Examensarbeten för masterexamen

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    Chemical diversity among asymptotic giant branch stars
    (2024) Brinkmalm, Johanna; Chalmers tekniska högskola / Institutionen för rymd-, geo- och miljövetenskap; Chalmers University of Technology / Department of Space, Earth and Environment; De Beck, Elvire; De Beck, Elvire
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    Ray-tracing based atmospheric propagation simulator for a 2x2 LOS MIMO system
    (2023) Zhou, Yongan; Chalmers tekniska högskola / Institutionen för rymd-, geo- och miljövetenskap; Chalmers University of Technology / Department of Space, Earth and Environment; Eriksson, Patrick; Bao, Lei; Coldrey, Mikael
    A microwave radio system with multiple antennas is one popular technology for backhaul network deployment to reach the capability increase required for 5G and 6G. Antenna separations at transmit and receive sites should be carefully designed to ensure a proper phase relation, in this Multiple Input Multiple Output (MIMO) system with long Line-of-Sight (LoS) paths between transmitter and receiver. The LOS MIMO system may fail to operate under an extremely refractive atmosphere due to a lack of sufficient system gain which is determined by the power level and phase condition of the received sub-streams. The contribution of the thesis is to provide a simulator that can model radio’s at mospheric propagation, and it can be further used to verify real link measurement data. It is tested that the simulator has minor accuracy loss over the propagating distance concerned in this study. The simulation of electromagnetic wave propa gation is based on Forward Ray Tracing (FRT). The results demonstrate that the simulator is capable of predicting channel performance (MIMO gain, MIMO phase, etc.) for a 2-by-2 LOS MIMO system over a refractive atmosphere. The results also demonstrate that the simulator is found to be in good agreement with the lit erature and with Parabolic Equation (PE) methods, validating its potential use for predicting the outage probability for the MIMO link. This study, to the author’s best knowledge, is the first work that models the im pact of atmospheric refractivity on LOS MIMO channels using FRT. It is found that for a 2x2 LOS MIMO system the antenna separation calculated assuming free space propagation is also valid for the case of standard refractivity. For other re fraction conditions, the link will more likely experience an outage due to variation in phase condition than loss of power. In addition, atmospheric multipath may in duce random MIMO phase variation. However, the simulator cannot yet properly tackle surface-induced effects on the signals; this requires further development of the software.
  • Post
    Predicting sea surface wave and wind parameters from satellite radar images using machine learning
    (2023) Borg, Filip; Brobeck, Axel; Chalmers tekniska högskola / Institutionen för rymd-, geo- och miljövetenskap; Chalmers University of Technology / Department of Space, Earth and Environment; Eriksson, Leif; Amell, Adrià; Elyouncha, Anis
    Accurate predictions of wave and wind parameters over oceans are crucial for various marine operations. Although buoys provide accurate measurements, their deployment is limited, which necessitates the exploration of alternative data sources. Sentinel-1, a satellite mission capturing Synthetic Aperture Radar (SAR) images with high coverage, presents a promising opportunity. However, establishing the relationship between SAR images and wave/wind parameters is not straightforward. This project aims to develop a machine learning model that can effectively extract this relationship. To accomplish this, data from all available buoys measuring significant wave height and wind speed in the year 2021 were utilized. The corresponding SAR images were located, and 2 km×2 km sub-images were extracted around each buoy. From each sub-image, a set of features were extracted. These sub-images and features served as input to train machine learning models capable of predicting buoy measurements, supplemented with model data as necessary. The project presents two final deep learning models: one utilizing only the extracted features and another employing both the sub-images and features. These multi-class regression models simultaneously predict significant wave height and wind speed. The model using only features achieved a Root Mean Square Error (RMSE) of 0.553 m for significant wave height and 1.573 m/s for wind speed. The model incorporating both sub-images and features achieved an RMSE of 0.459 m for significant wave height and 1.658 m/s for wind speed. The code for the project can be found on https://github.com/SEE-GEO/sarssw.
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    Beam selection optimization algorithm for the Satcube Ku.
    (2023) Olsson, Lucas; Saber, Pouria; Chalmers tekniska högskola / Institutionen för rymd-, geo- och miljövetenskap; Chalmers University of Technology / Department of Space, Earth and Environment; Haas, Rüdiger; Johansson, Jan; Malm, Calle
    The Satcube Ku is a satellite terminal which provides internet access to a user anywhere on Earth with the help of spot beam technology. For a given position on Earth, multiple intersecting beams will be present with varying signal strength. There is the need to distinguish one beam from another in order establish a hierarchy. The purpose of this master thesis is to investigate a way to rank the available beams at a position on Earth and develop that into a new beam selection algorithm for the Satcube Ku terminal. The new algorithm must address both circular and elliptical HTS-beams as the beams are projected across the surface of the Earth. There are many limitations to this project and many different approaches have been presented. The approach is to analyze user data and geospatial data combined with provided satellite information in order to find important aspects of the problem. A five step algorithm was ultimately decided. The algorithm takes the user position as an input and gives a sorted list from highest to lowest carrier-to-noise expected in that position as output. The steps are: Step 1: Position and all available beams, Step 2: Beamcenter of beams, Step 3: CNR value at beamcenter, Step 4: CNR reduction to the user posi tion, Step 5: CNR arranged list based on projection and accuracy. The step 1 was solved using polygon conversion of the beam contours given by the terminal and then calculating which polygons the user was inside of. In step 2 the beamcenter of the beams were estimated by measuring the distance from the polygon center to a beam center position provided by Intelsat for certain beams. In step 3 the each beamcenter was given a maximum theoretical value also provided by Intelsat. In step 4 three different methods were investigated to project what the received CNR would be at the user position. The methods were Concentric Contour Contraction, Concentric Elliptical Expansion and Least square fit method. The Concentric El liptical expansion was the most appropriate method available and was used in step 5 for a test position in Gothenburg. The resulting output was limited to only IS33 and IS37 satellites due to the lack of information regarding the beam center values. The final list projections compared to actual measurements performed within 1 dB.
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    Chemical-looping gasification for the production of aviation fuel with negative emissions: Full chain process modeling and techno-economic analysis
    (2022) Shahrivar, Mohammad; Saeed, Muhammad Nauman; Chalmers tekniska högskola / Institutionen för rymd-, geo- och miljövetenskap; Chalmers University of Technology / Department of Space, Earth and Environment; Mattisson, Tobias; Soleimani Salim, Amir H
    The greenhouse gases from the conversion of fossil fuels are the main culprits for the increase in the planet's temperature which is reflected in the global warming context. The aviation sector is more dependent on fossil fuels as there is less possibility to find a viable alternative for fuel requirements for this sector. Chemical Looping Gasification with biomass as a fuel combined with downstream Fischer-Tropsch (FT) synthesis for aviation fuel production is a possible way to decarbonize transportation sectors like aviation. Chemical Looping Gasification (CLG) is like indirect gasification in a circulating fluidized bed, except that instead of inert bed material, particles containing metal-oxides, called oxygen carriers (OCs) are used as the bed material. CLG process has advantage of unnecessary use of an expensive and energy-intensive air separation unit (ASU). Also, due to the presence of a more oxidizing environment in CLG and the catalysing property of OC, the tar yield drops substantially resulting in improved syngas yield and better biomass to syngas conversion compared to the conventional gasification processes. Moreover, all produced CO2 is concentrated in the fuel reactor, with no or limited emissions from the air reactor. This means that it could be a very good process for combined fuel production and capture of CO2, something which would result in net-negative emissions. The study is based on modeling the full chain process of biomass to liquid fuel (BtL) using Aspen Plus software. The model is designed for a gasifier load of around 80 MWth and includes drying of biomass followed by a CLG unit using different oxygen carriers (LD slag and Ilmenite). The circulation rate of an oxygen carrier is adjusted to achieve the desired autothermal CLG operation with temperature of 935oC in the fuel reactor (FR). The resulting syngas from CLG goes through syngas cleaning and conditioning units to meet the requirements for FT synthesis. The steam to biomass ratio is adjusted to 0.7 to achieve an H2/CO ratio of 2.1 before the FT reactor. In the FT reactor with cobalt as a catalyst and at temperature of 220oC, the syngas gets converted into hydrocarbons with carbon numbers ranging from 1 to 40 using the Anderson-Schulz-Flory distribution. Since the aim of the model is to produce aviation fuel, the FT synthesis process combined with a reformer in the recycle loop is adjusted for maximizing the yield of paraffin with carbon numbers ranging from 8 to 16. Based on the optimized model, the clean syngas after syngas cleaning units has an energy content of 8.68 MJ/Nm3 (LHV basis) with a cold-gas efficiency of 77.86 %. FT synthesis model with a reformer estimates an FT crude production of around 647 bbl/day with 154 kilo-tonne of CO2 captured every year and conversion efficiency of biomass to FT-crude of 38.98 %. The calculated levelized cost of fuel (LCOF) is 35.19 $ per GJ of FT crude, with an annual plant profit (cash inflow) of 11.09 M$ and a payback period of 11.56 years for the initial investment.