Ventilation real-time calculation and coordinated adjustment method for large underground powerhouse

Intelligent ventilation on demand is crucial for ensuring environmental safety in underground caving groups and for the high-quality construction and development of hydropower projects. Ventilation systems for large underground caving groups during construction frequently exhibit complex three-dimensional layouts, different air loads across regions, and dynamic demand under varying regulation conditions.

To achieve spatial node extraction, branch correlation decoupling, and stable joint adjustment of complex flow fields, this paper examines the development characteristics of fluids under construction ventilation in extensive spatial structures. It demonstrates the necessity of constructing a graph structure based on the ventilation flow characteristics for analyzing and adjusting ventilation system parameters. The regional modeling theory is discussed, detailing the principles and methods of node extraction for one-dimensional tube bundle fluids (network) and three-dimensional spatial flow field elements (field). Among these, the area where fluid parameter information changes along the main airflow direction employs network node extraction, while the regions with multi-directional complex flow paths utilize the three-dimensional field node extraction method. Virtual branches address the network-field coupling problem, utilizing the nodal pressure approach. This method treats the nodal pressure as the unknown variable and airflow deviation as the assessment criterion. Nodes with known pressure values serve as reference nodes for solving the pressure at all network nodes, and are further assigned to field simulation boundaries. By numerically simulating the three-dimensional spatial flow field, the virtual branch air flow rates are iteratively fed back into the air network calculation for a coupled solution. This paper also introduces the node-property-edge triplet, which effectively reflects the structure, performance, and behavioral characteristics of nodes. Furthermore, to optimize the ventilation coordination efficiency, a hypergraph structure for joint adjustment, with edges as the analysis object, displays the coupling interactions between the ventilation branches and loops. Considering the joint adjustment sensitivity, an optimal resistance control method is proposed, which involves constructing target and response node sets, setting response efficiency constraints, and optimizing to form a ventilation adjustment plan. An intelligent ventilation coordination platform integrates the resistance control model of coupling interactions, including modules for network design, ventilation design, field-network integration, loop generation, and optimization analysis. Within this framework, the network design module is dedicated to reconstructing the physical model of the ventilation system, while the ventilation design and field-network integration modules are used to assign basic fluid characteristic parameters of ventilation to the established model. The loop generation and optimization analysis modules are employed for solving the overall wind network parameters, including air volume, air pressure, and wind resistance.

The field-network coupling method using nodal pressure eliminated the need for loop identification and effectively addressed the interdependent coupling between network nodes and flow field boundaries. The intelligent ventilation coordination platform was integrated with online environmental monitoring devices to automatically gather critical ventilation environment parameters, thereby enabling real-time calculations of the ventilation system based on environmental monitoring data and providing 3D visualization and early warning capabilities.

The ventilation design parameters of an engineering project are used to implement targeted air volume control deployment. The integrated control system exhibits high responsiveness. On the premise that the air volume of each unit meets the threshold requirements, the air volume adjustment efficiency of the target unit and the overall stability of the air distribution network can always fulfill the specified requirements. The results indicate a timely and stable system response and can provide a reference for similar projects.