Thermal properties of $$^{172}\mathrm{Yb}$$ and $$^{162}\mathrm{Dy}$$ isotopes in the back-shifted Fermi gas model with temperature-dependent pairing energy

Pramana ◽  
2019 ◽  
Vol 93 (3) ◽  
Author(s):  
M R Pahlavani ◽  
M Masoumi Dinan
Keyword(s):  
Thermal Properties ◽  
Fermi Gas ◽  
Pairing Energy ◽  
Temperature Dependent

Analysis of Tempering and Rehardening for Grinding of Hardened Steels

1991 ◽  
Vol 113 (4) ◽  
pp. 388-394 ◽  
Author(s):  
O. B. Fedoseev ◽  
S. Malkin
Keyword(s):  
Thermal Properties ◽  
Heat Source ◽  
Hardened Steel ◽  
Temperature History ◽  
Hardness Distribution ◽  
Temperature Dependent ◽  
Thermally Activated ◽  
Reaction Equations ◽  
Rate Controlling Step ◽  
Good Agreement

An analysis is presented to predict the hardness distribution in the subsurface of hardened steel due to tempering and rehardening associated with high temperatures generated in grinding. The grinding temperatures are modeled with a triangular heat source at the grinding zone and temperature-dependent thermal properties. The temperature history, including the effect of multiple grinding passes, is coupled with thermally activated reaction equations for tempering and for reaustenitization which is the rate controlling step in rehardening. Experimental results from the literature are found to be in good agreement with the analytical predictions.

Thermal Properties of an Incompletely Degenerate Fermi Gas

1936 ◽  
Vol 32 (1) ◽  
pp. 108-111 ◽  
Author(s):  
N. F. Mott
Keyword(s):  
Thermal Properties ◽  
Specific Heat ◽  
Electron Gas ◽  
Electronic States ◽  
Fermi Gas ◽  
Paramagnetic Susceptibility ◽  
Free Electrons ◽  
Periodic Field ◽  
Degenerate Fermi Gas ◽  
Image Position

The purpose of this note is to calculate the specific heat and paramagnetic susceptibility of an electron gas obeying the Fermi-Dirac statistics for all temperatures, including those temperatures for which the gas is partially degenerate. The results are applicable to the electrons in a metal, whether free or moving in a periodic field, provided only that the number of electronic states per gram atom with energy between E and E + dE can be expressed in the formas for free electrons.

Grain Temperature-Dependent Thermal Properties Estimation Using FI-QPSO Algorithm

2021 ◽  
Author(s):  
Hongmei Xu ◽  
Juan Liu ◽  
Kun Wang ◽  
Songtao Kong ◽  
Yong Shi
Keyword(s):  
Particle Swarm Optimization ◽  
Thermal Properties ◽  
Measurement Errors ◽  
Fuzzy Inference ◽  
Quantum Particle ◽  
Estimation Method ◽  
Particle Swarm ◽  
Temperature Dependent ◽  
Swarm Optimization ◽  
Quantum Particle Swarm Optimization

Abstract A hybrid fuzzy inference-quantum particle swarm optimization (FI-QPSO) algorithm is developed to estimate the temperature-dependent thermal properties of grain. The fuzzy inference scheme is established to determine the contraction-expansion coefficient according to the aggregation degree of particles. The heat transfer process in the grain bulk is solved using the finite element method (FEM), and the estimation task is formulated as an inverse problem. Numerical experiments are performed to study the effects of the surface heat flux, number of measurement points, measurement errors and the individual space on the estimation results. Comparison with the quantum particle swarm optimization (QPSO) algorithm and conjugate gradient method (CGM) is also conducted, and it shows the validity of the estimation method established in this paper.

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