Hi,

im trying to calculate the divergence of a 3x3 tensor. The tensor is created by the following code:

with(VectorCalculus);
with(LinearAlgebra);
SetCoordinates(cartesian[x, y, z]);
alias(u = u(t, x, y, z), v = v(t, x, y, z), w = w(t, x, y, z)); alias(eta = eta(t, x, y, z));
U := VectorField(`<,>`(u, v, w));
M := OuterProductMatrix(U, U);

The last command gives a 3x3 tensor:

Now I want to calculate the divergence of this tensor. But the function "Divergence" (VectorCalculus-package) is only able to handle vectors. A workaround would be the extract the data row by row -> convert it to a vector -> calculate the divergence.

Is there a more elegant possibility to do this?

Thanks in advance.

Hi,

for my simulation I have to calculate several gradients and jacobian matrices. The equations are quite complex and with my current setup hard to read.

Here is some exampel code:

restart;
with(VectorCalculus);
SetCoordinates(cartesian[x, y, z]);
alias(u = u(t, x, y, z), v = v(t, x, y, z), w = w(t, x, y, z)); alias(eta = eta(t, x, y, z));
U := VectorField(`<,>`(u, v, w));
Divergence(U);
Jacobian(U);
Diff(U, t);

The Divergence operator gives me a very compact result:

But Jaobian and Diff look like:

To achive a better readability I want to do two things (if possible):

1) hide the independet variables (t,x,y,z) in the result of Jacobian, Diff

2) display the result of Diff in a row vector (3x1) instead

Is this possible?

Thanks in advance for your help

Hi,

I'm trying to solve the following non-linear ODE numerically:

by ececuting

but maple gives me this error-message:

"Error, (in dsolve/numeric/make_proc) Could not convert to an explicit first order system due to 'RootOf'"

I couldnt find any useful information in the manual. What does this error mean? Is there something wrong with my maple code or is there just no solution for this particulare differential equation?

Thanks in advance

Hi,

I'm trying to fit some parameters to the data of multiple slightly different experiments.

I've written a function which returns the sums of the error for all experiments.

The function which has to be minimized does the following:

1) Set parameters for the model ODE based on the input parameters

2) calculate the difference (numeric solution of ODE <-> experimentel data)

3) repeat step 1+2 for all experiments

4) return the sum of all differences

The function works as aspected. But when I try to minimize it by calling:

I got an error:

"Error, (in dsolve/numeric/process_parameters) parameter values must evaluate to numeric, got A = A"

For some reason Maple isnt able to set the new parameters of the ODE.

Anyone got an idea how to fix this?

Thanks in advance.

Hi,

I'm trying to solve the following differential equation numerically with dsolve:

but dsolve gives me this error:

> res := dsolve(DGL, numeric, parameters = [y0, A, B, C, E]);
Error, (in DEtools/convertsys) unable to convert to an explicit first-order system

I think the problem is that I use the wrong solver. Does Maple provide a solver which is capable of solving this kind of equations (nonlinear ODE)?

Thanks in advance!