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Coseismic slip model of the 2007 August Pisco earthquake (Peru) as constrained by Wide Swath radar observations 总被引：1，自引：0，他引：1
Mahdi Motagh Rongjiang Wang Thomas R. Walter Roland Bürgmann Eric Fielding Jan Anderssohn Jochen Zschau 《Geophysical Journal International》2008,174(3):842-848
The Pisco earthquake ( M w 8.0; 2007 August 15) occurred offshore of Peru's southern coast at the subduction interface between the Nazca and South American plates. It ruptured a previously identified seismic gap along the Peruvian margin. We use Wide Swath InSAR observations acquired by the Envisat satellite in descending and ascending orbits to constrain coseismic slip distribution of this subduction earthquake. The data show movement of the coastal regions by as much as 85 cm in the line-of-sight of the satellite. Distributed-slip model indicates that the coseismic slip reaches values of about 5.5 m at a depth of ∼18–20 km. The slip is confined to less than 40 km depth, with most of the moment release located on the shallow parts of the interface above 30 km depth. The region with maximum coseismic slip in the InSAR model is located offshore, close to the seismic moment centroid location. The geodetic estimate of seismic moment is 1.23 × 1021 Nm ( M w 8.06), consistent with seismic estimates. The slip model inferred from the InSAR observations suggests that the Pisco earthquake ruptured only a portion of the seismic gap zone in Peru between 13.5° S and 14.5° S, hence there is still a significant seismic gap to the south of the 2007 event that has not experienced a large earthquake since at least 1687. 相似文献
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Adaptation of ANFIS model to assess thermal comfort of an urban square in moderate and dry climate 总被引：1，自引：0，他引：1
Shahab Kariminia Shervin Motamedi Shahaboddin Shamshirband Dalibor Petković Chandrabhushan Roy Roslan Hashim 《Stochastic Environmental Research and Risk Assessment (SERRA)》2016,30(4):1189-1203
Attractiveness of the open urban spaces, such as plazas or squares, depends on the visitor’s thermal comfort. In this respect, it is important to assess the environment of such open space along with the demographic factors of the visitors. This study used the soft-computing method of adaptive neuro fuzzy inference system (ANFIS) to investigate the thermal comfort of visitors at a public square in Iran during hot and cold weather conditions. The ANFIS process for variable selection was implemented in order to detect the predominant variables affecting the individual’s comfortable feeling. Model’s training and testing data were collected through the field measurement and survey during hot and cold times of the year. We used 18 input parameters, representative of demographic and environmental factors, to compute visitor’s thermal sensation, comfort feeling, and 4 common indices, namely the mean radiant temperature (Tmrt), mean physiological equivalent temperature (PET), standard effective temperature (SET) and predicted mean vote (PMV). The results indicated that among the examined factors, the air temperature (Ta) is the most influential parameter and best predictor of accuracy for the individual’s comfort feeling at the studied urban square. The results show that Ta can best predict the common indices of outdoor comfort, namely the PMV, PET, SET, thermal sensation, Tmrt, and comfortable felling compared to other parameters with the least error of 1.94, 18.87, 13.67, 0.91, 7.80, and 0.34 %, respectively. Some of the main advantages of the ANFIS scheme are that it is adaptable to the optimization and adaptive methods, and is computationally efficient. 相似文献
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This article presents a comparison between two two-dimensional finite volume flood propagation models: SRH-2D and Hydro_AS-2D. The models are compared using an experimental dam-break test case provided by Soares-Frazão (J Hydraul Res, 2007. doi: 10.1080/00221686.2007.9521829). Four progressively refined meshes are used, and both models react adequately to mesh and time step refinement. Hydro_AS-2D shows some unphysical oscillations with the finest mesh and a certain loss of accuracy. For that test case, Hydro_AS-2D is more accurate for all meshes and generally faster than SRH-2D. Hydro_AS-2D reacts well to automatic calibration with PEST, whereas SRH-2D has some difficulties in retrieving the suggested Manning’s roughness coefficient. 相似文献
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Tayeb Sadeghifar Maryam Nouri Motlagh Massoud Torabi Azad Mahdi Mohammad Mahdizadeh 《Marine Geodesy》2017,40(6):454-465
The prediction of wave parameters has a great significance in the coastal and offshore engineering. For this purpose, several models and approaches have been proposed to predict wave parameters, such as empirical, soft computing, and numerical based approaches. Recently, soft computing techniques such as recurrent neural networks (RNN) have been used to develop sea wave prediction models. In this study, the RNN for wave prediction based on the data gathered and the measurement of the sea waves in the Caspian Sea, in the north of Iran is used for this study. The efficiency of RNNs for 3, 6, and 12 hourly and diurnal wave prediction using correlation coefficients is calculated to be 0.96, 0.90, 0.87, and 0.73, respectively. This indicates that wave prediction by using RNNs yields better results than the previous neural network approaches. 相似文献
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Local and mine scale exploration models for anomaly recognition within known ore fields are discussed. Traditional geochemical exploration methods are based on multivariate statistical analysis, metallometry, vertical geochemical zonality and criteria of natural field geochemical associations, which suffer several shortcomings, including lack of a geostatistical generalised approach for separating anomalies from background. These shortcomings make the interpretation process time consuming and costly. Fuzzy set theory, fuzzy logic and neural network techniques seem very well suited for typical mining geochemistry applications. The results, obtained from applying the proposed technique to a real scenario, reveals significant improvements, comparing the results obtained from applying multivariate statistical analysis. Computationally, the introduced technique makes possible, without exploration drilling, the distinction between blind mineralisation and zone of dispersed ore mineralisation. The methodology developed in this research study has been verified by testing it on various real-world mining geochemical projects. 相似文献
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Azam Shahnazar Hima Nikafshan Rad Mahdi Hasanipanah M. M. Tahir Danial Jahed Armaghani Mahyar Ghoroqi 《Environmental Earth Sciences》2017,76(15):527
Ground vibration is one of the common environmental effects of blasting operation in mining industry, and it may cause damage to the nearby structures and the surrounding residents. So, precise estimation of blast-produced ground vibration is necessary to identify blast-safety area and also to minimize environmental effects. In this research, a hybrid of adaptive neuro-fuzzy inference system (ANFIS) optimized by particle swarm optimization (PSO) was proposed to predict blast-produced ground vibration in Pengerang granite quarry, Malaysia. For this goal, 81 blasting were investigated, and the values of peak particle velocity, distance from the blast-face and maximum charge per delay were precisely measured. To demonstrate the performance of the hybrid PSO–ANFIS, ANFIS, and United States Bureau of Mines empirical models were also developed. Comparison of the predictive models was demonstrated that the PSO–ANFIS model [with root-mean-square error (RMSE) 0.48 and coefficient of determination (R 2) of 0.984] performed better than the ANFIS with RMSE of?1.61 and R 2 of 0.965. The mentioned results prove the superiority of the newly developed PSO–ANFIS model in estimating blast-produced ground vibrations. 相似文献
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A computationally robust framework for simulating geomaterial failure patterns is presented in this paper. Finite element simulations which feature the use of embedded discontinuities to track material failure are known to suffer from convergence issues due to a lack of robustness. Oftentimes, complex time step-cutting schemes or arc-length methods are required in order to achieve convergence. This may invariably limit the complexity of constitutive models available for use in tracking nonlinear material behavior. To this end, we use an implicit–explicit integration scheme [Impl–Ex (Oliver et al. in Comput Methods Appl Mech Eng 195(52):7093–7114, 2006)] coupled with a novel constitutive model which allows for combined opening and shearing displacement in tension, as well as frictional sliding in compression. We show that this framework is suitable for capturing complex fracture patterns in geomaterial structures without the need for elaborate continuance schemes. 相似文献
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The objective of research done in this study is to examine the variability of the length of day (LOD) and to investigate its correlation with ENSO (El Niño-Southern oscillation) episodes. For this purpose, the LOD time series (1962–2015), from the International Earth Rotation and Reference Systems Service (IERS), is investigated using the Singular Spectrum Analysis (SSA) technique. The results show that the LOD time series is very complex and is composed of several components: the long-term trend explains 95.97% of the original series, the annual harmonic 1.76% and the semi-annual 1.35%. Considering sea surface temperature anomalies (SSTA) index over the Niño3, Niño4 and Niño3.4 regions, Southern Oscillation Index (SOI) and Multivariate ENSO Index (MEI), the residuals signal, that represents only 0.92% of the initial LOD series, indicate a significant correlation with ENSO occurred during 1965–66, 1972–73, 1982–83 and 1997–98 El Niño events and 1970–71, 1973–74, 1988–89, 2007–08, 2010–11 La Niña ones. This is a pertinent result that suggests that LOD variability is at least partly related to ENSO phenomena. 相似文献