We build bespoke design optimisation software for any floating offshore structure

“Coming from a design process which involved slow optimisation directly with Orcaflex, I have been blown away by the speed and the accuracy of the neural networks. It enabled us to produce a Pareto plot in about 10 minutes showing the optimum design was very close to what 3 months of induction and manual iteration had converged to. I still like to manually review key simulations to understand the behaviour of the system but now we have covered a much wider design space in such a fast time that I can spend longer reviewing the results and generate fresh optimisation runs, improving the design further.” –

“When I learnt about xmoor’s work, I immediately saw the potential. With Python automation of time-domain problems, we can gain insight into large or complex design spaces, but we can also lose time and money spent solving and post-processing. By augmenting our design process with the neural network tool, we could achieve the same and more, orders of magnitude quicker.

However, what impressed me the most was the ability to apply Pareto optimisation to multi-objective design problems. When non-linear hydrodynamics and mechanical engineering come together, and you need a cost-optimal solution to succeed in the market, which is the case for floating renewables generally, this combination of ANN + Optimisation is the future for me.”