Sharif Digital Repository

In this paper, the application of neural networks for simulation and optimization of the cogeneration systems has been presented. CGAM problem, a benchmark in cogeneration systems, is chosen as a case study. Thermodynamic model includes precise modeling of the whole plant. For simulation of the steady sate behavior, the static neural network is applied. Then using dynamic neural network, plant is optimized thermodynamically. Multi- layer feed forward neural networks is chosen as static net and recurrent neural networks as dynamic net. The steady state behavior of Excellent CGAM problem is simulated by MFNN. Subsequently, it is optimized by dynamic net. Results of static net have excellent... 

Application of Cogeneration systems based gas turbine for heat and power production is increasing. Because of finite natural energy resources and increasing energy demand the cost effective design of energy systems is essential. CGAM problem as a cogeneration system is considered here for analyzing. Two new approaches are considered, first in thermodynamic model of gas turbine and cogeneration system considering blade cooling of gas turbine and second using genetic algorithm for optimization. The problem has been optimized from thermodynamic and thermoeconomic view point. Results show that Turbine Inlet Temperature (TIT) in thermodynamic optimum condition is higher than thermoeconomic one,... 

In this study, we have investigated the spray system's capabilities to reduce fission products in the containment atmosphere and control the containment pressure in a VVER-1000 nuclear power plant. Large Break Loss of Coolant Accident (LB-LOCA) without access to the active part of the Emergency Core Cooling System (ECCS), as a worst-case severe accident, has been investigated as a case study. Only containment is simulated via the MELCOR code, while leakage of various materials from the nuclear power plant's core and the primary circuit is considered as the boundary conditions. Following the Fukushima accident in 2011, many nuclear safety regulatory organizations focused on using portable... 

One of the most important challenges in target parameters estimation via model-free methods is selection of the most effective input parameters namely features selection (FS). Indeed, irrelevant features can degrade the estimation performance. In the current study, the challenge of choosing among the several plant parameters is tackled by means of the innovative FS algorithm named ranking of features with minimum deviation from the target parameter (RFMD). The selected features accompanied with the stable and the fast learning algorithm of multilayer perceptron (MLP) neural network (i.e. Levenberg-Marquardt algorithm) which is a combination of gradient descent and Gauss-newton learning... 

The paper presents further experiments with an extended version of a comprehensive model for assessment of energy technologies and research and development (R&D) planning to evaluate the impact of innovation programs on development of Iranian electricity-supply system. This analytical instrument is a model of energy R&D resource allocation with an explicit perspective of developing countries which has been linked to a bottom-up energy-systems model. Three emerging electricity generation technologies of solar PV, wind turbine and gas fuel cell are considered in the model and the impact of innovation programs on cost-reducing innovation for them is examined. The main results provided by the... 

Optimal allocation of resources for R&D on new energy technologies is an important issue in the process of development of energy system models. In this study, a model of R&D planning in energy sector has been developed and it is then linked to the energy system model. Energy system model is used as a tool for the technology assessment and prioritization of new energy technologies is evaluated with the help of this model. Based on the economic and environmental impact of new technologies, the optimal allocation of resources for R&D of new technology is estimated with the help of the R&D planning model. The conceptual formulation of the model and its integration with the energy technology... 

Application of Cogeneration systems based gas turbine for heat and power production is increasing. Because of finite natural energy resources and increasing energy demand the cost effective design of energy systems is essential. CGAM problem as a cogeneration system is considered here for analyzing. Two new approaches are considered, first in thermodynamic model of gas turbine and cogeneration system considering blade cooling of gas turbine and second using genetic algorithm for optimization. The problem has been optimized from thermodynamic and Thermoeconomic view point. Results show that Turbine Inlet Temperature (TIT) in thermodynamic optimum condition is higher than thermoeconomic one,... 

Gas turbine performances are directly related to site conditions. The use of gas turbines in combined gas-steam power plants, also applied to cogeneration, increases such dependence. In recent years, inlet air cooling systems have been introduced to control air temperature at compressor inlet, resulting in an increase in plant power and efficiency. In this paper, the dependence of outside conditions for a simple gas turbine and a combined cycle plant is studied, using absorption chiller as inlet air cooling system. We used, as case study, a simple plant equipped with one frame E gas turbine and a combined cycle with a two pressure level heat recovery steam generator (HRSG). It was found that... 

Time-frequency distributions have been used extensively for nonstationary signal analysis, they describe how the frequency content of a signal is changing in time. The Wigner-Ville distribution (WVD) is the best known. The draw back of WVD is cross-term artifacts. An alternative to the WVD is Gabor transform (GT), a signal decomposition method, which displays the time-frequency energy of a signal on a joint t-f plane without generating considerable cross-terms. In this paper the WVD and GT of ultrasound echo signals are computed analytically  

In this paper we have synthesized the Doppler signal with a known time varying mean frequency, then used the orthogonal-like Discrete Gabor Transform (DGT) and the spectrogram for analyzing the signal. Mean square error has been computed for each method respectively and at last we have analyzed the real clinical signal too  

Identification of NPP transients plays an important role in the prevention of accidents and mitigation of their consequences. NPP parameters may follow different patterns during each transient. So the transients can be identified by monitoring the operating parameters. It has been shown in several studies that data-driven methods, especially deep learning approaches, have a desirable performance in NPP transient identification. A hybrid deep learning technique is proposed in the present paper, in which transient identification is done using a CNN-LSTM neural network. The training data set is taken from a VVER-1000 full-scope simulator and the most important operating parameters are... 

Current researches on the development of gas turbine related power plants such as HAT cycle and Combined Cycle are aimed to increase the plant efficiency and output power, while reducing the cost of power generation and emission. Humid air turbine cycle (HAT) is one of innovative cycles, which are able to provide a substantial power boost of the system and an efficiency rise of several percentage points. In order to perform energy analysis of Full Flow HAT cycle and Part Flow HAT cycle an advanced thermodynamic model is developed, which is enabling evaluation of behavior of Full Flow and Part Flow Humid Air Turbines and predicting the influence of operational parameters in the performance of... 

In the calculation of the optimum loading pattern for a nuclear reactor, several parameters, including the multiplication factor maximization, the raising of the desired safety threshold during the cycle length and the flattening of the radial power peaking factor should be taken into account. Our evaluation of numerous probable arrangements within the VVER-1000 reactor core (approx. 6 × 10 14 cases) indicated that a direct search of the optimum loading pattern is not feasible. Hence, in this study, the weighting factor method and some constraints on the arrangement of the fuel assemblies were applied so that the above cases were reduced to only 244 possible arrangements. Then, using a... 

In this paper, the concentrations of fission products and fuel isotopes as well as the changes of the thermo-neutronic parameters of the Bushehr's VVER-1000 reactor were studied during the initial startup and the first cycle. In order to perform the time-dependent cell calculations and obtain the concentration of fuel elements, the WIMSD5-B code was used. Besides, by utilizing the CITATION-LDI2 code, the effective multiplication factor and the thermal power distribution of the reactor were calculated. A computer program (WERL code) was designed in order to perform accurate calculation of the temperature distribution of the reactor core. For this purpose, the Ross-Stoute, Weisman, and... 

Most of the strategies yet implemented to optimal fuel loading pattern design in nuclear power reactors, are based on maximizing the core effective multiplication factor (Keff) to extract maximum energy and lowering the local power peaking factor (Pq) from a predetermined value. However, a new optimization criterion could be of interest, aiming at maximum burn-up of the plutonium content in fuel assemblies, i.e., minimization of remaining plutonium in spent fuel at the end of cycle (EOC). In this research, we developed a new strategy for optimal fuel core loading pattern of a VVER-1000 reactor, based on multi-objective optimization: lowering the Pq, maximization of the Keff and minimization... 

Most of the strategies yet implemented to optimize fuel loading pattern design in the nuclear power reactors, are based on maximizing the core effective multiplication factor (Keff) in order to extract maximum energy and to reduce the local power peaking factor (Pq) from a set value. However, a new optimization criterion would be of interest in order to maximize the burn-up of the plutonium content (Pu) in the fuel assemblies. In this research we have developed a new strategy based on multi objective optimization, to optimize fuel core loading pattern for a VVER-1000 reactor. In this approach we simultaneously have reduced the Pq, maximized Keff and also minimized the plutonium content in... 

Effective delayed neutron fraction βeff and neutron generation time Λ are important factors in reactor physics calculation and transient analysis. In the first stage of this research, these kinetic parameters have been calculated for two states of Tehran Research Reactor (TRR), i.e. cold (fuel, clad and coolant temperatures equal to 20 °C) and hot (fuel, clad and coolant temperatures of 65, 49 and 44 °C, respectively) states using MTR_PC code. In the second stage, these parameters have been measured with an experimental method based on Inhour equation. For the cold state, calculated βeff and Λ by MTR_PC code are 0.008315 and 30.190 μs, respectively. In the hot state, these parameters being... 

Effective delayed neutron fraction βeff and neutron generation time Λare important factors in reactor physics calculation and transient analysis. In first stage of this research, these kinetics parameters have been calculated for two states of Tehran research reactor (TRR), i.e. cold (fuel, clad and coolant temperature 20°C) and hot (fuel, clad and coolant temperature 65, 49 and 44°C, respectively) using MTR-PC code. In second stage, these parameters have been measured with experimental method based on Inhour equation. For cold state, calculated βeff and Λ by MTR-PC are 0.008315 and 30.190 μsec, respectively. Same parameters in hot state are 0.008303 and 33.828 μsec, respectively. The... 

Efforts have been targeted at providing a comprehensive simulation of a centrifugal compressor undergoing surge. In the simulation process, an artificial neural network was utilized to produce an all-inclusive performance map encompassing those speeds not available in the provided curves. Two positive scenarios for the shaft speed, constant, and variable, were undertaken, and effects of load line on the dynamic response of the compressor have been studied. In order to achieve high-fidelity simulation in the variable speed case, an artificial neural network was utilized to produce an all-inclusive performance map encompassing those speeds not available in the provided curves. Moreover,... 

This research study presents an experimental investigation on forced convection heat transfer of an aqueous ferrofluid flow passing through a circular copper tube in the presence of an alternating magnetic field. The flow passes through the tube under a uniform heat flux and laminar flow conditions. The primary objective was to intensify the particle migration and disturbance of the boundary layer by utilizing the magnetic field effect on the nanoparticles for more heat transfer enhancement. Complicated convection regimes caused by interactions between magnetic nanoparticles under various conditions were studied. The process of heat transfer was examined with different volume concentrations...