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This study establishes a prediction model based on the back propagation (BP) neural network for controlling the underground directional drilling path in a coal mine. The four-layer BP neural network model chooses 11 trajectory parameters (dip angles and azimuths from 12 m after the measurement while drilling (MWD)) and two control parameters as inputs. Two parameters, the dip angle and azimuth at bit, are the outputs. Trained with data from 502 groups, the model was used to forecast 12 test data groups. The results were then compared with the prediction results of artificial experience from 24 technicians. The study shows that the mean absolute error of the dip angle and azimuth at bit are only 0.51° and 0.68°, respectively, as predicted by the prediction model, which uses the logsig activation function and has a double-hidden-layer with a point structure of 9×6. The prediction error also follows a normal distribution. Compared with technicians who have worked for more than five years, the accuracy of prediction results from the BP neural network model is reduced by 33.9% and meets the needs of drilling path control. [ABSTRACT FROM AUTHOR]

During the drilling process, horizontal drill strings are often subject to stick-slip and back-pressure phenomena, which undermine drilling safety and affect drilling costs. However, most of the models proposed in the existing literature apply only to the analysis of the drill string motion state and are irrelevant to the rotary drilling process in coal mines. This paper presents a lumped-mass model of a drill string in a horizontal coal mine well. First, based on reasonable assumptions, the drill-string system was considered as four lumped-mass units. The lateral-torsional dynamics model was established based on the Lagrange dynamics theory. Further, combined with lateral movement, the intermittent contact between the drill string and borehole wall is described, and the friction torque due to this intermittent contact is calculated. Combined with the Karnopp bit-rock interaction, a drill-string dynamics model of horizontal wells that considers intermittent contact friction was developed. The proposed horizontal well drill-string model is more suitable for rotary drilling in a coal mine, and the nonlinear influencing factors are considered more comprehensive. [ABSTRACT FROM AUTHOR]

Based on the advanced detection drilling rigs used in underground coal mines, a real-time method of obtaining the depth of drilling is proposed. Displacement sensors are used to measure the stroke of the drilling rig's feeding device during drilling, and an equation to calculate the depth of drilling is put forward. The same measurements are made by several sensors, improving measurement accuracy and reliability. The final drilling depth is obtained using a multi-sensor data fusion algorithm, combined with the calculation equation. The necessary derivation and calculation processes of the multi-sensor, adaptive weighted fusion algorithm are given. To optimize the integrated result, the weighting coefficients can be found through the algorithm corresponding to each sensor in an adaptive mode to optimize the fusion result. Three kinds of displacement sensors are installed on the feeding device of the drilling rig, and the drilling process is simulated in a laboratory test. The test proves that, compared with the mean method of three sensors, the data obtained by the multi-sensor and adaptive weighted fusion algorithm have the higher accuracy, and the sensor with the least variance in the fusion process has the most significant weighting coefficient. The drilling depth data that are obtained are more accurate than those obtained through the mean method with measurement data from a single sensor. The weighted coefficient of the measurement data is minimal when the measurement accuracy of the sensor suddenly deteriorates, so it has little effect on the measurement results. An experiment verifies this method's effectiveness and fault tolerance, showing an improvement in measurement accuracy. [ABSTRACT FROM AUTHOR]

Abstract: Background: In vivo imaging of the cells transplanted into the beating heart is very important for the study of the cell''s retention, migration. This study was designed to find a new labeling agent to trace and visualize the transplanted cells in vivo. Method: BMMSCs were incubated with SPIO for 48 h. The labeling efficiency was tested through Prussian blue staining, the growth ability was evaluated through MTT, and the cells viability was tested through Trypan blue rejection method, the migratory ability was assessed with Costar Transwell plates. After 10 days of coronary ligation of the Chinese mini swine, the labeled or unlabeled cells were transplanted into the myocardium. The MRI was carried out immediately and 1–4 weeks, respectively. After MRI the hearts were excised, the segment in which injections were performed were thin cut and stained with hematoxylin-eosin and Prussian blue staining. Results: There were intracytoplasmatic blue particles in nearly every cell in the Prussian blue staining. SPIO had no poison effect on the cells'' growth and proliferation. The cells'' viability was more than 95%. The migratory ability was not affected. The injected sites containing labeled cells could all be detected through MRI and were confirmed on pathology. After 4 weeks the injected labeled cells could still be detected through MRI. The pathology showed the injected cells could survive in the MI area, and parallel in the same direction. Conclusion: The cells could be efficiently and safely labeled with SPIO and the labeled cells could be reliably detected by MRI in vivo. [Copyright &y& Elsevier]

• SAP and CA were used together for crack healing of cement-based material. • The factors affecting SAP healing efficiency were tested by rapid permeability test. • The optimum crystalline admixture was explored for the complete closure. • Microscopic morphology of healing products was observed through SEM. The macro-crack is wide-spread in concrete structure, especially the width >0.5 mm, which is hard to be sealed with its self-healing capacity. This research investigated the synergetic effect of superabsorbent polymer (SAP) and crystalline admixture (CA) for macro-crack closure in cement-based materials (CBM). The affecting factors on SAP usage in CBM were studied, and the suitable CA was also explored for complete closure. The results indicated citric acid was an efficient additive for supplementary repair through promoting chemical precipitation. The optically and scanning electronically microscopic morphology also verified the hypothesis from data analysis. The leakage from macro-crack would facilitate the corrosion of reinforced steel and surrounding concrete. Hence, the optimum usage of combined CA and SAP is highly suggested, which is accessible and economical for macro-crack closure in waterproof projects. [ABSTRACT FROM AUTHOR]