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ABSTRACTIn this study, over 1000 data from the literature was used to characterize and compare the density, strengths, modulus, fracture toughness, porosity and the ultimate shear strengths of the gypsum, limestone and sandstone rocks. The compressive modulus and Mode-1 fracture toughness of the gypsum rock, limestone rock and sandstone rocks varied from 0.7 GPa to 70 GPa, and from 0.03 MPa.m0.5 to 2.6 MPa.m0.5 respectively. Vipulanandan correlation model was effective in relating the modulus of elasticity, fracture toughness with the relevant strengths of the rocks. A new nonlinear Vipulanandan failure criterion was developed to quantify the tensile strength, pure shear (cohesion) strength and to predict the maximum shear strength limit with applied normal stress on the gypsum, limestone and sandstone rocks. The Vipulanandan failure model predicts the maximum shear strength limit was, as the Mohr-Coulomb failure model does not have a limit on the maximum shear strength. With the Vipulanandan failure model based on the available data, the maximum shear strengths predicted for the gypsum, limestone and sandstone rocks were 64 MPa, 114 MPa and 410 MPa respectively. 相似文献
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Geotectonics - Kinematic characteristics of mylonite rocks in the footwall of the Chapedony detachment shear zone was investigated to highlight the exhumation style of the Chapedony Metamorphic... 相似文献
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Natural Hazards - Many landslides occur in the Karun watershed in the Zagros Mountains. In the present study, we employed a novel comparative approach for spatial modeling of landslides given the... 相似文献
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Saman Yaghmaei-Sabegh 《地震工程与工程振动(英文版)》2018,17(1):139-148
Macroseismic intensity data plays an important role in the process of seismic hazard analysis as well in developing of reliable earthquake loss models. This paper presents a physical-based model to predict macroseismic intensity attenuation based on 560 intensity data obtained in Iran in the time period 1975–2013. The geometric spreading and energy absorption of seismic waves have been considered in the proposed model. The proposed easy to implement relation describes the intensity simply as a function of moment magnitude, source to site distance and focal depth. The prediction capability of the proposed model is assessed by means of residuals analysis. Prediction results have been compared with those of other intensity prediction models for Italy, Turkey, Iran and central Asia. The results indicate the higher attenuation rate for the study area in distances less than 70 km. 相似文献
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Site classification is an important procedure for a reliable site-specific seismic hazard assessment. On the other hand, the site conditions at strong-motion stations are essential for accurate interpretation and analysis of the recorded ground motion data obtained from different regions of the world. For some countries with insufficient data on the subsurface geological settings, the required site condition information is not available. This paper presents a new and efficient approach for site classification based on artificial neural networks (ANN) along with a selected set of representative horizontal to vertical spectral ratio (HVSR) curves for four site classes. The nonlinear nature of ANN and their ability to learn in a complex environment make it highly suitable for function approximation and solving complicated engineering problems. Two types of radial basis function (RBF) neural networks, namely, probabilistic neural networks (PNN) and generalized regression neural networks (GRNN) were chosen in this study, as no separate training phase is required, rendering them particularly suitable for site classification. The proposed approach has been tested using data of the Chi-Chi, Taiwan, earthquake (Mw=7.6) recorded from 87 stations at which the site conditions are known. Analyses show that both the PNN and the GRNN perform very well with similar accuracy in estimating site conditions, with successful rates of 78% and 75%, respectively. 相似文献
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Natural Hazards - One of the most widely used relationships for prediction of b-value is the Aki–Utsu relationship, which is based on the maximum likelihood estimating. This method has some... 相似文献
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The characteristics of aftershocks can be quite different from those of mainshocks. However, most of the works in the past have generally focused on the aftershocks of strong earthquakes, while some moderate earthquakes can cause aftershocks with magnitudes close to the mainshocks. This paper focuses on the aftershocks characteristics of the 2012 Varzaghan–Ahar Doublet event (Mw?=?6.4, 6.2), northwest of Iran. Numerous aftershocks with magnitudes 3.7–5.5 recorded by the local seismic stations provide useful data to study the spectral characteristics at various periods. The predictive capability of the 2008 Next Generation Attenuation along with two regional models has been examined by several aftershock records obtained during these events. This paper is the first attempt made to compare the predictive capability of modern models based on significant aftershock data obtained for these two moderate events. Results confirmed that the ground motion models which have been derived based on larger-magnitude events should not directly be extrapolated to predict aftershock ground motions with magnitude smaller than 5.5, especially when we use relationships that developed without considering aftershock data. The residual analysis showed that the model of Abrahamson and Silva (Earthq Spectra, 24(1): 67–97, 2008) performed the best overall predictions in this study. However, this model performs poorly in the short period of 0.2 s at distances greater than 50 km which underestimates the spectral values for this case.
相似文献49.
F. Mirazizi A. Bahrami S. Soleimani Asl A. Zaribafan K. Haghbeen S. Aminzadeh 《International Journal of Environmental Science and Technology》2018,15(8):1679-1686
Tyrosinases, laccases, and peroxidases are three important groups of oxidative enzymes. A characteristic feature of these enzymes is their ability for the oxidation of aniline and phenolic compounds. Literature review reveals some overlap between the organic substrates of these enzymes, but how exactly they are different and how much they have in common from both substrate structure and rate of oxidation points of views. Can they complete functional efficiency of each other when co-immobilized in a multi-enzymes system? To address these questions, edible mushroom (Agaricus bisporus) tyrosinase, Neurospora crassa laccase, and horseradish peroxidase were examined for the oxidation of azo derivatives of anilines and phenols. These substances were selected because their enzymatic degradation is of interest to environmentalists and can be followed spectrophotometrically. Experiments showed that tyrosinase and laccase had limitations in oxidizing these substances, especially anilines, while peroxidase oxidized all the selected compounds. However, substrates carrying electron-withdrawing substituents had slower oxidation. Co-immobilization of tyrosinase and laccase would be effective against phenolic compounds, but phenols oxidation proceeds faster (between 100 and 500 times) if peroxidase and H2O2 are used. Combination of peroxidase and H2O2, instead of co-immobilization of tyrosinase, laccase, and peroxidase, seems to be more promising for the removal of organic pollutants from contaminated water resources. 相似文献
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ABSTRACTIn this study, we investigate the temporal oscillations of precipitation extremes in different climate regions of the United States. We apply quantile perturbation analysis to average daily precipitation and, to 1041 weather stations with high-quality data from 1900 to 2016. Moreover, we explore the relationship between the extreme precipitation and different well-known cyclical climate modes. Overall, the analysis of average daily precipitation identifies a drier condition in the middle decades of the twentieth century and, a wetter climate in the early century and recent decades. Moreover, the in situ analysis reveals a significant anomaly, mainly prevalent in the Central and Southern regions of the United States. We applied a finite set of linear regression models with different combinations of cyclical climate modes to inform the variability of anomalies with best performing models. Our results highlight the dominant effect of ENSO and NAO in the wide area of the United States. 相似文献