Sharif Digital Repository

The architecture of a hardwired simulator for implementation of a discrete event-driven simulation of digital systems at the logic level is presented. In the design of this system, attempts have been made to utilize techniques of high performance computing to have a system capable of simulating the digital circuits rapidly. The centralized event-driven simulation algorithm chosen here, has the advantages of being efficient and conceptually straightforward. The high reliability of the simulator has been taken care of through a collection of handshake signals between each two of the three main modules. © Sharif University of Technology, December 2007  

Well-Being reliability indices (Health, Margin and Risk), provide a comprehensive measure to assess the adequacy of composite power systems. Conventional reliability information about power system operation only considered health and risk states, which were not often adequate criteria in both power system planning and operation. Well-being approach for power system generation adequacy evaluation incorporates deterministic criteria in a probabilistic framework, and provides system operating information in addition to risk assessment and can be evaluated using analytical techniques. The most important part of this approach is the algorithm for calculating the probability of the states.... 

Three-dimensional thermo-hydrodynamic analysis of gas turbine combustion chambers is of great importance in the power generation industry to achieve higher efficiency and reduced emissions. However, it is prohibitive to use a comprehensive full-detailed mechanism in their simulation algorithms because of the huge CPU time and memory space requirements. Many reduction approaches are available in the literature to remedy this problem. Here a new approach is presented to reduce large detailed or skeletal mechanisms of oxidation of hydrocarbon fuels to a low-cost skeletal mechanism. The method involves an integrated procedure including a Sensitivity Analysis (SA) and a procedure of Gradual... 

The study of electrocardiogram (ECG) waveform amplitudes, timings and patterns has been the subject of intense research, for it provides a deep insight into the diagnostic features of the heart's functionality. In some recent works, a Bayesian filtering paradigm has been proposed for denoising and compression of ECG signals. In this paper, it is shown that this framework may be effectively used for ECG beat segmentation and extraction of fiducial points. Analytic expressions for the determination of points and intervals are derived and evaluated on various real ECG signals. Simulation results show that the method can contribute to and enhance the clinical ECG beat segmentation performance. ©... 

This paper develops a two dimensional Green element simulator based on a "compatibility-equation" algorithm for simulation of counter-current spontaneous imbibition (COUCSI) process. The Green element method is a novel computational approach based on the boundary integral theory, which is regarded as a hybrid combination of both boundary and finite element methods. The superiority of the Green element method in modeling of two phase water/oil flow is at the core of this paper. The developed simulator within the context of this proposition is explored to predict the oil recovery from a one dimensional single matrix block. The results are then compared with the experimental data, and they... 

Purpose: Mass-spring-damper (MSD) models are often used for real-time surgery simulation due to their fast response and fairly realistic deformation replication. An improved real time simulation model of soft tissue deformation due to a laparoscopic surgical indenter was developed and tested. Method: The mechanical realization of conventional MSD models was improved using nonlinear springs and nodal dampers, while their high computational efficiency was maintained using an adapted implicit integration algorithm. New practical algorithms for model parameter tuning, collision detection, and simulation were incorporated. Results: The model was able to replicate complex biological soft tissue... 

The present study focuses on the implementation of PISO algorithm to simulate cavitating flows. For simulation of unsteady behaviors of cavitation which have practical applications, the development of unsteady PISO algorithm based on the non-conservative approach is investigated. The effects of mixture compressibility are considered to improve accuracy of simulations. For multi-phase simulation, single-fluid Navier-Stokes equations, along with the volume fraction transport equation, are employed. The bubble dynamics model is utilized to simulate phase change. To prove capabilities of the developed PISO algorithm to simulate cavitating flows, unsteady simulation of cavitation around NACA0015... 

In this study, a novel pseudo-three-dimensional model is developed to find out both fluid and solid temperature distributions in multi-stream plate fin heat exchangers. In this simulation algorithm, heat exchangers can be in either parallel flow or cross flow configuration. The model considerations include: heat leakage of cap plates and side plates, conduction throughout the solid matrix of the heat exchanger, variable physical properties, and inlet mass flow rate maldistribution. Using the computational code, the effects of different factors such as: the number of layers, mass flow variation, inlet mass flow rate maldistribution, and stacking pattern on the thermal performance of the heat... 

Objective: Joint analysis of multi-subject brain imaging datasets has wide applications in biomedical engineering. In these datasets, some sources belong to all subjects (joint), a subset of subjects (partially-joint), or a single subject (individual). In this paper, this source model is referred to as joint/partially-joint/individual multiple datasets unidimensional (JpJI-MDU), and accordingly, a source extraction method is developed. Method: We present a deflation-based algorithm utilizing higher order cumulants to analyze the JpJI-MDU source model. The algorithm maximizes a cost function which leads to an eigenvalue problem solved with thin-SVD (singular value decomposition)... 

Brain connectivity estimation is a useful method to study brain functions and diagnose neuroscience disorders. Effective connectivity is a subdivision of brain connectivity which discusses the causal relationship between different parts of the brain. In this study, a dual Kalman-based method is used for effective connectivity estimation. Because of connectivity changes in autism, the method is applied to autistic signals for effective connectivity estimation. For method validation, the dual Kalman based method is compared with other connectivity estimation methods by estimation error and the dual Kalman-based method gives acceptable results with less estimation errors. Then, connectivities... 

Representational similarity analysis (RSA) summarizes activity patterns for a set of experimental conditions into a matrix composed of pairwise comparisons between activity patterns. Two examples of such matrices are the condition-by-condition inner product and correlation matrix. These representational matrices reside on the manifold of positive semidefinite matrices, called the Riemannian manifold. We hypothesize that representational similarities would be more accurately quantified by considering the underlying manifold of the representational matrices. Thus, we introduce the distance on the Riemannian manifold as a metric for comparing representations. Analyzing simulated and real fMRI... 

In the present contribution, a new approach based on mutual information (MI) is proposed for exploring the independence of feasible solutions in two component systems. Investigating how independent are different feasible solutions can be a way to bridge the gap between independent component analysis (ICA) and multivariate curve resolution (MCR) approaches and, to the best of our knowledge, has not been investigated before. For this purpose, different chromatographic and hyperspectral imaging (HSI) datasets were simulated, considering different noise levels and different degrees of overlap for two-component systems. Feasible solutions were then calculated by both grid search (GS) and... 

This paper presents a long-term dynamic multi-objective planning model for distribution network expansion along with distributed energy options. The proposed model optimizes two objectives, namely costs and emissions and determines the optimal schemes of sizing, placement and specially the dynamics (i.e., timing) of investments on distributed generation units and network reinforcements over the planning period. An efficient two-stage heuristic method is proposed to solve the formulated planning problem. The effectiveness of the proposed model is demonstrated by applying it to a distribution network and comparing the simulation results with other methods and models  

Rocks and rock-like materials frequently fail under compression due to the initiation, propagation and coalescence of the pre-existing microcracks. The mechanism of microcrack coalescence process in rock-like materials is experimentally and numerically investigated. The experimental study involves some uniaxial compression tests on rock-like specimens specially prepared from portland pozzolana cement, mica sheets and water. The microcrack coalescence is studied by scanning electron microscopy on some of the prepared thin specimens. It is assumed that the mica sheets play the role of microcracks within the specimens. Some analytical and numerical studies are also carried out to simulate the... 

Fluid flow behavior in a porous medium is a function of the geometry and topology of its pore space. The construction of a three dimensional pore space model of a porous medium is therefore an important first step in characterizing the medium and predicting its flow properties. A stochastic technique for reconstruction of the 3D pore structure of unstructured random porous media from a 2D thin section training image is presented. The proposed technique relies on successive 2D multiple point statistics simulations coupled to a multi-scale conditioning data extraction procedure. The Single Normal Equation Simulation Algorithm (SNESIM), originally developed as a tool for reproduction of... 

A numerical simulation algorithm based on the finite volume discretisation is presented for analyzing ship motions. The algorithm employs a fractional step method to deal with the coupling between the pressure and velocity fields. The free surface capturing is fulfilled by using a volume of fluid method in which the interface between the liquid (water) and gas (air) phases are computed by solving a scalar transport equation for the volume fraction of the liquid phase. The computed velocity field is employed to evaluate the acting forces and moments on the vessel. Using the strategy of boundary-fitted body-attached mesh and calculating all six degrees-of-freedom of motion in each time step,... 

The joint analysis of multiple data sets to extract their interdependency information has wide applications in biomedical and health informatics. In this paper, we propose an algorithm to extract joint and individual sources of multisubject data sets by using a deflation-based procedure, which is referred to as joint/individual thin independent component analysis (JI-ThICA). The proposed algorithm is based on two cost functions utilizing higher order cumulants to extract joint and individual sources. Joint sources are discriminated by fusing signals of all subjects, whereas individual sources are extracted separately for each subject. Furthermore, JI-ThICA algorithm estimates the number of...