Ground motion estimation during the Kashmir earthquake of 8th October 2005

In this article, analytical methods have been used to estimate ground motion during the 8 October 2005, Kashmir earthquake. Peak ground acceleration (PGA) values at several stations in the epicentral region have been estimated by empirical analytical source mechanism models. As an alternate analysis, PGA estimates have also been obtained using the stochastic finite fault seismological model. The estimated PGAs are compared with that obtained from damage values. A PGA contour map in the near-source region is provided. It is found that very near to the epicenter, PGA would have reached more than 1 g. It is demonstrated that empirical analytical models can be effectively used to estimate ground motion due to rupture of active faults.     

Implementation of reconstructed geomorphologic units in landslide susceptibility mapping: the Melen Gorge (NW Turkey)

In the international literature, although considerable amount of publications on the landslide susceptibility mapping exist, geomorphology as a conditioning factor is still used in limited number of studies. Considering this factor, the purpose of this article paper is to implement the geomorphologic parameters derived by reconstructed topography in landslide susceptibility mapping. According to the method employed in this study, terrain is generalized by the contours passed through the convex slopes of the valleys that were formed by fluvial erosion. Therefore, slope conditions before landsliding can be obtained. The reconstructed morphometric and geomorphologic units are taken into account as a conditioning parameter when assessing landslide susceptibility. Two different data, one of which is obtained from the reconstructed DEM, have been employed to produce two landslide susceptibility maps. The binary logistic regression is used to develop landslide susceptibility maps for the Melen Gorge in the Northwestern part of Turkey. Due to the high correct classification percentages and spatial effectiveness of the maps, the landslide susceptibility map comprised the reconstructed morphometric parameters exhibits a better performance than the other. Five different datasets are selected randomly to apply proper sampling strategy for training. As a consequence of the analyses, the most proper outcomes are obtained from the dataset of the reconstructed topographical parameters and geomorphologic units, and lithological variables that are implemented together. Correct classification percentage and root mean square error (RMSE) values of the validation dataset are calculated as 86.28% and 0.35, respectively. Prediction capacity of the different datasets reveal that the landslide susceptibility map obtained from the reconstructed parameters has a higher prediction capacity than the other. Moreover, the landslide susceptibility map obtained from the reconstructed parameters produces logical results.     

Nonlinear Analysis of Local Site Effects on Seismic Ground Response in the Bam Earthquake

The influence of local geologic and soil conditions on the intensity of ground shaking is addressed in this study. The amplification of the ground motion due to local site effects resulted in severe damage to dwellings in the Bam area during the 2003 Bam Earthquake. A unique set of strong motion acceleration recordings was obtained at the Bam accelerograph station. Although the highest peak ground acceleration recorded was the vertical component (nearly 1 g), the longitudinal component (fault-parallel motion) clearly had the largest maximum velocity as well as maximum ground displacement. Subsurface geotechnical and geophysical (down-hole) data in two different sites have been obtained and used to estimate the local site condition on earthquake ground motion in the area. The ground response analyses have been conducted considering the nonlinear behavior of the soil deposits using both equivalent linear and nonlinear approaches. The fully nonlinear method embodied in FLAC was used to evaluate the nonlinear soil properties on earthquake wave propagation through the soil layer, and compare with the response from the equivalent linear approach. It is shown that thick alluvium deposits amplified the ground motion and resulted in significant damage in residential buildings in the earthquake stricken region. The comparison of results indicated similar response spectra of the motions for both equivalent and nonlinear analyses, showing peaks in the period range of 0.3–1.5 s. However, the amplification levels of nonlinear analysis were less than the equivalent linear method especially in long periods. The observed response spectra are shown to be above the NEHRP building code design requirements, especially at high frequencies.     

Spatial Variability of Rock Depth in Bangalore Using Geostatistical, Neural Network and Support Vector Machine Models

Geospatial technology is increasing in demand for many applications in geosciences. Spatial variability of the bed/hard rock is vital for many applications in geotechnical and earthquake engineering problems such as design of deep foundations, site amplification, ground response studies, liquefaction, microzonation etc. In this paper, reduced level of rock at Bangalore, India is arrived from the 652 boreholes data in the area covering 220 km². In the context of prediction of reduced level of rock in the subsurface of Bangalore and to study the spatial variability of the rock depth, Geostatistical model based on Ordinary Kriging technique, Artificial Neural Network (ANN) and Support Vector Machine (SVM) models have been developed. In Ordinary Kriging, the knowledge of the semi-variogram of the reduced level of rock from 652 points in Bangalore is used to predict the reduced level of rock at any point in the subsurface of the Bangalore, where field measurements are not available. A new type of cross-validation analysis developed proves the robustness of the Ordinary Kriging model. ANN model based on multi layer perceptrons (MLPs) that are trained with Levenberg–Marquardt backpropagation algorithm has been adopted to train the model with 90% of the data available. The SVM is a novel type of learning machine based on statistical learning theory, uses regression technique by introducing loss function has been used to predict the reduced level of rock from a large set of data. In this study, a comparative study of three numerical models to predict reduced level of rock has been presented and discussed.     

Zur Ermittlung der bestanschmiegenden Ebene zu einer Anzahl von,aus Erdbeben bestimmten Richtungen

Zusammenfassung Es werden mit Hilfe der sphärischen Trigonometrie und der Ausgleichsrechnung Methoden angegeben, die die Berechnung der bestanschmiegenden Ebene an eine Anzahl von Geraden mit einem gemeinsamen Punkt ermöglichen.

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Summary With the aid of the spherical trigonometry and the adjustment, methods are given to determin the best-fitting plane for a given set of directions through a common point.

     

An attempt to the explanation and to the prediction of the eleven-year cycle of solar activity

Summary According to the author the reason of the subsistence of the 11 years' sunspot cycle is to be found in the conjunction of the planets. As a result of the investigations it has been stated that from among the nine planets the joint tidal effect of Venus-Jupiter-Earth is a decisive factor in the variations of sunspot activity. The above three planets are every 10.4 years and 12.0 years respectively, in a close conjunction. The mean value (11.2 years) is in an almost full accordance with the average cycle-period. The fluctuations of the period of the cycle come from the fact that the planets' getting into approximately one line takes a different time within each cycle. This time delay is the cause of the stronger or weaker sunspot activity, and of the shorter or longer cycles.     

Basalt from Louisiana continental shelf

A basalt outcrop was discovered on Alderdice Bank on the outer Louisiana continental shelf. The basalt shows an age of 76.8 ± 3.3 × 10⁶ years. Textural, mineralogical, and chemical characteristics indicate that it is an alkali basalt of shallow intrusive origin. It was probably brought to the seafloor by salt tectonics and exposed due to salt dissolution.An accurate account of the Mesozoic geologic history of the Gulf of Mexico must consider the apparent consanguinity of all magmatic rocks of the region, including the Alderdice Bank basalt, and the apparent basinward decrease in age of magmatic activities.