Sharif Digital Repository

Transmission of natural gas from its sources to end users in various geographical locations is carried out mostly by natural gas transmission pipeline networks (NGTNs). Effective design and operation of NGTNs requires insights into their steady-state and, particularly, dynamic behavior. This, in turn, calls for efficient computer-aided approaches furnished with accurate mathematical models. The conventional mathematical methods for the dynamic simulation of NGTNs are computationally intensive. In this paper, the use of autoregressive neural networks for cost-effective dynamic simulation of NGTNs is proposed. Considering the length, diameter, roughness, and elevation as the main... 

We proposed a personalized bolus advisor for patients with type 1 diabetes (T1D). A bolus advisor is a decision support system that recommends insulin doses based on an open-loop model-based optimization. To construct the bolus advisor, the optimal open-loop control of blood glucose (BG) concentration in T1D patients was represented as a multi-objective optimization problem. The insulin types, doses, and times for each injection were provided by the bolus advisor based on a personalized model and an average daily diet, which should be re-tuned frequently in specific time intervals. The constructed personalized model for T1D patients incorporates effects of the patient's age and body weight.... 

The bronchial tree plays a main role in the human respiratory system because the air distribution throughout the lungs and gas exchange with blood occur in the airways whose dimensions vary from several centimeters to micrometers. Organization of about 60,000 conducting airways and 33 million respiratory airways in a limited space results in a complex structure. Due to this inherent complexity and a high number of airways, using target-oriented dimensional reduction is inevitable. In addition, there is no general reduced-order model for various types of problems. This necessitates coming up with an appropriate model from a variety of different reduced-order models to solve the desired... 

Gas exchange, particle deposition, and drug delivery in the human lungs depend on the structure of the human bronchial tree. The conducting airways occupy the main portion of the human lungs and transport air from outside into pulmonary acini where the O2–CO2 exchange with blood occurs. Therefore, the generation of three-dimensional accurate structure of the conducting airways is required for simulation of the transport phenomena in the human respiratory system. The present study proposes an intelligent method for generation of conducting airways based on stochastic parametric Lindenmayer system (L-system). The conducting airways grow into the bronchopulmonary segments simultaneously using... 

Centralized and cloud computing-based network architectures are the promising tracks of future communication systems where a large scale compute power can be virtualized for various algorithms. These architectures rely on high-performance communication links between the base stations and the central computing systems. On the other hand, massive Multiple-Input Multiple-Output (MIMO) technology is a promising solution for base stations toward higher spectral efficiency. To reduce system complexity and energy consumption, 1-bit analog-to-digital converters (ADCs) are leveraged with the cost of lowering the signal quality. To recover the lost information, more sophisticated algorithms, like... 

This work presents a simulation framework to investigate the rigorous transient behavior of integrated systems comprising natural gas and power transmission networks, and 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 chemical system interdependencies, and their impacts on each other's supply reliability and security; (ii) providing an environment conducive to settling a critical question of how to prioritize the natural gas consumption as fuels of power... 

The bronchial tree plays a main role in the human respiratory system because the air distribution throughout the lungs and gas exchange with blood occur in the airways whose dimensions vary from several centimeters to micrometers. Organization of about 60,000 conducting airways and 33 million respiratory airways in a limited space results in a complex structure. Due to this inherent complexity and a high number of airways, using target-oriented dimensional reduction is inevitable. In addition, there is no general reduced-order model for various types of problems. This necessitates coming up with an appropriate model from a variety of different reduced-order models to solve the desired... 

Gas exchange, particle deposition, and drug delivery in the human lungs depend on the structure of the human bronchial tree. The conducting airways occupy the main portion of the human lungs and transport air from outside into pulmonary acini where the O2–CO2 exchange with blood occurs. Therefore, the generation of three-dimensional accurate structure of the conducting airways is required for simulation of the transport phenomena in the human respiratory system. The present study proposes an intelligent method for generation of conducting airways based on stochastic parametric Lindenmayer system (L-system). The conducting airways grow into the bronchopulmonary segments simultaneously using... 

A coupled statistical and conditional generative adversarial neural network is used for 3D reconstruction of both homogeneous and heterogeneous porous media from a single two-dimensional image. A statistical approach feeds the deep network with conditional data, and then the reconstruction is trained on a deep generative network. The conditional nature of the generative model helps in network stability and convergence which has been optimized through a gradient-descent-based optimization method. Moreover, this coupled approach allows the reconstruction of heterogeneous samples, a critical and serious challenge in conventional reconstruction methods. The main contribution of this work is to... 

Perturbed-Chain Statistical Associating Fluid Theory Equation of State (PC-SAFT EoS) requires cross interaction parameter for each binary pair in the mixture. For real mixtures, these parameters should be corrected by binary interaction coefficients (kij's). The values of kij's are tuned by an optimization method in order to minimize the deviation from equilibrium data. The Particle Swarm Optimization (PSO) algorithm is employed for optimization of kij's due to the continuous nature of kij and highly nonlinear nature of PC-SAFT EoS. Although kij can be adjusted using the mentioned algorithm, it is cumbersome and highly time-consuming because the optimization should be performed for each pair... 

In this work, a novel approach to model the dynamic behavior of the flash separation process (as a main building block of non-reacting stage-wise operations) based on Mamdani Fuzzy Inference Systems is proposed. This model surmounts the need to solve various types of mathematical equations governing the system and does not require thermodynamic properties which are either not available or computationally demanding. Hence it can be easily used in dynamic simulation of multi-phase flow in distributed systems. In the proposed approach the overall model is broken into several simple sub-models based on intuitive analysis of an expert. Moreover, a new fuzzy concept, named “Linguistic Composition... 

In this study, coupled Generative Adversarial and Auto-Encoder neural networks have been used to reconstruct realizations of three-dimensional porous media. The gradient-descent-based optimization method is used for training and stabilizing the neural networks. The multi-scale reconstruction has been conducted for both sandstone and carbonate samples from an Iranian oilfield. The sandstone contains inter and intra-grain porosity. The generative adversarial network predicts the inter-grain pores and the auto-encoder provides the generative adversarial network result with intra-grain pores (micro-porosity). Different matching criteria, including porosity, permeability, auto-correlation... 

In this study, ensemble Kalman filter (EnKF) is first applied to estimate absolute and relative permeabilities jointly under three-phase flow condition in the porous media. By assimilating historical data, absolute permeability field is adjusted progressively towards its reference. However, assimilation process does not improve the estimation of all relative permeability parameters, and some of them are poorly estimated at the end of assimilation. To improve the estimation of the relative permeability curves, we propose a new hybrid approach in which the estimation process of the absolute and relative permeabilities is separated. In this approach, gridblock permeabilities are again estimated... 

A new two-dimensional dynamic model was developed to simulate asphaltene precipitation, aggregation, and deposition at isothermal and non-isothermal conditions. The perturbed-chain statistical associating fluid theory equation of state was used to model the asphaltene precipitation. Also, novel kinetic models were used to account for the aggregation and deposition of asphaltene particles. The effect of the aggregate size on the rate of aggregation and deposition was studied, and it was concluded that the rate of asphaltene deposition increases, while the concentration of nanoaggregates increases in the well column. The tendency of smaller aggregates to deposit on the surface could be... 

In this study, impact of initial ensembles on posterior distribution of ensemble-based assimilation methods is statistically analyzed. Along with, sampling performance as well as uncertainty quantification of these methods are compared in terms of their ability to accurately and consistently evaluate unknown reservoir model parameters and reservoir future performance. For this purpose, a synthetic test problem, which is a small but highly nonlinear reservoir model under two-phase flow, is utilized. Subsequently, different initial ensemble sets are considered and are updated through the assimilation process performed on the test problem using ensemble-based assimilation methods. Afterwards,... 

The aim of this paper is to synthesize a hybrid controller for pressure swing adsorption (PSA) processes. Since the process is described by a set of partial differential algebraic equations, first a local reduced-order model (LROM) for the process is developed and is formalized as a hybrid system. A hybrid controller is designed for purity control of the process in the presence of external disturbances by determining the maximal safe set of the LROM. A hybrid backward reachability analysis is performed for this purpose. Considering a realistic scenario for PSA processes where the states are not available and the number of measurement sensors is very limited, the desired states are estimated... 

Structures of retinal blood vessels are of great importance in diagnosis and treatment of diseases that affect the eyes. Parametric Lindenmayer system (L-system) is one of the powerful rule-based methods that has a great capability for generating tree-like structures using simple rewriting rules. In this study, a novel framework, which can be used to model the retinal vasculature based on available images, has been proposed. This framework presents a solution to special instance of a general open problem, the L-system inverse problem, in which L-system rules should be obtained based on images representing a particular tree-like structure. In this study, genetic algorithm with a novel... 

Ensemble-based assimilation methods are the most promising tools for dynamic characterization of reservoir models. However, because of inherent assumption of Gaussianity, these methods are not directly applicable to channelized reservoirs wherein the distribution of petrophysical properties is multimodal. Transformation of facies field to level set functions have been proposed to alleviate the problem of multimodality. Level set representation ensures that the estimated fields are facies realizations as well as no modification of the assimilation method is required. Moreover, due to the complexity of the history matching problem in the channelized reservoirs, most researchers conventionally... 

A hybrid controller is proposed for Pressure Swing Adsorption (PSA) processes. Since the process is described by a set of Partial Differential Algebraic Equations (PDAE's), first a Local Reduced Order Model (LROM) for the process is developed and then it is formalized as a hybrid system. A controller is designed for purity control of the process in the presence of external disturbances, by determining the maximal safe set of the LROM. Hybrid backward reachability analysis is performed for this purpose. The controller is designed and applied to a two-bed, six-step PSA process whose dynamical behavior is simulated by a full-order principle-based model of the process. Excellent performance of... 

In this paper we propose a method towards purity control of pressure swing adsorption (PSA) processes which is based on the use of hybrid systems formalism. Hybrid systems feature both continuous and discrete-event dynamics and hence are very suited to describe in detail PSA processes. Based on mechanistic model of the processes, a local reduced-order model (LROM) is developed for PSA processes. Then the processes are represented as hybrid systems whose continuous evolution is described by the LROM. We then perform an analysis of hybrid reachability properties of the hybrid system obtained, based on which the so-called maximal safe set is computed. The analysis is performed for a two-bed,...