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Finite Element Modeling of Flash Thermographic Detection of Defect in a Steel Plate REU Fellow: Eric Feigin Mentor: Dr. Mannur Sundaresan July 27, 2018 NSF REU EMCoR@NCAT Grant # ACI-1560385 Motivation Defects are inevitable in


  1. Finite Element Modeling of Flash Thermographic Detection of Defect in a Steel Plate REU Fellow: Eric Feigin Mentor: Dr. Mannur Sundaresan July 27, 2018 NSF REU EMCoR@NCAT Grant # ACI-1560385

  2. Motivation ▪ Defects are inevitable in structures that are made of metal, composites or hybrid ▪ During flight – runway debris or foreign particles ▪ During fabrication or maintenance – dropping tools, walking over parts ▪ To identify these defects Non Destructive Evaluation (NDE) technologies are used ▪ Nondestructive testing is a wide group of analysis techniques used in science and technology industry to evaluate the properties of a material, component or system without causing damage. ▪ NDE techniques are Acoustic Emission, ultrasonic testing, thermography etc. EMCOR@NCAT North Carolina NSF Grant Agricultural and Technical State University

  3. Motivation ▪ Flawless manufacturing techniques are rarely achieved in the field, so inspection techniques are vital. ▪ Pulse or flash thermography is used to display differences in the decay of heat throughout a surface from a normal thermal flow in order to detect subsurface defects. ▪ Difficulties arise in simulating multiple differences in multiple materials to generate accurate results that can be experimentally calibrated ▪ Used to compare to field results to identify unknown defects and their dimensions. ▪ Takes a lot of time to create multiple thermographic profiles examining temperature with relation to time/length of profile EMCOR@NCAT North Carolina NSF Grant Agricultural and Technical State University

  4. Motivation EMCOR@NCAT North Carolina NSF Grant Agricultural and Technical State University

  5. Literature Review ▪ Sundaresan, M., & Sripragash, L. (2016). A normalization procedure for pulse thermographic nondestructive. NDT&E International, 14-23. ▪ Thermography ▪ Inspector uses infrared camera (IR) in a passive mode to measure the steady state surface temperature of a component ▪ Assesses large areas of structures in a relatively short duration of time, with heat applied to the surface of the test object by an external energy source (IR camera). ▪ Due to heat pulse, temperature rises instantly resulting in change of surface temperature. ▪ Rate of change of surface temperature is function of time. EMCOR@NCAT North Carolina NSF Grant Agricultural and Technical State University

  6. Literature Review ▪ Krishnapillai, M., Jones, R., Marshall, I., Bannister, M., & Rajic, N. (2006). NDTE using pulse thermography: Numerical modeling. Composite Structures, 241-249. ▪ Pulse Thermography ▪ A flash or pulse of heat is introduced for a fraction of a second ▪ Used to display differences in the decay of heat throughout a surface from a normal thermal flow. ▪ Thermography Technique Benefits ▪ Scanning broad areas ▪ Efficient prediction capabilities for anomalies underneath surfaces EMCOR@NCAT North Carolina NSF Grant Agricultural and Technical State University

  7. Literature Review ▪ Sundaresan, M., & Sripragash, L. (2016). A normalization procedure for pulse thermographic nondestructive. NDT&E International, 14-23. ▪ Temperature Contour Plot ▪ Measures temperature of pixels with respect to time and length along the profile ▪ Shows heat flow through surface with curved lines showing effect of defect EMCOR@NCAT North Carolina NSF Grant Agricultural and Technical State University

  8. Literature Review ▪ Sundaresan, M., & Sripragash, L. (2016). A normalization procedure for pulse thermographic nondestructive. NDT&E International, 14-23. ▪ 𝛽 is the diffusivity of the plate given by 𝜆 𝛽 = 𝑞𝑑 ▪ With 𝜆 as thermal conductivity, 𝑞 as density, and 𝑑 as heat capacity of the plate. t* 𝑀 2 𝑢 ∗ = 𝜌𝛽 ▪ With L as the thickness of the plate EMCOR@NCAT North Carolina NSF Grant Agricultural and Technical State University

  9. Literature Review ▪ Shepard, S. M., Lhota, J. R., Rubadeux, B. A., Wang, D., & Ahmed, T. (2003). Reconstruction and enhancement of active thermographic image sequences. Optical Engineering. ▪ Thermographic Signal Reconstruction ▪ Time-derivative images help identify subsurface defects ▪ A logarithmic scale is used to compare the time history of every pixel in the field of view, as changes from ideal behavior are easily identifiable EMCOR@NCAT North Carolina NSF Grant Agricultural and Technical State University

  10. Literature Review ▪ Thermographic Signal Reconstruction (cont.) ▪ Use time of first peak in second derivative of natural log of time versus natural log of pixel temperature to determine defect depth 𝑀 𝑒2 𝑢 𝑒 = 𝜌𝛽 ▪ In which t d is the time and L d is the defect depth EMCOR@NCAT North Carolina NSF Grant Agricultural and Technical State University

  11. Literature Review ▪ Mucha, M. (n.d.). Heat transfer analysis in ABAQUS. Kraków, Poland. ▪ Bathe, K.-J. (2009). Why to Study Finite Element Analysis. Cambridge, Massachusetts, United States ▪ The thermography process can be simulated using Finite Element Analysis tools such as ABAQUS. ▪ Finite element analysis is a numerical method for solving problems of engineering and mathematical physics. ▪ It subdivides a large problem into smaller, simpler parts that are called finite elements. ▪ The simple equations that model these finite elements are then assembled into a larger system of equations that models the entire problem. ▪ Abaqus is a Finite Element Analysis software that can simulate incredibly complicated components, structures and systems under a wide variety of situations and loading conditions. EMCOR@NCAT North Carolina NSF Grant Agricultural and Technical State University

  12. Research Goals ▪ Examine effect of defect on steel plate through plots for thermographic profile ▪ Use AISI 1018 Mild/Low Carbon Steel ▪ Use Abaqus to build a model and simulate transient heat transfer with pulse thermography ▪ Have temperature contour plot displaying effect of defect on heat flow ▪ Create graph of time versus temperature for nodes ▪ First and Second Derivative plots as well to measure expected numerically calculated depth to actual defect depth ▪ Be able to use my results in application to different metals, composites, hybrids whose properties are known EMCOR@NCAT North Carolina NSF Grant Agricultural and Technical State University

  13. Methodology ▪ Abaqus takes inputs for boundary conditions, such as the geometry of the surface or part, the type of load applied, the amplitude of the load, which set the load will be applied across, etc. ▪ Mesh is an arrangement of finite elements defined on an FEA model ▪ Once Abaqus has defined elements, it can solve multiple differential equations ▪ The user does not have to perform any physical calculations, Abaqus evaluates the temperature between steps of time (either user-inputted or automatically generated). EMCOR@NCAT North Carolina NSF Grant Agricultural and Technical State University

  14. Methodology ▪ Abaqus Use and Model Creation ▪ Following (Mucha) in steps for building model and running heat transfer analysis ▪ Geometry – 1.5 inch length by .5 inch height initial plate (cross section) ▪ .5 inch length by .4 inch height defect from bottom left corner ▪ Properties of AISI 1018 Mild/Low Carbon Steel used – density, conductivity, specific heat capacity EMCOR@NCAT North Carolina NSF Grant Agricultural and Technical State University

  15. Methodology ▪ Increment minimum of .0001 seconds and maximum of .05 ▪ Field/History Output request – only thermal data extracted ▪ Amplitude – temperature rises to 100000 degrees Celsius, remains for 1 millisecond, drops to zero for duration of job ▪ Meshed with approximate size of .0025 meters for each element. EMCOR@NCAT North Carolina NSF Grant Agricultural and Technical State University

  16. Methodology ▪ Numerical Modeling ▪ Abaqus, a finite element analysis software, finds the temperature change over time for each individual element/node ▪ Data is exported to Excel through Abaqus’ Excel plug -in ▪ First set of graphs ▪ Get rid of repeated data in Excel (time is repeated for each set of nodal temperatures) ▪ Use MATLAB ▪ Natural log of time versus natural log of temperature using log() command ▪ Use diff () function to create first and second derivatives of ln(temperature) with respect to ln(time) and plot versus ln(time) EMCOR@NCAT North Carolina NSF Grant Agricultural and Technical State University

  17. Methodology ▪ Contour Plot ▪ Create vector in MATLAB of nodal distance – distance divided by number of nodes with successive distance along path corresponding to node number ▪ Use contour and contourcbar commands in MATLAB to create contour plot of temperature with respect to distance along surface as well as natural log of time ▪ Download Mapping Toolbox for MATLAB if not working with full version ▪ Plot shows effect of defect not only for time but for how temperature changes along the surface in the x direction EMCOR@NCAT North Carolina NSF Grant Agricultural and Technical State University

  18. Results EMCOR@NCAT North Carolina NSF Grant Agricultural and Technical State University

  19. Results Abaqus results – see change of heat wave throughout surface ▪ Different colors at end as compared to animation – nodal temperature ▪ values very similar at end of simulation EMCOR@NCAT North Carolina NSF Grant Agricultural and Technical State University

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