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DOE OSTI2025

Electronic Structures of Iron in Oxide Glasses via 1s3p Resonant Inelastic X-ray Scattering

Electronic structures of iron in glasses are essential for unraveling the effect of transition metals on amorphous networks and controlling the electro-optical and transport properties of advanced glasses and amorphous energy-storing materials. The electronic configurations around iron in glasses, however, remain not well understood due to the structural disorders arising from multiple iron species with distinct valence, coordination, and spin states. Here, the first 1s3p resonant inelastic X-ray scattering (RIXS) for oxide glasses identifies hidden electronic configurations for Fe 2+ and Fe 3+ in amorphous networks. The results allow us to quantify the composition-induced evolution of oxygen ligand–field interactions of high-spin Fe 3d states with varying valence and coordination environments in complex glasses. The distinct electronic structures account for the electronic origins of iron-induced changes in the glass properties. The results offer prospects for a simultaneous probing of valence, coordination, and spin states of transition metals in diverse multicomponent oxide glasses and functional amorphous solids via 1s3p RIXS.

Kim, Yong-Hyun [Seoul National Univ. (Korea, Repub↗

DOE OSTI2020

Methods for R&D Portfolio Analysis and Evaluation (Workshop Report)

The Workshop on Methods for R&D Portfolio Analysis and Evaluation convened on 17–18 July 2019 at the National Renewable Energy Laboratory in Golden, Colorado, and examined strengths and weaknesses of the various methodologies applicable to R&D portfolio modeling, analysis, and decision support, given pragmatic constraints such as data availability, uncertainties in estimating the impact of R&D spending, and practical operational overheads. Participants employed their deep expertise in approaches such as stochastic optimization, real options, Monte-Carlo analysis, Bayesian networks, decision theory, complex systems analysis, deep uncertainty, and technology-evolution modeling to critique the initial example models developed by the project’s core team and to conduct thought experiments grounded in real-life technology models, progress data, expert elicitation, and portfolio information. This engagement of participants’ methodological expertise with the practical requirements of real-life portfolio decision support yielded ideas for improved approaches, alternative methodological hypotheses, and hybridization of methodologies that are well-grounded theoretically, computationally sound, and realistically executable given data availability and other practical constraints.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Methods for R&D Portfolio Analysis and Evaluation (Workshop Report)

The Workshop on Methods for R&D Portfolio Analysis and Evaluation convened on 17-18 July 2019 at the National Renewable Energy Laboratory in Golden, Colorado, and examined strengths and weaknesses of the various methodologies applicable to R&D portfolio modeling, analysis, and decision support, given pragmatic constraints such as data availability, uncertainties in estimating the impact of R&D spending, and practical operational overheads. Participants employed their deep expertise in approaches such as stochastic optimization, real options, Monte-Carlo analysis, Bayesian networks, decision theory, complex systems analysis, deep uncertainty, and technology-evolution modeling to critique the initial example models developed by the project’s core team and to conduct thought experiments grounded in real-life technology models, progress data, expert elicitation, and portfolio information. This engagement of participants’ methodological expertise with the practical requirements of real-life portfolio decision support yielded ideas for improved approaches, alternative methodological hypotheses, and hybridization of methodologies that are well-grounded theoretically, computationally sound, and realistically executable given data availability and other practical constraints.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Drop C: The Drop-In, Ring-of-Power Heliostat (Final Report)

This report summarizes the work performed within the Drop-C: The Drop-In, Ring-of-Power Heliostat project. The Drop-C project aimed to develop a novel heliostat with an installed cost of $\$50$/m 2 ($\$2015$) which is a drastic cost reduction compared to the state-of-the-art. The resulting 27m 2 SunRing TM heliostat’s relative small size necessitates the parallel development of a wireless solar field network and a rapid calibration system. The SunRing heliostat is an evolution of the Ring-of-Power (ROP) design from Abengoa Solar LLC which had a reported installed cost of $114/m 2 . Cost savings relative to the ROP were sought by increasing the mirror area, improving the structural efficiency, a more accurate assessment of wind loads, and an improved assembly and installation procedure. The project spanned three Budget Periods (BP) where a digital heliostat was developed in BP1 using wind tunnel testing to define load conditions.

14 SOLAR ENERGY↗

NASA NTRS1985

Evolution of weak solar magnetic fields

The present evaluation of Big Bear videomagnetograph studies of the evolution of weak solar magnetic fields notes that the general weak network fields are the remnants of ephemeral regions which also play a role in the field diffusion as proposed by Marsh (1978). The intranetwork elements show a shorter lifetime and much more rapid motion than the network elements. They are in some cases noted to stream into existing network elements and may merge to form new elements, but need also show no preferential motion to the network edges. There seem to be fewer ephemeral regions in magnetically active areas.

Zirin, H.↗

NASA NTRS1990

On-orbit structural health monitoring

On-orbit structural health monitoring aboard space platforms requires the development of sensor systems for assessing impact damage from particles and debris, the effects of atomic oxygen erosion, and the integrity of power systems, storage tanks, pressure vessels, and major structural elements. The task of implementing such a smart structure diagnostic system during the initial phase of the NASA Space Station Freedom is evaluated, with a view to more complete smart structures implementation in the course of station evolution. The data processing/cataloguing task may ultimately require AI and neural networks.

Rogowski, Robert S.↗

DOE OSTI2023

Finite-Time Analysis of Whittle Index based Q-Learning for Restless Multi-Armed Bandits with Neural Network Function Approximation

Whittle index policy is a heuristic to the intractable restless multi-armed bandits (RMAB) problem. Although it is provably asymptotically optimal, finding Whittle indices remains difficult. In this paper, we present Neural-Q-Whittle, a Whittle index based Q-learning algorithm for RMAB with neural network function approximation, which is an example of nonlinear two-timescale stochastic approximation with Q-function values updated on a faster timescale and Whittle indices on a slower timescale. Despite the empirical success of deep Q-learning, the non-asymptotic convergence rate of Neural-Q-Whittle, which couples neural networks with two-timescale Q-learning largely remains unclear. This paper provides a finite-time analysis of Neural-Q-Whittle, where data are generated from a Markov chain, and Q-function is approximated by a ReLU neural network. Our analysis leverages a Lyapunov drift approach to capture the evolution of two coupled parameters, and the nonlinearity in value function approximation further requires us to characterize the approximation error. Combing these provide Neural-Q-Whittle with convergence rate, where is the number of iterations.

reinforcement learning, structured learning, conve↗

NASA NTRS2015

Securing the Global Airspace System Via Identity-Based Security

Current telecommunications systems have very good security architectures that include authentication and authorization as well as accounting. These three features enable an edge system to obtain access into a radio communication network, request specific Quality-of-Service (QoS) requirements and ensure proper billing for service. Furthermore, the links are secure. Widely used telecommunication technologies are Long Term Evolution (LTE) and Worldwide Interoperability for Microwave Access (WiMAX) This paper provides a system-level view of network-centric operations for the global airspace system and the problems and issues with deploying new technologies into the system. The paper then focuses on applying the basic security architectures of commercial telecommunication systems and deployment of federated Authentication, Authorization and Accounting systems to provide a scalable, evolvable reliable and maintainable solution to enable a globally deployable identity-based secure airspace system.

Communications↗

NASA NTRS2012

The Connection between Model Performance on the CCMVal Transport Diagnostics and Simulated Sensitivity of Ozone to Chlorine Change

The chemistry climate models that contributed simulations for past and future ozone evolution to the 2010 Scientific Assessment of Ozone Depletion were subject to extensive evaluation by the SPARC (Stratospheric Processes and their Role in Climate) CCMVal (Chemistry-Climate Model Validation) activity. The sensitivity of ozone to changes in composition and climate varies among the models, but the relationship between these variations and the model evaluations of CCMVal is not obvious. We have learned that the transport evaluation can be used to interpret the comparisons between observed and simulated columns of chlorine reservoirs, hydrochloric acid (HCl) and chlorine nitrate (ClONO2); these comparisons were part of the CCMVal evaluation of chemistry. The simulations with best performance on the transport diagnostics most faithfully reproduce the evolution and seasonal variation of the chlorine reservoirs as observed at NDACC (Network for Detection of Atmospheric Composition Change) stations (NyAlesund 78.9N, Kiruna 67.8N, Harestua 60.2N, Jungfraujoch 46.6N, Toronto 43.6N, Kitt Peak 31.9N, Izana 28.3N, Mauna Loa 19.5N, Lauder 45S and Arrival Heights 77.8S). In the simulations, the HCl in the lower stratosphere depends on total inorganic chlorine (Cly) and partitioning between HCl and ClON02. Total inorganic chlorine depends on the fractional release of chlorine from source gases, and ratio of ClON02 to HCl is inversely dependent on methane and varies quadratically with ozone. Simulated HCl from various models may agree with observations even though Cly is in error, partitioning is in error, or both. Simulated ozone sensitivity to chlorine is shown to be greater for models that produce larger values of chlorine nitrate for background chlorine levels, and vice versa. Comparisons with the NDACC data show why the models with 'best' transport have similar sensitivity to chlorine change. The realistic evolution of the simulated HCl and ClONO2 columns suggests realistic levels of Cly in the lower atmosphere. In addition, the wide range values for the sensitivity of ozone to chlorine obtained from the CCMVal simulations is explained by the wide range in lower atmospheric columns of ClONO2 and the concomitant wide range of levels for chlorine monoxide.

Douglass, Anne↗

NASA NTRS2019

A Delay Tolerant Networking-Based Approach to a High Data Rate Architecture for Spacecraft

Historically, it has been the case that SWaP placed such severe constraints on radios that the links between spacecraft and the ground were relatively slow. This meant that the radio link was normally a significant bottleneck in returning scientific data. Over recent years, however, a combination of more efficient radio design, intelligent waveforms, and highly directed, high-frequency RF / optical systems have led to a rapid increase in the amount of data that can be pushed through radio and optical links. This has led to some cases where the radio links are capable of moving data much more quickly than the spacecraft and instruments are capable of actually generating it! In some instances, scientific data can therefore be lost not because the downlink is too slow to support the data rate, but instead because the spacecraft was not designed in a way that would let it fully utilize both the radio and the networking services available to it.The High Data Rate Architecture (HiDRA) project describes a packet-based approach to building modern, distributed spacecraft systems. It presents a means for spacecraft and other assets to participate in both present and future Delay Tolerant Networks (DTN), while simultaneously ensuring that the asset is able to fully utilize the new, high-speed links that have been seeing more widespread development and deployment in recent years. With this in mind, this paper begins with a discussion regarding HiDRA's evolution. Next, it discusses the capabilities and limitations of NASA's present DTN-enabled networks. Of particular note is the way in which principles of network design at the terrestrial level (e.g. use of programmable networks / software-defined networks, separation between data and control plane, infusion of COTS Ethernet switch chips, etc.) can all be translated into the space environment as well. After this, the paper discusses the design and implementation of a present prototype reference implementation of High-Rate DTN (HDTN), which is intended to demonstrate future high-rate networking concepts as part of a coherent demonstration on the International Space Station (ISS). The goal, of both the research and of this implementation, is to help develop a ready-made toolbox of ideas, approaches, and examples from which mission designers can draw when putting together new missions. Assuming all goes as planned, this should not only work to reduce the cost of individual mission design, but also improve the rate at which science data can be returned for mission participants to review.

Hylton, Alan↗

NASA NTRS2019

A Delay Tolerant Networking-Based Approach to a High Data Rate Architecture for Spacecraft

Historically, it has been the case that SWaP (Size, Weigh a lot, And consume Power) placed such severe constraints on radios that the links between spacecraft and the ground were relatively slow. This meant that the radio link was normally a significant bottleneck in returning scientific data. Over recent years, however, a combination of more efficient radio design, intelligent waveforms, and highly directed, high-frequency RF / optical systems have led to a rapid increase in the amount of data that can be pushed through radio and optical links. This has led to some cases where the radio links are capable of moving data much more quickly than the spacecraft and instruments are capable of actually generating it! In some instances, scientific data can therefore be lost not because the downlink is too slow to support the data rate, but instead because the spacecraft was not designed in a way that would let it fully utilize both the radio and the networking services available to it. The High Data Rate Architecture (HiDRA) project describes a packet-based approach to building modern, distributed spacecraft systems. It presents a means for spacecraft and other assets to participate in both present and future Delay Tolerant Networks (DTN), while simultaneously ensuring that the asset is able to fully utilize the new, high-speed links that have been seeing more widespread development and deployment in recent years. With this in mind, this paper begins with a discussion regarding HiDRA's evolution. Next, it discusses the capabilities and limitations of NASA's present DTN-enabled networks. Of particular note is the way in which principles of network designate the terrestrial level (e.g., use of programmable networks / software-defined networks, separation between data and control plane, infusion of COTS (Commercial Off-The-Shelf) Ethernet switch chips, etc.) can all be translated into the space environment as well. After this, the paper discusses the design and implementation of a present prototype reference implementation of High-Rate DTN (HDTN),which is intended to demonstrate future high-rate networking concepts as part of a coherent demonstration on the International Space Station (ISS). The goal, of both the research and of this implementation, is to help develop a ready-made toolbox of ideas, approaches, and examples from which mission designers can draw when putting together new missions. Assuming all goes as planned, this should not only work to reduce the cost of individual mission design, but also improve the rate at which science data can be returned for mission participants to review.

Hylton, Alan↗

DOE OSTI2021

Accelerating phase-field-based microstructure evolution predictions via surrogate models trained by machine learning methods

Abstract The phase-field method is a powerful and versatile computational approach for modeling the evolution of microstructures and associated properties for a wide variety of physical, chemical, and biological systems. However, existing high-fidelity phase-field models are inherently computationally expensive, requiring high-performance computing resources and sophisticated numerical integration schemes to achieve a useful degree of accuracy. In this paper, we present a computationally inexpensive, accurate, data-driven surrogate model that directly learns the microstructural evolution of targeted systems by combining phase-field and history-dependent machine-learning techniques. We integrate a statistically representative, low-dimensional description of the microstructure, obtained directly from phase-field simulations, with either a time-series multivariate adaptive regression splines autoregressive algorithm or a long short-term memory neural network. The neural-network-trained surrogate model shows the best performance and accurately predicts the nonlinear microstructure evolution of a two-phase mixture during spinodal decomposition in seconds, without the need for “on-the-fly” solutions of the phase-field equations of motion. We also show that the predictions from our machine-learned surrogate model can be fed directly as an input into a classical high-fidelity phase-field model in order to accelerate the high-fidelity phase-field simulations by leaping in time. Such machine-learned phase-field framework opens a promising path forward to use accelerated phase-field simulations for discovering, understanding, and predicting processing–microstructure–performance relationships.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Influence of oxygen on performance of multi-principal element alloy as braze filler for Ni-base alloys

In manufacturing of multi-principal element alloys (MPEAs), the casting process is often a primary point of oxygen introduction to the material system, which was demonstrated by the laboratory scale button arc-melting process. Oxygen introduction raises concerns for the mechanical performance of these alloys if employed as structural materials alone or in engineering applications, such as serving as filler materials to enable joining of similar or dissimilar alloy pairs that are conventionally considered difficult to join. In this work, oxide inclusions in an as-cast off-equiatomic MnFeCoNiCu MPEA and Ni-base alloy braze joints made with this MPEA were evaluated by synchrotron x-ray diffraction mapping and electron microscopy. MnO was found to be prevalent throughout the cast MPEA and was chemically reduced during brazing by trace Al from the base material, Ni-base Alloy 600. Incomplete reaction of the MnO with Al, and some alternative reaction with Cr, left a mixture of MnO, Al 2 O 3 , and Cr 2 O 3 in the as-brazed joint, with the oxides concentrated near the braze centerline due to directional solidification. Further, in the braze joints, the non-oxide constituent phases detected were an FCC matrix and particles of Cr 23 C 6 , Cr 7 C 3 , and TiN which are all native to Alloy 600. The evolution of oxides within the brazed joints at elevated service temperatures of 600-800°C was also evaluated. While MnO and Al 2 O 3 were stable during high-temperature service, Cr 2 O 3 particles grew to several hundred microns, with dissolved oxygen in the MPEA providing a significant source for oxide growth. Comparing tensile performance of the as-brazed condition with post-service conditions showed that the evolution of oxide particles contributed to an increase in strength and decrease in ductility of the brazed joints. Evaluating particle morphologies among fracture surfaces of individual specimens demonstrated that large Cr 2 O 3 particles and continuous cluster networks of Al 2 O 3 were the features most detrimental to total elongation. Hence, unmitigated evolution of oxygen-containing species during brazing and service conditions is detrimental to the ductility of the brazed joints, which highlights the importance of oxygen control in initial manufacturing of MPEAs for engineering applications.

36 MATERIALS SCIENCE↗

NASA NTRS1993

Knowledge Engineering for Temporal Dependency Networks as Operations Procedures

This paper presents a case study of the knowledge engineering process employed to support the Link Monitor & Control Operator Assistant (LMCOA). The LMCOA is a prototype system which automates equipment used to support space-ground communication with deep space spacecraft in NASA's Deep Space Network (DSN). The primary knowledge base in the LMCOA is the Temporal Dependency Network (TDN). The paper provides a brief background on the DSN, and describes the evolution of the TDN and supporting knowledge bases, the process used for knowledge engineering, and an analysis of the successes--and problems--of the knowledge engineering effort.

operations↗

DOE OSTI2024

A comparison of model validation approaches for echo state networks using climate model replicates

As global temperatures continue to rise, climate mitigation strategies such as stratospheric aerosol injections (SAI) are increasingly discussed, but the downstream effects of these strategies are not well understood. As such, there is interest in developing statistical methods to quantify the evolution of climate variable relationships during the time period surrounding an SAI. Feature importance applied to echo state network (ESN) models has been proposed as a way to understand the effects of SAI using a data-driven model. This approach depends on the ESN fitting the data well. If not, the feature importance may place importance on features that are not representative of the underlying relationships. Typically, time series prediction models such as ESNs are assessed using out-of-sample performance metrics that divide the times series into separate training and testing sets. However, this model assessment approach is geared towards forecasting applications and not scenarios such as the motivating SAI example where the objective is using a data driven model to capture variable relationships. Here, in this paper, we demonstrate a novel use of climate model replicates to investigate the applicability of the commonly used repeated hold-out model assessment approach for the SAI application. Simulations of an SAI are generated using a simplified climate model, and different initialization conditions are used to provide independent training and testing sets containing the same SAI event. The climate model replicates enable out-of-sample measures of model performance, which are compared to the single time series hold-out validation approach. For our case study, it is found that the repeated hold-out sample performance is comparable, but conservative, to the replicate out-of-sample performance when the training set contains enough time after the aerosol injection.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2020

Using Networked Pandora Observations to Capture Spatiotemporal Changes in Total Column Ozone Associated with Stratosphere-to-Troposphere Transport

Accurately capturing the evolution of episodic stratosphere-to-troposphere transport is critical due to the potential impacts on both climate and air quality. Until now, investigating associated spatiotemporal gradients in total column ozone (TCO) has primarily been the task of observations from polar-orbiting satellites as well as high-resolution models. We explore how a network of five ground-based Pandora spectrometer systems can be utilized in a similar fashion. The passage of a strong mid-latitude cyclone in March 2018 and its associated stratospheric intrusion is used as a case demonstrating the ability of networked Pandora observations to contextualize these regions of transport across space and time. Results show that the high temporal resolution of Pandora observations and the networked approach were able to resolve increases in TCO associated with stratosphere-to-troposphere transport and to capture the spatial context of the chosen episode. The use of networked Pandora observations shows promise for additional transport studies and for supporting future geostationary atmospheric composition satellite missions and modeling efforts.

J. Robinson↗

NASA NTRS1994

NASA Goddard Earth Sciences Graduate Student Program

The evolution of synoptic-scale dynamics associated with a middle and upper tropospheric cloud event that occurred on 26 November 1991 is examined. The case under consideration occurred during the FIRE CIRRUS-II Intensive Field Observing Period held in Coffeyville, KS during Nov. and Dec., 1991. Using data from the wind profiler demonstration network and a temporally and spatially augmented radiosonde array, emphasis is given to explaining the evolution of the kinematically-derived ageostrophic vertical circulations and correlating the circulation with the forcing of an extensively sampled cloud field. This is facilitated by decomposing the horizontal divergence into its component parts through a natural coordinate representation of the flow. Ageostrophic vertical circulations are inferred and compared to the circulation forcing arising from geostrophic confluence and shearing deformation derived from the Sawyer-Eliassen Equation. It is found that a thermodynamically indirect vertical circulation existed in association with a jet streak exit region. The circulation was displaced to the cyclonic side of the jet axis due to the orientation of the jet exit between a deepening diffluent trough and building ridge. The cloud line formed in the ascending branch of the vertical circulation with the most concentrated cloud development occurring in conjunction with the maximum large-scale vertical motion. The relationship between the large scale dynamics and the parameterization of middle and upper tropospheric clouds in large-scale models is discussed and an example of ice water contents derived from a parameterization forced by the diagnosed vertical motions and observed water vapor contents is presented.

Ackerman, Thomas P.↗

NASA NTRS1994

Extended field observations of cirrus clouds using a ground-based cloud observing system

Ackerman, Thomas P.↗