Search NASA⌕ Search

SEARCH · Search NASA

Results for “nondestructive analysis”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10

The Application of Principal Component Analysis Using Fixed Eigenvectors to the Infrared Thermographic Inspection of the Space Shuttle Thermal Protection System

The Nondestructive Evaluation Sciences Branch at NASA s Langley Research Center has been actively involved in the development of thermographic inspection techniques for more than 15 years. Since the Space Shuttle Columbia accident, NASA has focused on the improvement of advanced NDE techniques for the Reinforced Carbon-Carbon (RCC) panels that comprise the orbiter s wing leading edge. Various nondestructive inspection techniques have been used in the examination of the RCC, but thermography has emerged as an effective inspection alternative to more traditional methods. Thermography is a non-contact inspection method as compared to ultrasonic techniques which typically require the use of a coupling medium between the transducer and material. Like radiographic techniques, thermography can be used to inspect large areas, but has the advantage of minimal safety concerns and the ability for single-sided measurements. Principal Component Analysis (PCA) has been shown effective for reducing thermographic NDE data. A typical implementation of PCA is when the eigenvectors are generated from the data set being analyzed. Although it is a powerful tool 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 when a fixed set of eigenvectors is used to process the thermal data from the RCC materials. These eigen vectors can be generated either from an analytic model of the thermal response of the material under examination, or from a large cross section of experimental data. This paper will provide 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 embodiments of PCA on thermographic data from various RCC specimens. Details of a system that has been developed to allow insitu inspection of a majority of shuttle RCC components will be presented along with the acceptance test results for this system. Additionally, the results of applying this technology to the Space Shuttle Discovery after its return from flight will be presented.

Cramer, K. Elliott↗

Assessment of Internal Fabric of Particulate Materials

Particle arrangement and distribution within a soil matrix has long been recognized as having significant influence on the mechanical behavior of cohesionless soils. It is well known that two soil specimens having the same grain type (e.g., quartz, feldspar, etc.), same grain size distribution and relative density (or void ratio) can display completely different mechanical behavior. Because of the different fabric configurations in the otherwise similar specimens, they are likely to have different mechanical properties such as stress-strain response, anisotropy, dilatancy, etc. Soil Fabric is defined as the arrangement of particles, particle groups and associated pore space. In the literature, fabric analysis techniques are mainly classified as destructive (e.g., specimen stabilization, thin-sectioning, and microscopy), and nondestructive techniques (e.g., magnetic resonance imaging, ultrasonic testing, x-ray radiography, and computed tomography). Quantifying the void ratio and its distribution is the main parameter used to describe the fabric of particulate materials. This paper presents a comprehensive literature review of fabric analysis techniques applied to particulate materials. In addition, the results of a comprehensive investigation to quantify void ratio of sand specimens will be presented and discussed. The sand used in the experiments in a natural, uniform rounded to sub-rounded silica sand known as F-75 banding sand with mean particle size of 0.22 mm. Uniform specimens and specimens subjected to different axial-strain levels tested under triaxial and biaxial conditions are examined to evaluate void ratio evolution and its distribution using destructive thin-sectioning and nondestructive Computed Tomography (CT) techniques. Details of a new innovative polygon generation technique called Voronoi tessellation used to quantify void ratio of microscopic images of sand grains will be presented and compared to classical Oda's method. Finally, frequency distribution of void ratio calculated using CT analysis will be presented and discussed.

Alshibi, Khalid A.↗

Production of Cf-252 and other transplutonium isotopes at Oak Ridge National Laboratory

In 1957 Glenn T. Seaborg conceived and advocated for the construction of the High Flux Isotope Reactor (HFIR) and the Transuranium Processing Plant (since then renamed the Radiochemical Engineering Development Center, or REDC) at Oak Ridge National Laboratory. There, heavily shielded hot cells, glove boxes, and laboratories allow recovery of transuranium elements produced in substantial quantities. Seaborg’s vision of HFIR and REDC producing milligram quantities of berkelium, californium, and einsteinium has been fulfilled beginning in 1966 through May 2019 with 78 production campaigns yielding a cumulative totals of 1.2 g of 249 Bk, 10.2 g of 252 Cf, 39 mg of 253 Es, and 15 pg of 257 Fm. Notably, 252 Cf is a neutron source used in many industrial applications including oil exploration; process control systems for the cement industry, coal analysis, and power production; sources to start nuclear reactors and perform nondestructive materials analyses; homeland security and national defense detection devices; and medical research. Isotopes made available through transplutonium production at HFIR/REDC have enabled scientists to study the nuclear properties and reactions, chemical properties, optical properties, and solid-state properties of transplutonium elements. Long-lived isotopes have served as targets in heavy ion accelerators to produce heavier elements leading to the discovery of 104 Rf, 105 Db, 106 Sg, 113 Nh, 114 Fl, 115 Mc, 116 Lv, 117 Ts, and 118 Og. This paper reviews the evolution of the processing flowsheets to produce, separate, and purify transplutonium isotopes, which have evolved over 50 years of operation at HFIR and REDC, and summarizes directions of future work to improve the efficiency of the production operations.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

The detection of fatigue cracks by nondestructive test methods

X-radiographic, penetrant, ultrasonic, and eddy current techniques were optimized and applied to the evaluation of 2219-T87 aluminum alloy test specimens. One hundred eighteen specimens containing a total of 328 fatigue cracks were evaluated. The cracks ranged in length from 1.27 to 0.018 cm and in depth from 0.451 to 0.003 cm. Specimen thicknesses were nominally 0.152 and 0.532 cm. Specimens were evaluated in the 'as-milled' surface condition, in the etched surface condition, and, after proof loading, in a randomized inspection sequence. Results of the nondestructive test evaluations were compared with actual crack size obtained by analysis of the fractured specimens. Inspection data were then analyzed to provide a statistical basis for determining the threshold crack detection sensitivity for each of the inspection techniques at a 95% probability and 95% confidence level.

Rummel, W. D.↗

In-Flight Detection of Vibration Anomalies in Unmanned Aerial Vehicles

Owing to the frequency of occurrence and high risk associated with bearings, identification and characterization of bearing faults in motors via nondestructive evaluation (NDE) methods have been studied extensively, amongst which vibration analysis has been found to be a promising technique for early diagnosis of anomalies. However, a majority of the existing techniques rely on vibration sensors attached onto or in close proximity to the motor in order to collect signals with a relatively high SNR. Due to weight and space restrictions, these techniques cannot be used in unmanned aerial vehicles (UAVs), especially during flight operations since accelerometers cannot be attached onto motors in small UAVs. Small UAVs are often subjected to vibrational disturbances caused by multiple factors such as weather turbulence, propeller imbalance or bearing faults. Such anomalies may not only pose risks to UAV's internal circuitry, components or payload, they may also generate undesirable noise level particularly for UAVs expected to fly in low-altitudes or urban canyon. This paper presents a detailed discussion of challenges in in-flight detection of bearing failure in UAVs using existing approaches and offers potential solutions to detect overall vibration anomalies in small UAV operations based on IMU data.

Portia Banerjee↗

Time-Frequency Analysis of the Dispersion of Lamb Modes

Accurate knowledge of the velocity dispersion of Lamb modes is important for ultrasonic nondestructive evaluation methods used in detecting and locating flaws in thin plates and in determining their elastic stiffness coefficients. Lamb mode dispersion is also important in the acoustic emission technique for accurately triangulating the location of emissions in thin plates. In this research, the ability to characterize Lamb mode dispersion through a time-frequency analysis (the pseudo-Wigner-Ville distribution) was demonstrated. A major advantage of time-frequency methods is the ability to analyze acoustic signals containing multiple propagation modes, which overlap and superimpose in the time domain signal. By combining time-frequency analysis with a broadband acoustic excitation source, the dispersion of multiple Lamb modes over a wide frequency range can be determined from as little as a single measurement. In addition, the technique provides a direct measurement of the group velocity dispersion. The technique was first demonstrated in the analysis of a simulated waveform in an aluminum plate in which the Lamb mode dispersion was well known. Portions of the dispersion curves of the AO, A I , So, and S2 Lamb modes were obtained from this one waveform. The technique was also applied for the analysis of experimental waveforms from a unidirectional graphite/epoxy composite plate. Measurements were made both along and perpendicular to the fiber direction. In this case, the signals contained only the lowest order symmetric and antisymmetric modes. A least squares fit of the results from several source to detector distances was used. Theoretical dispersion curves were calculated and are shown to be in good agreement with experimental results.

Prosser, W. H.↗

Time-Frequency Analysis of the Dispersion of Lamb Modes

Accurate knowledge of the velocity dispersion of Lamb modes is important for ultrasonic nondestructive evaluation methods used in detecting and locating flaws in thin plates and in determining their elastic stiffness coefficients. Lamb mode dispersion is also important in the acoustic emission technique for accurately triangulating the location of emissions in thin plates. In this research, the ability to characterize Lamb mode dispersion through a time-frequency analysis (the pseudo Wigner-Ville distribution) was demonstrated. A major advantage of time-frequency methods is the ability to analyze acoustic signals containing multiple propagation modes, which overlap and superimpose in the time domain signal. By combining time-frequency analysis with a broadband acoustic excitation source, the dispersion of multiple Lamb modes over a wide frequency range can be determined from as little as a single measurement. In addition, the technique provides a direct measurement of the group velocity dispersion. The technique was first demonstrated in the analysis of a simulated waveform in an aluminum plate in which the Lamb mode dispersion was well known. Portions of the dispersion curves of the A(sub 0), A(sub 1), S(sub 0), and S(sub 2)Lamb modes were obtained from this one waveform. The technique was also applied for the analysis of experimental waveforms from a unidirectional graphite/epoxy composite plate. Measurements were made both along, and perpendicular to the fiber direction. In this case, the signals contained only the lowest order symmetric and antisymmetric modes. A least squares fit of the results from several source to detector distances was used. Theoretical dispersion curves were calculated and are shown to be in good agreement with experimental results.

Prosser, W. H.↗

Optical fiber sensors for damage analysis in aerospace materials

Under this grant, fiber optic sensors were investigated for use in the nondestructive evaluation of aging aircraft. Specifically, optical fiber sensors for detection and location of impacts on a surface, and for detection of corrosion in metals were developed. The use of neural networks was investigated for determining impact location by processing the output of a network of fiberoptic strain sensors distributed on a surface. This approach employs triangulation to determine location by comparing the arrival times at several sensors, of the acoustic signal generated by the impact. For this study, a neural network simulator running on a personal computer was used to train a network using a back-propagation algorithm. Fiber optic extrinsic Fabry-Perot interferometer (EFPI) strain sensors are attached to or embedded in the surface, so that stress waves emanating from an impact can be detected. The ability of the network to determine impact location by time-or-arrival of acoustic signals was assessed by comparing network outputs with actual experimental results using impacts on a panel instrumented with optical fiber sensors. Using the neural network to process the sensor outputs, the impact location can be inferred to centimeter range accuracy directly from the arrival time data. In addition, the network can be trained to determine impact location, regardless of material anisotropy. Results demonstrate that a back-propagation network identifies impact location for an anisotropic graphite/bismaleimide plate with the same accuracy as that for an isotropic aluminum plate. Two different approaches were investigated for the development of fiber optic sensors for corrosion detection in metals, both utilizing optical fiber sensors with metal coatings. In the first approach, an extrinsic Fabry-Perot interferometric fiber optic strain sensor was placed under tensile stress, and while in the resulting strained position, a thick coating of metal was applied. Due to an increase in the quantity of material, the sensor does not return to its original position upon removal of the applied stress, and some residual strain is maintained within the sensor element. As the metal thickness decreases due to corrosion, this strain is released, providing the sensing mechanism for corrosion detection. In the second approach, photosensitive optical fibers with long period Bragg gratings in the core were coated with metal. The Bragg gratings serve to couple core modes at discrete wavelengths to cladding modes. Since cladding modes interact with the metal coating surrounding the fiber cladding, the specific wavelengths coupled from core to cladding depend on the refractive index of the metal coating. Therefore, as the metal corrodes, the resulting change in index of the coating may be measured by measuring the change in wavelength of the coupled mode. Results demonstrate that both approaches can be successfully used to track the loss in metal coating on the optical fiber sensors due to corrosion.

Schindler, Paul↗

The Reconstruction and Failure Analysis of the Space Shuttle Columbia

Several days following the Columbia accident a team formed and began planning for the reconstruction of Columbia. A hangar at the Kennedy Space Center was selected for this effort due to it's size, available technical workforce and materials science laboratories and access to the vehicle ground processing infrastructure. The Reconstruction team established processes for receiving, handling, decontamination, tracking, identifying, cleaning and assessment of the debris. Initially, a 2-dimensional reconstruction of the Orbiter outer mold line was developed. As the investigation progressed fixtures which allowed a 3-dimensional reconstruction of the forward portions of the left wing's leading edge was developed. To support the reconstructions and forensic analyses a Materials and Processes (M&P) 'team was formed. This M&P team established processes for recording factual observations, debris cleaning, and engineering analysis. Fracture surfaces and thermal effects of selected airframe debris were assessed, and process flows for both nondestructive and destructive sampling and evaluation of debris were developed. The Team also assessed left hand airframe components that were believed to be associated with a structural breach of Columbia. A major portion of this analysis was evaluation of metallic deposits were prevalent on left wing leading edge components. Extensive evaluation of the visual, metallurgical and chemical nature of the deposits provided conclusions that were consistent with the visual assessments and interpretations of the NASA lead teams and the findings of the Columbia Accident Investigation Board. Analytical data collected by the M&P Team showed that a significant thermal event occurred at the left wing leading edge in the proximity of LH RCC Panels 8-9, and a correlation was formed between the deposits and overheating in these areas to the wing leading edge components. The analysis of deposits also showed exposure to temperatures in excess of 1649 C (3200 F), which would severely degrade support structure, tiles, and RCC panel materials. The integrated failure analysis of wing leading edge debris and deposits strongly supported the hypothesis that a breach occurred at LH RCC Panel 8.

Russell, Richard↗

Development of a Neutron List Mode Collar (LMCL) and a List Mode Response Matrix Analysis Concept

This report was prepared for the Safeguards Program of the US Department of Energy’s (DOE’s) National Nuclear Security Administration (NNSA), Office of Defense Nuclear Nonproliferation Research and Development (DNN R&D). The report presents the development of the neutron nondestructive assay system, the List Mode Collar (LMCL) for the project OR16-List Mode for Collar-PD1La “List Mode Response Matrix for Advanced Correlated Neutron Analysis for Nuclear Safeguards.” The new list mode electronics developed under this project, and a spatial analysis concept called the List Mode Response Matrix are also described in this report. Analysis algorithms based on classification methods are published in a separate report. This research addresses the need to expand the capabilities of current nondestructive assay systems used for nuclear safeguards applications and considers the sustainability of safeguards technologies by the development of a “retrofit” concept using electronics based on modern standards. Furthermore, employing list mode data acquisition enabled the development of a spatial analysis concept and empirical measurement of a spatial response not previously used for safeguards neutron counting applications or measured in a traditional neutron collar detector and, therefore, provides new capability.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Porosity Area Fraction Analysis of Bonded Borosilicate Specimens From in-Situ Optical Imagery

Image segmentation methods are routinely used to analyze data derived in nondestructive testing scenarios. A typical problem in this area is to estimate porosity from X-ray Computed Tomography (CT) inspections. This investigation aims to understand the effectiveness of open-source image segmentation methods for porosity estimation from optical images in the context of strength analysis of bonded materials and provides a benchmark of performance against a standard commercial software package. The rank ordering of the specimens by porosity area fraction is consistent across both methods.

Porosity area fraction↗

Porosity Area Fraction Analysis of Bonded Borosilicate Specimens From in-Situ Optical Imagery

Image segmentation methods are routinely used to analyze data derived in nondestructive testing scenarios. A typical problem in this area is to estimate porosity from X-ray Computed Tomography (CT) inspections. This investigation aims to understand the effectiveness of open-source image segmentation methods for porosity estimation from optical images in the context of strength analysis of bonded materials and provides a benchmark of performance against a standard commercial software package. The rank ordering of the specimens by porosity area fraction is consistent across both methods.

Porosity area fraction↗

A Plutonium Mass Uncertainty Assessment Using a Cherenkov-Based Neutron Multiplicity Water Detector

We present a new analysis of the sensitivity of a water Cherenkov-based neutron multiplicity counter for nondestructive assay of trace quantities of 240 Pu. The multiplicity counter [water-based neutron detector (WaND)] contains 1.0 m 3 of water doped with 0.2% gadolinium in the form of a gadolinium salt (0.4% GdCl 3 ). It can be used for testing the presence of trace quantities of 240 Pu within a sample of unknown material by observing the correlated timing behavior of neutron capture candidates in the detector. The new analysis takes advantage of the fact that the detector is comprised almost entirely of a homogeneous medium, which permits the use of a simple model to reproduce the observed neutron capture timing behavior. Finally, the results of this analysis indicate that the detector has an absolute neutron detection efficiency of 23.4 ± 1.1% and is sensitive to a 240 Pu mass as small as 2.3 mg (at 1σ) after a 1-h data acquisition.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Proceedings of the First Annual Symposium for Nondestructive Evaluation of Bond Strength

Quantitative adhesive bond strength measurement has been an issue for over thirty years. Utilization of nonlinear ultrasonic nondestructive evaluation methods has shown more effectiveness than linear methods on adhesive bond analysis, resulting in an increased sensitivity to changes in bondline conditions. Correlation to changes in higher order material properties due to microstructural changes using nonlinear ultrasonics has been shown and could relate to bond strength. Nonlinear ultrasonic energy is an order of magnitude more sensitive than linear ultrasound to these material parameter changes and to acoustic velocity changes caused by the acoustoelastic effect when a bond is prestressed. This increased sensitivity will assist in getting closer to quantitative measurement of adhesive bond strength. Signal correlations between non-linear ultrasonic measurements and initialization of bond failures have been successfully measured. This paper reviews nonlinear bond strength research efforts presented by university and industry experts at the First Annual Symposium for Nondestructive Evaluation of Bond Strength organized by the NDE Sciences Branch at NASA Langley in November 1997.

Roberts, Mark J.↗

A Robust Data-Driven Approach for Mechanical Serial Sectioning

Mechanical serial sectioning (MSS) provides detailed microstructural information across large length scales. By repeatedly removing thin layers of material and imaging the exposed surface, a 3D representation of a specimen’s internal structure can be constructed, enabling failure analysis and feature identification that are otherwise inaccessible via conventional 2D or nondestructive evaluation techniques. Achieving consistent and accurate material removal can be challenging due to system variability, requiring an experienced operator to manually adjust parameters, prolonging data collection times and necessitating post-processing routines to standardize the data. Here, to address these challenges, this paper presents the employment of a one-step model predictive control (MPC) framework tailored to a run-to-run (R2R) controller. The R2R-MPC controller automates the parameter selection process, improving the consistency of material removal through iterative feedback for disturbance rejection and accurate tracking of the target removal rate. Using a data-driven approach, the controller robustly adapts to changing material characteristics. The effectiveness of the R2R-MPC controller is demonstrated through simulation and experimental results and compared to previous data collection procedures.

3D Materials Science↗

Predicting Nugget Size of Resistance Spot Welds Using Infrared Thermal Videos With Image Segmentation and Convolutional Neural Network

Resistance spot welding (RSW) is a widely adopted joining technique in automotive industry. Recent advancement in sensing technology makes it possible to collect thermal videos of the weld nugget during RSW using an infrared (IR) camera. The effective and timely analysis of such thermal videos has the potential of enabling in situ nondestructive evaluation (NDE) of the weld nugget by predicting nugget thickness and diameter. Deep learning (DL) has demonstrated to be effective in analyzing imaging data in many applications. However, the thermal videos in RSW present unique data-level challenges that compromise the effectiveness of most pre-trained DL models. We propose a novel image segmentation method for handling the RSW thermal videos to improve the prediction performance of DL models in RSW. The proposed method transforms raw thermal videos into spatial-temporal instances in four steps: video-wise normalization, removal of uninformative images, watershed segmentation, and spatial-temporal instance construction. The extracted spatial-temporal instances serve as the input data for training a DL-based NDE model. The proposed method is able to extract high-quality data with spatial-temporal correlations in the thermal videos, while being robust to the impact of unknown surface emissivity. Overall, our case studies demonstrate that the proposed method achieves better prediction of nugget thickness and diameter than predicting without the transformation.

42 ENGINEERING↗

Computer-aided design of polymers and composites

This book on computer-aided design of polymers and composites introduces and discusses the subject from the viewpoint of atomic and molecular models. Thus, the origins of stiffness, strength, extensibility, and fracture toughness in composite materials can be analyzed directly in terms of chemical composition and molecular structure. Aspects of polymer composite reliability are considered along with characterization techniques for composite reliability, relations between atomic and molecular properties, computer aided design and manufacture, polymer CAD/CAM models, and composite CAD/CAM models. Attention is given to multiphase structural adhesives, fibrous composite reliability, metal joint reliability, polymer physical states and transitions, chemical quality assurance, processability testing, cure monitoring and management, nondestructive evaluation (NDE), surface NDE, elementary properties, ionic-covalent bonding, molecular analysis, acid-base interactions, the manufacturing science, and peel mechanics.

Kaelble, D. H.↗

Optical surface contouring for non-destructive inspection of turbomachinery

Detection of stress cracks and other surface defects during maintenance and in-service inspection of propulsion system components, including turbine blades and combustion compartments, is presently performed visually. There is a need for a non-contact, miniaturized, and fully fieldable instrument that may be used as an automated inspection tool for inspection of aircraft engines. During this SBIR Phase 1 program, the feasibility of a ruggedized optical probe for automatic and nondestructive inspection of complex shaped objects will be established. Through a careful analysis of the measurement requirements, geometrical and optical constraints, and consideration of issues such as manufacturability, compactness, simplicity, and cost, one or more conceptual optical designs will be developed. The proposed concept will be further developed and a prototype will be fabricated during Phase 2.

Modarress, Dariush↗