Sharif Digital Repository

The paper at hand intends to evaluate thermoelastic damping (TED) in circular plates by incorporating nonlocal effect within the constitutive and heat conduction frameworks. To attain this purpose, nonclassical coupled thermoelastic equations are established on the basis of nonlocal elasticity theory and Guyer–Krumhansl (GK) heat conduction model. By considering symmetric time–harmonic vibrations, the size-dependent thermoelastic frequency equation is derived. By solving this nonclassical eigenvalue problem, real and imaginary parts of damped natural frequency are separated. According to the definition of TED in the framework of complex frequency approach, a closed-form expression... 

In order to examine the impact of structural and thermal scale parameters on thermoelastic vibrations of Euler-Bernoulli nanobeams, this article intends to provide a size-dependent generalized thermoelasticity model with the help of nonlocal strain gradient theory (NSGT) in conjunction with dual-phase-lag (DPL) heat conduction model. To highlight the role of each scale parameter in size-dependent motion and heat conduction equations, normalized forms of these nonclassical coupled thermoelastic equations are extracted by introducing and exploiting some dimensionless parameters. By exploiting power series expansion as a general solution for arbitrary boundary conditions, system of partial... 

The wetting condition of the reservoir rock is the key to the success of any EOR technique and the ultimate oil recovery. Wettability is dictated by the surface chemistry related to the interactions between the fluids and the rock surface which determines the stability of the water film between the rock and the oil phase. Streaming potential measurement is one of the electrokinetic techniques used to determine the average zeta potential of porous rock which can provide reliable information on fluid-rock interaction and wettability state of the rock surface. Streaming potential measurement has recently been introduced in the oil reservoirs applications and there are still significant... 

We explore the dictionary learning problem for sparse representation when the signals are dependent. In this paper, a first-order Markovian model is considered for dependency of the signals, that has many applications especially in medical signals. It is shown that the considered dependency among the signals can degrade the performance of the existing dictionary learning algorithms. Hence, we propose a method using the Maximum Log-likelihood Estimator (MLE) and the Expectation Minimization (EM) algorithm to learn the dictionary from the signals generated under the first-order Markovian model. Simulation results show the efficiency of the proposed method in comparison with the... 

In this article, a size-dependent generalized thermoelasticity model is established to appraise the small-scale effect on thermoelastic vibrations of Euler-Bernoulli nanobeams. Small-scale effect on the structure and heat conduction is captured by exploiting nonlocal strain gradient theory (NSGT) and nonclassical heat conduction model of Guyer and Krumhansl (GK model). NSGT enables the model to account for both nonlocal and strain gradient effects on structure, and GK formulation empowers the model to incorporate both nonlocal and lagging effect into heat conduction equation. The normalized forms of size-dependent equations of motion and heat conduction are provided by introducing some...