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Navid Hosseini Kamran Goshtasbi Behdeen Oraee-Mirzamani Mehran Gholinejad 《Arabian Journal of Geosciences》2014,7(5):1951-1956
The state of periodic loading and the interval of periodic roof weighting have an important role in geomechanical stability and, hence, in the continuity of longwall mining operations. In this paper, the mechanism of roof caving in longwall mining—together with the effect of engineering and geomechanical properties of surrounding rock masses on the magnitude and timing of periodic loading—is studied. For this purpose, a longwall mine is first modeled using Phase2 software, and then, by simulating the roof caving process, the periodic roof weighting intervals is calculated. Based on the numerical modeling, the first roof weighting interval and the periodic roof weighting interval are calculated as 27.2 and 12.1 m, respectively. Sensitivity analysis is then applied to determine the effect of changes in the mechanical properties of the rock mass, especially in the main roof and immediate roof. The results of the analysis show that as GSI and quality of the immediate roof increases, the periodic roof weighting interval also increases. Hence, the applied algorithm in this research study can effectively be utilized to calculate the periodic roof weighting interval in the longwall mining method. 相似文献
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Elyas Hayati Ehsan Abdi Mohsen Mohseni Saravi John L. Nieber Baris Majnounian Giovanni B. Chirico 《水文研究》2018,32(16):2570-2583
An experimental campaign was set up to quantify the contribution of evapotranspiration fluxes on hillslope hydrology and stability for different forest vegetation cover types. Three adjacent hillslopes, respectively, covered by hardwood, softwood, and grass were instrumented with nine access tubes each to monitor soil water dynamics at the three depths of 30, 60, and 100 cm, using a PR2/6 profile probe (Delta‐T Devices Ltd) for about 6 months including wet periods. Soil was drier under softwood and wetter under grass at all the three depths during most of the monitoring period. Matric suction derived via the soil moisture measurements was more responsive to changes in the atmospheric conditions and also recovered faster at the 30 cm depth. Results showed no significant differences between mean matric suction under hardwood (101.6 kPa) with that under either softwood or grass cover. However, a significant difference was found between mean matric suction under softwood (137.5 kPa) and grass (84.3 kPa). Results revealed that, during the wettest period, the hydrological effects from all three vegetation covers were substantial at the 30 cm depth, whereas the contribution from grass cover at 60 cm (2.0 kPa) and 100 cm (1.1 kPa) depths and from hardwood trees at 100 cm depth (1.2 kPa) was negligible. It is surmised that potential instability would have occurred at these larger depths along hillslopes where shallow hillslope failures are most likely to occur in the region. The hydrological effects from softwood trees, 8.1 and 3.9 kPa, were significant as the corresponding factor of safety values showed stable conditions at both depths of 60 and 100 cm, respectively. Therefore, the considerable hydrological reinforcing effects from softwood trees to the 100 cm depth suggest that a hillslope stability analysis would show that hillslopes with softwood trees will be stable even during the wet season. 相似文献
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Soil water dynamics under different forest vegetation cover: Implications for hillslope stability 总被引:1,自引:0,他引:1
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Elyas Hayati Ehsan Abdi Mohsen Mohseni Saravi John L. Nieber Baris Majnounian Giovanni B. Chirico Bruce Wilson Moharramali Nazarirad 《地球表面变化过程与地形》2018,43(10):2106-2120
Though it is well known that vegetation affects the water balance of soils through canopy interception and evapotranspiration, its hydrological contribution to soil hydrology and stability is yet to be fully quantified. To improve understanding of this hydrological process, soil water dynamics have been monitored at three adjacent hillslopes with different vegetation covers (deciduous tree cover, coniferous tree cover, and grass cover), for nine months from December 2014 to September 2015. The monitored soil moisture values were translated into soil matric suction (SMS) values to facilitate the analysis of hillslope stability. Our observations showed significant seasonal variations in SMS for each vegetation cover condition. However, a significant difference between different vegetation covers was only evident during the winter season where the mean SMS under coniferous tree cover (83.6 kPa) was significantly greater than that under grass cover (41 kPa). The hydrological reinforcing contribution due to matric suction was highest for the hillslope with coniferous tree cover, while the hillslope with deciduous tree cover was second and the hillslope with grass cover was third. The greatest contributions for all cover types were during the summer season. During the winter season, the wettest period of the monitoring study, the additional hydrological reinforcing contributions provided by the deciduous tree cover (1.5 to 6.5 kPa) or the grass cover (0.9 to 5.4 kPa) were insufficient to avoid potential slope failure conditions. However, the additional hydrological reinforcing contribution from the coniferous tree cover (5.8 to 10.4 kPa) was sufficient to provide potentially stable hillslope conditions during the winter season. Our study clearly suggests that during the winter season the hydrological effects from both deciduous tree and grass covers are insufficient to promote slope stability, while the hydrological reinforcing effects from the coniferous tree cover are sufficient even during the winter season. Copyright © 2018 John Wiley & Sons, Ltd. 相似文献
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Georgios Technitis Walied Othman Kamran Safi Robert Weibel 《International journal of geographical information science》2013,27(6):912-934
For applications in animal movement, we propose a random trajectory generator (RTG) algorithm that combines the concepts of random walks, space-time prisms, and the Brownian bridge movement model and is capable of efficiently generating random trajectories between a given origin and a destination point, with the least directional bias possible. Since we provide both a planar and a spherical version of the algorithm, it is suitable for simulating trajectories ranging from the local scale up to the (inter-)continental scale, as exemplified by the movement of migrating birds. The algorithm accounts for physical limitations, including maximum speed and maximum movement time, and provides the user with either single or multiple trajectories as a result. Single trajectories generated by the RTG algorithm can be used as a null model to test hypotheses about movement stimuli, while the multiple trajectories can be used to create a probability density surface akin to Brownian bridges. 相似文献
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Mousa Abedini Bahareh Ghasemian Ataollah Shirzadi Himan Shahabi Kamran Chapi Binh Thai Pham 《国际地球制图》2013,28(13):1427-1457
AbstractA novel artificial intelligence approach of Bayesian Logistic Regression (BLR) and its ensembles [Random Subspace (RS), Adaboost (AB), Multiboost (MB) and Bagging] was introduced for landslide susceptibility mapping in a part of Kamyaran city in Kurdistan Province, Iran. A spatial database was generated which includes a total of 60 landslide locations and a set of conditioning factors tested by the Information Gain Ratio technique. Performance of these models was evaluated using the area under the ROC curve (AUROC) and statistical index-based methods. Results showed that the hybrid ensemble models could significantly improve the performance of the base classifier of BLR (AUROC?=?0.930). However, RS model (AUROC?=?0.975) had the highest performance in comparison to other landslide ensemble models, followed by Bagging (AUROC?=?0.972), MB (AUROC?=?0.970) and AB (AUROC?=?0.957) models, respectively. 相似文献
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An experimental investigation of the airflow structure in the near surface region over the wind-sheared air–water interface
is reported. The two-dimensional velocity fields in a plane perpendicular to the water surface were measured using particle
image velocimetry (PIV) technique over a wind speed range from 1.5 to 4.4 m s−1. The results show a reduction in the mean velocity magnitudes and the tangential stresses when gravity waves appear on the
surface. An enhanced vorticity layer was observed immediately above the water surface that extended to a height of approximately
2 cm. The vorticity was enhanced by an order of magnitude, and the energy dissipation rate was enhanced by a factor of 7 in
this layer at all wind speeds. The vertical profiles of Reynolds stress, energy production, and dissipation indicate the contribution
of surface waves in the enhanced transfer of momentum and energy between the two fluids. The results in this study show that
the flow dynamics in a layer immediately adjacent to the water surface whose thickness is of the order of the significant
wave height is significantly different from that at greater heights. Thus, it is concluded that the quantitative investigation
of the flow in the immediate vicinity of the interface is vital for an improved understanding of the heat, mass, and momentum
exchange between air and water. The present study demonstrates that PIV is an effective technique to accurately measure the
velocity fields in this region. 相似文献
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Najmeh?Khalili Saeed?Reza?KhodashenasEmail author Kamran?Davary Mohammad?Mousavi?Baygi Fatemeh?Karimaldini 《Arabian Journal of Geosciences》2016,9(13):624
In this paper, we have utilized ANN (artificial neural network) modeling for the prediction of monthly rainfall in Mashhad synoptic station which is located in Iran. To achieve this black-box model, we have used monthly rainfall data from 1953 to 2003 for this synoptic station. First, the Hurst rescaled range statistical (R/S) analysis is used to evaluate the predictability of the collected data. Then, to extract the rainfall dynamic of this station using ANN modeling, a three-layer feed-forward perceptron network with back propagation algorithm is utilized. Using this ANN structure as a black-box model, we have realized the complex dynamics of rainfall through the past information of the system. The approach employs the gradient decent algorithm to train the network. Trying different parameters, two structures, M531 and M741, have been selected which give the best estimation performance. The performance statistical analysis of the obtained models shows with the best tuning of the developed monthly prediction model the correlation coefficient (R), root mean square error (RMSE), and mean absolute error (MAE) are 0.93, 0.99, and 6.02 mm, respectively, which confirms the effectiveness of the developed models. 相似文献