Experimental and numerical research on the aerodynamics of unsteady moving aircraft

For the experimental determination of the dynamic wind tunnel data, a new combined motion test capability was developed at the German–Dutch Wind Tunnels DNW for their 3 m Low Speed Wind Tunnel NWB in Braunschweig, Germany, using a unique six degree-of-freedom test rig called ‘Model Positioning Mechanism’ (MPM) as an improved successor to the older systems. With that cutting-edge device, several transport aircraft configurations including a blended wing body configuration were tested in different modes of oscillatory motions roll, pitch and yaw as well as delta-wing geometries like X-31 equipped with remote controlled rudders and flaps to be able to simulate realistic flight maneuvers, e.g., a Dutch Roll. This paper describes the motivation behind these tests and the test setup and in addition gives a short introduction into time accurate maneuver-testing capabilities incorporating models with remote controlled control surfaces. Furthermore, the adaptation of numerical methods for the prediction of dynamic derivatives is described and some examples with the DLR-F12 configuration will be given. The calculations are based on RANS-solution using the finite volume parallel solution algorithm with an unstructured discretization concept (DLR TAU-code).     

Application of time-variable process noise in terrestrial reference frames determined from VLBI data

In recent years, Kalman filtering has emerged as a suitable technique to determine terrestrial reference frames (TRFs), a prime example being JTRF2014. The time series approach allows variations of station coordinates that are neither reduced by observational corrections nor considered in the functional model to be taken into account. These variations are primarily due to non-tidal geophysical loading effects that are not reduced according to the current IERS Conventions (2010). It is standard practice that the process noise models applied in Kalman filter TRF solutions are derived from time series of loading displacements and account for station dependent differences. So far, it has been assumed that the parameters of these process noise models are constant over time. However, due to the presence of seasonal and irregular variations, this assumption does not truly reflect reality. In this study, we derive a station coordinate process noise model allowing for such temporal variations. This process noise model and one that is a parameterized version of the former are applied in the computation of TRF solutions based on very long baseline interferometry data. In comparison with a solution based on a constant process noise model, we find that the station coordinates are affected at the millimeter level.     

Study of the radiation fields in LEO with the Space Application of Timepix Radiation Monitor (SATRAM)

We present the analysis of data taken by the Space Application of Timepix Radiation Monitor (SATRAM). It is centred on a Timepix detector (300?$\mathrm{\mu }$m thick silicon sensor, pixel pitch 55?$\mathrm{\mu }$m, 256?×?256 pixels). It was flown on Proba-V, an Earth observing satellite of the European Space Agency (ESA) from an altitude of 820?km on a sun-synchronous orbit, launched on May 7, 2013. A Monte Carlo simulation was conducted to determine the detector response to electrons (0.5–7?MeV) and protons (10–400?MeV) in an omnidirectional field taking into account the shielding of the detector housing and the satellite. With the help of the simulation, a strategy was developed to separate electrons, protons and ions in the data. The measured dose rate and stopping power distribution are presented as well as SATRAM’s capability to measure some of the stronger events in Earth’s magnetosphere. The stopping power, the cluster height and the shape of the particle tracks in the sensor were used to separate electrons, protons and ions. The results are presented as well. Finally, the pitch angles for a short period of time were extracted from the data and corrected with the angular response determined by the simulation.