Search results for: Turbulence modeling.

Authors: M. A. Ghorbani, M. Pasbani Khiavi

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In this paper, the dam-reservoir interaction is analyzed using a finite element approach. The fluid is assumed to be incompressible, irrotational and inviscid. The assumed boundary conditions are that the interface of the dam and reservoir is vertical and the bottom of reservoir is rigid and horizontal. The governing equation for these boundary conditions is implemented in the developed finite element code considering the horizontal and vertical earthquake components. The weighted residual standard Galerkin finite element technique with 8-node elements is used to discretize the equation that produces a symmetric matrix equation for the damreservoir system. A new boundary condition is proposed for truncating surface of unbounded fluid domain to show the energy dissipation in the reservoir, through radiation in the infinite upstream direction. The Sommerfeld-s and perfect damping boundary conditions are also implemented for a truncated boundary to compare with the proposed far end boundary. The results are compared with an analytical solution to demonstrate the accuracy of the proposed formulation and other truncated boundary conditions in modeling the hydrodynamic response of an infinite reservoir.

Keywords: Reservoir, finite element, truncated boundary, hydrodynamic pressure

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Authors: Shaharin A. Sulaiman, Malcolm Lawes

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Combustion of sprays is of technological importance, but its flame behavior is not fully understood. Furthermore, the multiplicity of dependent variables such as pressure, temperature, equivalence ratio, and droplet sizes complicates the study of spray combustion. Fundamental study on the influence of the presence of liquid droplets has revealed that laminar flames within aerosol mixtures more readily become unstable than for gaseous ones and this increases the practical burning rate. However, fundamental studies on turbulent flames of aerosol mixtures are limited particularly those under near mono-dispersed droplet conditions. In the present work, centrally ignited expanding flames at near atmospheric pressures are employed to quantify the burning rates in gaseous and aerosol flames. Iso-octane-air aerosols are generated by expansion of the gaseous pre-mixture to produce a homogeneously distributed suspension of fuel droplets. The effects of the presence of droplets and turbulence velocity in relation to the burning rates of the flame are also investigated.

Keywords: Burning Rate, Droplets, Flames, Turbulent

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Authors: Souhir Ben Amor, Heni Boubaker, Lotfi Belkacem

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This aims of this paper is to forecast the electricity spot prices. First, we focus on modeling the conditional mean of the series so we adopt a generalized fractional -factor Gegenbauer process (k-factor GARMA). Secondly, the residual from the -factor GARMA model has used as a proxy for the conditional variance; these residuals were predicted using two different approaches. In the first approach, a local linear wavelet neural network model (LLWNN) has developed to predict the conditional variance using the Back Propagation learning algorithms. In the second approach, the Gegenbauer generalized autoregressive conditional heteroscedasticity process (G-GARCH) has adopted, and the parameters of the k-factor GARMA-G-GARCH model has estimated using the wavelet methodology based on the discrete wavelet packet transform (DWPT) approach. The empirical results have shown that the k-factor GARMA-G-GARCH model outperform the hybrid k-factor GARMA-LLWNN model, and find it is more appropriate for forecasts.

Keywords: k-factor, GARMA, LLWNN, G-GARCH, electricity price, forecasting.

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Authors: Rida B. Arieby

Abstract:

This study deals with the experimental investigation and theoretical modeling of Semi crystalline polymeric materials with a rubbery amorphous phase (HDPE) subjected to a uniaxial cyclic tests with various maximum strain levels, even at large deformation. Each cycle is loaded in tension up to certain maximum strain and then unloaded down to zero stress with N number of cycles. This work is focuses on the measure of the volume strain due to the phenomena of damage during this kind of tests. On the basis of thermodynamics of relaxation processes, a constitutive model for large strain deformation has been developed, taking into account the damage effect, to predict the complex elasto-viscoelastic-viscoplastic behavior of material. A direct comparison between the model predictions and the experimental data show that the model accurately captures the material response. The model is also capable of predicting the influence damage causing volume variation.

Keywords: Cyclic test, large strain, polymers semi-crystalline, Volume strain, Thermodynamics of Irreversible Processes.

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Authors: Snezhana G. Gocheva-Ilieva, Maya P. Stoimenova

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Ambient air pollution with fine particulate matter (PM10) is a systematic permanent problem in many countries around the world. The accumulation of a large number of measurements of both the PM10 concentrations and the accompanying atmospheric factors allow for their statistical modeling to detect dependencies and forecast future pollution. This study applies the classification and regression trees (CART) method for building and analyzing PM10 models. In the empirical study, average daily air data for the city of Pleven, Bulgaria for a period of 5 years are used. Predictors in the models are seven meteorological variables, time variables, as well as lagged PM10 variables and some lagged meteorological variables, delayed by 1 or 2 days with respect to the initial time series, respectively. The degree of influence of the predictors in the models is determined. The selected best CART models are used to forecast future PM10 concentrations for two days ahead after the last date in the modeling procedure and show very accurate results.

Keywords: Cross-validation, decision tree, lagged variables, short-term forecasting.

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Authors: M.V Rajesh, Archana R, A Unnikrishnan, R Gopikakumari, Jeevamma Jacob

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The System Identification problem looks for a suitably parameterized model, representing a given process. The parameters of the model are adjusted to optimize a performance function based on error between the given process output and identified process output. The linear system identification field is well established with many classical approaches whereas most of those methods cannot be applied for nonlinear systems. The problem becomes tougher if the system is completely unknown with only the output time series is available. It has been reported that the capability of Artificial Neural Network to approximate all linear and nonlinear input-output maps makes it predominantly suitable for the identification of nonlinear systems, where only the output time series is available. [1][2][4][5]. The work reported here is an attempt to implement few of the well known algorithms in the context of modeling of nonlinear systems, and to make a performance comparison to establish the relative merits and demerits.

Keywords: Multilayer neural networks, Radial Basis Functions, Clustering algorithm, Back Propagation training, Extended Kalmanfiltering, Mean Square Error, Nonlinear Modeling, Cramer RaoLower Bound.

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Authors: Miroslav Popelka, Jakub Nožička

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The whole work is based on possibility to use Lego Mindstorms robotics systems to reduce costs. Lego Mindstorms consists of a wide variety of hardware components necessary to simulate, programme and test of robotics systems in practice. To programme algorithm, which simulates space using the ultrasonic sensor, was used development environment supplied with kit. Software Matlab was used to render values afterwards they were measured by ultrasonic sensor. The algorithm created for this paper uses theoretical knowledge from area of signal processing. Data being processed by algorithm are collected by ultrasonic sensor that scans 2D space in front of it. Ultrasonic sensor is placed on moving arm of robot which provides horizontal moving of sensor. Vertical movement of sensor is provided by wheel drive. The robot follows map in order to get correct positioning of measured data. Based on discovered facts it is possible to consider Lego Mindstorm for low-cost and capable kit for real-time modelling.

Keywords: LEGO Mindstorms, ultrasonic sensor, Real-time modeling, 2D object, low-cost robotics systems, sensors, Matlab, EV3 Home Edition Software.

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Authors: Petia Georgieva, Sebastião Feyo de Azevedo

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This paper is focused on issues of nonlinear dynamic process modeling and model-based predictive control of a fed-batch sugar crystallization process applying the concept of artificial neural networks as computational tools. The control objective is to force the operation into following optimal supersaturation trajectory. It is achieved by manipulating the feed flow rate of sugar liquor/syrup, considered as the control input. A feed forward neural network (FFNN) model of the process is first built as part of the controller structure to predict the process response over a specified (prediction) horizon. The predictions are supplied to an optimization procedure to determine the values of the control action over a specified (control) horizon that minimizes a predefined performance index. The control task is rather challenging due to the strong nonlinearity of the process dynamics and variations in the crystallization kinetics. However, the simulation results demonstrated smooth behavior of the control actions and satisfactory reference tracking.

Keywords: Feed forward neural network, process modelling, model predictive control, crystallization process.

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Authors: Yung-Yuan Hsu

Abstract:

The primary objective of this paper was to construct a “kinematic parameter-independent modeling of three-axis machine tools for geometric error measurement" technique. Improving the accuracy of the geometric error for three-axis machine tools is one of the machine tools- core techniques. This paper first applied the traditional method of HTM to deduce the geometric error model for three-axis machine tools. This geometric error model was related to the three-axis kinematic parameters where the overall errors was relative to the machine reference coordinate system. Given that the measurement of the linear axis in this model should be on the ideal motion axis, there were practical difficulties. Through a measurement method consolidating translational errors and rotational errors in the geometric error model, we simplified the three-axis geometric error model to a kinematic parameter-independent model. Finally, based on the new measurement method corresponding to this error model, we established a truly practical and more accurate error measuring technique for three-axis machine tools.

Keywords: Three-axis machine tool, Geometric error, HTM, Error measuring

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Authors: M. Raciti Castelli, G. Grandi, E. Benini

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This paper presents a study of laminar to turbulent transition on a profile specifically designed for wind turbine blades, the DU91-W2-250, which belongs to a class of wind turbine dedicated airfoils, developed by Delft University of Technology. A comparison between the experimental behavior of the airfoil studied at Delft wind tunnel and the numerical predictions of the commercial CFD solver ANSYS FLUENT® has been performed. The prediction capabilities of the Spalart-Allmaras turbulence model and of the γ-θ Transitional model have been tested. A sensitivity analysis of the numerical results to the spatial domain discretization has also been performed using four different computational grids, which have been created using the mesher GAMBIT®. The comparison between experimental measurements and CFD results have allowed to determine the importance of the numerical prediction of the laminar to turbulent transition, in order not to overestimate airfoil friction drag due to a fully turbulent-regime flow computation.

Keywords: CFD, wind turbine, DU91-W2-250, laminar to turbulent transition.

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Authors: C. V. Pietreanu, S. E. Zaharia, C. Dinu

Abstract:

The present research is built on three major pillars, commencing by making some considerations on accident investigation methods and pointing out both defining aspects and differences between linear and non-linear analysis. The traditional linear focus on accident analysis describes accidents as a sequence of events, while the latest systemic models outline interdependencies between different factors and define the processes evolution related to a specific (normal) situation. Linear and non-linear accident analysis methods have specific limitations, so the second point of interest is mirrored by the aim to discover the drawbacks of systemic models which becomes a starting point for developing new directions to identify risks or data closer to the cause of incidents/accidents. Since communication represents a critical issue in the interaction of human factor and has been proved to be the answer of the problems made by possible breakdowns in different communication procedures, from this focus point, on the third pylon a new error-modeling instrument suitable for risk assessment/accident analysis will be elaborated.

Keywords: Accident analysis, multi-factorial error modeling, risk, systemic methods.

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Authors: M. Raciti Castelli, A. Castelli, E. Benini

Abstract:

The flow field over a flat roof model building has been numerically investigated in order to determine threedimensional CFD guidelines for the calculation of the turbulent flow over a structure immersed in an atmospheric boundary layer. To this purpose, a complete validation campaign has been performed through a systematic comparison of numerical simulations with wind tunnel experimental data. Wind tunnel measurements and numerical predictions have been compared for five different vertical positions, respectively from the upstream leading edge to the downstream bottom edge of the analyzed model. Flow field characteristics in the neighborhood of the building model have been numerically investigated, allowing a quantification of the capabilities of the CFD code to predict the flow separation and the extension of the recirculation regions. The proposed calculations have allowed the development of a preliminary procedure to be used as guidance in selecting the appropriate grid configuration and corresponding turbulence model for the prediction of the flow field over a three-dimensional roof architecture dominated by flow separation.

Keywords: CFD, roof, building, wind

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Authors: Kristina Maiksteniene

Abstract:

Various formal and informal brand alliances are being formed in professional service firms. Professional service corporate brand is heavily dependent on brands of professional employees who comprise them, and professional employee brands are in turn dependent on the corporate brand. Prior work provides limited scientific evidence of brand alliance effects in professional service area – i.e., how professional service corporate-employee brand allies are affected by an alliance, what are brand attitude effects after alliance formation and how these effects vary with different strengths of an ally. Scientific literature analysis and theoretical modeling are the main methods of the current study. As a result, a theoretical model is constructed for estimating spillover effects of professional service corporate-employee brand alliances and for comparison among different professional service firm expertise practice models – from “brains" to “procedure" model. The resulting theoretical model lays basis for future experimental studies.

Keywords: Brand alliances, professional services, corporatebrand, employee brand.

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Authors: E. Hlavacova, J. Chrenova, Z. Rausova, M. Vlcek, A. Penesova, L. Dedik

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En bloc assumes modeling all phases of the orthostatic test with the only one mathematical model, which allows the complex parametric view of orthostatic response. The work presents the implementation of a mathematical model for processing of the measurements of systolic, diastolic blood pressure and heart rate performed on volunteers during orthostatic test. The original assumption of model hypothesis that every postural change means only one Stressor, did not complying with the measurements of physiological circulation factor-time profiles. Results of the identification support the hypothesis that second postural change of orthostatic test causes induced Stressors, with the observation of a physiological regulation mechanism. Maximal demonstrations are on the heart rate and diastolic blood pressure-time profile, minimal are for the measurements of the systolic blood pressure. Presented study gives a new view on orthostatic test with impact on clinical practice.

Keywords: En bloc modeling, physiological circulatory factor, postural change, stressor

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Authors: Weifeng Wang, Xianwei Zeng, Jianping Ding

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Nanomaterials have attracted considerable attention during the last two decades, due to their unusual electrical, mechanical and other physical properties as compared with their bulky counterparts. The mechanical properties of nanostructured materials show strong size dependency, which has been explained within the framework of continuum mechanics by including the effects of surface stress. The size-dependent deformations of two-dimensional nanosized structures with surface effects are investigated in the paper by the finite element method. Truss element is used to evaluate the contribution of surface stress to the total potential energy and the Gurtin and Murdoch surface stress model is implemented with ANSYS through its user programmable features. The proposed approach is used to investigate size-dependent stress concentration around a nanosized circular hole and the size-dependent effective moduli of nanoporous materials. Numerical results are compared with available analytical results to validate the proposed modeling approach.

Keywords: Nanomaterials, finite element method, sizedependency, surface stress

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Authors: H. Mat Kiah, Rafiziana M. Kasmani, Norazana Ibrahim, Roshafima R. Ali, Aziatul N.Sadikin

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An experimental study has been done to investigate the flame acceleration in a closed pipe. A horizontal steel pipe, 2m long and 0.1m in diameter (L/D of 20), was used in this work. For tests with 90 degree bends, the bend had a radius of 0.1m and thus, the pipe was lengthened 1m (based on the centreline length of the segment). Ignition was affected at one end of the vessel while the other end was closed. Only stoichiometric concentration (Ф, = 1.0) of natural gas/air mixtures will be reported in this paper. It was demonstrated that bend pipe configuration gave three times higher in maximum overpressure (5.5 bars) compared to straight pipe (2.0 bars). From the results, the highest flame speed, of 63ms^-1, was observed in a gas explosion with bent pipe; greater by a factor of ~3 as compared with straight pipe (23ms^-1). This occurs because bending acts similar to an obstacle, in which this mechanism can induce more turbulence, initiating combustion in an unburned pocket at the corner region and causing a high mass burning rate, which increases the flame speed.

Keywords: Bending, gas explosion, bending, flame acceleration, overpressure.

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Authors: H. Sajjadi, M. Gorji, GH.R. Kefayati, D. D. Ganji, M. Shayan Nia

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In this paper Lattice Boltzmann simulation of turbulent natural convection with large-eddy simulations (LES) in a square cavity which is filled by water has been investigated. The present results are validated by finds of other investigations which have been done with different numerical methods. Calculations were performed for high Rayleigh numbers of Ra=108 and 109. The results confirm that this method is in acceptable agreement with other verifications of such a flow. In this investigation is tried to present Large-eddy turbulence flow model by Lattice Boltzmann Method (LBM) with a clear and simple statement. Effects of increase in Rayleigh number are displayed on streamlines, isotherm counters and average Nusselt number. Result shows that the average Nusselt number enhances with growth of the Rayleigh numbers.

Keywords: Turbulent natural convection, Large Eddy Simulation, Lattice Boltzmann Method

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Authors: S. H. Lim, T. Furukawa

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This paper presents a generalized form of the mechanistic deconvolution technique (GMD) to modeling image sensors applicable in various pan–tilt planes of view. The mechanistic deconvolution technique (UMD) is modified with the given angles of a pan–tilt plane of view to formulate constraint parameters and characterize distortion effects, and thereby, determine the corrected image data. This, as a result, does not require experimental setup or calibration. Due to the mechanistic nature of the sensor model, the necessity for the sensor image plane to be orthogonal to its z-axis is eliminated, and it reduces the dependency on image data. An experiment was constructed to evaluate the accuracy of a model created by GMD and its insensitivity to changes in sensor properties and in pan and tilt angles. This was compared with a pre-calibrated model and a model created by UMD using two sensors with different specifications. It achieved similar accuracy with one-seventh the number of iterations and attained lower mean error by a factor of 2.4 when compared to the pre-calibrated and UMD model respectively. The model has also shown itself to be robust and, in comparison to pre-calibrated and UMD model, improved the accuracy significantly.

Keywords: Image sensor modeling, mechanistic deconvolution, calibration, lens distortion

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Authors: Vishwesh Kulkarni, Nikhil Bellarykar

Abstract:

Cellular complexity stems from the interactions among thousands of different molecular species. Thanks to the emerging fields of systems and synthetic biology, scientists are beginning to unravel these regulatory, signaling, and metabolic interactions and to understand their coordinated action. Reverse engineering of biological networks has has several benefits but a poor quality of data combined with the difficulty in reproducing it limits the applicability of these methods. A few years back, many of the commonly used predictive algorithms were tested on a network constructed in the yeast Saccharomyces cerevisiae (S. cerevisiae) to resolve this issue. The network was a synthetic network of five genes regulating each other for the so-called in vivo reverse-engineering and modeling assessment (IRMA). The network was constructed in S. cereviase since it is a simple and well characterized organism. The synthetic network included a variety of regulatory interactions, thus capturing the behaviour of larger eukaryotic gene networks on a smaller scale. We derive a new set of algorithms by solving a nonlinear optimization problem and show how these algorithms outperform other algorithms on these datasets.

Keywords: Synthetic gene network, network identification, nonlinear modeling, optimization.

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Authors: F. Kovács, K. Kádár, G. Hosszú, Á. T. Balogh, T. Zsedrovits, N. Kersner, A. Nagy, Gy. Jeney

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The paper presents a novel screening method to indicate congenital heart diseases (CHD), which otherwise could remain undetected because of their low level. Therefore, not belonging to the high-risk population, the pregnancies are not subject to the regular fetal monitoring with ultrasound echocardiography. Based on the fact that CHD is a morphological defect of the heart causing turbulent blood flow, the turbulence appears as a murmur, which can be detected by fetal phonocardiography (fPCG). The proposed method applies measurements on the maternal abdomen and from the recorded sound signal a sophisticated processing determines the fetal heart murmur. The paper describes the problems and the additional advantages of the fPCG method including the possibility of measurements at home and its combination with the prescribed regular cardiotocographic (CTG) monitoring. The proposed screening process implemented on a telemedicine system provides an enhanced safety against hidden cardiac diseases.

Keywords: Cardiac murmurs, fetal phonocardiography, screening of CHDs, telemedicine system.

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Authors: Yoshifumi Sakamoto, Kouichi Ono, Takeo Nakada, Yousuke Kubo, Hiroto Yasuura

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This paper describes a system-level SoC energy consumption estimation method based on a dynamic behavior of embedded software in the early stages of the SoC development. A major problem of SOC development is development rework caused by unreliable energy consumption estimation at the early stages. The energy consumption of an SoC used in embedded systems is strongly affected by the dynamic behavior of the software. At the early stages of SoC development, modeling with a high level of abstraction is required for both the dynamic behavior of the software, and the behavior of the SoC. We estimate the energy consumption by a UML model-based simulation. The proposed method is applied for an actual embedded system in an MFP. The energy consumption estimation of the SoC is more accurate than conventional methods and this proposed method is promising to reduce the chance of development rework in the SoC development. ∈

Keywords: SoC, Embedded Sytem, Energy Consumption, Dynamic behavior, UML, Modeling, Model-based simulation

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Authors: D. O. Omondi, M. K. Walingo, G. M. Mbagaya, L. O. A. Othuon

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Understanding patient factors related to physical activity behavior is important in the management of Type 2 Diabetes. This study applied the Theory of Planned Behavior model to understand physical activity behavior among sampled Type 2 diabetics in Kenya. The study was conducted within the diabetic clinic at Kisii Level 5 Hospital and adopted sequential mixed methods design beginning with qualitative phase and ending with quantitative phase. Qualitative data was analyzed using grounded theory analysis method. Structural equation modeling using maximum likelihood was used to analyze quantitative data. The common fit indices revealed that the theory of planned behavior fitted the data acceptably well among the Type 2 diabetes and within physical activity behavior {¤ç2 = 213, df = 84, n=230, p = .061, ¤ç2/df = 2.53; TLI = .97; CFI =.96; RMSEA (90CI) = .073(.029, .08)}. This theory proved to be useful in understanding physical activity behavior among Type 2 diabetics.

Keywords: Physical activity, Theory of Planned Behavior, Type2 diabetes, Kenya.

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Authors: Akhilesh Khapre, Basudeb Munshi

Abstract:

A computational fluid dynamics simulation is done for non-Newtonian fluid in a baffled stirred tank. The CMC solution is taken as non-Newtonian shear thinning fluid for simulation. The Reynolds Average Navier Stocks equation with steady state multi reference frame approach is used to simulate flow in the stirred tank. The turbulent flow field is modelled using realizable k-ε turbulence model. The simulated velocity profiles of Rushton turbine is validated with literature data. Then, the simulated flow field of CD-6 impeller is compared with the Rushton turbine. The flow field generated by CD-6 impeller is less in magnitude than the Rushton turbine. The impeller global parameter, power number and flow number, and entropy generation due to viscous dissipation rate is also reported.

Keywords: Computational fluid dynamics, non-Newtonian, Rushton turbine, CD-6 impeller, power number, flow number, viscous dissipation rate.

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Authors: Han-Taw Chen, Tzu-Hsiang Lin, Chung-Hou Lai

Abstract:

The present study applies the inverse method and three-dimensional CFD commercial software in conjunction with the experimental temperature data to investigate the heat transfer and fluid flow characteristics of the plate-fin heat sink in a rectangular closed enclosure. The inverse method with the finite difference method and the experimental temperature data is applied to determine the approximate heat transfer coefficient. Later, based on the obtained results, the zero-equation turbulence model is used to obtain the heat transfer and fluid flow characteristics between two fins. T0 validate the accuracy of the results obtained, the comparison of the heat transfer coefficient is made. The obtained temperature at selected measurement locations of the fin is also compared with experimental data. The effect of the height of the rectangular enclosure on the obtained results is discussed.

Keywords: Inverse method, FLUENT, Plate-fin heat sink, Heat transfer characteristics.

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Authors: Jonathan H. Perez, Fumihiko Tanaka, Daisuke Hamanaka, Toshitaka Uchino

Abstract:

A finite element analysis was conducted to determine the effect of moisture diffusion and hygroscopic swelling in rice. A parallel simple stochastic modeling was performed to predict the number of grains cracked as a result of moisture absorption and hygroscopic swelling. Rice grains were soaked in thermally (25 oC) controlled water and then tested for compressive stress. The destructive compressive stress tests revealed through compressive stress calculation that the peak force required to cause cracking in grains soaked in water reduced with time as soaking duration was extended. Results of the experiment showed that several grains had their value of the predicted compressive stress below the von Mises stress and were interpreted as grains which become cracked and/or broke during soaking. The technique developed in this experiment will facilitate the approximation of the number of grains which will crack during soaking.

Keywords: Cracking, Finite element analysis, hygroscopic swelling, moisture diffusion, von Mises stress.

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Authors: Kourosh Nazarian

Abstract:

Many of the engineering materials, such as behavioral metals, have at least a certain level of linear behavior. It means that if the stresses are doubled, the deformations would be also doubled. In fact, these materials have linear elastic properties. Soils do not follow this law, for example, when compressed, soils become gradually tighter. On the surface of the ground, the sand can be easily deformed with a finger, but in high compressive stresses, they gain considerable hardness and strength. This is mainly due to the increase in the forces among the separate particles. Creeps also deform the soils under a constant load over time. Clay and peat soils have creep behavior. As a result of this phenomenon, structures constructed on such soils will continue their collapse over time. In this paper, the researchers analyzed and modeled the stresses and creeps in the southern plains of Kerman province in Iran through library-documentary, quantitative and software techniques, and field survey. The results of the modeling showed that these plains experienced severe stresses and had a collapse of about 26 cm in the last 15 years and also creep evidence was discovered in an area with a gradient of 3-6 degrees.

Keywords: Stress, creep, surface runoff.

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Authors: S. Alih, A. Khelil

Abstract:

In the present work, behavior of inoxydable steel as reinforcement bar in composite concrete is being investigated. The bar-concrete adherence in reinforced concrete (RC) beam is studied and focus is made on the tension stiffening parameter. This study highlighted an approach to observe this interaction behavior in bending test instead of direct tension as per reported in many references. The approach resembles actual loading condition of the structural RC beam. The tension stiffening properties are then applied to numerical finite element analysis (FEA) to verify their correlation with laboratory results. Comparison with laboratory shows a good correlation between the two. The experimental settings is able to determine tension stiffening parameters in RC beam and the modeling strategies made in ABAQUS can closely represent the actual condition. Tension stiffening model used can represent the interaction properties between inoxydable steel and concrete.

Keywords: Inoxydable steel, Finite element modeling, Reinforced concrete beam, Tension-stiffening.

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Authors: A. Belayadi, A. Mougari, L. Ait-Gougam, F. Mekideche-Chafa

Abstract:

The artificial neural network is one of the interesting techniques that have been advantageously used to deal with modeling problems. In this study, the computing with artificial neural network (CANN) is proposed. The model is applied to modulate the information processing of one-dimensional task. We aim to integrate a new method which is based on a new coding approach of generating the input-output mapping. The latter is based on increasing the neuron unit in the last layer. Accordingly, to show the efficiency of the approach under study, a comparison is made between the proposed method of generating the input-output set and the conventional method. The results illustrated that the increasing of the neuron units, in the last layer, allows to find the optimal network’s parameters that fit with the mapping data. Moreover, it permits to decrease the training time, during the computation process, which avoids the use of computers with high memory usage.

Keywords: Neural network computing, information processing, input-output mapping, training time, computers with high memory.

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Authors: Christhu Raj M. R., Rajeev Sukumaran

Abstract:

Underwater acoustic networks have attracted great attention in the last few years because of its numerous applications. High data rate can be achieved by efficiently modeling the physical layer in the network protocol stack. In Acoustic medium, propagation speed of the acoustic waves is dependent on many parameters such as temperature, salinity, density, and depth. Acoustic propagation speed cannot be modeled using standard empirical formulas such as Urick and Thorp descriptions. In this paper, we have modeled the acoustic channel using real time data of temperature, salinity, and speed of Bay of Bengal (Indian Coastal Region). We have modeled the acoustic channel by using Mackenzie speed equation and real time data obtained from National Institute of Oceanography and Technology. It is found that acoustic propagation speed varies between 1503 m/s to 1544 m/s as temperature and depth differs. The simulation results show that temperature, salinity, depth plays major role in acoustic propagation and data rate increases with appropriate data sets substituted in the simulated model.

Keywords: Underwater Acoustics, Mackenzie Speed Equation, Temperature, Salinity.

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Authors: Zhen Peng, Baifeng Wu

Abstract:

Modern computing technology enters the era of parallel computing with the trend of sustainable and scalable parallelism. Single Instruction Multiple Data (SIMD) is an important way to go along with the trend. It is able to gather more and more computing ability by increasing the number of processor cores without the need of modifying the program. Meanwhile, in the field of scientific computing and engineering design, many computation intensive applications are facing the challenge of increasingly large amount of data. Data parallel computing will be an important way to further improve the performance of these applications. In this paper, we take the accurate collision detection in building information modeling as an example. We demonstrate a model for constructing a data parallel algorithm. According to the model, a complex object is decomposed into the sets of simple objects; collision detection among complex objects is converted into those among simple objects. The resulting algorithm is a typical SIMD algorithm, and its advantages in parallelism and scalability is unparalleled in respect to the traditional algorithms.

Keywords: Data parallelism, collision detection, single instruction multiple data, building information modeling, continuous scalability.

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