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NASA NTRS2014

Additive Manufacturing Infrared Inspection

Additive manufacturing is a rapid prototyping technology that allows parts to be built in a series of thin layers from plastic, ceramics, and metallics. Metallic additive manufacturing is an emerging form of rapid prototyping that allows complex structures to be built using various metallic powders. Significant time and cost savings have also been observed using the metallic additive manufacturing compared with traditional techniques. Development of the metallic additive manufacturing technology has advanced significantly over the last decade, although many of the techniques to inspect parts made from these processes have not advanced significantly or have limitations. Several external geometry inspection techniques exist such as Coordinate Measurement Machines (CMM), Laser Scanners, Structured Light Scanning Systems, or even traditional calipers and gages. All of the aforementioned techniques are limited to external geometry and contours or must use a contact probe to inspect limited internal dimensions. This presentation will document the development of a process for real-time dimensional inspection technique and digital quality record of the additive manufacturing process using Infrared camera imaging and processing techniques.

Gaddy, Darrell↗

NASA NTRS2014

Lightning Current Measurement with Fiber-Optic Sensor

A fiber-optic current sensor is successfully developed with many potential applications for electric current measurement. Originally developed for in-flight lightning measurement, the sensor utilizes Faraday Effect in an optical fiber. The Faraday Effect causes linear light polarization in a fiber to rotate when the fiber is exposed to a magnetic field. The polarization change is detected using a reflective polarimetric scheme. Forming fiber loops and applying Ampere's law, measuring the total light rotation results in the determination of the total current enclosed. The sensor is conformable to complex structure geometry. It is also non-conductive and immune to electromagnetic interference, saturation or hysteresis. Installation is non-intrusive, and the sensor can be safely routed through flammable areas. Two similar sensor systems are described in this paper. The first system operates at 1310nm laser wavelength and is capable of measuring approximately 300 A - 300 kA, a 60 dB range. Laboratory validation results of aircraft lighting direct and in-direct effect current amplitudes are reported for this sensor. The second system operates at 1550nm wavelength and can measure about 400 A - 400 kA. Triggered-lightning measurement data are presented for this system. Good results are achieved in all cases.

Nguyen, Truong X.↗

NASA NTRS2015

Statistical Analysis of Large Simulated Yield Datasets for Studying Climate Effects

Many studies have been carried out during the last decade to study the effect of climate change on crop yields and other key crop characteristics. In these studies, one or several crop models were used to simulate crop growth and development for different climate scenarios that correspond to different projections of atmospheric CO2 concentration, temperature, and rainfall changes (Semenov et al., 1996; Tubiello and Ewert, 2002; White et al., 2011). The Agricultural Model Intercomparison and Improvement Project (AgMIP; Rosenzweig et al., 2013) builds on these studies with the goal of using an ensemble of multiple crop models in order to assess effects of climate change scenarios for several crops in contrasting environments. These studies generate large datasets, including thousands of simulated crop yield data. They include series of yield values obtained by combining several crop models with different climate scenarios that are defined by several climatic variables (temperature, CO2, rainfall, etc.). Such datasets potentially provide useful information on the possible effects of different climate change scenarios on crop yields. However, it is sometimes difficult to analyze these datasets and to summarize them in a useful way due to their structural complexity; simulated yield data can differ among contrasting climate scenarios, sites, and crop models. Another issue is that it is not straightforward to extrapolate the results obtained for the scenarios to alternative climate change scenarios not initially included in the simulation protocols. Additional dynamic crop model simulations for new climate change scenarios are an option but this approach is costly, especially when a large number of crop models are used to generate the simulated data, as in AgMIP. Statistical models have been used to analyze responses of measured yield data to climate variables in past studies (Lobell et al., 2011), but the use of a statistical model to analyze yields simulated by complex process-based crop models is a rather new idea. We demonstrate herewith that statistical methods can play an important role in analyzing simulated yield data sets obtained from the ensembles of process-based crop models. Formal statistical analysis is helpful to estimate the effects of different climatic variables on yield, and to describe the between-model variability of these effects.

climate↗

NASA NTRS2016

Tholins as Coloring Agents on Pluto and Other Icy Solar System Bodies

Tholins are refractory organic solids of complex structure and high molecular weight, with a wide range of color ranging from yellow and orange to dark red, and through tan to black. They are made in the laboratory by energy deposition (photons or charged particles) in gases and ices containing the simple molecules (e.g., N2, CH4, CO) found in planetary atmospheres or condensed on planetary surfaces. They are widely implicated in providing the colors and albedos, particularly in the region 0.3-1.0 microns, of several outer Solar System bodies, including Pluto, as well as aerosols in planetary atmospheres such as Titan. Recent color images of Pluto with the New Horizons spacecraft show concentrations of coloring agent(s) in some regions of the surface, and apparent near-absence in other regions. Tholins that may to some degree represent surface chemistry on Pluto have been synthesized in the laboratory by energetic processing of mixtures of the ices (N2, CH4, CO) known on Pluto's surface, or the same molecules in the gas phase. Details of the composition and yield vary with experimental conditions. Chemical analysis of Pluto ice tholins shows evidence of amides, carboxylic acids, urea, carbodiimides, and nitriles. Aromatic/olefinic, amide, and other functional groups are identified in XANES analysis. The ice tholins produced by e- irradiation have a higher concentration of N than UV ice tholins, with N/C approx. 0.9 (versus approx. 0.5 for UV tholins) and O/C approx.0.2. Raman spectra of the electron tholin show a high degree of structural disorder, while strong UV fluorescence indicates a large aromatic content. EUV photolysis of a Pluto gaseous atmosphere analog yields pale yellow solids relatively transparent in the visual, and with aliphatic CH bonds prominent in IR spectra. This or similar material may be responsible for Pluto's hazes.

Tholins↗

NASA NTRS2016

Tribology of Polymer Matrix Composites (PMCs) Fabricated by Additive Manufacturing (AM)

The integral process of depositing thin layers of material, one after another, until the designed component is created is collectively referred to as Additive Manufacturing (AM). Fused deposition process (FDP) is a type of AM where feedstock is extruded into filaments which then are deposited by 3D printing, and the solidification occurs during cooling of the melt. Currently, complex structures are being fabricated by commercial and open source desktop 3D printers. Recently, metal powder containing composite filaments based on polylactic acid (PLA) and acrylonitrile butadiene styrene (ABS) have emerged, which could be utilized for multifunctional applications. For further deployment in the field, especially for aerospace and ground-based applications, it is critical to understand the tribological behavior of 3D printed materials. In this presentation, we will report the tribological behavior of different polymer matrix composites fabricated by fused deposition process. These results will be compared with the base polymer systems. During this study, the tribological behavior of all the samples will be evaluated with tab-on-disc method and compared for different metallic powder reinforcements.

additive manufacturing↗

NASA NTRS2015

Contemporary Impact Analysis Methodology for Planetary Sample Return Missions

Development of an Earth entry vehicle and the methodology created to evaluate the vehicle's impact landing response when returning to Earth is reported. NASA's future Mars Sample Return Mission requires a robust vehicle to return Martian samples back to Earth for analysis. The Earth entry vehicle is a proposed solution to this Mars mission requirement. During Earth reentry, the vehicle slows within the atmosphere and then impacts the ground at its terminal velocity. To protect the Martian samples, a spherical energy absorber called an impact sphere is under development. The impact sphere is composed of hybrid composite and crushable foam elements that endure large plastic deformations during impact and cause a highly nonlinear vehicle response. The developed analysis methodology captures a range of complex structural interactions and much of the failure physics that occurs during impact. Numerical models were created and benchmarked against experimental tests conducted at NASA Langley Research Center. The postimpact structural damage assessment showed close correlation between simulation predictions and experimental results. Acceleration, velocity, displacement, damage modes, and failure mechanisms were all effectively captured. These investigations demonstrate that the Earth entry vehicle has great potential in facilitating future sample return missions.

Perino, Scott V.↗

NASA NTRS2017

Association Between Vascular Density and Loss of Protective RAS During Early NPDR by Fractal Dimension

Purpose: Our hypothesis predicts that blood vessels within the retina increase in density during early-stage nonproliferative diabetic retinopathy (NPDR), based on previous results of a small retrospective study. For the current prospective study, the remodeling of arteries and veins during progression of early NPDR is assessed by a repertoire of parameters that includes the fractal dimension (D(sub f) ). In complex structures such as branching vascular trees, D(sub f) is a sensitive measure of space-filing capacity. The renin-angiotensin system (RAS) is implicated in DR pathogenesis and the function of circulating angiogenic cells (CACs), a critical bone marrow-derived population instrumental in vascular repair. Methods: Arterial and venous branching patterns were extracted from images of 6 normal controls and 3 early NPDR subjects (2 moderate, 1 mild) acquired by Heidelberg Spectralis (Registered Trademark) OCT following fluorescein angiography (FA). The vascular branching patterns were analyzed by NASAs VESsel GENeration Analysis (VESGEN) software, in which skeletonized representations were generated automatically to yield D(sub f) by the box-counting method. For binary 2D images, D(sub f) varies between limiting Euclidean dimensions of 1 and 2. Peripheral blood of diabetics and controls was collected for CD34+ CAC isolation. The gene expression of RAS in CACs was assessed by qPCR for Mas receptor to Ang-(1-7). The vasoreparative function of the CACs was measured by migration ability toward CXCL12 (SDF-1). Results: By D(sub f), venous and arterial densities were 1.370 +/- 0.006 and 1.329 +/- 0.016 for early NPDR, compared to 1.318 +/- 0.012 and 1.320 +/- 0.036 for control. The space filling capacity in early NPDR measured by D(sub f), a sensitive parameter, therefore demonstrated a pronounced increase for veins, but not for arteries. Mas receptor mRNA in CACs was increased in diabetics without DR but reduced with onset of NPDR, indicating possible loss of compensation of protective RAS during early DR. Migratory dysfunction of CD34+ cells was further associated with DR. Conclusions: As assessed by the fractal dimension in our preliminary study, the space-filling capacity of veins, but not arteries, was greater in early NPDR than in control. Larger patient populations will be examined as we complete our ongoing longitudinal study. Results further suggest the protective RAS axis within diabetic CACs is lost early in DR and is associated with increased vascular remodeling as evidenced by VESGEN analysis.

vascular↗

NASA NTRS2016

Reflectivity Around the Gold M-Edges of X-ray Reflector of the Soft X-Ray Telescope Onboard ASTRO-H

The X-ray astronomy satellite ASTRO-H are equipped with two equivalent soft X-ray telescopes (SXT-I and SXT-S) which cover the energy band 0.3-12 keV. The X-ray reflectors of the SXTs are coated with a gold monolayer by means of the replication technique. A series of gold M absorption edges in the 2-4 keV band causes complex structures in the energy response of the SXTs. In the same band, there are astrophysically important emission lines from Si, Ar and S. Since the SXS has unprecedentedly high spectral resolution, we have measured the reflectivity around the gold M-edges in an extremely fine energy pitch at the synchrotron radiation facility KEK PF BL11-B, with the 2 eV pitch in 2100 eV to 4100 eV band that covers the entire series of the absorption edges (M-I through M-V) at grazing incident angles to the reflectors of 0.5, 0.8, 1.0, 1.2, 1.4 degree, and with a finer pitch of 0.25 eV in the 2200 eV to 2350 eV band where the two deepest M-IV and M-V edges are included. In the resultant reflectivity curves, we have clearly identified the fine structures associated with all the M-edges. Using these data, we calculated atomic scattering factor f1 as a function of X-ray energy, with which we have built the mirror response function which can be applied to the Suzaku spectra. As a result, we have found that discrepancy of the spectral model to the Suzaku data of 4U1630-472 (a black hole transient) and the Crab nebula around the M-edges are significantly reduced from those with the official Suzaku response.

ASTRO-H↗

NASA NTRS2017

Remote Sensing of Crystal Shapes in Ice Clouds

Ice crystals in clouds exist in a virtually limitless variation of geometries. The most basic shapes of ice crystals are columnar or plate-like hexagonal prisms with aspect ratios determined by relative humidity and temperature. However, crystals in ice clouds generally display more complex structures owing to aggregation, riming and growth histories through varying temperature and humidity regimes. Crystal shape is relevant for cloud evolution as it affects microphysical properties such as fall speeds and aggregation efficiency. Furthermore, the scattering properties of ice crystals are affected by their general shape, as well as by microscopic features such as surface roughness, impurities and internal structure. To improve the representation of ice clouds in climate models, increased understanding of the global variation of crystal shape and how it relates to, e.g., location, cloud temperature and atmospheric state is crucial. Here, the remote sensing of ice crystal macroscale and microscale structure from airborne and space-based lidar depolarization observations and multi-directional measurements of total and polarized reflectances is reviewed. In addition, a brief overview is given of in situ and laboratory observations of ice crystal shape as well as the optical properties of ice crystals that serve as foundations for the remote sensing approaches. Lidar depolarization is generally found to increase with increasing cloud height and to vary with latitude. Although this variation is generally linked to the variation of ice crystal shape, the interpretation of the depolarization remains largely qualitative and more research is needed before quantitative conclusions about ice shape can be deduced. The angular variation of total and polarized reflectances of ice clouds has been analyzed by numerous studies in order to infer information about ice crystal shapes from them. From these studies it is apparent that pristine crystals with smooth surfaces are generally inconsistent with the data and thus crystal impurity, distortion or surface roughness is prevalent. However, conclusions about the dominating ice shapes are often inconclusive and contradictory and are highly dependent on the limited selection of shapes included in the investigations. Since ice crystal optical properties are mostly determined by the aspect ratios of the crystal components and their microscale structure, it is advised that remote sensing applications focus on the variation of these ice shape characteristics, rather than on the macroscale shape or habit. Recent studies use databases with nearly continuous ranges of crystal component aspect ratio and-or roughness levels to infer the variation of ice crystal shape from satellite and airborne remote sensing measurements. Here, the rationale and results of varying strategies for the remote sensing of ice crystal shape are reviewed. Observed systematic variations of ice crystal geometry with location, cloud height and atmospheric state suggested by the data are discussed. Finally, a prospective is given on the future of the remote sensing of ice cloud particle shapes.

clouds↗

NASA NTRS2017

The Latest on the Venus Thermospheric General Circulation Model: Capabilities and Simulations

Venus has a complex and dynamic upper atmosphere. This has been observed many times by ground-based, orbiters, probes, and fly-by missions going to other planets. Two over-arching questions are generally asked when examining the Venus upper atmosphere: (1) what creates the complex structure in the atmosphere, and (2) what drives the varying dynamics. A great way to interpret and connect observations to address these questions utilizes numerical modeling; and in the case of the middle and upper atmosphere (above the cloud tops), a 3D hydrodynamic numerical model called the Venus Thermospheric General Circulation Model (VTGCM) can be used. The VTGCM can produce climatological averages of key features in comparison to observations (i.e. nightside temperature, O2 IR nightglow emission). More recently, the VTGCM has been expanded to include new chemical constituents and airglow emissions, as well as new parameterizations to address waves and their impact on the varying global circulation and corresponding airglow distributions.

chemistry↗

NASA NTRS2018

Is Water Necessary for Life?

The universality of water as the solvent for life is usually justified by its role in supporting the rich organic chemistry. It has been pointed out, however, that even richer synthetic chemistry is possible in other organic solvents. Does it mean that water is not necessary for life? Here, other, essential criteria for solvent for life that have not been sufficiently considered are discussed. In biological systems, complex molecules are not only constantly synthesized but also degraded. Solvent-mediated degradation is essential for regulating cell content, preventing overcrowding and allowing for recycling organic material. Achieving a balance between synthetic and degradative processes is facile in water, but not in many other organic liquids. Thus, the so-called “water paradox” according to which water is both necessary to life and toxic to biopolymer synthesis might not be paradoxical at all. The machinery of life is based on non-covalent interactions that do not involve making or breaking chemical bonds. Their strength needs to be properly tuned. If they are too weak, there might be undesired response to natural fluctuations of physical or chemical parameters. If they are too strong, the kinetics and energetics of cellular processes could adversely influenced. The solvent must allow for balancing these interactions, which provides strong, universal constraints on the medium for life. Water influences non-covalent interactions mainly by two mechanisms. First, it reduces strong, electrostatic interactions between molecules, chemical groups or atoms carrying electric charge or dipole. Second, it induces the hydrophobic effect, the tendency to remove non-polar (hydrophobic) molecules and groups from direct contact with aqueous solution and, instead, interact with each other. In living systems, the hydrophobic effect is largely responsible for self-organization of molecules to more complex structures, such as aggregation of lipid molecules to form biological membranes and protein folding. Water exists as stable liquid in a large temperature range, and the hydrophobic effects are a consequence of the temperature insensitivity of essential properties of its liquid state. In summary, water accomplishes an amazing feat – it reduces strong interactions between dissolved species and simultaneously increases the strength of weak interactions, bringing all of them to the right range. Once we consider not only synthetic capabilities but also other required traits of the solvent for life, no viable alternative to water is currently known.

Life↗

NASA NTRS2019

Additive Manufacturing of Multi-Material Systems for Aerospace Applications

Additive manufacturing methods for producing single materials are rapidly improving. The resulting material properties and microstructures are becoming more comparable to those of conventionally fabricated materials. However, the need for multi-functional and complex structures and components requires additional innovations in manufacturing such as multi-material and hybrid additive manufacturing approaches. Additive manufacturing machines with multiple print capabilities and combinations of AM, machining, and conventional processing methods will further open up design spaces and possibilities. In this presentation, several examples of the needs and methods for multi-material fabrication will be discussed with a focus on aerospace applications. Direct printing of silver coils in conjunction with fused deposition modeling, machined parts, and, binder jetting is being developed for innovative stator designs. Binder jetting of silicon-based materials with powder bed additions is being developed for heat exchanger applications. Additive manufacturing of bi-material systems is being pursued to fabricate lightweight, integrated, multifunctional structures.

multi-materials↗

NASA NTRSDate not supplied

Understanding Thermal Transport in Polymer –Silver Nanowire Composites

Understanding thermal transport across filler-polymer interfaces and filler-filler contacts within polymer composites is of great importance for better thermal design of the composites that are widely used in high-performance heat exchangers, energy storage devices, and flexible electronics. Over the past several decades, considerable progress has been made in improving the thermal conductivity of polymer composites, but several key questions concerning the influence of interfacial thermal resistance, or Kapitza resistance, still remain. Firstly, the thermal properties of these composites are highly dependent on thermal transport through the filler network and its contacts. For metallic nanofillers, the thermal conductivity is often estimated using the Wiedemann-Franz law based on electrical conductivity; however, it remains a question whether the Wiedemann-Franz law still holds at nanoscale contacts. Through investigation of silver nanowires of varying sizes, we were able to demonstrate that the Lorenz number for silver nanowire increases with decreasing nanowire diameter. Examination of the corresponding electrical and thermal conductivities indicate that these changes are due to that the relative contribution of phonons becomes more significant as a result of elastic stiffening. Furthermore, we show that for silver nanowires, the contact thermal resistance is ~8 times lower than that of multi-walled carbon nanotube (MWCNT) of similar diameters. Additionally, through systematic studies of electrospun polymer-silver nanowire composite nanofibers, we investigated the impact of interface morphology on the thermal conductivity enhancement of the composite system and probed the value of the Kapitza resistance for individual polymer-filler interfaces. For polymer nanofibers containing continuous, single silver nanowires, the thermal conductivity increases linearly with increasing volume fraction of silver, which is consistent with the prediction of percolation theory for samples above the percolation limit. By comparing this linear trend to the measured thermal conductivities of composite nanofibers with more complex structures, we were able to determine the resistance associated with any additional polymer-filler boundaries. In doing so we find that the thermal boundary resistance for polyvinylpyrrolidone (PVP)–silver interfaces is significantly lower than that of comparable polymer-MWCNT composite systems.Together our studies provide new insights into thermal transport in polymer nanocomposites and should help facilitate the design of high performance polymeric thermal interface material.

Thermal transport↗

NASA NTRSDate not supplied

Understanding Thermal Transport in Polymer - Silver Nanowire Composites

Understanding thermal transport across filler-polymer interfaces and filler-filler contacts within polymer composites is of great importance for better thermal design of the composites that are widely used in high-performance heat exchangers, energy storage devices, and flexible electronics. Over the past several decades, considerable progress has been made in improving the thermal conductivity of polymer composites, but several key questions concerning the influence of interfacial thermal resistance, or Kapitza resistance, still remain. Firstly, the thermal properties of these composites are highly dependent on thermal transport through the filler network and its contacts. For metallic nanofillers, the thermal conductivity is often estimated using the Wiedemann-Franz law based on electrical conductivity; however, it remains a question whether the Wiedemann-Franz law still holds at nanoscale contacts. Through investigation of silver nanowires of varying sizes, we were able to demonstrate that the Lorenz number for silver nanowire increases with decreasing nanowire diameter. Examination of the corresponding electrical and thermal conductivities indicate that these changes are due to that the relative contribution of phonons becomes more significant as a result of elastic stiffening. Furthermore, we show that for silver nanowires, the contact thermal resistance is ~8 times lower than that of multi-walled carbon nanotube (MWCNT) of similar diameters. Additionally, through systematic studies of electrospun polymer-silver nanowire composite nanofibers, we investigated the impact of interface morphology on the thermal conductivity enhancement of the composite system and probed the value of the Kapitza resistance for individual polymer-filler interfaces. For polymer nanofibers containing continuous, single silver nanowires, the thermal conductivity increases linearly with increasing volume fraction of silver, which is consistent with the prediction of percolation theory for samples above the percolation limit. By comparing this linear trend to the measured thermal conductivities of composite nanofibers with more complex structures, we were able to determine the resistance associated with any additional polymer-filler boundaries. In doing so we find that the thermal boundary resistance for polyvinylpyrrolidone (PVP)–silver interfaces is significantly lower than that of comparable polymer-MWCNT composite systems. Together our studies provide new insights into thermal transport in polymer nanocomposites and should help facilitate the design of high performance polymeric thermal interface material.

Matthew L. Fitzgerald↗

NASA NTRS2020

Origins of X-ray Line Emissions in Circinus X-1 at Very Low X-ray Flux

Accretion conditions and morphologies of X-ray transients containing neutron stars are still poorly understood. Circinus X-1 is an enigmatic case where we observe X-ray flux changes covering four orders of magnitude. We observed Circinus X-1 several times at its very lowest X-ray flux using the high-energy transmission grating spectrometer on board the Chandra X-ray Observatory. At a flux of 1.8 ´ 10-11 erg cm−2 s−1 we observed a single 1.6 keV blackbody spectrum. The observed continuum luminosity of 1035 erg s−1 is about two orders of magnitude too low to explain the observed photoionized luminosity, suggesting a much more complex structure of the X-ray source that is partially or entirely obscured, as had been previously suggested. This affects most emissions from the accretion disk, including previously observed accretion-disk coronal line emissions. Instead, the strongest observed photoionized lines are blueshifted by about ∼400 km s−1, and we suggest that they originate in the ionized wind of a B5Ia supergiant companion, supporting a previous identification. The neutron star in Cir X-1 is very young and should have a high magnetic field. At the observed luminosity, the emission radius of the blackbody is small enough to be associated with the accretion hot spot as the X-ray-emitting region. The small emission radius then points to a field strength below 1012 G, which would be consistent with the observation of occasional type I X-ray bursts at high magnetic fields. We discuss Cir X-1 in the context of being a high-mass X-ray binary, with some emphasis on a possible Be-star X-ray binary nature.

N S Schulz↗

NASA NTRSDate not supplied

Understanding and Verifying Neural Networks

Deep Neural Networks (DNNs) have gained immense popularity in recent times and have widespread use in applications such as image classification, sentiment analysis, speech recognition and also in safety-critical applications such as autonomous driving. However, they suffer limitations such as lack of explainability and robustness which raise safety and security concerns in their usage. Further, the complex structure and large input spaces of DNNs act as an impediment to thorough verification and testing. The SafeDNN project at the Robust Software Engineering (RSE) group at NASA aims at exploring techniques to ensure that systems that use deep neural networks are safe, robust and interpretable. In this talk, I will be presenting our technique Prophecy that automatically infers formal properties of deep neural network models. The tool extracts patterns based on neuron activations as preconditions that imply certain desirable output properties of the model. I would be highlighting case studies that use Prophecy in obtaining explanations for network decisions, understanding correct and incorrect behavior, providing formal guarantees wrt safety and robustness, and debugging neural network models. We have applied the tool on image classification networks, neural network controllers providing turn advisories in unmanned aircrafts, regression models used for autonomous center-line tracking in aircrafts and neural network object detectors

Deep Neural Networks↗

NASA NTRS2021

Volatile Composition and Outgassing in C/2018 Y1 (Iwamoto): Extending Limits for High-Resolution Infrared Cometary Spectroscopy between 2.8 and 5.0 µm

We used the powerful high spectral resolution cross-dispersed facility spectrograph, iSHELL, at the NASAInfrared Telescope Facility(IRTF)to observe C/2018 Y1(Iwamoto), a long-period comet from the Oort cloud.We report production rates for water and eight other parent molecules(native ices),C2H6, CO, CH4,H2CO,CH3OH, HCN, NH3, and C2H2, on three preperihelion UT dates, 2019 January 13 and(near perihelion)February4–5. We present abundance ratios relative to both C2H6(a nonpolar molecule)and H2O(a polar molecule), thereby providing a more complete picture of the parent volatile composition of C/2018 Y1 and potential associations of ices in its nucleus. Overall, the measured spatial distributions for polar molecules(in particular, H2O and CH3OH)were broader, exhibiting more complex structure compared with nonpolar or weakly polar species(CH4,C2H6, andCO). Our January 13 results permitted quantitatively assessing the significant improvement in sensitivity delivered by iSHELL compared with previous capabilities at the IRTF. The efficient spectral coverage of iSHELL plus the favorable geocentric Doppler shift of C/2018 Y1 allowed for measuring>50% of CH4ν3-band emission intensity on both January 13 and February 5. Compositionally, compared to their respective mean abundances among comets from the Oort cloud, C2H6and CH3OH were enriched, CH4and HCN were near normal, and all other species were depleted. The abundance ratio CH3OH/C2H6was higher by 45%±8% on January 13 versusFebruary 5, whereas CH4/C2H6was unchanged within the uncertainty, suggesting nonhomogeneous composition among regions of the nucleus dominating activity on these dates

Michael A. Disanti↗

NASA NTRSDate not supplied

Model Assisted Probability of Detection for NASA Space Missions

Model assisted probability of detection (MAPOD) uses data from simulations to improve a traditional probability of detection (POD) study. This could include extending the parameter space to reduce uncertainty or substituting experimental data with simulated data to reduce the time and cost of a POD study. In the past MAPOD was difficult due to limited computational resources, but recent innovations in simulation tools and high-performance computing have made this type of high-degree-of-freedom modeling possible, and complex structures have made it necessary. This presentation will summarize the work done by the computational nondestructive evaluation (CNDE) specialists within the Nondestructive Evaluation Sciences branch at NASA Langley Research Center (LaRC) to complete a MAPOD study for phased array ultrasound testing (PAUT) of a friction stir welding (FSW) method to be used on Space Launch System (SLS) structures. The three critical needs for a MAPOD study are a validated and verified model of the inspection technique for the structure being inspected, some experimental POD data, and an uncertainty model for both the model and the experimental data. PAUT was simulated using Extende CIVA’s UT module. The model was validated using laboratory inspection data from NASA Marshall Space Flight Center (MSFC) for a Hit/Miss POD for FSW in 2219-T87 aluminum panels representative of those used in the SLS. This model was then used to simulate flaw sizes that were originally omitted from the original POD study. The results of this new MAPOD study will be presented along with a discussion of the methods and processes used to analyze the original data, selected simulation parameters, and development of the uncertainty model used for the statistical analysis. The goal of this effort is not just to improve the POD study but to demonstrate the value of MAPOD and provide a roadmap for application of MAPOD on future projects.

Elizabeth Gregory↗