A 3D-rendered car in a wind tunnel testing room, with flow streams passing over the car.

Overview Resources

Altair® HyperMesh® CFD

Unmatched Speed: Streamline CFD Workflows and Achieve High-Fidelity Results

Fast track your CFD simulation modeling with Altair HyperMesh CFD, delivering a seamless, end-to-end solution in a single, user-friendly interface. HyperMesh CFD optimizes every step of your CFD process—expertly navigating you from geometry preparation to meshing, case setup, post-processing, and automated reporting—complemented by customized, out-of-the-box solutions for specialized CFD applications. Maximize fidelity and minimize time with superior high-fidelity simulations that outpace competitors with faster turnaround times and leverage AI-powered CFD to augment the design process and predict results for new designs.

Why HyperMesh CFD?

View from above of a CFD simulation being performed on a car.

End-to-End CFD Solution

Simplify engineering with a single, user-friendly interface that integrates geometry, meshing, case setup, post-processing, design exploration, and report generation, enabling out-of-the-box workflows for external aerodynamics and fan noise solutions—ensuring quick adaptation and step-by-step guidance from start to finish.

CFD simulation being performed on a GPU.

Maximize Fidelity, Minimize Time

Benefit from superior high-fidelity CFD simulations that outpace competitors with an 80% faster turnaround in geometric model preparation. HyperMesh CFD ensures geometry integrity, creates watertight models with enhanced control, and delivers consistent results without oversimplification, complemented by streamlined workflows.

Zoomed in view of a CFD simulation being performed on the front of a car.

AI-Powered CFD

Learn from the past and predict the future with AI in three steps. Quickly locate your past simulation data, train an AI model to learn from it, and predict results for new designs in minutes—augmenting the design process and eliminating the long wait of traditional multi-day simulations.

Key Features

Faster Geometric Model Preparation

Work with large models with low memory footprint using HyperMesh CFD's lightweight modeling capabilities. Prepare and defeature CAD and discrete models, leveraging the auto enclosure tool to automatically create watertight, high-fidelity models. Additionally, AI integration enables users to search, group, and identify parts based on tags.

Solution-Centric Case Setup

Simplify virtual wind tunnel CFD simulation setups with an intuitive graphical UI. Built-in geometry editing capabilities lets users modify and transform parts for design changes. Set up and launch CFD simulations directly within the user interface, utilizing industry-trusted Lattice-Boltzmann and Navier-Stokes-based solvers. Leverage the power of Python-based automation to programmatically set up and simulate large design of experiments (DOEs), maximizing efficiency and streamlining workflows from start to finish.

High-Performance, Interactive Post-Processing

Gain in-depth insights with HyperMesh CFD's comprehensive, high-performance post-processing toolset. Easily generate slice planes, streamlines, iso surfaces, and contours based on result fields. Users can also utilize tools to create computational fields through expressions and calculate statistical quantities. Acoustic analysis and identification features round out the toolset, providing a complete post-processing environment.

Automated Report Generation

Streamline report generation with an automated tool. Users can generate comprehensive reports detailing geometry, contours, iso surfaces, slice planes, and animations with specified views based on a defined template.

Design Exploration Workflow with AI Integration

Accelerate design exploration with a dedicated workflow. Engineers can explore design possibilities efficiently by morphing models or updating CAD parameters to derive new designs and submit DOE studies. Powered by AI, the ability to search, group, and classify parts, as well as predict results using previously trained models, significantly accelerates the design optimization process.