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    Direct Elliptic Equation Solvers with Low Memory Requirements

    Source: Monthly Weather Review:;1980:;volume( 108 ):;issue: 009::page 1402
    Author:
    Schoeberl, Mark R.
    DOI: 10.1175/1520-0493(1980)108<1402:DEESWL>2.0.CO;2
    Publisher: American Meteorological Society
    Abstract: Several simple modifications of the Lindzen-Kuo Gaussian elimination algorithm for solving elliptic differential equations are derived. These modifications greatly decrease the auxiliary memory requirements with only some increase in computation, thus making this method suitable for solving general elliptic equations over large grids.
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      Direct Elliptic Equation Solvers with Low Memory Requirements

    URI
    https://yetl.yabesh.ir/yetl1/handle/yetl/4200302
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    • Monthly Weather Review

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    contributor authorSchoeberl, Mark R.
    date accessioned2017-06-09T16:02:59Z
    date available2017-06-09T16:02:59Z
    date copyright1980/09/01
    date issued1980
    identifier issn0027-0644
    identifier otherams-59713.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4200302
    description abstractSeveral simple modifications of the Lindzen-Kuo Gaussian elimination algorithm for solving elliptic differential equations are derived. These modifications greatly decrease the auxiliary memory requirements with only some increase in computation, thus making this method suitable for solving general elliptic equations over large grids.
    publisherAmerican Meteorological Society
    titleDirect Elliptic Equation Solvers with Low Memory Requirements
    typeJournal Paper
    journal volume108
    journal issue9
    journal titleMonthly Weather Review
    identifier doi10.1175/1520-0493(1980)108<1402:DEESWL>2.0.CO;2
    journal fristpage1402
    journal lastpage1406
    treeMonthly Weather Review:;1980:;volume( 108 ):;issue: 009
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian