Technology Category
- Analytics & Modeling - Digital Twin / Simulation
- Platform as a Service (PaaS) - Device Management Platforms
Applicable Industries
- Electronics
- Equipment & Machinery
Applicable Functions
- Product Research & Development
- Quality Assurance
Use Cases
- Digital Twin
- Virtual Prototyping & Product Testing
Services
- System Integration
- Testing & Certification
About The Customer
TEAMTAO is a collaboration of Newcastle University, SMD (Soil Machine Dynamics Ltd), and UK Research and Innovation. They were one of the competing teams in the Shell Ocean Discovery competition, a global challenge to advance deep-sea exploration using autonomous subsea drones. Their goal was to change the way ocean data is collected by developing a low-cost platform using a ‘CubeSat’ like philosophy. The compact autonomous platform consisted of the BEMs (Bathypelagic Excursion Module), a swarm of vertically swimming AUVs and the surface vessel. It also had a 'vending machine' style autonomous surface catamaran that was responsible for the horizontal transit, data handling, communication, and recharging of the BEMs.
The Challenge
TEAMTAO, a collaboration of Newcastle University, SMD (Soil Machine Dynamics Ltd), and UK Research and Innovation, was competing in the Shell Ocean Discovery competition, a global challenge to advance deep-sea exploration using autonomous subsea drones. The goal was to develop underwater robots that could fully map 500 km2 of seafloor at a 4 km depth in less than 24 hours with no human intervention. TEAMTAO’s unique concept was to develop a swarm of these devices all communicating with each other and sharing information. The compact autonomous platform consisted of the BEMs (Bathypelagic Excursion Module), a swarm of vertically swimming AUVs and the surface vessel. It also had a 'vending machine' style autonomous surface catamaran that was responsible for the horizontal transit, data handling, communication, and recharging of the BEMs. The challenge was to test the devices in a range of different scenarios at deep depths without risking the prototype.
The Solution
To virtually test the devices upfront and to predict what would happen in a range of different scenarios at deep depths without risking the prototype, TEAMTAO turned to Altair. Altair deployed computer aided engineering (CAE) tools from the Altair HyperWorks™ suite such as the nonlinear finite element solver Altair Radioss™, to understand the stressing of the mechanical components. Altair Activate® was used for electro-mechanical system development and Altair Compose® was used to study the custom loading routines. Altair OptiStruct™ was used for static stressing of components and structural topology optimization. A digital twin was used to collect data from the physical system in order to inform the digital model and control system how to further improve the capability and efficiency of the physical devices. This allowed for fast and focused design-to-prototype iterations.
Operational Impact
Quantitative Benefit
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