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With the spread of the Internet and a large number of network users, the problem of congestion on the network has arisen. This paper presents a strategy to reduce network congestion using clustering algorithms, K-means, and shortest path algorithms. The paper aims to solve the problems of congestion control, access to quality of service, reduce time wasted when sending and receiving network users, take advantage of network devices, and provide quality of service without data loss. The results of the proposed system simulation showed its effectiveness and accuracy through the simulation of the system. [ABSTRACT FROM AUTHOR]

The paper deals with the description of GNSS-INS simulator used for testing algorithms of the airborne gravimetry. At first, some specifications of the simulator are presented. Then the basic principles, models, algorithms used in the GNSS-INS simulator are described. The next part of the article concerns the usage of the simulator for testing algorithms of the airborne vector gravimetry. Some simulation results conclude the paper. [ABSTRACT FROM AUTHOR]

This paper is aimed to discuss modeling, construction and development of navigation algorithm of a two wheeled self balancing mobile robot in an enclosure. In this paper, we have discussed the design of two of the main controller algorithms, namely PID algorithms, on the robot model. Simulation is performed in the SIMULINK environment. The controller is developed primarily for self-balancing of the robot and also it's positioning. As for the navigation in an enclosure, template matching algorithm is proposed for precise measurement of the robot position. The navigation system needs to be calibrated before navigation process starts. Almost all of the earlier template matching algorithms that can be found in the open literature can only trace the robot. But the proposed algorithm here can also locate the position of other objects in an enclosure, like furniture, tables etc. This will enable the robot to know the exact location of every stationary object in the enclosure. Moreover, some additional features, such as Speech Recognition and Object Detection, are added. For Object Detection, the single board Computer Raspberry Pi is used. The system is programmed to analyze images captured via the camera, which are then processed through background subtraction, followed by active noise reduction. [ABSTRACT FROM AUTHOR]

This paper summarizes the collaborative work done by CENER, Fraunhofer ISE and CRS4 within the scope of the STAGE-STE project related to heliostat field generation algorithms and their application to small heliostats (<10 m²). Radially staggered heliostat field layouts have been commonly applied to real solar fields with known results. However, their use in conjunction with small heliostats or the use of brand new ways for heliostat allocation, such natural pattern based algorithms, is still unknown. Herein, the most promising heliostat field generation algorithms are studied and compared, in annual optical efficiency terms, for different scenarios. These efficiencies correspond to the best heliostat layouts found by the optimization process that each generation algorithm can create, for three scenarios. Results show that the fields from the selected algorithms lead to similar optical efficiencies. The slight differences are not enough evidence to nominate one of the algorithms as the best choice, taking into account the inherent error of the simulation tools, the optimization process and further requirements needed in commercial applications (e.g. access paths) not coped in this study. [ABSTRACT FROM AUTHOR]

Model predictive control (MPC) is the class of advanced control techniques. A primary advantage to this approach is the explicit handling of constraints. MPC utilizes an internal model to predict system dynamic behaviour over a finite horizon. MPC is a discrete-time form of control, so inaccuracies in predicted behavior are corrected at the next control interval. This technique makes the control of processes to become more efficient and cost effective. Most of its applications are in the refining, petrochemical industries and in other chemical plants. Dynamic Matrix Control(DMC) is a kind of model predictive control technique based on step response model of the process. In this paper, the dynamic matrix control algorithm is implemented on coupled tank system and control quality has been analyzed using a simulation model with different setting parameters. From the simulation results it has been observed that dynamic matrix control algorithm can achieve good results with accuracy. [ABSTRACT FROM AUTHOR]

The paper studies the effect of frictional pretreatment on the change in the properties of the surface layer of austenitic stainless steel subsequently subjected to low-temperature ionic nitriding in electron beam plasma. Under friction-force loading, near the specimen surface there appear residual compressive stresses changing the stress state in the gradient surface layer. Two mathematical models of the process of ion nitriding have been constructed, which take into consideration the effect of residual stresses with a constant diffusion coefficient. Besides, one of the models considers the effect of internal compressive stresses arising in the surface layer during the process of nitriding. Algorithms based on the boundary element method (BEM) are proposed for solving boundary value problems. Model examples illustrating the work of the algorithms have been solved. [ABSTRACT FROM AUTHOR]

The new integral-field spectrograph MUSE will acquire hyperspectral images of the deep sky, requiring huge amounts of raw data to be processed, posing a challenge to modern algorithms and technologies. In order to achieve the required sensitivity to observe very faint objects, many observations need to be reconstructed and co-added into a single data cube. In this paper, we propose a new fusion method to combine all raw observations while removing most of the instrumental and observational artifacts such as blur or cosmic rays. Thus, the results can be accurately and consistently analyzed by astronomers. We use a Bayesian framework allowing for optimal data fusion and uncertainty estimation. The knowledge of the instrument allows to write the direct problem (data acquisition on the detector matrix) and then to invert it through Bayesian inference, assuming a smoothness prior for the data cube to be reconstructed. Compared to existing methods, the originality of the new technique is in the propagation of errors throughout the fusion pipeline and the ability to deal with various acquisition parameters for each input image. For this paper, we focus on small-size, simulated astronomical observations with varying parameters to validate the image formation model, the reconstruction algorithm and the predicted uncertainties. [ABSTRACT FROM AUTHOR]

This paper describes a simulation system according to improve steelmaking's efficiency and to monitor its performances by anticipating the next period workload. Usually the production planning in those cases is made by the use of Gantt diagrams, based on operator's work. This means that if an accident occurs, the operator himself has to change in few minutes the production plan with a lower performance than the original one. The first consideration is obviously that the operator's experience itself it's not sufficient to re-plan a performing steelmaking chain. Hence the necessity of simulation as problem-solving technique in this complex situation. A brief introduction on this paper is devoted to identify the common problems in most plants about production planning, and this is indeed needed to define the boundary conditions and the framework of the problem. Then, a description of steelmaking processes and the general features of critical aspects about steelmaking planning (Paragraph 2) is given in order to understand the bonds, features, criticalities to be analyzed and implemented in the simulation model. In paragraph 3 a detailed analysis of proposed methodology and system architecture is given in order to make the reader understand the complexity that the Authors had to face in modeling the system and the solutions they found with approximations, considerations, techniques and algorithms that were the most suitable to be used in this particular situation. A short description of the likely steelmaking plant modeled and Verification and Validation (V&V) results are carried in paragraph 4. It was in fact very important in such a complex system, to define the acceptability of results in terms of verification of the correctness, validation of the results, and accreditation to the users. This is a generally valid principle in simulation, but moreover in a complex system modeling such a steelmaking process, where an error can cost millions. At last, in paragraph 5, the Authors present the conclusions of this work, with a particular attention to the savings that the simulation can bring to this real system, explaining the results of the case study to which it was applied, and the possible future developments of this research are discussed. This model can anyway be applied to other realities than the one exemplified in this paper. [ABSTRACT FROM AUTHOR]

In present paper, a two-dimensional numerical study on a standing-wave thermoacoustic engine was performed with compressible SIMPLE algorithm based on a pressure-correction method. First, the simulation model was developed, and the time-dependent compressible thermoacoustic engine system was chosen through substantive numerical tests. Appropriate governing equations for mass, momentum and energy were introduced. Then, the computational results of the onset of the self-excited oscillations across the entire evolution process and the acoustical characteristics of the pressure and velocity wave were presented and analyzed. In addition, the standing-wave of the pressure and velocity along the center of the two stacks are investigated. The crucial nonlinear phenomenon that cannot be captured by the existing linear theory, like high harmonic frequencies, is also revealed in present paper. It is concluded that compressible SIMPLE algorithm could be employed in our future work to simulate and optimize thermoacoustic system. The present result is an important step toward development to predict the high-amplitude thermoacoustic systems and optimize thermoacoustic engine performance. [ABSTRACT FROM AUTHOR]

The paper introduces a bio-inspired approach to solve the route allocation problem (RAP) in the transportation networks. The approach extends a well-known meta-heuristics algorithm with the real life constraints that are dealt with in the scheduling process (i.e. the uniform distribution of routes diversity for vehicles, the average distance travelled in a month, the driver’s rest between subsequent trips etc.). The paper is focusing on the engineering aspects of employing bio-inspired algorithms (which proved to have near-optimal results for toy-like problems) to a real-life application domain. The approach proved to be capable of preserving the software components (agents) to the complexity and dynamics of the situation when the RAP requires incremental extensions of constraints to reflect the traffic conditions in the transportation network. [ABSTRACT FROM AUTHOR]

REX Control System is a professional advanced tool for design and implementation of complex control systems that belongs to softPLC category. It covers the entire process starting from simulation of functionality of the application before deployment, through implementation on real-time target, towards analysis, diagnostics and visualization. Basically it consists of two parts: the development tools and the runtime system. It is also compatible with Simulink environment, and the way of implementation of control algorithm is very similar. The control scheme is finally compiled (using RexDraw utility) and uploaded into a chosen real-time target (using RexView utility). There is a wide variety of hardware platforms and real-time operating systems supported by REX Control System such as for exampleWindows Embedded, Linux, Linux/Xenomai deployed on SBC, IPC, PAC, Raspberry Pi and others with many I/O interfaces. It is modern system designed both for measurement and control applications, offering a lot of additional functions concerning data archiving, visualization based on HTML5, and communication standards. The paper will sum up possibilities of its use in educational process, focused on control of case studies of physical models with classical and advanced control algorithms. [ABSTRACT FROM AUTHOR]

The ITER-like Antenna (ILA) for JET [1] is a 2 toroidal by 2 poloidal array of Resonant Double Loops (RDL) featuring in-vessel matching capacitors feeding RF current straps in conjugate-T manner, a low impedance quarter-wave impedance transformer, a service stub allowing hydraulic actuator and water cooling services to reach the aforementioned capacitors and a 2nd stage phase-shifter-stub matching circuit allowing to correct/choose the conjugate-T working impedance. Toroidally adjacent RDLs are fed from a 3dB hybrid splitter. It has been operated at 33, 42 and 47MHz on plasma (2008-2009) while it presently estimated frequency range is from 29 to 49MHz. At the time of the design (2001-2004) as well as the experiments the circuit models of the ILA were quite basic. The ILA front face and strap array Topica model was relatively crude and failed to correctly represent the poloidal central septum, Faraday Screen attachment as well as the segmented antenna central septum limiter. The ILA matching capacitors, T-junction, Vacuum Transmission Line (VTL) and Service Stubs were represented by lumped circuit elements and simple transmission line models. The assessment of the ILA results carried out to decide on the repair of the ILA identified that achieving routine full array operation requires a better understanding of the RF circuit, a feedback control algorithm for the 2nd stage matching as well as tighter calibrations of RF measurements. The paper presents the progress in modelling of the ILA comprising a more detailed Topica model of the front face for various plasma Scrape Off Layer profiles, a comprehensive HFSS model of the matching capacitors including internal bellows and electrode cylinders, 3D-EM models of the VTL including vacuum ceramic window, Service stub, a transmission line model of the 2nd stage matching circuit and main transmission lines including the 3dB hybrid splitters. A time evolving simulation using the improved circuit model allowed to design and simulate the effectiveness of a feedback control algorithm for the 2nd stage matching and demonstrates the simultaneous matching and control of the 4 RDLs : 11 feedback loops control 21 actuators (8 capacitors, 4 phase shifters and 4 stubs for the 2nd stage matching, 4 main phase shifters controlling of the toroidal phasing and the electronically controlled phase between RF sources feeding top and bottom parts of the array and determines the poloidal phasing of the array which is solved explicitly at each time step) on (simulated) ELMy plasmas. [ABSTRACT FROM AUTHOR]

In this paper, we reported the results of the simulation of the electronic conduction in solids. The simulation is based on the Drude's models by applying molecular dynamics (MD) method, which uses the fifth-order predictorcorrector algorithm. A formula of the electrical conductivity as a function of lattice length and ion diameter τ (L, d) cand be obtained empirically based on the simulation results. [ABSTRACT FROM AUTHOR]

In this paper the dynamic performances of the Perturb and Observe and Incremental Conductance algorithms, which are commonly used to track the maximum power point of photovoltaic power plants, are analyzed according to the procedure provided in the European Standard EN 50530. The analysis was performed by simulation in MATLAB/SIMULINK for a grid-connected photovoltaic system. [ABSTRACT FROM AUTHOR]

The devastating 2004 Andaman tsunami and the crippling 2011 Fukushima tsunami highlight the vulnerability to future tsunamis for coastal communities living in affected regions. An important application of tsunami modeling is to simulate the maximum inundation distance and maximum run-up heights along beaches for improved tsunami hazard assessments. Numerical tsunami models are able to assess which coastal communities are vulnerable once a tsunami source is identified, helping emergency management to develop risk maps and evacuation routes. This paper begins with a brief introductory review on contemporary run-up and draw-down simulation models to provide insights for choosing an appropriate model to be developed. Based upon the nonlinear shallow water equations (NSWE) coupled with a moving boundary algorithm, a one-dimensional tsunami run-up model, codenamed TUNA-RP, is developed. The moving boundary algorithm implemented allows the NSWE to be computed over the entire computational domain, including dry nodes. TUNA-RP is validated by comparing simulation results to a known semi-analytical solution. TUNA-RP has a wider range of applicability compared to the semi-analytical solution. Some scenarios of potential tsunami inundation along Malaysian coasts will be presented to highlight vulnerability in the event of another large tsunami in the Andaman Sea. [ABSTRACT FROM AUTHOR]

The purpose of this paper is the comparison of two phase measurement methods commonly used in precision rangefinder systems and their suitability to work with high frequency signals. Basic detection circuits for an FFT and an IQ-based methods were proposed and hardware limitations were considered. A set of simulations to assess the behavior of the algorithms in the presence of the noise was performed. An influence of the ADC resolution on the measurement accuracy was also assessed. It is proved that the IQ-based method shows better resilience to signal distortions and puts lower requirements on the ADC circuit thus is better suited for real time high resolution laser rangefinders. [ABSTRACT FROM AUTHOR]

A standard algorithm for LMS-filter simulation, tested with several convergence criteria is presented in this paper. We analyze the steady-state mean square error (MSE) convergence of the LMS algorithm when random functions are used as reference inputs. In this paper, we make a more precise analysis using the deterministic nature of the reference inputs and their time-variant correlation matrix. Simulations performed under MATLAB show remarkable differences between convergence criteria with various value of the step size. [ABSTRACT FROM AUTHOR]

The paper presents a set of Monte Carlo algorithms, based on the Kac's stohastic gas model for simulation of the binary collision process in a homogenous rarefied gas. These collision algorithms avoid the repeat collisions and can be used for simualtion of the collsions in grid cells with small average number of particles, when the DSMC method is applied and the simulation requires computational resources of very large proportions. [ABSTRACT FROM AUTHOR]

Recently alternative approaches in cosmology seeks to explain the nature of dark matter as a direct result of the non-linear spacetime curvature due to different types of deformation potentials. In this context, a key test for this hypothesis is to examine the effects of deformation on the evolution of large scales structures. An important requirement for the fine analysis of this pure gravitational signature (without dark matter elements) is to characterize the position of a galaxy during its trajectory to the gravitational collapse of super clusters at low redshifts. In this context, each element in an gravitational N-body simulation behaves as a tracer of collapse governed by the process known as chaotic advection (or lagrangian turbulence). In order to develop a detailed study of this new approach we develop the COsmic LAgrangian TUrbulence Simulator (COLATUS) to perform gravitational N-body simulations based on Compute Unified Device Architecture (CUDA) for graphics processing units (GPUs). In this paper we report the first robust results obtained from COLATUS. [ABSTRACT FROM AUTHOR]

One of the most basic tasks in quantum information processing, communication and security (QIPCC) research, theoretically deep and practically important, is to find bounds on how really important are inherently quantum resources for speeding up computations. This area of research is bringing a variety of results that imply, often in a very unexpected and counter-intuitive way, that: (a) surprisingly large classes of quantum circuits and algorithms can be efficiently simulated on classical computers; (b) the border line between quantum processes that can and cannot be efficiently simulated on classical computers is often surprisingly thin; (c) the addition of a seemingly very simple resource or a tool often enormously increases the power of available quantum tools. These discoveries have put also a new light on our understanding of quantum phenomena and quantum physics and on the potential of its inherently quantum and often mysteriously looking phenomena. The paper motivates and surveys research and its outcomes in the area of de-quantisation, especially presents various approaches and their outcomes concerning efficient classical simulations of various families of quantum circuits and algorithms. To motivate this area of research some outcomes in the area of de-randomization of classical randomized computations. [ABSTRACT FROM AUTHOR]

The objective of this research is to build a nested generalized linear mixed model using an ordinal response variable with some covariates. There are three main jobs in this paper, i.e. parameters estimation procedure, simulation, and implementation of the model for the real data. At the part of parameters estimation procedure, concepts of threshold, nested random effect, and computational algorithm are described. The simulations data are built for 3 conditions to know the effect of different parameter values of random effect distributions. The last job is the implementation of the model for the data about poverty in 9 districts of Java Island. The districts are Kuningan, Karawang, and Majalengka chose randomly in West Java; Temanggung, Boyolali, and Cilacap from Central Java; and Blitar, Ngawi, and Jember from East Java. The covariates in this model are province, number of bad nutrition cases, number of farmer families, and number of health personnel. In this modeling, all covariates are grouped as ordinal scale. Unit observation in this research is sub-district (kecamatan) nested in district, and districts (kabupaten) are nested in province. For the result of simulation, ARB (Absolute Relative Bias) and RRMSE (Relative Root of mean square errors) scale is used. They show that prov parameters have the highest bias, but more stable RRMSE in all conditions. The simulation design needs to be improved by adding other condition, such as higher correlation between covariates. Furthermore, as the result of the model implementation for the data, only number of farmer family and number of medical personnel have significant contributions to the level of poverty in Central Java and East Java province, and only district 2 (Karawang) of province 1 (West Java) has different random effect from the others. The source of the data is PODES (Potensi Desa) 2008 from BPS (Badan Pusat Statistik). [ABSTRACT FROM AUTHOR]

In this paper we present a computer program called MINERVA, a mesh generator to be used in a few views tomography, varying from three to eighteen views. For the discretization of the domain, we used a natural base, based on the intersection of all radiation paths from the source to the detectors. The direct problem is solved as a linear system A σ = h, where A is a matrix related to the domain discretization, the vector σ represents the linear attenuation coefficients and h is related to measures of the detectors. The inverse problem is solved using an Algebraic Reconstruction Techniques algorithm. Cases testes of industrial computed tomography images reconstruction are presented using as experimental data, simulated data with the code MCNP5. [ABSTRACT FROM AUTHOR]

Nondestructive testing methods have been routinely, designed, evaluated and optimized using simulation models developed using various computational techniques. The simulated signal using computational model differs from the true signal in that the signal does not simulated experimental noise. In order to use the computational models more effectively for signal processing algorithm development, experimental noise should be injected in the simulated signals. Experimental noise PDF (probability density function) can be numerically calculated from measured noise. The experimental signal PDF can then be generated by combining the simulation signal and measurement noise PDF. Sampling from experimental signal distribution is not a straight forward task as the distribution is generally not a standard parametric distribution. This paper presents a method that approximates experimental signal PDF as a mixture of Gaussian densities. Maximum-likelihood estimate of the parameters of Gaussian distributions from a given data set are computed using expectation-maximization (EM) technique. A sampling scheme from the mixture of Gaussian densities is also discussed. The overall algorithm is implemented on eddy current inspection data from steam generator (SG) tubing. [ABSTRACT FROM AUTHOR]

This paper discusses the possibility of using evolutionary algorithms for the reconstruction of chaotic systems. The main aim of this work is to show that evolutionary algorithms are capable of the reconstruction of chaotic systems without any partial knowledge of internal structure, i.e. based only on measured data. Algorithm SOMA was used in reported experiments here. Systems selected for numerical experiments here is the well-known Lorenz system. For each algorithm and its version, repeated simulations were done, totaling 20 simulations. According to obtained results it can be stated that evolutionary reconstruction is an alternative and promising way as to how to identify chaotic systems. [ABSTRACT FROM AUTHOR]

The paper is devoted to the nature of the recirculation zone behind a Mach disk in an underexpanded jet predicted by CFD at some range of determining parameters. The free jet flow behind the axisymmetric sonic nozzle was simulated by two approaches-in the frames of the full set of Navier-Stokes (NS) equations and by the DSMC approach. No recirculation zone predicted by NS algorithm was observed in the flow field obtained by the DSMC approach. The nature of the discussed effect, therefore, seems to be purely computational and caused by limited applicability of the Navier-Stokes equations for the description of the flow in the vicinity of the Mach disk with the high gradients of the flow parameters at that location. [ABSTRACT FROM AUTHOR]

This paper is devoted to a foreground/background joint estimation and separation problem. We first observe that this problem is modeled by a conditionally linear and Gaussian hidden Markov chain (CLGHMC). We next propose a filtering algorithm in the general non-linear and non Gaussian conditionally hidden Markov chain (CHMC), allowing the propagation of the filtering densities associated to the foreground and the background. We then focus on the particular case of our CLGHMC in which these filtering densities are weighted sums of Gaussian distributions; the parameters of each Gaussian are computed by using the Kalman filter algorithm, while the weights are computed by using the particle filter algorithm. We finally perform some simulations to highlight the interest of our method in both signals and images foreground/backgound joint estimation and separation. [ABSTRACT FROM AUTHOR]

This paper proposes a new spectral unmixing strategy based on the normal compositional model that exploits the spatial correlations between the image pixels. The pure materials (referred to as endmembers) contained in the image are assumed to be available (they can be obtained by using an appropriate endmember extraction algorithm), while the corresponding fractions (referred to as abundances) are estimated by the proposed algorithm. Due to physical constraints, the abundances have to satisfy positivity and sum-to-one constraints. The image is divided into homogeneous distinct regions having the same statistical properties for the abundance coefficients. The spatial dependencies within each class are modeled thanks to Potts-Markov random fields. Within a Bayesian framework, prior distributions for the abundances and the associated hyperparameters are introduced. A reparametrization of the abundance coefficients is proposed to handle the physical constraints (positivity and sum-to-one) inherent to hyperspectral imagery. The parameters (abundances), hyperparameters (abundance mean and variance for each class) and the classification map indicating the classes of all pixels in the image are inferred from the resulting joint posterior distribution. To overcome the complexity of the joint posterior distribution, Markov chain Monte Carlo methods are used to generate samples asymptotically distributed according to the joint posterior of interest. Simulations conducted on synthetic and real data are presented to illustrate the performance of the proposed algorithm. [ABSTRACT FROM AUTHOR]

The paper deals with some basic problems of the DSMC method concerning the generation of new collision algorithms with improved stochastic properties, allowing simulation of non-equilibrium gas flows with a smaller number of particles in cells compared to the traditional collision schemes. The modified algorithms avoid the events of repeated collisions, which are ones of the basic sources of bias from the theoretical Boltzmann collision frequency. The considered modifications are validated on the one-dimensional unsteady-state problem of strong shock wave formation and the macroscopic characteristics of the shock wave obtained by traditional and new collision algorithms are compared. The efficiency of the modified DSMC method is illustrated by numerical results obtained from the simulation of three-dimensional Rayleigh-Bénard convection of a rarefied gas. [ABSTRACT FROM AUTHOR]

Computational Fluid Dynamics (CFD) is one of the branches of fluid mechanics, which uses numerical methods and algorithms to solve and analyze fluid flows. CFD is used in various domains, such as oil and gas reservoir uncertainty analysis, aerodynamic body shapes optimization (e.g. planes, cars, ships, sport helmets, skis), natural phenomena analysis, numerical simulation for weather forecasting or realistic visualizations. CFD problem is very complex and needs a lot of computational power to obtain the results in a reasonable time. We have implemented a parallel application for two-dimensional CFD simulation with a free surface approximation (MAC method) using new hardware architectures, in particular multi-GPU and hybrid computing environments. For this purpose we decided to use NVIDIA graphic cards with CUDA environment due to its simplicity of programming and good computations performance. We used finite difference discretization of Navier-Stokes equations, where fluid is propagated over an Eulerian Grid. In this model, the behavior of the fluid inside the cell depends only on the properties of local, surrounding cells, therefore it is well suited for the GPU-based architecture. In this paper we demonstrate how to use efficiently the computing power of GPUs for CFD. Additionally, we present some best practices to help users analyze and improve the performance of CFD applications executed on GPU. Finally, we discuss various challenges around the multi-GPU implementation on the example of matrix multiplication. [ABSTRACT FROM AUTHOR]

Due to the physical limitations on the speed of individual processors, we are currently experiencing a paradigm shift in computer architecture towards multi-processor, multi-core and multi-subcore systems. In order to take full advantage of these new architectures, some of the basic models, algorithms and data structures in Molecular Dynamics simulations need to be re-thought. In this paper, I present some simple, generic algorithmic considerations that can improve the performance of such simulations on the IBM Cell Broadband Engine Architecture, a multi-subcore processor. The accumulated effects of these improvements are on par with what can be achieved with hand-tuned architecture-specific optimizations in the innermost loops of the simulation. [ABSTRACT FROM AUTHOR]

An efficient and fast algorithm, which is based on the splitting-step idea, for simulations of mean-reverting square-root diffusions is presented in this paper. The local path wise error of this algorithm is considered, and an estimate of local error in the 2nd moment is proved. A series of numerical experiments based on MATLAB programs is given to compare the suggested algorithm with the present schemes: the BIM scheme and the BMM scheme. [ABSTRACT FROM AUTHOR]

This paper introduces a model-based approach to reconstruct the three-dimensional defect profiles using eddy-current heat exchanger tube inspection signals. The method uses a Woodbury’s substructure finite element forward model to simulate the underlying physics, a state space defect representation, and a tree search algorithm to solve the inverse problem. The advantage of the substructure method is that it divides the whole solution domain into two substructures and only the region of interest (ROI) with dramatic material changes will be updated in each iterative step. Since the number of elements inside the ROI is very small compared with the number of elements in the entire mesh, the computational effort needed in both LU factorization and coefficient matrix assembly is reduced. Therefore, the execution time is reduced significantly making the inversion very efficient. The initial inversion results are presented to confirm the validity of the approach. [ABSTRACT FROM AUTHOR]

Investigations of continuum percolation model are less than those of discrete percolation model, because of difficulty in simulation study. There is an alternative approach to simulation study in the discrete model such as kinetic growth model (Leath algorithm), where a single cluster is grown from a seed with a percolation probability p. This approach reproduces the same threshold value and critical exponent as the direct study of conventional model. In this paper we apply a kinetic growth approach (Leath algorithm) for the continuum percolation model starting with a seed at the origin. [ABSTRACT FROM AUTHOR]

We investigate in this paper the recovery of the local volatility surface in a parametric framework similar to that of Coleman, Li and Verma [1]. The quality of a surface is assessed through a functional which is optimized; the specificity of the approach is to separate the optimization on the parametric space (performed with any suitable optimization algorithm) from the computation of the functional where we use an adjoint formulation similar to that of the optimal control; the procedure can thus incorporate information from any derivative contract compatible with the adjoint approach. The procedure was implemented and was shown to perform satisfactory on real-world data. [ABSTRACT FROM AUTHOR]

ACS algorithms have been used in solving NP-hard and optimization problems in recent years. ACS ant colonies are homogeneous, but natural colonies are not. In this paper, a new ACS algorithm is proposed. It uses heterogeneous ant colonies which are evolved using a new type of genetic algorithm. Experimental results obtained from solving TSP problem, show the superiority of proposed algorithm over classical ACS. [ABSTRACT FROM AUTHOR]

An improved parallelized hybrid DSMC-NS algorithm presented and verified. In previous work [1], it showed the slow convergence of coupling between two numerical solvers if the normal velocities across the breakdown interfaces are very low. By detailed kinetic velocity sampling study from the pure DSMC simulation of a two-dimensional supersonic nitrogen flow (M∞ = 4) past a 25° finite wedge, we have found most of boundary layer region is in nearly thermal equilibrium, even with very high continuum breakdown Knmax [10]. Thus, a new continuum breakdown parameter based on pressure gradient, pressure and local mean free path, which can be used to effectively “exclude” the “false” breakdown region like the boundary layer, is proposed in this paper. Results show that the improved algorithm can greatly reduce the computational cost while maintaining essentially the same accuracy. [ABSTRACT FROM AUTHOR]

A technique called the DSMC Rapid Ensemble Averaging Method (DREAM) for reducing the statistical scatter in the output from unsteady DSMC simulations is introduced. During post-processing by DREAM, the DSMC algorithm is re-run multiple times over a short period before the temporal point of interest thus building up a combination of time- and ensemble-averaged sampling data. The particle data is regenerated several mean collision times before the output time using the particle data generated during the original DSMC run. This methodology conserves the original phase space data from the DSMC run and so is suitable for reducing the statistical scatter in highly non-equilibrium flows. In this paper, the DREAM-II method is investigated and verified in detail. Propagating shock waves at high Mach numbers (Mach 8 and 12) are simulated using a parallel DSMC code (PDSC) and then post-processed using DREAM. The ability of DREAM to obtain the correct particle velocity distribution in the shock structure is demonstrated and the reduction of statistical scatter in the output macroscopic properties is measured. DREAM is also used to reduce the statistical scatter in the results from the interaction of a Mach 4 shock with a square cavity and for the interaction of a Mach 12 shock on a wedge in a channel. [ABSTRACT FROM AUTHOR]

This paper proposes a new hybrid evolutionary algorithm (HEA) based on evolutionary programming (EP), tabu search (TS), and simulated annealing (SA) to determine the available transfer capability (ATC) of power transactions between different control areas in deregulated power systems. The optimal power flow (OPF)-based ATC determination is used to evaluate the feasible maximum ATC value within real and reactive power generation limits, line thermal limits, voltage limits, and voltage and angle stability limits. The HEA approach simultaneously searches for real power generations except slack bus in a source area, real power loads in a sink area, and generation bus voltages to solve the OPF-based ATC problem. Test results on the modified IEEE 24-bus reliability test system (RTS) indicate that ATC determination by the HEA could enhance ATC far more than those from EP, TS, hybrid TS/SA, and improved EP (IEP) algorithms, leading to an efficient utilization of the existing transmission system. [ABSTRACT FROM AUTHOR]

Advances in both reactor and feature scale modeling have been achieved in plasma processing. Models are being used to address several practical issues in industry. However, accurate predictions of physical phenomena that occur during the process need an integrated multiscale approach that couples reactor scale to feature scale. The implementation of multiscale codes is still a challenge where robustness plays a critical role. This paper addresses the weakest points of such codes especially at the feature scale and provides proper choices for successful implementations. It focuses on the level set methods and fast marching algorithms implemented on quadtree (2D) and octree (3D) data structures and possible extensions of semi-lagrangian methods. [ABSTRACT FROM AUTHOR]

Non-invasive monitoring of dielectric slab thickness is of great interest in various industrial applications. This paper focuses on estimating the thickness of dielectric slabs, and consequently monitoring their variations, utilizing wideband microwave signals and the MUtiple SIgnal Characterization (MUSIC) algorithm. The performance of the proposed approach is assessed by validating simulation results with laboratory experiments. The results clearly indicate the utility of this overall approach for accurate dielectric slab thickness evaluation. © 2007 American Institute of Physics [ABSTRACT FROM AUTHOR]

Numerical simulation technology and optimization method have been applied in sheet metal forming process to improve design quality and shorten design cycle. While the existence of fluctuation in design variables or operation condition has great influence on the quality. In addition to that, iterative solution in numerical simulation and optimization usually take huge computational time or endure expensive experiment cost In order to eliminate effect of perturbations in design and improve design efficiency, a CAE-based six sigma robust design method is developed in this paper. In the six sigma procedure for sheet metal forming, statistical technology and dual response surface approximate model as well as algorithm of “Design for Six Sigma (DFSS)” are integrated together to perform reliability optimization and robust improvement. A deep drawing process of a rectangular cup is taken as an example to illustrate the method. The optimization solutions show that the proposed optimization procedure not only improves significantly the reliability and robustness of the forming quality, but also increases optimization efficiency with approximate model. © 2005 American Institute of Physics [ABSTRACT FROM AUTHOR]

This paper presents several approaches for preform shape optimization in 3D forging. The process simulation is carried out using the FORGE3® finite element software, and the optimization problem regards the shape of initial axisymmetrical preforms. Several objective functions are considered, like the forging energy, the forging force or a surface defect criterion. Both deterministic and stochastic optimization algorithms are tested for 3D applications. The deterministic approach uses the sensitivity analysis that provides the gradient of the objective function. It is obtained by the adjoint-state method and semi-analytical differentiation. The study of stochastic approaches aims at comparing genetic algorithms and evolution strategies. Numerical results show the feasibility of such approaches, i.e. the achieving of satisfactory solutions within a limited number of 3D simulations, less than fifty. For a more industrial problem, the forging of a gear, encouraging optimization results are obtained. © 2004 American Institute of Physics [ABSTRACT FROM AUTHOR]

In this paper we review the simulation method of the non-smooth contact dynamics. This technique was designed to solve the unilateral and frictional contact problem for a large number of rigid bodies and has proved to be especially valuable in research of dense granular materials during the last decade. We present here the basic principles compared to other methods and the detailed description of a 3D algorithm. We point out an artifact manifesting itself in spurious sound waves and discuss the applicability of the method. [ABSTRACT FROM AUTHOR]