Search results for: lattice parameter
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2314

Search results for: lattice parameter

2224 MHD Stagnation Point Flow towards a Shrinking Sheet with Suction in an Upper-Convected Maxwell (UCM) Fluid

Authors: K. Jafar, R. Nazar, A. Ishak, I. Pop

Abstract:

The present analysis considers the steady stagnation point flow and heat transfer towards a permeable sheet in an upper-convected Maxwell (UCM) electrically conducting fluid, with a constant magnetic field applied in the transverse direction to flow, and a local heat generation within the boundary layer with a heat generation rate proportional to (T-T_inf)^p. Using a similarity transformation, the governing system of partial differential equations is first transformed into a system of ordinary differential equations, which is then solved numerically using a finite-difference scheme known as the Keller-box method. Numerical results are obtained for the flow and thermal fields for various values of the shrinking/stretching parameter lambda, the magnetic parameter M, the elastic parameter K, the Prandtl number Pr, the suction parameter s, the heat generation parameter Q, and the exponent p. The results indicate the existence of dual solutions for the shrinking sheet up to a critical value lambda_c whose value depends on the value of M, K, and s. In the presence of internal heat absorbtion (Q<0), the surface heat transfer rate decreases with increasing p but increases with parameter Q and s, when the sheet is either stretched or shrunk.

Keywords: magnetohydrodynamic (MHD), boundary layer flow, UCM fluid, stagnation point, shrinking sheet

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2223 Energy Saving Techniques for MIMO Decoders

Authors: Zhuofan Cheng, Qiongda Hu, Mohammed El-Hajjar, Basel Halak

Abstract:

Multiple-input multiple-output (MIMO) systems can allow significantly higher data rates compared to single-antenna-aided systems. They are expected to be a prominent part of the 5G communication standard. However, these decoders suffer from high power consumption. This work presents a design technique in order to improve the energy efficiency of MIMO systems; this facilitates their use in the next generation of battery-operated communication devices such as mobile phones and tablets. The proposed optimization approach consists of the use of low complexity lattice reduction algorithm in combination with an adaptive VLSI implementation. The proposed design has been realized and verified in 65nm technology. The results show that the proposed design is significantly more energy-efficient than conventional K-best MIMO systems.

Keywords: energy, lattice reduction, MIMO, VLSI

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2222 A New Conjugate Gradient Method with Guaranteed Descent

Authors: B. Sellami, M. Belloufi

Abstract:

Conjugate gradient methods are an important class of methods for unconstrained optimization, especially for large-scale problems. Recently, they have been much studied. In this paper, we propose a new two-parameter family of conjugate gradient methods for unconstrained optimization. The two-parameter family of methods not only includes the already existing three practical nonlinear conjugate gradient methods, but also has other family of conjugate gradient methods as subfamily. The two-parameter family of methods with the Wolfe line search is shown to ensure the descent property of each search direction. Some general convergence results are also established for the two-parameter family of methods. The numerical results show that this method is efficient for the given test problems. In addition, the methods related to this family are uniformly discussed.

Keywords: unconstrained optimization, conjugate gradient method, line search, global convergence

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2221 Parameter Estimation of Induction Motors by PSO Algorithm

Authors: A. Mohammadi, S. Asghari, M. Aien, M. Rashidinejad

Abstract:

After emergent of alternative current networks and their popularity, asynchronous motors became more widespread than other kinds of industrial motors. In order to control and run these motors efficiently, an accurate estimation of motor parameters is needed. There are different methods to obtain these parameters such as rotor locked test, no load test, DC test, analytical methods, and so on. The most common drawback of these methods is their inaccuracy in estimation of some motor parameters. In order to remove this concern, a novel method for parameter estimation of induction motors using particle swarm optimization (PSO) algorithm is proposed. In the proposed method, transient state of motor is used for parameter estimation. Comparison of the simulation results purtuined to the PSO algorithm with other available methods justifies the effectiveness of the proposed method.

Keywords: induction motor, motor parameter estimation, PSO algorithm, analytical method

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2220 2D Monte Carlo Simulation of Grain Growth under Transient Conditions

Authors: K. R. Phaneesh, Anirudh Bhat, G. Mukherjee, K. T. Kashyap

Abstract:

Extensive Monte Carlo Potts model simulations were performed on 2D square lattice to investigate the effects of simulated higher temperatures effects on grain growth kinetics. A range of simulation temperatures (KTs) were applied on a matrix of size 10002 with Q-state 64, dispersed with a wide range of second phase particles, ranging from 0.001 to 0.1, and then run to 100,000 Monte Carlo steps. The average grain size, the largest grain size and the grain growth exponent were evaluated for all particle fractions and simulated temperatures. After evaluating several growth parameters, the critical temperature for a square lattice, with eight nearest neighbors, was found to be KTs = 0.4.

Keywords: average grain size, critical temperature, grain growth exponent, Monte Carlo steps

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2219 Parameter Estimation via Metamodeling

Authors: Sergio Haram Sarmiento, Arcady Ponosov

Abstract:

Based on appropriate multivariate statistical methodology, we suggest a generic framework for efficient parameter estimation for ordinary differential equations and the corresponding nonlinear models. In this framework classical linear regression strategies is refined into a nonlinear regression by a locally linear modelling technique (known as metamodelling). The approach identifies those latent variables of the given model that accumulate most information about it among all approximations of the same dimension. The method is applied to several benchmark problems, in particular, to the so-called ”power-law systems”, being non-linear differential equations typically used in Biochemical System Theory.

Keywords: principal component analysis, generalized law of mass action, parameter estimation, metamodels

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2218 Numerical Modeling and Prediction of Nanoscale Transport Phenomena in Vertically Aligned Carbon Nanotube Catalyst Layers by the Lattice Boltzmann Simulation

Authors: Seungho Shin, Keunwoo Choi, Ali Akbar, Sukkee Um

Abstract:

In this study, the nanoscale transport properties and catalyst utilization of vertically aligned carbon nanotube (VACNT) catalyst layers are computationally predicted by the three-dimensional lattice Boltzmann simulation based on the quasi-random nanostructural model in pursuance of fuel cell catalyst performance improvement. A series of catalyst layers are randomly generated with statistical significance at the 95% confidence level to reflect the heterogeneity of the catalyst layer nanostructures. The nanoscale gas transport phenomena inside the catalyst layers are simulated by the D3Q19 (i.e., three-dimensional, 19 velocities) lattice Boltzmann method, and the corresponding mass transport characteristics are mathematically modeled in terms of structural properties. Considering the nanoscale reactant transport phenomena, a transport-based effective catalyst utilization factor is defined and statistically analyzed to determine the structure-transport influence on catalyst utilization. The tortuosity of the reactant mass transport path of VACNT catalyst layers is directly calculated from the streaklines. Subsequently, the corresponding effective mass diffusion coefficient is statistically predicted by applying the pre-estimated tortuosity factors to the Knudsen diffusion coefficient in the VACNT catalyst layers. The statistical estimation results clearly indicate that the morphological structures of VACNT catalyst layers reduce the tortuosity of reactant mass transport path when compared to conventional catalyst layer and significantly improve consequential effective mass diffusion coefficient of VACNT catalyst layer. Furthermore, catalyst utilization of the VACNT catalyst layer is substantially improved by enhanced mass diffusion and electric current paths despite the relatively poor interconnections of the ion transport paths.

Keywords: Lattice Boltzmann method, nano transport phenomena, polymer electrolyte fuel cells, vertically aligned carbon nanotube

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2217 New Estimation in Autoregressive Models with Exponential White Noise by Using Reversible Jump MCMC Algorithm

Authors: Suparman Suparman

Abstract:

A white noise in autoregressive (AR) model is often assumed to be normally distributed. In application, the white noise usually do not follows a normal distribution. This paper aims to estimate a parameter of AR model that has a exponential white noise. A Bayesian method is adopted. A prior distribution of the parameter of AR model is selected and then this prior distribution is combined with a likelihood function of data to get a posterior distribution. Based on this posterior distribution, a Bayesian estimator for the parameter of AR model is estimated. Because the order of AR model is considered a parameter, this Bayesian estimator cannot be explicitly calculated. To resolve this problem, a method of reversible jump Markov Chain Monte Carlo (MCMC) is adopted. A result is a estimation of the parameter AR model can be simultaneously calculated.

Keywords: autoregressive (AR) model, exponential white Noise, bayesian, reversible jump Markov Chain Monte Carlo (MCMC)

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2216 Effects of Roughness Elements on Heat Transfer During Natural Convection

Authors: M. Yousaf, S. Usman

Abstract:

The present study focused on the investigation of the effects of roughness elements on heat transfer during natural convection in a rectangular cavity using a numerical technique. Roughness elements were introduced on the bottom hot wall with a normalized amplitude (A*/H) of 0.1. Thermal and hydrodynamic behavior was studied using a computational method based on Lattice Boltzmann method (LBM). Numerical studies were performed for a laminar natural convection in the range of Rayleigh number (Ra) from 103 to 106 for a rectangular cavity of aspect ratio (L/H) 2 with a fluid of Prandtl number (Pr) 1.0. The presence of the sinusoidal roughness elements caused a minimum to the maximum decrease in the heat transfer as 7% to 17% respectively compared to the smooth enclosure. The results are presented for mean Nusselt number (Nu), isotherms, and streamlines.

Keywords: natural convection, Rayleigh number, surface roughness, Nusselt number, Lattice Boltzmann method

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2215 Seismic Analysis of Structurally Hybrid Wind Mill Tower

Authors: Atul K. Desai, Hemal J. Shah

Abstract:

The tall windmill towers are designed as monopole tower or lattice tower. In the present research, a 125-meter high hybrid tower which is a combination of lattice and monopole type is proposed. The response of hybrid tower is compared with conventional monopole tower. The towers were analyzed in finite element method software considering nonlinear seismic time history load. The synthetic seismic time history for different soil is derived using the SeismoARTIF software. From the present research, it is concluded that, in the hybrid tower, we are not getting resonance condition. The base shear is less in hybrid tower compared to monopole tower for different soil conditions.

Keywords: dynamic analysis, hybrid wind mill tower, resonance condition, synthetic time history

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2214 Parameter Estimation in Dynamical Systems Based on Latent Variables

Authors: Arcady Ponosov

Abstract:

A novel mathematical approach is suggested, which facilitates a compressed representation and efficient validation of parameter-rich ordinary differential equation models describing the dynamics of complex, especially biology-related, systems and which is based on identification of the system's latent variables. In particular, an efficient parameter estimation method for the compressed non-linear dynamical systems is developed. The method is applied to the so-called 'power-law systems' being non-linear differential equations typically used in Biochemical System Theory.

Keywords: generalized law of mass action, metamodels, principal components, synergetic systems

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2213 Adhesion Performance According to Lateral Reinforcement Method of Textile

Authors: Jungbhin You, Taekyun Kim, Jongho Park, Sungnam Hong, Sun-Kyu Park

Abstract:

Reinforced concrete has been mainly used in construction field because of excellent durability. However, it may lead to reduction of durability and safety due to corrosion of reinforcement steels according to damage of concrete surface. Recently, research of textile is ongoing to complement weakness of reinforced concrete. In previous research, only experiment of longitudinal length were performed. Therefore, in order to investigate the adhesion performance according to the lattice shape and the embedded length, the pull-out test was performed on the roving with parameter of the number of lateral reinforcement, the lateral reinforcement length and the lateral reinforcement spacing. As a result, the number of lateral reinforcement and the lateral reinforcement length did not significantly affect the load variation depending on the adhesion performance, and only the load analysis results according to the reinforcement spacing are affected.

Keywords: adhesion performance, lateral reinforcement, pull-out test, textile

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2212 Parameter Interactions in the Cumulative Prospect Theory: Fitting the Binary Choice Experiment Data

Authors: Elzbieta Babula, Juhyun Park

Abstract:

Tversky and Kahneman’s cumulative prospect theory assumes symmetric probability cumulation with regard to the reference point within decision weights. Theoretically, this model should be invariant under the change of the direction of probability cumulation. In the present study, this phenomenon is being investigated by creating a reference model that allows verifying the parameter interactions in the cumulative prospect theory specifications. The simultaneous parametric fitting of utility and weighting functions is applied to binary choice data from the experiment. The results show that the flexibility of the probability weighting function is a crucial characteristic allowing to prevent parameter interactions while estimating cumulative prospect theory.

Keywords: binary choice experiment, cumulative prospect theory, decision weights, parameter interactions

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2211 On Tarski’s Type Theorems for L-Fuzzy Isotone and L-Fuzzy Relatively Isotone Maps on L-Complete Propelattices

Authors: František Včelař, Zuzana Pátíková

Abstract:

Recently a new type of very general relational structures, the so called (L-)complete propelattices, was introduced. These significantly generalize complete lattices and completely lattice L-ordered sets, because they do not assume the technically very strong property of transitivity. For these structures also the main part of the original Tarski’s fixed point theorem holds for (L-fuzzy) isotone maps, i.e., the part which concerns the existence of fixed points and the structure of their set. In this paper, fundamental properties of (L-)complete propelattices are recalled and the so called L-fuzzy relatively isotone maps are introduced. For these maps it is proved that they also have fixed points in L-complete propelattices, even if their set does not have to be of an awaited analogous structure of a complete propelattice.

Keywords: fixed point, L-complete propelattice, L-fuzzy (relatively) isotone map, residuated lattice, transitivity

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2210 The Effect of Parameter Controls for Manure Composting in Waste Recycling Process

Authors: Junyoung Kim, Shangwha Cha, Soomee Kang, Jake S. Byun

Abstract:

This study shows the effect of parameter controls for livestock manure composting in waste recycling process for the development of a new design of a microorganism-oriented- composting system. Based on the preliminary studies, only the temperature control by changing mechanical mixing can reduce microorganisms’ biodegradability from 3 to 6 months to 15 days, saving the consumption of energy and manual labor. The final degree of fermentation in just 5 days of composting increased to ‘3’ comparing the compost standard level ‘4’ in Korea, others standards were all satisfied. This result shows that the controlling the optimum microorganism parameter using an ICT device connected to mixing condition can increase the effectiveness of fermentation system and reduce odor to nearly zero, and lead to upgrade the composting method than the conventional

Keywords: manure composting, odor removal, parameter control, waste recycling

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2209 Copper Doping for Enhancing Photocatalytic Efficiency of Barium Ferrite in Degradation of Atrazine under Visible Light

Authors: Tarek S. Jamil, H. A. Abbas, Rabab A. Nasr, Eman S. Mansor, Rose-Noëlle Vannier

Abstract:

The citrate manner (Pechini method) was utilized in elaboration of a novel Nano-sized BaFe(1-x)CuxO3 (x=0.01, 0.05 and 0.10). The prepared photocatalysts were characterized by x-ray diffraction, diffuse reflectance, TEM and the surface area. The prepared samples have a mixture of cubic perovskite structure (main) and orthorhombic phases. The effect of different loads of copper as dopant on the structural properties as well as the photocatalytic activity was demonstrated. The lattice parameter and the unit cell volume of the prepared materials are given. Doping with copper increased the photocatalytic activity of BaFeO3 several times in abstraction of hazardous atrazine that causes acute problems in drinking water treatment facilities. This may be reasoned to low band gap energy of copper doped BaFe(1-x)CuxO3 attributed to oxygen vacancies formation.

Keywords: photocatalysis, nano-sized, BaFeO3, copper doping, atrazine

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2208 Design of Ultra-Light and Ultra-Stiff Lattice Structure for Performance Improvement of Robotic Knee Exoskeleton

Authors: Bing Chen, Xiang Ni, Eric Li

Abstract:

With the population ageing, the number of patients suffering from chronic diseases is increasing, among which stroke is a high incidence for the elderly. In addition, there is a gradual increase in the number of patients with orthopedic or neurological conditions such as spinal cord injuries, nerve injuries, and other knee injuries. These diseases are chronic, with high recurrence and complications, and normal walking is difficult for such patients. Nowadays, robotic knee exoskeletons have been developed for individuals with knee impairments. However, the currently available robotic knee exoskeletons are generally developed with heavyweight, which makes the patients uncomfortable to wear, prone to wearing fatigue, shortening the wearing time, and reducing the efficiency of exoskeletons. Some lightweight materials, such as carbon fiber and titanium alloy, have been used for the development of robotic knee exoskeletons. However, this increases the cost of the exoskeletons. This paper illustrates the design of a new ultra-light and ultra-stiff truss type of lattice structure. The lattice structures are arranged in a fan shape, which can fit well with circular arc surfaces such as circular holes, and it can be utilized in the design of rods, brackets, and other parts of a robotic knee exoskeleton to reduce the weight. The metamaterial is formed by continuous arrangement and combination of small truss structure unit cells, which changes the diameter of the pillar section, geometrical size, and relative density of each unit cell. It can be made quickly through additive manufacturing techniques such as metal 3D printing. The unit cell of the truss structure is small, and the machined parts of the robotic knee exoskeleton, such as connectors, rods, and bearing brackets, can be filled and replaced by gradient arrangement and non-uniform distribution. Under the condition of satisfying the mechanical properties of the robotic knee exoskeleton, the weight of the exoskeleton is reduced, and hence, the patient’s wearing fatigue is relaxed, and the wearing time of the exoskeleton is increased. Thus, the efficiency and wearing comfort, and safety of the exoskeleton can be improved. In this paper, a brief description of the hardware design of the prototype of the robotic knee exoskeleton is first presented. Next, the design of the ultra-light and ultra-stiff truss type of lattice structures is proposed, and the mechanical analysis of the single-cell unit is performed by establishing the theoretical model. Additionally, simulations are performed to evaluate the maximum stress-bearing capacity and compressive performance of the uniform arrangement and gradient arrangement of the cells. Finally, the static analysis is performed for the cell-filled rod and the unmodified rod, respectively, and the simulation results demonstrate the effectiveness and feasibility of the designed ultra-light and ultra-stiff truss type of lattice structures. In future studies, experiments will be conducted to further evaluate the performance of the designed lattice structures.

Keywords: additive manufacturing, lattice structures, metamaterial, robotic knee exoskeleton

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2207 Torsional Vibration of Carbon Nanotubes via Nonlocal Gradient Theories

Authors: Mustafa Arda, Metin Aydogdu

Abstract:

Carbon nanotubes (CNTs) have many possible application areas because of their superior physical properties. Nonlocal Theory, which unlike the classical theories, includes the size dependency. Nonlocal Stress and Strain Gradient approaches can be used in nanoscale static and dynamic analysis. In the present study, torsional vibration of CNTs was investigated according to nonlocal stress and strain gradient theories. Effects of the small scale parameters to the non-dimensional frequency were obtained. Results were compared with the Molecular Dynamics Simulation and Lattice Dynamics. Strain Gradient Theory has shown more weakening effect on CNT according to the Stress Gradient Theory. Combination of both theories gives more acceptable results rather than the classical and stress or strain gradient theory according to Lattice Dynamics.

Keywords: torsional vibration, carbon nanotubes, nonlocal gradient theory, stress, strain

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2206 Lattice Boltzmann Simulation of Fluid Flow and Heat Transfer Through Porous Media by Means of Pore-Scale Approach: Effect of Obstacles Size and Arrangement on Tortuosity and Heat Transfer for a Porosity Degree

Authors: Annunziata D’Orazio, Arash Karimipour, Iman Moradi

Abstract:

The size and arrangement of the obstacles in the porous media has an influential effect on the fluid flow and heat transfer, even in the same porosity. Regarding to this, in the present study, several different amounts of obstacles, in both regular and stagger arrangements, in the analogous porosity have been simulated through a channel. In order to compare the effect of stagger and regular arrangements, as well as different quantity of obstacles in the same porosity, on fluid flow and heat transfer. In the present study, the Single Relaxation Time Lattice Boltzmann Method, with Bhatnagar-Gross-Ktook (BGK) approximation and D2Q9 model, is implemented for the numerical simulation. Also, the temperature field is modeled through a Double Distribution Function (DDF) approach. Results are presented in terms of velocity and temperature fields, streamlines, percentage of pressure drop and Nusselt number of the obstacles walls. Also, the correlation between tortuosity and Nusselt number of the obstacles walls, for both regular and staggered arrangements, has been proposed. On the other hand, the results illustrated that by increasing the amount of obstacles, as well as changing their arrangement from regular to staggered, in the same porosity, the rate of tortuosity and Nusselt number of the obstacles walls increased.

Keywords: lattice boltzmann method, heat transfer, porous media, pore-scale, porosity, tortuosity

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2205 First Principal Calculation of Structural, Elastic and Thermodynamic Properties of Yttrium-Copper Intermetallic Compound

Authors: Ammar Benamrani

Abstract:

This work investigates the equation of state parameters, elastic constants, and several other physical properties of (B2-type) Yttrium-Copper (YCu) rare earth intermetallic compound using the projected augmented wave (PAW) pseudopotentials method as implemented in the Quantum Espresso code. Using both the local density approximation (LDA) and the generalized gradient approximation (GGA), the finding of this research on the lattice parameter of YCu intermetallic compound agree very well with the experimental ones. The obtained results of the elastic constants and the Debye temperature are also in general in good agreement compared to the theoretical ones reported previously in literature. Furthermore, several thermodynamic properties of YCu intermetallic compound have been studied using quasi-harmonic approximations (QHA). The calculated data on the thermodynamic properties shows that the free energy and both isothermal and adiabatic bulk moduli decrease gradually with increasing of the temperature, while all other thermodynamic quantities increase with the temperature.

Keywords: Yttrium-Copper intermetallic compound, thermo_pw package, elastic constants, thermodynamic properties

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2204 Lattice Network Model for Calculation of Eddy Current Losses in a Solid Permanent Magnet

Authors: Jan Schmidt, Pierre Köhring

Abstract:

Permanently excited machines are set up with magnets that are made of highly energetic magnetic materials. Inherently, the permanent magnets warm up while the machine is operating. With an increasing temperature, the electromotive force and hence the degree of efficiency decrease. The reasons for this are slot harmonics and distorted armature currents arising from frequency inverter operation. To prevent or avoid demagnetizing of the permanent magnets it is necessary to ensure that the magnets do not excessively heat up. Demagnetizations of permanent magnets are irreversible and a breakdown of the electrical machine is inevitable. For the design of an electrical machine, the knowledge of the behavior of heating under operating conditions of the permanent magnet is of crucial importance. Therefore, a calculation model is presented with which the machine designer can easily calculate the eddy current losses in the magnetic material.

Keywords: analytical model, eddy current, losses, lattice network, permanent magnet

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2203 Effect of Radiation on MHD Mixed Convection Stagnation Point Flow towards a Vertical Plate in a Porous Medium with Convective Boundary Condition

Authors: H. Niranjan, S. Sivasankaran, Zailan Siri

Abstract:

This study investigates mixed convection heat transfer about a thin vertical plate in the presence of magnetohydrodynamic (MHD) and heat transfer effects in the porous medium. The fluid is assumed to be steady, laminar, incompressible and in two-dimensional flow. The nonlinear coupled parabolic partial differential equations governing the flow are transformed into the non-similar boundary layer equations, which are then solved numerically using the shooting method. The effects of the conjugate heat transfer parameter, the porous medium parameter, the permeability parameter, the mixed convection parameter, the magnetic parameter, and the thermal radiation on the velocity and temperature profiles as well as on the local skin friction and local heat transfer are presented and analyzed. The validity of the methodology and analysis is checked by comparing the results obtained for some specific cases with those available in the literature. The various parameters on local skin friction, heat and mass transfer rates are presented in tabular form.

Keywords: MHD, porous medium, soret/dufour, stagnation-point

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2202 Parameter Estimation for the Oral Minimal Model and Parameter Distinctions Between Obese and Non-obese Type 2 Diabetes

Authors: Manoja Rajalakshmi Aravindakshana, Devleena Ghosha, Chittaranjan Mandala, K. V. Venkateshb, Jit Sarkarc, Partha Chakrabartic, Sujay K. Maity

Abstract:

Oral Glucose Tolerance Test (OGTT) is the primary test used to diagnose type 2 diabetes mellitus (T2DM) in a clinical setting. Analysis of OGTT data using the Oral Minimal Model (OMM) along with the rate of appearance of ingested glucose (Ra) is performed to study differences in model parameters for control and T2DM groups. The differentiation of parameters of the model gives insight into the behaviour and physiology of T2DM. The model is also studied to find parameter differences among obese and non-obese T2DM subjects and the sensitive parameters were co-related to the known physiological findings. Sensitivity analysis is performed to understand changes in parameter values with model output and to support the findings, appropriate statistical tests are done. This seems to be the first preliminary application of the OMM with obesity as a distinguishing factor in understanding T2DM from estimated parameters of insulin-glucose model and relating the statistical differences in parameters to diabetes pathophysiology.

Keywords: oral minimal model, OGTT, obese and non-obese T2DM, mathematical modeling, parameter estimation

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2201 Identification of Impact Load and Partial System Parameters Using 1D-CNN

Authors: Xuewen Yu, Danhui Dan

Abstract:

The identification of impact load and some hard-to-obtain system parameters is crucial for the activities of analysis, validation, and evaluation in the engineering field. This paper proposes a method that utilizes neural networks based on 1D-CNN to identify the impact load and partial system parameters from measured responses. To this end, forward computations are conducted to provide datasets consisting of the triples (parameter θ, input u, output y). Then neural networks are trained to learn the mapping from input to output, fu|{θ} : y → u, as well as from input and output to parameter, fθ : (u, y) → θ. Afterward, feeding the trained neural networks the measured output response, the input impact load and system parameter can be calculated, respectively. The method is tested on two simulated examples and shows sound accuracy in estimating the impact load (waveform and location) and system parameters.

Keywords: convolutional neural network, impact load identification, system parameter identification, inverse problem

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2200 Multiscale Simulation of Ink Seepage into Fibrous Structures through a Mesoscopic Variational Model

Authors: Athmane Bakhta, Sebastien Leclaire, David Vidal, Francois Bertrand, Mohamed Cheriet

Abstract:

This work presents a new three-dimensional variational model proposed for the simulation of ink seepage into paper sheets at the fiber level. The model, inspired by the Hising model, takes into account a finite volume of ink and describes the system state through gravity, cohesion, and adhesion force interactions. At the mesoscopic scale, the paper substrate is modeled using a discretized fiber structure generated using a numerical deposition procedure. A modified Monte Carlo method is introduced for the simulation of the ink dynamics. Besides, a multiphase lattice Boltzmann method is suggested to fine-tune the mesoscopic variational model parameters, and it is shown that the ink seepage behaviors predicted by the proposed model can resemble those predicted by a method relying on first principles.

Keywords: fibrous media, lattice Boltzmann, modelling and simulation, Monte Carlo, variational model

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2199 An Estimating Parameter of the Mean in Normal Distribution by Maximum Likelihood, Bayes, and Markov Chain Monte Carlo Methods

Authors: Autcha Araveeporn

Abstract:

This paper is to compare the parameter estimation of the mean in normal distribution by Maximum Likelihood (ML), Bayes, and Markov Chain Monte Carlo (MCMC) methods. The ML estimator is estimated by the average of data, the Bayes method is considered from the prior distribution to estimate Bayes estimator, and MCMC estimator is approximated by Gibbs sampling from posterior distribution. These methods are also to estimate a parameter then the hypothesis testing is used to check a robustness of the estimators. Data are simulated from normal distribution with the true parameter of mean 2, and variance 4, 9, and 16 when the sample sizes is set as 10, 20, 30, and 50. From the results, it can be seen that the estimation of MLE, and MCMC are perceivably different from the true parameter when the sample size is 10 and 20 with variance 16. Furthermore, the Bayes estimator is estimated from the prior distribution when mean is 1, and variance is 12 which showed the significant difference in mean with variance 9 at the sample size 10 and 20.

Keywords: Bayes method, Markov chain Monte Carlo method, maximum likelihood method, normal distribution

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2198 The Role of Deformation Strain and Annealing Temperature on Grain Boundary Engineering and Texture Evolution of Haynes 230

Authors: Mohsen Sanayei, Jerzy Szpunar

Abstract:

The present study investigates the effects of deformation strain and annealing temperature on the formation of twin boundaries, deformation and recrystallization texture evolution and grain boundary networks and connectivity. The resulting microstructures were characterized using Electron Backscatter Diffraction (EBSD) and X-Ray Diffraction (XRD) both immediately following small amount of deformation and after short time annealing at high temperature to correlate the micro and macro texture evolution of these alloys. Furthermore, this study showed that the process of grain boundary engineering, consisting cycles of deformation and annealing, is found to substantially reduce the mass and size of random boundaries and increase the proportion of low Coincidence Site Lattice (CSL) grain boundaries.

Keywords: coincidence site lattice, grain boundary engineering, electron backscatter diffraction, texture, x-ray diffraction

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2197 Molecular Dynamics Simulation of Free Vibration of Graphene Sheets

Authors: Seyyed Feisal Asbaghian Namin, Reza Pilafkan, Mahmood Kaffash Irzarahimi

Abstract:

TThis paper considers vibration of single-layered graphene sheets using molecular dynamics (MD) and nonlocal elasticity theory. Based on the MD simulations, Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS), an open source software, is used to obtain fundamental frequencies. On the other hand, governing equations are derived using nonlocal elasticity and first order shear deformation theory (FSDT) and solved using generalized differential quadrature method (GDQ). The small-scale effect is applied in governing equations of motion by nonlocal parameter. The effect of different side lengths, boundary conditions and nonlocal parameter are inspected for aforementioned methods. Results are obtained from MD simulations is compared with those of the nonlocal elasticity theory to calculate appropriate values for the nonlocal parameter. The nonlocal parameter value is suggested for graphene sheets with various boundary conditions. Furthermore, it is shown that the nonlocal elasticity approach using classical plate theory (CLPT) assumptions overestimates the natural frequencies.

Keywords: graphene sheets, molecular dynamics simulations, fundamental frequencies, nonlocal elasticity theory, nonlocal parameter

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2196 InP Nanocrystals Core and Surface Electronic Structure from Ab Initio Calculations

Authors: Hamad R. Jappor, Zeyad Adnan Saleh, Mudar A. Abdulsattar

Abstract:

The ab initio restricted Hartree-Fock method is used to simulate the electronic structure of indium phosphide (InP) nanocrystals (NCs) (216-738 atoms) with sizes ranging up to about 2.5 nm in diameter. The calculations are divided into two parts, surface, and core. The oxygenated (001)-(1×1) facet that expands with larger sizes of nanocrystals is investigated to determine the rule of the surface in nanocrystals electronic structure. Results show that lattice constant and ionicity of the core part show decreasing order as nanocrystals grow up in size. The smallest investigated nanocrystal is 1.6% larger in lattice constant and 131.05% larger in ionicity than the converged value of largest investigated nanocrystal. Increasing nanocrystals size also resulted in an increase of core cohesive energy (absolute value), increase of core energy gap, and increase of core valence. The surface states are found mostly non-degenerated because of the effect of surface discontinuity and oxygen atoms. Valence bandwidth is wider on the surface due to splitting and oxygen atoms. The method also shows fluctuations in the converged energy gap, valence bandwidth and cohesive energy of core part of nanocrystals duo to shape variation. The present work suggests the addition of ionicity and lattice constant to the quantities that are affected by quantum confinement phenomenon. The method of the present model has threefold results; it can be used to approach the electronic structure of crystals bulk, surface, and nanocrystals.

Keywords: InP, nanocrystals core, ionicity, Hartree-Fock method, large unit cell

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2195 Electrochemical Performance of Al-Mn2O3 Based Electrode Materials

Authors: Noor Ul Ain Bhatti, M. Junaid Khan, Javed Ahmad, Murtaza Saleem, Shahid M. Ramay, Saadat A. Siddiqi

Abstract:

Manganese oxide is being recently used as electrode material for rechargeable batteries. In this study, Al incorporated Mn2O3 compositions were synthesized to study the effect of Al doping on electrochemical performance of host material. Structural studies were carried out using X-ray diffraction analysis to confirm the phase stability and explore the lattice parameters, crystallite size, lattice strain, density and cell volume. Morphology and composition were analyzed using field emission scanning electron microscope and energy dispersive X-ray spectroscopy, respectively. Dynamic light scattering analysis was performed to observe the average particle size of the compositions. FTIR measurements exhibit the O-Al-O and O-Mn-O and Al-O bonding and with increasing the concentration of Al, the vibrational peaks of Mn-O become sharper. An enhanced electrochemical performance was observed in compositions with higher Al content.

Keywords: Mn2O3, electrode materials, energy storage and conversion, electrochemical performance

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