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Designing a Trangia Coffee Brewer
(2026) Östman, Rasmus; Lindh, Agust
This master’s thesis explores the development of a specialised coffee brewing accessory tailored for Trangia AB, a leading Swedish manufacturer of outdoor cooking stoves. The aim of the project was to create a simple, reliable brewing solution that enriches the outdoor experience, uniting contemporary coffee habits with Trangia’s core values of sustainability, simplicity, and backwards compatibility. Through an exploratory design process involving benchmarking, brand analysis, and qualitative user research, the needs of the primary target user groups were identified. By utilising iterative concept generation methods such as brain drawing, rapid physical prototyping, and evaluation matrices, multiple brewing mechanisms were explored. The final selected concept is the ”Auto Drip”, an innovative solution that brings drip coffee to the outdoor segment. Powered by the stove’s heat, the device utilises the principles of a percolator, collecting steam in a pump base to push boiling water through a pipe and into a filter holder. This design provides a highly desirable ”set it and forget it” experience while delivering consistent drip coffee in the field. Prioritising packability and seamless integration, the lightweight metal components pack flat within Trangia’s existing 25 and 27 stove systems. Ultimately, the project resulted in a robust, modular accessory that maintains a visual language that respects Trangia’s heritage while meeting modern campers’ expectations for reliable outdoor functionality
Global Sensitivity Analysis of a Digital-Twin for Battery Electric Vehicles -Data Pipeline Development for Large-scale Simulations
(2026) Claesson, Hugo; Svanbro, Cassandra
Modeling is a central tool in the development of battery electric vehicles, particularly in applications of validation and system optimization. This thesis aims to assist the development of simulation platforms through a large-scale global sensitivity analysis of a digital twin representing a heavy duty battery electric vehicle, using energy consumption as the primary output. The Elementary Effects Test was implemented to screen the model input space, after which a Sobol’ sensitivity analysis was conducted on the most influential input parameters. The sensitivities were further explored through derivative-based measures, linear regression and Monte Carlo filtering. The results consistently identified the gross combination weight as the overwhelmingly most influential parameter. The Sobol’ analysis further indicated that, depending on the drive cycle, this parameter accounted for between 25% and 77% of the total output variance. In addition the initial temperature, the aerodynamic drag area and the rolling resistance coefficient were concluded as influential input parameters but not in the same magnitude. The relative ranking of parameter importance was found to vary with the drive cycle used for the simulations. The linearity of the relation between input parameter and output was also investigated. Gross combination weight, rolling resistance coefficient and the aerodynamic drag area were found to have mostly linear effects on the output, thus suggesting that these relationships can be represented by simplified models in future work.
Assessment of Post-printing Component Cleaning Solutions for Lithography-based Metal Additive Manufacturing
(2026) Bergvall, Noel; Pölder, Jakob; Nilsson, Måns; Thorstensson, Linus
Additive Manufacturing (AM) enables the production of highly detailed components with complex internal geometries difficult to manufacture conventionally. Lithography-based Metal Manufacturing (LMM) is one such novel AM method, and the subject of investigation of this thesis. Post-processing of LMM components with internal features smaller than 1.5mm presents significant cleaning challenges. During de-caking, heat is applied to liquefy and drain excess feedstock. However, capillary forces and surface films trap viscous excess feedstock within internal features, making removal difficult. The current cleaning procedure produces defects and lacks standardization. This thesis aims to develop a standardized post-processing method minimizing cleaning-induced defects and yielding reliable cleaning results. Ten batches of stainless steel 316L test components containing channels, junctions, and narrow fin arrays were manufactured and cleaned iteratively to identify defect-causing parameters. These parameters were validated through additional batches to establish a complete cleaning procedure. Mechanical and chemical agitation proved most effective for feedstock removal. The optimal method involved inverted printing to avoid flow restrictions caused by the build plate, followed by a 15-minute de-caking stage and intermittent cleaning cycles using pressurized air and heated proprietary solution IncuSOL. A final 60 second exposure to the ultrasonic bath in heated IncuSOL is used to clear residual feedstock from components. Since polymerization begins immediately after printing and is accelerated by heat, cleaning must start directly after the print, conclude within 30 minutes, with the heating temperature limited to 60 ◦C. Using this method, straight internal channels as small as 0.8mm in diameter and 5mm in length were successfully cleared. Further research is required to evaluate process consistency for other materials.
Development of a Mooring Calculation Model for Pontoons: Preliminary Dimensioning of Mooring Chains and Concrete Anchors
(2026) Aliprantis, Johannes; Jarlgren, Joel
Floating concrete pontoons require reliable mooring systems to limit movement and transfer environmental and operational loads to the seabed. In practice, anchoring solutions must also remain cost-effective, installable and compatible with available chain and anchor dimensions. The aim of this thesis was to develop a calculation prototype for preliminary dimensioning of mooring chains and concrete deadweight anchors for SF Marina’s floating pontoon systems. The prototype was developed in Python and combines analytical models for chain geometry, mooring loads and anchor capacity to evaluate feasible chain and anchor configurations under given environmental conditions. The chain model is based on static equilibrium and submerged chain weight, while the anchor capacity model uses capacity tables derived from a simplified Pearl Harbor type anchor formulation. The program evaluates discrete chain dimensions and anchor weights, allowing the selected solution to correspond to practical component alternatives rather than idealized continuous sizes. The prototype was evaluated using a reference case and a comparison between analytical anchor capacity tables and PLAXIS 2D simulations. The results were consistent with SF Marina’s proposed anchoring solution and showed that the chain strength margin was large, while the anchor capacity was more sensitive to seabed assumptions and anchor penetration depth. The developed prototype is considered suitable as an internal early-stage design support tool. It can help compare mooring alternatives, identify governing parameters and document preliminary chain and anchor selections. However, the results should be interpreted with caution where seabed conditions, penetration depth or dynamic loading effects are uncertain.
Maxwell's demon in dynamic quantum circuits
(2026) Hildeberg, Olof
Dynamic quantum circuits use intermediate measurements and classical feed-forward to change later operations during a computation. This makes them similar in spirit to Maxwell’s demon, since measurement information is used to guide the evolution of the system. In this thesis, this idea is studied in the context of Greenberger–Horne– Zeilinger (GHZ) states, that is, entangled states of the form (|0⟩⊗𝑁 + |1⟩⊗𝑁 )/√2, on noisy quantum devices. on noisy quantum devices. Three GHZ preparation protocols are compared: a non-adaptive protocol, a semi-adaptive protocol, and a fully adaptive protocol. The non-adaptive protocol uses only fixed unitary gates, while the adaptive protocols use ancilla measurements and conditional corrections. The protocols are implemented in a classical stabilizer simulation framework and compared using the final GHZ fidelity as the performance measure. The simulations isolate four different error sources: CX gate errors, measurement errors, relaxation, and pure dephasing. This makes it possible to study not only which protocol performs best, but also which physical effects limit the performance of each protocol. In the CX gate-error regime, the results are determined by the number of CX gates. In the measurement-error regime, the adaptive protocols are limited by their reliance on intermediate measurements. For idle-time errors, the comparison is more subtle, since adaptive protocols reduce quantum depth but also introduce ancilla overhead and measurement and feed-forward delays. For the noise models and timing assumptions used in this work, the non-adaptive protocol gives the highest fidelities in all isolated error regimes. The adaptive protocols therefore do not gain an advantage from their reduced depth under these conditions. The main bottleneck is found to be the measurement and feed-forward time, which exposes the data qubits to additional idle-time noise. This suggests that adaptive GHZ preparation could become more competitive on hardware with faster measurements, faster feed-forward, or lower-overhead adaptive constructions. The results show that reduced circuit depth alone is not sufficient to guarantee an advantage for dynamic circuits. Instead, the usefulness of adaptivity depends on the balance between gate count, circuit depth, measurement overhead, ancilla overhead, and hardware timing.