Browsing by Author "Rauhut, Angela C."

Now showing 1 - 2 of 2
  • Thumbnail Image
    ItemOpen Access
    Integrated deformation analysis of the Olympic Oval, Calgary
    (1987) Rauhut, Angela C.; Teskey, William F.
    In the past few years, survey determined deformations of engineering engineers structures repeated survey measurements alone. Today, it has been realized that additional data should be utilized to further improve the deformation analysis. In structural engineering it has been common for years to predict testing deformations of a structure from laboratory of the structure materials, the geometry of the structure and the loading of the structure using the displacement finite element method. In this thesis, the structural displacement solution is combined with the results from a geometric deformation analysis in an integrated deformation analysis. The load displacement behaviour of the structure is modelled by the displacement finite element method. The measured deformation data are incorporated into the analysis as weighted constraints using the method of least squares. Here, the method of integrated deformation analysis is derived for a three-dimensional frame structure. It then is applied to the Olympic Speedskating Oval in Calgary. It was found that the integrated analysis yields a more complete solution of the actual deformation behaviour of the structure under static loading than the individual analyses do.
  • Thumbnail Image
    ItemOpen Access
    Regularization methods for the solution of the inverse Stokes problem
    (1992) Rauhut, Angela C.; Schwarz, Klaus-Peter P.
    Several approaches with similar concepts for the regularization of improperly posed problems have been developed in different areas of science, especially in geophysics and mathematics. In mathematics, the solution approaches are based on Tikhonov's regularization [TIKHONOV, 1963] which a-priori defines some parameters of the unknown function. In geophysics, a regularization method based on classical logic has been proposed where probability statements are employed as a-priori information [TARANTOLA, 1987]. In surveying engineering, collocation is widely used to incorporate additional knowledge into the least squares solution [MORITZ, 1980; RAPP, 1985]. A theoretical comparison of some regularization methods is given in LOUIS [1989] and SANSO [1989]. However, these methods are seldom applied to actual data due to the enormous computational effort involved. This research compares several regularization methods for the solution of the inverse Stokes problem for gravity field determination from satellite altimeter data. The comparison is done from a theoretical point of view as well as by practical application. The theoretical comparison discusses equivalences and differences of the approaches. The application of the methods compares the numerical results obtained with the algorithms on two different data sets. The comparison of the regularization methods shows that the inversion of Stokes problem is only moderately unstable. Thus, a simple inversion routine works under favourable circumstances but provides no safeguard against instability. Tikhonov regularization with cross-validation is a user-independent methods and works well on all data sets. The truncated singular value decomposition gives good results only when the accuracy estimates of the singular values are adequate. Both these methods are very time-consuming due to the singular value decomposition routine. The probabilistic method reduces to a combined least squares adjustment for Gaussian statistics. It produces good results as long as the a-priori error estimates are correct. Collocation performs poorly on these small data sets. However, it is by far the fastest method when FFT algorithms are used. A method, which is fast and user-independent at the same time, would be ideal for gravity field determination from satellite altimeter data.