Gas–liquid two-phase flow abounds in industrial processes and facilities. Identification of its flow pattern plays an essential role in the field of multiphase flow measurement. A bluff body was introduced in this s...Gas–liquid two-phase flow abounds in industrial processes and facilities. Identification of its flow pattern plays an essential role in the field of multiphase flow measurement. A bluff body was introduced in this study to recognize gas–liquid flow patterns by inducing fluid oscillation that enlarged differences between each flow pattern. Experiments with air–water mixtures were carried out in horizontal pipelines at ambient temperature and atmospheric pressure. Differential pressure signals from the bluff-body wake were obtained in bubble, bubble/plug transitional, plug, slug, and annular flows. Utilizing the adaptive ensemble empirical mode decomposition method and the Hilbert transform, the time–frequency entropy S of the differential pressure signals was obtained. By combining S and other flow parameters, such as the volumetric void fraction β, the dryness x, the ratio of density φ and the modified fluid coefficient ψ, a new flow pattern map was constructed which adopted S（1–x）φ and （1–β）ψ as the vertical and horizontal coordinates, respectively. The overall rate of classification of the map was verified to be 92.9% by the experimental data. It provides an effective and simple solution to the gas–liquid flow pattern identification problems.展开更多
A model based on a thermodynamic approach is proposed for predicting the dynamics of communicable epidemics assumed to be governed by controlling eforts of multiple scales so that an entropy is associated with the sys...A model based on a thermodynamic approach is proposed for predicting the dynamics of communicable epidemics assumed to be governed by controlling eforts of multiple scales so that an entropy is associated with the system.All the epidemic details are factored into a single and time-dependent coefcient,the functional form of this coefcient is found through four constraints,including notably the existence of an inflexion point and a maximum.The model is solved to give a log-normal distribution for the spread rate,for which a Shannon entropy can be defined.The only parameter,that characterizes the width of the distribution function,is uniquely determined through maximizing the rate of entropy production.This entropy-based thermodynamic(EBT)model predicts the number of hospitalized cases with a reasonable accuracy for SARS in the year 2003.This EBT model can be of use for potential epidemics such as avian influenza and H7N9 in China.展开更多
基金Project(51576213)supported by the National Natural Science Foundation of ChinaProject(2015RS4015)supported by the Hunan Scientific Program,ChinaProject(2016zzts323)supported by the Innovation Project of Central South University,China
文摘Gas–liquid two-phase flow abounds in industrial processes and facilities. Identification of its flow pattern plays an essential role in the field of multiphase flow measurement. A bluff body was introduced in this study to recognize gas–liquid flow patterns by inducing fluid oscillation that enlarged differences between each flow pattern. Experiments with air–water mixtures were carried out in horizontal pipelines at ambient temperature and atmospheric pressure. Differential pressure signals from the bluff-body wake were obtained in bubble, bubble/plug transitional, plug, slug, and annular flows. Utilizing the adaptive ensemble empirical mode decomposition method and the Hilbert transform, the time–frequency entropy S of the differential pressure signals was obtained. By combining S and other flow parameters, such as the volumetric void fraction β, the dryness x, the ratio of density φ and the modified fluid coefficient ψ, a new flow pattern map was constructed which adopted S（1–x）φ and （1–β）ψ as the vertical and horizontal coordinates, respectively. The overall rate of classification of the map was verified to be 92.9% by the experimental data. It provides an effective and simple solution to the gas–liquid flow pattern identification problems.
文摘A model based on a thermodynamic approach is proposed for predicting the dynamics of communicable epidemics assumed to be governed by controlling eforts of multiple scales so that an entropy is associated with the system.All the epidemic details are factored into a single and time-dependent coefcient,the functional form of this coefcient is found through four constraints,including notably the existence of an inflexion point and a maximum.The model is solved to give a log-normal distribution for the spread rate,for which a Shannon entropy can be defined.The only parameter,that characterizes the width of the distribution function,is uniquely determined through maximizing the rate of entropy production.This entropy-based thermodynamic(EBT)model predicts the number of hospitalized cases with a reasonable accuracy for SARS in the year 2003.This EBT model can be of use for potential epidemics such as avian influenza and H7N9 in China.
