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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
NASA NTRS2009

Large Area Scene Selection Interface (LASSI). Methodology of Selecting Landsat Imagery for the Global Land Survey 2005

The Global Land Survey (GLS) 2005 is a cloud-free, orthorectified collection of Landsat imagery acquired during the 2004-2007 epoch intended to support global land-cover and ecological monitoring. Due to the numerous complexities in selecting imagery for the GLS2005, NASA and the U.S. Geological Survey (USGS) sponsored the development of an automated scene selection tool, the Large Area Scene Selection Interface (LASSI), to aid in the selection of imagery for this data set. This innovative approach to scene selection applied a user-defined weighting system to various scene parameters: image cloud cover, image vegetation greenness, choice of sensor, and the ability of the Landsat 7 Scan Line Corrector (SLC)-off pair to completely fill image gaps, among others. The parameters considered in scene selection were weighted according to their relative importance to the data set, along with the algorithm's sensitivity to that weight. This paper describes the methodology and analysis that established the parameter weighting strategy, as well as the post-screening processes used in selecting the optimal data set for GLS2005.

Franks, Shannon↗
NASA NTRS2011

Bridging the Gap between NASA Hydrological Data and the Geospatial Community

There is a vast and ever increasing amount of data on the Earth interconnected energy and hydrological systems, available from NASA remote sensing and modeling systems, and yet, one challenge persists: increasing the usefulness of these data for, and thus their use by, the geospatial communities. The Hydrology Data and Information Services Center (HDISC), part of the Goddard Earth Sciences DISC, has continually worked to better understand the hydrological data needs of the geospatial end users, to thus better able to bridge the gap between NASA data and the geospatial communities. This paper will cover some of the hydrological data sets available from HDISC, and the various tools and services developed for data searching, data subletting ; format conversion. online visualization and analysis; interoperable access; etc.; to facilitate the integration of NASA hydrological data by end users. The NASA Goddard data analysis and visualization system, Giovanni, is described. Two case examples of user-customized data services are given, involving the EPA BASINS (Better Assessment Science Integrating point & Non-point Sources) project and the CUAHSI Hydrologic Information System, with the common requirement of on-the-fly retrieval of long duration time series for a geographical point

Rui, Hualan↗
NASA NTRS2006

Space Human Factors Engineering Gap Analysis Project Final Report

Humans perform critical functions throughout each phase of every space mission, beginning with the mission concept and continuing to post-mission analysis (Life Sciences Division, 1996). Space missions present humans with many challenges - the microgravity environment, relative isolation, and inherent dangers of the mission all present unique issues. As mission duration and distance from Earth increases, in-flight crew autonomy will increase along with increased complexity. As efforts for exploring the moon and Mars advance, there is a need for space human factors research and technology development to play a significant role in both on-orbit human-system interaction, as well as the development of mission requirements and needs before and after the mission. As part of the Space Human Factors Engineering (SHFE) Project within the Human Research Program (HRP), a six-month Gap Analysis Project (GAP) was funded to identify any human factors research gaps or knowledge needs. The overall aim of the project was to review the current state of human factors topic areas and requirements to determine what data, processes, or tools are needed to aid in the planning and development of future exploration missions, and also to prioritize proposals for future research and technology development.

Hudy, Cynthia↗
NASA NTRS2014

Modeling of Commercial Turbofan Engine With Ice Crystal Ingestion: Follow-On

The occurrence of ice accretion within commercial high bypass aircraft turbine engines has been reported under certain atmospheric conditions. Engine anomalies have taken place at high altitudes that have been attributed to ice crystal ingestion, partially melting, and ice accretion on the compression system components. The result was degraded engine performance, and one or more of the following: loss of thrust control (roll back), compressor surge or stall, and flameout of the combustor. As ice crystals are ingested into the fan and low pressure compression system, the increase in air temperature causes a portion of the ice crystals to melt. It is hypothesized that this allows the ice-water mixture to cover the metal surfaces of the compressor stationary components which leads to ice accretion through evaporative cooling. Ice accretion causes a blockage which subsequently results in the deterioration in performance of the compressor and engine. The focus of this research is to apply an engine icing computational tool to simulate the flow through a turbofan engine and assess the risk of ice accretion. The tool is comprised of an engine system thermodynamic cycle code, a compressor flow analysis code, and an ice particle melt code that has the capability of determining the rate of sublimation, melting, and evaporation through the compressor flow path, without modeling the actual ice accretion. A commercial turbofan engine which has previously experienced icing events during operation in a high altitude ice crystal environment has been tested in the Propulsion Systems Laboratory (PSL) altitude test facility at NASA Glenn Research Center. The PSL has the capability to produce a continuous ice cloud which is ingested by the engine during operation over a range of altitude conditions. The PSL test results confirmed that there was ice accretion in the engine due to ice crystal ingestion, at the same simulated altitude operating conditions as experienced previously in flight. The computational tool was utilized to help guide a portion of the PSL testing, and was used to predict ice accretion could also occur at significantly lower altitudes. The predictions were qualitatively verified by subsequent testing of the engine in the PSL. In a previous study, analysis of select PSL test data points helped to calibrate the engine icing computational tool to assess the risk of ice accretion. This current study is a continuation of that data analysis effort. The study focused on tracking the variations in wet bulb temperature and ice particle melt ratio through the engine core flow path. The results from this study have identified trends, while also identifying gaps in understanding as to how the local wet bulb temperature and melt ratio affects the risk of ice accretion and subsequent engine behavior.

Jorgenson, Philip C. E.↗
NASA NTRS2014

Modeling of Commercial Turbofan Engine with Ice Crystal Ingestion; Follow-On

The occurrence of ice accretion within commercial high bypass aircraft turbine engines has been reported under certain atmospheric conditions. Engine anomalies have taken place at high altitudes that have been attributed to ice crystal ingestion, partially melting, and ice accretion on the compression system components. The result was degraded engine performance, and one or more of the following: loss of thrust control (roll back), compressor surge or stall, and flameout of the combustor. As ice crystals are ingested into the fan and low pressure compression system, the increase in air temperature causes a portion of the ice crystals to melt. It is hypothesized that this allows the ice-water mixture to cover the metal surfaces of the compressor stationary components which leads to ice accretion through evaporative cooling. Ice accretion causes a blockage which subsequently results in the deterioration in performance of the compressor and engine. The focus of this research is to apply an engine icing computational tool to simulate the flow through a turbofan engine and assess the risk of ice accretion. The tool is comprised of an engine system thermodynamic cycle code, a compressor flow analysis code, and an ice particle melt code that has the capability of determining the rate of sublimation, melting, and evaporation through the compressor flow path, without modeling the actual ice accretion. A commercial turbofan engine which has previously experienced icing events during operation in a high altitude ice crystal environment has been tested in the Propulsion Systems Laboratory (PSL) altitude test facility at NASA Glenn Research Center. The PSL has the capability to produce a continuous ice cloud which is ingested by the engine during operation over a range of altitude conditions. The PSL test results confirmed that there was ice accretion in the engine due to ice crystal ingestion, at the same simulated altitude operating conditions as experienced previously in flight. The computational tool was utilized to help guide a portion of the PSL testing, and was used to predict ice accretion could also occur at significantly lower altitudes. The predictions were qualitatively verified by subsequent testing of the engine in the PSL. In a previous study, analysis of select PSL test data points helped to calibrate the engine icing computational tool to assess the risk of ice accretion. This current study is a continuation of that data analysis effort. The study focused on tracking the variations in wet bulb temperature and ice particle melt ratio through the engine core flow path. The results from this study have identified trends, while also identifying gaps in understanding as to how the local wet bulb temperature and melt ratio affects the risk of ice accretion and subsequent engine behavior.

Jorgenson, Philip C. E.↗
NASA NTRS2021

Liana optical traits increase tropical forest albedo and reduce ecosystem productivity

Lianas are a key growth form in tropical forests. Their lack of self-supporting tissues and their vertical position on top of the canopy make them strong competitors of resources. A few pioneer studies have shown that liana optical traits differ on average from those of colocated trees. Those trait discrepancies were hypothesized to be responsible for the competitive advantage of lianas over trees. Yet, in the absence of reliable modelling tools, it is impossible to unravel their impact on the forest energy balance, light competition, and on the liana success in Neotropical forests. To bridge this gap, we performed a meta-analysis of the literature to gather all published liana leaf optical spectra, as well as all canopy spectra measured over different levels of liana infestation. We then used a Bayesian data assimilation framework applied to two radiative transfer models (RTMs) covering the leaf and canopy scales to derive tropical tree and liana trait distributions, which finally informed a full dynamic vegetation model. According to the RTMs inversion, lianas grew thinner, more horizontal leaves with lower pigment concentrations. Those traits made the lianas very efficient at light interception and significantly modified the forest energy balance and its carbon cycle. While forest albedo increased by 14% in the shortwave, light availability was reduced in the understorey (−30% of the PAR radiation) and soil temperature decreased by 0.5°C. Those liana-specific traits were also responsible for a significant reduction of tree (−19%) and ecosystem (−7%) gross primary productivity (GPP) while lianas benefited from them (their GPP increased by +27%). This study provides a novel mechanistic explanation to the increase in liana abundance, new evidence of the impact of lianas on forest functioning, and paves the way for the evaluation of the large-scale impacts of lianas on forest biogeochemical cycles.

Félicien Meunier↗
NASA NTRS2002

The Neutral Gas Desorption and Breakdown on a Metal-Dielectric Junction Immersed in a Plasma

New results are presented of an experimental study and theoretical analysis of arcing on metal-dielectric junctions immersed in a low-density plasma. Two samples of conventional solar arrays have been used to investigate the effects of arcing within a wide range of neutral gas pressures, ion currents, and electron number densities. All data (except video) were obtained in digital form that allowed us to study the correlation between external parameters (plasma density, additional capacitance, bias voltage, etc) and arc characteristics (arc rate, arc current pulse width and amplitude, gas species partial pressures, intensities of spectral lines, and so on). Arc sites were determined by employing a video-camera, and it is shown that the most probable sites for arc inception are trip le-junctions, even though some arcs were initiated in gaps between cells. The effect of surface conditioning (decrease of arc rate due to outgassing) was clearly demonstrated. Moreover, a considerable increase in arc rate due to absorption of molecules from atmospheric air has been confirmed. The analysis of optical spectra (240-800 nm) reveals intense narrow atomic lines (Ag, H) and wide molecular bands (OH, CH, SiH, SiN) that confirm a complicated mechanism of arc plasma generation. The rate of plasma contamination due to arcing was measured by employing a mass-spectrometer. These measurements provided quite reliable data for the development of a theoretical model of plasma contamination, In conclusion, the arc threshold was increased to above 350 V (from 190 V) by keeping a sample in vacuum (20 micronTorr) for seven days. The results obtained are important for the understanding of the arc inception mechanism, which is absolutely essential for progress toward the design of high voltage solar arrays for space applications.

Vayner, Boris↗
NASA NTRS1981

Results and analyses of ground-based and satellite ozone observations A review

The ground-based network that has been in existence for several decades is described. Attention is given to two basic questions, namely the way in which monthly satellite analyses compare with those from the ground-based network and the way in which the trends from the satellite and ground-based data compare. Synoptic analyses of total ozone for December 1970 are compared with a subjective analysis of the ground-based network and an objective backscatter ultraviolet (BUV) analysis. It is found that the BUV analysis is the more consistent of the two. Considering monthly analyses for September 1970, satellite and ground-based data are found to agree quite well. In considering the question of trend determination by the ground-based versus the satellite systems, attention is given to the sources of error in the satellite system. The principal sources of error in BUV analysis are thought to be calibration drift with time and the fact that, over the lifetime of the satellite spacecraft, power limitations result in a decrease in the number of data points per month, possibly with significant gaps in the coverage.

Miller, A. J.↗
NASA NTRS2013

Practical Application of PRA as an Integrated Design Tool for Space Systems

This paper presents the application of the first comprehensive Probabilistic Risk Assessment (PRA) during the design phase of a joint NASA/NOAA weather satellite program, Geostationary Operational Environmental Satellite Series R (GOES-R). GOES-R is the next generation weather satellite primarily to help understand the weather and help save human lives. PRA has been used at NASA for Human Space Flight for many years. PRA was initially adopted and implemented in the operational phase of manned space flight programs and more recently for the next generation human space systems. Since its first use at NASA, PRA has become recognized throughout the Agency as a method of assessing complex mission risks as part of an overall approach to assuring safety and mission success throughout project lifecycles. PRA is now included as a requirement during the design phase of both NASA next generation manned space vehicles as well as for high priority robotic missions. The influence of PRA on GOES-R design and operation concepts are discussed in detail. The GOES-R PRA is unique at NASA for its early implementation. It also represents a pioneering effort to integrate risks from both Spacecraft (SC) and Ground Segment (GS) to fully assess the probability of achieving mission objectives. PRA analysts were actively involved in system engineering and design engineering to ensure that a comprehensive set of technical risks were correctly identified and properly understood from a design and operations perspective. The analysis included an assessment of SC hardware and software, SC fault management system, GS hardware and software, common cause failures, human error, natural hazards, solar weather and infrastructure (such as network and telecommunications failures, fire). PRA findings directly resulted in design changes to reduce SC risk from micro-meteoroids. PRA results also led to design changes in several SC subsystems, e.g. propulsion, guidance, navigation and control (GNC), communications, mechanisms, and command and data handling (C&DH). The fault tree approach assisted in the development of the fault management system design. Human error analysis, which examined human response to failure, indicated areas where automation could reduce the overall probability of gaps in operation by half. In addition, the PRA brought to light many potential root causes of system disruptions, including earthquakes, inclement weather, solar storms, blackouts and other extreme conditions not considered in the typical reliability and availability analyses. Ultimately the PRA served to identify potential failures that, when mitigated, resulted in a more robust design, as well as to influence the program's concept of operations. The early and active integration of PRA with system and design engineering provided a well-managed approach for risk assessment that increased reliability and availability, optimized lifecyc1e costs, and unified the SC and GS developments.

Kalia, Prince↗
NASA NTRS2012

Hybrid Collaborative Learning for Classification and Clustering in Sensor Networks

Traditionally, nodes in a sensor network simply collect data and then pass it on to a centralized node that archives, distributes, and possibly analyzes the data. However, analysis at the individual nodes could enable faster detection of anomalies or other interesting events as well as faster responses, such as sending out alerts or increasing the data collection rate. There is an additional opportunity for increased performance if learners at individual nodes can communicate with their neighbors. In previous work, methods were developed by which classification algorithms deployed at sensor nodes can communicate information about event labels to each other, building on prior work with co-training, self-training, and active learning. The idea of collaborative learning was extended to function for clustering algorithms as well, similar to ideas from penta-training and consensus clustering. However, collaboration between these learner types had not been explored. A new protocol was developed by which classifiers and clusterers can share key information about their observations and conclusions as they learn. This is an active collaboration in which learners of either type can query their neighbors for information that they then use to re-train or re-learn the concept they are studying. The protocol also supports broadcasts from the classifiers and clusterers to the rest of the network to announce new discoveries. Classifiers observe an event and assign it a label (type). Clusterers instead group observations into clusters without assigning them a label, and they collaborate in terms of pairwise constraints between two events [same-cluster (mustlink) or different-cluster (cannot-link)]. Fundamentally, these two learner types speak different languages. To bridge this gap, the new communication protocol provides four types of exchanges: hybrid queries for information, hybrid "broadcasts" of learned information, each specified for classifiers-to-clusterers, and clusterers-to-classifiers. The new capability has the potential to greatly expand the in situ analysis abilities of sensor networks. Classifiers seeking to categorize incoming data into different types of events can operate in tandem with clusterers that are sensitive to the occurrence of new kinds of events not known to the classifiers. In contrast to current approaches that treat these operations as independent components, a hybrid collaborative learning system can enable them to learn from each other.

Wagstaff, Kiri L.↗
NASA NTRS2007

A Risk-Based Approach for Aerothermal/TPS Analysis and Testing

The current status of aerothermal and thermal protection system modeling for civilian entry missions is reviewed. For most such missions, the accuracy of our simulations is limited not by the tools and processes currently employed, but rather by reducible deficiencies in the underlying physical models. Improving the accuracy of and reducing the uncertainties in these models will enable a greater understanding of the system level impacts of a particular thermal protection system and of the system operation and risk over the operational life of the system. A strategic plan will be laid out by which key modeling deficiencies can be identified via mission-specific gap analysis. Once these gaps have been identified, the driving component uncertainties are determined via sensitivity analyses. A Monte-Carlo based methodology is presented for physics-based probabilistic uncertainty analysis of aerothermodynamics and thermal protection system material response modeling. These data are then used to advocate for and plan focused testing aimed at reducing key uncertainties. The results of these tests are used to validate or modify existing physical models. Concurrently, a testing methodology is outlined for thermal protection materials. The proposed approach is based on using the results of uncertainty/sensitivity analyses discussed above to tailor ground testing so as to best identify and quantify system performance and risk drivers. A key component of this testing is understanding the relationship between the test and flight environments. No existing ground test facility can simultaneously replicate all aspects of the flight environment, and therefore good models for traceability to flight are critical to ensure a low risk, high reliability thermal protection system design. Finally, the role of flight testing in the overall thermal protection system development strategy is discussed.

Wright, Michael J.↗
NASA NTRS2006

Boundary Layer Transition Results From STS-114

The tool for predicting the onset of boundary layer transition from damage to and/or repair of the thermal protection system developed in support of Shuttle Return to Flight is compared to the STS-114 flight results. The Boundary Layer Transition (BLT) Tool is part of a suite of tools that analyze the aerothermodynamic environment of the local thermal protection system to allow informed disposition of damage for making recommendations to fly as is or to repair. Using mission specific trajectory information and details of each damage site or repair, the expected time of transition onset is predicted to help determine the proper aerothermodynamic environment to use in the subsequent thermal and stress analysis of the local structure. The boundary layer transition criteria utilized for the tool was developed from ground-based measurements to account for the effect of both protuberances and cavities and has been calibrated against flight data. Computed local boundary layer edge conditions provided the means to correlate the experimental results and then to extrapolate to flight. During STS-114, the BLT Tool was utilized and was part of the decision making process to perform an extravehicular activity to remove the large gap fillers. The role of the BLT Tool during this mission, along with the supporting information that was acquired for the on-orbit analysis, is reviewed. Once the large gap fillers were removed, all remaining damage sites were cleared for reentry as is. Post-flight analysis of the transition onset time revealed excellent agreement with BLT Tool predictions.

Berry, Scott A.↗
NASA NTRSDate not supplied

New Developments in the CompDam Fiber Kinking Model for the Interaction

This paper describes two new additions to the CompDam fiber kinking model: 1) a failure index for fiber kinking to facilitate interaction between kinking and matrix cracking and 2) a strain-based criterion for fiber rupture to account for fiber breakage before or after fiber kinking. The model formulation is described with the aid of the graphical Considère construction, which is used to determine the conditions for fiber kinking. Verification studies are conducted with single element models to show the behavior of the model in light of the new developments and to evaluate the effect of numerical parameters of the model. The model is used to analyze open hole compression (OHC) specimens with soft, quasi-isotropic, and hard layups. Analysis results are shown for a conventional continuum damage mechanics model using a trilinear constitutive law for fiber damage and for the proposed model to highlight the differences between the two. Comparison with test data highlights the capabilities and remaining gaps in the quantitative prediction of the damage and failure response. While both models can predict many features of the OHC response, accurate prediction of kinking onset in the OHC specimens remains elusive. The results suggest that it is necessary to predict the combined effects of compression and shear loading as well as the structural effects (e.g., ply thickness, strain gradient effect) accurately to match the experimental observations of fiber kinking onset in the three OHC laminates.

Andrew C. Bergan↗
NASA NTRS2024

Ensuring Safe Decision-Making on the Moon and Mars: Cognitive Performance Assessment for Exploration Class Mission EVA

Extravehicular activity (EVA) is one of the most dangerous and cognitively demanding actions that astronauts can execute, and the cognitive demands associated with future partial gravity EVA on the Moon and Mars are expected to be higher compared to microgravity EVA currently conducted from the International Space Station (ISS). Decrements in cognitive performance present an important risk to crew safety during exploration mission class EVA. Yet there is currently insufficient data to characterize cognitive performance prior to, during, and following EVA. Furthermore, it is still unclear which cognitive domains are most important for conducting mission critical decisions with crew safety implications. To address this gap, we conducted a cognitive task analysis (CTA) of EVA to characterize the procedures, the cognitive demands required, and the critical safety decisions associated with decrements in cognitive performance. We used the applied cognitive task analysis method as outlined by Militello and Hutton (1998) and conducted interviews with subject matter experts (SMEs) in EVA at NASA Johnson Space Center in summer 2024. Interviews focused on exploration EVA and elicited feedback from SMEs on the cognitive skills required for specific EVA tasks including cognitive strategies, critical cues, and decision-making strategies. A cognitive demands table was assembled to consolidate and synthesize the information from all interviews. The information from this cognitive task analysis will inform ongoing work to identify the key cognitive domains for safe decision-making during exploration mission class EVA on the Moon and Mars. This work will importantly provide a link between cognitive domains identified in the cognitive task analysis and operationally-relevant performance metrics collected during spaceflight and simulation EVA that can be tracked and assessed by NASA mission operations. Ultimately, this work will aid in the development and application of exploration class cognitive performance monitoring capabilities to improve safe decision-making and inform EVA planning on future spaceflight missions to the Moon and Mars.

Steven R Anderson↗
NASA NTRSDate not supplied

Ensuring Safe Decision-Making on the Moon and Mars: Cognitive Performance Assessment for Exploration Class Mission EVA

Extravehicular activity (EVA) is one of the most dangerous and cognitively demanding actions that astronauts can execute, and the cognitive demands associated with future partial gravity EVAs on the Moon and Mars are expected to be higher compared to microgravity EVAs currently conducted from the International Space Station. Decrements in cognitive performance present an important risk to crew safety during exploration mission class EVA. Yet there is currently insufficient data to characterize cognitive performance prior to, during, and following EVA. Furthermore, it is still unclear which cognitive domains are most important for conducting mission critical decisions with crew safety implications. To address this gap, we conducted a cognitive task analysis (CTA) of EVA to characterize the procedures, the cognitive demands required, and the critical safety decisions associated with decrements in cognitive performance. We conducted a cognitive task analysis with 15 astronauts and subject matter experts in EVA operations and research. Interviews focused on surface exploration EVA and elicited feedback from experts on the cognitive skills required for specific EVA tasks, including cognitive strategies, critical cues, and decision-making strategies. A cognitive demands table was assembled to consolidate and synthesize the information from all interviews. The information from this cognitive task analysis informs ongoing exploration EVA for Moon to Mars. This work identifies the specific cognitive challenges that astronauts are likely to encounter during surface exploration EVA, and provides the foundation for: (1) prioritized and targeted cognitive performance measurement and functional performance tests, (2) EVA simulation design at varying levels of cognitive workload, and (3) the development of training and other technologies that can improve safe decision-making and inform EVA planning on future spaceflight missions to the Moon and Mars.

Steven R Anderson↗
NASA NTRS1998

Analysis of Phase Separation in Czochralski Grown Single Crystal Ilmenite

Ilmenite (FeTiOs) is a wide bandgap semiconductor with an energy gap of 2.58 eV. Ilmenite has properties suited for radiation tolerant applications, as well as a variety of other electronic applications. Single crystal ilmenite has been grown from the melt using the Czochralski method. Growth conditions have a profound effect on the microstructure of the samples. Here we present data from a variety of analytical techniques which indicate that some grown crystals exhibit distinct phase separation during growth. This phase separation is apparent for both post-growth annealed and unannealed samples. Under optical microscopy, there appear two distinct areas forming a matrix with an array of dots on order of 5 pm diameter. While appearing bright in the optical micrograph, atomic force microscope (AFM) shows the dots to be shallow pits on the surface. Magnetic force microscope (MFM) shows the dots to be magnetic. Phase identification via electron microprobe analysis (EMPA) indicates two major phases in the unannealed samples and four in the annealed samples, where the dots appear to be almost pure iron. This is consistent with micrographs taken with a scanning probe microscope used in the magnetic force mode. Samples that do not exhibit the phase separation have little or no discernible magnetic structure detectable by the MFM.

Wilkins, R.↗
NASA NTRS2014

Flash Infrared Thermography Contrast Data Analysis Technique

This paper provides information on an IR Contrast technique that involves extracting normalized contrast versus time evolutions from the flash thermography inspection infrared video data. The analysis calculates thermal measurement features from the contrast evolution. In addition, simulation of the contrast evolution is achieved through calibration on measured contrast evolutions from many flat-bottom holes in the subject material. The measurement features and the contrast simulation are used to evaluate flash thermography data in order to characterize delamination-like anomalies. The thermal measurement features relate to the anomaly characteristics. The contrast evolution simulation is matched to the measured contrast evolution over an anomaly to provide an assessment of the anomaly depth and width which correspond to the depth and diameter of the equivalent flat-bottom hole (EFBH) similar to that used as input to the simulation. A similar analysis, in terms of diameter and depth of an equivalent uniform gap (EUG) providing a best match with the measured contrast evolution, is also provided. An edge detection technique called the half-max is used to measure width and length of the anomaly. Results of the half-max width and the EFBH/EUG diameter are compared to evaluate the anomaly. The information provided here is geared towards explaining the IR Contrast technique. Results from a limited amount of validation data on reinforced carbon-carbon (RCC) hardware are included in this paper.

Koshti, Ajay↗
NASA NTRSDate not supplied

Developing a Vision for Heliophysics Infrastructure: The LIKED Resource and the DIARieS Ecosystem

Heliophysics data and computational infrastracture are not equipped for 21st science, suffering from holes in the know-how to build better systems. Without a clear vision, efforts to improve the infrastructure have been incremental and incoherent. This poster presents both the vision and the technology required: an online LIbrary KnowledgE and Discovery (LIKED) resource for discovering and implementing knowledge, data, and infrastructure resources; and an online analysis ecosystem to simplify Discovery, Implementation, Analysis, Reproducibility, and Sharing (DIARieS) of scientific results and environments. The LIKED and DIARieS solutions adopt FAIR data principles and the best practices from the budding field of open science. The proposed new infrastructure components will close many of the current gaps in heliophysics’ infrastructure, such as the ability to search for data and knowledge by phenomenon across domains, and to find software and examples relevant to the desired data set (including model data). Further, these components will enable community members to more efficiently use the resources already present and improve upon the content via a community-curated and trusted library. Combining these solutions lowers the barriers to heliophysics resources for all, increasing the return on our investments. Finally, the structure behind these ideas are topic-agnostic, so they are fully extensible to other fields, leading to invaluable connections to other disciplines. Just as with the development and construction of a long-term satellite mission, we must work together as a community to build a vision of the infrastructure that will most benefit the community, and then collaborate to construct, assemble, and test all the necessary pieces individually and as a unit. Our purpose in presenting this work is to not only describe the proposed vision, but also to gather feedback from the community on this topic.

infrastructure↗