Risk assessment of gas control and spontaneous combustion of coal under gas drainage of an upper tunnel

The adjustment of the gas drainage rate has an immediate impact on air leakage in gob,thus resulting in the change of self-heating of coal.While regulating the gas drainage parameters,the risk of spontaneous combustion of coal should be considered.The risk assessment of gas control and spontaneous combustion of coal under gas drainage in a tunnel was investigated at different gas drainage rates.The distributions of the air volume along the working face,the gas management effects and the width of the oxidation zone were subjected to risk analysis.As the simulation results showed,with increasing gas drainage rate,although the safety of gas dilution by ventilation was assured,the intensifying air leakage caused the oxidation zone to move into the deeper gob and led to an increase in the width of the oxidation zone.A risk assessment method was proposed to determine a suitable gas drainage rate for the upper tunnel.The correctness of the risk assessment and the validity of the numerical modelling were confirmed by the field measurements.

Olfactory ensheathing cell transplantation improves sympathetic skin responses in chronic spinal cord injury

Forty-three patients with chronic spinal cord injury for over 6 months were transplanted with bryonic olfactory ensheathing cells, 2-4 × 106, into multiple sites in the injured area under the sur-gical microscope. The sympathetic skin response in patients was measured with an electromyo-graphy/evoked potential instrument 1 day before transplantation and 3-8 weeks after trans-tion. Spinal nerve function of patients was assessed using the American Spinal Injury Association impairment scale. The sympathetic skin response was elicited in 32 cases before olfactory en-sheathing celltransplantation, while it was observed in 34 cases after transplantation. tantly, sympathetic skin response latency decreased significantly and amplitude increased cantly after transplantation. Transplantation of olfactory ensheathing cells also improved American Spinal Injury Association scores for movement, pain and light touch. Our findings indicate that factory ensheathing celltransplantation improves motor, sensory and autonomic nerve functions in patients with chronic spinal cord injury.

Chaotic Motion in a Nonlinear Car Model Excited by Multi-frequency Road Surface Profile

In order to solve the problem that existing non- linear suspension models have not considered chaotic motion in primary and other resonances, and numerical calculation model is too simplified to capture the accurate critical conditions for the chaotic motion, a nonlinear suspension model and its new paths of chaos are investi- gated. Primary resonances, secondary resonances, and combined resonances are performed using multiple-time scales method. Based on the Melnikov functions, the crit- ical conditions for the chaotic motion of the nonlinear system are found, which is 0.246 7 for the primary reso- nance, and 0.338 8 for the secondary resonance. The effects of parameters on chaotic range are considered, and results show that nonlinear stiffness of suspension k2 has the lar- gest impact on the chaotic range while damping coefficient C＋ has the smallest one. The chaotic responses on the area of the primary and secondary resonances are discussed via Lyapunov exponents and numerical integration of the equations of motion. It is found from Lyapunov exponents and Poincare maps that motions are chaos over critical conditions, and has shown two very different paths of chaos on the primary and secondary resonances. Chaotic motion patterns in the primary and secondary resonances are obtained with more accurate critical conditions, whichis a necessary complement to nonlinear study in nonlinear suspension mode.

A dynamic tire model based on HPSO-SVM

In order to accurately describe the force mechanism of tires on agricultural roads and improve the life cycle of agricultural tires,a tire-deformable terrain model was established.The effects of tread pattern,wheel spine,tire sidewall elasticity,inflation pressure and soil deformation were considered in the model and fitted with a support vector machine(SVM)model.Hybrid particle swarm optimization(HPSO)was used to optimize the parameters of SVM prediction model,of which inertia weight and learning factor were improved.To verify the performance of the model,a tire force prediction model of agricultural vehicle with the improved SVM method was investigated,which was a complex nonlinear problem affected by many factors.Cross validation(CV)method was used to evaluate the training precision accuracy of the model,and then the improved HPSO was adopted to select parameters.Results showed that the choice randomness of specifying the parameters was avoided and the workload of the parameter selection was reduced.Compared with the dynamic tire model without considering the influence of tread pattern and wheel spine,the improved SVM model achieved a better prediction performance.The empirical results indicate that the HPSO based parameters optimization in SVM is feasible,which provides a practical guidance to tire force prediction of agricultural transport vehicles.