Volume 64 (2017): Issue 3 (September 2017)

A twin highway Log tunnel is a part of a new motorway connection between Maribor and Zagreb, section Draženci-Gruškovje, which is located towards the border crossing between Slovenia and Croatia. The tunnel is currently under construction, and only the excavation works have been completed during the writing of this paper. The terrain in the area of the Log tunnel is diverse, and the route of the highway in its vicinity is characterised by deep excavations, bridges or viaducts. The Log tunnel is approximately 250 m long, partly constructed as a gallery. The geological conditions are dominated by Miocene base rock, featuring layers of well-connected clastic rocks, which are covered by diluvium clays, silts, sands and gravels of different thicknesses. Due to the short length of the tunnel, the usual separation of the motorway route to the left and the right tunnel axes was not carried out. Thus, the tunnel was constructed with an intermediate pillar and was designed as a three-lane tunnel, including the stopping lane. The construction of the tunnel was carried out using the New Austrian tunnelling method (NATM), in which the central adit was excavated first and the intermediate pillar was constructed within it. The excavation of the main tubes followed and was divided into the top heading, bench and the invert, enabling the intermediate pillar to take the load off the top heading of both tubes. The secondary lining of the tunnel is currently under construction. The experience of the tunnel construction gathered so far is presented in the paper. The main emphasis is on the construction of the intermediate pillar, which had to take the significant and asymmetrical ground load.

Work is directed on studying of a geodynamic condition under which the structural positions controlling process of endogenous ore formation were formed. It is shown that explosive region tectonics under the influence of regional tectonic efforts formed structural elements (positions) which controlled formation of gold deposits. It is recognized that structural positions are defined by variety of systems of disjunctive dislocation and their relationship among themselves. Formation of favorable positions depends as well on morphology of ore controlling structures, on degree of their tectonic activity and spatial situation in relation to the direction of tectonic (geodynamic) efforts.

Asymmetric rolling is a novel technique used to control both the texture and the grain refinement of metallic materials. The aim of asymmetric rolling is to apply a large shear strain uniformly through the thickness of the plate, by maintaining a high degree of friction between the sheet and the rolls. It can be used to improve the formability of material. One of the advantages of asymmetrical rolling is that the rolling force and torque can be decreased. The methods used for the asymmetric rolling are single roll drive, different work roll speeds, different work roll diameters or different lubricated work roll surfaces.

In the present contribution two tests for thermal fatigue testing, which have been developed in our group, are presented. First test has provided internal cooling system of sample, while second has external cooling. For both tests heating and cooling of samples are computer guided that enables very reliable results of testing. The first test is more appropriate for testing the base material, i.e. roll cast irons, roll steels, tool steels. The second test is more appropriate for experiments that are aimed for selection of appropriate tool surface treatment, i.e. laser cladding, nitriding, coating, etc., and to compare and to achieve improved resistance against thermal fatigue of produced surface layers.

Artificial neural network (ANN) was used to predict the dry density of soil from its thermal conductivity. The study area is a farmland located in Abeokuta, Ogun State, Southwestern Nigeria. Thirty points were sampled in a grid pattern, and the thermal conductivities were measured using KD-2 Pro thermal analyser. Samples were collected from 20 sample points to determine the dry density in the laboratory. MATLAB was used to perform the ANN analysis in order to predict the dry density of soil. The ANN was able to predict dry density with a root-mean-square error (RMSE) of 0.50 and a correlation coefficient (R²) of 0.80. The validation of our model between the actual and predicted dry densities shows R² to be 0.99. This fit shows that the model can be applied to predict the dry density of soil in study areas where the thermal conductivities are known.