Search results for: Computational Fluid Dynamics (CFD) model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8804

Search results for: Computational Fluid Dynamics (CFD) model

7574 Robust Batch Process Scheduling in Pharmaceutical Industries: A Case Study

Authors: Tommaso Adamo, Gianpaolo Ghiani, Antonio D. Grieco, Emanuela Guerriero

Abstract:

Batch production plants provide a wide range of scheduling problems. In pharmaceutical industries a batch process is usually described by a recipe, consisting of an ordering of tasks to produce the desired product. In this research work we focused on pharmaceutical production processes requiring the culture of a microorganism population (i.e. bacteria, yeasts or antibiotics). Several sources of uncertainty may influence the yield of the culture processes, including (i) low performance and quality of the cultured microorganism population or (ii) microbial contamination. For these reasons, robustness is a valuable property for the considered application context. In particular, a robust schedule will not collapse immediately when a cell of microorganisms has to be thrown away due to a microbial contamination. Indeed, a robust schedule should change locally in small proportions and the overall performance measure (i.e. makespan, lateness) should change a little if at all. In this research work we formulated a constraint programming optimization (COP) model for the robust planning of antibiotics production. We developed a discrete-time model with a multi-criteria objective, ordering the different criteria and performing a lexicographic optimization. A feasible solution of the proposed COP model is a schedule of a given set of tasks onto available resources. The schedule has to satisfy tasks precedence constraints, resource capacity constraints and time constraints. In particular time constraints model tasks duedates and resource availability time windows constraints. To improve the schedule robustness, we modeled the concept of (a, b) super-solutions, where (a, b) are input parameters of the COP model. An (a, b) super-solution is one in which if a variables (i.e. the completion times of a culture tasks) lose their values (i.e. cultures are contaminated), the solution can be repaired by assigning these variables values with a new values (i.e. the completion times of a backup culture tasks) and at most b other variables (i.e. delaying the completion of at most b other tasks). The efficiency and applicability of the proposed model is demonstrated by solving instances taken from a real-life pharmaceutical company. Computational results showed that the determined super-solutions are near-optimal.

Keywords: Constraint programming, super-solutions, robust scheduling, batch process, pharmaceutical industries.

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7573 Sloshing Control in Tilting Phases of the Pouring Process

Authors: Maria P. Tzamtzi, Fotis N. Koumboulis

Abstract:

We propose a control design scheme that aims to prevent undesirable liquid outpouring and suppress sloshing during the forward and backward tilting phases of the pouring process, for the case of liquid containers carried by manipulators. The proposed scheme combines a partial inverse dynamics controller with a PID controller, tuned with the use of a “metaheuristic" search algorithm. The “metaheuristic" search algorithm tunes the PID controller based on simulation results of the plant-s linearization around the operating point corresponding to the critical tilting angle, where outpouring initiates. Liquid motion is modeled using the well-known pendulumtype model. However, the proposed controller does not require measurements of the liquid-s motion within the tank.

Keywords: Robotic systems, Controller design, Sloshingsuppression, Metaheuristic optimization.

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7572 Selective Intra Prediction Mode Decision for H.264/AVC Encoders

Authors: Jun Sung Park, Hyo Jung Song

Abstract:

H.264/AVC offers a considerably higher improvement in coding efficiency compared to other compression standards such as MPEG-2, but computational complexity is increased significantly. In this paper, we propose selective mode decision schemes for fast intra prediction mode selection. The objective is to reduce the computational complexity of the H.264/AVC encoder without significant rate-distortion performance degradation. In our proposed schemes, the intra prediction complexity is reduced by limiting the luma and chroma prediction modes using the directional information of the 16×16 prediction mode. Experimental results are presented to show that the proposed schemes reduce the complexity by up to 78% maintaining the similar PSNR quality with about 1.46% bit rate increase in average.

Keywords: Video encoding, H.264, Intra prediction.

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7571 Numerical Optimization of Trapezoidal Microchannel Heat Sinks

Authors: Yue-Tzu Yang, Shu-Ching Liao

Abstract:

This study presents the numerical simulation of three-dimensional incompressible steady and laminar fluid flow and conjugate heat transfer of a trapezoidal microchannel heat sink using water as a cooling fluid in a silicon substrate. Navier-Stokes equations with conjugate energy equation are discretized by finite-volume method. We perform numerical computations for a range of 50 ≦ Re ≦ 600, 0.05W ≦ P ≦ 0.8W, 20W/cm2 q"≦ 40W/cm2. The present study demonstrates the numerical optimization of a trapezoidal microchannel heat sink design using the response surface methodology (RSM) and the genetic algorithm method (GA). The results show that the average Nusselt number increases with an increase in the Reynolds number or pumping power, and the thermal resistance decreases as the pumping power increases. The thermal resistance of a trapezoidal microchannel is minimized for a constant heat flux and constant pumping power.

Keywords: Microchannel heat sinks, Conjugate heat transfer, Optimization, Genetic algorithm method.

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7570 A New Approach to Face Recognition Using Dual Dimension Reduction

Authors: M. Almas Anjum, M. Younus Javed, A. Basit

Abstract:

In this paper a new approach to face recognition is presented that achieves double dimension reduction, making the system computationally efficient with better recognition results and out perform common DCT technique of face recognition. In pattern recognition techniques, discriminative information of image increases with increase in resolution to a certain extent, consequently face recognition results change with change in face image resolution and provide optimal results when arriving at a certain resolution level. In the proposed model of face recognition, initially image decimation algorithm is applied on face image for dimension reduction to a certain resolution level which provides best recognition results. Due to increased computational speed and feature extraction potential of Discrete Cosine Transform (DCT), it is applied on face image. A subset of coefficients of DCT from low to mid frequencies that represent the face adequately and provides best recognition results is retained. A tradeoff between decimation factor, number of DCT coefficients retained and recognition rate with minimum computation is obtained. Preprocessing of the image is carried out to increase its robustness against variations in poses and illumination level. This new model has been tested on different databases which include ORL , Yale and EME color database.

Keywords: Biometrics, DCT, Face Recognition, Illumination, Computation, Feature extraction.

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7569 Variable Rough Set Model and Its Knowledge Reduction for Incomplete and Fuzzy Decision Information Systems

Authors: Da-kuan Wei, Xian-zhong Zhou, Dong-jun Xin, Zhi-wei Chen

Abstract:

The information systems with incomplete attribute values and fuzzy decisions commonly exist in practical problems. On the base of the notion of variable precision rough set model for incomplete information system and the rough set model for incomplete and fuzzy decision information system, the variable rough set model for incomplete and fuzzy decision information system is constructed, which is the generalization of the variable precision rough set model for incomplete information system and that of rough set model for incomplete and fuzzy decision information system. The knowledge reduction and heuristic algorithm, built on the method and theory of precision reduction, are proposed.

Keywords: Rough set, Incomplete and fuzzy decision information system, Limited valued tolerance relation, Knowledge reduction, Variable rough set model

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7568 Influence of Valve Lift Timing on Producer Gas Combustion and Its Modeling Using Two-Stage Wiebe Function

Authors: M. Sreedhar Babu, Vishal Garg, S. B. Akella, Shibu Clement, N. K. S Rajan

Abstract:

Producer gas is a biomass derived gaseous fuel which is extensively used in internal combustion engines for power generation application. Unlike the conventional hydrocarbon fuels (Gasoline and Natural gas), the combustion properties of producer gas fuel are much different. Therefore, setting of optimal spark time for efficient engine operation is required. Owing to the fluctuating tendency of producer gas composition during gasification process, the heat release patterns (dictating the power output and emissions) obtained are quite different from conventional fuels. It was found that, valve lift timing is yet another factor which influences the burn rate of producer gas fuel, and thus, the heat release rate of the engine. Therefore, the present study was motivated to estimate the influence of valve lift timing analytically (Wiebe model) on the burn rate of producer gas through curve fitting against experimentally obtained mass fraction burn curves of several producer gas compositions. Furthermore, Wiebe models are widely used in zero-dimensional codes for engine parametric studies and are quite popular. This study also addresses the influence of hydrogen and methane concentration of producer gas on combustion trends, which are known to cause dynamics in engine combustion.

Keywords: Combustion Duration, crank angle, mass fraction burnt, producer gas, wiebe combustion model, wide open throttle.

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7567 Convective Interactions and Heat Transfer in a Czochralski Melt with a Model Phase Boundary of Two Different Shapes

Authors: R. Faiez, M. Mashhoudi, F. Najafi

Abstract:

Implicit in most large-scale numerical analyses of the crystal growth from the melt is the assumption that the shape and position of the phase boundary are determined by the transport phenomena coupled strongly to the melt hydrodynamics. In the present numerical study, the interface shape-effect on the convective interactions in a Czochralski oxide melt is described. It was demonstrated that thermocapillary flow affects inversely the phase boundaries of distinct shapes. The inhomogenity of heat flux and the location of the stagnation point at the crystallization front were investigated. The forced convection effect on the point displacement at the boundary found to be much stronger for the flat plate interface compared to the cone-shaped one with and without the Marangoni flow.

Keywords: Computer simulation, fluid flow, interface shape, thermocapillary effect.

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7566 Artificial Intelligence for Software Quality Improvement

Authors: Martín Agüero, Franco Madou, Gabriela Esperón, Daniela López De Luise

Abstract:

This paper presents a software quality support tool, a Java source code evaluator and a code profiler based on computational intelligence techniques. It is Java prototype software developed by AI Group [1] from the Research Laboratories at Universidad de Palermo: an Intelligent Java Analyzer (in Spanish: Analizador Java Inteligente, AJI). It represents a new approach to evaluate and identify inaccurate source code usage and transitively, the software product itself. The aim of this project is to provide the software development industry with a new tool to increase software quality by extending the value of source code metrics through computational intelligence.

Keywords: Software metrics, artificial intelligence, neuralnetworks, clustering algorithms, expert systems

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7565 DMC with Adaptive Weighted Output

Authors: Ahmed Abbas, M.R. M Rizk, Mohamed El-Sayed

Abstract:

This paper presents a new adaptive DMC controller that improves the controller performance in case of plant-model mismatch. The new controller monitors the plant measured output, compares it with the model output and calculates weights applied to the controller move. Simulations show that the new controller can help improve control performance and avoid instability in case of severe model mismatches.

Keywords: Adaptive control, dynamic matrix control, DMC, model predictive control

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7564 Comparative Study on Status and Development of Transient Flow Analysis Including Simple Surge Tank

Authors: I. Abuiziah, A. Oulhaj, K. Sebari, D. Ouazar

Abstract:

This paper presents the problem of modeling and simulating of transient phenomena in conveying pipeline systems based on the rigid column and full elastic methods. Transient analysis is important and one of the more challenging and complicated flow problem in the design and the operation of water pipeline systems. Transient can produce large pressure forces and rapid fluid acceleration into a water pipeline system, these disturbances may result in device failures, system fatigue or pipe ruptures, and even the dirty water intrusion. Several methods have been introduced and used to analyze transient flow, an accurate analysis and suitable protection devices should be used to protect water pipeline systems. The fourth-order Runge-Kutta method has been used to solve the dynamic and continuity equations in the rigid column method, while the characteristics method used to solve these equations in the full elastic method. The results obtained provide that the model is an efficient tool for flow transient analysis and provide approximately identical results by using these two methods. Moreover; using the simple surge tank ”open surge tank” reduces the unfavorable effects of transients.

Keywords: Elastic method, Flow transient, Open surge tank, Pipeline, Protection devices, Numerical model, Rigid column method.

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7563 Segmentation of Piecewise Polynomial Regression Model by Using Reversible Jump MCMC Algorithm

Authors: Suparman

Abstract:

Piecewise polynomial regression model is very flexible model for modeling the data. If the piecewise polynomial regression model is matched against the data, its parameters are not generally known. This paper studies the parameter estimation problem of piecewise polynomial regression model. The method which is used to estimate the parameters of the piecewise polynomial regression model is Bayesian method. Unfortunately, the Bayes estimator cannot be found analytically. Reversible jump MCMC algorithm is proposed to solve this problem. Reversible jump MCMC algorithm generates the Markov chain that converges to the limit distribution of the posterior distribution of piecewise polynomial regression model parameter. The resulting Markov chain is used to calculate the Bayes estimator for the parameters of piecewise polynomial regression model.

Keywords: Piecewise, Bayesian, reversible jump MCMC, segmentation.

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7562 Evaluation of Dynamic Behavior of a Rotor-Bearing System in Operating Conditions

Authors: Mohammad Hadi Jalali, Behrooz Shahriari, Mostafa Ghayour, Saeed Ziaei-Rad, Shahram Yousefi

Abstract:

Most flexible rotors can be considered as beam-like structures. In many cases, rotors are modeled as one-dimensional bodies, made basically of beam-like shafts with rigid bodies attached to them. This approach is typical of rotor dynamics, both analytical and numerical, and several rotor dynamic codes, based on the finite element method, follow this trend. In this paper, a finite element model based on Timoshenko beam elements is utilized to analyze the lateral dynamic behavior of a certain rotor-bearing system in operating conditions.

Keywords: Finite element method, Operational deflection shape, Timoshenko beam elements, Unbalance response.

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7561 A Stable Pose Estimation Method for the Biped Robot using Image Information

Authors: Sangbum Park, Youngjoon Han

Abstract:

This paper proposes a balance control scheme for a biped robot to trace an arbitrary path using image information. While moving, it estimates the zero moment point(ZMP) of the biped robot in the next step using a Kalman filter and renders an appropriate balanced pose of the robot. The ZMP can be calculated from the robot's pose, which is measured from the reference object image acquired by a CCD camera on the robot's head. For simplifying the kinematical model, the coordinates systems of individual joints of each leg are aligned and the robot motion is approximated as an inverted pendulum so that a simple linear dynamics, 3D-LIPM(3D-Linear Inverted Pendulum Mode) can be applied. The efficiency of the proposed algorithm has been proven by the experiments performed on unknown trajectory.

Keywords: Biped robot, Zero moment point, Balance control, Kalman filter.

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7560 Navigation and Guidance System Architectures for Small Unmanned Aircraft Applications

Authors: Roberto Sabatini, Celia Bartel, Anish Kaharkar, Tesheen Shaid, Subramanian Ramasamy

Abstract:

Two multisensor system architectures for navigation and guidance of small Unmanned Aircraft (UA) are presented and compared. The main objective of our research is to design a compact, light and relatively inexpensive system capable of providing the required navigation performance in all phases of flight of small UA, with a special focus on precision approach and landing, where Vision Based Navigation (VBN) techniques can be fully exploited in a multisensor integrated architecture. Various existing techniques for VBN are compared and the Appearance-Based Navigation (ABN) approach is selected for implementation. Feature extraction and optical flow techniques are employed to estimate flight parameters such as roll angle, pitch angle, deviation from the runway centreline and body rates. Additionally, we address the possible synergies of VBN, Global Navigation Satellite System (GNSS) and MEMS-IMU (Micro-Electromechanical System Inertial Measurement Unit) sensors, and the use of Aircraft Dynamics Model (ADM) to provide additional information suitable to compensate for the shortcomings of VBN and MEMS-IMU sensors in high-dynamics attitude determination tasks. An Extended Kalman Filter (EKF) is developed to fuse the information provided by the different sensors and to provide estimates of position, velocity and attitude of the UA platform in real-time. The key mathematical models describing the two architectures i.e., VBN-IMU-GNSS (VIG) system and VIGADM (VIGA) system are introduced. The first architecture uses VBN and GNSS to augment the MEMS-IMU. The second mode also includes the ADM to provide augmentation of the attitude channel. Simulation of these two modes is carried out and the performances of the two schemes are compared in a small UA integration scheme (i.e., AEROSONDE UA platform) exploring a representative cross-section of this UA operational flight envelope, including high dynamics manoeuvres and CAT-I to CAT-III precision approach tasks. Simulation of the first system architecture (i.e., VIG system) shows that the integrated system can reach position, velocity and attitude accuracies compatible with the Required Navigation Performance (RNP) requirements. Simulation of the VIGA system also shows promising results since the achieved attitude accuracy is higher using the VBN-IMU-ADM than using VBN-IMU only. A comparison of VIG and VIGA system is also performed and it shows that the position and attitude accuracy of the proposed VIG and VIGA systems are both compatible with the RNP specified in the various UA flight phases, including precision approach down to CAT-II.

Keywords: Global Navigation Satellite System (GNSS), Lowcost Navigation Sensors, MEMS Inertial Measurement Unit (IMU), Unmanned Aerial Vehicle, Vision Based Navigation.

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7559 Supervisory Controller with Three-State Energy Saving Mode for Induction Motor in Fluid Transportation

Authors: O. S. Ebrahim, K. O. Shawky, M. O. Ebrahim, P. K. Jain

Abstract:

Induction Motor (IM) driving pump is the main consumer of electricity in a typical fluid transportation system (FTS). Changing the connection of the stator windings from delta to star at no load can achieve noticeable active and reactive energy savings. This paper proposes a supervisory hysteresis liquid-level control with three-state energy saving mode (ESM) for IM in FTS including storage tank. The IM pump drive comprises modified star/delta switch and hydromantic coupler. Three-state ESM is defined, along with the normal running, and named analog to computer ESMs as follows: Sleeping mode in which the motor runs at no load with delta stator connection, hibernate mode in which the motor runs at no load with a star connection, and motor shutdown is the third energy saver mode. A logic flow-chart is synthesized to select the motor state at no-load for best energetic cost reduction, considering the motor thermal capacity used. An artificial neural network (ANN) state estimator, based on the recurrent architecture, is constructed and learned in order to provide fault-tolerant capability for the supervisory controller. Sequential test of Wald is used for sensor fault detection. Theoretical analysis, preliminary experimental testing and, computer simulations are performed to show the effectiveness of the proposed control in terms of reliability, power quality and energy/coenergy cost reduction with the suggestion of power factor correction.

Keywords: Artificial Neural Network, ANN, Energy Saving Mode, ESM, Induction Motor, IM, star/delta switch, supervisory control, fluid transportation, reliability, power quality.

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7558 Model-Based Software Regression Test Suite Reduction

Authors: Shiwei Deng, Yang Bao

Abstract:

In this paper, we present a model-based regression test suite reducing approach that uses EFSM model dependence analysis and probability-driven greedy algorithm to reduce software regression test suites. The approach automatically identifies the difference between the original model and the modified model as a set of elementary model modifications. The EFSM dependence analysis is performed for each elementary modification to reduce the regression test suite, and then the probability-driven greedy algorithm is adopted to select the minimum set of test cases from the reduced regression test suite that cover all interaction patterns. Our initial experience shows that the approach may significantly reduce the size of regression test suites.

Keywords: Dependence analysis, EFSM model, greedy algorithm, regression test.

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7557 Development of Coronal Field and Solar Wind Components for MHD Interplanetary Simulations

Authors: Ljubomir Nikolic, Larisa Trichtchenko

Abstract:

The connection between solar activity and adverse phenomena in the Earth’s environment that can affect space and ground based technologies has spurred interest in Space Weather (SW) research. A great effort has been put on the development of suitable models that can provide advanced forecast of SW events. With the progress in computational technology, it is becoming possible to develop operational large scale physics based models which can incorporate the most important physical processes and domains of the Sun-Earth system. In order to enhance our SW prediction capabilities we are developing advanced numerical tools. With operational requirements in mind, our goal is to develop a modular simulation framework of propagation of the disturbances from the Sun through interplanetary space to the Earth. Here, we report and discuss on the development of coronal field and solar wind components for a large scale MHD code. The model for these components is based on a potential field source surface model and an empirical Wang-Sheeley-Arge solar wind relation. 

Keywords: Space weather, numerical modeling, coronal field, solar wind.

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7556 Model of the Increasing the Capacity of the Train and Railway Track by Using the New Type of Wagon

Authors: Martin Kendra, Jaroslav Mašek, Juraj Čamaj, Martin Búda

Abstract:

The paper deals with possibilities of increase train capacity by using a new type of railway wagon. In the first part is created a mathematical model to calculate the capacity of the train. The model is based on the main limiting parameters of the train - maximum number of axles per train, maximum gross weight of train, maximum length of train and number of TEUs per one wagon. In the second part is the model applied to four different model trains with different composition of the train set and three different average weights of TEU and a train consisting of a new type of wagons. The result is to identify where the carrying capacity of the original trains is higher, respectively less than a capacity of train consisting of a new type of wagons.

Keywords: Loading units, theoretical capacity model, train capacity, wagon for intermodal transport.

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7555 A Microcontroller Implementation of Model Predictive Control

Authors: Amira Abbes Kheriji, Faouzi Bouani, Mekki Ksouri, Mohamed Ben Ahmed

Abstract:

Model Predictive Control (MPC) is increasingly being proposed for real time applications and embedded systems. However comparing to PID controller, the implementation of the MPC in miniaturized devices like Field Programmable Gate Arrays (FPGA) and microcontrollers has historically been very small scale due to its complexity in implementation and its computation time requirement. At the same time, such embedded technologies have become an enabler for future manufacturing enterprises as well as a transformer of organizations and markets. Recently, advances in microelectronics and software allow such technique to be implemented in embedded systems. In this work, we take advantage of these recent advances in this area in the deployment of one of the most studied and applied control technique in the industrial engineering. In fact in this paper, we propose an efficient framework for implementation of Generalized Predictive Control (GPC) in the performed STM32 microcontroller. The STM32 keil starter kit based on a JTAG interface and the STM32 board was used to implement the proposed GPC firmware. Besides the GPC, the PID anti windup algorithm was also implemented using Keil development tools designed for ARM processor-based microcontroller devices and working with C/Cµ langage. A performances comparison study was done between both firmwares. This performances study show good execution speed and low computational burden. These results encourage to develop simple predictive algorithms to be programmed in industrial standard hardware. The main features of the proposed framework are illustrated through two examples and compared with the anti windup PID controller.

Keywords: Embedded systems, Model Predictive Control, microcontroller, Keil tool.

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7554 Modeling and Simulation Methods Using MATLAB/Simulink

Authors: Jamuna Konda, Umamaheswara Reddy Karumuri, Sriramya Muthugi, Varun Pishati, Ravi Shakya,

Abstract:

This paper investigates the challenges involved in mathematical modeling of plant simulation models ensuring the performance of the plant models much closer to the real time physical model. The paper includes the analysis performed and investigation on different methods of modeling, design and development for plant model. Issues which impact the design time, model accuracy as real time model, tool dependence are analyzed. The real time hardware plant would be a combination of multiple physical models. It is more challenging to test the complete system with all possible test scenarios. There are possibilities of failure or damage of the system due to any unwanted test execution on real time.

Keywords: Model Based Design, MATLAB, Simulink, Stateflow, plant model, real time model, real-time workshop, target language compiler.

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7553 Fabrication and Electrical Characterization of Al/BaxSr1-xTiO3/Pt/SiO2/Si Configuration for FeFET Applications

Authors: Ala'eddin A. Saif , Z. A. Z. Jamal, Z. Sauli, P. Poopalan

Abstract:

The ferroelectric behavior of barium strontium titanate (BST) in thin film form has been investigated in order to study the possibility of using BST for ferroelectric gate-field effect transistor (FeFET) for memory devices application. BST thin films have been fabricated as Al/BST/Pt/SiO2/Si-gate configuration. The variation of the dielectric constant (ε) and tan δ with frequency have been studied to ensure the dielectric quality of the material. The results show that at low frequencies, ε increases as the Ba content increases, whereas at high frequencies, it shows the opposite variation, which is attributed to the dipole dynamics. tan δ shows low values with a peak at the mid-frequency range. The ferroelectric behavior of the Al/BST/Pt/SiO2/Si has been investigated using C-V characteristics. The results show that the strength of the ferroelectric hysteresis loop increases as the Ba content increases; this is attributed to the grain size and dipole dynamics effect.

Keywords: BST thin film, Electrical properties, Ferroelectrichysteresis, Ferroelectric FET.

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7552 Development of a Model for the Comprehensive Analysis and Evaluation of Service Productivity

Authors: A. Petz, S. Duckwitz, C. Schmalz, S. Meyer, S. Mütze-Niewöhner, C.M. Schlick

Abstract:

Although services play a crucial role in economy, service did not gain as much importance as productivity management in manufacturing. This paper presents key findings from literature and practice. Based on an initial definition of complex services, seven productivity concepts are briefly presented and assessed by relevant, complex service specific criteria. Following the findings a complex service productivity model is proposed. The novel model comprises of all specific dimensions of service provision from both, the provider-s as well as costumer-s perspective. A clear assignment of identified value drivers and relationships between them is presented. In order to verify the conceptual service productivity model a case study from a project engineering department of a chemical plant development and construction company is presented.

Keywords: assessment model, complex services, service productivity model, value driver.

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7551 Effect of Drawbar Force on the Dynamic Characteristics of a Spindle-Tool Holder System

Authors: Jui-Pui Hung, Yu-Sheng Lai, Tzuo-Liang Luo, Kung-Da Wu, Yun-Ji Zhan

Abstract:

This study presented the investigation of the influence of the tool holder interface stiffness on the dynamic characteristics of a spindle tool system. The interface stiffness was produced by drawbar force on the tool holder, which tends to affect the spindle dynamics. In order to assess the influence of interface stiffness on the vibration characteristic of spindle unit, we first created a three dimensional finite element model of a high speed spindle system integrated with tool holder. The key point for the creation of FEM model is the modeling of the rolling interface within the angular contact bearings and the tool holder interface. The former can be simulated by a introducing a series of spring elements between inner and outer rings. The contact stiffness was calculated according to Hertz contact theory and the preload applied on the bearings. The interface stiffness of the tool holder was identified through the experimental measurement and finite element modal analysis. Current results show that the dynamic stiffness was greatly influenced by the tool holder system. In addition, variations of modal damping, static stiffness and dynamic stiffness of the spindle tool system were greatly determined by the interface stiffness of the tool holder which was in turn dependent on the draw bar force applied on the tool holder. Overall, this study demonstrates that identification of the interface characteristics of spindle tool holder is of very importance for the refinement of the spindle tooling system to achieve the optimum machining performance.

Keywords: Dynamic stiffness, Drawbar force, Interface stiffness, Spindle-tool holder.

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7550 Source of Oseltamivir Resistance Due to R152K Mutation of Influenza B Virus Neuraminidase: Molecular Modeling

Authors: J. Tengrang, T. Rungrotmongkol, S. Hannongbua

Abstract:

Every 2-3 years the influenza B virus serves epidemics. Neuraminidase (NA) is an important target for influenza drug design. Although, oseltamivir, an oral neuraminidase drug, has been shown good inhibitory efficiency against wild-type of influenza B virus, the lower susceptibility to the R152K mutation has been reported. Better understanding of oseltamivir efficiency and resistance toward the influenza B NA wild-type and R152K mutant, respectively, could be useful for rational drug design. Here, two complex systems of wild-type and R152K NAs with oseltamivir bound were studied using molecular dynamics (MD) simulations. Based on 5-ns MD simulation, the loss of notable hydrogen bond and decrease in per-residue decomposition energy from the mutated residue K152 contributed to drug compared to those of R152 in wildtype were found to be a primary source of high-level of oseltamivir resistance due to the R152K mutation.

Keywords: Influenza B neuraminidase, Molecular dynamics simulation, Oseltamivir resistance, R152K mutant

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7549 Computational Simulation of Imploding Current Sheath Trajectory at the Radial Phase of Plasma Focus Performance

Authors: R. Amrollahi, M. Habibi

Abstract:

When the shock front (SF) hits the central electrode axis of plasma focus device, a reflected shock wave moves radially outwards. The current sheath (CS) results from ionization of filled gas between two electrodes continues to compress inwards until it hits the out-going reflected shock front. In this paper the Lagrangian equations are solved for a parabolic shock trajectory yielding a first and second approximation for the CS path. To determine the accuracy of the approximation, the same problem is solved for a straight shock.

Keywords: Radial compression, Shock wave trajectory, Current sheath, Slog model.

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7548 Effects of Nanolayer Structure and Brownian Motion of Particles in Thermal Conductivity Enhancement of Nanofluids

Authors: M. Izadi, S. Hossainpour, D. Jalali-Vahid

Abstract:

Nanofluids are novel fluids that are going to have an important role in future industrial thermal device designs. Studies are being predominantly conducted on the mechanism of these heat transfers. The key to this attraction is in the increase in thermal conductivity brought about by the Nanofluids compared with the base fluid. Different models have been proposed for calculation of effective thermal conduction that has been gradually modified. In this investigation effect of nanolayer structure and Brownian motion of particles are studied and a new modified thermal conductivity model is proposed. Temperature, concentration, nanolayer thickness and particle size are taken as variables and their effect are studied simultaneously on the thermal conductivity of the fluids, showing the concentration of the nanoparticles to affect the nanolayer thickness which also affects the Brownian motion.

Keywords: Relative thermal conductivity, Brownian motion, Nanolayer structure.

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7547 A Multiclass BCMP Queueing Modeling and Simulation-Based Road Traffic Flow Analysis

Authors: Jouhra Dad, Mohammed Ouali, Yahia Lebbah

Abstract:

Urban road network traffic has become one of the most studied research topics in the last decades. This is mainly due to the enlargement of the cities and the growing number of motor vehicles traveling in this road network. One of the most sensitive problems is to verify if the network is congestion-free. Another related problem is the automatic reconfiguration of the network without building new roads to alleviate congestions. These problems require an accurate model of the traffic to determine the steady state of the system. An alternative is to simulate the traffic to see if there are congestions and when and where they occur. One key issue is to find an adequate model for road intersections. Once the model established, either a large scale model is built or the intersection is represented by its performance measures and simulation for analysis. In both cases, it is important to seek the queueing model to represent the road intersection. In this paper, we propose to model the road intersection as a BCMP queueing network and we compare this analytical model against a simulation model for validation.

Keywords: Queueing theory, transportation systems, BCMPqueueing network, performance measures, modeling, simulation

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7546 Application of Computational Intelligence Techniques for Economic Load Dispatch

Authors: S.C. Swain, S. Panda, A.K. Mohanty, C. Ardil

Abstract:

This paper presents the applications of computational intelligence techniques to economic load dispatch problems. The fuel cost equation of a thermal plant is generally expressed as continuous quadratic equation. In real situations the fuel cost equations can be discontinuous. In view of the above, both continuous and discontinuous fuel cost equations are considered in the present paper. First, genetic algorithm optimization technique is applied to a 6- generator 26-bus test system having continuous fuel cost equations. Results are compared to conventional quadratic programming method to show the superiority of the proposed computational intelligence technique. Further, a 10-generator system each with three fuel options distributed in three areas is considered and particle swarm optimization algorithm is employed to minimize the cost of generation. To show the superiority of the proposed approach, the results are compared with other published methods.

Keywords: Economic Load Dispatch, Continuous Fuel Cost, Quadratic Programming, Real-Coded Genetic Algorithm, Discontinuous Fuel Cost, Particle Swarm Optimization.

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7545 An Automatic Model Transformation Methodology Based on Semantic and Syntactic Comparisons and the Granularity Issue Involved

Authors: Tiexin Wang, Sebastien Truptil, Frederick Benaben

Abstract:

Model transformation, as a pivotal aspect of Modeldriven engineering, attracts more and more attentions both from researchers and practitioners. Many domains (enterprise engineering, software engineering, knowledge engineering, etc.) use model transformation principles and practices to serve to their domain specific problems; furthermore, model transformation could also be used to fulfill the gap between different domains: by sharing and exchanging knowledge. Since model transformation has been widely used, there comes new requirement on it: effectively and efficiently define the transformation process and reduce manual effort that involved in. This paper presents an automatic model transformation methodology based on semantic and syntactic comparisons, and focuses particularly on granularity issue that existed in transformation process. Comparing to the traditional model transformation methodologies, this methodology serves to a general purpose: crossdomain methodology. Semantic and syntactic checking measurements are combined into a refined transformation process, which solves the granularity issue. Moreover, semantic and syntactic comparisons are supported by software tool; manual effort is replaced in this way.

Keywords: Automatic model transformation, granularity issue, model-driven engineering, semantic and syntactic comparisons.

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