Search NASA⌕ Search

SEARCH · Search NASA

Results for “DIGITAL INTEGRATORS”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 415 records · Page 23

SDSS-IV MaNGA: pyPipe3D Analysis Release for 10,000 Galaxies

We present here the analysis performed using the pyPipe3D pipeline for the final MaNGA data set included in the Sloan Digital Sky Survey data release 17. This data set comprises more than 10,000 individual data cubes, being the integral field spectroscopic (IFS) galaxy survey with the largest number of galaxies. pyPipe3D processes the IFS data cubes to extract spatially resolved spectroscopic properties of both the stellar population and the ionized gas emission lines. A brief summary of the properties of the sample and the characteristics of the analyzed data are included. The article provides details of: (i) the analysis performed; (ii) a description of the pipeline; (iii) the adopted stellar population library; (iv) the morphological and photometric analysis; (v) the adopted data model for the spatially resolved properties derived; and (vi) the individual integrated and characteristic galaxy properties included in the final catalog. Comparisons with the results from a previous version of the pipeline for earlier data releases and from other tools using this data set are included. A practical example of how to use the full data set and the final catalog illustrates how to handle the delivered product. Our full analysis can be accessed and downloaded from our web page.

79 ASTRONOMY AND ASTROPHYSICS↗

VisMetHack2022: Visualizing winds and surface variables from the ECMWF IFS 1-km nature run

This data collection was contributed to the Visualisation Hackathon 2022 (#VisMetHack2022), in conjunction with the Using ECMWF's Forecasts (UEF2022) workshop. The European Center for Medium-Range Weather Forecasts (ECMWF) and the Oak Ridge National Laboratory (ORNL) are pleased to announce access to the data collection from global 1-km nature run (NR) simulations using the Integrated Forecast System (IFS) with explicit convection. We invite you to join us in exploring this precursor to a digital twin of the earth! The NR simulations reveal unprecedented detail of the earth’s atmosphere, and the then outgoing Editor-in-Chief of AGU JAMES commended the project as one of “stunning ambitions,” enabled by computational capacity at scale. The project also won the 2020 HPCwire Readers Choice Award for Best Use of HPC in Physical Sciences. A set of two NR seasonal simulations have been completed, one corresponding to the northern hemispheric winter months (NDJF) and the other for the North Atlantic tropical cyclone season (ASO). The project used the Summit supercomputer at the Oak Ridge Leadership Computing Facility (OLCF). The simulations were facilitated with an INCITE award from the US Department of Energy Office of Science. For the first seasonal run of four months (NDJF), the hydrostatic IFS model was initialized at 00Z on 1 November 2018. The NR for the TC season (AS) was initialized at 00Z on 1 August 2019. The NR simulations were constrained only by sea surface temperatures (SST) at the lower boundary. The IFS output was saved every 3 hours. After feedback and interest from the scientific community, the simulations were rerun for four specific extreme events, with output every 15 minutes. The special cases include a tropical cycle and three severe storm events over the continental USA.

54 ENVIRONMENTAL SCIENCES↗

Data Centers and Digital Assurance Workshop 3 – Mitigations for Digital Assurance Risks

The third session of the TADA (Technical Assistance for Digital Assurance) Data Centers Cohort, held on November 18, 2025, focused on developing mitigation strategies for digital assurance risks identified in previous workshops. Hosted by Idaho National Laboratory (INL) and ScottMadden, the session emphasized the application of Cyber-Informed Engineering (CIE) to data center infrastructure, particularly at the utility–data center interface. Participants revisited and ranked key digital assurance risks, including architecture and interface weaknesses, governance gaps, and AI-enabled threats. The workshop introduced the 12 principles of CIE, advocating for consequence-focused design, engineered controls, and secure information architecture to proactively reduce cyber-physical vulnerabilities. These principles were applied to critical data center systems such as power distribution, UPS, cooling, SCADA/BMS, and grid-forming batteries. The session also addressed governance challenges at the interconnection boundary, highlighting the need for clear roles in telemetry sharing, firmware management, and trip settings. Special attention was given to emerging risks from behind-the-meter (BTM) generation, including reverse-power flow and the integration of small modular reactors (SMRs), which shift data centers from large loads to complex generation nodes. Participants explored how interconnection agreements can serve as enforceable instruments for digital assurance, and reviewed gaps in current standards such as NERC CIP, IEC 62443, and IEEE 1547. The workshop concluded with pathways to standardization, including model agreement language, state-level programs, and expanded NERC guidance. INL also presented tools and frameworks for secure procurement and supplier risk management, reinforcing the need for integrated engineering and policy solutions to secure the evolving data center–grid ecosystem. Session 3 of 3.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Advanced Reactor Control and Operations (ARCO): A University Research Facility for Developing Optimized Digital Control Rooms

The Advanced Reactor Control and Operations (ARCO) facility was constructed in January 2018 to serve as a test bed for advanced reactor control rooms and operator support systems. Since then, it has supported human-machine interface user experience research, fault detection and mitigation technology development, control room concept of operations development, and remote operations research. ARCO serves as the control room for the Compact Integral Effects Test (CIET) facility, which replicates the primary-side flow paths and thermal-hydraulic behavior of a fluoride-salt-cooled high-temperature reactor (FHR) using simulant fluids and scaling principles. New reactor designs feature different operating conditions and scenarios than those in existing reactors. ARCO supports the research and development of digital tools for operator communications, intuitive real-time data analysis, online health monitoring and prognostics, and control room cybersecurity. By integrating these different technologies, ARCO acts as a prototypical control system to iteratively develop methods and tools of operation in advanced small modular nuclear reactors. This paper describes the features of and challenges to operating advanced small modular reactors underlying the design basis for ARCO and its operator support systems.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Negative string tension of a higher-charge Schwinger model via digital quantum simulation

We study some properties of generalized global symmetry for the charge- q Schwinger model in the Hamiltonian formalism, which is the (1 + 1)D quantum electrodynamics with a charge- q Dirac fermion. This model has the |$\mathbb {Z}_q\, 1$| -form symmetry, which is a remnant of the electric |$U(1)\, 1$| -form symmetry in the pure Maxwell theory. It is known that, if we put the theory on closed space, then the Hilbert space is decomposed into q distinct sectors, called universes, and some states with higher energy density do not decay to the ground state due to the selection rule of the 1-form symmetry. Even with open boundaries, we can observe the stability of such states by seeing a negative string tension behavior, meaning that opposite charges repel each other. In order to see negative string tensions, the vacuum angle θ has to be large enough and the standard path-integral Monte Carlo method suffers from the sign problem. We develop a method based on the adiabatic state preparation to see this feature with digital quantum simulation and confirm it using a classical simulator of quantum devices. In particular, we measure the local energy density and see how it jumps between the inside and outside of the insertion of the probe charges. We explicitly see that the energy density inside is lower than that outside. This is a clear signature of the negative string tension.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

White Paper: Scalable Digital Twin Capabilities for Aging and Surveillance of Engineered Systems

This white paper presents a multi-year initiative to develop practical, secure, and scalable digital twin capabilities for engineered systems in aging and surveillance contexts—an approach pioneered at the National Nuclear Security Administration (NNSA) Lawrence Livermore National Laboratory (LLNL) that maps directly onto the needs and ambitions of the Navy for ship- and fleet-level digital twins. LLNL’s work in building part- and process-level digital twins for advanced manufacturing, with a vision to scale up to entire factory floors and, ultimately, enterprise-wide digital twins, offers an adaptable pathway for the Navy as it seeks to modernize lifecycle management, readiness, and predictive maintenance across ships and fleets. For our application, we integrate physics-based modeling with automated data ingestion, processing, and AI-driven calibration, creating hybrid models that are both interpretable and data responsive. We modernized legacy workflows, established centralized data infrastructure, automated experimental pipelines, and demonstrated end-to-end coupling of accelerated aging data with finite element simulations via optimization and surrogate modeling. The result is a generalizable framework that supports part-level digital twins today and lays the groundwork for future system-level twins suitable for Navy applications.

36 MATERIALS SCIENCE↗

SDSS-IV MaNGA: 3D spin alignment of spiral and S0 galaxies

ABSTRACT We investigate the 3D spin alignment of galaxies with respect to the large-scale filaments using the MaNGA survey. The cosmic web is reconstructed from the Sloan Digital Sky Survey using disperse and the 3D spins of MaNGA galaxies are estimated using the thin disc approximation with integral field spectroscopy kinematics. Late-type spiral galaxies are found to have their spins parallel to the closest filament’s axis. The alignment signal is found to be dominated by low-mass spirals. Spins of S0-type galaxies tend to be oriented preferentially in perpendicular direction with respect to the filament’s axis. This orthogonal orientation is found to be dominated by S0s that show a notable misalignment between their kinematic components of stellar and ionized gas velocity fields and/or by low-mass S0s with lower rotation support compared to their high-mass counterparts. Qualitatively similar results are obtained when splitting galaxies based on the degree of ordered stellar rotation, such that galaxies with high spin magnitude have their spin aligned, and those with low spin magnitude in perpendicular direction to the filaments. In the context of conditional tidal torque theory, these findings suggest that galaxies’ spins retain memory of their larger scale environment. In agreement with measurements from hydrodynamical cosmological simulations, the measured signal at low redshift is weak, yet statistically significant. The dependence of the spin-filament orientation of galaxies on their stellar mass, morphology, and kinematics highlights the importance of sample selection to detect the signal.

Kraljic, Katarina↗

Driven-dissipative quantum mechanics on a lattice: Simulating a fermionic reservoir on a quantum computer

The driven-dissipative many-body problem remains one of the most challenging unsolved problems in quantum mechanics. The advent of quantum computers may provide a unique platform for efficiently simulating such driven-dissipative systems. But, there are many choices for how one can engineer the reservoir. One can simply employ ancilla qubits to act as a reservoir and then digitally simulate them via algorithmic cooling. A more attractive approach, which allows one to simulate an infinite reservoir, is to integrate out the bath degrees of freedom and describe the driven-dissipative system via a master equation, that can also be simulated on a quantum computer. In this work, we consider the particular case of noninteracting electrons on a lattice driven by an electric field and coupled to a fermionic thermostat. Then, we provide two different quantum circuits: the first one reconstructs the full dynamics of the system using Trotter steps, while the second one dissipatively prepares the final nonequilibrium steady state in a single step. We run both circuits on the IBM quantum experience. For circuit (i), we achieved up to five Trotter steps. When partial resets become available on quantum computers, we expect that the maximum simulation time can be significantly increased. Lastly, the methods developed here suggest generalizations that can be applied to simulating interacting driven-dissipative systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Future of plasma etching for microelectronics: Challenges and opportunities

Plasma etching is an essential semiconductor manufacturing technology required to enable the current microelectronics industry. Along with lithographic patterning, thin-film formation methods, and others, plasma etching has dynamically evolved to meet the exponentially growing demands of the microelectronics industry that enables modern society. At this time, plasma etching faces a period of unprecedented changes owing to numerous factors, including aggressive transition to three-dimensional (3D) device architectures, process precision approaching atomic-scale critical dimensions, introduction of new materials, fundamental silicon device limits, and parallel evolution of post-CMOS approaches. The vast growth of the microelectronics industry has emphasized its role in addressing major societal challenges, including questions on the sustainability of the associated energy use, semiconductor manufacturing related emissions of greenhouse gases, and others. The goal of this article is to help both define the challenges for plasma etching and point out effective plasma etching technology options that may play essential roles in defining microelectronics manufacturing in the future. The challenges are accompanied by significant new opportunities, including integrating experiments with various computational approaches such as machine learning/artificial intelligence and progress in computational approaches, including the realization of digital twins of physical etch chambers through hybrid/coupled models. These prospects can enable innovative solutions to problems that were not available during the past 50 years of plasma etch development in the microelectronics industry. To elaborate on these perspectives, the present article brings together the views of various experts on the different topics that will shape plasma etching for microelectronics manufacturing of the future.

Engineering↗

Computational Modeling to Advance Novel Medical Isotopes for Radiotheranostics: A DOE-NIH Joint Workshop Executive Summary

The DOE-NIH Joint Workshop on Computational Modeling to Advance Novel Medical Isotopes for Radiotheranostics, held on September 27, 2024, brought together experts from government, academia, and industry to address critical challenges in radionuclide production and clinical translation. Here, the workshop emphasized interdisciplinary collaboration, particularly between the Department of Energy (DOE) and the National Institutes of Health (NIH), to strengthen the domestic isotope supply, streamline regulatory pathways, and further integrate computational tools into radiopharmaceutical therapy (RPT). Key discussions explored the role of AI-driven modeling, machine learning, and digital twin technologies in optimizing dosimetry, dynamically personalizing treatments, and reducing time to clinical adoption. Advances in predictive computational modeling were highlighted as essential for improving radionuclide yield, purity, and synthesis efficiency. Regulatory considerations and equitable access were central themes, with participants advocating for harmonized global standards, adaptive trial designs, and expanded infrastructure for clinical implementation. DOE computational and production infrastructure was emphasized. Future priorities identified include increased investment in radionuclide production infrastructure, expanded workforce development in radiopharmaceutical sciences and computational modeling, and the creation of robust public-private partnerships. The workshop concluded that continued strategic collaboration and sustained resources will be vital for advancing next-generation radiotheranostics, ensuring safe and effective therapies accessible to all patients.

digital twins↗

Integrated Risk-Informed Condition Based Maintenance Capability and Automated Platform: Technical Report 1

Due to continuing global energy market trends, driven heavily by the abundant preserves of natural gas, there is an immediate need to reduce costs associated with operation and maintenance (O&M) for the current domestic nuclear power industry and for future reactor developments. This is to ensure that nuclear power generation remains an economically competitive and viable option in the energy market. O&M costs include labor-intensive preventive maintenance (PM) programs, which involve manually-performed inspection, calibration, testing, and maintenance of plant assets at periodic frequency and time-based replacement of assets, irrespective of their condition. This has resulted in an expensive, labor-centric business model to achieve high capacity factors. Fortunately, there are technologies (advanced sensors, data analytics, and risk assessment methodologies) that can enable the transition from a labor-centric business model to a technology-centric business model. The technology-centric business model will result in a significant reduction of PM activities, laying the foundation for real-time condition assessment of plant assets, reducing overall labor and part costs. To enable this transition, PKMJ Technical Services LLC is partnering with the U.S. Department of Energy’s Idaho National Laboratory (operated by the Battelle Energy Alliance, LLC) and the Public Services Enterprise Group (PSEG) Nuclear, LLC in the Integrated Risk-Informed Condition-Based Maintenance Capability and Automated Platform Project. In this report, the configuration of a digital cloud platform using Microsoft Azure is discussed, data from the PSEG Salem Nuclear Generating Station Units 1 & 2 are imported into a digital cloud platform, and the data is used for an evaluation of several key areas: cost impact analysis, risk-informed model development, and preventive maintenance strategy optimization. First, the cost impact analysis reviews which plant assets are potential good candidates for condition-based monitoring. Next, INL utilized the data in their local environment to develop the risk-informed model; which provides estimates of failure rates and probability of failures of assets based upon their past performance. The developed model is performed on assets selected from the cost impact analysis. Lastly, engineers assess the preventive maintenance strategy for the selected assets at PSEG against maintenance strategies in the nuclear industry for similar assets to potentially identify acceptable justification for the extension of current maintenance frequencies.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Immersive Industrialized Construction Environments for Energy Efficiency Construction Workforce

The National Renewable Energy Laboratory is actively developing and testing Immersive Industrialized Construction Environments (IICE) for construction automation and worker-machine interaction to investigate possible solutions and increase workforce productivity. At full scope and matured functionality, IICE allows us to accelerate the development of and better explore industrialized construction approaches such as prefabrication. IICE also enables wider adoption of energy-efficient products and Industry 4.0 construction automation through worker-machine interaction pilots. Industry 4.0 and industrialized construction approaches can encourage workforce specialization in energy efficiency construction, address the lack of multi-skilled workers, and increase workforce productivity with construction automation. However, recent attempts to integrate these concepts with the industry have only been moderately successful. To address this, focusing the pedagogy on using a digital twin, its digital models, and virtual reality could make the experience of continuing education on construction automation more affordable, accessible, scalable, immersive, and safer, and could greatly improve the efficiency and robustness of the building and construction industry. IICE accurately represents the realities of construction uncertainties without having to create full scale physical prototypes of machines. In this paper, we address the following research question: How can a digital twin and its models in virtual reality enhance the learning experience and productivity of energy efficiency construction workers to gain the skills in operating Industry 4.0 components such as construction automation and handling energy-efficient products in industrialized construction factories and on-site? We introduce original research on developing IICE and present preliminary findings from time and motion pilot studies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Building a Trusted Roaming Hub [Slides]

The Trusted Roaming Hub is a U.S. Department of Energy-backed initiative led by the National Laboratory of the Rockies (NLR) to address one of the most persistent challenges in electric vehicle (EV) charging: fragmented roaming, inconsistent interoperability, and insufficient digital trust across charging networks. As EV adoption accelerates and charging infrastructure scales nationwide, today's many-to-many integration model between eMobility Service Providers (eMSPs) and Charge Point Operators (CPOs) has become increasingly brittle, costly, and difficult to secure. The Trusted Roaming Hub introduces a neutral, cybersecurity-forward "switchboard" architecture that enables standardized, secure, and scalable roaming interactions across the EV charging ecosystem. Rather than replacing existing networks or commercial relationships, the hub acts as a trusted intermediary that enforces consistent identity, authentication, authorization, and routing across participants improving reliability for drivers, lowering integration burden for industry, and creating a foundation for future grid-interactive charging services. This read-ahead provides an overview of the problem the hub is designed to solve, the core functional and security concepts behind the architecture, the value proposition to key stakeholders, and the near-term trajectory of the work.

33 ADVANCED PROPULSION SYSTEMS↗

A pixel detector ROIC with a 3-bit, 40 Msps synchronous ADC per pixel for HL LHC

The prototype Fermi Compact Muon Solenoid (CMS) Pixel (FCP130), manufactured in a 130 nm process, is a readout integrated circuit (ROIC) designed for the High Luminosity upgrade of the Large Hadron Collider. It employs a synchronous analog to digital converter (ADC) for the front-end design, with signal processing and data conversion within a single bunch crossing of 25 ns. It is therefore capable of accurately detecting hits occurring in consecutive bunch crossings, without off-time registration of events, making it particularly suitable for the inner most layers of the vertex detector. The ROIC consists of a matrix of 48 × 160 pixels, each 100 × 30 μm2 in size. Each pixel contains a charge sensitive preamplifier with self-biasing leakage current compensation, eight auto-zero comparators and a Gray code encoder for a 3-bit flash-type ADC. The total power consumption is approximately 24 μW per pixel. The measured noise at the output of all the hit comparators across the ROIC is < 80 e- with threshold dispersion < 110 e-RMS, which allows an in-time threshold setting of ~ 1000 e-.

43 PARTICLE ACCELERATORS↗

Networked HIL Simulation System for Modeling Large-scale Power Systems

This paper presents a network hardware-in-the-loop (HIL) simulation system for modeling large-scale power systems. Researchers have developed many HIL test systems for power systems in recent years. Those test systems can model both microsecond-level dynamic responses of power electronic systems and millisecond-level transients of transmission and distribution grids. By integrating individual HIL test systems into a network of HIL test systems, we can create large-scale power grid digital twins with flexible structures at required modeling resolution that fits for a wide range of system operating conditions. This will not only significantly reduce the need for field tests when developing new technologies but also greatly shorten the model development cycle. In this paper, we present a networked OPAL-RT based HIL test system for developing transmission-distribution coordinative Volt-VAR regulation technologies as an example to illustrate system setups, communication requirements among different HIL test systems, and connection mechanisms. Impacts of communication delays, information exchange cycles, and computing delays are illustrated. Simulation results show that the performance of a networked HIL test system is satisfactory.

digital twin, distribution system, co-simulation, ↗

Advanced Transmission Technologies – GETs and HPCs Session 1: ATT Foundations and Dynamic Line Ratings (DLRs)

The INL TADA GETs Cohort Session 1, held on November 4, 2025, convened experts to address the integration of advanced transmission technologies, including Grid-Enhancing Technologies (GETs) and High Performance Conductors (HPCs), with a focus on digital assurance challenges. The session highlighted the growing importance of cybersecurity, supply chain transparency, reliability, and business risk management in deploying GETs, especially Dynamic Line Ratings (DLRs). Participants examined how expanded attack surfaces, limited vendor pools, and new regulatory requirements—such as FERC Orders 881, 2023, and 1920—are influencing utilities and technology providers. The workshop underscored the need for cyber-informed engineering, secure-by-design principles, and practical risk management strategies, while fostering collaboration and knowledge sharing among industry peers. Technical discussions covered the evolution from static to dynamic line ratings, complexities of cloud-based architectures, and NERC CIP compliance challenges. The session concluded with a collaborative risk exercise and a preview of future workshops on advanced power flow control and transmission topology optimization, reinforcing the cohort’s commitment to advancing digital assurance in the energy sector.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Artificial Intelligence and Digital Engineering as Enablers for System Engineering in the Energy Sector

Systems engineering is of utmost importance for the success of high-cost, high-complexity megaprojects, which are common in the energy sector. However, the traditional document-centric systems engineering approach tends to be labor-intensive and time-consuming, which has inhibited its full adoption despite proven metrics on its return on investment. However, with the modern approach of digital engineering and technological advancements in artificial intelligence (AI) technologies, the barriers to systems engineering adoption can finally be broken. This paper goes through the systems engineering V-model for lifecycle management and assesses the current state of implementation of digital engineering (especially, mod-el-based systems engineering, digital twins, and digital threads) and AI for each step. It was observed that a combination of digital engineering and AI is being used across different industries to accelerate and optimize systems engineering processes such as concept development, requirements management, architecture definition, system development, verification and validation, operations, and maintenance. Specifically in the energy sector, AI-augmented digital engineering has shown initial potential in accelerated development and deployment, performance optimization, anomaly detection, predictive maintenance, and configuration management. However, challenges remain in integrating DE and AI into an end-to-end system lifecycle management ecosystem safely and reliably. Addressing these challenges and continuously developing impactful tools will enable fast, efficient, and high-frequency deployment of power generation capabilities to keep up with the world’s energy demands and build energy security.

42 - ENGINEERING↗

Artificial Intelligence and Digital Engineering as Enablers for Systems Engineering in the Energy Sector

Systems engineering is of utmost importance for the success of high-cost, high-complexity megaprojects, which are common in the energy sector. However, the traditional document-centric systems engineering approach tends to be labor-intensive and time-consuming, which has inhibited its full adoption despite proven metrics on its return on investment. However, with the modern approach of digital engineering and technological advancements in artificial intelligence (AI) technologies, the barriers to systems engineering adoption can finally be broken. This paper goes through the systems engineering V-model for lifecycle management and assesses the current state of implementation of digital engineering (especially, mod-el-based systems engineering, digital twins, and digital threads) and AI for each step. It was observed that a combination of digital engineering and AI is being used across different industries to accelerate and optimize systems engineering processes such as concept development, requirements management, architecture definition, system development, verification and validation, operations, and maintenance. Specifically in the energy sector, AI-augmented digital engineering has shown initial potential in accelerated development and deployment, performance optimization, anomaly detection, predictive maintenance, and configuration management. However, challenges remain in integrating DE and AI into an end-to-end system lifecycle management ecosystem safely and reliably. Addressing these challenges and continuously developing impactful tools will enable fast, efficient, and high-frequency deployment of power generation capabilities to keep up with the world?s energy demands and build energy security.

42 - ENGINEERING↗