On thermomechanics of multilayered beams

Barretta, Raffaele; Čanađija, Marko; Sciarra, Francesco Marotti de

doi:10.1016/j.ijengsci.2020.103364

Cited by 27 publications

(10 citation statements)

References 68 publications

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“…Simple mechanical models and quite complex [50,51] nonlocal formulations can be found in the literature nowadays, making various claims concerning the nonlocality of nanoscopic structures, carbon nanotubes in particular. Static [52] and dynamic [53] problems in homogeneous and composite structures [54][55][56] are addressed for both isothermal and nonisothermal environments. The nonlocal mechanics in the above works is based on the stress and strain fields in the neighborhood of a point under consideration and is also related to the size-effects in nanoscopic structures.…”

Section: Remark 2 a Separate Line Of Research Based On Size Effects H...mentioning

confidence: 99%

Deep learning framework for carbon nanotubes: Mechanical properties and modeling strategies

Čanađija

2021

Carbon

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Tensile tests at room temperature are performed using molecular dynamics on all configurations of single-walled carbon nanotubes up to 4 nm in diameter. Distributions of the Young's modulus, Poisson's ratio, ultimate tensile strength and fracture strain are determined and reported. The results show that the chirality of the nanotube has the greatest influence on the properties. An artificial neural network is developed for the dataset obtained by molecular dynamics and used to predict the mechanical properties.It is clearly shown that Deep Learning provides accurate predictions, with the further advantage that thermal fluctuations are smoothed out. In addition, a through analysis of the effect of dataset size on prediction quality is performed, providing modeling strategies for further researchers.

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Section: Remark 2 a Separate Line Of Research Based On Size Effects H...mentioning

confidence: 99%

Deep learning framework for carbon nanotubes: Mechanical properties and modeling strategies

Čanađija

2021

Carbon

Self Cite

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“…where M T ¼ 12=h 3 R h=2 Àh=2 θðx,z,tÞzdz is the thermal moment, and I ¼ bh 3 =12 is the inertia moment of the cross section. When equation ( 18) is substituted in (16), we obtain…”

Section: Problem Formulationmentioning

confidence: 99%

“…Many researchers have considered the mechanism of heat transfer and microbeam vibration. [13][14][15][16][17][18][19][20][21][22] The inclusion of different field effects, such as temperature or initial stress field effects, also represents an important problem in the simulation of microstructures and microscale systems. Initial stress is generated in the medium due to various factors, resulting from a tightening phase, temperature difference, shot pinning, varieties of gravity, differential forces external, etc.…”

Section: Introductionmentioning

confidence: 99%

Viscoelastic stressed microbeam analysis based on Moore–Gibson–Thompson heat equation and laser excitation resting on Winkler foundation

Abouelregal

Ahmad

Badr

et al. 2021

Journal of Low Frequency Noise, Vibration and Active Control

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In this work, a modified viscoelastic model of initially stressed microbeam on the base of the Winkler foundation under the effect of ultrafast laser heating and axial stress has been proposed. Viscosity effects are taken into account following the Kelvin–Voigt model. The governing equation for the thermoelastic vibration of the microbeam is obtained when the thermal field effect is defined by the non-Fourier Moore–Gibson–Thompson (MGT) heat equation. The microbeam is seen as an Euler–Bernoulli beam that is exposed to varying sinusoidal heat. An analytical solution to the problem has been presented on the basis of the Laplace transform in addition to applying a numerical method to find inverse transformations. A numerical illustration is organized in the discussion section which discusses the impact of different effective parameters both on the vibrational behavior of a microbeam system and on the field variables. The viscous damping coefficient, laser pulse duration, and axial load greatly affect the deflection and temperature responses. The results obtained are verified and compared with the literature.

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“…When the distance between two objects is comparable to or less than the thermal wavelength, the photon tunneling effect plays an essential role in the thermal radiative transfer, greatly enhancing the near-field radiative heat transfer (NFRHT) past the Planckian blackbody limit by several orders of magnitude [1][2][3][4][5][6]. Numerous theoretical studies on the NFRHT between various materials and nanostructures have been performed, such as transfer between two planar surfaces [1,7,8], two nanoparticles [8,9], two gratings [10][11][12][13][14], one sphere and plane [15], three bodies [16], and so on [17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32]. Recently, many experimental reports have indicated that the NFRHT can exceed the blackbody limit for a plane-plane configuration [33][34][35][36][37][38].…”

Section: Introductionmentioning

confidence: 99%

Effective Approximation Method for Nanogratings-induced Near-Field Radiative Heat Transfer

et al. 2022

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Nanoscale radiative thermal transport between a pair of metamaterial gratings is studied within this work. The effective medium theory (EMT), a traditional method to calculate the near-field radiative heat transfer (NFRHT) between nanograting structures, does not account for the surface pattern effects of nanostructures. Here, we introduce the effective approximation NFRHT method that considers the effects of surface patterns on the NFRHT. Meanwhile, we calculate the heat flux between a pair of silica (SiO2) nanogratings with various separation distances, lateral displacements, and grating heights with respect to one another. Numerical calculations show that when compared with the EMT method, here the effective approximation method is more suitable for analyzing the NFRHT between a pair of relatively displaced nanogratings. Furthermore, it is demonstrated that compared with the result based on the EMT method, it is possible to realize an inverse heat flux trend with respect to the nanograting height between nanogratings without modifying the vacuum gap calculated by this effective approximation NFRHT method, which verifies that the NFRHT between the side faces of gratings greatly affects the NFRHT between a pair of nanogratings. By taking advantage of this effective approximation NFRHT method, the NFRHT in complex micro/nano-electromechanical devices can be accurately predicted and analyzed.

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On thermomechanics of multilayered beams

Cited by 27 publications

References 68 publications

Deep learning framework for carbon nanotubes: Mechanical properties and modeling strategies

Deep learning framework for carbon nanotubes: Mechanical properties and modeling strategies

Viscoelastic stressed microbeam analysis based on Moore–Gibson–Thompson heat equation and laser excitation resting on Winkler foundation

Effective Approximation Method for Nanogratings-induced Near-Field Radiative Heat Transfer

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