On local finite element refinements in multiscale air quality modeling
Variable resolution is a highly desirable property in air quality models, especially in regional applications. Resolution can be increased in dense source regions by using finite element refinements. Here, the important principles that must be obeyed at refinement boundaries are discussed. Mass cons...
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Veröffentlicht in: | Environmental software 1994, Vol.9 (1), p.61-66 |
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creator | Odman, Mehmet T. Russell, Armistead G. |
description | Variable resolution is a highly desirable property in air quality models, especially in regional applications. Resolution can be increased in dense source regions by using finite element refinements. Here, the important principles that must be obeyed at refinement boundaries are discussed. Mass conservation is achieved by making the element basis functions continuous. Constraint relations that assure continuity for various refinement ratios are described. A second issue is to keep the refinement boundaries free of noise. Since coarse and fine elements act like different media, aliasing errors usually lead to noise waves. A non-linear filter is used to remove some of this noise. Tests are conducted with different refinement ratios to see the effect of increased resolution on accuracy. In general, refinements increase accuracy by reducing diffusion errors. The peak concentrations are overpredicted during the transition from the fine to the coarse grid. These overpredictions are smaller when the refinements are gradual. |
doi_str_mv | 10.1016/0266-9838(94)90015-9 |
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Resolution can be increased in dense source regions by using finite element refinements. Here, the important principles that must be obeyed at refinement boundaries are discussed. Mass conservation is achieved by making the element basis functions continuous. Constraint relations that assure continuity for various refinement ratios are described. A second issue is to keep the refinement boundaries free of noise. Since coarse and fine elements act like different media, aliasing errors usually lead to noise waves. A non-linear filter is used to remove some of this noise. Tests are conducted with different refinement ratios to see the effect of increased resolution on accuracy. In general, refinements increase accuracy by reducing diffusion errors. The peak concentrations are overpredicted during the transition from the fine to the coarse grid. 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subjects | Computer aided analysis Computer software Constraint theory Error analysis Finite element method Finite element refinements Mathematical models multiscale modeling Signal filtering and prediction Spurious signal noise variable resolution |
title | On local finite element refinements in multiscale air quality modeling |
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