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Superhigh‐water backfill mining can mitigate rockburst risks in rockburst‐prone deep coal mines and reduce pollution caused by traditional cemented paste backfill. In this mining method, the width of the rib pillar between two longwall panels is important to maintain roadway stability, prevent rockbursts and water seepage. To design the width of rib pillars, this study firstly established a T‐shaped overlying strata structure model and analyzed source of stress that caused deformation of the T‐shaped model. Based on this model, the abutment stress in the rib pillar was determined. Then, the criterion for overall burst instability of the rib pillar was proposed according to the derived abutment stress. The limit equilibrium theory was applied to obtain the pillar plasticity which can be used as the criterion for water‐seepage prevention. The proposed approach was used to design the width of a rib pillar in Yineng Coalmine located in Shandong Province, China. The analysis of the microseismic monitoring results and borehole drill cuttings show that the designed rib pillar with a width of 10 m was stable without water seepage during mining, indicating the width design method proposed in this study is effective. [ABSTRACT FROM AUTHOR]

In deep coalmines, longwall panels are subject to high static initial geostress andhigh dynamic stress caused by mining and tunnelling activities. Under the action of high static and dynamic stress, rockburst hazards are very likely to occur. To reduce rockburst risks, protective panels are commonly applied in deep coalmines. However, stress concentration in the protective coal panel often causes rockburst hazards in the gateway of the next longwall panel pending mining. To reduce such type of rockburst, this study firstly proposes a mathematic model to analyse the overall static stress distribution in the protective panel based on the mining practice in Longyun coalmine, Shandong Province, China. To evaluate the stress concentration caused by geological defects in the protective panel, a new rockburst evaluation index is proposed based on the computed tomography (CT) method. Finally, the extent of dynamic stress evolution caused by different working face advancing velocities is determined by microseismic monitoring. Results show that the areas with higher rockburst evaluation indexes are highly associated with the areas with large-energy microseismic events, indicating that the static stress concentration can be accurately identified by the CT method. A medium advancing velocity (4.0 m/s) is recommend during mining the longwall panel, which can ensure mining safety and improve mining productivity simultaneously. The integrated microseismic and CT monitoring methods can be used in other underground projects to guarantee construction safety and productivity. [ABSTRACT FROM AUTHOR]

Abstract The coalcrete, a new supporting material produced by jet grouting (JG) technique was firstly studied for improving soft coal mass to support roadways in Guobei coal mine, China. Young's modulus is an essential indicator to evaluate the deformation-resisting ability of coalcretes. In this study, for determining Young's modulus of coalcretes efficiently, an intelligent technique was proposed using the support vector machine (SVM) and beetle antennae search (BAS). The hyper-parameters of SVM were firstly tuned by BAS, and then the SVM-BAS model with optimum hyper-parameters was employed to model the non-linear relationship between the inputs (coal content, water content, cement content, and curing time) and output (Young's modulus). By combining these variables, 360 coalcrete samples in total were prepared and tested for establishing the dataset. The results show that BAS is more reliable and efficient than the trial–and–error tuning method. Moreover, by comparison with other baseline models such as back-propagation neural network (BPNN), logistic regression (LR) and multiple linear regression (MLR), the optimized SVM-BAS model is more reliable, accurate and less time consuming for predicting Young's modulus of coalcretes. Besides, by conducting sensitivity analysis (SA), the importance of different input variables was determined. This pioneering work provides guidelines for predicting Young's modulus of coalcretes and designing proper JG parameters in engineering applications. Highlights • The jet grouting technique was firstly utilized in underground coal mine for generating coalcrete to reinforce the roadway stability • A total of 360 specimens were tested to determine the deformation-resisting ability of coalcrete. • A support vector machine model was proposed for predicting Young's modulus of coalcrete. • The hyperparameters of support vector machine were tuned by beetle antennae search algorithm. [ABSTRACT FROM AUTHOR]

The efficiency of coal mining is seriously affected by roadway stability, as large time‐dependent deformation of roadway frequently occurs and needs to be maintained several times during its service life. Such rheological deformation was common in soft coal mass at Huaibei coalfield in China. To address this issue, in this study, the time‐dependent deformation of the soft coal roadway was analyzed and a new Jet Grouting (JG) technique was presented for controlling deformation. The time‐dependent deformation of the soft coal roadway was numerically simulated and validated. Based on the field test results and the verified model, a JG support model was established to examine its effect on roadway deformation. The JG support system can reduce the horizontal and vertical displacement of the roadway effectively and constrain the time‐dependent deformation of coal mass. The deformation rate and stabilization time of roadway decreased significantly by comparison with conventional support. This work presented a promising JG support scheme for controlling the time‐dependent deformation in the roadway in deep underground mine, which can greatly promote the JG design and application. [ABSTRACT FROM AUTHOR]

Background: Diclofenac diethylamine (DDEA) gel has demonstrated efficacy for treatment of ankle sprains in both the 1.16% four-times-daily (QID) and 2.32% twice-daily (BID) formulations. The objective of this study was to compare, for the first time, the efficacy of DDEA 2.32% gel BID and DDEA 1.16% gel QID. Methods: This was a phase 3, randomized, double-blind, multicenter, active-controlled, parallel-group study conducted in China from October 2019 to November 2020, designed to determine the noninferiority of DDEA 2.32% gel BID relative to DDEA 1.16% gel QID for treatment of grade I–II ankle sprain. At study entry, patients must have had pain on movement (POM) ≥50 mm on a 100-mm visual analogue scale (VAS), and not received any pain medication. The primary efficacy endpoint was the noninferiority of DDEA 2.32% gel BID vs DDEA 1.16% gel QID for POM as assessed by the patient using the 100-mm VAS, conducted on day 5. Secondary endpoints included measures of ankle tenderness, joint function, swelling, and patient-reported pain intensity and pain relief. Results: A total of 302 patients were randomized and 95.4% completed the study. The mean (SD) change in POM from baseline to day 5 using the 100-mm VAS was − 42.8 mm (19.7 mm) with DDEA 2.32% gel BID and − 43.1 mm (18.1 mm) with DDEA 1.16% gel QID for the per-protocol population. The least squares mean difference (DDEA gel 2.32% – DDEA gel 1.16%) at this timepoint was 1.11 mm (95% CI − 3.00, 5.22; P = 0.595), and the upper limit (5.22 mm) of the 95% CI was less than the noninferiority margin of 13 mm, demonstrating that DDEA 2.32% gel BID was noninferior to DDEA 1.16% gel QID. Similar trends were seen for the secondary efficacy endpoints. There was no significant difference in the incidence of treatment-emergent adverse events or adverse events adjudicated as being treatment related. All treatment-related adverse events were dermatological; one patient discontinued from the DDEA 2.32% gel BID arm due to application-site inflammation. Conclusions: DDEA 2.32% gel BID offers a convenient alternative to DDEA 1.16% gel QID, with similar pain reduction and relief, anti-inflammatory effects, and tolerability. Trial registration: NCT04052620. [ABSTRACT FROM AUTHOR]

• Applicability of the Witczak 1-40D model was evaluated. • Artificial intelligence model was employed to correct the inaccuracy of the Witczak 1-40D model. • Adaptive inertia weight and the Levy flight method were combined in BAS algorithm. The applicability of the widely used Witczak model was evaluated for the first time regarding the asphalt mixtures produced in the East part of China. 16 asphalt mixtures by 2 binders and 8 aggregate gradations were designed and the dynamic modulus testing was performed under various loading temperatures and frequencies. The results obtained are similar to previous studies from different countries (areas): the dynamic modulus of the asphalt mixture in the low-temperature region is overestimated. So then, a hybrid artificial intelligence algorithm to replace the traditional Witcazak model is implemented in this paper to correct the overestimation, using the same input parameters in the Witczak model. A modified beetle antennae search (BAS) algorithm was proposed in this study to improve the searching efficiency in the random forest (RF) model. The calculation process showed fast convergence and higher efficiency. The comparative results between the predicted and actual dynamic modulus showed higher prediction accuracy at all the temperature and frequency ranges, overcoming the weaknesses of the traditional Witczak model. The variable importance results showed that G* and phase angle of the binders have the greatest impact on the dynamic modulus. Volumetric properties also show certain influence ability, but the change of the variable controlling aggregate gradation has a weak influence on the dynamic modulus. [ABSTRACT FROM AUTHOR]