Physics‐Inspired, Ageing‐Aware Digital Twin Framework for Long‐Term Performance Prediction in Bioreactor Systems

Conventional bioreactor models and many existing digital twin formulations commonly assume constant transport and thermal properties, which limits their ability to represent the gradual degradation that occurs during long‐term operation. In practical bioprocess systems, ageing mechanisms such as biofilm formation and fouling progressively modify oxygen and heat transfer behaviour, influencing overall system performance over time. To address this limitation, this study presents a physics‐inspired, ageing‐aware digital twin framework in which degradation mechanisms are incorporated directly as time‐evolving internal state variables within the governing transport formulation. Unlike conventional approaches that treat transport coefficients as fixed or periodically adjusted parameters, the proposed framework enables continuous mechanistic representation of degradation‐driven transport evolution. The model integrates mechanistic mass and energy balances with ageing‐dependent transport relationships to describe the coupled evolution of oxygen transfer and thermal behaviour during prolonged operation. Simulation results demonstrate that ageing‐induced transport degradation leads to gradual reductions in oxygen transfer capacity, productivity decline, and measurable thermal drift, even under nominal operating conditions. The framework further provides mechanistic insight into how biofilm accumulation influences long‐term transport behaviour and system dynamics in ways not captured by time‐invariant formulations. By explicitly coupling ageing evolution with transport degradation, the proposed digital twin establishes a physically grounded and interpretable framework for degradation‐aware bioreactor modelling. The present study is intended as a mechanistic foundation that can support future experimental calibration, parameter estimation and integration with monitoring systems for long‐term sustainable bioprocess operation.