Artificial Intelligence for Life Extension of Assets

In today’s economically challenging environment, the extension of your asset’s fatigue life has become critically important from an economic perspective and because often, the design life has already been exceeded. Recently, Geanti has developed a new and innovative fatigue assessment tool that achieves the extension of your asset’s design life through AI (Artificial Intelligence) which we can use in conjunction with our advanced Risk Based Approach.

Artificial Neural Networks (ANNs) are excellent in the prediction, damage detection, online monitoring and controlling in offshore structures especially in cases where the formal Finite Element Analysis (FEA) is complicated and time consuming. Geanti uses state-of-the-art Artificial Neural Networks methodology for structural fatigue assessment and structural life extensions. From our experience as well as from several literature studies/surveys it has been proven that ANNs provide more accurate results compared to conventional FE methods in terms of fatigue life. Furthermore, long term erosion and corrosion experienced in such structures require complex analyses when using conventional FE Analysis techniques. ANNs are comparatively faster, reliable as well as computationally inexpensive and thus reduce the overall cost of life extension studies.

Machine Learning in the Environmental Data Prediction

Short-term wave forecast methodology based on the Artificial Neural Network (ANN) concept to predict significant wave heights, zero-up-crossing wave periods and peak wave periods can be achieved from as little as 24 hours of measurement time history. Through our in-house research and development studies we now provide the best possible realistic wave data. For short term prediction of ocean waves, the neural network can be “trained” and thereafter it can be used for wave forecasting for that location.