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A time-spectral approach to numerical weather prediction
KTH, School of Electrical Engineering (EES), Fusion Plasma Physics.
KTH, School of Electrical Engineering (EES), Fusion Plasma Physics.
2018 (English)In: Computer Physics Communications, ISSN 0010-4655, E-ISSN 1879-2944, Vol. 226, p. 127-135Article in journal (Refereed) Published
Abstract [en]

Finite difference methods are traditionally used for modelling the time domain in numerical weather prediction (NWP). Time-spectral solution is an attractive alternative for reasons of accuracy and efficiency and because time step limitations associated with causal CFL-like criteria, typical for explicit finite difference methods, are avoided. In this work, the Lorenz 1984 chaotic equations are solved using the time-spectral algorithm GWRM (Generalized Weighted Residual Method). Comparisons of accuracy and efficiency are carried out for both explicit and implicit time-stepping algorithms. It is found that the efficiency of the GWRM compares well with these methods, in particular at high accuracy. For perturbative scenarios, the GWRM was found to be as much as four times faster than the finite difference methods. A primary reason is that the GWRM time intervals typically are two orders of magnitude larger than those of the finite difference methods. The GWRM has the additional advantage to produce analytical solutions in the form of Chebyshev series expansions. The results are encouraging for pursuing further studies, including spatial dependence, of the relevance of time-spectral methods for NWP modelling. Program summary: Program Title: Time-adaptive GWRM Lorenz 1984 Program Files doi: http://dx.doi.org/10.17632/4nxfyjj7nv.1 Licensing provisions: MIT Programming language: Maple Nature of problem: Ordinary differential equations with varying degrees of complexity are routinely solved with numerical methods. The set of ODEs pertaining to chaotic systems, for instance those related to numerical weather prediction (NWP) models, are highly sensitive to initial conditions and unwanted errors. To accurately solve ODEs such as the Lorenz equations (E. N. Lorenz, Tellus A 36 (1984) 98–110), small time steps are required by traditional time-stepping methods, which can be a limiting factor regarding the efficiency, accuracy, and stability of the computations. Solution method: The Generalized Weighted Residual Method, being a time-spectral algorithm, seeks to increase the time intervals in the computation without degrading the efficiency, accuracy, and stability. It does this by postulating a solution ansatz as a sum of weighted Chebyshev polynomials, in combination with the Galerkin method, to create a set of linear/non-linear algebraic equations. These algebraic equations are then solved iteratively using a Semi Implicit Root solver (SIR), which has been chosen due to its enhanced global convergence properties. Furthermore, to achieve a desired accuracy across the entire domain, a time-adaptive algorithm has been developed. By evaluating the magnitudes of the Chebyshev coefficients in the time dimension of the solution ansatz, the time interval can either be decreased or increased.

Place, publisher, year, edition, pages
Elsevier, 2018. Vol. 226, p. 127-135
Keywords [en]
Chebyshev polynomials, NWP, Spectral, Time-spectral, Weighted residual methods
National Category
Physical Sciences
Identifiers
URN: urn:nbn:se:kth:diva-227591DOI: 10.1016/j.cpc.2018.01.010ISI: 000428483000011Scopus ID: 2-s2.0-85042148545OAI: oai:DiVA.org:kth-227591DiVA, id: diva2:1204949
Note

QC 20180509

Available from: 2018-05-09 Created: 2018-05-09 Last updated: 2024-03-18Bibliographically approved
In thesis
1. Time Spectral Methods - Towards Plasma Turbulence Modelling
Open this publication in new window or tab >>Time Spectral Methods - Towards Plasma Turbulence Modelling
2021 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Energy comes in two forms; potential energy and kinetic energy. Energyis stored as potential energy and released in the form of kinetic energy. This process of storage and release is the basic strategy of all energy alternatives in use today. This applies to solar, wind, fossil fuels, and the list goes on. Most of these come in diluted and scarce forms allowing only a portion of the energy to be used, which has prompted the quest for the original source, the Sun.

As early as 1905 in the work by Albert Einstein on the connection between mass and energy, it has been seen theoretically that energy can be extracted from the process of fusing lighter elements into heavier elements. Later, this process of fusion was discovered to be the very source powering the Sun. Almost a century later, the work continues to make thermonuclear fusion energy a reality.

Looking closer at the Sun, we see that it consists of a hot burning gas subject to electromagnetic fields, i.e. a plasma. The plasma in the Sun is contained by the massive gravitational force which allows for fusion to be created in a stable and continuous process. Taking inspiration from the Sun we see that a hot plasma and its containment are key to achieving fusion. The gravitational force is not present on Earth, and creating it artificially is, a sof today, an insurmountable task. Fortunately, the plasma can be contained in another way; with magnetic fields.

The challenges of making fusion a viable energy source are numerous and diverse. To deal with these challenges there are several fields of fusion research; engineering, physics, and numerical analysis. These of course overlap, but serve to illustrate the focus of different groups. This thesis work is focused on the latter two, physics and numerical analysis.

The containment of the plasma in a fusion device is degraded by drift wave turbulence. The turbulence in the plasma occurs on the micro-scale, namely on the scale of particles travelling around the magnetic field lines. The physics behind turbulence and the drift waves responsible is a rich field with many future topics.

Since the micro-turbulence can quickly grow and diffuse plasma throughout the device in a matter of micro-seconds, it becomes a difficult challenge to numerically resolve the turbulence over a longer span of time. The typical confinement times required in a fusion device is on the order of several seconds. Thus, the main focus of this thesis is on developing a numerical method that can effectively resolve the plasma physics over longer time-intervals. To this effect, a Time-Spectral method has been developed that utilizes the advantageous properties of spectral methods to all domains, specifically the temporal domain. The numerical method has been implemented on compressible Navier-Stokes, ideal magnetohydrodynamics (MHD), and a toroidal two-fluid plasma turbulence model called the Weiland model.

Place, publisher, year, edition, pages
KTH Royal Institute of Technology, 2021. p. 107
Series
TRITA-EECS-AVL ; 2021:7
Keywords
Fusion, Turbulence, Micro-instabilities, Time-spectral, Navier-Stokes, MHD, Weiland model
National Category
Computational Mathematics Astronomy, Astrophysics and Cosmology
Research subject
Electrical Engineering
Identifiers
urn:nbn:se:kth:diva-289443 (URN)
Public defence
2021-02-18, https://kth-se.zoom.us/webinar/register/WN_Bgjx0PKrRv6FdKwolR2Spg, Stockholm, 15:00 (English)
Opponent
Supervisors
Note

QC 20210129

Available from: 2021-01-29 Created: 2021-01-29 Last updated: 2024-11-26Bibliographically approved

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Scheffel, JanLindvall, Kristoffer

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