Sharif Digital Repository

We have developed a fourth order compact finite volume method for the solution of low Mach number compressible flow equations on arbitrary nonuniform grids. The formulation presented here uses collocated grid that preserves fourth order accuracy on nonuniform meshes. This was achieved by introduction of a new fourth order method for calculation of cell and face averaged metrics. A special treatment of nonlinear terms is used to guarantee the stability of the fourth order compact method. Moreover an approach for applying this method to multi-block domains is presented for complicated geometries and parallel processing applications. Several test cases including the flow in a lid-driven cavity,... 

Here, an excellent superhydrophobic and highly oleophobic nanocomposite coating composed of fluoroethylene-vinyl ether (FEVE) resin as a matrix for modified SiO2 nanoparticles was synthesized on a stainless-steel wire mesh substrate via a facile sol-gel method. The surface morphology, microstructure, composition, and roughness of the coatings were investigated by field emission scanning electron microscopy (FESEM) equipped with energy-dispersive spectroscopy (EDS) and atomic force microscopy (AFM). The most efficient coating with superhydrophobicity and high oleophobicity feature indicates the water and oil repellency with contact angles (CAs) of 152° and 141°, respectively, with the high... 

Employing deep learning makes it possible to learn high-level features from raw data, resulting in more precise models. On the other hand, submodularity makes the solution scalable and provides the means to guarantee a lower bound for its performance. In this paper, a deep submodular network (DSN) is introduced, which is a deep network meeting submodularity characteristics. DSN lets modular and submodular features to participate in constructing a tailored model that fits the best with a problem. Various properties of DSN are examined and its learning method is presented. By proving that cost function used for learning process is a convex function, it is concluded that minimization can be... 

Abstractive multi-document summarization is a type of automatic text summarization. It obtains information from multiple documents and generates a human-like summary from them. In this paper, we propose an abstractive multi-document summarization method called HMSumm. The proposed method is a combination of extractive and abstractive summarization approaches. First, it constructs an extractive summary from multiple input documents, and then uses it to generate the abstractive summary. Redundant information, which is a global problem in multi-document summarization, is managed in the first step. Specifically, the determinantal point process (DPP) is used to deal with redundancy. This step... 

The increase in online text generation by humans and machines needs automatic text summarization systems. Recent research studies commonly use deep learning, besides sentence embedding and feature learning mechanisms, to find a solution for text summarization. But they ignore the fact that while finding the optimal solution for extractive text summarization is NP-hard, how do they ensure the quality of their solution? In our previous work, an extractive summarizer, called DSNSum, was proposed based on deep submodular network (DSN) that uses handcrafted features. It leverages submodularity to guarantee a minimum bound for performance. In this paper, submodular graph convolutional summarizer... 

Using an array of coupled oscillators, a novel broadband radar signalling scheme is introduced. It is shown that the collective output of the oscillator array is a flexible signal that can be matched to a target at a specific aspect. Also, a new robust algorithm based on eigenvectors of the correlation matrix is introduced, by which the generated signal can be matched to the target over a limited range of aspects. This capability is important, because radars are unable to estimate the aspect of a real target precisely. In this new approach to radar target identification, after estimation of the approximate aspect of an unknown target, a variety of waveforms matched to different potential... 

A new method of spatial filtering in high-order finite volume methods is presented and assessed. The base of this method is to filter face-averaged variables (fluxes) and then the recovery of cell-averaged ones. Two kinds of filtering method are proposed. The first kind is highly dissipative and appropriate for the numerical regions that need high dissipation, e.g. sponge zones. The second kind, on the other hand, is a precise method and hence is suitable for applying the high-order finite difference filters to the finite volume methods. Applying high-order finite difference filters directly to the high-order finite volume methods without using the proposed method causes stability problems... 

We theoretically study a Kitaev chain with a quasiperiodic potential, where the quasiperiodicity is introduced by a Fibonacci sequence. Based on an analysis of the Majorana zero-energy mode, we find the critical p-wave superconducting pairing potential separating a topological phase and a non-topological phase. The topological phase diagram with respect to Fibonacci potentials follow a self-similar fractal structure characterized by the box-counting dimension, which is an example of the interplay of fractal and topology like the Hofstadter's butterfly in quantum Hall insulators. © 2017 The Physical Society of Japan  

The main focus of this paper is to find an upgrade plan for a microgrid. This plan includes system lines' upgrades, the place, and size of the new capacitors and DERs. As usual, the planning process is begun with the load forecasting. The main objectives include minimization of system upgrade cost, loss cost, loss cost in peak load, and finally demand cost. The last objective is realized here using the tap changer of the main station transformer and reactive power support of the sources available or planned for the future of the grid. This is always referred to as the conservation of voltage reduction. In order to consider the effects of bus voltages on the system demand, the ZIP model for...