Effects of phase-lag on thermoelastic damping in micromechanical resonators

The present article attempts to investigate thermoelastic damping (TED) of a microbeam resonator by employing the three-phase-lag (TPL) thermoelasticity theory proposed by Roychoudhuri. An explicit formula of TED has been derived and the effects of the beam height, the phase-lag parameters on TED of the microbeam resonator have been studied. Effects of beam height and phase-lags on TED have been shown with the numerical results. A comparison of the results with the corresponding results of the theory of thermoelasticity of type GN-III is also presented. It has been observed that GN-III predicts a high-quality factor of the resonator’s sensitivity as compared to TPL model.     

Small-scale thermoelastic damping in micro-beams utilizing the modified couple stress theory and the dual-phase-lag heat conduction model

In this article, the size-dependent behavior of micro-beams with the thermoelastic damping (TED) phenomenon is studied. The coupled thermoelasticity equations are derived on the basis of the modified couple stress theory (MCST) and dual-phase-lag (DPL) heat conduction model. By solving these coupled equations simultaneously, a closed-form expression for the TED parameter in micro-beams is presented which considers the small-scale effects incorporation. Then, the effect of various parameters on TED in micro-beams, such as micro-beam height, the type of material, boundary conditions, and aspect ratio is investigated. The results show that the influence of utilizing non-classical continuum and thermoelasticity theories on the amount of TED and the critical thickness is significant in small scales.     

Analysis of the quality factor of micro-beam resonators based on heat conduction model with a single delay term

The present article investigates the quality factor of thermoelastic damping in micro-beam resonator from the standpoint of a very recent thermoelasticity theory proposed by Quintanilla (2011). In recent years, significant attention is being paid to micro- and nano-resonators due to their wide applications in micro- and nano-electromechanical systems (MEMS/NEMS). The quality performance of a micro-beam resonator is usually measured by the quality factor and thermoelastic damping is considered to be the most important intrinsic dissipative mechanism in micro and nanoscale devices. In the present article, we consider the heat conduction model with a single delay term given by Quintanilla (2011) and derive an expression for thermoelastic damping by applying complex frequency approach. The variation of thermoelastic damping versus normalized frequency and thickness of Silicon micro-beam resonator for different aspect ratios have been studied. We compare the results of present model with the corresponding results of thermoelasticity theories of type GN-III, three-phase-lag (TPL), and Lord-Shulman (LS) models and investigate that the new model with a single delay term (NMSDT) gives high Q-factor of the micro-beam resonator’s sensitivity in comparison to LS and TPL models and the results under this model have more similarity to the results of GN-III model.     

The phase change thermoelastic analysis of biological tissue with variable thermal properties during cryosurgery

Abstract

In this work, the coupling phase change heat transfer process and thermal stress behavior of biological tissue during cryosurgery are studied in the context of a generalized thermoelastic theory. The nonlinear governing equations are constructed while considering the variable thermal properties and solved by a time-domain finite element method based on the effective heat capacity formulation. A 2-D tumor and normal tissue model is adopted for simulating the freezing process in cryosurgery. The effects of temperature-dependent thermal properties and relaxation time on the responses of biological tissue are discussed and illustrated graphically.     

An analytical study of the PEM fuel cell with axial convection in the gas channel

A quasi two-dimensional mathematical model for a polymer electrolyte membrane (PEM) fuel cell is developed with consideration of axial convection in the gas channel and analytical solutions are obtained. A half-cell model which contains the cathode gas channel, gas diffuser, catalyst layer, and the membrane is investigated. To account for the effect of gas velocity in the gas channel, axial convection is included in the oxygen transport equation of the gas channel. Expressions for the oxygen mass fraction distribution in the gas channel, gas diffuser, and catalyst layer, and the current density and the membrane phase potential in the catalyst layer and membrane are derived. The solutions are presented in the form of infinite series. The polarization curve is also expressed as a function of the surface overpotential. Due to the advantage of the closed-form solutions this model can be easily employed as a diagnostic tool for PEM fuel cell simulations.     

Effect of variable viscosity and thermal conductivity on heat transfer in a circular porous passage with axial conduction

In this study, heat transfer in a circular porous passage with axial conduction and variable viscosity and thermal conductivity numerically has been investigated. Heat transfer for the different values of Da and Pe is investigated. The results found show that Nusselt distribution with variable viscosity does not significantly differ from that with constant viscosity in both thermally developing and fully developed regions. However, in the developing region there is a significant difference between Nusselt distribution with variable thermal conductivity and Nusselt distribution with constant thermal conductivity. In the fully developed region Nusselt distribution with variable and constant thermal conductivities does not drastically differ. © 2012 Wiley Periodicals, Inc. Heat Trans Asian Res; Published online in Wiley Online Library (wileyonlinelibrary.com/journal/htj). DOI 10.1002/htj.21028     

Fourier finite element model for prediction of thermal buckling in disc clutches and brakes

Numerical analyses are performed on thermal buckling of annular rings using a reduced Fourier method. The stress stiffness matrix is derived from the geometric nonlinearity in the Green strains with a predefined circumferential wave number. The method is first validated through the commercial software Abaqus using an axisymmetric model. It is then implemented to solve more general nonaxisymmetric problems with multiple waves along thecircumference. It is shown that there exists a particular wave number with which the buckling temperature reaches a minimum. This research has potential applications in automotive clutch and brake designs against thermal buckling.     

Clustering assisted artificial neural network for handling noisy big data: An application for estimation of parameter in combined mode conduction and radiation heat transfer

A pattern net assisted mapping artificial neural network (PAMANN) model for estimation of parameters in problem with large data (1300 × 121 matrix size) is reported. A pattern net-based multilayer perceptron neural network (MLPNN) model for clustering the data, followed by mapping MLPNN model for mapping the target with the input, is developed as PAMANN model. A heat transfer problem with combined mode conduction and radiation in porous medium is solved numerically, and is called direct model. In the inverse model, a PAMANN model is developed by using data generated through the direct model. The PAMANN model is able to estimate two parameters (extinction coefficient β and convective coupling P₂) after taking temperature profile as input. The model is tested for different number of neurons in hidden layer, and different levels of noise in input data. Twelve different algorithms are explored in training of mapping MLPNN, and compared for performance. Levenberg–Marquardt algorithm is found to estimate the parameters with high accuracy, but took high CPU time. Bayesian regularization is found to consume very high CPU time with moderate accuracy in estimation of parameters. Variations in hidden layer neuron number and noise in input data, were done to analyze the performance of mapping MLPNN with different training algorithms. Algorithms O-Step Secant, conjugate gradient with Polak-Ribiére updates, and conjugate gradient with Fletcher-Reeves updates are able to handle all variations of noise and number of neurons in hidden layer, with good accuracy of estimation and low CPU time consumption. Under high computational resource LM algorithm can be used for all cases. Up to 0.99132 value of regression coefficient is obtained in mapping MLPNN model with 15 hidden neurons, indicating the high accuracy of the model. With the help of PAMANN model, highly accurate (absolute error 1.78%) estimation of parameters is obtained. The model can handle upto 1% noise in input data, while giving accurate results.     

Significance of time-dependent magnetohydrodynamic transient free convective flow in vertical annuli: An analytical approach with the finite Hankel transform

An analytical study is accomplished by using the Finite Hankel Transform Technique for the variation of the temperature and the velocity profile with several nondimensional parameters. In this problem, an electrically conducting fluid has been considered in the vertical concentric annulus, with a perpendicular radial magnetic field. Furthermore, a closed and exact type of expression for the velocity and the temperature are received in the form of Bessel functions of both kinds (first and second). The impact of emerging parameters in this model, such as time, Hartmann number, Prandtl number, and the annular gap between the cylinders, is discussed through graphs, whereas the numerical values of the skin friction, mass flux, and the Nusselt number are given in the tabular form. As a consequence of this, it is detected that the velocity and temperature distributions are increasing continuously with an enhanced time scale. Eventually, it gains its steady state very quickly. Moreover, the impact of the Prandtl number and the Hartmann number leads to a decrease in the velocity profiles.     

An analytical model for the transverse permeability of gas diffusion layer with electrical double layer effects in proton exchange membrane fuel cells

An analytical model is presented for the transverse permeability of gas diffusion layer (GDL) based on an ordered array of parallel charged circular cylinders at the steady state. The formula of calculating the permeability of the transverse direction is given by solving the fluid momentum equation in a unit cell. In the present approach, the proposed model is explicitly related to the porosity and fiber radius of fibrous porous media, the zeta potential, and the physical properties of the electrolyte solution. Besides, the effects of these parameters (the porosity, unit cell aspect ratio, fiber radius, and molar concentration) on the transverse permeability are discussed detailedly. The model predictions are compared with the previous studies in the available literature, and good agreement is found.     

Interaction among competitive producers in the electricity market: An iterative market model for the strategic management of thermal power plants

The liberalization of the electricity sector requires utilities to develop sound operation strategies for their power plants. In this paper, attention is focused on the problem of optimizing the management of the thermal power plants belonging to a strategic producer that competes with other strategic companies and a set of smaller non-strategic ones in the day-ahead market. The market model suggested here determines an equilibrium condition over the selected period of analysis, in which no producer can increase profits by changing its supply offers given all rivals’ bids. Power plants technical and operating constraints are considered. An iterative procedure, based on the dynamic programming, is used to find the optimum production plans of each producer. Some combinations of power plants and number of producers are analyzed, to simulate for instance the decommissioning of old expensive power plants, the installation of new more efficient capacity, the severance of large dominant producers into smaller utilities, the access of new producers to the market. Their effect on power plants management, market equilibrium, electricity quantities traded and prices is discussed.     

A dynamic two-level artificial neural network for estimation of parameters in combined mode conduction-radiation heat transfer in porous medium: An application to handle huge dataset with noise

A dynamic two-level artificial neural network (DTLANN) approach is used for the estimation of parameters in combined mode conduction–radiation heat transfer in a porous medium. Four commonly used neural networks: feed forward, cascade forward, fitnet, and radial basis are used in mapping artificial neural network (ANN), and their performance is compared under noisy big data (10,302 × 1300 matrix size). Governing equations for heat transfer in the porous medium through conduction and radiation modes are solved by finite volume method and discrete transfer method. This numerical model is called a direct model. A large amount of data is generated by using the direct model for different values of extinction coefficient β and convective coupling P₂. These data were divided into different groups (class) based on the temperature difference between the gas and solid phase. In the inverse analysis, a new pair of temperature profiles for the solid and gas phase is taken as input and classified with the help of a pattern net artificial neural network model. On the basis of classification, data from that particular class and its neighbor class are used for training the mapping ANN model. After the training of the mapping ANN model, corresponding values of β and P₂ are obtained as output for any new input. This DTLANN model has a high regression coefficient (R) of .99131 and can predict highly accurate values of parameters under a huge dataset with noise, within much less CPU time.     

Efficiency and economic benefit of dark-fermentative biohydrogen production in Asian circular economies: Evaluation using soft-link methodology with data envelopment analysis (DEA) and computable general equilibrium model (CGE)

This study combines a data envelopment analysis, a dynamic computable general equilibrium model with estimated secondary material flows for circular economy, based on economist Joseph Schumpeter's macroeconomic theory, to develop a novel soft-link model to determine the efficiency of forty-three dark-fermentative technology of biohydrogen, and technology improvement impacts on biohydrogen output and supply price for six major emerging Asian countries. The integrated model is found to be feasible.This study finds that efficiency of continuous technology significantly exceeds that of batch technology. Biomass substrate concentration is the most important input in the generation of biohydrogen statistically; pH influences the efficiency of the batch technology, and the efficiency of continuous production technologies significantly exceeds that of batch technologies, but still have a gap to improve to full production efficiency for most of continuous technologies. India and China generate highest output growth of biohydrogen in baseline scenario. Japan and India can most benefit from improvements in batch and continuous biohydrogen production technology. The models and results of this study provides guidelines and references for decision-makers in industry and government who are responsible for reforming future energy policy.     

An evaluation of energy-environment-economic efficiency for EU,APEC and ASEAN countries: Design of a Target-Oriented DFM model with fixed factors in Data Envelopment Analysis

This paper aims to offer an advanced assessment methodology for sustainable national energy-environment-economic efficiency strategies, based on an extended Data Envelopment Analysis (DEA). The use of novel efficiency-improving approaches based on DEA originates from the so-called Distance Friction Minimisation (DFM) method. To design a feasible improvement strategy for low-efficiency DMUs, we develop here a Target-Oriented (TO) DFM model. However, in many real-world cases input factors may not be flexibly adjusted in the short run. In this study, we integrate the TO-DFM model with a fixed (inflexible) factor (FF) approach to cope with such more realistic circumstances. Super-efficiency DEA is next used in our comparative study on the efficiency assessment of energy-environment-economic targets for the EU, APEC and ASEAN (A&A) countries, employing appropriate data sets from the years 2003 to 2012. We consider two inputs (primary energy consumption and population) and two outputs (CO₂ and GDP), including a fixed input factor (viz. population). On the basis of our DEA analysis results, EU countries appear to exhibit generally a higher efficiency than A&A countries. The above-mentioned TO-DFM-FF projection model is able to address realistic circumstances and requirements in an operational sustainability strategy for efficiency improvement in inefficient countries in the A&A region.