TU Delft AI Satellite

Bachelor Thesis (2022)
Author(s)

D. Canosa Ybarra (TU Delft - Aerospace Engineering)

K.I. Janisch (TU Delft - Aerospace Engineering)

N. Kalis (TU Delft - Aerospace Engineering)

D. Lentschig (TU Delft - Aerospace Engineering)

A. Lopez Rivera (TU Delft - Aerospace Engineering)

M. Manieri (TU Delft - Aerospace Engineering)

Kim Regnery

T.L. van der Wal (TU Delft - Aerospace Engineering)

Contributor(s)

Joris Melkert – Mentor (TU Delft - Flight Performance and Propulsion)

A. Menicucci – Mentor (TU Delft - Space Systems Egineering)

G. Gonzalez Saiz – Mentor (TU Delft - Aerodynamics)

O. Yuksel – Mentor (TU Delft - Group Çaglar)

Lorenza Mottinelli – Mentor (TU Delft - Aerospace Engineering)

Faculty
Aerospace Engineering
More Info
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Publication Year
2022
Language
English
Graduation Date
23-06-2022
Awarding Institution
Delft University of Technology
Project
['AE3200 - Design Synthesis Exercise']
Programme
['Aerospace Engineering']
Faculty
Aerospace Engineering
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Abstract

Solutions for reducing greenhouse gas emissions are paramount under the current environmental circumstances. With methane and carbon dioxide being the most critical emission gasses, SigmaSat set out to find a way to reduce these emissions and simultaneously fulfill its scientific mission. While executing the scientific mission of designing a small satellite mission to demonstrate the latest advances in artificial intelligence, SigmaSat managed to devise a design that allows players in the energy production industry (such as refineries) to drastically reduce their methane and CO2 emissions.

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