High Throughput Fatigue Characterization
Abstract
Fatigue failure represents one of the primary structural failure modes in sea-based aviation. Yet,reliable prediction remains a challenge. This has resulted in conservative maintenance programs,overdesigned structures, and unexpected failures. The challenge of predicting high cycle fatiguehas persisted partly due to engineering and research efforts operating in a data starved modality,which is due to the highly stochastic nature of fatigue data and the expense of collecting such data.The proposed work aims to overcome this deficiency utilizing recent technological advancements.Preliminary work suggests that a high throughput fatigue testing methodology that conforms withcommon standards is indeed possible and could have a wide range of applications, from traditionallegacy alloys to additively manufactured materials and repairs. The proposed work will test thisassertion, and if successful will provide a framework that enables large fatigue data sets to be morecommonly collected. This innovation would not only benefit existing life assessment efforts, butwould provide the necessary ingredient to harness the emerging power of artificial intelligence forboth fatigue prognosis and integrated computational materials engineering (ICME) frameworksaimed at rapidly exploring and qualifying materials for fatigue critical applications.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- May 08, 2020
- Source ID
- N000142012484
Entities
People
- Derek Warner
Organizations
- Cornell University
- Office of Naval Research
- United States Navy