Sökning: "experimental data"
Visar resultat 21 - 25 av 2016 uppsatser innehållade orden experimental data.
21. Drop-weight impact tests on reinforced concrete beams
Master-uppsats, KTH/BetongbyggnadSammanfattning : This master's thesis aimed to investigate the behaviour of reinforced concrete beams under dynamic loading conditions, specifically focusing on understanding shear failure. The study was conducted with KTH Royal Institute of Technology, the Swedish Fortifications Agency, and Tyréns. LÄS MER
22. Computational Fluid Dynamics and Modeling of a Free Surface Flow
Master-uppsats, KTH/Skolan för teknikvetenskap (SCI)Sammanfattning : This project deals with the CFD modelling of a free surface flow. The aim is to develop and validate a fast and accurate numerical model for stratified two-phase flows. Volume of Fluid (VOF) multiphase model is employed. The purpose is to use the developed numerical model for the design of an element within a compact nuclear reactor. LÄS MER
23. Creating a High-Throughput Workflow for Automated Peptide Characterization using LC-MS
Master-uppsats, Lunds universitet/Centrum för analys och syntesSammanfattning : In the early stage of a drug discovery project, there is a need for efficient methods that can analyse peptides in short time. This includes methods that confirm the peptide’s identity and estimates its relative purity in an efficient and reliable way. LÄS MER
24. Numerical Study on Acoustic Phenomena in Cavities for Aero-engine Applications
Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)Sammanfattning : For about seventy years, noise generated by grazing flow past a cavity has been thoroughly studied. Yet, a coherent theory that describes such phenomena is missing. Lately, this phenomena started to be investigated in bleeding systems of aero-engines. LÄS MER
25. Generating an Interpretable Ranking Model: Exploring the Power of Local Model-Agnostic Interpretability for Ranking Analysis
Magister-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskapSammanfattning : Machine learning has revolutionized recommendation systems by employing ranking models for personalized item suggestions. However, the complexity of learning-to-rank (LTR) models poses challenges in understanding the underlying reasons contributing to the ranking outcomes. LÄS MER