avoids these problems. This paper introduces an adaptive refinement procedure for these types of elements. The refinement is anh-method. Error estimation is performed using the Zienkiewicz-Zhu method. The refinement is controlled by a switching function representation. The method is applied to the plane stress problem. Numerical examples are given to show the efficiency of the methodology.     

Addressing spatiotemporal and computational heterogeneity in structured adaptive mesh refinement

Structured adaptive mesh refinement (SAMR) techniques can provide accurate and cost- effective solutions to realistic scientific and engineering simulations modeling complex physical phenomena. However, the adaptive nature and inherent space–time heterogeneity of SAMR applications result in significant runtime management challenges. Moreover, certain SAMR applications involving reactive flows exhibit pointwise varying workloads and cannot be addressed by traditional parallelization approaches, which assume homogeneous loads. This paper presents hierarchical partitioning, bin-packing based load balancing, and Dispatch structured partitioning strategies to manage the spatiotemporal and computational heterogeneity in SAMR applications. Experimental evaluation of these schemes using 3-D Richtmyer–Meshkov compressible turbulence and 2-D reactive-diffusion kernels demonstrates the improvement in overall performance.     

Structured mesh generation by kriging with local refinement with a new elliptic scheme

Accurate results in finite element analysis are strongly related to mesh quality. In this paper, an automatic quadrilateral mesh generation methodology using kriging interpolation is described, a quality mesh study is conducted, and the development of a new local refinement scheme, called the elliptic scheme, is presented. The new elliptic refinement scheme is evaluated using four standard structural cases, and it is shown that it compares very well with octree-based refinement schemes and other local refinement methods.     

Development of a parallel Poisson's equation solver with adaptive mesh refinement and its application in field emission prediction

A parallel electrostatic Poisson's equation solver coupled with parallel adaptive mesh refinement (PAMR) is developed in this paper. The three-dimensional Poisson's equation is discretized using the Galerkin finite element method using a tetrahedral mesh. The resulting matrix equation is then solved through the parallel conjugate gradient method using the non-overlapping subdomain-by-subdomain scheme. A PAMR module is coupled with this parallel Poisson's equation solver to adaptively refine the mesh where the variation of potentials is large. The parallel performance of the parallel Poisson's equation is studied by simulating the potential distribution of a CNT-based triode-type field emitter. Results with ∼100 000 nodes show that a parallel efficiency of 84.2% is achieved in 32 processors of a PC-cluster system. The field emission properties of a single CNT triode- and tetrode-type field emitter in a periodic cell are computed to demonstrate their potential application in field emission prediction.     

Multi-scale gas discharge simulations using asynchronous adaptive mesh refinement

The breakdown of a gas gap at high products of pd (pressure × distance) is a multi-scale phenomenon in both time and space. This is especially true when the plasma is interacting with a gas flow, a problem of considerable recent interest in the context of aerodynamic applications of surface discharges. This paper presents a contribution to the numerical modeling of such discharges. We describe here a new approach for adaptive meshing which is suitable for use with the explicit asynchronous integration scheme described in our previous publication. Rather than relying on a family of nested grids as is commonly done, this technique is based on a single unstructured mesh with possible non-conforming cells at the interface between coarse and fine areas. Substantial computational time saving has been achieved for a surface dielectric barrier discharge configuration of the kind proposed as plasma actuators for flow control.     

Enabling scalable parallel implementations of structured adaptive mesh refinement applications

Parallel implementations of dynamic structured adaptive mesh refinement (SAMR) methods lead to significant runtime management challenges that can limit their scalability on large systems. This paper presents a runtime engine that addresses the scalability of SAMR applications with localized refinements and high SAMR efficiencies on large numbers of processors (upto 1024 processors). The SAMR runtime engine augments hierarchical partitioning with bin-packing based load-balancing to manage the space-time heterogeneity of the SAMR grid hierarchy, and includes a communication substrate that optimizes the use of MPI non-blocking communication primitives. An experimental evaluation on the IBM SP2 supercomputer using the 3-D Richtmyer-Meshkov compressible turbulence kernel demonstrates the effectiveness of the runtime engine in improving SAMR scalability.

An implicit gas-kinetic scheme for turbulent flow on unstructured hybrid mesh

In this study, an implicit scheme for the gas-kinetic scheme (GKS) on the unstructured hybrid mesh is proposed. The Spalart–Allmaras (SA) one equation turbulence model is incorporated into the implicit gas-kinetic scheme (IGKS) to predict the effects of turbulence. The implicit macroscopic governing equations are constructed and solved by the matrix-free lower-upper symmetric-Gauss–Seidel (LU-SGS) method. To reduce the number of cells and computational cost, the hybrid mesh is applied. A modified non-manifold hybrid mesh data(NHMD) is used for both unstructured hybrid mesh and uniform grid. Numerical investigations are performed on different 2D laminar and turbulent flows. The convergence property and the computational efficiency of the present IGKS method are investigated. Much better performance is obtained compared with the standard explicit gas-kinetic scheme. Also, our numerical results are found to be in good agreement with experiment data and other numerical solutions, demonstrating the good applicability and high efficiency of the present IGKS for the simulations of laminar and turbulent flows.     

Parallel computation of unsteady three-dimensional incompressible viscous flow using an unstructured multigrid method

The development and validation of a parallel unstructured tetrahedral non-nested multigrid (MG) method for simulation of unsteady 3D incompressible viscous flow is presented. The Navier-Stokes solver is based on the artificial compressibility method (ACM) and a higher-order characteristics-based finite-volume scheme on unstructured MG. Unsteady flow is calculated with an implicit dual time stepping scheme. The parallelization of the solver is achieved by a MG domain decomposition approach (MG-DD), using the Single Program Multiple Data (SPMD) programming paradigm. The Message-Passing Interface (MPI) Library is used for communication of data and loop arrays are decomposed using the OpenMP standard. The parallel codes using single grid and MG are used to simulate steady and unsteady incompressible viscous flows for a 3D lid-driven cavity flow for validation and performance evaluation purposes. The speedups and efficiencies obtained by both the parallel single grid and MG solvers are reasonably good for all test cases, using up to 32 processors on the SGI Origin 3400. The parallel results obtained agree well with those of serial solvers and with numerical solutions obtained by other researchers, as well as experimental measurements.     

Finite element simulation of stretch forging using a mesh condensation method

In order to reduce the computation time of finite element simulations of stretch forging process,a mesh condensation method is presented and applied to a three-dimensional rigid-viscoplastic finite element program.In this method,a conventional mesh for the whole zone of a workpiece is condensed to a computational mesh for the active deformation zone.Two vital problems are solved,which are automatic construction of the computational mesh and treatment of interfaces between the deformation zone and the rigid ...     

Automatic hexahedral mesh generation for multi-domain composite models using a hybrid projective grid-based method

This paper presents an algorithm to generate an all-hexahedral mesh of a multi-domain solid model using a hybrid grid-based approach. This is based on a projective concept during the boundary adaptation of the initial mesh. In general, the algorithm involves the generation of a grid structure, which is superimposed on the solid model. This grid structure forms an initial mesh consisting of hexahedral elements, which intersect fully or partially with the solid model. This initial mesh is then shrunk in an outside-in manner to the faces of the model through a node projection process using the closest position approach. To match the resulting mesh to the edges of the model, a minimal deformation angle method is used. Finally, to match the vertices with the nodes on the mesh, a minimal warp angle method is employed. To create the mesh of a multi-domain solid model, an outside-in and inside-in hybrid of the grid-based method is used. This hybrid method ensures that the meshes of the different domains are conforming at their common boundary. This paper also describes two methods for resolving cases of degenerate elements: a splitting technique and a wedge insertion technique.     

Pricing high-dimensional Bermudan options using the stochastic grid method

This paper considers the problem of pricing options with early-exercise features whose pay-off depends on several sources of uncertainty. We propose a stochastic grid method for estimating the optimal exercise policy and use this policy to obtain a low-biased estimator for high-dimensional Bermudan options. The method has elements of the least-squares method (LSM) of Longstaff and Schwartz [Valuing American options by simulation: A simple least-squares approach, Rev. Finan. Stud. 3 (2001), pp. 113–147], the stochastic mesh method of Broadie and Glasserman [A stochastic mesh method for pricing high-dimensional American option, J. Comput. Finance 7 (2004), pp. 35–72], and stratified state aggregation along the pay-off method of Barraquand and Martineau [Numerical valuation of high-dimensional multivariate American securities, J. Financ. Quant. Anal. 30 (1995), pp. 383–405], with certain distinct advantages over the existing methods. We focus on the numerical results for high-dimensional problems such as max option and arithmetic basket option on several assets, with basic error analysis for a general one-dimensional problem.     

Optimal route selection based on Monte Carlo method and adaptive amoeba algorithm under uncertain environment

The fuzzy optimal path under uncertainty is one of the basic network optimization problems. Considering the uncertain environment, many fuzzy numbers are used to represent the edge weights, such as interval number and triangular fuzzy number. Then, these fuzzy numbers are converted to real numbers directly. This converting makes the optimal path the shortest path selection problem. However, much information of uncertainty get lost when converting fuzzy numbers to real numbers. In order to ensure all the origan data complete, in this paper, a fuzzy optimal path solving model based on the Monte Carlo method and adaptive amoeba algorithm is proposed. In Monte Carlo process, a random number which belongs to the fuzzy number is generated. Then, Physarum polycephalum algorithm is used to solve the shortest path every time and record the result. After many times calculation, many shortest paths have been found and recorded. At last, by analysing the characters of all the results, the optimal path can be selected. Several numerical examples are given to illustrate the effectiveness of the proposed method, the results show that the proposed method can deal with the fuzzy optimal path problems effectively.     

On the binomial confidence interval and probabilistic robust control

The Clopper-Pearson confidence interval has ever been documented as an exact approach in some statistics literature. More recently, such approach of interval estimation has been introduced to probabilistic control theory and has been referred as non-conservative in control community. In this note, we clarify the fact that the so-called exact approach is actually conservative. In particular, we derive analytic results demonstrating the extent of conservatism in the context of probabilistic robustness analysis. This investigation encourages seeking better methods of confidence interval construction for robust control purpose.     

Monte Carlo方法与计算机模拟应用研究

介绍了Monte Carlo方法,提出其在模拟Buffer问题时存在的一个问题,并给出改进的方法;提出了用Monte Carlo方法产生任意分布随机变量的原理及方法,并对Beta分布和标准正态分布随机变量进行了计算机模拟和效果检验。     

Numerical simulation of detonation using an adaptive Cartesian cut-cell method combined with a cell-merging technique

A second-order accurate scheme for the Cartesian cut-cell method developed previously by the authors [Ji H, Lien F-S, Yee E. Comput. Methods Appl. Mech. Eng. 198 (2008), 432] is generalized for application to both two- and three-dimensional inviscid compressible flow problems. A cell-merging approach is used to address the so-called “small cell” problem that has plagued Cartesian cut-cell methods. In the present cell-merging approach, the conservative variables are stored at the cut-cell centroid (including the non-merged and merged cut-cells) rather than at the Cartesian cell center. Although this approach results in a more complicated search algorithm for the determination of the neighbor cells (required for the computation of the spatial gradients of the conservative variables), this approach enables the straightforward formulation of a higher than first-order accurate discretization scheme in the vicinity of the (complex and irregular) internal boundaries of the flow domain. Six test cases (including detonation problems) are used to demonstrate the accuracy and capability of the adaptive cut-cell method, for which both mesh refinement and derefinement techniques are employed in the case of an unsteady shock diffraction problem.     

应用Monte Carlo方法对GaN基微型核电池的研究

应用Monte Carlo方法,建立了电子入射到半导体材料中的路径模型.基于此模型进行仿真,可以得到电子在半导体材料中的穿透深度和能量分布.对以同位素Ni-63为放射源的GaN基PN结微型核电池进行Monte Carlo分析,得出入射电子在GaN中的穿透路径和能量分布,以确定入射电子在GaN中能量最集中的位置,将GaN基PN结的结深设置在该位置可以大幅提高收集效率,进而提高输出功率与能量转换效率.实验中,分别制备了结深为1000,450 nm,放射源为Ni-63的GaN基微型核电池,测试结果验证了经优化结深为450 nm的微型核电池其电学输出性能有明显提高,能量转换效率达到了1.47％,输出功率达到了微瓦级.该结果可以为GaN基微型核电池的设计与制造提供有效的参考依据.     

Computation of complex turbulent flow using matrix-free implicit dual time-stepping scheme and LRN turbulence model on unstructured grids

In this study, a matrix-free implicit dual time-stepping method has been developed. It is implemented, together with a low-Reynolds-number q-ω turbulence model, in a high-order upwind finite-volume solver on unstructured grids. Semi-implicit treatment of the source terms of the q and ω equations is also introduced to further stabilize the numerical solution. It has been found that these techniques provide strong stabilization in the computation of a supersonic flow with complex shock-boundary-layer interactions in a channel with a backward-facing step. The proposed method has a low-memory overhead, similar to an explicit scheme, while it shows good stability and computational efficiency as an implicit scheme. The method developed has been validated by comparing the computed results with the corresponding experimental measurements and other calculated results, which shows good agreement. Research is being done to extend the method to calculate unsteady turbulent flows.     

An interative learning control scheme using the weighted least-squares method

An iterative learning control scheme is described for linear discrete-time systems. A weighted least-squares criterion of learning error is optimized to obtain a unique control gain for a case when the number of sampling is relatively small. It is then shown that algorithmic convergence can be readily guaranteed, because the present learning rule consists of a steady-state Kalman filter. By paying attention to the sparse system structure for the system's impulse response model, we further derive a suboptimal iterative learning control for a practical case when the number of sampling is large.