I am trying to solve a transient heat equation with space dependent heat flux. The case setup is shown in figure below. The top surface has changing heat flux as boundary condition. Hole surface has heat flux set to 0.1, and side/bottom surface are kept fixed at 110 °C.
I am interested in temperature distribution after 1 second. After specifying the time steps (10) and size (0.1) and running the case, I am getting temperature distribution that does not seem right. Even if I increase number of steps (100) and size (0.01), the result remains the same. Below are temperature distributions for both timesteps.
Next thing I remeshed the geometry and observed both result for different mesh densities. There is difference in temperature but the result still looks incorrect. The temperature distribution for both meshes is seen below
If I run the case up until 800 seconds (steps=200, size=4) the temperatures start to approach towards the steady state distribution. These two look correct. So it looks like the error is only in the early seconds and I am not sure how to tackle this.
Do you maybe have any advices on how to improve this study. Is there some explanation for the strange temperature distribution and how to solve it? I feel I have some errors in my transient parameters or am using the wrong approach here. The simulation and solver blocks are shown below.
Code: Select all
Simulation
Max Output Level = 5
Coordinate System = Cartesian
Coordinate Mapping(3) = 1 2 3
Simulation Type = Transient !steady state
timestep intervals(1) = 10
timestep sizes(1) = 0.1
Output Intervals(1) = 1
Steady State Max Iterations = 1
Timestepping Method = BDF
BDF Order = 3
Solver Input File = new_sif.sif
Post File = coarse_transient10_bicgstabl.vtu
!Use Mesh Names = Logical True
!element="p:3"
End
Code: Select all
Solver 1
equation = Heat Equation
procedure = "HeatSolve" "HeatSolver"
variable = Temperature
exec solver = Always
stabilize = True
bubbles = False
lumped mass matrix = True
optimize bandwidth = True
steady state convergence tolerance = 1.0e-5
nonlinear system convergence tolerance = 1.0e-9
nonlinear system max iterations = 200
nonlinear system relaxation factor = 0.5
nonlinear system newton after iterations = 3
nonlinear system newton after tolerance = 1.0e-5
linear system solver = Iterative
linear system iterative method = BiCGStabl
linear system max iterations = 500
linear system convergence tolerance = 1.0e-10
bicgstabl polynomial degree = 2
linear system preconditioning = ILU3
linear system ilut tolerance = 1.0e-3
linear system abort not converged = False
linear system residual output = 10
linear system precondition recompute = 1
End
mabr