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Senast publicerade
- Data-Driven Requirement Development - From Field Data to Reliability Requirements: Identifying and Analyzing High-Performing Automotive ECUs(2026) Wang, YiminThis thesis investigates a data-driven methodology for reliability-oriented requirement development in automotive electronics. Traditional automotive reliability engineering is primarily failure-focused, relying on warranty analysis and reactive investigation of defective components. However, such approaches provide limited understanding of why certain Electronic Control Units (ECUs) consistently demonstrate strong field reliability performance. The research initially aimed to analyze relationships between ECU operational conditions and field reliability behavior through classical data-driven analysis. However, the required centralized operational-condition dataset was not available within the industrial data environment. Consequently, the study evolved toward a practical industrial screening methodology based on available enterprise engineering and field-quality data resources. The proposed framework integrates multiple industrial datasets, including the KDP Engineering Database (KDP), Quality Follow-Up (QFU) warranty repair records, the Early Warning System (EWS), and procurement-related production volume data. By combining field repair occurrence with market exposure normalization, ECU populations with exceptionally low repair occurrence relative to deployment volume were identified. Selected ECUs subsequently underwent hardware-oriented engineering investigation, including open-lid assessment, Printed Circuit Board (PCB)-level visual inspection, and review of available Design Verification (DV) and Product Validation (PV) documentation. The investigation focused on identifying recurring robustness-related engineering characteristics rather than performing direct failure analysis. Observed features included reinforced PCB mechanical support structures, controlled PCB cleanliness, environmental protection strategies, and evidence of robustness-oriented validation practices. The work demonstrates how multiple industrial engineering and field-quality data sources can be systematically combined to support evidence-based reliability investigation and practical reliability requirement development in automotive electronics.
- Existence of Static Solutions to the Vlasov-Poisson and Einstein-Vlasov Systems as Fixed Points of a Mass-Preserving Algorithm(2026) Lehmann, LudvigThis thesis develops a new method for proving the existence of static, spherically symmetric solutions to the Einstein–Vlasov system by reformulating a masspreserving algorithm as a fixed-point problem. Building on earlier work for the Vlasov–Poisson system, we first extend an existing fixed-point existence proof from isotropic to anisotropic solutions. We then establish the corresponding result for the Einstein–Vlasov system, using a simple isotropic ansatz.
- Large-Scale Noise Simulation in Urban Environments Using a Preconditioned Helmholtz Solver(2026) Sahakyan, MarinaThis thesis studies the finite element solution of the time-harmonic Helmholtz equation for acoustic wave propagation in urban environments. The discretized Helmholtz equation gives rise to large, complex-valued, indefinite linear systems, for which standard iterative methods may converge very slowly. The aim of this work is to implement and evaluate a preconditioned GMRES solver for such systems, with focus on solver performance, parameter choices, and practical memory limitations. The solver uses a two-level restricted additive Schwarz preconditioner with a spectral coarse space, following the RAS/MS-GFEM approach of Ma, Alber, Scheichl, and Zhang. The implementation is first verified on an exact plane-wave problem, then tested on a controlled rectangular box domain, and finally applied to realistic city-domain meshes representing part of Gothenburg. The experiments investigate how mesh resolution, frequency, and the choice of coarse space affect convergence and computational cost. The results show that the two-level coarse correction considerably improves GMRES convergence compared with a one-level method and with plain GMRES without preconditioning. On the box domain, the method gives stable algebraic convergence up to 30 Hz, although the acoustic field is not fully mesh-converged at the higher frequencies. On the city geometry, the 5 Hz case gives the clearest mesh-refinement behaviour, while the 10 Hz, 20 Hz, and 30 Hz cases become increasingly demanding. The largest city runs show that explicit storage of the coarse basis can become memory-limiting. The study therefore shows that the two-level spectral Schwarz preconditioner is promising for large Helmholtz problems in urban acoustics, but that higher-frequency simulations require careful choices of mesh resolution, coarse-space size, and memory-efficient implementation. Keywords:
- Structuring Educational Media into a Searchable Digital Database with API Access - A prototype for educational media management(2026) Ramsten, Hampus; Tuovinen, JoakimDigimar is an educational platform for maritime communication that uses several types of learning material, such as videos, transcripts, presentations, documents, images and chatbot content. Before this project, the material lacked a centralized technical interface, which made it harder to search, organize and reuse content across different frontend applications. This thesis presents the design and implementation of a searchable digital database with API access for Digimar. The system consists of a Go based HTTP REST API, a PostgreSQL database, a static frontend console and a local Docker Compose setup. The API supports several resource types, including chapters, sections, content items, videos, transcripts, PowerPoint files, documents, images and chatbots. It also includes search across metadata and text fields, role based API keys, health and readiness endpoints, and documentation for the API and data model. The result is a working prototype that provides one shared backend for managing Digimar learning material. Most of the planned goals were completed, including storage of the planned content types, REST API access, search, access control, Docker based local development, documentation and a frontend tool for manual operation. The planned PDF to markdown conversion automation was not completed and remains future work. Other future improvements include more formal database migrations, improved file storage, search ranking based on user preferences and production concerns such as backups, caching and monitoring.