Investigation of Cycle Time Segments of Dragline Operation in Surface Coal Mine: A Statistical Approach

Dragline is highly capital intensive equipment to procure, operate and maintain in any surface mining operation. Given this, every second of operation of this capital intensive equipment is absolutely important. Improvement of even a single second in the total cycle time has a tremendous bearing on the overall performance of this equipment. In this light, the present paper is an endeavour to critically analyze the cycle time of dragline operations in a major surface coal mine in India. Rigorous statistical analysis has been performed on individual cycle time segments, of complete dragline cycle. The segmental cycle times have been found to be statistically significant and appear to be best represented by lognormal, normal and beta distributions. Furthermore, the mean time of the statistical distribution for segmental cycle time of dragline has revealed the dependence of cycle time on cut geometry and depth. Results have been illustrated in the form of figures, graphs and tables.     

Reefs at the edge: coral community structure around Rapa,southernmost French Polynesia

Rapa (27°36′ S, 144°20′ W) is a small (~40 km²) volcanic island isolated in the Southern Austral Archipelago, where direct anthropogenic stressors are extremely limited. Here, we present the results of the first quantitative survey of coral community structure across habitats and depths around the island. Despite its geographical isolation in the depauperate South Central Pacific, its small size and unfavourable environmental conditions (competition with macroalgae, low sea surface temperatures, reduced reef accretion), the diversity of scleractinian corals at Rapa is particularly high (112 species from 32 genera, including 37 species of Acropora) in comparison to other French Polynesian islands and subtropical Pacific locations. Our results indicate that the abundance (>100 colonies per 10 m² recorded at nine of the 17 sampling stations) and cover (>40% at four stations) of corals are relatively high for a marginal reef location. Strong spatial heterogeneity was found, with high variation in diversity, abundance, cover and community composition among stations. Variation in community composition was related to habitat types, with distinct assemblages among fringing reefs within bays, reef formations at bay entrances, and those on the submerged platform surrounding the island. On the platform, a depth gradient was detected, with generic richness, abundance and cover generally greater at deeper stations (18–20 m depth) compared with medium‐depth (10–12 m) and shallow (1–3 m) stations. A gradient was also recorded along bays, with increasing coral diversity and abundance from the bay heads to the bay entrances. The coral community at Rapa was characterized by the presence of several taxa not found in other French Polynesian archipelagos and the rarity of others that are common and abundant in the Society and the Tuamotu islands. Another distinctive feature of reef communities at Rapa is the high cover and dominance of macroalgae, particularly in the shallower parts of the surrounding platform, which probably explains the lower densities of coral colonies recorded there. These characteristics of the diversity and biogeographical composition of coral assemblages at Rapa provide considerable ecological grounds for its conservation.     

Prediction of Seaward Slope Recession in Berm Breakwaters Using M5' Machine Learning Approach

In the design process of berm breakwaters, their front slope recession has an inevitable rule in large number of model tests, and this parameter being studied. This research draws its data from Moghim’s and Shekari’s experiment results. These experiments consist of two different 2D model tests in two wave flumes, in which the berm recession to different sea state and structural parameters have been studied. Irregular waves with a JONSWAP spectrum were used in both test series. A total of 412 test results were used to cover the impact of sea state conditions such as wave height, wave period, storm duration and water depth at the toe of the structure, and structural parameters such as berm elevation from still water level, berm width and stone diameter on berm recession parameters. In this paper, a new set of equations for berm recession is derived using the M5'' model tree as a machine learning approach. A comparison is made between the estimations by the new formula and the formulae recently given by other researchers to show the preference of new M5'' approach.     

Comparison of univariate and multivariate geographically weighted regression for estimating air temperature over Iran

Station recording air temperature (T_a) has limited spatial coverage, especially in unpopulated areas. Since temperature can change greatly both spatially and temporally, stations data are often inadequate for meteorology and subsequently climatology studies. Time series of moderate-resolution imaging spectroradiometer (MODIS) land surface temperature (T_s) and normalized difference vegetation index (NDVI) products, combined with digital elevation model (DEM), albedo from Era-Interim and meteorological data from 2006 to 2015, were used to estimate daily mean air temperature over Iran. Geographically weighted regression was applied to compare univariate and multivariate model accuracy. In the first model, which only interfered with land surface temperature (LST), the results indicate a weak performance with coefficient of determination up to 91% and RMSE of 1.08 to 2.9 °C. The mean accuracy of a four-variable model (which used LST, elevation, slope, NDVI) slightly increased (6.6% of the univariate model accuracy) when compared to univariate model. RMSE dropped by 19% of the first model. By addition albedo in the third model, the coefficient of determination increased significantly. This increase was 32% of the univariate model and 23.75% of the 4-variable model accuracy. The statistical comparison between the three models revealed that there is significant improvement in air estimation by applying the geographically weighted regression (GWR) method with interfering LST, NDVI, elevation, slope, and albedo with mean absolute RMSE of 0.62 °C and mean absolute R² of 0.99. In order to better illustrate the third model, t values were spatially mapped at 0.05 level.     

Analysis of pervasive precipitation in similar gradient areas of Iran

Precipitation is a major climatic element with high spatial variations. Temporal and spatial variations may differ in large and small scales. It is, therefore, of utmost importance to study areas with similar gradients in terms of precipitation patterns in order to shed light on the complexities of precipitation variations. In the present study, attempts were made to identify areas with similar gradients experiencing the same precipitation pattern over a 50-year period (1964–2013). To this end, data were collected from synoptic stations in Iran in two phases (i.e., 1434 stations in the first phase and 673 stations in the second one). Alexanderson’s technique was adopted to examine sudden changes in precipitation patterns. The results showed that five regions with similar gradients could be identified in terms of precipitation patterns: negative and high variations, negative and moderate variations, positive and high variations, positive and moderate variations, and little or no variations. The distribution of such regions indicated that the regions with positive trends experienced more annual variations and had further spatial distribution. Furthermore, the findings revealed that the regions with negative precipitation patterns experienced more sudden changes in comparison with those with positive precipitation patterns. Additionally, more variations were observed in the precipitation patterns in recent years.     

The role of tourism in rural development: Evidence from Iran

GeoJournal - Tourism can play an important role in diversifying the rural economy and its expanding in rural areas contributes to the sustainability of the population and the economy of these areas...     

Damage Estimation in Masonry Buildings Based on Excavation-Induced Ground Movements

Excavation-induced ground movements and the resulting damages to adjacent structures and facilities is a source of concern for excavation projects in urban areas. The concern will be even higher if the adjacent structure is old or has low strength parameters like masonry building. Frame distortion and crack generation are predictors of building damage resulted from excavation-induced ground movements, which pose challenges to projects involving excavations. This study is aimed to investigate the relation between excavation-induced ground movements and damage probability of buildings in excavation affected distance. The main focus of this paper is on masonry buildings and excavations stabilized using soil nail wall method. To achieve this purpose, 21 masonry buildings adjacent to 12 excavation projects were studied. Parametric studies were performed by developing 3D FE models of brick walls and excavations stabilized using soil nail wall. Finally, probability evaluations were conducted to analyze the outputs obtained from case studies. Based on the obtained results, simple charts were established to estimate the damage of masonry structures in excavation affected distance with two key parameters including “Displacement Ratio” and “Normalized Distance”. The results also highlight the effects of building distance from excavation wall on its damage probability.

     

Least-squares modification of extended Stokes’ formula and its second-order radial derivative for validation of satellite gravity gradiometry data

The gravity anomalies at sea level can be used to validate the satellite gravity gradiometry data. Validation of such a data is important prior to downward continuation because of amplification of the data errors through this process. In this paper the second-order radial derivative of the extended Stokes’ formula is employed and the emphasis is on least-squares modification of this formula to generate the second-order radial gradient at satellite level. Two methods in this respect are proposed: (a) modifying the second-order radial derivative of extended Stokes’ formula directly, and (b) modifying extended Stokes’ formula prior to taking the second-order radial derivative. Numerical studies show that the former method works well but the latter is very sensitive to the proper choice of the cap size of integration and degree of modification.