Thermoacoustics describes energy conversion processes, activated by interaction temperature oscillation, accompanying the pressure oscillation in a sound wave, with solid boundaries. In ordinary experience this interaction of sound and heat cannot be observed, because of the very low temperature differences, but under suitable conditions, it can be emphasized and amplified to create remarkable ...

Neural network is one of the new soft computing methods commonly used for prediction of the thermodynamic properties of pure fluids and mixtures. In this study, we have used this soft computing method to predict the coefficients of the Antoine vapor pressure equation. Three transfer functions of tan-sigmoid (tansig), log-sigmoid (logsig), and linear were used to evaluate the performance of diff...

This paper presents a systematic comparison of ejector performance predictions between a thermodynamic model and a Computational Fluid Dynamics (CFD) model for different operating conditions. The thermodynamic model developed by Galanis and Sorin (2016) assumes the primary flow is always choked, and irreversibilities due to viscous dissipation are taken into account through polytropic efficienc...

In this study, the performance of an irreversible regenerative Brayton cycle is sought through power maximizations using finite-time thermodynamic concept in finite-size components. Optimizations are performed using a genetic algorithm. In order to take into account the finite-time and finite-size concepts in the current problem, a dimensionless mass-flow rate parameter is used to deploy ti...

An analytical equation of state is applied to calculate the thermodynamic properties for argon. Theequation of state is that of Song and Mason. It is based on a statistical-mechanical perturbation theory ofhard convex bodies and can be written as fifth-order polynomial in the density. There exist three temperaturedependentparameters: the second virial coefficient, an effective molecular volume,...

In this work, two different approaches – an iterative thermodynamic method and a neural network model – are proposed and compared for the modeling of steam turbines. The iterative thermodynamic model can predict steam mass flow, pressure, temperature, enthalpy and power on each turbine drum. The NN model can predict the generated mechanical power. Both models have been trained and validated on ...

We review the available experimental information on the thermodynamic properties of supercooled water and demonstrate the possibility of modeling these thermodynamic properties on a theoretical basis. We show that by assuming the existence of a liquid-liquid critical point in supercooled water, the theory of critical phenomena can give an accurate account of the experimental thermodynamic-prope...