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Trusted software for full-system drivetrain structural simulation and durability optimization.
Multi-fidelity simulation for the right balance of speed and accuracy from concept to detailed design.
Understand system performance early to minimize prototyping and make confident engineering decisions.
Consider manufacturing during the design stage to ensure manufacturability and robustness.
With Romax Enduro, adopt a robust, CAE-led design process for confident design space exploration. Ensure the drivetrain satisfies durability targets while linking to other tools to balance other performance aspects, such as NVH and efficiency, as well as understanding how the manufacturing process will affect design. The benefits of using Romax Enduro include:
With ultra-fast modeling, rapid analysis and optimization alongside intelligent automation processes, Romax Enduro helps design structurally sound, robust, and manufacturable drivetrains.
Features of Romax Enduro include:
Validated, full system drivetrain structural analysis, combining state-of-the-art component contact models with stress-based life calculations.
Discover component and system-level static results, including deflections, misalignments, loads, and stresses.
Effective gear design and optimization that accounts for load-dependent system misalignments.
Utilize interfaces to CAD, FEA and other CAE tools, for efficient workflows and robust exchange of design data, alongside parametric studies and batch running for optimization and automation.
We use other tools such as component-based tools for sizing components and gear design - isn't that enough for what we need?
To get accurate deflections and misalignments, it is essential to consider a fully flexible and coupled system. In some cases, like planetary gear arrangements, it is also important to consider load sharing between all gear meshes.
You claim that the Romax analysis is orders of magnitude faster than FEA and yet wholly accurate. How is this possible?
Romax Enduro uses a combination of analytical, numerical and empirical methods, fine-tuned to be as efficient as possible at solving specific rotating machinery problems, which gives significant benefits over general methods. The models have been validated repeatedly throughout the years, including correlations with FEA and physical tests.
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