Among many factors that influence an excavator’s performance and productivity, the volume of the bucket load and duration of the excavator working cycle are crucial. In this paper, both factors were investigated, including the granulometric composition of the excavated material. The volume of material in the bucket was determined by photogrammetric analysis while the excavator cycle time was measured by analysis of video recordings captured by a digital video camera during the excavator operation. Interconnections between the angle of repose, slewing angle, particle size distribution of material, and their effects on hydraulic excavator productivity were analyzed. It was found that a larger number of fine particles in granular materials with a higher coefficient of uniformity resulted in an increase in the volume of the bucket load. Correlation analysis revealed significant interconnection between the bucket fill factor and swell factor. It was also found that calculation of the production rate according to ISO (International Organization for Standardization) standards was more accurate for materials with a higher angle of repose while the CECE (Committee for European Construction Equipment) standard was more appropriate for materials with lower angles of repose.

Karst aquifers are important sources of thermal and groundwater in many parts of the world, such as the Alpine–Dinaric–Carpathian region in Europe. The Upper Triassic dolomites are regionally recognized thermal and groundwater aquifers but also hydrocarbon reservoirs. They are characterized by predominantly fractured porosity, but the actual share of depositional and diagenetic porosity is rarely investigated. In this research, we presented the geometric characterization of the measured microporosity of the Upper Triassic dolomites of the Žumberak Mts (Croatia), through thin-section image processing and particle analysis techniques. Pore parameters were analyzed on microphotographs of impregnated thin sections in scale. A total of 2267 pores were isolated and analyzed. The following parameters were analyzed: pore area, pore perimeter, circularity, aspect ratio (AR), roundness, solidity, Feret AR, compactness, and fractal dimension. Furthermore, porosity was calculated based on the pore portion in each image. The effective porosity on rock samples was determined using saturation and buoyancy techniques as an accompanying research method. We analyzed distributions of each parameter, their correlation, and most of the parameters are characterized by an asymmetric or asymmetric normal distribution. Parameters that quantify pore irregularities have similar distributions, and their values indicate the high complexity of the pore geometry, which can significantly impact permeability.

The determination and estimation of elastic behaviour are essential in engineering practise, especially in quarrying, mining, construction, and all engineering professions that perform operations dealing with rock materials. Young’s modulus, or modulus of elasticity, is the most important property describing the deformability of rock material. In this paper, grain-supported carbonates from Croatia are described and their elastic modulus and significant physical and mechanical properties are determined. The analysis of the collected data was performed in the R statistical environment. Estimation models based on multiple linear regression and the regression tree model were created. The methodology of model development and evaluation in R environment is described in detail. According to the more stringent coefficients (RMSECV and adjusted R²) used to evaluate the success of the estimation, simple regression tree models were found to perform well for the preliminary estimation, while more complex models based on Bagging performed very well.

Dimension stone is a valuable mineral raw material whose importance is increasing worldwide. According to its mineralogical and petrographical composition, Croatian dimension stone belongs to the carbonates, primarily limestones. As saturation influences the reduction of compressive strength, in this study, the relationship between the uniaxial compressive strength in the dry and saturated states is shown, which has a coefficient of determination of 0.9605. Models were created to estimate the compressive strength based on the values of water absorption, total porosity, and real density of the material from 26 sites, all determined according to the European standards EN 1936:2006 and EN 13755:2008. Thirty varieties of dimension stones were tested, and 150 values were collected from different tests. A dependence between the uniaxial compressive strength in the saturated state was established, including the explanation in which cases the correlation can be used to estimate the uniaxial compressive strength of carbonate dimension stones with a remarkably high degree of confidence (0.994 and 0.9374). In addition, the limitations of geomechanical estimation of the uniaxial compressive strength of rock material and its unsuitability for estimating of dimension stones construction are described.

There are a number of methods for estimating physical and mechanical characteristics. Principally, the most widely used method is regression, but recently, more sophisticated methods such as neural networks have frequently been applied as well. This paper presents the models of a simple and a multiple regression and neural networks –types Radial Basis Function and Multiple Layer Perceptron, which can be used for the estimate of the Brazilian indirect tensile strength in saturated conditions. The paper includes the issues of collecting data for the analysis and modelling and an overview of the performed analysis with an efficacy assessment of the estimate for each model. After the assessment, the model which provided the best estimate was selected, including the model which could have the most wide-spread application in the engineering practice.