CalculiX Thermal Analysis

Category: Analysis | Integrated 2026-04-06
CAE visualization for calculix thermal theory - technical simulation diagram
CalculiX Thermal Analysis

CalculiX Thermal Analysis: Theoretical Foundations

(CalculiX Thermal Analysis: Theoretical Foundations Section)

Computational Methods for CalculiX Thermal Analysis

Details of Numerical Methods

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Specifically, what algorithm is used to solve the CalculiX thermal analysis?


๐ŸŽ“

Let me explain the key points of the numerical methods and implementation for CalculiX thermal analysis.


๐Ÿง‘โ€๐ŸŽ“

After hearing this, I finally understand why the numerical methods and implementation for thermal analysis are so important!


Compilation and Build

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I've heard of "compilation and build," but I might not fully understand it...


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Building from source code uses CMake or dedicated build systems (like OpenFOAM's wmake). Proper version management of dependency libraries (MPI, PETSc, BLAS/LAPACK, etc.) is crucial. A Linux environment is recommended, but it's also possible to set up on Windows using WSL2 or Docker containers.


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So, cutting corners during the build from source part will come back to bite you later. I'll keep that in mind!


Input File Structure

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Are there any points to note when transferring data between different software?


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Understanding the structure of case files and the main parameter settings is the first step in implementation. The format of dictionary files (dict) or command files is specific to each software, and editing from official tutorial templates is efficient.



Script Automation

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I've heard of "script automation," but I might not fully understand it...


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Automating parameter studies with Python or Bash scripts is key to improving productivity. Also consider utilizing wrapper tools like PyFoam or cfMesh.



Debugging and Development Environment


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Memory leak detection and debugging with GDB, Valgrind, and AddressSanitizer are effective. Utilize the remote debugging features of IDEs (VSCode, CLion) to set up an efficient development environment. Introduce unit testing frameworks (Google Test, pytest) to automate regression testing.



Solver Settings and Algorithms

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I'd like to know a bit more about what's happening behind the scenes of the calculation!



OpenFOAM Solver Selection Guidelines

๐Ÿง‘โ€๐ŸŽ“

What exactly do you mean by solver selection guidelines?


SolverApplicationEquation System
simpleFoamSteady incompressible turbulenceSIMPLE
pimpleFoamUnsteady incompressiblePIMPLE (PISO+SIMPLE)
interFoamTwo-phase flow (VOF)MULES
rhoSimpleFoamSteady compressibleSIMPLE
buoyantSimpleFoamNatural ConvectionSIMPLE+Boussinesq
reactingFoamCombustionPIMPLE+Chemical Reaction

CalculiX Input File Structure

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What exactly do you mean by input file structure?


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```

*NODE


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1, 0.0, 0.0, 0.0

...


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*ELEMENT, TYPE=C3D8

1, 1, 2, 3, 4, 5, 6, 7, 8


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...

*MATERIAL, NAME=STEEL


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*ELASTIC

210000., 0.3


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*DENSITY

7.85e-9


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*STEP

*STATIC


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*BOUNDARY

1, 1, 3


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*CLOAD

100, 2, 1000.


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*END STEP

```


๐Ÿง‘โ€๐ŸŽ“

Ah, I see! So that's how the solver selection guidelines work.



Code_Aster Command File Structure

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Next is the topic of command file structure. What's it about?


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```

DEBUT()


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MAIL = LIRE_MAILLAGE()

MODELE = AFFE_MODELE(MAILLAGE=MAIL, ...)


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RESULT = MECA_STATIQUE(MODELE=MODELE, ...)

FIN()


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```




Discretization Scheme Selection

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Please tell me about "Discretization Scheme Selection"!


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OpenFOAM's discretization schemes are set in the fvSchemes file. The discretization of the convection term greatly affects accuracy and stability:


๐Ÿง‘โ€๐ŸŽ“

After hearing this, I finally understand why the solver selection guidelines are so important!


๐ŸŽ“
  • upwind: 1st order accuracy, stable but high numerical diffusion
  • linearUpwind: 2nd order accuracy, limited
  • limitedLinear: 2nd order accuracy, TVD limited
  • LUST: blended scheme, recommended for LES


Error Evaluation and Accuracy Verification

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I've heard of "error evaluation and accuracy verification," but I might not fully understand it...



Discretization Error Evaluation

๐Ÿง‘โ€๐ŸŽ“

What exactly do you mean by discretization error evaluation?


๐ŸŽ“

Estimation of discretization error using Richardson extrapolation:



$$ f_{\text{exact}} \approx f_h + \frac{f_h - f_{2h}}{r^p - 1} $$


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Here, $f_h$ is the solution with mesh width $h$, $r$ is the mesh ratio, and $p$ is the order of discretization.




GCI(Grid Convergence Index)

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Please tell me about "GCI"!


๐ŸŽ“

Quantitative evaluation of mesh convergence based on ASME V&V 20-2009:


๐Ÿง‘โ€๐ŸŽ“

After hearing this, I finally understand why discretization error evaluation is so important!


๐ŸŽ“

This can be expressed with the following formula.


$$ GCI_{\text{fine}} = \frac{F_s |\varepsilon|}{r^p - 1} $$

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Hmm, just the formula doesn't click... What does it represent?


๐ŸŽ“

Safety factor $F_s = 1.25$ (when comparing three or more mesh levels). GCI < 5% is a guideline for convergence.


๐Ÿง‘โ€๐ŸŽ“

Now I understand what my senior meant when they said, "At least do the discretization error evaluation properly."



Verification Benchmark Problems

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Please tell me about "Verification Benchmark Problems"!


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To ensure the reliability of analysis results, comparison with the following benchmark problems is recommended:


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