Sharif Digital Repository

Physics-informed neural networks (PINNs) have received significant attention as a unified framework for forward, inverse, and surrogate modeling of problems governed by partial differential equations (PDEs). Training PINNs for forward problems, however, pose significant challenges, mainly because of the complex non-convex and multi-objective loss function. In this work, we present a PINN approach to solving the equations of coupled flow and deformation in porous media for both single-phase and multiphase flow. To this end, we construct the solution space using multi-layer neural networks. Due to the dynamics of the problem, we find that incorporating multiple differential relations into the... 

In this paper, the extended finite element method is presented for thermo-hydro-mechanical (THM) modeling of impermeable discontinuities in saturated porous media. The X-FEM technique is applied to the THM governing equations for the spatial discretization, followed by a generalized Newmark scheme for the time domain discretization. The displacement field is enriched by the Heaviside and crack tip asymptotic functions, and the pressure and temperature fields are enriched by the Heaviside and appropriate asymptotic functions. The process is accomplished by partitioning the domain with triangular sub-elements. Numerical examples are presented to demonstrate the capability of proposed technique... 

Network forensic analysts employ payload attribution systems (PAS) as an investigative tool, which enables them to store and summarize large amounts of network traffic, including full packet payload. Hence an investigator could query the system for a specific string and check whether any of the packets transmitted previously in the network contained that specific string. As a shortcoming, the previously proposed techniques are unable to support wildcard queries. Wildcards are an important type of query that allow the investigator to locate strings in the payload when only part of the string is known. In this paper, a new data structure for payload attribution, named Character Dependent... 

Static bandwidth allocation for variable bit rate (VBR) video traffic forfeits the available bandwidth. Prediction of the next frame size is thus useful in dynamic bandwidth allocation. It has been shown that VBR video traces are long-range dependent, which makes one-frame-ahead prediction insufficient for dynamic bandwidth allocation. Several studies have been conducted based on the linear autoregressive (AR) model to address VBR traffic prediction. In this paper, we propose the use of a nonlinear model from the AR family called logistic smooth transition autoregressive (LSTAR) to predict VBR video traffic. Furthermore, we introduce adaptive algorithms, including least mean square (LMS),... 

With the development of computing systems for data processing, the image processing and image analyzing methods have been developed on the basis of pixel assessment. These methods can analyze and detect the images by assigning a value for each pixel and using the matrices calculations. In the present research, two methods have been used to assess the simulated material microstructures. In the first method, the vertices of the microstructure are counted to determine accurately the mean grain size by the Euler's relationship, while in the second method, the image processing and image analyzing methods are utilized to assess the microstructure image. To verify the accuracies of the methods...