Altair Case Studies TEAMTAO: Revolutionizing Deep-Sea Exploration with IoT and Simulation

	TEAMTAO: Revolutionizing Deep-Sea Exploration with IoT and Simulation Altair

TEAMTAO: Revolutionizing Deep-Sea Exploration with IoT and Simulation

Altair

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
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. Read More
About 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. Read More
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. Read More Log in to view content
Contents

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

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.

About 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.

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.

Impact #1	TEAMTAO was the only UK team and one of the smallest teams to reach the grand final of the XPRIZE. During the final round of testing, TEAMTAO successfully demonstrated their autonomous swarm system technology and competed against seven other teams from around the world to map an area the size of Paris in deep waters off the coast of Greece near the port of Kalamata. TEAMTAO was honored for their exceptional accomplishments and in recognition of their highly innovative approach with the $200,000 Moonshot Award. Using simulation to predict how the devices behave makes them more robust for scenarios that can’t be predicted. The full model also provided a parallel digital twin of the system, so any new aspect is able to be quickly considered and built into the system.

Impact #1

TEAMTAO was the only UK team and one of the smallest teams to reach the grand final of the XPRIZE. During the final round of testing, TEAMTAO successfully demonstrated their autonomous swarm system technology and competed against seven other teams from around the world to map an area the size of Paris in deep waters off the coast of Greece near the port of Kalamata. TEAMTAO was honored for their exceptional accomplishments and in recognition of their highly innovative approach with the $200,000 Moonshot Award. Using simulation to predict how the devices behave makes them more robust for scenarios that can’t be predicted. The full model also provided a parallel digital twin of the system, so any new aspect is able to be quickly considered and built into the system.

Benefit #1	Shorter development cycles
Benefit #2	Fewer prototypes
Benefit #3	Less physical testing

Benefit #1

Shorter development cycles

Benefit #2

Fewer prototypes

Benefit #3

Less physical testing

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Overview

TEAMTAO: Revolutionizing Deep-Sea Exploration with IoT and Simulation

Operational Impact

Quantitative Benefit