Massively Extended Modular Monitoring and a Second Life for Upper Stages

Launching science and technology experiments to space is expensive. Although commercial spaceflight has resulted in a drop of prices, the cost for a launch is still significant. However, most of theweight that is needed to conduct experiments in space belongs to the spacecraft’s bus and it is responsiblefor power distribution, thermal management, orbital control and communications. An upper stage, on the other hand, includes all the necessary subsystems andhas to be launched in any case. Many upper stages (e.g. ARIANE5) will even stay in orbit for severalyears after their nominal mission with all their subsystems intact but passivated.We proposea compact system based on a protective container and high-performance Commercial-off-the-Shelf (COTS) hardwarethat allows cost-efficient launching oftechnology experiments by reusing the launcher’s upper stage and its subsystems. Addingacquisition channels for various sensors gives the launch provider the ability to exploitthe computational power of the COTS hardwareduring the nominal mission. In contrast to existing systems,intelligent and mission-dependent data selection and compression can beapplied to the sensor data.In this paper, we demonstrate the implementation and qualification of a payload bussystem based on COTScomponentsthat is minimallyinvasive to the launcher(ARIANE5)and its nominal missionwhile offering computational power to both the launch provider and a potential payloaduser. The reliability of the COTS-based system is improvedby radiation hardening techniques and software-based self-test detecting and counteracting faults during the mission

Stochastic modelling of 3D fiber structures imaged with X-ray microtomography

Many products incorporate into their design fibrous material with particular levels of permeability as a way to control the retention and flow of liquid. The production and experimental testing of these materials can be expensive and time consuming, particularly if it needs to be optimised to a desired level of absorbency. We consider a parametric virtual fiber model as a replacement for the real material to facilitate studying the relationship between structure and properties in a cheaper and more convenient manner. 3D image data sets of a sample fibrous material are obtained using X-ray microtomography and the individual fibers isolated. The segmented fibers are used to estimate the parameters of a 3D stochastic model for generating softcore virtual fiber structures. We use several spatial measures to show the consistency between the real and virtual structures, and demonstrate with lattice Boltzmann simulations that our virtual structure has good agreement with respect to the permeability of the physical material