Solving a Nonlinear PDE in Maple 18 using Numeric Methods

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SUMMARY

The discussion focuses on solving a nonlinear partial differential equation (PDE) using Maple 18's numeric methods. The user encounters convergence issues while attempting to compute a solution for the PDE defined as u_x + u_t - (u_{xt})^2 = u. The provided code includes boundary and initial conditions, but the Newton iteration fails to converge, prompting the user to seek alternative methods, such as the Runge-Kutta method, for achieving convergence.

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  • Familiarity with Maple 18 programming and syntax
  • Understanding of partial differential equations (PDEs)
  • Knowledge of numerical methods for PDEs, specifically Newton's method
  • Basic concepts of boundary and initial value problems
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  • Research the implementation of the Runge-Kutta method in Maple 18
  • Explore alternative numerical methods for solving nonlinear PDEs
  • Learn about convergence criteria and techniques for Newton's method
  • Investigate the use of adaptive mesh refinement in numerical PDE solutions
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Mathematicians, engineers, and researchers working with nonlinear PDEs, as well as students and professionals seeking to enhance their skills in numerical methods using Maple 18.

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I wrote the next code:
Code:
restart;
pde := diff(u(x, t), t)+diff(u(x, t), x)-(diff(diff(u(x, t), x), t))^2 = u(x, t);
    
tmax := 0.5e-1; 
xmin := 0; 
xmax := 1;
 N := 10;
 bc1 := du(xmin, t) = 0;
 bc2 := u(xmax, t) = 0;
 ic1 := u(x, 0) = 1; 
ic2 := du(x, 0) = 2;
 bcs := {u(x, 0) = rhs(ic1), (D[1](u))(0, t) = rhs(bc1)};

pds := pdsolve(pde, bcs, numeric, time = t, range = 0 .. xmax, indepvars = [x, t], spacestep = (1/1000)*xmax, timestep = (1/1000)*tmax);
 
pds:-plot3d(t = 0 .. tmax, x = xmin .. xmax, axes = boxed, orientation = [-150, 80], shading = zhue, transparency = .1)

And I get the next two errors:
Code:
Error, (in pdsolve/numeric/plot3d) unable to compute solution for t>HFloat(0.0):
Newton iteration is not converging

Is there a method that will converge for this PDE?

Maybe Runga Kutta?

Thanks in advance.

Btw, the PDE that I had in mind is: u_x+u_t - (u_{xt})^2 = u a nonlinear pde.
 
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