To date, cardiovascular surgery enables the treatment of a wide range of aortic pathologies. One of the current challenges in this field is given by the detection of high-risk patients for adverse aortic events, who should be treated electively. Reliable diagnostic parameters, which indicate the urge of treatment, have to be determined. Functional imaging by means of 4D phase contrast-magnetic resonance imaging (PC-MRI) enables the time-resolved measurement of blood flow velocity in 3D. Applied to aortic phantoms, three dimensional blood flow properties and their relation to adverse dynamics can be investigated in vitro. Emerging "?in silico"? methods of numerical simulation can supplement these measurements in computing additional information on crucial parameters. We propose a framework that complements 4D PC-MRI imaging by means of numerical simulation based on the Finite Element Method (FEM). The framework is developed on the basis of a prototypic aortic phantom and validated by 4D PC-MRI measurements of the phantom. Based on physical principles of biomechanics, the derived simulation depicts aortic blood flow properties and characteristics. The framework might help identifying factors that induce aortic pathologies such as aortic dilatation or aortic dissection. Alarming thresholds of parameters such as wall shear stress distribution can be evaluated. The combined techniques of 4D PC-MRI and numerical simulation can be used as complementary tools for risk-stratification of aortic pathology.