Development of PVE Refrigeration Lubricants for R32

A New-PVE lubricant was developed for use with R32 refrigerant. R32 has been proposed as an alternative refrigerant for R410A refrigerant, to reduce global warming. In this report, we evaluated the relationship between the New-PVE lubricant and R32 and R410A refrigerants. The evaluation items were physical properties (miscibility, solubility, mixture viscosity and volumetric resistivity) and thermal stability and lubricity. In addition, a New-PVE was also developed to improve miscibility with R32 refrigerant

Zero-energy edge states and their origin in particle-hole symmetric systems: symmetry and topology

We propose a criterion to determine the existence of zero-energy edge states for a class of particle-hole symmetric systems. A loop is assigned for each system, and its topology and a symmetry play an essential role. Applications to d-wave superconductors are demonstrated.Comment: 2 pages, Proceedings of LT2

Calderon-preconditioned boundary integral equations of the Burton-Miller type for transmission problems

This paper proposes well-conditioned boundary integral equations based on the Burton-Miller method for solving transmission problems. The Burton-Miller method is widely accepted as a highly accurate numerical method based on the boundary integral equation for solving exterior wave problems. While this method can also be applied to solve the transmission problems, a straightforward formulation may yield ill-conditioned integral equations. Consequently, the resulting linear algebraic equations may involve a coefficient matrix with a huge condition number, leading to poor convergence of Krylov-based linear solvers. To address this challenge, our study enhances Burton-Miller-type boundary integral equations tailored for transmission problems by exploiting the Calderon formula. In cases where a single material exists in an unbounded host medium, we demonstrate the formulation of the boundary integral equation such that the underlying integral operator ${\cal A}$ is spectrally well-conditioned. Specifically, ${\cal A}$ can be designed in a simple manner that ensures ${\cal A}^2$ is bounded and has only a single eigenvalue accumulation point. Furthermore, we extend our analysis to the multi-material case, proving that the square of the proposed operator has only a few eigenvalues except for a compact perturbation. Through numerical examples of several benchmark problems, we illustrate that our formulation reduces the iteration number required by iterative linear solvers, even in the presence of material junction points; locations where three or more sub-domains meet on the boundary

Evaluation of Friction and Wear on PVE Refrigeration Lubricants for HFC Refrigerants

For the prevention of global warming, it is important for home electric appliance to improve the energy saving performance. Air-conditioner is one of home electric appliances, and the improvement of energy consumption efficiency is being performed by various ways. Lubricant for air-conditioner is used to protect sliding surfaces of a compressor. The low friction coefficient lubricant is considered to improve the friction coefficient between rotor and vane of the rotary-type compressor. We evaluated the friction and the wear on PVE refrigeration lubricants for HFC refrigerants. The friction coefficient and wear were measured by using the hermetic type block-on-ring tester. The evaluation items were physical properties (miscibility, solubility, mixture viscosity and volumetric resistivity) and thermal stability

Classifying topological sector via machine learning

We employ a machine learning technique for an estimate of the topological charge $Q$ of gauge configurations in SU(3) Yang-Mills theory in vacuum. As a first trial, we feed the four-dimensional topological charge density with and without smoothing into the convolutional neural network and train it to estimate the value of $Q$. We find that the trained neural network can estimate the value of $Q$ from the topological charge density at small flow time with high accuracy. Next, we perform the dimensional reduction of the input data as a preprocessing and analyze lower dimensional data by the neural network. We find that the accuracy of the neural network does not have statistically-significant dependence on the dimension of the input data. From this result we argue that the neural network does not find characteristic features responsible for the determination of $Q$ in the higher dimensional space.Comment: 7 pages, 4 figures, 4 tables, talk presented at the 37th International Symposium on Lattice Field Theory - Lattice 2019, 16-22 June 2019, Wuhan, Chin

Properties of lubricants for refrigeration system with the low GWP refrigerants

For the prevention of global warming, various low GWP refrigerants (R1234yf, R1234ze, R448A, R449A, R452A, R452B, R454B etc.) were proposed as the alternative to HFC refrigerants for refrigeration system. In this report, the combinations of the low GWP refrigerants and lubricants were evaluated. The evaluation items are physical properties (miscibility, solubility, viscosity, and electric property)and thermal stability