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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Submerged Fatigue Testing of Marine Energy Advanced Materials

Marine energy structures are typically made of advanced composite materials and are subjected to extreme ocean environments in service. In extreme ocean environments, seawater currents and waves load structures repeatedly, which cause two environmental conditions: water intrusion and mechanical fatigue. In prior research, the two environmental conditions were applied sequentially, where composite specimens were aged and then mechanically tested. To understand the combined effects of dynamic loading and water intrusion on composite materials, the present study involves the static and fatigue four-point bend testing of composite coupons in a water tank. The water tank was designed and built to fit either a 100 kN or a 250 kN load frame. Flexural strength value, cycles to failure, and failure mode results from submerged fatigue testing will be used to inform marine energy structure designs. The coupon-scale test method will be used to scale up to and inform methods for subsequent subcomponent testing and standards development. Finally, the benefits of designing marine energy structures to informed standards are decreased lifetime costs and increased reliability and energy production, ultimately leading to a sustainable and low-carbon energy system.

13 HYDRO ENERGY↗
DOE OSTI2026

UV–Vis–NIR Reflectance Spectroscopy and Chemometrics for Monitoring Pu Directly on an Ion Exchange Column

Here, we present a fiber-optic UV–vis–NIR reflectance spectroscopy method for direct, noninvasive monitoring of Pu(IV) in a glass ion exchange column during dynamic loading and elution in a glovebox. A movable probe enables spatially resolved spectral acquisition along the column axis, capturing distinct features associated with Pu(IV) nitrate complexes during loading and free ions during elution. Principal component analysis was applied to extract the dominant spectral variance and resolve relative concentration profiles without requiring precise knowledge of optical penetration depth or species identity. This in situ approach reveals spatial gradients and speciation dynamics in real time, which provides actionable insight into Pu(IV) ion migration, resin saturation, and breakthrough behavior under evolving flow conditions. The method offers a practical, fiber-compatible strategy to monitor glass column–based separations for Pu and other lanthanides or actinides and to characterize metal–resin interactions in flow-through systems.

actinide↗
DOE OSTI2026

Control Room of the Future Testbed Workshop – After-Action Report

The U.S. Department of Energy’s Office of Electricity is supporting a one-year, multi-laboratory effort to define the needs and requirements for a Control Room of the Future testbed, or CROFT. The effort responds to increasing grid complexity driven by large new loads, dynamic generation resources, and the growing adoption of advanced technologies and tools, including artificial intelligence (AI) and machine learning (ML). To support safe, secure, and effective grid modernization, CROFT will focus on how emerging technologies and tools can be rigorously evaluated in realistic operational settings, with attention to human-machine interaction, cognitive load, and workforce readiness. The project team includes Argonne National Laboratory, Idaho National Laboratory, National Laboratory of the Rockies, and Pacific Northwest National Laboratory. As part of the scoping effort, the team conducted two industry-focused workshops: one at DTECH on February 5, 2026, informed by prior industry interviews, and a second on May 4, 2026, adjacent to IEEE T&D. These engagements brought together utilities, vendors, consultants, national laboratories, academia, and government stakeholders to identify and prioritize use cases, barriers, validation needs, data-sharing constraints, and near- and longer-term requirements. This feedback will directly inform CROFT’s architecture and research focus areas, ensuring the testbed is grounded in real-world operational needs and designed to evaluate emerging technologies and tools in realistic control-room environments.

artificial intelligence↗
DOE OSTI2025

Multi-objective automatic discovery of optimized metamaterials for varying velocity impact protection

Mechanical metamaterials have demonstrated exceptional impact performance while remaining lightweight. Impact resistance has traditionally been investigated using quasi-static simulations, often with the assumption that performance will translate to high-velocity impact scenarios. However, critical crash protection parameters—such as peak stress and absorbed energy—are highly sensitive to impact velocity, leading to inconsistent performance under dynamic loading. To address this, we introduce a strain-rate-aware, active deep learning framework that enables multi-objective optimization of impact protection metrics across a wide range of impact velocities. Our framework captures the strain-rate sensitivity of architected lattices by learning to control spatial gradation in cellular metamaterials, resulting in over 200 % enhancement in impact protection relative to state-of-the-art designs such as Voronoi and re-entrant lattices. We demonstrate its practical utility by designing next-generation lattice structures for automotive bumper systems that satisfy multiple, velocity-specific safety criteria—capabilities beyond those of conventional designs. More than just a predictive tool, this framework marks the first step towards enabling adaptable impact-resistant structures across dynamic regimes.

Deep learning↗
DOE OSTI2025

Effect of pressure cycling and compression rate on the bcc-hcp transition in an FeNi alloy

Here, we investigate the body-centered cubic (bcc) to hexagonal close-packed (hcp) phase transition in Fe-10wt. %Ni alloy, combining pressure cycling and fast compression with time-resolved synchrotron x-ray diffraction in a dynamic diamond anvil cell. Three pressure cycles were conducted with compression rates ranging from 0.1 to nearly 10 3 GPa/s. During the first cycle with the slowest compression, the observed orientations in the bcc and hcp phases are consistent with the Burgers mechanism, followed by c-axis rotation of the hcp phase consistent with {$10$ $\bar{1}2$} twinning. During the following cycles with fast compression at 10 2 –10 3 GPa/s, the hcp phase exhibits negligible c-axis rotation with a nearly constant c/a ratio of ∼1.61 up to ∼30 GPa, indicating suppression of plastic deformation (especially, twinning) due to sample confinement from the gasket. Notably, the onset pressure of the transition decreases with additional pressure cycling and faster compression, which normally leads to over-pressurization. This suggests that defects or shear induced from the pressure cycling reduces the transition kinetics even during fast compression. These insights into the deformation and transition behavior in an FeNi alloy under multiple dynamic loading cycles can offer guidance for future design of advanced structural alloys and improve our understanding of planetary core processes.

FeNi alloy↗
DOE OSTI2025

An Integrated High-Speed Microstructural Characterization Method Using Simultaneous XRD, Stereo-DIC, and PCI

High-speed characterization of the deformation mechanisms in polycrystalline metals requires the quantification of full strain fields and local microstructural evolutions simultaneously. In this paper, we present a novel experimental method to integrate phase-contrast imaging (PCI), stereographic digital image correlation (stereo-DIC), and full-ring X-ray diffraction (XRD) to allow for the simultaneous characterization of polycrystalline metals at 1MHz or higher. A Kolsky bar was integrated into the synchrotron X-ray source in Sector 32 ID-B at the Advance Photon Source (APS) at Argonne National Laboratory. When the sample is dynamically loaded, the diagnostic methods of full-ring XRD, PCI, and stereo-DIC are properly synchronized to record the deformation behavior at both continuum and microstructural scales as a function of the loading history. An advanced high-strength steel (AHSS) is used as a model material to demonstrate the capabilities of this new experimental method.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Acceleration of the particle-in-cell code Osiris with graphics processing units

Fully relativistic particle-in-cell (PIC) simulations are crucial for advancing our knowledge of plasma physics. Modern supercomputers based on graphics processing units (GPUs) offer the potential to perform PIC simulations of unprecedented scale, but require robust and feature-rich codes that can fully leverage their computational resources. In this work, this demand is addressed by adding GPU acceleration to the PIC code Osiris. An overview of the algorithm, which features a CUDA extension to the underlying Fortran architecture, is given. Detailed performance benchmarks for thermal plasmas are presented, which demonstrate excellent weak scaling on NERSC's Perlmutter supercomputer and high levels of absolute performance. The robustness of the code to model a variety of physical systems is demonstrated via simulations of Weibel filamentation and laser-wakefield acceleration run with dynamic load balancing. Finally, measurements and analysis of energy consumption are provided that indicate that the GPU algorithm is up to ~14 times faster and ~7 times more energy efficient than the optimized CPU algorithm on a node-to-node basis. The described development addresses the PIC simulation community's computational demands both by contributing a robust and performant GPU-accelerated PIC code and by providing insight into efficient use of GPU hardware.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Compression rate effects on the Bi-III stability field in dynamic diamond anvil cell XFEL studies of bismuth

This study aims to resolve conflicting observations of bismuth’s high-pressure phase transitions across static, intermediate, and shock compression regimes. We probed its high-pressure structural sequence using the dynamic diamond anvil cell with and time-resolved X-ray diffraction with microsecond resolution at an X-ray free-electron laser. At room temperature and pressures up to 20 gigapascals, bismuth evolves through the same structural sequence previously identified under static compression. However, the transformation behavior differs in important ways under dynamic loading. In particular, the transition from the incommensurate intermediate-pressure phase to the high symmetry high pressure phase begins at pressures about 2 to 4 gigapascals lower than in static experiments, and the onset of this transformation depends on the compression rate. As a result, the stability field of the intermediate-pressure phase is reduced under rapid compression. Our results suggest that at sufficiently fast loading rates the intermediate phase may be bypassed entirely, consistent with previous shock-compression observations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Reinforcement Learning‐Based Adaptation of Grid Following Inverter's Internal Controller to Networked Microgrids' Strengths

The varying topological configurations, generator commitments and dispatches, and dynamic load demand lead to changing system's strengths during the operations of networked microgrids. When the system's strengths significantly change, the fixed control gains at large devices may result in unsatisfactory system performance; this necessitates the tuning of the control gains at large devices to adapt to the changing system's strengths. In this paper, observer-based reinforcement learning (RL) is utilised to automatically tune the proportional-integral (PI) gains of phase lock loop (PLL) controller of grid-following (GFL) inverters to adapt to the changing strengths of microgrids and networked microgrids. The RL agent in this framework augments an observer predicting system's strengths, from which the RL control policy will adjust accordingly to tune the PLL controller's gains towards the system's strengths. Also, to enhance the control performance, the recently introduced Barrier function-based RL framework is leveraged for the design of reward function to prevent the high frequency nadir. An operational 26 kV electric distribution system, which is modelled as networked microgrids, is used to illustrate the need and effectiveness of the proposed RL-tuned control.

frequency response↗
DOE OSTI2026

Mechanics of pore array collapse and interaction in shock-compressed polymethyl methacrylate (PMMA)

Recent studies on dynamic pore collapse have revealed significant development of shear localization, which can lead to material failure in porous structures and hot spot generation in energetic materials. These findings have dramatically improved the understanding of failure mechanisms during pore collapse but also prompt further investigation of realistic porous materials. In particular, porous media consist of many pores and porous networks. Even in low-porosity materials, pores can form in close proximity during the manufacturing process, leading to the critical question of pore–pore interaction during collapse under dynamic loading conditions. This study investigates, via plate impact experiments coupled with high-speed internal digital image correlation and shadowgraphy techniques, the collapse of two pores in shock-compressed PMMA at stresses between 0.4 and 1 GPa. The results of these experiments provide new insights into shear localization in pore collapse, in addition to distinct interactions between pores. Shadowgraphy measurements reveal novel, direct visualization of shear band development and crack evolution from pore surfaces. Spacing between adiabatic shear bands is measured over a range of impact stresses and is predicted accurately by the Grady–Kipp model. Pore interactions are found to effect a transition in the impact stress threshold at which different failure mechanisms initiate and are also found to possibly influence preferential sites for shear cracking. Throughout the study, numerical and theoretical models are leveraged to understand shear localization behavior. The role of baroclinicity and wave interactions between the pores is used to elucidate interaction mechanisms between pores.

Lawlor, Barry P. [California Institute of Technolo↗
DOE OSTI2026

Statistical Analysis of Inter-Area Oscillations in the U.S. Eastern Interconnection: A 2017-2023 Perspective

Recent advancements and the accumulation of high-resolution, long-term phasor measurement unit (PMU) data have provided detailed insights into inter-area oscillations in power grids. This study conducts a comprehensive statistical analysis of inter-area oscillations within the United States Eastern Interconnection from 2017 to 2023. Utilizing data captured by the advanced wide-area Frequency Monitoring Network (FNET/GridEye), this investigation examines the occurrence patterns, dominant frequencies, damping ratios, and excitation mechanisms of these oscillations. Our analysis sheds light on the evolving statistical behaviors of inter-area oscillations, offering updated and critical information for grid operators and planners. The insights gained from this study can be instrumental in enhancing the operational resilience of the power network and guiding strategic developments in grid infrastructure to accommodate future challenges. Additionally, the study discusses emerging challenges associated with the modernization of the power grid, including increased renewable penetration, dynamic load variability, and cyber-physical vulnerabilities that complicate oscillation monitoring and control.

Inter-area oscillations↗
DOE OSTI2025

Modeling suggests SARS-CoV-2 rebound after nirmatrelvir-ritonavir treatment is driven by target cell preservation coupled with incomplete viral clearance

In a subset of SARS-CoV-2-infected individuals treated with the antiviral nirmatrelvir-ritonavir, the virus rebounds following treatment. The mechanisms driving this rebound are not well understood. We used a mathematical model to describe the longitudinal viral load dynamics of 51 individuals treated with nirmatrelvir-ritonavir, 20 of whom rebounded. Target cell preservation, either by a robust innate immune response or initiation of N-R near the time of symptom onset, coupled with incomplete viral clearance, appears to be the main factor leading to viral rebound. Moreover, the occurrence of viral rebound is likely influenced by the time of treatment initiation relative to the progression of the infection, with earlier treatments leading to a higher chance of rebound. A comparison with an untreated cohort suggests that early treatments with nirmatrelvir-ritonavir may be associated with a delay in the onset of an adaptive immune response. Nevertheless, our model demonstrates that extending the course of nirmatrelvir-ritonavir treatment to a 10-day regimen may greatly diminish the chance of rebound in people with mild-to-moderate COVID-19 and who are at high risk of progression to severe disease. Altogether, our results suggest that in some individuals, a standard 5-day course of nirmatrelvir-ritonavir starting around the time of symptom onset may not completely eliminate the virus. Thus, after treatment ends, the virus can rebound if an effective adaptive immune response has not fully developed. These findings on the role of target cell preservation and incomplete viral clearance also offer a possible explanation for viral rebounds following other antiviral treatments for SARS-CoV-2.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Coupled momentum balance and phase-field solver with fenicsx module

Code solves momentum balance and phase-field equations simultaneously. The differential equations are solved on a discretized domain with appropriate boundary and initial conditions using finite element method. Primary purpose of the code is to simulate brittle fracture under dynamic loading. Constitutive equations are that of linear elasticity with degradation of stress due to fracture. Small strain formulation is used.

Zecevic, Milovan↗
DOE OSTI2024

UMap: An application-oriented user level memory mapping library

Exploiting the prominent role of complex memories in exascale node architecture, the UMap page fault handler offers new capabilities to access large memory-mapped data sets directly. UMap provides flexible configuration options to customize page handling to each application, including analysis of massive observational and simulation data sets. The high-performance design features I/O decoupling, dynamic load balancing, and application-level controls. Page faults triggered by application threads and processes accessing data mapped to a UMapp’ed region are handled via the Linux userfaultfd protocol, an asynchronous message-oriented kernel-user communication mechanism that avoids the context switch penalty of traditional signal fault handlers. UMap is fully open source. In this paper, we give an overview of the UMap library architecture, its extensible plugin architecture, and the use/performance of UMap in emerging heterogeneous memory hierarchies such as near-node Non-volatile Memory (NVM) and network attached memories. We highlight new capabilities in two pagefault management plugins, the NetworkStore and SparseStore. We demonstrate the integration between UMap and multiple ECP products including Caliper, Metall, ZFP, Mochi, and Ripples.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Dynamically Learning Incentives for Load Control

As electrical generation becomes more distributed and volatile, and loads become more uncertain, controllability of distributed energy resources (DERs), regardless of their ownership status, will be necessary for grid reliability. Grid operators lack direct control over end-users' grid interactions, such as energy usage, but incentives can influence behavior -- for example, an end-user that receives a grid-driven incentive may adjust their consumption or expose relevant control variables in response. A key challenge in studying such incentives is the lack of data about human behavior, which usually motivates strong assumptions, such as distributional assumptions on compliance or rational utility-maximization. In this paper, we propose a general incentive mechanism in the form of a constrained optimization problem -- our approach is distinguished from prior work by modeling human behavior (e.g., reactions to an incentive) as an arbitrary unknown function. We propose feedback-based optimization algorithms to solve this problem that each leverage different amounts of information and/or measurements. We show that each converges to an asymptotically stable incentive with (near)-optimality guarantees given mild assumptions on the problem. Finally, we evaluate our proposed techniques in voltage regulation simulations on standard test beds. We test a variety of settings, including those that break assumptions required for theoretical convergence (e.g., convexity, smoothness) to capture realistic settings. In this evaluation, our proposed algorithms are able to find near-optimal incentives even when the reaction to an incentive is modeled by a theoretically difficult (yet realistic) function.

demand response↗
DOE OSTI2024

Measurement of Wind Loading on Heliostats at the Crescent Dunes Power Plant: An Overview

The cost of solar collectors constitutes almost one third of the total cost of a CSP plant. One of the ongoing challenges in the design of these collectors is wind loading on mirrors, support structures, and drives. A particular challenge is dynamic wind loading, caused by the turbulent wind flow. To date, the design of solar collector structures has relied on wind tunnel experiments and numerical simulations that do not entirely capture the dynamic effects observed at scale. The CSP industry has shown increased interest in validating the idealized assumptions with measurements obtained in operational settings to improve wind load assumptions and increase reliability and cost-efficiency of the collector design. Further, performance models need realistic assumptions about wind loading and its impact on optical performance. In a parabolic trough field campaign, NREL successfully collected a wealth of long-term, high-resolution wind and loads data [2], that are publicly available and that can be used for the above-mentioned purposes. Heliostats are impacted differently by wind than parabolic troughs, due to their different shape, size, and field layout. To study the impact of wind and turbulence on heliostats, we initiated another field campaign in an operational power- tower plant, Crescent Dunes, in Nevada, USA. In this work, we present an overview of the measurements, first results, and potential implications of wind driven loads on Heliostats.

concentrated solar power↗