CAD Model Qualification for Reliable and Accurate Numerical Simulations

In the demanding world of numerical simulation, the accuracy of input data is as crucial as the calculation algorithms themselves. A recent study reveals that more than 70% of simulation failures are attributable not to solvers, but to geometric defects present in the CAD models used as the basis for calculation. Geometric qualification of models is therefore a decisive step to ensure reliable and usable results.

CAD qualification for simulation - this methodical verification aimed at certifying that no defect affects the reuse of a model for numerical simulation - represents a strategic issue today for aerospace, automotive, and energy industries, where each decision based on erroneous results can lead to considerable financial consequences.

Table of contents

• Challenges of CAD qualification for numerical simulation
• Typology of geometric defects affecting simulation
• Systematic CAD qualification process
• CADIQ: Advanced solution for CAD model quality verification
• Business benefits and ROI of CAD qualification
• Integration of qualification in simulation workflows

Challenges of CAD qualification for numerical simulation

The digital transformation of industrial processes has considerably accelerated the use of simulation as a decision-making tool. However, the reliability of these simulations depends entirely on the quality of the CAD models used as input data. Geometric defects, often invisible to the naked eye, compromise the validity of calculations and can lead to erroneous conclusions.

The statistics are revealing: according to a study conducted by NIST (National Institute of Standards and Technology), the American manufacturing industry loses more than $1.5 billion annually due to interoperability issues and CAD model quality problems. For simulation departments, these defects translate into:

• Repeated failures during automatic meshing attempts
• Model preparation times multiplied by 3 to 5
• Potentially erroneous calculation results despite successful meshing
• Loss of confidence in numerical simulation processes

The increasing complexity of modern CAD systems, coupled with the need to exchange data between different platforms, amplifies these challenges. Sophisticated parametric models, designed for manufacturing, are not necessarily optimized for the specific requirements of simulation software. This mismatch is particularly critical during model preparation for meshing, a fundamental step in any finite element simulation process.

Typology of geometric defects affecting simulation

To implement an effective CAD model qualification strategy, it is essential to understand the different categories of defects that can affect numerical simulation. These defects can be classified into four main families, each having specific impacts on the simulation process.

Model integrity defects

These defects compromise the topological and geometric consistency of the model. Particularly problematic for automatic meshers, they generally lead to complete failures of the meshing process:

• Free edges: edge segments belonging to only one face, creating discontinuities in the model's envelope
• Missing faces: absences in the solid envelope, making it impossible to define a closed volume
• Degenerate faces: surface elements whose area tends toward zero, disrupting meshing algorithms
• Self-intersections: surfaces intersecting each other, creating ambiguities in volume definition

Structure defects

These anomalies concern the organization and quality of the mathematical representation of the model. Although less visible than integrity defects, they have a significant impact on mesh quality and results accuracy:

• Embedded solids: overlapping volumes creating ambiguities in the definition of calculation domains
• Non-tangent surfaces: curvature discontinuities affecting element distribution during meshing
• Redundant geometries: duplicated elements unnecessarily increasing model complexity
• Inconsistent topological structures: organization of geometric entities not complying with solid modeling rules

Simulation-specific defects

This category includes geometric characteristics which, without being defects for CAD, pose specific problems for simulation software:

• Tiny edges: segments too short relative to the overall scale of the model, imposing excessive mesh refinement
• Narrow faces: surfaces where one dimension is disproportionate to the other, generating poor quality elements
• High curvature regions: areas requiring a particularly high density of elements
• "Slivers": extremely thin faces forming points, incompatible with quality meshing

Exchange-related defects

These problems occur when converting models between different CAD systems or when exporting to neutral formats (STEP, IGES, Parasolid):

• Continuity breaks: discontinuities appearing at junctions between surfaces during conversion
• Excessive simplifications: loss of important geometric details for simulation
• Degradation of complex surfaces: inadequate approximations of non-analytical geometry surfaces
• Loss of semantic information: disappearance of conceptual features necessary for model interpretation

The impact of these defects varies depending on the type of simulation envisaged. While structural analyses are particularly sensitive to integrity defects, fluid flow simulations will be more affected by surface continuity issues. This complexity justifies the adoption of a methodical approach for model qualification.

Systematic CAD qualification process

The qualification of a CAD model for simulation is not a one-time operation but a structured process that must be integrated into the product development chain. To be effective, this process must combine automated verifications and human expertise according to a proven methodology.

Key steps in a qualification process

A complete CAD qualification process for simulation generally revolves around five main phases:

1. Preliminary assessment: identification of specific requirements for the planned type of simulation (structural, thermal, fluid, etc.) and definition of corresponding quality criteria.
2. Automated analysis: systematic detection of geometric defects using specialized tools, with generation of detailed reports.
3. Problem prioritization: classification of identified defects according to their potential impact on the planned simulation.
4. Targeted correction: resolution of critical defects, with a differentiated approach according to their nature and origin.
5. Final validation: verification of the compliance of the corrected model and documentation of validated characteristics.

Qualification criteria adapted to simulation

Qualification criteria must be adapted not only to the type of simulation envisaged but also to the specific capabilities of the meshing software used. Standards such as SASIG PDQ (Strategic Automotive Product Data Standards Industry Group - Product Data Quality) or VDA 4955 provide reference bases, but often need to be supplemented with simulation-specific criteria.

For a typical finite element simulation, the following criteria constitute a minimum:

• Complete absence of free edges and missing faces
• Resolution of self-intersections and penetrations between solids
• Elimination or simplification of non-relevant geometric details (fillets, chamfers, etc.)
• Identification and specific treatment of narrow faces and tiny edges
• Verification of dimensional consistency and units

Documentation and traceability

Documentation of the qualification process is essential, both for the reproducibility of simulations and for regulatory requirements in certain sectors (aerospace, medical, nuclear). This documentation should include:

• The initial state of the model and identified defects
• The corrections made and their justification
• The validated geometric characteristics (areas, volumes, centers of gravity)
• Compliance with established qualification criteria
• Specific recommendations for using the model in simulation

This systematic approach allows not only to ensure the individual quality of models but also to establish metrics for continuous improvement of upstream CAD modeling processes.

CADIQ: Advanced solution for CAD model quality verification

Faced with the complex challenges of CAD qualification for simulation, CADIQ stands as a reference solution, specifically designed to meet the strictest requirements in terms of geometric verification of 3D models.

Fundamental capabilities of CADIQ

CADIQ distinguishes itself by its ability to precisely identify defects likely to affect the reuse of CAD models, particularly in the context of numerical simulation. Its philosophy is based on three essential pillars:

• Native analysis: use of native APIs of each CAD system for maximum precision without intermediate data conversion
• Comprehensive detection: identification of more than 100 types of geometric and topological defects
• Contextual visualization: precise location of problems in the 3D environment to facilitate their understanding and resolution

These capabilities are particularly valuable for simulation teams dealing with models from various sources and requiring rigorous preparation before meshing.

Simulation-specific diagnostics

CADIQ integrates a battery of diagnostics specially designed for numerical simulation needs. These checks target geometric characteristics problematic for meshers:

• Detection of tiny edges: identification of segments with length below acceptable thresholds for balanced meshing
• Analysis of narrow faces: spotting surfaces whose aspect ratio compromises element quality
• Identification of problematic regions: localization of areas requiring special attention during meshing (high curvatures, abrupt transitions)
• Detection of self-intersecting loops: analysis of topological configurations incompatible with conformal meshing

These diagnostics allow anticipating and resolving problems before they cause meshing failures or affect the quality of simulation results.

Advanced model comparison

A particularly useful feature of CADIQ is its ability to compare CAD models with unmatched precision. This capability proves crucial in several frequent simulation scenarios:

• Validation of conversions between native and neutral formats
• Identification of unintentional modifications between successive versions of a model
• Verification of the conformity of a simplified model with respect to the initial detailed geometry
• Control of the persistence of critical geometric properties after translation

CADIQ's comparison technology allows viewing up to four models side by side simultaneously, with precise identification of geometric, topological, and dimensional differences.

Multi-CAD compatibility and process integration

CADIQ distinguishes itself by its broad compatibility with the main CAD systems on the market:

• CATIA V5 and V4
• NX (all recent versions)
• Creo Parametric
• SOLIDWORKS
• Inventor
• Solid Edge

This compatibility also extends to essential neutral formats for interoperability:

• STEP (all versions)
• IGES
• Parasolid
• JT
• ACIS

In terms of integration, CADIQ offers several usage modalities:

• Interactive user interface for ad hoc analyses
• Automated batch mode for processing multiple models
• Command line interface for integration with PLM systems
• Distributed processing capabilities to optimize performance on large data volumes

Business benefits and ROI of CAD qualification

The systematic qualification of CAD models for simulation generates tangible benefits that manifest at different levels of the organization. Investment in a structured geometric verification process produces a measurable return both operationally and strategically.

Immediate operational gains

Simulation teams quickly observe several quantifiable improvements:

• Reduction in preparation times: 30-50% decrease in the time needed to make a CAD model suitable for simulation
• Increase in success rates: near-total elimination of meshing failures related to geometric defects
• Optimization of computing resources: reduction in meshing and resolution times thanks to more suitable models
• Decrease in iterations: fewer "trial-and-error" cycles to obtain a usable model

These gains directly translate into increased productivity for simulation teams and better utilization of IT infrastructure.

Improvement in results quality

Beyond purely operational aspects, CAD qualification has a direct impact on simulation reliability:

• Reduction of numerical artifacts: elimination of artificial stress concentrations linked to geometric defects
• Better solver convergence: more stable behavior of resolution algorithms
• Consistency between iterations: comparable results from one model version to another
• Reduction of uncertainties: better separation between numerical errors and physical phenomena

This qualitative improvement strengthens decision-makers' confidence in the conclusions drawn from numerical simulations.

Impacts on engineering processes

At the process level, systematic CAD qualification induces positive transformations:

• Standardization of practices: establishment of objective criteria for model quality
• Better interdisciplinary communication: clarification of requirements between CAD designers and simulation analysts
• Enhanced traceability: complete documentation of models and their modifications
• Knowledge capitalization: formalization of good modeling practices for simulation

These evolutions contribute to establishing a robust digital engineering culture within the organization.

Quantifiable return on investment

The ROI of a CAD qualification approach for simulation can be evaluated along several axes:

These benefits typically materialize within a few months of use, with a complete return on investment often achieved in less than a year for organizations regularly performing numerical simulations.

Integration of qualification in simulation workflows

To maximize the benefits of CAD qualification, it must be seamlessly integrated into existing numerical simulation workflows. This integration can take different forms depending on the digital maturity of the organization and the specificities of its processes.

Strategic insertion points

CAD model qualification can intervene at different moments in the product development process:

• Upstream validation: systematic verification of CAD models before making them available for simulation
• Import control: automatic verification during import into the simulation environment
• Specific qualification: targeted verification according to the type of simulation envisaged (structural, thermal, CFD, etc.)
• Long-term archiving: certification of models as part of LOTAR (Long Term Archiving and Retrieval) initiatives

The choice of insertion point depends on the priority objectives: maximum anticipation of problems, process fluidity, or final quality assurance.

Integration with PLM systems and simulation tools

CAD qualification gains in efficiency when integrated with product lifecycle management (PLM) systems and simulation environments:

• Automated quality control during check-in/check-out of models in PLM
• Validation of conversions between native formats and neutral formats
• Preliminary verification before launching simulation calculations
• Documentation of validated properties in PLM metadata

This integration can be achieved through various mechanisms:

• Use of command line interfaces for batch operations
• Development of specific extensions using PLM system APIs
• Configuration of automated workflows triggering verifications at key stages
• Implementation of web services for a service-oriented architecture

Progressive implementation and data governance

The adoption of a CAD qualification approach benefits from being progressive, with a phased ramp-up:

1. Pilot phase: application on a restricted perimeter to validate the approach and measure gains
2. Targeted deployment: extension to critical projects and components
3. Generalization: systematic integration in all simulation processes
4. Continuous optimization: adjustment of criteria and workflows based on feedback

This progression must be accompanied by adapted governance of technical data:

• Clear definition of qualification criteria according to simulation types
• Establishment of roles and responsibilities for model validation
• Implementation of performance indicators to monitor process efficiency
• Capitalization of good practices and solutions to recurring problems

Such a structured approach allows to sustainably anchor CAD qualification in the digital engineering practices of the company.

Towards predictive qualification

The evolution of technologies opens the way to more advanced approaches to CAD qualification:

• Predictive analysis of potentially problematic areas for simulation
• Automated recommendations for correcting identified defects
• Continuous learning of qualification criteria based on model history
• Adaptive optimization of geometries for different types of simulation

These advanced approaches, combined with the functionalities of solutions like CADIQ, constitute the new frontier of CAD qualification for numerical simulation.