Distinctive features of thermoelastic dissipation in microbeam resonators at nanoscale

In this work, thermoelastic damping in microbeam resonators is evaluated using the generalized thermoelasticity theory based on the dual-phase-lagging thermal conduction model with relaxation between temperature increment and thermal expansion. An explicit formula of thermoelastic damping has been derived. Influences of various affecting factors on thermoelastic damping, such as the beam height, aspect ratio, and relaxation time between temperature increment and thermal expansion, are examined. Numerical results show that the thermoelastic damping, obtained by the generalized thermoelasticity theory in the present study, exhibits distinctive features at nanoscale. This work reveals that non-Fourier thermal conduction and relaxation between temperature increment and thermal expansion may play a nonnegligible role at nanometer scale.     

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.     

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.     

Evaluation of thermoelastic damping in micromechanical resonators with axial pretension: An analytical model accounting for two-dimensional thermal conduction

It has been reported that application of tensile axial stress can simultaneously increase quality factor and resonant frequency for micromechanical resonators. In this study, we formulate an analytical model for evaluating thermoelastic damping in micromechanical resonators based on the thermal energy method, in which thermal conductions in both thickness direction and axial direction are considered. An explicit expression for thermoelastic damping in the form of infinite series has been obtained. The proposed analytical model is further validated by finite element analysis. Results of the present study demonstrate that the 2D model needs to be adopted in order to accurately evaluate thermoelastic damping of micromechanical resonators with axial pretension. In addition, the 2D model proposed in the present study eliminates the inherent inconsistency entailed in the 1D model.     

Stress constrained thermo-elastic topology optimization based on stabilizing control schemes

Abstract

This article proposes two effective stabilizing control schemes for addressing the stress constrained thermo-elastic topology optimization in a non-uniform temperature field. Based on the density interpolation scheme, two linear elastic equations for coupling a thermo-elastic problem are considered. For comparison, different topology problem formulations for minimizing compliance or volume subject to stress constraints are solved. By virtue of a stabilization transform method, two stabilizing control schemes combined with the grouped aggregation method are developed to handle the challenging difficulties stemming from the local nature of highly nonlinear stress constraints. Moreover, the adjoint method is adopted to perform the sensitivity analysis. The design variables are updated by utilizing the method of moving asymptotes. The results of several typical numerical examples verify the validity of the proposed methodology, including the present stabilizing control schemes which can be employed to obtain clear topological design and fast convergence rate for thermo-elastic coupling problems. Meanwhile, compliance minimization design with stress constraints is appropriate to achieve balance between stress level and stiffness.     

Thermoelastic damping of graphene nanobeams by considering the size effects of nanostructure and heat conduction

Thermoelastic damping of nanobeams by considering the size effects of nanostructure and heat conduction is studied herein. The size effect of nanostructure is investigated based on Euler–Bernoulli beam assumptions in the framework of nonlocal strain gradient elasticity, and the size dependence of heat conduction is taken into account by incorporating phase-lagging and nonlocal effects. Closed-form solutions of thermoelastic damping and quality factor characterized by thermoelastic coupling are derived. Graphene nanoribbon is chosen as a nanobeam. The effects of relaxation time, aspect ratio, elastic modulus, thermal expansion, and thermal conductivity on quality factor of graphene nanobeams are discussed in detail.     

Optimization of wind turbine energy and power factor with an evolutionary computation algorithm

An evolutionary computation approach for optimization of power factor and power output of wind turbines is discussed. Data-mining algorithms capture the relationships among the power output, power factor, and controllable and non-controllable variables of a 1.5 MW wind turbine. An evolutionary strategy algorithm solves the data-derived optimization model and determines optimal control settings. Computational experience has demonstrated opportunities to improve the power factor and the power output by optimizing set points of blade pitch angle and generator torque. It is shown that the pitch angle and the generator torque can be controlled to maximize the energy capture from the wind and enhance the quality of the power produced by the wind turbine with a DFIG generator. These improvements are in the presence of reactive power remedies used in modern wind turbines. The concepts proposed in this paper are illustrated with the data collected at an industrial wind farm.     

Multi-objective approach in thermoenvironomic optimization of a benchmark cogeneration system

Multi-objective optimization for designing of a benchmark cogeneration system known as CGAM cogeneration system has been performed. In optimization approach, the exergetic, economic and environmental aspects have been considered, simultaneously. The thermodynamic modeling has been implemented comprehensively while economic analysis conducted in accordance with the total revenue requirement (TRR) method. The results for the single objective thermoeconomic optimization have been compared with the previous studies in optimization of CGAM problem. In multi-objective optimization of the CGAM problem, the three objective functions including the exergetic efficiency, total levelized cost rate of the system product and the cost rate of environmental impact have been considered. The environmental impact objective function has been defined and expressed in cost terms. This objective has been integrated with the thermoeconomic objective to form a new unique objective function known as a thermoenvironomic objective function. The thermoenvironomic objective has been minimized while the exergetic objective has been maximized. One of the most suitable optimization techniques developed using a particular class of search algorithms known as multi-objective evolutionary algorithms (MOEAs) has been considered here. This approach which is developed based on the genetic algorithm has been applied to find the set of Pareto optimal solutions with respect to the aforementioned objective functions. An example of decision-making has been presented and a final optimal solution has been introduced. The sensitivity of the solutions to the interest rate and the fuel cost has been studied.     

Decoupling optimization of integrated energy system based on energy quality character

Connections among multi-energy systems become increasingly closer with the extensive application of various energy equipment such as gas-fired power plants and electricity-driven gas compressor. Therefore, the integrated energy system has attracted much attention. This paper establishes a gas-electricity joint operation model, proposes a system evaluation index based on the energy quality character after considering the grade difference of the energy loss of the subsystem, and finds an optimal scheduling method for integrated energy systems. Besides, according to the typical load characteristics of commercial and residential users, the optimal scheduling analysis is applied to the integrated energy system composed of an IEEE 39 nodes power system and a 10 nodes natural gas system. The results prove the feasibility and effectiveness of the proposed method.     

A multiobjective optimization of a catalyst distribution in a methane/steam reforming reactor using a genetic algorithm

The presented research focuses on an optimization design of a catalyst distribution inside a small-scale methane/steam reforming reactor. A genetic algorithm was used for the multiobjective optimization, which included the search for an optimum of methane conversion rate and a minimum of the difference between highest and lowest temperatures in the reactor. For the sake of computational time, the maximal number of the segment with different catalyst densities was set to be thirty in this study. During the entire optimization process, every part of the reactor could be filled, either with a catalyst material or non-catalytic metallic foam. In both cases, the porosity and pore size was also specified. The impact of the porosity and pore size on the active reaction surface and permeability was incorporated using graph theory and three-dimensional digital material representation. Calculations start with the generation of a random set of possible reactors, each with a different catalyst distribution. The algorithm calls reforming simulation over each of the reactors, and after obtaining concentration and temperature fields, the algorithms calculated fitness function. The properties of the best reactors are combined to generate a new population of solutions. The procedure is repeated, and after meeting the coverage criteria, the optimal catalyst distribution was proposed. The paper is summarized with the optimal catalyst distribution for the given size and working conditions of the system.     

康达喷气叶栅喷气内腔体拓扑优化设计及试验研究

为了减小从康达喷气叶栅内部流出的喷气方向与叶栅主流方向的偏差,进一步提升康达喷气对流动分离的抑制效果,本文基于流体拓扑优化技术及布置导流肋的方法对康达喷气叶片原始喷气内腔结构进行优化设计。采用数值计算和高速风洞试验评估优化的喷气内腔结构对康达喷气叶栅气动性能的改善效果。结果表明：优化设计的带肋喷气内腔结构可以减小康达喷气与主流掺混的偏差角,叶片吸力面尾缘的流动分离区域进一步减小;在来流Ma为0.5、攻角为0°、1.25%喷气量下,采用带肋喷气内腔的康达喷气叶栅总压损失系数较采用原始喷气内腔结构降低了7.15%;采用带肋喷气内腔结构能够使叶栅在不同工况条件下的总压损失小于原始内腔结构,且在最佳喷气量下获得最小的总压损失系数。     

Optimal decision making in ventilation control

In this paper, a two-mode ventilation control of a single facility is formulated as a scheduling model over multiple time horizons. Using the CO₂ concentration as the major indoor air quality index and expected room occupancy schedule, optimal solutions leading to reduced CO₂ concentration and energy costs are obtained by solving the multi-objective optimization model formulated in the paper. A modified evolutionary strategy algorithm is used to solve the model at different time horizons. The optimized ventilation schedules result in energy savings and maintain an acceptable level of indoor CO₂ concentration.     

Thermodynamic optimization of heat‐transfer equipment configuration in an environmental control system

In this paper, we show that many features of a heat transfer installation can be deduced from the maximization of the global performance of the greater system that employs the installation. The heat transfer installation is a series of two cross‐flow heat exchangers. The greater system is the environmental control system (ECS) of an aircraft. The global performance objective is the minimization of the total thermodynamic irreversibility of the ECS. Several architectural features are deduced from principle: the relative position of the two heat exchangers, their relative sizes, and all the geometric aspect ratios of the two heat exchanger cores. We find that the optimized architecture is insensitive (robust) to changes in some of the external parameters. Robustness is a useful feature because it simplifies the design work. Furthermore, one design that is built can be expected to function at near‐optimal levels when the external parameters change. The application of this method of topology optimization to more complex systems is discussed. Copyright © 2001 John Wiley & Sons, Ltd.     

Multi-objective optimization of a hydrogen production through the HyS process powered by solar energy in different scenarios

Thermochemical or hybrid cycles powered by concentrated solar energy are a very promising way to produce an effective clean hydrogen through the water splitting, in terms of greenhouse gas (GHG) emissions and power production sustainability. SOL2HY2 is an European project focused on this goal. It deepens the so-called HyS process in a closed or partially open version using a proper SO₂ depolarized electrolyser, and moreover, it investigates key materials and process solutions, along the entire production chain. However, the identification of the best solution to obtain a suitable hydrogen in terms of cost, efficiency, availability of energy and material, sharing of renewable energy source, continuity of operation in different locations and plant sizes, poses many challenges in terms of flexibility and complexity of the system. In fact, it involves various chemical equipment, different solar and thermal storage technologies, and variable operative conditions with different reaction temperatures and mixture concentrations. Hence it arises the importance to have a tool for the investigation of this system.In this paper, data analysis and multi-objective techniques are used to study and optimize the process under consideration. Several mathematical methods have been exploited to make the best use of the available data, such as Design of Experiments techniques, meta-modeling strategies and genetic algorithms. All these methods have been implemented in the open source environments Scilab and R.     

A study of power quality loss in PV modules caused by wind induced vibration located in Vienna

Mechanical vibrations of a solar module mounting rack cause oscillations in the orientation of the module towards the sun. The resulting intensity oscillations of the incident light generate an a.c. current at the module’s terminals.We have investigated this effect in the laboratory by means of a vibration table and outdoors, where wind forces induce vibrations to the mounting rack. Although the collected results are specific and restricted to our experimental set up and the regional environmental situation we deduce that vibration induced current transients and oscillations of a solar module’s output most often will be the dominant origin of distortion in the low frequency regime.     

Multi-objective optimization in a finite time thermodynamic method for dish-Stirling by branch and bound method and MOPSO algorithm

There are various analyses for a solar system with the dish-Stirling technology. One of those analyses is the finite time thermodynamic analysis by which the total power of the system can be obtained by calculating the process time. In this study, the convection and radiation heat transfer losses from collector surface, the conduction heat transfer between hot and cold cylinders, and cold side heat exchanger have been considered. During this investigation, four objective functions have been optimized simultaneously, including power, efficiency, entropy, and economic factors. In addition to the four-objective optimization, three-objective, two-objective, and single-objective optimizations have been done on the dish-Stirling model. The algorithm of multi-objective particle swarm optimization (MOPSO) with post-expression of preferences is used for multi-objective optimizations while the branch and bound algorithm with pre-expression of preferences is used for single-objective and multi-objective optimizations. In the case of multi-objective optimizations with post-expression of preferences, Pareto optimal front are obtained, afterward by implementing the fuzzy, LINMAP, and TOPSIS decision making algorithms, the single optimum results can be achieved. The comparison of the results shows the benefits of MOPSO in optimizing dish Stirling finite time thermodynamic equations.     

A novel real‐time energy management strategy for plug‐in hybrid electric vehicles based on equivalence factor dynamic optimization method

The universal adaptive equivalent consumption minimization strategy (A‐ECMS) has the potential of being implemented in real‐time for plug‐in hybrid electric vehicles (PHEVs). However, the imprecise prediction of a long‐term future driving cycle and biggish computation burdens remain the barriers for further real vehicle application. Thus, it is of great significance to develop a real‐time optimal energy management strategy for PHEVs by weakening the influence of future driving cycle to the control accuracy and improving its computation efficiency. In this paper, a novel real‐time energy management strategy for PHEVs based on equivalence factor (EF) dynamic optimization method is proposed. Firstly, a novel proportional plus integral adaption law for calculating the dynamic optimal EF is established for A‐ECMS using only instantaneous information of current vehicle speed and battery state of charge. Second, three key coefficients are obtained and converted into a three‐dimensional look up tables, so as to determine the dynamic optimal EF. Finally, the method of fast searching the optimal engine torque is proposed, which significantly enhances the computational efficiency. Compared with A‐ECMS, the computational time of A‐ECMS2 is decreased near 94.8% and the deviation of fuel consumption is controlled within 4.4%. Both the numerical results and hardware‐in‐loop results prove that the proposed novel energy management strategy A‐ECMS2 has better real‐time performance and less computing burden than the general A‐ECMS.     

Improvement of the heat transfer quality by air cooling of three-heated obstacles in a horizontal channel using the lattice Boltzmann method

This study focuses on the cooling of three heated obstacles with different heights mounted on the bottom of the channel wall using different aspects that influence the enhancement of the heat exchange, as is known in the concept of cooling electronic devices. The lattice Boltzmann method associated with multiple relaxation times (LBM-MRT) was adopted to simulate the physical configurations of the studied system. In this context, the D2Q9 and D2Q5 models are applied to describe the fluid flow behavior and conjugate heat transfer, respectively. The evaluation of heat exchange between the cold fluid and three-heated obstacles has been accurately analyzed under the effect of several parameters such as Reynolds number, obstacle spacing, and thermal conductivity ratio. In addition, the setting of two and three fluids flow inlets were also studied. The results are presented in terms of streamlines, isotherms, and local Nusselt curves. The heat transfer increases with increasing solid-fluid thermal conductivity. It is also more pronounced for large Reynolds numbers. Moreover, the heat transfer significantly enhances for the second and third obstacles when obstacle spacing increases. The improvement of the heat transfer is performed by the implementation of several jet flows in the studied system.     

Simulation and optimization of hydrogen production by steam reforming of natural gas for refining and petrochemical demands in Lebanon

Steam reforming of natural gas produces the majority of the world's hydrogen (H₂) and it is considered as a cost-effective method from a product yield and energy consumption point of view. In this work, we present a simulation and an optimization study of an industrial natural gas steam reforming process by using Aspen HYSYS and MATLAB software. All the parameters were optimized to successfully run a complete process including the hydrogen production zone units (reformer reactor, high temperature gas shift reactor HTS and low temperature gas shift reactor LTS) and the purification zone units (absorber and methanator). Optimum production of hydrogen (87,404 MT/year) was obtained by fixing the temperatures in the reformer and the gas shift reactors (HTS & LTS) at 900 °C, 500 °C and 200 °C respectively while maintaining a pressure of 7 atm, and a steam to carbon ratio (S/C) of 4. Moreover, ~99% of the undesired CO₂ and CO gases were removed in the purification zone and a reduction of energy consumption of 77.5% was reached in the heating and cooling units of the process.