Integrated Health Monitoring and Non-destructive Testing of Composite Structures

National Laboratory: 
Pacific Northwest National Laboratory
Characterization Class: 
Non-destructive examination
Computational Tools Class: 
Data Tools
Structure-Properties
Description: 

Structural health monitoring (SHM) can be defined as the process of on-demand, automated condition monitoring, or continuous self-interrogation of the state of health of a structure over its service lifetime. SHM requires a set of transducers that are energized either through passive or active sources of power and are generally mounted on a structure's surface. Alternatively, the transducers also may be integrated within the material system itself during the manufacturing stages and have the potential for process and quality control.

Ultrasound-waves-based SHM of composite structures enables automated detection and localization of damage precursors and flaws in real-time, as well as impact-induced damage. The following SHM tasks typically are envisioned:

  • Real-time detection, via active sensor networks, of material changes that are precursors to failures (e.g., inter-laminar delamination, matrix-fiber debonding).
  • Using large-scale data analytics tools, real-time damage assessment (i.e., characterization of severity and location) in composite structures.
  • Real-time detection and characterization (severity and location) of non-penetrating impact-induced damage, especially delamination between plies of composite laminated structures.
  • Integrated passive and active monitoring and diagnostic system extended by numerical models and prognostic algorithms for lifetime prediction of composite structures.

A key capability at PNNL is the ability to integrate sensor design, data analytics, and materials testing. This capability enables instrumented tests of composite materials under varying materials aging factors (mechanical, thermal, and radiation, either singly or jointly). Large-scale testbeds can be leveraged for SHM research and development toward generating large-scale data sets for technique validation, reliability assessments of SHM sensors and algorithms, and evaluation of SHM solutions from collaborators (national laboratories, universities, and commercial partners).

Capability Bounds: 

SHM ultrasonic transducers currently have an upper operating temperature limit of ~350°C. SHM requires direct contact between the transducers and the material or structure being monitored and communication networks for exfiltrating sensor measurements from the SHM sensors.

Unique Aspects: 

PNNL has integrated capabilities for non-destructive testing (NDT) and SHM that include ultrasonic transducer and sensor network design, finite element modeling and simulation, laboratories for accelerated material aging experiments (including aging from mechanical, thermal, and radiation effects, either singly or jointly) and experimental validation, and prognostic algorithms to predict failures and remaining life.

Availability: 

PNNL has integrated capabilities for non-destructive testing (NDT) and SHM that include ultrasonic transducer and sensor network design, finite element modeling and simulation, laboratories for accelerated material aging experiments (including aging from mechanical, thermal, and radiation effects, either singly or jointly) and experimental validation, and prognostic algorithms to predict failures and remaining life.

Single Point of Contact: 

Name: Darrell Herling
Email: darrell.herling@pnnl.gov
Phone: 509-375-6910

References: 
  1. Roy, S., Mueller, I., Janapati, V., Das, S., Chang, F.-K. 2012. 'Real-time prediction of impact-induced damage for composite structures based on failure analysis and efficient database methods,' Proceedings of SPIE Annual Conference on Smart Structure & NDE 2012, San Diego, California, 8348-55.
  2. Dib, G., Koricho, E., Karpenko, O., Haq, M., Udpa, L., Udpa, S. 2015. 'Feasibility of PZT ceramics for impact damage detection in composite structures,' Proceedings of 41st Annual Review of Progress in Quantitative Nondestructive Evaluation 2015, Boise, Idaho.
  3. .Ramuhalli, P., Roy, S., Chai, J. 2016. 'Online Monitoring and Prognostics for Passive Components in Nuclear Power Plants,' Nuclear Science and Engineering, vol. 182.
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