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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A galactic approach to neutron scattering science

Neutron scattering science is leading to significant advances in our understanding of materials and will be key to solving many of the challenges that society is facing today. Improvements in scientific instruments are actually making it more difficult to analyze and interpret the results of experiments due to the vast increases in the volume and complexity of data being produced and the associated computational requirements for processing that data. New approaches to enable scientists to leverage computational resources are required, and Oak Ridge National Laboratory (ORNL) has been at the forefront of developing these technologies. We recently completed the design and initial implementation of a neutrons data interpretation platform that allows seamless access to the computational resources provided by ORNL. For the first time, we have demonstrated that this platform can be used for advanced data analysis of correlated quantum materials by utilizing the world's most powerful computer system, Frontier. In particular, we have shown the end-to-end execution of the DCA++ code to determine the dynamic magnetic spin susceptibility χ(q, ω) for a single-band Hubbard model with Coulomb repulsion U/t = 8 in units of the nearest-neighbor hopping amplitude t and an electron density of n = 0.65. The following work describes the architecture, design, and implementation of the platform and how we constructed a correlated quantum materials analysis workflow to demonstrate the viability of this system to produce scientific results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Dynamical Instabilities in Systems of Multiple Short-period Planets Are Likely Driven by Secular Chaos: A Case Study of Kepler-102

We investigated the dynamical stability of high-multiplicity Kepler and K2 planetary systems. Our numerical simulations find instabilities in ∼20% of the cases on a wide range of timescales (up to 5 × 10{sup 9} orbits) and over an unexpectedly wide range of initial dynamical spacings. To identify the triggers of long-term instability in multiplanet systems, we investigated in detail the five-planet Kepler-102 system. Despite having several near-resonant period ratios, we find that mean-motion resonances are unlikely to directly cause instability for plausible planet masses in this system. Instead, we find strong evidence that slow inward transfer of angular momentum deficit (AMD) via secular chaos excites the eccentricity of the innermost planet, Kepler-102 b, eventually leading to planet–planet collisions in ∼80% of Kepler-102 simulations. Kepler-102 b likely needs a mass ≳0.1 M {sub ⊕}, hence a bulk density exceeding about half Earth’s, in order to avoid dynamical instability. To investigate the role of secular chaos in our wider set of simulations, we characterize each planetary system’s AMD evolution with a “spectral fraction” calculated from the power spectrum of short integrations (∼5 × 10{sup 6} orbits). We find that small spectral fractions (≲0.01) are strongly associated with dynamical stability on long timescales (5 × 10{sup 9} orbits) and that the median time to instability decreases with increasing spectral fraction. Our results support the hypothesis that secular chaos is the driver of instabilities in many nonresonant multiplanet systems and also demonstrate that the spectral analysis method is an efficient numerical tool to diagnose long-term (in)stability of multiplanet systems from short simulations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Wave like signatures in aerosol optical depth and associated radiative impacts over the central Himalayan region

Doppler Lidar and Multi-Filter Rotating Shadowband Radiometer (MFRSR) observations are utilized to show wave like signatures in aerosol optical depth (AOD) during daytime boundary layer evolution over the Himalayan region. Fourier analysis depicted 60–80 min periods dominant during afternoon hours, implying that observed modulations could be plausible reason for the AOD forenoon–afternoon asymmetry which was previously reported. Inclusion of wave amplitude in diurnal variation of aerosol radiative forcing estimates showed ~40% additional warming in the atmosphere relative to mean AOD. The present observations emphasize the importance of wave induced variations in AOD and radiation budget over the site.

Aerosol optical depth↗
DOE OSTI2026

Enhanced accuracy through ensembling of randomly initialized auto-regressive models for dynamical systems

Computational mechanics simulations using traditional finite element methods (FEM) require prohibitively expensive computational resources for real-time engineering applications, design optimization, and digital twin implementations. While machine learning (ML) surrogate models offer significant computational speedups, autoregressive ML models for time-dependent mechanical systems suffer from error accumulation that compromises long-term prediction reliability - a critical concern for engineering applications where accuracy over extended time horizons is essential for safety and performance assessments. Here, we propose a deep ensemble framework specifically designed to address this challenge in computational mechanics applications, where multiple ML surrogate models with random weight initializations are trained in parallel and their predictions aggregated during inference. This approach leverages statistical diversity to maximize information gain from a fixed set of training data and to mitigate error propagation, while maintaining the computational efficiency that makes ML surrogates attractive for engineering practice. We validate the framework on three representative problems spanning critical areas of computational mechanics: stress field evolution in heterogeneous microstructures under complex loading (relevant to advanced materials design and composite analysis), planetary-scale shallow water dynamics (applicable to environmental and geotechnical engineering), and Gray-Scott reaction-diffusion systems (relevant to mass transport and chemical process engineering). Across all test cases, the ensemble approach demonstrates consistent error reduction of 15-33% compared to individual models. The codes for this work are available on GitHub (https://github.com/Graham-Brady-Research-Group/AutoregressiveEnsemble_SpatioTemporal_Evolution).

autoregressive prediction↗
DOE OSTI2013

Conceptual Framework to Enable Early Warning of Relevant Phenomena (Emerging Phenomena and Big Data)

Graphs are commonly used to represent natural and man-made dynamic systems such as food webs, economic and social networks, gene regulation, and the internet. We describe a conceptual framework to enable early warning of relevant phenomena that is based on an artificial time-based, evolving network graph that can give rise to one or more recognizable structures. We propose to quantify the dynamics using the method of delays through Takens Theorem to produce another graph we call the Phase Graph. The Phase Graph enables us to quantify changes of the system that form a topology in phase space. Our proposed method is unique because it is based on dynamic system analysis that incorporates Takens Theorem, Graph Theory, and Franzosi-Pettini (F-P) theorem about topology and phase transitions. The F-P Theorem states that the necessary condition for phase transition is a change in the topology. By detecting a change in the topology that we represent as a set of M-order Phase Graphs, we conclude a corresponding change in the phase of the system. The onset of this phase change enables early warning of emerging relevant phenomena.

complexity↗
DOE OSTI2012

Design stress evaluation based on strain-rate sensitivity analysis for nickel alloys used in the very-high temperature nuclear system

Both Alloy 617 and Alloy 230 have been considered the most promising structural materials for the Very High Temperature Reactor (VHTR). In this study, mechanical properties of both alloys were examined by performing tensile tests at three different strain rates and at temperatures up to 1000 deg.C. This range covers time-dependent (plasticity) to time-independent (creep) deformations. Strain-rate sensitivity analysis for each alloy was conducted in order to approximate the long-term flow stresses. The strain-rate sensitivities for the 0.2% flow stress were found to be temperature independent (m {approx_equal} 0) at temperatures ranging from room temperature to 700 deg.C due to dynamic strain aging. At elevated temperatures (800-1000 deg.C), the strain-rate sensitivity significantly increased (m > 0.1). Compared to Alloy 617, Alloy 230 displayed higher strain-rate sensitivities at high temperatures. This leads to a lower estimated long-term flow stresses. Results of this analysis were used to evaluate current American Society of Mechanical Engineers (ASME) allowable design limits. According to the comparison with the estimated flow stresses, the allowable design stresses in ASME B and PV Code for either alloy did not provide adequate degradation estimation for the possible long-term service life in VHTR. However, rupture stresses for Alloy 617, developed in ASME code case N-47-28, can generally satisfy the safety margin estimated in the study following the strain-rate sensitivity analysis. Nevertheless, additional material development studies might be required, since the design parameters for rupture stresses are constrained such that current VHTR conceptual designs cannot satisfy the limits. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

Deformation and failure in extreme regimes by high-energy pulsed lasers: A review

The use of high-power pulsed lasers to probe the response of materials at pressures of hundreds of GPa up to several TPa, time durations of nanoseconds, and strain rates of 10 6 –10 1° s -1 is revealing novel mechanisms of plastic deformation, phase transformations, and even amorphization. This unique experimental tool, aided by advanced diagnostics, analysis, and characterization, allows us to explore these new regimes that simulate those encountered in the interiors of planets. Fundamental Materials Science questions such as dislocation velocity regimes, the transition between thermally-activated and phonon drag regimes, the slip-twinning transition, the ultimate tensile strength of metals, the dislocation mechanisms of void growth are being answered through this powerful tool. In parallel with experiments, molecular dynamics simulations provide modeling and visualization at comparable strain rates (10 8 –10 10 s -1 ) and time durations (hundreds of picoseconds). Finally, this powerful synergy is illustrated in our past and current work, using representative face-centered cubic (fcc) copper, body-centered cubic (bcc) tantalum and diamond cubic silicon as model structures.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Fast, Dynamic, and Scalable Algorithms for Large-Scale Constrained Optimization

Scientists and engineers constantly aim to optimize an objective subject to physical, environmental, and/or resource constraints. The technique of using mathematical models to formulate and find real solutions of such problems is known as mathematical optimization, a process that has become invaluable for design and discovery in numerous scientific fields. This project has focused on the design, analysis, and implementation of high-performance computing algorithms for solving cutting-edge optimization problems. These include problems that involve (1) data uncertainties, such as those in the future supply, demand, and capacity of a given power system, (2) extreme numbers of alternatives, such as in the design of electrical power grids to avoid network vulnerabilities, and (3) real-time decisions, such as in the control of chemical reactors. The key features of the new algorithms are that they are fast, dynamic, and scalable to meet the computational requirements of scientists and researchers working to optimize large-scale, complex systems. The algorithms that have been designed, analyzed, and tested as part of the project can be characterized based on the types of optimization problems they have been designed to solve. Much of the work has focused on algorithms for solving large-scale constrained optimization problems. Contributions have also been made in the design of algorithms for unconstrained optimization, with some specialized methods for solving problems that have inherent nonsmoothness. Contributions have also been made in areas that have grown to prominence in the field over the five-year award period. These include the design of algorithms for solving large-scale stochastic optimization problems, such as those that arise in large-scale machine learning, and in complexity analyses for solving nonconvex problems, which has been a focal point of much recent work in continuous optimization. Overall, the project has supported work that has led to almost 30 articles that have been published or accepted to top journals in the field of mathematical optimization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Optical pump-terahertz probe analysis of long-lived d-electrons and relaxation to self-trapped exciton states in MnO

The dynamics of photoexcited electrons in various excited d-states was investigated in a transition metal oxide MnO by tunable optical pump-terahertz probe measurements. Photoexcited electrons in the lowest excited d-state showed the longest relaxation time among the three excited d-states that are accessible in MnO at room temperature. The relaxation rate in the lowest excited d-state showed a drastic increase below the Neel temperature T{sub N} = 120 K in MnO. We conclude that this increase is caused by the appearance of a decay channel related to magnetic-excitation-assisted photoluminescence from self-trapped exciton (STE) states. The opening of relaxation channels to the STE states in an antiferromagnetic phase suggests that it may be possible to control photocarrier lifetime by magnetic order in transition metal oxides.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

A machine learning photon detection algorithm for coherent x-ray ultrafast fluctuation analysis

X-ray free electron laser experiments have brought unique capabilities and opened new directions in research, such as creating new states of matter or directly measuring atomic motion. One such area is the ability to use finely spaced sets of coherent x-ray pulses to be compared after scattering from a dynamic system at different times. This enables the study of fluctuations in many-body quantum systems at the level of the ultrafast pulse durations, but this method has been limited to a select number of examples and required complex and advanced analytical tools. By applying a new methodology to this problem, we have made qualitative advances in three separate areas that will likely also find application to new fields. As compared to the “droplet-type” models, which typically are used to estimate the photon distributions on pixelated detectors to obtain the coherent x-ray speckle patterns, our algorithm achieves an order of magnitude speedup on CPU hardware and two orders of magnitude improvement on GPU hardware. We also find that it retains accuracy in low-contrast conditions, which is the typical regime for many experiments in structural dynamics. Finally, it can predict photon distributions in high average-intensity applications, a regime which up until now has not been accessible. Our artificial intelligence-assisted algorithm will enable a wider adoption of x-ray coherence spectroscopies, by both automating previously challenging analyses and enabling new experiments that were not otherwise feasible without the developments described in this work.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Global soil consumption of atmospheric carbon monoxide: an analysis using a process-based biogeochemistry model

Carbon monoxide (CO) plays an important role in controlling the oxidizing capacity of the atmosphere by reacting with OH radicals that affect atmospheric methane (CH 4 ) dynamics. We develop a process-based biogeochemistry model to quantify the CO exchange between soils and the atmosphere with a 5 min internal time step at the global scale. The model is parameterized using the CO flux data from the field and laboratory experiments for 11 representative ecosystem types. The model is then extrapolated to global terrestrial ecosystems using monthly climate forcing data. Global soil gross consumption, gross production, and net flux of the atmospheric CO are estimated to be from -197 to -180, 34 to 36, and -163 to -145 Tg CO yr -1 (1 Tg = 10 12 g), respectively, when the model is driven with satellite-based atmospheric CO concentration data during 2000–2013. Tropical evergreen forest, savanna and deciduous forest areas are the largest sinks at 123 Tg CO yr -1 . The soil CO gross consumption is sensitive to air temperature and atmospheric CO concentration, while the gross production is sensitive to soil organic carbon (SOC) stock and air temperature. By assuming that the spatially distributed atmospheric CO concentrations (~ 128 ppbv) are not changing over time, the global mean CO net deposition velocity is estimated to be 0.16–0.19 mm s -1 during the 20th century. Under the future climate scenarios, the CO deposition velocity will increase at a rate of 0.0002–0.0013 mm s -1 yr -1 during 2014–2100, reaching 0.20–0.30 mm s -1 by the end of the 21st century, primarily due to the increasing temperature. Areas near the Equator, the eastern US, Europe and eastern Asia will be the largest sinks due to optimum soil moisture and high temperature. The annual global soil net flux of atmospheric CO is primarily controlled by air temperature, soil temperature, SOC and atmospheric CO concentrations, while its monthly variation is mainly determined by air temperature, precipitation, soil temperature and soil moisture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Numerical analysis of radiation dynamics in a combined hohlraum in the X-ray opacity experiments on the 'Iskra-5' laser facility

We report the results of numerical analysis of radiation dynamics (laser absorption and X-ray generation) by using SNDLIRA code in a combined box used in the X-ray opacity measurements on the 'Iskra-5' facility (laser radiation wavelength, λ = 0.66 μm; laser pulse duration, τ{sub 0.5} ≈ 0.6 ns; and energy, 900 J). Combined boxes used in these experiments comprised three sections: two illuminators delivering laser radiation and a central diagnostic section with a test sample. We have proposed a scheme for step-by-step calculation of the heating dynamics of the sample under study in a three-section hohlraum. Two designs of a combined box, which differ in the ways the laser radiation is injected, are discussed. It is shown that the axial injection of the beams results in intense secondary laser irradiation of the illuminator edge which leads to its partial disruption and penetration of laser radiation into the central diagnostic section. In this case the sample under study is exposed to additional uncontrolled action of scattered laser radiation. Such an undesirable action may be avoided by using the lateral injection of the beams through four holes on the lateral side of the illuminators. For the latter case we have calculated the heating dynamics for the sample and found an optimal time delay for an X-ray probe pulse. (interaction of laser radiation with matter. laser plasma)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Analysis of seismicity at observed at station BCE using subspace detectors

A dynamic correlation processor (DCP) was used to process 90 days of 3-component seismic data recorded by station BCE. Two methods of detector creation were compared. The first attempted to span the signal space with a small number of subspace detectors having minimal projections on one another, and the second used a much larger number of detectors with substantial inter-template projections. After two passes over the data the results were compared, and the second approach was found to have produced more than 3 times the number of detections. For events in common, the average correlation statistic for the second approach was 0.77 compared to a statistic of 0.65 for the first approach. Also, analysis of the detection statistics as a function of SNR showed a strong functional relationship between SNR and correlation statistic for the second approach not found in the first approach. I interpret this to mean that the intra-group variability of signals produced by the second method is due primarily to noise rather than variations in source or path. These results show that (in an environment with large numbers of repeaters) if precise classification is a goal, it is better to operate a DCP with many correlators with substantial inter-template projections and that fully span the signal space. The performance of the DCP was also measured using a small set of “ground truth” picks for BCE from the Chip Brogan catalog. The catalog spanned less than three days out of the 90 days of the experiment and is also incomplete, but the comparison identified 12 signals missed by the DCP because of low SNR. Combining detections by the DCP and picks from the Brogan catalog, identifies 76 unique signals. Of these, the DCP detected 64 (84%) and the Catalog contained between 48/76 (63%) and 48/62 (77%). Analysis of time-of-day and day-of-week statistics was not useful in identifying the signal sources. However, magnitude recurrence statistics were consistent with mining induced seismicity (a preponderance of small sources). Failure of the temporal discriminants may indicate that the events being detected are not coupled in the same way to the mining activity, e.g. secondary failures. Correlation data from explosions at the Nevada test site (NTS) were used to bound the separation of events within groups. Nearly all the NTS correlations with the same passband and time bandwidth product as the detections and having a correlation statistic >= 0.8 are from sources separated by less than 1 km. Even at correlation values of 0.6 nearly all the source separations are less than about 3 km. Because the DCP detectors were formed to span the signal space at a correlation value of 0.9 and because the intra-group variability is most likely due to noise and not source variability, it is likely that the sources associated with each detector are separated by one km or less, and almost certain that the majority are separated by no more than 3 km.

47 OTHER INSTRUMENTATION↗
DOE OSTI2017

Comparing capacity coefficient and dual task assessment of visual multitasking workload

Capacity coefficient analysis could offer a theoretically grounded alternative approach to subjective measures and dual task assessment of cognitive workload. Workload capacity or workload efficiency is a human information processing modeling construct defined as the amount of information that can be processed by the visual cognitive system given a specified of amount of time. In this paper, I explore the relationship between capacity coefficient analysis of workload efficiency and dual task response time measures. To capture multitasking performance, I examine how the relatively simple assumptions underlying the capacity construct generalize beyond the single visual decision making tasks. The fundamental tools for measuring workload efficiency are the integrated hazard and reverse hazard functions of response times, which are defined by log transforms of the response time distribution. These functions are used in the capacity coefficient analysis to provide a functional assessment of the amount of work completed by the cognitive system over the entire range of response times. For the study of visual multitasking, capacity coefficient analysis enables a comparison of visual information throughput as the number of tasks increases from one to two to any number of simultaneous tasks. I illustrate the use of capacity coefficients for visual multitasking on sample data from dynamic multitasking in the modified Multi-attribute Task Battery.

capacity coefficient↗
DOE OSTI2022

Quantifying Dynamic Signal Spread in Real-Time High-Energy X-ray Diffraction

Abstract Measured intensity in high-energy monochromatic X-ray diffraction (HEXD) experiments provides information regarding the microstructure of the crystalline material under study. The location of intensity on an areal detector is determined by the lattice spacing and orientation of crystals so that changes in the heterogeneity of these quantities are reflected in the spreading of diffraction peaks over time. High temporal resolution of such dynamics can now be experimentally observed using technologies such as the mixed-mode pixel array detector (MM-PAD) which facilitates in situ dynamic HEXD experiments to study plasticity and its underlying mechanisms. In this paper, we define and demonstrate a feature computed directly from such diffraction time series data quantifying signal spread in a manner that is correlated with plastic deformation of the sample. A distinguishing characteristic of the analysis is the capability to describe the evolution from the distinct diffraction peaks of an undeformed alloy sample through to the non-uniform Debye–Scherrer rings developed upon significant plastic deformation. We build on our previous work modeling data using an overcomplete dictionary by treating temporal measurements jointly to improve signal spread recovery. We demonstrate our approach in simulations and on experimental HEXD measurements captured using the MM-PAD. Our method for characterizing the temporal evolution of signal spread is shown to provide an informative means of data analysis that adds to the capabilities of existing methods. Our work draws on ideas from convolutional sparse coding and requires solving a coupled convex optimization problem based on the alternating direction method of multipliers.

Engineering↗
DOE OSTI2023

Estimates of the wavenumber wavelet power spectrum of magnetic fluctuations during magnetic reconnection

Fluctuation analyses of experimental observations generally lack high temporal resolution and are in frequency-space f, contrary to theoretical efforts in wavenumber-space k. This is due to the inherent limits of the Fourier transform, though it is prominent due to the ease of diagnostic implementation. Advances in wavelet-based analysis have provided relief due to its temporal resolution, but in its common use, is still hard to compare to theoretical models. By using the two-point correlation technique in conjunction with large data sets, a wavelet power spectrum in wavenumber-space can be created. Dubbed the wavenumber wavelet power spectrum, this spectrum relates wavenumber to power in time. Further, this analysis technique more closely connects characterizations of experimentally observed fluctuations with other system parameters and theoretical predictions. In this article, we develop the wavenumber wavelet power spectrum using magnetic fluctuations caused by tearing instability driven magnetic reconnection in reproducible, high temperature laboratory plasmas. These dynamic magnetic fluctuations generated in reversed field pinch plasmas are broadband, ranging from the low frequency, 10's of kHz, up to the ion gyroradii frequencies, 100's of kHz. The dominant fluctuations have poloidal and toroidal mode numbers (m,n)=(1,6−10) and can grow to 2%–3% of the mean magnetic field. During these reconnection events, ions, and electrons are energized, magnetic fluctuation amplitudes increase, plasma flow is halted, and the toroidal magnetic flux increases, all on a semi-periodic basis. The newly developed spectrum provides better temporal resolution of spectrum characteristics to correlate with these particle energization phenomena.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Constraints on a φCDM model from strong gravitational lensing and updated Hubble parameter measurements

We constrain the scalar field dark energy model with an inverse power-law potential, i.e., V(φ) ∝ φ{sup −α} (α > 0), from a set of recent cosmological observations by compiling an updated sample of Hubble parameter measurements including 30 independent data points. Our results show that the constraining power of the updated sample of H(z) data with the HST prior on H{sub 0} is stronger than those of the SCP Union2 and Union2.1 compilations. A recent sample of strong gravitational lensing systems is also adopted to confine the model even though the results are not significant. A joint analysis of the strong gravitational lensing data with the more restrictive updated Hubble parameter measurements and the Type Ia supernovae data from SCP Union2 indicates that the recent observations still can not distinguish whether dark energy is a time-independent cosmological constant or a time-varying dynamical component.

79 ASTRONOMY AND ASTROPHYSICS↗