Sharif Digital Repository

An accurate thermal model to predict the heat generation in rechargeable batteries is an essential tool for advanced thermal management in high power applications, such as electric vehicles. For such applications, the battery materials' details and cell design are normally not provided. In this work a simple, though accurate, thermal model for batteries has been developed, considering the temperature- and current-dependent overpotential heat generation and State-of-Charge dependent entropy contributions. High power rechargeable Li-ion (7.5 Ah) batteries have been experimentally investigated and the results are used for model verification. It is shown that the State-of-Charge dependent... 

The existence of periodic solutions for a forced Hill's equation is proved. The proof is then extended to the case of a non-homogeneous matrix valued Hill's equation. Under the stated conditions, using Lyapunov's criteria [Proc. AMS 13 (1962) 601; Hill's Equation, Interscience Publishers, New York, 1966] some results on the stability oh Hill's equation are obtained. © 2004 Elsevier Inc. All rights reserved  

An efficient algorithm for the design optimization of the compressible fluid flow problem through a flexible structure is presented. The methodology has three essential parts: first the behavior of compressible flow in a supersonic diffuser was studied numerically in quasi-one-dimensional form using a flux splitting method. Second, a fully coupled sequential iterative procedure was used to solve the steady state aeroelastic problem of a flexible wall diffuser. Finally, a robust Genetic Algorithm was implemented and used to calculate the optimum shape of the flexible wall diffuser for a prescribed pressure distribution. © 2006 Elsevier Ltd. All rights reserved  

The Phase I applications of the statistical profile monitoring have recently been extended to the case when the response variable is binary. We are motivated to undertake the current research in an attempt to try to provide a unified framework for the Phase I control in the context of statistical profile monitoring that can be used to tackle a large class of response variables, such as continuous, count, or categorical response variables. The unified framework is essentially based on applying the change point model to the class of generalized linear models. The proposed Phase I control chart is assessed and compared with the existing charts under binomial and Poisson profiles. Some... 

In this article, we adopt the change point approach to monitor the generalized linear profiles in phase II Statistical process control (SPC). Generalized linear profiles include a large class of profiles defined in one framework. In contrast to the conventional change point approach, we adopt the Rao score test rather than the likelihood ratio test. Simulated results show that our approach has a good performance over any possible single step change in process parameters for two special cases of generalized linear profiles, namely Poisson and binomial profiles. Some diagnostic aids are also given and a real example is introduced to shed light on the merits of our approach in real... 

This research aims to propose a thermodynamic model for predicting asphaltene precipitation upon diluting a crude oil with a paraffinic solvent. To this end, a thorough mathematical formulation was carried out to derive a novel micellization model based on the associative properties of asphaltenic compounds. It was assumed that asphaltenes exist in the oil both as monomeric molecules and aggregated cores; with stabilization latter by attachment of resin on its periphery. The aggregation equilibrium was established by taking into account asphaltene's lyophobic tendency, heat of resin adsorption, and interfacial tension between micelle and oil media which is the main driving factor... 

In this work, we attempted to develop an Implicit Coupled Density-Based (ICDB) solver using LU-SGS algorithm based on the AUSM+ up scheme in OpenFOAM. Then sonicFoam solver was modified to include viscous dissipation in order to improve its capability to capture shock wave and aerothermal variables. The details of the ICDB solver as well as key implementation details of the viscous dissipation to energy equation were introduced. Finally, two benchmark tests of hypersonic airflow over a flat plate and a 2-D cylinder were simulated to show the accuracy of ICDB solver. To verify and validate the ICDB solver, the obtained results were compared with other published experimental data. It was... 

The performance of a gas centrifuge that is used for isotopes separation is dependent on the gas flow inside it. In this study, for modeling the UF6 gas flow, an Implicit Coupled Density-Based (ICDB) solver, was developed in OpenFOAM. To validate the ICDB solver, the gas flow within the rotor in total reflux state was compared with the analytical solution obtained by Onsager model and the numerical solution obtained by the Fluent software. The results showed that the ICDB solver had acceptable accuracy and validity. Also the computational efficiency of Roe, AUSM (Advection Upstream Splitting Method) and AUSM+ up schemes were compared. The results showed AUSM+ up scheme is efficient. Then,... 

UF6 gas flow in the total regions of a rotor with the radius of 0.1 m and the length of 1 m in axisymmetric and steady states was simulated using a new hybrid CFD-DSMC method in the OpenFOAM framework. Implicit coupled density-based scheme was performed for CFD method, and Variable Hard Sphere (VHS) and diffuse model were employed in DSMC method. Also, as an initial estimation, the local Knudsen number was applied to determine the interface location between the continuum-rarefied regions (r = 0.0855 m). Then it was modified (r = 0.084 m) to reduce the computational cost. The comparison results of pure CFD and CFD-DSMC methods illustrated that there were large differences between the flow... 

UF6 gas flow in the total regions of a rotor with the radius of 0.1 m and the length of 1 m in axisymmetric and steady states was simulated using a new hybrid CFD-DSMC method in the OpenFOAM framework. Implicit coupled density-based scheme was performed for CFD method, and Variable Hard Sphere (VHS) and diffuse model were employed in DSMC method. Also, as an initial estimation, the local Knudsen number was applied to determine the interface location between the continuum-rarefied regions (r = 0.0855 m). Then it was modified (r = 0.084 m) to reduce the computational cost. The comparison results of pure CFD and CFD-DSMC methods illustrated that there were large differences between the flow... 

Nowadays, the number of digital images has increased so that the management of this volume of data needs an efficient system for browsing, categorising and searching. Automatic image annotation is designed for assigning tags to images for more accurate retrieval. Non-negative matrix factorisation (NMF) is a traditional machine learning technique for decomposing a matrix into a set of basis and coefficients under the non-negative constraints. In this study, the authors propose a two-step algorithm for designing an automatic image annotation system that employs the NMF framework for its first step and a variant of K-nearest neighbourhood as its second step. In the first step, a new multimodal... 

Gas detectors play an important role in safety of process plants. In-time detection of flammable gas releases may prevent major fire and explosion as well as property loss in process plants. One of the challenges of the gas detection system design is determining the best layout for detectors in order to reduce the risk of gas releases as much as possible. However, current methods do not address the risk concept in placement of detectors quantitatively. A risk-based methodology is proposed for optimal placement of point type flammable gas detectors in which first the risk (defined as a combination of scenario frequency, delayed ignition probability and damage) is estimated for any release... 

In automatic image annotation (AIA) different features describe images from different aspects or views. Part of information embedded in some views is common for all views, while other parts are individual and specific. In this paper, we present the Mvg-NMF approach, a multi-view-group non-negative matrix factorization (NMF) method for an AIA system which considers both common and individual factors. The NMF framework discovers a latent space by decomposing data into a set of non-negative basis vectors and coefficients. The views divided into homogeneous groups and latent spaces are extracted for each group. After mapping the test images into these spaces, a unified distance matrix is... 

In automatic image annotation (AIA) different features describe images from different aspects or views. Part of information embedded in some views is common for all views, while other parts are individual and specific. In this paper, we present the Mvg-NMF approach, a multi-view-group non-negative matrix factorization (NMF) method for an AIA system which considers both common and individual factors. The NMF framework discovers a latent space by decomposing data into a set of non-negative basis vectors and coefficients. The views divided into homogeneous groups and latent spaces are extracted for each group. After mapping the test images into these spaces, a unified distance matrix is... 

Automatic Image Annotation (AIA) helps image retrieval systems by predicting tags for images. In this paper, we propose an AIA system using Non-negative Matrix Factorization (NMF) framework. The NMF framework discovers a latent space, by factorizing data into a set of non-negative basis and coefficients. To model the images, multiple features are extracted, each one represents images from a specific view. We use multi-view graph regularization NMF and allow NMF to choose a different number of basis vectors for each view. For tag prediction, each test image is mapped onto the multiple latent spaces. The distances of images in these spaces are used to form a unified distance matrix. The...