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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 487 records · Page 27

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NASA NTRS2018

Solid State Air Purification System

Life support systems in spacecraft are designed to provide a safe, habitable environment for the astronauts, and one of the most significant challenges is managing acceptable air quality. Carbon dioxide (CO2) is respired normally by humans at concentrations that are toxic if inhaled directly, and as a result cabin air must be tightly managed. The Carbon Dioxide Removal Assembly (CDRA) currently on board the ISS is the best functioning technology for manned space cabins, but has two significant drawbacks:1. The CDRA requires that air be dried prior to CO2 capture, and this costs energy _ in fact, the system spends 4X more energy drying the air than in actually capturing and releasing carbon dioxide. 2. The CDRA works in batch mode, while downstream CO2 processing systems require a continuous stream of CO2. This adds unnecessary complexity, as well as a second parasitic energy loss.An ideal system would process CO2 continuously without any need for drying of the air, and without any moving parts. Such a system would require a fraction of the size and weight of the CDRA while dropping the cost of CO2 capture by 5X or more. Such a technology would be enabling for future long term manned flight missions, such as a mission to Mars. eSionic is developing a new electrochemical membrane technology using its patented innovations in electrolyte materials. In Phase I of this program eSionic has demonstrated continuous gas separation using only electricity to drive the separation, with no moving parts or pressure drops. In Phase II, eSionic will demonstrate long-term operation of the membranes consistent with the needs of NASA for this development program.

Life Support↗

NASA NTRSDate not supplied

Perceptual Attributes of eVTOL Noise Noticeability and Blend with Reference to the Ambient

In most prior laboratory research, studies of human response to aircraft and rotorcraft noise have emphasized annoyance ratings, usually as a function of level. Estimates of detection and noticeability have also been addressed, e.g. in surveys of community response. This presentation explores an alternative subjective criterion, based on an average threshold where trained subjects estimate the level at which a new auditory object (an eVTOL event) “blends” into the existing ambient, as an experimentally defined threshold of acceptance. Contrasting an annoyance rating, subjects rate the level at which sound is no more significant than any other sound source in ambient, with a prescribed attitude focusing on the acceptance of an inevitable new transportation source with positive attributes for the community. The approach utilizes manipulations of ambient type as an experimental variable, using spatially veridical recordings in the laboratory. In one example, the method of limits can be used for determining blend as a function of eVTOL level; other manipulations include the spatial trajectory of the eVTOL relative to the listener, and/or manipulations of its tonal spectra. It is likely that a “blend” threshold lies somewhere between a detection and annoyance threshold as a function of level.

urban air mobility↗

NASA NTRSDate not supplied

Investigation of Liquid Fuel Injection Processes in a Rotating Detonation Combustor using Megahertz Planar Laser-Induced Fluorescence Imaging

Direct imaging of liquid fuel injection is performed within an optically accessible rotating detonation combustor (RDC) using planar laser-induced fluorescence (PLIF) to spatio-temporally resolve the highly dynamic spray characteristics at rates up to 1 MHz. The RDC is operated on air and hydrogen to sustain a stable, cyclically propagating detonation wave with cycle periods of up to ∼250 μs. One of the hydrogen fuel injection sites is replaced with a liquid jet to introduce a diesel spray as a fuel surrogate to enable tracer-free fluorescence excitation using the 355 nm third-harmonic output of a burst-mode Nd:YAG laser. The time-resolved PLIF measurements reveal the evolution of the highly unsteady spray, including the dwell period after the arrival of the detonation wave, the jet recovery, breakup and entrainment into the supersonic crossflow of air, propagation into the detonation chamber, and interaction with the detonation wave. Following passage of the detonation wave, the spray characteristics reveal significant changes in the momentum flux ratio between the liquid and air streams, altering the jet trajectory and temporarily halting fuel delivery to the detonation channel. This temporary cessation of fuel spray injection into the combustor is quantified, along with the fill rate as a function of time. As the injection system recovers, the fuel spray eventually returns to a quasi-steady position prior to the arrival of the detonation wave, allowing qualitative comparisons with theoretical jet trajectories for a range of air mass-flux conditions. These data, enabled by ultra-high-speed PLIF imaging, represent some of the first detailed measurements for characterizing and quantifying the interactions of liquid jets and detonations in an operating RDC.

Propulsion↗

NASA NTRSDate not supplied

Investigation of Liquid Fuel Refill Dynamics in a Rotating Detonation Combustor using Megahertz Planar Laser-Induced Fluorescence

Propulsion↗

NASA NTRSDate not supplied

Cryogenic Modules for Synergistic O2 Generation and CO2 Retention in Closed-Circuit Escape Respirators

Since 2018, NASA and the National Institute for Occupational Safety and Health (NIOSH) have been developing a liquid oxygen storage module (LOXSM) based on the NASA patent-pending Cryogenic Flux Capacitor (CFC) technology. LOXSM’s could potentially replace the gaseous or chemical-based oxygen supply in current closed-circuit escape respirators (CCER), with reducing CCER size being a primary goal. By virtue of the CFC functionality, cryogenic oxygen stored within the LOXSM is released in response to heat input, ideally from the breathing loop. Prior efforts focused on the oxygen storage potential of silica aerogel materials that the CFC utilizes, and were previously reported. Current work explored the LOXSM’s potential to remove and retain CO 2 produced by the CCER user, in conjunction with oxygen generation, creating a synergy that may be exploited to reduce or eliminate the chemical CO 2 absorber used in current CCERs. A test program for determining CO 2 retention is presented, as well as the evolution of LOXSM prototypes. Testing showed that it is possible to completely remove CO 2 out of an effluent stream at the flowrate required for the capacity of the CCER for an appreciable time, and that the LOXSM prototype design progression had a positive effect on that duration.

A.M. Swanger↗

DOE OSTI2023

A small-box approach to the local crystal structure of Y 3 NbO 7

The local crystal structure of Y 3 NbO 7 was probed using neutron total scattering. Five different structural models were fit to the experimental pair distribution function of this material up to 15 Å. Fits of defect fluorite (Fm$\overline{3}$m), pyrochlore (Fd$\overline{3}$m), and orthorhombic C weberite models (C222 1 ) were attempted based on prior structural investigations of Y 3 NbO 7 and related fluorite-based materials. Orthorhombic P weberite (P222 1 ) and monoclinic weberite models (P112 1 ) were derived via symmetry reduction of the orthorhombic C weberite structure. All models except monoclinic weberite failed to reproduce the experimental pair distribution function. Misfits were clearly visible for peaks arising from atom pairs within the first coordination shell (defect fluorite and pyrochlore) and beyond (orthorhombic C and P weberite). By contrast, monoclinic weberite (γ ≈ 91.8°) provided an excellent fit, with no major misfits observed. This unit cell features distorted YO 8 dodecahedra, YO 7 monocapped octahedra, and NbO 6 octahedra as building blocks. Comparison between the topologies of the cationic and anionic substructures in monoclinic weberite and its parent orthorhombic C structure revealed displacements of the metal atoms along the [100] direction and a less compact spatial distribution of oxygen atoms along the a axis. In conclusion, the monoclinic weberite model presented herein may serve as a starting point to revisit structural modeling of fluorite-based materials with challenging local structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2017

Wheels-Off Time Uncertainty Impact on Benefits of Early Call for Release Scheduling

Arrival traffic scenarios with 808 flights from 173 airports to Houston George Bush International airport are simulated to determine if Call For Release flights can receive a benefit in terms of less delay over other flights by scheduling prior to gate pushback (look-ahead in time) as opposed to at gate pushback. Call for Release flights are departures that require approval from Air Route Traffic Control Center prior to release. Realism is brought to the study by including gate departure delay and taxi-out delay uncertainties for the 77 major U. S. airports. Gate departure delay uncertainty is assumed to increase as a function of look-ahead time. Results show that Call For Release flights from an airport within the freeze horizon (a region surrounding the arrival airport) can get an advantage over other flights to a capacity constrained airport by scheduling prior to gate pushback, provided the wheels-off time uncertainty with respect to schedule is controlled to a small value, such as within a three-minute window. Another finding of the study is that system delay, measured as the sum of arrival delays, is smaller when flights are scheduled in the order of arrival compared to in the order of departure. Because flights from airports within the freeze horizon are scheduled in the order of departure, an increase in the number of internal airports with a larger freeze horizon increases system delay. Delay in the given scenario was found to increase by 126% (from 13.8 hours to 31.2 hours) as freeze horizon was increased from 30-minutes to 2-hours in the baseline scenario.

wheels-off time uncertainty↗

NASA NTRS2000

Does Warming a Lysozyme Solution Cook Ones Data?

Chicken egg white lysozyme has a well characterized thermally driven phase transition. Between pH 4.0 and 5.2, the transition temperature, as defined by the point where the tetragonal and orthorhombic solubility are equal, is a function of the pH, salt (precipitant) type and concentration, and most likely of the buffer concentration as well. This phase transition can be carried out with protein solution alone, prior to the initiation of the crystallization process. We have now measured the kinetics of this process and investigated its reversibility. An aliquot of a stock protein solution is held at a given temperature, and at periodic intervals used to set up batch crystallization experiments. The batch solutions were incubated at 20 C until macroscopic crystals were obtained, at which point the number of crystals in each well were counted. The transition effects increased with temperature, slowly falling off at 30 C with a half time (time to approx. 1/2 the t = 0 number of crystals) of approx. 5 hours, and an estimated half time of approx. 0.5 hours at 43 C. Further, the process was not reversible by simple cooling. After holding a lysozyme solution at 37 C (prior to addition of precipitant) for 16 hours, then cooling and holding it at 4 C, no return to the pre-warmed nucleation kinetics are observed after at least 4 weeks. Thus every thermal excursion above the phase transition point results in a further decrease in the nucleation rate of that solution, the extent being a function of the time and temperature. Orthorhombic lysozyme crystals apparently do not undergo the flow-induced growth cessation of tetragonal lysozyme crystals. We have previously shown that putting the protein in the orthorhombic form does not affect the averaged face growth kinetics, only nucleation, for tetragonal crystals. We may be able to use this differential behavior to elucidate how flow affects tile lysozyme crystal growth process.

Pusey, Marc↗

DOE OSTI2023

Convex Q-Learning in Continuous Time with Application to Dispatch of Distributed Energy Resources

Convex Q-learning is a recent approach to reinforcement learning, motivated by the possibility of a firmer theory for convergence, and the possibility of making use of greater a priori knowledge regarding policy or value function structure. This paper explores algorithm design in the continuous time domain, with a finite-horizon optimal control objective. The main contributions are (i) The new Q-ODE: a model-free characterization of the Hamilton-Jacobi-Bellman equation. (ii) A formulation of Convex Q-learning that avoids approximations appearing in prior work. The Bellman error used in the algorithm is defined by filtered measurements, which is necessary in the presence of measurement noise. (iii) Convex Q-learning with linear function approximation is a convex program. It is shown that the constraint region is bounded, subject to an exploration condition on the training input. (iv) The theory is illustrated in application to resource allocation for distributed energy resources, for which the theory is ideally suited.

Lu, Fan↗

DOE OSTI2021

Operando Elucidation on the Working State of Immobilized Fluorinated Iron Porphyrin for Selective Aqueous Electroreduction of CO 2 to CO

Iron porphyrin-based molecular catalysts can electrocatalyze CO 2 reduction to CO at nearly 100% selectivity in water. Nevertheless, the associated active sites and reaction mechanisms remain debatable, impeding the establishment of design guidelines for effective catalysts. This study reports coupling in operando experiments and theoretical calculations for immobilized 5,10,15,20-tetrakis(pentafluorophenyl) porphyrin Fe(III) chloride (FeF 20 TPP) for electrocatalytic CO 2 reduction in an aqueous phase. In operando UV–vis and X-ray absorption near-edge structure spectra indicated the persisting presence of Fe(II) species during the cathodic reaction, acting as catalytic sites that accommodate CO as Fe(II)–CO adducts. Consistently, the density functional calculations pointed out that the ligand-reduced state with oxidized Fe, namely, [Fe(II)F 20 (TPP • )] - , prevails in the catalytic cycle prior to the rate-controlling step. This work provides the conclusive representation related to the working states of Fe-based molecular catalysts under reaction conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Geometric prior of multi-resolution yielding manifolds and the local closest point projection for nearly non-smooth plasticity

Elastoplasticity models often introduce a scalar-valued yield function to implicitly represent the boundary between elastic and plastic material states. Here this paper introduces a new alternative where the yield envelope is represented by a manifold of which the topology and the geometry are learned from a set of data points in a parametric space (e.g. principal stress space, π-plane). Here, deep geometric learning enables us to reconstruct a highly complex yield envelope by breaking it down into multiple coordinate charts. The global atlas that consists of these coordinate charts in return allows us to represent the yield surface via multiple overlapping patches, each with a specific local parametrization. This setup provides several advantages over the classical implicit function representation approach. For instance, the availability of coordinate charts enables us to introduce an alternative stress integration algorithm where the trial stress may project directly on a local patch and hence circumvent the issues related to non-smoothness and the lack of convexity of yield surfaces. Meanwhile, the local parametric approach also enables us to predict hardening/softening locally in the parametric space, even without complete knowledge of the yield surface. Comparisons between the classical yield function approach on the non-smooth plasticity and anisotropic cam-clay plasticity model are provided to demonstrate the capacity of the models for highly precise yield surface and the feasibility of the implementation of the learned model in the local stress integration algorithm.

42 ENGINEERING↗

DOE OSTI2025

Adversarial Binaries: AI-guided Instrumentation Methods for Malware Detection Evasion

Adversarial binaries are executable files that have been altered without loss of function by an AI agent in order to deceive malware detection systems. Progress in this emergent vein of research has been constrained by the complex and rigid structure of executable files. Although prior work has demonstrated that these binaries deceive a variety of malware classification models which rely on disparate feature sets, a consensus as to the best approach has not been reached, either in terms of the optimization algorithms or the instrumentation methods. Furthermore, although inconsistencies in the data sets, target classifiers, and functionality verification methods make head-to-head comparisons difficult, here we extract lessons learned and make recommendations for future research.

malware obfuscation↗

DOE OSTI2022

Date Release Report for Large Surface Explosion Coupling Experiment (LSECE) Nevada National Security Site

The DTRA sponsored 2020-2022 Large Surface Explosion Coupling Experiment (LSECE) consists of two large ground surface chemical explosions, data collection, analysis and modeling carried out in 2020-2022. The LSECE chemical explosions were carried out at the site of prior NNSA sponsored buried chemical explosions that were part of the Source Physics Experiment (SPE) Phase II in Dry Alluvium Geology (DAG). This report described the data collected under LSECE that is being made publicly available. The prior buried explosion DAG data are described in a separate report (https://www.osti.gov/biblio/1825534) and are also publicly available. The LSECE explosions, data analysis and numerical modeling work sponsored by DTRA were intended to address three objectives: 1) Generate seismo-acoustic data to test and improve numerical models of explosion energy coupling in dry alluvium geology; 2) To improve seismo-acoustic yield estimation techniques as a function of depth and medium properties; 3) To study and improve acoustic propagation modeling under two different atmospheric conditions. The LSECE data that were collected have expanded the prior DAG buried explosion dataset to include surface chemical explosions recorded on a common set of seismo-acoustic stations. They have allowed a more detailed study of above and below surface seismo-acoustic energy coupling with applications to explosion monitoring and assessment. The two approximately 1-ton TNT equivalent yield LSECE explosions were detonated at different times of the day to explore the effects of the different atmospheric conditions. The first chemical explosion “Artemis” was conducted before dawn when temperature inversions were present. The second chemical explosion “Apollo” was conducted on a sunny afternoon when the temperature gradient was more linear. The LSECE chemical explosion data were also collected across a variety of different sensor types to allow evaluation of their effectiveness in recovering useful information. The LSECE instrumentation included fiber optic or Distributed Acoustic Sensing (DAS), a dense array or Large-N array of seismometers, borehole accelerometers, DAS and a velocity meter, airborne acoustic instruments and a variety of visual and remote sensing data.

58 GEOSCIENCES↗

DOE OSTI2025

Bayesian model mixing with multireference energy density functional

Reliably predicting nuclear properties across the entire chart of isotopes is important for applications ranging from nuclear astrophysics to superheavy science to nuclear technology. To this day, however, all the theoretical models that can scale at the level of the chart of isotopes remain semiphenomenological. Because they are fitted locally, their predictive power can vary significantly; different versions of the same theory provide different predictions. Bayesian model mixing takes advantage of such imperfect models to build a local mixture of a set of models to make improved predictions. Earlier attempts to use Bayesian model mixing for mass table calculations relied on models treated at single-reference energy density functional level, which fail to capture some of the correlations caused by configuration mixing or the restoration of broken symmetries. In this study we have applied Bayesian model mixing techniques within a multireference energy density functional (MR-EDF) framework. We considered predictions of two-particle separation energies from particle number projection or angular momentum projection with four different energy density functionals—a total of eight different MR-EDF models. We used a hierarchical Bayesian stacking framework with a Dirichlet prior distribution over weights together with an inverse log-ratio transform to enable positive correlations between different models. We found that Bayesian model mixing provides significantly improved predictions compared to the participating models. Published by the American Physical Society 2025

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

Dissection of Grass Cell Wall Lignin Formation and their Associated Dirigent Protein

This Final Report describes work underway to establish why monocot (e.g. grasses) lignins are more readily (bio)degradable than their woody gymnosperm, angiosperm, and fern counterparts. Our hypothesis is that monocot specific dirigent protein (DP) sub-families are wholly or partly involved in generating these more readily (bio)degradable lignins. Three approaches are underway: metabolomics and lignin analyses of stem and leaf tissues of the grass, Brachypodium; Crispr/Cas9 gene editing of monocot specific DP sub-families in this species, and recombinant protein expression of Brachypodium’s 44 DPs. Metabolomic and lignin analyses were completed for 6 and 8 week old Brachypodium in order to establish the molecular diversity of its largely phenolic metabolites: Crispr/Cas9 gene editing has also been done on specific DPs known to be expressed in lignifying stems, and T 2 generation plant lines are now being generated, prior to establishing the effects on lignin composition and content; in the recombinant DP work (which addresses establishing the biochemical function of the monocot specific DPs and other DPOs as needed), all 44 constructs have been generated (in collaboration with DOE JGI) and are being systematically expressed in either E. coli or yeast (Pichia sp.) for future studies. Future work will be directed towards bringing the current studies to completion, and in establishing the biochemical basis as to how these more readily (bio)degradable lignins are generated/assembled.

(bio)degradability↗

NASA NTRS1975

Hematology and immunology studies

The hematology and immunology program conducted in support of the Apollo missions was designed to acquire specific laboratory data relative to the assessment of the health status of the astronauts prior to their commitment to space flight. A second objective was to detect and identify any alterations in the normal functions of the immunohematologic systems which could be attributed to space flight exposure, and to evaluate the significance of these changes relative to man's continuing participation in space flight missions. Specific changes observed during the Gemini Program formed the basis for the major portion of the hematology-immunology test schedule. Additional measurements were included when their contribution to the overall interpretation of the flight data base became apparent.

Stephen L. Kimzey↗

NASA NTRS1992

Eccentric and concentric muscle performance following 7 days of simulated weightlessness

Changes in skeletal muscle strength occur in response to chronic disuse or insufficient functional loading. The purpose of this study was to examine changes in muscle performance of the lower extremity and torso prior to and immediately after 7 days of simulated weightlessness (horizontal bed rest). A Biodex was used to determine concentric and eccentric peak torque and angle at peak torque for the back, abdomen, quadriceps, hamstring, soleus, and tibialis anterior. A reference angle of 0 degrees was set at full extension. Data were analyzed by ANOVA.

Hayes, Judith C.↗

NASA NTRS2012

Hybrid Collaborative Learning for Classification and Clustering in Sensor Networks

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

Wagstaff, Kiri L.↗