Analytical network modeling of heterogeneous large-scale cluster systems

The study of the communication networks for distributed systems is very important, since the overall performance of these systems is often depends on the effectiveness of its communication network. In this paper, we address the problem of networks modeling for heterogeneous large-scale cluster systems. We consider the large-scale cluster systems as a typical cluster of clusters system. Since the heterogeneity is becoming common in such systems, we take into account network as well as cluster size heterogeneity to propose the model. To this end, we present an analytical network model and validate the model through comprehensive simulation. The results of the simulation demonstrated that the proposed model exhibits a good degree of accuracy for various system organizations and under different working conditions.

Analytical modeling of communication latency in multi-cluster systems

This paper addresses the problem of performance modeling of large-scale distributed systems with emphasis on communication networks in heterogeneous multi-cluster systems. The study of interconnection networks is important because the overall performance of a distributed system is often critically hinged on the effectiveness of this part. We present an analytical model to predict message latency in multi-cluster systems in the presence of processor heterogeneity. The model is validated through comprehensive simulation, which demonstrates that the proposed model exhibits a good degree of accuracy for various system sizes and under different operating conditions.

Performance modeling and analysis of heterogeneous meta-computing systems interconnection networks

The overall performance of a distributed system often depends on the effectiveness of its interconnection network. Thus, the study of the communication networks for distributed systems is very important, which is the focus of this paper. In particular, we address the problem of interconnection networks performance modeling for heterogeneous meta-computing systems. We consider the meta-computing system as a typical multi-cluster system. Since the heterogeneity is becoming common in such systems, we take into account network as well as cluster size heterogeneity to propose the model. To this end, we present an analytical network model and validate the model through comprehensive simulation. The results of the simulation demonstrated that the proposed model exhibits a good degree of accuracy for various system organizations and under different working conditions.

Modeling and simulation for large scale production systems

Computer modeling and simulation provide a foundation upon which industrial processes and systems can be transformed and innovation dramatically accelerated. Computer modeling and simulation is also an indispensable tool of the information age, used extensively in design, analysis, operations, decision-making, optimization, and education and training. Manufacturing, production and design relies upon simulation to develop efficient production systems and factories that produce quality products. Simulation in industry has yet to meet its full potential. The development of models is very time consuming, particularly for geometries of complex engineering systems such as manufacturing plants, automobiles, aircraft and ships. Computer simulation allows scientists and engineers to understand and predict three-dimensional and time-dependent phenomena in science and engineering discipline. This talk will focus on challenges associated with modeling and simulation in the manufacturing sector and through a number of case studies highlight the benefits gained through the use of such technologies.

Interpreting and modeling baggage handling systems as a system of systems

The topic of systems of systems has been one of the most challenging areas in science and engineering due to its multidisciplinary scope and inherent complexity. Despite all attempts carried out so far in both academia and industry, real world applications are far remote. The purpose of this paper is to modify and adopt a recently developed modeling paradigm for system of systems and then employ it to model a generic baggage handling system of an airport complex. In a top-down design approach, we start modeling process by definition of some modeling goals that guide us in selection of some high level attributes. Then functional attributes are defined which act as ties between high level attributes (the first level of abstraction) and low level metrics/measurements. Since the most challenging issues in developing models for system of systems are identification and representation of dependencies amongst constituent entities, a machine learning technique is adopted for addressing these issues.

Efficient management of drinking water distribution systems through the application of water quality modeling

The quality of drinking water generally degrades when it is delivered through a distribution system due to the decay of disinfectant, which subsequently allows the re-growth of microorganisms in the distribution system. A model that describes the changes that occur in the water quality in distribution system is needed to determine whether to enhance the treatment processes or to improve the distribution system so that microbiological criteria are met. This paper describes how chlorine decay kinetics are modeled and the model output is used in finding the elements that are contributing to the consumption of chlorine at the treatment plant other than the water itself; this allows better control of chlorine dosing at the treatment plant, which in tum will reduce the formation of disinfectant by-products. In addition, the model will accurately predict the decay due to the organic/inorganic and nitrogenous compounds that are remaining in the water at any point in the distribution system, which will indicate the status of the distribution system with respect to its chlorine consumption. Further, if re-chlorination is introduced in the distribution system downstream of the treatment plant, the model will predict the chlorine decay due to the slow reacting organic and nitrogenous compounds accurately.

Interval-based and fuzzy set-based approaches to modeling of fuzzy inference systems with the local monotonicity property

Even though the importance of the local monotonicity property for function approximation problems is well established, there are relative few investigations addressing issues related to the fulfillment of the local monotonicity property in Fuzzy Inference System (FIS) modeling. We have previously conducted a preliminary study on the local monotonicity property of FIS models, with the assumption that the extrema point(s) (i.e., the maximum and/or minimum point(s)) is either known precisely or totally unknown. However, in some practical situations, the extrema point(s) can be known imprecisely (as an interval or a fuzzy set). In this paper, the imprecise information is exploited to construct an FIS model that fulfills the local monotonicity property. A procedure to estimate the extrema point(s) of a function is devised. Applicability of the findings to a datadriven modeling problem is further demonstrated.

Analytical modeling of partially shaded photovoltaic systems

As of today, the considerable influence of select environmental variables, especially irradiance intensity, must still be accounted for whenever discussing the performance of a solar system. Therefore, an extensive, dependable modeling method is required in investigating the most suitable Maximum Power Point Tracking (MPPT) method under different conditions. Following these requirements, MATLAB-programmed modeling and simulation of photovoltaic systems is presented here, by focusing on the effects of partial shading on the output of the photovoltaic (PV) systems. End results prove the reliability of the proposed model in replicating the aforementioned output characteristics in the prescribed setting. The proposed model is chosen because it can, conveniently, simulate the behavior of different ranges of PV systems from a single PV module through the multidimensional PV structure.

Contagion in financial networks: a network theory and agent-based approaches to modeling the spread of risk in financial systems

Esta dissertação estuda a propagação de crises sobre o sistema financeiro. Mais especi- ficamente, busca-se desenvolver modelos que permitam simular como um determinado choque econômico atinge determinados agentes do sistema financeiro e apartir dele se propagam, transformando-se em um problema sistêmico. A dissertação é dividida em dois capítulos,além da introdução. O primeiro capítulo desenvolve um modelo de propa- gação de crises em fundos de investimento baseado em ciência das redes.Combinando dois modelos de propagação em redes financeiras, um simulando a propagação de perdas em redes bipartites de ativos e agentes financeiros e o outro simulando a propagação de perdas em uma rede de investimentos diretos em quotas de outros agentes, desenvolve-se um algoritmo para simular a propagação de perdas através de ambos os mecanismos e utiliza-se este algoritmo para simular uma crise no mercado brasileiro de fundos de investimento. No capítulo 2,desenvolve-se um modelo de simulação baseado em agentes, com agentes financeiros, para simular propagação de um choque que afeta o mercado de operações compromissadas.Criamos também um mercado artificial composto por bancos, hedge funds e fundos de curto prazo e simulamos a propagação de um choque de liquidez sobre um ativo de risco securitizando utilizado para colateralizar operações compromissadas dos bancos.

Parameterized fast decoupled power flow methods for obtaining the maximum loading point of power systems. Part I. Mathematical modeling

The conventional Newton and fast decoupled power flow (FDPF) methods have been considered inadequate to obtain the maximum loading point of power systems due to ill-conditioning problems at and near this critical point. It is well known that the PV and Q-theta decoupling assumptions of the fast decoupled power flow formulation no longer hold in the vicinity of the critical point. Moreover, the Jacobian matrix of the Newton method becomes singular at this point. However, the maximum loading point can be efficiently computed through parameterization techniques of continuation methods. In this paper it is shown that by using either theta or V as a parameter, the new fast decoupled power flow versions (XB and BX) become adequate for the computation of the maximum loading point only with a few small modifications. The possible use of reactive power injection in a selected PV bus (Q(PV)) as continuation parameter (mu) for the computation of the maximum loading point is also shown. A trivial secant predictor, the modified zero-order polynomial which uses the current solution and a fixed increment in the parameter (V, theta, or mu) as an estimate for the next solution, is used in predictor step. These new versions are compared to each other with the purpose of pointing out their features, as well as the influence of reactive power and transformer tap limits. The results obtained with the new approach for the IEEE test systems (14, 30, 57 and 118 buses) are presented and discussed in the companion paper. The results show that the characteristics of the conventional method are enhanced and the region of convergence around the singular solution is enlarged. In addition, it is shown that parameters can be switched during the tracing process in order to efficiently determine all the PV curve points with few iterations. (C) 2003 Elsevier B.V. All rights reserved.

Mathematical modeling and control of population systems: Applications in biological pest control

The aim of this paper is to apply methods from optimal control theory, and from the theory of dynamic systems to the mathematical modeling of biological pest control. The linear feedback control problem for nonlinear systems has been formulated in order to obtain the optimal pest control strategy only through the introduction of natural enemies. Asymptotic stability of the closed-loop nonlinear Kolmogorov system is guaranteed by means of a Lyapunov function which can clearly be seen to be the solution of the Hamilton-Jacobi-Bellman equation, thus guaranteeing both stability and optimality. Numerical simulations for three possible scenarios of biological pest control based on the Lotka-Volterra models are provided to show the effectiveness of this method. (c) 2007 Elsevier B.V. All rights reserved.

A new three-phase transformer modeling for three-phase harmonic analysis in distribution systems

This work presents a new three-phase transformer modeling suitable for simulations in Pspice environment, which until now represents the electrical characteristics of a real transformer. It is proposed the model comparison to a three-phase transformer modeling present in EMTP - ATP program, which includes the electrical and magnetic characteristics. In addition, a set including non-linear loads and a real three-phase transformer was prepared in order to compare and validate the results of this new proposed model. The three-phase Pspice transformer modeling, different from the conventional one using inductance coupling, is remarkable for its simplicity and ease in simulation process, since it uses available voltage and current sources present in Pspice program, enabling simulations of three-phase network system including the most common configuration, three wires in the primary side and four wires in the secondary side (three-phases and neutral). Finally, the proposed modeling becomes a powerful tool for three-phase network simulations due to its simplicity and accuracy, able to simulate and analyze harmonic flow in three-phase systems under balanced and unbalanced conditions.

Structural deformation monitored by vibrational properties and orbital modeling in (Pb,Sm)TiO3 systems

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)