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Optimizing the effect of tramp elements on intermetallic phases in HPDC Al alloys – A thermodynamic approach
No full textThe growing interest in increasing the recycled content of aluminium for highpressure
die casting (HPDC) is driven by a demand for greater sustainability, as
recycled content offers a ∼nearly 95% reduction in energy compared to primary aluminium.
However, elevated levels of elemental contamination from recycled content,
mainly tramp elements such as iron (Fe) and manganese (Mn), pose significant challenges.
This thesis focuses on the thermodynamic analysis of the Al-Si-Fe-Mn system
with additions of magnesium (Mg) by using Thermo-Calc through CALPHAD-based
Scheil simulations at a high rate of 100 K/s, in conjunction with validation using
complementary microstructure analysis.
The simulations, comprising over 300 compositions, demonstrated a strong linear
correlation between increasing Fe content and the fraction of the β-Al5FeSi phase.
In contrast, increasing Mn content suppresses β phase formation by promoting the
more benign α-Al15(MnFe)3Si2 phase. Si notably altered the solidification range and
eutectic transitions within the system. Higher Mg levels led to phase competition
between π-AlFeMgSi and β phases. The potential evaporation of Mg was also found
to shift phase equilibria, increasing the fraction of β phase, emphasising the need
for accuracy control of alloy compositions.
Microstructure analysis, employing SEM and EDS on the cast alloys, shows that Fe
influences β-intermetallics, as it is composed of Fe instead of Mn. The analysis also
reveals compositional variations that influence kinetic effects, such as the formation
of the δ-AlFeSi phase and localised solute depletion zones around α-phase particles.
These findings clarify the effects of Fe, Mn, Si, and Mg on intermetallic phase formation
and emphasise the importance of integrating kinetic effects to contribute to
a more comprehensive understanding of optimising recycled aluminium alloys
Utveckling av en humanoid robotprototyp
No full textDetta arbete har utförts tillsammans med institutionen för mekanik och maritima vetenskaper på Chalmers tekniska högskola. Syftet med projektet var att utveckla en ny humanoid robot som används i kursen TIF160 Humanoid Robotics på Chalmers. Målet var att förbättra den mekaniska strukturen hos roboten då den tidigare roboten som användes i kursen var väldigt instabil vilket ledde till stora vibrationer och sämre precision. Dessutom skulle roboten vara uppbyggd av mestadels standardkomponenter för att enkelt kunna tillverka flertalet likadana exemplar.
Arbetet följde en klassisk produktutvecklingsmetodik där tillvägagångssättet inleddes med att identifiera problemet genom en undersökning av den tidigare roboten. Sedan skapades nya idéer genom en marknadsundersökning och fri idegenerering som vidareutvecklades till koncept genom kombinering av idéer och dellösningar. Dessa genomgick en konceptutvärdering för att få fram tre slutkoncept. Dessa koncept genomgick en mer detaljerad designprocess där stort fokus låg på komponentval. Till sist skapades två prototyper som sedan genomgick tester för att se om målet uppfylldes. I testerna användes en accelerometer för att mäta vibrationer genom rörelse och frekvenser.
Slutkoncepten resulterade i två olika prototyper som skapades och testades. Testerna gav ett resultat som tydligt visade på att målet med att göra en stabilare robot med mindre vibrationer och mer precision uppnåddes. Robotens design påminner om den tidigare roboten, men med en mer robust design, komponenter som gör produkten mer modulär samt utan specialtillverkade komponenter.
I slutet av rapporten diskuteras resultatet och förslag på vidareutveckling presentera
Enhancing geospatial tools through integration of climate data: A path toward more sustainable infrastructure planning and decision-making
No full textClimate impact is an important dimension in today’s urban planning since the construction
of new roads contributes to large emissions of greenhouse gases as well as
environmental impacts on the ecosystem. One approach, part of the strategies from
the action plan developed by governmental initiative Fossilfritt Sverige, to mitigate
climate impact relates to increased use of digital tools of which includes different
types of geo tools. The objective of this thesis is to investigate if climate data can
be effectively integrated into a Geo tool and to evaluate its role in mitigating climate
impacts in infrastructure projects. Furthermore, to analyze to what extent
geo tools can support and streamline decision-making during the early design phase
in infrastructure projects.
This study examines a route analysis planning tool named Georaptor using a weighting
method called AHP. To determine whether the weighting method is effective in
drawing conclusions based on climate data, a case study was conducted in the area
around Bergkvara, Kalmar County. In addition, perspectives from previous projects,
expert opinions, and comparisons between different weightings were analyzed. The
result reveals that the tool is useful for analyzing where to construct a road in a
given area, taking climate impacts into account. By identifying areas with high
ecological value, it is possible to avoid sensitive areas and thereby reduce the road’s
carbon footprint and preserve important natural values. The tool helps streamline
the decision-making process by quickly generating multiple corridor alternatives during
the design phase, which can later be manually evaluated. This minimizes the
workload and provides transparency, as both good and less favorable alternatives
are compared
AI-driven single-particle tracking for cancer cell characterization
No full textProstate cancer exhibits altered intracellular phenotypes that require novel biomarker
approaches for accurate diagnosis and treatment stratification. This thesis presents
an integrated computational framework to reconstruct and analyze the intracellular
dynamics of vesicle-encapsulated gold nanoparticles (AuNPs) from large-scale scat tering microscopy videos, with the goal of identifying dynamic indices that can serve
as potential biomarkers for distinguishing between prostate cancer cell lines.
The proposed framework combines two major components: trajectory recon struction using deep learning models, specifically the MAGIK graph neural network,
and inference of diffusion properties from the reconstructed trajectories. To address
the challenges caused by the large scale of the experimental videos, the study intro duces a segmentation-based pipeline that processes smaller video sequences, inte grates predicted graphs, and builds accurate nanoparticle trajectories. Importantly,
the MAGIK model is trained on simulated trajectories that simulate biologically
relevant motion types, reducing the need for labor-intensive manual annotations.
Subsequently, the study applies a modified version of the MAGIK model to pre dict point-wise diffusion exponent values for each trajectory, allowing classification of
distinct motion types such as directed motion and subdiffusive motion. Among the
extracted dynamic indices, nanoparticle velocities during directed motion emerge as
promising biomarkers, showing different distributions between the LNCaP and PC3
prostate cancer cell lines.
Overall, this work demonstrates the potential of applying deep learning methods
to uncover novel dynamic biomarkers in cancer research. Future directions include
extending the analysis to additional diffusion properties and expanding the reper toire of dynamic indices with biological significance to further enhance biomarker
discovery and improve our understanding of intracellular transport in cancer cells
Aerodynamic investigation of a vehicle in highly turbulent flow
No full textThis master’s thesis presents the design, simulation, and experimental validation of
an active turbulence generator aimed at reproducing realistic, highly turbulent flow
conditions for vehicle aerodynamic testing in a scale wind tunnel. The main goal
is to bridge the gap between idealized wind tunnel tests and the unsteady, turbulent
flow scenarios encountered during real-world highway and urban driving. To
achieve this, an active turbulence generator using oscillating airfoils was developed.
The airfoils, based on the NACA 0015 profile, were actuated to produce adjustable
turbulence intensities and length scales, matching conditions such as turbulence intensities
of 1–5% for highway speeds in real-world driving scenarios. Computational
Fluid Dynamics (CFD) simulations were conducted using the κ−ω SST turbulence
model with an overset mesh technique to accurately resolve the unsteady interaction
between the moving airfoils and the freestream. The simulations analyzed characteristic
parameters including turbulence intensity, turbulent length scale distributions,
and aerodynamic loads on a DrivAer reference model. The design was optimized
to ensure turbulence generation across the test section while keeping the required
mechanical power within feasible limits. A mechanical system driven via a single
motor through a chain was designed and manufactured using rapid prototyping techniques,
allowing synchronized oscillatory motion of all seven airfoils. The system
was integrated into the Chalmers scale wind tunnel and tested. The findings serve
as a solid foundation to be built upon in future projects regarding the development
of an active turbulence generator
Electrochemical investigation of Fe- and Zr-based alloys in standard conditions and under gamma irradiation in contact with H2O2
No full textRadiation induced corrosion is a major problem for the longevity of nuclear power plants,
and the research into this field is hampered by the requirement to accurately simulate
reactor conditions in experiments. This study attempts to electrochemically investigate
the interaction between hydrogen peroxide (H2O2) and the alloys AISI 441 and Zircalloy-2
(Zry2), both under standard conditions and under γ irradiation.
The results from the linear scan voltammetry (LSV) indicate that the anodic oxidation
reaction between AISI 441 and H2O2 might be catalyzed by γ irradiation. Whereas the
cathodic reduction reaction may be inhibited by the radiation. With regards to Zry2 the
anodic LSV results show a possible surface area limitation on the reaction. The cathodic
experiments highlight the chemical inertness that the alloy is known for, though there
appears to be a inhibitory effect of γ radiation upon the evolution of hydrogen.
These findings highlight the greater sensitivity of AISI 441 to radioactive environments,
which may have implications for material selection in reactor design
Användning av smarta glasögon för effektiv lastning av trailrar
No full textWarehouse operations are facing increasing demands for efficiency and sustainability. At the same time, the loading of pallets into trailers is still largely performed manually, which increases the risk of errors, inefficiencies, and learning difficulties for new staff.
The purpose of this study is to explore how smart glasses can be used to streamline and support the loading process in a warehouse environment. The aim has been to develop and evaluate a concept in which visual guidance is presented to the user through smart glasses.
The study was built on data collected through information searches, field studies, interviews, and user evaluations. Based on this material, a concept was developed iteratively and tested in prototype form with users experienced in warehouse work.
The results show that there exist clear shortcomings in current working methods and that smart glasses have the potential to provide support through clear real-time visual information. Users found the concept user-friendly and relevant for the task of loading trailers.
The conclusion is that smart glasses can contribute to a more efficient and understandable loading process, but continued technical development, practical testing, and organizational adaptation are required before broad implementation is possible
Techno-Economic Comparison of Chemical Looping Combustion (CLC) in Canada and Sweden
No full textIn order to mitigate global warming by reducing industrial emissions, use of CO2 capture
technologies is critical. Chemical Looping Combustion (CLC) is a promising, yet uncommer cialized, method with potentially improved environmental benefits compared to conventional
carbon capture technologies. The aim of this work is to investigate the commercialization po tential of a 100 MW CLC power plant in Sweden and Canada through simulations using Aspen
Plus and a techno-economic analysis.
A reference simulation was developed, which was based on the Örtofta combined heat and power
(CHP) plant in Sweden, that was used as a basis for building the CLC cases. For the Canadian
CLC case, sub-bituminous coal was used as the fuel and district heating was excluded, while the
Swedish CLC case used bark as fuel and co-generated electricity and district heating. Ilmenite
was selected as the oxygen carrier (OC) in all CLC scenarios. Key assumptions included an
investment return rate of 9% and a 30 year plant lifetime.
When comparing the CLC scenarios, significantly higher commercialization potential could be
observed for the Swedish CLC plant, with a payback period (PBP) of 11.45 years and a net
present value (NPV) of -e37.05 million, compared to 41.02 years and -e231.74 million for the
Canadian case. The primary factor behind this difference was identified to be the choice of
including district heating or not. Of all simulation scenarios, the Canadian CLC case had the
by far highest electricity yield (2127.7 kWh/tonne fuel) but generated the least profit (e7.18
million/year). The Swedish CHP plant without CO2 capture had the lowest levelized cost of
electricity (LCOE) at e0.0899/kWh, as well as superior results compared to the CLC scenarios
regarding the NPV and the PBP at e173.86 million and 5.74 years.
Sensitivity analysis showed that capital expenditure (CAPEX) had the most significant influ ence on NPV in all simulation cases, while electricity price came as the second most important.
Comparatively, fuel and OC costs had minor impacts. To make the NPV of the Canadian CLC
plant positive, the incentive for CO2 capture in Canada would need to be increased by 3.6 times
(to e220/tCO2). In order to make the NPV of the Swedish CLC case positive, the incentive
would need an increase of about 1.2 times (to e110/tCO2). For the Swedish CLC scenario
to have a higher NPV than that of the Swedish CHP plant without CO2 capture, either the
incentive would need to be increased by 2.4 times (to e220/tCO2) or the carbon tax for biofuels
would need to be increased by 4.6 times (to e160 /tCO2)
The root of an effective root cause analysis
No full textManufacturing process variations can remain unsolved despite repeated problemsolving
efforts, even though a large variety of root cause analysis tools are well
known. This study investigates the practical challenges and opportunities that influence
the efficiency of root cause analysis in complex manufacturing contexts.
Using an action research approach, a longstanding manufacturing instability related
to windshield adhesive at a knock-down truck assembly plant was analyzed through
the Six Sigma DMAIC framework.
Throughout the study barriers and enablers were identified on both previous problemsolving
attempts and the newly conducted root cause analysis. 30 barriers and 20
enablers were identified and categorized. The findings demonstrate that problemsolving
tools and methods alone are not sufficient. Effective root cause analysis requires
a fact based approach, supported by high-quality and accessible data, strong
communication and collaboration, clearly defined roles and responsibilities, ownership
of the problem, clear standardized procedures, and management commitment.
A conceptual model was developed to illustrate the interrelations between these factors
within the organizational system. The study concludes that effective root cause
analysis depends not solely on the method, but on the organizational system that
shapes how issues are framed, understood and addressed