G
Goran Turk
Researcher at University of Ljubljana
Publications - 90
Citations - 1750
Goran Turk is an academic researcher from University of Ljubljana. The author has contributed to research in topics: Finite element method & Beam (structure). The author has an hindex of 20, co-authored 85 publications receiving 1472 citations.
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Prediction of concrete strength using ultrasonic pulse velocity and artificial neural networks.
TL;DR: The paper demonstrates that artificial neural networks can be successfully used in modelling the velocity-strength relationship and enables us to easily and reliably estimate the compressive strength of concrete by using only the ultrasonic pulse velocity value and some mix parameters of concrete.
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Analytical Solution of Two-Layer Beam Taking into account Interlayer Slip and Shear Deformation
TL;DR: In this paper, a mathematical model is proposed and its analytical solution derived for the analysis of the geometrically and materially linear two-layer beams with different material and geometric characteristics of an individual layer.
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Possibilities of using the ultrasonic wave transmission method to estimate initial setting time of cement paste
TL;DR: In this article, the applicability of the ultrasonic wave transmission method to estimate the initial setting time of an arbitrary cement paste is discussed and the Vicar Needle Test is used in order to determine the initial set time of cement pastes.
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Prediction of subsidence due to underground mining by artificial neural networks
Tomaž Ambrožič,Goran Turk +1 more
TL;DR: The applicability of ANN for the prediction of surface subsidence was verified in different subsidence models and proved on actual excavated levels and in levelled data on surface profile points in the Velenje Coal Mine.
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Impact of open access on citation of scholarly publications in the field of civil engineering
TL;DR: The aim of the research was to determine if open access articles from the field of civil engineering receive more citations than non-open access articles, and found that open access is not a sufficient condition for citation, but increases the number of citations for articles published in journals with high impact.