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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 OSTI2021

Santa Barbara Desalination Digital Twin Technical Report

A digital twin is a computer model that has sufficient breadth and fidelity to enable diagnostic and predictive analyses for outputs of interest. We have constructed a digital twin of the SB desal plant using the ProteusLib software developed for NAWI under task 4.2.2, and specifically the ProteusLib models of pumps, filters, mixers, splitters, and reverse osmosis units and a seawater property model. The steps needed to configure this digital twin with the real conditions of the SB desal plant are: (1) Data reconciliation, which is gathering the data and plant connectivity and ensure that all relevant values are present and in the correct units and validating the data using material and energy balances, and correct for errors, gaps, or deviations; (2) Parameter estimation, which is matching model parameters with data from previous step, filling missing parameters with initial estimates, then iteratively refining estimated values. Once we completed the digital twin, we used the optimization capabilities of ProteusLib to compute outputs of interest over a chosen range of inputs. The primary output of interest to the owners of the plant is its specific energy consumption (kWh/acre-foot). The remainder of this report will provide more detail on the data reconciliation, parameter estimation, and analyses we performed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

A data-driven framework for permeability prediction of natural porous rocks via microstructural characterization and pore-scale simulation

Understanding the microstructure–property relationships of porous media is of great practical significance, based on which macroscopic physical properties can be directly derived from measurable microstructural informatics. However, establishing reliable microstructure–property mappings in an explicit manner is difficult, due to the intricacy, stochasticity, and heterogeneity of porous microstructures. In this paper, a data-driven computational framework is presented to investigate the inherent microstructure–permeability linkage for natural porous rocks, where multiple techniques are integrated together, including microscopy imaging, stochastic reconstruction, microstructural characterization, pore-scale simulation, feature selection, and data-driven modeling. A large number of 3D digital rocks with a wide porosity range are acquired from microscopy imaging and stochastic reconstruction techniques. A broad variety of morphological descriptors are used to quantitatively characterize pore microstructures from different perspectives, and they compose the raw feature pool for feature selection. Here high-fidelity lattice Boltzmann simulations are conducted to resolve fluid flow passing through porous media, from which reliable permeability references are obtained. The optimal feature set that best represents permeability is identified through a performance-oriented feature selection process, upon which a cost-effective surrogate model is rapidly fitted to approximate the microstructure-permeability mapping via data-driven modeling. This surrogate model exhibits great advantages over empirical/analytical formulas in terms of prediction accuracy and generalization capacity, which can predict reliable permeability values spanning four orders of magnitude. Besides, feature selection also greatly enhances the interpretability of the data-driven prediction model, from which new insights into the mechanism of how microstructural characteristics determine intrinsic permeability are obtained.

58 GEOSCIENCES↗
DOE OSTI2014

A digital map of the high center (HC) and low center (LC) polygon boundaries delineated from high-resolution LiDAR data for Utqiagvik (Barrow), Alaska

This dataset represents a map of the high center (HC) and low center (LC) polygon boundaries delineated from high resolution LiDAR data for the arctic coastal plain at Barrow, Alaska, presented as Figure 3a in the publication by Gangodagamage et al. (2014). The polygon troughs are considered as the surface expression of the ice-wedges. The troughs are in lower elevations than the interior polygon. The trough widths were initially identified from LiDAR data, and the boundary between two polygons assumed to be located along the lowest elevations on trough widths between them. Included are the components of a shapefile, PNG files, and the file-level metadata. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Wildlife Densities and Habitat Use Across Temporal and Spatial Scales on the Mid-Atlantic Outer Continental Shelf. Final Report to the Department of Energy EERE Wind & Water Power Technologies Office

The Mid-Atlantic Baseline Studies Project helped address environmental barriers to offshore wind energy development in the mid-Atlantic region by providing regulators, developers, and other stakeholders with comprehensive baseline ecological data and analyses. Project funders and collaborators from a range of academic institutions, non-governmental organizations, federal agencies, foundations, and private companies came together to study bird, sea turtle, and marine mammal distributions, densities, and movements on the mid-Atlantic Outer Continental Shelf between 2012 and 2014. Specific project activities and goals included the following: (1) Conduct standardized surveys to quantify bird, sea turtle, and marine mammal densities seasonally and annually throughout the study region and identify important habitat use or aggregation areas. (2) Develop statistical models to help understand the drivers of wildlife distribution and abundance patterns. (3) Use individual tracking data for several focal bird species to provide information on population connectivity and individual movements that is complementary to survey data. (4) Identify species that are likely to be exposed to offshore wind energy development activities in the mid-Atlantic study area. (5) Develop U.S.-based technological resources and assessment methods for future monitoring efforts, including a comparison of high resolution digital video aerial surveys to boat-based surveys. (6) Help meet data needs associated with National Environmental Policy Act (NEPA), Marine Mammal Protection Act, and Endangered Species Act requirements, by contributing several years of data and analysis towards future Environmental Impact Statements. This report consists of six parts: Project overview (executive summary and Chapters 1-2); Examining wildlife distributions and relative abundance from a digital video aerial survey platform (Chapters 3-6); Examining wildlife distributions and abundance using boat-based surveys (Chapters 7-12); Integrating data across survey platforms (Chapters 13-19); Individual movements and habitat use for focal bird species (Chapters 20-25); and Nocturnal avian migration monitoring (Chapters 26-27). Boat-based and digital video aerial surveys each had specific advantages and disadvantages, but were largely complementary (Chapters 1, 5, 13-14). Digital aerial surveys were particularly useful for covering offshore areas at broad scales, where general distributions of taxonomic groups were a priority; boat surveys could provide more detailed data on species identities and behaviors, but were more limited in geographic scope due to their slower survey pace. The mid-Atlantic study area was important for wintering and breeding taxa, and its location also made it a key migratory corridor. There was considerable variation in species composition and spatial patterns by season, largely driven by dynamic environmental conditions (Chapters 12, 15, and 20-22). Habitat gradients in nearshore waters, however, were reliable influences on productivity and patterns of species distributions and abundance. Areas within about 30-40 km of the coast offshore of the mouths of Chesapeake and Delaware Bays, as well as to the south of Delaware Bay along the coast, were consistent hotspots of abundance and species diversity, regardless of survey methodology or analytical approach (Chapters 2, 12, 17). Inter-annual variation was substantial, and the importance of certain environmental variables in predicting animal distributions indicates that these species may well respond to future environmental shifts brought about by anthropogenic effects and climatic change. This study is an important first step, however, towards understanding how bird, marine mammal, and sea turtle populations in the mid-Atlantic may be exposed to offshore wind energy development and other anthropogenic activities. The results of this study provide insight to help address environmental permitting requirements for current and future offshore development projects, and serve as a starting point for more site-specific studies, risk analyses, and evaluation of potential measures to avoid and minimize those risks.

17 WIND ENERGY↗
DOE OSTI2023

Advanced Monitoring and Control in the ANL METL Facility Using an Engineering Digital Twin

The potential benefits of using an engineering digital twin to achieve greater autonomy for monitoring and control functions in advanced reactors was investigated for the Mechanisms Engineering Test Loop (METL) liquid sodium facility at Argonne National Laboratory. The METL sodium purification system served as a representative system as it requires significant human in-the-loop interaction to accomplish its design function. The objective was to demonstrate how real-time operation could be automated while preserving oversight of the operator for ensuring that the system design functions are met. A digital twin model of the purification system was developed for both the cold trap purification loop and plugging meter diagnostic loop using information from the METL piping and instrumentation diagram (P&ID). Automated monitoring and diagnosis of component degradation in the METL facility was demonstrated in tests using the PRO-AID health monitoring software with the digital twin model incorporated in the library of components. Component failures were introduced and were successfully diagnosed in real time. These tests serve to demonstrate an advanced monitoring capability able to differentiate sensor degradation from component degradation, to generate a rank ordering of probabilities of different failure mechanisms that serves to circumvent the false alarm problem with current anomaly detection methods, and how facility monitoring can be transformed from anomaly detection to identification of a specific fault. Automated control of the purification system was demonstrated through simulations that exercised a model predictive controller designed using the digital twin model. Results of these simulations compared favorably with experimental data showing very good reference tracking response with negligible overshoot. In conclusion, these pilot tests and simulations successfully demonstrated the use of a digital twin for improved automation of monitoring and control. It was shown how the digital twin enables switching between control modes from cold trap operation where impurities are removed to plugging meter operation where impurity concentrations are measured.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Development of a Data Overflow Protection System for Super-Kamiokande to Maximize Data from Nearby Supernovae

Neutrinos from very nearby supernovae, such as Betelgeuse, are expected to generate more than ten million events over 10 s in Super-Kamokande (SK). At such large event rates, the buffers of the SK analog-to-digital conversion board (QBEE) will overflow, causing random loss of data that are critical for understanding the dynamics of the supernova explosion mechanism. In order to solve this problem, two new data-acquisition (DAQ) modules were developed to aid in the observation of very nearby supernovae. The first of these, the SN module, is designed to save only the number of hit photomultiplier tubes during a supernova burst and the second, the Veto module, prescales the high-rate neutrino events to prevent the QBEE from overflowing based on information from the SN module. In the event of a very nearby supernova, these modules allow SK to reconstruct the time evolution of the neutrino event rate from beginning to end using both QBEE and SN module data. This paper presents the development and testing of these modules together with an analysis of supernova-like data generated with a flashing laser diode. We demonstrate that the Veto module successfully prevents DAQ overflows for Betelgeuse-like supernovae as well as the long-term stability of the new modules. During normal running the Veto module is found to issue DAQ vetos a few times per month resulting in a total dead-time less than 1 ms, and does not influence ordinary operations. Additionally, using simulation data we find that supernovae closer than 800 pc will trigger the Veto module, resulting in a prescaling of the observed neutrino data.

F20 Instrumentation and technique↗
DOE OSTI2026

A Comparative Analysis of Infrastructure-Based Perception Sensors for Intelligent Transportation Systems

The rise of privatized and public investment in smart city infrastructure and intelligent transportation systems has generated a heightened demand for perception sensors that effectively track and detect objects while being reliable in diverse weather and lighting conditions. This growing demand for perception sensors has accelerated their development and enhanced their capabilities. With these new capabilities, it is challenging to determine the most suitable sensing unit to use in each situation. Therefore, it is essential to have a comprehensive understanding of the benefits and limitations of each sensing unit to effectively leverage their capabilities. The purpose of this paper is to provide a detailed evaluation of various perception sensors. Additionally, this paper will demonstrate the benefits of combining multiple perception sensors, which complement each other by addressing data gaps inherent to single-sensor systems, to facilitate the creation of a digital twin that models the real world. The Infrastructure, Perception, and Control (IPC) team will conduct data analysis using data collected through field testing at traffic intersections in Colorado Springs, Colorado, to make comparisons between sensors. This research aims to provide clear and concise information about modern perception systems, which will support the development of intelligent transportation systems.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

FAIR for AI: An interdisciplinary and international community building perspective

A foundational set of findable, accessible, interoperable, and reusable (FAIR) principles were proposed in 2016 as prerequisites for proper data management and stewardship, with the goal of enabling the reusability of scholarly data. The principles were also meant to apply to other digital assets, at a high level, and over time, the FAIR guiding principles have been re-interpreted or extended to include the software, tools, algorithms, and workflows that produce data. FAIR principles are now being adapted in the context of AI models and datasets. Here, we present the perspectives, vision, and experiences of researchers from different countries, disciplines, and backgrounds who are leading the definition and adoption of FAIR principles in their communities of practice, and discuss outcomes that may result from pursuing and incentivizing FAIR AI research. The material for this report builds on the FAIR for AI Workshop held at Argonne National Laboratory on June 7, 2022.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Data center growth in the United States: Decoupling the demand for services from electricity use

Data centers are energy intensive buildings that have grown in size and number to meet the increasing demands of a digital economy. This paper presents a bottom-up model to estimate data center electricity demand in the United States over a 20 year period and examines observed and projected electricity use trends in the context of changing data center operations. Results indicate a rapidly increasing electricity demand at the turn of the century that has significantly subsided to a nearly steady annual electricity use of about 70 billion kWh in recent years. While data center workloads continue to grow exponentially, comparable increases in electricity demand have been avoided through the adoption of key energy efficiency measures and a shift towards large cloud-based service providers. Alternative projections from the model illustrate the wide range in potential electricity that could be consumed to support data centers, with the US data center workload demand estimated for 2020 requiring a total electricity use that varies by about 135 billion kWh, depending on the adoption rate of efficiency measures during this decade. While recent improvements in data center energy efficiency have been a success, the growth of data center electricity use beyond 2020 is uncertain, as modeled trends indicate that the efficiency measures of the past may not be enough for the data center workloads of the future. The results show that successful stabilization of data center electricity will require new innovations in data center efficiency to further decouple electricity demand from the ever-growing demand for data center services.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Big Data Analytics for Scanning Transmission Electron Microscopy Ptychography

Electron microscopy is undergoing a transition; from the model of producing only a few micrographs, through the current state where many images and spectra can be digitally recorded, to a new mode where very large volumes of data (movies, ptychographic and multi-dimensional series) can be rapidly obtained. In this paper, we discuss the application of so-called “big-data” methods to high dimensional microscopy data, using unsupervised multivariate statistical techniques, in order to explore salient image features in a specific example of BiFeO 3 domains. Remarkably, k-means clustering reveals domain differentiation despite the fact that the algorithm is purely statistical in nature and does not require any prior information regarding the material, any coexisting phases, or any differentiating structures. While this is a somewhat trivial case, this example signifies the extraction of useful physical and structural information without any prior bias regarding the sample or the instrumental modality. Further interpretation of these types of results may still require human intervention. Finally, however, the open nature of this algorithm and its wide availability, enable broad collaborations and exploratory work necessary to enable efficient data analysis in electron microscopy.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Digital Infrastructure Migration Framework Report

This document presents a full-scope Digital Infrastructure implementation and associated lifecycle support recommendations that enable a plant life of 80+ years. Specific technologies and software applications are researched, developed, selected, implemented, and then integrated by utilities to enhance safety, reliability, and economic performance such that the result provides much more than the sum of its parts. Specific selection of these technologies is driven by business case analyses which are utility, station, and unit specific.

42 ENGINEERING↗
DOE OSTI2026

A Real2Sim Digital Twin Pipeline for Photorealistic Robot Simulation: Evaluating VLA Policy Deployment on a Bimanual Mobile Robot

Digital twins that are automatically constructed from robot sensor data offer a promising pathway for scalable Real2Sim and Sim2Real transfer. However, it remains an open question whether photorealistic reconstruction alone is sufficient to support reliable deployment of vision-language-action (VLA) policies. We present a generative-AI-assisted Real2Sim pipeline that generates simulation-ready digital twins from real-world RGB observations with minimal manual intervention. The pipeline uses prompted segmentation to isolate scene components and a generative 3D model to directly produce simulation assets, eliminating the need for traditional multi-view reconstruction or manual 3D modeling.\r\nTo evaluate simulation fidelity, we deploy and compare policies from two VLA models in both the real robot and the reconstructed\r\nsimulation under identical tasks and initial conditions. We compare joint-level action trajectories and analyze how divergence evolves over time in closed-loop execution. Although the reconstructed environments are visually accurate, we observe increasing trajectory divergence during closedloop operation. These results indicate that photorealistic reconstruction alone is insufficient to preserve closed-loop control behavior\r\nin VLA policies, particularly in contact-rich manipulation settings where small perceptual errors compound over time.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

The Completed Sloan Digital Sky Survey IV Extended Baryon Oscillation Spectroscopic Survey: The Damped Lyα Systems Catalog

We present the characteristics of the damped Lyα (DLA) systems found in data release DR16 of the extended Baryon Oscillation Spectroscopic Survey of the Sloan Digital Sky Survey. The DLAs were identified using the convolutional neural network of Parks et al. (2018). A total of 117,458 absorber candidates were found with 2 ≤ $z_{DLA}$ ≤ 5.5 and 19.7 ≤ log(N(H I )/cm -2 ) ≤ 22, including 57,136 DLA candidates with log(N(H I )/cm -2 ) ≥ 20.3. Mock quasar spectra were used to estimate the DLA detection efficiency and the purity of the resulting catalog. Restricting the quasar sample to bright forests, i.e., those with mean forest fluxes $\bar{f_{λ}}$ > 2 × 10 -19 W m -2 nm -1 , the efficiency and purity are greater than 90% for DLAs with column densities in the range 20.1 ≤ log(N(H I )/cm -2 ) ≤ 22.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

A probabilistic graphical model foundation for enabling predictive digital twins at scale

A unifying mathematical formulation is needed to move from one-off digital twins built through custom implementations to robust digital twin implementations at scale. This work proposes a probabilistic graphical model as a formal mathematical representation of a digital twin and its associated physical asset. We create an abstraction of the asset–twin system as a set of coupled dynamical systems, evolving over time through their respective state spaces and interacting via observed data and control inputs. The formal definition of this coupled system as a probabilistic graphical model enables us to draw upon well-established theory and methods from Bayesian statistics, dynamical systems and control theory. The declarative and general nature of the proposed digital twin model make it rigorous yet flexible, enabling its application at scale in a diverse range of application areas. Here, we demonstrate how the model is instantiated to enable a structural digital twin of an unmanned aerial vehicle (UAV). The digital twin is calibrated using experimental data from a physical UAV asset. Its use in dynamic decision-making is then illustrated in a synthetic example where the UAV undergoes an in-flight damage event and the digital twin is dynamically updated using sensor data. The graphical model foundation ensures that the digital twin calibration and updating process is principled, unified and able to scale to an entire fleet of digital twins.

42 ENGINEERING↗
DOE OSTI2015

The alfalfa “almost darks” campaign: Pilot VLA HI observations of five high mass-to-light ratio systems

We present new Very Large Array (VLA) H i spectral line imaging of five sources discovered by the ALFALFA extragalactic survey. These targets are drawn from a larger sample of systems that were not uniquely identified with optical counterparts during ALFALFA processing, and as such have unusually high H i mass to light ratios. The candidate “Almost Dark” objects fall into four broad categories: (1) objects with nearby H i neighbors that are likely of tidal origin; (2) objects that appear to be part of a system of multiple H i sources, but which may not be tidal in origin; (3) objects isolated from nearby ALFALFA H i detections, but located near a gas-poor early type galaxy; (4) apparently isolated sources, with no object of coincident redshift within ∼400 kpc. Roughly 75% of the 200 objects without identified counterparts in the α.40 database (Haynes et al. 2011) fall into category 1 (likely tidal), and were not considered for synthesis follow-up observations. The pilot sample presented here (AGC193953, AGC208602, AGC208399, AGC226178, and AGC233638) contains the first five sources observed as part of a larger effort to characterize H i sources with no readily identifiable optical counterpart at single dish resolution (3.′5). These objects span a range of H i mass [7.41 < log(M{sub Hi}) < 9.51] and H i mass to B-band luminosity ratios (3 < M{sub Hi}/L{sub B} < 9). We compare the H i total intensity and velocity fields to optical imaging drawn from the Sloan Digital Sky Survey and to ultraviolet imaging drawn from archival GALEX observations. Four of the sources with uncertain or no optical counterpart in the ALFALFA data are identified with low surface brightness optical counterparts in Sloan Digital Sky Survey imaging when compared with VLA H i intensity maps, and appear to be galaxies with clear signs of ordered rotation in the H i velocity fields. Three of these are detected in far-ultraviolet GALEX images, a likely indication of star formation within the last few hundred Myrs. One source (AGC208602) is likely tidal in nature, associated with the NGC 3370 group. Consistent with previous efforts, we find no “dark galaxies” in this limited sample. However, the present observations do reveal complex sources with suppressed star formation, highlighting both the observational difficulties and the necessity of synthesis follow-up observations to understand these extreme objects.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

A superconducting nanowire binary shift register

We present a design for a superconducting nanowire binary shift register, which stores digital states in the form of circulating supercurrents in high-kinetic-inductance loops. Adjacent superconducting loops are connected with nanocryotrons, three-terminal electrothermal switches, and fed with an alternating two-phase clock to synchronously transfer the digital state between the loops. A two-loop serial-input shift register was fabricated with thin-film NbN and a bit error rate of less than 10 –4 was achieved, when operated at a maximum clock frequency of 83 MHz and in an out-of-plane magnetic field of up to 6 mT. A shift register based on this technology offers an integrated solution for low-power readout of superconducting nanowire single photon detector arrays and is capable of interfacing directly with room-temperature electronics and operating unshielded in high magnetic field environments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

MuSIKAL: Multiphysics Simulations and Knowledge Discovery through AI/ML Technologies

Under the MuSiKAL project, we developed a framework for a coastal digital twin (DT) platform capable of integrating diverse data resources, configuring multiscale model simulations, performing SciML‐accelerated predictions, with applications primarily driven by storm surge and heavily rainfall events impacting the Gulf Coast of the U.S.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Monitoring for Additive Manufacturing Technologies: Report on Progress, Achievements, and Limitations of Monitoring Techniques

The Transformational Challenge Reactor (TCR) program is leveraging additive manufacturing (AM) technologies to produce multiple nuclear components to be assembled into a fully functional microreactor core. AM was selected as the main manufacturing technology of choice for TCR because it has the potential to disrupt the nuclear industry on two fronts: (1) it enables the manufacturing of very complex geometries with optimized and tailored material properties for the intended use of the component, opening up new options for reactor designs, and (2) it allows for a better understanding of the manufacturing process through real-time in situ monitoring, data analytics, and artificial intelligence that can lead to a streamlined qualification and certification process. Within TCR, the development and deployment of a digital platform aims at addressing the latter opportunity. As part of this effort, the collection of pedigree data sets is vital, should these data be generated before, during, or after the manufacturing process. This report focuses on the collection of manufacturing process data using systems instrumentation and monitoring. It presents an inventory of the various monitoring modalities installed on the manufacturing systems by the machine manufacturer or specifically designed by our team to fill information gaps. It also provides details on other relevant data streams available and leverageable to evaluate the manufacturing process on all classes of AM systems investigated during the first year of this program. Through examples, the report gives an overview of the data collected and presents a path forward for the digital platform.

42 ENGINEERING↗