Search results for: climatic parameters
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3846

Search results for: climatic parameters

3606 Alternative Robust Estimators for the Shape Parameters of the Burr XII Distribution

Authors: F. Z. Doğru, O. Arslan

Abstract:

In general, classical methods such as maximum likelihood (ML) and least squares (LS) estimation methods are used to estimate the shape parameters of the Burr XII distribution. However, these estimators are very sensitive to the outliers. To overcome this problem we propose alternative robust estimators based on the M-estimation method for the shape parameters of the Burr XII distribution. We provide a small simulation study and a real data example to illustrate the performance of the proposed estimators over the ML and the LS estimators. The simulation results show that the proposed robust estimators generally outperform the classical estimators in terms of bias and root mean square errors when there are outliers in data.

Keywords: Burr XII distribution, robust estimator, M-estimator, maximum likelihood, least squares.

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3605 Estimating Regression Effects in Com Poisson Generalized Linear Model

Authors: Vandna Jowaheer, Naushad A. Mamode Khan

Abstract:

Com Poisson distribution is capable of modeling the count responses irrespective of their mean variance relation and the parameters of this distribution when fitted to a simple cross sectional data can be efficiently estimated using maximum likelihood (ML) method. In the regression setup, however, ML estimation of the parameters of the Com Poisson based generalized linear model is computationally intensive. In this paper, we propose to use quasilikelihood (QL) approach to estimate the effect of the covariates on the Com Poisson counts and investigate the performance of this method with respect to the ML method. QL estimates are consistent and almost as efficient as ML estimates. The simulation studies show that the efficiency loss in the estimation of all the parameters using QL approach as compared to ML approach is quite negligible, whereas QL approach is lesser involving than ML approach.

Keywords: Com Poisson, Cross-sectional, Maximum Likelihood, Quasi likelihood

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3604 Optimization of Surface Roughness and Vibration in Turning of Aluminum Alloy AA2024 Using Taguchi Technique

Authors: Vladimir Aleksandrovich Rogov, Ghorbani Siamak

Abstract:

Determination of optimal conditions of machining parameters is important to reduce the production cost and achieve the desired surface quality. This paper investigates the influence of cutting parameters on surface roughness and natural frequency in turning of aluminum alloy AA2024. The experiments were performed at the lathe machine using two different cutting tools made of AISI 5140 and carbide cutting insert coated with TiC. Turning experiments were planned by Taguchi method L9 orthogonal array.Three levels for spindle speed, feed rate, depth of cut and tool overhang were chosen as cutting variables. The obtained experimental data has been analyzed using signal to noise ratio and analysis of variance. The main effects have been discussed and percentage contributions of various parameters affecting surface roughness and natural frequency, and optimal cutting conditions have been determined. Finally, optimization of the cutting parameters using Taguchi method was verified by confirmation experiments.

Keywords: Turning, Cutting conditions, Surface roughness, Natural frequency, Taguchi method, ANOVA, S/N ratio.

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3603 Optimum Design of Launching Nose during Incremental Launching Construction of Same-Span Continuous Bridge

Authors: Weifeng Wang, Hengbin Zheng, Xianwei Zeng

Abstract:

The launching nose plays an important role in the incremental launching construction. The parameters of the launching nose essentially affect the internal forces of the girder during the construction. The appropriate parameters can decrease the internal forces in the girder and save the material and reduce the cost. The simplified structural model, which is made with displacement method according to the characteristic of incremental launching construction and the variation rule of the internal forces, calculates and analyzes the effect of the length, the rigidity and weight of launch nose on the internal forces of girder during the incremental launching construction. The method, which can calculate the launching nose parameters for the optimum incremental launching construction, is achieved. This method is simple, reliable and easy for practical use.

Keywords: incremental launching, launching nose, optimumanalysis, displacement method

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3602 The Magnetic Susceptibility of the Late Quaternary Loess in North-East of Iran and Its Correlation with Other Palaeoclimatical Parameters

Authors: Fereshteh M. Haskouei, Habib Alimohammadian

Abstract:

Magnetic susceptibility (χ) is operational to identify of late quaternary glacial-interglacial cycles in loess-paleosol sequences. It is well accepted that many loess-paleosol sequences bear witness to cold-dry/warm-humid periods, well known as glacial-interglacial cycles, respectively. For this study, loess-paleosol sequence of north-east of Iran was magnetically investigated. The study area is situated at about 8 km away of Neka city, on the main road of Sari-Behshahr, in Mazandaran Province, north of Iran. The youngest deposits of study area are the late Quaternary wind-blown accumulations. In this study, the total number of 117 samples was collected from loess-paleosols units. After that, the natural remnant magnetization (NRM) and magnetic susceptibility (MS) of the samples were measured. Variation of MS of more than 110 loess samples was plotted to reveal the correlation of the MS and paleoclimatic changes. This study aims reconstruction of climatic changes (glacial-interglacial and stadials-interstadials cycles). To confirm our results we compared MS (χ) and the curves of other investigations in paleoclimatology. This correspondence abled us to recognize worldly events in the study area such as: Younger Dryas, the Last Glacial Maximum (LGM), deglaciation of Northern Hemisphere etc. The obtained magnetic data indicate that during almost 50 ka, at least two glacial-interglacial periods occurred in north-east of Iran. Further, variation of χ values revealed short period of climatically cycles known as stadials-interstadials. We recognized 4 stadials and a single stadial as colder sub-periods for S0 (recently soil-paleosol) and S2 (lower paleosol), respectively, Moreover, we recognized 6 warmer sub-periods (interstadials) for L1 (upper loess) and one interstadial L2 (lower loess).

Keywords: Glacial-interglacial cycles, Iran, last glacial maximum, loess, magnetic susceptibility (χ), Neka, Stadials-Interstadials sub-periods, younger dryas.

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3601 Photocatalytic Detoxification Method for Zero Effluent Discharge in Dairy Industry: Effect of Operational Parameters

Authors: Janhavi Inamdar, S.K. Singh

Abstract:

Laboratory experiments have been performed to investigate photocatalytic detoxification by using TiO2 photocatalyst for treating dairy effluent. Various operational parameters such as catalyst concentration, initial concentration, angle of tilt of solar flat plate reactor and flow rate were investigated. Results indicated that the photocatalytic detoxification process can efficiently treat dairy effluent. Experimental runs with dairy wastewater can be used to identify the optimum operational parameters to perform wastewater degradation on large scale for recycling purpose. Also effect of two different types of reactors on degradation process was analyzed.

Keywords: Photocatalytic detoxification, TiO2 photocatalyst, solar flat plate reactor, Zero effluent discharge.

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3600 Analysis of Trend and Variability of Rainfall in the Mid-Mahanadi River Basin of Eastern India

Authors: Rabindra K. Panda, Gurjeet Singh

Abstract:

The major objective of this study was to analyze the trend and variability of rainfall in the middle Mahandi river basin located in eastern India. The trend of variation of extreme rainfall events has predominant effect on agricultural water management and extreme hydrological events such as floods and droughts. Mahanadi river basin is one of the major river basins of India having an area of 1,41,589 km2 and divided into three regions: Upper, middle and delta region. The middle region of Mahanadi river basin has an area of 48,700 km2 and it is mostly dominated by agricultural land, where agriculture is mostly rainfed. The study region has five Agro-climatic zones namely: East and South Eastern Coastal Plain, North Eastern Ghat, Western Undulating Zone, Western Central Table Land and Mid Central Table Land, which were numbered as zones 1 to 5 respectively for convenience in reporting. In the present study, analysis of variability and trends of annual, seasonal, and monthly rainfall was carried out, using the daily rainfall data collected from the Indian Meteorological Department (IMD) for 35 years (1979-2013) for the 5 agro-climatic zones. The long term variability of rainfall was investigated by evaluating the mean, standard deviation and coefficient of variation. The long term trend of rainfall was analyzed using the Mann-Kendall test on monthly, seasonal and annual time scales. It was found that there is a decreasing trend in the rainfall during the winter and pre monsoon seasons for zones 2, 3 and 4; whereas in the monsoon (rainy) season there is an increasing trend for zones 1, 4 and 5 with a level of significance ranging between 90-95%. On the other hand, the mean annual rainfall has an increasing trend at 99% significance level. The estimated seasonality index showed that the rainfall distribution is asymmetric and distributed over 3-4 months period. The study will help to understand the spatio-temporal variation of rainfall and to determine the correlation between the current rainfall trend and climate change scenario of the study region for multifarious use.

Keywords: Eastern India, long-term variability and trends, Mann-Kendall test, seasonality index, spatio-temporal variation.

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3599 Optimization of Process Parameters for Friction Stir Welding of Cast Alloy AA7075 by Taguchi Method

Authors: Dhairya Partap Sing, Vikram Singh, Sudhir Kumar

Abstract:

This investigation proposes Friction stir welding technique to solve the fusion welding problems. Objectives of this investigation are fabrication of AA7075-10%wt. Silicon carbide (SiC) aluminum metal matrix composite and optimization of optimal process parameters of friction stir welded AA7075-10%wt. SiC Composites. Composites were prepared by the mechanical stir casting process. Experiments were performed with four process parameters such as tool rotational speed, weld speed, axial force and tool geometry considering three levels of each. The quality characteristics considered is joint efficiency (JE). The welding experiments were conducted using L27 orthogonal array. An orthogonal array and design of experiments were used to give best possible welding parameters that give optimal JE. The fabricated welded joints using rotational speed of 1500 rpm, welding speed (1.3 mm/sec), axial force (7 k/n) of and tool geometry (square) give best possible results. Experimental result reveals that the tool rotation speed, welding speed and axial force are the significant process parameters affecting the welding performance. The predicted optimal value of percentage JE is 95.621. The confirmation tests also have been done for verifying the results.

Keywords: Metal matrix composite, axial force, joint efficiency, rotational speed, traverse speed, tool geometry.

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3598 Optimal Tuning of a Fuzzy Immune PID Parameters to Control a Delayed System

Authors: S. Gherbi, F. Bouchareb

Abstract:

This paper deals with the novel intelligent bio-inspired control strategies, it presents a novel approach based on an optimal fuzzy immune PID parameters tuning, it is a combination of a PID controller, inspired by the human immune mechanism with fuzzy logic. Such controller offers more possibilities to deal with the delayed systems control difficulties due to the delay term. Indeed, we use an optimization approach to tune the four parameters of the controller in addition to the fuzzy function; the obtained controller is implemented in a modified Smith predictor structure, which is well known that it is the most efficient to the control of delayed systems. The application of the presented approach to control a three tank delay system shows good performances and proves the efficiency of the method.

Keywords: Delayed systems, Fuzzy Immune PID, Optimization, Smith predictor.

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3597 An Empirical Validation of the Linear- Hyperbolic Approximation of the I-V Characteristic of a Solar Cell Generator

Authors: A. A. Penin

Abstract:

An empirical linearly-hyperbolic approximation of the I - V characteristic of a solar cell is presented. This approximation is based on hyperbolic dependence of a current of p-n junctions on voltage for large currents. Such empirical approximation is compared with the early proposed formal linearly-hyperbolic approximation of a solar cell. The expressions defining laws of change of parameters of formal approximation at change of a photo current of family of characteristics are received. It allows simplifying a finding of parameters of approximation on actual curves, to specify their values. Analytical calculation of load regime for linearly - hyperbolic model leads to quadratic equation. Also, this model allows to define soundly a deviation from the maximum power regime and to compare efficiency of regimes of solar cells with different parameters.

Keywords: a solar cell generator, I − V characteristic, p − n junction, approximation

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3596 A Numerical Framework to Investigate Intake Aerodynamics Behavior in Icing Conditions

Authors: Ali Mirmohammadi, Arash Taheri, Meysam Mohammadi-Amin

Abstract:

One of the major parts of a jet engine is air intake, which provides proper and required amount of air for the engine to operate. There are several aerodynamic parameters which should be considered in design, such as distortion, pressure recovery, etc. In this research, the effects of lip ice accretion on pitot intake performance are investigated. For ice accretion phenomenon, two supervised multilayer neural networks (ANN) are designed, one for ice shape prediction and another one for ice roughness estimation based on experimental data. The Fourier coefficients of transformed ice shape and parameters include velocity, liquid water content (LWC), median volumetric diameter (MVD), spray time and temperature are used in neural network training. Then, the subsonic intake flow field is simulated numerically using 2D Navier-Stokes equations and Finite Volume approach with Hybrid mesh includes structured and unstructured meshes. The results are obtained in different angles of attack and the variations of intake aerodynamic parameters due to icing phenomenon are discussed. The results show noticeable effects of ice accretion phenomenon on intake behavior.

Keywords: Artificial Neural Network, Ice Accretion, IntakeAerodynamics, Design Parameters, Finite Volume Method.

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3595 An Experimental Study on the Effect of Operating Parameters during the Micro-Electro-Discharge Machining of Ni Based Alloy

Authors: Asma Perveen, M. P. Jahan

Abstract:

Ni alloys have managed to cover wide range of applications such as automotive industries, oil gas industries, and aerospace industries. However, these alloys impose challenges while using conventional machining technologies. On the other hand, Micro-Electro-Discharge machining (micro-EDM) is a non-conventional machining method that uses controlled sparks energy to remove material irrespective of the materials hardness. There has been always a huge interest from the industries for developing optimum methodology and parameters in order to enhance the productivity of micro-EDM in terms of reducing machining time and tool wear for different alloys. Therefore, the aims of this study are to investigate the effects of the micro-EDM process parameters, in order to find their optimal values. The input process parameters include voltage, capacitance, and electrode rotational speed, whereas the output parameters considered are machining time, entrance diameter of hole, overcut, tool wear, and crater size. The surface morphology and element characterization are also investigated with the use of SEM and EDX analysis. The experimental result indicates the reduction of machining time with the increment of discharge energy. Discharge energy also contributes to the enlargement of entrance diameter as well as overcut. In addition, tool wears show reduction with the increase of discharge energy. Moreover, crater size is found to be increased in size along with the increment of discharge energy.

Keywords: Micro EDM, Ni alloy, discharge energy, micro-holes.

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3594 Sustainability in Space Composition of Traditional Architecture of Hot Arid Zones of Iran

Authors: Farshad Kheiri

Abstract:

Iran Central Plateau encompasses a large proportion of this country. The weather in these flat plains is warm and arid with very little precipitation. Different attempts in architecture have been done to alleviate the weather severity of this area and create a living place compatible with humans’ comfort criteria. Investigations have showed that some of the most successful approaches in traditional architecture of the area has been forgotten or are not being used widely. As sustainability is defined as an appropriate solution for environmental, economical, and social disorders, this research is a try to demonstrate the sustainability in aforementioned architecture and based on these studies, propounds solutions for today architecture in hot arid zones.

Keywords: Hot arid climatic zone, Iranian Architecture, Sustainability, Vernacular architecture.

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3593 About the Structural Stability of the Model of the Nonelectroneutral Current Sheath

Authors: V.V. Lyahov, V.M. Neshchadim

Abstract:

The structural stability of the model of a nonelectroneutral current sheath is investigated. The stationary model of a current sheath represents the system of four connected nonlinear differential first-order equations and thus they should manifest structural instability property, i.e. sensitivity to the infinitesimal changes of parameters and starting conditions. Domains of existence of the solutions of current sheath type are found. Those solutions of the current sheath type are realized only in some regions of sevendimensional space of parameters of the problem. The phase volume of those regions is small in comparison with the whole phase volume of the definition range of those parameters. It is shown that the offered model of a nonelectroneutral current sheath is applicable for theoretical interpretation of the bifurcational current sheaths observed in the magnetosphere.

Keywords: Distribution function, electromagnetic field, magnetoactive plasma, nonelectroneutral current sheath, structural instability, bifurcational current sheath.

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3592 Person Identification by Using AR Model for EEG Signals

Authors: Gelareh Mohammadi, Parisa Shoushtari, Behnam Molaee Ardekani, Mohammad B. Shamsollahi

Abstract:

A direct connection between ElectroEncephaloGram (EEG) and the genetic information of individuals has been investigated by neurophysiologists and psychiatrists since 1960-s; and it opens a new research area in the science. This paper focuses on the person identification based on feature extracted from the EEG which can show a direct connection between EEG and the genetic information of subjects. In this work the full EO EEG signal of healthy individuals are estimated by an autoregressive (AR) model and the AR parameters are extracted as features. Here for feature vector constitution, two methods have been proposed; in the first method the extracted parameters of each channel are used as a feature vector in the classification step which employs a competitive neural network and in the second method a combination of different channel parameters are used as a feature vector. Correct classification scores at the range of 80% to 100% reveal the potential of our approach for person classification/identification and are in agreement to the previous researches showing evidence that the EEG signal carries genetic information. The novelty of this work is in the combination of AR parameters and the network type (competitive network) that we have used. A comparison between the first and the second approach imply preference of the second one.

Keywords: Person Identification, Autoregressive Model, EEG, Neural Network

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3591 Optimization of Control Parameters for MRR in Injection Flushing Type of EDM on Stainless Steel 304 Workpiece

Authors: M. S. Reza, M. Hamdi, A.S. Hadi

Abstract:

The operating control parameters of injection flushing type of electrical discharge machining process on stainless steel 304 workpiece with copper tools are being optimized according to its individual machining characteristic i.e. material removal rate (MRR). Lower MRR during EDM machining process may decrease its- machining productivity. Hence, the quality characteristic for MRR is set to higher-the-better to achieve the optimum machining productivity. Taguchi method has been used for the construction, layout and analysis of the experiment for each of the machining characteristic for the MRR. The use of Taguchi method in the experiment saves a lot of time and cost of preparing and machining the experiment samples. Therefore, an L18 Orthogonal array which was the fundamental component in the statistical design of experiments has been used to plan the experiments and Analysis of Variance (ANOVA) is used to determine the optimum machining parameters for this machining characteristic. The control parameters selected for this optimization experiments are polarity, pulse on duration, discharge current, discharge voltage, machining depth, machining diameter and dielectric liquid pressure. The result had shown that the higher the discharge voltage, the higher will be the MRR.

Keywords: ANOVA, EDM, Injection Flushing, L18 OrthogonalArray, MRR, Stainless Steel 304

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3590 Auto Tuning of PID Controller for MIMO Processes

Authors: M. J. Lengare, R. H. Chile, L. M. Waghmare, Bhavesh Parmar

Abstract:

One of the most basic functions of control engineers is tuning of controllers. There are always several process loops in the plant necessitate of tuning. The auto tuned Proportional Integral Derivative (PID) Controllers are designed for applications where large load changes are expected or the need for extreme accuracy and fast response time exists. The algorithm presented in this paper is used for the tuning PID controller to obtain its parameters with a minimum computing complexity. It requires continuous analysis of variation in few parameters, and let the program to do the plant test and calculate the controller parameters to adjust and optimize the variables for the best performance. The algorithm developed needs less time as compared to a normal step response test for continuous tuning of the PID through gain scheduling.

Keywords: Auto tuning; gain scheduling; MIMO Processes; Optimization; PID controller; Process Control.

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3589 Studies on Seasonal Variations of Physico- Chemical Parameters of Fish Farm at Govt. Nursery Unit, Muzaffargarh, Punjab, Pakistan

Authors: Muhammad Naeem, Abdus Salam, Muhammad Ashraf, Muhammad Imran, Mehtab Ahmad, Muhammad Jamshed Khan, Muhammad Mazhar Ayaz, Muzaffar Ali, Arshad Ali, Memoona Qayyum Abir Ishtiaq

Abstract:

The present study was designed to demonstrate the seasonal variations in physico-chemical parameters of fish farm at Govt. Nursery Unit, Muzaffargarh, Department of Fisheries Govt. of Punjab, Pakistan for a period of eight months from January to August 2008. Water samples were collected on fifteen days basis and have been analyzed for estimation of Air temperature, Water temperature, Light penetration, pH, Total dissolved oxygen, Clouds, Carbonates, Bicarbonates, Total carbonates, Total dissolved solids, Chlorides, Calcium and Hardness. Seasonal fluctuations were observed in all the physico-chemical parameters of fish farm. The overall physicochemical parameters of fish pond water remained within the tolerable range throughout the study period.

Keywords: Freshwater, Fish farm, Water quality, Seasonal variation, Chemical factor

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3588 An Optimization of the New Die Design of Sheet Hydroforming by Taguchi Method

Authors: M. Hosseinzadeh, S. A. Zamani, A. Taheri

Abstract:

During the last few years, several sheet hydroforming processes have been introduced. Despite the advantages of these methods, they have some limitations. Of the processes, the two main ones are the standard hydroforming and hydromechanical deep drawing. A new sheet hydroforming die set was proposed that has the advantages of both processes and eliminates their limitations. In this method, a polyurethane plate was used as a part of the die-set to control the blank holder force. This paper outlines the Taguchi optimization methodology, which is applied to optimize the effective parameters in forming cylindrical cups by the new die set of sheet hydroforming process. The process parameters evaluated in this research are polyurethane hardness, polyurethane thickness, forming pressure path and polyurethane hole diameter. The design of experiments based upon L9 orthogonal arrays by Taguchi was used and analysis of variance (ANOVA) was employed to analyze the effect of these parameters on the forming pressure. The analysis of the results showed that the optimal combination for low forming pressure is harder polyurethane, bigger diameter of polyurethane hole and thinner polyurethane. Finally, the confirmation test was derived based on the optimal combination of parameters and it was shown that the Taguchi method is suitable to examine the optimization process.

Keywords: Sheet Hydroforming, Optimization, Taguchi Method

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3587 Using Genetic Algorithms in Closed Loop Identification of the Systems with Variable Structure Controller

Authors: O.M. Mohamed vall, M. Radhi

Abstract:

This work presents a recursive identification algorithm. This algorithm relates to the identification of closed loop system with Variable Structure Controller. The approach suggested includes two stages. In the first stage a genetic algorithm is used to obtain the parameters of switching function which gives a control signal rich in commutations (i.e. a control signal whose spectral characteristics are closest possible to those of a white noise signal). The second stage consists in the identification of the system parameters by the instrumental variable method and using the optimal switching function parameters obtained with the genetic algorithm. In order to test the validity of this algorithm a simulation example is presented.

Keywords: Closed loop identification, variable structure controller, pseud-random binary sequence, genetic algorithms.

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3586 On-line Identification of Continuous-time Hammerstein Systems via RBF Networks and Immune Algorithm

Authors: Tomohiro Hachino, Kengo Nagatomo, Hitoshi Takata

Abstract:

This paper deals with an on-line identification method of continuous-time Hammerstein systems by using the radial basis function (RBF) networks and immune algorithm (IA). An unknown nonlinear static part to be estimated is approximately represented by the RBF network. The IA is efficiently combined with the recursive least-squares (RLS) method. The objective function for the identification is regarded as the antigen. The candidates of the RBF parameters such as the centers and widths are coded into binary bit strings as the antibodies and searched by the IA. On the other hand, the candidates of both the weighting parameters of the RBF network and the system parameters of the linear dynamic part are updated by the RLS method. Simulation results are shown to illustrate the proposed method.

Keywords: Continuous-time System, Hammerstein System, OnlineIdentification, Immune Algorithm, RBF network.

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3585 Optimization of Process Parameters Affecting on Spring-Back in V-Bending Process for High Strength Low Alloy Steel HSLA 420 Using FEA (HyperForm) and Taguchi Technique

Authors: Navajyoti Panda, R. S. Pawar

Abstract:

In this study, process parameters like punch angle, die opening, grain direction, and pre-bend condition of the strip for deep draw of high strength low alloy steel HSLA 420 are investigated. The finite element method (FEM) in association with the Taguchi and the analysis of variance (ANOVA) techniques are carried out to investigate the degree of importance of process parameters in V-bending process for HSLA 420&ST12 grade material. From results, it is observed that punch angle had a major influence on the spring-back. Die opening also showed very significant role on spring back. On the other hand, it is revealed that grain direction had the least impact on spring back; however, if strip from flat sheet is taken, then it is less prone to spring back as compared to the strip from sheet metal coil. HyperForm software is used for FEM simulation and experiments are designed using Taguchi method. Percentage contribution of the parameters is obtained through the ANOVA techniques.

Keywords: Bending, V-bending, FEM, spring-back, Taguchi, HyperForm, profile projector, HSLA 420 & St12 materials.

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3584 Influence Analysis of Macroeconomic Parameters on Real Estate Price Variation in Taipei, Taiwan

Authors: Li Li, Kai-Hsuan Chu

Abstract:

It is well known that the real estate price depends on a lot of factors. Each house current value is dependent on the location, room number, transportation, living convenience, year and surrounding environments. Although, there are different experienced models for housing agent to estimate the price, it is a case by case study without overall dynamic variation investigation. However, many economic parameters may more or less influence the real estate price variation. Here, the influences of most macroeconomic parameters on real estate price are investigated individually based on least-square scheme and grey correlation strategy. Then those parameters are classified into leading indices, simultaneous indices and laggard indices. In addition, the leading time period is evaluated based on least square method. The important leading and simultaneous indices can be used to establish an artificial intelligent neural network model for real estate price variation prediction. The real estate price variation of Taipei, Taiwan during 2005 ~ 2017 are chosen for this research data analysis and validation. The results show that the proposed method has reasonable prediction function for real estate business reference.

Keywords: Real estate price, least-square, grey correlation, macroeconomics.

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3583 A Software for Calculation of Optimum Conditions for Cotton Bobbin Drying in a Hot-Air Bobbin Dryer

Authors: Hilmi Kuscu, Ahmet Cihan, Kamil Kahveci, Ugur Akyol

Abstract:

In this study, a software has been developed to predict the optimum conditions for drying of cotton based yarn bobbins in a hot air dryer. For this purpose, firstly, a suitable drying model has been specified using experimental drying behavior for different values of drying parameters. Drying parameters in the experiments were drying temperature, drying pressure, and volumetric flow rate of drying air. After obtaining a suitable drying model, additional curve fittings have been performed to obtain equations for drying time and energy consumption taking into account the effects of drying parameters. Then, a software has been developed using Visual Basic programming language to predict the optimum drying conditions for drying time and energy consumption.

Keywords: Drying, bobbin, cotton, PLC control, Visual Basic.

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3582 Genetic Programming: Principles, Applications and Opportunities for Hydrological Modelling

Authors: Oluwaseun K. Oyebode, Josiah A. Adeyemo

Abstract:

Hydrological modelling plays a crucial role in the planning and management of water resources, most especially in water stressed regions where the need to effectively manage the available water resources is of critical importance. However, due to the complex, nonlinear and dynamic behaviour of hydro-climatic interactions, achieving reliable modelling of water resource systems and accurate projection of hydrological parameters are extremely challenging. Although a significant number of modelling techniques (process-based and data-driven) have been developed and adopted in that regard, the field of hydrological modelling is still considered as one that has sluggishly progressed over the past decades. This is majorly as a result of the identification of some degree of uncertainty in the methodologies and results of techniques adopted. In recent times, evolutionary computation (EC) techniques have been developed and introduced in response to the search for efficient and reliable means of providing accurate solutions to hydrological related problems. This paper presents a comprehensive review of the underlying principles, methodological needs and applications of a promising evolutionary computation modelling technique – genetic programming (GP). It examines the specific characteristics of the technique which makes it suitable to solving hydrological modelling problems. It discusses the opportunities inherent in the application of GP in water related-studies such as rainfall estimation, rainfall-runoff modelling, streamflow forecasting, sediment transport modelling, water quality modelling and groundwater modelling among others. Furthermore, the means by which such opportunities could be harnessed in the near future are discussed. In all, a case for total embracement of GP and its variants in hydrological modelling studies is made so as to put in place strategies that would translate into achieving meaningful progress as it relates to modelling of water resource systems, and also positively influence decision-making by relevant stakeholders.

Keywords: Computational modelling, evolutionary algorithms, genetic programming, hydrological modelling.

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3581 Improving Convergence of Parameter Tuning Process of the Additive Fuzzy System by New Learning Strategy

Authors: Thi Nguyen, Lee Gordon-Brown, Jim Peterson, Peter Wheeler

Abstract:

An additive fuzzy system comprising m rules with n inputs and p outputs in each rule has at least t m(2n + 2 p + 1) parameters needing to be tuned. The system consists of a large number of if-then fuzzy rules and takes a long time to tune its parameters especially in the case of a large amount of training data samples. In this paper, a new learning strategy is investigated to cope with this obstacle. Parameters that tend toward constant values at the learning process are initially fixed and they are not tuned till the end of the learning time. Experiments based on applications of the additive fuzzy system in function approximation demonstrate that the proposed approach reduces the learning time and hence improves convergence speed considerably.

Keywords: Additive fuzzy system, improving convergence, parameter learning process, unsupervised learning.

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3580 Factors in a Sustainability Assessment of New Types of Closed Cavity Façades

Authors: Zoran Veršić, Josip Galić, Marin Binički, Lucija Stepinac

Abstract:

With the current increase in CO2 emissions and global warming, the sustainability of both existing and new solutions must be assessed on a wide scale. As the implementation of closed cavity façades (CCF) is on the rise, various factors must be included in the analysis of new types of CCF. This paper aims to cover the relevant factors included in the sustainability assessment of new types of CCF. Several mathematical models are being used to describe the physical behavior of CCF. Depending on the type of CCF, they cover the main factors which affect the durability of the façade: thermal behavior of various elements in the façade, stress and deflection of the glass panels, pressure and the moisture control in the cavity. CCF itself represents a complex system in which all mentioned factors must be considered mutually. Still, the façade is only an envelope of a more complex system, the building. Choice of the façade dictates the heat loss and the heat gain, thermal comfort of inner space, natural lighting, and ventilation. Annual energy consumption for heating, cooling, lighting, and maintenance costs will present the operational advantages or disadvantages of the chosen façade system in economic and environmental aspects. Still, the only operational viewpoint is not all-inclusive. As the building codes constantly demand higher energy efficiency as well as transfer to renewable energy sources, the ratio of embodied and lifetime operational energy footprint of buildings is changing. With the drop in operational energy CO2 emissions, embodied energy emissions present a larger and larger share in the lifecycle emissions of the building. Taking all into account, the sustainability assessment of a façade, as well as other major building elements, should include all mentioned factors during the lifecycle of an element. The challenge of such an approach is a timescale. Depending on the climatic conditions on the building site, the expected lifetime of a glazed façade can exceed 25 years. In such a timespan, some of the factors can be estimated more precisely than the others. However, the ones depending on the socio-economic conditions are more likely to be harder to predict than the natural ones like the climatic load. This work recognizes and summarizes the relevant factors needed for the assessment of a new type of CCF, considering the entire lifetime of a façade element in an environmental aspect.

Keywords: Assessment, closed cavity façade, life cycle, sustainability.

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3579 Thermal Modeling of Dry-Transformers and Estimating Temperature Rise

Authors: M. Ghareh, L. Sepahi

Abstract:

Temperature rise in a transformer depends on variety of parameters such as ambient temperature, output current and type of the core. Considering these parameters, temperature rise estimation is still complicated procedure. In this paper, we present a new model based on simple electrical equivalent circuit. This method avoids the complication associated to accurate estimation and is in very good agreement with practice.

Keywords: Thermal modeling, temperature rise, equivalent thermal circuit.

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3578 Tool Wear and Surface Roughness Prediction using an Artificial Neural Network (ANN) in Turning Steel under Minimum Quantity Lubrication (MQL)

Authors: S. M. Ali, N. R. Dhar

Abstract:

Tool wear and surface roughness prediction plays a significant role in machining industry for proper planning and control of machining parameters and optimization of cutting conditions. This paper deals with developing an artificial neural network (ANN) model as a function of cutting parameters in turning steel under minimum quantity lubrication (MQL). A feed-forward backpropagation network with twenty five hidden neurons has been selected as the optimum network. The co-efficient of determination (R2) between model predictions and experimental values are 0.9915, 0.9906, 0.9761 and 0.9627 in terms of VB, VM, VS and Ra respectively. The results imply that the model can be used easily to forecast tool wear and surface roughness in response to cutting parameters.

Keywords: ANN, MQL, Surface Roughness, Tool Wear.

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3577 Need for Standardization of Manual Inspection in Small and Medium-Scale Manufacturing Industries

Authors: Adithya Nadig

Abstract:

In the field of production, characterization of surface roughness plays a vital role in assessing the quality of a manufactured product. The defined parameters for this assessment, each, have their own drawbacks in describing a profile surface. From the purview of small-scale and medium-scale industries, an increase in time spent for manual inspection of a product for various parameters adds to the cost of the product. In order to reduce this, a uniform and established standard is necessary for quantifying a profile of a manufactured product. The inspection procedure in the small and medium-scale manufacturing units at Jigani Industrial area, Bangalore, was observed. The parameters currently in use in those industries are described in the paper and a change in the inspection method is proposed.

Keywords: Efficiency of quality assessment, areal profiling technique, manufacturing, standardization, Surface Roughness Characterization.

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