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
The“average occupant”methodology is widely used in energy consumption simulations of residential buildings;however,it fails to consider the differences in energy use behavior among family members.Based on a field su...The“average occupant”methodology is widely used in energy consumption simulations of residential buildings;however,it fails to consider the differences in energy use behavior among family members.Based on a field survey on the Central Shaanxi Plain,to identify the energy use behavior patterns of typical families,a stochastic energy use behavior model considering differences in energy use behavior among family members was proposed,to improve the accuracy of energy consumption simulations of residential buildings.The results indicated that the surveyed rural families could be classified into the following four types depending on specific energy use behavior patterns:families of one elderly couple,families of one middle-aged couple,families of one elderly couple and one child,and families of one couple and one child.Moreover,on typical summer days,the results of daily building energy consumption simulation obtained by the“average occupant”methodology were 25.39%and 28%lower than the simulation results obtained by the model proposed in this study for families of one elderly couple and families of one middle-aged couple,and 13.05%and 23.05%higher for families of one elderly couple and one child,and families of one couple and one child.On typical winter days,for the four types of families,the results of daily building energy consumption simulation obtained by the“average occupant”methodology were 21.69%,10.84%,1.21%,and 8.39%lower than the simulation results obtained by the model proposed in this study,respectively.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
In gene regulatory networks, gene regulation loops often occur with multiple positive feedback, multiple negative feedback and coupled positive and negative feedback forms. In above gene regulation loops, auto-activat...In gene regulatory networks, gene regulation loops often occur with multiple positive feedback, multiple negative feedback and coupled positive and negative feedback forms. In above gene regulation loops, auto-activation loops are ubiquitous regulatory motifs. This paper aims to investigate a two-component dual-positive feedback genetic circuit, which consists of a double negative feedback circuit and an additional positive feedback loop(APFL). We study effect of substrate concentration on gene expression in the single and the networked systems with APFLs, respectively. We find that substrate concentration can tune stochastic switch behavior in the signal system and then we explore relationship of substrate concentration with positive feedback strength in aspect of stochastic switch behavior. Furthermore, we also discuss gene expression and stochastic switch behavior in the networked systems with APFLs. Based on analysis in the networked systems, we discover that genes express in some specific cells and do not express in the other cells when the expression achieves its steady state. These results can be used to well explain the character of regionalization in the expression of genes and the phenomenon of gene differentiation.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.
基金funded by the National Natural Science Foundation of China(52378109)Shaanxi Provincial Department of Science and Technology(2023KJXX-043).
文摘The“average occupant”methodology is widely used in energy consumption simulations of residential buildings;however,it fails to consider the differences in energy use behavior among family members.Based on a field survey on the Central Shaanxi Plain,to identify the energy use behavior patterns of typical families,a stochastic energy use behavior model considering differences in energy use behavior among family members was proposed,to improve the accuracy of energy consumption simulations of residential buildings.The results indicated that the surveyed rural families could be classified into the following four types depending on specific energy use behavior patterns:families of one elderly couple,families of one middle-aged couple,families of one elderly couple and one child,and families of one couple and one child.Moreover,on typical summer days,the results of daily building energy consumption simulation obtained by the“average occupant”methodology were 25.39%and 28%lower than the simulation results obtained by the model proposed in this study for families of one elderly couple and families of one middle-aged couple,and 13.05%and 23.05%higher for families of one elderly couple and one child,and families of one couple and one child.On typical winter days,for the four types of families,the results of daily building energy consumption simulation obtained by the“average occupant”methodology were 21.69%,10.84%,1.21%,and 8.39%lower than the simulation results obtained by the model proposed in this study,respectively.
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.
基金supported by the National Key Research and Development Program of China(Grant No.2016YFB0800401)the National Natural Science Foundation of China(Grant Nos.61773153,61621003,61532020,11472290,and 61472027)
文摘In gene regulatory networks, gene regulation loops often occur with multiple positive feedback, multiple negative feedback and coupled positive and negative feedback forms. In above gene regulation loops, auto-activation loops are ubiquitous regulatory motifs. This paper aims to investigate a two-component dual-positive feedback genetic circuit, which consists of a double negative feedback circuit and an additional positive feedback loop(APFL). We study effect of substrate concentration on gene expression in the single and the networked systems with APFLs, respectively. We find that substrate concentration can tune stochastic switch behavior in the signal system and then we explore relationship of substrate concentration with positive feedback strength in aspect of stochastic switch behavior. Furthermore, we also discuss gene expression and stochastic switch behavior in the networked systems with APFLs. Based on analysis in the networked systems, we discover that genes express in some specific cells and do not express in the other cells when the expression achieves its steady state. These results can be used to well explain the character of regionalization in the expression of genes and the phenomenon of gene differentiation.