This dissertation addresses practical use of multiwavelets and outlier detection for troubled-cell indication for discontinuous Galerkin (DG) methods. For smooth solutions, the DG approximation converges to the exact solution with a high order of accuracy. However, problems may arise when shock waves or discontinuities appear: non-physical spurious oscillations are formed close to these discontinuous regions. These oscillations can be prevented by applying a limiter near these regions. One of the difficulties in using a limiter is identifying the difference between a true discontinuity and a local extremum of the approximation. Troubled-cell indicators can help to detect this difference and identify the discontinuous regions (so-called ’troubled cells’) where a limiter should be applied. In this dissertation, a multiwavelet formulation is used to decompose the DG approximation. The multiwavelet coefficients act as a troubled-cell indicator since they suddenly increase in the neighborhood of a discontinuity. This leads to the definition of a new multiwavelet indicator that detects elements as troubled if the coefficient is large enough in absolute value. Here, a problem-dependent parameter is needed to define the strictness of the indicator. To forgo the reliance on a parameter, a new outlier-detection algorithm is defined that uses boxplot theory. This method can also be applied to different troubled-cell indicators. Results are shown for regular one-dimensional and tensor-product two-dimensional meshes, as well as for irregular meshes in one dimension and triangular meshes in two dimensions.@en

In Vuik and Ryan [J. Comput. Phys., 270 (2014), pp. 138–160] we studied the
use of troubled-cell indicators for discontinuity detection in nonlinear hyperbolic partial differential equations and introduced a new multiwavelet technique to detect troubled cells. We found that these methods perform well as long as a suitable, problem-dependent parameter is chosen. This parameter is used in a threshold which decides whether or not to detect an element as a troubled cell. Until now, these parameters could not be chosen automatically. The choice of the parameter has an impact on the approximation: it determines the strictness of the troubled-cell indicator. An inappropriate choice of the parameter will result in the detection (and limiting) of too few or too many elements. The optimal parameter is chosen such that the minimal number of troubled cells is detected and the resulting approximation is free of spurious oscillations. In this paper we will see that for each troubled-cell indicator the sudden increase or decrease of the indicator value with respect to the neighboring values is important for detection. Indication basically reduces to detecting the outliers of a vector (one dimension) or matrix (two dimensions). This is done using Tukey’s boxplot approach to detect which coefficients in a vector are straying far beyond the others [J. W. Tukey, Exploratory Data Analysis, Addison-Wesley, 1977]. We provide an algorithm that can be applied to various troubled-cell indication variables. With this technique, the problem-dependent parameter that the
original indicator requires is no longer necessary as the parameter will be chosen automatically.@en

In general, solutions of nonlinear hyperbolic PDEs contain shocks or develop discontinuities. One option for improving the numerical treatment of the spurious oscillations that occur near these artifacts is through the application of a limiter. The cells where such treatment is necessary are referred to as troubled cells. In this article, we discuss the multiwavelet troubled-cell indicator that was introduced by Vuik and Ryan (J Comput Phys 270:138–160, 2014). We focus on the relation between the highest-level multiwavelet coefficients and jumps in (derivatives of) the DG approximation. Based on this information, we slightly modify the originalmultiwavelet troubled-cell indicator. Furthermore, we show onedimensional test cases using the modified multiwavelet troubled-cell indicator.

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