Developing a Simple and an Accurate Formula for the Conduction Angle of a Single Phase Rectifier with RL Load

The paper presents a simple and an accurate formula that has been developed for the conduction angle (δ) of a single phase half-wave or full-wave controlled rectifier with RL load. This formula can be also used for calculating the conduction angle (δ) in case of A.C. voltage regulator with inductive load under discontinuous current mode. The simulation results shows that the conduction angle calculated from the developed formula agree very well with that obtained from the exact solution arrived from the iterative method. Applying the developed formula can reduce the computational time and reduce the time for manual classroom calculation. In addition, the proposed formula is attractive for real time implementations.

Improved Back Propagation Algorithm to Avoid Local Minima in Multiplicative Neuron Model

The back propagation algorithm calculates the weight changes of artificial neural networks, and a common approach is to use a training algorithm consisting of a learning rate and a momentum factor. The major drawbacks of above learning algorithm are the problems of local minima and slow convergence speeds. The addition of an extra term, called a proportional factor reduces the convergence of the back propagation algorithm. We have applied the three term back propagation to multiplicative neural network learning. The algorithm is tested on XOR and parity problem and compared with the standard back propagation training algorithm.

Correlation of Viscosity in Nanofluids using Genetic Algorithm-neural Network (GA-NN)

An accurate and proficient artificial neural network (ANN) based genetic algorithm (GA) is developed for predicting of nanofluids viscosity. A genetic algorithm (GA) is used to optimize the neural network parameters for minimizing the error between the predictive viscosity and the experimental one. The experimental viscosity in two nanofluids Al2O3-H2O and CuO-H2O from 278.15 to 343.15 K and volume fraction up to 15% were used from literature. The result of this study reveals that GA-NN model is outperform to the conventional neural nets in predicting the viscosity of nanofluids with mean absolute relative error of 1.22% and 1.77% for Al2O3-H2O and CuO-H2O, respectively. Furthermore, the results of this work have also been compared with others models. The findings of this work demonstrate that the GA-NN model is an effective method for prediction viscosity of nanofluids and have better accuracy and simplicity compared with the others models.

Role-play Gaming Simulation for Flood Management on Cultural Heritage: A Case Study of Ayutthaya Historic City

The main aim of this research is to develop a methodology to encourage people's awareness, knowledge and understanding on the participation of flood management for cultural heritage, as the cooperation and interaction among government section, private section, and public section through role-play gaming simulation theory. The format of this research is to develop Role-play gaming simulation from existing documents, game or role-playing from several sources and existing data of the research site. We found that role-play gaming simulation can be implemented to help improving the understanding of the existing problem and the impact of the flood on cultural heritage, and the role-play game can be developed into the tool to improve people's knowledge, understanding and awareness about people's participation for flood management on cultural heritage, moreover the cooperation among the government, private section and public section will be improved through the theory of role-play gaming simulation.

Visualising Energy Efficiency Landscape

This paper discusses the landscape design that could increase energy efficiency in a house. By planting trees in a house compound, the tree shades prevent direct sunlight from heating up the building, and it enables cooling off the surrounding air. The requirement for air-conditioning could be minimized and the air quality could be improved. During the life time of a tree, the saving cost from the mentioned benefits could be up to US $ 200 for each tree. The project intends to visually describe the landscape design in a house compound that could enhance energy efficiency and consequently lead to energy saving. The house compound model was developed in three dimensions by using AutoCAD 2005, the animation was programmed by using LightWave 3D softwares i.e. Modeler and Layout to display the tree shadings in the wall. The visualization was executed on a VRML Pad platform and implemented on a web environment.

Current Status and Energy Savings Potential of Solar Shading in Ningbo

To investigate the energy performance of solar shading devices, this paper carried out a survey on the current status of solar shading utilization in buildings in Ningbo and performed building simulations to evaluate the energy savings potential by adopting different solar shading devices. Results show that solar shading utilization in this area is not popular and effective, and should be considered firstly in the design stage since the potential for energy savings is up to 6.8% for residential buildings and 9.4% for commercial buildings.

Ensembling Adaptively Constructed Polynomial Regression Models

The approach of subset selection in polynomial regression model building assumes that the chosen fixed full set of predefined basis functions contains a subset that is sufficient to describe the target relation sufficiently well. However, in most cases the necessary set of basis functions is not known and needs to be guessed – a potentially non-trivial (and long) trial and error process. In our research we consider a potentially more efficient approach – Adaptive Basis Function Construction (ABFC). It lets the model building method itself construct the basis functions necessary for creating a model of arbitrary complexity with adequate predictive performance. However, there are two issues that to some extent plague the methods of both the subset selection and the ABFC, especially when working with relatively small data samples: the selection bias and the selection instability. We try to correct these issues by model post-evaluation using Cross-Validation and model ensembling. To evaluate the proposed method, we empirically compare it to ABFC methods without ensembling, to a widely used method of subset selection, as well as to some other well-known regression modeling methods, using publicly available data sets.

The Sequestration of Heavy Metals Contaminating the Wonderfonteinspruit Catchment Area using Natural Zeolite

For more than 120 years, gold mining formed the backbone the South Africa-s economy. The consequence of mine closure was observed in large-scale land degradation and widespread pollution of surface water and groundwater. This paper investigates the feasibility of using natural zeolite in removing heavy metals contaminating the Wonderfonteinspruit Catchment Area (WCA), a water stream with high levels of heavy metals and radionuclide pollution. Batch experiments were conducted to study the adsorption behavior of natural zeolite with respect to Fe2+, Mn2+, Ni2+, and Zn2+. The data was analysed using the Langmuir and Freudlich isotherms. Langmuir was found to correlate the adsorption of Fe2+, Mn2+, Ni2+, and Zn2+ better, with the adsorption capacity of 11.9 mg/g, 1.2 mg/g, 1.3 mg/g, and 14.7 mg/g, respectively. Two kinetic models namely, pseudo-first order and pseudo second order were also tested to fit the data. Pseudo-second order equation was found to be the best fit for the adsorption of heavy metals by natural zeolite. Zeolite functionalization with humic acid increased its uptake ability.

Three Dimensional Modeling of Mixture Formation and Combustion in a Direct Injection Heavy-Duty Diesel Engine

Due to the stringent legislation for emission of diesel engines and also increasing demand on fuel consumption, the importance of detailed 3D simulation of fuel injection, mixing and combustion have been increased in the recent years. In the present work, FIRE code has been used to study the detailed modeling of spray and mixture formation in a Caterpillar heavy-duty diesel engine. The paper provides an overview of the submodels implemented, which account for liquid spray atomization, droplet secondary break-up, droplet collision, impingement, turbulent dispersion and evaporation. The simulation was performed from intake valve closing (IVC) to exhaust valve opening (EVO). The predicted in-cylinder pressure is validated by comparing with existing experimental data. A good agreement between the predicted and experimental values ensures the accuracy of the numerical predictions collected with the present work. Predictions of engine emissions were also performed and a good quantitative agreement between measured and predicted NOx and soot emission data were obtained with the use of the present Zeldowich mechanism and Hiroyasu model. In addition, the results reported in this paper illustrate that the numerical simulation can be one of the most powerful and beneficial tools for the internal combustion engine design, optimization and performance analysis.

A Practical Approach for Electricity Load Forecasting

This paper is a continuation of our daily energy peak load forecasting approach using our modified network which is part of the recurrent networks family and is called feed forward and feed back multi context artificial neural network (FFFB-MCANN). The inputs to the network were exogenous variables such as the previous and current change in the weather components, the previous and current status of the day and endogenous variables such as the past change in the loads. Endogenous variable such as the current change in the loads were used on the network output. Experiment shows that using endogenous and exogenous variables as inputs to the FFFBMCANN rather than either exogenous or endogenous variables as inputs to the same network produces better results. Experiments show that using the change in variables such as weather components and the change in the past load as inputs to the FFFB-MCANN rather than the absolute values for the weather components and past load as inputs to the same network has a dramatic impact and produce better accuracy.

Secure Protocol for Short Message Service

Short Message Service (SMS) has grown in popularity over the years and it has become a common way of communication, it is a service provided through General System for Mobile Communications (GSM) that allows users to send text messages to others. SMS is usually used to transport unclassified information, but with the rise of mobile commerce it has become a popular tool for transmitting sensitive information between the business and its clients. By default SMS does not guarantee confidentiality and integrity to the message content. In the mobile communication systems, security (encryption) offered by the network operator only applies on the wireless link. Data delivered through the mobile core network may not be protected. Existing end-to-end security mechanisms are provided at application level and typically based on public key cryptosystem. The main concern in a public-key setting is the authenticity of the public key; this issue can be resolved by identity-based (IDbased) cryptography where the public key of a user can be derived from public information that uniquely identifies the user. This paper presents an encryption mechanism based on the IDbased scheme using Elliptic curves to provide end-to-end security for SMS. This mechanism has been implemented over the standard SMS network architecture and the encryption overhead has been estimated and compared with RSA scheme. This study indicates that the ID-based mechanism has advantages over the RSA mechanism in key distribution and scalability of increasing security level for mobile service.

Quantum Computation using Two Component Bose-Einstein Condensates

Quantum computation using qubits made of two component Bose-Einstein condensates (BECs) is analyzed. We construct a general framework for quantum algorithms to be executed using the collective states of the BECs. The use of BECs allows for an increase of energy scales via bosonic enhancement, resulting in two qubit gate operations that can be performed at a time reduced by a factor of N, where N is the number of bosons per qubit. We illustrate the scheme by an application to Deutsch-s and Grover-s algorithms, and discuss possible experimental implementations. Decoherence effects are analyzed under both general conditions and for the experimental implementation proposed.

Accurate Visualization of Graphs of Functions of Two Real Variables

The study of a real function of two real variables can be supported by visualization using a Computer Algebra System (CAS). One type of constraints of the system is due to the algorithms implemented, yielding continuous approximations of the given function by interpolation. This often masks discontinuities of the function and can provide strange plots, not compatible with the mathematics. In recent years, point based geometry has gained increasing attention as an alternative surface representation, both for efficient rendering and for flexible geometry processing of complex surfaces. In this paper we present different artifacts created by mesh surfaces near discontinuities and propose a point based method that controls and reduces these artifacts. A least squares penalty method for an automatic generation of the mesh that controls the behavior of the chosen function is presented. The special feature of this method is the ability to improve the accuracy of the surface visualization near a set of interior points where the function may be discontinuous. The present method is formulated as a minimax problem and the non uniform mesh is generated using an iterative algorithm. Results show that for large poorly conditioned matrices, the new algorithm gives more accurate results than the classical preconditioned conjugate algorithm.

Dynamic Modeling of Intelligent Air-Cushion Tracked Vehicle for Swamp Peat

Modeling of the dynamic behavior and motion are renewed interest in the improved tractive performance of an intelligent air-cushion tracked vehicle (IACTV). This paper presents a new dynamical model for the forces on the developed small scale intelligent air-cushion tracked vehicle moving over swamp peat. The air cushion system partially supports the 25 % of vehicle total weight in order to make the vehicle ground contact pressure 7 kN/m2. As the air-cushion support system can adjust automatically on the terrain, so the vehicle can move over the terrain without any risks. The springdamper system is used with the vehicle body to control the aircushion support system on any undulating terrain by making the system sinusoidal form. Experiments have been carried out to investigate the relationships among tractive efficiency, slippage, traction coefficient, load distribution ratio, tractive effort, motion resistance and power consumption in given terrain conditions. Experiment and simulation results show that air-cushion system improves the vehicle performance by keeping traction coefficient of 71% and tractive efficiency of 62% and the developed model can meet the demand of transport efficiency with the optimal power consumption.

Indoor Moisture Control of Auckland Houses with Different Ventilation Systems

Auckland has a temperate climate with comfortable warm, dry summers and mild, wet winters. Auckland house design not only focus on winter thermal performance and indoor thermal condition, but also indoor moisture control, which is closely related to indirect health effects such as dust mites, fungi, etc. Most Auckland houses are designed to use temporary heating for winter indoor thermal comfort. Based on field study data of indoor microclimate conditions of two Auckland townhouses with a whole home mechanical ventilation system or a passive wind directional skylight vent, this study is to evaluate and compare indoor moisture conditions of two insulated townhouses only using temporary heating with different ventilation systems.

Mathematical Modeling of Asphaltene Precipitation: A Review

In the Enhanced Oil Recovery (EOR) method, use of Carbon dioxide flooding whereby CO2 is injected into an oil reservoir to increase output when extracting oil resulted significant recovery worldwide. The carbon dioxide function as a pressurizing agent when mixed into the underground crude oil will reduce its viscosity and will enable a rapid oil flow. Despite the CO2’s advantage in the oil recovery, it may result to asphaltene precipitation a problem that will cause the reduction of oil produced from oil wells. In severe cases, asphaltene precipitation can cause costly blockages in oil pipes and machinery. This paper presents reviews of several studies done on mathematical modeling of asphaltene precipitation. The synthesized result from several researches done on this topic can be used as guide in order to better understand asphaltene precipitation. Likewise, this can be used as initial reference for students, and new researchers doing study on asphaltene precipitation.

Profit Optimization for Solar Plant Electricity Production

In this paper a stochastic scenario-based model predictive control applied to molten salt storage systems in concentrated solar tower power plant is presented. The main goal of this study is to build up a tool to analyze current and expected future resources for evaluating the weekly power to be advertised on electricity secondary market. This tool will allow plant operator to maximize profits while hedging the impact on the system of stochastic variables such as resources or sunlight shortage. Solving the problem first requires a mixed logic dynamic modeling of the plant. The two stochastic variables, respectively the sunlight incoming energy and electricity demands from secondary market, are modeled by least square regression. Robustness is achieved by drawing a certain number of random variables realizations and applying the most restrictive one to the system. This scenario approach control technique provides the plant operator a confidence interval containing a given percentage of possible stochastic variable realizations in such a way that robust control is always achieved within its bounds. The results obtained from many trajectory simulations show the existence of a ‘’reliable’’ interval, which experimentally confirms the algorithm robustness.

Investigation of Regenerative and Recuperative Burners for Different Sizes of Reheating Furnaces

This research aims to analyze the regenerative burner and the recuperative burner for the different reheating furnaces in the steel industry. The warm air temperatures of the burners are determined to suit with the sizes of the reheating furnaces by considering the air temperature, the fuel cost and the investment cost. The calculations of the payback period and the net present value are studied to compare the burners for the different reheating furnaces. The energy balance is utilized to calculate and compare the energy used in the different sizes of reheating furnaces for each burner. It is found that the warm air temperature is different if the sizes of reheating furnaces are varied. Based on the considerations of the net present value and the payback period, the regenerative burner is suitable for all plants at the same life of the burner. Finally, the sensitivity analysis of all factors has been discussed in this research.

Study on Damage Tolerance Behavior of Integrally Stiffened Panel and Conventional Stiffened Panel

The damage tolerance behavior of integrally and conventional stiffened panel is investigated based on the fracture mechanics and finite element analysis. The load bearing capability and crack growth characteristic of both types of the stiffened panels having same configuration subjected to distributed tensile load is examined in this paper. A fourteen-stringer stiffened panel is analyzed for a central skin crack propagating towards the adjacent stringers. Stress intensity factors and fatigue crack propagation rates of both types of the stiffened panels are then compared. The analysis results show that integral stiffening causes higher stress intensity factor than conventional stiffened panel as the crack tip passes through the stringer and the integrally stiffened panel has less load bearing capability than the riveted stiffened panel.