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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

Implementation and Validation of a Generalized Actuator Disk Parameterization for Wind Turbine Simulations Within the FastEddy Model

ABSTRACT Fast and accurate large‐eddy simulation (LES) of the atmospheric boundary layer plays a crucial role in advancing wind energy research. Long‐duration wind farm studies at turbine‐resolving scales have become increasingly important to understand the intricate interactions between large wind farms and the atmospheric boundary layer. However, the prohibitive computational cost of these turbulence‐ and turbine‐resolving simulations has precluded such modeling to be exercised on a regular basis. To that end, we implement and validate the generalized actuator disk (GAD) model in the computationally efficient, graphics processing unit (GPU)–resident, LES model FastEddy. We perform single‐turbine simulations under three atmospheric stabilities (neutral, unstable, and stable) and compare them against observations from the Scaled Wind Farm Technology (SWiFT) facility and other LES codes from the recent Wakebench turbine wake model benchmark. Our idealized LES results agree well with observed wake velocity deficit and downstream recovery across stability regimes. Turbine response in terms of rotational speed, generated power, torque, and thrust coefficient are well predicted across stability regimes and are consistent with the LES results from the benchmark. The FastEddy simulations are found to be at least two orders of magnitude more efficient than the traditional CPU‐based LES models, opening the door for realistic LES simulations of full wind plants as a viable standard practice.

17 WIND ENERGY↗
DOE OSTI2024

Atomistic simulations to reveal HIP-bonding mechanisms of Al6061/Al6061

Molecular dynamics simulations were employed to understand the diffusion bonding process during hot isostatic pressing (HIP) of Al6061/Al6061 alloy. Simulations of the HIP process reveal atomistic phenomena that are difficult or unlikely to be observed experimentally and provide useful insights into the mechanism of diffusion and bonding. Here, the results reveal that at the start of the HIP process, a massive incursion of oxygen atoms occurs from the pre-existing γ-Al 2 O 3 to the 6061 region across the interphase interface. These oxygen atoms interact with the enriched Mg atom layer present at the existing γ-Al 2 O 3 and 6061 matrix to form a secondary complex Mg 2 Al 2 O 5 phase. Diffusion calculations also show that transport of atoms due to the applied pressure is 4–5 orders of magnitude higher than would occur in the absence of HIP conditions. The Mg 2 Al 2 O 5 phase also provides efficient pathways for the rapid transport of Mg atoms. Because of the higher diffusion coefficients observed for Mg within the phase, Mg atoms can move more swiftly compared to their diffusion within other phases such as γ-Al 2 O 3 . This accelerated mobility facilitates the rapid movement of Mg atoms across the interface, leading to changes in the local composition and the potential growth of the Mg 2 Al 2 O 5 phase.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Distinctive features of fluorescence and waveguides in magnesium aluminate spinel crystals driven by structural discrepancy

Transparent polycrystalline ceramics are of significant importance for a wide range of scientific and industrial applications. Developing a deeper understanding of their thermodynamic behavior is essential for achieving their maximum output performance in technological applications. This study provides a systematic investigation into the thermal excitation-induced fluorescence kinetics and waveguide characteristics of Magnesium Aluminate Spinel (MgAl 2 O 4 ) single crystals, with a focus on the intricate relationship between structure and properties. High-temperature extreme environments through irradiation with swift heavy ions 645.0 MeV Xe and 352.8 MeV Fe ions were created; the atomic deposition energy threshold (E th ) associated with disorder morphologies was assessed between 0.91 and 0.99 eV atom –1 . The track prediction model was developed to support the theoretical prediction of track formation. Electronic energy loss (E ele ) disrupts the balance of the initial structure through the thermal spike effect, leading to the formation of absorption-related F and F + color centers. These defects enhance photoluminescence in the visible spectrum and result in an effective modulation of the intrinsic bandgap. Moreover, as ion beams penetrate into the material, the uneven damage distribution induces the formation of waveguide structures. In conclusion, these findings provide valuable insights into the fabrication of functional devices through irradiation technologies and the structural changes of MgAl 2 O 4 at high temperatures within extreme environments.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Enhancing operational safety: The NSTX-U Shorted Turn Protection (STP) system

The NSTX-U Shorted Turn Protection (STP) system is a vital safety feature designed to protect the tokamak’s coils during operations. It employs a Kalman filter-based algorithm to monitor coil currents and detect faults in real-time. If an anomaly is detected, the system swiftly terminates the tokamak pulse to prevent damage. Developed with Matlab and Simulink, the STP system has been validated through real-time simulations, ensuring its effectiveness for the upcoming upgrades of the NSTX-U facility. In conclusion, this article presents the theory for implementation of the STP algorithm and the results from simulation and real-time implementation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Large language models for transportation research: Methodologies, state of the art, and future opportunities

The rapid rise of large language models (LLMs) is transforming transportation research, with significant advancements emerging between 2023 and 2025, a period marked by the inception and swift growth of adopting and adapting LLMs for various transportation applications. Despite these significant advancements, however, a systematic review and synthesis of the existing literature remains lacking. This paper aims to fill this gap by providing a comprehensive review of the methodologies and applications of LLMs in transportation. We explore key applications, including autonomous driving, travel behavior prediction, and general transportation-related queries, alongside LLM methodologies such as zero- or few-shot learning, prompt engineering, and fine-tuning. From the review, critical research gaps are identified. From the methodological perspective, many of the research limitations can be addressed by integrating LLMs with existing tools and refining LLM architectures. From the application perspective, research opportunities for LLMs to address various transportation challenges are also explored. By synthesizing these findings, this review not only presents the state-of-the-art LLM adoption and adaptation in transportation, but also proposes future research directions as well as insights and recommendations for policymakers and practitioners, paving the way for greater LLM-driven research innovations in transportation in the future.

42 ENGINEERING↗
DOE OSTI2025

ER stress and viral defense: Advances and future perspectives on plant unfolded protein response in pathogenesis

Viral infections pose significant threats to crop productivity and agricultural sustainability. The frequency and severity of these infections are increasing, and pathogens are evolving rapidly under the influence of climate change. This underscores the importance of exploring the fundamental mechanisms by which plants defend themselves against dynamic viral threats. One such mechanism is the unfolded protein response (UPR), which is activated when the protein folding demand exceeds the capacity of the endoplasmic reticulum, particularly under adverse environmental conditions. While the key regulators of the UPR in response to viral infections have been identified, our understanding of how they modulate the UPR to suppress plant viral infections at the molecular and genetic levels is still in its infancy. Recent findings have shown that, in response to plant viral infections, the UPR swiftly reprograms transcriptional changes to support cellular, metabolic, and physiological processes associated with cell viability. However, the underlying mechanisms and functional outcomes of these changes remain largely unexplored. Here, we highlight recent advances in plant UPR research and summarize key findings related to viral infection–induced UPR, focusing on the balance between prosurvival and prodeath strategies. We also discuss the potential of systems-level approaches to uncover the full extent of the functional link between the UPR and plant responses to viral infections.

ER stress↗
DOE OSTI2024

Integrative Multi-PTM Proteomics Reveals Dynamic Global, Redox, Phosphorylation, and Acetylation Regulation in Cytokine-treated Pancreatic Beta Cells

Studying regulation of protein function at a systems level necessitates an understanding of the interplay among diverse post-translational modifications (PTMs). A variety of proteomics sample processing workflows are currently used to study specific PTMs but rarely characterize multiple types of PTMs from the same sample inputs. Method incompatibilities and laborious sample preparation steps complicate large-scale physiological investigations and can lead to variations in results. The single-pot, solid-phase-enhanced sample preparation (SP3) method for sample cleanup is compatible with different lysis buffers and amenable to automation, making it attractive for high-throughput multi-PTM profiling. Herein, we describe an integrative SP3 workflow for multiplexed quantification of protein abundance, cysteine thiol oxidation, phosphorylation, and acetylation. The broad applicability of this approach is demonstrated using cell and tissue samples, and its utility for studying interacting regulatory networks is highlighted in a time-course experiment of cytokine-treated ß-cells. We observed a swift response in global regulation of protein abundances consistent with rapid activation of JAK-STAT and NF-?B signaling pathways. Regulators of these pathways as well as proteins involved in their target processes displayed multi-PTM dynamics indicative of a complex cellular response stages: acute, adaptation, and chronic (prolonged stress). PARP14, a negative regulator of JAK-STAT, had multiple co-localized PTMs that may be involved in intraprotein regulatory crosstalk. Our workflow provides a high-throughput platform that can profile multi-PTMomes from the same sample set, which is valuable in unraveling the functional roles of PTMs and their co-regulation.

proteomics, PTM, automation, SP3, cysteine thiol o↗
DOE OSTI2025

Dynamic response of a freely rotating butterfly valve in the advanced test reactor – dynamic fluid-body interaction modeling

To regulate primary coolant flow in the Advanced Test Reactor (ATR), a butterfly valve was installed between the primary coolant pumps and the reactor core. If the mechanical connection between the valve's disk and its shaft ever fails, the disk will rotate freely. Rapid disk rotation may induce pressure surges that could damage upstream pipes. In the present work, the rotational trajectory and pressure evolution during a disk free-rotation scenario were analyzed via the dynamic fluid-body interaction (DFBI) approach in STAR-CCM+, with the movement of a solid being driven by the forces and moment/torque imposed by its surrounding fluid. Assuming a large initial opening angle, the disk accelerates slowly, but swiftly passes the closed position. As a result of the sudden valve closure, a pressure surge occurs in the upstream pipes, exceeding their maximum allowable pressure. Furthermore, the disk does not stabilize at the closed position but continually oscillates due to the unsteady nature of the coolant flow. Because of the significant and continuous water hammer effect, a fix to the butterfly valve is being implemented to prevent rapid valve closure due to failure at the valve's disk/shaft mechanical connection.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

High-throughput multimodal exploration of a nanocrystalline Cu-Ag library

Sputter-deposited, nanocrystalline Cu-Ag thin films produced across a broad compositional and deposition-parameter space were evaluated to unravel the process-structure-property relationships important for creating hard, conductive electrical contacts and coatings. Combinatorial deposition involving pulsed direct current magnetron sputtering of elemental targets enabled swift examination of nearly the full range of alloy compositions and a relevant portion of deposition atomistics. Several high-throughput characterization modalities were employed to evaluate the chemistry, structure, and properties of the films. The resultant hardness, modulus, film density, crystal texture, and resistivity were analyzed in terms of key deposition characteristics (incident atom kinetic energy and incidence angle) predicted by binary-collision, kinematic Monte Carlo simulations. The study revealed improved hardness, parabolic resistivity dependence on composition, and compositional and process dependencies of film tarnishing. The results are discussed in the context of variations in microstructure and film density. Transmission electron microscopy and X-ray diffraction demonstrate several forms of compositional variation including solute segregation to grain boundaries as well as periodic, intragranular compositional modulations. Annealing of a Cu-rich alloy film exhibiting grain boundary segregation showed that this as-deposited, compositional variation is not stable above 100 °C. Finally, the Cu-Ag system is shown to have potential for hard, conductive, tarnish-resistant and room temperature-stable nanocrystalline thin films across the composition space.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Funding a Just Transition Away from Coal in the U.S. Considering Avoided Damage from Air Pollution

Abstract Coal is declining in the U.S. as part of the clean energy transition, resulting in remarkable air pollution benefits for the American public and significant costs for the industry. Using the AP3 integrated assessment model, we estimate that fewer emissions of sulfur dioxide, nitrogen oxides, and primary fine particulate matter driven by coal’s decline led to $300 billion in benefits from 2014 to 2019. Conversely, we find that job losses driven by less coal plant and mining activity resulted in $7.84 billion in foregone wages over the same timeframe. While the benefits were greatly distributed (mostly throughout the East), costs were highly concentrated in coal communities. Transferring a small fraction of the benefits to workers could cover these costs while maintaining societal net benefits. Forecasting coal fleet damages from 2020 to 2035, we find that buying out or replacing these plants would result in $589 billion in air quality benefits, which considerably outweigh the costs. The return on investment increases when policy targets the most damaging capacity, and net benefits are maximized when removing just facilities where marginal benefits exceed marginal costs. Evaluating competitive reverse auction policy designs akin to Germany’s Coal Exit Act, we find that adjusting bids based on monetary damages rather than based only on carbon dioxide emissions – the German design – provides a welfare advantage. Our benefit–cost analyses clearly support policies that drive a swift and just transition away from coal, thereby clearing the air while supporting communities needing assistance.

Dennin, Luke R. (ORCID:0000000205405520)↗
DOE OSTI2024

Ubiquitous short-range order in multi-principal element alloys

Recent research in multi-principal element alloys (MPEAs) has increasingly focused on the role of short-range order (SRO) on material performance. However, the mechanisms of SRO formation and its precise control remain elusive, limiting the progress of SRO engineering. Here, leveraging advanced additive manufacturing techniques that produce samples with a wide range of cooling rates (up to 10 7 K s –1 ) and an enhanced semi-quantitative electron microscopy method, we characterize SRO in three CoCrNi-based face-centered-cubic (FCC) MPEAs. Surprisingly, irrespective of the processing and thermal treatment history, all samples exhibit similar levels of SRO. Atomistic simulations reveal that during solidification, prevalent local chemical order arises in the liquid-solid interface (solidification front) even under the extreme cooling rate of 10 11 K s –1 . This phenomenon stems from the swift atomic diffusion in the supercooled liquid, which matches or even surpasses the rate of solidification. Therefore, SRO is an inherent characteristic of most FCC MPEAs, insensitive to variations in cooling rates and even annealing treatments typically available in experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Improving the fast-charging capability of NbWO-based Li-ion batteries

The discovery of Nb-W-O materials years ago marks the milestone of charging a lithium-ion battery in minutes. Nevertheless, for many applications, charging lithium-ion battery within one minute is urgently demanded, the bottleneck of which largely lies in the lack of fundamental understanding of Li + storage mechanisms in these materials. Herein, by visualizing Li + intercalated into representative Nb 16 W 5 O 55 , we find that the fast-charging nature of such material originates from an interesting rate-dependent lattice relaxation process associated with the Jahn-Teller effect. Furthermore, in situ electron microscopy further reveals a directional, [010]-preferred Li + transport mechanism in Nb 16 W 5 O 55 crystals being the “bottleneck” toward fast charging that deprives the entry of any desolvated Li + through the prevailing non-(010) surfaces. Hence, we propose a machine learning-assisted interface engineering strategy to swiftly collect desolvated Li + and relocate them to (010) surfaces for their fast intercalation. As a result, a capacity of ≈ 116 mAh g −1 (68.5% of the theoretical capacity) at 80 C (45 s) is achieved when coupled with a Li negative electrode.

batteries↗
DOE OSTI2025

Automation and machine learning drive rapid optimization of isoprenol production in Pseudomonas putida

Advances in genome engineering have improved our ability to perturb microbial metabolic networks, yet bioproduction campaigns often struggle with parsing complex metabolic datasets to efficiently enhance product titers. We address this challenge by coupling laboratory automation with machine learning to systematically optimize the production of isoprenol, a sustainable aviation fuel precursor, in Pseudomonas putida. The simultaneous downregulation through CRISPR interference of combinations of up to four gene targets, guided by machine learning, permitted us to increase isoprenol titer 5-fold in six consecutive design-build-test-learn cycles. Moreover, machine learning enabled us to swiftly explore a vast experimental design space of 800,000 possible combinations by strategically recommending approximately 400 priority constructs. High-throughput proteomics allowed us to validate CRISPRi downregulation and identify biological mechanisms driving production increases. Our work demonstrates that ML-driven automated design-build-test-learn cycles, when combined with rigorous data validation, can rapidly enhance titers without specific biological knowledge, suggesting that it can be applied to any host, product, or pathway.

Carruthers, David N↗
DOE OSTI2025

Online energy consumption forecast for battery electric buses using a learning-free algebraic method

Accurately predicting the energy consumption plays a vital role in battery electric buses (BEBs) route planning and deployment. Based on the algebraic derivative estimation, we present a novel method to forecast the energy consumption in real time. In contrast to the mainstream machine-learning-based methods, the proposed method does not require access to the historical energy consumption data. It eliminates the time-consuming and computationally expensive offline training. Consequently, its prediction performance is not constrained by the quantity and quality of the training data. Moreover, the method can swiftly adapt to new situations not included in the previous driving cycles, which makes it especially suitable for emerging transport modes, e.g., on-demand transit services. In addition, its online execution only involves algebraic calculations, yielding superior calculation efficiency. Using real-world data, we comprehensively compare the performance of the proposed learning-free algebraic method with multiple representative machine-learning-based methods. Finally, the advantages and limitations of the proposed method are discussed in detail.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Early photometric and spectroscopic observations of the extraordinarily bright INTEGRAL-detected GRB 221009A

Context. GRB 221009A, initially detected as an X-ray transient by Swift, was later revealed to have triggered the Fermi satellite about an hour earlier, marking it as a post-peak observation of the event’s emission. This GRB distinguished itself as the brightest ever recorded, presenting an unparalleled opportunity to probe the complexities of GRB physics. The unprecedented brightness, however, challenged observation efforts, as it led to the saturation of several high-energy instruments.Aims. Our study seeks to investigate the nature of the INTEGRAL-detected GRB 221009A and elucidate the environmental conditions conducive to these exceptionally powerful bursts. Moreover, we aim to understand the fundamental physics illuminated by the detection of teraelectronvolt (TeV) photons emitted by GRB 221009A.Methods. We conducted detailed analyses of early photometric and spectroscopic observations that span from the Fermi trigger through to the initial days following the prompt emission phase in order to characterize GRB 221009A’s afterglow, and we complemented these analyses with a comparative study.Results. Our findings from analyzing INTEGRAL data confirm GRB 221009A as the most energetic event observed to date. Early optical observations during the prompt phase negate the presence of bright optical emissions with internal or external shock origins. Spectroscopic analyses enabled us to measure GRB 221009A’s distance and line-of-sight properties. The afterglow’s temporal and spectral analysis suggests prolonged activity of the central engine and a transition in the circumburst medium’s density. Finally, we discuss the implications for fundamental physics of detecting photons as energetic as 18 TeV from GRB 221009A.Conclusions. Early optical observations have proven invaluable for distinguishing between the potential origins of optical emissions in GRB 221009A, underscoring their utility in GRB physics studies. However, the rarity of such data underscores the need for dedicated telescopes capable of synchronous multiwavelength observations. Additionally, our analysis suggests that the host galaxies of TeV GRBs share commonalities with those of long and short GRBs. Expanding the sample of TeV GRBs could further solidify these findings.Key words: techniques: photometric / techniques: spectroscopic / gamma-ray burst: general / gamma-ray burst: individual: GRB 221009A

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Exploring the connection between compact object mergers and fast X-ray transients

Context. The connection between compact object mergers and some extragalactic fast X-ray transients (FXRTs) has long been hypothesised but never ultimately established. Aims. In this work, we investigate two FXRTs, the LEIA X-ray Transient LXT 240402A and the Einstein Probe EP 250207b, whose precise positions lie close to nearby (z ≲ 0.1) quiescent galaxies with a negligible probability of chance coincidence, identifying them as particularly promising cases of merger-driven explosions in the local Universe. Methods. We used Chandra to derive accurate localisations for both events and secure otherwise ambiguous associations with their optical counterparts. Deep optical and near-infrared observations with VLT, GTC, and LBT were performed to characterise the surrounding environment and search for kilonova emission, the hallmark of neutron star mergers. Complementary early-time X-ray monitoring with Swift and Einstein Probe was used to constrain the non-thermal afterglow. Results. We find that both FXRTs remain compatible with a compact binary merger progenitor, which produced low-mass ejecta and kilonova emission subdominant to the afterglow. However, alternative explanations such as a distant (z ≳ 1) core-collapse supernova cannot be conclusively ruled out.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Polariton-assisted incoherent to coherent excitation energy transfer between colloidal nanocrystal quantum dots

Here, we explore the dynamics of energy transfer between two nanocrystal quantum dots placed within an optical microcavity. By adjusting the coupling strength between the cavity photon mode and the quantum dots, we have the capacity to fine-tune the effective coupling between the donor and acceptor. Introducing a non-adiabatic parameter, γ, governed by the coupling to the cavity mode, we demonstrate the system’s capability to shift from the overdamped Förster regime (γ $\ll$ 1) to an underdamped coherent regime (γ $\gg$ 1). In the latter regime, characterized by swift energy transfer rates, the dynamics are influenced by decoherence time. To illustrate this, we study the exciton energy transfer dynamics between two closely positioned CdSe/CdS core/shell quantum dots with sizes and separations relevant to experimental conditions. Employing an atomistic approach, we calculate the excitonic level arrangement, exciton–phonon interactions, and transition dipole moments of the quantum dots within the microcavity. These parameters are then utilized to define a model Hamiltonian. Subsequently, we apply a generalized non-Markovian quantum Redfield equation to delineate the dynamics within the polaritonic framework.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

High-Fidelity Multiphysics Modeling of a Heat Pipe Microreactor Using BlueCrab

Researchers who are actively developing nuclear microreactors are planning to employ innovative designs and features using traditional commercial modeling tools that may be inadequate for their design and licensing activities. The codes developed under the U.S. Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation (NEAMS) program provide flexibility in terms of geometry modeling and multiphysics coupling and are particularly well suited for modeling novel microreactor concepts. To test the maturity of these codes, this paper introduces a conceptual heat pipe microreactor (HP-MR) designed to gather various technologies of interest to microreactor developers such as control drums, heat pipes, and hydride moderators. Here, the objective of this effort is to demonstrate NEAMS tools capability to perform high-fidelity multiphysics simulations, using coupled neutronics (via the Griffin code), heat conduction (via the BISON code), heat pipe modeling (via the Sockeye code), and hydrogen redistribution in hydride metal moderator (via the SWIFT code). Codes are coupled in-memory through the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, which permits flexible multiphysics data transfer schemes. The analysis confirmed two key aspects of the HP-MR concept: (1) its ability to follow the power load requested from the heat pipe and (2) its ability to avoid heat pipe cascading failure unless designed with high power close to operating failure limits of its heat pipes. The developed computational model was distributed publicly on the Virtual Test Bed for training purposes to accelerate adoption by industry and to provide a high-fidelity multiphysics solution for benchmarking against other tools. Additional multiphysics analyses including other transients and coupled physics were identified as necessary future work, together with a focus on validating multiphysics behavior against experiments.

Microreactor↗