Numerical identification of the thermal properties of early age concrete using inverse heat transfer problem

Grzegorz Knor , Roman Jaskulski , Michał A. Glinicki , Jan Holnicki-Szulc


The procedure of numerical identification of thermophysical properties of concrete during its hardening is presented. Heat of cement hydration, thermal conductivity and specific heat are determined for purpose of modelling temperature evolution in massive concrete elements. The developed method is based on point temperature measurements in a cylindrical mould and the numerical solution of the inverse heat transfer problem by means of direct search optimization algorithm. The determined thermal characteristics of concrete are not constant and depend on the maturity of concrete. The procedure was verified on set of concrete mixes designed with Portland cement CEM I 42.5R and Portland-slag cement CEM II/B-S 32.5 N. Calcareous fly ash was also used for partial replacement of cement in the mixtures. The obtained results have been compared with experimentally measured temperature in concrete and a fair agreement has been found.
Author Grzegorz Knor - [Institute of Fundamental Technological Research of the Polish Academy of Sciences]
Grzegorz Knor,,
, Roman Jaskulski (FCEMP / ICEn)
Roman Jaskulski,,
- Insitute of Civil Engineering
, Michał A. Glinicki - [Institute of Fundamental Technological Research of the Polish Academy of Sciences]
Michał A. Glinicki,,
, Jan Holnicki-Szulc - [Institute of Fundamental Technological Research of the Polish Academy of Sciences]
Jan Holnicki-Szulc,,
Journal seriesHeat and Mass Transfer, ISSN 0947-7411, (N/A 70 pkt)
Issue year2019
Publication size in sheets0.6
ASJC Classification1507 Fluid Flow and Transfer Processes; 3104 Condensed Matter Physics
Languageen angielski
Score (nominal)70
Score sourcejournalList
ScoreMinisterial score = 70.0, 04-01-2020, ArticleFromJournal
Publication indicators WoS Citations = 0; Scopus Citations = 0; Scopus SNIP (Source Normalised Impact per Paper): 2018 = 0.81; WoS Impact Factor: 2018 = 1.551 (2) - 2018=1.604 (5)
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