MATLAB: How to solve a system of Nonlinear Differential Equations?

In summary, the conversation discusses the task of solving a system of nonlinear equations for simulating the growth of a solid tumor using MATLAB. The system includes five unknowns, f, g, m, p, and n, which represent different aspects of the tumor. Wise et al have derived a hard-to-solve system for simulating the tumor, which involves equations for each of the unknowns and outer boundary conditions. The speaker is asking for guidance on how to solve this system using MATLAB.
  • #1
aroniotis
2
0
Hello to everybody,
I'm very new to solving ODES and equations with MATLAB. I have been asked to solve a system of nonlinear equations for simulating the growth of a solid tumor.

Assuming that we have the 5 unknowns which are dxd arrays: f,g,m,p and n.
f(x,t) is the volume fraction of tumor (the fraction of tumor tissue against water and healthy tissue)
g(x,t) is the volume fraction of dead tumor tissue (the fraction of dead tumor cells, i.e. necrotic cells)
m(x,t) is a variable call "cell chemical potential"
p(x,t) is the cell-to-cell solid pressure
n(x,t) is the concentration of nutrients

Then Wise et al (An adaptive multigrid algorithm for simulating solid tumor growth using mixture models, doi: 10.1016/j.mcm.2010.07.007) have derived that the tumor can be simulated by solving the following hard-to-solve system:

(1) df/dt=M*div(f*grad (m))+n*(f-g)-lamdaL*g-div(-grad(p)+m*grad(f))
(2) m=f^3-1.5*f^2+0.5*f-div(grad(f))
(3) dg/dt=M*div(g*grad (m))+heaviside(nN-n)*(f-g)-lamdaL*g-div(-grad(p)+m*grad(f))
(4) -div(grad(p))=n*(f-g)-lamdaL-div(m*grad(f))
(5) 0=div(D*grad(n))+(vp)*(nc-n)-n(f-g)

For outer boundary conditions m=p=q=0, n=1, z*grad(f)=0, where z is the outward pointing unit normal.
(The rest parameters that have not been mentioned are scalars).

Could someone please show me the way how to solve that with Matlab?
 
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  • #2
Any idea?
 

What is MATLAB and how is it used to solve a system of Nonlinear Differential Equations?

MATLAB is a high-level programming language and interactive environment used for numerical computation, visualization, and programming. It has built-in functions and tools specifically designed for solving systems of nonlinear differential equations. These equations involve variables that change with respect to time and have nonlinear relationships between them.

What is the process for solving a system of Nonlinear Differential Equations in MATLAB?

The first step is to define the system of equations using the symbolic math toolbox in MATLAB. This allows the equations to be represented symbolically rather than numerically. Then, use the "dsolve" function to solve the system of equations. This function uses various numerical methods to find a solution. Finally, use the "ode45" function to solve the differential equations numerically and plot the results.

How do I know if the solution obtained from MATLAB is accurate?

One way to check the accuracy of the solution is to vary the initial conditions and see if the solution changes significantly. Another method is to use the "odeplot" function to plot the solution and visually inspect it for any unexpected behavior. Additionally, you can compare the numerical solution to an analytical solution, if one exists.

Can I solve a system of Nonlinear Differential Equations with more than two variables in MATLAB?

Yes, MATLAB can handle systems of nonlinear differential equations with any number of variables. The process for solving these equations is the same as for a system with two variables. However, as the number of equations and variables increases, the complexity of the problem also increases, and it may take longer for MATLAB to find a solution.

Can I use MATLAB to solve a system of Nonlinear Differential Equations with boundary conditions?

Yes, MATLAB has functions specifically designed for solving boundary value problems, which involve finding a solution to differential equations with given boundary conditions. These functions include "bvpinit" to specify initial conditions and "bvp4c" to solve the boundary value problem numerically. It is important to note that these methods may require more computational time and resources compared to solving initial value problems.

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