14. Weighted Residual Method : Least Square, Point Collocation, Sub Domain and Galerkin's Method

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  • Опубліковано 30 жов 2024

КОМЕНТАРІ • 12

  • @ahmetozbekler
    @ahmetozbekler 4 роки тому +3

    Thanks for all. You tell this perfectly. Everything is so clear.
    👍👏👏👏👌

  • @RameshThakur-us7ic
    @RameshThakur-us7ic 3 роки тому +1

    thank you sir, very clearly you have explained

  • @poojashivraj3196
    @poojashivraj3196 2 роки тому +1

    Sir thank you very much

  • @rutvikbade
    @rutvikbade 4 роки тому +2

    Hey! Thanks for the video and the plots.
    Can someone please explain why the value of y at x=0.5 is not same for exact and point collocation even if we force the residue to zero at x=0.5??

    • @nikjay_music
      @nikjay_music 3 роки тому

      same doubt

    • @exoplanetanime4453
      @exoplanetanime4453 Рік тому

      Keep in mind that y is the trial function so even if we force R to be 0 in x=a for example there is a low probability for y(a) = exact(a)

    • @angelmusonda7951
      @angelmusonda7951 Рік тому

      @@nikjay_music The residue we are minimising is that of the governing equation itself, not necessarily the residue in the field variable u(x).

  • @advancedappliedandpuremath
    @advancedappliedandpuremath 7 місяців тому

    Reference book please

  • @jayjayf9699
    @jayjayf9699 4 роки тому

    I don’t understand why you integrate the residual function