Sharif Digital Repository

Smart materials and structures are among the research fields that have been expanded significantly in recent years. At a glance, a smart structure consists of sensors and actuators in which the recorded data are used to control the structural response against the applied lateral loadings, utilizing a specific control algorithm. In this regard, the Piezo-electric materials are widely used both as sensors and actuators in smart structures. In this thesis, the dynamic behavior of a simply supported Euler-Bernoulli beam that beside the effect of moving load or mass is subjected to support excitation is evaluated and the dynamic response of its mid-span is determined. Then, an extensive... 

The purpose of this research is to investigate the capability of process-oriented modeling and deep learning for monitoring and forecasting the water quality of stratified lakes and to provide a unified framework integrating these two models to improve the monitoring and prediction of water quality. In this thesis, the process-oriented General Ocean Turbulence Model (GOTM) has been developed to simulate the hydrodynamic and thermodynamic processes of Gull Lake from 2008 to 2017. Subsequently, the MLP deep learning model has been employed to study the lake's key water quality indicators during this period. Meteorological data serves as input for the GOTM. Calibration and validation of the... 

Due to anthropogenic activities and climate change, Lake Urmia, one of the largest hypersaline lakes, is exposed to desiccating. The increase in salinity in this lake up to more than 400 p.s.u has endangered the ecology of this lake. In this study, a three-dimensional, unstructured grid and finite volume model FVCOM has been developed to investigate Lake Urmia's hydrodynamics, salinity, and water temperature over the year 2016. Some of the model inputs were lake bathymetry, meteorological data (including air temperature and pressure, wind speed and direction, short-wave and longwave radiation), precipitation, evaporation, river flux, salinity, and temperature. The model was calibrated... 

The advancement of technology in the semiconductor industry and the resulting increase in the number of transistors on a chip has led to an increase in the number of processing cores an increase in the number of processing cores in a system on chip (SoC). A surge in the number of processing cores, makes their communication more and more noteworthy. This communication is established through the network on chip (NoC). One of the main challenges in NoC design is power management, as it constitutes a high percentage of the overall power consumption of the chip. One of the most power-hungry components of NoC is the router. According to our observation, some of the components of the routers are... 

Wetlands are valuable ecosystems that have a wide variety of functions to protect biodiversity, natural, economic and social values. Hydrological changes and nutrient enrichment, resulting from population growth, economic development and climate change are threatening the wetlands. Recently, assessing spatial and temporal variations of water quality has become an important aspect of the physical and chemical characterization of aquatic environments. Anzali wetland is one of the international wetlands in Iran, located in the southern part of the Caspian Sea in Gilan province. This wetland has been exposed to many pollution sources including agricultural, industrial, and municipal wastewater... 

Considering the significant impact of salinity and temperature on the life of aquatic ecosystems, the growth of plants and animals, and the health of people; it is necessary to predict the spatiotemporal distribution of these qualitative characteristics in aquatic environments by using precise algorithms through hydrodynamic models. This research presents an improved algorithm for calculating qualitative characteristics of aquatic environments, such as salinity, during the wet/drying processes. The developed algorithm in this study has been incorporated into FVCOM which is a three-dimensional hydrodynamic model. The current algorithm governing the FVCOM model is not capable of accurately... 

The objective of this research is to enhance the accuracy of temperature and pressure variables derived from global meteorological models such as ERA5 using machine learning and deep learning (ML-DL) techniques. Since variables like temperature and pressure are critical metrics for various processes and decision-making in fields such as agriculture and limnology, and they serve as input variables in most hydrological, hydrodynamic, and meteorological models, accessing high-precision time series with appropriate temporal resolution is of great importance. Currently, global meteorological models like ERA5 provide relatively long time series of these variables on a grid with spatial resolutions... 

The problem of PM pollutants has become one of the main environmental concerns of Tehran city due to the growth of city population and industrialization. As a consequence of this problem there is an increasing trend in the number of unhealthy days in Tehran in terms of air quality in recent years. Solving this problem needs strict regulations to limit the amount of pollutants released from vehicles, industries and power plants. To help this cause, this study investigates the effect of emissions and climate change under RCP scenarios on future PM2.5 concentration in Tehran by using WRF-SMOKE-CMAQ modeling system. The result of simulation of climate conditions under RCP8.5 scenario in 2050... 

The relative lack of research concerning the potential impacts of climate change on different sectors in developing countries, especially the Middle Eastern countries, as the essential prerequisite of climate policy actions has made these countries the frontline against climate impacts. To fill this gap, in the first phase, we first analyzed spatial distributions and trends in thirty-seven hydro-climatic mean and extreme indices across Iran based on the state-of-the-art reanalysis datasets (ERA5-Land and AgERA5) at the county level from 1986 to 2015 using several nonparametric approaches such as multiple modified Mann-Kendall statistical tests and Sen’s Slope estimator. Their interannual... 

This research develops a probabilistic framework for evaluating community resilience subject to earthquake events by modeling the water distribution system and its prevailing inter- and intra-dependencies with other infrastructure systems of the community. This framework is entitled “Rtx,” which is under continuous development at the Center for Infrastructure Sustainability and Resilience Research (INSURER) at Sharif University of Technology, Tehran, Iran. It quantifies the community resilience by integrating hazard models, risk models, and recovery models within an agent-based simulation. Comprehensive modeling of the water distribution system requires a library of probabilistic models,... 

The present study aims to evaluate the flood risk of Poldokhtar city probabilistically using Monte Carlo Simulations (MCS). Two-dimensional (2D) models, which are highly accurate, have been used widely for flood modeling. However, they are not suitable for applications such as MCSs that need to be repeated many times or real-time flood forecasting applications, which require that flood inundation maps quickly be produced. In the current study, we developed a data-driven surrogate model based on the Least Squares Support Vector Machine (LS-SVM), a supervised machine learning method, to predict flood depth in order to simulate similar results to 2D hydraulic modeling. HEC-RAS was used for 2D... 

The aim of this research is to use data assimilation in hydrodynamic modeling of Lake Urmia, which is known as one of the world's hypersaline lakes. In other words, it is the first time that the development of a numerical model for Lake Urmia has been accompanied by data assimilation. In recent years, Lake Urmia has experienced unfavorable climatic conditions, resulting in a decline of over 8 meters in its water level over the past 20 years. Hydrodynamic analysis of the lake can play a crucial role in major management decisions for restoration of the lake ecosystem. In this project, the three-dimensional FVCOM model was used to perform numerical modeling, and efforts were made to improve... 

The purpose of this study is to investigate the resilience of the urban water supply network against earthquakes, A hydraulic analysis of the water supply network was implemented in Rtx software to study the effective parameters in the resilience of the network. Rtx software is a tool for assessing the reliability and resilience of communities and infrastructure to natural hazards by taking into account related uncertainties. The water supply network, like other networks, is affected by earthquakes. The seismic damage varies depending on the vulnerability of the network, the intensity of the earthquake, the focal depth, and the distance from the epicenter. Thus, it reduces the ability of the... 

In this study the kinetic modeling of visbreaking reactions of heavy oils was investigated using available experimental data from the literatures. The continuous lumping model was developed for kinetic analysis of visbreaking reactions. The normalized boiling point was used to describe the reactant mixture as a continuous mixture and the concentration distribution of the mixture would change under reaction conditions. The continuous model with five adjustable parameters was used to describe visbreaking reactions and these parameters were optimized for each feed and reaction temperatures in the range of 400 to 430ºC using the available experimental data. Therefore for a special feed in a... 

The kinetics of side reactions in dehydrogenation of propane over a supported platinum catalyst modified by tin was investigated. Catalytic dehydrogenation over a commercial Pt-Sn/γ-Al2O3 was carried out in a laboratory-scale plug-flow reactor at 580 to 620oC under atmospheric pressure. Several kinetic models derived from different reaction mechanisms were tested using experimental data obtained over a range of reaction conditions. It was found that the kinetics of the main dehydrogenation reaction was best described in terms of a Langmuir-Hinshelwood mechanism where adsorption of propane was the rate controlling step. Simple power low rate expressions were used to express the kinetics of... 

The traders exchange currencies in an online foreign exchange market (Forex), so they need to know ways help them to predict trend of market. There are some methods to forecast exchange rate based on experiment. However they can submit good signals, they are too late for exchange. Two things are important, they should be correct and on time. In this research, we try to submit a prediction by Adaptive Methods in which provides both of them. In first approach, we test 468 models of Artificial Neural Network to achieve the best; and in second approach, Genetic Algorithm and Swarm Intelligence are applied to training Artificial Neural Network. Finally, in addition to forecasting exchange rate,... 

Government intervention in markets may go beyond the market regulation. Interventions may cause some idiosyncratic price distortions. It means the relative prices of factors to become different among firms. Therefore, micro conditions for firms will be changed. These will result in misallocation of factor production between firms and change in manufacturing TFP. According to data from about 14000 medium and small industrial firms in Iran, removing misallocation of production factors (capital and energy) and output idiosyncratic distortions between industrial firms would result in 115 percent increase in manufacturing TFP.

 

In this research a monopolist is considered which its object is maximization of profit during a predetermined period. Optimal control theory is used as a tool for determining of optimal trend for control variables. Price, warranty length and production rate are considered as control variables and cumulative demand and production are considered as state variables. Learning effect in production side and demand side are entered in the model too. In the demand side, learning effect shows its influences with movement of market from diffusion phase to saturation phase. In diffusion phase the demanded quantity of productions increases by increase of cumulative demand, on the contrary in the... 

In this research, a new metaheuristic algorithm is developed for solving the Discrete Time- Resource Trade off Problem in the field of project scheduling.In this problem ,a project contains activities interrelated by finish-start type precedence constraints and each has a specified work content and can be performed in different combinations of duration and resource requirement.Since the problem is NP-hard , the Particle Swarm Optimization is adopted due to minimization of the makespan subject to precedence relations and a single renewable resource. Basically PSO is used to solve continous problems and discrete problems have just begun to be solved by the discrete PSO.In proposed method,a... 

Nanotechnology requires a number of infrastructures for reaching its sustainable development. For each step of its development , various infrastructures should be studied and prepared in advance.In this direction, by introducing and recognizing the priority of Iran Nanotechnology R&D indexes ,the present research is going to propose an effective help. In this case, after studying the related literature and gathering the needed data , 27 indexes were recognized. Then , the indexes were divided in 7 criteria.In order to find the priority of the applied indexes , Fuzzy Multiple Criteria Decision Making (FMCDM) was applied. As the weighting of 7 criteria had been found by FANP , the...