Sharif Digital Repository

Access to a reduced and fast mathematical model that can predict the input-output behavior of interconnected systems with acceptable accuracy and in a short time is crucial. The purpose of this project is to provide an object-oriented platform for identifying a model based on input-output data of interconnected systems in real-time. On this basis, in the case of developing fast estimation algorithms and updating the model quickly (in case of extensive changes in the system), good predictions of the model can be used for various applications. In this research, machine learning and data analysis methods are used to extract useful features and relations from data. Then, taken advantage of this... 

A mathematical model helps to understand any system with any level of complication, such as the human body. The heart, vascular system, and lungs are three important parts of each body that life is impossible without them. The performance of the cardiovascular and respiratory systems is tuned by a group of complex mechanisms which are called regulatory mechanisms. Therefore, a model which describes the behavior of these mechanisms has great importance. The goal of this research is to provide and simulate the newest and most complete model in this field. The presented model should consist of the heart, vascular system, lungs, respiratory system, gas exchange and transport, and finally... 

Monitoring of natural gas transmission networks, is one of the necessities for efficient, safe, and economical operation of energy supply networks. In order to efficiently control and monitor the operation of gas transmission network, various states of the network (like temperature, pressure, and flow) should be available. Among these states, some can be easily measured, and the rest should be estimated based on these measurements throughout the network. In this project, an algorithm to obtain near optimal locations of various measuring devices has been proposed. Furthermore, a method for estimation of the states of transmission network based on these measurements and Machine Learning has... 

Multi-vector energy (MVE) networks are one of the most complex systems which are attractive to many researchers. In this work, an integrated gas-power transmission network as an MVE network has been studied. The MVE benchmark used in this work comprises a gas transmission network, which is the core of the MVE, a power transmission network, and a Syn-Gas plant. The gas transmission network supplies the gas demands of its consumers. The main objective of this thesis is to design appropriate controllers to maintain the states of the gas network in its desired condition. Since the gas network is distributed parameter system and its model is an infinite dimensional state space, it is either... 

Gas transmission networks play an important role in multi-vector energy networks. Therefore, reliable and efficient control of gas transmission networks with the minimum energy consumption is utmost task and is still an active research area. This work, introduces a distributed, model-free, and game-theoretic approach comprising a simultaneous game followed by a sequential game, to achieve the control objectives in gas transmission networks. The cooperative game approach is adopted for this purpose. In the proposed method two fuzzy inference systems have been used to obtain the payoff of each player in the game of gas transmission network control, the first one has been used to determine the... 

Gas transmission networks, as one of the most important energy transport networks, are used to transport gas from production facilities to major gas consumers. These networks possess very complex behavior due to their severely nonlinear equations, their temporal and spatial broadness, the compressibility feature of the fluid that passes through them, and their relationship and interdependency with other energy material generation, transportation, and distribution infrastructures through multi-vector energy systems. Hence, the management and coordination of these networks are challenging. In this regard, the most demanding problem of such networks is their expansion planning due to the... 

Digital analysis of reservoir rocks prepares a powerful tool in the field of porous media studies and provides appropriate information of single / multiphase flows by performing numerical simulations on porous media images. In order to access the necessary tools to benefit from digital rock analysis and characterization, we need accessing the porous media images, the geometric distribution and the spatial distribution of pores and grains through imaging or reconstruction methods. Porous media reconstruction methods are known as an alternative to imaging techniques. In addition, reconstruction methods have the ability to fix problems and imperfections associated with imaging, such as... 

The kidney is one of the most complicated organs in terms of structure and physiology, in part because it is highly vascularized. Previous investigations have focused on specific characteristics like length and diameter. There are a few methods like those which are based on image processing techniques, that have been focused on all features as a unique structure. The clear drawback of these approaches is inability to justify growth and changes. Lindenmayer system (L-system) is parallel rewriting method and a type of graph grammars. L-system can justify growth and all characteristic changes and adopt itself to them. Parametric rewriting rules incorporating within physiological laws of the... 

Kidney is one of the most complicated organs in terms of functionality and physiology due to its complicated unique vascular structure. Previous investigations have focused on specific characteristics like length and diameter. Most of these methods are based on Image Processing techniques which prevent a comprehensive study in growth and changes of the vascular system. Lindenmyaer system (L-system) is a parallel rewriting system and a type of formal grammar and had been used to create graphs and natural patterns. By absorbing the physiological characteristics of the kidney and integrating them into parametric L-system, a highly dense and accurate vascular system could be generated with few... 

The industrial paradigm shift toward intelligent and sustainable management stimulates policymakers to leverage artificial intelligence for the decentralized planning of chemical industries with energy networks. By doing so, this work firstly presents a simulation framework to investigate the rigorous transient behavior of integrated systems comprising natural gas and power transmission networks, along with a chemical plant whose feedstock is natural gas. This framework entails dynamic models for the gas transmission network and the SynGas plant, and a continuous-time AC-power flow formulation with dispatchable loads. It addresses the following key challenges: (i) analyzing energy and... 

In various industries, particularly in the process industries, computational fluid dynamics (CFD) stands as the predominant method for simulating distributed systems. In these methods, discretization of system geometry and partial differential equations is necessary, resulting in a system of algebraic or ordinary differential equations, or a combination thereof. The significant computational demands arising from the extensive number of equations derived from dynamic system simulations highlight the necessity for substantial processing and computing power. The objective of this project is to reduce the computational load associated with solving these equations. It focuses on utilizing machine...