Search results for: Mathematical Modeling.

Authors: B. Vahdani, R. Tavakkoli-Moghaddam, A. Baboli, S. M. Mousavi

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Focusing on the environmental issues, including the reduction of scrap and consumer residuals, along with the benefiting from the economic value during the life cycle of goods/products leads the companies to have an important competitive approach. The aim of this paper is to present a new mixed nonlinear facility locationallocation model in recycling collection networks by considering multi-echelon, multi-suppliers, multi-collection centers and multifacilities in the recycling network. To make an appropriate decision in reality, demands, returns, capacities, costs and distances, are regarded uncertain in our model. For this purpose, a fuzzy mathematical programming-based possibilistic approach is introduced as a solution methodology from the recent literature to solve the proposed mixed-nonlinear programming model (MNLP). The computational experiments are provided to illustrate the applicability of the designed model in a supply chain environment and to help the decision makers to facilitate their analysis.

Keywords: Location-allocation model, recycling collection networks, fuzzy mathematical programming.

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Authors: A. Pashayev, D. Askerov, R.Sadiqov, A. Samedov, C. Ardil

Abstract:

In contrast to existing methods which do not take into account multiconnectivity in a broad sense of this term, we develop mathematical models and highly effective combination (BIEM and FDM) numerical methods of calculation of stationary and cvazistationary temperature field of a profile part of a blade with convective cooling (from the point of view of realization on PC). The theoretical substantiation of these methods is proved by appropriate theorems. For it, converging quadrature processes have been developed and the estimations of errors in the terms of A.Ziqmound continuity modules have been received. For visualization of profiles are used: the method of the least squares with automatic conjecture, device spline, smooth replenishment and neural nets. Boundary conditions of heat exchange are determined from the solution of the corresponding integral equations and empirical relationships. The reliability of designed methods is proved by calculation and experimental investigations heat and hydraulic characteristics of the gas turbine 1st stage nozzle blade

Keywords: multiconnected systems, method of the boundary integrated equations, splines, neural networks.

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Authors: A. Pashayev, D. Askerov, C. Ardil, R. Sadiqov

Abstract:

In contrast to existing methods which do not take into account multiconnectivity in a broad sense of this term, we develop mathematical models and highly effective combination (BIEM and FDM) numerical methods of calculation of stationary and quasi-stationary temperature field of a profile part of a blade with convective cooling (from the point of view of realization on PC). The theoretical substantiation of these methods is proved by appropriate theorems. For it, converging quadrature processes have been developed and the estimations of errors in the terms of A.Ziqmound continuity modules have been received. For visualization of profiles are used: the method of the least squares with automatic conjecture, device spline, smooth replenishment and neural nets. Boundary conditions of heat exchange are determined from the solution of the corresponding integral equations and empirical relationships. The reliability of designed methods is proved by calculation and experimental investigations heat and hydraulic characteristics of the gas turbine first stage nozzle blade.

Keywords: Multiconnected systems, method of the boundary integrated equations, splines, neural networks.

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Authors: W. D. Wan Rosli, Z. Zainuddin, R. Lanouette, S. Sathasivam

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This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear underlying phenomena contained in the data set and to partly eliminate the burden of having to specify completely the structure of the model. Two different types of neural networks were used for the application of Pulping of Sugar Maple problem. A three layer feed forward neural networks, using the Preconditioned Conjugate Gradient (PCG) methods were used in this investigation. Preconditioning is a method to improve convergence by lowering the condition number and increasing the eigenvalues clustering. The idea is to solve the modified problem where M is a positive-definite preconditioner that is closely related to A. We mainly focused on Preconditioned Conjugate Gradient- based training methods which originated from optimization theory, namely Preconditioned Conjugate Gradient with Fletcher-Reeves Update (PCGF), Preconditioned Conjugate Gradient with Polak-Ribiere Update (PCGP) and Preconditioned Conjugate Gradient with Powell-Beale Restarts (PCGB). The behavior of the PCG methods in the simulations proved to be robust against phenomenon such as oscillations due to large step size.

Keywords: Convergence, Modeling, Neural Networks, Preconditioned Conjugate Gradient.

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Authors: Mahmoud Zarrini

Abstract:

Avalanche release of snow has been modeled in the present studies. Snow is assumed to be represented by semi-solid and the governing equations have been studied from the concept of continuum approach. The dynamical equations have been solved for two different zones [starting zone and track zone] by using appropriate initial and boundary conditions. Effect of density (ρ), Eddy viscosity (η), Slope angle (θ), Slab depth (R) on the flow parameters have been observed in the present studies. Numerical methods have been employed for computing the non linear differential equations. One of the most interesting and fundamental innovation in the present studies is getting initial condition for the computation of velocity by numerical approach. This information of the velocity has obtained through the concept of fracture mechanics applicable to snow. The results on the flow parameters have found to be in qualitative agreement with the published results.

Keywords: Snow avalanche, fracture mechanics, avalanche velocity, avalanche zones.

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Authors: Bharat Raj Singh, Onkar Singh

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This paper details a new concept of using compressed air as a potential zero pollution power source for motorbikes. In place of an internal combustion engine, the motorbike is equipped with an air turbine transforms the energy of the compressed air into shaft work. The mathematical modeling and performance evaluation of a small capacity compressed air driven vaned type novel air turbine is presented in this paper. The effect of isobaric admission and adiabatic expansion of high pressure air for different rotor diameters, casing diameters and ratio of rotor to casing diameters of the turbine have been considered and analyzed. It is concluded that the work output is found optimum for some typical values of rotor / casing diameter ratios. In this study, the maximum power works out to 3.825 kW (5.20 HP) for casing diameter of 200 mm and rotor to casing diameter ratio of 0.65 to 0.60 which is sufficient to run motorbike.

Keywords: zero pollution, compressed air, air turbine, injectionangle, rotor / casing diameter ratio.

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Authors: Evgeniy Burlutskiy

Abstract:

The paper presents a numerical investigation on the rapid gas decompression in pure nitrogen which is made by using the one-dimensional (1D) and three-dimensional (3D) mathematical models of transient compressible non-isothermal fluid flow in pipes. A 1D transient mathematical model of compressible thermal multicomponent fluid mixture flow in pipes is presented. The set of the mass, momentum and enthalpy conservation equations for gas phase is solved in the model. Thermo-physical properties of multicomponent gas mixture are calculated by solving the Equation of State (EOS) model. The Soave-Redlich-Kwong (SRK-EOS) model is chosen. This model is successfully validated on the experimental data [1] and shows a good agreement with measurements. A 3D transient mathematical model of compressible thermal single-component gas flow in pipes, which is built by using the CFD Fluent code (ANSYS), is presented in the paper. The set of unsteady Reynolds-averaged conservation equations for gas phase is solved. Thermo-physical properties of single-component gas are calculated by solving the Real Gas Equation of State (EOS) model. The simplest case of gas decompression in pure nitrogen is simulated using both 1D and 3D models. The ability of both models to simulate the process of rapid decompression with a high order of agreement with each other is tested. Both, 1D and 3D numerical results show a good agreement between each other. The numerical investigation shows that 3D CFD model is very helpful in order to validate 1D simulation results if the experimental data is absent or limited.

Keywords: Mathematical model, Rapid Gas Decompression

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Authors: Mohsen Ebrahimi, Milad M. Rabieh

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In this paper, two very different optimization algorithms, Genetic and DIRECT algorithms, are used to history match a bottomhole pressure response for a reservoir with wellbore storage and skin with the best possible analytical model. No initial guesses are available for reservoir parameters. The results show that the matching process is much faster and more accurate for DIRECT method in comparison with Genetic algorithm. It is furthermore concluded that the DIRECT algorithm does not need any initial guesses, whereas Genetic algorithm needs to be tuned according to initial guesses.

Keywords: DIRECT algorithm, Genetic algorithm, Analytical modeling, History match

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Authors: Catherine A. Todd, Fazel Naghdy

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In this work a surgical simulator is produced which enables a training otologist to conduct a virtual, real-time prosthetic insertion. The simulator provides the Ear, Nose and Throat surgeon with real-time visual and haptic responses during virtual cochlear implantation into a 3D model of the human Scala Tympani (ST). The parametric model is derived from measured data as published in the literature and accounts for human morphological variance, such as differences in cochlear shape, enabling patient-specific pre- operative assessment. Haptic modeling techniques use real physical data and insertion force measurements, to develop a force model which mimics the physical behavior of an implant as it collides with the ST walls during an insertion. Output force profiles are acquired from the insertion studies conducted in the work, to validate the haptic model. The simulator provides the user with real-time, quantitative insertion force information and associated electrode position as user inserts the virtual implant into the ST model. The information provided by this study may also be of use to implant manufacturers for design enhancements as well as for training specialists in optimal force administration, using the simulator. The paper reports on the methods for anatomical modeling and haptic algorithm development, with focus on simulator design, development, optimization and validation. The techniques may be transferrable to other medical applications that involve prosthetic device insertions where user vision is obstructed.

Keywords: Haptic modeling, medical device insertion, real-time visualization of prosthetic implantation, surgical simulation.

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Authors: Marinka K. Baghdasaryan, Siranush M. Muradyan, Avgen A. Gasparyan

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Analytical expressions of the current and angular errors, as well as the frequency characteristics of an induction converter describing the relation with its structural parameters, the core and winding characteristics are obtained. Based on estimation of the dependences obtained, a mathematical problem of parametric optimization is formulated which can successfully be used for investigating and diagnosing an induction converter.

Keywords: Induction converters, magnetic circuit material, current and angular errors, frequency response, mathematical formulation, structural parameters.

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Authors: Surinder Deswal, Mahesh Pal

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An Artificial Neural Network based modeling technique has been used to study the influence of different combinations of meteorological parameters on evaporation from a reservoir. The data set used is taken from an earlier reported study. Several input combination were tried so as to find out the importance of different input parameters in predicting the evaporation. The prediction accuracy of Artificial Neural Network has also been compared with the accuracy of linear regression for predicting evaporation. The comparison demonstrated superior performance of Artificial Neural Network over linear regression approach. The findings of the study also revealed the requirement of all input parameters considered together, instead of individual parameters taken one at a time as reported in earlier studies, in predicting the evaporation. The highest correlation coefficient (0.960) along with lowest root mean square error (0.865) was obtained with the input combination of air temperature, wind speed, sunshine hours and mean relative humidity. A graph between the actual and predicted values of evaporation suggests that most of the values lie within a scatter of ±15% with all input parameters. The findings of this study suggest the usefulness of ANN technique in predicting the evaporation losses from reservoirs.

Keywords: Artificial neural network, evaporation losses, multiple linear regression, modeling.

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Authors: S. Loumi, H. Merrad, F. Alilat, B. Sansal

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In this article, we propose a methodology for the characterization of the suspended matter along Algiers-s bay. An approach by multi layers perceptron (MLP) with training by back propagation of the gradient optimized by the algorithm of Levenberg Marquardt (LM) is used. The accent was put on the choice of the components of the base of training where a comparative study made for four methods: Random and three alternatives of classification by K-Means. The samples are taken from suspended matter image, obtained by analytical model based on polynomial regression by taking account of in situ measurements. The mask which selects the zone of interest (water in our case) was carried out by using a multi spectral classification by ISODATA algorithm. To improve the result of classification, a cleaning of this mask was carried out using the tools of mathematical morphology. The results of this study presented in the forms of curves, tables and of images show the founded good of our methodology.

Keywords: Classification K-means, mathematical morphology, neural network MLP, remote sensing, suspended particulate matter

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Authors: Jawad Al Khaburi, Abbas A. Dehghani-Sanij, E. Andrea Nelson, Jerry Hutchinson

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Medical compression bandages are widely used in the treatment of chronic venous disorder. In order to design effective compression bandages, researchers have attempted to describe the interface pressure applied by multi-layer bandages using mathematical models. This paper reports on the work carried out to compare and validate the mathematical models used to describe the interface pressure applied by multi-layer bandages. Both analytical and experimental results showed that using simple multiplication of a number of bandage layers with the pressure applied by one layer of bandage or ignoring the increase in the limb radius due to former layers of bandage will result in overestimating the pressure. Experimental results showed that the mathematical models, which take into consideration the increase in the limb radius due to former bandage layers, are more accurate than the one which does not.

Keywords: Compression bandages, FlexiForce, interface pressure, venous ulcer

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Authors: Erfan Niazi, Marianne Fenech

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Red Blood Cells (RBCs) or erythrocytes tend to form chain-like aggregates under low shear rate called rouleaux. This is a reversible process and rouleaux disaggregate in high shear rates. Therefore, RBCs aggregation occurs in the microcirculation where low shear rates are present but does not occur under normal physiological conditions in large arteries. Numerical modeling of RBCs interactions is fundamental in analytical models of a blood flow in microcirculation. Population Balance Modeling (PBM) is particularly useful for studying problems where particles agglomerate and break in a two phase flow systems to find flow characteristics. In this method, the elementary particles lose their individual identity due to continuous destructions and recreations by break-up and agglomeration. The aim of this study is to find RBCs aggregation in a dynamic situation. Simplified PBM was used previously to find the aggregation rate on a static observation of the RBCs aggregation in a drop of blood under the microscope. To find aggregation rate in a dynamic situation we propose an experimental set up testing RBCs sedimentation. In this test, RBCs interact and aggregate to form rouleaux. In this configuration, disaggregation can be neglected due to low shear stress. A high-speed camera is used to acquire video-microscopic pictures of the process. The sizes of the aggregates and velocity of sedimentation are extracted using an image processing techniques. Based on the data collection from 5 healthy human blood samples, the aggregation rate was estimated as 2.7x10³(±0.3 x10³) 1/s.

Keywords: Red blood cell, Rouleaux, microfluidics, image processing, population balance modeling.

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Authors: B. S. Sindu, Saptarshi Sasmal, Smitha Gopinath

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Cement, the most widely used construction material is very brittle and characterized by low tensile strength and strain capacity. Macro to nano fibers are added to cement to provide tensile strength and ductility to it. Carbon Nanotube (CNT), one of the nanofibers, has proven to be a promising reinforcing material in the cement composites because of its outstanding mechanical properties and its ability to close cracks at the nano level. The experimental investigations for CNT reinforced cement is costly, time consuming and involves huge number of trials. Mathematical modeling of CNT reinforced cement can be done effectively and efficiently to arrive at the mechanical properties and to reduce the number of trials in the experiments. Hence, an attempt is made to numerically study the effective mechanical properties of CNT reinforced cement numerically using Representative Volume Element (RVE) method. The enhancement in its mechanical properties for different percentage of CNTs is studied in detail.

Keywords: Carbon Nanotubes, Cement composites, Representative Volume Element, Numerical simulation

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Authors: Shinpei Ogata, Yoshitaka Aoki, Hirotaka Okuda, Saeko Matsuura

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A key to success of high quality software development is to define valid and feasible requirements specification. We have proposed a method of model-driven requirements analysis using Unified Modeling Language (UML). The main feature of our method is to automatically generate a Web user interface mock-up from UML requirements analysis model so that we can confirm validity of input/output data for each page and page transition on the system by directly operating the mock-up. This paper proposes a support method to check the validity of a data life cycle by using a model checking tool “UPPAAL" focusing on CRUD (Create, Read, Update and Delete). Exhaustive checking improves the quality of requirements analysis model which are validated by the customers through automatically generated mock-up. The effectiveness of our method is discussed by a case study of requirements modeling of two small projects which are a library management system and a supportive sales system for text books in a university.

Keywords: CRUD, Model Checking, Model Driven Development, Requirements Analysis, Unified Modeling Language, UPPAAL.

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Authors: Akinola Ikudayisi, Josiah Adeyemo

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The correct estimation of reference evapotranspiration (ETₒ) is required for effective irrigation water resources planning and management. However, there are some variables that must be considered while estimating and modeling ETₒ. This study therefore determines the multivariate analysis of correlated variables involved in the estimation and modeling of ETₒ at Vaalharts irrigation scheme (VIS) in South Africa using Principal Component Analysis (PCA) technique. Weather and meteorological data between 1994 and 2014 were obtained both from South African Weather Service (SAWS) and Agricultural Research Council (ARC) in South Africa for this study. Average monthly data of minimum and maximum temperature (°C), rainfall (mm), relative humidity (%), and wind speed (m/s) were the inputs to the PCA-based model, while ETₒ is the output. PCA technique was adopted to extract the most important information from the dataset and also to analyze the relationship between the five variables and ETₒ. This is to determine the most significant variables affecting ETₒ estimation at VIS. From the model performances, two principal components with a variance of 82.7% were retained after the eigenvector extraction. The results of the two principal components were compared and the model output shows that minimum temperature, maximum temperature and windspeed are the most important variables in ETₒ estimation and modeling at VIS. In order words, ETₒ increases with temperature and windspeed. Other variables such as rainfall and relative humidity are less important and cannot be used to provide enough information about ETₒ estimation at VIS. The outcome of this study has helped to reduce input variable dimensionality from five to the three most significant variables in ETₒ modelling at VIS, South Africa.

Keywords: Irrigation, principal component analysis, reference evapotranspiration, Vaalharts.

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Authors: Arshia Azam, J. Amarnath, Ch. D. V. Paradesi Rao

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The advantage of solving the complex nonlinear problems by utilizing fuzzy logic methodologies is that the experience or expert-s knowledge described as a fuzzy rule base can be directly embedded into the systems for dealing with the problems. The current limitation of appropriate and automated designing of fuzzy controllers are focused in this paper. The structure discovery and parameter adjustment of the Branched T-S fuzzy model is addressed by a hybrid technique of type constrained sparse tree algorithms. The simulation result for different system model is evaluated and the identification error is observed to be minimum.

Keywords: Fuzzy logic, branch T-S fuzzy model, tree modeling, complex nonlinear system.

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Authors: Wichai Pattanapol, Sarah J. Wakes, Michael J. Hilton, Katharine J.M. Dickinson

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Turbulence modeling of large-scale flow over a vegetated surface is complex. Such problems involve large scale computational domains, while the characteristics of flow near the surface are also involved. In modeling large scale flow, surface roughness including vegetation is generally taken into account by mean of roughness parameters in the modified law of the wall. However, the turbulence structure within the canopy region cannot be captured with this method, another method which applies source/sink terms to model plant drag can be used. These models have been developed and tested intensively but with a simple surface geometry. This paper aims to compare the use of roughness parameter, and additional source/sink terms in modeling the effect of plant drag on wind flow over a complex vegetated surface. The RNG k-ε turbulence model with the non-equilibrium wall function was tested with both cases. In addition, the k-ω turbulence model, which is claimed to be computationally stable, was also investigated with the source/sink terms. All numerical results were compared to the experimental results obtained at the study site Mason Bay, Stewart Island, New Zealand. In the near-surface region, it is found that the results obtained by using the source/sink term are more accurate than those using roughness parameters. The k-ω turbulence model with source/sink term is more appropriate as it is more accurate and more computationally stable than the RNG k-ε turbulence model. At higher region, there is no significant difference amongst the results obtained from all simulations.

Keywords: CFD, canopy flow, surface roughness, turbulence models.

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Authors: M. Rozanek, K. Roubik

Abstract:

A mathematical model of the respiratory system is introduced in this study. Geometrical dimensions of the respiratory system were used to compute the acoustic properties of the respiratory system using the electro-acoustic analogy. The effect of the geometrical proportions of the respiratory system is observed in the paper.

Keywords: Electro-acoustic analogy, total lung impedance, mechanical parameters, respiratory system.

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Authors: S. Deswal, M. Pal

Abstract:

Presently various computational techniques are used in modeling and analyzing environmental engineering data. In the present study, an intra-comparison of polynomial and radial basis kernel functions based on Support Vector Regression and, in turn, an inter-comparison with Multi Linear Regression has been attempted in modeling mass transfer capacity of vertical (θ = 90O) and inclined (θ multiple plunging jets (varying from 1 to 16 numbers). The data set used in this study consists of four input parameters with a total of eighty eight cases, forty four each for vertical and inclined multiple plunging jets. For testing, tenfold cross validation was used. Correlation coefficient values of 0.971 and 0.981 along with corresponding root mean square error values of 0.0025 and 0.0020 were achieved by using polynomial and radial basis kernel functions based Support Vector Regression respectively. An intra-comparison suggests improved performance by radial basis function in comparison to polynomial kernel based Support Vector Regression. Further, an inter-comparison with Multi Linear Regression (correlation coefficient = 0.973 and root mean square error = 0.0024) reveals that radial basis kernel functions based Support Vector Regression performs better in modeling and estimating mass transfer by multiple plunging jets.

Keywords: Mass transfer, multiple plunging jets, polynomial and radial basis kernel functions, Support Vector Regression.

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Authors: H. M. Farghally, N. M. Ahmed, H. T. El-Madany, D. M. Atia, F. H. Fahmy

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Energy is required in almost every aspect of human activities and development of any nation in the world. Increasing fossil fuel price, energy security and climate change have important bearings on sustainable development of any nation. The renewable energy technology is considered one of the drastic approaches which taken over the world to reduce the energy problem. The preservation of vegetables by freezing is one of the most important methods of retaining quality in agricultural products over long-term storage periods. Freezing factories show high demand of energy for both heat and electricity; the hybrid Photovoltaic/Thermal (PV/T) systems could be used in order to meet this requirement. This paper presents PV/T system design for freezing factory. Also, the complete mathematical modeling and MATLAB SIMULINK of PV/T collector is introduced. The sensitivity analysis for the manufacturing parameters of PV/T collector is carried out to study their effect on both thermal and electrical efficiency.

Keywords: Renewable energy, Hybrid PV/T system, Sensitivity analysis.

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Authors: Heejung Lee

Abstract:

In a highly competitive environment, it becomes more important to shorten the whole business process while delivering or even enhancing the business value to the customers and suppliers. Although the workflow management systems receive much attention for its capacity to practically support the business process enactment, the effective workflow modeling method remain still challenging and the high degree of process complexity makes it more difficult to gain the short lead time. This paper presents a workflow structuring method in a holistic way that can reduce the process complexity using activity-needs and formal concept analysis, which eventually enhances the key performance such as quality, delivery, and cost in business process.

Keywords: Workflow management, reengineering, formal concept analysis.

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Authors: Mohammad Lemar Zalmai, Mustafa Nabi Kocakaya, Cemil Akcay, Ekrem Manisali

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In recent years, the Building Information Modeling (BIM) approach has been developed expeditiously. As people see the benefits of this approach, it has begun to be used widely in construction projects and some countries made it mandatory to get more benefits from it. To promote the implementation of BIM in construction projects, it will be helpful to get some relevant information from surveys and interviews. The purpose of this study is to research the current adoption and implementation of BIM in public projects in Turkey. This study specified the challenges of BIM implementation in Turkey and proposed some solutions to overcome them. In this context, the challenges for BIM implementation and the factors that affect the BIM usage are determined based on previous academic researches and expert opinions by conducting interviews and questionnaire surveys. Several methods are used to process information in order to obtain weights of different factors to make BIM widespread in Turkey. This study concluded interviews' and questionnaire surveys' outcomes and proposed some suggestions to promote the implementation of BIM in Turkey. We believe research findings will be a good reference for boosting BIM implementation in Turkey.

Keywords: Building Information Modeling, BIM, BIM implementations, Turkish construction industry, Turkish government sector projects.

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Authors: J. G. Batista, T. S. Santiago, E. A. Ribeiro, ¬G. A. P. Thé

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This work deals with parameter identification of permanent magnet motors, a class of ac motor which is particularly important in industrial automation due to characteristics like applications high performance, are very attractive for applications with limited space and reducing the need to eliminate because they have reduced size and volume and can operate in a wide speed range, without independent ventilation. By using experimental data and genetic algorithm we have been able to extract values for both the motor inductance and the electromechanical coupling constant, which are then compared to measure and/or expected values.

Keywords: Modeling, AC servomotor, Permanent Magnet Synchronous Motor-PMSM, Genetic Algorithm, Vector Control, Robotic Manipulator, Control.

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Authors: Kayijuka Idrissa

Abstract:

This work investigates a mathematical study for traffic flow and traffic density in Kigali city roads and the data collected from the national police of Rwanda in 2012. While working on this topic, some mathematical models were used in order to analyze and compare traffic variables. This work has been carried out on Kigali roads specifically at roundabouts from Kigali Business Center (KBC) to Prince House as our study sites. In this project, we used some mathematical tools to analyze the data collected and to understand the relationship between traffic variables. We applied the Poisson distribution method to analyze and to know the number of accidents occurred in this section of the road which is from KBC to Prince House. The results show that the accidents that occurred in 2012 were at very high rates due to the fact that this section has a very narrow single lane on each side which leads to high congestion of vehicles, and consequently, accidents occur very frequently. Using the data of speeds and densities collected from this section of road, we found that the increment of the density results in a decrement of the speed of the vehicle. At the point where the density is equal to the jam density the speed becomes zero. The approach is promising in capturing sudden changes on flow patterns and is open to be utilized in a series of intelligent management strategies and especially in noncurrent congestion effect detection and control.

Keywords: Statistical methods, Poisson distribution, car moving techniques, traffic flow.

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Authors: Gholamreza Zahedi, M. Tarin, M. Biglari

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This work investigated the steady state and dynamic simulation of a fixed bed industrial naphtha reforming reactors. The performance of the reactor was investigated using a heterogeneous model. For process simulation, the differential equations are solved using the 4th order Runge-Kutta method .The models were validated against measured process data of an existing naphtha reforming plant. The results of simulation in terms of components yields and temperature of the outlet were in good agreement with empirical data. The simple model displays a useful tool for dynamic simulation, optimization and control of naphtha reforming.

Keywords: Dynamic simulation, fixed bed reactor, modeling, reforming

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Authors: Yuan-Jye Tseng, Yi-Shiuan Chen

Abstract:

The paper presented a sustainable design model for integrated evaluation of the design and supply chain of a product for the sustainable objectives. To design a product, there can be alternative ways to assign the detailed specifications to fulfill the same design objectives. In the design alternative cases, different material and manufacturing processes with various supply chain activities may be required for the production. Therefore, it is required to evaluate the different design cases based on the sustainable objectives. In this research, a closed-loop design model is developed by integrating the forward design model and reverse design model. From the supply chain point of view, the decisions in the forward design model are connected with the forward supply chain. The decisions in the reverse design model are connected with the reverse supply chain considering the sustainable objectives. The purpose of this research is to develop a mathematical model for analyzing the design cases by integrated evaluating the criteria in the closed-loop design and the closed-loop supply chain. The decision variables are built to represent the design cases of the forward design and reverse design. The cost parameters in a forward design include the costs of material and manufacturing processes. The cost parameters in a reverse design include the costs of recycling, disassembly, reusing, remanufacturing, and disposing. The mathematical model is formulated to minimize the total cost under the design constraints. In practical applications, the decisions of the mathematical model can be used for selecting a design case for the purpose of sustainable design of a product. An example product is demonstrated in the paper. The test result shows that the sustainable design model is useful for integrated evaluation of the design and the supply chain to achieve the sustainable objectives.

Keywords: Closed-loop design, closed-loop supply chain, design evaluation, mathematical model, supply chain management, sustainable design model.

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Authors: S. Ariffin, K. Hasnan, R.H. Weston

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A new generation of manufacturing machines so-called MIMCA (modular and integrated machine control architecture) capable of handling much increased complexity in manufacturing control-systems is presented. Requirement for more flexible and effective control systems for manufacturing machine systems is investigated and dimensioned-which highlights a need for improved means of coordinating and monitoring production machinery and equipment used to- transport material. The MIMCA supports simulation based on machine modeling, was conceived by the authors to address the issues. Essentially MIMCA comprises an organized unification of selected architectural frameworks and modeling methods, which include: NISTRCS, UMC and Colored Timed Petri nets (CTPN). The unification has been achieved; to support the design and construction of hierarchical and distributed machine control which realized the concurrent operation of reusable and distributed machine control components; ability to handle growing complexity; and support requirements for real- time control systems. Thus MIMCA enables mapping between 'what a machine should do' and 'how the machine does it' in a well-defined but flexible way designed to facilitate reconfiguration of machine systems.

Keywords: Machine control, architectures, Petri nets, modularity, modeling, simulation.

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Authors: Minky Son, Chanin Park, Ayoung Baek, Shalini John, Keun Woo Lee

Abstract:

3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGR) catalyzes the conversion of HMG-CoA to mevalonate using NADPH and the enzyme is involved in rate-controlling step of mevalonate. Inhibition of HMGR is considered as effective way to lower cholesterol levels so it is drug target to treat hypercholesterolemia, major risk factor of cardiovascular disease. To discover novel HMGR inhibitor, we performed structure-based pharmacophore modeling combined with molecular dynamics (MD) simulation. Four HMGR inhibitors were used for MD simulation and representative structure of each simulation were selected by clustering analysis. Four structure-based pharmacophore models were generated using the representative structure. The generated models were validated used in virtual screening to find novel scaffolds for inhibiting HMGR. The screened compounds were filtered by applying drug-like properties and used in molecular docking. Finally, four hit compounds were obtained and these complexes were refined using energy minimization. These compounds might be potential leads to design novel HMGR inhibitor.

Keywords: Anti-hypercholesterolemia drug, HMGR inhibitor, Molecular dynamics simulation, Structure-based pharmacophore modeling.

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