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At least 667 records · Page 37

Measurement of Material Recession and Shock Standoff in Plasma Windtunnel using Neural Nets

Arcjets are plasma wind tunnels used to test the performance of heatshield materials for spacecraft atmospheric entry. These facilities present an extremely harsh flow environment with heat fluxes up to 109 W/m2 for up to 30 minutes. The plasma is low-temperature (∼1 eV) but high pressure (> 10 kPa) creating high-enthalpy supersonic flows similar to atmospheric entry conditions. Typically, material samples are measured before and after a test to characterize the total recession. However, this does not capture time-dependent effects such as material expansion and non-linear recession. This work will present new analysis of arcjet test videos which measure both the time-dependent 2D recession of the material samples and the shock standoff distance. The results show non-linear time-dependent effects are present for some conditions. The material and shock edges are extracted from the videos by training and applying a convolutional neural network. Due to the consistent camera settings, the machine learning model achieves high accuracy (± 2 px) relative to manually segmented images with only a small number of training frames (80).

Neural network↗

Theoretical and kinetic modeling study of hydrazine oxidation

The present work constitutes the first theoretical and kinetic modeling study of hydrazine oxidation, which may be important for burnout in ammonia-fueled combustion. The kinetics of the oxidation of N 2 H 4 , N 2 H 3 and tHNNH by molecular oxygen were investigated via a quantum chemistry/canonical transition state theory approach. Geometries and anharmonic frequencies were obtained with density functional theory, and energies from coupled cluster calculations (CCSD(T)) extrapolated to the infinite basis set limit, with corrections for core-valence electron correlation, scalar relativistic effects, and higher level correlation up to lambda coupled cluster, CCSDT(Q) Λ . The key reactions occurred on the N 2 H 4 O 2 potential energy surface, where the results indicated a fast reaction of N 2 H 3 with HO 2 via singlet adducts to yield tHNNH + H 2 O 2 and HNN(H)O + H 2 O, while reaction on the triplet surface proceeds via a bound complex followed by a tight, submerged barrier to yield N 2 H 4 + O 2 . The results were incorporated in a detailed reaction mechanism, which was used to interpret the shock tube results from Michel and Wagner (1965) on the effect of O 2 on hydrazine conversion at 1100–1400 K. The kinetic model captured qualitatively the observed behavior, but underestimated the reaction rate under oxidizing conditions. The hydrazine pyrolysis chemistry dominated conversion at reducing conditions and/or high temperature. At oxidizing conditions and intermediate temperatures (≲ 1400 K), reactions of N 2 -amines with HO 2 and O 2 were important for the oxidation rate.

Ab initio calculations↗

Transient Two-Dimensional Analysis of Side Load in Liquid Rocket Engine Nozzles

Two-dimensional planar and axisymmetric numerical investigations on the nozzle start-up side load physics were performed. The objective of this study is to develop a computational methodology to identify nozzle side load physics using simplified two-dimensional geometries, in order to come up with a computational strategy to eventually predict the three-dimensional side loads. The computational methodology is based on a multidimensional, finite-volume, viscous, chemically reacting, unstructured-grid, and pressure-based computational fluid dynamics formulation, and a transient inlet condition based on an engine system modeling. The side load physics captured in the low aspect-ratio, two-dimensional planar nozzle include the Coanda effect, afterburning wave, and the associated lip free-shock oscillation. Results of parametric studies indicate that equivalence ratio, combustion and ramp rate affect the side load physics. The side load physics inferred in the high aspect-ratio, axisymmetric nozzle study include the afterburning wave; transition from free-shock to restricted-shock separation, reverting back to free-shock separation, and transforming to restricted-shock separation again; and lip restricted-shock oscillation. The Mach disk loci and wall pressure history studies reconfirm that combustion and the associated thermodynamic properties affect the formation and duration of the asymmetric flow.

Wang, Ten-See↗

Measurement of material recession and shock standoff in plasma windtunnel using neural nets

Arcjets are plasma wind tunnels used to test the performance of heatshield materials for spacecraft atmospheric entry. These facilities present an extremely harsh flow environment with heat fluxes up to 10^9 W/m^2 for up to 30 minutes. The plasma is low-temperature (~1 eV) but high pressure (> 10 kPa) creating high-enthalpy supersonic flows similar to atmospheric entry conditions. Typically, material samples are measured before and after a test to characterize the total recession. However, this does not capture time-dependent effects such as material expansion and non-linear recession. This work will present new analysis of arcjet test videos which measure both the time-dependent 2D recession of the material samples and the shock standoff distance. New results showing non-linear material erosion rates will be highlighted. The material and shock edges are extracted from the videos by training and applying a convolutional neural network. Due to the consistent camera settings, the machine learning model achieves high accuracy (~99%) on new data with only a small number of training frames (~80). The new results will be discussed in the context of temperature dependent plasma-surface interaction.

Magnus A Haw↗

Numerical simulations of the Los Alamos gapstick experiment

The gapstick is a high explosive (HE) sensitivity test recently developed at Los Alamos. The experiment design was motivated by the traditional gap test and consists of a series of HE and inert pellets in a rate stick configuration. The inert pellets are made increasingly longer so that eventually the attenuated shock is unable to initiate the next HE pellet. While the gapstick is a mechanically simple experiment it poses several challenges for numerical simulation. In particular, accurately modeling the HE initiation and detonation phenomena requires a reactive burn model with sufficient mesh resolution to capture the reaction scales. In this work, the Scaled Uniform Reactive Front (SURF) and Arrhenius Wescott-Stewart-Davis (AWSD) burn models are used for simulations of a PBX 9501 (95 wt% HMX, 5% binder) gapstick. Furthermore, the material model for the inert pellet material, Polyvinylidene Fluoride (PVDF), has a direct influence on the shock propagation and a new equation of state (EOS) calibration for PVDF is developed using available Hugoniot data. Despite some challenges, the simulations are able to reasonably predict shock transit velocities and detonation failure in the gapstick.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Spectroscopic Measurement of the Flows in an Arc-Jet Facility

To provide the proper test conditions for various applications, the characteristics of arcjet test facilities should be known. To determine the operational characteristics of an arcjet facility, emission spectroscopy measurements have been performed and analyzed in a previous study. As an extension of the study, radiation from the free stream and the shock layer of 15 cm diameter blunt-body test articles is measured under different test conditions in the NASA Ames 20 MW Arcjet Facility. The test gas is a mixture of argon and air or N2 and argon. To capture the spatially resolved emission spectra along the stagnation streamline of the blunt-body, a CCD camera (1024 x 256 array) with .275 m Czerny-Turner spectrograph is used. The optical system is calibrated in situ using tungsten and deuterium radiation sources. The emission measurements supplement the existing data base and will help provide better understanding of the equilibration processes in the shock layer region.

Park, C. S.↗

Strength of porous α-SiO 2 in a shock loaded environment: Calibration via Richtmyer–Meshkov instability and validation via Mach lens

The strength of brittle porous media is of concern in numerous applications, for example, earth penetration, crater formation, and blast loading. Thus, it is of importance to possess techniques that allow for constitutive model calibration within the laboratory setting. The goal of the current work is to demonstrate an experimental technique allowing for strength assessment of porous media subjected to shock loading, which can be implemented into pressure-dependent yield surfaces within numerical simulation schemes. As a case study, the deviatoric response of distended α-SiO 2 has been captured in a tamped Richtmyer–Meshkov instability (RMI) environment at a pressure regime of 4–10 GPa. Hydrocode simulations were used to interpret RMI experimental data, and a resulting pressure-dependent yield surface akin to the often employed modified Drucker–Prager model was calibrated. Simulations indicate that the resulting jet length generated by the RMI is sensitive to the porous media strength, thereby providing a feasible experimental platform capable of capturing the pressurized granular deviatoric response. Furthermore, in efforts to validate the RMI-calibrated strength model, a set of Mach-lens experiments was performed and simulated with the calibrated pressure-dependent yield surface. Excellent agreement between the resulting Mach-lens length in experiment and simulation provides additional confidence to the RMI yield-surface calibration scheme.

36 MATERIALS SCIENCE↗

Data Processing and Experimental Design for Micrometeorite Impacts in Small Bodies

Comets and asteroids have been altered from their original "pristine" state by impacts occurring throughout their 4.5 billion year lives: [1]. Proof of shock deformation has been detected in the crystal structure of several Stardust samples from Comet Wild 2 [2, 3]. Analyses indicated that the planar dislocations in the crystal structure of the minerals had been imparted by impacts sustained during their lives, and not due to the aerogel capture process. Distortions to crystal structure also affect the ideal absorption spectra in the infrared, and [4], thus providing indirect evidence of its impact history and a means of remotely investigating the impact history of small bodies through comparing laboratory spectra with spectra observed by telescopes or spacecraft. -The effects of impacts propagating shock waves through minerals were investigated through laboratory impact experiments. Utilizing NASA Johnson Space Center's Experimental Impact Laboratory, projectiles were fired from the vertical gun at velocities ranging from 2.0 to 2.8 km/sec, projected impact velocities between Kuiper Belt Objects. Two types of projectiles were used, including spherical alumina ceramic, whose density mimics that of rock, and cylinders made from the same material that they impacted. The target materials chosen for testing included: OLIVINES forsterite (Mg2SiO4) and fayalite, Fe2SiO4); PYROXENES enstatite (Mg2Si2O6) and diopside (MgCaSi2O6); and CARBONATES magnesite (MgCO3) and siderite (FeCO3). Targets were impacted at either 25 C or cooled to -20 C to examine the effects of temperature, if any, on lattice distortions during the shock propagation. As comets and asteroids can undergo a wide range of temperatures in their orbital lifetimes, the effect of temperature on the equation of state of minerals being shocked needs to be examined for interpreting the results of these experiments. The porosity of the target mineral is varied by either grinding it into a powder/granular texture or as whole mineral rocks to investigate the differences in shock propagation when voids are present. By varying velocity, ambient temperature, and porosity, we can investigate different variables affecting impacts in the solar system. -Data indicates that there is a non-linear relationship between peak shock pressure and the variation in infrared spectral absorbances by the distorted crystal structure. The maximum variability occurs around 37 GPa in enstatite and forsterite. The particle size distribution of the impacted material similarly changes with velocity/peak shock pressure. -The experiments described above are designed to measure the near- to mid-IR effects from these changes to the mineral structure. See Lederer et al., this meeting for additional experimental results.

Jensen, E.↗

Lessons Learned in the Selection and Development of Test Cases for the Aeroelastic Prediction Workshop: Rectangular Supercritical Wing

The Aeroelastic Prediction Workshop brought together an international community of computational fluid dynamicists as a step in defining the state of the art in computational aeroelasticity. The Rectangular Supercritical Wing (RSW) was chosen as the first configuration to study due to its geometric simplicity, perceived simple flow field at transonic conditions and availability of an experimental data set containing forced oscillation response data. Six teams performed analyses of the RSW; they used Reynolds-Averaged Navier-Stokes flow solvers exercised assuming that the wing had a rigid structure. Both steady-state and forced oscillation computations were performed by each team. The results of these calculations were compared with each other and with the experimental data. The steady-state results from the computations capture many of the flow features of a classical supercritical airfoil pressure distribution. The most dominant feature of the oscillatory results is the upper surface shock dynamics. Substantial variations were observed among the computational solutions as well as differences relative to the experimental data. Contributing issues to these differences include substantial wind tunnel wall effects and diverse choices in the analysis parameters.

Heeg, Jennifer↗

Experimentally validated multiphysics modeling of fracture induced by thermal shocks in sintered UO 2 pellets

Uranium Dioxide (UO 2 ) fuel powers almost all commercial Nuclear Power Plants (NPPs) worldwide, generating carbon-free energy and contributing to the fight against climate change. UO 2 fuel incurs damage and fractures due to large thermal gradients that develop across the fuel pellet during normal and transient operating conditions. A comprehensive understanding of the underlying mechanisms by which these processes take place is still lacking. A combined experimental and computational approach is utilized here to quantify the behavior of UO 2 fuel fracture induced by thermal shock. Here, this work introduces both (1) an experimental study to understand the fuel fracturing behavior of sintered UO 2 pellets when exposed to thermal shock, and (2) a Multiphysics phase-field fracture model capable of simulating this process. Parametric studies were conducted to evaluate the effects of uncertainties in fracture properties on the fracture behavior of UO 2 due to thermal shocking. A set of energy release rate (or equivalently fracture toughness) and contract area (the part of the fuel pellet in direct contact with the cold bath) were able to capture the overall fracture trends of the corresponding experimental data. Our combined approach presents a new method for accounting for the effects of microstructure and sample size on the energy release rate/fracture toughness. The experimental data were collected from multiple experiments that exposed UO 2 pellets to high-temperature conditions (589–676 °C) followed by a quench in sub-zero water. This work demonstrates that joint experimental and computational efforts are able to advance the understanding of thermal fracture in the primary fuel source for existing and future NPPs.

36 MATERIALS SCIENCE↗

The origin of the Crab Nebula and the electron capture supernova in 8-10 M solar mass stars

The chemical composition of the Crab Nebula is compared with several presupernova models. The small carbon and oxygen abundances in the helium-rich nebula are consistent with only the presupernova model of the star whose main sequence mass was MMS approximately 8-9.5 M. More massive stars contain too much carbon in the helium layer and smaller mass stars do not leave neutron stars. The progenitor star of the Crab Nebula lost appreciable part of the hydrogen-rich envelope before the hydrogen-rich and helium layers were mixed by convection. Finally it exploded as the electron capture supernova; the O+Ne+Mg core collapsed to form a neutron star and only the extended helium-rich envelope was ejected by the weak shock wave.

Nomoto, K.↗

IceCube Sensitivity for Low-Energy Neutrinos from Nearby Supernovae

This paper describes the response of the IceCube neutrino telescope located at the geographic South Pole to outbursts of MeV neutrinos from the core collapse of nearby massive stars. IceCube was completed in December 2010 forming a lattice of 5160 photomultiplier tubes that monitor a volume of approx. 1 cu km in the deep Antarctic ice for particle induced photons. The telescope was designed to detect neutrinos with energies greater than 100 GeV. Owing to subfreezing ice temperatures, the photomultiplier dark noise rates are particularly low. Hence IceCube can also detect large numbers of MeV neutrinos by observing a collective rise in all photomultiplier rates on top of the dark noise. With 2 ms timing resolution, IceCube can detect subtle features in the temporal development of the supernova neutrino burst. For a supernova at the galactic center, its sensitivity matches that of a background-free megaton-scale supernova search experiment. The sensitivity decreases to 20 standard deviations at the galactic edge (30 kpc) and 6 standard deviations at the Large Magellanic Cloud (50 kpc). IceCube is sending triggers from potential supernovae to the Supernova Early Warning System. The sensitivity to neutrino properties such as the neutrino hierarchy is discussed, as well as the possibility to detect the neutronization burst, a short outbreak's released by electron capture on protons soon after collapse. Tantalizing signatures, such as the formation of a quark star or a black hole as well as the characteristics of shock waves, are investigated to illustrate IceCube's capability for supernova detection.

Stamatikos, M.↗

Hybrid Kinetic Model of the Interaction Between the Dense Plasma Clouds and Magnetospheric Plasma on Large Time and Spatial Scales, and Comparison With MMS Observations

We present a new simulation results of the cloud dynamics in the ambient magnetospheric plasma on the large time and spatial scales. It was assumed that these impulsive structures observed by the MMS spacecraft originally were created because of the reconnection at the magnetopause. Our new 3-D hybrid kinetic modeling on the large time and spatial scales captures several of these processes: an excitation of the electromagnetic waves (whistler and shear-Alfvén waves) and plasma instabilities (mirror and flute); a formation of shock waves, and collapsing diamagnetic cavity; particle acceleration. A strong overshoot in plasma density profile was observed in the modeling and MMS observation at the interface between the cloud and magnetospheric plasma. The cloud expansion into ambient magnetospheric plasma causes the flute waves connected with excitation of the Rayleigh-Taylor instability observed at the overshoot in plasma density profile across the external magnetic field. The modeling demonstrates a formation of the whistler waves at the initial stage which propagate in the external magnetic field direction. At the later stage, a formation of shear-Alfvén waves was observed

A. S. Lipatov↗

Enabling Intelligent Data Downlink Prioritization of In-Situ Observations through Generalizable and Computationally Inexpensive Anomaly Detection

High-fidelity measurements of magnetic fields and other observed properties, such as energetic particle fluxes, are a necessary component to our understanding of the highly dynamic near-Earth space environment. As our desire to study smaller-scale phenomena such as shocks and dipolorizations has increased, we have been driven to take and telemeter measurements at higher cadences. Unfortunately, many missions are unable to downlink all their captured data due to the well-known data transmission bottleneck at the DSN. These missions must then prioritize their high-cadence data such that the most scientifically useful intervals are transmitted. One simple prioritization technique uses the spacecraft position to telemeter data from only the region of interest. Although easy to implement, this method does not leverage the available scientific data and can omit intervals of useful scientific data when they lie outside the region of interest. The Magnetospheric Multiscale Mission (MMS) uses mission-specific parameterization of several data products to automatically prioritize scientifically useful intervals. Then, MMS verifies the automatically selected intervals by having a domain expert manually select intervals for downlink. The overall complexity required by this technique make it prohibitive for deployment on low-cost platforms (i.e., CubeSats) or on future missions featuring large constellations of satellites such as the Geospace Dynamics Constellation (GDC). We present preliminary results for a simple, generic, and data-driven method of downlink prioritization for magnetic field (and other) measurements. Specifically, Principal Components Analysis (PCA) and One-Class Support Vector Machines (OC-SVMs) are used to detect intervals containing anomalous activity, which can then be prioritized for subsequent downlink. The computational simplicity of this algorithm makes it an excellent candidate for implementation on spaceflight hardware, as well as provide generalizability to a broad range of missions and data products. Initial analysis of this technique has been performed using magnetic field measurements from the Magnetospheric Multiscale Mission and CASSIOP, where it automatically identified scientifically interesting intervals containing Alfvén waves and EMIC activity.

Matthew G. Finley↗

Enabling Intelligent Data Downlink Prioritization of In-Situ Observations through Generalizable and Computationally Inexpensive Anomaly Detection

High-fidelity measurements of magnetic fields and other observed properties, such as energetic particle fluxes, are a necessary component to our understanding of the highly dynamic near-Earth space environment. As our desire to study smaller-scale phenomena such as shocks and dipolorizations has increased, we have been driven to take and telemeter measurements at higher cadences. Unfortunately, many missions are unable to downlink all their captured data due to the well-known data transmission bottleneck at the DSN. These missions must then prioritize their high-cadence data such that the most scientifically useful intervals are transmitted. One simple prioritization technique uses the spacecraft position to telemeter data from only the region of interest. Although easy to implement, this method does not leverage the available scientific data and can omit intervals of useful scientific data when they lie outside the region of interest. The Magnetospheric Multiscale Mission (MMS) uses mission-specific parameterization of several data products to automatically prioritize scientifically useful intervals. Then, MMS verifies the automatically selected intervals by having a domain expert manually select intervals for downlink. The overall complexity required by this technique make it prohibitive for deployment on low-cost platforms (i.e., CubeSats) or on future missions featuring large constellations of satellites such as the Geospace Dynamics Constellation (GDC). We present preliminary results for a simple, generic, and data-driven method of downlink prioritization for magnetic field (and other) measurements. Specifically, Principal Components Analysis (PCA) and One-Class Support Vector Machines (OC-SVMs) are used to detect intervals containing anomalous activity, which can then be prioritized for subsequent downlink. The computational simplicity of this algorithm makes it an excellent candidate for implementation on spaceflight hardware, as well as provide generalizability to a broad range of missions and data products. Initial analysis of this technique has been performed using magnetic field measurements from the Magnetospheric Multiscale Mission and CASSIOP, where it automatically identified scientifically interesting intervals containing Alfvén waves and EMIC activity.

Matthew G. Finley↗

Numerical Simulation and Experimental Comparison of System Analysis Module 1D Mixing Model for Cold Shock Transients in the Gallium Thermal-Hydraulic Mixing Facility

Abstract Liquid metals are being investigated as coolants in many advanced reactor designs because of their high thermal conductivity and effectiveness at high temperatures. However, they often pose challenges to reactor operation and safety because of the complex thermal mixing and stratification in the plenum of pool-type reactor designs. The advanced system analysis code System Analysis Module (SAM) currently under development at Argonne National Laboratory aims to develop and implement thermal mixing models to accurately capture these complex thermal fluid behaviors. In this study, the SAM thermal mixing model was compared against experimental data from the Gallium Thermal-Hydraulic Experiment facility, a scaled liquid metal test facility that uses gallium as a surrogate fluid to investigate the stratification and thermal mixing of low-Prandtl-number fluids in the upper plenum of a liquid metal-cooled reactor. Two cold shock transient cases were used: one with stable stratified flow (Ri = 32) and one with stronger thermal mixing (Ri = 0.5). The resultant temperatures were then compared with the experimental temperatures over the entire plenum to assess the ability of the mixing models to capture the thermal behavior and to better correspond mixing parameters to various flow scenarios. Generally, the zero-dimensional mixing model was more capable of capturing the bulk temperature of the component modeled assuming that an accurate mass flow rate was provided, but it was inherently unable to capture thermal gradients in space. The one-dimensional mixing model was capable of capturing that the thermal gradients provided accurate selection of the mixing coefficients. Further, the temperature at the outlet junction was compared over time for each of the mixing models with the recorded experimental temperature. The implemented mixing models demonstrated the ability to effectively capture the overall thermal behavior for stronger mixing scenarios but struggled with more stably stratified flows. It was found that a system analysis code's covering of the entire range of different operating conditions still remains a challenging task, and it is suggested that further model and closure improvements are necessary to accurately capture complex thermal mixing and stratification phenomena.

stratification↗

The use of silica aerogel to collect interplanetary dust in space

We report on impact experiments to evaluate the suitability of silica aerogel as a capture medium for interplanetary dust particles in space. The structure of silica aerogel is such that even micrometer-sized hypervelocity particles may sense it as a target of very low density; consequently shock stresses and temperatures due to impact should be minimized. We performed impact experiments in a light gas gun that employed projectiles manufactured from forsterite, pyrrhotite, and calcite. From these experiments we have developed techniques that will permit the successful extrication of interplanetary dust particles from aerogel. We note a rough correlation between increasing particle penetration lengths and decreasing aerogel density, and there is a poor correlation of track lengths with impact velocity at laboratory-attainable velocities of 5-7 km/s. We conclude that aerogel track length should not be used even as (crude) velocity indicators. Transmission electron microscope studies show the re covered particulate residues are encased in melted silica aerogel, which possibly protects the residue from some impact damage. Individual minerals within interplanetary dust are expected to exhibit differential survival, and may be vaporized, melted, dehydrated, or structurally reordered. However, some mineral grains should successfully be captured in an unmelted state at encounter velocities less than 8 km/s.

Zolensky, Michael E.↗

Capturing, Analyzing, Maintaining, and Disseminating Shape Memory Material Data Between Information Management Systems

With an increased demand on reducing the time, cost, and effort to develop new materials, Integrated Computational Materials Engineering (ICME) has received widespread attention in various engineering disciplines as a catalyst for significantly reducing experimental testing during the material design process. An ICME approach to design can enable ‘fit-for-purpose’ materials to be realized in engineering applications by incorporating well-understood process-property-performance relationships between the various length and time scales in a material’s structure, enabling material optimization. However, such an approach requires validated multiscale models at the various length scales for a material, which in turn requires a large amount of data, a robust means of storing the data, and the ability to link data to developed material models. The NASA Vision 2040 [1] has identified nine key elements to enabling ICME approaches in system level design, with one being “Data, Information, and Visualization”, thus outlining the importance of a robust information management system for ICME. As the relationship between microstructure, properties, and material performance become better understood and incorporated into multiscale models that can be leveraged in application design, the emergence of new materials with application-driven properties can be realized. One such new material class that has seen growing attention are shape memory materials (SMM), in which a material can transition between a deformed and undeformed state via a reversible phase transformation when subject to a thermal, mechanical, or magnetic load [2]. SMMs have been used widely in aerospace and biomedical industries, including applications such as actuators, low-shock mechanisms, medical staples, braces, and stents [3, 4]. These materials exhibit unique behavior due to their ability to transition between phases, and thus the mechanisms that enable this transition must be captured in a data information management system and incorporated into SMM material models. At NASA Glenn Research Center, the Shape Memory Materials Database (SMMD) Tool has been developed to capture the necessary information that governs SMM material behavior and provide users the ability to select and visualize various SMMs for a specific application [5]. The database contains point-wise data for published SMM materials, along with the pedigree metadata for traceability necessary for a robust information management system. The database is also capable of storing in-house test data performed at NASA GRC by interacting with the developed Shape Memory Alloy (SMA) Analytics tool to extract the necessary point-wise values and populate the database. Although the SMMD Tool offers its users a single, authoritative source for SMM material data that is critical for model development and material design, the full material pedigree of the in-house test data for SMMs is not currently captured and is out of the scope for the SMMD tool. In this work, the schema for capturing SMM test data within the larger NASA GRC ICME Schema [6, 7, 8, 9] will be developed and implemented for thermomechanical tests conducted at NASA GRC. The developed schema will not only store the relevant data needed for the SMMD tool, but also the material pedigree (i.e., production of the bulk material, bulk material analysis, sample cut-out diagrams, sample fabrication procedure, etc.), test pedigree (i.e., test equipment used, measurement systems used, raw test data), and analysis pedigree (i.e., how the data in the SMMD tool is calculated). Furthermore, a Python-based framework will be developed to seamlessly interact between the SMA Analytics and SMMD tools, which will write the full dataset and associated metadata to the GRC Information Management System before passing the required point-wise data to the SMMD tool. Data informatics is a key element of the NASA Vision 2040, which requires not only that data is stored and maintained throughout the material lifecycle, but that the data is also accessible and reusable such that material development efforts can be minimized. Therefore, for an ICME design approach to be realized, a centralized information management system that drives the ICME process must be able to communicate with other databases. The work that will be presented in this presentation will therefore not only demonstrate the ability of NASA GRC’s information management system to capture SMM data, but also its ability to interact with pre-existing tools specialized for such materials.

Data management↗