引入风量波动因子动态解算矿井热流耦合通风网络

Dynamic calculation of heat-flow coupled mine ventilation network with introduction of air volume fluctuation factor

  • 摘要: 为解决非定常风流介质在通风系统管道域中热流动,导致矿井风量产生连续状态下的多尺度波动,使得利用静态热压湿变风网解算模型映射的系统状态精准度不高问题,在风流流动实质为空气动力过程与热力过程耦合形成的多变过程的框架下,将系统运行状态实时精准映射等效为动态解算时间序列下矿井热流耦合波动通风网络。溯源热流耦合风量多尺度波动原理,明确风量波动致因主体为风流密度,以此为表征变量,以非稳态环境场和梯度流动场为边界条件,利用微元法研究风流的热流耦合属性随时间变化规律,提出了以时间为根变量的风流瞬态流动特征模型。定义风量波动因子以表示波动风量瞬态位置,代入风网静态解算模型中,构建连续空间特征下波动风网解算模型,提出波动因子与风流瞬态流动特征模型的转换方程,将瞬态流动函数作为波动传递变量代入波动风网解算模型中,形成了时间序列下波动风网动态解算模型,达到了实时精准映射风网运行状态的目的。为验证模型生产可行性,以双马一矿为工程对象,将时间序列下矿井跨岩层热环境信息作为初始值代入动态解算模型中,完成了全局风网实时解算,实现了将初始固定风量值拓展为时间序列下风量波动区间,实时反映了在风流热流耦合作用下的生产矿井通风系统运行特征。波动风网动态解算通过实时分析矿内环境−通风变量耦合效应,实现了风网状态精准定量映射,为后续定量决策提供数据基础和优化路径以提高智能控风的动态适应性和本质精度。

     

    Abstract: To address the issue of continuous multi-scale fluctuations in air volume due to the thermal flow within the unsteady airflow medium in the ventilation system pipe domain, which limits the accuracy of system state mapping when using a static thermal-pressure-humidity ventilation calculation model. Under the framework that the air flow is a polytropic process involving coupled aerodynamic and thermodynamic processes, the real-time and accurate mapping of the system operation state is equivalent to dynamically calculation the heat-flow coupling fluctuation mine ventilation network under time series. The underlying multiscale fluctuation principles of heat-flow coupled air volume were examined, identifying airflow density as the primary cause of volume fluctuation. Using this as a characterization variable, with unsteady environmental and gradient flow fields as boundary conditions, an infinitesimal approach was used to analyze the time-variant law of heat-flow coupled property of airflow. A transient airflow feature model was developed with time as the root variable. An air volume fluctuation factor was defined to capture the transient position of fluctuating air volume, which was then incorporated into a static ventilation network model, yielding a fluctuating ventilation network calculation model with continuous spatial characteristics. Additionally, a transformation equation linking the fluctuation factor with the transient airflow feature model was established to integrate the transient flow function as a fluctuation transfer variable in the fluctuating ventilation network model, thereby forming a time-series-based dynamic calculation model for the fluctuating ventilation network to achieve real-time, precise mapping of the network state. To validate the production feasibility of the dynamic calculation model for the fluctuating ventilation network, Shuangma I Mine was taken as the engineering case, with cross-strata thermal environment data in time series applied as the initial condition. This enabled real-time global ventilation network calculation, expanding the fixed initial air volume value into a time-series fluctuation range and accurately reflecting the real-time operational characteristics of the production ventilation system under the heat-flow coupled airflow condition. The dynamic calculation for the fluctuating ventilation network facilitates precise quantitative mapping of the ventilation network state through real-time analysis of the coupling effect between the mine environment and ventilation variables, establishing a data foundation and optimized pathway for subsequent intelligent quantitative decision-making to enhance the adaptive adaptability and intrinsic precision of intelligent ventilation control.

     

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