Search results for: Chemical Reaction Optimization
2989 Ultrasound Assisted Method to Increase the Aluminum Dissolve Rate from Acidified Water
Authors: Wen Po Cheng, Chi Hua Fu, Ping Hung Chen, Ruey Fang Yu
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Aluminum salt that is generally presents as a solid phase in the water purification sludge (WPS) can be dissolved, recovering a liquid phase, by adding strong acid to the sludge solution. According to the reaction kinetics, when reactant is in the form of small particles with a large specific surface area, or when the reaction temperature is high, the quantity of dissolved aluminum salt or reaction rate, respectively are high. Therefore, in this investigation, water purification sludge (WPS) solution was treated with ultrasonic waves to break down the sludge, and different acids (1 N HCl and 1 N H2SO4) were used to acidify it. Acid dosages that yielded the solution pH of less than two were used. The results thus obtained indicate that the quantity of dissolved aluminum in H2SO4-acidified solution exceeded that in HCl-acidified solution. Additionally, ultrasonic treatment increased the rate of dissolution of aluminum and the amount dissolved. The quantity of aluminum dissolved at 60℃ was 1.5 to 2.0 times higher than that at 25℃.Keywords: Coagulant, Aluminum, Ultrasonic, Acidification, Temperature, Sludge.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22762988 On the Parameter Optimization of Fuzzy Inference Systems
Authors: Erika Martinez Ramirez, Rene V. Mayorga
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Nowadays, more engineering systems are using some kind of Artificial Intelligence (AI) for the development of their processes. Some well-known AI techniques include artificial neural nets, fuzzy inference systems, and neuro-fuzzy inference systems among others. Furthermore, many decision-making applications base their intelligent processes on Fuzzy Logic; due to the Fuzzy Inference Systems (FIS) capability to deal with problems that are based on user knowledge and experience. Also, knowing that users have a wide variety of distinctiveness, and generally, provide uncertain data, this information can be used and properly processed by a FIS. To properly consider uncertainty and inexact system input values, FIS normally use Membership Functions (MF) that represent a degree of user satisfaction on certain conditions and/or constraints. In order to define the parameters of the MFs, the knowledge from experts in the field is very important. This knowledge defines the MF shape to process the user inputs and through fuzzy reasoning and inference mechanisms, the FIS can provide an “appropriate" output. However an important issue immediately arises: How can it be assured that the obtained output is the optimum solution? How can it be guaranteed that each MF has an optimum shape? A viable solution to these questions is through the MFs parameter optimization. In this Paper a novel parameter optimization process is presented. The process for FIS parameter optimization consists of the five simple steps that can be easily realized off-line. Here the proposed process of FIS parameter optimization it is demonstrated by its implementation on an Intelligent Interface section dealing with the on-line customization / personalization of internet portals applied to E-commerce.Keywords: Artificial Intelligence, Fuzzy Logic, Fuzzy InferenceSystems, Nonlinear Optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19842987 Optimization of the Input Layer Structure for Feed-Forward Narx Neural Networks
Authors: Zongyan Li, Matt Best
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This paper presents an optimization method for reducing the number of input channels and the complexity of the feed-forward NARX neural network (NN) without compromising the accuracy of the NN model. By utilizing the correlation analysis method, the most significant regressors are selected to form the input layer of the NN structure. An application of vehicle dynamic model identification is also presented in this paper to demonstrate the optimization technique and the optimal input layer structure and the optimal number of neurons for the neural network is investigated.Keywords: Correlation analysis, F-ratio, Levenberg-Marquardt, MSE, NARX, neural network, optimisation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21882986 Experimental Investigation and Optimization of Nanoparticle Mass Concentration and Heat Input of Loop Heat Pipe
Authors: P. Gunnasegaran, M. Z. Abdullah, M. Z. Yusoff, Nur Irmawati
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This study presents experimental and optimization of nanoparticle mass concentration and heat input based on the total thermal resistance (Rth) of loop heat pipe (LHP), employed for PCCPU cooling. In this study, silica nanoparticles (SiO2) in water with particle mass concentration ranged from 0% (pure water) to 1% is considered as the working fluid within the LHP. The experimental design and optimization is accomplished by the design of experimental tool, Response Surface Methodology (RSM). The results show that the nanoparticle mass concentration and the heat input have significant effect on the Rth of LHP. For a given heat input, the Rth is found to decrease with the increase of the nanoparticle mass concentration up to 0.5% and increased thereafter. It is also found that the Rth is decreased when the heat input is increased from 20W to 60W. The results are optimized with the objective of minimizing the Rth, using Design-Expert software, and the optimized nanoparticle mass concentration and heat input are 0.48% and 59.97W, respectively, the minimum thermal resistance being 2.66 (ºC/W).Keywords: Loop heat pipe, nanofluid, optimization, thermal resistance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18232985 Design Optimization of Cutting Parameters when Turning Inconel 718 with Cermet Inserts
Authors: M. Aruna, V. Dhanalaksmi
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Inconel 718, a nickel based super-alloy is an extensively used alloy, accounting for about 50% by weight of materials used in an aerospace engine, mainly in the gas turbine compartment. This is owing to their outstanding strength and oxidation resistance at elevated temperatures in excess of 5500 C. Machining is a requisite operation in the aircraft industries for the manufacture of the components especially for gas turbines. This paper is concerned with optimization of the surface roughness when turning Inconel 718 with cermet inserts. Optimization of turning operation is very useful to reduce cost and time for machining. The approach is based on Response Surface Method (RSM). In this work, second-order quadratic models are developed for surface roughness, considering the cutting speed, feed rate and depth of cut as the cutting parameters, using central composite design. The developed models are used to determine the optimum machining parameters. These optimized machining parameters are validated experimentally, and it is observed that the response values are in reasonable agreement with the predicted values.Keywords: Inconel 718, Optimization, Response Surface Methodology (RSM), Surface roughness
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28382984 Non-Sensitive Solutions in Multi-Objective Optimization of a Solar Photovoltaic/Thermal(PV/T) Air Collector
Authors: F. Sarhaddi, S. Farahat, M .A. Alavi, F. Sobhnamayan
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In this paper, an attempt has been made to obtain nonsensitive solutions in the multi-objective optimization of a photovoltaic/thermal (PV/T) air collector. The selected objective functions are overall energy efficiency and exergy efficiency. Improved thermal, electrical and exergy models are used to calculate the thermal and electrical parameters, overall energy efficiency, exergy components and exergy efficiency of a typical PV/T air collector. A computer simulation program is also developed. The results of numerical simulation are in good agreement with the experimental measurements noted in the previous literature. Finally, multi-objective optimization has been carried out under given climatic, operating and design parameters. The optimized ranges of inlet air velocity, duct depth and the objective functions in optimal Pareto front have been obtained. Furthermore, non-sensitive solutions from energy or exergy point of view in the results of multi-objective optimization have been shown.Keywords: Solar photovoltaic thermal (PV/T) air collector, Overall energy efficiency, Exergy efficiency, Multi-objectiveoptimization, Sensitivity analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21572983 Robust Power System Stabilizer Design Using Particle Swarm Optimization Technique
Authors: Sidhartha Panda, N. P. Padhy
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Power system stabilizers (PSS) are now routinely used in the industry to damp out power system oscillations. In this paper, particle swarm optimization (PSO) technique is applied to design a robust power system stabilizer (PSS). The design problem of the proposed controller is formulated as an optimization problem and PSO is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved; stability performance of the system is improved. The non-linear simulation results are presented under wide range of operating conditions; disturbances at different locations as well as for various fault clearing sequences to show the effectiveness and robustness of the proposed controller and their ability to provide efficient damping of low frequency oscillations. Further, all the simulations results are compared with a conventionally designed power system stabilizer to show the superiority of the proposed design approach.
Keywords: Particle swarm optimization, power system stabilizer, low frequency oscillations, power system stability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23582982 Multiparametric Optimization of Water Treatment Process for Thermal Power Plants
Authors: B. Mukanova, N. Glazyrina, S. Glazyrin
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The formulated problem of optimization of the technological process of water treatment for thermal power plants is considered in this article. The problem is of multiparametric nature. To optimize the process, namely, reduce the amount of waste water, a new technology was developed to reuse such water. A mathematical model of the technology of wastewater reuse was developed. Optimization parameters were determined. The model consists of a material balance equation, an equation describing the kinetics of ion exchange for the non-equilibrium case and an equation for the ion exchange isotherm. The material balance equation includes a nonlinear term that depends on the kinetics of ion exchange. A direct problem of calculating the impurity concentration at the outlet of the water treatment plant was numerically solved. The direct problem was approximated by an implicit point-to-point computation difference scheme. The inverse problem was formulated as relates to determination of the parameters of the mathematical model of the water treatment plant operating in non-equilibrium conditions. The formulated inverse problem was solved. Following the results of calculation the time of start of the filter regeneration process was determined, as well as the period of regeneration process and the amount of regeneration and wash water. Multi-parameter optimization of water treatment process for thermal power plants allowed decreasing the amount of wastewater by 15%.
Keywords: Direct problem, multiparametric optimization, optimization parameters, water treatment.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21372981 Multi-Objective Random Drift Particle Swarm Optimization Algorithm Based on RDPSO and Crowding Distance Sorting
Authors: Yiqiong Yuan, Jun Sun, Dongmei Zhou, Jianan Sun
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In this paper, we presented a Multi-Objective Random Drift Particle Swarm Optimization algorithm (MORDPSO-CD) based on RDPSO and crowding distance sorting to improve the convergence and distribution with less computation cost. MORDPSO-CD makes the most of RDPSO to approach the true Pareto optimal solutions fast. We adopt the crowding distance sorting technique to update and maintain the archived optimal solutions. Introducing the crowding distance technique into MORDPSO can make the leader particles find the true Pareto solution ultimately. The simulation results reveal that the proposed algorithm has better convergence and distribution.Keywords: Multi-objective optimization, random drift particle swarm optimization, crowding distance, Pareto optimal solution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14702980 Optimization Parameters of Rotary Positioner Controller using CDM
Authors: Meemongkol A., Tipsuwanporn V., Numsomran A.
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The authors present optimization parameters of rotary positioner controller in hard disk drive servo track writing process using coefficient diagram method; CDM. Due to estimation parameters in PI Positioning Control System by expected ratio method cannot meet the required specification of response effectively, we suggest coefficient diagram method for defining controller parameters under the requirement of the system. Finally, the simulation results show that our proposed method can improve the problem in tuning parameter of rotary positioner controller. It is satisfied specification of performance of control system. Furthermore, it is very convenient as a fast adjustment damping ratio as well as a high speed response.Keywords: Optimization Parameters, Rotary Positioner, CDM
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15482979 Influence of Garbage Leachate on Soil Reaction,Salinity and Soil Organic Matter in East of Isfahan
Authors: Ebrahim Panahpour, Ali Gholami, Amir Hossein Davami
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During this day a considerable amount of Leachate is produced with high amounts of organic material and nutrients needed plants. This study has done in order to scrutinize the effect of Leachate compost on the pH, EC and organic matter percentage in the form of statistical Factorial plan through randomizing block design with three main and two minor treatments and also three replications during three six month periods. Major treatments include N: Irrigation with the region-s well water as a control, I: Frequent irrigation with well water and Leachate, C: Mixing Leachate and water well (25 percent leachate + 75 percent ordinary well water) and secondary treatments, include DI: surface drip irrigation and SDI: sub surface drip irrigation. Results of this study indicated significant differences between treatments and also there were mixing up with the control treatment in the reduction of pH, increasing soluble salts and also increasing the organic matter percentage. This increase is proportional to the amount of added Leachate and in the treatment also proportional to higher mixture of frequent treatment. Therefore, since creating an acidic pH increases the ability to absorb some nutrient elements such as phosphorus, iron, zinc, copper and manganese are increased and the other hand, organic materials also improve many physical and chemical properties of soil are used in Leachate trash Consider health issues as refined in the green belts around cities as a liquid fertilizer recommended.
Keywords: Leachate, compost, drip irrigation, liquid fertilizer, soil reaction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22802978 Optimization of Solar Rankine Cycle by Exergy Analysis and Genetic Algorithm
Authors: R. Akbari, M. A. Ehyaei, R. Shahi Shavvon
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Nowadays, solar energy is used for energy purposes such as the use of thermal energy for domestic, industrial and power applications, as well as the conversion of the sunlight into electricity by photovoltaic cells. In this study, the thermodynamic simulation of the solar Rankin cycle with phase change material (paraffin) was first studied. Then energy and exergy analyses were performed. For optimization, a single and multi-objective genetic optimization algorithm to maximize thermal and exergy efficiency was used. The parameters discussed in this paper included the effects of input pressure on turbines, input mass flow to turbines, the surface of converters and collector angles on thermal and exergy efficiency. In the organic Rankin cycle, where solar energy is used as input energy, the fluid selection is considered as a necessary factor to achieve reliable and efficient operation. Therefore, silicon oil is selected for a high-temperature cycle and water for a low-temperature cycle as an operating fluid. The results showed that increasing the mass flow to turbines 1 and 2 would increase thermal efficiency, while it reduces and increases the exergy efficiency in turbines 1 and 2, respectively. Increasing the inlet pressure to the turbine 1 decreases the thermal and exergy efficiency, and increasing the inlet pressure to the turbine 2 increases the thermal efficiency and exergy efficiency. Also, increasing the angle of the collector increased thermal efficiency and exergy. The thermal efficiency of the system was 22.3% which improves to 33.2 and 27.2% in single-objective and multi-objective optimization, respectively. Also, the exergy efficiency of the system was 1.33% which has been improved to 1.719 and 1.529% in single-objective and multi-objective optimization, respectively. These results showed that the thermal and exergy efficiency in a single-objective optimization is greater than the multi-objective optimization.
Keywords: Exergy analysis, Genetic algorithm, Rankine cycle, Single and Multi-objective function.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6302977 Parallel Particle Swarm Optimization Optimized LDI Controller with Lyapunov Stability Criterion for Nonlinear Structural Systems
Authors: P.-W. Tsai, W.-L. Hong, C.-W. Chen, C.-Y. Chen
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In this paper, we present a neural-network (NN) based approach to represent a nonlinear Tagagi-Sugeno (T-S) system. A linear differential inclusion (LDI) state-space representation is utilized to deal with the NN models. Taking advantage of the LDI representation, the stability conditions and controller design are derived for a class of nonlinear structural systems. Moreover, the concept of utilizing the Parallel Particle Swarm Optimization (PPSO) algorithm to solve the common P matrix under the stability criteria is given in this paper.
Keywords: Lyapunov Stability, Parallel Particle Swarm Optimization, Linear Differential Inclusion, Artificial Intelligence.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18652976 Solution of Optimal Reactive Power Flow using Biogeography-Based Optimization
Authors: Aniruddha Bhattacharya, Pranab Kumar Chattopadhyay
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Optimal reactive power flow is an optimization problem with one or more objective of minimizing the active power losses for fixed generation schedule. The control variables are generator bus voltages, transformer tap settings and reactive power output of the compensating devices placed on different bus bars. Biogeography- Based Optimization (BBO) technique has been applied to solve different kinds of optimal reactive power flow problems subject to operational constraints like power balance constraint, line flow and bus voltages limits etc. BBO searches for the global optimum mainly through two steps: Migration and Mutation. In the present work, BBO has been applied to solve the optimal reactive power flow problems on IEEE 30-bus and standard IEEE 57-bus power systems for minimization of active power loss. The superiority of the proposed method has been demonstrated. Considering the quality of the solution obtained, the proposed method seems to be a promising one for solving these problems.Keywords: Active Power Loss, Biogeography-Based Optimization, Migration, Mutation, Optimal Reactive Power Flow.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 42772975 Modeling and Optimization of Process Parameters in PMEDM by Genetic Algorithm
Authors: Farhad Kolahan, Mohammad Bironro
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This paper addresses modeling and optimization of process parameters in powder mixed electrical discharge machining (PMEDM). The process output characteristics include metal removal rate (MRR) and electrode wear rate (EWR). Grain size of Aluminum powder (S), concentration of the powder (C), discharge current (I) pulse on time (T) are chosen as control variables to study the process performance. The experimental results are used to develop the regression models based on second order polynomial equations for the different process characteristics. Then, a genetic algorithm (GA) has been employed to determine optimal process parameters for any desired output values of machining characteristics.
Keywords: Regression modeling, PMEDM, GeneticAlgorithm, Optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14932974 Optimal Planning of Ground Grid Based on Particle Swam Algorithm
Authors: Chun-Yao Lee, Yi-Xing Shen
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This paper presents an application of particle swarm optimization (PSO) to the grounding grid planning which compares to the application of genetic algorithm (GA). Firstly, based on IEEE Std.80, the cost function of the grounding grid and the constraints of ground potential rise, step voltage and touch voltage are constructed for formulating the optimization problem of grounding grid planning. Secondly, GA and PSO algorithms for obtaining optimal solution of grounding grid are developed. Finally, a case of grounding grid planning is shown the superiority and availability of the PSO algorithm and proposal planning results of grounding grid in cost and computational time.Keywords: Genetic algorithm, particle swarm optimization, grounding grid.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20802973 Transform-Domain Rate-Distortion Optimization Accelerator for H.264/AVC Video Encoding
Authors: Mohammed Golam Sarwer, Lai Man Po, Kai Guo, Q.M. Jonathan Wu
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In H.264/AVC video encoding, rate-distortion optimization for mode selection plays a significant role to achieve outstanding performance in compression efficiency and video quality. However, this mode selection process also makes the encoding process extremely complex, especially in the computation of the ratedistortion cost function, which includes the computations of the sum of squared difference (SSD) between the original and reconstructed image blocks and context-based entropy coding of the block. In this paper, a transform-domain rate-distortion optimization accelerator based on fast SSD (FSSD) and VLC-based rate estimation algorithm is proposed. This algorithm could significantly simplify the hardware architecture for the rate-distortion cost computation with only ignorable performance degradation. An efficient hardware structure for implementing the proposed transform-domain rate-distortion optimization accelerator is also proposed. Simulation results demonstrated that the proposed algorithm reduces about 47% of total encoding time with negligible degradation of coding performance. The proposed method can be easily applied to many mobile video application areas such as a digital camera and a DMB (Digital Multimedia Broadcasting) phone.Keywords: Context-adaptive variable length coding (CAVLC), H.264/AVC, rate-distortion optimization (RDO), sum of squareddifference (SSD).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16062972 Aspen Plus Simulation of Saponification of Ethyl Acetate in the Presence of Sodium Hydroxide in a Plug Flow Reactor
Authors: U. P. L. Wijayarathne, K. C. Wasalathilake
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This work presents the modelling and simulation of saponification of ethyl acetate in the presence of sodium hydroxide in a plug flow reactor using Aspen Plus simulation software. Plug flow reactors are widely used in the industry due to the non-mixing property. The use of plug flow reactors becomes significant when there is a need for continuous large scale reaction or fast reaction. Plug flow reactors have a high volumetric unit conversion as the occurrence for side reactions is minimum. In this research Aspen Plus V8.0 has been successfully used to simulate the plug flow reactor. In order to simulate the process as accurately as possible HYSYS Peng- Robinson EOS package was used as the property method. The results obtained from the simulation were verified by the experiment carried out in the EDIBON plug flow reactor module. The correlation coefficient (r2) was 0.98 and it proved that simulation results satisfactorily fit for the experimental model. The developed model can be used as a guide for understanding the reaction kinetics of a plug flow reactor.
Keywords: Aspen Plus, Modelling, Plug Flow Reactor, Simulation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 93962971 Investigation of Monochromatization Light Effect at Molecular/Atomic Level in Electronegative-Electropositive Gas Mixtures Plasma
Authors: L.C. Ciobotaru
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In electronegative-electropositive gas mixtures plasma, at a total pressure varying in the range of ten to hundred Torr, the appearance of a quasi-mochromatization effect of the emitted radiation was reported. This radiation could be the result of the generating mechanisms at molecular level, which is the case of the excimer radiation but also at atomic level. Thus, in the last case, in (Ne+1%Ar/Xe+H2) gas mixtures plasma in a dielectric barrier discharge, this effect, called M-effect, consists in the reduction of the discharge emission spectrum practice at one single, strong spectral line with λ = 585.3 nm. The present paper is concerned with the characteristics comparative investigation of the principal reaction mechanisms involved in the quasi-monochromatization effect existence in the case of the excimer radiation, respectively of the Meffect. Also, the paper points out the role of the metastable electronegative atoms in the appearance of the monochromatization – effect at atomic level.
Keywords: Colombian forces, Direct Harpoon reaction, Monochromatization – effect, Resonant polar three-body reaction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14072970 A Theoretical Analysis for Modeling and Prediction of the Jet Engine Emissions
Authors: Jamal S. Yassin
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This paper is to formulate a mathematical model to predict the amounts of the emissions produced from the combustion process of the gas turbine unit of the jet engine. These emissions have bad impacts on the environment if they are out of standards, which cause real threats to all type of life on the earth. The amounts of the emissions from the gas turbine engine are functions to many operational and design factors. In landing-takeoff (LTO) these amounts are not the same as in taxi or cruise of the plane using jet engines, because of the difference in the activity period during these operating modes. These emissions can be affected by several physical and chemical variables, such as fuel type, fuel to air ratio or equivalence ratio, flame temperature, combustion pressure, in addition to some inlet conditions such as ambient temperature and air humidity. To study the influence of these variables on the amounts of these emissions during the combustion process in the gas turbine unit, a computer program has been developed by using the visual basic 6 software. Here, the analysis of the combustion process is carried out by considering it as a chemical reaction with shifting equilibrium to find the products of the combustion of the octane fuel, at different equivalence ratios, compressor pressure ratios (CPR) and combustion temperatures. The results obtained have shown that there is noticeable influence of the equivalence ratio, CPR, and the combustion temperature on the amounts of the main emissions which are considered pollutants, such as CO, CO2 and NO.
Keywords: Mathematical model, gas turbine unit, equivalence ratio, emissions, shifting equilibrium.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7362969 Solution of Density Dependent Nonlinear Reaction-Diffusion Equation Using Differential Quadrature Method
Authors: Gülnihal Meral
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In this study, the density dependent nonlinear reactiondiffusion equation, which arises in the insect dispersal models, is solved using the combined application of differential quadrature method(DQM) and implicit Euler method. The polynomial based DQM is used to discretize the spatial derivatives of the problem. The resulting time-dependent nonlinear system of ordinary differential equations(ODE-s) is solved by using implicit Euler method. The computations are carried out for a Cauchy problem defined by a onedimensional density dependent nonlinear reaction-diffusion equation which has an exact solution. The DQM solution is found to be in a very good agreement with the exact solution in terms of maximum absolute error. The DQM solution exhibits superior accuracy at large time levels tending to steady-state. Furthermore, using an implicit method in the solution procedure leads to stable solutions and larger time steps could be used.Keywords: Density Dependent Nonlinear Reaction-Diffusion Equation, Differential Quadrature Method, Implicit Euler Method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22732968 A Theory in Optimization of Ad-hoc Routing Algorithms
Authors: M. Kargar, F.Fartash, T. Saderi, M. Ebrahimi Dishabi
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In this paper optimization of routing in ad-hoc networks is surveyed and a new method for reducing the complexity of routing algorithms is suggested. Using binary matrices for each node in the network and updating it once the routing is done, helps nodes to stop repeating the routing protocols in each data transfer. The algorithm suggested can reduce the complexity of routing to the least amount possible.Keywords: Ad-hoc Networks, Algorithm, Protocol, RoutingTrain.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16722967 Multiple Input Multiple Output Detection Using Roulette Wheel Based Ant Colony Optimization Technique
Authors: B. Rebekka, B. Malarkodi
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This paper describes an approach to detect the transmitted signals for 2×2 Multiple Input Multiple Output (MIMO) setup using roulette wheel based ant colony optimization technique. The results obtained are compared with classical zero forcing and least mean square techniques. The detection rates achieved using this technique are consistently larger than the one achieved using classical methods for 50 number of attempts with two different antennas transmitting the input stream from a user. This paves the path to use alternative techniques to improve the throughput achieved in advanced networks like Long Term Evolution (LTE) networks.Keywords: MIMO, ant colony optimization, roulette wheel, soft computing, LTE.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10772966 Contaminated Soil Remediation with Hydrogen Peroxide Oxidation
Authors: A. Goi, M. Trapido, N. Kulik
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The hydrogen peroxide treatment was able to remediate chlorophenols, polycyclic aromatic hydrocarbons, diesel and transformer oil contaminated soil. Chemical treatment of contaminants adsorbed in peat resulted in lower contaminants- removal and required higher addition of chemicals than the treatment of contaminants in sand. The hydrogen peroxide treatment was found to be feasible for soil remediation at natural soil pH. Contaminants in soil could degrade with the addition of hydrogen peroxide only indicating the ability of transition metals ions and minerals of these metals presented in soil to catalyse the reaction of hydrogen peroxide decomposition.Keywords: Hydrogen peroxide, oxidation, soil treatment, decontamination.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 43922965 Crashworthiness Optimization of an Automotive Front Bumper in Composite Material
Authors: S. Boria
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In the last years, the crashworthiness of an automotive body structure can be improved, since the beginning of the design stage, thanks to the development of specific optimization tools. It is well known how the finite element codes can help the designer to investigate the crashing performance of structures under dynamic impact. Therefore, by coupling nonlinear mathematical programming procedure and statistical techniques with FE simulations, it is possible to optimize the design with reduced number of analytical evaluations. In engineering applications, many optimization methods which are based on statistical techniques and utilize estimated models, called meta-models, are quickly spreading. A meta-model is an approximation of a detailed simulation model based on a dataset of input, identified by the design of experiments (DOE); the number of simulations needed to build it depends on the number of variables. Among the various types of meta-modeling techniques, Kriging method seems to be excellent in accuracy, robustness and efficiency compared to other ones when applied to crashworthiness optimization. Therefore the application of such meta-model was used in this work, in order to improve the structural optimization of a bumper for a racing car in composite material subjected to frontal impact. The specific energy absorption represents the objective function to maximize and the geometrical parameters subjected to some design constraints are the design variables. LS-DYNA codes were interfaced with LS-OPT tool in order to find the optimized solution, through the use of a domain reduction strategy. With the use of the Kriging meta-model the crashworthiness characteristic of the composite bumper was improved.
Keywords: Composite material, crashworthiness, finite element analysis, optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11292964 Heavy Metal Concentration in Orchard Area, Amphawa District, Samut Songkram Province, Thailand
Authors: Sisuwan Kaseamsawat, Sivapan Choo-In
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A study was conducted in May to July 2013 with the aim of determination of heavy metal concentration in orchard area. 60 samples were collected and analyzed for Cadmium (Cd), Copper (Cu), Lead (Pb), and Zinc (Zn) by Atomic Absorption Spectrophotometer (AAS).
The heavy metal concentrations in sediment of orchards, that use chemical for Cd (1.13 ± 0.26 mg/l), Cu (8.00 ± 1.05 mg/l), Pb (13.16 ± 2.01) and Zn (37.41 ± 3.20 mg/l). The heavy metal concentrations in sediment of the orchards, that do not use chemical for Cd (1.28 ± 0.50 mg/l), Cu (7.60 ± 1.20 mg/l), Pb (29.87 ± 4.88) and Zn (21.79 ± 2.98 mg/l). Statistical analysis between heavy metal in sediment from the orchard, that use chemical and the orchard, that not use chemical were difference statistic significant of 0.5 level of significant for Cd and Pb while no statistically difference for Cu and Zn.
Keywords: Heavy metal, Orchard, Pollution and monitoring, Sediment.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20012963 Harmonic Elimination of Hybrid Multilevel Inverters Using Particle Swarm Optimization
Authors: N. Janjamraj, A. Oonsivilai
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This paper present the harmonic elimination of hybrid multilevel inverters (HMI) which could be increase the number of output voltage level. Total Harmonic Distortion (THD) is one of the most important requirements concerning performance indices. Because of many numbers output levels of HMI, it had numerous unknown variables of eliminate undesired individual harmonic and THD nonlinear equations set. Optimized harmonic stepped waveform (OHSW) is solving switching angles conventional method, but most complicated for solving as added level. The artificial intelligent techniques are deliberation to solve this problem. This paper presents the Particle Swarm Optimization (PSO) technique for solving switching angles to get minimum THD and eliminate undesired individual harmonics of 15-levels hybrid multilevel inverters. Consequently it had many variables and could eliminate numerous harmonics. Both advantages including high level of inverter and Particle Swarm Optimization (PSO) are used as powerful tools for harmonics elimination.Keywords: Multilevel Inverters, Particle Swarms Optimization, Harmonic Elimination.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25202962 Design Optimization of a Compact Quadrupole Electromagnet for CLS 2.0
Authors: Md. Armin Islam, Les Dallin, Mark Boland, W. J. Zhang
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This paper reports a study on the optimal magnetic design of a compact quadrupole electromagnet for the Canadian Light Source (CLS 2.0). The nature of the design is to determine a quadrupole with low relative higher order harmonics and better field quality. The design problem was formulated as an optimization model, in which the objective function is the higher order harmonics (multipole errors) and the variable to be optimized is the material distribution on the pole. The higher order harmonics arose in the quadrupole due to truncating the ideal hyperbola at a certain point to make the pole. In this project, the arisen harmonics have been optimized both transversely and longitudinally by adjusting material on the poles in a controlled way. For optimization, finite element analysis (FEA) has been conducted. A better higher order harmonics amplitudes and field quality have been achieved through the optimization. On the basis of the optimized magnetic design, electrical and cooling calculation has been performed for the magnet.Keywords: Drift, electrical, and cooling calculation, integrated field, higher order harmonics (multipole errors), magnetic field gradient, quadrupole.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8172961 Optimization of Kinematics for Birds and UAVs Using Evolutionary Algorithms
Authors: Mohamed Hamdaoui, Jean-Baptiste Mouret, Stephane Doncieux, Pierre Sagaut
Abstract:
The aim of this work is to present a multi-objective optimization method to find maximum efficiency kinematics for a flapping wing unmanned aerial vehicle. We restrained our study to rectangular wings with the same profile along the span and to harmonic dihedral motion. It is assumed that the birdlike aerial vehicle (whose span and surface area were fixed respectively to 1m and 0.15m2) is in horizontal mechanically balanced motion at fixed speed. We used two flight physics models to describe the vehicle aerodynamic performances, namely DeLaurier-s model, which has been used in many studies dealing with flapping wings, and the model proposed by Dae-Kwan et al. Then, a constrained multi-objective optimization of the propulsive efficiency is performed using a recent evolutionary multi-objective algorithm called є-MOEA. Firstly, we show that feasible solutions (i.e. solutions that fulfil the imposed constraints) can be obtained using Dae-Kwan et al.-s model. Secondly, we highlight that a single objective optimization approach (weighted sum method for example) can also give optimal solutions as good as the multi-objective one which nevertheless offers the advantage of directly generating the set of the best trade-offs. Finally, we show that the DeLaurier-s model does not yield feasible solutions.
Keywords: Flight physics, evolutionary algorithm, optimization, Pareto surface.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16462960 An Optimization Tool-Based Design Strategy Applied to Divide-by-2 Circuits with Unbalanced Loads
Authors: Agord M. Pinto Jr., Yuzo Iano, Leandro T. Manera, Raphael R. N. Souza
Abstract:
This paper describes an optimization tool-based design strategy for a Current Mode Logic CML divide-by-2 circuit. Representing a building block for output frequency generation in a RFID protocol based-frequency synthesizer, the circuit was designed to minimize the power consumption for driving of multiple loads with unbalancing (at transceiver level). Implemented with XFAB XC08 180 nm technology, the circuit was optimized through MunEDA WiCkeD tool at Cadence Virtuoso Analog Design Environment ADE.Keywords: Divide-by-2 circuit, CMOS technology, PLL phase locked-loop, optimization tool, CML current mode logic, RF transceiver.
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