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.     

Mooring optimization of floating platforms using a genetic algorithm

This paper presents a new procedure for the optimization of the mooring design of floating platforms, in which an automatic design sequence is also established. Regarding the optimization philosophy, the following aspects are dealt with:

• The optimization of the platform heading and its mooring pattern, taking into account the environmental force spreading;

• optimum line length or line tension for each mooring line, associated to the optimization of the mooring line materials and sizes.

Basically, the main goal of this paper is to introduce a new method, which will provide the quickest way to find the best mooring system, defined here as that which minimizes platform responses.A genetic algorithm (GA) is applied in this contribution, and this paper describes exactly the procedure of developing a GA code directed toward the solution of mooring design optimization problems. In order to prove the efficiency and the vast potential of the proposed algorithm as a design tool, sample moorings are analyzed for different environmental conditions and the final results, including the time required to run them, are presented.     

Zircon U-Pb geochronology and geochemistry of Late Devonian–Carboniferous granitoids in NW Iran: implications for the opening of Paleo-Tethys

ABSTRACT

We present zircon U-Pb crystallization ages combined with bulk rock major and trace element geochemistry and Sr-Nd-Pb and zircon in-situ Hf isotopic compositions of the Amand and Moro granitoid intrusions in northwest Iran. The Amand and Moro plutons include granite and syeno-diorite with LA-ICP-MS U-Pb zircon ages of 367 ± 6.8 Ma and 351 ± 1.3 Ma, respectively, representative of Late Devonian-Early Carboniferous magmatic activity in NW Iran. Geochemical characteristics such as typical enrichments in alkalis, Nb, Zr, Ga and Y, depletion in P and Sr and fractionated REE patterns with high Ga/Al ratios and Eu negative anomalies are consistent with A-type magmatic signatures. The granitoids are classified as A₂-type and within-plate granitoids. The bulk rock geochemistry (enrichments in Th, Nb and, high Th/Yb, Zr/Y ratios) along with low variation of ¹⁴³Nd/¹⁴⁴Nd_(i) and ⁸⁷Sr/⁸⁶Sr_(i) ratios and positive zircon εHf_(t) support the role of a mantle plume component for the evolution of the Amand and Moro A-type granitoids in an extensional tectonic environment. In fitting with wider regional knowledge, this magmatism occurred during Paleo-Tethys opening in northern Gondwana.     

Dynamic Positioning System Design for A Marine Vessel with Unknown Dynamics Subject to External Disturbances Including Wave Effect

China Ocean Engineering - In this paper, a new control system is proposed for dynamic positioning (DP) of marine vessels with unknown dynamics and subject to external disturbances. The control...     

Association between cloudiness and rainfall over Fars province in Iran

Relationship between precipitation sum and cloud properties over Fars province in Iran was analyzed for the cases of light (4 mm), moderate (17 mm), and heavy (62 mm) precipitation. The cloud properties (temperature and pressure at the top, cloud optical thickness and cloud water path) were obtained from satellite data of spectoradiometer MODIS (MODO6). The spatial distribution of rainfall was obtained from the 3-hourly data of TRMM (3B42). The multivariate regression model was developed to predict the spatial distribution of rainfall. A strong significant positive association between the spatial distribution of cloud characteristics and heavy precipitation was found, while no clear correlation was revealed between light precipitation and cloud properties. The developed regression model comprised 64, 47, and 24% of spatial variance of heavy, moderate, and light rainfall, respectively. The influence of cloud water path on the spatial distribution of rainfall dominates.     

Interference of Human Impacts in Urban Growth Modelling with Transition Rules of Cellular Automata, GIS and Multi-Temporal Satellite Imagery: A Case Study of Maraghe, Iran

Urban growth is the result of physical and human impacts. In this study Cellular Automata (CA) has been used to analyze physical suitability and human forces in urban growth modelling of Maraghe. The multi-temporal satellite imagery, physical suitability and human impacts Layers have been applied to the modelling. In order to evaluate the accuracy of the image classification methods, Fuzzy ARTMAP is compared with Maximum Likelihood Classification (MLC) and Minimum Distance Classification (MDC) methods. The image classification results showed an overall accuracy of 93 %. Therefore, it is employed for classification of multi-temporal satellite imagery. In order to weight physical suitability and human impacts layers or geographical transition rules in the modelling, regression analysis, the correlation coefficient, trial-and-error method and visual comparison used. The statistical methods are presented to validate neighbourhood scales in the urban growth modelling. The calibration of the model is in fact to the estimate value of the physical suitability and human impacts layer (combinatory layer of demand for urban land and the government facilities) in the modelling. The results obtained from the model calibration showed that human impacts have the highest influence in the urban growth among other factors. Also a small neighbourhood scale (25:5?×?5 cells) is more realistic in the modeling. The accuracy of final validation is 83 % and the final scenario is based on this validation. A fuzzy CA has been used in urban growth modeling of Maraghe. The final scenario shows that Maraghe will growth on the east side, where the land demand for built up area and government facilities plays the significant role.     

The dichotomous Markov process with nonparametric test application; a decision support method in long-term river behavioural analysis: the Zayandeh Rud River; a case study from central Iran

We use the Dichotomous Markov Noise model with constant transition rates to describe the dynamics of fluctuations in the water level as a stochastic process, which is imposed on river discharge changes. By applying this model, two different regimes are determined for the long-term behaviour of the river. Based on these regimes, we define two nonparametric classes of the overall increasing/decreasing nature of the water level in the long-term behaviour, which are separated by an exponential steady state regime. In this paper, we develop a nonparametric testing procedure to test exponentially (steady state regime) against an alternative overall decreasing level distribution. The proposed test predicts the long-term regime behaviour of the river. The mathematical tools introduced to handle the problem should be of general use and the testing procedure can be considered as a new mathematical tool in the study of water level dynamics. Under conditions of data austerity and as a case of study, we examine the stochastic characteristics of the Zayandeh Rud (Zāyandé-Rūd or Zāyanderūd, also spelled as Zayandeh-Rood or Zayanderood) River (Isfahan, Iran) water level.     

“Phasic” metropolitan settlers: a phase-based model for the distribution of households in US metropolitan regions

In this article, we develop a model for explaining spatial patterns in the distribution of households across metropolitan regions in the United States. First, we use housing consumption and residential mobility theories to construct a hypothetical probability distribution function for the consumption of housing services across three phases of household life span. We then hypothesize a second probability distribution function for the offering of housing services based on the distance from city center(s) at the metropolitan scale. Intersecting the two hypothetical probability functions, we develop a phase-based model for the distribution of households in US metropolitan regions. We argue that phase one households (young adults) are more likely to reside in central city locations, whereas phase two and three households are more likely to select suburban locations, due to their respective housing consumption behaviors. We provide empirical validation of our theoretical model with the data from the 2010 US Census for 35 large metropolitan regions.     

Analyzing spatiotemporal land use/cover dynamic using remote sensing imagery and GIS techniques case: Kan basin of Iran

Land use/land cover (LU/LC) that are significant elements for the interconnection of human activities and environment monitoring can be useful to find out the deviations of saving a maintainable environment. Remote sensing is a very useful tool for the affair of land use or land cover monitoring, which can be helpful to decide the allocation of land use and land cover. Supervised classification-maximum likelihood algorithm in GIS was applied in this study to detect land use/land cover changes observed in Kan basin using multispectral satellite data obtained from Landsat 5 (TM) and 8 (OLI) for the years 2000 and 2016, respectively. The main aim of this study was to gain a quantitative understanding of land use and land cover changes in Kan basin of Tehran over the period 2000–2016. For this purpose, firstly supervised classification technique was applied to Landsat images acquired in 2000 and 2016. The Kan basin was classified into five major LU/LC classes including: Built up areas, garden, pasture, water and bare-land. Change detection analysis was performed to compare the quantities of land cover class conversions between time intervals. The results revealed both increase and decrease of the different LU/LC classes from 2000 to 2016. The results indicate that during the study period, built-up land, and pastures have increased by 0.2% (76.4 km²) and 0.3% (86.03 km²) while water, garden and bare land have decreased by 0, 0.01% (3.62 km²) and 0.4% (117.168 km²), respectively. Information obtained from change detection of LU/LC can aid in providing optimal solutions for the selection, planning, implementation and monitoring of development schemes to meet the increasing demands of human needs in land management.