In the last decade, the demand for the prediction of complex multi-physics prob- lems such as fluid-structure interaction (FSI) has strongly increased. For the development and improvement of appropriate numerical tools several test cases were designed in order to vali- date the numerical results based on experimental reference data [4, 12, 13, 8, 9, 10]. Since FSI problems often occur in turbulent flows also in the experiments similar conditions have to be provided. In the test-case FSI-PfS-1a [7] presented in the first contribution to this session, a cylinder is used with an attached flexible rubber plate. The resulting FSI problem is nearly two-dimensional regarding the phase-averaged flow and the structure deformations. The ac- tual test case FSI-PfS-3a is the reasonable further development step of this two-dimensional benchmark to a forced fully three-dimensional flow, which now also leads to a significant three- dimensional structure deformation. The cylinder is replaced by a truncated cone. Similar to FSI-PfS-1a [7] a rubber plate is attached at the backside. This geometrical setup is exposed to a constant flow at Re = 32,000 which is in the subcritical regime. Due to the linearly increasing diameter of the cone the alternating eddies in the wake even become larger resulting in corre- spondingly increasing structural displacements. Owing to these challenging flow and structure effects, this benchmark will be the next step for validating FSI predictions for real applications. The experiments are performed in a water channel with clearly defined and controllable bound- ary and operating conditions. For measuring the flow a two-dimensional mono-particle-image velocimetry (PIV) system is applied. In order to characterize the three-dimensional behavior of the flow, phase-averaged PIV measurements are performed at three different planes. The structural deformations are measured along a line on the structure surface with a time-resolved laser distance sensor. The resulting FSI problem shows a quasi-periodic deformation behavior so that a phase averaging of the results is reasonable. By phase-averaging turbulent fluctua- tions are averaged out and thus a comparison with corresponding numerical simulations based on LES [3] and RANS [12, 13] approaches is possible.