Sharif Digital Repository

In a gas transmission network (GTN), faults can easily propagate due to the interconnections of streams. The main objective of this paper is to develop a systematic framework for an online decision support system (DSS) in order to make the right decisions to get the GTN out of critical conditions (which cannot be handled by the plant controllers) smoothly. One of the key features of the proposed scheme is its lack of dependence on prior knowledge of the fault signals (e.g., number of faults, and their origin). In this article, the GTN is modeled by a fuzzy directed graph (FDG). The proposed approach utilizes a reasoning algorithm based on the deviations that exist in the process variables... 

Recently production optimization has gained increasing interest in the petroleum industry. The most computationally expensive part of the production optimization process is the evaluation of the objective function performed by a numerical reservoir simulator. Employing surrogate models (a.k.a. proxy models) as a substitute for the reservoir simulator is proposed for alleviating this high computational cost.In this study, a novel approach for constructing adaptive surrogate models with application in production optimization problem is proposed. A dynamic Artificial Neural Networks (ANNs) is employed as the approximation function while the training is performed using an adaptive sampling... 

Normal basis multiplication in finite fields is vastly utilized in different applications, including error control coding and the like due to its advantageous characteristics and the fact that squaring of elements can be obtained without hardware complexity. In this brief, we present decomposition algorithms to develop novel systolic structures for digit-level Gaussian normal basis multiplication over GF (2m). The proposed architectures are suitable for high-performance applications, which require fast computations in finite fields with high throughputs. We also present the results of our application-specific integrated circuit synthesis using a 65-nm standard-cell library to benchmark the... 

Abstract In this paper, the solution of multi-group neutron/adjoint equation using Finite Element Method (FEM) for hexagonal and rectangular reactor cores is reported. The spatial discretization of the neutron diffusion equation is performed based on two different Finite Element Methods (FEMs) using unstructured triangular elements generated by Gambit software. Calculations are performed using Galerkin and Generalized Least Squares FEMs; based on which results are compared. Using the power iteration method for the neutron and adjoint calculations, the neutron and adjoint flux distributions with the corresponding eigenvalues are obtained. The results are then validated against the valid... 

New heuristic filters are proposed for state estimation of nonlinear dynamic systems based on particle swarm optimization (PSO) and differential evolution (DE). The methodology converts state estimation problem into dynamic optimization to find the best estimate recursively. In the proposed strategy the particle number is adaptively set based on the weighted variance of the particles. To have a filter with minimal parameter settings, PSO with exponential distribution (PSO-E) is selected in conjunction with jDE to self-adapt the other control parameters. The performance of the proposed adaptive evolutionary algorithms i.e. adaptive PSO-E, adaptive DE and adaptive jDE is studied through a... 

Finding a Pareto-optimal frontier is widely favorable among researchers to model existing conflict objectives in an optimization problem. Project scheduling is a well-known problem in which investigating a combination of goals eventuate in a more real situation. Although there are many different types of objectives based on the situation on hand, three basic objectives are the most common in the literature of the project scheduling problem. These objectives are: (i) the minimization of the makespan, (ii) the minimization of the total cost associated with the resources, and (iii) the minimization of the variability in resources usage. In this paper, three genetic-based algorithms are proposed... 

Energy reduction in embedded processors is a must since most embedded systems run on batteries and processor energy reduction helps increase usage time before needing a recharge. Register files are among the most power consuming parts of a processor core. Register file power consumption mainly depends on its size (height as well as width), especially in newer technologies where leakage power is increasing. We provide a register file architecture that, depending on the application behavior, dynamically (i) adapts the width of individual registers, and (ii) puts partitions of temporarily unused registers into low-power mode, so as to save both static and dynamic power. We show that our scheme... 

In this study, cell-centered (CC) and cell-vertex (CV) finite volume (FV) approaches are applied and assessed for the simulation of two-dimensional structural dynamics on arbitrary quadrilateral grids. For the calculation of boundary nodes displacement in the CC FV approach, three methods are employed. The first method is a simple linear regression of displacement of boundary nodes from the displacement of interior cell centers. In the second method, an extrapolation technique is applied for this purpose and, in the third method; the line boundary cell technique is incorporated into the solution algorithm in an explicit manner. To study the effects of grid irregularity on the results of CC... 

The current study aims at introducing a 2D and fast-running code for the issues pertinent to design, analysis and safety in modular high temperature reactors. While the porous media approach is only applied to pebble bed type, the analysis in this paper covers both pebble bed and prismatic reactor. A time-dependent mass equation along with energy conservation equation for the cooling gas and a time-dependent energy conservation equation for the solid was solved. Appropriate series of constitutive equations (e.g. heat transfer coefficient, effective heat conductivity of solid, heat transfer coefficient, pressure drop etc.) has been recruited as well. In addition a finite-volume method is... 

Process variation has already emerged as a major concern in design of multi-processor system on chips (MPSoC). In recent years, there have been several attempts to bring variability awareness into the task scheduling process of embedded MPSoCs to improve performance yield. This study attempts to provide a comparative study of the current variation-aware design-time task and communication scheduling techniques that target embedded MPSoCs. To this end, the authors first use a sign-off variability modelling framework to accurately estimate the frequency distribution of MPSoC components. The task scheduling methods are then compared in terms of both the quality of the final solution and the... 

This paper surveys the literature associated with the application of evolutionary algorithms (EAs) in coastal groundwater management problems (CGMPs). This review demonstrates that previous studies were mostly relied on the application of limited and particular EAs, mainly genetic algorithm (GA) and its variants, to a number of specific problems. The exclusive investigation of these problems is often not the representation of the variety of feasible processes may be occurred in coastal aquifers. In this study, eight EAs are evaluated for CGMPs. The considered EAs are: GA, continuous ant colony optimization (CACO), particle swarm optimization (PSO), differential evolution (DE), artificial bee... 

In this paper, a framework for distributed and decentralized state estimation in high-pressure and long-distance gas transmission networks (GTNs) is proposed. The non-isothermal model of the plant including mass, momentum and energy balance equations are used to simulate the dynamic behavior. Due to several disadvantages of implementing a centralized Kalman filter for large-scale systems, the continuous/discrete form of extended Kalman filter for distributed and decentralized estimation (DDE) has been extended for these systems. Accordingly, the global model is decomposed into several subsystems, called local models. Some heuristic rules are suggested for system decomposition in gas pipeline... 

Data stream classification is one of the most challenging areas in the machine learning. In this paper, we focus on three major challenges namely infinite length, concept-drift and concept-evolution. Infinite length causes the inability to store all instances. Concept-drift is the change in the underlying concept and occurs in almost every data stream. Concept-evolution, in fact, is the arrival of novel classes and is an undeniable phenomenon in most real world data streams. There are lots of researches about data stream classification, but most of them focus on the first two challenges and ignore the last one. In this paper, we propose new method based on ensembles whose classifiers use... 

Delay in communication wires causes design iterations in system-on-chip. Latency-insensitive design copes with this issue by encapsulating each core in a shell wrapper and inserting buffers in the wires to separate the design of core from that of communication wires. Scheduling-based latency-insensitive protocol is a methodology which employs shift registers for periodic clock gating of blocks instead of the shell wrappers. In many cases, the bit sequences inside the shift registers are too long and therefore consume a large area. This study presents a heuristic algorithm that optimises the bit sequences and produces them with shorter lengths compared with the existing method. The algorithm... 

Human Brain is one of the most wonderful and complex systems which is designed for ever; A huge complex network composed of neurons as tiny biological and chemical processors which are distributed and work together as a super parallel system to do control and vital activities of human body. Brain learning simulation and hardware implementation is one of the most interesting research areas in order to make artificial brain. One of the researches in this area is Active Learning Method in brief ALM. ALM is an adaptive recursive fuzzy learning algorithm based on brain functionality and specification which models a complex Multi Input Multi Output System as a fuzzy combination of Single Input... 

Supply Chain Operations Reference (SCOR) model is developed and maintained by the Supply Chain Council (SCC). The model is a reference model which can be used to map, benchmark and improve the supply chain operations. SCOR model provides companies with a basic process modeling tool, an extensive benchmark database and defines a set of supply chain metrics. Mobarakeh Steel Company (located in Isfahan, Iran) initiated the project of studying and analyzing its supply chain performance based on the SCOR model. This paper explains the steps and the results of the project. Interviews with the managers and considering the documents on the four major subjects of planning, logistics, information flow... 

This paper presents the results of validation of an open source Direct Simulation Monte Carlo (DSMC) code for general application to rarefied gas flows. The new DSMC code, called dsmcFoam, has been written within the framework of the open source C++ CFD toolbox OpenFOAM. The main features of dsmcFoam code include the capability to perform both steady and transient solutions, to model arbitrary 2D/3D geometries, and unlimited parallel processing. Test cases have been selected to cover a wide range of benchmark examples from 1D to 3D. These include relaxation to equilibrium, 2D flow over a flat plate and a cylinder, and 3D supersonic flows over complex geometries. In all cases, dsmcFoam shows... 

Flapping wings are promising lift and thrust generators, especially for very low Reynolds numbers. To investigate aeroelastic effects of flexible wings (specifically, wing's twisting stiffness) on hovering and cruising aerodynamic performance, a flapping-wing system and an experimental setup were designed and built. This system measures the unsteady aerodynamic and inertial forces, power usage, and angular speed of the flapping wing motion for different flapping frequencies and for various wings with different chordwise flexibility. Aerodynamic performance of the vehicle for both no wind (hovering) and cruise condition was investigated. Results show how elastic deformations caused by... 

The disguise of traditional monopolistic electricity markets into deregulated competitive ones has made 'price forecasting' a crucial strategy for both producers and consumers: for the producers, to maximize their profit and hedge against price volatilities and for the consumers to manage their utility. Electricity price forecasting has thus emerged as a progressive field of study and numerous researches have been conducted to improve and optimize the price forecast methods. This paper proposes a precise and computationally efficient method to perform price forecasting in deregulated power markets. A locally linear neuro-fuzzy model is developed for price forecasting. The model is trained by... 

In today's competitive world, having an effective business intelligent (BI) system for monitoring and evaluation of industrial and product oriented organizations is vital. A perfect BI must help managers not only to speed up his decision making process; but also to increase quality of their decision. But how? One of the main specifications of an effective BI system is providing managers by correct format of information and at the correct time. Critical Success Factors (CSFs) are a kind of significant factors that must be considered in attaining an organization's goal; and key performance indicators (KPIs) are a type of quantitative and measurable CSF; and one character of an effective BI is...