Model-based systems engineering (MBSE) is an emerging methodology not only in the field of spacecraft systems engineering. The key objective is to store the whole system design in one single source of truth system model. The continuously maintained and customizable open-source MBSE tool Virtual Satellite developed by German Aerospace Center (DLR) offers a framework for storing such a system model. Since the open-source 3D computer aided design (CAD) software FreeCAD has a dedicated Virtual Satellite workbench for importing the 3D model file generated by Virtual Satellite, it is possible to export the 3D model from Virtual Satellite, apply changes to it in FreeCAD, and afterwards reimport it in Virtual Satellite. This paper presents a workflow implementation to conduct automated steady-state and transient thermal analyses using the Virtual Satellite system model as a basis, utilizing the aforementioned features. Part of this effort was to extend Virtual Satellite by thermal modeling capabilities, such as material parameters, surface characteristics, thermal interfaces, boundary conditions and further relevant aspects. With custom Java applications, so-called “Apps”, all aspects of the system model relevant for a thermal analysis are exported from Virtual Satellite and written to accordingly generated text files. Moreover, the before described 3D model export is used to export the model to FreeCAD. The FreeCAD Python console, in combination with the finite element method (FEM) workbench, is used to create a script that executes meshing, application of the boundary and initial conditions, as well as identification of contacts between parts and application of the specified contact conductance values. The obtained files form a complete thermal model and can be fed directly into the open-source FEM software CalculiX for executing the thermal analysis. Then, the result can be processed by an additional Virtual Satellite App. To account for the space thermal environment an additional feature was added to the FreeCAD script. The feature uses orbit information obtained from external mission analysis tools to calculate the approximate combined heat load from Sun, Earth infrared, and albedo radiation at each time point in the specified simulation time interval. This new workflow allows to execute quick thermal analyses at an early design stage and therefore opens new opportunities in the evaluation of different system designs, as early as in a concurrent engineering study. Configuration parameters are provided that also allow more sophisticated analyses in later development phases, such as custom mesh definition and local mesh refinement.

DLR is using a data model for their Concurrent Engineering studies. This model is intended to be used for the whole life-cycle of a spacecraft. Here, the system is usually decomposed by so called product structures. So far, the used product structures in the model differ between life-cycle Phase A and B. This leads to reuse problems, requires complicated transformations, and potentially incurs information loss. As a consequence, it is required to harmonize these product structures. This paper defines a reasonable subset of Phase B product structures for the application in CE. They will have an increase in model size as well as user interactions. The increase is quantified in this paper and discussed with qualitative observations of two studies where these new product structures have been used.

In model-based systems engineering projects, engineers from multiple domains collaborate by establishing a common system model. Multi-level modeling is a technique that can be used to model the development from abstract ideas to concrete implementations. However, current multi-level modeling approaches are not adequate for processes with multiple modeling phases that might have to be rearranged later. In this paper, we introduce multi-phase modeling that utilizes concepts of multi-level modeling by considering a description of the expected phase ordering per domain. Constraints aware of this context can express that certain elements are only valid in specific phases without having to determine a concrete phase ordering for a particular model. This enables using multi-phase modeling in flexible workflows, adapting to changing requirements and the definition of access rules in domain notation. We show feasibility of this multi-phase modeling by applying it to multiple real-life systems engineering projects of the aerospace domain.

This paper presents the software responsible for the design and execution of the experiments in the Bose-Einstein Condensate and Cold Atom Laboratory (BECCAL) mission, an experiment with ultra-cold and condensed atoms on the International Space Station. The software consists of two parts: the experiment control software and the experiment design tools. The first corresponds to the software running on the payload and is in charge of controlling and executing the experiments, while the latter are the tools used by the scientists to create the experiment definition that will be later uploaded to the instrument to be executed. To overcome the challenge of developing software with such complexity, it was decided to follow a model-driven development approach. Several domain-specific languages (DSLs) have been created to allow scientists to describe their experiments in a domain-specific way. These descriptions are then uploaded and executed by different interpreters onboard. The paper details the architecture of the experiment control software and the different modules that compose it, as well as the developed languages and tools used to describe new experiments. The paper also discusses and evaluates some important aspects of the software, such as how resilient it is to failures, as well as the advantages and disadvantages of the selected approach compared to other approaches used in similar missions. The developed software will also be used for the MAIUS-2/3 missions.

Microgravity eases several constraints limiting experiments with ultracold and condensed atoms on ground. It enables extended times of flight without suspension and eliminates the gravitational sag for trapped atoms. These advantages motivated numerous initiatives to adapt and operate experimental setups on microgravity platforms. We describe the design of the payload, motivations for design choices, and capabilities of the Bose-Einstein Condensate and Cold Atom Laboratory (BECCAL), a NASA-DLR collaboration. BECCAL builds on the heritage of previous devices operated in microgravity, features rubidium and potassium, multiple options for magnetic and optical trapping, different methods for coherent manipulation, and will offer new perspectives for experiments on quantum optics, atom optics, and atom interferometry in the unique microgravity environment on board the International Space Station.

The ScOSA project (Scalable On-board Computing for Space Avionics) of the German Aerospace Center aims at combining radiation hardened space hardware together with unreliable, but high performance COTS (commercial off-the-shelf) components as the processing nodes in a heterogeneous on-board network in order to provide future space missions with the necessary processing capabilities. However, such a system needs to cope with node failures. Our approach is to use a static reconfiguration graph that controls how software tasks are mapped to the processing nodes, and how this mapping should change in response to possible node failures. In this paper we present a model-based approach and a tool for automatic generation of reconfiguration graphs. Based on the software and hardware models, we traverse the graph of all possible failure situations. For every node of this graph we solve a combinatorial optimization problem of mapping tasks to processing nodes either with an SMT solver or using a genetic algorithm. The resulting reconfiguration graph can then be translated into the configuration files that are deployed on the target system, eliminating the need for tedious and error-prone manual configuration design.

Owing to the low-gravity conditions in space, space-borne laboratories enable experiments with extended free-fall times. Because Bose-Einstein condensates have an extremely low expansion energy, space-borne atom interferometers based on Bose-Einstein condensation have the potential to have much greater sensitivity to inertial forces than do similar ground-based interferometers. On 23 January 2017, as part of the sounding-rocket mission MAIUS-1, we created Bose-Einstein condensates in space and conducted 110 experiments central to matter-wave interferometry, including laser cooling and trapping of atoms in the presence of the large accelerations experienced during launch. Here we report on experiments conducted during the six minutes of in-space flight in which we studied the phase transition from a thermal ensemble to a Bose-Einstein condensate and the collective dynamics of the resulting condensate. Our results provide insights into conducting cold-atom experiments in space, such as precision interferometry, and pave the way to miniaturizing cold-atom and photon-based quantum information concepts for satellite-based implementation. In addition, space-borne Bose-Einstein condensation opens up the possibility of quantum gas experiments in low-gravity conditions1,2.

The project Autonomous Terrain-based Optical Navigation (ATON) at the German Aerospace Center (DLR) is developing an optical navigation system for future landing missions on celestial bodies such as the moon or asteroids. Image data obtained by optical sensors can be used for autonomous determination of the spacecraft’s position and attitude. Camera-in-the-loop experiments in the Testbed for Robotic Optical Navigation (TRON) laboratory and flight campaigns with unmanned aerial vehicle (UAV) are performed to gather flight data for further development and to test the system in a closed-loop scenario. The software modules are executed in the C++ Tasking Framework that provides the means to concurrently run the modules in separated tasks, send messages between tasks, and schedule task execution based on events. Since the project is developed in collaboration with several institutes in different domains at DLR, clearly defined and well-documented interfaces are necessary. Preventing misconceptions caused by differences between various development philosophies and standards turned out to be challenging. After the first development cycles with manual Interface Control Documents (ICD) and manual implementation of the complex interactions between modules, we switched to a model-based approach. The ATON model covers a graphical description of the modules, their parameters and communication patterns. Type and consistency checks on this formal level help to reduce errors in the system. The model enables the generation of interfaces and unified data types as well as their documentation. Furthermore, the C++ code for the exchange of data between the modules and the scheduling of the software tasks is created automatically. With this approach, changing the data flow in the system or adding additional components (e.g., a second camera) have become trivial.

Since 2010 the German Aerospace Center is working on the project Autonomous Terrain-based Optical Navigation (ATON). Its objective is the development of technologies which allow autonomous navigation of spacecraft in orbit around and during landing on celestial bodies like the Moon, planets, asteroids and comets. The project developed different image processing techniques and optical navigation methods as well as sensor data fusion. The setup—which is applicable to many exploration missions—consists of an inertial measurement unit, a laser altimeter, a star tracker and one or multiple navigation cameras. In the past years, several milestones have been achieved. It started with the setup of a simulation environment including the detailed simulation of camera images. This was continued by hardware-in-the-loop tests in the Testbed for Robotic Optical Navigation (TRON) where images were generated by real cameras in a simulated downscaled lunar landing scene. Data were recorded in helicopter flight tests and post-processed in real-time to increase maturity of the algorithms and to optimize the software. Recently, two more milestones have been achieved. In late 2016, the whole navigation system setup was flying on an unmanned helicopter while processing all sensor information onboard in real time. For the latest milestone the navigation system was tested in closed-loop on the unmanned helicopter. For that purpose the ATON navigation system provided the navigation state for the guidance and control of the unmanned helicopter replacing the GPS-based standard navigation system. The paper will give an introduction to the ATON project and its concept. The methods and algorithms of ATON are briefly described. The flight test results of the latest two milestones are presented and discussed.

Developing software for large and complex experiments is a challenging task. It must incorporate many requirements from different domains, all with their own conceptions about the overall systems. An additional level of complexity is added if the experiment is conducted autonomously during a sounding rocket flight. Without a proper software architecture and development techniques, achieving and maintaining a high code quality is a very cumbersome task. This paper describes the architecture and the model-driven development approach we used to implement the control software of the experiments in the MAIUS-1 mission (matter-wave interferometry in microgravity). In this mission, the software had to handle around 150 experiments in six minutes autonomously and adapt to changes in the control flow according to real-time data from the experiment. The MAIUS-1 mission was the first mission to create Bose-Einstein condensates in space and conduct other experiments with ultra-cold gases on a sounding rocket. Besides the scientific goals in the area of quantum-optics, other important objectives of the mission were the miniaturization and further development of laser systems, vacuum components, optical sensors, and other related technologies. To fulfil these goals, new experimental hardware has been created which had to be integrated and tested with the software of the experiment computer. The custom-made hardware and the considerable number of domains involved brought up many challenges for the software engineering. To face all these challenges of developing software with this high complexity, we chose to follow a model-driven software development approach. Several domain-specific languages (DSLs) accompanied with specialized tools were created to allow the physicists and electronic engineers to describe system components and the experiments in a domain-specific way. These descriptions were then automatically transformed in C++ code for the flight software. This way we could actively incorporate all the domains involved in conducting the experiment directly in building the flight software without compromising the software quality. We created a versatile software platform not only for the MAIUS-1 mission but also for upcoming missions with similar experiments and hardware. With our approach we were able to generate around 84% of the source code for the final flight software from the domain-specific models. Besides the improvement of the development process, the code generation made a significant contribution to the overall software quality as almost all manual coding of error-prone boilerplate code could be mitigated.