1. Peter B. Nagy Department of Aerospace Engineering University of Cincinnati Cincinnati, Ohio 45221-0070 Electromagnetic Materials State Awareness Monitoring

2. Past and Present Goals Health Monitoring and Materials Damage Prognosis for Metallic Aerospace Propulsion and Structural Systems (FY06 DoD MURI BAA, AFOSR) Integrated with Structure ● enables real-time monitoring ● in-situ interrogation, reduces costly tear-down ● integrated with autonomic logistic methods Integrated with Prognosis ● sensitive to microstructural change and damage evolution ● quantitative probabilistic life prediction rather than warning ● integrated with physics-based materials damage models

3. Future Goals: Materials State Awareness Prognosis of Aircraft and Space Devices, Components, and Systems (Discovery Challenge Thrust, AFOSR, 2008) Problem Determine in real time the current state so that the remaining capabilities of the system or component can be predicted with a high degree of accuracy and known level of confidence ● for any material systems and material processing ● operational environments, component usage history ● failure or material/structure/system degradation mode monitoring community prognostics community Is there a sufficient finite set of parameters? Can a specific set of parameters be determined? What can we monitor? What can we predict?

4. Technology Challenges (Discovery Challenge Thrust, AFOSR, 2008) ● Assess early and progressive changes in material state associated with operational usage and exposure. ● Predict the real-time physical, chemical or electronic state at any location for complex systems subject service loads and environmental exposure over time. ● Relate the current and evolving state of microstructure and damage processes to enable probabilistic prognosis modeling of the material/structural/system state. monitoring community prognostics community Is there a sufficient finite set of parameters? Can a specific set of parameters be determined? What can we monitor? What can we predict?

5. What Can We Monitor? ● microstructure ● phase transformation ● plastic strain ● elastic strain ● hardening ● embrittlement ● creep damage ● fatigue damage etc. ● crack initiation ● crack growth ● impact damage ● erosion ● corrosion etc. by electromagnetic means (measuring electric signals produced by electric, magnetic, or thermal stimulus) ● material state ● component state ● structure state ● system state ● service loads ● environment etc. ● electric conductivity ● magnetic permeability ● thermal conductivity ● thermoelectric power ● electric conductance ● magnetic conductance ● thermal conductance sensitivity selectivity

6. Example I: Microstructure Evolution seven different nickel-base powder-metallurgy alloys (Ni, Al, Cr, Fe) after five different heat temper NAC1NAC2NAF1NAF2NACF1NATNACF2 10 -5 10 -4 10 -3 10 -2 10 -1 10 +0 Alloy Designation Magnetic Susceptibility.. 1.0 1.5 2.0 2.5 3.0 Alloy Designation AECC [%IACS] -5 0 5 10 15 Alloy Designation Thermoelectric Power [μV/°C] ● material state ● electric conductivity ● magnetic permeability ● thermoelectric power ● microstructure evolution ● phase transformation ● hardening ● embrittlement ● elastic strain etc.

7. Example I: Microstructure Evolution NAF1-1 nickel-base powder-metallurgy alloy (70.5% Ni, 24.5% Al, 0% Cr, 5% Fe) room temperature ● material state ● electric conductivity ● microstructure evolution ● phase transformation ● hardening ● embrittlement ● elastic strain etc.

8. Example I: Microstructure Evolution NAC2-1 nickel-base powder-metallurgy alloy (65.5% Ni, 24.5% Al, 10% Cr, 0% Fe) room temperature ● material state ● electric conductivity ● microstructure evolution ● phase transformation ● hardening ● embrittlement ● elastic strain etc.

9. Example II: Elastic Strain residual stress assessment in surface-treated nickel-base superalloys 10 6 2 without residual stress with opposite residual stress Fatigue Life [cycles] 10 4 8 0 500 1000 1500 endurance limit service load natural life time increased life time Alternating Stress [MPa] ● material state ● component state ● electric conductivity ● elastic strain ● plastic strain ● microstructure evolution ● phase transformation ● hardening etc.

10. Example II: Elastic Strain electric conductivity versus uniaxial elastic strain in various metals ● electric conductivity ● material state ● elastic strain parallel -0.004 -0.002 0 0.002 0.004 -0.00100.0010.002 τ ua / E   Δσ / σ 0 normal Copper Ti-6Al-4V parallel -0.004 -0.002 0 0.002 0.004 -0.00200.0020.004 τ ua / E   Δσ / σ 0 normal parallel -0.004 -0.002 0 0.002 0.004 -0.00100.0010.002 τ ua / E   Δσ / σ 0 normal Al 2024 parallel -0.004 -0.002 0 0.002 0.004 -0.00100.0010.002 τ ua / E   Δσ / σ 0 normal Al 7075 Waspaloy parallel -0.004 -0.002 0 0.002 0.004 -0.00200.0020.004 τ ua / E   Δσ / σ 0 normal IN718 parallel -0.004 -0.002 0 0.002 0.004 -0.00200.0020.004 τ ua / E   Δσ / σ 0 normal

11. ● elastic strain ● plastic strain ● microstructure ● material state ● electric conductivity Example II: Elastic Strain eddy current spectroscopy in shot-peened IN100 eddy current– solid circles, XRD – open squares κ ip = -1.06 (+33% “empirical” correction of AECC data)

12. Example III: Plastic Strain effect of uniaxial plastic strain in various nickel-base superalloys at room temperature 500 kHz Normalized Electro-Elastic Coefficient 0 1 2 01020304050 Cold Work [%] IN718 Waspaloy 300 kHz ● piezoelectricity ● magnetic permeability ● electric conductivity ● material state ● plastic strain

13. Example III: Plastic Strain 304 austenitic stainless steel, 15% plastic strain ● magnetic permeability ● electric conductivity ● material state ● plastic strain 0.000 0.001 0.002 0.003 0.004 RT 50ºC 100ºC150ºC200ºC250ºC intact Magnetic Susceptibility 2.60 2.62 2.64 2.66 2.68 2.70 AECC [%IACS] | RT 50ºC 100ºC150ºC200ºC250ºC intact

14. Example IV: Thermal Exposure microstructure evolution thirty-two as-forged Waspaloy specimens subsequent heat treatments of 24 hours thermal relaxation Waspaloy, Almen 8A, repeated 24-hour heat treatments at increasing temperatures ● microstructure ● elastic strain ● material state ● electric conductivity

15. Example VI: Thermal Relaxation ● material state ● thermoelectric power ● elastic strain ● plastic strain ● microstructure evolution ● phase transformation ● hardening etc. 0481216 Almen Intensity (A) 0 1 2 3 4 5 6 7 8 Magnetic Signature [nT] series 1 (intact) series 2 (intact) series 1 (565 °C) series 2 (675 °C) shot-peened C11000 Copper noncontacting thermoelectric inspection shot-peened IN100

16. Example V: Microstructure Evolution A503 ferritic steel, thermal embrittlement (β = 0.00123 ºC -1 ) ● material state ● thermoelectric power ● microstructure evolution ● phase transformation ● hardening ● embrittlement ● elastic strain etc.

17. Example VI: Corrosion and Erosion ½”-thick 304 austenitic stainless steel, thermal embrittlement (β = 0.00117 ºC -1 ) ● electric resistance ● component state ● crack growth ● corrosion ● erosion etc. erosion events

18. Example VII: Creep Damage directionally solidified GTD-111 coarse grained GTD-111 ● microstructure ● plastic strain ● material state ● electric anisotropy 0.99 1 1.01 1.02 00 0.25 0.5 0.60.9 11 222 Creep Strain [%] Anisotropy Factor

19. Conclusions Electromagnetic methods offer unique opportunities for materials state awareness monitoring. A variety of sensors can be built based on electric, magnetic, electromagnetic, and thermoelectric principles. These very simple and robust sensors can detect and quantitatively characterize subtle environmentally-assisted and/or service- related changes in the state of metals, such as microstructural evolution, phase transformation, plastic deformation, hardening, residual stress relaxation, increasing dislocation density, etc. In most cases, the detection sensitivity is sufficiently high for the purposes materials state awareness monitoring and the feasibility of the sensing method is mainly determined by its selectivity, or the lack of it, to a particular type of damage mechanism.

20. Thank You!