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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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At least 1,297 records · Page 72

INTEGRATE – Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements

The INTEGRATE (Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements) project developed a new inverse-design capability for the aerodynamic design of wind turbine rotors using invertible neural networks. Training data was obtained from improved turbulence and transition models for RANS and hybrid RANS/LES solvers with machine-learned physics-based data-augmented corrections and then using the resulting neural-network(s) augmented RANS model to run thousands of 2-D and 3-D CFD simulations.

17 WIND ENERGY↗

S&TR July-August: Beyond Ignition

On December 5, 2022, Lawrence Livermore’s National Ignition Facility achieved the first-ever successful positive-gain ignition shot. This scientific advance, heralded worldwide, required a multidecadal effort to synthesize physics theory, laser technologies, computation and diagnostic capabilities, as well as engineering, materials development, and other inputs. The question, “Can ignition be achieved?” had been answered. Since then, the Laboratory has answered the question, “Can we do it again?” with additional ignition shots at increasing yield. Now Lawrence Livermore researchers ask, “Can we improve ignition outcomes?” for the benefit of the Stockpile Stewardship Program. Interrelated articles presenting the Laboratory’s ignition science, the role of supercomputing in achieving ignition, the evolution of diagnostic instruments to measure ignition data, and the ambitious steps required to realize a fusion energy future lead to one answer: “Yes, we can.”

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Use Case Specification

Over the past three years, the Use Case Specification project has provided scenarios that have driven the development of key E-COMP capabilities and demonstrated their application to problems that the electric power industry is facing. These scenarios have provided the basis for which each Thrust has performed technical work, tying together E-COMP work under a common umbrella. Documented in this report is a summary of the background, motivations, and work – completed or proposed – under the three E-COMP use cases pursued to date: Offshore Wind, Remote Communities on the Olympic Peninsula, and Large Electric Loads.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Firmware Tampering Detection in Heavy-Duty Vehicles through J1939 CAN Analysis

Modern heavy-duty vehicles rely on complex networks of Electronic Control Units (ECUs) that communicate using the J1939 protocol. While this system makes it easier to update and configure vehicle components, it also opens the door to serious cybersecurity risks if not properly secured. This work investigates the potential for firmware tampering through the J1939 communication protocol, which enables ECU configuration and reprogramming over the Controller Area Network (CAN) bus. By monitoring CAN traffic during legitimate maintenance operations and reverse-engineering OEM diagnostic software, we identified common and proprietary J1939 message identifiers, authentication patterns, and vulnerabilities within Unified Diagnostic Services (UDS). These findings demonstrate that inadequate authentication mechanisms can allow malicious actors to alter ECU firmware or disable safety functions, posing severe operational and safety risks. Our analysis contributes to the development of vehicle intrusion detection systems capable of recognizing abnormal reprogramming activity and future firmware fingerprinting methods to verify software integrity across ECUs. This work highlights the importance of standardizing secure firmware authentication across manufacturers to strengthen cyber resilience in heavy-duty vehicle systems.

33 ADVANCED PROPULSION SYSTEMS↗

Digital Twin Framework for PIP-II Linac: AI-Driven Multi-Scale Modeling from Ion Source to 800 MeV

The PIP-II linac will enable >1.2 MW beam power for DUNE, requiring unprecedented operational reliability across its warm front-end (RFQ, MEBT) and five distinct SRF sections operating at 162.5/325/650 MHz. We present a comprehensive digital twin framework uniquely combining a fully differentiable fast beam transport code with neural network surrogates trained on high-fidelity PIC simulations, capturing space charge and nonlinear dynamics beyond traditional envelope codes while achieving 10⁴ speedup at <1% accuracy. End-to-end differentiability enables gradient-based optimization across 500+ parameters simultaneously previously impossible with conventional tools while the model incorporates static/dynamic errors and serves as a virtual commissioning platform for diverse hardware integration. The framework facilitates reinforcement learning for pulsed/CW mode transitions, predictive maintenance through anomaly detection, and autonomous tuning algorithm development with real-time execution capability. Validation against physics simulations shows excellent agreement for the front-end, with initial results demonstrating potential for 30% commissioning time reduction and proactive fault mitigation, providing a scalable blueprint for operating next-generation high-intensity accelerators.

Pathak, Abhishek [Fermilab] (ORCID:000000021704208↗

Probing Dynamic Phase Changes in Electrochemical Systems with Cryogenic and in Situ Analytical Electron Microscopy (Final Technical Report)

In this project, we focus on the advancement of our newly developed, unique in situ and cryogenic analytical electron microscopy (AEM) techniques and the development of additional high-end capabilities to quantitatively elucidate the mechanisms of resistive state changes in solid-state electrochemical materials for non-volatile, neuromorphic memory. The objectives of the proposed research are (1) to characterize and elucidate the mechanisms by which electronic state changes occur in various solid-state devices to build guiding principles for electrochemically activated smart materials; (2) to advance our understanding of such mechanisms by coupling cryogenic and in situ techniques to control kinetics of the observed mechanisms while mitigating probe-induced damage; and (3) to utilize additional advanced techniques including electron-beam induced current and quantum mechanical simulations in order to identify the underlying fundamental science of such processes, including roles of defect formation and its effect on phase nucleation, as well as dynamics of these processes in the electrochemical systems at the nanometer scale.

25 ENERGY STORAGE↗

New correlated numerical methods for attosecond molecular single and double ionization

This project resulted in the development of ASTRA, a new molecular ionization code capable of describing single and double ionization processes in polyatomic molecules with correlated electrons and time-dependent fields. Key achievements include: (i) the development of the PRISM hybrid-integral library enabling core-ionization and high-angular-momentum convergence; (ii) implementation of time-dependent Schrödinger equation solvers for pump–probe spectroscopies; (iii) validation against experimental and theoretical benchmarks for atoms and molecules; and (iv) extension to two-photon double ionization using the finite-pulse virtual-sequential model. These developments establish ASTRA as a versatile platform for attosecond molecular dynamics.

74 ATOMIC AND MOLECULAR PHYSICS↗

Understanding and Predicting Pedestal Scenarios on NSTX-U (Final Technical Report)

This project investigated gyrokinetic instabilities in the NSTX pedestal, identified the major transport mechanisms (some of them novel) in the NSTX pedestal, and developed and validated a predictive modeling capability for pedestal transport in spherical tokamaks, with particular emphasis on NSTX discharges. The work combined first-principles gyrokinetic simulations, reduced transport models, integrated transport calculations with ASTRA, and exploratory machine learning tools. The central outcome is a practical modeling capability for pedestal temperature profiles based on reduced models informed and constrained by gyrokinetic physics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NRIC Annual Report FY 2025

The National Reactor Innovation Center (NRIC), established in August 2019, is a national United States (U.S.) Department of Energy (DOE) program. NRIC’s mission is to partner with industry and national laboratories to bridge the gap between concept, demonstration, and commercialization of advanced nuclear technology. NRIC accomplishes this through building or enhancing existing DOE infrastructure to support testing of components and systems that are key to successfully deploying advanced nuclear technology. NRIC’s vision is that by 2028, NRIC will be partnered with industry and accelerating the demonstration and deployment of advanced nuclear technology using DOE national laboratory infrastructure and expertise. NRIC will establish four new experimental facilities and two large reactor test beds for integrated technology demonstrations and experimentation by 2028 and complete two advanced nuclear technology tests by 2030. Achieving this vision will enable urgently needed abundant and affordable clean energy both domestically and internationally. NRIC’s success will inspire our nation and the global community to embrace the promising contribution of innovative nuclear reactor technologies to the clean energy economy and re-establish the U.S. as the global leader in advanced nuclear energy. NRIC is tasked with expediting the development of advanced nuclear energy technologies by bringing together private-sector technology developers and the world-class capabilities of the DOE national laboratory system. Through this program, the U.S. private sector is given access to the physical infrastructure available at DOE national laboratories to test and demonstrate their reactor concepts. NRIC works closely with the DOE-Nuclear Energy (NE) program that grants access to technical, regulatory, and financial support for commercializing nuclear energy. NRIC builds upon these new reactor concepts and technology successes to effectively strengthen U.S. nuclear leadership.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

EDEN Tube Interface Characterization Report

In 2022 Eden Radioisotopes and Los Alamos National Laboratory entered into a Creative Research and Development Agreement (CRADA) leveraging the metallography capabilities of the Characterization and Special Projects Team of Sigma-2 at LANL. EDEN identified a need to characterize the condition of metallic interfaces within their product created at different pressure conditions to see which processing parameters achieved interfaces within specifications for intended use. A total of 4 samples were sent to the Characterization Projects team and 3 were later sent to another facility (MST-7) where Micro CT was performed.

36 MATERIALS SCIENCE↗

High-brightness electron injectors for high-duty cycle X-ray free electron lasers

The successful development in the last two decades of X-ray free electron lasers (FELs) with their revolutionary brightness performance has been tightly dependent on the parallel development of electron guns and injectors capable of providing the high-brightness electron beams required by FELs lasing at these short wavelengths. The ultimate brightness delivered by a linear accelerator (linac) is already set at its injector and the remaining part of the accelerator can be only designed to preserve the injector performance. The technology to be used for the accelerator part of an X-Ray FEL strongly depends on the duty-cycle at which the FEL operates. Normal-conducting, room-temperature, copper-based radio frequency (RF) technology is typically used for low duty-cycles of up to approximately 10 −3 . For higher duty-cycles and up to continuous wave (CW) operation, the linac must rely on superconductive RF technology because, with the higher duty-cycle, the increasingly higher power dissipated in normal conducting RF structures becomes excessive for the warm technology. The situation changes in the lower energy part of the accelerator, where injector schemes, based on direct current, normal-conducting, and superconducting RF electron guns, are demonstrating the beam quality performance required by high-duty-cycle X-ray FELs. In this paper we start with a description of the requirements for such injectors, followed by an overview of the pursued technologies and schemes, and by a discussion on the main differences in terms of beam dynamics between low and high duty-cycle injectors.

Sannibale, Fernando↗

Tools Assessing Performance

For the distributed wind industry, it can be challenging to accurately predict the performance and annual energy production of projects prior to their installation. The U.S. Department of Energy’s Tools Assessing Performance (TAP) project aims to improve wind resource characterization, thereby reducing the uncertainty of project performance and financing costs, increasing consumer confidence, and lowering the levelized cost of distributed wind energy. A collaborative effort among DOE National Laboratories, TAP will create a computational framework that provides the distributed wind community with access to newly developed wind resource data and modeling capabilities. These capabilities will allow users to perform timely and accurate performance assessments for distributed wind projects at locations across the United States.

wind, distributed, tools, performance↗

Enabling Innovation in Wind Turbine Design Using Artificial Intelligence

The Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements (INTEGRATE) project is developing a new inverse-design capability for wind turbine rotors using invertible neural networks. This artificial intelligence (AI)-based technology can capture complex nonlinear aerodynamic effects 100 times faster than alternative design approaches.

aerodynamics↗

Enabling Innovation in Wind Turbine Design Using Artificial Intelligence

The Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements (INTEGRATE) project is developing a new inverse-design capability for wind turbine rotors using invertible neural networks. This artificial intelligence (AI)-based technology can capture complex nonlinear aerodynamic effects 100 times faster than alternative design approaches.

aerodynamics↗

Achieving American Leadership in the Grid Storage Supply Chain Factsheet

To meet growing demand for long duration energy storage, domestic manufacturing will have to increase significantly. The use of renewables is rapidly increasing, and the adaption of electric vehicles is on the rise, which will require the national grid to not only produce and deliver electricity, but also store it reliably and cost-effectively. The International Energy Agency (IEA) recently released a report showing that to reach a goal of net-zero emissions by 2050, grid storage will need to grow to almost 2,500 gigawatt hours (GWh) in less than a decade. Currently, across the globe, battery technologies provide over 30 GWh of grid storage(BloombergNEF, 2020) while pumped storage hydropower (PSH)provides 160 gigawatts (GW) of long-duration energy storage (LDES) (PSH) (U.S. Department of Energy, 2020). This fact sheet summarizes strategies to address key vulnerabilities in the grid storage supply chain, the United States. These strategies include: • Developing domestic, sustainable manufacturing and recycling capabilities along the energy storage supply chain. • Maximizing the use of domestic resources by focusing on second-life and recycling technologies. • Enabling the diversification and deployment of grid storage technologies through targeted research activities. Addressing these opportunities will have significant impacts with respect to increasing well-paying skilled domestic jobs, improving the gross domestic product (GDP), and ensuring minimal environmental and climate impacts.

Source record↗

Application of Dimensionality Reduction in Machine Learning Modeling of CO2 Storage

In this study, we developed deep learning models that are capable of predicting spatio-temporal outputs of CO2 saturation, pressure, and brine production in a 3D saline storage reservoir over 30 years of continuous CO2 injection and a 50-year post-injection timeframe. To improve computational efficiency and maintain performance accuracy, the model framework involves ensembling multi-layer autoencoder networks that provide dimensionality reduction of geologic inputs with fully connected long short-term memory (LSTM) neural networks that generate time-series prediction. This study was presented as poster at the 2022 Carbon Management Project Review Meeting held in Pittsburgh, PA (August 15 – 19, 2022).

Bello, Kolawole↗

PELE - Transforming Combustion Science and Technology with Exascale Simulations

This poster presents the status of the Pele Combustion project, an applications project in the Exascale Computing Project. It summarizes the goal of the projects, developments added to the Pele simulation capabilities over the last year, some example performance figures that target ultimate application on the Frontier supercomputer, and show a number of published and in-progress simulation results, by us and our collaborators.

combustion↗

High fidelity ground deposition measurement with robots after explosive radiological dispersion

A team of scientists from the Remote Sensing Laboratory at Joint Base Andrews, Maryland, has assembled a remote-controlled robot to field a few sodium iodide scintillators of different size and shape 18″ above ground for measurement of ground deposition of gamma-emitting particles after an explosion of a radiological dispersal device. This system uses a high-precision differential GPS device with submeter accuracy for radiation mapping. The system is most useful in characterizing large-area contamination and detecting gamma radioactivity in invisible, submicron particulate debris deposited on the ground at surface level or embedded in subsurface up to 3″ deep. The system was assembled as part of a larger effort to integrate advanced radiological detection devices into autonomous or remote-controlled robotic systems to eliminate or minimize the need for emergency responders to enter areas that pose significant health and safety risks to humans following a major radiological incident or accident. Research into autonomous algorithms is required to develop automated robotic systems for radiological survey and characterization activities in highly contaminated areas. The scope of this project also includes developing communications pathways and supporting infrastructure capabilities for different types of robotic technologies. The expected result is an advanced autonomous robotic system with integrated radiation detection electronics that allows emergency response personnel to view data remotely and in real time for radiological emergency response and consequence management purposes.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗