About the Customer
At the end of 2015, the XPRIZE foundation launched the Shell Ocean Discovery competition,
a three-year global challenge to advance deep-sea exploration using autonomous
subsea drones. Teams competed 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.
One of the competing teams was TEAMTAO, a collaboration of Newcastle University,
SMD (Soil Machine Dynamics Ltd), and UK Research and Innovation. Altair joined
the project as a technical design partner and provided the team with simulation expertise
to virtually simulate, optimize, and test the devices. The Altair simulation specialists
followed a simulation-driven design approach in order to save on development time
and physical prototyping.
TEAMTAO’s 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. At its core development, TEAMTAO strived for three main
principles: minimal localized complexity, self-sustainability, and scalability.
TEAMTAO’s unique concept was to develop a swarm of these devices all communicating
with each other and sharing information. Originally, the swarm included about 20 subsea
devices but could easily be scaled to higher numbers depending on the site being scanned.
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. For example, the team tested how the structure would deal with extremely
high pressures. The simulation also provided insights on how efficiently the device might
move from the surface to its target, whether the power requirements are sufficient
to get it from the start to the end position, and whether there might be any overheating
during that process.
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
While the team used a test tank to physically assess single components, they studied
larger assemblies by simulating their functions to learn if the structure would or would
not suffer any damage at depth. In addition to reaching structural efficiency, the system
model gave high-level insights on the control system for different scenarios like frequently
changing deep-sea currents at depths up to 4 km. The device still needed to be able to
find its way to the target position even though there was no constant data stream and the
passing of signals from the device to the surface was on a low frequency with big gaps of
time in-between. 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. Due to the multitude of difficult scenarios that can push
the device off target, the ability to make the device dive more efficiently is a key feature
of the digital twin.
“Using Altair solutions, TEAMTAO was able to test the
control system and the system behavior with the digital
twin prior to the field test. This virtual commissioning
allowed a rapid project progress and is also a promising
approach for the further development of the SMD offering.”
– Chris Wilkinson
Chief Technology Officer, SMD
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. By simulating and optimizing models of single components as well
as assemblies and entire systems, the team was able to develop a swarm system that can
bear high pressure in deep-sea while fully autonomously reaching its target position to
scan the sea floor. 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. In combination with
the structural simulation, this allowed for fast and focused design-to-prototype iterations.