Sökning: "uncertainty reduction"
Visar resultat 1 - 5 av 114 avhandlingar innehållade orden uncertainty reduction.
Sammanfattning : For automotive structures, built-up of hundreds of components with property spread, knowing the effects of component variability and its propagation through the system assembly is important in order to mitigate noise and vibration problems. To increase the understanding of how the spread propagates into variability in built-up structures, both experimental and computational aspects are considered in this thesis. LÄS MER
2. Hydro-Climatic Variability and Change in Central America : Supporting Risk Reduction Through Improved Analyses and Data
Sammanfattning : Floods and droughts are frequent in Central America and cause large social, economic and environmental impacts. A crucial step in disaster risk reduction is to have a good understanding of the causing mechanisms of extreme events and their spatio-temporal characteristics. LÄS MER
3. Nuclear data uncertainty quantification and data assimilation for a lead-cooled fast reactor : Using integral experiments for improved accuracy
Sammanfattning : For the successful deployment of advanced nuclear systems and optimization of current reactor designs, high quality nuclear data are required. Before nuclear data can be used in applications they must first be evaluated, tested and validated against a set of integral experiments, and then converted into formats usable for applications. LÄS MER
Sammanfattning : Feedback control of systems modelled as single input, time invariant, linear and continuous time systems is the subject of this thesis. A growing interest in the design of feedback control systems that can cope with model uncertainties has been the motivation for the study. LÄS MER
Sammanfattning : In this thesis we consider two great challenges in computer simulations of partial differential equations: multiscale data, varying over multiple scales in space and time, and data uncertainty, due to lack of or inexact measurements.We develop a multiscale method based on a coarse scale correction, using localized fine scale computations. LÄS MER