Implementation of a transient adaptive sub-cell module for the parallel-DSMC code using unstructured grids

A method of transient adaptive sub-cells (TAS) suitable for unstructured grids that is modified from the existing one for the structured grids of DSMC is introduced. The TAS algorithm is implemented within the framework of a parallelized DSMC code (PDSC). Benchmarking tests are conducted for steady driven cavity flow, steady hypersonic flow over a two-dimensional cylinder, steady hypersonic flow over a cylinder/flare and the unsteady vortex shedding behind a two-dimensional cylinder. The use of TAS enables a reduction in the computational expense of the simulation since larger sampling cells and less simulation particles can be employed. Furthermore, the collision quality of the simulation is maintained or improved and the preservation of property gradients and vorticity at the scale of the sub-cells enables correct unsteady vortex shedding frequencies to be predicted. The use of TAS in a parallel-DSMC code allows simulations of unsteady processes at a level to be carried out efficiently, accurately and with acceptable computational time.     

Investigation of flow around a pair of side-by-side square cylinders using the lattice Boltzmann method

The low-Reynolds number flow around two square cylinders placed side-by-side is investigated using the lattice Boltzmann method (LBM). The effects of the gap ratio s/d (s is the separation between the cylinders and d is the characteristic dimension) on the flow are studied. These simulations reveal the existence of regimes with either synchronized or non-synchronized vortex-shedding, with transition occurring at s/d ≈ 2, which is larger than for circular cylinders. Detailed results are presented at Re = 73 for s/d = 2.5 and 0.7 corresponding to the synchronized and flip-flop regimes, respectively. Vortex-shedding from the cylinder occurs either in-phase or in-antiphase in the synchronized regime. However, linear stochastic estimate (LSE) calculations show that in-phase locking is the predominant mode. LSE is also employed to educe the underlying modes in the flip-flop regime, where evidence for both in-phase and anti-phase locked vortices is found, indicating that this regime is in a quasi-stable state between these two modes. The merging of the wakes, which is gradual for the synchronized regime, occurs rapidly in the flip-flop regime. The mean pressure on the upstream surface is symmetric and asymmetric for the synchronized and flip-flop regimes, respectively. Differences in results between the two regimes are interpreted in terms of the interaction of the jet formed between the cylinders with the adjoining wakes, the strength of this interaction depending on the spacing.     

Numerical simulation of the transonic turbulent flow around a wedge-shaped body with a backward-facing step

A fully three-dimensional near-wall complex turbulent flow around a wedge-shaped body with a backward-facing step is considered with the transonic flow regime (Mach number M = 0.913) at the Reynolds number Re = 7.2 × 10⁶. The technology of the numerical simulation of problems of the class under study is represented in detail. A series of preliminary auxiliary calculations is carried out for choosing the optimal computational algorithm. The numerical results of the problem simulation based on the eddy-resolving hybrid RANS-LES approach IDDES are finally given for the full configuration. The validity of the results obtained is confirmed by comparing them to the corresponding experimental data.     

韩国科学技术卫星二号主载荷-双频微波辐射计

双频微波辐射计是韩国科学技术卫星二号的主载荷,目前已完成了正样研制并交付韩国。双频微波辐射计是全功率形式的微波辐射计,星上采用两点定标方式。由于受卫星平台的限制,天线不能做得很大并进行扫描,因此选择了接收机定标的方案,即定标支路和观测支路采用了不同的天线,通过多路开关与接收机连接。系统及验收测试表明,双频微波辐射计满足韩方的各项功能和性能指标要求。介绍了韩国科学技术卫星二号的基本情况以及双频微波辐射计的设计方案。给出了主要指标和系统试验结果。     

A hybrid meta heuristic algorithm for bi-objective minimum cost flow (BMCF) problem

In this paper we study the bi-objective minimum cost flow (BMCF) problem which can be categorized as multi objective minimum cost flow problems. Generally, the exact computation of the efficient frontier is intractable and there may exist an exponential number of extreme non-dominated objective vectors. Hence, it is better to employ an approximate method to compute solutions within reasonable time. Therefore, we propose a hybrid meta heuristic algorithm (memetic algorithm hybridized with simulated annealing MA/SA) to develop an efficient approach for solving this problem. In order to show the efficiency of the proposed MA/SA some problems have been generated and solved by both the MA/SA and an exact method. It is perceived from this evaluation that the proposed MA/SA outputs are very close to the exact solutions. It is shown that when the number of arcs and nodes exceed 30 (large problems) the MA/SA model will be more preferred because of its strongly shorter computational time in comparison with exact methods.     

Two-level refined direct optimization scheme using intermediate surrogate models for electromagnetic optimization of a switched reluctance motor

Electromagnetic optimization procedures require a large number of evaluations in numerical forward models. These computer models simulate complex problems through the use of numerical techniques, e.g. finite elements. Hence, the evaluations need a large computational time. Two-level methods such as space mapping have been developed that include a second model so as to accelerate the inverse procedures. Contrary to existing two-level methods, we propose a scheme that enables acceleration when the second model is based on the initial numerical model with coarse discretizations. This paper validates the proposed refined direct optimization method onto algebraic test functions. Moreover, we applied the methodology onto the geometrical optimization of the magnetic circuit of a switched reluctance motor. The obtained numerical results show the efficiency of the optimization algorithm with respect to the computational time and the accuracy.     

Numerical investigations on dynamic stall of low Reynolds number flow around oscillating airfoils

This paper presents a 2D computational investigation on the dynamic stall phenomenon associated with unsteady flow around the NACA0012 airfoil at low Reynolds number (Re_c ≈ 10⁵). Two sets of oscillating patterns with different frequencies, mean oscillating angles and amplitudes are numerically simulated using Computational Fluid Dynamics (CFD), and the results obtained are validated against the corresponding published experimental data. It is concluded that the CFD prediction captures well the vortex-shedding predominated flow structure which is experimentally obtained and the results quantitatively agree well with the experimental data, except when the blade is at a very high angle of attack.     

Multidisciplinary Simulation of the Maneuvering of an Aircraft

A computational methodology for the simulation of the transient aeroelastic response of an unrestrained and flexible aircraft during high-G maneuvers is presented. The key components of this methodology are: (a) a three-field formulation for coupled fluid/structure interaction problems; (b) a second-order time-accurate and geometrically conservative flow solver for CFD computations on unstructured dynamic meshes; (c) a corotational finite element method for the solution of geometrically nonlinear and unrestrained structural dynamics problems; (d) a robust method for updating an unrestrained and unstructured moving fluid mesh; and (e) a second-order time-accurate staggered algorithm for time-integrating the coupled fluid/structure semi-discrete equations of motion. This computational methodology is illustrated with the simulation on a parallel processor of several three-dimensional high-G pullup maneuvers of the Langley Fighter in the transonic regime, using a detailed finite element aeroelastic model.     

公路清扫车集尘系统仿真设计与优化

运用计算流体力学技术对高速公路清扫车集尘系统的流场进行了仿真分析与结构改进。仿真采用有限体积法FVM,利用非结构化网格对集尘箱模型进行网格划分,采用k-ε湍流双方程模型模拟湍流流动。分析不同的集尘箱设计方案对灰尘沉降效率的影响,经过一系列优化,最后得到一个优化的设计方案。新集尘箱延长了气流在集尘箱内的停留时间,降低了靠近底部位置的气流速度,有利于垃圾的沉降与堆积,达到了实际设计要求,为开发具有自主知识产权高效率的公路清扫车做出了重要贡献。     

On time bounds, the work-time scheduling principle, and optimalityfor BSR

Constant time solutions for many applications have been obtained on BSR, but some theoretical problems on BSR (broadcasting with selective reduction) that raised when BSR was proposed have not been solved. Three of them are: 1) No lower bound for any problem on BSR is known except trivial constant time, 2) is there any improvement with nonconstant BSR time but still better than the lower bound for CRCW?, and 3) how to characterize problems for which BSR achieves constant time performance. In this paper, we have solved these three problems. For Problem 1, a lower bound on BSR is shown for any computational problem with an optimal sequential solution. An efficient sorting algorithm answers the second problem. A necessary condition is given for the third problem. The work-time (WT) scheduling principle and optimality for BSR are also introduced for investigating the BSR performance when the number of processors available, p, is different from the input size, n, of problems     

Using sampled information: is it enough for the sparse matrix–vector product locality optimization?

One of the main factors that affect the performance of the sparse matrix–vector product (SpMV) is the low data reuse caused by the irregular and indirect memory access patterns. Different strategies to deal with this problem such as data reordering techniques have been proposed. The computational cost of these techniques is typically high because they consider all the nonzeros of the sparse matrix in order to find an appropriate permutation of rows and columns that improves the SpMV performance. In this paper, we analyze the possibility of increasing the locality of the SpMV using incomplete information in the reordering process. This partial information comes as a consequence of considering only a subset of the nonzero elements of the matrix. These nonzeros are obtained from the original matrix through a sampling process. In particular, two different sampling methods have been considered: a random sampling and an event‐based sampling using hardware counters. We have detected that a small number of samples is enough to obtain quality reorderings. As a consequence, using sampling‐based reorderings leads to noticeable performance improvements with respect to the non‐reordered matrices, reaching speedup values up to 2.1 × . In addition, an important reduction in the computational time required by the reordering technique has been observed. Copyright © 2012 John Wiley & Sons, Ltd.     

Using a parallelized MCMC algorithm in R to identify appropriate likelihood functions for SWAT

Markov Chain Monte Carlo (MCMC) algorithms allow the analysis of parameter uncertainty. This analysis can inform the choice of appropriate likelihood functions, thereby advancing hydrologic modeling with improved parameter and quantity estimates and more reliable assessment of uncertainty. For long-running models, the Differential Evolution Adaptive Metropolis (DREAM) algorithm offers spectacular reductions in time required for MCMC analysis. This is partly due to multiple parameter sets being evaluated simultaneously. The ability to use this feature is hindered in models that have a large number of input files, such as SWAT. A conceptually simple, robust method for applying DREAM to SWAT in R is provided. The general approach is transferrable to any executable that reads input files. We provide this approach to reduce barriers to the use of MCMC algorithms and to promote the development of appropriate likelihood functions.     

基于多班教学优化的多目标分布式混合流水车间调度

单工厂环境下的混合流水车间调度问题已受到广泛关注,而多工厂环境下的分布式混合流水车间调度问题(distributed hybrid flow shop scheduling problem,DHFSP)研究进展则较小.针对考虑顺序相关准备时间的DHFSP,提出一种多班教学优化(multi-class teaching-...     

Solving for a quadratic programming with a quadratic constraint based on a neural network frame

In many applications, a class of optimization problems called quadratic programming with a special quadratic constraint (QPQC) often occurs, such as in the fields of maximum entropy spectral estimation, FIR filter design with time–frequency constraint and design of an FIR filter bank with perfect reconstruction property. In order to deal with this kind of optimization problems and be inspired by the computational virtue of analog or dynamic neural networks, a feedback neural network is proposed for solving for this class of QPQC computation problems in real time in this paper. The stability, convergence and computational performance of the proposed neural network have also been analyzed and proved in detail so as to theoretically guarantee the computational effectiveness and capability of the network. From the theoretical analyses it turns out that the solution of a QPQC problem is just the generalized minimum eigenvector of the objective matrix with respect to the constrained matrix. A number of simulation experiments have been given to further support our theoretical analysis and illustrate the computational performance of the proposed network.     

A multi-criteria trajectory-based parameter sampling strategy for the screening method of elementary effects

Environmental models are inherently complex and often characterized by high dimensionality. The method of elementary effects (EE) is one of the most widely used parameter screening technique implemented to reduce burden on computational resources required for thorough model evaluation. Due to issues like inefficient screening and excessive sampling time, the development of more effective EE sampling strategies has been a recent research focus. This paper presents a new sampling strategy - Sampling for Uniformity (SU) – based on the principles of meeting close-to-theoretical parameter distributions and maximizing trajectory spread. The performance of the SU relative to existing strategies was evaluated using a number of criteria including generated parameter distributions' uniformity, time efficiency, trajectory spread, and screening efficiency. The SU performed better than some trajectory-based benchmark strategies across the evaluation criteria, underlining the effectiveness of multi-criteria based sampling and the need to focus future efforts on exploring other combinations of sampling criteria.     

Genetic algorithms applied to the continuous flow shop problem

This research develops an approach for applying Genetic Algorithms (GA) to scheduling problems. We generate a GA based heuristic for continuous flow shop problems with total flow time as the criterion. The effects of several crucial factors of GA on the performance of the heuristic for the problem are explored in detail. The computational experience of heuristic provides several observations of the application of GA, and strongly supports that the applications of GA are problem specific. The computational experience also shows that GA can be good techniques for scheduling problems.     

Separation-bubble flow solution using Euler/Navier-Stokes zonal approach with downstream compatibility conditions

An Euler/Navier-Stokes zonal scheme is developed to numerically simulate the two-dimensional flow over a blunt leading-edge plate. The computational domain has been divided into inner and outer regions where the Navier-Stokes and Euler equations are used, respectively. On the downstream boundary, compatibility conditions derived from the boundary-layer equations are used. The grid is generated by using conformal mapping and the problem is solved by using a compressible Navier-Stokes code, which has been modified to treat Euler and Navier-Stokes regions. The accuracy of the solution is determined by the reattachment location. Bench-mark solutions have been obtained using the Navier-Stokes equations throughout the optimum computational domain and size. The problem is recalculated with sucessive decrease of the computational domain from the downstream side where the compatibility conditions are used, and with successive decrease of the Navier-Stokes computational region. The results of the zonal scheme are in excellent agreement with those of the benchmark solutions and the experimental data. The CPU time saving is about 15%.     

Calibrating a forest landscape model to simulate frequent fire in Mediterranean-type shrublands

In Mediterranean-type ecosystems (MTEs), fire disturbance influences the distribution of most plant communities, and altered fire regimes may be more important than climate factors in shaping future MTE vegetation dynamics. Models that simulate the high-frequency fire and post-fire response strategies characteristic of these regions will be important tools for evaluating potential landscape change scenarios. However, few existing models have been designed to simulate these properties over long time frames and broad spatial scales. We refined a landscape disturbance and succession (LANDIS) model to operate on an annual time step and to simulate altered fire regimes in a southern California Mediterranean landscape. After developing a comprehensive set of spatial and non-spatial variables and parameters, we calibrated the model to simulate very high fire frequencies and evaluated the simulations under several parameter scenarios representing hypotheses about system dynamics. The goal was to ensure that observed model behavior would simulate the specified fire regime parameters, and that the predictions were reasonable based on current understanding of community dynamics in the region. After calibration, the two dominant plant functional types responded realistically to different fire regime scenarios. Therefore, this model offers a new alternative for simulating altered fire regimes in MTE landscapes.     

An algorithm for sampling subsets of H/sub /spl infin// with applications to risk-adjusted performance analysis and model (in)validation

In spite of their potential to reduce computational complexity, the use of probabilistic methods in robust control has been mostly limited to parametric uncertainty, since the problem of sampling causal bounded operators is largely open. In this note, we take steps toward removing this limitation by proposing a computationally efficient algorithm aimed at uniformly sampling suitably chosen subsets of H/sub /spl infin//. As we show in the note, samples taken from these sets can be used to carry out model (in)validation and robust performance analysis in the presence of structured dynamic linear time-invariant uncertainty, problems known to be NP-hard in the number of uncertainty blocks.