Unnatural dynamics of the notorious vortex in the left ventricle is often associated with cardiac disease. Understanding how different cardiac diseases alter the flow physics in the left ventricle may therefore provide a powerful tool for disease detection. This experimental in vitro work investigates the fluid dynamics within a model left ventricle in the case of progressive chronic aortic regurgitation, a valvular disease characterized by a leaking aortic valve and consequently double-jet filling within the elastic left ventricular geometry. The experiment consists of simulating different severities of the disease on a novel left heart simulator and the corresponding flow fields are acquired by time-resolved planar particle image velocimetry. Progressive diastolic vortex reversal was observed in the left ventricle accompanied by an increase in viscous energy dissipation. The corresponding material transport phenomena were strongly determined by the motion of the counter-rotating vortices driven by the regurgitant aortic and mitral jets. Particularly, the overall particle residence time appeared to be significantly longer with moderate aortic regurgitation, attributed to the dynamics resulting from the timing between the onset of the two jets. Increasing regurgitation severity was shown to be associated with higher frequencies in the time-frequency spectra of the velocity signals at various points in the flow, suggesting non-laminar mixing past moderate aortic regurgitation. Furthermore, a large part of the regurgitant inflow was found to be retained for at least one full cardiac cycle. Such an increase in particle residence time accompanied by the occurrence and persistence of a number of attracting Lagrangian coherent structures presents favourable conditions and locations for activated platelets to agglomerate within the left ventricle, potentially posing an additional risk factor for patients with aortic regurgitation. In view of the lack of available fluid dynamics data in the literature regarding aortic regurgitation and even healthy left ventricular flow, this dissertation constructs reduced-order models of the acquired data using the proper orthogonal and dynamic mode decompositions. The performance of the two methods in reconstructing the intraventricular flows and derived quantities was evaluated, and the selected reduced-order models were made publicly available.