Khaled Lotfy, Ibrahim S. Elshazly, Borhen Halouani, Praveen Ailawalia, Alaa A. El-Bary
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引用次数: 0
Abstract
This study introduces a generalized photothermal model to analyze the coupled thermo-hydromechanical behavior of a poroelastic, nonlocal semiconductor medium subjected to laser excitation. The medium is modeled as a saturated, dynamic, poroelastic half-space under time-harmonic loads, including thermal and mechanical forces and plasma electron distribution induced by laser pulses. A novel framework that integrates photo-thermoelasticity with hydrodynamic and poroelastic effects, capturing the nonlocal interactions at the nanoscale. At first, we subjected this medium to time-harmonic loads comprising thermal and normal loads and a distribution of plasma electrons applied with heating laser pulses. Afterward, we compared the photo-thermoelastic dynamic models to the coupled thermo-hydromechanical ones. The resulting nondimensional coupled equations were solved using two-dimensional normal mode analysis. The resulting nondimensional coupled equations were solved using two-dimensional normal mode analysis. The study examined the effects of nondimensional displacement, mechanical stress, excess pore water pressure, carrier concentration (density), and temperature distribution on the poroelastic half-space medium. Graphical representations were produced to highlight these effects based on specific parameters.
期刊介绍:
Archive of Applied Mechanics serves as a platform to communicate original research of scholarly value in all branches of theoretical and applied mechanics, i.e., in solid and fluid mechanics, dynamics and vibrations. It focuses on continuum mechanics in general, structural mechanics, biomechanics, micro- and nano-mechanics as well as hydrodynamics. In particular, the following topics are emphasised: thermodynamics of materials, material modeling, multi-physics, mechanical properties of materials, homogenisation, phase transitions, fracture and damage mechanics, vibration, wave propagation experimental mechanics as well as machine learning techniques in the context of applied mechanics.