The thermophysical properties of hafnium in the temperature range from 293 to 2000 K

Onufriev, S. V.; Петухов, В. А.; Pesochin, V. R.; Tarasov, V. D.

doi:10.1134/s10740-008-2008-8

Cited by 6 publications

(2 citation statements)

References 14 publications

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“…In this paper, results for EBMR of copper and hafnium are presented and discussed. The temperature variations of the thermal conductivity λ and the heat capacity

for Cu and Hf are estimated using experimental data [ 19 , 21 ]. The obtained dependencies are presented in Table 1 .…”

Section: Resultsmentioning

confidence: 99%

“…When

, the model describes the solidification of the cast ingot in the water-cooled crucible—“drip melting process" ( Figure 1 ), while the case

describes the “disks melting method" (no material is added to the ingot by pouring) [ 2 , 10 ]. The thermo-physical parameters λ and

of the investigated metals are modeled as functions of the temperature (by linear regression method) using experimental data [ 19 , 20 , 21 , 22 ].…”

Section: Modeling and Mathematical Setting Of The Problemmentioning

confidence: 99%

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Electron Beam Melting and Refining of Metals: Computational Modeling and Optimization

Vutova

Donchev

2013

Materials

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Computational modeling offers an opportunity for a better understanding and investigation of thermal transfer mechanisms. It can be used for the optimization of the electron beam melting process and for obtaining new materials with improved characteristics that have many applications in the power industry, medicine, instrument engineering, electronics, etc. A time-dependent 3D axis-symmetrical heat model for simulation of thermal transfer in metal ingots solidified in a water-cooled crucible at electron beam melting and refining (EBMR) is developed. The model predicts the change in the temperature field in the casting ingot during the interaction of the beam with the material. A modified Pismen-Rekford numerical scheme to discretize the analytical model is developed. These equation systems, describing the thermal processes and main characteristics of the developed numerical method, are presented. In order to optimize the technological regimes, different criteria for better refinement and obtaining dendrite crystal structures are proposed. Analytical problems of mathematical optimization are formulated, discretized and heuristically solved by cluster methods. Using important for the practice simulation results, suggestions can be made for EBMR technology optimization. The proposed tool is important and useful for studying, control, optimization of EBMR process parameters and improving of the quality of the newly produced materials.

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“…In this paper, results for EBMR of copper and hafnium are presented and discussed. The temperature variations of the thermal conductivity λ and the heat capacity

for Cu and Hf are estimated using experimental data [ 19 , 21 ]. The obtained dependencies are presented in Table 1 .…”

Section: Resultsmentioning

confidence: 99%

“…When

, the model describes the solidification of the cast ingot in the water-cooled crucible—“drip melting process" ( Figure 1 ), while the case

describes the “disks melting method" (no material is added to the ingot by pouring) [ 2 , 10 ]. The thermo-physical parameters λ and

of the investigated metals are modeled as functions of the temperature (by linear regression method) using experimental data [ 19 , 20 , 21 , 22 ].…”

Section: Modeling and Mathematical Setting Of The Problemmentioning

confidence: 99%

Electron Beam Melting and Refining of Metals: Computational Modeling and Optimization

Vutova

Donchev

2013

Materials

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Estimation of surface tension of grain boundaries in allotropes of elements

Prokofjev

2019

J Mater Sci

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Thermodynamic Properties of Hafnium

Arblaster

2014

J. Phase Equilib. Diffus.

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The thermophysical properties of hafnium in the temperature range from 293 to 2000 K

Cited by 6 publications

References 14 publications

Electron Beam Melting and Refining of Metals: Computational Modeling and Optimization

Electron Beam Melting and Refining of Metals: Computational Modeling and Optimization

Estimation of surface tension of grain boundaries in allotropes of elements

Thermodynamic Properties of Hafnium

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