Seismic damage assessment based on regional synthetic ground motion dataset: a case study for Erzincan,Turkey

Estimation of seismic losses is a fundamental step in risk mitigation in urban regions. Structural damage patterns depend on the regional seismic properties and the local building vulnerability. In this study, a framework for seismic damage estimation is proposed where the local building fragilities are modeled based on a set of simulated ground motions in the region of interest. For this purpose, first, ground motion records are simulated for a set of scenario events using stochastic finite-fault methodology. Then, existing building stock is classified into specific building types represented with equivalent single-degree-of-freedom models. The response statistics of these models are evaluated through nonlinear time history analysis with the simulated ground motions. Fragility curves for the classified structural types are derived and discussed. The study area is Erzincan (Turkey), which is located on a pull-apart basin underlain by soft sediments in the conjunction of three active faults as right-lateral North Anatolian Fault, left-lateral North East Anatolian Fault, and left-lateral Ovacik Fault. Erzincan city center experienced devastating earthquakes in the past including the December 27, 1939 (Ms = 8.0) and the March 13, 1992 (Mw?=?6.6) events. The application of the proposed method is performed to estimate the spatial distribution of the damage after the 1992 event. The estimated results are compared against the corresponding observed damage levels yielding a reasonable match in between. After the validation exercise, a potential scenario event of Mw?=?7.0 is simulated in the study region. The corresponding damage distribution indicates a significant risk within the urban area.     

Fossil findings from the Sıcak Çermik fissure ridge-type travertines and possible hominid tracks,Sivas, Central Turkey

S?cak Çermik (Sivas) is an important geothermal and recent travertine formation area in Central Anatolia. The majority of travertines found in the region comprise fissure-ridge type travertines according to morphological classification. At the location called Tepe Çermik within the travertine area, fill containing fossil bone fragments of Equus sp., Bovidae and other abundant animals formed within the fracture axis of a N–S striking fissure-ridge travertine developed under control of tectonic forces. The finds of these fossils in fissure-ridge travertines linked to tectonic forces indicates formation of a unique fossil environment created under the control of these forces. The Accelerator Mass Spectrometry Radiocarbon Dating analyses of fossils from the study area determined the fills were older than 43,000 years. The U/Th age of a sample from the most recently-formed banded travertine in the axis of the fracture was identified as 278,540 ± 18,436 years. As a result, the ages of fossils found within this fill are thought to be between 43,000 and 278,540 ± 18,436 years old. The high amount of perissodactyla and artiodactyla fossils found within fill in the axis of the fissure-ridge travertine probably indicates the presence of hominids who chose the region for hunting or settlement. The Equus sp. and Bovidae fossil samples found in the axis of the fracture indicate that in the dry and cold glacial period the paleogeography in a large portion of Anatolia comprised desert-like steppe.     

A case study of in situ oil contamination in a mangrove swamp (Rio De Janeiro, Brazil)

Mangroves are sensitive ecosystems of prominent ecological value that lamentably have lost much of their areas across the world. The vulnerability of mangroves grown in proximity to cities requires the development of new technologies for the remediation of acute oil spills and chronic contaminations. Studies on oil remediation are usually performed with in vitro microcosms whereas in situ experiments are rare. The aim of this work was to evaluate oil degradation on mangrove ecosystems using in situ microcosms seeded with an indigenous hydrocarbonoclastic bacterial consortium (HBC). Although the potential degradation of oil through HBC has been reported, their seeding directly on the sediment did not stimulate oil degradation during the experimental period. This is probably due to the availability of carbon sources that are easier to degrade than petroleum hydrocarbons. Our results emphasize the fragility of mangrove ecosystems during accidental oil spills and also the need for more efficient technologies for their remediation.     

Modeling of trophospheric ozone concentrations using genetically trained multi-level cellular neural networks

Tropospheric ozone concentrations, which are an important air pollutant, are modeled by the use of an artificial intelligence structure. Data obtained from air pollution measurement stations in the city of Istanbul are utilized in constituting the model. A supervised algorithm for the evaluation of ozone concentration using a genetically trained multi-level cellular neural network （ML-CNN） is introduced, developed, and applied to real data. A genetic algorithm is used in the optimization of CNN templates. The model results and the actual measurement results are compared and statistically evaluated. It is observed that seasonal changes in ozone concentrations are reflected effectively by the concentrations estimated by the multilevel-CNN model structure, with a correlation value of 0.57 ascertained between actual and model results. It is shown that the multilevel-CNN modeling technique is as satisfactory as other modeling techniques in associating the data in a complex medium in air pollution applications.     

Automated 1D interpretation of resistivity soundings by simultaneous use of the direct and iterative methods*

Noise contamination of measured data greatly affects the final results of inversion. Three types of noise source — random and systematic errors and the uncertainties due to the inadequacy of the mathematical model in representing the actual physical conditions — are discussed in the framework of resistivity sounding data. Two methods are proposed for describing these uncertainties. The first possibility is to smooth the measured data by a combination of simple fitting functions that satisfies the ‘1D smoothness’ criteria and consequently simulates the behaviour of a 1D Schlumberger apparent resistivity curve. The second method is to derive weight coefficients from the differences between the measured and the smoothed data sets. Both methods are carried out under the control of the interpreter. The relative merits and drawbacks of the direct and iterative interpretation methods used for the estimation of the parameters of the layered earth model are summarized. Two variants of the combination of these methods are presented to obtain more powerful and automatic interpretation schemes. In the sequential interpretation, an initial guess supplied by the direct method is improved by the iterative method to obtain a reasonable fit between the measured data and the model response. In the simultaneous interpretation, the successive application of the direct and iterative methods is carried out, starting from the first branch of the apparent resistivity curve. The operation is then shifted to subsequent branches that represent the deeper parts of the geoelectric section. This is similar to the data acquisition applied in direct current sounding in which the depth penetration is increased by expanding the current electrode spacings. The proposed sequential and simultaneous interpretation algorithms require minimum aids and efforts of the interpreter.     

Nonlinear meta-models for conceptual seakeeping design of fishing vessels

The scope of this paper is to develop the nonlinear meta-models for seakeeping behaviour, considering the fishing vessels. These models are intended to be inserted either in a multiattribute design selection process or in a comprehensive multiobjective optimization procedure. For this purpose, seakeeping data of fishing vessels in regular head waves are used to develop meta-models of transfer functions of heave, pitch and vertical acceleration by nonlinear analysis. A home-made software considers two databases; the first is composed by the ship dimensions and coefficients of fishing vessels, and the second is their ship motion data obtained by employing a strip-theory calculation. The meta-models are proposed to predict the vertical motion characteristics for given ranges of speed and wave length during the concept design stage. The independent variables are hull size (Δ), main dimensions (L, B, T), and some hydrostatic parameters (C_WP, C_VP, LCB, LCF, etc.). The results estimated by the software show good correspondences with the ones achieved by direct computations. The study provides additional insight on the influence of hull form parameters on seakeeping performance of small vessels having form properties and parametric range corresponding to the investigated vessels.