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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Membrane Degradation in PEM Fuel Cells: Part I. Modeling Gas Crossover and the Pt Band

Understanding chemical degradation of the proton-exchange membrane in fuel cells is crucial for extending their lifetimes. Herein, various degradation reactions reported in literature are organized and analyzed, including direct radical generation and an indirect (Fenton) pathway. To understand the transport of dissolved H 2 and O 2 crossover gases as they relate to membrane degradation, an agglomerate-scale model is introduced, treating gas, ionomer, and catalyst as discrete phases. The model reveals a key phenomenon: at working potentials, dissolved gases are mostly consumed at the interface between the catalyst layer and the membrane, leaving little gas to cross the membrane. Under open-circuit conditions, dissolved gases are not consumed and can then cross the membrane. This explains high H 2 O 2 concentrations and degradation rates seen in experiments but not captured in previous models. Following mixed-potential theory, crossover gases supply the hydrogen-oxidation and oxygen-reduction reactions, which occur simultaneously on individual Pt particles comprising the Pt band in the membrane, forming reactive species (H 2 O 2 , OH·). Results show crossover gas almost entirely reacts on the Pt band, allowing little to reach the opposite electrode. Furthermore, the micro-scale geometry of the catalyst-layer/membrane interface impacts the gas crossover at working potentials, indicating that cell construction affects membrane durability.

Johnson, Evan F. [Lawrence Berkeley National Labor↗
DOE OSTI2023

Directed Energy Deposition Process Modeling, Validation, and Process-Informed Optimization

The directed energy deposition (DED) process, one of the most popular additive manufacturing techniques in use today, involves various complex physical mechanisms that are not yet well understood. In this regard, computational tools show promise for elucidating the manufacturing process and enabling nondestructive performance evaluations of manufactured parts. To better control and optimize the DED process?thereby improving the manufactured product? the present work develops and demonstrates a novel artificial intelligence (AI)-based process control and optimization technique. Specifically, a geometry-free thermo-mechanical model with adaptive subdomain construction is developed to accurately capture the material?s thermo-mechanical response under cyclical reheating and high cooling rates [1]. The model is demonstrated and validated with experimental measurements, in light of various geometries and processing parameters. Moreover, based on this thermo-mechanical model, a physics-informed reduced-order model is developed to enable quick predictions of the temperature field at every time step. Furthermore, an AI-based controller is developed that can adapt to the ever-changing system states by automatically adjusting the manufacturing process parameters. This entire work is based on the open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) [2] and its recent integration with Libtorch (the C++ frontend of PyTorch [3]). The combined development of the adaptive material deposition scheme, thermo-mechanical model, associated reduced-order model, and AI-based process controller carries great potential for improving advanced manufacturing processes.

36 MATERIALS SCIENCE↗
NASA NTRS1995

Neutron-capture Cl-36, Ca-41, Ar-36, and Sm-150 in large chondrites: Evidence for high fluences of thermalized neutrons

We have measured significant concentrations of Cl-36, Ca-41, Ar-36 from decay of Cl-36, and Sm-150 produced from the capture of thermalized neutrons in the large Chico L6 chondrite. Activities of Cl-36 and Ca-41, corrected for a high-energy spallogenic component and a terrestrial age of approximately 50 ka, give average neutron-capture production rates of 208 atoms/min/g-Cl and 1525 atoms/min/kg-Ca, which correspond to thermal neutron (n) fluxes of 6.2 n/sq cm/s and 4.3 n/sq cm/s, respectively. If sustained for the approximately 65 Ma single-stage, cosmic ray exposure age of Chico, these values correspond to thermal neutron fluences of approximately 1.3 x 10(exp 16) and 0.8 x 10(exp 16) n/sq cm for Cl-36 and Ca-41, respectively. Stepwise temperature extraction of Ar in Chico impact melt shows Ar-36/Ar-38 ratios as large as approximately 9. The correlation of high Ar-36/Ar-38 with high Cl/Ca phases in neutron-irradiated Chico indicates that the excess Ar-36 above that expected from spallation is due to decay of neutron-produced Cl-36. Excess Ar-36 in Chico requires a thermal neutron fluence of 0.9-1.7 x 10(exp 16) n/sq cm. Decreases in Sm-149/Sm-152 due to neutron-capture by Sm-149 correlate with increases in Sm-150/Sm-152 for three samples of Chico, and one of the Torino H-chondrite. The 0.08% decrease in Sm-149 shown by Chico corresponds to a neutron fluence of 1.23 x 10(exp 16) n/sq cm. This fluence derived from Sm considers capture of epithermal neutrons and effects of chemical composition on the neutron energy distribution. Excess Ar-36 identified in the Arapahoe, Bruderheim, and Torino chondrites and the Shallowater aubrite suggest exposure to neutron fluences of approximately 0.2-0.2 x 10(exp 16) n/sq cm. Depletion of Sm-149 in Torino and the LEW86010 angrite suggest neutron fluences of 0.8 x 10(exp 16) n/sq cm and 0.25 x 10(exp 16) n/sq cm, respectively. Neutron fluences of approximately 10(exp 16) n/sq cm in Chico are almost as large as those previously observed for some lunar soils. Consideration of exposure ages suggests that the neutron flux in Chico may have been greater than that in many lunar soils.

Bogard, D. D.↗
DOE OSTI2020

Megahertz-rate shock-wave distortion cancellation via phase conjugate digital in-line holography

Abstract Holography is a powerful tool for three-dimensional imaging. However, in explosive, supersonic, hypersonic, cavitating, or ionizing environments, shock-waves and density gradients impart phase distortions that obscure objects in the field-of-view. Capturing time-resolved information in these environments also requires ultra-high-speed acquisition. To reduce phase distortions and increase imaging rates, we introduce an ultra-high-speed phase conjugate digital in-line holography (PCDIH) technique. In this concept, a coherent beam passes through the shock-wave distortion, reflects off a phase conjugate mirror, and propagates back through the shock-wave, thereby minimizing imaging distortions from phase delays. By implementing the method using a pulse-burst laser setup at up to 5 million-frames-per-second, time-resolved holograms of ultra-fast events are now possible. This technique is applied for holographic imaging through laser-spark plasma-generated shock-waves and to enable three-dimensional tracking of explosively generated hypersonic fragments. Simulations further advance our understanding of physical processes and experiments demonstrate ultra-high-speed PCDIH techniques for capturing dynamics.

Science & Technology - Other Topics↗
DOE OSTI2021

A duality-based coupling of Cosserat crystal plasticity and phase field theories for modeling grain refinement

High-rate deformation processes of metals entail intense grain refinement and special attention needs to be paid to capture the evolution of microstructure. In this article, a new formulation for coupling Cosserat crystal plasticity and phase field is developed. A common approach is to penalize kinematic incompatibility between lattice orientation and displacement-based elastic rotation. However, this can lead to significant solution sensitivity to the penalty parameter, resulting in low accuracy and convergence rates. To address these issues, a duality-based formulation is developed which directly imposes the rotational kinematic compatibility. A weak inf-sup-based skew-symmetric stress projection is introduced to suppress instabilities present in the dual formulation. An additional least squares stabilization is introduced to suppress the spurious lattice rotation with a suitable parameter range derived analytically and validated numerically. The required high-order continuity is attained by the reproducing kernel approximation. It is observed that equal order displacement-rotation-phase field approximations are stable, which allows efficient employment of the same set of shape functions for all independent variables. The proposed formulation is shown to yield superior accuracy and convergence with marginal parameter sensitivity compared to the penalty-based approach and successfully captures the dominant rotational recrystallization mechanism including block dislocation structures and grain boundary migration.

42 ENGINEERING↗
DOE OSTI2021

Novel Algae Technology for CO2 Utilization

The United States, the world’s largest energy user and second largest CO2 emitter, is heavily dependent on fossil energy. In 2014, U.S. coal burning utilities emitted ~1562 million (MM) tons/year (TPY) of CO2 into the atmosphere, accounting for 76% of the total US power sector emissions1. Hence, reducing the CO2 emission footprint from coal plants is widely viewed as a key element in mitigating global warming. Despite significant interest, implementation of CO2 capture technologies has been constrained by the high capture cost which significantly increases the total cost of electricity. Not only is capturing CO2 with traditional technologies expensive, but generally the CO2 has little value and additional expense must be incurred for sequestration. This project funded by a SBIR grant from the U.S. D.O.E. to Helios-NRG in collaboration with the State University of New York at Buffalo (UB) and Membrane Technology and Research Inc. (MTR) aimed to develop a novel, algae based technology to capture CO2 from the effluent of coal-based power plants and convert it to renewable bio-fuels and higher value co-products such as animal feed and nutraceuticals with the potential to enable a substantial reduction in the net cost of carbon capture. The Phase 2 project was aimed at further demonstrating the technical feasibility of the proposed multi-stage continuous (MSC) flow CO2 capture system and the generation of high-value co-products to offset the CO2 capture cost. The project was completed and the project objectives were met and exceeded. A first-of-a-kind integrated, laboratory scale MSC process unit was fabricated and tested in a greenhouse. The tests were conducted with the preferred algae species identified in Phase I and simulated flue gas containing contaminants at levels typically present in the post flue gas desulfurization (FGD) stream, including ~12% CO2, acid gas (SOX, NOX), and a large number of heavy metals. The tests were successful and demonstrated a 25g/m2/day seasonal average algae productivity and an 80% CO2 capture efficiency. Two new algae species were identified for high-value nutraceutical production. Studies to improve growth rate and nutraceutical content of these algae species were performed and a pathway for further improvements was identified. A new dewatering technology called DeAqua was further advanced. Significant improvement in the performance index was achieved. The anti-fouling membrane was developed and fabricated into a module. The fabricated membrane module was tested with algae slurry and demonstrated improved fouling resistant properties, that can potentially reduce the cost and energy of the critical dewatering step. Test data were used to simulate operation of the overall process. The preliminary economic analysis was updated and modelled based on a 5000-acre algae farm. To the extent possible, the financial and operating assumptions used were the same as those used in the DOE’s 2022 projections for algae technology for CO2 capture and utilization. The results showed the proposed technology’s potential to significantly reduce the cost of CO2 capture compared to current options and that the high value products generated from the CO2 captured can make a step change in the cost of carbon capture. Plans to advance the technology to Phase 2B were developed and potential end-user partners were identified.

Maloney, James↗
NASA NTRSDate not supplied

Capturing Multivariate Time Series Interactions to Detect High‑Risk Instability During Approach

The reduction of aviation safety metrics below target thresholds continue to drive down the number of aviation fatalities and accidents. To meet future safety demands, sustained efforts by aviation agencies promoting safety assurance processes and systems have prompted ongoing research on identifying and mitigating in-flight risks. With the projected increase in passenger load factor and rollout of more autonomous systems into the national airspace, the need to detect high-risk events in-time or ahead-of-time is becoming increasingly crucial. New anomaly detection and precursor identification algorithms will need to scale to different airframes, levels of autonomy, and system complexity. While the pervasiveness of deep learning has resulted in the development of performant anomaly detection methods, these sophisticated models currently suffer from low end-user interpretability. Building off our previous work on identifying adverse events in multivariate flight data during descent, we propose a data-driven approach for detecting in-flight adverse events caused by the complex interplay of flight variables. Our approach utilizes ordinal patterns of important aircraft stability variables (e.g., airspeed and descent rate) to capture multivariate flight dynamics that can be used to predict the onset of unstable approaches, a high-risk adverse event that can occur during approach. Through the use of ordinal patterns, we aim to create more interpretable detection models of in-flight adverse events that can be translated to future autonomous systems without difficulty. Our analysis shows the presence of distinct ordinal pattern distributions that can be used to predict unstable approaches 1 minute ahead of time with an accuracy of 0.69 and a recall of 0.73 and 30 seconds ahead with an accuracy of 0.70 and a recall of 0.86.

Risk detection↗
NASA NTRSDate not supplied

Capturing Complex Multivariate Time Series Interactions to Detect High-Risk Adverse Events During Flight

The reduction of aviation safety metrics below target thresholds continue to drive down the number of aviation fatalities and accidents. To meet future safety demands, sustained efforts by aviation agencies promoting safety assurance processes and systems have prompted ongoing research on identifying and mitigating in-flight risks. With the projected increase in passenger load factor and rollout of more autonomous systems into the national airspace, the need to detect high-risk events in-time or ahead-of-time is becoming increasingly crucial. New anomaly detection and precursor identification algorithms will need to scale to different airframes, levels of autonomy, and system complexity. While the pervasiveness of deep learning has resulted in the development of performant anomaly detection methods, these sophisticated models currently suffer from low end-user interpretability. Building off our previous work on identifying adverse events in multivariate flight data during descent, we propose a data-driven approach for detecting in-flight adverse events caused by the complex interplay of flight variables. Our approach utilizes ordinal patterns of important aircraft stability variables (e.g., airspeed and descent rate) to capture multivariate flight dynamics that can be used to predict the onset of unstable approaches, a high-risk adverse event that can occur during approach. Through the use of ordinal patterns, we aim to create more interpretable detection models of in-flight adverse events that can be translated to future autonomous systems without difficulty. Our analysis shows the presence of distinct ordinal pattern distributions that can be used to predict unstable approaches 1 minute ahead of time with an accuracy of 0.69 and a recall of 0.73 and 30 seconds ahead with an accuracy of 0.70 and a recall of 0.86.

Risk detection↗
DOE OSTI2022

An Eulerian crystal plasticity framework for modeling large anisotropic deformations in energetic materials under shocks

Here, this paper demonstrates a novel Eulerian computational framework for modeling anisotropic elastoplastic deformations of organic crystalline energetic materials (EM) under shocks. While Eulerian formulations are advantageous for handling large deformations, constitutive laws in such formulations have been limited to isotropic elastoplastic models, which may not fully capture the shock response of crystalline EM. The present Eulerian framework for high-strain rates, large deformation material dynamics of EM incorporates anisotropic isochoric elasticity via a hypo-elastic constitutive law and visco-plastic single-crystal models. The calculations are validated against atomistic calculations and experimental data and benchmarked against Lagrangian (finite element) crystal plasticity computations for shock-propagation in a monoclinic organic crystal, octahydro-1,3,5,7-tetranitro-1,3,5,7 tetrazocine (β-HMX). The Cauchy stress components and the resolved shear stresses calculated using the present Eulerian approach are shown to be in good agreement with the Lagrangian computations for different crystal orientations. The Eulerian framework is then used for computations of shock-induced inert void collapse in β-HMX to study the effects of crystal orientations on hotspot formation under different loading intensities. The computations show that the hotspot temperature distributions and the collapse profiles are sensitive to the crystal orientations at lower impact velocities (viz., 500 m/s); when the impact velocity is increased to 1000 m/s, the collapse is predominantly hydrodynamic and the role of anisotropy is modest. The present methodology will be useful to simulate energy localization in shocked porous energetic material microstructures and other situations where large deformations of single and polycrystals govern the thermomechanical response.

42 ENGINEERING↗
NASA NTRS1995

The Polar Plasma Wave Instrument

The Plasma Wave Instrument on the Polar spacecraft is designed to provide measurements of plasma waves in the Earth's polar regions over the frequency range from 0.1 Hz to 800 kHz. Three orthogonal electric dipole antennas are used to detect electric fields, two in the spin plane and one aligned along the spacecraft spin axis. A magnetic loop antenna and a triaxial magnetic search coil antenna are used to detect magnetic fields. Signals from these antennas are processed by five receiver systems: a wideband receiver, a high-frequency waveform receiver, a low-frequency waveform receiver, two multichannel analyzers; and a pair of sweep frequency receivers. Compared to previous plasma wave instruments, the Polar plasma wave instrument has several new capabilities. These include (1) an expanded frequency range to improve coverage of both low- and high-frequency wave phenomena, (2) the ability to simultaneously capture signals from six orthogonal electric and magnetic field sensors, and (3) a digital wideband receiver with up to 8-bit resolution and sample rates as high as 249k samples s(exp -1).

Gurnett, D. A.↗
NASA NTRS2004

Exploring the limits of crop productivity: beyond the limits of tipburn in lettuce

The productivity of lettuce in a combination of high light, high temperature, and elevated CO2 has not been commonly studied because rapid growth usually causes a calcium deficiency in meristems called tipburn, which greatly reduces quality and marketability. We eliminated tipburn by blowing air directly onto the meristem, which allowed us to increase the photosynthetic photon flux (PPF) to 1000 micromoles m-2 s-1 (57.6 mol m-2 d-1); two to three times higher than normally used for lettuce. Eliminating tipburn doubled edible yield at the highest PPF level. In addition to high PPF, CO2 was elevated to 1200 micromoles m-2 mol-1, which increased the temperature optimum from 25 to 30 degrees C. The higher temperature increased leaf expansion rate, which improved radiation capture and more than doubled yield. Photosynthetic efficiency, measured as canopy quantum yield in a whole-plant gas exchange system, steadily increased up to the highest temperature of 32 degrees C in high CO2. The highest productivity was 19 g m-2 d-1 of dry biomass (380 g d-1 fresh mass) averaged over the 23 days the plants received light. Without the limitation of tipburn, the combination of high PPF, high temperature, and elevated CO2 resulted in a 4-fold increase in growth rate over productivity in conventional environments.

NASA Discipline Life Support Systems↗
DOE OSTI2022

Quantitative spatiotemporal mapping of thermal runaway propagation rates in lithium-ion cells using cross-correlated Gabor filtering

Abuse testing of lithium-ion batteries is widely performed in order to develop new safety standards and strategies. However, testing methodologies are not standardised across the research community, especially with failure mechanisms being inherently difficult to reproduce. High-speed X-ray radiography is proven to be a valuable tool to capture events occurring during cell failure, but the observations made remain largely qualitative. We have therefore developed a robust image processing toolbox that can quantify, for the first time, the rate of propagation of battery failure mechanisms revealed by high-speed X-ray radiography. Using Gabor filter, the toolbox selectively tracks the electrode structure at the onset of failure. This facilitated the estimation of the displacement of electrodes undergoing abuse via nail penetration, and also the tracking of objects, such as the nail, as it propagates through a cell. Further, by cross-correlating the Gabor signals, we have produced practical, illustrative spatiotemporal maps of the failure events. From these, we can quantify the propagation rates of electrode displacement prior to the onset of thermal runaway. The highest recorded acceleration (≈514 mm s -2 ) was when a nail penetrated a cell radially (perpendicular to the electrodes) as opposed to axially (parallel to the electrodes). The initiation of thermal runaway was also resolved in combination with electrode displacement, which occurred at a lower acceleration (≈108 mm s -2 ). Our assistive toolbox can also be used to study other types of failure mechanisms, extracting otherwise unattainable kinetic data. Ultimately, this tool can be used to not only validate existing theoretical mechanical models, but also standardise battery failure testing procedures.

25 ENERGY STORAGE↗
NASA NTRS1973

Muon capture rates on O-16 leading to bound states of N-16.

A low-energy spectrum of gamma-rays following muon capture in O-16 was obtained with a high-resolution 1 cu cm Ge(Li) detector. The graph of the spectrum shows the separation of contaminant peaks from the 120 keV N-16 line. It is pointed out that there is a large discrepancy between the capture rate obtained in the investigation and results reported by Deutsch et al. (1969).

Kane, F. R.↗
DOE OSTI2022

Simulation of dislocation evolution in microparticle impacts over a wide range of impact velocities

We report the dynamic loading environment created by high velocity microparticle impacts is very difficult to model. The extremely high strain rates, large deformations, and high temperatures affect the flow stress of the material in ways that standard flow stress models cannot capture. Plastic deformation and strain hardening in metals is controlled by the motion of dislocations. Dislocations can be nucleated, stored as forest dislocations, or be annihilated as loading progresses. A comprehensive accounting of dislocation density change is needed to accurately describe rate and temperature dependent dislocation glide and evolution across the wide rage of loading conditions present in microparticle impact problems. Therefore, we implement and apply a newly proposed flow stress model (Hunter and Preston, 2015, 2022) that is then coupled with mobile and immobile dislocation density evolution equations. This model is implemented in Los Alamos National Laboratory’s hydrodynamics code, FLAG, to model copper-on-copper microparticle impacts. This new strength model allows for accurate simulation of particle rebound and flattening across a wide range of impact velocities.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Dual function materials (Ru+Na 2 O/Al 2 O 3 ) for direct air capture of CO 2 and in situ catalytic methanation: The impact of realistic ambient conditions

Here a dual function material (DFM) comprised of 1% Ru, 10% Na 2 O/γ–Al 2 O 3 was studied for combined direct air capture (DAC) of CO 2 and catalytic methanation in a temperature swing operation. In the newly proposed operation, the DFM captures CO 2 (400 ppm) from air at ambient conditions. The material is then heated in H 2 to a temperature sufficient for catalytic conversion of the captured CO 2 to renewable natural gas. In this study, we demonstrate high CO 2 adsorption capacity and rates at ambient conditions (25 °C); the adsorbed CO 2 is then successfully catalytically methanated upon heating in H 2 . Adsorption was also carried out in humid conditions, more closely simulating ambient air. Adsorption and methane production were greatly improved with stable initial performance. The rate of adsorption is shown to be flowrate-dependent, which is critical for future reactor design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2008

Forebody and Inlet Design for the HIFiRE 2 Flight Test

A forebody and inlet have been designed for the HIFiRE 2 scramjet flight test. The test will explore the operating, performance, and stability characteristics of a simple hydrocarbon-fueled scramjet combustor as it transitions from dual-mode to scramjet-mode operation and during supersonic combustion at Mach 8+ flight conditions. Requirements for the compression system were derived from inlet starting and combustor inflow requirements as well as physical size constraints. The design process is described. A planar, fixed geometry, mixed compression concept was used to produce laterally uniform flow at the inlet entrance and a conservative amount of internal contraction with respect to inlet starting. A grid sensitivity study was performed so that important flow physics caused by three-dimensional shock boundary layer interactions could be captured with confidence. Results from low Mach number operability studies, nominal trajectory cases, and high dynamic pressure heat load cases are discussed. The forebody and inlet solutions provide information for on-going combustor calculations, mass capture across the trajectory for fuel system design, and surface heating rates for thermal/structural analysis. The design has a one freestream Mach number margin for inlet starting, exceeds the high Mach number combustor entrance pressure requirement, produces high quality flow at the inlet exit for all Mach numbers and vehicle attitudes in the design space, and fits inside the booster shroud.

Ferlemann, Paul G.↗
DOE OSTI2025

Implementation of compound refractive lenses for large field-of-view x-ray phase-contrast imaging during hypervelocity impact experiments

Synchrotron x-ray phase-contrast imaging (XPCI) offers time-resolved visualization of dynamic compression phenomena, but its intrinsically small field-of-view (FOV) limits the time that key features remain in frame. A novel approach to enlarge the FOV is achieved by positioning a two-dimensional parabolic compound refractive lens (CRL) upstream of the sample to deliberately defocus the white beam. Ray-tracing simulations and XPCI measurements show that this CRL configuration can expand the beam by ∼50% vertically and ∼15% horizontally based on the full width at half-maximum of the beam. Implementing the CRL, however, attenuates the photon flux and lowers signal-to-noise ratio (SNR). Task-based analysis using a calibration grid (30 μm dots) showed that both setups fail to consistently meet the Rose criterion (SNR ≥ 5) for features of this size in single-bunch imaging. Extrapolating the measured SNR Rose values suggests that the minimum consistently detectable feature lies closer to 30–40 μm for the standard XPCI setup and above 40 μm for CRL-XPCI. Despite this limitation, the CRL configuration nearly doubles the illuminated area, enabling simultaneous tracking of front and rear observations of boron carbide targets subjected to rod and sphere impacts at 1.0–2.6 km/s. Image tracking algorithms and photonic Doppler velocimetry were used to measure penetration and rear-surface velocity histories. Together, these measurements capture crack fronts, penetration, and material breakout, offering new benchmark data for validating high-strain-rate constitutive models of ceramic materials.

Ceramic materials↗
NASA NTRS1999

One GigaSample Per Second Data Acquisition using Available Gate Array Technology

A new National Aeronautics and Space Administration instrument forced demanding requirements upon its altimeter digitizer system. Eight-bit data would be generated at a rate of one billion samples per second. NASA had never before attempted to capture such high-speed data in the radiation, low-power, no-convective-cooling, limited-board-area environment of space. This presentation describes how the gate array technology available at the time of the design was used to implement this one gigasample per second data acquisition system

Wagner, K.W.↗