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Rock engineering especially deep rock engineering undergoing long-term effects of external loading and gravity all or most may gradually damage deformation or creep deformation accumulation, leading rock structures to damage, crack, such as severe plastic deformation or even progressive failure. In this paper, based on the nonlinear damage creep characteristics of rock and damage variable, a new nonlinear damage creep constitutive model of high-stress soft rock is defined in series with the improved Burgers model, Hooke model and St. Venant model. This new nonlinear damage creep constitutive model can work out fairly reasonably explanations for the soft rock creep deformation. A series of uniaxial compression creep tests were performed to study the creep damage characteristics of typical soft rock in Jinchuan No.2 Mine in the northwest of China. Using the increment step loading and single-step loading, the results of creep experiments and nonlinear damage creep constitutive model results are very consistent in this study. The new model not only can reflect the whole course of creep deformation, but also can reasonably describe the soft rock under different initial creep stage, steady-state creep stage and accelerated creep stage. Therefore, the new nonlinear creep damage model is a reasonable reference model for the research of soft rock creep.

This study was undertaken to research the effects of jute fiber content, fiber length, water content and dry density of reinforced and unreinforced soil on the strength influence mechanism by implementing a series of laboratory tests and analysis. The most efficient fiber reinforcement effects was achieved by means of adding jute fiber with content of 0.6 % and length of 6 mm into expansive soil specimen prepared at maximum dry density and optimum moisture content. The cohesion of reinforced specimens increased first with increasing fiber content and fiber length and then decreased with further increase in fiber content and fiber length. The internal friction angle of reinforced specimens were not affected significantly by fiber content and fiber length. Higher water content reduces the fiber reinforcement effects by means of acting as lubricant in the interface of fiber and soil particles. Fiber reinforcement effects is more prominent for specimens prepared at higher dry density by increasing the effective contact area of fiber/soil. The application prospect of soil reinforcement using natural fiber is impeded by the hydrophilic nature and biodegradability of natural fiber, thus, studies on using chemical additive to do surface treatment for natural fiber are needed to improve the interfacial interaction of fiber/soil so as to widen the application of natural fiber.

More broadly, the mining-induced ground pressure disasters result from numerous contributing factors. In addition, the mutually independent multi-source parameters exhibit complicated intrinsic correlations. Nonetheless, the false-positive rates of ground pressure disasters of conventional single-parameter forecasting tend to be excessively higher, significantly hindering their widespread application. In this study, the support numerical models of mining-induced rock roadways in nine categories of three-centered arch cross-sections in metal mines were created, and the substantial computer simulation was carried out under the condition of reciprocally various rock mass quality and roadway support parameters. Moreover, the extensive simulation results of rock roadway support optimization design covering adequate information were quantitatively analyzed. Furthermore, the underlying association laws between the integral stability safety factor and the information entropy of the system chaos representation parameter were revealed during the instability evolution process of mining-induced rock roadways. Meanwhile, the presented time-varying characteristics of the entropy value of surrounding rock system were deduced. Consequently, the summarized research achievements can provide pivotal theoretical support for multi-scale stability evaluation of complex ore-rock geological mass, and prediction and early warning of ground pressure catastrophes integrating multi-source information.

The beneficial role of combining fiber reinforcement with lime stabilization in altering soil behavior has been established in the literature. However, the coupling effect of their combination still remains unclear in terms of its magnitude and microscopic mechanism, especially for natural fibers with special microstructures. The objective of this study was to investigate the coupling effect of wheat straw fiber reinforcement and lime stabilization on the mechanical behavior of Hefei clayey soil. To achieve this, an experimental program including unconsolidated–undrained (UU) triaxial tests and SEM analysis was implemented. Static compaction test samples were prepared on untreated soil, fiber-reinforced soil, lime-stabilized soil, and lime-stabilized/fiber-reinforced soil at optimum moisture content with determining of the maximum dry density of the untreated soil. The lime was added in three different contents of 2%, 4%, and 6%, and 13 mm long wheat straw fiber slices with a cross section one-quarter that of the intact ones were mixed in at 0.2%, 0.4%, and 0.6% by dry weight of soil. Analysis of the derived results indicated that the addition of a small amount of wheat straw fibers into lime-stabilized soil improved the intensity of the strain-softening behavior associated with mere lime stabilization. The observed evidence that the shear strength increase brought by a combination of 0.4% fiber reinforcement and 4% lime stabilization was smaller than the summation of the shear strength increases brought by their presence alone in a sample demonstrated a coupling effect between fiber reinforcement and lime stabilization. This coupling effect was also detected in the comparisons of the secant modulus and failure pattern between the combined treatment and the individual treatments. These manifestations of the coupling effect were explained by a microscopic mechanism wherein the fiber reinforcing effect was made more effective by the ways in which lime chemically stabilized the soil and lime stabilization development was quickened by the water channels passing through the surfaces and honeycomb pores of the wheat straw fibers.

In general, the ultimate parameter selection method of the failure approach index theory among the three-dimensional problems in geotechnical engineering is unclear in theory, and the symbol convention of the failure approach index in engineering calculation is contrary to the stipulation of the numerical simulation software. Hence, the values of the ultimate plastic shear strain are difficult to determine. To solve this problem, the criterion of positive tension and negative compression and the sequence of the principal stress σ 1 ≤ σ 2 ≤ σ 3 are defined in this paper, and the expression of Mohr–Coulomb yield approach index id deduced. Under the condition of the principal strain sequence ε 1 ≤ ε 2 ≤ ε 3 , the formula of the ultimate shear strain is derived using the method of the ultimate strain analysis so as to obtain the simple expression and calculation method of the ultimate plastic shear strain, which has provided the calculation parameters for the three-dimensional ultimate plastic shear strain in the Mohr–Coulomb strain softening model and improved the failure approach index theory. In the light of the aforementioned theory, the ultimate strains of cubic concrete specimens are analyzed, and the obtained ultimate strain values are found consistent with previous research findings, which verifies the correctness and reliability of the ultimate strain analysis method. In addition, it is applied to the quantitative elastic–plastic failure analysis of the section coal pillar in Hengjin coal industry for determining its reasonable retainment width. Consequently, the research results can be embraced as the theoretical basis for the stability analysis of geotechnical materials and exhibits engineering application potential.

Sewage sludge is the major by-product of wastewater treatment plants, and about 30% readily biodegradable organic matters might be reused through the mass reduction process, which could be also reduced the disposal fee. In this study, the microbubble ozonation (MB-O 3 ) was employed to improve the oxidation efficiency for sludge solubilization. At 160 mgO 3 /gSS, the maximum mixed liquor suspended solids (MLSS) reduction ratio was 37.5% and the protein and polysaccharide contents increased to 31.6 and 138.6 mg/L, respectively. It was proposed that aromatic protein and soluble microbial in sludge were oxidized preferentially by MB-O 3 , and the dissolved organic matter (DOM) fractions (mainly humic-acid-like substances) exhibited low degradability according to the variations of fluorescence excitation-emission spectrum coupled with fluorescence regional integration. MB-O 3 could enhance the settleability, but deteriorate sludge dewaterability at low dosage (< 160 mgO 3 /gSS) due to a reduction in particle size from 61.7 to 47.5 μm. MB-O 3 has a good performance on the mass reduction of sludge through the improvement of the radical generated.

In general, the design of a safe and rational laneway support scheme signifies a crucial prerequisite for ensuring the security and efficiency of mining exploitation in mines. Nevertheless, the conventional empirical support system for mining laneways faces challenges in assessing the rationality of support methods, which can compromise the safety and reliability of the laneways. To address this issue, the safety factor was incorporated into research on laneway support, and a safety evaluation method for laneway support in line with the safety factor was established. In light of the data from a specific iron mine laneway in central China, the CRITIC method was employed to preprocess the sample data. Going one step further, a Bayesian algorithm was utilized to optimize the hyperparameters of the CatBoost model, followed by proposing a prediction model based on the BO-CatBoost model for evaluating laneway safety factors of plain shotcrete support. Furthermore, the performance indexes, such as the root mean square error (RMSE), the mean absolute error (MAE), the correlation coefficient (R2), the variance accounts for (VAF), and the a-20 index, were determined to examine the predictive performance of each proposed model. In contrast to the other models, the BO-CatBoost model demonstrated the optimal predictive output item for safety factors with the lowest RMSE and MAE, the largest R2 and VAF, and an appropriate a-20 index value of 0.5688, 0.4074, 0.9553, 95.25%, and 0.9167 in the test set, respectively. Therefore, the BO-CatBoost model was proven to be the most appropriate machine learning method that can more accurately predict the safety factor, which will provide a novel approach for optimizing laneway support design and laneway safety evaluation.

The risk evaluation indexes of goaf are multi-source and have complex mutual internal correlations, and there are great differences in the risk identification of goaf from different mines among the various influencing factors. This paper mainly focuses on principal component analysis (PCA) and the differential evolution algorithm (DE), while a multi-classification support vector machine (SVM) is adopted to classify the risks of goaf. Then, the K-fold cross-validation method is used to prevent the overfitting of selection in the model. After the analysis, nine factors affecting the risk identification of goaf in a certain area of East China were determined as the primary influencing factors, and 120 measured goafs were taken as examples for classifying the risks. More specifically, the classification results show that: (1) SVM has the useful ability of generalization, especially when solving the problems of overfitting, and it is easy to fall into the local minima under the conditions of small samples; (2) PCA is employed to realize the intelligent dimensionality reduction and denoising of multi-source impact indicators for goaf risk identification, which immensely improves the prediction accuracy and classification efficiency of the model; (3) after using the DE, the optimal solutions of the problems to be optimized are automatically obtained through the global optimization search mechanism, namely, the kernel function parameter, ‘γ’, and the penalty factor, ‘C’, of the SVM, which further verifies that the characteristics of clear logic, strong convergence, and good robustness can be found in the DE. As demonstrated, this method has the advantages of guiding significance and application value for goaf risk identification.

It is generally acknowledged that the stability evaluation of surrounding rock denotes nonlinear complex system engineering. In order to accurately and quantitatively assess the safety states of surrounding rock and provide a scientific basis for the prevention and control of surrounding rock stability, the analysis method of the synergetic theory of information entropy using the failure approach index has been proposed. By means of deriving the general relationship between the total two-dimensional plastic shear strain and the total three-dimensional plastic shear strain and obtaining the numerical limit analysis step of the plastic shear strain, the threshold value of the ultimate plastic shear strain can be determined, which has provided the key criterion for the calculation of the information entropy based on the failure approach index. In addition, combining with the synergetic theory of the principle of maximum information entropy, the evolution equation of the excavation step and information entropy based on the failure approach index of the surrounding rock system in underground mining space are established, and the equations of the general solution and particular solution as well as the expression of the destabilizing excavation step are given. To account for this, the method is applied to analyze the failure states of the floor surrounding rock after the mining of the 71 coal seam in Xutuan Coal Mine and involve the disturbance effect and stability control method of the underlying 72 coal seam roof from the macroscopic and microscopic aspects. Consequently, the validity of the analysis method of synergetic theory of information entropy based on the failure approach index has been verified, which presents an updated approach for the stability evaluation of surrounding rock systems that is of satisfactory capability and value in engineering applications.

In order to conduct an intelligent early warning assessment of stope rock burst disasters in mining areas, and effectively prevent and control them, the principal component analysis (PCA) method was embraced to perform dimensionality reduction and feature information extraction from 10 main factors that affect the occurrence of rock bursts. On this basis, six principal component elements of the influencing factors of rock bursts have been obtained as the input vectors for an extreme learning machine (ELM). In the meantime, the parameter optimization ability of the PSO algorithm was adopted, the input weight values of the ELM and the threshold values of the hidden layer were optimized, and the functions of the three models were completely combined. Therefore, an early warning model of rock bursts based on the PCA-PSO-ELM combined algorithm was creatively proposed and the risk rank of rock bursts in the Yanshitai Coal Mine was predicted and evaluated. Consequently, the research results indicated that the prediction accuracy of the PCA-PSO-ELM model improved the prediction performance and generalization ability and reached a 100% contrast with the three models, namely the BP neural network, the radial basis function, and the extreme learning machine, which presented an updated method for the early warning investigation of rock burst disasters and had favorable engineering significance.