Assimilated Physical Digital Twin of Venous Valve for Biological Flows

Venous valves play a critical role in maintaining unidirectional blood flow under low-pressure, low-Reynolds-number conditions, where structural-flow interactions and wall dynamics significantly influence hemodynamics. This work presents the development of an Assimilated Physical Digital Twin (APDT) framework for modeling venous valve dynamics by coupling real-time digital simulations with some high-fidelity physical experimentation. A sensor-integrated, 3D-printed benchtop platform, featuring soft, flexible valve leaflets within a water-flow-guided loop, enables precise acquisition of flow, pressure, and displacement data. The physical model is integrated with a digital twin that leverages patient-specific anatomical data, multi-scale CFD modeling, and two-way data assimilation to mirror and predict venous valve behavior across varying physiological, pathological, and microgravity conditions. This cyber-physical environment enables closed-loop refinement, where real-world sensor data continuously updates the digital model, enhancing simulation accuracy through iterative learning. Predictive capabilities of the system support the analysis of retrograde flow, valve dysfunction, and thrombus formation, offering a powerful tool for preclinical testing, surgical planning, and assessing thrombosis risk in extreme environments such as spaceflight. The APDT platform represents a novel convergence of experimental and computational biomechanics, advancing personalized diagnostics and therapeutic strategies in vascular health.