Resolving ‘Too Many Attempts Made for This Increment’ in FEA/CFD

troubleshooting
Hosseini Saman
February 26, 2026
16 Minute

Introduction to ‘Too Many Attempts Made for This Increment’

In the realm of advanced engineering simulations, particularly within Finite Element Analysis (FEA) and Computational Fluid Dynamics (CFD), engineers frequently encounter convergence challenges. One of the most common and often frustrating messages is: “Too Many Attempts Made for This Increment”. This error signals that the solver is struggling to find a stable solution within a given load or time step (increment), leading to non-convergence and halting the simulation.

This article provides a comprehensive, engineer-to-engineer guide to understanding, diagnosing, and effectively resolving this critical simulation error. We’ll delve into the underlying causes, present systematic diagnostic approaches, and offer actionable strategies to overcome non-convergence, enabling you to achieve robust and reliable simulation results for structural integrity, FFS Level 3 assessments, aerospace components, oil & gas infrastructure, and other complex engineering applications.

What Does ‘Too Many Attempts’ Mean?

When an implicit solver (e.g., in Abaqus/Standard, ANSYS Mechanical, MSC Nastran, or certain Fluent/CFX solvers) attempts to solve a non-linear problem, it typically employs an iterative Newton-Raphson scheme or similar method. For each load or time increment, the solver takes an initial guess and then iteratively refines it until the residual forces (or fluxes) fall below a predefined tolerance. Each refinement step is an “attempt.”

The “Too Many Attempts” message means that the solver has exhausted its maximum allowed number of iterations within that single increment without achieving convergence. This can happen due to a variety of factors, ranging from severe non-linearities in the model to numerical instabilities.

Common Scenarios and Root Causes

Understanding the root causes is the first step toward resolution. This error typically arises in non-linear analyses, which can include geometric non-linearity (large deformations), material non-linearity (plasticity, hyperelasticity), and contact non-linearity.

Severe Nonlinearities

Sudden Changes: Abrupt changes in boundary conditions, loads, or material behavior (e.g., phase transformations, sudden buckling) can make it difficult for the solver to converge in a single step.
Unstable Behavior: Physical instabilities like local buckling, snap-through, or dynamic collapse, if not properly handled, can lead to severe convergence difficulties.

Poor Mesh Quality

Distorted Elements: Elements with high aspect ratios, warpage, or skewness (common in models from CAD tools like CATIA or SolidWorks, especially after complex boolean operations) can lead to inaccurate stiffness matrices and poor convergence.
Insufficient Refinement: Areas of high stress gradients, contact, or large deformation require finer meshes to accurately capture the physics. Coarse meshes in these regions can lead to numerical oscillations. Tools like HyperMesh or ANSYS Meshing are critical for quality control.

Inadequate Boundary Conditions or Loads

Over-constraining/Under-constraining: Improperly defined boundary conditions (BCs) can either prevent physically plausible deformation or allow rigid body motion, leading to singularity issues.
Discontinuities: Abrupt application of loads or BCs can introduce sharp numerical gradients, especially at the beginning of an analysis step.
Incorrect Load Path: In structural integrity assessments, especially FFS Level 3, ensuring loads are applied realistically to represent operational conditions is crucial.

Material Model Issues

Incorrect Parameters: Errors in material properties (e.g., Young’s modulus, yield strength, hardening curves for metals, or hyperelastic parameters for biomechanics models) can lead to an inaccurate representation of stiffness.
Convergence Difficulties of Specific Models: Some complex material models (e.g., concrete damage plasticity, viscoelasticity, or plasticity with very flat hardening) can be numerically challenging.

Time Increment Control Problems

Large Initial Increments: If the initial time or load increment is too large, the solver may struggle to find a solution, especially at the start of a non-linear step.
Fixed Increment Size: Using a fixed, large increment size in highly non-linear problems prevents the solver from adapting and taking smaller steps when needed.

Contact Instabilities

Initial Penetrations: Gaps or overlaps in initial contact definitions.
Chattering/Oscillations: Contact points repeatedly engaging and disengaging, often due to stiff contact algorithms or insufficient stabilization.
Friction: High friction values or sudden changes in friction conditions can exacerbate convergence issues.

Solver Settings and Convergence Criteria

Loose/Tight Tolerances: While loose tolerances might lead to convergence, they compromise accuracy. Overly tight tolerances can prevent convergence even for physically sound solutions.
Maximum Iterations: Insufficient maximum iterations for a challenging increment.
Solution Control Parameters: Specific parameters in solvers like Abaqus (e.g., stabilization, arc length methods) or ANSYS (e.g., automatic time stepping, adaptive descent) are crucial.

Diagnosing the Problem: A Systematic Approach

Effective diagnosis is key to efficient resolution. Follow a systematic approach to pinpoint the exact cause of non-convergence.

Initial Checks (Pre-analysis)

Model Review: Visually inspect the geometry in CAD/CAE tools (e.g., CATIA, Abaqus/CAE, ANSYS Workbench). Look for small features, sharp corners, or unwanted gaps/overlaps.
Mesh Quality Report: Generate a mesh quality report. Identify elements with poor aspect ratios, Jacobian distortion, or skewness, especially in critical regions (contact, high stress). Tools like MSC Patran or HyperMesh excel here.
Boundary Condition & Load Verification: Double-check the magnitude, direction, and application points of all loads and BCs. Ensure no rigid body motions are permitted if a static analysis. A Python script can automate checks for zero-energy modes.
Material Properties: Confirm material data inputs. Run a simple element test (e.g., uniaxial tension) to verify the material model behavior independently.
Contact Definitions: Verify contact pair definitions, initial gaps/overlaps, and friction coefficients. Use contact stabilization if available and appropriate.

During or Post-Analysis Investigation

Reviewing the Solver Output File

The solver’s output file (.dat, .msg, .out) is your most valuable diagnostic tool.

Last Converged Increment: Note the last successfully converged increment. This often points to the onset of the problem.
Iteration History: Examine the force/moment residual and displacement correction norms for the failed increment. Are they oscillating, diverging, or simply stagnating?
Warning/Error Messages: Look for specific warnings about contact overclosure, negative eigenvalues (buckling warnings), large distortions, or material instability.
Solver Diagnostics: Some solvers provide more detailed diagnostics, such as “cut-back” information, indicating why the automatic time stepping algorithm reduced the increment size.

Visualizing Results at Failed Increment

If your solver allows, visualize the results just before or at the failed increment:

Deformed Shape: Observe the deformed shape. Is it physically realistic? Are there regions of excessive distortion, interpenetration (in contact), or localized buckling?
Stress/Strain Contours: Check stress and strain concentrations. Do they align with expected failure modes? Are there sudden, unphysical jumps?
Contact Status: Plot contact pressure and status to see if contact is closing/opening rapidly, or if contact areas are “chattering.”
Energy Plots: Plot internal energy, kinetic energy, and external work (if applicable). Significant kinetic energy in a static analysis indicates instability.

Actionable Strategies to Resolve the Error

Once you’ve diagnosed the likely cause, apply these strategies to resolve the “Too Many Attempts” error.

Mesh Refinement and Quality Improvement

Local Refinement: Refine the mesh in areas of high stress gradients, large deformation, or contact zones. For example, in FEA of welded structures for structural integrity, weld toes and roots require fine meshes.
Element Type: Consider higher-order elements (e.g., quadratic) if the problem involves bending or high strain gradients. For large deformation problems, reduced integration elements might be suitable, but be wary of hourglassing.
Mesh Quality Metrics: Utilize pre-processors to ensure elements meet quality criteria.

Metric	Description	Typical Good Value	Impact on Convergence
Aspect Ratio	Ratio of longest edge to shortest edge	< 5-10 (quad/hex), < 20 (tri/tet)	High values cause inaccurate stiffness, poor convergence.
Jacobian Ratio	Measure of element distortion from ideal shape	> 0.5-0.7	Low values indicate severe distortion, leading to non-convergence.
Skewness	Angle deviation from ideal element angles	< 45-60 degrees	High skewness creates inaccuracy, can prevent convergence.
Warpage (Shells)	Deviation of shell element from a plane	< 5-10 degrees	Significant warpage leads to incorrect bending behavior.

Refining Boundary Conditions and Loads

Smooth Load Application: Ramp up loads gradually over time rather than applying them instantaneously. For implicit solvers, defining several small load steps is often better than one large one.
Weak Springs/Stabilization: For models with potential rigid body modes or initial contact issues, adding very weak springs (e.g., to an arbitrary node) or using contact stabilization techniques (e.g., in Abaqus) can provide numerical stability without significantly affecting the structural response.
Pre-loading/Pre-straining: In some cases, applying a small initial load or strain can help stabilize the model before the main loading event.

Material Model Adjustments

Linearization: Start with simpler material models (e.g., linear elastic) to ensure the model converges, then progressively introduce non-linearity.
Viscous Regularization: Some solvers allow for viscous regularization, which adds numerical damping to material models, helping convergence in highly non-linear material problems (e.g., hyperelasticity, plasticity).
Validate Properties: Ensure material data is accurate for the expected strain and temperature ranges. Consult material handbooks or perform experimental characterization.

Time Increment Control and Solution Techniques

Automatic Time Stepping: Always enable automatic time stepping. This allows the solver to reduce the increment size when difficulties arise and increase it when convergence is easy. Define initial, minimum, and maximum increment sizes thoughtfully.
Smaller Initial Increment: For models with severe initial non-linearity (e.g., contact closure, sudden load application), start with a very small initial increment.
Arc-Length Method: For problems involving structural instability (snap-through, buckling beyond critical load), methods like the Riks method (Abaqus) or arc-length methods (ANSYS Mechanical) are indispensable.
Restart Capabilities: If the simulation fails, use the restart capability to continue from the last converged increment after making adjustments.
Python/MATLAB for Adaptive Control: For highly customized or complex simulations (e.g., biomechanics where material properties might evolve), Python scripts can be used for advanced control of increment sizes, even interacting with the solver’s API for adaptive strategies. Similarly, MATLAB can be used for post-processing iteration data to identify patterns in non-convergence.

Stabilizing Contact Definitions

Adjust Contact Tolerances: Increase the allowable penetration tolerance slightly, if physical accuracy is not compromised.
Frictionless Initial Step: Sometimes, running an initial step with frictionless contact to establish stable contact surfaces, followed by a step with friction, can help.
Surface Smoothing: Ensure contact surfaces are smooth. Excessive facetting can cause numerical noise.
Contact Algorithms: Experiment with different contact algorithms (e.g., “hard contact,” “soft contact,” augmented Lagrange, penalty methods) if available in your solver.

Adjusting Solver Parameters

Increase Maximum Iterations: Incrementally increase the maximum number of iterations allowed per increment.
Relax Convergence Tolerances: As a last resort, slightly relax the force/moment residual tolerances. However, always verify that the solution remains physically meaningful and accurate for your application (e.g., FFS Level 3 acceptance criteria).
Solution Control Options: Explore advanced solution control options specific to your software (e.g., “Stabilization” in Abaqus, “Nonlinear controls” in ANSYS).

Practical Workflow for Iterative Resolution

Here’s a checklist for a systematic resolution process:

Simplify the Model: Start with a simplified version of your model (e.g., linear elastic materials, no contact, simpler geometry) to establish a baseline for convergence.
Isolate Non-Linearities: Introduce non-linearities one by one (e.g., first geometry, then material, then contact). Identify which non-linearity triggers the “Too Many Attempts” error.
Incremental Loading: Apply loads in very small increments. For example, if your total load is 100 N, apply 10 increments of 10 N each instead of one 100 N step.
Monitor Output Closely: Actively watch the solver output file for warnings and error messages as the simulation progresses.
Visualize Intermediate Results: Periodically check results at converged increments to ensure physical realism.
Document Changes: Keep a log of every change made to the model and its effect on convergence.
Consult Documentation/Community: Refer to the official software documentation or online forums for specific solver settings and best practices.

Verification & Sanity Checks After Resolution

Simply getting a simulation to converge isn’t enough. It’s crucial to verify the quality and accuracy of the converged solution.

Convergence Plots

Examine the convergence plots for your final run. Ensure that the force/moment residuals and displacement corrections truly converge to within acceptable tolerances for each increment. Oscillatory convergence might still hide numerical issues.

Energy Balance

For explicit dynamics, check the energy balance. The ratio of internal energy plus kinetic energy to external work should remain close to 1.0 (or within a few percent). For implicit, ensure plastic dissipation (if applicable) and strain energy are reasonable.

Deformed Shape and Stress Distribution

Critically evaluate the deformed shape, stress, and strain contours. Ask yourself:

Is the deformation physically intuitive and expected?
Are stress concentrations where they should be?
Are there any unphysical deformations or stress hot spots that indicate numerical artifacts?
Do the results make sense in the context of your engineering problem (e.g., structural integrity limits)?

Sensitivity Analysis

Perform a sensitivity analysis on key parameters (e.g., mesh density, material properties within their uncertainty bounds, load application method). Does the solution change significantly? A robust solution should show reasonable sensitivity to parameter variations, not erratic behavior.

Advanced Techniques and When to Seek Expert Help

For exceptionally challenging non-linear problems – perhaps involving extreme deformations, highly complex contact, or sophisticated multi-physics interactions (e.g., in biomechanics or advanced FFS Level 3 assessments) – conventional techniques might fall short. Advanced stabilization methods, specialized element formulations, or even switching to an explicit dynamics solver for quasi-static problems might be necessary.

If you’ve exhausted common troubleshooting steps and are still facing persistent “Too Many Attempts” errors, it might be time to leverage external expertise. For in-depth project support, access to specialized downloadable templates/projects/scripts, or one-on-one expert tutoring and online consultancy, consider exploring the resources available through EngineeringDownloads.com. Our experts can provide tailored guidance and accelerate your problem-solving capabilities.

Conclusion

The “Too Many Attempts Made for This Increment” error is a common hurdle in non-linear FEA and CFD. While frustrating, it serves as a critical indicator that the solver is struggling to capture the physics accurately or stably. By systematically diagnosing the root cause—be it mesh quality, boundary conditions, material models, time stepping, or contact issues—and applying the actionable strategies outlined in this guide, you can overcome these convergence challenges. Remember that successful simulation isn’t just about obtaining a result, but about obtaining a converged, physically meaningful, and verified result that you can trust for critical engineering decisions.