Sharif Digital Repository

The phenomenon of soil liquefaction has caused significant damage to deep foundations of engineering structures such as bridges and buildings in past earthquakes. In recent years, many researchers have studied the effects of soil liquefaction on the pile response, but there are still many unknowns that require further research and study. The present study is part of a comprehensive research that involves several Ph.D. and master students at Sharif University of Technology (SUT). In this study, the effects of soil liquefaction on two pile 2×2 groups (one with a lumped mass and another without) in a level ground with a sloping bed were investigated. A surface non-liquefied layer was also... 

The parameters within the reactor core can be categorized into two distinct groups of measurable parameters and unmeasurable parameters. The determination of unmeasurable parameters, such as void fraction and critical heat flux, plays a pivotal and fundamental role in predicting the occurrence of accidents and emergency situations within the reactor. The utilization of deep neural networks represents one of the methods for accurately and reliably estimating these parameters within future temporal intervals. Such estimations facilitate the implementation of necessary measures to prevent accidents or mitigate their consequences. In this study, we employ three deep neural network models namely... 

Concrete dams are one of the most important infrastructures in any country. In recent years new safety standards, such as the analysis of concrete dams in various modes of potential failure or performance-based design are proposed. Many of existing dams may fail to meet revised safety criteria. For this reason it is necessary to control built dams with this new standards. In this reseach, fragility assessment is used for rational safety evalution and decision-making. fragility curves are defined by the probability of a structural limit. We examined the fragility curves for the nonlinear behavior and safety of the dam under earthquakes. fragility curves based on the cracking area are more... 

In finance literature there are different views of individual and institutional investors for variety of reasons. Despite having consensus on the difference of individual and institutional investors due to complexity and size, it seems there are much disagreement on how they affect the key process of market like return and liquidity. In this paper we consider the effect of individual and institutional trading on the short-term return of stocks. Specifically, first we define some factors to measure the trading activity of individual and institutional investors. Then we use these factors to sort each stock in the cross section to create decile portfolios and we compare the short-term return... 

In recent years, machine learning techniques have been available to predict and interpret the structural behavior of dams. The main goal of this research is to predict structural behavior through modeling with data read by accurate instruments of dams. This requires the selection of several machine learning methods such as Random Forests (RF), Boosted Regression Trees (BRT), Artificial Neural Networks (ANN), Support Vector Regression (SVR), and Decision Tree Regression (DTR) algorithms. In this research, considering the 24 target variables defined from the detailed instrumentations studied, the behavior of the dam is modeled using selected machine learning models. These precision instruments...