The concept of using the vibration transmitted through the structure of space systems whilst they are in flight for monitoring purposes is proposed and analysed.The performed patent review seems to indicate that this technique is not currently used despite being, in principle, a good way to obtain valuable knowledge about the spacecraft’s condition. Potential sources of vibration were listed and some of them were down-selected via a trade-off analysis for implementation in a numerical model of a CubeSat structure. Models were proposed for the sources chosen and implemented in the Ansys Workbench software, along with a simplified structure designed to be representative of a generic picosatellite mission.The results confirmed very different amplitude and frequency ranges for the sources of interest, which would make it difficult to monitor them with one type of sensor.Basic system requirements for accelerometer operating under space conditions were derived and commercial sources were identified as already having the technologies needed.The conclusion was a positive evaluation of the overall concept, although revising negatively the initial expectations for its performance due to the diversity encountered in the sources.

This master's thesis was conducted in collaboration with ECAPS, where a conjugate heat transfer analysis on their High Performance Green Propulsion (HPGP) 22N thruster was done. ECAPS is a Swedish propulsion company specializing in green propulsion. They develop thrusters for spacecraft orbit and attitude control, utilizing the propellant LMP-103S. LMP-103S is a non-toxic propellant, in contrast to the hazardous monopropellant hydrazine commonly used in thrusters. A previous master's thesis modified the original design of the 22N thruster to make it compatible with additive manufacturing. Some concerns about heat transfer in the feed tube surfaced with the new design as it showed elevated temperatures. The feed tube is a component that works as a pathway where liquid propellant is transported from the flow control assembly to the reactor chamber assembly, where combustion begins. The goal of this master's thesis was to determine the temperatures the liquid propellant reached, and to assess if the liquid propellant was at risk of vaporization in the feed tube before reaching the reactor chamber assembly. Since the feed tube is a limited volume, vaporization of the liquid propellant in the feed tube could have devastating consequences of the structure. Ansys Fluent was used as the Computational Fluid Dynamics (CFD) software, along with the Computer Aided Design (CAD) software NX and Matlab for data handling.  Four extreme case scenarios were determined to be simulated, varying the liquid propellant inlet temperatures from highest to lowest operable temperatures, as well as the thruster's highest and lowest operable inlet pressures. A literature study on conjugate heat transfer in CFD was done, along with determination and calculations of necessary parameters for a correct simulation setup, and a grid independence study. Both steady-state and transient simulations were conducted. The results indicate that when the thruster operates with the highest inlet pressure, there is a risk of vaporization, but critical consequences are less likely to have time to develop. However, for the cases where the thruster operates with its lowest inlet pressure, a significant risk of vaporization in the feed tube is present. The simulated temperature results suggest that the liquid propellant will rapidly vaporize, where increased pressure at the feed tube outlet will be building up as a result of the expanding vapor, leading to a feed tube failure for the vapor to escape through. Therefore, the new design change of the feed tube will most likely not work for the thruster to be able to work under all necessary conditions. New modifications to the feed tube are necessary, or alternatively, the original design of the feed tube could be added afterward to the 3D-printed structure, though this may result in the loss of some benefits of manufacturing the entire structure in one piece.

Low Reynolds number airfoil analysis has become increasingly significant as urban air mobility vehicles and unmanned aerial vehicles surge in popularity. The Green Raven project at KTH Aero aims to use reflex airfoils where little data is available beyond classical analysis. Viscous formulations of the panel method and computational fluid dynamics (CFD) have been used to simulate lift, drag and moments for the MH61 and MH104 airfoils at different angles of attack (AOAs). XFOIL and CFD turbulence models such as Spalart-Allmaras (SA), k-w Shear Stress Transport (SST) with and without damping coefficients were used. The strengths and limitations of each model were used to justify results. Due to clear computational advantages, XFOIL produced adequate results and is tailored toward use in initial design stages where repeated measurements are crucial. The SA turbulence stood out as the model produced accurate results in a reasonable time. The abundance of published CFD material comparing different turbulence models increased the credibility of the results. The two airfoils had similar lift and drag characteristics at AOAs of 0-6 deg while the MH104 was superior near stall. However, due to the lack of experimental data of the airfoils no particular model could be commended or verified.

The oil circuit of a jet engine is required to lubricate and cool mechanical parts. The oil is pumped from the oil tank and flows through heat exchangers. Then it is injected on the bearings for lubrication and cooling, before being scavenged at the bottom of the sumps and finally flows back to the oil tank. During flight, the volume of oil inside the tank fluctuates depending on many parameters like the engine rotation speed and the oil temperature to name but a few. The flow inside the sumps is diphasic with oil and air mixing up. The physical phenomena taking place in the oil circuit are complex and understanding them is essential to size an oil circuit for a new engine design. Mass is a critical factor in aviation and being able to design accordingly an oil circuit is a valuable asset.This work focuses on improving a 1D model predicting the evolution of the oil level in the tank. The model relies on the geometry of the engine, the architecture of the oil circuit and real flight data provided by the airline companies. This data contains flight parameters such as engine rotation speed, oil temperature and pressure. The prediction is then compared with the real volume of oil in the tank measured during the flight. The model is compared to experimental data to access its accuracy. Finally, the model is adapted to three different engines produces by Safran to test its robustness to geometry changes. / Oljekrets behövs i en jetmotor i syfte att smörja och kyla dess inre mekaniska komponenter. Oljan som pumpas från reservoaren passerar igenom värmeväxlare. Oljan injiceras sedan på kullagren som kräver kontinuerlig smörjning och kylning innan den når sitt slutförlopp i botten av tråget där den filtreras och dirigeras tillbaka till reservoaren. Oljevolymen i reservoaren varierar under färd, och är beroende av parametrar som motorns rotationshastighet, oljetemperatur och med mera. Flödet i tråget är tvåfasisk där olja och luft blandas samman. De fysiska fenomenen som inträffar i oljekretsen är komplexa och förståelse för dessa är essentiell för att kunna dimensionera kretsen för en ny motordesign. Då massa är en viktig aspekt inom flygindustrin så är det ideellt att kunna dimensionera och designa en oljekrets utefter ett givet masskriterium.Detta arbete fokuserar på att förbättra en endimensionell modell som predicerar den periodiska variansen i oljenivån i reservoaren. Modellen beror av motorgeometrin, oljekretsens struktur och realtidsflygdata givna från fåtals flygbolag. Dessa data innehåller flygparametrar såsom motorns rotationshastighet, oljetemperatur och oljetryck. De predicerade beteenden jämfördes sedan med den faktiska oljevolymen i reservoaren uppmätt under färd. Som verifikation och överensstämmelse jämfördes modellen med experimentella data. Slutligen är denna modell anpassad efter tre motormodeller från Safran i syfte att testa dess robusthet med avseende på geometriska variationer.

Maintenance and diagnostics play a vital role in the aviation sector. This is especially true for the engines, being one of the most vital components. Lack of maintenance, or poor knowledge of the current health status of the engines, may lead to unforeseen disruptions and possibly catastrophic effects. To keep track of the health status, and thereby supporting maintenance planning, model based diagnostics is a key factor.  In the work going into this thesis, various aspects of model based gas turbine diagnostics, focused on aero engines, are covered. First, the importance of knowing what health parameters may be derived from a set of measurements is addressed. The selected combination is herein denoted as a matching scheme. A framework is proposed where the most suitable matching scheme is selected for a numerically robust diagnostic system. If a sensor malfunction is detected, the system automatically adapts. The second subject is a system for detecting a burn-through of an afterburner inner liner. This kind of burn-through event has a very small impact on available on-board measurements, making it difficult to detect numerically. A method is proposed performing back-to-back testing after each engine start. The method has shown potential to detect major burn-through events under the preconditions, regarding data collection time and frequency. Increasing these will allow for more accurate estimations. The third subject covers the importance of knowing the airplane installation effects. These are generally the intake pressure recovery, bleed and shaft power extraction. Just like inaccurate measurements affect diagnostic results, so does erroneous installation effects. A method for estimating said effects in the presence of gradual degradation has been proposed by using neural networks. By retraining the networks throughout the degradation process, the estimation errors is reduced, ensuring relevant estimations even at severe degradations. Finally, an issue related to the general lack of on-board measurements for diagnostics is addressed. Due to lack of measurements, the diagnostic model tend to be underdetermined. A least square solver working without a priori information has been implemented and evaluated. Results from the solver is very much dependent on available instrumentation. In well instrumented components, such as the compressors, good diagnostic accuracy was achieved while the turbine health estimations suffer from smeared out results due to poor instrumentation.

For complex satellite missions that rely on agile and high-precision manoeuvres, the low-friction aspect of the space environment is a critical component in understanding the attitude control dynamics of the spacecraft. The Kinesthetic Node and Autonomous Table-Top Emulator (KNATTE) is a three-degree-of-freedom frictionless vehicle that serves as the foundation of a multipurpose platform for real-time spacecraft hardware-in-the-loop experiments, and allows emulation of these conditions in two dimensions with the purpose of validating various guidance, navigation, and control algorithms. The data acquisition of the vehicle depends on a computer vision system (CVS) that yields position and attitude data, but also suffers from unpredictable blackout events. To complement such measurements, KNATTE incorporates an inertial measurement unit (IMU) that yields accelerometer, gyroscope, and magnetometer data. This study describes a multisensor data fusion approach to obtain accurate attitude information by combining the measurements from the CVS and the IMU using nonlinear Kalman filter algorithms. To do this, the data fusion algorithms are developed and tested in a Matlab/Simulink environment. After that, the algorithms are adapted to the KNATTE platform and their performance is confirmed in various conditions. Through this work, the accuracy and efficiency of the approach can be checked by numerical simulation and real-time experiments. In addition, the quality of the CVS measurements are further improved by the introduction of a neural network to the image processing pipeline of the original system.

The COmpton Spectrometer and Imager (COSI) is a space telescope that aims to study the soft gamma regime (0.2-5 MeV), capable of performing spectroscopy, imaging and polarimetry of cosmic gamma sources. COSI will use an active shield made of Bismuth Germanium Oxide (BGO), a known scintillator material, in order to reduce the instrumental background produced by primary and secondary particles. When a cosmic ray particle or gamma interacts with the active shield, they will produce scintillation photons. Thanks to the optical coupling of photomultipliers tubes (PMT) to the BGO walls, it is possible to detect these scintillation photons and remove the background events from the analysis with the Compton telescope. IRAP (Research Institute in Astrophysics and Planetology) is the organization responsible of providing the photodetector (PMT with its electronics and mechanics) design to the COSI mission. The main objective of my internship is to study the performance of the photodetector of the active shield, focusing on the development of simulations with Geant4. The first study investigates the propagation of optical photons inside a PMT, comparing an analytical method versus a Geant4 simulation. Geant4 perfectly simulates the transmission and reflection of photons. However, if some of the photons are absorbed by the materials, Geant4 starts to slightly differ. This happens because the absorption is computed with different physic processes in both models. The second study is focused on obtaining measurements from the PMTs at the laboratory. The pulse amplitude at the preamplifier level is analysed, as well as the transmission of the Si pad. The third and fourth studies are focused on the simulation, with Geant4, of the performance of a PMT optically coupled to two different scintillator materials, CsI(Tl) and BGO, respectively. The correct set-up of a simulation is always critical, especially for a space mission like COSI. Both studies aim to find the correct set-up in order to get the most precise simulation. The results are great, showing a really good correlation between the simulation and the real data. During the fifth study, I updated the photodetector engineering model, called DACS (Detector for the AntiCoincidence System), taking into consideration the new electronic board designs and the previous engineering models. The results obtained in this thesis help to understand the performance of the photodetectors that will be used on the COSI telescope, as well as to show the benefits of using a toolkit like Geant4 in projects with propagation of scintillation photons.

While the use of Artificial Intelligence (AI) has faced a sharp up-rise in popularity in ground-based industries, such as for autonomous navigation in the automotive industry and predictive maintenance in manufacturing processes, it is yet only rarely used in space industry. Hence, this thesis aims to investigate the possibilities of using AI for processing on-board Earth-orbiting satellites while in orbit. In a first step, the interests and trends of deploying AI on-board satellites are studied, followed by challenges that are hindering the progression of its development. In a second step, five potential on-board applications are selected for investigation of their overall relevance to space industry, as well as their benefits compared to traditional approaches. Out of these, the possibility of using AI for predicting the degradation of batteries is selected for further study, as it shows the highest potential. Today’s approaches for monitoring battery degradation on satellites are highly insufficient and there is a great demand for a new approach. Several AI-based methods have been proposed in literature, but only rarely for processing directly on-board. Thus, I investigate the feasibility of adopting such an algorithm for on-board use, including an evaluation of the suitability of different algorithms, as well as the choice of input parameters and training data. I find that the use of AI could highly improve various aspects of satellite performance both on a platform and a payload level, by making them more efficient, but also more capable, such as for in-orbit battery prediction on-board. However, its implementation is still heavily hampered by the lack of validation and verification standards for AI in space, along with limitations imposed by the space environment, restricting the satellite design. In the investigation of using AI for on-board battery prediction, I find that this would be a suitable application for constellation satellites in LEO, in particular for prolonging their operations beyond their planned lifetime while still being able to ensure safe decommissioning. I estimate that this would lead to a yearly minimal average saved satellite replacement cost of $ 22 million in a constellation with 500 satellites, assuming an extension of the satellite lifetime from 7 to 7.5 years when using this application. Based on references in literature, I find that using a Long Short-Term Memory (LSTM) algorithm could make the most intricate predictions, whereas a Gated Recurrent Unit (GRU) algorithm would be less processing-heavy at the cost of a loss in accuracy. Training needs to be done on ground, either on telemetry data from past, similar missions or on synthetic data from simulations. Its implementation needs to be investigated in future research, including the selection of a suitable framework, but also benchmarking for evaluating the necessary processing power and memory space.

The effect of flexible panels on a spacecraft during attitude movement may induce problems if not correctly accounted for in the control system for the spacecraft. The aim of this thesis is to find and evaluate, control algorithms that could be suitable for the Kinesthetic Node and Autonomous Table-Top Emulator (KNATTE) with two flexible mock-up solar panels during an attitude movement of 20 degrees. A simulation model of KNATTE was derived in a previous thesis where a Linear– quadratic–Gaussian (LQG) controller was also found, after a literature review the secondary controller was selected to be a Sliding mode control (SMC) and to accurately simulated the environment of KNATTE the continuous control signal would need to be converted to a pulse due to the thrusters on KNATTE either being on or off. The thesis found that the Pulse-width pulse-frequency (PWPF) modulation is necessary for both controllers to have the best performance as the Pulse-width modulation (PWM) is not able to generate a thrust output that gives a desired result. It is also found that the SMC will provide the shortest settling time for the attitude manoeuvre while also displacing the panels the least amount compared to that of the LQG controller.

The main issues discussed in this paper are related to the refinement of the on-ground casualty risk computation for the specific case of INTErnational Gamma-Ray Astrophysics Laboratory (INTEGRAL). The current approach, unable to predict the spacecraft attitude motion, assumes random tumbling motion as initial condition to simulate the fragmentation process. The wide experience in break-up analysis, acquired after years of practice with simulation, identified attitude to be one of the major drivers of uncertainty. The Space Debris Office (SDO) demanded a specific research in the field of the long-term propagation applied to the attitude motion and INTEGRAL offered the perfect test bench to conduct a preliminary study in this direction. In particular, observing whether environmental torques were able to trigger stable attitude motion, maintainable till re-entry, was considered to be the major challenge. The propagation of coupled orbital􀀀attitude motion for a random attitude configuration represents only one side of the coin. Indeed, chaos theory analysis constituted the other. The use of the Poincaré map in a non-canonical way managed to bring evidence for constrained motion in the angular rate motion of INTEGRAL, under gravity perturbations. Such results allowed to conduct further investigation on the overall attitude motion and estimate that the attitude configuration at the re-entry appears as precession about the maximum axis of inertia, in the majority of the cases. / De aspekter som behandlas i detta examensarbete är relaterade till skaderisken när rymdskrot som passerar atmosfären och landar på marken. Detta illustreras för en specifik satellit: INTEGRAL. Den nuvarande strategin som används i rymdindustrin är oförmögen att tillräckligt noggrant prediktera satellitens at-titydförändring vid atmosfärsinträdet och antar därför en stokastisk tumlande rörelse som initialvillkor för en analys av sönderdelningen av farkosten när den passerar atmosfären. Den erfarenhet som finns i rymdindustrin kring sönderdelningssimuleringar har identifierat att attityden är den faktor som genererar störst osäkerhet i resultaten. För att bättre förstå attitydens betydelse användes INTEGRAL i den fallstudie som presenteras i denna rapport. Specifikt studerades hur externa kraftmoment från rymdmiljön kan skapa en stabil attitydrörelse, som behålls ända till farkostens inträde i atmosfären. Propageringen av den kopplade rörelsen bana-attityd för en stokastisk attitydkonfiguration representerar endast en del av denna analys, där kaosteori representerar den andra delen. Med hjälp av Poincaré-mappning har simuleringar som indikerar en begränsad vinkelhastighet för INTEGRAL-satelliten när den utsätts för gravitationsstörning. I majoriteten av de analyserade fallen representerades attityden av en precession kring den största huvudtröghetsaxeln.