Sökning: "uncertainty reduction"

Visar resultat 1 - 5 av 114 avhandlingar innehållade orden uncertainty reduction.

  1. 1. Identification and synthesis of components for uncertainty propagation

    Författare :Mladen Gibanica; Chalmers University of Technology; []
    Nyckelord :NATURVETENSKAP; TEKNIK OCH TEKNOLOGIER; TEKNIK OCH TEKNOLOGIER; NATURAL SCIENCES; ENGINEERING AND TECHNOLOGY; ENGINEERING AND TECHNOLOGY; substructuring; system identification; interface reduction; uncertainty quantification; experimental methods; uncertainty propagation; Monte Carlo method; state-space models; surrogate modelling;

    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. 2. Hydro-Climatic Variability and Change in Central America : Supporting Risk Reduction Through Improved Analyses and Data

    Författare :Beatriz Quesada-Montano; Sven Halldin; Hugo G. Hidalgo; Ida K. Westerberg; Fredrik Wetterhall; Denis Hughes; Uppsala universitet; []
    Nyckelord :NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; Central America; climate variability; disaster risk reduction; droughts; drought indices; floods; hydrological model; process constraints; statistical downscaling; uncertainty; ungauged basins; water resources.; Hydrology; Hydrologi;

    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. 3. Nuclear data uncertainty quantification and data assimilation for a lead-cooled fast reactor : Using integral experiments for improved accuracy

    Författare :Erwin Alhassan; Henrik Sjöstrand; Rochman Dimitri; Michael Österlund; Stephan Pomp; Oscar Cabellos; Uppsala universitet; []
    Nyckelord :NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; Total Monte Carlo; ELECTRA; nuclear data; uncertainty propagation; integral experiments; nuclear data adjustment; uncertainty reduction;

    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

  4. 4. Uncertainty, Robustness and Sensitivity Reduction in the Design of Single Input Control Systems

    Författare :Kjell Nordström; Linköpings universitet; []
    Nyckelord :ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Uncertainty; Robustness; Sensitivity; Single input control systems;

    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

  5. 5. Multiscale Methods and Uncertainty Quantification

    Författare :Daniel Elfverson; Axel Målqvist; Frédéric Legoll; Uppsala universitet; []
    Nyckelord :NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; multiscale methods; finite element method; discontinuous Galerkin; Petrov-Galerkin; a priori; a posteriori; complex geometry; uncertainty quantification; multilevel Monte Carlo; failure probability; Beräkningsvetenskap med inriktning mot numerisk analys; Scientific Computing with specialization in Numerical Analysis;

    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