Multi Objective Micro Genetic Algorithm for Combine and Reroute Problem

Several approaches such as linear programming, network modeling, greedy heuristic and decision support system are well-known approaches in solving irregular airline operation problem. This paper presents an alternative approach based on Multi Objective Micro Genetic Algorithm. The aim of this research is to introduce the concept of Multi Objective Micro Genetic Algorithm as a tool to solve irregular airline operation, combine and reroute problem. The experiment result indicated that the model could obtain optimal solutions within a few second.

Heat Transfer Modeling in Multi-Layer Cookware using Finite Element Method

The high temperature degree and uniform Temperature Distribution (TD) on surface of cookware which contact with food are effective factors for improving cookware application. Additionally, the ability of pan material in retaining the heat and nonreactivity with foods are other significant properties. It is difficult for single material to meet a wide variety of demands such as superior thermal and chemical properties. Multi-Layer Plate (MLP) makes more regular TD. In this study the main objectives are to find the best structure (single or multi-layer) and materials to provide maximum temperature degree and uniform TD up side surface of pan. And also heat retaining of used metals with goal of improving the thermal quality of pan to economize the energy. To achieve this aim were employed Finite Element Method (FEM) for analyzing transient thermal behavior of applied materials. The analysis has been extended for different metals, we achieved the best temperature profile and heat retaining in Copper/ Stainless Steel MLP.

MIMCA: A Modelling and Simulation Approach in Support of the Design and Construction of Manufacturing Control Systems Using Modular Petri net

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.

Modeling of a Second Order Non-Ideal Sigma-Delta Modulator

A behavioral model of a second order switchedcapacitor Sigma-Delta modulator is presented. The purpose of this work is the presentation of a behavioral model of a second order switched capacitor ΣΔ modulator considering (Error due to Clock Jitter, Thermal noise Amplifier Noise, Amplifier Slew-Rate, Non linearity of amplifiers, Gain error, Charge Injection, Clock Feedthrough, and Nonlinear on-resistance). A comparison between the use of MOS switches and the use transmission gate switches use is analyzed.

CFD Simulation of Condensing Vapor Bubble using VOF Model

In this study, direct numerical simulation for the bubble condensation in the subcooled boiling flow was performed. The main goal was to develop the CFD modeling for the bubble condensation and to evaluate the accuracy of the VOF model with the developed CFD modeling. CFD modeling for the bubble condensation was developed by modeling the source terms in the governing equations of VOF model using UDF. In the modeling, the amount of condensation was determined using the interfacial heat transfer coefficient obtained from the bubble velocity, liquid temperature and bubble diameter every time step. To evaluate the VOF model using the CFD modeling for the bubble condensation, CFD simulation results were compared with SNU experimental results such as bubble volume and shape, interfacial area, bubble diameter and bubble velocity. Simulation results predicted well the behavior of the actual condensing bubble. Therefore, it can be concluded that the VOF model using the CFD modeling for the bubble condensation will be a useful computational fluid dynamics tool for analyzing the behavior of the condensing bubble in a wide range of the subcooled boiling flow.

Cyprus- Offshore Aquaculture Mooring Systems: Current Status and Future Development

Cyprus- offshore aquaculture industry has promising prospects taking into account that Cyprus is an island. Its production trend is increasing overtaking bigger countries such Greece and Italy. However, current mooring systems seem to be under-performing acting as obstacles for its future development. Furthermore, shallow coastal waters scarcity due to competing industries dictates future development to come by moving further from shore exposing fish farms and subsequently mooring systems to harsher environmental loadings. It is, therefore, of paramount importance to design mooring systems based on engineering and scientific principles and leave behind the present “trial and error" methods. This paper presents the current state of Cyprus- offshore aquaculture industry and focuses of its mooring designs by proposing a new methodology for designing more reliable systems, hence ensuring its future.

The Optimized Cascade PI Controllers of the Generator Control Unit in the Aircraft Power System

This paper presents the optimal controller design of the generator control unit in the aircraft power system. The adaptive tabu search technique is applied to tune the controller parameters until the best terminal output voltage of generator is achieved. The output response from the system with the controllers designed by the proposed technique is compared with those from the conventional method. The transient simulations using the commercial software package show that the controllers designed from the adaptive tabu search algorithm can provide the better output performance compared with the result from the classical method. The proposed design technique is very flexible and useful for electrical aircraft engineers.

LQR Based PID Controller Design for 3-DOF Helicopter System

In this article, LQR based PID controller design for 3DOF helicopter system is investigated. The 3-DOF helicopter system is a benchmark laboratory model having strongly nonlinear characteristics and unstable dynamics which make the control of such system a challenging task. This article first presents the mathematical model of the 3DOF helicopter system and then illustrates the basic idea and technical formulation for controller design. The paper explains the simple approach for the approximation of PID design parameters from the LQR controller gain matrix. The simulation results show that the investigated controller has both static and dynamic performance, therefore the stability and the quick control effect can be obtained simultaneously for the 3DOF helicopter system.

3D Face Modeling based on 3D Dense Morphable Face Shape Model

Realistic 3D face model is more precise in representing pose, illumination, and expression of face than 2D face model so that it can be utilized usefully in various applications such as face recognition, games, avatars, animations, and etc. In this paper, we propose a 3D face modeling method based on 3D dense morphable shape model. The proposed 3D modeling method first constructs a 3D dense morphable shape model from 3D face scan data obtained using a 3D scanner. Next, the proposed method extracts and matches facial landmarks from 2D image sequence containing a face to be modeled, and then reconstructs 3D vertices coordinates of the landmarks using a factorization-based SfM technique. Then, the proposed method obtains a 3D dense shape model of the face to be modeled by fitting the constructed 3D dense morphable shape model into the reconstructed 3D vertices. Also, the proposed method makes a cylindrical texture map using 2D face image sequence. Finally, the proposed method generates a 3D face model by rendering the 3D dense face shape model using the cylindrical texture map. Through building processes of 3D face model by the proposed method, it is shown that the proposed method is relatively easy, fast and precise.

Analysis of Target Location Estimation in High Performance Radar System

In this paper, an analysis of a target location estimation system using the best linear unbiased estimator (BLUE) for high performance radar systems is presented. In synthetic environments, we are here concerned with three key elements of radar system modeling, which makes radar systems operates accurately in strategic situation in virtual ground. Radar Cross Section (RCS) modeling is used to determine the actual amount of electromagnetic waves that are reflected from a tactical object. Pattern Propagation Factor (PPF) is an attenuation coefficient of the radar equation that contains the reflection from the surface of the earth, the diffraction, the refraction and scattering by the atmospheric environment. Clutter is the unwanted echoes of electronic systems. For the data fusion of output results from radar detection in synthetic environment, BLUE is used and compared with the mean values of each simulation results. Simulation results demonstrate the performance of the radar system.

Data Oriented Modeling of Uniform Random Variable: Applied Approach

In this paper we introduce new data oriented modeling of uniform random variable well-matched with computing systems. Due to this conformity with current computers structure, this modeling will be efficiently used in statistical inference.

Estimating Spatial Disaggregation of Urban Thermal Responsiveness on Summer Diurnal Range with a Numerical Modeling Approach in Bangkok, Thailand

Facing the concern of the population to its environment and to climatic change, city planners are now considering the urban climate in their choices of planning. The urban climate, representing different urban morphologies across central Bangkok metropolitan area (BMA), are used to investigates the effects of both the composition and configuration of variables of urban morphology indicators on the summer diurnal range of urban climate, using correlation analyses and multiple linear regressions. Results show first indicate that approximately 92.6% of the variation in the average maximum daytime near-surface air temperature (Ta) was explained jointly by the two composition variables of urban morphology indicators including open space ratio (OSR) and floor area ratio (FAR). It has been possible to determine the membership of sample areas to the local climate zones (LCZs) using these urban morphology descriptors automatically computed with GIS and remote sensed data. Finally result found the temperature differences among zones of large separation, such as the city center could be respectively from 35.48±1.04ºC (Mean±S.D.) warmer than the outskirt of Bangkok on average for maximum daytime near surface temperature to 28.27±0.21ºC for extreme event and, can exceed as 8ºC. A spatially disaggregation of urban thermal responsiveness map would be helpful for several reasons. First, it would localize urban areas concerned by different climate behavior over summer daytime and be a good indicator of urban climate variability. Second, when overlaid with a land cover map, this map may contribute to identify possible urban management strategies to reduce heat wave effects in BMA.

A Study on Crashworhiness Assessment and Improvement of Tilting Train Made of Sandwich Composites

This paper describes the crashworthiness assessment and improvement of tlting train made of sandwich composites. The crashworhiness assessment of tilting train was conducted according to four collision scenarios of the Korean railway safety law. Collision analysis was carried out using explicit finite element analysis code LS-DYNA 3D. The finite element model consists of 3-D finite element model and 1-D equivalent model to save the finite element modeling and calculation time. It found that the crashworthiness analysis results were satisfied with the performance requirements except the crash scenario-2. In order to meet the crashworthiness requirements for crash scenario-2, the stiffness reinforcement for the laminate composite cover and metal frames of cabmask structure were proposed. Consequentially, it has satisfied the requirement for crash scenario-2.

Probabilistic Electrical Power Generation Modeling Using Decimal to Binary Conversion

Generation system reliability assessment is an important task which can be performed using deterministic or probabilistic techniques. The probabilistic approaches have significant advantages over the deterministic methods. However, more complicated modeling is required by the probabilistic approaches. Power generation model is a basic requirement for this assessment. One form of the generation models is the well known capacity outage probability table (COPT). Different analytical techniques have been used to construct the COPT. These approaches require considerable mathematical modeling of the generating units. The unit-s models are combined to build the COPT which will add more burdens on the process of creating the COPT. Decimal to Binary Conversion (DBC) technique is widely and commonly applied in electronic systems and computing This paper proposes a novel utilization of the DBC to create the COPT without engaging in analytical modeling or time consuming simulations. The simple binary representation , “0 " and “1 " is used to model the states o f generating units. The proposed technique is proven to be an effective approach to build the generation model.

Modeling Parametric Vibration of Multistage Gear Systems as a Tool for Design Optimization

This work presents a numerical model developed to simulate the dynamics and vibrations of a multistage tractor gearbox. The effect of time varying mesh stiffness, time varying frictional torque on the gear teeth, lateral and torsional flexibility of the shafts and flexibility of the bearings were included in the model. The model was developed by using the Lagrangian method, and it was applied to study the effect of three design variables on the vibration and stress levels on the gears. The first design variable, module, had little effect on the vibration levels but a higher module resulted to higher bending stress levels. The second design variable, pressure angle, had little effect on the vibration levels, but had a strong effect on the stress levels on the pinion of a high reduction ratio gear pair. A pressure angle of 25o resulted to lower stress levels for a pinion with 14 teeth than a pressure angle of 20o. The third design variable, contact ratio, had a very strong effect on both the vibration levels and bending stress levels. Increasing the contact ratio to 2.0 reduced both the vibration levels and bending stress levels significantly. For the gear train design used in this study, a module of 2.5 and contact ratio of 2.0 for the various meshes was found to yield the best combination of low vibration levels and low bending stresses. The model can therefore be used as a tool for obtaining the optimum gear design parameters for a given multistage spur gear train.

Impacts of Climate Change under the Threat of Global Warming for an Agricultural Watershed of the Kangsabati River

The effects of global warming on India vary from the submergence of low-lying islands and coastal lands to the melting of glaciers in the Indian Himalayas, threatening the volumetric flow rate of many of the most important rivers of India and South Asia. In India, such effects are projected to impact millions of lives. As a result of ongoing climate change, the climate of India has become increasingly volatile over the past several decades; this trend is expected to continue. Climate change is one of the most important global environmental challenges, with implications for food production, water supply, health, energy, etc. Addressing climate change requires a good scientific understanding as well as coordinated action at national and global level. The climate change issue is part of the larger challenge of sustainable development. As a result, climate policies can be more effective when consistently embedded within broader strategies designed to make national and regional development paths more sustainable. The impact of climate variability and change, climate policy responses, and associated socio-economic development will affect the ability of countries to achieve sustainable development goals. A very well calibrated Soil and Water Assessment Tool (R2 = 0.9968, NSE = 0.91) was exercised over the Khatra sub basin of the Kangsabati River watershed in Bankura district of West Bengal, India, in order to evaluate projected parameters for agricultural activities. Evapotranspiration, Transmission Losses, Potential Evapotranspiration and Lateral Flow to reach are evaluated from the years 2041-2050 in order to generate a picture for sustainable development of the river basin and its inhabitants. India has a significant stake in scientific advancement as well as an international understanding to promote mitigation and adaptation. This requires improved scientific understanding, capacity building, networking and broad consultation processes. This paper is a commitment towards the planning, management and development of the water resources of the Kangsabati River by presenting detailed future scenarios of the Kangsabati river basin, Khatra sub basin, over the mentioned time period. India-s economy and societal infrastructures are finely tuned to the remarkable stability of the Indian monsoon, with the consequence that vulnerability to small changes in monsoon rainfall is very high. In 2002 the monsoon rains failed during July, causing profound loss of agricultural production with a drop of over 3% in India-s GDP. Neither the prolonged break in the monsoon nor the seasonal rainfall deficit was predicted. While the general features of monsoon variability and change are fairly well-documented, the causal mechanisms and the role of regional ecosystems in modulating the changes are still not clear. Current climate models are very poor at modelling the Asian monsoon: this is a challenging and critical region where the ocean, atmosphere, land surface and mountains all interact. The impact of climate change on regional ecosystems is likewise unknown. The potential for the monsoon to become more volatile has major implications for India itself and for economies worldwide. Knowledge of future variability of the monsoon system, particularly in the context of global climate change, is of great concern for regional water and food security. The major findings of this paper were that of all the chosen projected parameters, transmission losses, soil water content, potential evapotranspiration, evapotranspiration and lateral flow to reach, display an increasing trend over the time period of years 2041- 2050.

Stochastic Learning Algorithms for Modeling Human Category Learning

Most neural network (NN) models of human category learning use a gradient-based learning method, which assumes that locally-optimal changes are made to model parameters on each learning trial. This method tends to under predict variability in individual-level cognitive processes. In addition many recent models of human category learning have been criticized for not being able to replicate rapid changes in categorization accuracy and attention processes observed in empirical studies. In this paper we introduce stochastic learning algorithms for NN models of human category learning and show that use of the algorithms can result in (a) rapid changes in accuracy and attention allocation, and (b) different learning trajectories and more realistic variability at the individual-level.

Viscosity of Vegetable Oils and Biodiesel and Energy Generation

The present work describes an experimental investigation concerning the determination of viscosity behavior with shear rate and temperature of edible oils: canola; sunflower; corn; soybean and the no edible oil: Jatropha curcas. Besides these, it was tested a blend of canola, corn and sunflower oils as well as sunflower and soybean biodiesel. Based on experiments, it was obtained shear stress and viscosity at different shear rates of each sample at 40ºC, as well as viscosity of each sample at various temperatures in the range of 24 to 85ºC. Furthermore, it was compared the curves obtained for the viscosity versus temperature with the curves obtained by modeling the viscosity dependency on temperature using the Vogel equation. Also a test in a stationary engine was performed in order to study the energy generation using blends of soybean oil and soybean biodiesel with diesel.

E-Learning Methodology Development using Modeling

Simulation and modeling computer programs are concerned with construction of models for analyzing different perspectives and possibilities in changing conditions environment. The paper presents theoretical justification and evaluation of qualitative e-learning development model in perspective of advancing modern technologies. There have been analyzed principles of qualitative e-learning in higher education, productivity of studying process using modern technologies, different kind of methods and future perspectives of e-learning in formal education. Theoretically grounded and practically tested model of developing e-learning methods using different technologies for different type of classroom, which can be used in professor-s decision making process to choose the most effective e-learning methods has been worked out.

CFD Modeling of PROX Microreactor for Fuel Processing

In order to investigate a PROX microreactor performance, two-dimensional modeling of the reacting flow between two parallel plates is performed through a finite volume method using an improved SIMPLE algorithm. A three-step surface kinetics including hydrogen oxidation, carbon monoxide oxidation and water-gas shift reaction is applied for a Pt-Fe/γ-Al2O3 catalyst and operating temperatures of about 100ºC. Flow pattern, pressure field, temperature distribution, and mole fractions of species are found in the whole domain for all cases. Also, the required reactive length for removing carbon monoxide from about 2% to less than 10 ppm is found. Furthermore, effects of hydraulic diameter, wall temperature, and inlet mole fraction of air and water are investigated by considering carbon monoxide selectivity and conversion. It is found that air and water addition may improve the performance of the microreactor in carbon monoxide removal in such operating conditions; this is in agreement with the pervious published results.