Interpretation of variability of rock mass rating by geostatistical analysis: a case study in Western Turkey

Geotechnical interpretation of drillholes for rock mass characterization is commonly based on the engineering judgment. This might result in misrepresentation of the rock mass at unsampled locations. This paper investigates the reproducibility of the spatial variability of rock mass quality (rock mass rating, RMR) using geostatistics. Geotechnical data from an exploratory phase mining project in Western Turkey that covers 2.7 km depth with a total of 14 drillholes composed of 700 samples was used to perform a geostatistical analysis. RMR values of positions, where geotechnical logging was missing, were estimated by applying inverse distance weighting (IDW) and the ordinary kriging (OK) methods. The validation process showed that the OK method is consistently estimating the RMR values better than IDW. The spatial variability of RMR values by geostatistical analysis could provide valuable information in the design and development of underground or surface structures.     

Source Based Characterization and Pollution Profile of a Baker's Yeast Industry

Baker's yeast industry has significant effects on environment due to significant water consumption and high strength wastewater production. Effluents from baker's yeast industry are characterized by high concentrations of biological oxygen demand (BOD₅), chemical oxygen demand (COD), total Kjeldahl nitrogen (TKN), total dissolved solids (TDS), sulfate, and dark brown color. The aim of this study is to provide a detailed quantitative and qualitative identification and characterization of the wastewater sources from different processes of a baker's yeast industry. It is identified that the most polluted wastewater components of the facility are coming from rotary drum filter and evaporation process. However, the highest pollution loads is identified as tank and equipment cleaning effluent due to very high flow rate from this source. The efforts should be on the way to minimize the water usage for the tank and equipment cleaning process, and to recycle less polluted waste streams back to the process.     

Operation analysis of Eleviyan irrigation reservoir dam by optimization and stochastic simulation

Rainfall distributions in Iran are spatially and temporally heterogeneous, a fact probably linked to the mostly arid and semi-arid climate of the country. On the other hand, water demand is increasing with increasing population and improving life style. At present, the optimal utilization of water resources and irrigation dams is the primary concern of water resource managers. The Eleviyan dam (with a capacity of 60 hm³) was constructed to meet the irrigation and municipal water needs of the Maraghan region (Northwestern Iran). In this study, the efficiency of the Eleviyan irrigation dam system was investigated in three phases by setting up the optimization model that maximized the water release for irrigation purposes after municipal water need were met. In the first phase, the inflows measured in the 21 years prior to the construction of the reservoir, and in the second, the inflows generated by the Monte Carlo simulation method, and in the third phase, the inflows after the construction of the reservoir were used. The results demonstrate that the capacity determined during the preliminary studies was accurate and the operation carried out in the recent periods of operation life was up to a satisfactory standard.     

Flow estimations for the Sohu Stream using artificial neural networks

In this study, daily rainfall–runoff relationships for Sohu Stream were modelled using an artificial neural network (ANN) method by including the feed-forward back-propagation method. The ANN part was divided into two stages. During the first stage, current flows were estimated by using previously measured flow data. The best network architecture was found to utilise two neurons in the input layer (the delayed flows from the first and second days), two hidden layers, and one output layer (the current flow). The coefficient of determination (R ²) in this architecture was 81.4%. During the second stage, the current flows were estimated by using a combination of previously measured values for precipitation, temperature, and flows. The best architecture consisted of an input layer of 2 days of delayed precipitation, 3 days of delayed flows, and temperature of the current. The R ² in this architecture was calculated to be 85.5%. The results of the second stage best reflected the real-world situation because they accounted for more input variables. In all models, the variables with the highest R ² ranked as the previous flow (81.4%), previous precipitation (21.7%), and temperature.     

M5 model tree application in daily river flow forecasting in Sohu Stream, Turkey

This study investigate the potential of M5 model tree in predicting daily stream flows in Sohu river located within the municipal borders of Ankara, Turkey. The results of the M5 model tree was compared with support vector machines. Both modelling approaches were used to forecast up to 7-day ahead stream flow. A comparison of correlation coefficient and root mean square value indicates that M5 model tree approach works equally well to the SVM for same day discharge prediction. The M5 model tree also works well up to 7-day ahead discharge forecasting in comparison of SVM with this data set. An advantage of using M5 model tree approach is the availability of simple linear models to predict the discharge as well use of less computational time.     

Spatial variations of fundamental seismotectonic parameters for the earthquake occurrences in the Eastern Mediterranean and Caucasus

Natural Hazards - In this study, a comprehensive statistical analysis was made for different parts of the world. For this purpose, fundamental seismotectonic earthquake parameters such as b-value,...     

Work of Adhesion of Thin Spray-On Liners

The interface property known as work of adhesion incorporates both adhesion and effective bond width, which are two important design parameters in thin spray-on liner (TSL) support design. The value of this parameter is yet to be recognized by the mining industry and liner manufacturers. The importance of this parameter is introduced in this study. A new methodology using pull-out load–displacement data was developed to calculate the work of adhesion between a TSL and a substrate. Tests were performed using Tekflex as a liner material, which was applied to concrete, granite or sandstone substrate. It was found that a Tekflex liner, when sprayed onto substrates, will likely have work of adhesion values around 777–973?N/m depending on the type of substrate. In addition, for the first time in TSL literature, an effective bond width calculation is introduced in this study. It was found that Tekflex has average effective bond width of 0.7?mm on different substrates. Liner manufacturers should measure and document work of adhesion for their products on a standard substrate.