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During its four-years mission, ARIEL will observe several hundreds of exoplanets ranging from Jupiter- and Neptune-size down to super-Earth and Earth-size with its 1 meter-class telescope.3 The analysis of spectra and photometric data will allow to extract the chemical fingerprints of gases and condensates in the planets atmospheres, including the elemental composition for the most favorable targets. It will also enable the study of thermal and scattering properties of the atmosphere as the planet orbits around its parent star.
The practical implementation in real large-scale projects is not uniform across fields. In space science missions, the usage has been limited to subsystems or sample projects with modeling being performed 'a-posteriori' in many instances. The main hurdle for the introduction of MBSE practices in new projects is still the difficulty to demonstrate their added value to a project and whether their benefit is commensurate with the level of effort required to put them in place.
In this paper we present the implemented Euclid system modeling activities, and an analysis of the benefits and limitations identified to support in particular requirement break-down and allocation, and verification planning at mission level.
Performance requirements on spacecraft, telescope assembly, scientific instruments and the ground data-processing have been carefully budgeted to meet the demanding top level science requirements. As part of the mission development, the verification of scientific performances needs mission-level end-to-end analyses in which the Euclid systems are modeled from as-designed to final as-built flight configurations. We present the plan to carry out end-to-end analysis coordinated by the ESA project team with the collaboration of the Euclid Consortium. The plan includes the definition of key performance parameters and their process of verification, the input and output identification and the management of applicable mission configurations in the parameter database.
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