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Senast inlagda
RANS-based aerodynamic optimization of a pickup truck: performance assessment and verification of add-on improvements
(2025) Piferi, Alessandro
Pickup trucks represent a significant share of the global automotive market yet
remain characterized by poor aerodynamic efficiency due to their inherent bluffbody geometry. This study investigates the aerodynamics of a generic double-cab
pickup truck, in two configurations: the open and closed bed, using steady state
RANS turbulence model and wind tunnel validation. Three turbulence models,
Realizable k − ε, Lag EB k − ε, and SST k − ω were evaluated against experimental
data to determine the most accurate approach for predicting drag trends across
configurations. The Lag EB k−ε model demonstrated superior fidelity in predicting
∆CD trends and was selected for the baseline flow topology study and optimization
phases. The baseline flow topology analysis identified various critical sources of
drag and the generation of a distinct pair of counter-rotating vortex that negatively
impacts the drag generation. Several aerodynamic add-on devices were designed
and assessed, including a sealed cabin-bed gap, a shortened tailgate, and a rearcab spoiler. Results indicate that sealing the cabin-bed gap yields a drag reduction
of approximately 2.0%. The optimal configuration, combining the gap seal with
the spoiler, achieved a drag reduction of 3.2% for the open bed configuration and
2.4% for the closed bed configuration. These findings demonstrate that targeted
management of the cabin wake and gap flow can significantly mitigate form drag
without altering the primary vehicle architecture.
Ersättning av betongstomme med korslimmat trä i ett flerbostadshus: Analys och jämförelse mellan en befintlig stomme i betong och en motsvarande stomme i korslimmat trä ur en konstruktion och hållbarhetsperspektiv
(2025) Brolin, David; Johansson, Erik
Detta examensarbete undersöker möjligheten att ersätta en betongstomme i ett befintligt flerbostadshus med en stomme i korslimmatträ. Syftet är att jämföra vilken påverkan de olika materialen kommer få utifrån ett ekologiskt perspektiv. För jämförelse av utsläpp kommer information från en KLT leverantör och en betongleverantör att användas för utsläppsdata via deras miljövarudeklarationer samt utsläppen för transport av produkten.
Resultatet visar att trästommen väger ca 76% mindre än betongstommen vilket underlättar för installation och transport. Utsläppen från Råmaterialutvinning, transport och production i form av ton CO2-ekvivalenter är hela 84% lägre för trästommen. Däremot blir de bärande elementen i trästommen tjockare och tar upp större delar av byggnadens boarea.
Assessment of swashplateless rotor systems for sensor carrying drones: An investigation into control, efficiency, and feasibility
(2025) Nordling, Jesper; Björklund, Simon
This thesis investigates two rotorhead configurations, a fully articulated dual hinge
and a semi-rigid teetering hinge rotor, for potential use in swashplateless helicopters
or drones, aiming to expand the understanding of their respective mechanical and
aerodynamical behaviours. Experiments were conducted on a fixed test rig designed
for easy interchangeability between the two rotor types. Both rotors were tested
with identical blades at fixed pitch angles of 8°, 10°, and 12°, using the same control
system.
Three test types were performed. First, a constant roll input was applied while
rotor speed varied from 500 to 3000 RPM, across three increasing roll magnitudes.
Second, a step response test measured the time required for the rotor to transition
from maximum to minimum roll output, assessing dynamic response. Third, a roll
sweep test was conducted at approximately 2500 RPM using stepwise increases in
roll input. High-speed video analysis was used to observe dynamic behaviour.
Results show that the fully articulated dual hinge rotor provides more effective
thrust vectoring across all roll inputs and RPMs, while operating at significantly
lower vibration levels. Both rotors exhibited similar energy consumption and roll
rates. While the dual hinge rotor’s improved thrust control and smoother operation suggest advantages for general purpose drones and helicopters, especially those
carrying sensitive sensors and equipment, the semi-rigid teetering hinge rotor’s simplicity and robustness is attractive for applications where mechanical reliability,
weight reduction, and ease of maintenance are prioritized. Further exploration of
teetering rotor concepts, especially in alternative configurations and with a further
optimized control system, may reveal additional potential not fully captured in this
study.
Performance of a new Risk Score in a Patient Monitoring System in Low-Resource Settings in a Hospital in Zomba, Malawi
(2025) Morrenhof, Kelly
In Low- and Middle-Income countries (LMIC), it is hard to provide adequate healthcare
to critically ill children due to limited resources in staff and equipment. Within
these Low-Resource settings (LRS), pediatric mortality and the occurrence of Critical
Illness Events (CIE) are high. Continuous patient monitoring of vital signs
can be particularly helpful in LRS, especially for critically ill children. GOAL 3
designed a Continuous Patient Monitoring System (CPMS), service, and training fit
for LRS, IMPALA, and implemented it in the Pediatric High-Dependency Unit of
Zomba Central Hospital in Malawi, Africa. To this IMPALA CPMS, a newly developed
Risk Score was added. This Risk Score, adjusted from an earlier developed
physiological score, can potentially assign a health risk level with a score between
0-100, show the progress of the patient over time, and function as an early warning
system. In this study, the performance of the Risk Score is assessed, based on its
distinctive ability to assign a high-risk level to patients who eventually passed away
and to patients who had one or more CIE. The study consisted of 192 participants
under 5 years of age, whose clinical and score data were analyzed. With a mortality
rate of 12% and 140 CIE in total, there were many critically ill children. That
group showed the highest average Risk Score of 64 in the death subset, and 37 in
all patients with one or more CIE, significantly different from an average score of
23 in participants who had no CIE and survived. With an AUROC in the range
of comparable literature, it shows that the Risk Score can distinguish and potentially
predict patients who pass away moderately to well, especially in the last 6-8
hours before discharge. Observations and data analysis revealed challenges with the
Risk Score availability, which results in an average score coverage of 82%, mainly
due to problems with the oxygen saturation probe and nurses not implementing the
score system in their routines at the beginning of the study. Optimization and more
research have to be done to improve these challenges and validate the Risk Score.
Fault Detection of HVDC Transformer Windings using Impedance Protection
(2025) Meegodage, Sewwandi Subhashini Meegoda
Power transformers play a key role in high voltage direct current (HVDC) systems to overcome the limitations of conventional AC transmission and are expensive and fundamental
components in power systems. Transformer winding faults are among the most frequent issues in transformers. Since winding faults are inherently aggravated, transformer winding short circuits need to be detected at an early stage. The existing transformer protection methods encounter difficulties in detecting winding faults in transformers. This study investigates and develops a reliable method for transformer winding fault detection based on impedance protection by calculating the winding impedance utilizing the terminal voltage and current measurements, and comparing the impedance values under fault conditions with their steady-state condition values. A three-phase transformer was modelled in PSCAD simulation software using three multi-winding single-phase transformers to model internal faults. Turn-to-turn faults were simulated for different fault locations, and analyzed impedance values of each scenario using a conventional impedance protection method and Machine Learning algorithms (ML) i.e. Support Vector Machine (SVM), Decision Tree and
Artificial Neural Networks (ANNS) to detect and classify the winding faults and identify their locations. The fault studies were conducted on a symmetric monopolar Voltage Source Converter (VSC) based HVDC system. The terminal voltage and current measurements were utilized to derive impedance values for each fault condition. The obtained voltage, current, and impedance measurements were fed to train the developed Machine Learning algorithm Models. A higher accuracy is obtained by optimizing the ML model parameters in fault detection, classification, and fault location detection.