The propulsion systems represent a significant part of launch system costs. It is necessary to mature new or optimised low cost effective, high performance and green propulsion concepts, technologies and propellants for high thrust engines

– Low cost propulsion
– Throttability
– Reduced number of parts with extensive application of Additive manufacturing, or new composite technologies

– Maintenance/overhaul

– Associated fluidics

– Contribution to the overarching objective of launch cost/price reduction by 50% by 2030
– Innovation acceleration of enabling technologies
– Identification of mature technologies at TRL 3-4 for cost-reduction possibilities in the current European launchers
– Matured technologies up to TRL 5-6 by 2023/24, prototyping and on ground tests at engine subsystem and system level by 2025/26
– Cost reduction investigation and demonstration

Introduction

The actions under this topic are expected to exploit “extreme data”: (defined as data that exhibits one or more of the following characteristics, to an extent that makes current technologies fail: increasing volume, speed, variety; complexity/diversity/multilinguality of data; the dispersed data sources; sparse/missing/insufficient data/extreme variations in values) to push the frontiers of analytics, prediction, simulation and visualisation to provide extremely precise, timely and useful results from data and knowledge, to support (human or automated) decision-making, saving lives or otherwise providing great positive impact (economic, societal, environmental) compared to traditional methods of decision making.

Scope

Integrity and ethical aspects of the outcomes should be in line with the principles of responsible/trustworthy AI. The use of European data sources (such as Copernicus, Galileo/EGNOS for satellite data) is encouraged in the use cases, where appropriate. Analytics should be transparent, trustworthy, flexible, fit for the purpose and user needs, intuitive and (when necessary) provided as efficient and scalable “Analytics-as-a-Service”, including, where appropriate, federated analytics on distributed/decentralized data. Prediction should be extremely precise and/or span over longer time period and/or account for uncertainty factors. Simulation should allow precise replication and modelling of the real phenomenon or system (generating accurate synthetic data, when appropriate), with minimal differences and/or minimize the footprint/cost of the simulation model while generating useful data (considering context), exploiting augmented reality when appropriate. Actions should consider quality standards and assessment criteria for data generated by simulation. Visualisation should be interactive (and facilitate human interaction and collaboration), intuitive, accessible and allow people (with different needs, interests and backgrounds) to understand complex phenomena by smart selection of parameters, anticipation of user needs/interest and by novel ways of combining visual and non-visual elements and/or augmented reality.

Objectives

Improving automated ways for extracting meaning and providing insights from data
extremely fast and/or accurately in order to optimize decision making (ranging from crisis/emergency management to predictive maintenance) or action planning, as well as demonstrating how these improvements can have great positive impacts for society, people, economy, or the environment

Intro

Land use and management has a key role to play in Europe in terms of boosting carbon storage, producing biomass for the bioeconomy, reducing urban sprawl and attaining the objective of climate neutrality by 2050 while ensuring food and nutrition security, biodiversity commitments and well-being in general. There are however substantial knowledge gaps regarding, in particular, the understanding of the impacts of farming / forestry practices at various scales, from local to global, and the capacity to model these impacts (economic and environmental).

Scope

Analysis of land use dynamics and trends between arable land, permanent grassland, land abandonment / marginal lands, forest areas, for which quantifications and an identification of drivers and impacts should be done in an integrated manner.

Objective

– Land use dynamics and explore the effects of policy measures that can influence such dynamics, in particular agricultural, land use and climate policies.
– Focus on agriculture and forest land use/cover extending to interactions of the former with other main land uses/covers and drivers
– Simulations and projections ranging from medium-term to long-term policy scenarios covering the whole of the EU and its Member States and possibly Associated Countries.

The global economic interest in deep-sea mineral resources has been growing and so are the concerns with the negative impacts on the deep sea ecosystems if mining activities start. Before any deep-sea mining activities start, the environmental impacts, and how to mitigate them, need to be well understood

– Identify all the bio-chemical-physical parameters to be monitored at the bottom of the sea, along the water column and at the surface
– Identify all technical requirements needed for a real time monitoring of all parameters at the bottom, along the water column and surface, including the use of satellite data (Global Navigation Satellite System and Copernicus’ satellite constellation) and to make it continuously available for remote access
– Identify existing technological solutions and develop new ones to fulfil the technical requirements
– Design and develop the architecture of the system in view of incorporating the monitoring parameters, the technical requirements and the legal constrains
– Develop a trial version of the system and test it

– Develop technologies and systems to continuously monitor environmental impacts and

mitigation methods of deep sea exploration and future mining

– Develop multi-scale systems to identify gaps on the relevant available environmental

data needed to develop statistically robust baselines that take into account the three-

dimensional and temporal natural variability of the marine environment

– Provide technological and systemic solutions for forecasting potential environmental

impacts of using the developed monitoring and mitigation methods