A probabilistic approach for design and certification of self-healing advanced composite structures

H R Williams, R S Trask and I P Bond

Journal of Risk and Reliability, 2011, vol. 225, issue 4, 435-449

Abstract: Design and certification of novel self-healing aerospace structures was explored by reviewing the suitability of conventional deterministic certification approaches. A sandwich structure with a vascular network self-healing system was used as a case study. A novel probabilistic approach using a Monte Carlo method to generate an overall probability of structural failure yields notable new insights into design of self-healing systems, including a drive for a faster healing time of less than two flight hours. In the case study considered, a mature self-healing system could be expected to reduce the probability of structural failure (compared to a conventional damage-tolerant construction) by almost an order of magnitude. In a risk-based framework this could be traded against simplified maintenance activity (to save cost) and/or increased allowable stress (to allow a lighter structure). The first estimate of the increase in design allowable stresses permitted by a self-healing system is around 8 per cent, with a self-healing system much lighter than previously envisaged. It is thought these methods and conclusions could have wider application to self-healing and conventional high-performance composite structures.

Keywords: self-healing; self-repair; composite; Monte Carlo; certification; impact damage; sandwich structure (search for similar items in EconPapers)
Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/1748006X10397847 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:risrel:v:225:y:2011:i:4:p:435-449

DOI: 10.1177/1748006X10397847

Access Statistics for this article

More articles in Journal of Risk and Reliability
Bibliographic data for series maintained by SAGE Publications ().