Search results for: optimum parameters
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4340

Search results for: optimum parameters

4160 Identification of an Mechanism Systems by Using the Modified PSO Method

Authors: Chih-Cheng Kao, Hsin- Hua Chu

Abstract:

This paper mainly proposes an efficient modified particle swarm optimization (MPSO) method, to identify a slidercrank mechanism driven by a field-oriented PM synchronous motor. In system identification, we adopt the MPSO method to find parameters of the slider-crank mechanism. This new algorithm is added with “distance" term in the traditional PSO-s fitness function to avoid converging to a local optimum. It is found that the comparisons of numerical simulations and experimental results prove that the MPSO identification method for the slider-crank mechanism is feasible.

Keywords: Slider-crank mechanism, distance, systemidentification, modified particle swarm optimization.

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4159 The Optimum Operating Conditions for the Synthesis of Zeolite from Waste Incineration Fly Ash by Alkali Fusion and Hydrothermal Methods

Authors: Yi-Jie Lin, Jyh-Cherng Chen

Abstract:

The fly ash of waste incineration processes is usually hazardous and the disposal or reuse of waste incineration fly ash is difficult. In this study, the waste incineration fly ash was converted to useful zeolites by the alkali fusion and hydrothermal synthesis method. The influence of different operating conditions (the ratio of Si/Al, the ratio of hydrolysis liquid to solid, and hydrothermal time) was investigated to seek the optimum operating conditions for the synthesis of zeolite from waste incineration fly ash. The results showed that concentrations of heavy metals in the leachate of Toxicity Characteristic Leaching Procedure (TCLP) were all lower than the regulatory limits except lead. The optimum operating conditions for the synthesis of zeolite from waste incineration fly ash by the alkali fusion and hydrothermal synthesis method were Si/Al=40, NaOH/ash=1.5, alkali fusion at 400 oC for 40 min, hydrolysis with Liquid to Solid ratio (L/S)= 200 at 105 oC for 24 h, and hydrothermal synthesis at 105 oC for 24 h. The specific surface area of fly ash could be significantly increased from 8.59 m2/g to 651.51 m2/g (synthesized zeolite). The influence of different operating conditions on the synthesis of zeolite from waste incineration fly ash followed the sequence of Si/Al ratio > hydrothermal time > hydrolysis L/S ratio. The synthesized zeolites can be reused as good adsorbents to control the air or wastewater pollutants. The purpose of fly ash detoxification, reduction and waste recycling/reuse is achieved successfully.

Keywords: Alkali fusion, hydrothermal, fly ash, zeolite.

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4158 Performance Analysis of Adaptive LMS Filter through Regression Analysis using SystemC

Authors: Hyeong-Geon Lee, Jae-Young Park, Suk-ki Lee, Jong-Tae Kim

Abstract:

The LMS adaptive filter has several parameters which can affect their performance. From among these parameters, most papers handle the step size parameter for controlling the performance. In this paper, we approach three parameters: step-size, filter tap-size and filter form. The regression analysis is used for defining the relation between parameters and performance of LMS adaptive filter with using the system level simulation results. The results present that all parameters have performance trends in each own particular form, which can be estimated from equations drawn by regression analysis.

Keywords: System level model, adaptive LMS FIR filter, regression analysis, systemC.

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4157 Effect of Span 60, Labrasol, and Cholesterol on Labisia pumila Loaded Niosomes Quality

Authors: H. Binti Ya’akob, C. Siew Chin, A. Abd Aziz, I. Ware, M. Fauzi Abd Jalil, N. Rashidah Ahmed, R. Sabtu

Abstract:

Labisia pumila (LP) plant extract has the potential to be applied in cosmeceutical products due to its anti-photoaging properties. The main purpose of this study was to improve transdermal delivery of LP by encapsulating LP in niosomes. Niosomes loaded LPs were prepared by coacervation phase separation method using non-ionic surfactant (Span 60), labrasol, and cholesterol. The optimum formula obtained were Span 60, labrasol and cholesterol at the mole ratio of 6:1:4. At the optimum formulation, the niosome obtained significantly improved the quality of transdermal penetration of LP compared to free LP.

Keywords: Labisia pumila, niosomes, transdermal, quality.

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4156 Parameters Extraction for Pseudomorphic HEMTs Using Genetic Algorithms

Authors: Mazhar B. Tayel, Amr H. Yassin

Abstract:

A proposed small-signal model parameters for a pseudomorphic high electron mobility transistor (PHEMT) is presented. Both extrinsic and intrinsic circuit elements of a smallsignal model are determined using genetic algorithm (GA) as a stochastic global search and optimization tool. The parameters extraction of the small-signal model is performed on 200-μm gate width AlGaAs/InGaAs PHEMT. The equivalent circuit elements for a proposed 18 elements model are determined directly from the measured S- parameters. The GA is used to extract the parameters of the proposed small-signal model from 0.5 up to 18 GHz.

Keywords: PHEMT, Genetic Algorithms, small signal modeling, optimization.

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4155 A Study on the Heading of Spur Gears: Numerical Analysis and Experiments

Authors: M.Zadshakouyan, E.Abdi Sobbouhi, H.Jafarzadeh

Abstract:

In this study, the precision heading process of spur gears has been investigated by means of numerical analysis. The effect of some parameters such as teeth number and module on the forming force and material flow were presented. The simulation works were performed rigid-plastic finite element method using DEFORM 3D software. In order to validate the estimated numerical results, they were compared with those obtained experimentally during heading of spur gear using lead as a model material. Results showed that the optimum number of gear teeth is between 10 to 20, that is because of being the specific pressure in its minimum value.

Keywords: Heading, spur gear, numerical analysis, experiments.

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4154 Optimization of the Process of Osmo – Convective Drying of Edible Button Mushrooms using Response Surface Methodology (RSM)

Authors: Behrouz Mosayebi Dehkordi

Abstract:

Simultaneous effects of temperature, immersion time, salt concentration, sucrose concentration, pressure and convective dryer temperature on the combined osmotic dehydration - convective drying of edible button mushrooms were investigated. Experiments were designed according to Central Composite Design with six factors each at five different levels. Response Surface Methodology (RSM) was used to determine the optimum processing conditions that yield maximum water loss and rehydration ratio and minimum solid gain and shrinkage in osmotic-convective drying of edible button mushrooms. Applying surfaces profiler and contour plots optimum operation conditions were found to be temperature of 39 °C, immersion time of 164 min, salt concentration of 14%, sucrose concentration of 53%, pressure of 600 mbar and drying temperature of 40 °C. At these optimum conditions, water loss, solid gain, rehydration ratio and shrinkage were found to be 63.38 (g/100 g initial sample), 3.17 (g/100 g initial sample), 2.26 and 7.15%, respectively.

Keywords: Dehydration, Mushroom, Optimization, Osmotic, Response Surface Methodology

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4153 Optimization the Process of Osmo – Convective Drying of Edible Button Mushrooms using Response Surface Methodology (RSM)

Authors: Behrouz Mosayebi Dehkordi

Abstract:

Simultaneous effects of temperature, immersion time, salt concentration, sucrose concentration, pressure and convective dryer temperature on the combined osmotic dehydration - convective drying of edible button mushrooms were investigated. Experiments were designed according to Central Composite Design with six factors each at five different levels. Response Surface Methodology (RSM) was used to determine the optimum processing conditions that yield maximum water loss and rehydration ratio and minimum solid gain and shrinkage in osmotic-convective drying of edible button mushrooms. Applying surfaces profiler and contour plots optimum operation conditions were found to be temperature of 39 °C, immersion time of 164 min, salt concentration of 14%, sucrose concentration of 53%, pressure of 600 mbar and drying temperature of 40 °C. At these optimum conditions, water loss, solid gain, rehydration ratio and shrinkage were found to be 63.38 (g/100 g initial sample), 3.17 (g/100 g initial sample), 2.26 and 7.15%, respectively.

Keywords: Dehydration, mushroom, optimization, osmotic, response surface methodology.

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4152 Optimum Design of an Absorption Heat Pump Integrated with a Kraft Industry using Genetic Algorithm

Authors: B. Jabbari, N. Tahouni, M. H. Panjeshahi

Abstract:

In this study the integration of an absorption heat pump (AHP) with the concentration section of an industrial pulp and paper process is investigated using pinch technology. The optimum design of the proposed water-lithium bromide AHP is then achieved by minimizing the total annual cost. A comprehensive optimization is carried out by relaxation of all stream pressure drops as well as heat exchanger areas involving in AHP structure. It is shown that by applying genetic algorithm optimizer, the total annual cost of the proposed AHP is decreased by 18% compared to one resulted from simulation.

Keywords: Absorption Heat Pump, Genetic Algorithm, Kraft Industry, Pinch Technology

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4151 Predicting Extrusion Process Parameters Using Neural Networks

Authors: Sachin Man Bajimaya, SangChul Park, Gi-Nam Wang

Abstract:

The objective of this paper is to estimate realistic principal extrusion process parameters by means of artificial neural network. Conventionally, finite element analysis is used to derive process parameters. However, the finite element analysis of the extrusion model does not consider the manufacturing process constraints in its modeling. Therefore, the process parameters obtained through such an analysis remains highly theoretical. Alternatively, process development in industrial extrusion is to a great extent based on trial and error and often involves full-size experiments, which are both expensive and time-consuming. The artificial neural network-based estimation of the extrusion process parameters prior to plant execution helps to make the actual extrusion operation more efficient because more realistic parameters may be obtained. And so, it bridges the gap between simulation and real manufacturing execution system. In this work, a suitable neural network is designed which is trained using an appropriate learning algorithm. The network so trained is used to predict the manufacturing process parameters.

Keywords: Artificial Neural Network (ANN), Indirect Extrusion, Finite Element Analysis, MES.

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4150 Optimization Parameters of Rotary Positioner Controller using CDM

Authors: Meemongkol A., Tipsuwanporn V., Numsomran A.

Abstract:

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

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4149 Structural Damage Detection Using Sensors Optimally Located

Authors: Carlos Alberto Riveros, Edwin Fabián García, Javier Enrique Rivero

Abstract:

The measured data obtained from sensors in continuous monitoring of civil structures are mainly used for modal identification and damage detection. Therefore, when modal identification analysis is carried out the quality in the identification of the modes will highly influence the damage detection results. It is also widely recognized that the usefulness of the measured data used for modal identification and damage detection is significantly influenced by the number and locations of sensors. The objective of this study is the numerical implementation of two widely known optimum sensor placement methods in beam-like structures.

Keywords: Optimum sensor placement, structural damage detection, modal identification, beam-like structures.

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4148 A Methodology for Reducing the BGP Convergence Time

Authors: Eatedal A. Alabdulkreem, Hamed S. Al-Raweshidy, Maysam F. Abbod

Abstract:

Border Gateway Protocol (BGP) is the standard routing protocol between various autonomous systems (AS) in the internet. In the event of failure, a considerable delay in the BGP convergence has been shown by empirical measurements. During the convergence time the BGP will repeatedly advertise new routes to some destination and withdraw old ones until it reach a stable state. It has been found that the KEEPALIVE message timer and the HOLD time are tow parameters affecting the convergence speed. This paper aims to find the optimum value for the KEEPALIVE timer and the HOLD time that maximally reduces the convergence time without increasing the traffic. The KEEPALIVE message timer optimal value founded by this paper is 30 second instead of 60 seconds, and the optimal value for the HOLD time is 90 seconds instead of 180 seconds.

Keywords: BGP, Convergence Time, HOLD time, Keep alive.

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4147 A Method for Identifying Physical Parameters with Linear Fractional Transformation

Authors: Ryosuke Ito, Goro Obinata, Chikara Nagai, Youngwoo Kim

Abstract:

This paper proposes a new parameter identification method based on Linear Fractional Transformation (LFT). It is assumed that the target linear system includes unknown parameters. The parameter deviations are separated from a nominal system via LFT, and identified by organizing I/O signals around the separated deviations of the real system. The purpose of this paper is to apply LFT to simultaneously identify the parameter deviations in systems with fewer outputs than unknown parameters. As a fundamental example, this method is implemented to one degree of freedom vibratory system. Via LFT, all physical parameters were simultaneously identified in this system. Then, numerical simulations were conducted for this system to verify the results. This study shows that all the physical parameters of a system with fewer outputs than unknown parameters can be effectively identified simultaneously using LFT.

Keywords: Identification, Linear Fractional Transformation, Right inverse system

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4146 A Statistical Approach for Predicting and Optimizing Depth of Cut in AWJ Machining for 6063-T6 Al Alloy

Authors: Farhad Kolahan, A. Hamid Khajavi

Abstract:

In this paper, a set of experimental data has been used to assess the influence of abrasive water jet (AWJ) process parameters in cutting 6063-T6 aluminum alloy. The process variables considered here include nozzle diameter, jet traverse rate, jet pressure and abrasive flow rate. The effects of these input parameters are studied on depth of cut (h); one of most important characteristics of AWJ. The Taguchi method and regression modeling are used in order to establish the relationships between input and output parameters. The adequacy of the model is evaluated using analysis of variance (ANOVA) technique. In the next stage, the proposed model is embedded into a Simulated Annealing (SA) algorithm to optimize the AWJ process parameters. The objective is to determine a suitable set of process parameters that can produce a desired depth of cut, considering the ranges of the process parameters. Computational results prove the effectiveness of the proposed model and optimization procedure.

Keywords: AWJ machining, Mathematical modeling, Simulated Annealing, Optimization

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4145 Matrix-Based Linear Analysis of Switched Reluctance Generator with Optimum Pole Angles Determination

Authors: Walid A. M. Ghoneim, Hamdy A. Ashour, Asmaa E. Abdo

Abstract:

In this paper, linear analysis of a Switched Reluctance Generator (SRG) model is applied on the most common configurations (4/2, 6/4 and 8/6) for both conventional short-pitched and fully-pitched designs, in order to determine the optimum stator/rotor pole angles at which the maximum output voltage is generated per unit excitation current. This study is focused on SRG analysis and design as a proposed solution for renewable energy applications, such as wind energy conversion systems. The world’s potential to develop the renewable energy technologies through dedicated scientific researches was the motive behind this study due to its positive impact on economy and environment. In addition, the problem of rare earth metals (Permanent magnet) caused by mining limitations, banned export by top producers and environment restrictions leads to the unavailability of materials used for rotating machines manufacturing. This challenge gave authors the opportunity to study, analyze and determine the optimum design of the SRG that has the benefit to be free from permanent magnets, rotor windings, with flexible control system and compatible with any application that requires variable-speed operation. In addition, SRG has been proved to be very efficient and reliable in both low-speed or high-speed applications. Linear analysis was performed using MATLAB simulations based on the (Modified generalized matrix approach) of Switched Reluctance Machine (SRM). About 90 different pole angles combinations and excitation patterns were simulated through this study, and the optimum output results for each case were recorded and presented in detail. This procedure has been proved to be applicable for any SRG configuration, dimension and excitation pattern. The delivered results of this study provide evidence for using the 4-phase 8/6 fully pitched SRG as the main optimum configuration for the same machine dimensions at the same angular speed.

Keywords: Generalized matrix approach, linear analysis, renewable applications, switched reluctance generator, SRG.

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4144 The Influence of Preprocessing Parameters on Text Categorization

Authors: Jan Pomikalek, Radim Rehurek

Abstract:

Text categorization (the assignment of texts in natural language into predefined categories) is an important and extensively studied problem in Machine Learning. Currently, popular techniques developed to deal with this task include many preprocessing and learning algorithms, many of which in turn require tuning nontrivial internal parameters. Although partial studies are available, many authors fail to report values of the parameters they use in their experiments, or reasons why these values were used instead of others. The goal of this work then is to create a more thorough comparison of preprocessing parameters and their mutual influence, and report interesting observations and results.

Keywords: Text categorization, machine learning, electronic documents, classification.

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4143 Statistical Optimization of Adsorption of a Harmful Dye from Aqueous Solution

Authors: M. Arun, A. Kannan

Abstract:

Textile industries cater to varied customer preferences and contribute substantially to the economy. However, these textile industries also produce a considerable amount of effluents. Prominent among these are the azo dyes which impart considerable color and toxicity even at low concentrations. Azo dyes are also used as coloring agents in food and pharmaceutical industry. Despite their applications, azo dyes are also notorious pollutants and carcinogens. Popular techniques like photo-degradation, biodegradation and the use of oxidizing agents are not applicable for all kinds of dyes, as most of them are stable to these techniques. Chemical coagulation produces a large amount of toxic sludge which is undesirable and is also ineffective towards a number of dyes. Most of the azo dyes are stable to UV-visible light irradiation and may even resist aerobic degradation. Adsorption has been the most preferred technique owing to its less cost, high capacity and process efficiency and the possibility of regenerating and recycling the adsorbent. Adsorption is also most preferred because it may produce high quality of the treated effluent and it is able to remove different kinds of dyes. However, the adsorption process is influenced by many variables whose inter-dependence makes it difficult to identify optimum conditions. The variables include stirring speed, temperature, initial concentration and adsorbent dosage. Further, the internal diffusional resistance inside the adsorbent particle leads to slow uptake of the solute within the adsorbent. Hence, it is necessary to identify optimum conditions that lead to high capacity and uptake rate of these pollutants. In this work, commercially available activated carbon was chosen as the adsorbent owing to its high surface area. A typical azo dye found in textile effluent waters, viz. the monoazo Acid Orange 10 dye (CAS: 1936-15-8) has been chosen as the representative pollutant. Adsorption studies were mainly focused at obtaining equilibrium and kinetic data for the batch adsorption process at different process conditions. Studies were conducted at different stirring speed, temperature, adsorbent dosage and initial dye concentration settings. The Full Factorial Design was the chosen statistical design framework for carrying out the experiments and identifying the important factors and their interactions. The optimum conditions identified from the experimental model were validated with actual experiments at the recommended settings. The equilibrium and kinetic data obtained were fitted to different models and the model parameters were estimated. This gives more details about the nature of adsorption taking place. Critical data required to design batch adsorption systems for removal of Acid Orange 10 dye and identification of factors that critically influence the separation efficiency are the key outcomes from this research.

Keywords: Acid Orange 10, Activated carbon, Optimum conditions, Statistical design.

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4142 The Multi-objective Optimization for the SLS Process Parameters Based on Analytic Hierarchy Process

Authors: Yang Laixia, Deng Jun, Li Dichen, Bai Yang

Abstract:

The forming process parameters of Selective Laser Sintering(SLS) directly affect the forming efficiency and forming quality. Therefore, to determine reasonable process parameters is particularly important. In this paper, the weight of each target of the forming quality and efficiency is firstly calculated with the Analytic Hierarchy Process. And then the size of each target is measured by orthogonal experiment. Finally, the sum of the product of each target with the weight is compared to the process parameters in each group and obtained the optimal molding process parameters.

Keywords: Analytic Hierarchy Process, Multi-objective optimization, Orthogonal test, Selective Laser Sintering

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4141 Optimization of Process Parameters for Diesters Biolubricant using D-optimal Design

Authors: Bashar Mudhaffar Abdullah, Jumat Salimon

Abstract:

Optimization study of the diesters biolubricant oleyl 9(12)-hydroxy-10(13)-oleioxy-12(9)-octadecanoate (OLHYOOT) was synthesized in the presence of sulfuric acid (SA) as catalyst has been done. Optimum conditions of the experiment to obtain high yield% of OLHYOOT were predicted at ratio of OL/HYOOA of 1:1 g/g, ratio of SA/HYOOA of 0.20:1 g/g, reaction temperature 110 °C and 4.5 h of reaction time. At this condition, the Yield% of OLHYOOT was 88.7. Disappearance of carboxylic acid (C=O) peak has observed by FTIR with appearance ester (C=O) at 1738 cm-1. 1H NMR spectra analyses confirmed the result of OLHYOOT with appearance ester (-CHOCOR) at 4.05ppm and also the 13C-NMR confirmed the result with appearance ester (C=O) peak at 173.93ppm.

Keywords: Esterification, Diesters, Biolubricant, D-optimaldesign.

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4140 Perturbed-Chain Statistical Association Fluid Theory (PC-SAFT) Parameters for Propane, Ethylene, and Hydrogen under Supercritical Conditions

Authors: Ilke Senol

Abstract:

Perturbed-Chain Statistical Association Fluid Theory (PC-SAFT) equation of state (EOS) is a modified SAFT EOS with three pure component specific parameters: segment number (m), diameter (σ) and energy (ε). These PC-SAFT parameters need to be determined for each component under the conditions of interest by fitting experimental data, such as vapor pressure, density or heat capacity. PC-SAFT parameters for propane, ethylene and hydrogen in supercritical region were successfully estimated by fitting experimental density data available in literature. The regressed PCSAFT parameters were compared with the literature values by means of estimating pure component density and calculating average absolute deviation between the estimated and experimental density values. PC-SAFT parameters available in literature especially for ethylene and hydrogen estimated density in supercritical region reasonably well. However, the regressed PC-SAFT parameters performed better in supercritical region than the PC-SAFT parameters from literature.

Keywords: Equation of state, perturbed-chain, PC-SAFT, super critical.

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4139 Optimization of End Milling Process Parameters for Minimization of Surface Roughness of AISI D2 Steel

Authors: Pankaj Chandna, Dinesh Kumar

Abstract:

The present work analyses different parameters of end milling to minimize the surface roughness for AISI D2 steel. D2 Steel is generally used for stamping or forming dies, punches, forming rolls, knives, slitters, shear blades, tools, scrap choppers, tyre shredders etc. Surface roughness is one of the main indices that determines the quality of machined products and is influenced by various cutting parameters. In machining operations, achieving desired surface quality by optimization of machining parameters, is a challenging job. In case of mating components the surface roughness become more essential and is influenced by the cutting parameters, because, these quality structures are highly correlated and are expected to be influenced directly or indirectly by the direct effect of process parameters or their interactive effects (i.e. on process environment). In this work, the effects of selected process parameters on surface roughness and subsequent setting of parameters with the levels have been accomplished by Taguchi’s parameter design approach. The experiments have been performed as per the combination of levels of different process parameters suggested by L9 orthogonal array. Experimental investigation of the end milling of AISI D2 steel with carbide tool by varying feed, speed and depth of cut and the surface roughness has been measured using surface roughness tester. Analyses of variance have been performed for mean and signal-to-noise ratio to estimate the contribution of the different process parameters on the process.

Keywords: D2 Steel, Orthogonal Array, Optimization, Surface Roughness, Taguchi Methodology.

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4138 Process Parameter Optimization for the Production of Gentamicin using Micromonouspora Echiniospora

Authors: M.Rajasimman, S.Subathra

Abstract:

The process parameters, temperature, pH and substrate concentration, were optimized for the production of gentamicin using Micromonouspora echinospora. Experiments were carried out according to central composite design in response surface method. The optimum conditions for the maximum production of gentamicin were found to be: temperature – 31.7oC, pH – 6.8 and substrate concentration – 3%. At these optimized conditions the production of gentamicin was found to be – 1040 mg/L. The R2 value of 0.9465 indicates a good fitness of the model.

Keywords: Gentamicin, Micromonouspora echinospora, response surface method, optimization, central composite design.

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4137 Experimental Design and Performance Analysis in Plasma Arc Surface Hardening

Authors: M.I.S. Ismail, Z. Taha

Abstract:

In this paper, the experimental design of using the Taguchi method is employed to optimize the processing parameters in the plasma arc surface hardening process. The processing parameters evaluated are arc current, scanning velocity and carbon content of steel. In addition, other significant effects such as the relation between processing parameters are also investigated. An orthogonal array, signal-to-noise (S/N) ratio and analysis of variance (ANOVA) are employed to investigate the effects of these processing parameters. Through this study, not only the hardened depth increased and surface roughness improved, but also the parameters that significantly affect the hardening performance are identified. Experimental results are provided to verify the effectiveness of this approach.

Keywords: Plasma arc, hardened depth, surface roughness, Taguchi method, optimization.

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4136 Evaluation of Optimum Performance of Lateral Intakes

Authors: Mohammad Reza Pirestani, Hamid Reza Vosoghifar, Pegah Jazayeri

Abstract:

In designing river intakes and diversion structures, it is paramount that the sediments entering the intake are minimized or, if possible, completely separated. Due to high water velocity, sediments can significantly damage hydraulic structures especially when mechanical equipment like pumps and turbines are used. This subsequently results in wasting water, electricity and further costs. Therefore, it is prudent to investigate and analyze the performance of lateral intakes affected by sediment control structures. Laboratory experiments, despite their vast potential and benefits, can face certain limitations and challenges. Some of these include: limitations in equipment and facilities, space constraints, equipment errors including lack of adequate precision or mal-operation, and finally, human error. Research has shown that in order to achieve the ultimate goal of intake structure design – which is to design longlasting and proficient structures – the best combination of sediment control structures (such as sill and submerged vanes) along with parameters that increase their performance (such as diversion angle and location) should be determined. Cost, difficulty of execution and environmental impacts should also be included in evaluating the optimal design. This solution can then be applied to similar problems in the future. Subsequently, the model used to arrive at the optimal design requires high level of accuracy and precision in order to avoid improper design and execution of projects. Process of creating and executing the design should be as comprehensive and applicable as possible. Therefore, it is important that influential parameters and vital criteria is fully understood and applied at all stages of choosing the optimal design. In this article, influential parameters on optimal performance of the intake, advantages and disadvantages, and efficiency of a given design are studied. Then, a multi-criterion decision matrix is utilized to choose the optimal model that can be used to determine the proper parameters in constructing the intake.

Keywords: Diversion structures lateral intake, multi criteria decision making, optimal design, sediment control.

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4135 Physicochemical Parameters of Tap Water in Dhahran, Saudi Arabia: An Empirical Assessment

Authors: Ahmed A. Hassan, Bassam Tawabini

Abstract:

In this study, the physicochemical parameters of Dhahran tap water were assessed to determine its suitability for drinking purposes. A total of 45 water samples were collected from different locations. The results indicate temperature ranges of 19.76 to 22.86 °C, pH (6.5 to 8.23), dissolved oxygen (4.21 to 8.32 mg/L), conductivity (232 to 2586 uS/cm), turbidity (0.17 to 0.37 Nephelometric Turbidity unit (NTU)), total dissolved solids (93 to 1671 mg/L), total alkalinity (4.11 to 24.04 mg/L), calcium (0.02 to 164 mg/L), magnesium (0 .6 to 77.9 mg/L), chloride (32.7 to 568.7 mg/L), nitrate (0.02 to 3 mg/L), fluoride (0.001 to 0.591 mg/L), sodium (18.4 to 232 mg/L), potassium (0.5 to 26.4 mg/L), and sulphate (2.39 to 258 mg/L). The results were compared with the drinking water standards recommended by the World Health Organization (WHO) and the United States Environmental Protection Agency (USEPA). The study determined that though the levels of most of the physicochemical parameters comply with the standards, however, slight deviations exist. This is evident in the values of the physical parameters (conductivity and total dissolved solids), and the chemical parameters (sulphate, chloride, and sodium) recorded at a few sample sites.

Keywords: Physicochemical parameters, tap water, water quality, Dhahran.

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4134 Composite Programming for Electric Passenger Car Selection in Multiple Criteria Decision Making

Authors: C. Ardil

Abstract:

This paper discusses the use of the composite programming method to identify the optimum electric passenger automobile in multiple criteria decision making. With the composite programming approach, a set of alternatives are compared using an optimality measure that gauges how far apart they are from the optimum solution. In this paper, some key factors (range, battery, engine, maximum speed, acceleration) that customers should consider while purchasing an electric passenger car for daily use are discussed. A numerical illustration is provided to demonstrate the validity and applicability of the proximity measure approach

Keywords: electric passenger car selection, multiple criteria decision making, proximity measure method, composite programming, entropic weight method

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4133 Simultaneous Optimization of Machining Parameters and Tool Geometry Specifications in Turning Operation of AISI1045 Steel

Authors: Farhad Kolahan, Mohsen Manoochehri, Abbas Hosseini

Abstract:

Machining is an important manufacturing process used to produce a wide variety of metallic parts. Among various machining processes, turning is one of the most important one which is employed to shape cylindrical parts. In turning, the quality of finished product is measured in terms of surface roughness. In turn, surface quality is determined by machining parameters and tool geometry specifications. The main objective of this study is to simultaneously model and optimize machining parameters and tool geometry in order to improve the surface roughness for AISI1045 steel. Several levels of machining parameters and tool geometry specifications are considered as input parameters. The surface roughness is selected as process output measure of performance. A Taguchi approach is employed to gather experimental data. Then, based on signal-to-noise (S/N) ratio, the best sets of cutting parameters and tool geometry specifications have been determined. Using these parameters values, the surface roughness of AISI1045 steel parts may be minimized. Experimental results are provided to illustrate the effectiveness of the proposed approach.

Keywords: Taguchi method, turning parameters, tool geometry specifications, S/N ratio, statistical analysis.

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4132 The Hardware Implementation of a Novel Genetic Algorithm

Authors: Zhenhuan Zhu, David Mulvaney, Vassilios Chouliaras

Abstract:

This paper presents a novel genetic algorithm, termed the Optimum Individual Monogenetic Algorithm (OIMGA) and describes its hardware implementation. As the monogenetic strategy retains only the optimum individual, the memory requirement is dramatically reduced and no crossover circuitry is needed, thereby ensuring the requisite silicon area is kept to a minimum. Consequently, depending on application requirements, OIMGA allows the investigation of solutions that warrant either larger GA populations or individuals of greater length. The results given in this paper demonstrate that both the performance of OIMGA and its convergence time are superior to those of existing hardware GA implementations. Local convergence is achieved in OIMGA by retaining elite individuals, while population diversity is ensured by continually searching for the best individuals in fresh regions of the search space.

Keywords: Genetic algorithms, hardware-based machinelearning.

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4131 Calculation of the Ceramics Weibull Parameters

Authors: V. Fuis, T. Navrat

Abstract:

The paper deals with calculation of the parameters of ceramic material from a set of destruction tests of ceramic heads of total hip joint endoprosthesis. The standard way of calculation of the material parameters consists in carrying out a set of 3 or 4 point bending tests of specimens cut out from parts of the ceramic material to be analysed. In case of ceramic heads, it is not possible to cut out specimens of required dimensions because the heads are too small (if the cut out specimens were smaller than the normalised ones, the material parameters derived from them would exhibit higher strength values than those which the given ceramic material really has). On that score, a special testing jig was made, in which 40 heads were destructed. From the measured values of circumferential strains of the head-s external spherical surface under destruction, the state of stress in the head under destruction was established using the final elements method (FEM). From the values obtained, the sought for parameters of the ceramic material were calculated using Weibull-s weakest-link theory.

Keywords: Hip joint endoprosthesis, ceramic head, FEM analysis, Weibull's weakest-link theory, failure probability, material parameters

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