Space Systems Finland (Finland)

Abstract To study the evolution and propagation of Coronal Mass Ejections (CMEs), the advanced magnetized flux rope CME model, Flux Rope in 3D (FRi3D), has been integrated into the European Heliospheric Forecasting Information Asset (EUHFORIA). Recent updates have been addressing the computational efficiency and numerical stability issues of this CME model. In this work, the latest improvements to the FRi3D model are represented, including optimizations of the integral calculations in the ai.fri3d Python package, an updated CME leg disconnection method, and the introduction of a new datacube injection methodology for time‐efficient FRi3D simulations. Within the datacube injection method, the input values of FRi3D at the inner boundary of EUHFORIA are precomputed, eliminating the need to calculate the FRi3D CME model during the solar wind simulation with superimposed CMEs. The datacube injection method is tested by modeling the CME event of 12 July 2012, and by conducting ensemble runs for this event. The updates to the FRi3D Python package reduced the computation time to , and the datacube methodology achieved a computational time reduction of up to compared to previous FRi3D versions. Numerical stability was significantly improved, and ensemble simulations demonstrated robust ensemble spreads for the thermodynamic and magnetic time profiles on Earth. These updates enhance the efficiency, stability, and accuracy of the FRi3D model, making it highly suitable for predicting both the CME arrival time, magnetic field strength, and velocity. As a result, the advancements contribute significantly to the future operational space weather forecasting capabilities of the FRi3D CME model.

Abstract Coronal mass ejections (CMEs) and solar energetic particles (SEPs) are two phenomena that can cause severe space weather effects throughout the heliosphere. The evolution of CMEs, especially in terms of their magnetic structure, and the configuration of the interplanetary magnetic field (IMF) that influences the transport of SEPs are currently areas of active research. These two aspects are not necessarily independent of each other, especially during solar maximum when multiple eruptive events can occur close in time. Accordingly, we present the analysis of a CME that erupted on May 11, 2012 (SOL2012‐05‐11) and an SEP event following an eruption that took place on May 17, 2012 (SOL2012‐05‐17). After observing the May 11 CME using remote‐sensing data from three viewpoints, we evaluate its propagation through interplanetary space using several models. Then, we analyze in‐situ measurements from five predicted impact locations (Venus, Earth, the Spitzer Space Telescope, the Mars Science Laboratory en route to Mars, and Mars) in order to search for CME signatures. We find that all in‐situ locations detect signatures of an SEP event, which we trace back to the May 17 eruption. These findings suggest that the May 11 CME provided a direct magnetic connectivity for the efficient transport of SEPs. We discuss the space weather implications of CME evolution, regarding in particular its magnetic structure, and CME‐driven IMF preconditioning that facilitates SEP transport. Finally, this work remarks the importance of using data from multiple spacecraft, even those that do not include space weather research as their primary objective.

Context.We assess statistical inversion of asteroid rotation periods, pole orientations, shapes, and phase curve parameters from photometric lightcurve observations, here sparse data from the ESAGaiaspace mission (Data Release 2) or dense and sparse data from ground-based observing programs.Aims.Assuming general convex shapes, we develop inverse methods for characterizing the Bayesian a posteriori probability density of the parameters (unknowns). We consider both random and systematic uncertainties (errors) in the observations, and assign weights to the observations with the help of Bayesian a priori probability densities.Methods.For general convex shapes comprising large numbers of parameters, we developed a Markov-chain Monte Carlo sampler (MCMC) with a novel proposal probability density function based on the simulation of virtual observations giving rise to virtual least-squares solutions. We utilized these least-squares solutions to construct a proposal probability density for MCMC sampling. For inverse methods involving triaxial ellipsoids, we update the uncertainty model for the observations.Results.We demonstrate the utilization of the inverse methods for three asteroids withGaiaphotometry from Data Release 2: (21) Lutetia, (26) Proserpina, and (585) Bilkis. First, we validated the convex inverse methods using the combined ground-based andGaiadata for Lutetia, arriving at rotation and shape models in agreement with those derived with the help of Rosetta space mission data. Second, we applied the convex inverse methods to Proserpina and Bilkis, illustrating the potential of theGaiaphotometry for setting constraints on asteroid light scattering as a function of the phase angle (the Sun-object-observer angle). Third, with the help of triaxial ellipsoid inversion as applied toGaiaphotometry only, we provide additional proof that the absoluteGaiaphotometry alone can yield meaningful photometric slope parameters. Fourth, for (585) Bilkis, we report, with 1-σuncertainties, a refined rotation period of (8.5750559 ± 0.0000026) h, pole longitude of 320.6° ± 1.2°, pole latitude of − 25.6° ± 1.7°, and the first shape model and its uncertainties from convex inversion.Conclusions.We conclude that the inverse methods provide realistic uncertainty estimators for the lightcurve inversion problem and that theGaiaphotometry can provide an asteroid taxonomy based on the phase curves.

Hierarchical block diagrams (HBDs) are at the heart of embedded system design tools, including Simulink. Numerous translations exist from HBDs into languages with formal semantics, amenable to formal verification. However, none of these translations has been proven correct, to our knowledge.

The selection of an effective software development process is a crucial element in any space SW project. The waterfall software life cycle model as is can not provide an adequate solution to their relevant complexity and central role in the elicitation of spacecraft system-level requirements. Its main assumption of moving into a phase only when the preceding one is mature and complete is actually not attainable. In this paper, a tailoring of the waterfall model (named “Robust Feedback Software Life-cycle Model”) is presented. The proposed process sorts out these issues by combining a SW waterfall model with a SW incremental approach. It is currently used in satellite SW projects at OHB System AG. SW product metrics gathered from real SW space projects bear out its effectiveness and robustness against SW requirement evolution.

The use of formal methods has been recognized in different domains as a potential means for early validation and verification. However, correctly specifying formal properties is difficult due to the ambiguity of the typical textual requirements and the complexity of the formal languages. To address this, we define the Catalogue of System and Software Properties. Starting from a taxonomy of requirements extracted from space standards, we derive a list of design attributes divided per requirement type. We map these design attributes to AADL system architectures and properties, for which we define formal semantics and properties. We exemplify the approach using AADL models taken from the space domain.

Modes are widely used to structure the behaviour of control systems. For many such systems, derivation and verification of a mode logic is challenging due to a large number of modes and complex mode transitions. In this paper we propose an approach to deriving, formalising and verifying consistency of a mode logic for fault tolerant control systems. We demonstrate how to use Failure Modes and Effects Analysis (FMEA) to systematically derive the fault tolerance part of the mode logic. To tackle the problem of mode consistency, we propose a formalisation of the mode logic and mode consistency conditions for layered systems with reconfigurable components. We use our formalisation to develop and verify a mode-rich system by refinement in Event-B.