Behavior of a Single-layer Latticed Cylinder Steel Shell with a Long Span under Wind Load

, M.Sc. Thesis Sharif University of Technology Daghestani, Shahrooz (Author) ; Khalu, Alireza (Supervisor)

Abstract

Single-layer steel grid shell structures are a good structural solution to new buildings by specific properties that are required by long-span structures and provide at the same time the opportunity to produce immense verity of design shapes and free form architecture; complex curved surfaces expect to be covered with low weight material. A grid shell is essentially a shell with its structure concentrated into individual linear element in relatively thin grid compared to the overall dimension of the grid shell. This research investigates single-layer grid structures with emphasis on design of load details. The application of single-layer for transparent structures enhances use of glazed...

Analysis of distribution of thrust, torque and efficiency of a constant chord, constant pitch C.R.P. fan by H.E.S. method

, Article World Academy of Science, Engineering and Technology ; Volume 79 , 2011 , Pages 546-550 ; 2010376X (ISSN) Abbaszadeh, M ; Nikpoorparizi, P ; Shahrooz, M ; Sharif University of Technology

2011

Abstract

For the first time since 1940 and presentation of theodorson's theory, distribution of thrust, torque and efficiency along the blade of a counter rotating propeller axial fan was studied with a novel method in this research. A constant chord, constant pitch symmetric fan was investigated with Reynolds Stress Turbulence method in this project and H.E.S. method was utilized to obtain distribution profiles from C.F.D. tests outcome. C.F.D. test results were validated by estimation from Playlic's analytical method. Final results proved ability of H.E.S. method to obtain distribution profiles from C.F.D test results and demonstrated interesting facts about effects of solidity and differences...

Graph Learning from Incomplete and Noisy Graph Signals

, M.Sc. Thesis Sharif University of Technology Daghestani, Amir Hossein (Author) ; Babaiezadeh, Masoud (Supervisor)

Abstract

The problem of inferring a graph from a set of graph signals over it plays a crucial role in the field of Graph Signal Processing (GSP). When provided with a graph that best models the structure of data, the GSP algorithms can offer high data processing capability. However, a meaningful graph of data is not always available, hence in some applications, the graph needs to be learned from the data itself. When the data is corrupted and missing, this task becomes even more challenging. In this paper, we present a graph learning algorithm that is capable of learning the underlying structure of data from an incomplete and noisy dataset of graph signals. We propose an algorithm that jointly...