Analysis of the Relationship between Mechanical Properties and Pore Structure of MSW Incineration Bottom Ash Fine Aggregate Concrete after Freeze-Thaw Cycles Based on the Gray Theory

The destruction of concrete building materials in severely cold regions of the north is more severely affected by freeze-thaw cycles,and the relationship between the mechanical properties and pore structure of concrete with fine aggregate from municipal solid waste(MSW)incineration bottom ash after freeze-thaw cycles is analyzed under the degree of freeze-thaw hazard variation.In this paper,the gray correlation method is used to calculate the correlation between the relative dynamic elastic modulus,compressive strength,and microscopic porosity parameters to speculate on the most important factors affecting their changes.The GM(1,1)model was established based on the compressive strength of the waste incineration ash aggregate concrete,the relative error between the simulated and actual values in the model was less than 5%,and the accuracy of the model was level 1,indicating that the GM(1,1)model can well reflect the change in the compressive strength of the MSW incineration bottom ash aggregate concrete during freeze-thaw cycles.Using the gray correlation method,the correlation between the relative dynamic elastic modulus,compressive strength,air content,specific surface area,pore spacing coefficient,and pore average chord length was calculated,and the pore spacing coefficient and pore average chord length were determined to be highly correlated with each other.This determination can help analyze and infer the deterioration mechanism of concrete subject to freeze-thaw cycles.These results can provide a theoretical basis for guiding the engineering practice of concrete with fine aggregates of household bottom ash in the northern cold region.

Preliminary Study on Gray Theory in Forecasting Great Drought in Shaoyang District

By using occurrence years of great drought in Shaoyang district in recent 20 years,the time sequence was established,and by gray disaster prediction theory,the possible great drought years in future in Shaoyang district were predicted. The results showed that one quasi-periodic of great drought occurrence in Shaoyang district is 2 years,the next great drought years are 2010,2012 and 2015. Gray prediction drought theory will provide scientific basis for drought resistance work in Shaoyang district.

Controlled-source electromagnetic data processing based on gray system theory and robust estimation

We propose a novel method that combines gray system theory and robust M-estimation method to suppress the interference in controlled-source electromagnetic data. We estimate the standard deviation of the data using a gray model because of the weak dependence of the gray system on data distribution and size. We combine the proposed and threshold method to identify and eliminate outliers. Robust M-estimation is applied to suppress the effect of the outliers and improve the accuracy. We treat the M-estimators of the preserved data as the true data. We use our method to reject the outliers in simulated signals containing noise to verify the feasibility of our proposed method. The processed values are observed to be approximate to the expected values with high accuracy. The maximum relative error is 3.6676%, whereas the minimum is 0.0251%. In processing field data, we observe that the proposed method eliminates outliers, minimizes the root-mean-square error, and improves the reliability of controlled-source electromagnetic data in follow-up processing and interpretation.

Deformation mechanism of high-stress and broken-expansion surrounding rock and supporting optimization based on the gray correlation theory

Aiming at the large deformation and support problems of high-stress and broken-expansion surrounding rock, and taking 1 000 m level roadway of Mine II in Jinchuan as the research object, an investigation on the deformation and damage of roadway surrounding rock and an analysis of its mechanism were carried out. The gray correlation theory was used in support scheme optimization design. First, causes and mechanism of deformation of the 1 000 m horizontal transport channel were analyzed through field investigation, laboratory test and data processing methods. We arguued that poor engineering geological conditions and deep pressure increases were the main factors, and the deformation mechanism was mainly the ground deformation pressure. Second, the gray correlation theory was used to construct supporting optimization decision method in the deep roadway. This method more comprehensively considers various factors, including construction, costs, and supporting material functions. The combined support with pre-stressed anchor cables, shotcrete layer, bolt and metal net was put forward according to the actual roadway engineering characteristics. Finally, 4 support schemes were put forward for new roadways. The gray relational theory was applied to optimizing the supporting method, undertaking technical and economic comparison to obtain the correlation degree, and accordingly the schemes were evaluated. It was concluded as follows： the best was the flexible retaining scheme using the steel strand anchor; the second best was the one using plate anchors on the top and rigid common screw steel bolt on the two sides; the ttiird was; the rigid common screw steel bolt in full section of roadway; and the worst is the planished steel rigid support. The optimized scheme was applied to the 1000 m level of new excavation roadway. The results show that the roadway surrounding rock can reach a stable state after 5 to 6 months monitoring, with a convergence rate less than 1 mm/d.

Improve power quality of coal mine power network based on gray system theory

Unified Power Quality Controller（UPQC） was proposed to comprehensively improve power quality of coal mine power network and its basic structure and operation principle was introduced. In order to overcome time lag of Active Power Filter（APF） in compensating harmonic and reactive current, a novel method based on gray system theory was proposed to predict harmonic current and other distortion component. The mathematical model of component to be compensated was constructed by data sequence of distortion component, which could exactly forecast compensation signal of next period. The optimal control strategy was selected according to the principle of output signal approaching component to be compensated as near as possible. Before predicating each time the oldest data was eliminated while the latest data was added to data sequence. Then new predication model was established once again. The results show that the method can always construct mathematical model with variation of system parameters, reflect the latest state of system and not increase calculation quantity. The feasible and effective control strategy can improve power quality of coal mine power network.

New seismic attribute:Fractal scaling exponent based on gray detrended fluctuation analysis

Seismic attributes have been widely used in oil and gas exploration and development. However, owing to the complexity of seismic wave propagation in subsurface media, the limitations of the seismic data acquisition system, and noise interference, seismic attributes for seismic data interpretation have uncertainties. Especially, the antinoise ability of seismic attributes directly affects the reliability of seismic interpretations. Gray system theory is used in time series to minimize data randomness and increase data regularity. Detrended fluctuation analysis （DFA） can effectively reduce extrinsic data tendencies. In this study, by combining gray system theory and DFA, we propose a new method called gray detrended fluctuation analysis （GDFA） for calculating the fractal scaling exponent. We consider nonlinear time series generated by the Weierstrass function and add random noise to actual seismic data. Moreover, we discuss the antinoise ability of the fractal scaling exponent based on GDFA. The results suggest that the fractal scaling exponent calculated using the proposed method has good antinoise ability. We apply the proposed method to 3D poststack migration seismic data from southern China and compare fractal scaling exponents calculated using DFA and GDFA. The results suggest that the use of the GDFA-calculated fractal scaling exponent as a seismic attribute can match the known distribution of sedimentary facies.

A comprehensive evaluation of enterprise emergency management capacity （EEMC） based on variable weight gray cluster

On the basis of the initial definition of Enterprise Emergency Management Capacity（EEMC）, the paper has established evaluation index system of EEMC, and provided a method to calculate index weight, with the regard to subjectivity existing in the comprehensive evaluation of EEMC multi-indicators, in accordance with the principle of Variable weight Gray Cluster, which makes the weight of indicators generate automatically in the evaluation process and not judged by human, thus decreasing subjective factors during the evaluation.

Prediction of Injection-Production Ratio with BP Neural Network

Injection of water to enhance oil production is commonplace, and improvements in understanding the process are economically important. This study examines predictive models of the injection-to-production ratio. Firstly, the error between the fitting and actual injection-production ratio is calculated with such methods as the injection-production ratio and water-oil ratio method, the material balance method, the multiple regression method, the gray theory GM (1,1) model and the back-propogation (BP) neural network method by computer applications in this paper. The relative average errors calculated are respectively 1.67%, 1.08%, 19.2%, 1.38% and 0.88%. Secondly, the reasons for the errors from different prediction methods are analyzed theoretically, indicating that the prediction precision of the BP neural network method is high, and that it has a better self-adaptability, so that it can reflect the internal relationship between the injection-production ratio and the influencing factors. Therefore, the BP neural network method is suitable to the prediction of injection-production ratio.

Mobility factors of cracked ore in vibrating-ore draw shafts

The mobile factors of cracked ore in vibrating-ore draw shafts were analyzed. The results show that the mobile coefficient of cracked ores will be mainly influenced by the combination of ore physical factors if the structure dimension and parameters of vibrating ore-draw shafts are sure. It decreases with increasing the cohesion, lump content, lump size and powder content and increases with increasing the porosity. The coefficient decreases with increasing the moisture content, but increases after the moisture content reaches a certain value. Uniform grain leads to better mobility, non-uniform grain leads to worse mobility. The value of the mobile coefficient should be in a range of 0.3-1.1 when designing the vibrating ore-draw shafts. According to correlation degree of grey system (theory,) the effects of factors on the mobility of cracked ore are given in the weight decreasing consequence as follows: moisture content, lump content, distribution of grain size, lump size, porosity, cohesion and powder ore content. It is unreasonable to neglect any one because the values of their weights are not obvious.

Neural Network Applications in Petroleum Exploration Based on Statistical Space Mapping

In this paper, we propose the statistical space mapping thought and classify the seismic body space throughlithology space clustering combining to the actual application background of petroleum exploration. A new method ofstratum petroleum recognition based on neural network was set up through the foundation of the data mapping relationbetween log and seismic body. It can break a new path for recognition petroleum using both log and seismic data. Andthis method has been validated in the practical data analysis in Liaohe oil field.

Building a Comprehensive Well-off Society in Yunnan＇s Minority Areas A Study of the Prediction on the Differences in Economic Development Indexes

Based on the gray theory and GM （1, 1） model, the various indexes in 2013-2020 are predicted using the data of all indexes of the economic development of Yunnan＇ s 8 minority areas in 2013-2020 and also compared with the standard values of all indexes of building a well-off society in 2020, and the differences between them are analyzed. The purpose of this study is to provide a reference basis for Yunnan province＇ s government to analyze the economic development of the minority areas.

GGC:Gray-Granger Causality Method for Sensor Correlation Network Structure Mining on High-Speed Train

Vehicle information on high-speed trains can not only determine whether the various parts of the train are working normally,but also predict the train’s future operating status.How to obtain valuable information from massive vehicle data is a difficult point.First,we divide the vehicle data of a high-speed train into 13 subsystem datasets,according to the functions of the collection components.Then,according to the gray theory and the Granger causality test,we propose the Gray-Granger Causality(GGC)model,which can construct a vehicle information network on the basis of the correlation between the collection components.By using the complex network theory to mine vehicle information and its subsystem networks,we find that the vehicle information network and its subsystem networks have the characteristics of a scale-free network.In addition,the vehicle information network is weak against attacks,but the subsystem network is closely connected and strong against attacks.