andrea_ferrero
Spaceflight 🚀🇩🇪 #ATMOS has few competitors, of which #VardaSpace and #InversionSpace both apply parachutes 🪂 for the final descent of their return capsules. #Phoenix doesn’t require parachutes due to its large surface area and low mass, allowing its shape to essentially act as a parachute. The ballistic coefficient is lower than #NASA’s #LOFTID demonstrator. The next Phoenix to launch will carry "green #propulsion; ethane and nitrous oxide” https://www.nasaspaceflight.com/2025/06/atmos-space-cargo
From Earth to #Mars lasts about 200 days. To safely go from those speeds down to zero in that short amount of time requires “slamming on the brakes”. Successful #aerobraking depends upon precise navigation, knowledge of weather, and a solid understanding of the forces the craft can withstand. https://science.nasa.gov/planetary-science/programs/mars-exploration/mission-timeline
🇮🇳 #Mangalyaan2 will perform a direct entry, meaning the descent stage will plunge straight into the atmosphere without first orbiting the planet. The landing sequence will begin with #aerobraking to slow the spacecraft using atmospheric drag. At an altitude of approximately 1.3 kilometres above the Martian surface, powered descent engines will ignite 🔥 https://timesofindia.indiatimes.com/science/how-mangalyaan-2-will-land-on-mars-isro-chief-reveals-plan/articleshow/120306889.cms
For a trip to #Mars 🔴, decreasing travel time by 10% necessitates twice as much fuel, while cutting travel time in half requires ten times as much. May prove worthwhile when considering factors such as decreased exposure time to #radiation ☢️ for crewed 👩🚀 missions. Extra speed must be lost at Mars. Many Mars missions do this, taking about 6 6️⃣ to 7 months for transit to the Red Planet. https://marspedia.org/Hohmann_transfer#Type-I_and_Type-II_Trajectories
#AMAT allows the user to simulate #atmospheric entry trajectories, compute deceleration and heating🌡️loads, compute aerocapture entry corridors and simulate aerocapture trajectories. AMAT supports analysis for all #atmosphere-bearing destinations in the #SolarSystem: #Venus, #Earth, #Mars, #Jupiter, #Saturn, #Titan, #Uranus, and #Neptune https://amat.readthedocs.io/en/master
Parachute 🪂 is not the only means for descent, as high-mass class vehicles are emerging for human 👩🚀 missions. Shallow entry flight-path angles are preferred in order to achieve a lower terminal velocity to ensure a safe descent phase. Retro-propulsion could be activated at Mach 2 and above https://www.intechopen.com/chapters/72944#
Aerocapture, Aerobraking, and Entry for Robotic and Human Mars Missions
This chapter provides an overview of the aeroassist technologies and performances for Mars missions. We review the current state-of-the-art aeroassist technologies for Mars explorations, including aerocapture, aerobraking, and entry. Then we present a parametric analysis considering key design parameters such as interplanetary trajectory and vehicle design parameters (lift-to-drag ratio, ballistic coefficient, peak g-load, peak heat rate, and total heat load) for aerocapture, aerobraking, and entry. A new perspective on a rapid aerobraking concept will be provided. The analysis will include first-order estimates for thermal loading, thermal protection systems material selection, and vehicle design. Results and discussion focus on both robotic missions and human missions as landed assets and orbiters.
It makes sense to use the Martian #atmosphere to help with deceleration and save on propellant. https://www.youtube.com/watch?v=5seefpjMQJI This method has been tested and validated on Earth, using #SpaceX #Falcon9 first stages in the high atmosphere to simulate #Martian conditions https://marspedia.org/Landing_on_Mars#Powered_landing
Vehicle Landing
As the #spacecraft approaches Mars 🔴, it will need to perform a capture burn 🔥 to slow down and be captured by Mars' gravity. This requires a delta-v of about 0.7 to 1.3 km/s to enter Mars' orbit or to land on the planet's surface. #Starship 🚀 will enter #Mars’ atmosphere at 7.7 km/sec and decelerate #aerodynamically https://www.uc.edu/content/dam/refresh/cont-ed-62/olli/fall-23-class-handouts/SpaceX%208%20%20Mars%20%20Vision%20Summary.pdf
By Giusy Falcone Dec 2021 https://gfalcon2.web.illinois.edu
With a 6 m/s increase in the Delta-V budget, the deep reinforcement learning approach shortened the #aerobraking time by 68.3% 📉. The DRL algorithm does not encounter any thermal violations over 40 episodes compared to the 2.8 average thermal violations experienced by the state-of-the-art heuristic https://arc.aiaa.org/doi/10.2514/6.2022-2497