Search results for: Chebyshev polynomial
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 253

Search results for: Chebyshev polynomial

13 Statistical Screening of Medium Components on Ethanol Production from Cashew Apple Juice using Saccharomyces diasticus

Authors: Karuppaiya Maruthai, Viruthagiri Thangavelu, Manikandan Kanagasabai

Abstract:

In the present study, effect of critical medium components (a total of fifteen components) on ethanol production from waste cashew apple juice (CAJ) using yeast Saccharomyces diasticus was studied. A statistical response surface methodology (RSM) based Plackett-Burman Design (PBD) was used for the design of experiments. The design contains a total of 32 experimental trails. The effect of medium components on ethanol was studied at two different levels such as low concentration level (-) and high concentration levels (+). The dependent variables selected in this study were ethanol concentration (g/L) and cellmass concentration (g/L). Data obtained from RSM on ethanol production were subjected to analysis of variance (ANOVA). In general, initial substrate concentration significantly influenced the microbial growth and product formation. Of the medium components evaluated, CAJ concentration, yeast extract, (NH4)2SO4, and malt extract showed significant effect on ethanol fermentation. A second-order polynomial model was used to predict the experimental data and the model fitted the data with a high correlation coefficient (R2 > 0.98). Maximum ethanol (15.3 g/L) and biomass (6.4 g/L) concentrations were obtained at the optimum medium composition and at optimum condition (temperature-30°C; initial pH-6.8) after 72 h fermentation using S.diasticus.

Keywords: cashew apple juice, ethanol, fermentation, yeast, response surface methodology

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12 Preparation of Corn Flour Based Extruded Product and Evaluate Its Physical Characteristics

Authors: C. S. Saini

Abstract:

The composite flour blend consisting of corn, pearl millet, black gram and wheat bran in the ratio of 80:5:10:5 was taken to prepare the extruded product and their effect on physical properties of extrudate was studied. The extrusion process was conducted in laboratory by using twin screw extruder. The physical characteristics evaluated include lateral expansion, bulk density, water absorption index, water solubility index, and rehydration ratio and moisture retention. The Central Composite Rotatable Design (CCRD) was used to decide the level of processing variables i.e. feed moisture content (%), screw speed (rpm), and barrel temperature (oC) for the experiment. The data obtained after extrusion process were analyzed by using response surface methodology. A second order polynomial model for the dependent variables was established to fit the experimental data. The numerical optimization studies resulted in 127°C of barrel temperature, 246 rpm of screw speed, and 14.5% of feed moisture as optimum variables to produce acceptable extruded product. The responses predicted by the software for the optimum process condition resulted in lateral expansion 126%, bulk density 0.28 g/cm3, water absorption index 4.10 g/g, water solubility index 39.90%, rehydration ratio 544% and moisture retention 11.90% with 75% desirability.

Keywords: Black gram, corn flour, extrusion, physical characteristics.

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11 Conventional and PSO Based Approaches for Model Reduction of SISO Discrete Systems

Authors: S. K. Tomar, R. Prasad, S. Panda, C. Ardil

Abstract:

Reduction of Single Input Single Output (SISO) discrete systems into lower order model, using a conventional and an evolutionary technique is presented in this paper. In the conventional technique, the mixed advantages of Modified Cauer Form (MCF) and differentiation are used. In this method the original discrete system is, first, converted into equivalent continuous system by applying bilinear transformation. The denominator of the equivalent continuous system and its reciprocal are differentiated successively, the reduced denominator of the desired order is obtained by combining the differentiated polynomials. The numerator is obtained by matching the quotients of MCF. The reduced continuous system is converted back into discrete system using inverse bilinear transformation. In the evolutionary technique method, Particle Swarm Optimization (PSO) is employed to reduce the higher order model. PSO method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Both the methods are illustrated through numerical example.

Keywords: Discrete System, Single Input Single Output (SISO), Bilinear Transformation, Reduced Order Model, Modified CauerForm, Polynomial Differentiation, Particle Swarm Optimization, Integral Squared Error.

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10 Simultaneous Saccharification and Fermentation(SSF) of Sugarcane Bagasse - Kinetics and Modeling

Authors: E.Sasikumar, T.Viruthagiri

Abstract:

Simultaneous Saccharification and Fermentation (SSF) of sugarcane bagasse by cellulase and Pachysolen tannophilus MTCC *1077 were investigated in the present study. Important process variables for ethanol production form pretreated bagasse were optimized using Response Surface Methodology (RSM) based on central composite design (CCD) experiments. A 23 five level CCD experiments with central and axial points was used to develop a statistical model for the optimization of process variables such as incubation temperature (25–45°) X1, pH (5.0–7.0) X2 and fermentation time (24–120 h) X3. Data obtained from RSM on ethanol production were subjected to the analysis of variance (ANOVA) and analyzed using a second order polynomial equation and contour plots were used to study the interactions among three relevant variables of the fermentation process. The fermentation experiments were carried out using an online monitored modular fermenter 2L capacity. The processing parameters setup for reaching a maximum response for ethanol production was obtained when applying the optimum values for temperature (32°C), pH (5.6) and fermentation time (110 h). Maximum ethanol concentration (3.36 g/l) was obtained from 50 g/l pretreated sugarcane bagasse at the optimized process conditions in aerobic batch fermentation. Kinetic models such as Monod, Modified Logistic model, Modified Logistic incorporated Leudeking – Piret model and Modified Logistic incorporated Modified Leudeking – Piret model have been evaluated and the constants were predicted.

Keywords: Sugarcane bagasse, ethanol, optimization, Pachysolen tannophilus.

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9 Simulating Dynamics of Thoracolumbar Spine Derived from Life MOD under Haptic Forces

Authors: K. T. Huynh, I. Gibson, W. F. Lu, B. N. Jagdish

Abstract:

In this paper, the construction of a detailed spine model is presented using the LifeMOD Biomechanics Modeler. The detailed spine model is obtained by refining spine segments in cervical, thoracic and lumbar regions into individual vertebra segments, using bushing elements representing the intervertebral discs, and building various ligamentous soft tissues between vertebrae. In the sagittal plane of the spine, constant force will be applied from the posterior to anterior during simulation to determine dynamic characteristics of the spine. The force magnitude is gradually increased in subsequent simulations. Based on these recorded dynamic properties, graphs of displacement-force relationships will be established in terms of polynomial functions by using the least-squares method and imported into a haptic integrated graphic environment. A thoracolumbar spine model with complex geometry of vertebrae, which is digitized from a resin spine prototype, will be utilized in this environment. By using the haptic technique, surgeons can touch as well as apply forces to the spine model through haptic devices to observe the locomotion of the spine which is computed from the displacement-force relationship graphs. This current study provides a preliminary picture of our ongoing work towards building and simulating bio-fidelity scoliotic spine models in a haptic integrated graphic environment whose dynamic properties are obtained from LifeMOD. These models can be helpful for surgeons to examine kinematic behaviors of scoliotic spines and to propose possible surgical plans before spine correction operations.

Keywords: Haptic interface, LifeMOD, spine modeling.

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8 Response Surface Methodology Approach to Defining Ultrafiltration of Steepwater from Corn Starch Industry

Authors: Zita I. Šereš, Ljubica P. Dokić, Dragana M. Šoronja Simović, Cecilia Hodur, Zsuzsanna Laszlo, Ivana Nikolić, Nikola Maravić

Abstract:

In this work the concentration of steepwater from corn starch industry is monitored using ultrafiltration membrane. The aim was to examine the conditions of ultrafiltration of steepwater by applying the membrane of 2.5nm. The parameters that vary during the course of ultrafiltration, were the transmembrane pressure, flow rate, while the permeate flux and the dry matter content of permeate and retentate were the dependent parameter constantly monitored during the process. Experiments of ultrafiltration are conducted on the samples of steepwater, which were obtained from the starch wet milling plant „Jabuka“ Pancevo. The procedure of ultrafiltration on a single-channel 250mm lenght, with inner diameter of 6.8mm and outer diameter of 10mm membrane were carried on. The membrane is made of a-Al2O3 with TiO2 layer obtained from GEA (Germany). The experiments are carried out at a flow rate ranging from 100 to 200lh-1 and transmembrane pressure of 1-3 bars. During the experiments of steepwater ultrafiltration, the change of permeate flux, dry matter content of permeate and retentate, as well as the absorbance changes of the permeate and retentate were monitored. The experimental results showed that the maximum flux reaches about 40lm-2h-1. For responses obtained after experiments, a polynomial model of the second degree is established to evaluate and quantify the influence of the variables. The quadratic equitation fits with the experimental values, where the coefficient of determination for flux is 0.96. The dry matter content of the retentate is increased for about 6%, while the dry matter content of permeate was reduced for about 35-40%, respectively. During steepwater ultrafiltration in permeate stays 40% less dry matter compared to the feed.

Keywords: Ultrafiltration, steepwater, starch industry, ceramic membrane.

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7 Parameter Optimization and Thermal Simulation in Laser Joining of Coach Peel Panels of Dissimilar Materials

Authors: Masoud Mohammadpour, Blair Carlson, Radovan Kovacevic

Abstract:

The quality of laser welded-brazed (LWB) joints were strongly dependent on the main process parameters, therefore the effect of laser power (3.2–4 kW), welding speed (60–80 mm/s) and wire feed rate (70–90 mm/s) on mechanical strength and surface roughness were investigated in this study. The comprehensive optimization process by means of response surface methodology (RSM) and desirability function was used for multi-criteria optimization. The experiments were planned based on Box– Behnken design implementing linear and quadratic polynomial equations for predicting the desired output properties. Finally, validation experiments were conducted on an optimized process condition which exhibited good agreement between the predicted and experimental results. AlSi3Mn1 was selected as the filler material for joining aluminum alloy 6022 and hot-dip galvanized steel in coach peel configuration. The high scanning speed could control the thickness of IMC as thin as 5 µm. The thermal simulations of joining process were conducted by the Finite Element Method (FEM), and results were validated through experimental data. The Fe/Al interfacial thermal history evidenced that the duration of critical temperature range (700–900 °C) in this high scanning speed process was less than 1 s. This short interaction time leads to the formation of reaction-control IMC layer instead of diffusion-control mechanisms.

Keywords: Laser welding-brazing, finite element, response surface methodology, multi-response optimization, cross-beam laser.

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6 Statistical Analysis and Optimization of a Process for CO2 Capture

Authors: Muftah H. El-Naas, Ameera F. Mohammad, Mabruk I. Suleiman, Mohamed Al Musharfy, Ali H. Al-Marzouqi

Abstract:

CO2 capture and storage technologies play a significant role in contributing to the control of climate change through the reduction of carbon dioxide emissions into the atmosphere. The present study evaluates and optimizes CO2 capture through a process, where carbon dioxide is passed into pH adjusted high salinity water and reacted with sodium chloride to form a precipitate of sodium bicarbonate. This process is based on a modified Solvay process with higher CO2 capture efficiency, higher sodium removal, and higher pH level without the use of ammonia. The process was tested in a bubble column semi-batch reactor and was optimized using response surface methodology (RSM). CO2 capture efficiency and sodium removal were optimized in terms of major operating parameters based on four levels and variables in Central Composite Design (CCD). The operating parameters were gas flow rate (0.5–1.5 L/min), reactor temperature (10 to 50 oC), buffer concentration (0.2-2.6%) and water salinity (25-197 g NaCl/L). The experimental data were fitted to a second-order polynomial using multiple regression and analyzed using analysis of variance (ANOVA). The optimum values of the selected variables were obtained using response optimizer. The optimum conditions were tested experimentally using desalination reject brine with salinity ranging from 65,000 to 75,000 mg/L. The CO2 capture efficiency in 180 min was 99% and the maximum sodium removal was 35%. The experimental and predicted values were within 95% confidence interval, which demonstrates that the developed model can successfully predict the capture efficiency and sodium removal using the modified Solvay method.

Keywords: Bubble column reactor, CO2 capture, Response Surface Methodology, water desalination.

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5 Forecast of the Small Wind Turbines Sales with Replacement Purchases and with or without Account of Price Changes

Authors: V. Churkin, M. Lopatin

Abstract:

The purpose of the paper is to estimate the US small wind turbines market potential and forecast the small wind turbines sales in the US. The forecasting method is based on the application of the Bass model and the generalized Bass model of innovations diffusion under replacement purchases. In the work an exponential distribution is used for modeling of replacement purchases. Only one parameter of such distribution is determined by average lifetime of small wind turbines. The identification of the model parameters is based on nonlinear regression analysis on the basis of the annual sales statistics which has been published by the American Wind Energy Association (AWEA) since 2001 up to 2012. The estimation of the US average market potential of small wind turbines (for adoption purchases) without account of price changes is 57080 (confidence interval from 49294 to 64866 at P = 0.95) under average lifetime of wind turbines 15 years, and 62402 (confidence interval from 54154 to 70648 at P = 0.95) under average lifetime of wind turbines 20 years. In the first case the explained variance is 90,7%, while in the second - 91,8%. The effect of the wind turbines price changes on their sales was estimated using generalized Bass model. This required a price forecast. To do this, the polynomial regression function, which is based on the Berkeley Lab statistics, was used. The estimation of the US average market potential of small wind turbines (for adoption purchases) in that case is 42542 (confidence interval from 32863 to 52221 at P = 0.95) under average lifetime of wind turbines 15 years, and 47426 (confidence interval from 36092 to 58760 at P = 0.95) under average lifetime of wind turbines 20 years. In the first case the explained variance is 95,3%, while in the second – 95,3%.

Keywords: Bass model, generalized Bass model, replacement purchases, sales forecasting of innovations, statistics of sales of small wind turbines in the United States.

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4 Twin-Screw Extruder and Effective Parameters on the HDPE Extrusion Process

Authors: S. A. Razavi Alavi, M. Torabi Angaji, Z. Gholami

Abstract:

In the process of polyethylene extrusion polymer material similar to powder or granule is under compression, melting and transmission operation and on base of special form, extrudate has been produced. Twin-screw extruders are applicable in industries because of their high capacity. The powder mixing with chemical additives and melting with thermal and mechanical energy in three zones (feed, compression and metering zone) and because of gear pump and screw's pressure, converting to final product in latest plate. Extruders with twin-screw and short distance between screws are better than other types because of their high capacity and good thermal and mechanical stress. In this paper, process of polyethylene extrusion and various tapes of extruders are studied. It is necessary to have an exact control on process to producing high quality products with safe operation and optimum energy consumption. The granule size is depending on granulator motor speed. Results show at constant feed rate a decrease in granule size was found whit Increase in motor speed. Relationships between HDPE feed rate and speed of granulator motor, main motor and gear pump are calculated following as: x = HDPE feed flow rate, yM = Main motor speed yM = (-3.6076e-3) x^4+ (0.24597) x^3+ (-5.49003) x^2+ (64.22092) x+61.66786 (1) x = HDPE feed flow rate, yG = Gear pump speed yG = (-2.4996e-3) x^4+ (0.18018) x^3+ (-4.22794) x^2+ (48.45536) x+18.78880 (2) x = HDPE feed flow rate, y = Granulator motor speed 10th Degree Polynomial Fit: y = a+bx+cx^2+dx^3... (3) a = 1.2751, b = 282.4655, c = -165.2098, d = 48.3106, e = -8.18715, f = 0.84997 g = -0.056094, h = 0.002358, i = -6.11816e-5 j = 8.919726e-7, k = -5.59050e-9

Keywords: Extrusion, Extruder, Granule, HDPE, Polymer, Twin-Screw extruder.

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3 Bond Graph Modeling of Mechanical Dynamics of an Excavator for Hydraulic System Analysis and Design

Authors: Mutuku Muvengei, John Kihiu

Abstract:

This paper focuses on the development of bond graph dynamic model of the mechanical dynamics of an excavating mechanism previously designed to be used with small tractors, which are fabricated in the Engineering Workshops of Jomo Kenyatta University of Agriculture and Technology. To develop a mechanical dynamics model of the manipulator, forward recursive equations similar to those applied in iterative Newton-Euler method were used to obtain kinematic relationships between the time rates of joint variables and the generalized cartesian velocities for the centroids of the links. Representing the obtained kinematic relationships in bondgraphic form, while considering the link weights and momenta as the elements led to a detailed bond graph model of the manipulator. The bond graph method was found to reduce significantly the number of recursive computations performed on a 3 DOF manipulator for a mechanical dynamic model to result, hence indicating that bond graph method is more computationally efficient than the Newton-Euler method in developing dynamic models of 3 DOF planar manipulators. The model was verified by comparing the joint torque expressions of a two link planar manipulator to those obtained using Newton- Euler and Lagrangian methods as analyzed in robotic textbooks. The expressions were found to agree indicating that the model captures the aspects of rigid body dynamics of the manipulator. Based on the model developed, actuator sizing and valve sizing methodologies were developed and used to obtain the optimal sizes of the pistons and spool valve ports respectively. It was found that using the pump with the sized flow rate capacity, the engine of the tractor is able to power the excavating mechanism in digging a sandy-loom soil.

Keywords: Actuators, bond graphs, inverse dynamics, recursive equations, quintic polynomial trajectory.

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2 Implementing an Intuitive Reasoner with a Large Weather Database

Authors: Yung-Chien Sun, O. Grant Clark

Abstract:

In this paper, the implementation of a rule-based intuitive reasoner is presented. The implementation included two parts: the rule induction module and the intuitive reasoner. A large weather database was acquired as the data source. Twelve weather variables from those data were chosen as the “target variables" whose values were predicted by the intuitive reasoner. A “complex" situation was simulated by making only subsets of the data available to the rule induction module. As a result, the rules induced were based on incomplete information with variable levels of certainty. The certainty level was modeled by a metric called "Strength of Belief", which was assigned to each rule or datum as ancillary information about the confidence in its accuracy. Two techniques were employed to induce rules from the data subsets: decision tree and multi-polynomial regression, respectively for the discrete and the continuous type of target variables. The intuitive reasoner was tested for its ability to use the induced rules to predict the classes of the discrete target variables and the values of the continuous target variables. The intuitive reasoner implemented two types of reasoning: fast and broad where, by analogy to human thought, the former corresponds to fast decision making and the latter to deeper contemplation. . For reference, a weather data analysis approach which had been applied on similar tasks was adopted to analyze the complete database and create predictive models for the same 12 target variables. The values predicted by the intuitive reasoner and the reference approach were compared with actual data. The intuitive reasoner reached near-100% accuracy for two continuous target variables. For the discrete target variables, the intuitive reasoner predicted at least 70% as accurately as the reference reasoner. Since the intuitive reasoner operated on rules derived from only about 10% of the total data, it demonstrated the potential advantages in dealing with sparse data sets as compared with conventional methods.

Keywords: Artificial intelligence, intuition, knowledge acquisition, limited certainty.

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1 GridNtru: High Performance PKCS

Authors: Narasimham Challa, Jayaram Pradhan

Abstract:

Cryptographic algorithms play a crucial role in the information society by providing protection from unauthorized access to sensitive data. It is clear that information technology will become increasingly pervasive, Hence we can expect the emergence of ubiquitous or pervasive computing, ambient intelligence. These new environments and applications will present new security challenges, and there is no doubt that cryptographic algorithms and protocols will form a part of the solution. The efficiency of a public key cryptosystem is mainly measured in computational overheads, key size and bandwidth. In particular the RSA algorithm is used in many applications for providing the security. Although the security of RSA is beyond doubt, the evolution in computing power has caused a growth in the necessary key length. The fact that most chips on smart cards can-t process key extending 1024 bit shows that there is need for alternative. NTRU is such an alternative and it is a collection of mathematical algorithm based on manipulating lists of very small integers and polynomials. This allows NTRU to high speeds with the use of minimal computing power. NTRU (Nth degree Truncated Polynomial Ring Unit) is the first secure public key cryptosystem not based on factorization or discrete logarithm problem. This means that given sufficient computational resources and time, an adversary, should not be able to break the key. The multi-party communication and requirement of optimal resource utilization necessitated the need for the present day demand of applications that need security enforcement technique .and can be enhanced with high-end computing. This has promoted us to develop high-performance NTRU schemes using approaches such as the use of high-end computing hardware. Peer-to-peer (P2P) or enterprise grids are proven as one of the approaches for developing high-end computing systems. By utilizing them one can improve the performance of NTRU through parallel execution. In this paper we propose and develop an application for NTRU using enterprise grid middleware called Alchemi. An analysis and comparison of its performance for various text files is presented.

Keywords: Alchemi, GridNtru, Ntru, PKCS.

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