Aortic dissection is a life-threatening vascular emergency, and accurate prediction and mechanistic analysis of false lumen thrombosis are of substantial clinical importance. However, existing porous media–based algorithms remain limited in their ability to precisely capture thrombus growth dynamics and the associated hemodynamic alterations. In this study, a novel multiphase porous media framework is proposed, in which an extended Darcy–Brinkman–Stokes equation is employed to describe solid–liquid phase interactions, and a newly formulated porosity equation is introduced to simplify platelet transport and deposition processes. When applied to patient-specific models, the proposed method demonstrated high predictive accuracy, achieving a correlation coefficient of 0.97 between predicted and measured thrombus volumes in 12 cases with partially thrombosed false lumens and 9 cases with completely thrombosed false lumens. The average computational time per case was reduced to 40 minutes, corresponding to an improvement in efficiency of approximately 70%. In addition, a quantitative relationship between Hounsfield units derived from patient imaging and thrombus porosity was established. Hemodynamic simulations under varying degrees of thrombus formation revealed that modest changes in thrombus permeability can induce pronounced pressure fluctuations at the blind end of the false lumen. Compared with conventional Navier–Stokes–based models, false lumen pressures were significantly elevated when thrombus permeability was explicitly considered (P < 0.005). From a mechanistic perspective, the DBS-based model captures intensified blood flow–thrombus interactions and increased wall shear stress at the tear site. Collectively, the proposed algorithm offers a mechanistic explanation for the inconsistent prognostic implications of partial false lumen thrombosis and provides a quantitative framework for postoperative risk assessment in patients with aortic dissection.