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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

A Nonlinear Viscoelastic Model for Ceramics at High Temperatures

High-temperature creep behavior of ceramics is characterized by nonlinear time-dependent responses, asymmetric behavior in tension and compression, and nucleation and coalescence of voids leading to creep rupture. Moreover, creep rupture experiments show considerable scatter or randomness in fatigue lives of nominally equal specimens. To capture the nonlinear, asymmetric time-dependent behavior, the standard linear viscoelastic solid model is modified. Nonlinearity and asymmetry are introduced in the volumetric components by using a nonlinear function similar to a hyperbolic sine function but modified to model asymmetry. The nonlinear viscoelastic model is implemented in an ABAQUS user material subroutine. To model the random formation and coalescence of voids, each element is assigned a failure strain sampled from a lognormal distribution. An element is deleted when its volumetric strain exceeds its failure strain. Element deletion has been implemented within ABAQUS. Temporal increases in strains produce a sequential loss of elements (a model for void nucleation and growth), which in turn leads to failure. Nonlinear viscoelastic model parameters are determined from uniaxial tensile and compressive creep experiments on silicon nitride. The model is then used to predict the deformation of four-point bending and ball-on-ring specimens. Simulation is used to predict statistical moments of creep rupture lives. Numerical simulation results compare well with results of experiments of four-point bending specimens. The analytical model is intended to be used to predict the creep rupture lives of ceramic parts in arbitrary stress conditions.

Powers, Lynn M.↗
DOE OSTI2023

BISON validation to in situ cladding burst test and high-burnup LOCA experiments

The process for developing and qualifying nuclear fuels for commercial nuclear application requires fundamental material development, characterization, and design; out-of-pile testing on unirradiated materials; integral fuel rod irradiations, testing, and postirradiation examinations; and transient analyses. The historical approach depends on the generation of large empirical datasets and series of integral fuel rod irradiations, and this approach ultimately takes ~20 years—or sometimes longer—to acquire data through extensive sequential testing. Thus, the qualification and eventual deployment of new fuel systems constitute a long process. However, recent technological advancements have provided researchers the opportunity to perform out-of-cell, in situ measurements to assess material performance for the duration of the experiment. One such example of this capability is the use of digital image coordination and thermal imaging to assess Zircaloy cladding performance under a simulated loss-of-coolant accident (LOCA) transient condition. In situ measurements generally provide high-fidelity strain, strain rates, and temperature surface maps. This is critical for the US nuclear industry, which is actively developing a technical basis to support extending the peak rod average burnup from 62 to ~75 GWd/tU and the deployment of accident-tolerant fuel. However, the US Nuclear Regulatory Commission (NRC) outlined in its research information letter several technical issues that the industry must address before extending burnup. One topic of specific interest is understanding the cladding balloon and rupture geometry during the LOCA heat-up phase. By leveraging these advanced in situ capabilities, this work used in situ data generated from a simulated LOCA to better understand high-temperature creep and its effect on Zircaloy balloon and rupture performance. Here, this work used the BISON fuel performance code to assess the high-temperature creep model predictions with in situ data.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Deciphering the Mechanism of Base-Triggered Conversion of Ammonia to Molecular Nitrogen and Methylamine to Cyanide

Here we report an in-depth investigation into the ammonia oxidation mechanism by the catalyst [Ru III (tpy)(dmabpy)NH 3 ] 3 + ([Ru(NH 3 )] 3 + ). Stoichiometric reactions of [Ru(NH 3 )] 3 + were carried out with exogenous noncoordinating bases to trigger a proposed redox disproportionation reaction, which was followed using variable-temperature NMR spectroscopy. An intermediate species was identified as a dinitrogen-bridged complex using 15 N NMR and Raman spectroscopy on isotopically labeled complexes. This intermediate is proposed to derive from coupling of nitridyl species formed upon sequential redox disproportion reactions. Acetonitrile displaces the dinitrogen bridge to yield free N 2 . DFT calculations support this lower-energy pathway versus that previously reported for ammonia oxidation by the parent [Ru III (tpy)(bpy)NH 3 ] 3 + complex. These experimental and computational results are consistent with the interpretation of redox disproportionation involving sequential hydrogen atom transfer reactions by an amide/aminyl intermediate, [Ru(NH 2 ) – ] + $\Leftrightarrow$ [Ru(NH 2 ) • ] + , formed upon deprotonation of the parent complex. Control experiments employing a large excess of ammonia as a base indicate this new proposed lower-energy pathway contributes to the oxidation of ammonia to dinitrogen in conditions relevant to electrocatalysis. In addition, analogous methylamine complexes, [Ru(NH 2 CH 3 )] 2 + /3 + , were prepared to further test the proposed mechanism. Treating [Ru(NH 2 CH 3 )] 3 + with a base cleanly yields two products [Ru(NH 2 CH 3 )] 2 + and [Ru(CN)] + in an ~3:1 ratio, fully consistent with the proposed cascade of hydrogen atom transfer reactions by an intermediate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Active learning path-dependent properties using a cloud-based materials acceleration platform

Solid state materials are central to many modern technologies in which a given material may be exposed to a variety of environments. The material properties often vary with the sequence of environments in an irreversible manner, resulting in a quintessential path-dependency in experimental observables. While sequential learning techniques have been effectively deployed for accelerating learning of state properties of materials, they often use a consistent environment path in all experiments. To elevate such techniques for making optimal decisions in experimental investigations of path-dependent properties, we introduce an iterated expected information gain acquisition function that optimizes over entire experimental trajectories. This approach is implemented within a cloud-based Materials Acceleration Platform architecture utilizing an event-driven stateful broker coupled with remote HELAO (Hierarchical Experimental Laboratory Automation and Orchestration) instances and an AI science manager. The platform's efficacy was demonstrated through a case study optimizing multi-step spectro-electrochemical experiments to identify optically stable potential windows in (Co–Ni–Sb)O z metal oxides. The system successfully integrated AI-driven experiment design, remote laboratory automation, and cloud-based data infrastructure, validating the platform's capability for managing complex, adaptive, path-dependent workflows in materials discovery.

Guevarra, Dan [California Institute of Technology ↗
DOE OSTI2022

A physics-constrained neural network for multiphase flows

The present study develops a physics-constrained neural network (PCNN) to predict sequential patterns and motions of multiphase flows (MPFs), which includes strong interactions among various fluid phases. To predict the order parameters, which locate individual phases in the future time, a neural network (NN) is applied to quickly infer the dynamics of the phases by encoding observations. The multiphase consistent and conservative boundedness mapping algorithm (MCBOM) is next implemented to correct the predicted order parameters. This enforces the predicted order parameters to strictly satisfy the mass conservation, the summation of the volume fractions of the phases to be unity, the consistency of reduction, and the boundedness of the order parameters. Then, the density of the fluid mixture is updated from the corrected order parameters. Finally, the velocity in the future time is predicted by another NN with the same network structure, but the conservation of momentum is included in the loss function to shrink the parameter space. The proposed PCNN for MPFs sequentially performs (NN)-(MCBOM)-(NN), which avoids nonphysical behaviors of the order parameters, accelerates the convergence, and requires fewer data to make predictions. Numerical experiments demonstrate that the proposed PCNN is capable of predicting MPFs effectively.

Mechanics↗
DOE OSTI2021

Evaluating Gaussian process metamodels and sequential designs for noisy level set estimation

Abstract We consider the problem of learning the level set for which a noisy black-box function exceeds a given threshold. To efficiently reconstruct the level set, we investigate Gaussian process (GP) metamodels. Our focus is on strongly stochastic simulators, in particular with heavy-tailed simulation noise and low signal-to-noise ratio. To guard against noise misspecification, we assess the performance of three variants: (i) GPs with Student- t observations; (ii) Student- t processes (TPs); and (iii) classification GPs modeling the sign of the response. In conjunction with these metamodels, we analyze several acquisition functions for guiding the sequential experimental designs, extending existing stepwise uncertainty reduction criteria to the stochastic contour-finding context. This also motivates our development of (approximate) updating formulas to efficiently compute such acquisition functions. Our schemes are benchmarked by using a variety of synthetic experiments in 1–6 dimensions. We also consider an application of level set estimation for determining the optimal exercise policy of Bermudan options in finance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Reaction Pathways over ZnZrO 2 -Based Catalysts and Catalytic Sorbents

Reactive capture and conversion (RCC) is a process intensification approach that integrates CO 2 capture and hydrogenation within a single unit, removing the CO 2 purification and storage steps of traditional process flow schemes. This alters the catalytic step from a traditional steady-state (SS) flow process to a transient capture and conversion cycle, which could lead to product distributions distinct from those observed in conventional SS experiments. Such differences are investigated in the combined capture and hydrogenation of carbon dioxide to methanol over a ZnZrO 2 catalyst and a ZnZrO 2 + NaNO 3 /Mg 3 AlO x catalytic sorbent (CS) using fixed-bed kinetic measurements, in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), and steady-state isotopic transient kinetic analysis-DRIFTS (SSITKA-DRIFTS). Under SS conditions, ZnZrO 2 produced methanol through sequential hydrogenation of HCOO* and CH 3 O* intermediates. On the contrary, CO was attributed primarily to CO 2 dissociation at oxygen vacancies, as supported by isotopic shifts and measured reaction orders. For the CS, isotopic switching experiments suggested that monodentate carbonate species (CO 3 2− , abbreviated as m-CO 3 2− ) act as active intermediates that can be hydrogenated to HCOO* and subsequently to CH 3 O. Under RCC conditions, in situ DRIFTS and isotopic experiments reveal that m-CO 3 2− species formed during the CO 2 capture step follow two competing routes upon H 2 exposure: (i) direct hydrogenation to methane on the sorbent domain or (ii) migration of m-CO 3 2− to the ZnZrO 2 domain, where they are hydrogenated to methanol through the HCOO pathway. Overall, RCC enables carbonate hydrogenation routes not observed under SS cofeed conditions. Thus, the reaction pathways and rates during RCC can be different from operation under conventional SS conditions, and the product distribution is determined here by competition between carbonate hydrogenation on sorbent sites and migration to ZnZrO 2 for methanol synthesis.

CCUS↗
NASA NTRS1994

TDRSS Onboard Navigation System (TONS) flight qualification experiment

The National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) is currently developing an operational Tracking and Data Relay Satellite (TDRS) System (TDRSS) Onboard Navigation System (TONS) to provide realtime, autonomous, high-accuracy navigation products to users of TDRSS. A TONS experiment was implemented on the Explorer Platform/Extreme Ultraviolet Explorer (EP/EUVE) spacecraft, launched June 7, 1992, to flight qualify the TONS operational system using TDRSS forward-link communications services. This paper provides a detailed evaluation of the flight hardware, an ultrastable oscillator (USO) and Doppler extractor (DE) card in one of the TDRSS user transponders and the ground-based prototype flight software performance, based on the 1 year of TONS experiment operation. The TONS experiment results are used to project the expected performance of the TONS 1 operational system. TONS 1 processes Doppler data derived from scheduled forward-link S-band services using a sequential estimation algorithm enhanced by a sophisticated process noise model to provide onboard orbit and frequency determination and time maintenance. TONS 1 will be the prime navigation system on the Earth Observing System (EOS)-AM1 spacecraft, currently scheduled for launch in 1998. Inflight evaluation of the USO and DE short-term and long-term stability indicates that the performance is excellent. Analysis of the TONS prototype flight software performance indicates that realtime onboard position accuracies of better than 25 meters root-mean-square are achievable with one tracking contact every one to two orbits for the EP/EUVE 525-kilometer altitude, 28.5 degree inclination orbit. The success of the TONS experiment demonstrates the flight readiness of TONS to support the EOS-AM1 mission.

Gramling, C. J.↗
DOE OSTI2022

BISON Validation to In-Situ Cladding Burst Test and High Burnup LOCA Experiments

The process to develop and qualify nuclear fuels for commercial nuclear application requires fundamental material development, characterization, and design; out-of-pile testing on unirradiated materials; integral fuel rod irradiations, testing, and post irradiation examinations (PIEs); and transient analyses. The historical approach depends on the generation of large empirical datasets and series of integral fuel rod irradiations, and this approach ultimately takes approximately 20 years—or sometimes longer—to acquire data through extensive sequential testing. Thus, the qualification and eventual deployment of new fuel systems constitute a long and drawn-out process. However, recent technological advancements have provided researchers the opportunity to perform out-of-cell, in-situ measurements to assess material performance for the duration of the experiment. One such example of this capability is the use of digital image coordination and thermal imaging to assess Zircaloy cladding performance under a simulated loss-of-coolant accident (LOCA) transient condition. In general, the in-situ measurements provide high-fidelity strain, strain rates, and temperature surface maps. This is critical for the United States nuclear industry, which is actively developing a technical basis to support extending the peak rod average burnup from 62 to ~75 GWd/tU and the deployment of accident-tolerant fuel. However, the Nuclear Regulatory Commission, through their research information letter, outlined a number of technical issues for the industry to address before extending burnup. One topic of specific interest is understanding the cladding balloon and rupture geometry during the LOCA heatup phase. Leveraging these advanced in-situ capabilities, this work intends to use insitu data generated from a simulated LOCA in the Severe Accident Test Station at Oak Ridge National Laboratory to better understand high-temperature creep and its impact on Zircaloy balloon and rupture performance. This work used the BISON fuel performance code to compare BISON’s high-temperature creep model predictions to in-situ data and identify limitations and gaps within the model. Additionally, BISON will subsequently be used to simulate relevant high-burnup LOCA tests. The results will be analyzed and compared to the available post-test data in a manner consistent with the approach outlined in the Nuclear Regulatory Commission research information letter.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

AI for Experimental Controls at Jefferson Lab

We report the AI for Experimental Controls project is developing an AI system to control and calibrate detector systems located at Jefferson Laboratory. Currently, calibrations are performed offline and require significant time and attention from experts. This work would reduce the amount of data and the amount of time spent calibrating in an offline setting. The first use case involves the Central Drift Chamber (CDC) located inside the GlueX spectrometer in Hall D. We use a combination of environmental and experimental data, such as atmospheric pressure, gas temperature, and the flux of incident particles as inputs to a sequential Neural Network (NN) to recommend a high voltage setting and the corresponding calibration constants in order to maintain consistent gain and optimal resolution throughout the experiment. Utilizing AI in this manner represents an initial shift from offline calibration towards near real time calibrations performed at Jefferson Laboratory.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Two-XUV-photon double ionization of neon

Two XUV-photon double ionization of Ne, induced by an intense few-pulse attosecond train with a ~ 4 fs envelope duration is investigated experimentally and theoretically. The experiment is performed at ELI-ALPS utilizing the recently constructed 10 Hz gas phase high-order harmonic generation SYLOS GHHG-COMPACT beamline. A total pulse energy up to ~1 {\mu}J generated in Argon in conjunction with high reflectivity optics in the XUV region, allowed the observation of the doubly charged state of Ne induced by 40 eV central XUV photon energies. The interaction of the intense attosecond pulse train with Ne is also theoretically studied via a second-order time dependent perturbation theory equations-of-motion. Further, the results of this work, combined with the feasibility of conducting XUV-pump-XUV-probe experiments, constitute a powerful tool for many potential applications. Those include attosecond pulse metrology as well as time resolved investigations of the dynamics underlying direct and sequential double ionization and their electron correlation effects.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Nuclear temperature and its dependence on the source neutron-proton asymmetry deduced using the Albergo thermometer

Albergo thermometers with double isotope, isotone and isobar yield ratio pairs with one proton or/and neutron difference are investigated. Without any extra sequential decay correction, a real temperature value of 4.9 ± 0.5 MeV is deduced from the yields of the experimentally reconstructed primary hot intermediate mass fragments (IMFs) from 64 Zn + 112 Sn collisions at 40 MeV/nucleon using the Albergo thermometer for the first time. An experimental sequential decay correction from the apparent temperatures to the real ones for twelve other reaction systems with different neutron-proton (N/Z) asymmetries in the same experiment, 70 Zn, 64 Ni on 112,124 Sn, 58,64 Ni, 197 Au, 232 Th at 40 MeV/nucleon, is performed using an empirical correction factor approach of Tsang et al. with the deduced 4.9 MeV temperature value. The dependence of nuclear temperature on the source N/Z asymmetry is further investigated using these deduced real source temperature values from the present thirteen systems. It is found that the deduced real source temperatures at the present source N/Z range show a rather weak dependence on the source N/Z asymmetry. In conclusion, by comparison between our previous results and those from other independent experiments, a consistent description for the N/Z asymmetry dependence of nuclear temperature is addressed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1979

Effects of space environment on composites: An analytical study of critical experimental parameters

A generalized methodology currently employed at JPL, was used to develop an analytical model for effects of high-energy electrons and interactions between electron and ultraviolet effects. Chemical kinetic concepts were applied in defining quantifiable parameters; the need for determining short-lived transient species and their concentration was demonstrated. The results demonstrates a systematic and cost-effective means of addressing the issues and show qualitative and quantitative, applicable relationships between space radiation and simulation parameters. An equally important result is identification of critical initial experiments necessary to further clarify the relationships. Topics discussed include facility and test design; rastered vs. diffuse continuous e-beam; valid acceleration level; simultaneous vs. sequential exposure to different types of radiation; and interruption of test continuity.

Gupta, A.↗
NASA NTRS1985

Airborne Lidar measurements of aerosols, mixed layer heights, and ozone during the 1980 PEPE/NEROS summer field experiment

A detailed summary of the NASA Ultraviolet Differential Absorption Lidar (UV DIAL) data archive obtained during the EPA Persistent Elevated Pollution Episode/Northeast Regional Oxidant Study (PEPE/NEROS) Summer Field Experiment Program (July through August 1980) is presented. The UV dial data set consists of remote measurements of mixed layer heights, aerosol backscatter cross sections, and sequential ozone profiles taken during 14 long-range flights onboard the NASA Wallops Flight Center Electra aircraft. These data are presented in graphic and tabular form, and they have been submitted to the PEPE/NEROS data archive on digital magnetic tape. The derivation of mixing heights and ozone profiles from UV Dial signals is discussed, and detailed intercomparisons with measurements obtained by in situ sensors are presented.

Browell, E. V.↗
NASA NTRS1988

Convective effects on directional solidification of a simulated metal alloy

The first significant results of a ground-based experimental program which supports a low gravity space processing Spacelab experiment are reported. The phenomena which precipitate pluming and thus freckling in a metal alloy analog (ammonium chloride and water) are studied in detail and the sequential events leading to massive channeling and convection are optically documented. The pluming is shown to be other than a random burst of unstable fluid from a preferred channel but rather a natural occurrence resulting from a fundamental (Rayleigh-Benard) fluid dynamic instability at the density inversion interface. This extrapolates to critical size parameters appropriate to processing of actual metal alloys.

Mccay, T. D.↗
DOE OSTI2023

Modeling the sequential dissociative double ionization of O 2 by ultrashort intense infrared laser pulses

A density matrix approach for sequential double ionization (DM-SDI) of molecules has been developed recently and was applied to the N 2 molecule. In this article, we extended the DM-SDI model to O 2 , which is a more complicated system to model than N 2 , due to its electronic structures and spin-orbit and laser couplings in the manifold of doubly charged states. We obtained a good agreement on the kinetic energy release spectrum of O + + O + from previous experiments. Thanks to the low computational cost of the model, we explored the mechanism behind the ionization and dissociation dynamics as well as the effects of lasers on the spectrum. Furthermore, this work will pave the way to model sequential dissociative double ionization of larger molecules and to probe molecular dynamics by measuring kinetic energy release spectra from this process.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS1975

Failure detection by pilots during automatic landing: Models and experiments

A model of the pilot as a monitor of instrument failures during automatic landing is proposed. The failure detection model consists of two stages: a linear estimator (Kalman Filter) and a decision mechanism which is based on sequential analysis. The filter equations are derived from a simplified version of the linearized dynamics of the airplane and the control loop. The perceptual observation noise is modelled to include the effects of the partition of attention among the several instruments. The final result is a simple model consisting of a high pass filter to produce the observation residuals, and a decision function which is a pure integration of the residuals minus a bias term. The dynamics of a Boeing 707 were used to simulate the fully coupled final approach in a fixed base simulator which also included failures in the airspeed, glideslope, and localizer indicators. Subjects monitored the approaches and detected the failures; their performance was compared with the predictions of the model with good agreement between the experimental data and the model.

Gai, E. G.↗
DOE OSTI2021

NEXTorch: A Design and Bayesian Optimization Toolkit for Chemical Sciences and Engineering

Automation and optimization of chemical systems require well-informed decisions on what experiments to run to reduce time, materials, and/or computations. Data-driven active learning algorithms have emerged as valuable tools to solve such tasks. Bayesian optimization, a sequential global optimization approach, is a popular active-learning framework. Past studies have demonstrated its efficiency in solving chemistry and engineering problems. Here we introduce NEXTorch, a library in Python/PyTorch, to facilitate laboratory or computational design using Bayesian optimization. NEXTorch offers fast predictive modeling, flexible optimization loops, visualization capabilities, easy interfacing with legacy software, and multiple types of parameters and data type conversions. It provides GPU acceleration, parallelization, and state-of-the-art Bayesian optimization algorithms and supports both automated an d human-in-the-loop optimization. The comprehensive online documentation introduces Bayesian optimization theory and several examples from catalyst synthesis, reaction condition optimization, parameter estimation, and reactor geometry optimization. NEXTorch is open-source and available on GitHub

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗