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NASA NTRS2019

ESD Reviews: Model Dependence in Multi-Model Climate Ensembles: Weighting, Sub-Selection and Out-Of-Sample Testing

The rationale for using multi-model ensembles in climate change projections and impacts research is often based on the expectation that different models constitute independent estimates; therefore, a range of models allows a better characterisation of the uncertainties in the representation of the climate system than a single model. However, it is known that research groups share literature, ideas for representations of processes, parameterisations, evaluation data sets and even sections of model code. Thus, nominally different models might have similar biases because of similarities in the way they represent a subset of processes, or even be near-duplicates of others, weakening the assumption that they constitute independent estimates. If there are near-replicates of some models, then treating all models equally is likely to bias the inferences made using these ensembles. The challenge is to establish the degree to which this might be true for any given application. While this issue is recognised by many in the community, quantifying and accounting for model dependence in anything other than an ad-hoc way is challenging. Here we present a synthesis of the range of disparate attempts to define, quantify and address model dependence in multi-model climate ensembles in a common conceptual framework, and provide guidance on how users can test the efficacy of approaches that move beyond the equally weighted ensemble. In the upcoming Coupled Model Intercomparison Project phase 6 (CMIP6), several new models that are closely related to existing models are anticipated, as well as large ensembles from some models. We argue that quantitatively accounting for dependence in addition to model performance, and thoroughly testing the effectiveness of the approach used will be key to a sound interpretation of the CMIP ensembles in future scientific studies.

Abramowitz, Gab↗

NASA NTRSDate not supplied

A Transmission Electron Microscopy Study of a Refractory Metal Grain from a Calcium-Aluminum-Rich Inclusion in the Leoville CV3 Chondrite

Introduction: Calcium-aluminum-rich inclusions (CAIs) are an important component of chondritic meteorites. They can contain materials that are thermodynamically predicted and isotopically age dated to be among the first-formed solids in our solar system [1-5]. Observed in some CAIs are micron to sub-micron sized inclusions rich in Fe, Ni, and high-Z elements such as Pt, Os, Ir and W, in the form of refractory metal nuggets (RMNs), fremdlinges, and ‘nugget like objects’ (NLOs) [1,6]. Refractory siderophile elements such as Os, Ir and Ru are thermodynamically predicted to condense at temperatures well in excess of the major CAI phases such as melilite, perovskite, spinel and hibonite [2,7-9]. These refractory metal inclusions in CAIs can therefore serve as probes into the thermodynamic landscape of the early solar protoplanetary disk. Here we report on a refractory grain identified in a CAI of the Leoville CV3 chondrite. This work is part of an ongoing effort to gain insight into the thermochemistry of the early solar system through systematic analyses of the structure and chemistry of various components in CAIs [10-13]. Sample and Analytical Techniques: A fluffy type A CAI (Fig. 1A) was identified in a section of the Leoville, CV3 chondrite (Center for Meteorite Studies, Arizona State University collection, #821_C_3) using a JOEL-JXA 8530F electron microprobe at Arizona State University. Backscattered electron (BSE) imaging and energy-dispersive X-ray spectroscopy (EDS) were used to identify refractory metal grains in the CAI using a Thermo Fisher (formerly FEI) Helios NanoLab 660 G3 focused-ion-beam scanning-electron microscope (FIBSEM) located at the Kuiper Materials Imaging and Characterization Facility (KMICF) at the Lunar and Planetary Laboratory, University of Arizona. The FIB is equipped with an EDAX EDS system. We selected one of the larger (micron-sized) refractory metal grains, designated as ‘Spud’ (Fig. 1B) for further analysis. ‘Spud’ was extracted and thinned to electron transparency (<100 nm) using the FIB-SEM located in KMICF, following methods described by [14- 15]. The FIB section was analyzed using a 200 keV Hitachi HF5000 scanning transmission electron microscope (S/TEM) located at KMICF. The HF5000 is equipped with cold-field emission gun, 3rd-order spherical aberration corrector for STEM imaging, and an Oxford Instruments X-Max N 100 TLE energydispersive spectroscopy (EDS) system with dual 100 mm2 windowless silicon-drift detectors (Ω = 2.0 sr). Selected-area electron-diffraction (SAED) patterns were acquired to aid in determination of crystallinity and phase. Results: The mineralogy, texture, and morphology of the CAI are consistent with that of a fluffy type A (FTA) CAI [16]. BSE imaging at high magnifications revealed grains with high contrast, indicative of compositions rich in elements of higher atomic number relative to surrounding material. These high-Z grains have sizes that range from ∼250 nm to 4 µm. EDS analyses confirm that the bright grains are metal-rich inclusions. A minor fraction of the grains are composed of only Fe and Ni, but the majority (∼60%) of the identified inclusions also contained various refractory siderophiles including Os, Ru, Zr, Ir and Mo. EDS analysis on the FIB-SEM of Spud shows that it contains Fe, Ni, Mo and Ru. High-angle annular dark-field (HAAFD) imaging and EDS mapping in the TEM (Fig. 2) show that Spud occurs in melilite (Ca1.9Al1.99Si1.06O7). Spud contains a subhedral to anhedral morphology and is compositionally heterogenous (polyphasic, Fig. 2). Local spatial correlation occurs among Fe, Ni, and Pt, and also among Os, Ru, and Mo. SAED patterns show that the Fe-Ni-Pt, Fe-Os-Mo-Ru and Fe-Pt regions are crystalline. Discussion: CAIs can contain various types of inclusions rich in Fe, Ni and refractory siderophiles such as Os, Ru, W and Pt [1]. RMNs are micron-sized, single phase alloy grains and can contain Os, Ir, Ru and Rh [1,7,17]. NLOs are also micron-sized inclusions, but contain two phases, a refractory metal, and an oxide [6]. Fremdlinge are the largest of such inclusions (tens of microns in size) and are complex aggregates of Fe-Ni alloy, silicates, oxides, and sulfides [1,17]. While the size of Spud matches previous descriptions of RMNs and NLOs, Spud is neither a single-phase alloy like RMNs, nor does it contain one metal phase and one oxide like NLOs. Spud does not match the above described categories of refractory metal inclusions. The presence of refractory siderophiles such as Mo, Os, Ru, and Pt suggests a high-temperature origin. Thermodynamic modelling by [7] indicates condensation temperatures of 1917 K, 1693 K, 1613 K and 1415 K for Os, Mo, Ru and Pt respectively. These models also show that following the initial condensation of a refractory metal, alloying of solutes such as Fe, Ni and W, occurs in levels proportional to their partial pressures in the surrounding gas. Such alloying occurs at temperatures above the condensation temperatures of common CAI phases such as melilite (1529 K), perovskite (1441 K), spinel (197 K) and forsterite (1354 K) [2]. The polyphasic nature of Spud could be the result of such high-temperature alloying, possibly shortly after the condensation of Mo and Ru at 1693 K and 1613 K respectively. That Spud occurs as an inclusion is consistent with it having formed prior to and at temperature above that of its host melilite in this FTA CAI, which is qualitatively consistent with such prior thermodynamic modeling. Further, the polyphasic nature of Spud is similar to refractory grains from a FTA CAI in the Northwest Africa (NWA) 8323, CV3 chondrite [11-13]. These data suggest that such refractory metal grains could have been widespread in the inner and early solar protoplanetary disk and represent some of the earliest formed solids to have condensed. Acknowledgments: Research and instrumentation supported by NASA grants #NNX12AL47G, #NNX15AJ22G and #80NSSC19K0509, and NSF grants #1531243 and #0619599. Fig 2. STEM data on ‘Spud’. HAADF Image (Top) False-color EDS Maps (Bottom) References: [1] MacPherson G. J. (2014) T. of Geochem. Vol I: Met. And Cosmochem. Processes, 139-179. [2] Lodders K. (2003) ApJ, 591, 1220-1247. [3] Ebel D. S. (2006) Met. & the Early S. Sys. II., 253- 277. [4] Amelin Y. (2002) Science, 297, 1678-1683. [5] Connelly J.N. et.al. (2012) Science, 338, 651-655. [6] Schwander D. et al. (2015) GCA, 18, 70-87. [7] Palme H. and Wlotzka F. (1976) EPSL, 33, 45-60. [8] Berg T. et al. (2009) ApJ, 702, 172-176. [9] Liffman K. et al. (2021) Icarus, 221, 89-105. [10] Zega T.J. et al. (2021) PSJ, 2, 115. [11] Ramprasad T. et al. (2020) LPSC LI, Abstract #2472. [12] Ramprasad T. et al. (2021) Microscopy & Microanalysis, S1, 2792-2794. [13] Ramprasad T. et al. (2021) 84th MetSoc, Abstract #6123. [14] Zega T.J. et al. (2007) MAPS, 42, 1373-1386. [15] Ramprasad T. et al. (2022) MAPS, in revision. [16] Grossman L. (1975), GCA, 39, 433-454. [17] El Goresy A. et al. (1978) LPSC IX, Abstract#1100

T. Ramprasad↗

DOE OSTI2024

Relevance of anisotropy in the Kondo effect: Lessons from the symplectic case

A Kondo model with symplectic symmetry was recently put forward as the effective low-energy theory of a superconducting-island device coupled to multiple leads. This model, which possesses non-Fermi liquid physics and effective anyons, was argued to belong to the class of topological Kondo effects. Here, we clarify the extent of stability of its exotic fixed point using perturbative and numerical renormalization group in conjunction with bosonization and conformal field theory. In contrast to previous claims, we show that asymmetry in the coupling to the leads destabilizes the non-Fermi liquid. Other destabilizing perturbations include asymmetry in the superconducting pairing or internal energy of the individual quantum dots in the island. Nevertheless, these perturbations all generate the same relevant operators. Thus, only a small number of couplings need to be tuned individually, and these can be selected according to experimental convenience. Our results highlight a common misconception that anisotropy in single-channel Kondo couplings is always irrelevant. As demonstrated, relevant terms will emerge whenever the group generators do not span the full space of impurity operators. This calls for a more detailed inspection of models that exhibit this property, such as large-spin impurities and SO⁡( M ) Kondo models.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Bridging Hydrological Ensemble Simulation and Learning Using Deep Neural Operators

Ensemble-based simulation and learning (ESnL) has long been used in hydrology for parameter inference, but computational demands of process-based ESnL can be quite high. To address this issue, we propose a deep neural operator learning approach. Neural operators are generic machine learning algorithms that can learn functional mappings between infinite-dimensional spaces, providing a highly flexible tool for scientific machine learning. Our approach is built upon DeepONet, a specific deep neural operator, and is designed to address several common problems in hydrology, namely, model parameter estimation, prediction at ungaged locations, and uncertainty quantification. Here we demonstrate the effectiveness of our DeepONet-based workflow using an existing large model ensemble created for an eastern U.S. watershed that is instrumented with 10 streamflow gages. Results suggest DeepONet achieves high efficiency in learning an ML surrogate model from the model ensemble, with the modified Kling-Gupta Efficiency exceeding 0.9 on holdout test sets. Parameter inference, carried out using the trained DeepONet surrogate model and genetic algorithm, also yields robust results. Additionally, we formulate and train a separate DeepONet model for physics-informed, seq-to-seq streamflow forecasting, which further reduces biases in the pre-trained DeepONet surrogate model. While this study focuses primarily on a single watershed, our approach is general and may be extended to enable learning from model ensembles across multiple basins or models. Thus, this research represents a significant contribution to the application of hybrid machine learning in hydrology.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Laser melting modes in metal powder bed fusion additive manufacturing

In laser powder bed fusion additive manufacturing of metals, extreme thermal conditions create many highly dynamic physical phenomena such as vaporization and recoil, Marangoni convection, and protrusion and keyhole instability. Collectively however, the full set of phenomena is too complicated for practical applications and, in reality, the melting modes are used as a guideline for printing. With increasing local material temperature beyond the boiling point, the mode can change from conduction to keyhole. These mode designations ignore laser-matter interaction details but in many cases are adequate to determine the approximate microstructures and hence the properties of the build. To date, no consistent, common, and coherent definitions have been agreed upon because of historic limitations in melt pool and vapor depression morphology measurements. Here, we distinguish process-based definitions of different melting modes from those based on postmortem evidence. The latter are mainly derived from the transverse cross-sections of the fusion zone, whereas the former come directly from time-resolved x-ray imaging of melt pool and vapor depression morphologies. These process-based definitions are more strict and physically sound, and they offer new guidelines for laser additive manufacturing practices and create new research directions. Further, we highlight the significance of the keyhole, which substantially enhances the laser energy absorption by the melt pool. Recent studies strongly suggest that stable-keyhole laser melting enables efficient, sustainable, and robust additive manufacturing. The realization of this scenario demands the development of multiphysics models, signal translations from morphology to other feasible signals, and in-process metrology across platforms and scales.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Multiscale modeling of HBV infection integrating intra- and intercellular viral propagation to analyze extracellular viral markers

Chronic infection with hepatitis B virus (HBV) is caused by the persistence of closed circular DNA (cccDNA) in the nucleus of infected hepatocytes. Despite available therapeutic anti-HBV agents, eliminating the cccDNA remains challenging. Thus, quantifying and understanding the dynamics of cccDNA are essential for developing effective treatment strategies and new drugs. However, such study requires repeated liver biopsy to measure the intrahepatic cccDNA, which is basically not accepted because liver biopsy is potentially morbid and not common during hepatitis B treatment. We here aimed to develop a noninvasive method for quantifying cccDNA in the liver using surrogate markers in peripheral blood. We constructed a multiscale mathematical model that explicitly incorporates both intracellular and intercellular HBV infection processes. The model, based on age-structured partial differential equations, integrates experimental data from in vitro and in vivo investigations. By applying this model, we roughly predicted the amount and dynamics of intrahepatic cccDNA within a certain range using specific viral markers in serum samples, including HBV DNA, HBsAg, HBeAg, and HBcrAg. Our study represents a significant step towards advancing the understanding of chronic HBV infection. The noninvasive quantification of cccDNA using our proposed method holds promise for improving clinical analyses and treatment strategies. By comprehensively describing the interactions of all components involved in HBV infection, our multiscale mathematical model provides a valuable framework for further research and the development of targeted interventions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Techno-Economic Analysis for Shear Assisted Processing and Extrusion (ShAPE) of High Strength Aluminum Alloys

Aluminum alloy 7075 (AA7075) is a high strength aluminum alloy (HSAL), attractive for applications such as automotive, aviation, aerospace, defense, and marine applications. However, AA7075 has not yet been widely adopted due slow extrusion speed, high energy use, narrow process window, and sensitivity to incipient melting common in conventional extrusion methods. Alternative extrusion methods may overcome these limitations. New research funded by the U.S. Department of Energy (DOE) Advanced Manufacturing Office (AMO) is exploring the use of a new SPP approach called Shear Assisted Processing and Extrusion (ShAPE) for the manufacture of AA7075 extrusions. Pacific Northwest National Laboratory (PNNL) are leading the development, testing and characterization of ShAPE, which is showing that high speed ShAPE extrusions (e.g., above 12 meters/min) which is significantly faster than the 1-2 meters/min possible with conventional AA7075 extrusions. Initial findings from the economic and energy analysis indicate that AA7075 tubes created with ShAPE use less energy than tubes that are conventionally heated and extruded. The reduction in energy use is primarily a result of using direct chill cast (non-homogenized) billets, eliminating the pre-heating step, and faster extrusion speeds. The TEA model translates CAPEX and O&M costs to a manufacturing cost, and then a minimum sustainable price (MSP) per ton of extruded product for multiple facility capacities. A sample output figure of the TEA model is presented below. It presents results of the preliminary version of the TEA model.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS2004

Optical Tweezer Assembly and Calibration

An Optical Tweezer, as the name implies, is a useful tool for precision manipulation of micro and nano scale objects. Using the principle of electromagnetic radiation pressure, an optical tweezer employs a tightly focused laser beam to trap and position objects of various shapes and sizes. These devices can trap micrometer and nanometer sized objects. An exciting possibility for optical tweezers is its future potential to manipulate and assemble micro and nano sized sensors. A typical optical tweezer makes use of the following components: laser, mirrors, lenses, a high quality microscope, stage, Charge Coupled Device (CCD) camera, TV monitor and Position Sensitive Detectors (PSDs). The laser wavelength employed is typically in the visible or infrared spectrum. The laser beam is directed via mirrors and lenses into the microscope. It is then tightly focused by a high magnification, high numerical aperture microscope objective into the sample slide, which is mounted on a translating stage. The sample slide contains a sealed, small volume of fluid that the objects are suspended in. The most common objects trapped by optical tweezers are dielectric spheres. When trapped, a sphere will literally snap into and center itself in the laser beam. The PSD s are mounted in such a way to receive the backscatter after the beam has passed through the trap. PSD s used with the Differential Interference Contrast (DIC) technique provide highly precise data. Most optical tweezers employ lasers with power levels ranging from 10 to 100 miliwatts. Typical forces exerted on trapped objects are in the pico-newton range. When PSDs are employed, object movement can be resolved on a nanometer scale in a time range of milliseconds. Such accuracy, however, can only by utilized by calibrating the optical tweezer. Fortunately, an optical tweezer can be modeled accurately as a simple spring. This allows Hook s Law to be used. My goal this summer at NASA Glenn Research Center is the assembly and calibration of an optical tweezer setup in the Instrumentation and Controls Division (5520). I am utilizing a custom LabVIEW Virtual Instrument program for data collection and microscope stage control. Helping me in my assignment are the following people: Mentor Susan Wrbanek (5520), Dr. Baha Jassemnejad (UCO) and Technicians Ken Weiland (7650) and James Williams (7650). Without their help, my task would not be possible.

Collins, Timothy M.↗

NASA NTRS2006

Identifying Basic Factors for Communal Prosperity - Space Technologies are Bridging this Gap

There are many aspects, which are important for maintaining environmentally clean and safe conditions for a healthy and economically self-sufficient community. This problem was somewhat of a lesser concern in earlier days because many communities were small, isolated and solely dependent upon their owners or landlords. Due to an astronomical growth in human population within the last century, extensive use of combustion technologies, and changing environmental conditions has resulted in scarcity of natural resources. In reality, the societal sustainability issues are becoming much more acute and complex. Therefore, the researchers and social scientists are joining forces to address these topics and find solutions to many contentious areas such as public health and diseases, water resources, agriculture production, survivability during and after the natural disasters, energy needs and many others. Forthrightly speaking, there is no canned solution or a methodology to go about solving these issues since the magnitude and complexity of these issues are multi-dimensional and are further inter-locked with other areas. A common sense tells us that we need data, resources and technologies to begin addressing these problems. This is where space observations have provided us with tremendous information and opportunities, which are of great assets to the science, economist, and social scientists. This paper specifically addresses what are critical areas for a successful societal sustainability and growth; and how can we take advantage of multiple sensors and models already in existence. Increasing our knowledge of the home planet, via amplified set of observations, is certainly a right step in a right direction. Furthermore, this is a pre-requisite in understanding multiple hazard phenomena's. This paper further examines various space sensors and observing architectures that can be useful specifically in addressing some of these complex issues. The ultimate goal is to serve the society by providing such valuable information so the decision makers can take full advantage in making timely societal decisions.

Habib, Shahid↗

NASA NTRS2013

The Digital Astronaut Project Computational Bone Remodeling Model (Beta Version) Bone Summit Summary Report

Under the conditions of microgravity, astronauts lose bone mass at a rate of 1% to 2% a month, particularly in the lower extremities such as the proximal femur [1-3]. The most commonly used countermeasure against bone loss in microgravity has been prescribed exercise [4]. However, data has shown that existing exercise countermeasures are not as effective as desired for preventing bone loss in long duration, 4 to 6 months, spaceflight [1,3,5,6]. This spaceflight related bone loss may cause early onset of osteoporosis to place the astronauts at greater risk of fracture later in their lives. Consequently, NASA seeks to have improved understanding of the mechanisms of bone demineralization in microgravity in order to appropriately quantify this risk, and to establish appropriate countermeasures [7]. In this light, NASA's Digital Astronaut Project (DAP) is working with the NASA Bone Discipline Lead to implement well-validated computational models to help predict and assess bone loss during spaceflight, and enhance exercise countermeasure development. More specifically, computational modeling is proposed as a way to augment bone research and exercise countermeasure development to target weight-bearing skeletal sites that are most susceptible to bone loss in microgravity, and thus at higher risk for fracture. Given that hip fractures can be debilitating, the initial model development focused on the femoral neck. Future efforts will focus on including other key load bearing bone sites such as the greater trochanter, lower lumbar, proximal femur and calcaneus. The DAP has currently established an initial model (Beta Version) of bone loss due to skeletal unloading in femoral neck region. The model calculates changes in mineralized volume fraction of bone in this segment and relates it to changes in bone mineral density (vBMD) measured by Quantitative Computed Tomography (QCT). The model is governed by equations describing changes in bone volume fraction (BVF), and rates of changes in bone cell populations that remove and replace bone in packets within the bone region. The DAP bone model is unique in several respects. In particular in takes former models of volume fraction changes one step higher in fidelity and separates BVF into separate equations for mineralized and osteoid volume fractions governed by a mineralization rate. This more closely follows the physiology of the remodeling unit cycles where bone is first resorbed and then followed by the action of osteoblasts to lay down collagen matrix which eventually becomes mineralized. In another respect, the modules allow the functional description of the time rate of change of other parameters and variables in the model during a computational simulation. More detailed description of the model, preliminary validation results, current limitation and caveats, and planned advancements are provided in sections 2 through 5. The DAP bone model is being developed primarily as a research tool, and not as a clinical tool like QCT. Even if it transitions to a clinical tool, it is not intended to replace QCT or any other clinical tool. Moreover, the DAP bone model does not predict bone fracture. Its purpose is to provide valuable additional data via "forward prediction" simulations for during and after spaceflight missions to gain insight on, (1) mechanisms of bone demineralization in microgravity, and (2) the volumetric changes at the various bone sites in response to in-flight and post-flight exercise countermeasures. This data can then be used as input to the Keyak [8] (or equivalent) FE analysis method to gain insight on how bone strength may change during and after flight. This information can also be useful to help optimize exercise countermeasure protocols to minimize changes in bone strength during flight, and improve regain of bone strength post-flight. To achieve this goal, the bone model will be integrated with DAP's exercise countermeasure models to simulate the effect of exercise prescriptions on preserving bone. More specifically, the model will accept loading history due to muscle and joint force on bone and produce quantified remodeling within the bone region under influence of the applied stress. Furthermore, because they tend to respond differently, the bone remodeling model includes both trabecular bone and cortical bone.

Pennline, James↗

NASA NTRSDate not supplied

Application of ML/AI for Identifying Earth Science Datasets in Research Publications

NASA Data Active Archive Centers, or DAACs, ingest, store and distribute data acquired from satellites, ground systems as well as modelling data. These data are organized by the datasets, each presenting collection of files usually associated with the certain mission, instrument, processing level, parameter(s), algorithm and/or model. The number of datasets offered by a single DAAC to the public varies. GES DISC, for example, currently offers for public use approximately ~1,300 datasets. While each publicly offered dataset comes with supporting documentation, it is challenging for novice and even experienced scientists to navigate among the datasets that offer similar parameters to find the datasets for their particular research application. Supplying dataset documentation with the scientific paper citations that refer to that dataset provides means for the dataset users to educate themselves with the application research that dataset is being used in. Collecting citations of the papers that use the datasets for their research yield valuable insights into application areas of those datasets, information about usage of the dataset groups for specific applications and those application topics. It also gives insights into the “deep metrics” of the dataset usage, as opposed to the common metrics of the dataset usage such as number of users who downloaded the dataset files and volumes of downloaded data. Association of a certain scientific paper with the dataset(s) presents a challenge because most of the paper authors do not properly cite the datasets, datasets usually have cryptic names and Digital Object Identifiers (DOIs) that are used for dataset identification were assigned to the datasets only few years ago. Simple Google or online library search do not provide even meaningful fraction of the results when performed by the dataset name or DOI, however they provide too many results when the search is done by more broader terms such as mission and instrument names. Attempts to create an AI system capable to identify dataset in the scientific papers have already been made using neural networks classifiers on the basis of the dataset mission, instrument and variable name. This method was applied to NASA SEDAC, which has 41 datasets in total. In GES DISC there can be as many as ~100 datasets per mission/instrument with some of the datasets consisting of multiple variables so there is a need for more differentiating parameters for dataset identification in the paper. The approach we are currently investigating is creating AI classifiers that are based on multiple dataset features, or keywords, extracted from the NASA Earthdata Common Dataset Repository (CMR). The features are weighted based on how precisely they can identify a dataset. The classifier uses preprocessed paper text as input and searches for the CMR datasets whose feature sets are the closest to the feature sets contained in the paper. The challenges of dataset identification include variety of ways the paper authors describe the datasets in their papers and incomplete tagging of the CMR dataset description (DIFs).

Irina Gerasimov↗

NASA NTRS2000

Three-Dimensional Electron Optics Model Developed for Traveling-Wave Tubes

A three-dimensional traveling-wave tube (TWT) electron beam optics model including periodic permanent magnet (PPM) focusing has been developed at the NASA Glenn Research Center at Lewis Field. This accurate model allows a TWT designer to develop a focusing structure while reducing the expensive and time-consuming task of building the TWT and hot-testing it (with the electron beam). In addition, the model allows, for the first time, an investigation of the effect on TWT operation of the important azimuthally asymmetric features of the focusing stack. The TWT is a vacuum device that amplifies signals by transferring energy from an electron beam to a radiofrequency (RF) signal. A critically important component is the focusing structure, which keeps the electron beam from diverging and intercepting the RF slow wave circuit. Such an interception can result in excessive circuit heating and decreased efficiency, whereas excessive growth in the beam diameter can lead to backward wave oscillations and premature saturation, indicating a serious reduction in tube performance. The most commonly used focusing structure is the PPM stack, which consists of a sequence of cylindrical iron pole pieces and opposite-polarity magnets. Typically, two-dimensional electron optics codes are used in the design of magnetic focusing devices. In general, these codes track the beam from the gun downstream by solving equations of motion for the electron beam in static-electric and magnetic fields in an azimuthally symmetric structure. Because these two-dimensional codes cannot adequately simulate a number of important effects, the simulation code MAFIA (solution of Maxwell's equations by the Finite-Integration-Algorithm) was used at Glenn to develop a three-dimensional electron optics model. First, a PPM stack was modeled in three dimensions. Then, the fields obtained using the magnetostatic solver were loaded into a particle-in-cell solver where the fully three-dimensional behavior of the beam was simulated in the magnetic focusing field. For the first time, the effects of azimuthally asymmetric designs and critical azimuthally asymmetric characteristics of the focusing stack (such as shunts, C-magnets, or magnet misalignment) on electron beam behavior have been investigated. A cutaway portion of a simulated electron beam focused by a PPM stack is illustrated.

Kory, Carol L.↗

NASA NTRS2009

Medical Devices Assess, Treat Balance Disorders

You may have heard the phrase as difficult as walking and chewing gum as a joking way of referring to something that is not difficult at all. Just walking, however, is not all that simple physiologically speaking. Even standing upright is an undertaking requiring the complex cooperation of multiple motor and sensory systems including vision, the inner ear, somatosensation (sensation from the skin), and proprioception (the sense of the body s parts in relation to each other). The compromised performance of any of these elements can lead to a balance disorder, which in some form affects nearly half of Americans at least once in their lifetimes, from the elderly, to those with neurological or vestibular (inner ear) dysfunction, to athletes with musculoskeletal injuries, to astronauts returning from space. Readjusting to Earth s gravity has a significant impact on an astronaut s ability to balance, a result of the brain switching to a different "model" for interpreting sensory input in normal gravity versus weightlessness. While acclimating, astronauts can experience headaches, motion sickness, and problems with perception. To help ease the transition and study the effects of weightlessness on the body, NASA has conducted many investigations into post-flight balance control, realizing this research can help treat patients with balance disorders on Earth as well. In the 1960s, the NASA-sponsored Man Vehicle Laboratory at the Massachusetts Institute of Technology (MIT) studied the effects of prolonged space flight on astronauts. The lab s work intrigued MIT doctoral candidate Lewis Nashner, who began conducting NASA-funded research on human movement and balance under the supervision of Dr. Larry Young in the MIT Department of Aeronautics and Astronautics. In 1982, Nashner s work resulted in a noninvasive clinical technique for assessing the cooperative systems that allow the body to balance, commonly referred to as computerized dynamic posturography (CDP). CDP employs a series of dynamic protocols to isolate and assess balance function deficiencies. The technology was based on Nashner s novel, engineering-inspired concept of balance as an adaptable collaboration between multiple sensory and motor systems. CDP proved useful not only for examining astronauts, but for anyone suffering from balance problems. Today, CDP is the standard medical tool for objectively evaluating balance control.

Source record↗

NASA NTRSDate not supplied

Investigations of an Aeroelastic Optimization Benchmark Problem with MPhys and FUN3D

High-fidelity aeroelastic optimization capabilities are becoming more common in recent years. In this field, researchers typically present results on the design problems of greatest interest to them. The lack of consistency with respect to baseline configurations, design variables, objectives and constraints, etc., makes it difficult to compare approaches and creates an obstacle for the community to work together to advance the state of the art. The High-Fidelity Aeroelastic Optimization Benchmark Working Group has been established to create and study a series of benchmark aeroelastic optimization problems that the community can utilize to compare methods on the same optimization problem. This paper presents optimization results from NASA Langley Research Center for the first benchmark case of this series with analysis based on MPhys, a multiphysics library for OpenMDAO, and FUN3D, an unstructured computational fluid dynamics suite of tools. For the optimization case presented, it is demonstrated that a progression of increasing aerodynamic model fidelity reduces the wall time required to complete the optimization.

Aeroelasticity↗

NASA NTRSDate not supplied

Investigations of an Aeroelastic Optimization Benchmark Problem with MPhys and FUN3D

CFD↗

DOE OSTI2023

Circularity in polymers: addressing performance and sustainability challenges using dynamic covalent chemistries

The circularity of current and future polymeric materials is a major focus of fundamental and applied research, as undesirable end-of-life outcomes and waste accumulation are global problems that impact our society. The recycling or repurposing of thermoplastics and thermosets is an attractive solution to these issues, yet both options are encumbered by poor property retention upon reuse, along with heterogeneities in common waste streams that limit property optimization. Dynamic covalent chemistry, when applied to polymeric materials, enables the targeted design of reversible bonds that can be tailored to specific reprocessing conditions to help address conventional recycling challenges. In this review, we highlight the key features of several dynamic covalent chemistries that can promote closed-loop recyclability and we discuss recent synthetic progress towards incorporating these chemistries into new polymers and existing commodity plastics. Next, we outline how dynamic covalent bonds and polymer network structure influence thermomechanical properties related to application and recyclability, with a focus on predictive physical models that describe network rearrangement. Finally, we examine the potential economic and environmental impacts of dynamic covalent polymeric materials in closed-loop processing using elements derived from techno-economic analysis and life-cycle assessment, including minimum selling prices and greenhouse gas emissions. Throughout each section, we discuss interdisciplinary obstacles that hinder the widespread adoption of dynamic polymers and present opportunities and new directions toward the realization of circularity in polymeric materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2000

Ensemble Diffraction Measurements of Spray Combustion in a Novel Vitiated Coflow Turbulent Jet Flame Burner

An experimental investigation is presented of a novel vitiated coflow spray flame burner. The vitiated coflow emulates the recirculation region of most combustors, such as gas turbines or furnaces; additionally, since the vitiated gases are coflowing, the burner allows exploration of the chemistry of recirculation without the corresponding fluid mechanics of recirculation. As such, this burner allows for chemical kinetic model development without obscurations caused by fluid mechanics. The burner consists of a central fuel jet (droplet or gaseous) surrounded by the oxygen rich combustion products of a lean premixed flame that is stabilized on a perforated, brass plate. The design presented allows for the reacting coflow to span a large range of temperatures and oxygen concentrations. Several experiments measuring the relationships between mixture stoichiometry and flame temperature are used to map out the operating ranges of the coflow burner. These include temperatures as low 300 C to stoichiometric and oxygen concentrations from 18 percent to zero. This is achieved by stabilizing hydrogen-air premixed flames on a perforated plate. Furthermore, all of the CO2 generated is from the jet combustion. Thus, a probe sample of NO(sub X) and CO2 yields uniquely an emission index, as is commonly done in gas turbine engine exhaust research. The ability to adjust the oxygen content of the coflow allows us to steadily increase the coflow temperature surrounding the jet. At some temperature, the jet ignites far downstream from the injector tube. Further increases in the coflow temperature results in autoignition occurring closer to the nozzle. Examples are given of methane jetting into a coflow that is lean, stoichiometric, and even rich. Furthermore, an air jet with a rich coflow produced a normal looking flame that is actually 'inverted' (air on the inside, surrounded by fuel). In the special case of spray injection, we demonstrate the efficacy of this novel burner with a methanol spray in a vitiated coflow. As a proof of concept, an ensemble light diffraction (ELD) optical instrument was used to conduct preliminary measurements of droplet size distribution and liquid volume fraction.

Cabra, R.↗

DOE OSTI2021

Guided Resilience Self Assessment Application

Reliable electricity access is vital for everything from hospitals to national security. When grid disturbances occur, it is crucial to minimize the amount of time it takes to recover. Grid resiliency considers both the preparation for and recovery from high-impact low-frequency disturbances (HILF) such as weather events and cyber attacks. The Department of Energy (DOE) Wind Energy Technologies Office (WETO) funds the multi-laboratory Microgrids, Infrastructure Resilience, and Advanced Control Launchpad (MIRACL) project to investigate technologies to support and grow distributed wind. Researchers at Idaho National Laboratory (INL) contribute to resilience and cybersecurity efforts for the project, and have produced a resilience framework to evaluate system resilience based on individual system specifications. In order to make this framework easy for anyone to apply, I have coded a web application that allows users to input their power system qualities, goals, and perceived risks and then receive suggestions on how to improve their grid resiliency. The web application follows the seven steps in the planning stage of the framework process, allowing the user to input information about their grid and select from common goals, metrics, and hazards, as well as add their own. The application currently provides information about how to complete each step, requiring minimal prior knowledge of the framework. Future work for this application will include allowing the user to submit line drawings of their system and incorporate modeling tools so that the hazard simulations of applying the framework is completed for the user.

97 MATHEMATICS AND COMPUTING↗