Introduction

In CAE driven NVH development, Noise, Vibration, and Harshness (NVH) performance is a critical differentiator in modern product design local stiffness features such as beads and cups play a critical role in controlling vibration, noise transmission, crash and structural dynamic behaviour. These features strongly influence natural frequencies, vibration modes, and acoustic radiation, particularly in plastics and sheet-metal components.

Meshing is very important in the CAE process because it converts CAD geometry into small elements that the solver can calculate. In NVH analysis, features like beads and cups are very important because they control the stiffness of the structure and affect vibration and natural frequencies. If these features are not meshed properly, their stiffness effect will not be captured correctly.

If the mesh in beads and cups is poor (too coarse, distorted, or not properly shaped), the NVH solver may give wrong natural frequencies and incorrect vibration results. This can lead to wrong conclusions and design changes. Poor meshing also causes rework, and repeated solver runs, which increases time and effort in the CAE process.

Xipa is a machine learning driven CAE automation platform designed to standardize and accelerate CAE pre-processing workflows. A key capability of Xipa ML trained is automated beads and cups capturing, enabling CAE engineers to generate high-quality, solver-ready representations with minimal manual intervention. By embedding engineering intelligence directly into the CAE workflow, Xipa ensures consistency, repeatability, and continuity across the digital thread.

Challenges in Manual Beads and Cups Modelling

• High manual effort and rework
  Extensive clean-up, defeaturing, and remeshing are required to make models solver-ready, increasing turnaround time.
• Inconsistent meshing quality
  Beads and cups frequently introduce distorted or non-uniform elements, resulting in stiffness accuracy and may cause unrealistic mode shapes or stress concentrations in solver results.
• Poor pattern and feature repeatability
  Manual modelling may create beads and cups differently across models, causing inconsistent structural behaviour. This results in unreliable NVH, durability, and crash predictions and increases validation effort.
• Inconsistent meshing patterns

Manual Meshing Variation in element size and pattern during manual meshing changes local stiffness and mass distribution. This affects NVH frequencies, durability stress results, and crash deformation accuracy, leading to rework and repeated solver runs.

To overcome these limitations, ML Trained Xipa is deployed to generate solver-ready bead and cup models using deterministic meshing that strictly adhere to company-defined mesh standards. The process preserves design intent, ensures repeatable and consistent mesh pattern representation, and maintains an uninterrupted digital thread across the product lifecycle.

Powered by machine learning, Xipa enables intelligent automation of NVH-focused bead and cup design, accelerating model preparation while improving consistency, quality, and downstream simulation reliability.

ML Trained Xipa Beads Modelling Examples:

ML Trained Xipa Cups Modelling Examples:

What is Xipa?

Xipa is an intelligent, machine learning–driven CAE automation platform designed to standardize and accelerate pre-processing workflows, one of its key capabilities is beads and cups modelling, key features in structural and NVH simulations. It automatically captures recurring geometric patterns and generates consistent, solver-ready meshes with minimal manual intervention, ensuring high-quality results aligned with company standards. By embedding engineering intelligence directly into the CAE process, Xipa preserves design intent, improves repeatability, and maintains seamless digital thread continuity without the need for rework.

How Xipa Automates Beads and Cups Features

1. Intelligent Bead and Cup Detection

Xipa automatically identifies bead and cup locations from CAD or FE models by recognizing geometric features. Repetitive bead and cup patterns across panels

This eliminates manual identification of beads and cups and ensures all functional stiffening and energy-management features are captured systematically, even as designs evolve.

2. Parametric Bead and Cup Creation

Using predefined forming standards and ML-trained parameters, Xipa generates parametric bead and cup mesh representations, including:

• Simplified Idealized Bead profile shape Modelling
  · Pattern capturing as per the requirement

The Mesh is created consistently across the model, ensuring compliance with CAE best practices and uniform structural behaviour across vehicle platforms.

3. Mesh-Ready Output

The generated beads and cups are optimized for meshing, maintaining element quality and solver compatibility. This significantly reduces rework during meshing and solving stages.

Conclusion

Bead and cup features are very important for NVH, crash, and overall structural performance. In CAE-based NVH analysis, these features must be modelled accurately because mesh quality directly affects stiffness, natural frequencies, and mode shapes. If meshing is inaccurate or inconsistent, it can lead to wrong stiffness prediction, distorted vibration modes, and unreliable noise results.

With Machine Learning, Xipa automates bead and cup modelling to create accurate, solver-ready meshes as per engineering standards. It supports a smooth digital thread for NVH workflows and allows engineers to quickly create, update, and validate features without manual rework. This helps achieve up to 70% reduction in manual effort, better simulation accuracy and quality, improved digital continuity, and faster project turnaroundtime.