Development of a hybrid, ANN-linear model for building drainage systems subject to multiple simultaneous discharges

The discharge of wastewater from multiple floors into a vertical stack presents significant simulation challenges due to the complex two-phase flow, involving annular water movement and airflow induced by the ventilation network. These challenges are particularly pronounced in high-rise drainage systems. Previous studies by the authors successfully simulated classical pressure profiles using ANN models; however, limitations arose in predicting pressure variations under simultaneous discharge. In this study, a hybrid modelling approach was developed by integrating a linear component into the ANN framework. Initially, Feed Forward Back Propagation and Radial Basis Function ANN models were trained and tested. To enhance accuracy, a Particle Swarm Optimization (PSO) algorithm was later applied to optimize the Feed Forward model’s weights and biases. To capture different flow regimes, a hybrid ANN–Linear model was developed by separating dry-stack and wet-stack zone data. The predictions were validated against experimental data from a unique 32-storey drainage test facility (NLT Tower, UK). The model used discharge flow rate and stack height as inputs, with stack pressure as the output. The hybrid model, trained with real-world data, demonstrated reliable performance and proved an effective tool for designing and optimizing Building drainage system in high-rise buildings under simultaneous discharge conditions. Practical Application The simulation of two-phase flow phenomena in high-rise building with simultaneous discharges mimics the realistic situation. The hybrid ANN–linear model can be applied in the design and optimisation of high-rise building drainage systems to ensure safe and efficient operation under peak load conditions. By accurately predicting pressure profiles across both dry and wet stack zones, the model enables engineers to size vent pipes, select stack diameters, and configure branch connections to minimise the risk of trap seal loss, backflow, and system noise. Incorporating real-world data allows for site-specific calibration, supporting compliance with building codes and reducing overdesign.