Three-dimensional seismic stability of locally loaded slopes under a rotational velocity field

In practical engineering, slopes subjected to local loads, like footings of buildings, are common. This paper aims to give an insight into the effect of seismic force on the stability of locally loaded slopes. Numerical methods can be used to study this problem, but they require much computational time. Contrarily, limit analysis method is an approach to perform slope stability analysis with high computational efficiency. Thus, an accurate approach in mechanical points is proposed for this problem based on limit analysis method herein. In the framework of limit analysis, existing research about this problem used a kinematically translational velocity field. However, the velocity field of the locally loaded slope at failure is proved to be rotational possibly. Thus, to fill this gap, a 3D rotational velocity field is employed herein to obtain limit loads on the slope top, which improves the existing upper-bound solutions obtained by using the translational velocity field. The particle swarm optimization algorithm and the Nelder-Mead simplex algorithm are employed to search the global minimum of the upper-bound estimation of the limit load. Parametric analysis is performed and it shows that the limit load increases with the increase of a/H or the internal friction angle φ but decreases as the slope angle β or the length-to-width ratio (L/t) of the local load increases. Furthermore, the limit load is found to decrease with the increase of the seismic coefficient kh and it is proportional to the seismic coefficient

Photometric Variability in the CSTAR Field: Results From the 2008 Data Set

The Chinese Small Telescope ARray (CSTAR) is the first telescope facility built at Dome A, Antarctica. During the 2008 observing season, the installation provided long-baseline and high-cadence photometric observations in the i-band for 18,145 targets within 20 deg2 CSTAR field around the South Celestial Pole for the purpose of monitoring the astronomical observing quality of Dome A and detecting various types of photometric variability. Using sensitive and robust detection methods, we discover 274 potential variables from this data set, 83 of which are new discoveries. We characterize most of them, providing the periods, amplitudes and classes of variability. The catalog of all these variables is presented along with the discussion of their statistical properties.Comment: 38 pages, 11 figures, 4 tables; Accepted for publication in ApJ

Bearing Fault Diagnosis in the Mixed Domain Based on Crossover-Mutation Chaotic Particle Swarm

The classification frameworks for fault diagnosis of rolling element bearings in rotating machinery are mostly based on analysis in a single time-frequency domain, where sensitive features are not completely extracted. To solve this problem, a new fault diagnosis technique is proposed in the mixed domain, based on the crossover-mutation chaotic particle swarm optimization support vector machine. Firstly, fault features are generated using techniques in the time domain, the frequency domain, and the time-frequency domain. Secondly, the weighted maximum relevance minimum redundancy (WMRMR) algorithm is adopted to reduce the dimension of the feature set and to establish the representative feature set. Thirdly, a new crossover-mutation strategy is suggested to reduce the local minima in optimization, and an optimization disturbance is added. Finally, the support vector machine is optimized using the improved chaotic particle swarm to improve fault classification diagnosis. The effectiveness of the proposed new bearing fault diagnostic technique is verified by experimental tests under different bearing conditions. Test results showed that the bearing fault classification accuracy of CMCPSO-SVM in the mixed domain was much higher than those in a single feature domain

Predictions of Geological Interface Using Relevant Vector Machine with Borehole Data

Due to the discreteness, sparsity, multidimensionality, and incompleteness of geotechnical investigation data, traditional methods cannot reasonably predict complex stratigraphic profiles, thus hindering the three-dimensional (3D) reconstruction of geological formation that is vital to the visualization and digitization of geotechnical engineering. The machine learning method of relevant vector machine (RVM) is employed in this work to predict the 3D stratigraphic profile based on limited geotechnical borehole data. The hyper-parameters of kernel functions are determined by maximizing the marginal likelihood using the particle swarm optimization algorithm. Three kinds of kernel functions are employed to investigate the prediction performance of the proposed method in both 2D analysis and 3D analysis. The 2D analysis shows that the Gauss kernel function is more suitable to deal with nonlinear problems but is more sensitive to the number of training data and it is better to use spline kernel functions for RVM model trainings when there are few geotechnical investigation data. In the 3D analysis, it is found that the prediction result of the spline kernel function is the best and the relevant vector machine model with a spline kernel function performs better in the area with a fast change in geological formation. In general, the RVM model can be used to achieve the purpose of 3D stratigraphic reconstruction

Transiting Exoplanet Monitoring Project (TEMP). I. Refined System Parameters and Transit Timing Variations of HAT-P-29b

© 2018. The American Astronomical Society. All rights reserved. We report the photometry of six transits of the hot Jupiter HAT-P-29b obtained from 2013 October to 2015 January. We analyze the new light curves, in combination with the published photometric, Doppler velocimetric, and spectroscopic measurements, finding an updated orbital ephemeris for the HAT-P-29 system, TC TDB [0 2456170.5494 15 BJD = ] and P=5.723390(13) days. This result is 17.63 s (4.0s) longer than the previously published value, amounting to errors exceeding 2.5 hr at the time of writing (on UTC 2018 June 1). The measured transit mid-times for HAT-P-29b show no compelling evidence of timing anomalies from a linear model, which rules out the presence of perturbers with masses greater than 0.6, 0.7, 0.5, and 0.4 M? near the 1:2, 2:3, 3:2, and 2:1 resonances with HAT-P-29b, respectively

Transiting Exoplanet Monitoring Project (TEMP). I. Refined System Parameters and Transit Timing Variations of HAT-P-29b

We report the photometry of six transits of the hot Jupiter HAT-P-29b obtained from 2013 October to 2015 January. We analyze the new light curves, in combination with the published photometric, Doppler velocimetric, and spectroscopic measurements, finding an updated orbital ephemeris for the HAT-P-29 system, TC TDB [0 2456170.5494 15 BJD = ] and P=5.723390(13) days. This result is 17.63 s (4.0s) longer than the previously published value, amounting to errors exceeding 2.5 hr at the time of writing (on UTC 2018 June 1). The measured transit mid-times for HAT-P-29b show no compelling evidence of timing anomalies from a linear model, which rules out the presence of perturbers with masses greater than 0.6, 0.7, 0.5, and 0.4 M? near the 1:2, 2:3, 3:2, and 2:1 resonances with HAT-P-29b, respectively