TRED aims to study the fundamental phenomena governing the evaporation and combustion of droplets in the transcritical regime. These conditions can be verified in liquid rocket engines using methane and oxygen as propellants and a gas generator cycle, as envisaged in future European launchers. Despite the many studies that have been carried out to understand the impact of the transcritical transition on reactive flows, these phenomena remain unclear and need to be analysed at the level of fundamental problems such as that of the isolated droplet before they can be scaled up. It is difficult to obtain detailed experimental diagnostics under conditions of high temperature and pressure, and numerical simulation can play a key role in these studies. However, to date there are no suitable numerical approaches for fine simulation of this phenomenon. TRED will make it possible to remove this obstacle by setting up an innovative numerical approach for the study of transcritical phenomena. A solver for the simulation of compressible two-phase flows with phase change, based on a robust and consistent thermodynamic formulation, will be extended in TRED so as to be able to simulate the evaporation and combustion of drops under transcritical conditions. A major effort will be devoted to experimental validation with data available for transcritical evaporation and combustion. Finally, the solver will be used to study the combustion of oxygen drops in methane during a transcritical transition. The project will enable a PhD student and a post-doc to be hired. The results will make it possible to remove obstacles to the phenomenological nature and modelling of transcritical transitions. Following the TRED project, the numerical method could be extended to simulate scales that are more interesting for rocket engine applications, such as jets.

As the number of space missions involving surface interactions increases, so does the need to understand the behaviour of planetary surfaces. The surface properties also are crucial for human exploration, and play a key role in the evolution of planetary bodies. In terrestrial geophysics and planetary exploration, two techniques are widely used for in-situ determination of soil mechanical properties: seismic sounding, and penetration testing. However, the GRAVITE PI hypothesizes that these techniques are not directly applicable for space exploration due to implicit assumptions that become invalid in low-gravity environments, and that this has resulted in erroneous interpretations of data from multiple space missions. Whereas others use limited experimental data points, numerical simulations or untested extrapolations, GRAVITE will build a unique high-performance, low and variable gravity laboratory to extensively explore, for the first time, the complex interactions between particle size, friction and cohesion in the response of granular materials to both small and large deformations, under vacuum, and in reduced-gravity conditions. The GRAVITE facility, capable of reaching gravity levels three orders of magnitude less than Earth’s gravity (in order to simulate small body surfaces), and of finely adjusting the gravity level of each individual experiment, will bridge an existing gap in facilities and provide exceptional experimental data covering a wide range of gravity conditions. The GRAVITE data from two custom experiments will be used to test the limits of existing theories, and validate new models accounting for previously unexplored regimes. As such, GRAVITE will provide the planetary science and exploration communities with much needed models that can be used to predict and interpret the behaviour of extra-terrestrial surface materials. The results will have direct applications to current and future space missions that interact with planetary surfaces.

Air transportation is a crucial contributor to the world economy, and thus its continued growth is essential. However, environmental impact and the increase in fuel prices make sustainable aviation a challenge. To address this challenge, we propose to develop state-of-the-art computational tools for the design optimization of next-generation airliners with unprecedented fuel efficiency. We will achieve this by leveraging the expertise of the researcher on high-fidelity computational design of aircraft, together with Airbus’ vast experience in practical aircraft design, and the network of academics at ISAE. The proposed research is expected to make a lasting impact at Airbus by implementing new computational tools, and by developing design concepts for the next-generation of aircraft.

As the number of space missions involving surface interactions increases, so does the need to understand the behaviour of planetary surfaces. The surface properties also are crucial for human exploration, and play a key role in the evolution of planetary bodies. In terrestrial geophysics and planetary exploration, two techniques are widely used for in-situ determination of soil mechanical properties: seismic sounding, and penetration testing. However, the GRAVITE PI hypothesizes that these techniques are not directly applicable for space exploration due to implicit assumptions that become invalid in low-gravity environments, and that this has resulted in erroneous interpretations of data from multiple space missions. Whereas others use limited experimental data points, numerical simulations or untested extrapolations, GRAVITE will build a unique high-performance, low and variable gravity laboratory to extensively explore, for the first time, the complex interactions between particle size, friction and cohesion in the response of granular materials to both small and large deformations, under vacuum, and in reduced-gravity conditions. The GRAVITE facility, capable of reaching gravity levels three orders of magnitude less than Earth’s gravity (in order to simulate small body surfaces), and of finely adjusting the gravity level of each individual experiment, will bridge an existing gap in facilities and provide exceptional experimental data covering a wide range of gravity conditions. The GRAVITE data from two custom experiments will be used to test the limits of existing theories, and validate new models accounting for previously unexplored regimes. As such, GRAVITE will provide the planetary science and exploration communities with much needed models that can be used to predict and interpret the behaviour of extra-terrestrial surface materials. The results will have direct applications to current and future space missions that interact with planetary surfaces.

This project joins within the framework of the societal challenge 6 " Mobility and sustainable urban systems " of the generic call for projects of the ANR 2017 in conformance with the instrument of financing Young Researcher ( CJC). It is interested in the improvement of the positioning for the navigation of the urban vehicles. This project is interested in the implementation of a geolocalized map of objects and semantic events adapted to the urban navigation. The peculiarity of these works lies in the implementation of a bidirectional strong interaction between the mapping and the semantic navigation in an innovative approach of simultaneous localization and semantic mapping (SLAM) using a tight fusion between a semantic visual approach and a GNSS positioning. Thus the objective is to study the possibilities offered by the active collaboration of a classical GNSS/IMU/Visual Odometry and of a SLAM approach based only on semantic objects for the improvement of the positioning in urban areas in the context of the autonomous navigation. This project so attacks two main aspects of an accurate navigation in urban areas: the precise positioning and the scene analysis and understanding. The ambition of this project is to integrate different levels of intelligence within the framework of the autonomous navigation, namely to integrate the semantic information into the low level navigation task (only based on the geometrical structure of the scene). For that purpose, surrounding area of Machine-Learning will be integrated to detect, extract and identify static and dynamic objects of the environment more easily recognizable on the long term or according to the weather or visibility conditions. A higher level of intelligence could also be studied concerning the analysis of the inter-object's interactions to include a certain semantic of action (accidents, pedestrians' crossing etc.). The long-term ambition is to create an intelligence of the situation, allowing a safe navigation in urban context.