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The Barndorff–Nielsen and Shephard (BNS) model is a representative jump-type stochastic volatility model. Still, no method exists to compute option prices numerically for the non-martingale case with infinite active jumps. In this paper, selecting the minimal martingale measure (MMM) as a representative martingale measure, we develop two simulation methods for the BNS model under the MMM. The first method simulates the asset price at maturity and the Radon–Nikodym density of the MMM separately. On the other hand, the second method directly computes the asset price distribution under the MMM. In addition, we implement some numerical experiments to evaluate the performance of our simulation methods. [ABSTRACT FROM AUTHOR]

Practical fracture problems are characterised by complex patterns of multiple and branching cracks, somewhat far removed from the fracture problems used for validation of numerical methods, involving single cracks, and the simulation of complex multi-tipped cracks brings many challenges to current numerical methods. The cracking particle method (CPM) incorporates the description of a crack path into the meshless nodes or particles used to discretise a problem domain. The CPM has recently been improved to make the crack paths continuous and to include adaptivity. In this paper we take this improved CPM further and introduce new crack particles which can model multiple fractures to handle crack branches and crack junctions without the need for any specialised techniques such as enrichment. Some examples with complex crack patterns are tested to show the performance of the proposed methodology and good results are obtained which agree well with previous papers. [ABSTRACT FROM AUTHOR]

Traffic congestion is a global problem that cannot be solved by continuing to add new roads and extra capacity, which is accentuated in the areas where roads of unlimited-access (e.g. arterial streets) interface those of limited-access (e.g. freeways). Many researchers have addressed this problem but we present here a novel method to utilize a fuzzy logic model to reduce traffic congestion in such interfacing areas during saturated traffic conditions. More specifically this paper presents a control method for a complex traffic control system: Diverging Diamond Interchange (DDI) - Ramp Metering (RM), under oversaturated traffic conditions. The DDI is a relatively new concept of an alternative intersection geometry where two intersections serve left-turn movements without conflicts. However, such DDI left-turn movements, along with the right-turn movements from the opposite direction, put additional 'pressure' on the on-ramp of the freeways or multilane highways that intersect with DDIs. If freeway operations are saturated or near saturation, which may be the result of RM operations, this type of traffic control system can lead to a fully jammed condition with a potential spillback. The purpose of the proposed fuzzy-logic control is to prevent such a queue spillback from the metering ramp to the DDI. After presenting the fuzzy-logic control (FLC) model, we compare it to the conventional fixed time control (FTC) to evaluate potential benefits. To assess the quality of proposed analytical solutions in the real-traffic-like environment we evaluated the two logics in a VISSIM microsimulation model. The results show that, when compared to FTC, the FLC method improves traffic conditions moderately but in the oversaturated environment where there is very little room for improvement. [ABSTRACT FROM AUTHOR]

This is a companion paper based on our previous work on rare event simulation methods. In this paper, we provide an alternative proof for the ergodicity of shaking transformation in the Gaussian case and propose two variants of the existing methods with comparisons of numerical performance. In numerical tests, we also illustrate the idea of extreme scenario generation based on the convergence of marginal distributions of the underlying Markov chains and show the impact of the discretization of continuous time models on rare event probability estimation. [ABSTRACT FROM AUTHOR]

In modelling and simulation a user performs complex sequences of tasks that are intrinsically linked in the form of networks. Tasks include simpler steps such as copying and transforming files to using mesh generation or visualisation software to create inputs or to analyse outputs. Typically, these sequences involve manual steps which are time expensive, often involve use of multiple, incompatible software tools of various levels of usability, which are usually not well documented, and so create significant challenges for provenance, reproducibility and transfer to other users. These semi-manual workflows also inhibit sharing of capabilities and commercialisation. This paper explores how the adoption of the scientific workflow system Workspace can significantly improve such research and engineering activities by streamlining and automating the workflows involved. Benefits ensue in terms of improved collaboration through the sharing of workflow components, higher productivity, reduced costs and shorter development cycles through the reuse of software components and workflows and a reduction in risk due to improved reproducibility, documentation and provenance. The use of the Workspace platform allows such workflows to be executed via an interactive GUI, in batch mode via the command prompt, or embedded within self-contained applications. These applications can take the form of closed source binaries, web services or 'software as a service' applications. This supports significantly improved translation of research prototype software to end users and creates low cost pathways for commercialisation. [ABSTRACT FROM AUTHOR]

Traditional grey forecasting models cannot achieve satisfactory predictive accuracy on approximate non-homogeneous exponential sequence with acceleration, velocity and constant perturbation terms. Hence, it is hard to forecast the developing trend of non-homogeneous exponential data sequences widespread in the real world. It is for this reason that an extended intelligent grey forecasting model with variable speed and adaptive structure (VSSGM for short) is provided in this paper. The proposed model possesses three advantages, namely, strong adaptability to perturbation sequence, self-changing structure, and outstanding accuracy in simulation and prediction. One prominent property is that it can simulate/forecast any given inhomogeneous sequence with acceleration, velocity and constant disturbances, which are the most common perturbations widespread in nature and society. And the proposed VSSGM model can be reducible to DGM(1,1), NDGM, SAIGM and VCGM models in theory. Therefore, the proposed model outperforms the traditional grey models. In order to verify the effectiveness, universality, practicality and feasibility of the model, we conducted an experiment to analyze the precision of the model and employ it to simulate China's industrial added value from 2006 to 2015, then utilize it to forecast the industrial added values from 2019 to 2022. Comparing with the real statistic data, it shows that the proposed model has better prediction performance than traditional grey models. • VSSGM model has characteristics of varistructure and speed adaption. • Possess alterable structure and strong adaptability to perturbation sequence. • Simulate and forecast linear autoregressive sequence unbiasedly. • Proposed model has better performance than traditional GM(1,1) derived models. • China's industrial added value has been predicted effectively. [ABSTRACT FROM AUTHOR]

The paper analyzes two different procurement strategies, i.e. single sourcing and double sourcing, for a buyer that adopts the economic order interval (EOI) reorder policy. The analysis consists of two steps. We start by developing a simulation model, which reproduces the two procurement strategies. In the single sourcing scenario, the buyer exploits only one supplier for purchasing. This supplier owns a defined level of reliability, i.e. a given capacity of providing the product when requested. In the case of double sourcing, besides the first supplier, the buyer can exploit a second vendor, which is always able to deliver the product required (reliability=100%); however, it sells its product at a higher price, generating higher cost. The simulation model, built on Microsoft Excel TM , allows deriving the total cost of the system under the two scenarios, thus helping the buyer select the most suitable (i.e. minimum cost) purchasing strategy. As a second step, for the double sourcing scenario, the analytic formulae of the total cost as a function of the supplier’s reliability are derived and a sensitivity analysis is carried out to investigate how the total cost changes as a function of the input parameters. This paper expressively links the strategic decision of single sourcing vs. double sourcing to a specific reorder policy, such as EOI, which is very often implemented in real cases but not so widely investigated in literature. The proposed approach is thus expected to be of interest under both a practical perspective and a scientific one. [ABSTRACT FROM AUTHOR]

Abstract Zika virus epidemic poses a major threat to public health globally. Initially, this disease was limited to Africa but now it is spreading throughout the World. It is well known that zika virus is transmitted to human by the bites of Aedes mosquitoes. Recently, there are reported cases of sexual transmission and transmission due to blood transfusion in many countries e.g., Argentina, France, New Zealand, USA etc. In this paper a mathematical model of Zika virus on complex network is formulated and analyzed keeping in mind both mosquito-borne and sexual transmission of this disease. The existence and global stability of disease-free equilibrium are discussed in detail. The basic reproduction number R 0 of the model is computed and it is found that for R 0 < 1 , the disease-free equilibrium of the model is globally asymptotically stable under some condition. In addition to this the final size relation of the proposed model is also computed. The key parameters of the model are computed using curve fitting to the real data by least-square method. Sensitivity analysis and numerical simulation are also performed for our proposed model. Finally, this model is extended to optimal control problem, to find the suitable cost-effective and time-dependent control strategies to reduce the number of infectives in a desired interval of time. [ABSTRACT FROM AUTHOR]

Abstract The paper focuses on single and multiple current sensors fault detection and isolation (FDI) for induction motor (IM) drives using only two current sensors. Two model based diagnosis methods are proposed to estimate the current residuals dynamics in the stationary reference frame: The first one is a differential algebraic estimation of fault dynamics and the second one is based on a combination of the Robust Integral Sign of the Error (RISE) observer with the algebraic approach. After detecting the fault occurrence, a logic based decision unit is then built to identify the faulty sensors. The resulting residuals are robust to load torque disturbances. Moreover, the developed fault estimators are simple with a 1-D model, based only on the input–output measurements and their derivatives and do not require a bank of observers. Furthermore, the used residual threshold is well defined and is suitable for the whole operating range. The ability of diagnosing the recovery of a sensor from a fault is also demonstrated. The validity of the developed approaches is analytically proved and a comparative study is carried out between the two FDI schemes. [ABSTRACT FROM AUTHOR]

Abstract As a consequence of the rapid growth of vehicles in cities, urban traffic congestion has become more and more serious nowadays. As an effective control approach, Model Predictive Control (MPC) has been deeply studied for transportation management. However, the relatively complex on-line computing hinders MPC from being further applied on transportation system, especially for large scale transportation networks. Based on the refined store-and-forward model, we propose a signal split control approach with Explicit Model Predictive Control (EMPC) in this paper, by which the complexity of online optimization can be significantly reduced. With multi-parametric Quadratic Program (mp-QP), our approach can generate explicit signal control law, and then shifts the former repeated online signal split optimization offline. As a result, the real time signal control becomes an easier task by searching the lookup table corresponding to the transportation state. The simulation experiments demonstrate that our EMPC based approach outperforms the traditional fix-time signal control. Meanwhile, compared with traditional MPC based approach, our approach can decrease the total computation complexity, and then increase the applicability for real transportation system. [ABSTRACT FROM AUTHOR]

Simulation is a very important tool which has been used for several years in several fields (with computer and non computer systems). Given its importance, simulation has been used as soon as possible during a system’s design phase. This paradigm is called ”Simulation-Based Design” or SBD. Using SBD aims at eliminating unfit designs as early as possible before significant resources have been consumed. It is the process in which simulation is the primary means of evaluation and verification. In this paper, we give an overview about related works. We classify the related work in three classes: simulation to design non computer systems in several domains, simulation to design software and simulation to design Multi-Agent Systems, Self-Organizing Systems or Systems with Emergent Functionality. [ABSTRACT FROM AUTHOR]

Modeling the wetland plant–nutrient interaction is significant for elucidating the complex mechanisms of the nutrient absorption. In this paper, the effect of pollutant dispersal and impulsive input on the growth of wetland plant is presented. By using the theory of impulsive differential equations, we obtain that the wetland plant-eradication periodic solution is globally asymptotically stable if some conditions are satisfied. In addition, the permanent conditions are given by means of the comparison theorem of impulsive differential equations. Finally, numerical simulations are given to justify our results. [ABSTRACT FROM AUTHOR]

Knowledge of tumor growth kinetics constitutes a challenge for researchers. Different models have been used to describe data of unperturbed and perturbed tumors. The modified Gompertz equation had been proposed to describe diverse responses of direct current treated tumors (disease progression, stable disease, partial response and complete response). Nevertheless, diffusion processes involved in the tumor growth are not integrated in this equation. This paper analyzes the viscous modified Gompertz equation. It is shown that for certain input parameters the corresponding solutions decrease exponentially in appropriate time intervals. [ABSTRACT FROM AUTHOR]

Abstract: Real-time simulation allows rapid deployment and thorough testing of prototyped hardware in the automotive and aerospace industries. However, the simulation of power electronic circuits (PECs) in the context of PC-based simulations is challenging for several reasons, and imposes a limit in the 1–5kHz range to the achievable switching frequencies. As FPGA devices gain computing power, conducting the real-time simulation of PECs on chip becomes an attractive alternative. This paper demonstrates the feasibility of high-performance floating-point calculation engines aimed for the real-time simulation of PECs on high-end and low-cost FPGAs as well. The paper discusses emerging paradigms for reconfigurable floating-point computing that favor optimal performance and offer near double precision arithmetic at a minimal hardware cost. The effectiveness of the approach is demonstrated by considering three different circuit topologies and simulating their high-frequency stimulation (20kHz) using the same automated calculation engine. The considered circuits are a boost converter, a two-level three-phase bridge, and a two-level-three-phase bridge driven by a boost converter. [Copyright &y& Elsevier]

Abstract: Model-based predictive control (MBPC) for power-electronic converters offers fast and accurate control. Based on the prediction of the future system states the optimal control input sequence is obtained by calculating a cost for each sequence. The control objectives are expressed as terms in the cost function which are weighted to divide the control effort. However, selecting good values for the weight factors is not a trivial task. In this paper a method is discussed for the weight factor selection based on extensive system simulations. The simulation approach for the hybrid system of power electronic converter and its load is discussed as well. In this paper a specific application is considered: the combined output current and capacitor voltage control of a 4-level flying-capacitor converter (FCC). This inverter topology possesses important advantages, but the control is also challenging. The high computational burden of MBPC is often restrictive for a good implementation. In this paper the implementation in a field-programmable gate array (FPGA) of an efficient prediction and optimization calculation core for finite-set MBPC is discussed. The core is fully implemented in programmable digital logic and a good performance is obtained by exploiting the strong points of the FPGA: parallelism and pipe-lining. The calculation core can be used in three applications: for hardware co-simulations, for hardware acceleration with processor-based implementations and for full FPGA implementations. Experimental results obtained with an FPGA implementation are presented. [Copyright &y& Elsevier]

Abstract: The paper deals with the dynamic modeling of mechatronic devices, which usually need detailed modeling to be described and to take into account the physical properties of the VHDL-AMS, which is a powerful unified modeling language for mixed system, allows to describe a large range of physical systems, for their dynamic simulation. It allows to describe models of physical components and then to connect them to obtain the model of a system. However, this language cannot support the description of some physical phenomena, such local ones, defined by numerical methods (e.g.: finite element method, special numerical integrals). When an aspect of a model cannot be described in VHDL-AMS, the paper proposes to use software components. So, the aim of the paper is to propose a generic way to extend the computation capability of VHDL-AMS, by coupling the models described in VHDL-AMS with external ones specified as software components (where VHDL-AMS fails). The approach has been applied on several applications, among them the time simulation of an electrical plunger. [Copyright &y& Elsevier]

Abstract: The paper deals with a model of the homogenized fluid saturated porous material which recently was obtained by the authors using the asymptotic analysis of the Biot type medium characterized by the double porosity. The homogenized macroscopic model is featured by the fading memory effects arising from the microflow in the dual porosity. We derive the steady state formulations and discuss several topics related to the numerical implementation of the model, namely the solution procedure of the discretized microscopic problems, evaluation of the homogenized coefficients and an approximation of the convolution integrals of the macroscopic model, so that the fading memory effects are computationally tractable. Numerical examples are presented to illustrate the approximation schemes discussed in the paper. All computations were performed using the in-house developed finite element code SfePy allowing the multiscale simulations. Besides various potential engineering applications, the present model is intended for simulations of compact bone poroelasticity. [Copyright &y& Elsevier]

Abstract: Sparsified Randomization Monte Carlo (SRMC) algorithms introduced in our recent paper for solving systems of linear algebraic equations are extended to construct the SVD-based randomized low rank approximations for large matrices. We suggest some efficient implementations of SRMC based on low rank approximations, and give different applications. In particular, an important application we present in this paper is a fast simulation algorithm for a randomized approximation of non-homogeneous random fields based on a discrete version of the Karhunen-Loéve expansion. We present two examples of non-homogeneous random field simulation which include a long-correlated Lorenzian random field and the fractional Wiener process. Another application we deal in this paper concerns the randomized solvers for large linear systems. We suggest a hybrid method which combines SRMC with an algorithm for solving boundary integral equations based on a separation representation of the kernel. This method is illustrated in this paper by solving a 2D boundary integral equation from potential theory governing the Dirichlet problem for the Laplace equation. [Copyright &y& Elsevier]

Abstract: Multi-drive systems are frequently used in many industry applications such as in paper, textile, and plastic winding process. Adjustable speed drives are very sensitive to power quality problems in particular to voltage sags, short-duration reductions in the rms voltage. This paper presents a multi-drive management strategy to mitigate voltage sags based on the self-kinetic process energy recovery. Simulation and experimental results are shown to demonstrate the efficiency of the proposition. [ABSTRACT FROM AUTHOR]

Abstract: This paper proposes an alternative procedure to test for cointegration in smooth transition autoregressive (STAR) models. We consider the exponential STAR (ESTAR) and double logistic STAR (D-LSTAR) models. The proposed tests are -tests with a null hypothesis of no cointegration and an alternative hypothesis of cointegration with STAR adjustment. The procedure introduced in this paper employs a grid search to compute a test statistic. Monte Carlo simulations demonstrate that as compared to other tests, the proposed approach has better power when the persistence of the process toward equilibrium and the sample size increase. [Copyright &y& Elsevier]

Abstract: This paper examines how an asset price is determined in a market, and how it changes as circumstances in the market change, making use of a standard asset price model. The motivation of the paper is to examine if the model can explain a bubble economy in which individuals are risk averse. It is known that if the relative risk aversion of an investor''s utility function does not exceed 1 and is not decreasing, the equilibrium asset price declines when uncertainty increases with respect to the prospect of a dividend receipt. In this paper we examine if there is any utility function which provides the counter example, one in which the asset price rises despite increased uncertainty. Starting from a two period maximization problem with risk aversion, with certain dividends for the two periods, it is shown that if uncertainty is introduced for the second period, the exponential utility function provides this counter example. It is shown that in this particular case that the asset in question has the characteristics of a Giffen good when the asset price is already high. However, when uncertainty is introduced for two periods, the exponential utility function does not provide this counter example. Thus, when uncertainty is not as great, the income effect may raise the asset price despite increased uncertainty. It is also found that a quadratic utility function may explain the collapse of a bubble economy. The standard asset price model is formulated as the pure-exchange economy, without production. Finally, this paper points out that the existence of an asset price may be guaranteed even if production is incorporated into the standard model so long as a certain degree of uniformity is assumed about the distribution of the investors’ initial possession of assets. [Copyright &y& Elsevier]

Abstract: A risk assessment model for water shortage is constructed using a risk analysis method based on the information diffusion theory. The application of this model is demonstrated in the city of Yiwu in Zhejiang Province, China. Based on the analytical results from a small sample, this study indicates that the present model is more stable and effective than the traditional model. Risk assessment results are used to analyze the carrying capacity of water resources from an ecological angle. For this study, the carrying capacity of water resources is defined as the maximum volume of water suitable for supporting human activity in certain stages of social development that can be borne by water resources under favorable ecological conditions. Further study on Yiwu is also performed, with results indicating that water shortages in this city are not related to types of water source, but can be classified in terms of water quality and conservation. To verify the results of theoretical investigation in this paper, the authors simulate changes in the carrying capacity of water resources under the conditions of future water management policies. This simulation uses the system dynamics (SD) model, based on the historical data collected by the city over the past 20 years and governmental plans to raise inhabitants’ living standards between the present and 2020. The paper simultaneously indicates that both singularly pursuing fast economic development at the expense of the environment and promoting environmental protection via reduced economic development are undesirable for Yiwu. Simultaneously giving consideration to both the economic development and environmental protection is likely to produce better overall results. However, if the present water supply level is maintained but does not increase in the near future, Yiwu''s water supply will be unable to satisfy requirements even under this scheme. In this case, the carrying capacity of water resources in the region can only be effectively improved by promoting more efficient use of water and water conservation schemes, as well as strengthening long-term investment in environmental protection. [Copyright &y& Elsevier]

The paper is devoted to the numerical solution of both elliptic and parabolic problems by overlapping Schwarz methods. It demonstrates that while the two-level Schwarz method is necessary for the efficient solution of discrete elliptic problems, the one-level Schwarz method can be sufficiently efficient in the parabolic case. The paper includes results from numerical simulations of a large-scale model of the performance of a nuclear waste repository. [Copyright &y& Elsevier]

Abstract: Recent research has shown that it is possible to connect in series stator windings of multi-phase machines and control all the machines in the group independently using vector control principles, although the complete multi-drive system is supplied from a single multi-phase voltage source inverter (VSI). The concept has been investigated so far only for symmetrical n-phase machines (i.e., machines with spatial displacement between any two consecutive phases equal to 2π/n). This paper considers all possible configurations for the asymmetrical six-phase machines, with two three-phase stator windings displaced by 30°. Two possible two-motor configurations are presented. The first one utilises two quasi-six-phase machines while the second one connects in series a quasi-six-phase machine and a two-phase machine. Inverter current control schemes in both the stationary reference frame and the rotating reference frame are considered. Verification of the proposed multi-phase multi-machine drive is provided by simulation and the results are given in the paper. [Copyright &y& Elsevier]

Abstract: In this paper, the modelling of an autonomous variable speed micro hydropower station is presented. It is composed of a doubly fed induction generator linked mechanically and electrically to a permanent magnet synchronous machine which may recover or supply the slip power and which feeds the DFIG with its magnetizing reactive power leading to classical capacitor removing. The model lies on a classical approach, based on a Park representation, and on an energetic macroscopic representation (EMR). In its first part, this paper develops the modelling principles and underlines the complementarity of both approaches. The control strategy is then depicted in the case of passive loads supplying. Finally, some simulation results are showed and commented. [Copyright &y& Elsevier]

Abstract: Agent-based simulation is a decision support tool that has recently been used by park managers to better plan the development of tourist infrastructure such as paths, buildings and viewing platforms and to understand the relationships between visitor flows and acceptable levels of crowding. The objective in these studies is to simulate the current and projected movement of individuals in relationship to pedestrian infrastructure or management actions to determine the impact on visitor experience and infrastructure capacity. A number of projects have been undertaken in Australia and the United States using agent-based models. However, research has shown that there is a need for new methods to collect calibration and validation data in order to validate spatial/temporal simulation models. This paper presents the results of experiments designed to track humans at the Twelve Apostles National Park, Victoria, Australia over 3 days in an effort to develop typologies of trip itineraries. The research used running race timing equipment known as the Alge timing system to monitor the movement of people in the park along a constrained network. A series of receivers recorded the precise positions of 900 individuals who were wearing unobtrusive ankle transmitters. This paper examines the technical aspects of tracking humans using race-timing technology and proposes some methods to analyse this data to determine whether typologies of tourist behaviour do indeed exist. The research also comments on the utility of the data to address the requirements of the recreational behaviour simulator, an agent-based modeling framework which has been used extensively for national park management. [Copyright &y& Elsevier]

Abstract: The simulation model is a proven tool in solving nonlinear and stochastic problems and allows examination of the likely behavior of a proposed manufacturing system under selected conditions. However, it does not provide a method for optimization. A practical problem often embodies many characteristics of a multiresponse optimization problem. The present paper proposes to solve the multiresponse simulation-optimization problem by a multiple-attribute decision-making method—a technique for order preference by similarity to ideal solution (TOPSIS). The method assumes that the control factors have discrete values and that each control factor has exactly three control levels. Taguchi quality-loss functions are adapted to model the factor mean and variance effects. TOPSIS is then used to find the surrogate objective function for the multiple responses. The present paper predicts the system performances for any combination of levels of the control factors by using the main effects of the control factors according to the principles of a robust design method. The optimal design can then be obtained. A practical case study from an integrated-circuit packaging company illustrates the efficiency and effectiveness of the proposed method. Finally, constraints of the proposed method are addressed. [Copyright &y& Elsevier]

In this paper, the Takagi–Sugeno (T–S) fuzzy model representation is extended to the stability analysis for nonlinear interconnected systems with multiple time-delays using linear matrix inequality (LMI) theory. In terms of Lyapunov’s direct method for multiple time-delay fuzzy interconnected systems, a novel LMI-based stability criterion which can be solved numerically is proposed. Then, the common P matrix of the criterion is obtained by LMI optimization algorithms to guarantee the asymptotic stability of nonlinear interconnect systems with multiple time-delay. Finally, the proposed stability conditions are demonstrated with simulations throughout this paper. [Copyright &y& Elsevier]

This paper presents an extension of a previously-described framework for the specification and manipulation of models of systems. The original framework and its extension include a convenient application programming interface (API), and this paper describes examples of the use of this API in the context of graphical simulation. These examples include the simulation of objects whose definition involves torques, and a brief description of the simulation of air and smoke by means of a model involving particles moving in fluid. [Copyright &y& Elsevier]

In this paper, two new maximum likelihood methods are proposed to estimate the unknown sample size n in a simple random sample from an absolutely continuous population. These methods are based on the number of records and the record values in the sample. The use of these methods is explored through simulations. An application to a real data set is also included. [ABSTRACT FROM AUTHOR]

Abstract: Multi-wing chaotic attractors are highly complex nonlinear dynamical systems with higher number of index-2 equilibrium points. Due to the presence of several equilibrium points, randomness and hence the complexity of the state time series for these multi-wing chaotic systems is much higher than that of the conventional double-wing chaotic attractors. A real-coded genetic algorithm (GA) based global optimization framework has been adopted in this paper as a common template for designing optimum Proportional-Integral-Derivative (PID) controllers in order to control the state trajectories of four different multi-wing chaotic systems among the Lorenz family viz. Lu system, Chen system, Rucklidge (or Shimizu Morioka) system and Sprott-1 system. Robustness of the control scheme for different initial conditions of the multi-wing chaotic systems has also been shown. [Copyright &y& Elsevier]

Abstract: One of the most difficult tasks in subsurface flow simulations is the reliable characterization of properties of the subsurface. A typical situation employs dynamic data integration such as sparse (in space and time) measurements to be matched with simulated responses associated with a set of permeability and porosity fields. Among the challenges found in practice are proper mathematical modeling of the flow, persisting heterogeneity in the porosity and permeability, and the uncertainties inherent in them. In this paper we propose a Bayesian framework Monte Carlo Markov Chain (MCMC) simulation to sample a set of characteristics of the subsurface from the posterior distribution that are conditioned to the production data. This process requires obtaining the simulated responses over many realizations. In reality, this can be a prohibitively expensive endeavor with possibly many proposals rejection, and thus wasting the computational resources. To alleviate it, we employ a two-stage MCMC that includes a screening step of a proposal whose simulated response is obtained via an inexpensive coarse-scale model. A set of numerical examples using a two-phase flow problem in an oil reservoir as a benchmark application is given to illustrate the procedure and its use in predictive simulation. [Copyright &y& Elsevier]

Abstract: This paper considers a discontinuous dynamical observers stack and presents its possible application in the framework of fault detection and isolation (FDI) problems. Non-standard forms for the discontinuous observer injection signals, based on second-order sliding-mode techniques with dynamical sliding manifolds, are employed in the present work. A unified treatment covering at the same time integer-order and fractional-order (FO) dynamics is developed. Appropriate non-smooth Lyapunov analysis is made to support the theoretical properties of the suggested FDI observers, which yields simple tuning formulas for the corresponding parameters. Numerical implementation aspects are discussed. Finally, simulation and experimental results are presented to support the theoretical treatment, which confirm the expected performance. [Copyright &y& Elsevier]

Abstract: This paper reviews maximum power point tracking (MPPT) algorithms dedicated for small wind turbines (SWTs). Many control strategies with different features are available and it is very important to select proper one in order to achieve best performance and low cost. Three most widely used algorithms are discussed. Two are based on turbine static parameters such as power versus rotational speed characteristic P m (ω) and optimum tip-speed ratio λ opt . Third one, which seems to be most promising, iteratively searches for optimum operating point and it does not require prior knowledge of the turbine. This work attempts to summarize and compare these algorithms. Detailed description of each one is made with most significant qualities emphasized. Discussion is supported by the simulation studies using Synopsys Saber software. Results for 5kW SWT with diode rectifier and DC/DC boost converter are shown and commented. [Copyright &y& Elsevier]

Abstract: Although three-phase open-end winding drives have been under investigation for two decades, there is hardly any work available related to multiphase (more than three phases) open-end winding drive structures. This paper extends one possible PWM technique, recently introduced in conjunction with five-phase drives, to seven- and nine-phase open-end winding structures. Both multiphase inverters are two-level and require two isolated dc sources of equal voltage values. The technique, termed unequal reference sharing (URS), is explained and subsequently applied in simulations to examine the performance of the drive systems. Benchmarking is performed with respect to the equivalent single-sided supply with a two-level inverter and with respect to another PWM method recently developed for the dual-inverter supply structure. This enables a comparison of the achievable performance in single-sided and dual-inverter supply modes. Simulation results are given for both phase numbers. The THDs, obtained in this manner, are compared throughout the modulation index range for both phase numbers as well. The simulation results are verified experimentally on a seven-phase laboratory set-up in the whole linear modulation index range. [Copyright &y& Elsevier]

Abstract: High aspect-ratio grids are required for accurate solution of boundary layer and wake flow. An approach for the efficient generation of isotropic and stretched viscous unstructured grids is introduced in this paper. The proposed grid generation algorithm starts with a very coarse initial grid. In far field regions, isotropic cells of excellent quality are produced using a combination of point insertion and cell subdivision techniques. Simultaneously, a directional grid refinement strategy is used to construct highly stretched triangular cells in viscous dominated regions. First, anisotropic unstructured grids are produced in the stream-wise direction. Then, cells close to the solid surface are refined to highly stretched layer of triangles suitable for boundary layer region. The accuracy of the current grid generation approach is assessed by laminar and turbulent compressible flow solutions around NACA0012, RAE2822, and NHLP multi-element airfoils. Numerical flow simulation results are compared with published data. Comparisons point to accuracy of the proposed unstructured viscous grid generation procedure. [Copyright &y& Elsevier]

Abstract: Random orthogonal matrix (ROM) simulation is a very fast procedure for generating multivariate random samples that always have exactly the same mean, covariance and Mardia multivariate skewness and kurtosis. This paper investigates how the properties of parametric, data-specific and deterministic ROM simulations are influenced by the choice of orthogonal matrix. Specifically, we consider how cyclic and general permutation matrices alter their time-series properties, and how three classes of rotation matrices – upper Hessenberg, Cayley, and exponential – influence both the unconditional moments of the marginal distributions and the behaviour of skewness when samples are concatenated. We also perform an experiment which demonstrates that parametric ROM simulation can be hundreds of times faster than equivalent Monte Carlo simulation. [Copyright &y& Elsevier]

Abstract: The paper deals with photosynthetic microorganism growth modelling and simulation in a distributed parameter system. Main result concerns the development and comparison of two modeling frameworks for photo-bioreactor modelling. The first “classical” approach is based on PDE (reaction–turbulent diffusion system) and finite difference method. The alternative approach is based on random walk model of transport by turbulent diffusion. The complications residing in modelling of multi-scale transport and reaction phenomena in microalgae are clarified and the solution is chosen. It consists on phenomenological state description of microbial culture by the lumped parameter model of photosynthetic factory (PSF model) in the re-parametrized form, published recently in this journal by Papáček, et al. (2010). Obviously both approaches lead to the same simulation results, nevertheless they provide different advantages. [Copyright &y& Elsevier]

Abstract: In this paper, conceptual modeling as well as numerical simulation of two-phase flow in deep, deformable geological formations induced by CO2 injection are presented. The conceptual approach is based on balance equations for mass, momentum and energy completed by appropriate constitutive relations for the fluid phases as well as the solid matrix. Within the context of the primary effects under consideration, the fluid motion will be expressed by the extended Darcy''s law for two phase flow. Additionally, constraint conditions for the partial saturations and the pressure fractions of carbon dioxide and brine are defined. To characterize the stress state in the solid matrix, the effective stress principle is applied. Furthermore, the interaction of fluid and solid phases is illustrated by constitutive models for capillary pressure, porosity and permeability as functions of saturation. Based on this conceptual model, a coupled system of nonlinear differential equations for two-phase flow in a deformable porous matrix (H2M model) is formulated. As the displacement vector acts as primary variable for the solid matrix, multiphase flow is simulated using both pressure/pressure or pressure/saturation formulations. An object-oriented finite element method is used to solve the multi-field problem numerically. The capabilities of the model and the numerical tools to treat complex processes during CO2 sequestration are demonstrated on three benchmark examples: (1) a 1-D case to investigate the influence of variable fluid properties, (2) 2-D vertical axi-symmetric cross-section to study the interaction between hydraulic and deformation processes, and (3) 3-D to test the stability and computational costs of the H2M model for real applications. [Copyright &y& Elsevier]

Abstract: In this paper, we introduce fractional-order derivatives into a model of HIV infection of CD4+ T-cells with time delay. We deal with the stability of both the viral free equilibrium and the infected equilibrium. Criteria are given to ensure that both the equilibria are asymptotically stable for all delay under some conditions. Numerical simulations are carried out to illustrate the results. [Copyright &y& Elsevier]

Abstract: Evaluation of the distance between the electrodes, voltage applied to them, and number of electrodes in tumor growth kinetics is very useful for effective tumor destruction when electrotherapy is used. However, a study of this type has not yet been proposed. The aim of this paper is to simulate the influence of such parameters and the point–point electrode configuration on the tumor growth kinetics through a Modified Gompertz Equation. The results show a good agreement between the simulations performed in this study and the experimental results reported by our group and other authors. A critical distance between electrodes and a threshold ratio between the applied electric field and that distributed in the tumor are revealed, for which higher electrotherapy antitumor effectiveness is reached. In conclusion, electrotherapy antitumor effectiveness not only depends on the distance between the electrodes, voltage applied to them, and number of electrodes, but also on the ratio between the applied electric field and that distributed in the tumor. In addition, the results of these simulations may be used to help physicians choose the most appropriate treatment for patients with malignant solid tumors, as we have implemented in a current clinical trial. [Copyright &y& Elsevier]

Abstract: In this paper, a variable gain design approach for the high-gain disturbance observer, called Proportional-Integral-Observer (PI-Observer), is proposed to solve the problem of choosing suitable observer gains. The high-gain PI-Observer is successfully applied to estimate unknown inputs of systems together with the system states. It is known that reasonable estimations of unknown inputs can only be derived using high observer gains. On the other hand, extremely large gains will cause serious problems with respect to measurements noise and unmodeled dynamics. According to the analysis of the estimation quality regarding to the factors which influence the estimation results, the optimal level of observer gains is changing during the estimation, an online adaption for the observer gains is therefore developed. The designed PI-Observer, called Advanced PI-Observer (API-Observer), will use changing observer gains from the adaption algorithm, which is proved to give stable estimation error dynamics. Simulation results from an elastic beam example are shown to illustrate the implementation of the API-Observer. [Copyright &y& Elsevier]

Abstract: In this paper we consider the simulation of probabilistic chemical reactions in isothermal and adiabatic conditions. Models for reactions under isothermal conditions result in advection equations, adiabatic conditions yield the reactive Euler equations. In order to treat with scattering data, the equations are projected onto the polynomial chaos space. Scattering data can largely affect the estimation of quantities in the system, including variable optimization. This is demonstrated on a selective non-catalytic reduction of nitric oxide. [Copyright &y& Elsevier]

Abstract: This paper considers identification problems of multirate multiple-input output error systems, derives the input-output representations by using the state space models of the multirate systems, and presents two auxiliary model based recursive least squares algorithms for the corresponding output error models with each subsystem having different or same denominator polynomials. The simulation results show the effectiveness of the proposed algorithms. [Copyright &y& Elsevier]

Abstract: Ranking and selection (R&S) procedures have been considered an effective tool to solve simulation optimization problems with a discrete and finite decision space. Control variate (CV) is a variance reduction technique that requires no intervention in the way the simulation experiment is performed, and the least-squares regression package needed to implement CV is readily available. In this paper we propose two provably valid selection procedures that employ weighted CV estimators in different ways. Both procedures are guaranteed to select the best system with a prespecified confidence level. Empirical results and simple analyses are performed to compare the efficiency of our new procedures with some existing procedures. [Copyright &y& Elsevier]

Abstract: After investigating the effect of the frequency of an external electrical stimulation on the chaotic dynamics of a single FitzHugh–Nagumo (FHN) neuron, this paper derives both a sufficient and a necessary condition of the coupling coefficient for self-synchronization of two interacting FHN neurons by using the Lyapunov function method and the largest transverse Lyapunov exponent, respectively. Also, for the cases that self-synchronization is not achieved through the coupling coefficient, a feedback control law for synchronization using the Lyapunov method is investigated. The performance of the proposed control law is compared with that of an existing one in the literature. Simulation results are provided. [Copyright &y& Elsevier]

Abstract: In this paper, we explore the loss data collection exercise for operational risk in Chinese commercial banks from 1999 to first half of 2006. Firstly, the above data are bootstrapped to analyze the capital allocation for a medium-scaled commercial bank in China. Secondly, for every selected cell, we calibrate two truncated distributions to fit the loss severity, one for ‘normal’ losses and the other for the ‘extreme’ losses. Moreover, a more realistic dependence structure – multivariate t copula function is used to measure the relation among the selected cells. In the final, the simulation results suggest that substantial savings can be achieved through measuring the dependence by means of multivariate t copula function than by means of perfect positive dependence. [Copyright &y& Elsevier]

Abstract: In this paper, we propose a new model of a three-parameter stochastic growth, based on a stochastic gamma diffusion process, with a third, threshold, parameter. This model can be considered a stochastic version of a three-parameter deterministic growth curve, structured such that its trend function is of the type given by this same growth curve. We develop the statistical inference of this model on the basis of maximum likelihood methodology, analysing on simulated data the computational problem associated with the threshold parameter, a problem that is of great importance in its application to real data. [Copyright &y& Elsevier]

Abstract: In this paper we present a finite element approximation of a model of a linear stochastic partial differential equation driven by additive and multiplicative white noises. Using the Wick-product properties and the Wiener–Itô chaos expansion, the stochastic variational problem is reformulated as a set of deterministic variational problems. To obtain the chaos coefficients in the corresponding deterministic equations, we use the usual Galerkin finite element method. Once this approximation is performed, the statistics of the numerical solution can be easily evaluated. [Copyright &y& Elsevier]

Abstract: This paper proposes a Nash equilibrium model that applies continuous time replicator dynamics to the analysis of oligopoly markets. The robustness of the proposed simple Nash equilibrium model under the simultaneous constraints of allocation of product and market share using a simulation method to derive an optimal solution for production decisions by rival firms in oligopoly markets is tested by changing profit and cost function parameters, as well as the initial production values and market shares of the firms examined in this study. The effects of differences in conjectural variation and initial allocation of market share on the convergent values are considered, particularly in the case of corner solutions. This approach facilitates the understanding of the robustness of attaining equilibrium in an oligopoly market. [Copyright &y& Elsevier]