Hydrogeochemical evaluation of Umut geothermal field (SW Turkey)

Tekkehamam geothermal field is located in the South of Menderes Graben (Aegean region) and is one of the most important geothermal sites of Western Anatolia. Umut geothermal field is a part of the Tekkehamam field. This study was conducted in order to determine the origin and hydrogeochemical properties of the geothermal waters. For this purpose, sampling was done in order to check the chemistry of the water, and ¹⁸O, ²H isotope analyses done at four wells, nine natural springs and three cold water sources. According to the results of the chemical analysis, the geothermal waters were determined to be of Na + K-SO₄ type. Additionally, ¹⁴C and ³H analyses were done in selected well and spring waters for the purpose of age determination of groundwater; most of the waters were determined to be submodern. Geothermometer calculations show that the reservoir temperature for the Umut geothermal field ranges between 148 and 180 °C. Stable isotope results indicate that Umut geothermal waters are meteoric in origin. Mixing between shallow and deep waters is the dominant subsurface process that determines the physical and chemical character of the waters.     

Investigation of the Kumdanlı and surrounding faults on the Eğirdir Lake by conducting ground penetrating radar (GPR) profiles

A ground penetrating radar (GPR) survey was performed on the E?irdir Lake to obtain the structural properties of Kumdanl? and surrounding faults. GPR data was collected along ten profiles in various directions by using 100–200-MHz GPR antennas. The radar sections showed that the Kumdanl? Fault, SW-NE in direction, and also some other neighboring NW-SE normal faults have played an active role in forming the E?irdir-Hoyran Lakes. The deformation and the geometry obtained from the results show that the Kumdanl? Fault is a sinistral strike-slip fault including oblique and segmented displacements. The other faults (Kemerdam? and Akkeçili) have mainly normal fault systems. Their trends are generally NW-SE in direction. It is also observed that they are younger than the Kumdanl? Fault system. These fault properties demonstrate the E?irdir Lake side has an extensional structure trending SW-NE.     

Displacement amplification factors for steel eccentrically braced frames

Inelastic deformation capacity of links is a factor that significantly influences design of steel eccentrically braced frames (EBFs). The link rotation angle is used to describe inelastic link deformation. The link rotation angle is generally calculated by making use of design story drifts that in turn are calculated by modifying the elastic displacements by a displacement amplification factor. This paper presents a numerical study undertaken to evaluate the displacement amplification factor given in ASCE7‐10 for EBFs and the rigid‐plastic mechanism used for calculating link rotation angles. A total of 72 EBFs were designed by considering the number of stories, the bay width, the link length to bay width ratio, and the seismic hazard level as the prime variables. All structures were analyzed using elastic and inelastic time history analyses. The results indicated that the displacement amplification factor given in ASCE7‐10 provides unconservative estimates of the story drifts. On the other hand, the rigid‐plastic mechanism provides conservative estimates of link rotations. Based on the results of the numerical study, a new set of displacement amplification factors that vary along the height of the structure and modifications to the rigid‐plastic mechanism were developed. In light of the proposed modifications, the EBFs were redesigned and analyzed using inelastic time history analysis. The results indicated that the proposed modifications provide improvements for the displacement amplification factor and link rotation angle calculation procedures. Copyright © 2014 John Wiley & Sons, Ltd.     

Joint parameter estimation from magnetic resonance and vertical electric soundings using a multi‐objective genetic algorithm

Magnetic resonance sounding (MRS) has increasingly become an important method in hydrogeophysics because it allows for estimations of essential hydraulic properties such as porosity and hydraulic conductivity. A resistivity model is required for magnetic resonance sounding modelling and inversion. Therefore, joint interpretation or inversion is favourable to reduce the ambiguities that arise in separate magnetic resonance sounding and vertical electrical sounding (VES) inversions. A new method is suggested for the joint inversion of magnetic resonance sounding and vertical electrical sounding data. A one‐dimensional blocky model with varying layer thicknesses is used for the subsurface discretization. Instead of conventional derivative‐based inversion schemes that are strongly dependent on initial models, a global multi‐objective optimization scheme (a genetic algorithm [GA] in this case) is preferred to examine a set of possible solutions in a predefined search space. Multi‐objective joint optimization avoids the domination of one objective over the other without applying a weighting scheme. The outcome is a group of non‐dominated optimal solutions referred to as the Pareto‐optimal set. Tests conducted using synthetic data show that the multi‐objective joint optimization approximates the joint model parameters within the experimental error level and illustrates the range of trade‐off solutions, which is useful for understanding the consistency and conflicts between two models and objectives. Overall, the Levenberg‐Marquardt inversion of field data measured during a survey on a North Sea island presents similar solutions. However, the multi‐objective genetic algorithm method presents an efficient method for exploring the search space by producing a set of non‐dominated solutions. Borehole data were used to provide a verification of the inversion outcomes and indicate that the suggested genetic algorithm method is complementary for derivative‐based inversions.     

Key pluvial parameters in assessing rainfall erosivity in the south-west development region,Romania

Located in the south-western part of Romania, the south-west development region overlaps the main relief forms: the Carpathians mountains, the Getic Subcarpathians, the Getic piedmont, the Romanian plain and the Danube valley. The study aims at providing an overview on the main pluvial parameters and their role in assessing rainfall erosivity in the study area. The authors assessed the occurrence, frequency and magnitude of some of the most significant pluvial parameters and their impact on the climatic aggressiveness in the study area. Thus, the monthly and annual mean and extreme climatic values for different rainfall related parameters (e.g., maximum amounts of precipitation/24 hr, heavy rainfall), as well as relevant indices and indicators for pluvial aggressiveness (Fournier, Fournier Modified, Angot) were calculated. The rainfall erosivity was assessed in order to provide both the spatial distribution of the triggering extreme weather phenomena and the resulted intensity classes for the analysed indices and indicators. The authors used long-term precipitation records (1961–2010) for the selected relevant meteorological stations distributed throughout all analysed relief units.     

Batch and Column Experiments to Support Heavy Metals (Cu,Zn, and Mn) Transport Modeling in Alluvial Sediments Between the Mogan Lake and the Eymir Lake,Gölbaşı, Ankara

This article describes laboratory batch sorption and column transport experiments that were conducted using heterogeneous alluvial sediments with a wide physical characteristic from wells, located between Lake Mogan and Lake Eymir, Gölbaşı, Ankara. The batch sorption experiment was conducted in two separate systems, that is, single and multicomponents. Single batch experiment was performed to determine equilibrium condition between the heavy metal ions and the soil adsorption sites. The sorption isotherms data from multibatch experiments were used to calculate the sorption parameters. Single batch experiment indicated that equilibrium was attained within 9 days from the start of the sorption test. As a result of multicomponents batch experiments, for Zn and Mn, the sorption process was well described by the Freundlich or Langmuir isotherm model, whereas sorption of Cu was better described by the linear isotherm model. The K_d of Cu were found to be highest in soil 1 (32550.350 L kg⁻¹) and lowest in soil 5 (18170.76 L kg⁻¹). The maximum and minimum sorption capacity values for Zn were found to be in soil 1 (10985.148 mg kg⁻¹) and in soil 2 (8597.14 mg kg⁻¹) units, respectively. [Correction added after online publication 15 July, 2010: In the preceding sentence, the words “minimum” and “maximum” were initially switched.] Similarly, soil 1 (7587.391 mg kg⁻¹) and soil 5 (4908.695 mg kg⁻¹) units provided the maximum and minimum values for Mn. In the column experiments, flow and tracer transport was studied under saturated conditions using conservative tracer to determine the transport parameters. Transport parameter values were obtained by curve-fitting using the nonlinear least-squares optimization code CXTFIT. Results of the column experiments indicated that the dispersivity values obtained for soil samples were in the range of 0.024 to 1.13 cm.     

Adaptive neuro-fuzzy modeling for the swelling potential of compacted soils

This paper aims to present the usability of an adaptive neuro fuzzy inference system (ANFIS) for the prediction swelling potential of the compacted soils that are important materials for geotechnical purposes such as engineered barriers for municipal solid waste, earth dams, embankment and roads. In this study the swelling potential that is also one of significant parameters for compacted soils was modeled by ANFIS. For the training and testing of ANFIS model, data sets were collected from the tests performed on compacted soils for different geotechnical application in Nigde. Four parameters such as coarse-grained fraction ratio (CG), fine-grained fraction ratio (FG), plasticity index (PI) and maximum dry density (MDD) were presented to ANFIS model as inputs. The results obtained from the ANFIS models were validated with the data sets which are not used for the training stage. The analyses revealed that the predictions from ANFIS model are in sufficient agreement with test results.