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DOE OSTI2022

Is the Adoption of Electric Vehicles (EVs) and Solar Photovoltaics (PVs) Interdependent or Independent? An Integrated EVs-PVs Modeling Framework

Transportation and residential energy consumption account for more than one-half of the overall energy consumption in the United States. Adoption of electric vehicles (EVs) can play a key role in decarbonizing the transportation sector, while the adoption of renewable energy sources (e.g., solar photovoltaics or PVs) could bring similar benefits to the residential energy sector and in turn support transport electrification. Although the market share for both EVs and PVs continue to grow, both these emerging technologies are deployed rather disjoint without considering the existence of potential similarities among users who own (or aspire to own) EVs and PVs. This might be due to lack of understanding of the behavioral interdependence in consumer preferences towards these technologies. To fill this gap in knowledge, this study utilizes data from the 2018 WholeTraveler Transportation Behavior Study to develop an integrated model system that explores EV and PV adoption behaviors. A structural equations model (SEM) is employed that incorporates direct effects as well as error correlations among the adoption behaviors for EVs and PVs. Model results indicate that the adoption behavior for both these technologies is indeed interconnected and significantly influenced by attitudes, values and personality traits. Findings from this research suggest that incentives (e.g., subsidies) that drive 'bundled' adoption of EVs and PVs could accelerate the adoption of both these sustainable technologies. The results highlights the need to consider transport and building energy efficient technology adoption behavior in a single integrated structure.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

DOE OSTI2019

Alliance Project: Secure Control Systems for the Energy Sector

The Alliance Project addresses Area of Interest 4: Secure Remote Access for the Energy Sector, by combining physical and cyber access under one cybersecurity access system. The Alliance Project built on the successful completion of the Lemnos and Padlock Project (DOE-Funded Project started in 2007 and 2010) and researched and developed a solution for an Ethernet Security Gateway with the functionality required to integrate the physical access control cyber system and interface with legacy and new proximity card readers used for physical access requests. This project focused on securing and enhancing the cyber system the physical access control system operates on. The team tested and demonstrated the system solution on the SEL campus. Currently the physical access cyber system is completely separate from the cyber access control cyber system. With a single system industry benefits include: (1) Single system to learn and teach employees; (2) Single system that collects and alerts on logs and events simplifying incident response plans and NERC CIP compliance; (3) Unifies trust management to a single system reducing the potential errors in privilege escalation or revocation; (4) Provides a stronger cybersecurity platform the physical access control system operates on. Today they are mostly plain text protocols and little cyber awareness; (5) Integration of physical access awareness allows the cyber system to react and adjust. In some cases, the cyber access can be enhanced with authorized physical access and other cases the cyber access can be more restricted with unauthorized physical access; and (6) Enables the utility to establish as large or as small a physical access control system as they require. One example would be when a utility shares a substation with a neighbor utility and can’t rely on the substation door for the physical access control. The Alliance technology enables them to lock equipment racks simply with no scalability issues because it stands on the cyber security infrastructure which is already highly scalable.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2004

Discovery of a Transient Magnetar: XTE J1810-197

We report the discovery of a new X-ray pulsar, XTE J1810-197, that was serendipitously discovered on 2003 July 15 by the Rossi X-Ray Timing Explorer (RXTE) while observing the soft gamma repeater SGR 1806-20. The pulsar has a 5.54 s spin period, a soft X-ray spectrum (with a photon index of approx. = 4). and is detectable in earlier RXTE observations back to 2003 January but not before. These show that a transient outburst began between 2002 November 17 and 2003 January 23 and that the source's persistent X-ray flux has been declining since then. The pulsar exhibits a high spin-down rate P approx.= l0(exp -11) s/s with no evidence of Doppler shifts due to a binary companion. The rapid spin-down rate and slow spin period imply a supercritical characteristic magnetic field B approx. = 3 x l0(exp 14) G and a young age tau less than or = 7600 yr. Follow-up Chandra observations provided an accurate position of the source. Within its error radius, the 1.5 m Russian-Turkish Optical Telescope found a limiting magnitude R(sub c) = 21.5. All such properties are strikingly similar to those of anomalous X-ray pulsars ad soft gamma repeaters, providing strong evidence that the source is a new magnetar. However, archival ASCA and ROSAT observations found the source nearly 2 orders of magnitude fainter. This transient behavior and the observed long-term flux variability of the source in absence of an observed SGR-like burst activity make it the first confirmed transient magnetar and suggest that other neutron stars that share the properties of XTE 51810- 197 during its inactive phase may be unidentified transient magnetars awaiting detection via a similar activity. This implies a larger population of magnetars than previously surmised and a possible evolutionary connection between magnetars and other neutron star families. Subject headings: pulsars: general -pulsars: individual (XTE 51810- 197) - stars: magnetic fields -

Ibrahim, Alaa I.↗

DOE OSTI2018

Identifying an efficient, thermally robust inorganic phosphor host via machine learning

Abstract Rare-earth substituted inorganic phosphors are critical for solid state lighting. New phosphors are traditionally identified through chemical intuition or trial and error synthesis, inhibiting the discovery of potential high-performance materials. Here, we merge a support vector machine regression model to predict a phosphor host crystal structure’s Debye temperature, which is a proxy for photoluminescent quantum yield, with high-throughput density functional theory calculations to evaluate the band gap. This platform allows the identification of phosphors that may have otherwise been overlooked. Among the compounds with the highest Debye temperature and largest band gap, NaBaB 9 O 15 shows outstanding potential. Following its synthesis and structural characterization, the structural rigidity is confirmed to stem from a unique corner sharing [B 3 O 7 ] 5– polyanionic backbone. Substituting this material with Eu 2+ yields UV excitation bands and a narrow violet emission at 416 nm with a full-width at half-maximum of 34.5 nm. More importantly, NaBaB 9 O 15 :Eu 2+ possesses a quantum yield of 95% and excellent thermal stability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2011

Complex Biological Event Extraction from Full Text using Signatures of Linguistic and Semantic Features

Building on technical advances from the BioNLP 2009 Shared Task Challenge, the 2011 challenge sets forth to generalize techniques to other complex biological event extraction tasks. In this paper, we present the implementation and evaluation of a signature-based machine-learning technique to predict events from full texts of infectious disease documents. Specifically, our approach uses novel signatures composed of traditional linguistic features and semantic knowledge to predict event triggers and their candidate arguments. Using a leave-one out analysis, we report the contribution of linguistic and shallow semantic features in the trigger prediction and candidate argument extraction. Lastly, we examine evaluations and posit causes for errors of infectious disease track subtasks.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Strong parametric dispersive shifts in a statically decoupled two-qubit cavity QED system

Qubits in cavity quantum electrodynamic (QED) architectures are often operated in the dispersive regime, in which the operating frequency of the cavity depends on the energy state of the qubit, and vice versa. The ability to tune these dispersive shifts provides additional options for performing either quantum measurements or logical manipulations. Here we couple two transmon qubits to a lumped-element cavity through a shared superconducting quantum interference device (SQUID). In this work, our design balances the mutual capacitive and inductive circuit components so that both qubits are statically decoupled from the cavity with low flux sensitivity, offering protection from decoherence processes. Parametric driving of the SQUID flux enables independent, dynamical tuning of each qubit’s interaction with the cavity. As a practical demonstration, we perform pulsed parametric dispersive readout of both qubits. The dispersive frequency shifts of the cavity mode follow the theoretically expected magnitude and sign. This parametric approach creates an extensible, tunable cavity QED framework with various future applications, such as entanglement and error correction via multi-qubit parity readout, state and entanglement stabilization, and parametric logical gates.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

NASA NTRS2013

Evidence Report: Risk of Inadequate Human-Computer Interaction

Human-computer interaction (HCI) encompasses all the methods by which humans and computer-based systems communicate, share information, and accomplish tasks. When HCI is poorly designed, crews have difficulty entering, navigating, accessing, and understanding information. HCI has rarely been studied in an operational spaceflight context, and detailed performance data that would support evaluation of HCI have not been collected; thus, we draw much of our evidence from post-spaceflight crew comments, and from other safety-critical domains like ground-based power plants, and aviation. Additionally, there is a concern that any potential or real issues to date may have been masked by the fact that crews have near constant access to ground controllers, who monitor for errors, correct mistakes, and provide additional information needed to complete tasks. We do not know what types of HCI issues might arise without this "safety net". Exploration missions will test this concern, as crews may be operating autonomously due to communication delays and blackouts. Crew survival will be heavily dependent on available electronic information for just-in-time training, procedure execution, and vehicle or system maintenance; hence, the criticality of the Risk of Inadequate HCI. Future work must focus on identifying the most important contributing risk factors, evaluating their contribution to the overall risk, and developing appropriate mitigations. The Risk of Inadequate HCI includes eight core contributing factors based on the Human Factors Analysis and Classification System (HFACS): (1) Requirements, policies, and design processes, (2) Information resources and support, (3) Allocation of attention, (4) Cognitive overload, (5) Environmentally induced perceptual changes, (6) Misperception and misinterpretation of displayed information, (7) Spatial disorientation, and (8) Displays and controls.

Kritina Holden↗

NASA NTRS1988

Diagnostics in the Extendable Integrated Support Environment (EISE)

Extendable Integrated Support Environment (EISE) is a real-time computer network consisting of commercially available hardware and software components to support systems level integration, modifications, and enhancement to weapons systems. The EISE approach offers substantial potential savings by eliminating unique support environments in favor of sharing common modules for the support of operational weapon systems. An expert system is being developed that will help support diagnosing faults in this network. This is a multi-level, multi-expert diagnostic system that uses experiential knowledge relating symptoms to faults and also reasons from structural and functional models of the underlying physical model when experiential reasoning is inadequate. The individual expert systems are orchestrated by a supervisory reasoning controller, a meta-level reasoner which plans the sequence of reasoning steps to solve the given specific problem. The overall system, termed the Diagnostic Executive, accesses systems level performance checks and error reports, and issues remote test procedures to formulate and confirm fault hypotheses.

Brink, James R.↗

DOE OSTI2016

Accelerated Monte Carlo Fission Source Convergence with Fission Matrix and Kernel Density Estimators

Accurate solution of the k-eigenvalue form of the Boltzmann radiation transport equation is required in many application areas, including nuclear reactor analysis and criticality safety. Monte Carlo calculations are free of the discretization errors inherent to deterministic methods and therefore offer the most accurate solutions. However, converging the fission source can be difficult for many problems, resulting in either a substantial computational overhead or potential inaccuracies that negate many of the benefits of using Monte Carlo methods. Difficulty in converging the fission source occurs for two distinct reasons. The first is the existence of a high dominance ratio in the problem (i.e. the largest and second largest eigenvalues have approximately the same magnitude). The second difficulty arises due to undersampling of the fission source because an insufficient number of particle histories are simulated. The first difficulty is shared by deterministic solvers when using power iteration, while the second difficulty is unique to Monte Carlo solvers. In practice, both difficulties may be present in the same problem, compounding the difficulty in achieving a converged distribution. In this paper, we consider a new approach to accelerate the convergence of the fission source based on combining the use of fission matrix methods with kernel density estimators (KDEs). It has been observed that deterministic fission matrix methods show the potential to accelerate the convergence of the fission source in Monte Carlo criticality calculations but may introduce significant additional noise for difficult problems. In this paper, we have demonstrated the use of a KDE approach in combination with the fission matrix acceleration. Although the addition of the KDE initially slows the convergence of the fission matrix acceleration, it decreases the magnitude of the noise while still offering significantly improved convergence relative to analog Monte Carlo. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Rapid wavefield forecasting for earthquake early warning via deep sequence to sequence learning

We propose a deep learning model, WaveCastNet, to forecast high-dimensional wavefields. WaveCastNet integrates a convolutional long expressive memory architecture into a sequence-to-sequence forecasting framework, enabling it to model long-term dependencies and multiscale patterns in both space and time. By sharing weights across spatial and temporal dimensions, WaveCastNet requires significantly fewer parameters than more resource-intensive models such as transformers, resulting in faster inference times. Crucially, WaveCastNet also generalizes better than transformers to rare and critical seismic scenarios, such as high-magnitude earthquakes. Here, we show the ability of the model to predict the intensity and timing of destructive ground motions in real time, using simulated data from the San Francisco Bay Area. Furthermore, we demonstrate its zero-shot capabilities by evaluating WaveCastNet on real earthquake data. Our approach does not require estimating earthquake magnitudes and epicenters, steps that are prone to error in conventional methods, nor does it rely on empirical ground-motion models, which often fail to capture strongly heterogeneous wave propagation effects.

Geophysics↗

DOE OSTI2023

A database of hourly wind speed and modeled generation for US wind plants based on three meteorological models

Abstract In 2022, wind generation accounted for ~10% of total electricity generation in the United States. As wind energy accounts for a greater portion of total energy, understanding geographic and temporal variation in wind generation is key to many planning, operational, and research questions. However, in-situ observations of wind speed are expensive to make and rarely shared publicly. Meteorological models are commonly used to estimate wind speeds, but vary in quality and are often challenging to access and interpret. The Plant-Level US multi-model WIND and generation (PLUSWIND) data repository helps to address these challenges. PLUSWIND provides wind speeds and estimated generation on an hourly basis at almost all wind plants across the contiguous United States from 2018–2021. The repository contains wind speeds and generation based on three different meteorological models: ERA5, MERRA2, and HRRR. Data are publicly accessible in simple csv files. Modeled generation is compared to regional and plant records, which highlights model biases and errors and how they differ by model, across regions, and across time frames.

17 WIND ENERGY↗

DOE OSTI2023

Combining cosmic shear data with correlated photo-z uncertainties: constraints from DESY1 and HSC-DR1

An accurate calibration of the source redshift distribution p(z) is a key aspect in the analysis of cosmic shear data. This, one way or another, requires the use of spectroscopic or high-quality photometric samples. However, the difficulty to obtain colour-complete spectroscopic samples matching the depth of weak lensing catalogs means that the analyses of different cosmic shear datasets often use the same samples for redshift calibration. This introduces a source of statistical and systematic uncertainty that is highly correlated across different weak lensing datasets, and which must be accurately characterised and propagated in order to obtain robust cosmological constraints from their combination. In this paper we introduce a method to quantify and propagate the uncertainties on the source redshift distribution in two different surveys sharing the same calibrating sample. The method is based on an approximate analytical marginalisation of the p(z) statistical uncertainties and the correlated marginalisation of residual systematics. We apply this method to the combined analysis of cosmic shear data from the DESY1 data release and the HSC-DR1 data, using the COSMOS 30-band catalog as a common redshift calibration sample. We find that, although there is significant correlation in the uncertainties on the redshift distributions of both samples, this does not change the final constraints on cosmological parameters significantly. The same is true also for the impact of residual systematic uncertainties from the errors in the COSMOS 30-band photometric redshifts. Additionally, we show that these effects will still be negligible in Stage-IV datasets. Finally, the combination of DESY1 and HSC-DR1 allows us to constrain the "clumpiness" parameter to S 8 = ${0.768}_{-0.017}^{+0.021}$. This corresponds to a ~√(2) improvement in uncertainties with respect to either DES or HSC alone.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2018

A Hierarchical Multi-Agent Based Anomaly Detection for Wide-Area Protection in Smart Grid

Future smart grid capabilities provide assurance to expand the advanced information and communication technologies to evolve into densely interconnected cyber physical system. Remedial Action Scheme (RAS), widely used for wide-area protection, relies on the interconnected networks and data sharing devices, which are exposed to the multitude of vulnerabilities. This paper presents our proposed approach to developing multi-agent based RAS scheme against the system-aware stealthy cyber-attacks. Specifically, we propose the two-level hierarchical architecture which consists of distributed local RAS controllers (RAScs) as local agents, operating at different zones/ areas, which are constantly monitored by an overseer, the central agent. The local controllers receive local and randomly changing outside zonal measurements and cyclically forwards to the overseer. The overseer identifies the corrupted controller using the anomaly detection algorithm which processes the measurements coming from the local controllers, compute measurement errors using local and outside zonal measurements, perform validation checks, and finally detect anomalies based on the two-step verification. Next, as a proof of concept, we have implemented and validated the proposed methodology in cyber physical environment at Iowa State’s PowerCyber testbed. We have also implemented the coordinated attack vectors which involve corrupting the local controller and later performing stealthy attacks on the system’s generator. We have evaluated its performance during the online testing in terms of detection rate and Iatency. The experimental results show that it is efficient in detecting different classes of attacks, including ramp and pulse attacks.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2011

DETAILED CHEMICAL ABUNDANCES OF FOUR STARS IN THE UNUSUAL GLOBULAR CLUSTER PALOMAR 1

Detailed chemical abundances for 21 elements are presented for four red giants in the anomalous outer halo globular cluster Palomar 1 (R{sub GC} = 17.2 kpc, Z = 3.6 kpc) using high-resolution (R = 36, 000) spectra from the High Dispersion Spectrograph on the Subaru Telescope. Pal 1 has long been considered unusual because of its low surface brightness, sparse red giant branch, young age, and its possible association with two extragalactic streams of stars. This paper shows that its chemistry further confirms its unusual nature. The mean metallicity of the four stars, [Fe/H] = -0.60 {+-} 0.01, is high for a globular cluster so far from the Galactic center, but is low for a typical open cluster. The [{alpha}/Fe] ratios, though in agreement with the Galactic stars within the 1{sigma} errors, agree best with the lower values in dwarf galaxies. No signs of the Na/O anticorrelation are detected in Pal 1, though Na appears to be marginally high in all four stars. Pal 1's neutron-capture elements are also unusual: its high [Ba/Y] ratio agrees best with dwarf galaxies, implying an excess of second-peak over first-peak s-process elements, while its [Eu/{alpha}] and [Ba/Eu] ratios show that Pal 1's contributions from the r-process must have differed in some way from normal Galactic stars. Therefore, Pal 1 is unusual chemically, as well in its other properties. Pal 1 shares some of its unusual abundance characteristics with the young clusters associated with the Sagittarius dwarf galaxy remnant and the intermediate-age LMC clusters, and could be chemically associated with the Canis Majoris overdensity; however, it does not seem to be similar to the Monoceros/Galactic Anticenter Stellar Stream.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Inverter Model Validation and Calibration Using Phasor Measurement Unit Data

As the penetration of inverter-based renewable energy resources increases in the power grid, especially at the distribution and microgrid levels, the need to accurately represent them in planning studies increases as well. However, due to the lack of well-established standard procedures, and vendor reluctance towards the detailed sharing of proprietary models, automated dynamic model validation and parameter calibration tools for inverter based resources (IBRs) remain scarce. This work presents a model validation and parameter calibration platform for representing IBRs with generic phasor-domain models. Phasor measurements of power system events are used for continuous validation using the data playback method, and model parameters are re-calibrated if a significant mismatch between measurements and model response is observed. Unique features of the proposed platform include- (a) an iterative Bayesian optimization approach towards parameter calibration to address a possible mismatch between the structures of generic models implemented in simulation softwares and actual commercial inverters, (b) error metrics designed to account for a possible mismatch between the time resolution of simulation and measurements, and (c) analysis of the measurement-simulation mismatch to provide guidance to engineering personnel regarding model shortcomings. The performance of the platform has been illustrated using both simulated data and field measurements to validate/calibrate inverter models in GridLAB-D.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRSDate not supplied

A Preliminary Development of The Intelligent Change Detection System (ICDS): Using Machine Learning to Combat Change Blindness in Remote Operation Environments

The emergence of Advance Air Mobility (AAM) will increase the number and types of aerial vehicles operating in shared airspaces, which will subsequently affect the amount of actionable data that ground control station operators (GCSOs) will be expected to manage. In this environment, GCSOs are particularly susceptible to the visual perceptual phenomenon known as change blindness, in which a stimulus undergoes a change without the change being noticed by its observer. A machine agent designed to detect change blindness and mitigate the effects could improve human agent performance in a data-saturated remote operations environment. The objective of this paper is to describe a proof-of-concept system architecture that integrates real-time eye tracking and vehicle telemetry data to prevent human-agent errors resulting from change blindness while operating aircraft from a remote ground control station (GCS).

Real-Time Streaming Data Architecture↗

NASA NTRSDate not supplied

A Preliminary Development of The Intelligent Change Detection System (ICDS): Using Machine Learning to Combat Change Blindness in Remote Operation Environments

Real-Time Streaming Data Architecture↗

DOE OSTI2017

Unveiling a Drift Resistant Cryptotope within Marburgvirus Nucleoprotein Recognized by Llama Single-Domain Antibodies

Marburg virus (MARV) is a highly lethal hemorrhagic fever virus that is increasingly re-emerging in Africa, has been imported to both Europe and the US, and is also a Tier 1 bioterror threat. As a negative sense RNA virus, MARV has error prone replication which can yield progeny capable of evading countermeasures. To evaluate this vulnerability, we sought to determine the epitopes of 4 llama single-domain antibodies (sdAbs or VHH) specific for nucleoprotein (NP), each capable of forming MARV monoclonal affinity reagent sandwich assays. Here, we show that all sdAb bound the C-terminal region of NP, which was produced recombinantly to derive X-ray crystal structures of the three best performing antibody-antigen complexes. The common epitope is a trio of alpha helices that form a novel asymmetric basin-like depression that accommodates each sdAb paratope via substantial complementarity-determining region (CDR) restructuring. Shared core contacts were complemented by unique accessory contacts on the sides and overlooks of the basin yielding very different approach routes for each sdAb to bind the antigen. The C-terminal region of MARV NP was unable to be crystallized alone and required engagement with sdAb to form crystals suggesting the antibodies acted as crystallization chaperones. While gross structural homology is apparent between the two most conserved helices of MARV and Ebolavirus, the positions and morphologies of the resulting basins were markedly different. Naturally occurring amino acid variations occurring in bat and human Marburgvirus strains all mapped to surfaces distant from the predicted sdAb contacts suggesting a vital role for the NP interface in virus replication. As an essential internal structural component potentially interfacing with a partner protein it is likely the C-terminal epitope remains hidden or “cryptic” until virion disruption occurs. Conservation of this epitope over 50 years of Marburgvirus evolution should make these sdAb useful foundations for diagnostics and therapeutics resistant to drift.

60 APPLIED LIFE SCIENCES↗