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North China type coalfield are gradually mining deep, and the mixing of groundwater is intensified. Hydrogen and oxygen isotopes are important elements for tracing groundwater movement. The fractionation response mechanism under mining conditions is not clear. In this paper, combined with numerical simulation, MixSIAR isotope mixing model and other methods, according to the δD, δ18O and hydrochemical information of various water bodies, the impact of coal mining on hydrogen and oxygen isotope fractionation is analyzed from multiple perspectives. The results show that summer soil water is the main source of recharge for limestone water, accounting for 30.7%–41.5%, and the Zhan River is the main source of recharge for limestone water. Before groundwater recharge, evaporation leads to the increase of δ18O in surface water by 0.31‰–5.58‰, water loss by 1.81%–28.00%, the increase of δ18O in soil water by 0.47‰–6.33‰, and water loss by 2.74%–35.80%. Compared with the coal mining layer, the degree of hydrogen and oxygen isotope drift and water-rock interaction in the coal mine stopping layer are significantly improved. The results of numerical simulation show that the pumping activity reduces the 18O concentration in the mining layer. The ion ratio is used as a new variable to eliminate the influence of water-rock interaction when calculating the mixing ratio. The results show that the limestone water is in a state of receiving external recharge, and mixing effect increases the δ18O in limestone water by 0.86‰ on average, and the δD increases by 0.72‰ on average. The research results explain the controlled process of hydrogen and oxygen isotope fractionation under mining conditions, which is of great significance to coal mine safety production. • The contribution ratio of surface water and soil water to limestone water in different seasons was estimated. • Summer soil water is the main recharge source of limestone water. • The mixing effect increases δ18O and δD in limestone water. • The isotope exchange and water-rock interaction in coal mine stopping layer are stronger than coal mining layer. • High temperature does not promote the drift of 18O in limestone water. [ABSTRACT FROM AUTHOR]

• The geometric dimension of the package shell of the sensing unit are studied by theory and experiment, and improper design of the package housing may degrade the frequency response characteristics of the sensing unit. • The influence of prestress on the frequency response characteristic of sensor is studied. • The geometric dimension of the package shell and the prestress of the sensing unit are reasonably optimized to make the working frequency of the sensor avoid the resonant frequency of the shell. • The paper provides a theoretical basis for the design and manufacture of the sensors with wide frequency response and high sensitivity in different engineering applications, such as high frequency small amplitude and low frequency large amplitude. In coal mine, military, oil well monitoring and other fields, the traditional electrical accelerometers based on piezoelectric and capacitive can not meet the needs of high-performance applications. The optical fiber acceleration sensor with high precision, large dynamic, wide frequency response, anti-electromagnetic interference and other unique advantages, can meet a variety of applications. The complete optical fiber acceleration sensor consists of a package housing and an internal sensing unit. Some factors, including the vibration and deformation of the housing itself, and the prestress of the sensing unit will directly affect the frequency response characteristics of the sensor. The experimental results show that the resonant frequency of the package housing is outside the operating frequency band of the sensor through reasonable design of shell parameters; in a certain torque range (0.2 N . m ∼ 0.8 N . m), the resonant frequency increases with the increase of the torque. The research provides a theoretical basis for the design and manufacture of the sensors with wide frequency response and high sensitivity in different engineering applications, such as high frequency small amplitude and low frequency large amplitude. [ABSTRACT FROM AUTHOR]

Land subsidence induced by coal mining (MLS) has posed a huge threat to the ecological environment, buildings, roads, and other infrastructure safety in mining areas. However, the prediction and evaluation of MLS is relatively complex, and the reliability of the prediction results is closely related to factors such as the professional knowledge and engineering experience of researchers. This paper aims to combine intelligent optimization algorithms: ant lion optimizer (ALO), bald eagle search (BES), bird swarm algorithm (BSA), harris hawks optimization (HHO), and sparrow search algorithm (SSA), with machine learning model of gradient boosting with categorical features support algorithm (CatBoost) to predict MLS. To achieve this goal, five hybrid models based CatBoost were developed and the prediction accuracy and reliability of the models were compared and analyzed. The prediction performance of the hybrid models has been significantly improved on the basis of a single model, of which the SSA-CatBoost model has the most obvious improvement (from R2 = 0.927 to 0.965, RMSE = 0.541 to 0.377, MAE = 0.386 to 0.297, VAF = 92.720 to 95.837). The importance and predictive contribution of all input features to predictive labels were studied with the Shapley method. The research results indicate that hybrid model technology is a reliable MLS prediction method. This study can help mining technicians use machine learning methods to study the degree of MLS damage to the surface environment and provide scientific advanced prediction and evaluation for the protection and management of the ecological environment in mining areas and the formulation of safety production measures. • High-precision prediction model of Mining Land Subsidence (MLS) was proposed. • The intelligence algorithms were used to Automatically optimize the hyperparameters of CatBoost. • The hybrid model can more reliably and intelligently evaluate the degree of MLS harm. • The hybrid model can scientifically guide mining environmental protection. [ABSTRACT FROM AUTHOR]