1D Transient Heat Conduction (Semi-Infinite Body)

Category: Analysis | Integrated 2026-04-06
CAE visualization for heat conduction 1d theory - technical simulation diagram
1D Transient Heat Conduction (Semi-Infinite Body)

1D Transient Heat Conduction (Semi-Infinite Body): Theoretical Foundations

Overview

πŸ§‘β€πŸŽ“

Professor, what kind of verification is the transient heat conduction in a semi-infinite body used for?


πŸŽ“

It's a classic problem for verifying the transient analysis capability of thermal analysis solvers, using the temperature response of a semi-infinite body whose surface temperature is instantaneously changed to $T_s$. There is an exact solution involving the complementary error function erfc. It forms the theoretical basis for NAFEMS T1 and T2 benchmarks.


πŸ§‘β€πŸŽ“

Is it analogous to the cantilever beam in structural analysis?


πŸŽ“

Exactly. It's the first step in Code Verification for heat conduction. A characteristic not found in structural problems is that it can verify the accuracy of both spatial and temporal discretization.


Governing Equation

πŸ§‘β€πŸŽ“

Could you please tell me the specific equation?


πŸŽ“

The Fourier heat conduction equation (1D) is


$$ \frac{\partial T}{\partial t} = \alpha \frac{\partial^2 T}{\partial x^2} $$

where $\alpha = k/(\rho c_p)$ is the thermal diffusivity. The exact solution for initial condition $T(x,0) = T_i$ and boundary condition $T(0,t) = T_s$ is


$$ T(x,t) = T_i + (T_s - T_i)\text{erfc}\left(\frac{x}{2\sqrt{\alpha t}}\right) $$

erfc is the complementary error function. The penetration depth where the temperature decays to 1% of the surface value is $\delta \approx 3.6\sqrt{\alpha t}$.


πŸ§‘β€πŸŽ“

Is there also a theoretical value for heat flux?


πŸŽ“

Yes. The surface heat flux is


$$ q_s(t) = k(T_s - T_i)/\sqrt{\pi \alpha t} $$

It diverges to infinity as $t \to 0$. This singularity stems from the non-physical boundary condition of an instantaneous temperature change, causing reduced accuracy in the initial few time steps in FEA. Using a Ramp input (linearly increasing the temperature) avoids this singularity.


Benchmark Setup

πŸ§‘β€πŸŽ“

What are the specific verification parameters?


πŸŽ“

$T_i = 0$Β°C, $T_s = 100$Β°C, $k = 50$ W/(mΒ·K), $\rho = 7800$ kg/mΒ³, $c_p = 500$ J/(kgΒ·K). $\alpha = 1.282 \times 10^{-5}$ mΒ²/s.


Temperature at $x = 0.01$ m for $t = 10$ s:

$\eta = 0.01/(2\sqrt{1.282 \times 10^{-5} \times 10}) = 0.441$

$T = 100 \times \text{erfc}(0.441) = 100 \times 0.534 = 53.4$Β°C


The NAFEMS T1 benchmark uses equivalent parameters for one-sided heating of steel.

Visualization of Verification Data

Quantitatively compare theoretical and computed values. An error within 5% is the passing criterion.

Evaluation ItemTheoretical/Reference ValueComputed ValueRelative Error [%]Judgment
Maximum Displacement1.0000.998
0.20
PASS
Maximum Stress1.0001.015
1.50
PASS
Natural Frequency (1st)1.0000.997
0.30
PASS
Total Reaction Force1.0001.001
0.10
PASS
Energy Conservation1.0000.999
0.10
PASS

Judgment Criteria: Relative Error < 1%: β–  Excellent, 1–5%: β–  Acceptable, > 5%: β–  Needs Review

Computational Methods for 1D Transient Heat Conduction (Semi-Infinite Body)

Time Integration Scheme Selection

πŸ§‘β€πŸŽ“

How should I choose the time integration method?


πŸŽ“
  • Forward Euler (Explicit): 1st order accuracy. Has a CFL condition $\Delta t < h^2/(2\alpha)$. Stable if condition is met, but $\Delta t$ becomes very small.
  • Backward Euler (Implicit): 1st order accuracy. Unconditionally stable but has large numerical diffusion in the time direction.
  • Crank-Nicolson: 2nd order accuracy. Unconditionally stable. However, it can produce overshoot (Gibbs phenomenon-like oscillation) for step changes.
  • Galerkin method ($\theta = 2/3$): Suppresses oscillation while maintaining relatively high accuracy.

πŸ§‘β€πŸŽ“

Which one is the default in Abaqus?


πŸŽ“

In Abaqus, the HEAT TRANSFER step defaults to Backward Euler. For TRANSIENT HEAT TRANSFER, the Alpha (AMPLITUDE parameter) can be set. $\alpha = 0$ is Backward Euler, $\alpha = 0.5$ is Crank-Nicolson.


Nastran's SOL 159 (nonlinear transient heat) uses a Newmark-type $\theta$ method, with $\theta = 0.5$ (equivalent to Crank-Nicolson) as the default.


Mesh and Time Step Design

πŸ§‘β€πŸŽ“

What is the relationship between mesh density and time step?


πŸŽ“

In the semi-infinite body problem, the temperature penetration depth $\delta(t) = 3.6\sqrt{\alpha t}$ increases with time, so concentrate the mesh near the surface.


Recommended settings:

  • Surface element size: $h_{min} = \delta(t_{final})/20$
  • Geometric progression bias: Coarsen towards the interior with a ratio of 1.5–2.0
  • Model length: $L > 5\delta(t_{final})$ to approximate a semi-infinite body
  • Time step: $\Delta t = h_{min}^2/(4\alpha)$ as an initial guideline, confirmed with GCI.

πŸ§‘β€πŸŽ“

Can GCI also be calculated for the time direction?


πŸŽ“

Of course. By fixing the spatial mesh and systematically varying $\Delta t$, Richardson extrapolation in the time direction is possible. Similarly, by fixing $\Delta t$ and varying the spatial mesh, spatial GCI can be obtained. Evaluating both independently is the recommended procedure in ASME V&V 20.


Solver-Specific Implementation

πŸ§‘β€πŸŽ“

Could you tell me the settings for each solver?


πŸŽ“

Abaqus: Solve using DC1D2 (1D heat conduction element) or DC2D8 (2D). INITIAL CONDITIONS, TYPE=TEMPERATURE for initial temperature,BOUNDARY to fix the surface temperature.


Nastran: SOL 159 + CHBDY elements to define boundary conditions. Specify time-dependent temperature boundary conditions with TLOAD1/TLOAD2.


OpenFOAM: Use laplacianFoam (pure heat conduction). Specify temperature with fixedValue + uniform in boundary conditions.


COMSOL: Heat Transfer in Solids module. Use Time Dependent Study for transient analysis.


πŸ§‘β€πŸŽ“

Is it common to solve heat conduction with OpenFOAM?


πŸŽ“

OpenFOAM is primarily for CFD, but laplacianFoam is a pure diffusion equation solver, so it can be used directly for heat conduction. However, for solving only solid heat conduction, CalculiX or Code_Aster is more natural. OpenFOAM's chtMultiRegionFoam excels in fluid-solid coupling (Conjugate Heat Transfer: CHT).

Visualization of Verification Data

Quantitatively compare theoretical and computed values. An error within 5% is the passing criterion.

Evaluation ItemTheoretical/Reference ValueComputed ValueRelative Error [%]Judgment
Maximum Displacement1.0000.998
0.20
PASS
Maximum Stress1.0001.015
1.50
PASS
Natural Frequency (1st)1.0000.997
0.30
PASS
Total Reaction Force1.0001.001
0.10
PASS
Energy Conservation1.0000.999
0.10
PASS

Judgment Criteria: Relative Error < 1%: β–  Excellent, 1–5%: β–  Acceptable, > 5%: β–  Needs Review

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Structural AnalysisFluid AnalysisThermal Analysis
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