Cantilever Beam Bending (Concentrated Load)

Category: 解析 | Integrated 2026-04-06
CAE visualization for cantilever beam theory - technical simulation diagram
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Theory and Physics

Overview

🧑‍🎓

Professor, I heard that the problem of applying a concentrated load to the tip of a cantilever beam is a standard material for V&V verification. How is it actually used?


🎓

Cantilever beam bending is a benchmark problem widely used in the industry as a starting point for FEA verification. Since there exists an exact solution for tip deflection $\delta = PL^3/(3EI)$ and maximum stress at the fixed end $\sigma_{max} = PLc/I$, it allows for quantitative checking of the implementation accuracy of numerical methods. This problem is also included in NAFEMS' introductory benchmark collection.


🧑‍🎓

So because there's an exact solution, you can "check your answers." Is that the core of Code Verification?


🎓

Exactly right. ASME V&V 10-2006 positions Code Verification as the stage to confirm the mathematical correctness of an analysis code. Demonstrating agreement between the numerical solution and problems with exact solutions is the first step. The cantilever beam is optimal as an entry point for this; within the range where Euler-Bernoulli beam theory assumptions hold, it matches exactly with 1D beam elements.


Governing Equations

🧑‍🎓

Could you please teach me the specific equations?


🎓

The deflection curve based on Euler-Bernoulli beam theory is as follows.


$$ w(x) = \frac{Px^2}{6EI}(3L - x) $$

Here, $P$ is the tip load, $L$ is the beam length, $E$ is Young's modulus, and $I$ is the second moment of area. It is uniquely determined from the boundary conditions: $w=0$, $w'=0$ at the fixed end $x=0$, and moment and shear force are zero at the free end $x=L$.


🧑‍🎓

Where does the stress become maximum?


🎓

Since the bending moment is maximum at the fixed end $M_{max} = PL$, the maximum bending stress occurs at the outermost fiber of the fixed end.


$$ \sigma_{max} = \frac{PL \cdot c}{I} = \frac{PL}{Z} $$

$c$ is the distance from the neutral axis to the outermost fiber, and $Z$ is the section modulus. For a rectangular cross-section, $I = bh^3/12$ and $c = h/2$.


🧑‍🎓

How does it change with Timoshenko beam theory?


🎓

Timoshenko beam theory considers shear deformation. An additional deflection increment due to shear deformation $\delta_s = \kappa PL/(GA)$ is added. $\kappa$ is the shear correction factor (5/6 for a rectangular cross-section). If the span/depth ratio $L/h$ is 10 or more, the contribution of shear deformation becomes less than 1%, so Euler-Bernoulli theory is sufficient. For deep beams with $L/h < 5$, Timoshenko theory or 3D solid elements become essential.


Benchmark Verification Data

🧑‍🎓

I'd like to compare with specific numerical values. Could you tell me the parameter settings?


🎓

The standard settings are $L = 1$ m, $b = 0.1$ m, $h = 0.05$ m, $P = 1000$ N, $E = 200$ GPa, $\nu = 0.3$. For these, the theoretical values are $\delta_{tip} = 0.160$ mm, $\sigma_{max} = 240$ MPa.


Element TypeMeshDOFδ_tip [mm]σ_max [MPa]Displacement Error [%]
BEAM2 (Linear Beam)10 elements660.160240.00.00
QUAD8 (Quadratic Shell)10×21,2600.160239.50.00
HEX8 (Linear Solid)40×8×415,1200.155228.13.13
HEX20 (Quadratic Solid)20×4×215,1200.160239.20.00
TET10 (Quadratic Tetrahedron)Automatic~25,0000.159237.50.63
🧑‍🎓

Why is the error larger only for HEX8?


🎓

HEX8 with full integration suffers from shear locking, causing the beam to behave stiffer than it actually is. Lower-order hexahedra are inherently disadvantaged in bending-dominated problems; convergence is slow unless reduced integration or the B-bar method is used. Quadratic elements can accurately represent bending deformation modes with their mid-side nodes, achieving high accuracy even with coarse meshes.


Theoretical Basis for Convergence

🧑‍🎓

Is there a theoretical basis for the speed of convergence with mesh refinement?


🎓

Yes. According to the FEM error estimation theorem (a priori error estimate derived from Céa's lemma), the energy norm error decreases as $O(h^p)$ for $p$-th order elements. That is, halving the element size reduces the error by about half for linear elements, and by about a quarter for quadratic elements. The essence of Code Verification is whether this theoretical convergence rate can be reproduced in actual mesh convergence studies.


🧑‍🎓

In what cases does the convergence rate deviate from the theoretical value?


🎓

A typical case is when there is a stress singularity. The fixed end of a cantilever beam is not actually a stress singularity, but depending on the implementation method of the fixed constraint, stress concentration can occur locally, degrading the convergence rate. Countermeasures include evaluating at a location sufficiently far from the constrained end, mindful of Saint-Venant's principle, or using distributed constraints.

Physical Meaning of Each Term
  • Time Variation Term of Conserved Quantity: Represents the rate of change over time of the physical quantity in question. Becomes zero for steady-state problems. 【Image】When filling a bathtub with hot water, the water level rises over time—this "rate of change per time" is the time variation term. The state where the valve is closed and the water level is constant is "steady," and the time variation term is zero.
  • Flux Term (Flow Term): Describes the spatial transport/diffusion of a physical quantity. Broadly classified into convection and diffusion. 【Image】Convection is like "a river's current carrying a boat," where something is carried by the flow. Diffusion is like "ink naturally spreading in still water," where something moves due to concentration differences. The competition between these two transport mechanisms governs many physical phenomena.
  • Source Term (Generation/Annihilation Term): Represents the local generation or annihilation of a physical quantity due to external forces/reactions. 【Image】Turning on a heater in a room "generates" thermal energy at that location. When fuel is consumed in a chemical reaction, mass is "annihilated." This term represents physical quantities injected into the system from the outside.
Assumptions and Applicability Limits
  • The continuum assumption holds for the spatial scale.
  • The constitutive laws of the material/fluid (stress-strain relationship, Newtonian fluid law, etc.) are within the applicable range.
  • Boundary conditions are physically reasonable and mathematically well-defined.
Dimensional Analysis and Unit Systems
VariableSI UnitNotes / Conversion Memo
Characteristic Length $L$mMust match the unit system of the CAD model.
Characteristic Time $t$sTime step for transient analysis should consider CFL condition and physical time constants.

Visualization of Verification Data

Quantitative comparison between theoretical and computed values. A pass criterion is within 5% error.

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%: Excellent, 1–5%: Acceptable, > 5%: Needs Review

Numerical Methods and Implementation

Finite Element Formulation

🧑‍🎓

When solving a cantilever beam with FEM, what is the standard practice for which elements to use and how?


🎓

It depends on the purpose. Beam elements directly discretize Euler-Bernoulli theory, so they reach the exact solution with the minimum degrees of freedom. When using shells or solids for verification purposes, discretization of the weak form via the Galerkin method is fundamental.


The element stiffness matrix is calculated by numerical integration.


$$ K_e = \int_{\Omega_e} B^T D B \, d\Omega \approx \sum_{g=1}^{n_g} w_g B^T(\xi_g) D B(\xi_g) |J(\xi_g)| $$

$B$ is the strain-displacement matrix, $D$ is the material stiffness matrix, and $J$ is the Jacobian.


🧑‍🎓

The global stiffness equation is $[K]\{u\} = \{F\}$, right? For linear static analysis, is it solved in one shot with a direct method?


🎓

Exactly. For a scale like a cantilever beam, a direct method (Cholesky decomposition) is fine. When DOF exceeds tens of thousands, preconditioned CG methods are more memory efficient. The essence of this problem is confirming the accuracy of element formulation, so focus should be on element type and mesh density rather than solver selection.


Implementation Guidelines for Element Selection

🧑‍🎓

Could you tell me the settings in actual solvers?


🎓

In Nastran, the CBEAM element gives exact agreement for $w_{tip}$. In Abaqus, B31 (Timoshenko beam) is similar. For solid verification, Abaqus' C3D20R (quadratic hexahedron, reduced integration) is a standard. In Nastran, CHEXA (20-node).


SolverBeam ElementShell ElementSolid Element
NastranCBEAMCQUAD8CHEXA(20)
AbaqusB31S8RC3D20R
AnsysBEAM188SHELL281SOLID186
CalculiX*BEAM*SHELL, S8C3D20
🧑‍🎓

How does the choice of integration scheme affect the results?


🎓

HEX8 with full integration (2×2×2 Gauss points) locks in bending problems. Reduced integration (1×1×1) eliminates locking but risks zero-energy modes (hourglass modes). The B-bar method or EAS (Enhanced Assumed Strain) method avoids locking while also suppressing hourglassing. Abaqus' C3D8I (incompatible mode) is also an option.


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