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Explanatory model for the occurrence of iron and manganese in the groundwater in Umeälvsåsen
No full textHigh concentrations of iron and manganese are common substances in Swedish
groundwater that require treatment before use in drinking water. Elevated
concentrations of these elements have been detected by Ramboll in
Umeälvsåsen, a glaciofluvial esker in northern Sweden, which is under
consideration as a future groundwater source. This thesis aims to identify the
underlying causes of the elevated concentrations and develop an explanatory
model applicable to similar projects.
The study combined theoretical background with site-specific data to establish
theories of potential underlaying causes. Verification of theories was made using
statistical analysis, laboratory testing, and GIS-based spatial analyses. The
findings indicate a strong correlation between wetlands and high iron and
manganese concentrations, supporting the hypothesis of hydraulic connectivity
between wetlands and groundwater. Additionally, lower groundwater velocity
and deeper wells were found to significantly influence groundwater
geochemistry.
The results did not support other potential explanations, such as seasonal
variability or the presence of organic lenses. The proposed model emphasizes
the importance of early stage hydrogeochemical assessments and provides a
methodological framework for identifying underlying contamination sources in
future groundwater projects.
These insights contribute to more effective planning and management of
groundwater resources in glaciofluvial deposits, avoiding problems with iron
and manganese
Time-dependent stress behavior: A study on creep and relaxation performance for heat treatment-free fasteners
No full textThe increasing demand for sustainable manufacturing processes has driven the company Bulten to develop new fasteners (BUFOe), which are heat treatment-free, to minimize its carbon footprint.
This thesis examines the time-dependent stress behavior of BUFOe fasteners (non-heat-treated) in comparison to regular heat-treated fasteners under ambient and elevated temperature conditions. It is essential to quantify the mechanical stability of the new fasteners during thermal loading to give clear recommendations regarding suitable service conditions. To achieve this goal, a testing procedure was established to measure creep strain over short periods at both ambient and elevated temperatures. The comparison between BUFOe fasteners and regular heat-treated fasteners indicates that BUFOe800X fasteners exhibit excellent performance in resisting creep deformation (0.07%), which is superior to their counterpart 8.8 fasteners and comparable to that of regular heat-treated fasteners (10.9) at room temperature.
This shows that non-heat-treated fasteners may be a viable alternative in engineering applications at room temperature.
However, at higher temperatures, all fasteners of BUFOe exhibited increased susceptibility to creep deformation compared with regular heat-treated fasteners within the same propertyclasses.
These findings provide valuable references for optimizing the reliability and integrity of fasteners under various industrial conditions in the continually evolving field of fastener design and manufacturing processe
Mitigation of torque signal fluctuations in wear rig using digital filters and motor alternatives
No full textIn current modern industries, maximizing the lifespan and efficiency of machines is of a great importance to companies. A key factor in doing this is by understanding how different material influence the wear and performance on the machines. This is very important for Comminution Reimagined Sweden (CRS) since they work with machines that will experience change of material depending on where their machines are placed. To understand the effect of the material interactions, a torque sensor is used to gather data. That data is later on used for energy calculations.
As of now, the torque signal is fluctuating in amplitude suspiciously much and this report investigates methods for reducing these torque fluctuations for CRS wear rigs, using digital filters and alternative motors as solutions. By analyzing frequencies and identifying the sources of these fluctuations, more precise solutions can be discovered. Various motors and digital filters are compared, to try and find a suitable solution to these fluctuations. The result of these studies indicates that a more suitable motor and digital filter in combination could significantly reduce the torque fluctuations. No real test have been done where a new motor and digital filter have been implemented and tested. The study therefore aims to provide a guidance for CRS on how future implementations can enhance the reliability of the torque signal
From image to graph: Topological representation of Wire harnesses using deep learning
No full textThe ability to classify an abstract representation into an image of a wire harness is a key step in automating the wire harness assembly industries. This study examines different methods and machine learning architectures to extract visual and physical features from an image of a wire harness. To identify suitable methods for abstractly representing and classifying a wire harness, a systematic literature review was con ducted. The systematic literature review was not limited to studies about wire harnesses, but expanded to studies about deformable linear objects. Following the systematic literature review, an experimental study was conducted that evaluated an existing implementation for graph representation of a wire harness and a novel method based on a You Only Live Once (YOLO) segmentation model together with a Graph Convolutional Network (GCN) to classify the graph representation against a validation file of known harnesses. The segmentation output from the YOLO network is fed into a skeletonization method that returns a graph that represents the wire harness. In order to classify the graph representation against known harness structures, a GCN along with a validation step is performed. The models are trained on a proprietary dataset and two open-source datasets. The proposed solution can be easily adapted to classify new wire harnesses
Fault Detection of HVDC Transformer Windings using Impedance Protection
No full textPower 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
AI-driven Player Experience Modeling in Serious Games for Software Engineering
No full textSerious games offer great potential for enhancing software engineering education, yet the use of AI-driven Player Experience Modelling (PEM) remains under-explored in this context. This study investigates how AI-enhanced adaptive features such
as difficulty adjustment and dynamic guidance affect player engagement and skill acquisition in the programming game Elara. By comparing AI-driven and traditional versions of the game, the research highlights the benefits of personalized gameplay for supporting learning and motivation. The study demonstrates the promise of AI in tailoring educational experiences and calls for future work to incorporate automated player profiling, larger datasets, and emotional state recognition to further improve adaptive learning in serious games
Concept exploration; Integrating atmospheric water generation systems onto spray drying process
No full textWater is a scarce resource in many places of the world, and the problem with access to clean water increases. There are several ways to mitigate the problem and produce clean water and one of them is atmospheric water generation (AWG). Although water is a scarce resource it occurs as a residual product from the drying process spray drying. The Uppsala based startup company Drupps has developed technology for water recovery using a liquid desiccant to absorb the residual hot fumes emitted into the atmosphere. The company has built a pilot plant in a test facility with the necessary components for the system.
The purpose of the thesis was to develop a product architecture to be retrofitted on existing productions that use spray dryers. The target customers was productions with spray dryers emitting approximately 250 000 cubic meters of moisture per hour. To develop a customer focused product, the product development method is based on the one presented in the book “Product design and development” by Karl T. Ulrich and Steven D. Eppinger from 2016. The thesis elicits customer needs, mainly through interviews, searching for solutions that solve similar problems, decision matrices.
The final concept design is an modular architecture, consisting of a load-carrying structure of a square cube frame with interface to enable more cubes to be connected. The majority of the components of the Drupps atmospheric water generation system fit inside the cubic frames, and by increasing and alternating the three different cubes, the system can fit a wide variety of volumetric flows as well as different potential customer segments
Point Load Distribution in Overhang Slabs: Effects of Model Complexity and Load History
No full textUnderstanding the distribution of point loads in overhang slabs is crucial for improving
design and assessment of reinforced concrete bridges. The concept of an effective width
allows shear forces and bending moments to be evaluated at critical sections and used
in the dimensioning of the slab. While linear Finite Element (FE) analyses generally
provide conservative and sufficiently accurate results, they may not fully capture the
structural behaviour. Non-linear FE analyses offer a more realistic representation, but
at the cost of increased computational effort and complexity. Finding a balance between
accuracy and efficiency is therefore a key consideration.
This Master’s thesis investigates the load-bearing capacity and force distribution re sulting from concentrated loads using analysis models of varying complexity, aligned
with current regulations. A series of load cases and geometries were analysed using
conventional hand calculations, linear FE models, and non-linear FE models.
Findings reveal a significantly higher load-bearing capacity in non-linear analysis due to
force redistribution following reinforcement yielding. Furthermore, the edge beam has
little effect on the load-bearing capacity in linear models, while in non-linear analysis
it significantly improves both capacity and force distribution. Hand calculations and
linear analysis are conservative, simple, and relatively quick to perform, making them
suitable for an initial evaluation of load-bearing capacity. However, if a higher capacity
needs to be verified, non-linear FE analysis can be used to provide a more refined and
potentially less conservative assessment.
The non-linear FE model was also subjected to a loading history, where the cantilever
slab experienced sequential point loads at multiple locations, resulting in increased per manent deflections and cracking. However, the prior loading had low effect on the
ultimate load-bearing capacity. Its main influence was observed in the serviceability
limit state, where both deflection and crack width were increase