Using the mean-field theory and Glauber-type stochastic dynamics, we study the dynamic magnetic properties of the mixed spin （2, 5/2） Ising system for the antiferromagnetic/antiferromagnetic （AFM/AFM） interactions...Using the mean-field theory and Glauber-type stochastic dynamics, we study the dynamic magnetic properties of the mixed spin （2, 5/2） Ising system for the antiferromagnetic/antiferromagnetic （AFM/AFM） interactions on the bilayer square lattice under a time varying （sinusoidal） magnetic field. The time dependence of average magnetizations and the thermal variation of the dynamic magnetizations are examined to calculate the dynamic phase diagrams. The dynamic phase diagrams are presented in the reduced temperature and magnetic field amplitude plane and the effects of interlayer coupling interaction on the critical behavior of the system are investigated. We also investigate the influence of the frequency and find that the system displays richer dynamic critical behavior for higher values of frequency than that of the lower values of it. We perform a comparison with the ferromagnetic/ferromagnetic （FM/FM） and AFM/FM interactions in order to see the effects of AFM/AFM interaction and observe that the system displays richer and more interesting dynamic critical behaviors for the AFM/AFM interaction than those for the FM/FM and AFM/FM interactions.展开更多
A combined-cycle power plant (CCPP) is broadly utilized in many countries to cover energy demand due to its higher efficiency than other conventional power plants. The performance of a CCPP is highly sensitive to ambi...A combined-cycle power plant (CCPP) is broadly utilized in many countries to cover energy demand due to its higher efficiency than other conventional power plants. The performance of a CCPP is highly sensitive to ambient air temperature (AAT) and the generated power varies widely during the year with temperature fluctuations. To have an accurate estimation of power generation, it is necessary to develop a model to predict the average monthly power of a CCPP considering ambient temperature changes. In the present work, the Monte Carlo (MC) method was used to obtain the average generated power of a CCPP. The case study was a combined-cycle power plant in Tehran, Iran. The region’s existing meteorological data shows significant fluctuations in the annual ambient temperature, which severely impact the performance of the mentioned plant, causing a stochastic behavior of the output power. To cope with this stochastic nature, the probability distribution of monthly outdoor temperature for 2020 was determined using the maximum likelihood estimation (MLE) method to specify the range of feasible inputs. Furthermore, the plant was accurately simulated in THERMOFLEX to capture the generated power at different temperatures. The MC method was used to couple the ambient temperature fluctuations to the output power of the plant, modeled by THERMOFLEX. Finally, the mean value of net power for each month and the average output power of the system were obtained. The results indicated that each unit of the system generates 436.3 MW in full load operation. The average deviation of the modeling results from the actual data provided by the power plant was an estimated 3.02%. Thus, it can be concluded that this method helps achieve an estimation of the monthly and annual power of a combined-cycle power plant, which are effective indexes in the economic analysis of the system.展开更多
文摘Using the mean-field theory and Glauber-type stochastic dynamics, we study the dynamic magnetic properties of the mixed spin （2, 5/2） Ising system for the antiferromagnetic/antiferromagnetic （AFM/AFM） interactions on the bilayer square lattice under a time varying （sinusoidal） magnetic field. The time dependence of average magnetizations and the thermal variation of the dynamic magnetizations are examined to calculate the dynamic phase diagrams. The dynamic phase diagrams are presented in the reduced temperature and magnetic field amplitude plane and the effects of interlayer coupling interaction on the critical behavior of the system are investigated. We also investigate the influence of the frequency and find that the system displays richer dynamic critical behavior for higher values of frequency than that of the lower values of it. We perform a comparison with the ferromagnetic/ferromagnetic （FM/FM） and AFM/FM interactions in order to see the effects of AFM/AFM interaction and observe that the system displays richer and more interesting dynamic critical behaviors for the AFM/AFM interaction than those for the FM/FM and AFM/FM interactions.
文摘A combined-cycle power plant (CCPP) is broadly utilized in many countries to cover energy demand due to its higher efficiency than other conventional power plants. The performance of a CCPP is highly sensitive to ambient air temperature (AAT) and the generated power varies widely during the year with temperature fluctuations. To have an accurate estimation of power generation, it is necessary to develop a model to predict the average monthly power of a CCPP considering ambient temperature changes. In the present work, the Monte Carlo (MC) method was used to obtain the average generated power of a CCPP. The case study was a combined-cycle power plant in Tehran, Iran. The region’s existing meteorological data shows significant fluctuations in the annual ambient temperature, which severely impact the performance of the mentioned plant, causing a stochastic behavior of the output power. To cope with this stochastic nature, the probability distribution of monthly outdoor temperature for 2020 was determined using the maximum likelihood estimation (MLE) method to specify the range of feasible inputs. Furthermore, the plant was accurately simulated in THERMOFLEX to capture the generated power at different temperatures. The MC method was used to couple the ambient temperature fluctuations to the output power of the plant, modeled by THERMOFLEX. Finally, the mean value of net power for each month and the average output power of the system were obtained. The results indicated that each unit of the system generates 436.3 MW in full load operation. The average deviation of the modeling results from the actual data provided by the power plant was an estimated 3.02%. Thus, it can be concluded that this method helps achieve an estimation of the monthly and annual power of a combined-cycle power plant, which are effective indexes in the economic analysis of the system.
