This paper describes instrumental measurement uncertainties and their influence on the result obtained from determination of rock sample uniaxial compressive strength and deformability. The interdependence of uncertainty contribution is analyzed and guides for improving measurement uncertainty are given. The achieved uncertainties are compared to typical uncertainties in the determination of concrete and metallic material compressive strength and deformability.
This paper presents the virtual instrument for measurement and determination of uniaxial compression strength and rock sample deformability. It analyzes properties and limitations of several implemented virtual instruments. Furthermore, comparison of implemented virtual instrument properties is presented.
Modeli za procjenu jednoosne tlačne čvrstoće i modula elastičnosti U ovom radu ukratko je izložen pregled najznačajnijih metoda za procjenu jednoosne tlačne čvrstoće i Yangovog modula elastičnosti intaktnog stijenskog materijala koje su nastale u okviru mnogobrojnih istraživanja. Iznesen je prijedlog podjele metoda prema kojemu se one u osnovi mogu podijeliti na jednostavne i složene metode. Jednostavne metode uključuju različite dijagrame i tablice te primjenu jednadžbi jednostruke regresije, a složene metode uključuju primjene jednadžbi višestruke regresije, modela neizrazite logike, neuronskih mreža, evolucijskog programiranja i regresijskog stabla.
Models for estimating uniaxial compressive strength and elastic modulusThe most significant methods for estimating the uniaxial compressive strength and Young's modulus of intact rock material, formulated in the scope of numerous previous studies, are briefly presented in the paper. The proposal for classification of these methods, according to which they can generally be divided into simple and complex methods, is also presented. Simple methods include various diagrams and tables and the use of simple regression equations, while complex methods comprise the use of multiple regression equations, fuzzy logic models, neural networks, evolutionary programming, and regression trees.
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