Scripts and data for application of the Adaptive Screening method to three applications
doi: 10.4121/f1348609-c912-4d06-82b8-197c01f3437b
CC BY 4.0
This set of scripts and data files can be used to re-generate the Adaptive Screening method and the three applications described in the paper "Designing for dangerous waves – definition and application of a new ‘Adaptive Screening’ method to predict extreme values of non-linear ship responses to waves".
Predicting extreme values of strongly non-linear ship responses (such as wave impact loads) is crucial for ensuring safety and performance of maritime structures. However, this is challenging due to the complexity and rarity of the responses. Existing methods are limited, as they are either suitable for weakly non-linear responses only, or are very computationally intensive. The paper above in combination with this dataset introduces a new event-based multi-fidelity method called ‘Adaptive Screening’ to efficiently predict extreme values of strongly non-linear wave-induced responses. It combines elements of screening, multi-fidelity Gaussian Process Regression, and adaptive sampling. Three applications validate the effectiveness of the new method in the paper: one weakly non-linear case where we predict extreme values of second-order waves, one intermediate case where we predict extreme values of vertical bending moments, and one strongly non-linear case where we predict extreme values of green water impact loads. The input necessary to reproduce applications 1 and 2 is also included in the dataset (application 3 relies on proprietary data, which are not part of this repository).
The paper demonstrates that Adaptive Screening outperforms conventional brute-force methods, achieving comparable accuracy in predicting extreme values while significantly reducing high-fidelity simulation times (especially for the most non-linear cases). Like many alternative methods, Adaptive Screening relies on a response-dependent low-fidelity indicator variable. We also show that the method performs well with realistic indicators for a range of applications. The test cases indicate that Adaptive Screening is very promising for the strongly non-linear responses it was designed for.
- 2024-02-16 first online
- 2024-11-07 published, posted
DATA
- 32,731,722 bytesMD5:
1aacd0125c695788f826597a13c8ea90Repository_scripts_4TU.zip -
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