EWP to develop Digital Twin Platform for Sea Wave Energy Technology

6 September, 2026

"An opportunity to fundamentally improve how we understand, design, predict and ultimately operate wave energy systems"

image above: An illustration of a digital model of a wave energy generation system. Source: EWP.

Eco Wave Power Global (EWP) announced that its wholly owned U.S. subsidiary, Eco Wave Power U.S, has entered into an agreement with Germany-based AI engineering GmbH to develop a physics- and data-driven Digital Twin platform for Eco Wave Power’s proprietary wave energy technology. Both Eco Wave Power U.S. and AI engineering are members of the NVIDIA Inception program.

Under the agreement, the companies have commenced Phase 1 of the project, combining advanced physics-based simulation with EWP’s real-world engineering, wave and operational data. The initial phase will focus on digitally modeling how ocean waves interact with EWP’s proprietary floaters. Using AI engineering’s PAMICS simulation technology, the companies will evaluate floater behavior, structural loads and theoretical energy input under different sea conditions.

“For us, AI is an opportunity to fundamentally improve how we understand, design, predict and ultimately operate wave energy systems,” said Inna Braverman, Founder and CEO of EWP. “Phase 1 of this collaboration is therefore very practical. We will model wave loading, floater behavior, structural forces and theoretical energy input, while beginning to develop machine-learning capabilities for forecasting loads and energy yield. Importantly, we will also examine how those models can be transferred to new sites with different wave conditions.”

Digital representation of EWP system

AI engineering is specializes in applied fluid mechanics, numerical flow simulation and high-performance computing. Its PAMICS technology is a particle-based multiphysics simulation framework designed for complex fluid-dynamics and fluid-structure interaction applications. “Wave energy is a particularly challenging engineering problem because it combines complex free-surface fluid dynamics, structural motion, and highly variable environmental conditions,” said Dr. Stefan Adami, Co-Founder and General Manager of AI engineering GmbH.

“Our goal is to create a physics-based digital representation of Eco Wave Power’s system that links high-fidelity simulation with operational data. This approach allows us to better understand energy capture, structural loading, and system behavior across a wide range of sea states. Combining these physics models with ML can support more accurate forecasting, design optimization, and scalable deployment of wave energy technology.”

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