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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.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Advances in the photon avalanche luminescence of inorganic lanthanide-doped nanomaterials

Photon avalanche (PA)—where the absorption of a single photon initiates a ‘chain reaction’ of additional absorption and energy transfer events within a material—is a highly nonlinear optical process that results in upconverted light emission with an exceptionally steep dependence on the illumination intensity. Over 40 years following the first demonstration of photon avalanche emission in lanthanide-doped bulk crystals, PA emission has been achieved in nanometer-scale colloidal particles. The scaling of PA to nanomaterials has resulted in significant and rapid advances, such as luminescence imaging beyond the diffraction limit of light, optical thermometry and force sensing with (sub)micron spatial resolution, and all-optical data storage and processing. In this review, we discuss the fundamental principles underpinning PA and survey the studies leading to the development of nanoscale PA. Finally, we offer a perspective on how this knowledge can be used for the development of next-generation PA nanomaterials optimized for a broad range of applications, including mid-IR imaging, luminescence thermometry, (bio)sensing, optical data processing and nanophotonics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2017

Hydrazine Conservation for the Dawn Spacecraft Operations at the Dwarf Planet Ceres

Dawn is a low-thrust interplanetary spacecraft currently orbiting the dwarf planet Ceres. After successfully completing its Vesta and Ceres prime missions, Dawn is now in its extended mission, continuously exploring Ceres. After losing the second reaction wheel assembly at the end of the Vesta mission, the feasibility of the Ceres mission was at risk due to the potentially significant increase in hydrazine consumption from using only the reaction control system thrusters. This paper summarizes the intense, collaborative efforts undertaken by the project to conserve hydrazine prior to Vesta departure, during cruise to Ceres, and throughout the Ceres mission. The project’s efforts in minimizing the number of turns are discussed. A special emphasis is given to describing various efforts taken by the Attitude Control Subsystem team in an attempt to reduce hydrazine consumption. These efforts include: changing default slew rates, control gain tuning, changing nadir pointing strategy with Ahead Cross Nadir pointing, hybrid control implementation using hydrazine based thrusters and two remaining reaction wheels, optimal science turn location analysis, and reaction wheel angular momentum management strategies for reducing the number of momentum unloadings. In addition to the Attitude Control Subsystem team’s efforts, the Mission Design and Navigation team’s efforts taken in designing hydrazine friendly orbit transfers are discussed. The trade study performed collaboratively by the Attitude Control Subsystem team and the Science Operations Support Team in choosing hydrazine friendly off-nadir targets is also discussed. Various simulation results are presented and compared against actual flight data obtained. Lastly, remaining hydrazine status at the end of the prime Ceres mission and the hydrazine management planning for the extended mission are discussed.

Salami, Mana↗
NASA NTRS2016

Computing Highly Accurate Spectroscopic Line Lists for Characterization of Planetary Atmospheres: CO2 and SO2 Line Lists Needed for Modeling Venus

Over the last decade, it has become apparent that the most effective approach for determining highly accurate rotational and rovibrational line lists for molecules of interest in planetary atmospheres and other astrophysical environments is through a combination of highresolution laboratory experiments coupled with state-of-the art ab initio quantum chemistry methods. The approach involves computing the most accurate potential energy surface (PES) possible using state-of-the art electronic structure methods, followed by computing rotational and rovibrational energy levels using an exact variational method to solve the nuclear Schrödinger equation. Then, reliable experimental data from high-resolution experiments is used to refine the ab initio PES in order to improve the accuracy of the computed energy levels and transition energies. From the refinement step, we have been able to achieve an accuracy of approximately 0.015 cm-1 for rovibrational transition energies, and even better for purely rotational transitions. This combined "experiment / theory" approach allows for determination of essentially a complete line list, with hundreds of millions of transitions, and having the transition energies and intensities be highly accurate. Our group has successfully applied this approach to determine highly accurate line lists for NH3, CO2 and isotopologues, and SO2 and isotopologues. Here I will report our latest results for CO2 and SO2 including all isotopologues. Comparisons to the available data in HITRAN2012 and other available databases will be shown, though we note that our line lists for SO2 are significantly more complete than any other databases. Since it is important to span a large temperature range in order to model the spectral signature of Venus as well as exoplanets, we will demonstrate how the spectra change on going from low temperatures (100 K) to higher temperatures (500 K to 1500 K).

potential energy surface (PES)5405 PLANETARY SCIEN↗
NASA NTRS2018

Field Camp for Astronauts: NASA's Geoscience Training Program for Planetary Exploration

Fifty years ago Apollo astronauts walked on the Moon to explore the geology and collect samples for Earth return. Several authors have discussed the strategic planning and training that enabled the Apollo successes, and assembled recommendations regarding today’s lunar science objectives and astronaut training required to achieve those science goals. Since the 1980s, geoscience training for astronauts focused on observing the Earth from orbit. Today, we are building a geoscience training program to support informed Earth observations as well as the exploration culture for future human missions to the Moon and Mars. Our team partnered with JSC’s crew training and astronaut offices to develop our 4-week geoscience program for the 2017 astronaut class. Because the astronauts have a variety of professional backgrounds, we provide a broad introduction to Earth and planetary sciences. But our prime focus is 2 weeks of intensive field work, a methodology introduced with the 2013 astronaut class. We completed the first half of the training – a field trip to observe hurricane deposits along Galveston Bay; keynotes by Apollo colleagues highlighting Apollo experiences; a tightly-integrated week of introductory geology in the classroom followed by a week of fieldwork in the Rio Grande del Norte National Monument. The classroom included interactive map exercises that allowed the students to progressively build a base map of the field area that they used as a starting point for their week-long mapping exercise. We divided the class into small mapping groups to conduct their observations, mapping and interpretation of the geology. In addition to learning geological field work, our field training provided the platform for practicing expeditionary leadership, a key skill set valued by NASA for astronaut crews. Next summer the capstone fieldwork for the 2017 astronauts will include both mapping and rock sampling. Throughout the mapping, the class will collect additional data to help inform field and sampling decisions using diagnostic field instruments that are being tested in analog settings for their operational efficacy for future planetary exploration.

Evans, Cynthia A.↗
DOE OSTI2024

Considerations for Introducing Artificial Intelligence into Nuclear Power Plants

Advanced computational tools and techniques such as artificial intelligence and machine learning (AI/ML) can transform the nuclear power industry. This is necessary given that the economic viability of the existing fleet is in jeopardy and its labor-centric approach to operations and maintenance. Currently, AI/ML research is being undertaken for reactor system design and analysis including fault and accident prognosis, nuclear risk analysis such as plant safety and security evaluation, and plant operations and maintenance including predictive maintenance. Applications include both existing and advanced reactor technologies with the aim of improving operational and business efficiencies. Most every aspect of the organization can benefit, from instrumentation and control, to work planning, to human-machine interactions and business management. AI/ML in nuclear can simplify complex problems and produce more effective decision-making. Nonetheless, careful consideration must be given to the implementation of an AI/ML initiative. The aims of this research are to 1) review barriers to AI/ML adoption within the nuclear power industry, and 2) suggest potential solutions. These barriers are organized along five distinct categories (Figure 1) that are interconnected. The first are historical barriers that track the industry’s development over the decades including worldwide nuclear events that shaped public perceptions. The resulting federal scrutiny and intense safety culture that emerged are discussed. Technical barriers to AI/ML adoption are considerable, and include data privacy concerns, data governance, and the current lack of AI/ML expert knowledge at the plants. The main business case barrier remains cost, but an absence of an industry-wide vision and wide-scale adoption also produces reluctance. Stakeholder readiness is reviewed with special attention given to regulatory readiness. The 5-year strategic plan for AI readiness recently published by the U.S. Nuclear Regulatory Commission is highlighted. Last, adoption barriers at the user level are addressed including the importance of user experience and explainable AI. The AI adoption barriers described here are inter-related and ideally should be addressed in a holistic fashion.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Airborne LiDAR to Improve Canopy Fuels Mapping for Wildfire Modeling

Increasing conflict between wildfire and the built environment has increased the need for more up-to-date and finer resolution canopy fuels data to improve wildfire modeling and associated risk forecasts. The US Forest Service and US Department of the Interior’s LANDFIRE product, which provides 30-m resolution canopy fuels data for the entire US, is one of the most widely used sources of fuels data. However, the last complete mapping effort for LANDFIRE is based on 2016 conditions, and subsequent updates reflect disturbances 1-2 years behind the release year. Airborne systems equipped with Light Detection and Ranging (LiDAR) sensors can be deployed to actively sense canopy structure and estimate canopy fuels data (cover, height, base height, bulk density) at finer resolutions. Canopy base height (CBH) and canopy bulk density (CBD) are difficult to measure both in the field and in LiDAR point clouds. Still, they are important for accurately modeling crown fires, which are often intense and difficult to contain. Additionally, point cloud datasets are large, and calculations require efficient utilization of computational resources. To address these challenges, we are working on an approach that uses openly available National Ecological Observatory Network (NEON) airborne LiDAR data, with calculations processed in the R programming language and parallelized through the lidR package. CBH and CBD are often derived from tree height, diameter at breast height, and species-specific allometries using the Fire and Fuels Extension of the Forest Vegetation Simulator (FFE-FVS). We aim to test if airborne LiDAR can estimate CBH and CBD without the use of empirical equations. Reliable estimates of canopy fuels data directly from airborne LiDAR could streamline quick, fine-resolution updates for use in wildfire behavior models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2013

SPoRT Participation in the GOES-R and JPSS Proving Grounds

For the last several years, the NASA Short-term Prediction Research and Transition (SPoRT) project at has been working with the various algorithm working groups and science teams to demonstrate the utility of future operational sensors for GOES-R and the suite of instruments for the JPSS observing platforms. For GOES-R, imagery and products have been developed from polar-orbiting sensors such as MODIS and geostationary observations from SEVIRI, simulated imagery, enhanced products derived from existing GOES satellites, and data from ground-based observing systems to generate pseudo or proxy products for the ABI and GLM instruments. The suite of products include GOES-POES basic and RGB hybrid imagery, total lightning flash products, quantitative precipitation estimates, and convective initiation products. SPoRT is using imagery and products from VIIRS, CrIS, ATMS, and OMPS to show the utility of data and products from their operational counterparts on JPSS. The products include VIIRS imagery in swath form, the GOES-POES hybrid, a suite of RGB products including the air mass RGB using water vapor and ozone channels from CrIS, and several DNB products. Over a dozen SPoRT collaborative WFOs and several National Centers are involved in an intensive evaluation of the operational utility of these products.

Jedlovec, Gary↗
DOE OSTI2026

21 cm Power Spectrum Analysis of North Celestial Pole Observations with the Tianlai Dish Pathfinder Array

The Tianlai Dish Pathfinder Array (TDPA) is a radio interferometer designed to test techniques for 21 cm intensity mapping in the post-reionization Universe as a means of measuring large-scale cosmic structure. Using nine nights of observations targeting the North Celestial Pole field, totaling approximately 107 hr of integration time, we analyze data in the frequency range 700–800 MHz (corresponding to redshift z ∼ 0.9). We do the data format conversion, radio frequency interference flagging, calibration, imaging and point source subtraction, and foreground removal via Singular Value Decomposition. The spherically averaged power spectrum Δ 2 (k) is obtained. Furthermore, this work successfully establishes and validates a comprehensive data analysis framework for the TDPA. We identify key improvements including sky model refinement, increased integration time, and pipeline optimization that will enable future detection of the 21 cm signal through auto-correlation and cross-correlation with optical galaxy surveys.

cosmology: large-scale structure of universe↗
NASA NTRS1995

Space Station Biological Research Project

NASA Ames Research Center is responsible for the development of the Space Station Biological Research Project (SSBRP) which will support non-human life sciences research on the International Space Station Alpha (ISSA). The SSBRP is designed to support both basic research to understand the effect of altered gravity fields on biological systems and applied research to investigate the effects of space flight on biological systems. The SSBRP will provide the necessary habitats to support avian and reptile eggs, cells and tissues, plants and rodents. In addition a habitat to support aquatic specimens will be provided by our international partners. Habitats will be mounted in ISSA compatible racks at u-g and will also be mounted on a 2.5 m diameter centrifuge except for the egg incubator which has an internal centrifuge. The 2.5 m centrifuge will provide artificial gravity levels over the range of 0.01 G to 2 G. The current schedule is to launch the first rack in 1999, the Life Sciences glovebox and a second rack early in 2001, a 4 habitat 2.5 in centrifuge later the same year in its own module, and to upgrade the centrifuge to 8 habitats in 2004. The rodent habitats will be derived from the Advanced Animal Habitat currently under development for the Shuttle program and will be capable of housing either rats or mice individually or in groups (6 rats/group and at least 12 mice/group). The egg incubator will be an upgraded Avian Development Facility also developed for the Shuttle program through a Small Business and Innovative Research grant. The Space Tissue Loss cell culture apparatus, developed by Walter Reed Army Institute of Research, is being considered for the cell and tissue culture habitat. The Life Sciences Glovebox is crucial to all life sciences experiments for specimen manipulation and performance of science procedures. It will provide two levels of containment between the work volume and the crew through the use of seals and negative pressure. The glovebox will accommodate use by two crew persons simultaneously and the capability for real time video down-link and data acquisition. In house testbeds and Phase B studies of the centrifuge validated the concepts of vibration isolation and autobalancing systems to meet the ISSA microgravity requirements. The vibration isolation system is effective above the centrifuge rotation frequency while the autobalancing system on the rotor removes vibration at and below the rotation rate. Torque of the Station, induced by spin-up/spindown of the centrifuge, can be minimized by controlling spin-up/spin-down rates. The SSBRP and ISSA will provide the opportunity to perform long-term, repeatable and high quality science. The long duration increments available on the Station will permit multigeneration studies of both plants and animals which have not previously been possible. The u-g habitat racks and the eight habitat centrifuge will accommodate sufficient number of specimens to permit statistically significant sampling of specimens to investigate the time course of adaptation to altered gravity environments. The centrifuge will, for the first time, permit investigators to use gravity itself as a tool to investigate fundamental processes, to investigate the intensity and duration of gravity to maintain normal structure and function, to separate the effects of u-g from other environmental factors and to examine artificial gravity as a potential countermeasure for the physical deconditioning observed during space flight.

Johnson, Catherine C.↗
NASA NTRS2017

TPSAS-NF1676L-21094-DND

Advanced knowledge in atmospheric CO 2 distributions is critical in predicting the Earth's future climate. Large uncertainties in the prediction persist due to limited observations. This study focuses on the development and demonstration of the Intensity-Modulated Continuous-Wave (IM-CW) lidar for atmospheric CO 2 measurements. Simulations show that IM-CW lidar systems operating at 1.57 um will provide precise atmospheric column CO 2 measurements from space. Airborne systems have demonstrated the feasibility of the technology and instrumentation for space active atmospheric CO 2 missions. In this presentation, the atmospheric CO 2 column measurements from airborne flight campaigns and lidar system simulations for space missions will be discussed. Data analysis shows that airborne lidar CO 2 column measurements over desert and vegetated surfaces agree well with in-situ measurements. A measurement precision of 0.08% or ~0.3 ppmv for a 10-s average over these surfaces has also been achieved. Generally, airborne flight campaigns have demonstrated that the column CO 2 measurements of the current IM-CW lidar systems meet the accuracy and precision requirements of atmospheric CO 2 measurements. Furthermore, analyses of space CO 2 measurements shows that the current IM-CW lidar technology and approach will enable space missions to achieve their science goals.

Bing Lin↗
NASA NTRS2003

Evolution of Local Microstructures: Spatial Instabilities in Coarsening Clusters

Diffusion-limited capillarity-driven coarsening of precipitates is an important and intensively studied phenomenon. The classic coarsening theory developed by Lifshitz and Syozov and Wagner (LSW theory) is limited to infinitesimally small volume fractions, V(sub nu), therefore neglects all direct interparticle interactions. This work uses modeling and holographic imaging to compare coarsening rates in "high" volume fraction versus low volume fraction microstructures by observing mixed-dimensional droplets (spherical caps on a surface coarsening by two-dimensional diffusion) during ground-based investigations. The method involves filling a cell with selected homogeneous parent phase, and cooling below the consolute temperature to the isopycnic temperature in the two-phase region of a monotectic system. A microgravity holographic experiment is required for three-dimensional observations to minimize sedimentation during long-term coarsening. Determination of sizes and positions of the many droplets in the holographic images requires automation. We have developed software for automated data analysis, and demonstrated good agreement between regenerated maps and scaled photographs of the original holograms for mixed dimensional coarsening. The results of these experiments were presented in a formal microgravity Science Concept Review (SCR) on December 18, 2000.

Source record↗
DOE OSTI2025

Soil microbial ecology and microbiome-metabolite linkages improve understanding of ecosystem states along terrestrial-aquatic interfaces

These data are from Bandopadhyay et al., "Soil microbial ecology and microbiome-metabolite linkages improve understanding of ecosystem states along terrestrial-aquatic interfaces". This study aims to understand the soil microbial ecology along terrestrial-aquatic interfaces of a freshwater and estuarine region and how it relates to organic matter. We analyzed soil microbial (16S rRNA gene) and organic matter (Fourier-transform ion cyclotron resonance mass spectrometry, FTICR-MS) composition from upland (forested), transition (stressed forest), and wetland positions at three sites in each of the Lake Erie (freshwater) and Chesapeake Bay (estuarine) regions. This dataset includes 16S rRNA gene amplicon data (only processed file types included here) and organic matter composition from FTICR-MS data (raw and processed files included here) from upland (forested), transition (stressed forest), and wetland positions at three sites in each of the Lake Erie and Chesapeake Bay regions. These sites are part of the COMPASS-FME project (https://compass.pnnl.gov/FME/COMPASSFME). File formats and software needed to access files: 16S rRNA gene amplicon data: These files follow the format reported here https://ess-dive.gitbook.io/amplicon-sequencing-reporting-format#updates-in-v1.0.1. As per this format, there are four file types reported: 1. Taxon tables (also called sequence-by-sample or OTU (operational taxonomic unit)/ESV (exact sequence variant) tables) : available in a .txt file format and accessible using TextEdit or MS Excel. 2. Representative sequences (also called consensus sequences) : available in a .fasta format and accessible using TextEdit. 3. Sequencing metadata : available in a MS Excel workbook file format and CSV file format 4. Bioinformatic metadata : available in a MS Excel workbook file format and CSV file format FTICR-MS data: 1. Raw data converted to a processed file with intensities of the peaks in the given samples : available in a MS Excel CSV file format 2. Processed file used in analyses and visualizations (appended as icr_long_) : available in a MS Excel CSV file format 3. Metadata file for ICR features (appended as icr_meta) : available in a MS Excel CSV file format

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Reducing the Cost of Fatigue Crack Growth Testing for Storage Vessel Steels in Hydrogen Gas

Hydrogen storage pressure vessels are designed against fatigue crack growth, and the ASME Boiler and Pressure Vessel Code requires the fatigue crack growth rate (da/dN) vs. stress-intensity factor range (ΔK) relationship of the construction steel to be measured directly in hydrogen gas. These measurements are notoriously slow and expensive: the cyclic loading frequencies prescribed by standards (often 0.1 Hz) are two or more orders of magnitude below those for conventional fatigue testing, individual tests run for days to weeks, and the high-pressure test-chamber set-up imposes a significant per-specimen labor cost. Due to these time and cost constraints, near-threshold data—the regime most valuable for extending design fatigue life—are rarely generated for ferritic storage vessel steels in hydrogen gas.

08 HYDROGEN↗
DOE OSTI2024

Identifying atmospheric rivers and their poleward latent heat transport with generalizable neural networks: ARCNNv1

Abstract. Atmospheric rivers (ARs) are extreme weather events that can alleviate drought or cause billions of US dollars in flood damage. By transporting significant amounts of latent energy towards the poles, they are crucial to maintaining the climate system's energy balance. Since there is no first-principle definition of an AR grounded in geophysical fluid mechanics, AR identification is currently performed by a multitude of expert-defined, threshold-based algorithms. The variety of AR detection algorithms has introduced uncertainty into the study of ARs, and the thresholds of the algorithms may not generalize to new climate datasets and resolutions. We train convolutional neural networks (CNNs) to detect ARs while representing this uncertainty; we name these models ARCNNs. To detect ARs without requiring new labeled data and labor-intensive AR detection campaigns, we present a semi-supervised learning framework based on image style transfer. This framework generalizes ARCNNs across climate datasets and input fields. Using idealized and realistic numerical models, together with observations, we assess the performance of the ARCNNs. We test the ARCNNs in an idealized simulation of a shallow-water fluid in which nearly all the tracer transport can be attributed to AR-like filamentary structures. In reanalysis and a high-resolution climate model, we use ARCNNs to calculate the contribution of ARs to meridional latent heat transport, and we demonstrate that this quantity varies considerably due to AR detection uncertainty.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Classification of events from α -induced reactions in the MUSIC detector via statistical and ML methods

The Multi-Sampling Ionization Chamber (MUSIC) detector is typically used to measure nuclear reaction cross sections relevant for nuclear astrophysics, fusion studies, and other applications. From the MUSIC data produced in one experiment scientists carefully extract an order of 10 3 events of interest from about 10 9 total events, where each event can be represented by an 18-dimensional vector. However, the standard data classification process is based on expert driven, manually intensive data analysis techniques that require several months to identify patterns and classify the relevant events from the collected data. Here, to address this issue, we present a method for the classification of events originating from specific α-induced reactions by combining statistical and machine learning methods that require significantly less input from the domain scientist, relative to the standard technique. Here, we applied the new method to two experimental data sets and compared our results with those obtained using traditional methods. With few exceptions, the number of events classified by our method agrees within ±20% with the results obtained using traditional methods. With the present method, which is the first of its kind for the MUSIC data, we have established the foundation for the automated extraction of physical events of interest from experiments using the MUSIC detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1993

Simulation of a data archival and distribution system at GSFC

A version-0 of a Data Archive and Distribution System (DADS) is being developed at GSFC to support existing and pre-EOS Earth science datasets and test Earth Observing System Data and Information System (EOSDIS) concepts. The performance of DADS is predicted using a discrete event simulation model. The goals of the simulation were to estimate the amount of disk space needed and the time required to fulfill the DADS requirements for ingestion (14 GB/day) and distribution (48 GB/day). The model has demonstrated that 4 mm and 8 mm stackers can play a critical role in improving the performance of the DADS, since it takes, on average, 3 minutes to manually mount/dismount tapes compared to less than a minute with stackers. With two 4 mm stackers and two 8 mm stackers, and a single operator per shift, the DADS requirements can be met within 16 hours using a total of 9 GB of disk space. When the DADS has no stacker, and the DADS depends entirely on operators to handle the distribution tapes, the simulation has shown that the DADS requirements can still be met within 16 hours, but a minimum of 4 operators per shift were required. The compression/decompression of data sets is very CPU intensive, and relatively slow when performed in software, thereby contributing to an increase in the amount of disk space needed.

Bedet, Jean-Jacques↗
NASA NTRS2005

The Application of Infrared Thermographic Inspection Techniques to 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 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 the RCC materials. Details of a one-dimensional analytic model and a two-dimensional finite-element model will be presented. 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 will be shown. Finally, a number of different applications of this technology to various RCC components will be presented.

Cramer, K. E.↗
NASA NTRS2006

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↗