Partial derivative calculation for circular or iterative functions
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I have a question of partial derivatives for implicit functions. I have three equations:
$rho_k=rho_lfrac{lambda_l}{H_l}+rho_gfrac{(1-lambda_l)}{1-H_l}$
$Re=frac{rho_kv_mphi}{mu}$
$H_l=f(Re,lambda_l)$
$phi$ is a constant and $f()$ is a complex function. $rho_l,rho_g,lambda_l,v_m,mu$ are all functions of $P$ (and $Q$). I solve these iteratively for $H_l$ given $P$ and $Q$. Now I need $frac{partial H_l}{partial P}$. I do this by differentiating all three equations:
$frac{partial rho_k}{partial P}=frac{partial rho_k}{partial rho_l}frac{partial rho_l}{partial P}+frac{partial rho_k}{partial rho_g}frac{partial rho_g}{partial P}+frac{partial rho_k}{partial lambda_l}frac{partial lambda_l}{partial P}+frac{partial rho_k}{partial H_l}frac{partial H_l}{partial P}$
$frac{partial Re}{partial P}=frac{partial Re}{partial rho_k}frac{partial rho_k}{partial P}+frac{partial Re}{partial v_m}frac{partial v_m}{partial P}+frac{partial Re}{partial mu}frac{partial mu}{partial P}$
$frac{partial H_L}{partial P}=frac{partial H_L}{partial Re}frac{partial Re}{partial P}+frac{partial H_L}{partial lambda_l}frac{partial lambda_l}{partial P}$
I can solve these for $frac{partial H_L}{partial P}$ if I have all the other derivatives.
However I have a question on how I calculate some of the other derivatives needed, in particular $frac{partial rho_k}{partial lambda_l}$ ? Do I keep $H_l$ constant or do I need to take into consideration $frac{partial H_L}{partial lambda_l}$ ?
Mathematically, is $frac{partial rho_k}{partial lambda_l}$ equal to:
$rho_lfrac{2.0lambda_l}{H_l}-rho_gfrac{2.0(1.0-lambda_l)}{1.0-H_l}$, or
$rho_lfrac{2.0H_llambda_l-lambda_l^2frac{partial H_L}{partial lambda_l}}{H_l^2}-rho_gfrac{2.0(1.0-H_l)(1.0-lambda_l)+(1-lambda_l)^2frac{partial H_L}{partial lambda_l}}{(1.0-H_l)^2}$ ?
Neither of these formulations give the same analytical value of $frac{partial H_L}{partial P}$ as a numerical perturbation though, so I'm wondering if I am doing this all correctly.
systems-of-equations partial-derivative implicit-differentiation
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I have a question of partial derivatives for implicit functions. I have three equations:
$rho_k=rho_lfrac{lambda_l}{H_l}+rho_gfrac{(1-lambda_l)}{1-H_l}$
$Re=frac{rho_kv_mphi}{mu}$
$H_l=f(Re,lambda_l)$
$phi$ is a constant and $f()$ is a complex function. $rho_l,rho_g,lambda_l,v_m,mu$ are all functions of $P$ (and $Q$). I solve these iteratively for $H_l$ given $P$ and $Q$. Now I need $frac{partial H_l}{partial P}$. I do this by differentiating all three equations:
$frac{partial rho_k}{partial P}=frac{partial rho_k}{partial rho_l}frac{partial rho_l}{partial P}+frac{partial rho_k}{partial rho_g}frac{partial rho_g}{partial P}+frac{partial rho_k}{partial lambda_l}frac{partial lambda_l}{partial P}+frac{partial rho_k}{partial H_l}frac{partial H_l}{partial P}$
$frac{partial Re}{partial P}=frac{partial Re}{partial rho_k}frac{partial rho_k}{partial P}+frac{partial Re}{partial v_m}frac{partial v_m}{partial P}+frac{partial Re}{partial mu}frac{partial mu}{partial P}$
$frac{partial H_L}{partial P}=frac{partial H_L}{partial Re}frac{partial Re}{partial P}+frac{partial H_L}{partial lambda_l}frac{partial lambda_l}{partial P}$
I can solve these for $frac{partial H_L}{partial P}$ if I have all the other derivatives.
However I have a question on how I calculate some of the other derivatives needed, in particular $frac{partial rho_k}{partial lambda_l}$ ? Do I keep $H_l$ constant or do I need to take into consideration $frac{partial H_L}{partial lambda_l}$ ?
Mathematically, is $frac{partial rho_k}{partial lambda_l}$ equal to:
$rho_lfrac{2.0lambda_l}{H_l}-rho_gfrac{2.0(1.0-lambda_l)}{1.0-H_l}$, or
$rho_lfrac{2.0H_llambda_l-lambda_l^2frac{partial H_L}{partial lambda_l}}{H_l^2}-rho_gfrac{2.0(1.0-H_l)(1.0-lambda_l)+(1-lambda_l)^2frac{partial H_L}{partial lambda_l}}{(1.0-H_l)^2}$ ?
Neither of these formulations give the same analytical value of $frac{partial H_L}{partial P}$ as a numerical perturbation though, so I'm wondering if I am doing this all correctly.
systems-of-equations partial-derivative implicit-differentiation
How is $x_2$ both a function of $(x_1,y_1)$ and of $(P,Q)$? It seems you are abusing notation and using $x_2$ to refer to a variable, a function of $(x_1,x_2)$ and a function of $(P,Q)$. Sorting out the notation, and defining the functions more carefully might help. Perhaps an example might be helpful too.
– smcc
Nov 17 at 16:37
I have now added my real world example as my simplification using x and y might not have shown all the subtleties of the original problem.
– dacfer
Nov 17 at 17:27
In fact I removed the simplification. Just the real world problem there now.
– dacfer
Nov 17 at 17:43
add a comment |
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I have a question of partial derivatives for implicit functions. I have three equations:
$rho_k=rho_lfrac{lambda_l}{H_l}+rho_gfrac{(1-lambda_l)}{1-H_l}$
$Re=frac{rho_kv_mphi}{mu}$
$H_l=f(Re,lambda_l)$
$phi$ is a constant and $f()$ is a complex function. $rho_l,rho_g,lambda_l,v_m,mu$ are all functions of $P$ (and $Q$). I solve these iteratively for $H_l$ given $P$ and $Q$. Now I need $frac{partial H_l}{partial P}$. I do this by differentiating all three equations:
$frac{partial rho_k}{partial P}=frac{partial rho_k}{partial rho_l}frac{partial rho_l}{partial P}+frac{partial rho_k}{partial rho_g}frac{partial rho_g}{partial P}+frac{partial rho_k}{partial lambda_l}frac{partial lambda_l}{partial P}+frac{partial rho_k}{partial H_l}frac{partial H_l}{partial P}$
$frac{partial Re}{partial P}=frac{partial Re}{partial rho_k}frac{partial rho_k}{partial P}+frac{partial Re}{partial v_m}frac{partial v_m}{partial P}+frac{partial Re}{partial mu}frac{partial mu}{partial P}$
$frac{partial H_L}{partial P}=frac{partial H_L}{partial Re}frac{partial Re}{partial P}+frac{partial H_L}{partial lambda_l}frac{partial lambda_l}{partial P}$
I can solve these for $frac{partial H_L}{partial P}$ if I have all the other derivatives.
However I have a question on how I calculate some of the other derivatives needed, in particular $frac{partial rho_k}{partial lambda_l}$ ? Do I keep $H_l$ constant or do I need to take into consideration $frac{partial H_L}{partial lambda_l}$ ?
Mathematically, is $frac{partial rho_k}{partial lambda_l}$ equal to:
$rho_lfrac{2.0lambda_l}{H_l}-rho_gfrac{2.0(1.0-lambda_l)}{1.0-H_l}$, or
$rho_lfrac{2.0H_llambda_l-lambda_l^2frac{partial H_L}{partial lambda_l}}{H_l^2}-rho_gfrac{2.0(1.0-H_l)(1.0-lambda_l)+(1-lambda_l)^2frac{partial H_L}{partial lambda_l}}{(1.0-H_l)^2}$ ?
Neither of these formulations give the same analytical value of $frac{partial H_L}{partial P}$ as a numerical perturbation though, so I'm wondering if I am doing this all correctly.
systems-of-equations partial-derivative implicit-differentiation
I have a question of partial derivatives for implicit functions. I have three equations:
$rho_k=rho_lfrac{lambda_l}{H_l}+rho_gfrac{(1-lambda_l)}{1-H_l}$
$Re=frac{rho_kv_mphi}{mu}$
$H_l=f(Re,lambda_l)$
$phi$ is a constant and $f()$ is a complex function. $rho_l,rho_g,lambda_l,v_m,mu$ are all functions of $P$ (and $Q$). I solve these iteratively for $H_l$ given $P$ and $Q$. Now I need $frac{partial H_l}{partial P}$. I do this by differentiating all three equations:
$frac{partial rho_k}{partial P}=frac{partial rho_k}{partial rho_l}frac{partial rho_l}{partial P}+frac{partial rho_k}{partial rho_g}frac{partial rho_g}{partial P}+frac{partial rho_k}{partial lambda_l}frac{partial lambda_l}{partial P}+frac{partial rho_k}{partial H_l}frac{partial H_l}{partial P}$
$frac{partial Re}{partial P}=frac{partial Re}{partial rho_k}frac{partial rho_k}{partial P}+frac{partial Re}{partial v_m}frac{partial v_m}{partial P}+frac{partial Re}{partial mu}frac{partial mu}{partial P}$
$frac{partial H_L}{partial P}=frac{partial H_L}{partial Re}frac{partial Re}{partial P}+frac{partial H_L}{partial lambda_l}frac{partial lambda_l}{partial P}$
I can solve these for $frac{partial H_L}{partial P}$ if I have all the other derivatives.
However I have a question on how I calculate some of the other derivatives needed, in particular $frac{partial rho_k}{partial lambda_l}$ ? Do I keep $H_l$ constant or do I need to take into consideration $frac{partial H_L}{partial lambda_l}$ ?
Mathematically, is $frac{partial rho_k}{partial lambda_l}$ equal to:
$rho_lfrac{2.0lambda_l}{H_l}-rho_gfrac{2.0(1.0-lambda_l)}{1.0-H_l}$, or
$rho_lfrac{2.0H_llambda_l-lambda_l^2frac{partial H_L}{partial lambda_l}}{H_l^2}-rho_gfrac{2.0(1.0-H_l)(1.0-lambda_l)+(1-lambda_l)^2frac{partial H_L}{partial lambda_l}}{(1.0-H_l)^2}$ ?
Neither of these formulations give the same analytical value of $frac{partial H_L}{partial P}$ as a numerical perturbation though, so I'm wondering if I am doing this all correctly.
systems-of-equations partial-derivative implicit-differentiation
systems-of-equations partial-derivative implicit-differentiation
edited Nov 17 at 20:52
asked Nov 17 at 15:53
dacfer
689
689
How is $x_2$ both a function of $(x_1,y_1)$ and of $(P,Q)$? It seems you are abusing notation and using $x_2$ to refer to a variable, a function of $(x_1,x_2)$ and a function of $(P,Q)$. Sorting out the notation, and defining the functions more carefully might help. Perhaps an example might be helpful too.
– smcc
Nov 17 at 16:37
I have now added my real world example as my simplification using x and y might not have shown all the subtleties of the original problem.
– dacfer
Nov 17 at 17:27
In fact I removed the simplification. Just the real world problem there now.
– dacfer
Nov 17 at 17:43
add a comment |
How is $x_2$ both a function of $(x_1,y_1)$ and of $(P,Q)$? It seems you are abusing notation and using $x_2$ to refer to a variable, a function of $(x_1,x_2)$ and a function of $(P,Q)$. Sorting out the notation, and defining the functions more carefully might help. Perhaps an example might be helpful too.
– smcc
Nov 17 at 16:37
I have now added my real world example as my simplification using x and y might not have shown all the subtleties of the original problem.
– dacfer
Nov 17 at 17:27
In fact I removed the simplification. Just the real world problem there now.
– dacfer
Nov 17 at 17:43
How is $x_2$ both a function of $(x_1,y_1)$ and of $(P,Q)$? It seems you are abusing notation and using $x_2$ to refer to a variable, a function of $(x_1,x_2)$ and a function of $(P,Q)$. Sorting out the notation, and defining the functions more carefully might help. Perhaps an example might be helpful too.
– smcc
Nov 17 at 16:37
How is $x_2$ both a function of $(x_1,y_1)$ and of $(P,Q)$? It seems you are abusing notation and using $x_2$ to refer to a variable, a function of $(x_1,x_2)$ and a function of $(P,Q)$. Sorting out the notation, and defining the functions more carefully might help. Perhaps an example might be helpful too.
– smcc
Nov 17 at 16:37
I have now added my real world example as my simplification using x and y might not have shown all the subtleties of the original problem.
– dacfer
Nov 17 at 17:27
I have now added my real world example as my simplification using x and y might not have shown all the subtleties of the original problem.
– dacfer
Nov 17 at 17:27
In fact I removed the simplification. Just the real world problem there now.
– dacfer
Nov 17 at 17:43
In fact I removed the simplification. Just the real world problem there now.
– dacfer
Nov 17 at 17:43
add a comment |
1 Answer
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It turns out the first formulation for $frac{partial rho_k}{partial lambda_l}$ is correct, that is:
$rho_lfrac{2.0lambda_l}{H_l}-rho_gfrac{2.0(1.0-lambda_l)}{1.0-H_l}$
The errors with $frac{partial H_L}{partial P}$ were in the derivatives I was calculating for $H_l=f(Re,lambda_l)$. This is a graph which I was using Bezier functions to interpolate. This works well in 1d, but 2d Bezier interpolation causes noise, resulting in erroneous derivatives.
add a comment |
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
0
down vote
It turns out the first formulation for $frac{partial rho_k}{partial lambda_l}$ is correct, that is:
$rho_lfrac{2.0lambda_l}{H_l}-rho_gfrac{2.0(1.0-lambda_l)}{1.0-H_l}$
The errors with $frac{partial H_L}{partial P}$ were in the derivatives I was calculating for $H_l=f(Re,lambda_l)$. This is a graph which I was using Bezier functions to interpolate. This works well in 1d, but 2d Bezier interpolation causes noise, resulting in erroneous derivatives.
add a comment |
up vote
0
down vote
It turns out the first formulation for $frac{partial rho_k}{partial lambda_l}$ is correct, that is:
$rho_lfrac{2.0lambda_l}{H_l}-rho_gfrac{2.0(1.0-lambda_l)}{1.0-H_l}$
The errors with $frac{partial H_L}{partial P}$ were in the derivatives I was calculating for $H_l=f(Re,lambda_l)$. This is a graph which I was using Bezier functions to interpolate. This works well in 1d, but 2d Bezier interpolation causes noise, resulting in erroneous derivatives.
add a comment |
up vote
0
down vote
up vote
0
down vote
It turns out the first formulation for $frac{partial rho_k}{partial lambda_l}$ is correct, that is:
$rho_lfrac{2.0lambda_l}{H_l}-rho_gfrac{2.0(1.0-lambda_l)}{1.0-H_l}$
The errors with $frac{partial H_L}{partial P}$ were in the derivatives I was calculating for $H_l=f(Re,lambda_l)$. This is a graph which I was using Bezier functions to interpolate. This works well in 1d, but 2d Bezier interpolation causes noise, resulting in erroneous derivatives.
It turns out the first formulation for $frac{partial rho_k}{partial lambda_l}$ is correct, that is:
$rho_lfrac{2.0lambda_l}{H_l}-rho_gfrac{2.0(1.0-lambda_l)}{1.0-H_l}$
The errors with $frac{partial H_L}{partial P}$ were in the derivatives I was calculating for $H_l=f(Re,lambda_l)$. This is a graph which I was using Bezier functions to interpolate. This works well in 1d, but 2d Bezier interpolation causes noise, resulting in erroneous derivatives.
answered Nov 19 at 21:30
dacfer
689
689
add a comment |
add a comment |
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How is $x_2$ both a function of $(x_1,y_1)$ and of $(P,Q)$? It seems you are abusing notation and using $x_2$ to refer to a variable, a function of $(x_1,x_2)$ and a function of $(P,Q)$. Sorting out the notation, and defining the functions more carefully might help. Perhaps an example might be helpful too.
– smcc
Nov 17 at 16:37
I have now added my real world example as my simplification using x and y might not have shown all the subtleties of the original problem.
– dacfer
Nov 17 at 17:27
In fact I removed the simplification. Just the real world problem there now.
– dacfer
Nov 17 at 17:43