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Thermography has been shown to be a viable technique for inspection of composites. Impact damage in composites typically contains multiple overlapping delaminations at different depths. Understanding the limitations of the thermographic inspection is enhanced by performing simulations of the technique. Most simulations of composite thermographic inspections have focused on simulations of a single delamination at a fixed depth. The quadrupole method has been shown as a viable technique for rapid three-dimensional thermographic simulations of a delamination. This method is expanded to enable rapid simulation of multiple overlapping delaminations at different depths. Quadrupole simulations are compared to finite element simulations of multiple delaminations at different depths. The simulations are also compared to the thermographic measurements on impacted composites where shape and depth of the delaminations are known from x-ray computed tomography data.

Passive thermography has been shown to be an effective method for in-situ and real time nondestructive evaluation (NDE) to measure damage growth in a composite structure during cyclic loading. The heat generation by subsurface flaw results in a measurable thermal profile at the surface. This paper models the heat generation as a planar subsurface source and calculates the resultant temperature profile at the surface using a three dimensional quadrupole. The results of the model are compared to finite element simulations of the same planar sources and experimental data acquired during cyclic loading of composite specimens.

The application of the quadrupole method for simulating thermal responses of delaminations in carbon fiber reinforced epoxy composites materials is presented. The method solves for the flux at the interface containing the delamination. From the interface flux, the temperature at the surface is calculated. While the results presented are for single sided measurements, with ash heating, expansion of the technique to arbitrary temporal flux heating or through transmission measurements is simple. The quadrupole method is shown to have two distinct advantages relative to finite element or finite difference techniques. First, it is straight forward to incorporate arbitrary shaped delaminations into the simulation. Second, the quadrupole method enables calculation of the thermal response at only the times of interest. This, combined with a significant reduction in the number of degrees of freedom for the same simulation quality, results in a reduction of the computation time by at least an order of magnitude. Therefore, it is a more viable technique for model based inversion of thermographic data. Results for simulations of delaminations in composites are presented and compared to measurements and finite element method results.

The use of composite materials continues to increase in the aerospace community due to the potential benefits of reduced weight, increased strength, and manufacturability. Ongoing work at NASA involves the use of the large-scale composite structures for spacecraft (payload shrouds, cryotanks, crew modules, etc). NASA is also working to enable the use and certification of composites in aircraft structures through the Advanced Composites Project (ACP). The rapid, in situ characterization of a wide range of the composite materials and structures has become a critical concern for the industry. In many applications it is necessary to monitor changes in these materials over a long time. The quantitative characterization of composite defects such as fiber waviness, reduced bond strength, delamination damage, and microcracking are of particular interest. The research approaches of NASA's Nondestructive Evaluation Sciences Branch include investigation of conventional, guided wave, and phase sensitive ultrasonic methods, infrared thermography and x-ray computed tomography techniques. The use of simulation tools for optimizing and developing these methods is also an active area of research. This paper will focus on current research activities related to large area NDE for rapidly characterizing aerospace composites.

Numerical simulations of thermographic responses in composite materials have been a useful for evaluating and optimizing thermographic analysis techniques. Numerical solutions are particularly beneficial for thermographic techniques, since the fabrication of specimens with realistic flaws is difficult. Simulations are presented with different ply layups that incorporated the anisotropic thermal properties that exist in each ply. The results are compared to analytical series solutions and thermal measurements on composites with flat bottom holes and delaminations.

Simple methods for reducing the pulsed thermographic responses of flaws have tended to be based on either the spatial or temporal response. This independent assessment limits the accuracy of characterization. A variational approach is presented for reducing the thermographic data to produce an estimated size for a flaw that incorporates both the temporal and spatial response to improve the characterization. The size and depth are determined from both the temporal and spatial thermal response of the exterior surface above a flaw and constraints on the length of the contour surrounding the delamination. Examples of the application of the technique to simulation and experimental data acquired are presented to investigate the limitations of the technique.

Principal Component Analysis (PCA) has been shown effective for reducing thermographic NDE data. While a reliable technique for enhancing the visibility of defects in thermal data, PCA can be computationally intense and time consuming when applied to the large data sets typical in thermography. Additionally, PCA can experience problems when very large defects are present (defects that dominate the field-of-view), since the calculation of the eigenvectors is now governed by the presence of the defect, not the "good" material. To increase the processing speed and to minimize the negative effects of large defects, an alternative method of PCA is being pursued where a fixed set of eigenvectors, generated from an analytic model of the thermal response of the material under examination, is used to process the thermal data from composite materials. This method has been applied for characterization of flaws.

Simple methods for reducing the pulsed thermographic responses of delaminations tend to overestimate the size of the delamination, since the heat diffuses in the plane parallel to the surface. The result is a temperature profile over the delamination which is larger than the delamination size. A variational approach is presented for reducing the thermographic data to produce an estimated size for a flaw that is much closer to the true size of the delamination. The method is based on an estimate for the thermal response that is a convolution of a Gaussian kernel with the shape of the flaw. The size is determined from both the temporal and spatial thermal response of the exterior surface above the delamination and constraints on the length of the contour surrounding the delamination. Examples of the application of the technique to simulation and experimental data are presented to investigate the limitations of the technique.

Conventional methods for reducing the pulsed thermographic responses of delaminations tend to overestimate the size of the flaw. Since the heat diffuses in the plane parallel to the surface, the resulting temperature profile over the flaw is larger than the flaw. A variational method is presented for reducing the thermographic data to produce an estimated size for the flaw that is much closer to the true size of the flaw. The size is determined from the spatial thermal response of the exterior surface above the flaw and a constraint on the length of the contour surrounding the flaw. The technique is applied to experimental data acquired on a flat bottom hole composite specimen.

Flaw detection and characterization with thermographic techniques in graphite polymer composites are often limited by localized variations in the thermographic response. Variations in properties such as acceptable porosity, fiber volume content and surface polymer thickness result in variations in the thermal response that in general cause significant variations in the initial thermal response. These result in a "noise" floor that increases the difficulty of detecting and characterizing deeper flaws. A method is presented for computationally removing a significant amount of the "noise" from near surface porosity by diffusing the early time response, then subtracting it from subsequent responses. Simulations of the thermal response of a composite are utilized in defining the limitations of the technique. This method for reducing the data is shown to give considerable improvement characterizing both the size and depth of damage. Examples are shown for data acquired on specimens with fabricated delaminations and impact damage.

Impact damage in thin carbon fiber reinforced polymer composites often results in a relatively small region of damage at the front surface, with increasing damage near the back surface. Conventional methods for reducing the pulsed thermographic responses of the composite tend to underestimate the size of the back surface damage, since the smaller near surface damage gives the largest thermographic indication. A method is presented for reducing the thermographic data to produce an estimated size for the impact damage that is much closer to the size of the damage estimated from other NDE techniques such as microfocus x-ray computed tomography and pulse echo ultrasonics. Examples of the application of the technique to experimental data acquired on specimens with impact damage are presented. The method is also applied to the results of thermographic simulations to investigate the limitations of the technique.

A recently developed technique is presented for thermographic detection of delaminations in composites by performing temperature measurements with fiber optic Bragg gratings. A single optical fiber with multiple Bragg gratings employed as surface temperature sensors was bonded to the surface of a composite with subsurface defects. The investigated structure was a 10-ply composite specimen with prefabricated delaminations of various sizes and depths. Both during and following the application of a thermal heat flux to the surface, the individual Bragg grating sensors measured the temporal and spatial temperature variations. The data obtained from grating sensors were analyzed with thermal modeling techniques of conventional thermography to reveal particular characteristics of the interested areas. Results were compared and found to be consistent with the calculations using numerical simulation techniques. Also discussed are methods including various heating sources and patterns, and their limitations for performing in-situ structural health monitoring.

Principal Component Analysis (PCA) has been shown effective for reducing thermographic NDE data. This paper will discuss an alternative method of analysis that has been developed where a predetermined set of eigenvectors is used to process the thermal data from both reinforced carbon-carbon (RCC) and graphiteepoxy honeycomb materials. These eigenvectors can be generated either from an analytic model of the thermal response of the material system under examination, or from a large set of experimental data. This paper provides the details of the analytic model, an overview of the PCA process, as well as a quantitative signal-to-noise comparison of the results of performing both conventional PCA and fixed eigenvector analysis on thermographic data from two specimens, one Reinforced Carbon-Carbon with flat bottom holes and the second a sandwich construction with graphite-epoxy face sheets and aluminum honeycomb core.

Flaw detection and characterization with thermographic techniques in graphite polymer composites is often limited by localized variations in the thermographic response. Variations in properties such as acceptable porosity, variations in fiber volume content and surface polymer thickness result in variations in the thermal response that in general cause significant variations in the initial thermal response. These variations result in a noise floor that increases the difficulty of detecting and characterizing deeper flaws. The paper investigates comparing thermographic responses taken before and after a change in state in a composite to improve the detection of subsurface flaws. A method is presented for registration of the responses before finding the difference. A significant improvement in the detectability is achieved by comparing the differences in response. Examples of changes in state due to application of a load and impact are presented.

Acoustic thermography uses a housing configured for thermal, acoustic and infrared radiation shielding. For in-situ applications, the housing has an open side adapted to be sealingly coupled to a surface region of a structure such that an enclosed chamber filled with air is defined. One or more acoustic sources are positioned to direct acoustic waves through the air in the enclosed chamber and towards the surface region. To activate and control each acoustic source, a pulsed signal is applied thereto. An infrared imager focused on the surface region detects a thermal image of the surface region. A data capture device records the thermal image in synchronicity with each pulse of the pulsed signal such that a time series of thermal images is generated. For enhanced sensitivity and/or repeatability, sound and/or vibrations at the surface region can be used in feedback control of the pulsed signal applied to the acoustic sources.

A recently developed technique is presented for thermographic detection of flaws in composite materials by performing temperature measurements with fiber optic Bragg gratings. Individual optical fibers with multiple Bragg gratings employed as surface temperature sensors were bonded to the surfaces of composites with subsurface defects. The investigated structures included a 10-ply composite specimen with subsurface delaminations of various sizes and depths. Both during and following the application of a thermal heat flux to the surface, the individual Bragg grating sensors measured the temporal and spatial temperature variations. The data obtained from grating sensors were analyzed with thermal modeling techniques of conventional thermography to reveal particular characteristics of the interested areas. Results were compared with the calculations using numerical simulation techniques. Methods and limitations for performing in-situ structural health monitoring are discussed.

A noncontact method has been devised for mapping or imaging spatial variations in the thickness and microstructure of a layer of a dielectric material. The method involves (1) placement of the dielectric material on a metal substrate, (2) through-the-thickness pulse-echo measurements by use of electromagnetic waves in the terahertz frequency range with a raster scan in a plane parallel to the substrate surface that do not require coupling of any kind, and (3) appropriate processing of the digitized measurement data.

Thermographic inspection is a viable technique for detecting in-service damage in reinforced carbon-carbon (RCC) composites that are used for thermal protection in the leading edge of the shuttle orbiter. A thermographic technique for detection of near surface flaws in RCC composite structures is presented. A finite element model of the heat diffusion in structures with expected flaw configurations is in good agreement with the experimental measurements.

Optical fibers with multiple Bragg gratings bonded to surfaces of structures were used for thermographic detection of subsurface defects in structures. The investigated structures included a 10-ply composite specimen with subsurface delaminations of various sizes and depths. Both during and following the application of a thermal heat flux to the surface, the individual Bragg grating sensors measured the temporal and spatial temperature variations. The obtained data were analyzed with thermal modeling to reveal particular characteristics of the interested areas. These results were found to be consistent with the simulation results.

The increased role played by probability of detection (POD) in structural integrity programs, combined with the significant time and cost associated with the purely empirical determination of POD, provides motivation for alternate means to estimate this important metric of NDE techniques. One approach to make the process of POD estimation more efficient is to complement limited empirical experiments with information from physics-based models of the inspection process or controlled laboratory experiments. The Model-Assisted Probability of Detection (MAPOD) Working Group was formed by the Air Force Research Laboratory, the FAA Technical Center, and NASA to explore these possibilities. Since the 2004 inception of the MAPOD Working Group, 11 meetings have been held in conjunction with major NDE conferences. This paper will review the accomplishments of this group, which includes over 90 members from around the world. Included will be a discussion of strategies developed to combine physics-based and empirical understanding, draft protocols that have been developed to guide application of the strategies, and demonstrations that have been or are being carried out in a number of countries. The talk will conclude with a discussion of future directions, which will include documentation of benefits via case studies, development of formal protocols for engineering practice, as well as a number of specific technical issues.

Conventional thermography with an infrared imager has been shown to be an extremely viable technique for nondestructively detecting subsurface anomalies such as thickness variations due to corrosion. A recently developed technique using fiber optic sensors to measure temperature holds potential for performing similar inspections without requiring an infrared imager. The structure is heated using a heat source such as a quartz lamp with fiber Bragg grating (FBG) sensors at the surface of the structure to detect temperature. Investigated structures include a stainless steel plate with thickness variations simulated by small platelets attached to the back side using thermal grease. A relationship is shown between the FBG sensor thermal response and variations in material thickness. For comparison, finite element modeling was performed and found to agree closely with the fiber optic thermography results. This technique shows potential for applications where FBG sensors are already bonded to structures for Integrated Vehicle Health Monitoring (IVHM) strain measurements and can serve dual-use by also performing thermographic detection of subsurface anomalies.