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Linearisation has many different meanings.. one is spectral methods, it is also used to linearize the system.
The others are numerical schemes like finite difference methods. Like forward, backward,
forward difference: U = [ U_(t+1) - U_t ] / dt
backward difference: U = [ U_t - U_(t-1) ] / dt
Basically, you try to model the higher order terms, derivatives etc with simple algebraic functions.
When you linearize then you get truncation errors and also an artificial viscosity term arises called CFL thanks to the numerical methods and this term has the effect of edge smoothing and determines the convergence or divergence of the problem based on step time. Because we want to reduce the computational time from orderOf(N^2) to N-log(N).

I need to go through my notices. BTW which text books are you following? and is it graduate or undergrad level course?

:hitwall::hitwall::hitwall:
 
Tana nana din din lala Lala lalaaaaa :D


Dafa-ria her back.... :D

Haha. No actually i am the one spreading the virus ....
 
Those are definitely to our east. Hands down. No contest.

On serious note* we are far better nation as compare to our humsaye in east.
We lacked a good leadership all these years :(

Haha. No actually i am the one spreading the virus ....

Raat ko jo sisha night Manai this yeh to hona tha
 
Raat ko jo sisha night Manai this yeh to hona tha

Dafa-ria ka virus baaji.. kia ho gya. 48 ki umar me satya gae ho kaa...

Btw shesha chelum jaisa hota ??


Sis is allergic to bullshit , and you posted lot of it in that single post
 
Linearisation has many different meanings.. one is spectral methods, it is also used to linearize the system.
The others are numerical schemes like finite difference methods. Like forward, backward,
forward difference: U = [ U_(t+1) - U_t ] / dt
backward difference: U = [ U_t - U_(t-1) ] / dt
Basically, you try to model the higher order terms, derivatives etc with simple algebraic functions.
When you linearize then you get truncation errors and also an artificial viscosity term arises called CFL thanks to the numerical methods and this term has the effect of edge smoothing and determines the convergence or divergence of the problem based on step time. Because we want to reduce the computational time from orderOf(N^2) to N-log(N).

I need to go through my notices. BTW which text books are you following? and is it graduate or undergrad level course?
This is exactly what we are doing. This has been covered in the last lecture though.
Undergrad Level.
CFD by Hoffman.
CFD An Into By JD Anderson.

Hey can i get your email? I am thinking of taking up FYP in CFD, and i could always do with little help.
 
This is exactly what we are doing. This has been covered in the last lecture though.
Undergrad Level.
CFD by Hoffman.
CFD An Into By JD Anderson.

Hey can i get your email? I am thinking of taking up FYP in CFD, and i could always do with little help.
Oh I also followed JD Andersons during my undergrad. and then by Hirsch (a bit more advanced) at Masters.
okay I will give you my email :)
 
Why sis?

Abhi tu Turbulence baqi hai :partay:

I am gonna leave the thread in protest. :(

Dafa-ria ka virus baaji.. kia ho gya. 48 ki umar me satya gae ho kaa...

Btw shesha chelum jaisa hota ??



Sis is allergic to bullshit , and you posted lot of it in that single post

One of us miss the point :lol:
 
Sis is allergic to bullshit , and you posted lot of it in that single post

That too when it’s 3:05 am here.
 
I am gonna leave the thread in protest. :(
Please tell me which part did you not understand in that, I can elaborate dobara phir se try :-)
 
He’s my favorite ❤️
243BCB0B-20CF-49ED-B1C6-CAAE6A87A060.jpeg


Please tell me which part did you not understand in that, I can elaborate dobara phir se try :-)

It’s not about understanding but how boring it is.
 

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