A comparative assessment of indirect methods for estimating the uniaxial compressive and tensile strength of rocks

Arabian Journal of Geosciences - The uniaxial compressive and tensile strength of rocks are crucial parameters in the design stage of geotechnical structures. However, direct determination of these...     

Multi-criteria optimal structural design under uncertainty

A general framework for multi-criteria optimal design is presented which is well suited for performance-based design of structural systems operating in an uncertain dynamic environment. A decision theoretic approach is used which is based on aggregation of preference functions for the multiple, possibly conflicting, design criteria. This allows the designer to trade off these criteria in a controlled manner during the optimization. Reliability-based design criteria are used to maintain user-specified levels of structural safety by properly taking into account the uncertainties in the modelling and seismic loads that a structure may experience during its lifetime. Code-based requirements are also easily incorporated into this optimal design process. The methodology is demonstrated with a simple example involving the design of a three-storey steel-frame building for which the ground motion uncertainty is characterized by a probabilistic response spectrum which is developed from available attenuation formulas and seismic hazard models. Copyright © 1999 John Wiley & Sons, Ltd.     

Application of Generalized Regression Neural Networks in Predicting the Unconfined Compressive Strength of Carbonate Rocks

Measuring unconfined compressive strength (UCS) using standard laboratory tests is a difficult, expensive, and time-consuming task, especially with highly fractured, highly porous, weak rock. This study aims to establish predictive models for the UCS of carbonate rocks formed in various facies and exposed in Tasonu Quarry, northeast Turkey. The objective is to effectively select the explanatory variables from among a subset of the dataset containing total porosity, effective porosity, slake durability index, and P-wave velocity in dry samples and in the solid part of samples. This was based on the adjusted determination coefficient and root-mean-square error values of different linear regression analysis combinations using all possible regression methods. A prediction model for UCS was prepared using generalized regression neural networks (GRNNs). GRNNs were preferred over feed-forward back-propagation algorithm-based neural networks because there is no problem of local minimums in GRNNs. In this study, as a result of all possible regression analyses, alternative combinations involving one, two, and three inputs were used. Through comparison of GRNN performance with that of feed-forward back-propagation algorithm-based neural networks, it is demonstrated that GRNN is a good potential candidate for prediction of the unconfined compressive strength of carbonate rocks. From an examination of other applications of UCS prediction models, it is apparent that the GRNN technique has not been used thus far in this field. This study provides a clear and practical summary of the possible impact of alternative neural network types in UCS prediction.     

Assessment of soil and water contamination around an ash-disposal site: a case study from the Seyitömer coal-fired power plant in western Turkey

Seyitömer power plant comprises 4.8% of Turkey's total energy production. The fly ash produced has been deposited in the area, since the 1960s, by a dry disposal technique. In 1997, wet disposal was improperly exercised in the area causing ash flow over agricultural fields. This study is concerned with the chemical analysis of ash, soil and water samples collected in the area following ash-removal studies after the ash flow in 1997. The results reveal that Na, K, Ca, Mg, Mn, Al, Fe, Co, and Cr contents of soil and water are governed by basement lithology in the area, whereas Cd, Pb, Zn, and Cu contents are determined by fly ash from disposal sites. Although lithogenic Cr and Co contents are exceedingly high, comparison with the regulatory standards for drinking water, irrigation water and agricultural soils reveals no pollution pertinent to solid waste production in waters, whereas there is moderate pollution by Pb and Cu in soils.     

Geoid determination in Turkey (TG-91)

It is considered that precise geoid determination is one of the main current geodetic problems in Turkey since GPS defined coordinates require geoidal heights in practice. In order to determine the geoid by least squares collocation (LSC) the area covering Turkey was divided into 114 blocks of size 1° × 1°. LSC approximation to the geoid based upon the tailored geopotential model GPM2-T1 is constructed within each block. The model GPM2-T1 complete to degree and order 200 has been developed by tailoring of the model GPM2 to mean free-air anomalies and mean heights of one degree blocks in Turkey. Terrain effect reduced point gravity data spaced 5 × 5 within each block which the sides extended 0°.5 were used in LSC. Residual terrain model (RTM) depends on point heights at 15×20 griding and 5×5 and 15×15 mean heights has been carried out in terrain effect reduction. Indirect effect of RTM on geoid is also taken into account. The geoid, called Turkish Geoid 1991 (TG-91), referenced to GRS-80 ellipsoid has been computed at 3 × 3 griding nodes within each block. The quality of the TG-91 is also evaluated by comparing computed and GPS derived geoidal height differences, and 2.1 – 2.6 ppm accuracy for average baseline lenght of 45 km is obtained.     

Seismotectonic database of Turkey

Turkey is located in one of the most seismically active regions in the world. Characterizing seismic source zones in this region requires evaluation and integration of geological, geophysical, seismological and geodetical data. This first seismotectonic database for Turkey presented herein was prepared, under the framework of the National Earthquake Strategy and Action Plan—2023. The geographic information system (GIS)-based database includes maps of active faults, catalogues of instrumental and historical earthquakes, moment tensor solutions and data on crustal thickness. On the basis of these data, 18 major seismotectonic zones were delineated for Turkey and the surrounding region. The compilation and storage of the seismotectonic data sets in a digital GIS will allow analyses and systematic updates as new data accrete over time.     

Equilibrium data and process design for adsorption of disperse dyes onto Alunite

Adsorption of disperse dyes from aqueous solutions onto calcined alunite has been investigated to assess the possibility of using alunite for removing disperse dyes from aqueous solutions. The effects of particle size, adsorbent mass, initial pH and temperature of the dye solution on the adsorption capacities have been evaluated. Acidic pH was favorable for the adsorption of all dyes: Disperse Blue 56 (DB56), Disperse Red 74 (DR74) and Disperse Yellow 119 (DY119). The experimental data were correlated reasonably well by the Langmuir isotherm and the isotherm parameters (K_L and a_L) have been calculated. The adsorption capacities were found to be 498, 525 and 500 mg of dye per g of calcined alunite for DB56, DR74 and DY119, respectively. The single-stage batch adsorber design of the adsorption of disperse dyes onto alunite has been studied based on the Langmuir isotherm equation.