The seismic behaviour of a building on a liquefiable deposit is a complex interaction which involves quantifying both shaking induced damage and permanent ground deformation-related damage. In this paper the key parameters that influence both surface shaking and foundation settlements have been identified as the depth, thickness and liquefaction resistance of an equivalent liquefiable layer. These parameters can be used to develop an ‘equivalent soil profile’ that is analogous to the equivalent single degree-of-freedom that reduces the complexity of the dynamic response of a building into comparable and easily understood quantities. The equivalent soil profile is quantified independent of the seismic hazard, making it compatible with performance based design and assessment frameworks such that the building and soil profile can be directly assessed at different levels of seismic hazard. Several numerical studies are presented that demonstrate the influence of these key parameters on the ground surface shaking and foundation settlement. A set of criteria are proposed for classifying soil profiles into 22 different soil classes for regional loss assessment. An algorithm was developed for automatically fitting the equivalent soil profile to a cone penetration test trace and issues with the fitting are discussed. Field reconnaissance was undertaken to collect additional data to support existing datasets on the performance of buildings in Adapazari, during the 1999 Kocaeli, Turkey, earthquake (Mw = 7.4). The field case history data was used to investigate the correlation between the depth, thickness and liquefaction resistance of an equivalent liquefiable layer, on the extent of foundation permanent deformation. The case history data showed that in general a shallow, thick and weak liquefiable layer near the surface results in significant settlement but a lack of data for buildings on non-liquefiable deposits and the additional complexities involved with real buildings and soil deposits, meant that the trends observed in the idealised numerical models could not identified in the field case history data set.
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Izvestiya, Physics of the Solid Earth - Abstract—A devastating earthquake with magnitude Mw = 7.2 occurred in the Van region, Eastern Turkey, on October 23, 2011. This study analyzes the... 相似文献
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Geomagnetism and Aeronomy - Abstract—The main subject of the study is an analysis of time series of the width of annual rings of spruce and pine (D) that were obtained during the... 相似文献
3.
Gravity anomalies always include the total effects (combination of the structures which have different densities and depths) of the study area and beyond. And the well-known non-uniqueness of potential field modelling may lead to very different interpretation results.The finite element method (FEM), which has been used in potential field interpretation for decades, makes complex problems to be solved easily and accurately. The first step of FEM is to identify the elements and then to decide on the boundary of the solution space. In this step, the solution space is divided into elements. After determination of the geometrical structure of the solution space, the most suitable elements should be chosen for this geometrical structure. The agreement between the geometry and the elements is quite important for the convergence to the best possible solution.In this work, the methods of trend analysis, filtering, analytical continuation and FEM were applied to a theoretical model and to gravity data from western Turkey to produce the regional and the residual anomalies. The results were compared and it was found that the FEM produced more accurate results than other methods did. 相似文献
4.
Millen Maxim Viana da Fonseca Antonio Quintero Julieth Ferreira Cristiana Oztoprak Sadik Oser Cihan Bozbey Ilknur Aysal Namik Kosič Mirko Logar Janko 《Bulletin of Earthquake Engineering》2021,19(10):3987-4012
5.
The results of Global Navigational Satellite System (GNSS) observations in the regions of large earthquakes are analyzed. The characteristics of the Earth’s surface deformations before, during, and after the earthquakes are considered. The obtained results demonstrate the presence of anomalous deformations close to the epicenters of the events. Statistical estimates of the anomalous strains and their relationship with measurement errors are obtained. Conclusions are drawn about the probable use of local GNSS networks to assess the risk of the occurrence of strong seismic events. 相似文献
6.
Gvishiani A. D. Tatarinov V. N. Kaftan V. I. Losev I. V. Manevich A. I. 《Izvestiya Atmospheric and Oceanic Physics》2021,57(9):1151-1161
Izvestiya, Atmospheric and Oceanic Physics - In 2019, the construction of an underground research laboratory for justifying the geoecological safety of the disposal of highly active radioactive... 相似文献
7.
This study investigates the inverse solution on a buried and polarized sphere-shaped body using the self-potential method via multilayer perceptron neural networks (MLPNN). The polarization angle (α), depth to the centre of sphere (h), electrical dipole moment (K) and the zero distance from the origin (x 0) were estimated. For testing the success of the MLPNN for sphere model, parameters were also estimated by the traditional Damped Least Squares (Levenberg–Marquardt) inversion technique (DLS). The MLPNN was first tested on a synthetic example. The performance of method was also tested for two S/N ratios (5 % and 10 %) by adding noise to the same synthetic data, the estimated model parameters with MLPNN and DLS method are satisfactory. The MLPNN also applied for the field data example in ?zmir, Urla district, Turkey, with two cross-section data evaluated by MLPNN and DLS, and the two methods showed good agreement. 相似文献
8.
İlknur Kaftan 《Acta Geophysica》2017,65(4):627-634
A genetic algorithm (GA) is an artificial intelligence method used for optimization. We applied a GA to the inversion of magnetic anomalies over a thick dike. Inversion of nonlinear geophysical problems using a GA has advantages because it does not require model gradients or well-defined initial model parameters. The evolution process consists of selection, crossover, and mutation genetic operators that look for the best fit to the observed data and a solution consisting of plausible compact sources. The efficiency of a GA on both synthetic and real magnetic anomalies of dikes by estimating model parameters, such as depth to the top of the dike (H), the half-width of the dike (B), the distance from the origin to the reference point (D), the dip of the thick dike (δ), and the susceptibility contrast (k), has been shown. For the synthetic anomaly case, it has been considered for both noise-free and noisy magnetic data. In the real case, the vertical magnetic anomaly from the Pima copper mine in Arizona, USA, and the vertical magnetic anomaly in the Bayburt–Sar?han skarn zone in northeastern Turkey have been inverted and interpreted. We compared the estimated parameters with the results of conventional inversion methods used in previous studies. We can conclude that the GA method used in this study is a useful tool for evaluating magnetic anomalies for dike models. 相似文献
9.
Gvishiani A. D. Tatarinov V. N. Kaftan V. I. Manevich A. I. Dzeboev B. A. Losev I. V. 《Doklady Earth Sciences》2020,493(1):544-547
Doklady Earth Sciences - The paper presents the results of GNSS observations, provided by the authors in 2010-2019 years, in the zone of contact of tectonic structures of the Siberian platform,... 相似文献
10.
Artificial neural networks (ANN) have been used in a variety of problems in the fields of science and engineering. Applications of ANN to the geophysical problems have increased within the last decade. In particular, it has been used to solve such inversion problems as seismic, electromagnetic, resistivity. There are also some other applications such as parameter estimation, prediction, and classification. In this study, multilayer perceptron neural networks (MLPNN) and radial basis function neural networks (RBFNN) were applied to synthetic gravity data and Seferihisar gravity data to investigate the applicability and performance of these networks for the method of gravity. Additionally performance of MLPNN and RBFNN were tested by adding random noise to the same synthetic test data. The structure parameters, such as the depths, the density contrasts, and the locations of the structures were obtained closely for different signal-to-noise ratios (S/N). Bouguer data of Seferihisar area were analyzed by MLPNN and RBFNN to estimate depth, density contrast, and location of the structure. The results of MLPNN, RBFNN, and classical inversion method were compared for real data obtained from Seferihisar Geothermal area and similar structure parameters were obtained. The experiments show that in general RBFNN not only increases the speed of the training stage enormously, but also provides slightly better performance. 相似文献
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