Evolution mechanism and treatment timing of penetrating fissures

The Inner Mongolia mining area in western China are characterized by the development of numerous penetrating fissures,resulting in severe land damage.It is significant to reveal the underlying evolution mechanism and identify treatment timing for restoring the ecological environment.The Guanbanwusu mining subsidence area in Inner Mongolia,China was selected as the research case for this study.The evolution mechanism of different penetrating fissures was revealed by field measurement,physical simulation and theoretical analysis.The treatment timing prediction model for the mining subsidence area was established based on the enhanced Weibull time function.The results show that the ground fissures are mainly step-type and collapse-type fissures.The breaking form of overlying strata determines their vertical opening and horizontal dislocation.The high mining intensity in the western mining area results in a shortened period of dynamic fissure expansion and reduced closure degree.The damage extent of the overlying strata exhibits zoning characteristics both vertically and horizontally.The relative standard deviation of the prediction model is only 3.7%.Concurrently,the prediction model is employed to determine the optimal timing for treatment in the study area,estimated to be 259 days.Subsequently,once this threshold is reached,the study area undergoes treatment and restoration of its e cological environment.This study addresses the knowledge gap in this field by highlighting the interconnectedness between rock strata structure and evolution mechanism of penetrating fissures,thereby providing a method for determining the treatment timing in mining subsidence areas.

Heterogeneous information phase space reconstruction and stability prediction of filling body–surrounding rock combination

Traditional research believes that the filling body can effectively control stress concentration while ignoring the problems of unknown stability and the complex and changeable stress distribution of the filling body–surrounding rock combination under high-stress conditions.Current monitoring data processing methods cannot fully consider the complexity of monitoring objects,the diversity of monitoring methods,and the dynamics of monitoring data.To solve this problem,this paper proposes a phase space reconstruction and stability prediction method to process heterogeneous information of backfill–surrounding rock combinations.The three-dimensional monitoring system of a large-area filling body–surrounding rock combination in Longshou Mine was constructed by using drilling stress,multipoint displacement meter,and inclinometer.Varied information,such as the stress and displacement of the filling body–surrounding rock combination,was continuously obtained.Combined with the average mutual information method and the false nearest neighbor point method,the phase space of the heterogeneous information of the filling body–surrounding rock combination was then constructed.In this paper,the distance between the phase point and its nearest point was used as the index evaluation distance to evaluate the stability of the filling body–surrounding rock combination.The evaluated distances(ED)revealed a high sensitivity to the stability of the filling body–surrounding rock combination.The new method was then applied to calculate the time series of historically ED for 12 measuring points located at Longshou Mine.The moments of mutation in these time series were at least 3 months ahead of the roadway return dates.In the ED prediction experiments,the autoregressive integrated moving average model showed a higher prediction accuracy than the deep learning models(long short-term memory and Transformer).Furthermore,the root-mean-square error distribution of the prediction results peaked at 0.26,thus outperforming the no-prediction method in 70%of the cases.

Influences of Mixed Traffic Flow and Time Pressure on Mistake-Prone Driving Behaviors among Bus Drivers

Bus safety is a matter of great importance in many developing countries, with driving behaviors among bus drivers identified as a primary factor contributing to accidents. This concern is particularly amplified in mixed traffic flow (MTF) environments with time pressure (TP). However, there is a lack of sufficient research exploring the relationships among these factors. This study consists of two papers that aim to investigate the impact of MTF environments with TP on the driving behaviors of bus drivers. While the first paper focuses on violated driving behaviors, this particular paper delves into mistake-prone driving behaviors (MDB). To collect data on MDB, as well as perceptions of MTF and TP, a questionnaire survey was implemented among bus drivers. Factor analyses were employed to create new measurements for validating MDB in MTF environments. The study utilized partial correlation and linear regression analyses with the Bayesian Model Averaging (BMA) method to explore the relationships between MDB and MTF/TP. The results revealed a modified scale for MDB. Two MTF factors and two TP factors were found to be significantly associated with MDB. A high presence of motorcycles and dangerous interactions among vehicles were not found to be associated with MDB among bus drivers. However, bus drivers who perceived motorcyclists as aggressive, considered road users’ traffic habits as unsafe, and perceived bus routes’ punctuality and organization as very strict were more likely to exhibit MDB. Moreover, the results from the three MDB predictive models demonstrated a positive impact of bus route organization on MDB among bus drivers. The study also examined various relationships between the socio-demographic characteristics of bus drivers and MDB. These findings are of practical significance in developing interventions aimed at reducing MDB among bus drivers operating in MTF environments with TP.

The development of real time data driving multi-axis linkage and synergic movement control system of 3D variable cross-section roll forming machine

The three dimensional variable cross-section roll forming is a kind of new metal forming technol- ogy which combines large forming force, multi-axis linkage movement and space synergic movement, and the sequential synergic movement of the ganged roller group is used to complete the metal sheet forming according to the shape of the complicated and variable forming part data. The control system should meet the demands of quick response to the test requirements of the product part. A new kind of real time data driving multi-axis linkage and synergic movement control strategy of 3D roll forming is put forward in the paper. In the new control strategy, the forming data are automatically generated according to the shape of the parts, and the multi-axis linkage movement together with cooperative motion among the six stands of the 3D roll forming machine is driven by the real-time information, and the control nodes are also driven by the forming data. The new control strategy is applied to a 48 axis 3D roll forming machine developed by our research center, and the control servo period is less than 10ms. A forming experiment of variable cross section part is carried out, and the forming preci- sion is better than ＋ 0.5mm by the control strategy. The result of the experiment proves that the control strategy has significant potentiality for the development of 3D roll forming production line with large scale, multi-axis ganged and svner^ic movement

Sediment settlement rate and consolidation time of flling reclamation in coal mining subsidence land

With the continuous growth of the population and the continuous reduction of cultivated land,China’s food security is greatly threatened.In addition,China’s coal mining has been mainly underground mining,causing land subsidence and damaging existing cultivated land.This efect intensifes the contradiction between the growth of the risk population and the reduction of cultivated land.The reclamation of mining subsidence land with Yellow River sediment is often used as an efective way to improve the recovery rate of cultivated land.Shortening the reclamation time and realizing continuous flling are signifcant issues.The work presented in this paper studied the sediment settlement rate and consolidation time by combining theory,feld flling and reclamation tests and numerical simulations.A feld flling test study was carried out in the lowlands of Jibeiwang Village,Qihe County,Shandong Province,China.By calculating the drainage consolidation time,the consolidation factor of 0.015656 m^(2)/d,and the time factor for sediment consolidation of 0.575 were determined.The sediment consolidation time for this test was 9.18 days.The calculation of sediment deposition rate and consolidation time is of great practical signifcance to guide the Yellow River sediment flling,realize continuous flling,and save reclamation time and cost.

Development of a time-dependent energy model to calculate the mining-induced stress over gates and pillars

Generally, longwall mining-induced stress results from the stress relaxation due to destressed zone that occurs above the mined panel. Knowledge of induced stress is very important for accurate design of adjacent gateroads and intervening pillars which helps to raise the safety and productivity of longwall mining operations. This study presents a novel time-dependent analytical model for determination of the longwall mining-induced stress and investigates the coefficient of stress concentration over adjacent gates and pillars. The model is developed based on the strain energy balance in longwall mining incorporated to a rheological constitutive model of caved materials with time-varying parameters. The study site is the Tabas coal mine of Iran. In the proposed model, height of destressed zone above the mined panel, total longwall mining-induced stress, abutment angle, induced vertical stress, and coefficient of stress concentration over neighboring gates and intervening pillars are calculated. To evaluate the effect of proposed model parameters on the coefficient of stress concentration due to longwall mining, sensitivity analysis is performed based on the field data and experimental constants. Also, the results of the proposed model are compared with those of existing models. The comparative results confirm a good agreement between the proposed model and the in situ measurements. According to the obtained results, it is concluded that the proposed model can be successfully used to calculate the longwall mining-induced stress. Therefore, the optimum design of gate supports and pillar dimensions would be attainable which helps to increase the mining efficiency.

Data—mining massive real—time data in a power plant：challenges,problems and solutions

Nowadays, the scale of data normally stored in a database collected by Data Acquisition System (DAS) or Distributed Control System (DCS) in a power plant is becoming larger and larger. However there are abundant valuable knowledge hidden behind them. It will be beyond people's capacity to analyze and understand these data stored in such a scale database. Fortunately data mining techniques are arising at the historic moment. In this paper, we explain the basic concept and general knowledge of data mining; analyze the characteristics and research method of data mining; give some typical applications of data mining system based on power plant real time database on intranet.

Bifurcation analysis of visual angle model with anticipated time and stabilizing driving behavior

In the light of the visual angle model(VAM),an improved car-following model considering driver's visual angle,anticipated time and stabilizing driving behavior is proposed so as to investigate how the driver's behavior factors affect the stability of the traffic flow.Based on the model,linear stability analysis is performed together with bifurcation analysis,whose corresponding stability condition is highly fit to the results of the linear analysis.Furthermore,the time-dependent Ginzburg–Landau(TDGL)equation and the modified Korteweg–de Vries(m Kd V)equation are derived by nonlinear analysis,and we obtain the relationship of the two equations through the comparison.Finally,parameter calibration and numerical simulation are conducted to verify the validity of the theoretical analysis,whose results are highly consistent with the theoretical analysis.

Selection of the Proper Hammer in Pile Driving and Estimation of the Total Driving Time

There are various methods for analyzing pile driving process such as dynamic formulas, wave equation analyses and dynamic measurements. The programs of the two latter methods are relatively expensive to purchase and also require trained engineers to interpret the data it collects. Meanwhile, the use of the site specific empirical formulas based on the real cases of pile driving and output analyses of the wave equation analysis programs can be beneficial. In the current study, pile driving data from three sites in the south of Iran were collected. Using the data of these cases and one-dimensional wave equation analysis program GRLWEAP, couple of experimental formulas which determine the proper range of hammer＇s ID for driving a pile, are proposed. Finally, due to the importance of the time in marine projects, another experimental formula is also proposed for estimation of the total driving time.

Fuzzy Inference System Design Based on Data Mining Concepts and Its Application in Time Series Forecasting

This paper adopts data mining(DM) technique and fuzzy system theory for robust time series forecasting.By introducing DM technique,the fuzzy rule extraction algorithm is improved to be more robust with the noises and outliers in time series.Then,the constructed fuzzy inference system(FIS) is optimized with a partition refining strategy to balance the system's accuracy and complexity.The proposed algorithm is compared with the WangMendel(WM) method,a benchmark method for building FIS,in comprehensive analysis of robustness.In the classical Mackey-Glass time series forecasting,the simulation results prove that the proposed method is able to predict time series with random perturbation more accurately.For the practical application,the proposed FIS is applied to predicting the time series of ship maneuvering motion.To obtain actual time series data records,the ship maneuvering motion trial is conducted in the Yukun ship of Dalian Maritime University in China.The time series forecasting results show that the FIS constructed with DM concepts can forecast ship maneuvering motion robustly and effectively.

Time-lapse geophysical technology-based study on overburden strata changes induced by modern coal mining

To study the impact of modern coal mining on overlying strata and its water bearing conditions,integrated time-lapse geophysical prospecting integrating 3D seismic,electrical and ground penetrating radar method were used.Through observing and analyzing the geophysical data variations of all stages of pre-mining,mining and post-mining as well as post-mining deposition stable period,impacts of coal mining on stratigraphic structure and its water bearing were studied and modern coal mining induced stratigraphic change pattern was summarized.The research result shows that the stratigraphic structure and the water bearing of surface layer during modern coal mining have self-healing pattern with mining time;the self-healing capability of near-surface strata is relatively strong while the roof weak;water bearing selfhealing of near-surface strata is relatively high while the roof strata adjacent to mined coal beds low.Due to integrated time-lapse geophysical prospecting technology has extra time dimension which makes up the deficiency of static analysis of conventional geophysical methods,it can better highlight the dynamic changes of modern coal mining induced overburden strata and its water bearing conditions.

Outliers Mining in Time Series Data Sets

In this paper, we present a cluster-based algorithm for time series outlier mining.We use discrete Fourier transformation (DFT) to transform time series from time domain to frequency domain. Time series thus can be mapped as the points in k -dimensional space.For these points, a cluster-based algorithm is developed to mine the outliers from these points.The algorithm first partitions the input points into disjoint clusters and then prunes the clusters,through judgment that can not contain outliers.Our algorithm has been run in the electrical load time series of one steel enterprise and proved to be effective.

Analysis to driving forces of land use change in Lu’an mining area

By selecting impact factors of driving force and formulating evaluation criteria of the impacts, the evaluation system of corresponding driving force impact of land use change was established. Taking Lu'an mining area as an example, the specific impact factors of coal mine were comprehensively evaluated and analyzed in order to carry out qualitative and quantitative analysis for the driving force of mining-land use change. The principal component analysis shows that the social and economic development in mining area from 2000 to 2007 demonstrates continuous accelerate trends, and the impacts of its overall driving force to land use change are increased gradually. The socio-economic factors have more impacts to mining-land use change than those of the natural resources. The main driving force of mining-land use change also include population, technological progress and policy.

Research on Energy Efficiency Characteristics of Mining Shovel Hoisting and Slewing System Driven by Hydraulic-Electric Hybrid System

Mining shovel is a crucial piece of equipment for high-efficiency production in open-pit mining and stands as one of the largest energy consumption sources in mining.However,substantial energy waste occurs during the descent of the hoisting system or the deceleration of the slewing platform.To reduce the energy loss,an innovative hydrau-lic-electric hybrid drive system is proposed,in which a hydraulic pump/motor connected with an accumulator is added to assist the electric motor to drive the hoisting system or slewing platform,recycling kinetic and potential energy.The utilization of the kinetic and potential energy reduces the energy loss and installed power of the min-ing shovel.Meanwhile,the reliability of the mining shovel pure electric drive system also can be increased.In this paper,the hydraulic-electric hybrid driving principle is introduced,a small-scale testbed is set up to verify the feasibil-ity of the system,and a co-simulation model of the proposed system is established to clarify the system operation and energy characteristics.The test and simulation results show that,by adopting the proposed system,compared with the traditional purely electric driving system,the peak power and energy consumption of the hoisting electric motor are reduced by 36.7%and 29.7%,respectively.Similarly,the slewing electric motor experiences a significant decrease in peak power by 86.9%and a reduction in energy consumption by 59.4%.The proposed system expands the application area of the hydraulic electric hybrid drive system and provides a reference for its application in over-sized and super heavy equipment.

Using Data Mining with Time Series Data in Short-Term Stocks Prediction: A Literature Review

Data Mining (DM) methods are being increasingly used in prediction with time series data, in addition to traditional statistical approaches. This paper presents a literature review of the use of DM with time series data, focusing on shorttime stocks prediction. This is an area that has been attracting a great deal of attention from researchers in the field. The main contribution of this paper is to provide an outline of the use of DM with time series data, using mainly examples related with short-term stocks prediction. This is important to a better understanding of the field. Some of the main trends and open issues will also be introduced.

A New Method Based on Association Rules Mining and Geo-filter for Mining Spatial Association Knowledge

Association rule mining methods, as a set of important data mining tools, could be used for mining spatial association rules of spatial data. However, applications of these methods are limited for mining results containing large number of redundant rules. In this paper, a new method named Geo-Filtered Association Rules Mining(GFARM) is proposed to effectively eliminate the redundant rules. An application of GFARM is performed as a case study in which association rules are discovered between building land distribution and potential driving factors in Wuhan, China from 1995 to 2015. Ten sets of regular sampling grids with different sizes are used for detecting the influence of multi-scales on GFARM. Results show that the proposed method can filter 50%–70% of redundant rules. GFARM is also successful in discovering spatial association pattern between building land distribution and driving factors.

Computer Programs for Prediction of Mining Area Deformation with Time Factor Taken into Consideration

This paper discussed the current of works on computerisation of all problems related to mining subsidence, including the time factor,carried out in the Division of Mining Geodesy of Technical University of Silesia, Poland. First, the formulas implemented in the programs were presented. These formulas considerably increase the description accuracy of final deformations by taking into uncaved strip along extraction rib (extraction margin). They also improve the deformation description of areas located far from the extraction place. Then, the research results aiming to improving the description of deformation with time were introduced. Finally, the Windows based version of the program for the creation of mining geological opinions were presented in the form accepted by Mining Offices of Poland.

Spatio-temporal Variations in Plantation Forests'Disturbance and Recovery of Northern Guangdong Province Using Yearly Landsat Time Series Observations(1986-2015)

Forest disturbance plays a vital role in modulating carbon storage,biodiversity and climate change.Yearly Landsat imagery from 1986 to 2015 of a typical plantation region in the northern Guangdong province of southern China was used as a case study.A Landsat time series stack(LTSS) was fed to the vegetation change tracker model(VCT) to map long-term changes in plantation forests' disturbance and recovery,followed by an intensive validation and a continuous 27-yr change analysis on disturbance locations,magnitudes and rates of plantations' disturbance and recovery.And the validation results of the disturbance year maps derived from five randomly identified sample plots with 25 km^2 located at the four corners and the center of the scene showed the majority of the spatial agreement measures ranged from 60% to 83%.A confusion matrix summary of the accuracy measures for all four validation sites in Fogang County showed that the disturbance year maps had an overall accuracy estimate of 71.70%.Forest disturbance rates' change trend was characterized by a decline first,followed by an increase,then giving way to a decline again.An undulated and gentle decreasing trend of disturbance rates from the highest value of 3.95% to the lowest value of 0.76% occurred between 1988 and 2001,disturbance rate of 4.51% in 1994 was a notable anomaly,while after 2001 there was a sharp ascending change,forest disturbance rate spiked in 2007(5.84%).After that,there was a significant decreasing trend up to the lowest value of 1.96% in 2011 and a slight ascending trend from 2011 to 2015(2.59%).Two obvious spikes in post-disturbance recovery rates occurred in 1995(0.26%) and 2008(0.41%).Overall,forest recovery rates were lower than forest disturbance rates.Moreover,forest disturbance and recovery detection based on VCT and the Landsat-based detections of trends in disturbance and recovery(LandT rendr) algorithms in Fogang County have been conducted,with LandT rendr finding mostly much more disturbance than VCT.Overall,disturbances and recoveries in northern Guangdong were triggered mostly by timber needs,policies and decisions of the local governments.This study highlights that a better understanding about plantations' changes would provide a critical foundation for local forest management decisions in the southern China.

Cable-truss supporting system for gob-side entry driving in deep mine and its application

In order to solve the large deformation controlling problem for surrounding rock of gob-side entry driving under common cable anchor support in deep mine, site survey, physical modeling experiment, numerical simulation and field measurement were synthetically used to analyze the deformation and failure characteristics of surrounding rock. Besides, applicability analysis, prestress field distribution characteristics of surrounding rock and the control effect on large deformation of surrounding rock were also further studied for the gob-side entry driving in deep mine using the cable-truss supporting system. The results show that, first, compared with no support and traditional bolt anchor support, roof cable-truss system can effectively restrain the initiation and propagation of tensile cracks in the roof surrounding rock and arc shear cracks in the two sides, moreover, the broken development of surrounding rock, roof separation and extrusion deformation between the two sides of the roadway are all controlled; second, a prestressed belt of trapezoidal shape is generated in the surrounding rock by the cable-truss supporting system, and the prestress field range is wide. Especially, the prestress concentration belt in the shallow surrounding rock can greatly improve the anchoring strength and deformation resisting capability of the rock stratum;third, an optimized support system of ‘‘roof and side anchor net beam, roof cable-truss supporting system and anchor cable of the narrow coal pillar" was put forward, and the support optimization design and field industrial test were conducted for the gob-side entry driving of the working face 5302 in Tangkou Mine, from which a good supporting effect was obtained.