Publication Date: 2021
Iranian Journal Of Fuzzy Systems (17350654)18(5)pp. 181-198
A novel strategy to design optimization is expressed using the fuzzy preference function concept. This method efficiently uses the designer’s experiences by preference functions and it is also able to transform a constrained multi-objective optimization problem into an unconstrained single-objective optimization problem. These two issues are the most important features of the proposed method which using them, you can achieve a more practical solution in less time. To implement the proposed method, two design optimizations of an unmanned aerial vehicle are considered which are: deterministic and non-deterministic optimizations. The optimization problem in this paper is a constrained multi-objective problem that with attention to the ability of genetic algorithm, this algorithm is selected as the optimizer. Uncertainties are considered and the Monte Carlo simulation (MCS) method is used for uncertainties modeling. The obtained results show a good performance of this technique in achieving optimal and robust solutions. © 2021, University of Sistan and Baluchestan. All rights reserved.
Motahar, S.,
Nikkam, N.,
Alemrajabi, A.A.,
Khodabandeh, R.,
Toprak, M.S.,
Muhammed, M. Publication Date: 2014
International Communications in Heat and Mass Transfer (07351933)56pp. 114-120
In this research, mesoporous silica (MPSiO2) nanoparticles were dispersed in n-octadecane as an organic phase change material (PCM) in order to produce a novel composite for thermal storage. Stable PCMs containing 1wt.%, 3wt.% and 5wt.% MPSiO2 nanoparticles (PCM/MPSiO2) were fabricated by dispersing MPSiO2 in PCM. MPSiO2 particles were investigated by SEM and TEM techniques, which showed high order of porosity and spherical particles of ca. 300nm. The thermal conductivity in both solid and liquid phases was measured by transient plane source (TPS) technique in the temperature range of 5-55°C. A maximum thermal conductivity enhancement of 5% for 3wt.% MPSiO2 at 5°C, and 6% for 5wt.% MPSiO2 at 55°C was experimentally obtained. Moreover, it was observed that enhancement in thermal conductivity is non-monotonic in solid phase with increasing MPSiO2 particle loading. The viscosity results showed that for mass fractions of nanoparticles greater than 3% in liquid PCM, the behavior of liquid is non-Newtonian. Also, the viscosity of PCM containing MPSiO2 nanoparticles was measured to be increased up to 60% compared to the liquid PCM for 5wt.% MPSiO2 at 35°C. © 2014.
Publication Date: 2023
International Journal of Advanced Manufacturing Technology (02683768)129(7-8)pp. 2949-2968
The mechanistic force model is one of the most common methods used to predict cutting forces in milling processes. In this model, the cutting forces are considered a function of cutting geometry and the material properties of the tool and workpiece, generally known as cutting coefficients. These coefficients are commonly identified by performing special calibration tests and are applied to predict cutting forces for other conditions. Although the mechanistic model is a powerful tool for predicting cutting forces, its accuracy decreases as the cutter-workpiece engagement geometry differs from the calibration tests. Thus, it is necessary to update the cutting coefficients to preserve the accuracy of the model. This paper proposes a real-time intelligent method, named “the mechanistic network,” for identifying and updating the cutting coefficients. To this end, an analogy between the mechanistic force model and artificial neural networks is identified, in which the weight coefficients of the artificial neural networks have been replaced with the cutting coefficients. To identify and update the cutting coefficients, an algorithm is proposed using stochastic gradient descent, which updates the coefficients in each iteration. In addition, some other important parameters in milling processes, such as the phase shift between the measured and predicted forces and run-out parameters, are calculated using stochastic gradient descent. The good performance of the proposed network is shown through case studies by utilizing reliable data existing in the literature and also by performing ball-end milling experimental tests. The results show that the proposed network can predict the cutting forces with an error of less than 10% and update the cutting coefficients with a calculation speed of 125k iterations per second. The robustness of the network against noise that may arise in real machining conditions is also shown. The proposed mechanistic network is a reliable and efficient tool that can be applied to real-time applications such as cyber-physical manufacturing systems and condition monitoring of machining processes. © 2023, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.
Publication Date: 2020
Proceedings of the Institution of Mechanical Engineers, Part N: Journal of Nanomaterials, Nanoengineering and Nanosystems (23977922)234(1-2)pp. 3-10
The two-dimensional nanostructures such as graphene, silicene, germanene, and stanene have attracted a lot of attention in recent years. Many studies have been done on graphene, but other two-dimensional structures have not yet been studied extensively. In this work, a molecular dynamics simulation of silicene was done and stress–strain curve of silicene was obtained. Then, the mechanical properties of silicene were investigated using the proposed structural molecular mechanics method. First, using the relations governing the force field and the Lifson–Wershel potential function and structural mechanics relations, the coefficients for the BEAM elements was determined, and a structural mechanics model for silicene was proposed. Then, a silicene sheet with 65 Å × 65 Å was modeled, and Young’s modulus of silicene was obtained. In addition, the natural frequencies and mode shapes of silicene were calculated using finite element method. The results are in good agreement with reports by other papers. © IMechE 2020.
Publication Date: 2019
International Journal of Geometric Methods in Modern Physics (17936977)16(6)
Microtubules (MTs), the intracellular structures, are made-up of polar polymers that are composed of α and β tubulins. The functions of MTs are shape the way for vesicles movement and asexual mitosis division. However, one of the main functions of MTs is stability of cells. Fewer geometrical methods are available in the literature to explore the molecular dynamics (MDs) of a MT, which is a difficult task due to its microscopic size and complex structure. A structural mechanics model with rather similar properties to MT can demonstrate the dynamics of MT. The first and most important step for this process is to obtain the interaction force between tubulins, and a mechanical model can be used to simulate the mechanical and dynamical properties of MTs by using meso-and macro-scale simulations. This work reports the interaction properties of β-α tubulin in MT. During this research, with the aid of the MD simulations, the interaction energy in β-α dimer is evaluated. The alpha-beta force-distance diagram is sketched with the aid of force and energy formulae. Thus, the graphical analysis supported the findings of this study. © 2019 World Scientific Publishing Company.
Publication Date: 2018
Chinese Journal of Aeronautics (10009361)31(12)pp. 2248-2259
This paper presents a Fuzzy Preference Function-based Robust Multidisciplinary Design Optimization (FPF-RMDO) methodology. This method is an effective approach to multidisciplinary systems, which can be used to designer experiences during the design optimization process by fuzzy preference functions. In this study, two optimizations are done for Predator MQ-1 Unmanned Aerial Vehicle (UAV): (A) deterministic optimization and (B) robust optimization. In both problems, minimization of takeoff weight and drag is considered as objective functions, which have been optimized using Non-dominated Sorting Genetic Algorithm (NSGA). In the robust design optimization, cruise altitude and velocity are considered as uncertainties that are modeled by the Monte Carlo Simulation (MCS) method. Aerodynamics, stability and control, mass properties, performance, and center of gravity are used for multidisciplinary analysis. Robust design optimization results show 46% and 42% robustness improvement for takeoff weight and cruise drag relative to optimal design respectively. © 2018 Chinese Society of Aeronautics and Astronautics
Publication Date: 2010
International Journal Of Thermodynamics (13019724)13(4)pp. 153-160
In this paper, an exergetic performance analysis of unglazed transpired collectors (UTC), as well as an exergetic optimization of a typical UTC is performed. A steady-state model is used to calculate heat transfers and pressure drop through the perforated plate and back wall. In order to maximize the exergy efficiency, the optimization procedure is carried out for some important parameters including plate hole diameter and hole pitch. A maximum efficieny of 2.28% is obtained. In spite of all the thermal performance advantages, the exergetic efficiency of the UTC is significantly lower than its energetic efficiency. Other parameters such as incident solar radiation, approach velocity, plate hole diameter and pitch are examined in the parametric study.
Publication Date: 2019
International Journal of Advanced Manufacturing Technology (02683768)102(5-8)pp. 1635-1657
This paper presents a new analytical model for calculating the cutter-workpiece engagement (CWE) boundaries in the ball-end finish milling process of curved surfaces. To this end, first, a quadratic mathematical representation considering the principal curvatures of the surface is employed to locally describe the workpiece surface around the instantaneous cutting region. This description, then, is utilized to find the intersection curves of the tool rotary and workpiece surfaces in three ball-end milling modes including slotting, first cutting, and following cutting. Through comparison studies, the model predictions are verified by the corresponding results obtained via solid modeling in computer-aided design (CAD) environment. The agreement between the results indicates that the model can accurately calculate the CWE boundaries in the ball-end milling of all inclined, convex, concave, and saddle surfaces. Good performance of the model is also demonstrated by comparing the computation time of the model with that of the z-map method. Finally, parametric studies are performed to reveal the effects of surface curvatures and cutting depth on the CWE region. The results show that the CWE is more affected by the surface curvatures as the cutting depth decreases, especially at the concave and saddle regions of the workpiece surface. The proposed analytical model is capable of calculating the CWE boundaries in both three-axis and five-axis milling processes, and there is no need to neither use any numerical solutions nor update the in-process workpiece geometry during the simulation of the CWE boundaries. © 2019, Springer-Verlag London Ltd., part of Springer Nature.
Publication Date: 2022
Optik (00304026)
This article presents a modified version of the WENO numerical method with an increased order of accuracy over critical points and higher resolution in detecting shock-turbulence interactions. The proposed method is an improved version of the WENO-η-Z scheme. The optimization is based on a new Global Smoothness Indicator definition that produces less numerical error at relative extremum points as an indicator of fluctuations in the flow field. Both 1-D and 2-D benchmark problems are implemented to verify the proposed scheme's accuracy. The convergence of the presented scheme is compared with that of a standard and optimal WENO-η-Z, in the linear wave transfer problem, which shows better convergence for the proposed method. The modified method's capability to detect discontinuity and shocks in the flow-field has been evaluated by solving two shock-tube problems, namely the Lax shock tube problem and Sod's problem. The proposed method's ability to detect fluctuations and disturbances in the flow-field in the presence of shocks has also been assessed in two problems, including the 1-D Shu-Osher shock-disturbance interaction and the 2-D shock-turbulence interaction. Improvements is observed in convergence and reduction in numerical errors in the proposed method compared to the standard WENO and WENO-η-Z method, whilst the capability to detect shocks has not reduced in the modified version. © 2022 Elsevier GmbH
Publication Date: 2023
Journal of Thermal Biology (18790992)112
An extensive algorithm based on both analytical and numerical solution methodologies is proposed to obtain transient temperature distributions in a three-dimensional living tissue subjected to a moving single-point and multi-point laser beam by considering metabolic heat generation and blood perfusion rate. Here, the dual-phase lag/Pennes equation is analytically solved by using the method of Fourier series and the Laplace transform. The ability to model single-point or multi-point laser beams as an arbitrary function of place and time is a significant advantage of the proposed analytical approach, which can be used to solve similar heat transfer problems in other living tissues. Besides, the related heat conduction problem is numerically solved based on the finite element method. The effects of laser beam transitional speed, laser power, and the number of laser points on the temperature distribution within the skin tissue are investigated. Moreover, the temperature distribution predicted by the dual-phase lag model is compared with that of the Pennes model under different working conditions. For the studied cases, it is observed that the maximum tissue temperature decreased about 63% by an increase of 6mm/s in the speed of the laser beam. An increase in the laser power from 0.8W/cm3 to 1.2W/cm3 results in a 28 °C increase in the maximum temperature of the skin tissue. It is observed that the maximum temperature predicted by the dual-phase lag model is always lower than that of the Pennes model and the temperature variations over time are sharper, while their results are entirely consistent over the simulation time. The obtained numerical results indicated that the dual-phase lag model is preferred in heating processes occurring at short intervals. Among the investigated parameters, the laser beam speed has the most considerable effect on the difference between the results of the Pennes and the dual-phase lag models. © 2022 Elsevier Ltd
Publication Date: 2021
Journal of Engineering Mathematics (15732703)131(1)
In the present study, the temporal and spatial variation of temperature in a three-dimensional triple-layer skin tissue under the laser heating is determined. Using the method of separation of variables along with the Laplace transform, the so-called Pennes bio-heat equation is analytically solved in a 3D triple-layer tissue in which each layer has its own thermo-physical properties. The laser heating of the skin, with both single and multiple laser beams, is modelled based on time-dependent Gaussian-shaped irradiance distributions with exponential axial attenuation. For the presented solution approach, it can be shown that the laser can be considered as an arbitrary function of time such as pulses with a specified time interval with each desired spatial distribution. Besides the analytical solution, the governing equations are solved numerically by using the standard finite element method and the results are compared with the analytical solution to investigate the effects of laser heating on human skin. The effects of using single and multiple-point laser beams on the temperature increment are investigated. A good agreement between both analytical and numerical solutions is observed. The obtained results indicate that a better temperature distribution in the skin tissue is obtained; whenever, a multi-point laser is employed. © 2021, The Author(s), under exclusive licence to Springer Nature B.V.
Publication Date: 2024
Proceedings of the Institution of Mechanical Engineers, Part N: Journal of Nanomaterials, Nanoengineering and Nanosystems (23977922)238(1-2)pp. 40-46
Nanocomposites have low weight and the improvement in properties is significant due to their nanostructure. Finding the properties of nanocomposites by experimental or computational methods is the priorities of researchers. Numerous studies on stress-strain behavior, strength, elastic-plastic behavior, bending, buckling, torsion, and other material behavior have been performed using the finite element method, which was reviewed in this study. In all the researches, the results obtained from the finite element method were in proper agreement with the experimental and analytical results. The use of the finite element method allows further studies on nanocomposites, which may not be possible in an experimental method or may require a lot of time and cost. In the following, a model of copper/CNT nanocomposite was studied using finite element method. The model was composed of a CNT in a box of pure copper. The stress contour and displacement contour of model was obtained and the results showed a 135% growth in nanocomposite Young’s module. © IMechE 2022.
Publication Date: 2021
International Journal of Energy Research (1099114X)45(10)pp. 15092-15109
The weak thermal conductance of a phase change material (PCM) can be intensified by dispersing nanostructured materials called nano-PCM. Accurate thermal conductivity (TC) prediction of nano-PCM is essential to evaluate heat transport during phase change processes, namely, melting and solidification. The present study develops an artificial neural network (ANN) to forecast the TC of n-octadecane as a PCM with dispersed oxide nanoparticles. A total of 122 experimental datasets from existing literature with a wide range of temperatures (5-60°C), nanoparticles (CuO, Al2O3, TiO2, and mesoporous SiO2), nanoparticle mass fractions (0.5-12 wt%) are compiled to train a multi-layered feed-forward ANN with Levenberg-Marquardt back-propagation algorithm. An optimal architecture of the neural network is acquired by varying the number of network hidden layers, the number of neurons in each layer, and the transfer function of layers. The minimum mean square error (MSE) of 1.3512 × 10−5 is obtained for the best developed ANN. Results show that average absolute deviation (AAD) of 0.002458, mean absolute percentage error (MAPE) of 0.8260%, and correlation coefficient (R) of 0.999964948 are achieved for training data. Moreover, MAPE, AAD, and R values are, respectively, 0.9478, 0.002167, and 0.9999715861 for testing data. The maximum percentage errors of ANN computed values are 2.31%, and 0.812% for liquid and solid phases, respectively. This indicates that the ANN model accurately predicts the enhanced TC of nano-PCM across various oxide nanoparticles, temperatures, and nanoparticle loadings. © 2021 John Wiley & Sons Ltd.
Publication Date: 2020
Sustainable Energy Technologies and Assessments (2213-1388)39
In this paper, an artificial neural network (ANN) is developed to assess hybrid photovoltaic thermal (PVT) systems for grid-connected (GC) electricity generation, space heating and domestic hot water providing in heating dominated regions of Iran. To do so, monthly and annual performance of a 5 kWp GCPVT system is simulated for a single-family house. The simulation results show that the GCPVT system is very promising whereas the annual yield factor varies from 1506 kWh/kWp to 1891 kWh/kWp. Also, an appropriate solar fractions for covering hot water are achieved in a range from 74.5% to 49.4%. A multilayered perceptron feed-forward neural network which is trained by Levenberg-Marquardt algorithm is used to predict AC electrical energy and solar thermal output of the GCPVT system. The developed ANN is based on global horizontal irradiance, ambient temperature, ambient relative humidity and wind speed as inputs. The proposed configuration of ANN presents a high accuracy in predicting output energy of the GCPVT system according to minimum mean square error and maximum correlation coefficient. Analysis of variance is performed to determine the significant control parameters influencing the output energy of the GCPVT system. © 2020 Elsevier Ltd
Publication Date: 2018
Materials Physics and Mechanics (16052730)40(2)pp. 304-312
Microtubules are filamentous intracellular structures that are responsible for various kinds of movements in all eukaryotic cells. The dynamic assembly and disassembly of microtubules and the mechanical properties of these polymers are essential for many key cellular processes such as spermatogenesis and the processes of neurons. Mathematical and computational modeling, especially coupled mechanochemical modeling, has contributed a lot to understand their dynamics. However, it has remained a great challenge to reduce the critical discrepancies, which exist between the experimental observations and modeling results. During this research, the small scaling parameter of the nonlocal Euler-Bernoulli beam theory is analyzed to demonstrate the free vibration problem of microtubules. © 2018, Institute of Problems of Mechanical Engineering RAS.
Publication Date: 2024
Journal of Materials Engineering and Performance (10599495)33(6)pp. 2616-2622
CMSX-4 nickel base superalloy is the second-generation alloy of this single crystal, which has improved its mechanical properties due to the lack of grain boundaries. According to the working conditions in using this superalloy, achieving less surface defects and lower surface roughness after the manufacturing process is very important. Therefore, the comparison of the surface of this superalloy after grinding, wire electro discharge machining (WEDM) and electrochemical machining (ECM) has been investigated by scanning electron microscope (SEM) and surface roughness. Surface roughness after WEDM, ECM and grinding are 3.337, 0.549, and 0.458 micro-meter, respectively. ECM and grinding processes are suitable from the point of view of surface roughness. On the other hand, in the SEM images after ECM, the defects caused by this process were not observed (compared to the other two processes). Besides, hardness after WEDM, ECM and grinding are 38.9, 39.7 and 40.1 HRC respectively. To conclude, the ECM process has desirable results and is a suitable alternative process for manufacturing parts with smooth surface and less surface defects. © ASM International 2023.
Publication Date: 2011
Micro and Nano Letters (17500443)6(6)pp. 402-404
Nanostructured thin film copper fabricated by electron beam-physical vapour deposition (EB-PVD) method has unique properties, which make it different from the other deposits. In this study, nanostructured copper deposits were produced by EB-PVD as well as pulse plating techniques. Transmission electron microscopy was used for investigating the morphology of the deposited film. Surface roughness of deposits was measured by DEKTAK profilometer. Furthermore, electrochemical impedance spectroscopy (EIS) and potentiodynamic polarisation methods were used to study the corrosive behaviour of the films. The surface morphology of corroded samples was obtained by scanning electron microscopy (SEM). Data obtained by polarisation, EIS and SEM suggested that corrosion resistance of EB-PVD deposit was higher than pulse plating deposit. This might be caused by its lower surface roughness and high purity owing to deposition in high vacuum. © 2011 The Institution of Engineering and Technology.
Publication Date: 2012
Journal Of Applied Fluid Mechanics (17353572)(3)
In this paper vorticity confinement parameters are successfully developed for compressible flows. The first new confinement parameter is proportional to spectral radii of the flux Jacobian matrix. Therefore, the confinement parameter implicitly contains the local conditions of the flow field. This new method is named as lambda vorticity confinement method. In order to gain confidence in the applicability of vorticity confinement, it would be ideal to completely eliminate constant coefficients from confinement parameters. Because these constant coefficients should be determined for every problem by trial and error and it takes a long time. In the next part of this paper, a suitable relation is introduced for the vorticity confinement parameter that doesn't need any constant coefficient. This new method is named as adaptive vorticity confinement method. Then the capability of these new methods is compared with the other vorticity confinement methods for solving shock-vortex interaction and three dimensional moving vortex problems.
Publication Date: 2011
International Review of Mechanical Engineering (19708734)(1)
The SCalar Dissipation Scheme (SCDS-1) and MAtrix Dissipation Scheme (MADS-1) are two common artificial dissipation schemes that have been used for several years. Two new artificial dissipation schemes are introduced by using the QUICK scheme in this paper (SCDS-2, MADS-2). The capability of these four artificial dissipation schemes is compared for two different problems. First for the channel flow problem and then for the moving vortex problem. The results of two problems show that the accuracy of these new artificial dissipation schemes (SCDS-2, MADS-2) are almost equal to two other schemes (SCDS-1, MADS-1). The implementation of the boundary conditions is more convenient in the new schemes. Also the new artificial dissipation schemes don't need any sensor. © 2011 Praise Worthy Prize S.r.l. - All rights reserved.
Publication Date: 2011
Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering (20413025)(8)
The conventional vorticity confinement methods have a constant confinement parameter that should be determined for every problem by trial and error. In this article, vorticity confinement parameters are successfully developed for compressible flows. The first new confinement parameter is proportional to spectral radii of the flux Jacobian matrix. Therefore, the confinement parameter implicitly contains the grid size and the other local fluid properties. In order to gain confidence in the applicability of vorticity confinement, it would be ideal to completely eliminate such constant parameters. In the next part of this article, a suitable relation is introduced for the vorticity confinement parameter that does not need any constant coefficient. The scalar dissipation scheme (SCDS-1) and matrix dissipation scheme (MADS-1) are two common artificial dissipation schemes that have been used for several years. Two new artificial dissipation schemes are introduced by using the QUICK scheme in this article (SCDS-2, MADS-2). The capabilities of these four artificial dissipation schemes are compared for channel flow problem. Then, the new confinement parameters and artificial dissipation schemes are used for solving moving vortex in a uniform flow and supersonic shear layer problems. The methods have been shown to be very effective at treating shock waves and vortex dominant flows. © Authors 2011.
Publication Date: 2016
Journal of Solid Mechanics (discontinued) (20087683)8(4)pp. 781-787
This work is conducted to obtain mechanical properties of microtubule. For this aim, interaction energy in alpha-beta, beta-alpha, alpha-alpha, and beta-beta dimers was calculated using the molecular dynamic simulation. Force-distance diagrams for these dimers were obtained using the relation between potential energy and force. Afterwards, instead of each tubulin, one sphere with 55 KDa weight connecting to another tubulin with a nonlinear connection such as nonlinear spring could be considered. The mechanical model of microtubule was used to calculate Young's modulus based on finite element method. Obtained Young's modulus has good agreement with previous works. Also, natural frequency of microtubules was calculated based on finite element method. © 2016 IAU, Arak Branch. All rights reserved.
Publication Date: 2018
Journal of Nano Research (16619897)55pp. 22-31
Graphene is a thin sheet with special properties and complicated mechanical behavior. It's important to study graphene experimentally and theoretically. Stone-Wales defects, cracks and atom vacancy are popular defects in carbon allotropes especially in graphene. In this paper, effect of center cracks on graphene was discussed. At first, mechanical properties of non-defected graphene sheet was obtained using molecular dynamics simulation. Comparing result with theoretical and experimental studies showing good agreements and proofing the results. Then, 8 different cracks were considered in center of graphene sheets. Stress-strain curves of defected graphene sheets with different tension strain rates were plotted. The results showed that increasing crack length lead to decreasing Young's modulus of graphene from 905GPa to 697GPa. Also, fracture occurred in less tensile strain. In the following, structural molecular mechanics method was used to simulate cracked graphene sheets. The results showed good agreement between two methods. © 2018 Trans Tech Publications, Switzerland.
Publication Date: 2022
Silicon (18769918)14(10)pp. 5527-5534
The mechanical properties of nanostructures are a researcher’s favorite topics. In the meantime, the mechanical and physical properties of the two dimensional structures and the nanotubes have attracted greater attention due to their wide application. Si (Si) nanotubes are structures consisting of Si atoms that are arranged as honeycombs. This structure has created some special properties in Si nanotubes. In this paper, Young’s modulus values and stress strain diagrams of Si nanotubes are investigated using molecular dynamics method and the Tersoff potential. Then, the changes effect of size and dimension was investigated for a closer look. For this purpose, the effect of nanotube diameter, length, and chirality shift from zigzag to armchair were studied. The results showed that the fracture stress of nanotube decreased with increasing the length of Si nanotube. It was also shown that the armchair structure was stronger than the zigzag. The effect of diameter change on the mechanical properties was also investigated and it was observed that no specific order could be found between the diameter changes with the Si nanotube strength. The results were in good agreement with other studies. © 2021, Springer Nature B.V.
Publication Date: 2021
International Communications in Heat and Mass Transfer (07351933)129
One of the most important properties of nanomaterials is their thermal conductivity, which is particularly needed by researchers in electronic equipment. In this research, the thermal conductivity properties of carbon nanotubes were first investigated. Next, the thermal conductivity of silicon nanotubes was investigated using the molecular dynamics method. For this purpose, five important effects were investigated: the effect of changing the potential function, the effect of changing the length of the heat bath region, the effect of changing the length, the effect of changing diameter, and the effect of changing the temperature of the nanotube. The results indicated that by changing the potential function, the thermal conductivity was decreased. Additionally, the result demonstrated that by increasing the length of the heat bath region, the thermal conductivity of silicon nanotubes was decreased, while in carbon nanotubes, the thermal conductivity was increased. Also, in both carbon nanotubes and silicon nanotubes, increasing temperature between 100 K and 300 K decreased kappa coefficient. On the other hand, increasing diameters, increased the kappa coefficient. Finally, as the length of the nanotubes was increased, no significant change was observed in the kappa coefficient of silicon nanotubes, while in carbon nanotubes, the kappa coefficient was increased. © 2021 Elsevier Ltd
Publication Date: 2018
Advances in Mechanical Engineering (16878132)10(12)
In this study, an investigation of “the free vibrations of hollow circular plates’’ is reported. The study is based on elastic foundation and the results depicted are further extended to study the special case of “graphene sheets.’’ The first-order shear deformation theory is applied to study the elastic properties of the material. A hollow circular sheet is modeled and the vibrations are simulated with the aid of finite element method. The results obtained are in good agreement with the theoretical findings. After the validation, a model of graphene is presented. Graphene contains a layer of honeycomb carbon atoms. Inside a layer, each carbon atom C is attached to three other carbon atoms and produces a sheet of hexagonal array. A 25 nm × 25 nm graphene sheet is modeled and simulated using the validated technique, that is, via the first-order shear deformation theory. The key findings of this study are the vibrational frequencies and vibrational mode shapes. © The Author(s) 2018.
Publication Date: 2012
Materials and Design (0264-1275)34pp. 603-608
Elastomers, particularly rubbers, are viscoelastic polymers with low Young's modulus. In this research, carbon nanotubes were used in the rubber and a rubber-carbon nanotube composite was modeled by ABAQUS™ software. Due to hyperelastic behavior of the rubber, strain function energy was used for the modeling. A sample of rubber was tested and uniaxial, biaxial, as well as planar test data obtained in these tests were used to get an energy function. Polynomial and reduced polynomial form are two common methods to achieve strain energy function. In this paper, elasticity modulus and Poisson ratio were measured for a representative volume element (RVE) of composite. Rubber was also considered as an elastic material and its composite properties in this state compared by hyperelastic rubber matrix assumption. ABAQUS was used to create a three dimensional finite element model of a single long wavy nanotube with diameter of D which perfectly bonded to matrix material. Nanotube waviness was modeled by sinusoidal carbon nanotube shape. Results showed that mechanical properties of the rubber will extremely change by adding carbon nanotube. Furthermore, several volume fractions of carbon nanotube in rubber were modeled and it was shown that stiffness of nanocomposite increases by more volume fraction of carbon nanotubes. © 2011 Elsevier Ltd.
