Volume 46, Issue 4

Equimolar mixtures composed of isomers were firstly used to investigate the molecular branching effect on thermal diffusion behavior, which was not disturbed by factors of molecular mass and composition in this work. Eight heptane isomers, including n -heptane, 2-methylhexane, 3-methylhexane, 2,2-dimethylpentane, 2,3-dimethylpentane, 2,4-dimethylpentane, 3,3-dimethylpentane and 3-ethylpentane, were chosen as the researched mixtures. A non-equilibrium molecular dynamics (NEMD) simulation with enhanced heat exchange (eHEX) algorithm was applied to calculate the Soret coefficient at T = 303.15T=303.15 K and P = 1.0 atmP=1.0\hspace{0.1667em}\text{atm}. An empirical correlation based on an acentric factor was proposed and its calculation coincides with the simulated results, which showed the validity of the NEMD simulation. It is demonstrated that the isomer with higher acentric factor has a stronger thermophilic property and tends to migrate to the hot region in the heptane isomer mixture, and the extent of thermal diffusion is proportional to the difference between the acentric factors of the isomers.

Recent studies have revealed the complex structure of nerve signals in axons. Besides the electrical signal, mechanical and thermal effects are also detected in many experimental studies. In this paper, the mathematical models of heat generation are analysed within the framework of a general model derived earlier by the authors. The main mechanisms of heat generation are seemingly Joule heating and endo- and exothermic reactions. The concept of internal variables permits to model the heat relaxation typical to these reactions. The general energy balance of the whole signal is analysed based on physical mechanisms responsible for emerging the components of a signal which constitutes a wave ensemble. The novelty of this study is in describing the energy for all the components of the wave ensemble. Some open questions are listed for further studies.

In this work, we develop a method for learning interpretable, thermodynamically stable and Galilean invariant partial differential equations (PDEs) based on the conservation-dissipation formalism of irreversible thermodynamics. As governing equations for non-equilibrium flows in one dimension, the learned PDEs are parameterized by fully connected neural networks and satisfy the conservation-dissipation principle automatically. In particular, they are hyperbolic balance laws and Galilean invariant. The training data are generated from a kinetic model with smooth initial data. Numerical results indicate that the learned PDEs can achieve good accuracy in a wide range of Knudsen numbers. Remarkably, the learned dynamics can give satisfactory results with randomly sampled discontinuous initial data and Sod’s shock tube problem although it is trained only with smooth initial data.

The thermal modeling of biological systems is increasingly important in the development of more advanced and more precise techniques such as ultrasound surgery. One of the primary barriers is the complexity of biological materials: the geometrical, structural, and material properties vary in a wide range. In the present paper, we focus on the continuum modeling of heterogeneous materials of biological origin. There are numerous examples in the literature for non-Fourier thermal models. However, as we realized, they are associated with a few common misconceptions. Therefore, we first aim to clarify the basic concepts of non-Fourier thermal models. These concepts are demonstrated by revisiting two experiments from the literature in which the Cattaneo–Vernotte and the dual phase lag models are utilized. Our investigation revealed that these non-Fourier models are based on misinterpretations of the measured data, and the seeming deviation from Fourier’s law originates from the source terms and boundary conditions.

This study aims to identify the thermodynamic cycle that produces the maximum possible power output from a heat source and sink with finite heat capacities. Earlier efforts used sequential Carnot cycles governed by heat transfer rate equations to determine the maximum power cycle. In this paper, a hypothesis is proposed where the heat capacities of the heat addition and rejection processes of the proposed maximum power cycle are assumed to match the heat source and sink, respectively. The result is a simple thermodynamic model that approximately defines the performance and shape of the proposed maximum power cycle, which are compared and verified with the shape and performance of optimized sequential Carnot cycles with closely matching results.

It is a long-lasting task to understand heat conduction phenomena beyond Fourier. Besides the low-temperature experiments on extremely pure crystals, it has turned out recently that heterogeneous materials with macro-scale size can also show thermal effects that cannot be modeled by the Fourier equation. This is called over-diffusive propagation, different from low-temperature observations, and is found in numerous samples made from metal foam, rocks, and composites. The measured temperature history is indeed similar to what Fourier’s law predicts but the usual evaluation cannot provide reliable thermal parameters. This paper is a report on our experiments on several rock types, each type having multiple samples with different thicknesses. We show that size-dependent thermal behavior can occur for both Fourier and non-Fourier situations. Moreover, based on the present experimental data, we find an empirical relation between the Fourier and non-Fourier parameters, which may be helpful in later experiments to develop a more robust and reliable evaluation procedure.

The proposal of models that account for the irreversibilities within the core engine has been the topic of interest to quantify the useful energy available during its conversion. In this work, we analyze the energetic optimization and stability (local and global) of three power plants, nuclear, combined-cycle, and simple-cycle ones, by means of the Curzon–Ahlborn heat engine model which considers a linear heat transfer law. The internal irreversibilities of the working fluid measured through the r -parameter are associated with the so-called “uncompensated Clausius heat.” In addition, the generalization of the ecological function is used to find operating conditions in three different zones, which allows to carry out a numerical analysis focused on the stability of power plants in each operation zone. We noted that not all power plants reveal stability in all the operation zones when irreversibilities are considered through the r -parameter on real-world power plants. However, an improved stability is shown in the zone limited by the maximum power output and maximum efficiency regimes.