Bodo Reimann

CALLISTO is a collaborative project between JAXA, CNES, and DLR, focused on developing and operating a scaled reusable vertical-takeoff vertical-landing rocket stage demonstrator. This initiative is a crucial step for advancing reusable launch vehicle (RLV) technology in Europe and Japan. Significant strides have been made during the recently completed phase C of the project, particularly in aerodynamic modeling, guidance, navigation, and control design, landing dynamics, and flight domain definitions. These advancements facilitate the development of future operational vehicles and provide insights applicable to other RLV projects. This paper provides an update on the design and development status of the CALLISTO vehicle. It outlines the program objectives, focusing on mission design, vehicle life cycle, and their distinctions from legacy expendable launch vehicles in Europe and Japan. Details of the flight test plan, including in-flight experimentation, are elucidated, demonstrating incremental progress toward acquiring key technology and preparing for high-energy missions. Furthermore, the paper offers an overview of the CALLISTO vehicle’s development status, highlighting key architectural features such as load-carrying structures, avionics, rocket propulsion system, flight control systems, and approach and landing system. It underscores the milestones achieved over the past years and the progress toward the first flights. With a flight test campaign to be performed at Europe’s Spaceport in French Guiana, the CALLISTO project signifies a crucial step toward enhancing launch system affordability, competitiveness, versatility, and sustainability. This collaboration among three space organizations highlights the importance of shared expertise in advancing RLV technology and preparing for the next generation of launch vehicles.

Defining aerodynamic databases is an important yet very complex and labor-intensive task during the design of new aerospace vehicles. This is particularly true for reusable launch vehicles, as observed during the development of CALLISTO, a demonstrator for a vertical-takeoff–vertical-landing first stage that is jointly developed, manufactured, and tested by German Aerospace Center (DLR), Japan Aerospace Exploration Agency (JAXA), and French National Centre for Space Studies (CNES). In this paper, we present an inference-based methodology to define various types of Bayesian models exemplarily for a subset of CALLISTO’s Aerodynamic Database to assess their usability and prediction qualities. First, a short introduction to the underlying aerodynamic dataset will be given, which has been aggregated from various computational fluid dynamics simulations and wind tunnel test campaigns. Then, the different Bayesian models will be defined and their inference results compared against each other, according to common error metrics. It will be shown that, within the limits and assumptions of this study, several types of Bayesian models provide better accuracy in the prediction of uncertain aerodynamic coefficients compared to classical expert-fitted models for the given CALLISTO dataset. Generally, it can be concluded that Bayesian models provide a promising approach for the definition of aerodynamic databases and could also find many potential applications in other engineering domains.

JAXA, CNES and DLR have decided to join their force to develop and fly a scaled reusable VTVL rocket stage called CALLISTO (Cooperative Action Leading to Launcher Innovation in Stage Toss - back Operations). This vehicle will pave the way for future reusable launch vehicles. One of its main goals is to demonstrate the mastering of key techniques and technologies that will be needed later by operational reusable launch vehicles. Indeed in the frame of CALLISTO numerous challenging technologies are being matured for the specific case of reusable launch vehicles. The challenges of a selection of key technologies developed for CALLISTO are discussed and the solutions retained for CALLISTO are presented.