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The increase in the number of vehicles on roads has compounded the difficulty in parking them when people go out for movies, shopping, theatre, etc. Thus, this paper proposes smart parking system. The reservation of the parking slots can be made using this proposed smart parking system. Unlike the methods proposed in the existing research, the system proposed in this paper divides the parking area into 3 parts. One for conventional parking, one for vehicles with reservation and the other for the vehicles with and without reservation. Learning automata is used in the proposed system to determine the percentage of the parking area for conventional parking. In general, the proportionate of the slots for reserved parking, conventional parking and common slots need to be assumed. Learning Automata helps in determining this proportionate optimally. The AES-256 encryption algorithm is used to provide security for the details provided by the user during reservation process. Goodput value is maintained for each vehicle which increases or decreases the chances of getting a reservation. The time limit for the reservation of the parking slot is also maintained after which the reservation gets cancelled automatically. Markov Model is used to represent the system. The performance of the proposed algorithm, Learning Automata and Reservation based Secure Smart Parking System (LA-RSSPS) is simulated and evaluated in terms of average waiting time, search time, the probability with which the vehicles do not get parking slot when they do not have reservation and the probability with which the vehicles do not get reservation and is compared with ProNet and iERS. Results have shown that our scheme preforms better than the ProNet and iERS competing schemes. The comparison of analytical and simulations results are also presented. [ABSTRACT FROM AUTHOR]

Hybrid systems are inherently fragile with respect to perturbations when their state experiences jumps on surfaces. Zero-crossing detection algorithms are capable of robustly detecting the crossing of such surfaces, but, up to now, the effects of adding such algorithms to the system being simulated are unknown. In this paper, we propose a mathematical model for hybrid systems that incorporates zero-crossing detection as well as a hybrid simulator for it. First, we discuss adverse effects that measurement noise and discretization can have on hybrid systems jumping on surfaces and prove that, under mild regularity conditions, zero-crossing detection algorithms can robustify the original system. Then, we show that integration schemes with zero-crossing detection actually compute a robustified version of the fragile nominal model. In this way, we rigorously characterize their effect on solutions to the simulated system. Finally, we show that both the model and simulator are not only robust, but also that the hybrid simulator preserves asymptotic stability properties, semiglobally and practically (on the step size), of the original system. Several examples throughout the paper illustrate these ideas and results. [ABSTRACT FROM AUTHOR]

Abstract: Testing algorithms with real cars is a mandatory step in developing new intelligent abilities for future transportation systems. However, this step is sometimes hard to accomplish especially due to several problems. It is also difficult to reproduce the same scenario several times. Besides, some critical and/or real world forbidden scenarios cannot be tested. Thus, the comparison of several algorithms using the same experimental conditions is hard to realize. Considering that, it seems important to use simulation tools to perform scenarios with realistic conditions. The main problem with these tools is their distance from real conditions, since they deeply simplify the reality. This paper presents the architecture of the simulation/prototyping tool named Virtual Intelligent Vehicle Urban Simulator (vivus). The goal of vivus is thus to overcome the general drawbacks of classical solutions by providing the possibility of designing a vehicle virtual prototype with simulated embedded sensors and physical properties. Experiments made on linear platoon algorithms are exposed in this paper in order to illustrate the similarities between simulated results and those obtained with real cars. [Copyright &y& Elsevier]

Abstract: We propose a new motion planning and simulation scheme for nonholonomic systems in this paper to provide a practical solution for these application problems taking into account of real-time obstacle avoidance and the continuous curvature path generation simultaneously in 3D unknown environment. The proposed motion planning and simulation scheme generates the motion path using a new universal Euler spiral generation algorithm, which is locally optimal based on perceived points of view. The generated Euler spiral solution can be non-symmetrical and easily implemented while maintaining a C 2 continuous. It is therefore more flexible and powerful in dealing with dynamic situations in real-time, compared with current symmetrical Euler spirals solutions. Real-time solutions are particularly important in navigation in unknown environments. The universal Euler spiral algorithm proposed displays a smaller maximum curvature value and smaller mean square curvature value than the conventional symmetrical algorithm in tested cases. Another significant contribution of our work is the new motion planning scheme which extend current 2D based motion planning into three-dimensional (3D) space. In this paper, we have conducted experiments and describe simulation results including 3D motion trajectory modeling for a flight simulation. [ABSTRACT FROM AUTHOR]

Abstract: Metal organic chemical vapor deposition (MOCVD) technology is a very efficient way to uniformly grow multi-chip, multilayer and a big area thin film. Kinetic Monte Carlo (KMC) method is one of the important research tools that carry out dynamic simulation of atomic thin films growth. Based on the method of KMC, this paper proposes an algorithm of the process of GaInP thin film grown by MOCVD. KMC simulation and the visualization emulation of GaInP thin film growth in MOCVD reactor are realized. The results of simulation and visualization truly and intuitively displayed process of GaInP thin film growth in MOCVD reactor. The simulation results with this paper’s algorithm well coincide with experimental results. This visualization results provide the optimizations of processing parameters which grow GaInP thin film by MOCVD with theoretical basis. [Copyright &y& Elsevier]

Abstract: This paper describes a parameter design (PD) approach that incorporates Taguchi’s robustness into the Genetic Algorithm (GA) search for optimal stochastic outputs of discrete event simulation (DES). The simulation’s stochastic nature, caused by various elements of model randomness leads to varying response averages amongst simulation runs. Ignoring such variability, when ranking solution candidates in a standard GA selection scheme, may result in search convergence to bad solutions. It is clear that adopting such solutions often results in various system design and operational difficulties. The proposed approach, therefore, aims at providing settings to model control parameters at which a certain model outcome is best in performance and is less sensitive to variations in model random (noise) factors. To this end, this paper combines Taguchi’s robust design with the flexibility of simulation–evaluation to enhance the GA selection scheme and to incorporate robustness into the GA search. Taguchi measures robustness in terms of the signal-to-noise (S/N) ratio and the quality loss function (QLF), estimated through full or fractional factorial experimental designs. The proposed approach, however, utilizes the effective GA search to replace Taguchi’s experimental design with orthogonal designs, which compensates for the various shortcomings of Taguchi’s approach. Through both robustness measures, therefore, the stochastic simulation response, estimated in terms of a mean and variance based on multiple independent simulation replicates, is transformed into a scalar GA fitness evaluation. This is expected to guide the GA selection scheme to converge to a near-optimal robust parameter design. A hypothetical job shop example is used to illustrate the application of the proposed approach. [Copyright &y& Elsevier]

This paper describes four design patterns that aim at systematizing and simplifying the modelling and the implementation of multi-level agent-based simulations. Such simulations are meant to handle entities belonging to different, yet coupled, abstractions or organization levels. The patterns we propose are based on minimal typical situations drawn from the literature. For each pattern, we present use cases, associated data structures and algorithms. For genericity purposes, these patterns rely on a unified description of the capabilities for action and change of the agents. Thus, we propose a precise conceptual and operational framework for the designers of multi-level simulations. [ABSTRACT FROM AUTHOR]

• Discrete event simulation models for improving healthcare processes performances. • Process mining techniques: gaining insights into business processes functioning. • Timely approaches required for modeling hospital processes from event logs. • Essence of process mining: a strongly connection between logs and process models. The purpose of this paper is to show how the knowledge of Process Mining techniques can provide a robust premise to build a Discrete Event Simulation (DES) model of a healthcare process. In order to analyze some specific processes of an ophthalmology ward of a large Italian hospital, ProM6 framework was implemented, which supports process mining techniques in form of plug-ins; the plug-ins process data, in form of Event Log, in order to extract information about the process. The DES model based on such information was run via a commercial tool, Simul8, which allows building sophisticated process models. A timely algorithm was then deployed to adapt the ProM6 information to the DES model. Following, a conformance analysis was conducted by comparing the original Event Log, and the Simulation tool data, taking into account the main case-related model attributes (routing probabilities profile, time perspective, and resources perspective). The paper aims at developing the line of inquiry for what concerns the deployment of approaches to set forth the link between Process mining and Simulation modeling. [ABSTRACT FROM AUTHOR]

Ns-3 simulator provides a great platform for experimental studies on different communication technologies and network topologies, and it is already used by many researchers all around the world. Unfortunately, its current TCP implementation is outdated and not ready for being used as reference platform for TCP-centered research, relegating ns-3 to play a background role in favor of its predecessor, ns-2. This paper presents the update process of ns-3 TCP module, that offers to TCP developers and researchers a consistent and RFC-compliant platform to base their works on. The method involves the addition of a new congestion-based state machine, the split of congestion control out from the socket core, and the development of a very detailed and complete testing framework, which can be easily extended. Performance tests follow the description, comparing RAM usage and execution time between ns-3 releases. Also, a case study over high-delay links on the interaction between the Transmission Control Protocol (TCP) and CoDel, an Active Queue Management algorithm born to control queuing delay, is presented. [ABSTRACT FROM AUTHOR]

Abstract: Complex cognitive processes corresponding to human control behaviors cannot be easily inferred using (1) a logical rule-based model, (2) a statistical model, or (3) an analytical predictive model. Predicting human behaviors in complex and uncertain environments like emergency evacuation is considered almost impossible (at least NP hard) in systems theory. In this paper, we explore simulating human behaviors using affordance-based finite state automata (FSA) modeling, based on the ecological concept of affordance theory. To this end, we introduce the conceptual and generic framework of affordance-based human behavior simulation developed through our previous work. Following the generic framework, formal simulation models of affordance-based human behaviors are developed, especially for emergency evacuation, to mimic perception-based dynamic human actions interacting with emergent environmental changes, such as fire. A “warehouse fire evacuation” case is used to demonstrate the applicability of the proposed framework. The human action planning algorithms in the simulation model are developed and implemented using the Adjusted Floor Field Indicators, which represent not only the evacuee’s prior knowledge of the floor layout but the perceivable information about dynamic environmental changes. The results of our simulation study verify that the proposed framework accurately simulates human fire evacuation behavior. The proposed framework is expected to capture the natural manner in which humans behave in emergency evacuation and enhance the simulation fidelity of analyses and predictions of perceptual human behaviors/responses in the systems by incorporating cognitive intent into human behavior simulations. [Copyright &y& Elsevier]

Abstract: This paper presents a particle swarm optimization with differentially perturbed velocity hybrid algorithm with adaptive acceleration coefficient (APSO-DV) for solving the optimal power flow problem with non-smooth and non-convex generator fuel cost characteristics. The APSO-DV employs differentially perturbed velocity with adaptive acceleration coefficient for updating the positions of particles for the particle swarm optimization. The feasibility of the proposed approach was tested on IEEE 30-bus and IEEE 118-bus systems with three different objective functions. Several cases were investigated to test and validate the robustness of the proposed method in finding the optimal solution. The effectiveness of the proposed approach was tested including contingency also. Simulation results demonstrate that the APSO-DV provides superior results compared to classical DE, PSO, PSO-DV and other methods recently reported in the literature. An innovative statistical analysis based on central tendency measures and dispersion measures was carried out on the bus voltage profiles and voltage stability indices. [Copyright &y& Elsevier]

Abstract: In this paper a new energy-aware weighted dynamic topology control (WDTC) algorithm is proposed to extend the lifetime of wireless network and balance the nodes’ energy consumption. The idea is that each node builds its local minimum spanning tree (MST) based on the energy-aware weighted graph and the network topology is adjusted accordingly. It was proved theoretically that the topology under WDTC algorithm could preserve the network connectivity and a sufficient condition for the degree of no more than 6 was also given. Simulation shows that WDTC algorithm can effectively prolong the network lifetime and has good topological features. [Copyright &y& Elsevier]

Abstract: This paper proposes accurate partial shading modeling of photovoltaic (PV) system. The main contribution of this work is the utilization of the two-diode model to represent the PV cell. This model requires only four parameters and known to have better accuracy at low irradiance level, allowing for more accurate prediction of PV system performance during partial shading condition. The proposed model supports a large array simulation that can be interfaced with MPPT algorithms and power electronic converters. The accurateness of the modeling technique is validated by real time simulator data and compared with the three other types of modeling, namely Neural Network, P&O and single-diode model. It is envisaged that the proposed work is very useful for PV professionals who require simple, fast and accurate PV model to design their systems. [Copyright &y& Elsevier]

Abstract: This paper presents the application of immune algorithm (IA) to find optimal location of unified power flow controller (UPFC) to achieve optimal power flow (OPF) and congestion management. Objective function in the OPF, that is to be minimized, is the overall cost functions, which includes the total active and reactive production cost function of the generators and installation cost of UPFCs. The OPF constraints are generators, transmission lines and UPFCs limits. In power system, it may not always be possible to dispatch all of the contracted power transactions due to congestion of the transmission corridors. We propose IA method to minimize the objective function under all equality and inequality constraints. Simulations are performed on 4-bus, IEEE 14-bus and IEEE 30-bus test systems for optimal location of UPFC and the results obtained are encouraging and will be useful in electrical restructuring. [Copyright &y& Elsevier]

Abstract: This paper describes INSEE, a simulation framework developed at the University of the Basque Country. INSEE is designed to carry out performance-related studies of interconnection networks. It is composed of two main modules: a Functional Simulator of Interconnection Networks (FSIN) and a TRaffic GENeration module (TrGen), together with several other modules that extend INSEE’s functionality. The router models and topologies implemented in FSIN are included in this description. Likewise, the available methods to generate traffic are described thoroughly. Finally, the resource consumption of INSEE when managing different systems and workloads is also evaluated. INSEE has been used to conduct a variety of studies, including evaluation of novel topologies, diagnosis of causes of network congestion and evaluation of parallel scheduling algorithms. [ABSTRACT FROM AUTHOR]

Abstract: The most crucial aspect of distributed real-time systems is the scheduling algorithm, which must guarantee that every job in the system will meet its deadline. In this paper, we evaluate by simulation the performance of strategies for the dynamic scheduling of composite jobs in a heterogeneous distributed real-time system. Each job that arrives in the system is a directed acyclic graph of component tasks and has an end-to-end deadline. For each scheduling policy, we provide alternative versions which allow the insertion of tasks into idle time slots, using various bin packing techniques. The comparison study, based on different workloads and system heterogeneity levels, shows that the alternative versions of the algorithms outperform their respective counterparts. [ABSTRACT FROM AUTHOR]

Abstract: The aim of this paper is to implement a sensorless Indirect Stator Field Oriented Control (ISFOC) of Single-Phase Induction Motor Drive (SPIMD) with stator resistance tuning. The proposed method for the estimation of speed is based only on measurement of stator currents. A very simple identification algorithm using d-axis stator current error for identifying the stator resistance is proposed. Experimental results for SPIMD are presented and analyzed by using a dSpace system with DS1104 control board based on the Digital Signal Processor (DSP) TMS320F240. Simulated results are compared with experimental results on a test 1.1kW SPIM setup. The agreement between simulated and experimental results proves the validity of the proposed method. [ABSTRACT FROM AUTHOR]

Abstract: In this study, a mathematical model is described and developed based on a set of algebraic equations which is capable of artificially generating normal events of the electrocardiogram (ECG) such as P-wave, QRS complex, T-wave or synthetic abnormal phenomena like ST-segment episodes (i.e. depression, elevation, and sloped ascending or descending) and repolarization abnormalities such as T-wave alternans (TWA). In order to demonstrate the flexibility of the presented model for the simulation of various ECG signals, fascicular ventricular tachycardia, rate dependent conduction block, and acute Q-wave infarctions of inferior and anterior-lateral walls are simulated. Then, using the proposed artificial ECG signal, two new developed QRS detection algorithms (Modified Hilbert transform-MHT and discrete wavelet curve length-DWCL algorithms) evolved, respectively based on the implementation of some modifications to the conventional Hilbert and discrete wavelet transforms of the ECG signal, are then evaluated. To meet this end, a mathematically-simulated ECG signal with a weak R-wave is embedded into a Gaussian noise with a wide range for variances (powers) and the MHT and DWCL algorithms are applied to the resulted signal to detect QRS complexes. In the next step, an artificial baseline wander is added to the ECG signal and the performance of the MHT and DWCL algorithms in cases of high baseline wander are studied. After conducting numerous simulations, it was concluded that for the values of signal to noise ratio (SNR) larger than −5dB and amplitudes of baseline wanders approximately less than 5 times of R-wave amplitude, the two detection algorithms will have acceptable performance while it is seen that in low (negative) SNR values, performance endurance of the DWCL based detection algorithm is higher than MHT method. The Matlab m-file script of the synthetic ECG generator will be freely available from the Appendix of this paper. [Copyright &y& Elsevier]

Abstract: In this paper, an active vibration control (AVC) incorporating active piezoelectric actuator and self-learning control for a flexible plate structure is presented. The flexible plate system is first modelled and simulated via a finite difference (FD) method. Then, the validity of the obtained model is investigated by comparing the plate natural frequencies predicted by the model with the reported values obtained from literature. After validating the model, a proportional or P-type iterative learning (IL) algorithm combined with a feedback controller is applied to the plate dynamics via the FD simulation platform. The algorithms were then coded in MATLAB to evaluate the performance of the control system. An optimized value of the learning parameter and an appropriate stopping criterion for the IL algorithm were also proposed. Different types of disturbances were employed to excite the plate system at different excitation points and the controller ability to attenuate the vibration of observation point was investigated. The simulation results clearly demonstrate an effective vibration suppression capability that can be achieved using piezoelectric actuator with the incorporated self-learning feedback controller. [Copyright &y& Elsevier]

Abstract: In this paper, the numerical solution of the Navier–Stokes equations by the Characteristic-Based-Split (CBS) scheme is accelerated with the Minimum Polynomial Extrapolation (MPE) method to obtain the steady state solution for evolution incompressible and compressible problems. The CBS is essentially a fractional time-stepping algorithm based on an original finite difference velocity-projection scheme where the convective terms are treated using the idea of the Characteristic-Galerkin method. In this work, the semi-implicit version of the CBS with global time-stepping is used for incompressible problems whereas the fully-explicit version is used for compressible flows. At the other end, the MPE is a vector extrapolation method that transforms the original sequence into another sequence converging to the same limit faster then the original one without the explicit knowledge of the sequence generator. The developed algorithm, tested on two-dimensional benchmark problems, demonstrates the new computational features arising from the introduction of the extrapolation procedure to the CBS scheme. In particular, the results show a remarkable reduction of the computational cost of the simulation. [Copyright &y& Elsevier]

Abstract: Balancing the work load can improve the performance of distributed simulation systems. In this paper we propose a fast adaptive balancing method, in which a binary tree structure is used to partition the simulation region into sub-domains. From a global view to local views, we balance the loads between sub-domains recursively by compressing and stretching sub-domains in group. This method can adjust the sub-domains with heavy loads and decompose their loads very fast. Then we compare the algorithm with two previously proposed algorithms by an artificial case and a real distributed case respectively. In both cases, our method can get a faster convergence speed and a lower communication overhead. [Copyright &y& Elsevier]

Abstract: Today’s time-of-flight (TOF) sensors measure full-range distance information by estimating the elapsed time between emission and receiving of active light in real-time. Such sensors are inexpensive, compact, and they have a high performance, which especially fits real-time applications, e.g. in the fields of automotive, robotics, 3D imaging, and visualization. The simulation of such sensors is an essential building block for hardware design and application development. Therefore, the simulation data must capture the major sensor characteristics. This paper introduces a simulation approach, which is motivated by physics, for the Photonic Mixing Device (PMD) sensor which is a specific type of time-of-flight sensor. Dynamic motion blurring and resolution artifacts such as flying pixels as well as the typical deviation error are prominent effects of real world systems. Flying pixels arise when an area of inhomogeneous depth is covered by a single PMD-pixel whereas the deviation error is based on the anharmonic properties of the optical signal. The modeling of these artifacts is essential for an authentic simulation approach. We present a detailed comparison between a real PMD-device and the simulation data regarding the sensor characteristics. The proposed algorithms are implemented in a hardware accelerated solution which makes use of the programmability of modern Graphics Processing Units (GPUs). This way, an interactive simulation feedback is provided for applications and further data processing. The simulation takes place in real-time and thus all required control mechanisms are accessible in real-time, too. [Copyright &y& Elsevier]

Abstract: This paper presents a speed estimation technique for the permanent magnet synchronous motor drive. A Model Reference Adaptive System (MRAS) has been formed using the instantaneous and steady-state reactive powers to estimate the speed. It has been shown that such unique MRAS offers several desirable features. The proposed technique is completely independent of stator resistance and is less parameter sensitive, as the estimation-algorithm is only dependent on q-axis stator inductance. Also, the method requires less computational effort as the simplified expressions are used in the MRAS. The stability of the proposed system is achieved through Popov’s Hyperstability criteria. Extensive simulation results are presented to validate the proposed technique. The system is tested at different speeds including zero speed and a very satisfactory performance has been achieved. [Copyright &y& Elsevier]

Abstract: This paper presents a novel methodology involving a Virtual Reality (VR)-based Belief, Desire, and Intention (BDI) software agent to construct crowd simulation and demonstrates the use of the same for crowd evacuation management under terrorist bomb attacks in public areas. The proposed BDI agent framework allows modeling of human behavior with a high degree of fidelity. The realistic attributes that govern the BDI characteristics of the agent are reverse-engineered by conducting human-in-the-loop experiments in the VR-based Cave Automatic Virtual Environment (CAVE). To enhance generality and interoperability of the proposed crowd simulation modeling scheme, input data models have been developed to define environment attributes (e.g., maps, demographics, evacuation management parameters). The validity of the proposed data models are tested with two different evacuation scenarios. Finally, experiments are conducted to demonstrate the effect of various crowd evacuation management parameters on the key performance indicators in the evacuation scenario such as crowd evacuation rate and densities. The results reveal that constructed simulation can be used as an effective emergency management tool. [Copyright &y& Elsevier]

Abstract: Inverse simulation algorithms based on integration have been widely applied to predict the control input time histories required for aircraft to follow ideally defined manoeuvres. Several different inverse simulation algorithms are available but these different methods are all subject to a number of numerical and stability problems, such as high frequency oscillation effects and also lower frequency oscillatory phenomena termed “constraint oscillations”. Difficulties can also arise in applications involving discontinuous manoeuvres, discontinuities within the model or input constraints involving actuator saturation. This paper has shown that the dynamic response properties of the internal system are the cause of the so-called “constraint oscillation” phenomenon. In addition, a new inverse simulation approach based on the constrained derivative-free Nelder–Mead search-based optimisation method has been developed to eliminate problems of discontinuities and saturation. Simulation studies involving nonlinear ship models suggest that this new approach leads to improved properties in terms of convergence and numerical stability. [Copyright &y& Elsevier]

Abstract: In this paper biomechanical interaction between osseointegrated dental implants and bone is numerically investigated through 3D linearly elastic finite-element analyses, when static functional loads occur. Influence of some mechanical and geometrical parameters on bone stress distribution is highlighted and risk indicators relevant to critical overloading of bone are introduced. Insertions both in mandibular and maxillary molar segments are analyzed, taking into account different crestal bone loss configurations. Stress-based performances of five commercially-available dental implants are evaluated, demonstrating as the optimal choice of an endosseous implant is strongly affected by a number of shape parameters as well as by anatomy and mechanical properties of the site of placement. Moreover, effectiveness of some double-implant devices is addressed. The first one is relevant to a partially edentulous arch restoration, whereas other applications regard single-tooth restorations based on non-conventional endosteal mini-implants. Starting from computer tomography images and real devices, numerical models have been generated through a parametric algorithm based on a fully 3D approach. Furthermore, effectiveness and accuracy of finite-element simulations have been validated by means of a detailed convergence analysis. [Copyright &y& Elsevier]

Abstract: A novel track initiation method using ants of different tasks, a kind of ant colony optimization (ACO) algorithm, is developed in this paper. For the proposed system of ants of different tasks, we assume that the number of tracks to be initiated equals the one of tasks, and moreover, ants of the same task search for a given track by collaboration, while ants of different tasks will compete with each other during the search process. In order to fulfill such behaviors, the pheromone model is established, and the corresponding objective function to be optimized is also presented. Numerical simulation results indicate that, for the case of bearings-only multi-sensor-multi-target tracking, the track initiation performance for the proposed system of ants of different tasks performs well compared to other track initiation methods. [Copyright &y& Elsevier]

Abstract: Ad hoc networks are characterized by fast, dynamic changes in the topology of the network. Introduction of new routing algorithms requires a deep and reliable evaluation process. In this paper, we describe an interactive flexible ad hoc simulator (IFAS) that presents a modern and novel approach to the family of ad hoc simulators. This simulator supports unique viewing, debugging, tuning and interactive capabilities that shorten significantly the design and debug process of new algorithms. The development of the IFAS is ongoing; however, we consider this new simulator as an innovative tool that will supplement traditional simulators. [Copyright &y& Elsevier]

Abstract: The paper reports the results of a comparison of the four finite-volume-algorithms SIMPLE, SIMPLEC, SIMPLER and PISO. The analysis has been done to explore and compare the suitability of the algorithms for the dynamic simulation of natural circulation steam generators based on a so called tube-header-model. The suitability of the algorithms was tested with the results of two simulation examples – a heat recovery steam generator with a horizontal tube bank (a) and a two-drum steam generator with a vertical tube bank (b). The calculations are done at low system pressure and under hot start-up conditions for the boilers. The results of the computations demonstrate that the SIMPLER algorithm should be preferred for dynamic simulations which are based on the tube-header-model. The algorithm shows a high stability, an extended field of variability of the under-relaxation factors as well as small required under-relaxation. The strong dependence of the calculation time on the number of control volumes is the only unfavourable characteristic of the SIMPLER algorithm. [Copyright &y& Elsevier]

Abstract: Automated Guided Vehicle (AGV) systems have been frequently used as material handling equipment in manufacturing systems since the last two decades. The use of AGV systems has taken attention of practitioners and researchers. Although there are numerous studies concerning with AGV systems in literature, a few of them deal with the adaptation of these systems into JIT systems. Moreover, the facility layouts considered in those studies have flow-shop environment. In this paper, a simulation model of a hypothetical system which has a job shop environment and which is based on JIT philosophy was developed. In addition, a dispatching algorithm for vehicles moving through stations was presented in order to improve transportation efficiency. In given layout, multiple vehicles can move and their bi-directional flow is allowed. After the model had been established, it was mentioned how to perform simulation output analysis. The factors which may be important for the system were determined by output analysis. An experiment plan was prepared by taking into account these factors. In this plan, two levels were selected for each factor and an experimental design was conducted. The effect of each factor on each performance measure and the interaction of these factors were examined. [Copyright &y& Elsevier]

Abstract: Discrete event modeling allows designing an easy-to-handle and reusable representation of a system but, in its classical form, only permits one simulation at a time for a system. Concurrent and Comparative Simulation (CCS) with Multi-List Propagation (MLP) appears to be an adapted solution, by providing a way to perform several simulations in a single execution run. Concurrent Fault Simulation (CFS) has been one of the first applications of the CCS. The main obstacles to a wide use of this technique are the high complexity of the concurrent simulation algorithms, along with the difficulty to integrate them in a simulation kernel. We focus in this paper on the CFS with MLP of systems described in the new BFS-DEVS formalism, which is an evolution of the original DEVS simulator that integrates the CCS algorithm. The application is performed in the behavioral digital domain of systems described in the VHDL language. [Copyright &y& Elsevier]

Abstract: Many fully-adaptive algorithms have been proposed to overcome the performance limitations of deterministic routing in networks used in high-performance multicomputers, such as the well-known regular n-D torus. This paper proposes a simple yet reasonably accurate analytical performance model to predict message communication latency in tori networks. This model requires a running time of O(1) which is the fastest model yet reported in the literature. Extensive simulations reveal that the new performance model maintains a reasonable accuracy when the network operates under different traffic conditions. The model is then used to perform an extensive investigation into the performance merits of n-D tori using adaptive routing and virtual channels. [Copyright &y& Elsevier]

Abstract: This research solves a multiresponse simulation problem by using a dual-response system and scatter-search method. The proposed dual-response system constructs a response surface for each response. It then transforms the dual-response problem into a standard non-linear programming formulation. The transformation treats the secondary response as a constraint. In addition, the sample variance from simulation replications is considered simultaneously by adding search area constraints to variance. The proposed scatter-search method uses the scatter-search algorithms as an embedded mechanism in a simulation program to guide the solution-search process. This is an iterative process between the scatter-search algorithms and the simulation program. A practical case study is adopted for empirical illustration. Both the proposed methods are efficient and effective in solving the case-study problem. Finally, the paper discusses the advantages and disadvantages of the proposed methods, and suggests future research opportunities. [Copyright &y& Elsevier]

• The Downhill-Simplex-Algorithm is applicable to the inverse material parameter determination • Selection of the optimization parameters influences the determined results • Adaptive Downhill-Simplex-Algorithm reduces the computational effort • Uniqueness of Johnson-Cook material model parameters is not given for machining simulations Modeling the machining process by means of simulation techniques became more and more popular within the last decades. The increasing use of simulation techniques can be attributed to the enhancing computational performance. To accurately model the machining process, different input models are required. Among them, the material model has a crucial impact on the quality of the simulated results. To determine the underlying material model parameters, an inverse procedure has been established, where the material model parameters are adjusted within a chip formation simulation until a reasonable match between simulations and experiments is achieved. However, the procedure of the inverse determination requires high computational efforts and is not robust. This paper presents a novel approach to determine material model parameters inversely from FE-machining simulations by means of the Downhill-Simplex-Algorithm. An effect study was conducted to investigate the influence of the initial simplex, the boundary conditions, and the underlying parameters of the Downhill-Simplex-Algorithm. Further, the validated procedure has been extended to consider multiple cutting conditions and an adaptive step-size has been implemented into the algorithm. The results of the procedure were validated by re-identification of process observables from the target simulations and it was aimed to re-identify the material model parameters of the target simulations. Based on the algorithm, a robust and systematical method has been developed to determine material model parameters inversely from the machining process. [ABSTRACT FROM AUTHOR]

Cloud computing provides a new infrastructure for the research of complex system simulation (CSS). However, insufficient computing resource allocation results in lower performance of a CSS application. On the other hand, excessive computing resource allocation will lead to the increase of simulation communication overhead and simulation synchronous computing. Therefore, accurate computing resource prediction is important to achieve optimal scheduling for CSS applications in the cloud environment. In this paper, a computing resource prediction approach based on ensemble learning has been proposed, which includes a cloud computing resource prediction framework and an intelligent ensemble algorithm. The framework with three–level architecture (simulation as a service, cloud computing resource predictor, and cloud computing resource pool) can provide computing resources to deal with the demands of the simulation applications. The intelligent ensemble algorithm uses an Accuracy and Relative Error-based Pruning algorithm to ensure the effective ensemble of base models (support vector machine, decision tree, and k-nearest neighbor). To improve the performance of the intelligent ensemble algorithm, a Feature Capability-based forward search Feature Selection algorithm is introduced to reduce redundancy between features. The experiments are presented to demonstrate that the intelligent ensemble algorithm can achieve higher accuracy by 4%-20% when compared with existing resource prediction models such as Regressive Ensemble Approach for Prediction, Bayesian, Linear Regression, Random Forest, and Fuzzy Neural Network. [ABSTRACT FROM AUTHOR]