Experimental Study on Emergency Psychophysiological and Behavioral Reactions to Coal Mining Accidents.

Effective emergency responses are crucial for preventing coal mine accidents and mitigating injuries. This paper aims to investigate the characteristics of emergency psychophysiological reactions to coal mine accidents and to explore the potential of key indicators for identifying emergency behavioral patterns. Initially, virtual reality technology facilitated a simulation experiment for emergency escape during coal mine accidents. Subsequently, the characteristics of emergency reactions were analyzed through correlation analysis, hypothesis testing, and analysis of variance. The significant changes in physiological indicators were then taken as input features and fed into the three classifiers of machine learning algorithms. These classifications ultimately led to the identification of behavioral patterns, including agility, defensiveness, panic, and rigidity, that individuals may exhibit during a coal mine accident emergency. The study results revealed an intricate relationship between the mental activities induced by accident stimuli and the resulting physiological changes and behavioral performances. During the virtual reality simulation of a coal mine accident, subjects were observed to experience significant physiological changes in electrodermal activity, heart rate variability, electromyogram, respiration, and skin temperature. The random forest classification model, based on SCR + RANGE + IBI + SDNN + LF/HF, outperformed all other models, achieving accuracies of up to 92%. These findings hold promising implications for early warning systems targeting abnormal psychophysiological and behavioral reactions to emergency accidents, potentially serving as a life-saving measure in perilous situations and fostering the sustainable growth of the coal mining industry.

Research on psychophysiological characteristics of construction workers during consciously unsafe behaviors.

Workers' unsafe behavior is a primary cause leading to falling accidents on construction sites. This study aimed to explore how to utilize psychophysiological characteristics to predict consciously unsafe behaviors of construction workers. In this paper, a psychological questionnaire was compiled to measure risky psychology, and wireless wearable physiological recorders were employed to real-timely measure the physiological signals of subjects. The psychological and physiological characteristics were identified by correlation analysis and significance test, which were then utilized to develop unsafe behavior prediction models based on multiple linear regression and decision tree regressor. It was revealed that unsafe behavior performance was negatively correlated with task-related risk perception, while positively correlated with hazardous attitude. Subjects experienced remarkable increases in skin conductivity, while notable decreases in the inter-beat interval and skin temperature during consciously unsafe behavior. Both models developed for predicting unsafe behavior were reliably and well-fitted with coefficients of determination higher than 0.8. Whereas, each model exhibited its unique advantages in terms of prediction accuracy and interpretability. Not only could study results contribute to the body of knowledge on intrinsic mechanisms of unsafe behavior, but also provide a theoretical basis for the automatic identification of workers' unsafe behavior.

Effect of Water on the Chain Reaction Characteristics of Gas Explosion.

In order to explore the influence of water on the chain reaction characteristics of gas explosion, the 20 L explosion ball experiment and the homogeneous constant volume combustion reactor of CHEMKIN 17.0 simulations were carried out. The gas explosion response under four different water contents was tested and simulated. The effects of water on the pressure, free radicals, and reactants of gas explosion were compared and analyzed. The research results show that the inhibition of water on gas explosion was enhanced with the increase of water fraction in the initial mixture; the temperature, pressure, catastrophic gases such as CO, and concentration of activation centers in the reaction system can be reduced by water; the intensity of gas explosion can be reduced by inhibiting the formation of H, O, and OH free radicals, the main reactants of gas explosion and gas explosion energy.