E
Edvard Govekar
Researcher at University of Ljubljana
Publications - 99
Citations - 2054
Edvard Govekar is an academic researcher from University of Ljubljana. The author has contributed to research in topics: Laser & Probabilistic forecasting. The author has an hindex of 19, co-authored 94 publications receiving 1792 citations.
Papers
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Journal ArticleDOI
Advances in Modeling and Simulation of Grinding Processes
Ekkard Brinksmeier,Jan C. Aurich,Edvard Govekar,Carsten Heinzel,H.-W. Hoffmeister,Fritz Klocke,Jacques Peters,R. Rentsch,David J. Stephenson,Eckart Uhlmann,Klaus Weinert,M. Wittmann +11 more
TL;DR: In this paper, the authors present an overview of the current state of the art in modeling and simulation of grinding processes: physical process models (analytical and numerical models) and empirical process models(regression analysis, artificial neural net models) as well as rule based models (rule based models) are taken into account.
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On stability prediction for milling
Janez Gradišek,Martin Kalveram,Tamás Insperger,Klaus Weinert,Gabor Stepan,Edvard Govekar,Igor Grabec +6 more
TL;DR: In this article, the authors investigated the stability of 2-dof milling by using the zeroth order approximation (ZOA) and semi-discretization (SD) methods.
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Correlations of electrochemical noise, acoustic emission and complementary monitoring techniques during intergranular stress-corrosion cracking of austenitic stainless steel
TL;DR: In this paper, the AISI 304 stainless steel was subjected to constant load and exposed to an aqueous sodium thiosulphate solution, and a section of the gauge length was monitored optically with subsequent analysis by digital image correlation.
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Machine Tool Chatter and Surface Location Error in Milling Processes
TL;DR: In this article, a two degree of freddom model of the milling process is investigated and the stability chart is derived by using the semi-discretization method for the delay-differential equation corresponding to the chatter motion.
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Improving the residential natural gas consumption forecasting models by using solar radiation
TL;DR: In this paper, the influence of solar radiation on forecasting residential natural gas consumption was investigated, and it is recommended to use solar radiation as an input variable in building forecasting models, such as auto-regressive model with exogenous inputs, stepwise regression and nonlinear models (neural networks, support vector regression).