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Ahmadreza Hedayat Laura J. Pyrak-Nolte Antonio Bobet 《Rock Mechanics and Rock Engineering》2014,47(5):1575-1587
Seismic wave transmission and digital image correlation (DIC) are employed to study slip processes along frictional discontinuities. A series of biaxial compression experiments are performed on gypsum specimens with non-homogeneous contact surfaces. The specimens are composed of two blocks with perfectly mated contact surfaces with a smooth surface with low frictional strength on the upper half and a rough surface with high frictional strength on the lower half. Compressional, P, and shear, S, wave pulses were transmitted through the discontinuity while digital images of the specimen surface were acquired during the test. A distinct peak in the amplitude of transmitted wave occurs prior to the peak shear strength and is considered a “precursor” to the failure. Precursors indicate that slip initiates from the smooth surface and extends to the rough surface as the shear load is increased. From the DIC data, slip is identified as a jump in the displacement field along the fracture that initiates from the smooth surface and propagates to the rough surface. Precursors are associated with an increase in the rate of slip across the discontinuity and are a measure of the reduction in the fracture shear stiffness. 相似文献
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Sayed Zia Mohammadi Daryoush Afzali Mohammad Ali Taher Hedayat Darijani 《洁净——土壤、空气、水》2010,38(2):140-145
In the present article, a procedure for the simultaneous separation and preconcentration of trace amounts of cadmium and zinc is proposed. It is based on the adsorption of cadmium and zinc ions onto a column of Amberlite XAD‐4 resin loaded with aluminon reagent. Cadmium and zinc ions are quantitatively retained on the column in the pH range from 6.5–7.5, at a flow rate of 2 mL min–1. The cadmium and zinc ions are eluted with 5.0 mL of 5 mol L–1 HNO3 solution. Cadmium and zinc are measured by flame atomic absorption spectrometry (FAAS). In the present case, 0.1 μg of cadmium and 0.5 μg of zinc can be concentrated in the column from 1000 mL of aqueous sample, where their concentrations are as low as 0.1 and 0.5 ng mL–1, respectively. The relative standard deviations, for seven replicated determinations of 1.0 μg mL–1 of cadmium and zinc, are 1.2 and 1.1%, respectively. The detection limits for cadmium and zinc in the original solution are 0.02 and 0.11 ng mL–1, respectively. The interference of a large number of anions and cations has been studied and the optimized conditions are utilized for the determination of trace amounts of cadmium and zinc in different environmental and standard samples. 相似文献
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Talatahari Siamak Veladi Hedayat Azizi Mahdi Moutabi-Alavi Ali Rahnema Salar 《地震工程与工程振动(英文版)》2022,21(3):825-842
Earthquake Engineering and Engineering Vibration - In this paper, the potential of utilizing improved metaheuristic approaches in optimal design of building structures is concerned. In this regard,... 相似文献
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Learning from data for wind-wave forecasting 总被引：1，自引：0，他引：1
Along with existing numerical process models describing the wind-wave interaction, the relatively recent development in the area of machine learning make the so-called data-driven models more and more popular. This paper presents a number of data-driven models for wind-wave process at the Caspian Sea. The problem associated with these models is to forecast significant wave heights for several hours ahead using buoy measurements. Models are based on artificial neural network (ANN) and instance-based learning (IBL) .To capture the wind-wave relationship at measurement sites, these models use the existing past time data describing the phenomenon in question. Three feed-forward ANN models have been built for time horizon of 1, 3 and 6 h with different inputs. The relevant inputs are selected by analyzing the average mutual information (AMI). The inputs consist of priori knowledge of wind and significant wave height. The other six models are based on IBL method for the same forecast horizons. Weighted k-nearest neighbors (k-NN) and locally weighted regression (LWR) with Gaussian kernel were used. In IBL-based models, forecast is made directly by combining instances from the training data that are close (in the input space) to the new incoming input vector. These methods are applied to two sets of data at the Caspian Sea. Experiments show that the ANNs yield slightly better agreement with the measured data than IBL. ANNs can also predict extreme wave conditions better than the other existing methods. 相似文献
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In this research, the simulation of Urmia Lake water level fluctuation by means of two models was applied. For this, Support Vector Machines (SVM), and Neural Wavelet Network (NWN) models that conjugated both the wavelet function and ANN, developed for simulating the Urmia Lake water level fluctuation. The yearly data of rainfall, temperature and discharge to the Urmia Lake and water level fluctuation were used. Urmia Lake is the biggest and the hyper saline lake in Iran. The outcome of the SVM based models are compared with the NWN. The results of SVM model performs better than NWN and offered a practical solution to the problem of water level fluctuation predictions. Analysis results showed that the optimal situation occurred with use of precipitation, temperature and discharge for all station and water level fluctuations at the lag time of one year (RMSEs) of 0.23, 0.41 m obtained by SVM, NWN, respectively, and SSEs of 0.43, 1.33 and R 2 of 0.97, 0 obtained by SVM, NWN, respectively. The results of SVM model show better accuracy in comparison with the NWN model. 相似文献
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The hyperbolic Radon transform has a long history of applications in seismic data processing because of its ability to focus/sparsify the data in the transform domain. Recently, deconvolutive Radon transform has also been proposed with an improved time resolution which provides improved processing results. The basis functions of the (deconvolutive) Radon transform, however, are time-variant, making the classical Fourier based algorithms ineffective to carry out the required computations. A direct implementation of the associated summations in the time–space domain is also computationally expensive, thus limiting the application of the transform on large data sets. In this paper, we present a new method for fast computation of the hyperbolic (deconvolutive) Radon transform. The method is based on the recently proposed generalized Fourier slice theorem which establishes an analytic expression between the Fourier transforms associated with the data and Radon plane. This allows very fast computations of the forward and inverse transforms simply using fast Fourier transform and interpolation procedures. These canonical transforms are used within an efficient iterative method for sparse solution of (deconvolutive) Radon transform. Numerical examples from synthetic and field seismic data confirm high performance of the proposed fast algorithm for filling in the large gaps in seismic data, separating primaries from multiple reflections, and performing high-quality stretch-free stacking. 相似文献
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