After two decades of research and innovation in mesh morphing and numerical simulation, RBF Morph, an internationally recognized Italian software company, introduces rbfCAE, the platform that redefines how complex products are designed and evaluated. The new solution combines artificial intelligence, virtual reality, and high-performance reduced-order modeling, offering designers, analysts, and decision-makers a completely new experience: faster, more accessible, and above all more collaborative.

Artificial intelligence at the core of digital design

Thanks to its ability to rapidly generate geometric variants and synthetic datasets, RBF Morph technology becomes a fundamental data engine for AI. The rbfCAE platform enables the creation, training, and use of reduced-order models based on POD techniques and deep learning.

Once training and validation are completed on synthetic datasets and high-fidelity simulations, these models can predict, in just a few moments, the aerodynamic, structural, or thermal performance of new geometries. Even when analyzing entirely new shapes—never seen during training and without high-fidelity simulation—the system provides an estimate of prediction reliability, allowing users to immediately assess how trustworthy the model’s response is. This approach accelerates decision-making: instead of waiting days for a single simulation, companies can quickly explore a wide range of alternatives and evaluate the best options. The result is a process that is faster, more flexible, and better suited to the pace of modern innovation.

One of the platform’s most innovative aspects is its native integration with virtual reality. The VR experience developed by RBF Morph allows designers, stylists, engineers, and other stakeholders to literally step inside the 3D model, modify geometries, observe performance effects in real time, and discuss them together—even from different locations. Simulation thus becomes a universal language that goes beyond technical boundaries: it is visual, immediate, and capable of connecting diverse expertise. It not only enhances the industrial design phase but also opens up new possibilities in all contexts where direct and intuitive evaluation plays a decisive role.

Full interoperability and intelligent automation

At the core of rbfCAE lies a clear philosophy: geometric control must be independent of software and data format. The platform interfaces with major industrial and open-source solvers through a series of vertical connectors and enables the synchronization of heterogeneous physics and models within the same automated workflow.

This architecture drastically reduces the need for manual intervention, eliminates redundant steps, and enables multisolver processes. Companies can therefore work up to five times faster than with traditional workflows, shifting from a sequential to a simultaneous and automated approach.

New rbfCAE tools designed for industry

At the center of this ecosystem is rbfCONNECT, the suite of connectors that allows rbfCAE to interface with different solvers within the same workflow. The integration of advanced simulation, workflow automation, and HPC infrastructure is now one of the key factors in bringing these technologies from research into full industrial application.

“In the POC developed within the PNRR project with the DAMAS Digital Hub, rbfCAE plays a key role in integrating advanced simulation with HPC infrastructures. Workflow automation and the use of AI-based predictive models allow us to create scalable industrial demonstrators, reducing analysis time and improving design decisions,” says Ivan Spisso, Senior HPC Specialist for CFD/CAE Applications, Leonardo.

rbfAI is the environment that brings artificial intelligence, automated data generation, and immersive interaction into simulation. It includes four key modules:

• rbfROM compresses large volumes of simulations into reduced-order models capable of operating almost in real time. These models enable rapid exploration of new configurations, performance prediction, and much faster design decision-making compared to traditional CAE cycles.
• rbfVR brings these models into virtual reality, offering a unique interactive experience in the simulation landscape: users can enter the geometry, modify it through natural gestures, and instantly see how performance changes. This technology is already attracting interest from sectors such as medical, aerospace, and automotive, where the ability to “see and understand” a design before it exists can radically transform both timing and quality of decision-making. Artificial intelligence places data at the service of engineers rather than relying on a fully automated algorithm.

In the automotive sector, where weight reduction and multiphysics optimization are crucial, tools capable of accelerating the design process are becoming increasingly strategic.
“rbfCAE represents a concrete response to the most relevant challenges in the automotive sector: reducing time-to-market, accelerating the design process, and overcoming dependence on legacy tools. Thanks to an integrated multiphysics approach, we can explore lighter and more efficient structural solutions much more quickly. It is a real leap forward in the way we design,” comments Claudio Ponzo, R&D Digital Lead, Nissan Motor Corporation

• rbfADJOINT allows users to instantly assess the impact of shape modifications on performance: each change is accompanied by indicators that suggest in real time whether a specific KPI is improving or worsening. It is designed to increase design awareness and reduce trial-and-error experimentation, bringing an intelligent guidance component into simulation. At the cost of a single adjoint simulation, any modification can be applied with CAD-level precision.
• rbfROC completes the framework as the module that directly connects geometric variations with the CAD world. It enables both mesh adaptation to different CAD configurations and CAD model updates to reflect simulated deformations, integrating into a single pipeline what typically requires completely separate tools and expertise.

From industrial design to the medicine of the future

The AI and VR technologies integrated into the platform are already operational in strategic sectors. In aerospace, companies can analyze full-scale aircraft before they even exist, evaluating modifications and performance in an immersive environment. In automotive, the convergence of engineering and design finds in VR a shared ground for faster and more informed decisions, with applications ranging from aerodynamics to styling.

In the medical field, demonstrators are being developed to help surgeons prepare complex procedures using interactive anatomical models, also thanks to the European project ROMed2VR dedicated to pediatric cardiac surgery. Here, advanced simulation and virtual reality open new perspectives for personalized clinical planning.
“Our collaboration with RBF Morph, strengthened through European projects such as Meditate, Copernicus, DITAiD, and now ROMed2VR, is enabling us to bring advanced simulation and virtual reality into the heart of cardiovascular medicine. Tools like rbfCAE offer new opportunities to better understand patient physiology and support clinicians in planning increasingly personalized treatments,” explains Simona Celi, Director of the Bioengineering Unit, Fondazione Toscana Gabriele Monasterio.

For RBF Morph, rbfCAE represents a strategic step toward a new generation of simulation tools.
“With rbfCAE, we bring artificial intelligence and virtual reality into the heart of design,” says Marco Evangelos Biancolini, founder of RBF Morph. “It is a paradigm shift that transforms simulation from a technical tool into an immersive and collaborative experience, capable of accelerating innovation across all industrial sectors.”