Hiller, Wolfgang

Lade...
Vorschaubild
Preferred name
Hiller, Wolfgang
Official Name
Hiller, Wolfgang

Einstellungen

Gerade angezeigt 1 - 3 von 3
  • Lade...
    Vorschaubild
    Some of the metrics are blocked by your 
    consent settings
    Item-typ:Veröffentlichung,
    Effiziente parallele Verfahren zur Lösung verteilter, dünnbesetzer Gleichungssysteme eines nichthydrostatischen Tsunamimodells
    (2013-09-17)
    Fuchs, Annika
    ;
    Schmidt, Alfred
    ;
    Hiller, Wolfgang
    ;
    Hiller, Wolfgang
    In the framework of this dissertation, the nonhydrostatic tsunami simulation model TsunAWI-NH was developed as a modular extension of the hydrostatic shallow water model TsunAWI by accounting for terms that are neglected in the hydrostatic approach. Applied on test cases depending on tank experiments, the comparison of hydrostatic and nonhydrostatic model results shows a significant improvement by using TsunAWI-NH. However, in each time step, a system of linear equations has to be solved. That results in a long computing time and an increased demand for memory resources. Several numerical techniques are investigated, e.g., sequential and parallel preconditioning methods applied to the Krylov subspace method FGMRES(m), domain decomposition techniques and resorting algorithms. A sophisticated implementation enables TsunAWI-NH to simulate complex tsunami scenarios. For some real tsunami events, the model results of TsunAWI-NH and TsunAWI are compared with observation data.
    Dissertation
      519  151
  • Lade...
    Vorschaubild
    Some of the metrics are blocked by your 
    consent settings
    Item-typ:Veröffentlichung,
    Adaptive Mesh Refinement Applied to Tsunami Modeling: TsunaFLASH
    (2010-07-29)
    Pranowo, Widodo Setiyo
    ;
    Behrens, Jörn
    ;
    Hiller, Wolfgang
    ;
    Hiller, Wolfgang
    The devastating Sumatra-Andaman tsunami of December 2004, is a milestone for the internationalcommunity striving to introduce measures to prevent hazards from (future) tsunamis. One of themeasures is numerical modeling which plays a key role for predictions as well as inundation mappingdevelopments.Numerical modeling has been used as a tool for analyzing and reconstructing tsunamis foralmost 40 years. Nowadays, many tsunami codes are available as open-source or free-ware andwidely used in the tsunami modeling community. Many numerical methods have been applied suchas finite difference, finite element and finite volume. The same applies to gridding methods, such asstructured and unstructured non-adaptive types.This thesis introduces a new triangle-based adaptive mesh finite element model for tsunamipropagation (and inundation) simulations. TsunaFLASH combines a numerical method developed inthe framework of the unstructured triangular element, yet non-adaptive, tsunami model TsunAWIwith adaptive mesh refinement capabilities provided by the library amatos. The methods are wellsuited for accurate resolution of localized features, maintaining computational efficiency in terms ofthe number of computations and the required memory.In this first developments of TsunaFLASH, a number of experiments have been performed fortesting. There are: An experiments on various initial conditions, from an analytical source up to acoupling to the sophisticated rupture generator RuptGen; experiments with diverse error estimatorsfor testing refinement criteria and adaptation algorithms; benchmark experiments using analyticalsolutions and field observations where the analytical solution is derived from the first benchmarkproblem from The International LongWaves reference; and the sea surface elevation in the field dataexperiment is used from the satellite tracks of Jason-1 and Topex for verification of the Sumatra-Andaman mega-tsunami 2004 event, while the water level reading of DART 23401 is used for the verification of the Andaman minor tsunami 2009.Some additional studies have been conducted to assess the physical background of tsunamissimulation and test proper supporting tools for TsunaFLASH. There experiments comprise sourcemodel reconstructions and simulations based upon these in the context of a probable worst casetsunami simulation for Padang; experiments to test the influence of different types of topographieson the inundation behavior; and an investigation of the most representative source model for theAndaman-Sumatra mega-tsunami of 2004. Finally, the ambiguity of the arrival time of the Javaminor tsunami 2009 is experimentally investigated.
    Dissertation
      560  376
  • Lade...
    Vorschaubild
    Some of the metrics are blocked by your 
    consent settings
    Item-typ:Veröffentlichung,
    Parallel Filter Algorithms for Data Assimilation in Oceanography
    (2004-02-12)
    Nerger, Lars
    ;
    Schröter, Jens
    ;
    Hiller, Wolfgang
    ;
    Hiller, Wolfgang
    A consistent systematic comparison of filter algorithms based on the Kalman filter and intended for data assimilation with large-scale nonlinear models is presented. Considered are the EnsembleKalman Filter (EnKF), the Singular Evolutive Extended Kalman (SEEK) filter, and the Singular Evolutive Interpolated Kalman (SEIK) filter. Within the two parts of this thesis, the filter algorithms are compared with a focus on their mathematical properties as Error Subspace KalmanFilters (ESKF). Further, the filters are studied as parallel algorithms. This study includes the development of an efficient framework for parallel filtering. In the first part, the filters are motivated in the context of statistical estimation. The unified interpretation as ESKF algorithms provides the basis for the consistent comparison of the filters. Numerical data assimilation experiments with a model based on the shallow water equations show how choices of the filter schemeand particular state ensembles for the filter initialization lead to variations of the data assimilation performance.The application of the three filter algorithms on parallel computers is studied in the second part. The parallelization possibilities of the different phases of the algorithms are examined. Further, a framework for parallel filtering is developed which allows to combine filter algorithms with existing numerical models requiring only minimal changes to the source code of the model.The framework is used to combine the parallel filters with the 3D finite element ocean model FEOM. Numerical data assimilation experiments are utilized to assess the parallel efficiency of the filtering framework and the parallel filters. The experiments yield an excellent parallel efficiency for the filtering framework. Further, the framework and the filter algorithms are well suited for application to realistic large-scale data assimilation problems.
    Dissertation
      349  218