A Fragility-Based Approach Supporting Enhanced Resilience of Manned and Unmanned Surface Vessels Under Uncertain Demand
Abstract
Naval vessels operate under harsh environments and aggressive operational conditions. Their structural and non-structural systems ar e subjected to various extreme events throughout the service life. These events may include aggressive wave conditions, collisions, missile attacks, and underwater explosions, among others. The presence of deterioration due to normal operation may exacerbate the i mpact of these sudden events on the reliability of the vessel. In addition, the uncertainties associated with the demand arising fro m these extreme events adds to the challenges related to the performance quantification. Furthermore, with the increasing need for u nmanned surface vessels, questions often arise about the target performance level that should be met to ensure their resilience agai nst operational extreme events. In addition, the impact of different damage states on the functionality of the vessel and its abilit y to complete its mission should be well characterized. Unfortunately, current design and assessment approaches do not offer a prope r mechanism for specifying the desired system performance under various intensities of an extreme event. Moreover, traditional asses sment techniques and operational parameters, developed for manned vessels, may not be directly applicable to unmanned systems since they can operate under different conditions; especially, when the human factors are precluded. Accordingly, a new generation of desi gn and assessment approaches capable of systematically predicting the extent of damage under different intensities of an extreme eve nt are needed to (a) maintain an acceptable safety level under operational hazards and (b) reduce the failure risk and improve the r esilience of the vessel under extreme conditions. Such approaches will not only result in more efficient design and assessment proce sses, but they will also support risk and resilience informed decision-making throughout the service life of a vessel. This project harnesses the recent developments in machine learning, meta-modeling, and uncertainty quantification to develop a novel framework fo r assessing the fragility and enhancing the resilience of manned and unmanned surface vessels subjected to uncertain loading demand. The framework utilizes the digital twin of the system, and its surrogates, to determine the system-level performance criteria to be met under various demand levels arising from normal operational and extreme events. An approach for establishing the fragility prof iles of the system under the combined action of extreme events and gradual deterioration will be developed. These fragility profiles will be integrated into a holistic methodology for risk quantification that supports informed decision-making aiming at improving t he reliability and resilience of surface vessels. In addition, the research will establish a new class of probabilistic management p rocedures for ship hulls that can be applied throughout the service life to mitigate the risk associated with extreme events. Althou gh the developed approach can be applicable to various structural and non-structural systems within a surface vessel, the applicatio n of the framework will be illustrated on ship hulls. Large-scale experimental analysis on stiffened box girders will be designed an d conducted to validate and quantify the prediction accuracy of the developed fragility quantification approach. Ultimately, the pro ject will assist in solving complex decision-making problems related to enhancing the reliability and resilience of surface vessels.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Sep 07, 2021
- Source ID
- N000142112689
Entities
People
- Mohamed Soliman
Organizations
- Office of Naval Research
- Oklahoma State University–Stillwater
- United States Navy