Sharif Digital Repository

In this paper, a framework for distributed and decentralized state estimation in high-pressure and long-distance gas transmission networks (GTNs) is proposed. The non-isothermal model of the plant including mass, momentum and energy balance equations are used to simulate the dynamic behavior. Due to several disadvantages of implementing a centralized Kalman filter for large-scale systems, the continuous/discrete form of extended Kalman filter for distributed and decentralized estimation (DDE) has been extended for these systems. Accordingly, the global model is decomposed into several subsystems, called local models. Some heuristic rules are suggested for system decomposition in gas pipeline... 

In this paper, a non-isothermal model of natural gas in pipelines including mass, momentum and energy balance equations are used as model equations for modeling and state estimation in gas pipeline systems. It is shown that differential equations describing the dynamic behavior of a high-pressure and long-distance gas transmission network (GTN) can be solved efficiently using the orthogonal collocation method. The issues corresponding to the presence of discontinuities in the dynamic model is substantially discussed and studied. The non-isothermal model of a GTN can experience discontinuities during transient operations, which causes challenges in simulation and state estimation in this... 

In natural gas transmission networks, the efficiency of daily operation is strongly dependent on our knowledge about the customer future demands. Unavailability of accurate demand forecasts makes it more important to be able to characterize the loads and quantify the corresponding uncertainty. A planning strategy for natural gas transmission networks under future demand uncertainty is addressed, which involves coupling of a gas transmission network dynamic simulator with the stochastic optimization framework. Loads from a gas-fired power plant are studied where the loads are characterized by a number of uncertain parameters, and unscented transform is utilized for uncertainty propagation.... 

The activity coefficient at infinite dilution is a representative of the limiting non-ideality of a solute in a mixture. Various methods for the prediction of infinite dilution activity coefficients (IDACs) have been developed. Artificial neural networks are powerful mapping tools for nonlinear function approximations. Accordingly, an artificial neural network model is proposed for the prediction of the IDACs of binary systems where the properties of the individual components are used as inputs to the network. The input parameters of the neural network are the mixture temperature, critical temperature, critical pressure, critical volume, molecular weight, dipole moment and the acentric... 

This paper aims to identify an optimum bone fracture stabilizer. For this purpose, three design variables including the ratio of the screw diameter to the plate width at three levels, the ratio of the plate thickness to the plate width at three levels, and the diameter of the bone at two levels were selected for analysis. Eighteen 3D verified finite element models were developed to examine the effects of these parameters on the weight, maximum displacement and maximum von Mises stress of the fixation structure. Considering the relations between the inputs and outputs using multivariate regression, a genetic algorithm was used to find the optimal choices. Results showed that the diameter of... 

The purpose of this study is providing a framework for the evaluation of process and content of development programs and evaluating the fourth and fifth law development program of Iran. Policy evaluation is one the most important measures in the policy cycle and is implemented with the purpose of learning from the results of stage. Given the wide dimensions of policy making, achieving a model for evaluating policy is faced with many complexities. In this study with reviewing previous experiences in the field of policy evaluation, an integrated model for evaluating policy, is presented from two main aspects of the process and the content and then with using this model, the Fourth Program and... 

Using control charts to monitor healthcare systems has gained particular attention. In this paper, a risk-adjusted cumulative sum control chart is designed to monitor surgery outputs. Before undergoing surgery, the patients have some unique risk factors which influence the surgery outputs. Thus, risk-adjustment is carried out with the purpose of taking these risks into account using an accelerated failure time model. But the technical implementation of the chart requires determining the design parameters which should be selected in an optimal way putting the desired statistical and economic considerations into service. To this end, a multi-objective model, considering multiple assignable... 

Improving detection efficiency in small animal PET scanners without degrading spatial resolution is one of the main problems of these scanners. Commercial small animal PET scanners use different methods to achieve desirable levels of sensitivity and spatial resolution. GE Healthcare eXplore VISTA PET scanner uses double layer (LYSO-GSO) depth-of-interaction (DOI) capable cuboid detector modules. In this work, the design of GE Healthcare eXplore VISTA PET scanner is improved using tapered detector geometry instead of cuboid geometry. Using tapered detector geometry, the gaps between adjacent modules are filled and the sensitive volume has increased about 11.5%. The new designed PET scanner...