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Accelerating engineering design with neural surrogates

Learn 5 key stages for accelerating engineering work with neural surrogates

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Key takeaways

  • MultiphysicsAI integrates neural surrogate models with conventional multiphysics solvers to accelerate engineering design workflows.

  • Neural surrogates allow rapid evaluation of large numbers of design configurations at minimal computational cost.

  • Candidate designs identified by surrogates are verified with full solvers to ensure physical accuracy.

 

  • The approach enables exploration of previously inaccessible regions of the design space.

  • Applications in microspeaker and PMUT optimization demonstrated measurable improvements in key performance metrics.

  • The framework is generalizable across multiple engineering domains, including acoustics, piezoelectric, thermal, and structural systems.

Who is this for?

This white paper is for simulation engineers, technical leads, and heads of R&D across all engineering disciplines. It is designed for those looking to automate manual design loops with AI-driven workflows that deliver solver-level accuracy at a fraction of the computational cost.

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Capture in-depth insights on multiphysics simulations and expert design methodologies.

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Trusted by both industry and academia

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Quanscient Allsolve

See how it could work for you

Submit the form to talk with our experts—we'll respond within 1 business day. You'll learn:

  • How Allsolve could fit your use case
  • What results to expect (accuracy, runtime, design exploration capabilities and rough cost range)
  • How it could plug into your workflow today

Interested in just seeing an on-demand demo? Watch the 3-minute demo here