Sharif Digital Repository

In recent years, due to the energy price increase, great efforts were made to optimize the operating conditions of various chemical processes in order to reduce the operating cost and obtain the maximum possible profit. Decision makers should usually deal with different kinds of uncertainty in process optimization. In this situation, fuzzy optimization is an ideal method, since it represents and handles the underlying uncertainty of the optimization problems. In this paper, the optimization problem for production process of dimethyl ether (DME) as an alternative fuel to diesel is considered. Both crisp and fuzzy approaches are applied to formulate the optimization problem while sensitivity... 

Three different feedback linearization control methods are applied to nonlinear control of type I diabetes mellitus model. One is exact FBL and the two others are approximate manners based on approximations of the nonlinear system and its duality one-form, utilizing uniform approximation and a homotopy operator, respectively. An extended luenberger observer is also employed to observe the required states of designed compensators. The nonlinear compensators are designed based on a minimal model and applied to the minimal model, as well as Sorensen’s physiological model. In addition to the mentioned close-loop control strategies, a discrete control strategy based on an optimization problem is... 

Hydrocarbon reservoirs development and management is based on their dynamic models. To encounter various types of error during model building, model parameters are adjusted to produce reservoir historical data by assimilation (history matching) of reservoir production or 4D seismic data. Among the existing sequential methods for automatic history matching, ensemble Kalman filter and its variants have displayed promising results. The innovations of this thesis for ensemble Kalman filter (EnKF) are presented into three major orients; these includes adaptive localization/regularization, characterization of original PUNQ test model and characterization of channelized reservoir.
To mitigate... 

Hybrid systems are the systems that in addition to their dependency on time, the occurrence of variouis events paly a vital role in their dynamic behavior. These systems inherit the characteristics of two inherently different categories of the dynamic systems which are: a) the continuous-variable dynamic systems; and b) discrete-event systems. Many systems in science and engineering can be considered as hybrid systems; among these one can mention the dynamic operation of stage wise processes, in which each mode of operation has its own dynamic behavior. Transition from one mode to another one is caused by the occurrence of various events. The main objective of this work is to investigate... 

Total Energy consumed in the compressor stations severely affects the gas transmission costs. Currently steady-state optimizations are used to solve “Minimize Fuel Cost Problem” (MFCP) in gas transmission networks. But due to the fast changing demand and maintaining the linepack of network, these methods are not able to find best solution for MFCP. Control of natural gas transmission system is a challenging task due to the system large dimension, lots of operating constraints and small number of measurements compared to the number of system states. In this thesis it is first shown that most of the pipeline systems have a mild nonlinear behavior. A heuristic method for identification of large... 

A genetic-based pore network extraction method from micro-CT images is proposed in this work. Several variables such as the number, radius and location of pores, the coordination number, as well as the radius and length of the throats are used herein as the optimization parameters. Two methods are presented for modeling the pore network structure. Unlike the previous models, these methods are directly based on minimizing the error between the extracted network and the real porous medium. This leads to the generation of more accurate results while reducing required computational memories. Two different objective functions are used in building the network. In the first method, only the... 

Process optimization is a technique by which the plant operating condition is obtained such that a specific objective is achieved while the other process requirements are still met. These requirements can include product quality specifications, physical equipment limitations, and the constraints corresponding to the environmental, health, and safety issues. Frequently, this objective is an economic one. In the process optimization, the use of improper optimization techniques may lead to impractical results. One of these strategies is the plant wide optimization. In order to show the effect of plant wide optimization, one should use a complicated enough process as a bench mark of the... 

Hydrocarbon reservoir management and development as well as planning of enhanced oil recovery (EOR) processes are based on the reservoir dynamic model. Thus, successful implementation of EOR scenarios greatly depends on the quality of the dynamic model and accuracy of the associated parameters in order to correctly describe fluid flow through porous media. First, a dynamic model is constructed based on the prior knowledge. However, because of the various types of error during model building, the prior model is not so accurate and perfect. Accordingly, new observation data, such as production and 4D seismic data, are utilized to calibrate the prior model and characterize the reservoir under a... 

Monitoring and control of gas transmission networks are very challenging and important, this is due to the fact that interactions between various elements in the transmission network severely affect network’s overall performance. This makes it crucial for the monitoring and control systems to take into account the topology of the network, in their decision making and control scenario’s. On the other hand, in the event of any abnormality in the network behavior, , in order to accurately and quickly detect the cause of the abnormal conditions, there is a need for rapid and effective analysis of the network based on the measurements made therein and to identify the key and effective situations... 

Natural Gas is one of the most important energy resources in the world. The U.S energy information administration(EIA) has reported that natural gas consumption will increase until 2030 in all participating sectors including industrial, domestic and electricity production.Although the use of natural gas as a source of energy has many advantages, natural gas physical condition made it’s transfer so challenging. Among the various types of transmission methods, using pipline is so conventional. Natural gas can be transmited through pipelines in a safe and reliable manner upto thousands of kilometers. For this reason, operation monitoring and control of gas transmission networks are so... 

Whenever continuous and discrete dynamics interact, hybrid systems arise. Basically, models of such systems consisted of differential or difference equations to represent continuous dynamics and automata or other discrete variables to describe behavioral mode of the systems. Our main concern is focused on two types of hybrid systems: Discrete controllers which are combined with continuous physical process like biological systems can often be well described by hybrid systems. Our approach in this thesis deals with optimal multiple daily insulin injections which are introduced as an offline control approach on a simulated patient with type I diabetes. Simulated patient is provided via GlucoSim... 

In plant-wide systems, faults can easily propagate due to the interconnection of streams. The main objective of this paper is to develop a systematic framework for online decision support system (DSS) in order to make the right decision to get the process out of critical conditions (which cannot be handled by the plant controllers) smoothly. One of the key features of the proposed approach is its lack of dependence on prior knowledge of the fault signals (e.g. number of faults, and their origin). In the proposed scheme, the plant is modeled by a fuzzy directed graph (FDG). The proposed scheme utilizes a backward reasoning based on the deviations that exists in the process variables... 

An anatomically accurate model of conducting airways is essential for adequately simulating gas mixing and fluid distribution. In the current study, Lindenmayer systems (L-systems) as a type of graph grammars method has been formulated to generate bronchial tree structure in human lung. It has been considered that the structure of bronchial tree is divided into two main parts: 1) The central airways (from the trachea to segmental bronchi); and 2) the dichotomous branching structure (from segmental bronchi to alveolar duct). Nine parametric rewriting rules incorporating within physiological laws of the airway branching are used to generate each parts of the bronchial tree. Comparison of the... 

In this research, the aim is to investigate the use of data assimilation method for better reservoir model updating in the reservoir management. In addition, multi-objective optimization concept is studied for the production optimization. The application of these methods is applied for reservoir management in the naturally fractured reservoirs. To update the reservoir, ensemble based methods, especially ensemble Kalman filter and ensemble smoother, are used. To tackle the challenges encountered with these methods, modifications are proposed to obtain a better history matching and more accurate reservoir characterization. The proposed framework for history matching is implemented for the... 

Identification and control of nonlinear systems have been always such important subjects based on nonlinearities of many processes. For instance, identification and control of gas transmission networks can be mentioned as one of the challenging problems related to their complexity and existence of different variables. The purpose of this project is identification of a nonlinear model for defining a gas transmission network and implementing a model predictive control algorithm based on identified model. Hence, first, a volterra model is implemented for identification of a pH neutralization process and then, that model is used for identification of a gas transmission network. Finally, by... 

Fault diagnosis in complex processes is very difficult due to their complexity and dimensionality, so it is of great importance. In previous works, concurrent fault diagnosing methods have not been able to diagnose faults with overlapping symptoms. On the other hand, there is no established and general method by which asynchronous concurrent faults with overlapping symptoms can be diagnosed. The purpose of this work is to come up with such a method in order to mitigate the shortcomings of the available methods which are not appropriate to be used for such a problem. In this problem, the main objective is to come up with course of events of faults according to their times occurrence. The... 

The environmental impact of process plants is one of the causes of the environmental disturbance in the world. Including the effects of these destructive impacts can be mentioned to the phenomena such as global warming, climate change, severe air pollution and water shortage. Hence, the economic justification of a process, without the review of relevance of its environmental impacts, it does not lead to the implementation and construction of a process plant. For this reason, it is a requirement to provide a software platform (preferably object-oriented) for quick and automatic checking of this item and the exact determining of these effects. On the other hand, due to the complexity of the... 

Simulation of biological behaviors as the pre requirement for control and optimization, especially for recognition and treating diseases, requires studying involved reactions which may or may not be accessible. In the other side, finding the correct network structures and related mathematical expressions to simulate biological behaviors is a complicated problem due to multi aspect interactions among biological reactions, which imply an approach that integrate the knowledge coming from multiple discipline including biological concepts, mathematical modelling, bioinformatics and advanced programming. In this study we aim to analyze this problem using ontological inference to develop a... 

In this study, in order to enhance data contaminated with random and gross errors, the implementation of data reconciliation technique on large-scale industrial unit was investigated. Data reconciliation results on the naphtha reformer unit, revealed that uncertainty in estimation of input and output reactor temperatures, decreased up to 2% in comparison with measured ones. In addition, uncertainties in estimation of the mass flow rates have declined by nearly 30%. Also, an object-oriented framework for plant wide data reconciliation was designed. This framework was designed as an extension of plant wide identification software developed previously. Moreover, adding five classes to the... 

Increasing demand for natural gas in various parts of energy sectors results in the rapid boost of analysis tools necessitates the development of the appropriate pieces of software for both simulation and optimization of the transient behavior of the gas transmission networks as an important part of the gas industries. The main objective of this project was the development of a dynamic and compositional simulator in an extensible, robust, reusable and yet maintainable manner. To achieve this goal, the object-oriented approach was used as the software development paradigm. After going through the analysis and design of this software based on an object-oriented methodology, it has been...