Structural Hybrid Layer for Critical Strain Detection in Composite Parts: A Multifunctional Approach

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

The rapid expansion of composite structures in different fields such as aerospace and automotive industries has highlighted the need for a new
generation of hybrid materials able to overcome the current limitations of traditional laminates. In particular, because of their intrinsic layered structure,
composite materials are sensible to impact damage that can generate internal damage that, if not detected, can lead to critical failures over short periods of time. In this context, a multifunctional approach would guarantee an extension
of the life of the composite part by intervening simultaneously on two different aspects: first, the weak out-of-plane properties of the laminate need to be enhanced by introducing an additional hybrid phase within the composite structure and second, critical loads and internal damaged areas need to be
immediately detected by monitoring the variation over time of specific electrical properties measured on the same embedded hybrid phase. By operating on both fronts (mechanical and non-mechanical) a true novel multifunctional material can be developed, able to resist to harsh environments and guarantee in-situ structural health monitoring features.
This work is focused on the development of a smart hybrid composite layer that can be used in traditional manufacturing procedures and it is obtained by
embedding an array of metal wires (e.g. copper, steel and Shape Memory Alloys) at specific depths within the structure of a traditional fibres reinforced
polymer (FRP). The correct location and specific nature of the wires was evaluated via a mechanical tests campaign in order to optimise the
enhancement of the impact resistance, while the non-structural properties were tested by monitoring the variation of specific electrical properties (e.g.
resistance and impedance) during flexural and push tests. The outcomes from the mechanical tests campaign were compared with those of traditional FRP
samples while the feasibility and resolution of the SHM feature was analysed against traditional NDT techniques such as C-Scan or Phased Array. Results
showed that by including the Structural Hybrid Layer within a traditional laminate it is possible to increase the total safety of a structure by enhancing its
reliability and at the same time to reduce maintenance costs via in-situ SHM.
Original languageEnglish
Title of host publicationStructural Health Monitoring 2017
Subtitle of host publicationReal-Time Material State Awareness and Data-Driven Safety Assurance
EditorsFu-Kuo Chang, Fotis Kopsaftopoulos
Pages1 - 8
Number of pages8
VolumeProceedings of the Eleventh International Workshop on Structural Health Monitoring
Publication statusPublished - Sep 2017
Event11th International Workshop on Structural Health Monitoring 2017: Real-Time Material State Awareness and Data-Driven Safety Assurance, IWSHM 2017: Real-Time Material State Awareness and Data-Driven Safety Assurance - Stanford University, Stanford, USA United States
Duration: 12 Sep 201714 Sep 2017
http://web.stanford.edu/group/sacl/workshop/IWSHM2017/index.html

Conference

Conference11th International Workshop on Structural Health Monitoring 2017: Real-Time Material State Awareness and Data-Driven Safety Assurance, IWSHM 2017
Abbreviated titleIWSHM 2017
CountryUSA United States
CityStanford
Period12/09/1714/09/17
Internet address

Fingerprint

Laminates
Composite structures
Composite materials
Electric properties
Wire
Impact resistance
Fibers
Monitoring
Aerospace industry
Structural health monitoring
Hybrid materials
Polymers
Nondestructive examination
Shape memory effect
Automotive industry
Copper
Steel
Metals
Costs

Cite this

Rizzo, F., Iervolino, O., Pinto, F., & Meo, M. (2017). Structural Hybrid Layer for Critical Strain Detection in Composite Parts: A Multifunctional Approach. In F-K. Chang, & F. Kopsaftopoulos (Eds.), Structural Health Monitoring 2017: Real-Time Material State Awareness and Data-Driven Safety Assurance (Vol. Proceedings of the Eleventh International Workshop on Structural Health Monitoring, pp. 1 - 8)

Structural Hybrid Layer for Critical Strain Detection in Composite Parts: A Multifunctional Approach. / Rizzo, Francesco; Iervolino, Onorio; Pinto, Fulvio; Meo, Michele.

Structural Health Monitoring 2017: Real-Time Material State Awareness and Data-Driven Safety Assurance. ed. / Fu-Kuo Chang; Fotis Kopsaftopoulos. Vol. Proceedings of the Eleventh International Workshop on Structural Health Monitoring 2017. p. 1 - 8.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Rizzo, F, Iervolino, O, Pinto, F & Meo, M 2017, Structural Hybrid Layer for Critical Strain Detection in Composite Parts: A Multifunctional Approach. in F-K Chang & F Kopsaftopoulos (eds), Structural Health Monitoring 2017: Real-Time Material State Awareness and Data-Driven Safety Assurance. vol. Proceedings of the Eleventh International Workshop on Structural Health Monitoring, pp. 1 - 8, 11th International Workshop on Structural Health Monitoring 2017: Real-Time Material State Awareness and Data-Driven Safety Assurance, IWSHM 2017, Stanford, USA United States, 12/09/17.
Rizzo F, Iervolino O, Pinto F, Meo M. Structural Hybrid Layer for Critical Strain Detection in Composite Parts: A Multifunctional Approach. In Chang F-K, Kopsaftopoulos F, editors, Structural Health Monitoring 2017: Real-Time Material State Awareness and Data-Driven Safety Assurance. Vol. Proceedings of the Eleventh International Workshop on Structural Health Monitoring. 2017. p. 1 - 8
Rizzo, Francesco ; Iervolino, Onorio ; Pinto, Fulvio ; Meo, Michele. / Structural Hybrid Layer for Critical Strain Detection in Composite Parts: A Multifunctional Approach. Structural Health Monitoring 2017: Real-Time Material State Awareness and Data-Driven Safety Assurance. editor / Fu-Kuo Chang ; Fotis Kopsaftopoulos. Vol. Proceedings of the Eleventh International Workshop on Structural Health Monitoring 2017. pp. 1 - 8
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