Real-Time Design-Data Feedback Critical To Industrial Digital Twin

As engineers in industry and research look to develop Digital Twins of their physical products—with the longer-term goal of integration with the Industrial Internet of Things (IIoT)—the pivotal importance of up-front, accurate, real-time modeling and simulation to optimize both manufacturing and product performance is becoming very clear.

Enabling the development of this critical functionality is RBF Morph, a technology deeply embedded within ANSYS’ newly released R3 version of its advanced engineering software suite, in particular the ANSYS® Twin Builder™ systems-design tool. Also available as a standalone product, RBF Morph provides advanced mesh-morphing capabilities that enable rapid prediction of the outcomes of design changes. Based on radial basis functions (RBF) the software is used to drive mesh-smoothing (morphing) from source points and their displacements.

Mesh morphing is essential for successful reduced-order modeling (ROM), which allows physics-based analysis of product performance and durability to be carried out more accurately and in much less time than traditional methods. “Developing ROM within ANSYS has been a priority for us,” says Michel Rochette, Director of Research at ANSYS. “Merging physics-based understanding with manufacturing analytics delivers the insights that unlock the true value of the Digital Twin. The mathematical techniques behind ROM require that everything has the same mesh topology for all the geometrical parameters in your model—and RBF Morph provides that.”

RBF Morph has been offered within ANSYS® Mechanical™ and ANSYS Fluent™ CFD capabilities for several years. The new coupling with Twin Builder underscores the value of the technology to Digital-Twin functionality, which optimizes control of a company’s product and/or equipment assets. “If you want to include real-time 3D simulation in your Digital-Twin approach it is mandatory to have the approximation that a reduced-order model can provide,” says Rochette. “The future of the IIoT is being built on that, thanks to ROM and RBF Morph.”

RINA, a leading global provider of engineering consulting for industrial services and advanced technology, has an ongoing partnership with RBF Morph to offer Digital-Twin-based workflows for product development.

For a turbine-blade project, RINA was looking for a methodology to quickly predict how any redesigns would affect the blade’s structural response and aerodynamics. The goal was to modify the curved fillet region at the root of the blade to reduce the stress concentration and increase service life by limiting fatigue.

Rather than create a new geometry, mesh and simulation for each design iteration, RINA used RBF Morph, in conjunction with ANSYS Mechanical, to explore the blade’s design space efficiently and determine the effects of design changes.

Meshing the original blade design and using finite element analysis (FEA), the engineers calculated a maximum principal stress of about 195 MPa; the stress peak occurred close to the point where the cross section of the blade had an important geometrical variation. The engineers were looking to smooth out the force and reduce peak stress by adopting a larger radius at the root of the fillet.

The RBF Morph process RINA used involved varying the positions of two curves that controlled the shape of the fillet. First the mesh’s nodes were extracted to follow the new shape of the fillet; the engineers specified how the nodes could move as the mesh’s volume morphed along the new curves. They were also able to define nodes that stayed fixed during the morph. With the right inputs, the engineers were able to control the morphing process so the volume and surfaces deformed smoothly and properly. Ultimately 125,000 nodes were updated in just 15 seconds to accommodate the deformation without excessively degrading the quality of the mesh.

RINA uses RBF Morph to explore a turbine blade’s design space quickly and determine the effects of design changes.

With their RBF Morph procedure established, RINA’s engineers then carried out a two-parameter optimization of the fillet control points using response surface methods, design of experiments (DoE) and parallel plots. These tools allowed the engineers to identify the optimal blade design where the stress was spread out and had a smaller peak. The result: a substantial stress reduction of 22.5 percent in the optimal blade design.

“We found that using RBF Morph was intuitive, effective, and fast,” says Emiliano Costa, Senior Engineering Specialist for Industrial Design & CAE at RINA. “We now include RBF Morph in our design processes to help us more quickly develop better solutions for our customers.”

“This RBF Morph/ROM shape-parametrization methodology used by RINA to optimize turbine blade designs enables the ‘squeezing’ of high-fidelity CAE simulations into real-time Digital Twins,” says RBF Morph founder and CTO Marco Evangelos Biancolini. “When integrated via the IIoT, the technology is ultimately intended to support field-equipment maintenance—tracking performance and predicting or detecting worn parts in need of repair or redesign.”

Biancolini, Associate Professor of Machine Design at the University of Rome, appreciates the broad reach of applications for which his software is being used. “Digital Twins are the future of enterprises of all sizes,” he says. “Now that large solver capacity and high-performance computing are available and considered standard resources for product design, a wide range of industry users can take advantage of our technology to help them optimize their designs at lightening speeds.”

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