In the quest to access valuable critical minerals, humankind is expanding the frontier into extreme
environments like space and deep-sea mining. These ambitious enterprises involve considerable
costs and lengthy development cycles to ensure the robustness of mining systems in the face of
the harshest conditions and unforeseen challenges. Unfortunately, obtaining information from
these unexplored territories is complicated. Data is often scarce, incomplete or impossible to obtain
until equipment is deployed, leaving engineers facing many uncertainties throughout the design,
testing, production and preparation of such missions. Despite these challenges, these extreme
environments operate under consistent physical and chemical principles that can be faithfully
digitally replicated. However, unexplored areas and dynamic systems like weather and geology
continue to carry uncertainties. While eliminating uncertainties remains elusive, Digital Twins offers
a means of robust risk management tool. These virtual replicas can excel in simulating extreme
conditions and unexpected events, helping optimise and validate mining system designs tailored
for such hostile environments.
This study takes inspiration from the Mars Science Laboratory (MSL) Curiosity Rover’s wheel
damage rate to develop a Multiphysics Modelling and Virtual Motion Simulation (MMVMS) system.
Using advanced Generative Design, this MMVMS system refines the MSL’s design, simulates
component and system performance, and assesses the risk of premature damage while operating
on Mars. Additionally, MMVMS integrates cutting-edge CAD design technologies from aerospace
and manufacturing to realistically recreate the Martian environment and a detailed representation
of MSL, allowing mobility verification and validation simulation to test different components in terms
of materials, design, weight, power and, therefore, cost. The research highlights the precision of
MMVMS in replicating extreme conditions, simulating and evaluating internal and external
variables influencing the entire system (Rover) in real-time, and predicting movements, failures,
and premature damage. This sophisticated Digital Twin technology, showcased in this research,
holds promise not only for space missions but also to be adapted for terrestrial and deep-sea
mining operations.