Volker Maiwald

Solar magnetism eXplorer (SolmeX)

The magnetic field plays a pivotal role in many fields of Astrophysics. This is especially true for the physics of the solar atmosphere. Measuring the magnetic field in the upper solar atmosphere is crucial to understand the nature of the underlying physical processes that drive the violent dynamics of the solar corona—that can also affect life on Earth. SolmeX, a fully equipped solar space observatory for remote-sensing observations, will provide the first comprehensive measurements of the strength and direction of the magnetic field in the upper solar atmosphere. The mission consists of two spacecraft, one carrying the instruments, and another one in formation flight at a distance of about 200 m carrying the occulter to provide an artificial total solar eclipse. This will ensure high-quality coronagraphic observations above the solar limb. SolmeX integrates two spectro-polarimetric coronagraphs for off-limb observations, one in the EUV and one in the IR, and three instruments for observations on the disk. The latter comprises one imaging polarimeter in the EUV for coronal studies, a spectro-polarimeter in the EUV to investigate the low corona, and an imaging spectro-polarimeter in the UV for chromospheric studies. SOHO and other existing missions have investigated the emission of the upper atmosphere in detail (not considering polarization), and as this will be the case also for missions planned for the near future. Therefore it is timely that SolmeX provides the final piece of the observational quest by measuring the magnetic field in the upper atmosphere through polarimetric observations.

Decision Support Tool for Concurrent Engineering in Space Mission Design

The concurrent engineering (CE) approach has been successfully applied to the early design phase of space missions. During CE sessions, a software support is needed to allow multidisciplinary design data exchange. At the moment, a spreadsheet-based solution enhanced with macros is used at the German Aerospace Center (DLR) to create a system model of a space mission during the early design phase. Now there is an increasing demand to take advantage of this system model and provide data analysis features which improve the decision making during CE sessions. Since the current approach is limited for such analysis, DLR has started developing a new tool called Virtual Satellite. It offers extended software support required by the Concurrent Engineering Facility of DLR in Bremen. On top of the previous spreadsheet functionalities, it provides means for online data analysis and system modeling. The results of these data analyses are presented to the discipline experts using different views which help in performing an early design optimization. In this paper, the impact of these views on the decision making during the AEGIS space mission study is presented as a proof of concept.

Greenhouse Modules and Regenerative Life-Support Systems for Space

Long exploration missions to the Moon and Mars will require the growth of food on site to sustain the crew because current launchers are unable to send the required mass of consumables into orbit at an affordable cost. Growing fresh food will also be of prime importance for the crew dietary and psychological requirements. ESA expertise on advanced life support systems within the MELiSSA (Micro-Ecological Life Support System Alternative) project, coupled to the EDEN (Evolution and Design of Environmentally-closed Nutrition Sources) project in DLR join forces to study a greenhouse within the MELiSSA loop for a manned base on the Moon surface. Both projects are aimed at studying and developing regenerative life support systems for long duration space missions: MELiSSA is a closed artificial ecosystem program based on microbiological and physicochemical waste degradation and higher plants; EDEN combines different CEA Technologies (Controlled Environmental Agriculture) within an automatic planetary Greenhouse-Module (GHM). Previous studies on Greenhouse Modules have addressed mass, volume, and energy consumption needs but the technologies and data on which these calculations were based are now outdated or were limited at that time. They thus need to be reassessed to have better estimates of these variables and evaluate what it takes to grow plants on the Moon. A study of the lunar environment based on various elements such as illumination, radiation levels, accessibility, and temperature gradients, enables to make a comparative analysis for the best location to setup a greenhouse module on the Moon surface. Trade-offs between electrical and natural lighting, and various grow accommodation options, based on the ALISSE criteria are also conducted. Finally, this leads to the identification of critical points and recommendation on future work for preliminary greenhouse concepts.

Conceptual data model: A foundation for successful concurrent engineering

Today, phase A studies of future space systems are often conducted in special design facilities such as the Concurrent Engineering Facility at the German Aerospace Center (DLR). Within these facilities, the studies are performed following a defined process making use of a data model for information exchange. Quite often it remains unclear what exactly such a data model is and how it is implemented and applied. Nowadays, such a data model is usually a software using a formal specification describing its capabilities within a so-called meta-model. This meta-model, often referred as conceptual data model, is finally used and instantiated as system model during these concurrent engineering studies. Such software also provides a user interface for instantiating and sharing the system model within the design team and it provides capabilities to analyze the system model on the fly. This is possible due to the semantics of the underlying conceptual data model creating a common language used to exchange and process design information. This article explains the implementation of the data model at DLR and shows information how it is applied in the concurrent engineering process of the Concurrent Engineering Facility. It highlights important aspects concerning the modeling capabilities during a study and discusses how they can be implemented into a corresponding conceptual data model. Accordingly, the article presents important aspects such as rights management and data consistency and the implications of them to the software’s underlying technology. A special use case of the data model is depicted and shows the flexibility of the implementation proven by a study of a multi-module space station.

GTOC 9: Results from the German Aerospace Center (Team DLR)

This paper discusses the methods used by the team from the German Aerospace Center (DLR) for solving the 9th Global Trajectory Optimization Competition (GTOC) problem. The GTOC is an event taking place every year lasting roughly one month during which the best aerospace engineers and mathematicians world wide challenge themselves to solve a nearlyimpossible problem of trajectory design.