scholarly journals Sensitivity Analysis and 3D-displacement Inversion of Rock Parameters for High Steep Slope in Open-pit Mining

2016 ◽  
Vol 10 (1) ◽  
pp. 448-460 ◽  
Author(s):  
C.B. Zhou ◽  
R. He ◽  
N. Jiang ◽  
S.W. Lu
Keyword(s):  
Neural Network ◽  
Sensitivity Analysis ◽  
Back Propagation ◽  
Back Analysis ◽  
Steep Slope ◽  
Open Pit ◽  
Open Pit Mining ◽  
Mechanical Parameters ◽  
The Real ◽  
Geological Conditions

Due to the complexity of multiple rocks and multiple parameters circumstance, various parameters are often reduced to only one parameter empirically to generalize geological conditions, ignoring the really influential parameters. A developed method was presented as a complement to 3D displacement inversion to obtain the relative important parameters under complex conditions with limited computational work. Furthermore, this method was applied to a high steep slope in open-pit mining to investigate field applicability of the developed system. Back analysis was conducted in the reality of the east open-pit working area of Daye Iron Mine and propositional steps were presented for parameters solving in complex circumstance. Firstly, multi-factor and single-factor sensitivity analysis were carried out to classify rock mass and mechanical parameters respectively according to the extent of their effects on deformations. Secondly, based on the results, main influence factors were selected as inversion parameters and taken into a 3D calculating model to get the displacement field and stress field, all of which would be the artificial network training samples together with inversion parameters. Thirdly, taking the real deformations as input for the trained back propagation (BP) neural network, the real material mechanical parameters could be obtained. Finally, the results of trained neural network have been confirmed by field monitoring data and provide a reference to obtain the matter parameters in complicated environment for other similar projects.

Analysis of Efficiency of Drilling of Large-Diameter Wells With a Profiled Wing Bit / Badania Efektywności Wiercenia Studni Wielkośrednicowych Świdrem Skrawającym z Profilowanymi Skrzydłami

2012 ◽  
Vol 57 (2) ◽  
pp. 363-373
Author(s):  
Jan Macuda
Keyword(s):  
Average Rate ◽  
Large Diameter ◽  
Open Pit ◽  
Mechanical Parameters ◽  
Drilling Rate ◽  
Geological Conditions ◽  
Rock Drillability ◽  
Drilling Technology ◽  
Weight On Bit ◽  
Rotary Speed

Abstract In Poland all lignite mines are dewatered with the use of large-diameter wells. Drilling of such wells is inefficient owing to the presence of loose Quaternary and Tertiary material and considerable dewatering of rock mass within the open pit area. Difficult geological conditions significantly elongate the time in which large-diameter dewatering wells are drilled, and various drilling complications and break-downs related to the caving may occur. Obtaining higher drilling rates in large-diameter wells can be achieved only when new cutter bits designs are worked out and rock drillability tests performed for optimum mechanical parameters of drilling technology. Those tests were performed for a bit ø 1.16 m in separated macroscopically homogeneous layers of similar drillability. Depending on the designed thickness of the drilled layer, there were determined measurement sections from 0.2 to 1.0 m long, and each of the sections was drilled at constant rotary speed and weight on bit values. Prior to drillability tests, accounting for the technical characteristic of the rig and strength of the string and the cutter bit, there were established limitations for mechanical parameters of drilling technology: P ∈ (Pmin; Pmax) n ∈ (nmin; nmax) where: Pmin; Pmax - lowest and highest values of weight on bit, nmin; nmax - lowest and highest values of rotary speed of bit, For finding the dependence of the rate of penetration on weight on bit and rotary speed of bit various regression models have been analyzed. The most satisfactory results were obtained for the exponential model illustrating the influence of weight on bit and rotary speed of bit on drilling rate. The regression coefficients and statistical parameters prove the good fit of the model to measurement data, presented in tables 4-6. The average drilling rate for a cutter bit with profiled wings has been described with the form: Vśr= Z ·Pa· nb where: Vśr- average drilling rate, Z - drillability coefficient, P - weight on bit, n - rotary speed of bit, a - coefficient of influence of weight on bit on drilling rate, b - coefficient of influence of rotary speed of bit on drilling rate. Industrial tests were performed for assessing the efficiency of drilling of large-diameter wells with a cutter bit having profiled wings ø 1.16 m according to elaborated model of average rate of drilling. The obtained values of average rate of drilling during industrial tests ranged from 8.33×10-4 to 1.94×10-3 m/s and were higher than the ones obtained so far, i.e. from 181.21 to 262.11%.

scholarly journals On evaluation of complex-structured coal deposits based on their typical geometric features

2021 ◽  
Vol 303 ◽  
pp. 01029
Author(s):  
Alexander Katsubin ◽  
Victor Martyanov ◽  
Milan Grohol
Keyword(s):  
Surface Mining ◽  
Geological Structure ◽  
Point Of View ◽  
Open Pit ◽  
Open Pit Mining ◽  
Mining Operations ◽  
Coal Deposits ◽  
Geological Conditions ◽  
Wide Range ◽  
Large Length

Information about the geological structure of Kuznetsky coal basin (Kuzbass) allows us to note that coal deposits developed by open-cast method are characterized by complicated conditions and have the following features: large length of deposits at significant depths of occurrence; coal series bedding of different thicknesses (from 1 to 40 m); different dip angles (from 3 to 90º); a significant number of dip and direction disturbances; different thickness of unconsolidated quaternary sediments (from 5 to 40 m); a wide range of strength values of rocks. In addition, there is a thickness irregularity and frequent variability of elements of occurrence of coal seams within the boundaries of a quarry field both in length and depth of mining. From the point of view of open-pit mining, such deposits are complex-structured. The factors listed above have a decisive influence on the choice of technical means, the order of development and the possibility of carrying out surface mining operations. Therefore, there is a need for a systematization of mining and geological conditions for the development of coal deposits, the purpose of which is to ensure a process of evaluation of complex-structured coal deposits for the development of coal-bearing zones by various complexes of equipment.

scholarly journals Prediction Model of Iron Ore Pellet Ambient Strength and Sensitivity Analysis on the Influence Factors

Metals ◽  
2018 ◽  
Vol 8 (8) ◽  
pp. 593 ◽  
Author(s):  
Qiangjian Gao ◽  
Yingyi Zhang ◽  
Xin Jiang ◽  
Haiyan Zheng ◽  
Fengman Shen
Keyword(s):  
Neural Network ◽  
Sensitivity Analysis ◽  
Prediction Model ◽  
Bp Neural Network ◽  
Back Propagation ◽  
Influence Factors ◽  
Principal Component ◽  
Bp Network ◽  
Input Variables ◽  
Artificial Neural Network Ann

The Ambient Compressive Strength (CS) of pellets, influenced by several factors, is regarded as a criterion to assess pellets during metallurgical processes. A prediction model based on Artificial Neural Network (ANN) was proposed in order to provide a reliable and economic control strategy for CS in pellet production and to forecast and control pellet CS. The dimensionality of 19 influence factors of CS was considered and reduced by Principal Component Analysis (PCA). The PCA variables were then used as the input variables for the Back Propagation (BP) neural network, which was upgraded by Genetic Algorithm (GA), with CS as the output variable. After training and testing with production data, the PCA-GA-BP neural network was established. Additionally, the sensitivity analysis of input variables was calculated to obtain a detailed influence on pellet CS. It has been found that prediction accuracy of the PCA-GA-BP network mentioned here is 96.4%, indicating that the ANN network is effective to predict CS in the pelletizing process.

ASSESSMENT OF THE GEOMECHANICAL CONDITION OF THE KALMAKYR COPPER-PORPHYRY ORE DEPOSIT MINING SYSTEM

2021 ◽  
Vol 3 ◽  
pp. 1212-127
Author(s):  
E.N. ESINA ◽  
◽  
A.E. KIRKOV ◽  
A.I. DOSKALOV ◽  
◽  
...  
Keyword(s):  
System Analysis ◽  
Porphyry Copper ◽  
Three Dimensional ◽  
Open Pit ◽  
Open Pit Mining ◽  
Three Dimensional Model ◽  
Mining System ◽  
Ore Deposit ◽  
Copper Porphyry ◽  
Geological Conditions

The Almalyk deposit of porphyry copper ores (Kalmakyr quarry) here is the subject for exploration of the open-pit mining parameters. A three-dimensional model of the quarry is developed by the modern geoinformation modeling method basing on system analysis of mining and geological conditions and technical mining parameters of the Almalyk copper-porphyry ore deposit open-pit. Main factors influencing the deformation processes development in the rock mass are identified. The probable zones of deformations of the Kalmakyr quarry sides with an increase in its depth are determined. It is recommended to organize and carry out continuous comprehensive geomechanical monitoring to ensure the safe further exploration at the quarry. This measures allow to quickly determine the signs preceding the occurrence of emergency situations, take preventive steps to stabilize the geomechanical condition of considered mining system.

A Hybrid Learning Strategy for Real Hardware of Swing-Up Pendulum

2007 ◽  
Vol 11 (8) ◽  
pp. 972-978 ◽  
Author(s):  
Shingo Nakamura ◽  
◽  
Ryo Saegusa ◽  
Shuji Hashimoto
Keyword(s):  
Neural Network ◽  
Learning Strategy ◽  
Back Propagation ◽  
Optimal Controller ◽  
Learning Approaches ◽  
Learning Method ◽  
Data Sampling ◽  
Target Task ◽  
The Real ◽  
Real Hardware

Generally, the bottom-up learning approaches, such as neural-network, to obtain the optimal controller of target task for mechanical system face a problem including huge number of trials, which require much time and give stress against the hardware. To avoid such problems, a simulator is often built and performed with a learning method. However, there are also problems that how simulator is constructed and how accurate it performs. In this paper, we are considering a construction of simulator directly from the real hardware. Afterward a constructed simulator is used for learning target task and the obtained optimal controller is applied to the real hardware. As an example, we picked up the pendulum swing-up task which was a typical nonlinear control problem. The construction of a simulator is performed by back-propagation method with neural-network and the optimal controller is obtained by reinforcement learning method. Both processes are implemented without using the real hardware after the data sampling, therefore, load against the hardware gets sufficiently smaller, and the objective controller can be obtained faster than using only the hardware. And we consider that our proposed method can be a basic learning strategy to obtain the optimal controller of mechanical systems.

scholarly journals The Challenges of Open-Pit Mining in the Vicinity of the Salt Dome (Bełchatów Lignite Deposit, Poland)

Energies ◽  
2020 ◽  
Vol 13 (8) ◽  
pp. 1913
Author(s):  
Marek Cała ◽  
Katarzyna Cyran ◽  
Joanna Jakóbczyk ◽  
Michał Kowalski
Keyword(s):  
Rock Mass ◽  
Large Scale ◽  
Salt Dome ◽  
Open Pit ◽  
Open Pit Mining ◽  
Stability Conditions ◽  
Mining Operations ◽  
Mass Behavior ◽  
Geological Conditions ◽  
Wall Slope

The extraction of the Bełchatów lignite deposit located in the vicinity of the Dębina salt dome requires careful planning that considers the influence of mining projects on the slope and salt dome stability conditions. The instability problem is directly related to horizontal and vertical displacement, as well as the complex geological and mining conditions. These conditions are very unique with regard to the co-occurrence of the salt dome and lignite deposits in the same area, as well as the large scale of the pit wall slope. Thus, predicting rock mass behavior and ensuring the safety of mining operations are important issues. The presented analysis focused on the influence of long-term lignite extraction on the western pit wall slope of the Bełchatów field and the salt dome’s stability conditions. This study offers a comprehensive approach to a complex geotechnical problem defined by large-scale, complex geometry, and geological conditions. The rock mass behavior and stress conditions are simulated in numerical modelling. The results of the presented analysis will be useful not only for present mining activities but also for future developments related to post-mining and recultivation plans.

Determination of Mechanical Parameters of Reservoir Landslide Based on Back Analysis Using Evolutionary Artificial Network

2012 ◽  
Vol 170-173 ◽  
pp. 729-734
Author(s):  
Fan Zhen Meng ◽  
Shao Jun Li ◽  
Zhen Hua Zhang
Keyword(s):  
Neural Network ◽  
Back Analysis ◽  
Mechanical Parameters ◽  
Three Gorges ◽  
Geological Materials ◽  
Highly Nonlinear ◽  
Artificial Network ◽  
The Relationship ◽  
Rock And Soil

Back analysis of displacement is an effective method for parameter recognition in geotechnical engineering. As rock and soil are complex geological materials, the relationship between the mechanical parameters of slope sliding mass and its displacement is incompletely quantified and highly nonlinear, but traditional back analysis of displacement has poor adaptability for this. So in this paper an integrating method of genetic algorithm, neural network and numerical analysis (GA-NN) is presented to carry out back analysis for mechanical parameters of slope sliding mass, and procedures to perform the intelligent back analysis are described in detail. Finally, this new method is applied and verified by a practical landslide in the reservoir area of Three Gorges, the results indicate the method is efficient for determination of mechanical parameters of sliding mass.

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