Heat Dynamic Scaling

Thermal flow system have wide applications in industry. It is a problem of Engineering Thermophysics. In the past, static thermodynamics viewpoints were mainly used to study these kinds of problem. Because equilibrium thermodynamics is built on the base of proximate equilibrium state, the analysis deal with only the result of equilibrium, not the process of changing. In these decades, the industry processes were complex further and the dynamic characteristics were apparent further. For the sake of controlling the stability of dynamic process,more attentions must be paid to dynamic process of these thermodynamics processes in some occasion, such as on-line controlling and accident analysis.Conventional analysis methods of static state aren't enough to satisfy the requirement of dynamic process studying. The temporal and spatial scales of dynamic process have been not in the macro-scales. Researchers have calibrated their analyzing scale to micro or meso scales to satisfy these changes. The equilibrium of system is the relaxation process. The phase shift between flow and potential is caused by the relaxation time of viscous and thermal. Because the phase shift is the cause of acoustic power,the process time is an important parameter. Every process has its own characteristic time which is the integral effect of geometry dimension,physic parameters changing and affecting field. So the characteristic time could be used to describe the changing of state. More and more researchers agree that the characteristic time and the characteristic parameters could be used to quantify system changing. In the thermal flow system, different physical processes have their own temporal and spatial scales. In this paper, the author study experimentally and theoretically several different thermal flow systems. And those systems have been divided into two districts, heating district and main flow district. Then network models of them are built. The correlation between parameters, such as time or time parameters, and system stability, is discussed. And the author suggests that the ratio of the characteristic time in the heating district and the characteristic time in the main flow district can be the thermodynamic criterion that can been used to describe system state. The main studying content are:A comprehensive review is given systemically and objectively on the historical development of thermal flow system as well as the latest advances in this field. The achievements in thermoacoustic and boiling two-phase flow have been paid more attentions in the analytical survey. The fundamental equations for thermoacoustic engine and boiling two-phase flow are well summarized together and also derived in detail. On the base of distinguishing different districts according to different temporal scales in the thermal flow system, the heat dynamics network model with two districts is built. The quantifying method of network parameters is analyzed . There are different data processing methods between static studying and dynamic studying. Author suggests that more attentions should be paid to the dynamic data collection and dynamic data processing. All of them could be used to deal with the experiment data.The experimental results in those thermal flow systems are studied in detail. Author's interest focuses on the correlation between system stability and time parameters as shown above.Basing on the commonness of thermal flow system, the general method of building the two-districts heat dynamic network has been discussed. In this paper, the author emphasizes that time scale and time characteristic parameters are the key of quantifying system changing. The dimensionless time parameter is suggested to describe integral effect of two subsystems. It is named heat dynamic scaling criterion. Then the author compare heat dynamic scaling method with the hierarchical model approach basing on that is suggested by Zuber. Their differences are discussed. Some experimental results are used to verify the usability of this method.