PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
February 5, 20260 citations

Experimental measurement andits irreplaceability for the numerical simulation of temperature fields of technological processes

View Full Paper
FKFrantisek KavickaJKJ. KatolickýJHJiri Hejcik

Key Points

  • The study aims to demonstrate the necessity of experimental measurements for accurate numerical simulations of temperature fields in casting processes.
  • Conducted numerical simulations of solidification in casting processes
  • Considered thermophysical parameters of materials in the simulation
  • Utilized experimental measurements to refine simulation results
  • Provided examples from gravity and continuous casting processes
  • Experimental measurements significantly improved the accuracy of numerical models
  • Optimized casting processes led to better control of solidification and cooling
  • Demonstrated the critical role of initial and boundary conditions in simulations

Abstract

Solidification and cooling of the gravitationally cast steels metals or ceramic materials or continuously cast metals rank among the major technological processes. Optimization of these processes is unthinkable without numerical simulation of the non-stationary temperature field during solidification including phase change and cooling. The success of the models is conditioned by knowledge of the thermophysical parameters of all materials entering the casting-mold-surroundings system, as well as knowledge of all initial and boundary conditions of the simulated process at all system boundaries. However, it is also necessary to refine and correct the results of the numerical model by experimental measurements. The importance and benefit of experiments is shown as an example in the numerical optimization of gravity casting of massive castings from steel and ductile cast-iron or material EUCOR as well as in the numerical optimization of continuous casting of a steel slab.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Kavicka et al. (2025) studied this question.

synapsesocial.com/papers/698433c8f1d9ada3c1fb138fhttps://doi.org/10.1051/matecconf/202541201002/pdf
Ask AI
Helpful
Bookmark
Share
View Full Paper