Search results for: Computational Complexity

Authors: S. Chonsatidjamroen , K-N. Areerak, K-L. Areerak

Abstract:

This paper presents the averaging model of a buck converter derived from the generalized state-space averaging method. The sliding mode control is used to regulate the output voltage of the converter and taken into account in the model. The proposed model requires the fast computational time compared with those of the full topology model. The intensive time-domain simulations via the exact topology model are used as the comparable model. The results show that a good agreement between the proposed model and the switching model is achieved in both transient and steady-state responses. The reported model is suitable for the optimal controller design by using the artificial intelligence techniques.

Keywords: Generalized state-space averaging method, buck converter, sliding mode control, modeling, simulation.

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Authors: N. Outili, A-H. Meniai

Abstract:

Modeling transfer phenomena in several chemical engineering operations leads to the resolution of partial differential equations systems. According to the complexity of the operations mechanisms, the equations present a nonlinear form and analytical solution became difficult, we have then to use numerical methods which are based on approximations in order to transform a differential system to an algebraic one.Finite element method is one of numerical methods which can be used to obtain an accurate solution in many complex cases of chemical engineering.The packed columns find a large application like contactor for liquid-liquid systems such solvent extraction. In the literature, the modeling of this type of equipment received less attention in comparison with the plate columns.A mathematical bidimensionnal model with radial and axial dispersion, simulating packed tower extraction behavior was developed and a partial differential equation was solved using the finite element method by adopting the Galerkine model. We developed a Mathcad program, which can be used for a similar equations and concentration profiles are obtained along the column. The influence of radial dispersion was prooved and it can-t be neglected, the results were compared with experimental concentration at the top of the column in the extraction system: acetone/toluene/water.

Keywords: finite element method, Galerkine method, liquidliquid extraction modelling, packed column simulation, two dimensional model

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Authors: Zane Turner, Kevin Labille, Susan Gauch

Abstract:

Sentiment analysis is a broad and expanding field that aims to extract and classify opinions from textual data. Lexicon-based approaches are based on the use of a sentiment lexicon, i.e., a list of words each mapped to a sentiment score, to rate the sentiment of a text chunk. Our work focuses on predicting stock price change using a sentiment lexicon built from financial conference call logs. We introduce a method to generate a sentiment lexicon based upon an existing probabilistic approach. By using a domain-specific lexicon, we outperform traditional techniques and demonstrate that domain-specific sentiment lexicons provide higher accuracy than generic sentiment lexicons when predicting stock price change.

Keywords: Computational finance, sentiment analysis, sentiment lexicon, stock movement prediction.

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Authors: C. A. Gilkeson, C. J. Noakes, P. A. Sleigh, M. A. I. Khan, M. A. Camargo-Valero

Abstract:

Understanding how airborne pathogens are transported through hospital wards is essential for determining the infection risk to patients and healthcare workers. This study utilizes Computational Fluid Dynamics (CFD) simulations to explore possible pathogen transport within a six-bed partitioned Nightingalestyle hospital ward. Grid independence of a ward model was addressed using the Grid Convergence Index (GCI) from solutions obtained using three fullystructured grids. Pathogens were simulated using source terms in conjunction with a scalar transport equation and a RANS turbulence model. Errors were found to be less than 4% in the calculation of air velocities but an average of 13% was seen in the scalar field. A parametric study of variations in the pathogen release point illustrated that its distribution is strongly influenced by the local velocity field and the degree of air mixing present.

Keywords: Natural, Ventilation, Pathogen, Transport

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Authors: Yi Chao Huang, Yu Ling Liao, Chiu Shuang Lin

Abstract:

A data cutting and sorting method (DCSM) is proposed to optimize the performance of data mining. DCSM reduces the calculation time by getting rid of redundant data during the data mining process. In addition, DCSM minimizes the computational units by splitting the database and by sorting data with support counts. In the process of searching for the relationship between metabolic syndrome and lifestyles with the health examination database of an electronics manufacturing company, DCSM demonstrates higher search efficiency than the traditional Apriori algorithm in tests with different support counts.

Keywords: Data mining, Data cutting and sorting method, Apriori algorithm, Metabolic syndrome

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Authors: Peng He

Abstract:

Imprecision is a long-standing problem in CAD design and high accuracy image-based reconstruction applications. The visual hull which is the closed silhouette equivalent shape of the objects of interest is an important concept in image-based reconstruction. We extend the domain-theoretic framework, which is a robust and imprecision capturing geometric model, to analyze the imprecision in the output shape when the input vertices are given with imprecision. Under this framework, we show an efficient algorithm to generate the 2D partial visual hull which represents the exact information of the visual hull with only basic imprecision assumptions. We also show how the visual hull from polyhedra problem can be efficiently solved in the context of imprecise input.

Keywords: Geometric Domain, Computer Vision, Computational Geometry, Visual Hull, Image-Based reconstruction, Imprecise Input, CAD object

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Authors: F. Laaouad, M. Bouguerra, A. Hafaifa, A. Iratni

Abstract:

In this work, we treat the problems related to chemical and petrochemical plants of a certain complex process taking the centrifugal compressor as an example, a system being very complex by its physical structure as well as its behaviour (surge phenomenon). We propose to study the application possibilities of the recent control approaches to the compressor behaviour, and consequently evaluate their contribution in the practical and theoretical fields. Facing the studied industrial process complexity, we choose to make recourse to fuzzy logic for analysis and treatment of its control problem owing to the fact that these techniques constitute the only framework in which the types of imperfect knowledge can jointly be treated (uncertainties, inaccuracies, etc..) offering suitable tools to characterise them. In the particular case of the centrifugal compressor, these imperfections are interpreted by modelling errors, the neglected dynamics, no modelisable dynamics and the parametric variations. The purpose of this paper is to produce a total robust nonlinear controller design method to stabilize the compression process at its optimum steady state by manipulating the gas rate flow. In order to cope with both the parameter uncertainty and the structured non linearity of the plant, the proposed method consists of a linear steady state regulation that ensures robust optimal control and of a nonlinear compensation that achieves the exact input/output linearization.

Keywords: Compressor, Fuzzy logic, Surge control, Bilinearcontroller, Stability analysis, Nonlinear plant.

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Authors: Hiroto Nakashima, Toshihiro Morita, Koichiro Ohgushi

Abstract:

Laser Profiler (LP) data from aerial laser surveys have been increasingly used as topographical inputs to numerical simulations of flooding and inundation in river basins. LP data has great potential for reproducing topography, but its effective usage has not yet been fully established. In this study, flooding and inundation are simulated numerically using LP data for the Jobaru River basin of Japan’s Saga Plain. The analysis shows that the topography is reproduced satisfactorily in the computational domain with urban and agricultural areas requiring different grid sizes. A 2-D numerical simulation shows that flood flow behavior changes as grid size is varied.

Keywords: LP data, numerical simulation, topological analysis, mesh size.

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Authors: E.V. Butilă, F. Gîrbacia

Abstract:

In order to give high expertise the computer aided design of mechanical systems involves specific activities focused on processing two type of information: knowledge and data. Expert rule based knowledge is generally processing qualitative information and involves searching for proper solutions and their combination into synthetic variant. Data processing is based on computational models and it is supposed to be inter-related with reasoning in the knowledge processing. In this paper an Intelligent Integrated System is proposed, for the objective of choosing the adequate material. The software is developed in Prolog – Flex software and takes into account various constraints that appear in the accurate operation of gears.

Keywords: Expert System, computer aided design, gear boxdesign, chose material, Prolog, Flex

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Authors: Sh. Khalilarya, S. Jafarmadar, H. Khatamnezhad, Gh. Javadirad, M. Pourfallah

Abstract:

One promising way to achieve low temperature combustion regime is the use of a large amount of cooled EGR. In this paper, the effect of injection timing on low temperature combustion process and emissions were investigated via three dimensional computational fluid dynamics (CFD) procedures in a DI diesel engine using high EGR rates. The results show when increasing EGR from low levels to levels corresponding to reduced temperature combustion, soot emission after first increasing, is decreased beyond 40% EGR and get the lowest value at 58% EGR rate. Soot and NOx emissions are simultaneously decreased at advanced injection timing before 20.5 ºCA BTDC in conjunction with 58% cooled EGR rate in compared to baseline case.

Keywords: Diesel Engine, Low Temperature Combustion, High Cooled EGR Rates, Combustion, Emissions

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Authors: M. Raciti Castelli, E. Benini

Abstract:

This paper presents a numerical investigation of the unsteady flow around an American 19th century vertical-axis windmill: the Stevens & Jolly rotor, patented on April 16, 1895. The computational approach used is based on solving the complete transient Reynolds-Averaged Navier-Stokes (t-RANS) equations: a full campaign of numerical simulation has been performed using the k-ω SST turbulence model. Flow field characteristics have been investigated for several values of tip speed ratio and for a constant unperturbed free-stream wind velocity of 6 m/s, enabling the study of some unsteady flow phenomena in the rotor wake. Finally, the global power generated from the windmill has been determined for each simulated angular velocity, allowing the calculation of the rotor power-curve.

Keywords: CFD, vertical-axis rotor, windmill.

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Authors: S. Benzarti, H. Mhiri, H. Bournot

Abstract:

In the current work, a numerical parametric study was performed in order to model the fluid mechanics in the riser of a bubbling fluidized bed (BFB). The gas-solid flow was simulated by mean of a multi-fluid Eulerian model incorporating the kinetic theory for solid particles. The bubbling fluidized bed was simulated two dimensionally by mean of a Computational Fluid Dynamic (CFD) commercial software package, Fluent. The effects of using different inter-phase drag function (the drag model of Gidaspow, Syamlal and O-Brien and the EMMS drag model) on the model predictions were evaluated and compared. The results showed that the drag models of Gidaspow and Syamlal and O-Brien overestimated the drag force for the FCC particles and predicted a greater bed expansion in comparison to the EMMS drag model.

Keywords: Bubbling fluidized bed, CFD, drag model, EMMS

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Authors: Bingchun Liu, Pei-Chann Chang, Natasha Huang, Dun Li

Abstract:

Machine Learning and Data Mining are the two important tools for extracting useful information and knowledge from large datasets. In machine learning, classification is a wildly used technique to predict qualitative variables and is generally preferred over regression from an operational point of view. Due to the enormous increase in air pollution in various countries especially China, Air Quality Classification has become one of the most important topics in air quality research and modelling. This study aims at introducing a hybrid classification model based on information theory and Support Vector Machine (SVM) using the air quality data of four cities in China namely Beijing, Guangzhou, Shanghai and Tianjin from Jan 1, 2014 to April 30, 2016. China's Ministry of Environmental Protection has classified the daily air quality into 6 levels namely Serious Pollution, Severe Pollution, Moderate Pollution, Light Pollution, Good and Excellent based on their respective Air Quality Index (AQI) values. Using the information theory, information gain (IG) is calculated and feature selection is done for both categorical features and continuous numeric features. Then SVM Machine Learning algorithm is implemented on the selected features with cross-validation. The final evaluation reveals that the IG and SVM hybrid model performs better than SVM (alone), Artificial Neural Network (ANN) and K-Nearest Neighbours (KNN) models in terms of accuracy as well as complexity.

Keywords: Machine learning, air quality classification, air quality index, information gain, support vector machine, cross-validation.

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Authors: Mohamed Al Mahdi Eshtawie, Masuri Bin Othman

Abstract:

Finite impulse response (FIR) filters have the advantage of linear phase, guaranteed stability, fewer finite precision errors, and efficient implementation. In contrast, they have a major disadvantage of high order need (more coefficients) than IIR counterpart with comparable performance. The high order demand imposes more hardware requirements, arithmetic operations, area usage, and power consumption when designing and fabricating the filter. Therefore, minimizing or reducing these parameters, is a major goal or target in digital filter design task. This paper presents an algorithm proposed for modifying values and the number of non-zero coefficients used to represent the FIR digital pulse shaping filter response. With this algorithm, the FIR filter frequency and phase response can be represented with a minimum number of non-zero coefficients. Therefore, reducing the arithmetic complexity needed to get the filter output. Consequently, the system characteristic i.e. power consumption, area usage, and processing time are also reduced. The proposed algorithm is more powerful when integrated with multiplierless algorithms such as distributed arithmetic (DA) in designing high order digital FIR filters. Here the DA usage eliminates the need for multipliers when implementing the multiply and accumulate unit (MAC) and the proposed algorithm will reduce the number of adders and addition operations needed through the minimization of the non-zero values coefficients to get the filter output.

Keywords: Pulse shaping Filter, Distributed Arithmetic, Optimization algorithm.

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Authors: Nicolae Bold, Daniel Nijloveanu

Abstract:

The idea of cropping-system is a method used by farmers. It is an environmentally-friendly method, protecting the natural resources (soil, water, air, nutritive substances) and increase the production at the same time, taking into account some crop particularities. The combination of this powerful method with the concepts of genetic algorithms results into a possibility of generating sequences of crops in order to form a rotation. The usage of this type of algorithms has been efficient in solving problems related to optimization and their polynomial complexity allows them to be used at solving more difficult and various problems. In our case, the optimization consists in finding the most profitable rotation of cultures. One of the expected results is to optimize the usage of the resources, in order to minimize the costs and maximize the profit. In order to achieve these goals, a genetic algorithm was designed. This algorithm ensures the finding of several optimized solutions of cropping-systems possibilities which have the highest profit and, thus, which minimize the costs. The algorithm uses genetic-based methods (mutation, crossover) and structures (genes, chromosomes). A cropping-system possibility will be considered a chromosome and a crop within the rotation is a gene within a chromosome. Results about the efficiency of this method will be presented in a special section. The implementation of this method would bring benefits into the activity of the farmers by giving them hints and helping them to use the resources efficiently.

Keywords: Genetic algorithm, chromosomes, genes, cropping, agriculture.

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Authors: S. Sarumathi, N. Shanthi, S. Vidhya, P. Ranjetha

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Data mining idea is mounting rapidly in admiration and also in their popularity. The foremost aspire of data mining method is to extract data from a huge data set into several forms that could be comprehended for additional use. The data mining is a technology that contains with rich potential resources which could be supportive for industries and businesses that pay attention to collect the necessary information of the data to discover their customer’s performances. For extracting data there are several methods are available such as Classification, Clustering, Association, Discovering, and Visualization… etc., which has its individual and diverse algorithms towards the effort to fit an appropriate model to the data. STATISTICA mostly deals with excessive groups of data that imposes vast rigorous computational constraints. These results trials challenge cause the emergence of powerful STATISTICA Data Mining technologies. In this survey an overview of the STATISTICA software is illustrated along with their significant features.

Keywords: Data Mining, STATISTICA Data Miner, Text Miner, Enterprise Server, Classification, Association, Clustering, Regression.

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Authors: Alemu Moges Belay

Abstract:

In the 1980s, companies began to feel the effect of three major influences on their product development: newer and innovative technologies, increasing product complexity and larger organizations. And therefore companies were forced to look for new product development methods. This paper tries to focus on the two of new product development methods (DFM and CE). The aim of this paper is to see and analyze different product development methods specifically on Design for Manufacturability and Concurrent Engineering. Companies can achieve and be benefited by minimizing product life cycle, cost and meeting delivery schedule. This paper also presents simplified models that can be modified and used by different companies based on the companies- objective and requirements. Methodologies that are followed to do this research are case studies. Two companies were taken and analysed on the product development process. Historical data, interview were conducted on these companies in addition to that, Survey of literatures and previous research works on similar topics has been done during this research. This paper also tries to show the implementation cost benefit analysis and tries to calculate the implementation time. From this research, it has been found that the two companies did not achieve the delivery time to the customer. Some of most frequently coming products are analyzed and 50% to 80 % of their products are not delivered on time to the customers. The companies are following the traditional way of product development that is sequentially design and production method, which highly affect time to market. In the case study it is found that by implementing these new methods and by forming multi disciplinary team in designing and quality inspection; the company can reduce the workflow steps from 40 to 30.

Keywords: Design for manufacturability, Concurrent Engineering, Time-to-Market, Product development

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Authors: Kyoung Hoon Kim, Giman Kim

Abstract:

The cycles of the steam-injection gas-turbine systems are studied. The analyses of the parametric effects and the optimal operating conditions for the steam-injection gas-turbine (STIG) system and the regenerative steam-injection gas-turbine (RSTIG) system are investigated to ensure the maximum performance. Using the analytic model, the performance parameters of the system such as thermal efficiency, fuel consumption and specific power, and also the optimal operating conditions are evaluated in terms of pressure ratio, steam injection ratio, ambient temperature and turbine inlet temperature (TIT). It is shown that the computational results are presented to have a notable enhancement of thermal efficiency and specific power.

Keywords: gas turbine, RSTIG, steam injection, STIG, thermal efficiency.

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Authors: Pucheng Zhou, Bingrong Hong

Abstract:

How to coordinate the behaviors of the agents through learning is a challenging problem within multi-agent domains. Because of its complexity, recent work has focused on how coordinated strategies can be learned. Here we are interested in using reinforcement learning techniques to learn the coordinated actions of a group of agents, without requiring explicit communication among them. However, traditional reinforcement learning methods are based on the assumption that the environment can be modeled as Markov Decision Process, which usually cannot be satisfied when multiple agents coexist in the same environment. Moreover, to effectively coordinate each agent-s behavior so as to achieve the goal, it-s necessary to augment the state of each agent with the information about other existing agents. Whereas, as the number of agents in a multiagent environment increases, the state space of each agent grows exponentially, which will cause the combinational explosion problem. Profit sharing is one of the reinforcement learning methods that allow agents to learn effective behaviors from their experiences even within non-Markovian environments. In this paper, to remedy the drawback of the original profit sharing approach that needs much memory to store each state-action pair during the learning process, we firstly address a kind of on-line rational profit sharing algorithm. Then, we integrate the advantages of modular learning architecture with on-line rational profit sharing algorithm, and propose a new modular reinforcement learning model. The effectiveness of the technique is demonstrated using the pursuit problem.

Keywords: Multi-agent learning; reinforcement learning; rationalprofit sharing; modular architecture.

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Authors: N. M. Thao, I. Dolguntseva, M. Leijon

Abstract:

Flow blockages referring to the increase in flow are being considered as a vital equipment for marine current energy conversion. However, the shape of these devices will result in extracted energy under the operation. The present work investigates the effect of two configurations of a grating, convergent and divergent that located upstream, to the water flow velocity. The flow characteristics are studied by Computational Fluid Dynamic simulation by using the ANSYS Fluent solver for these specified arrangements of the grating. The results indicate that distinguished characteristics of flow velocity between “convergent” and “divergent” grating placements is up to 10% in confined conditions. Furthermore, the velocity in case of convergent grating is higher than that of divergent grating.

Keywords: Marine current energy, marine current energy converter, turbine grating, RANS simulation, water flow velocity.

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Authors: Muqdad Al-Juboori, Bithin Datta

Abstract:

Hydraulic structures such as gravity dams are classified as essential structures, and have the vital role in providing strong and safe water resource management. Three major aspects must be considered to achieve an effective design of such a structure: 1) The building cost, 2) safety, and 3) accurate analysis of seepage characteristics. Due to the complexity and non-linearity relationships of the seepage process, many approximation theories have been developed; however, the application of these theories results in noticeable errors. The analytical solution, which includes the difficult conformal mapping procedure, could be applied for a simple and symmetrical problem only. Therefore, the objectives of this paper are to: 1) develop a surrogate model based on numerical simulated data using SEEPW software to approximately simulate seepage process related to a hydraulic structure, 2) develop and solve a linked simulation-optimization model based on the developed surrogate model to describe the seepage occurring under a concrete gravity dam, in order to obtain optimum and safe design at minimum cost. The result shows that the linked simulation-optimization model provides an efficient and optimum design of concrete gravity dams.

Keywords: Artificial neural network, concrete gravity dam, genetic algorithm, seepage analysis.

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Authors: Raksha Sharma, Vishnu Kant Soni, Manoj Kumar Mishra, Prachet Bhuyan

Abstract:

Grid computing is a form of distributed computing that involves coordinating and sharing computational power, data storage and network resources across dynamic and geographically dispersed organizations. Scheduling onto the Grid is NP-complete, so there is no best scheduling algorithm for all grid computing systems. An alternative is to select an appropriate scheduling algorithm to use in a given grid environment because of the characteristics of the tasks, machines and network connectivity. Job and resource scheduling is one of the key research area in grid computing. The goal of scheduling is to achieve highest possible system throughput and to match the application need with the available computing resources. Motivation of the survey is to encourage the amateur researcher in the field of grid computing, so that they can understand easily the concept of scheduling and can contribute in developing more efficient scheduling algorithm. This will benefit interested researchers to carry out further work in this thrust area of research.

Keywords: Grid Computing, Job Scheduling, ResourceScheduling.

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Authors: Patrick Cummings, Laura Cassani, Deirdre Kelliher

Abstract:

In this paper we present findings from a research effort to apply a hybrid collaborative-context approach for a system focused on Marine Corps civil affairs data collection, aggregation, and analysis called the Marine Civil Information Management System (MARCIMS). The goal of this effort is to provide operators with information to make sense of the interconnectedness of entities and relationships in their area of operation and discover existing data to support civil military operations. Our approach to build a recommendation engine was designed to overcome several technical challenges, including 1) ensuring models were robust to the relatively small amount of data collected by the Marine Corps civil affairs community; 2) finding methods to recommend novel data for which there are no interactions captured; and 3) overcoming confirmation bias by ensuring content was recommended that was relevant for the mission despite being obscure or less well known. We solve this by implementing a combination of collective matrix factorization (CMF) and graph-based random walks to provide recommendations to civil military operations users. We also present a method to resolve the challenge of computation complexity inherent from highly connected nodes through a precomputed process.

Keywords: Recommendation engine, collaborative filtering, context based recommendation, graph analysis, coverage, civil affairs operations, Marine Corps.

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Authors: S. S. Mishra, D. K. Yadav

Abstract:

This paper focuses on cost and profit analysis of single-server Markovian queuing system with two priority classes. In this paper, functions of total expected cost, revenue and profit of the system are constructed and subjected to optimization with respect to its service rates of lower and higher priority classes. A computing algorithm has been developed on the basis of fast converging numerical method to solve the system of non linear equations formed out of the mathematical analysis. A novel performance measure of cost and profit analysis in view of its economic interpretation for the system with priority classes is attempted to discuss in this paper. On the basis of computed tables observations are also drawn to enlighten the variational-effect of the model on the parameters involved therein.

Keywords: Cost and Profit, Computing, Expected Revenue, Priority classes

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Authors: Izian Abd. Karim, Kachalla Mohammed, Nora Farah A. A. Aziz, Law Teik Hua

Abstract:

The economic use and ease of construction of profiled deck composite slab is marred with the complex and un-economic strength verification required for the serviceability and general safety considerations. Beside these, albeit factors such as shear span length, deck geometries and mechanical frictions greatly influence the longitudinal shear strength, that determines the ultimate strength of profiled deck composite slab, and number of methods available for its determination; partial shear and slope-intercept are the two methods according to Euro-code 4 provision. However, the complexity associated with shear behavior of profiled deck composite slab, the use of these methods in determining the load carrying capacities of such slab yields different and conflicting values. This couple with the time and cost constraint associated with the strength verification is a source of concern that draws more attentions nowadays, the issue is critical. Treating some of these known shear strength influencing factors as random variables, the load carrying capacity violation of profiled deck composite slab from the use of the two-methods defined according to Euro-code 4 are determined using reliability approach, and comparatively studied. The study reveals safety values from the use of m-k method shows good standing compared with that from the partial shear method.

Keywords: Composite slab, first order reliability method, longitudinal shear, partial shear connection, slope-intercept.

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Authors: N. Tuncbag, T. Haliloglu, O. Keskin

Abstract:

Understanding the cell's large-scale organization is an interesting task in computational biology. Thus, protein-protein interactions can reveal important organization and function of the cell. Here, we investigated the correspondence between protein interactions and function for the yeast. We obtained the correlations among the set of proteins. Then these correlations are clustered using both the hierarchical and biclustering methods. The detailed analyses of proteins in each cluster were carried out by making use of their functional annotations. As a result, we found that some functional classes appear together in almost all biclusters. On the other hand, in hierarchical clustering, the dominancy of one functional class is observed. In brief, from interaction data to function, some correlated results are noticed about the relationship between interaction and function which might give clues about the organization of the proteins.

Keywords: Pair-wise protein interactions, DIP database, functional correlations, biclustering.

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Authors: David Lávicka

Abstract:

This paper looks into detailed investigation of thermal-hydraulic characteristics of the flow field in a fuel rod model, especially near the spacer. The area investigate represents a source of information on the velocity flow field, vortex, and on the amount of heat transfer into the coolant all of which are critical for the design and improvement of the fuel rod in nuclear power plants. The flow field investigation uses three-dimensional Computational Fluid Dynamics (CFD) with the Reynolds stresses turbulence model (RSM). The fuel rod model incorporates a vertical annular channel where three different shapes of spacers are used; each spacer shape is addressed individually. These spacers are mutually compared in consideration of heat transfer capabilities between the coolant and the fuel rod model. The results are complemented with the calculated heat transfer coefficient in the location of the spacer and along the stainless-steel pipe.

Keywords: CFD, fuel rod model, heat transfer, spacer

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Authors: M. Behbahani-Nejad, Y. Shekari

Abstract:

A reduced order modeling approach for natural gas transient flow in pipelines is presented. The Euler equations are considered as the governing equations and solved numerically using the implicit Steger-Warming flux vector splitting method. Next, the linearized form of the equations is derived and the corresponding eigensystem is obtained. Then, a few dominant flow eigenmodes are used to construct an efficient reduced-order model. A well-known test case is presented to demonstrate the accuracy and the computational efficiency of the proposed method. The results obtained are in good agreement with those of the direct numerical method and field data. Moreover, it is shown that the present reduced-order model is more efficient than the conventional numerical techniques for transient flow analysis of natural gas in pipelines.

Keywords: Eigenmode, Natural Gas, Reduced Order Modeling, Transient Flow.

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Authors: V. Salajka, J. Kala, P. Hradil

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The presented article deals with the description of a numerical model of a corridor at a Central Interim Spent Fuel Storage Facility (hereinafter CISFSF). The model takes into account the effect of air flows on the temperature of stored waste. The computational model was implemented in the ANSYS/CFX programming environment in the form of a CFD task solution, which was compared with an approximate analytical calculation. The article includes a categorization of the individual alternatives for the ventilation of such underground systems. The aim was to evaluate a ventilation system for a CISFSF with regard to its stability and capacity to provide sufficient ventilation for the removal of heat produced by stored casks with spent nuclear fuel.

Keywords: Temperature fields, Spent Fuel, Interim storage facility, CFD.

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Authors: S. H. R. Lo

Abstract:

Virtual engineering technology has undergone rapid progress in recent years and is being adopted increasingly by manufacturing companies of many engineering disciplines. There is an increasing demand from industry for qualified virtual engineers. The qualified virtual engineers should have the ability of applying engineering principles and mechanical design methods within the commercial software package environment. It is a challenge to the engineering education in universities which traditionally tends to lack the integration of knowledge and skills required for solving real world problems. In this paper, a case study shows some recent development of a MSc Mechanical Engineering course at Department of Engineering and Technology in MMU, and in particular, two units Simulation of Mechanical Systems(SMS) and Computer Aided Fatigue Analysis(CAFA) that emphasize virtual engineering education and promote integration of knowledge acquisition, skill training and industrial application.

Keywords: Computational modelling and simulation, mechanical engineering education.

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