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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Examining Tropical Convection Features at Storm-Resolving Scales Over the Maritime Continent Region

Global Storm Resolving Models (GSRMs) provide a way to understand weather and climate events across scales for better-informed climate impacts. In this work, we apply the recently developed and validated CAM (Community Atmosphere Model)—MPAS (Model for Prediction Across Scales) modeling framework, based on the open-source Community Earth System Model (CESM2), to examine the tropical convection features at the storm resolving scale over the Maritime Continent region at 3 km horizontal spacing. We target two global numerical experiments during the winter season of 2018 for comparison with observation in the region. Here we focus on the investigation of the representations of the convective systems, precipitation statistics, and tropical cyclone behaviors. We found that regional-refined experiments show more accurate precipitation distributions, diurnal cycles, and better agreement with observations for tropical cyclone features in terms of intensity and strength statistics. We expect the exploration of this work will further advance the development and use of the storm-resolving model in precipitation predictions across scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Measuring thermomechanical response of large-format printed polymer composite structures via digital image correlation

Large-format additive manufacturing (LFAM) is a branch of additive manufacturing (AM) research with the ability to create large structures typically measuring several meters in scale. LFAM is advantageous for tooling applications, not only because it offers the ability to create complex geometries not easily made using subtractive manufacturing processes, but the cost savings of pelletized feedstock used by these systems result in larger parts printed at faster speeds than traditional AM systems. Fiber reinforced polymer (FRP) is a commonly used feedstock material in LFAM structures because it reduces the distortion experienced during printing. However, FRP introduces highly anisotropic thermomechanical properties and contributes to a nonhomogeneous microstructure that can result in critical distortion of dimensions during tooling. Measuring the global thermomechanical response of LFAM structures requires a more representative method that accounts for not only anisotropic properties but also the nonhomogeneous nature of the final part. This is where traditional techniques to measure thermomechanical response, such as thermomechanical analysis (TMA), fall short as they assume homogeneity. This study evaluated the coefficient of thermal expansion (CTE) of LFAM structures as measured by TMA as compared to a novel digital image correlation oven (DIC Oven) system. The LFAM structures were made from 20 % by weight carbon fiber reinforced acrylonitrile butadiene styrene (CF-ABS). TMA measurements showed significant variations in CTE across a single LFAM bead, confirming the need for a global technique that captures overall thermomechanical response. The CTE values measured using the DIC Oven compared well to average TMA values obtained from localized measurements across the sample. The DIC Oven was also used to quantify the effects of different layer orientations on thermomechanical properties, which cannot be easily captured using TMA. A predictive model was also developed by using localized TMA values across an LFAM bead to predict the overall thermomechanical response of an LFAM structure.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Low-Cost, High-Performance Carbon Fiber for Compressed Natural Gas Storage Tanks (Final Technical Report – Down Select Report)

The aim of this project is to reduce the cost of Type IV, carbon fiber (CF) composite overwrap compressed gas storage tanks by reducing the cost of CF and CF composites. The project team worked to reduce the cost of CF by exploring and testing opportunities for a low-cost alternative precursor material for CF production to supplant market-dominant and costly polyacrylonitrile (PAN). Concurrently, the team aimed to reduce the cost of the tanks at the composite level by improving the interfacial adhesion between the fibers and the matrix resin through the incorporation of low-cost nanoparticles recycled from waste materials, which would reduce the volume of costly CF required to achieve the same tank performance. At the end of the first year, the project team selected mesophase pitch as the primary precursor candidate from a field of materials based on the superior mechanical performance and cost-saving potential. During the second year, the team produced CFs derived from mesophase pitch achieving an average tensile strength of 365.6 ksi and average tensile modulus of 40.74 Msi. Facility availability for spinning and converting these fibers at greater scale has hindered scale-up demonstration, but the team has identified opportunities to conduct this work in the near term. Cost modeling shows that these mesophase pitch-derived CFs can be up to 40% less expensive than PAN-derived CFs due to the lower cost of the feedstock material, higher throughput, greater conversion yield, and lower cost spinning method and compared to PAN. Additionally, the team has demonstrated at lab-scale that nanoparticle coating CFs can significantly increase the interfacial shear strength and load transfer efficiency of CFs in a matrix. Single filament pull-out testing showed a 27% average increase in max interfacial shear strength due to this coating. A continuous method of applying these coatings to a tow of CF has been developed for scale-up. 26 m tows of coated CFs were produced using this system and formed into composite ring samples for ASTM ring burst testing. Issues with the testing protocol have limited assessment of these results. A prototype Type IV tank was designed to meet ANSI HGV2 standards, and the design criteria set out by DOE, using the CF properties developed by the team paired with a proprietary resin matrix, a polyamide liner, and aluminum end bosses. The tank weighs 153.1 kg and with a total capacity of 5.8 kg H2 (5.6 kg usable), which yields a gravimetric capacity of 1.17 kWh/kg. Cost modeling predicts that the tank will have a projected cost of $15.73/kWh. Tank performance modeling does not include considerations for fiber-matrix load transfer efficiency improvements offered by nanoparticle coating method.

08 HYDROGEN↗
DOE OSTI2025

Technical Assessment of the Application of Digital Twin and Prognostic Tools for Condition Monitoring

This report was prepared for the U.S. Nuclear Regulatory Commission (NRC) to present use cases of the application of advanced technologies toward meeting the current and future regulatory requirements for maintenance and condition monitoring of structures, systems, and components (SSCs). The advanced technologies considered in this work, collectively referred to as digital twin (DT) technologies, are advanced sensors and instrumentation, data analytics, machine learning and artificial intelligence (ML/AI), and physics-based models. The report presents two use cases of reactor coolant pumps (RCPs) and heat pipes in nuclear power plants (NPPs) with technical and regulatory considerations and opportunities in using advanced technologies for conditional monitoring. Key findings from the exploration of these considerations are as follows: - Uncertainties in sensor data and model predictions must be rigorously addressed through validation and verification processes - Regulatory compliance is paramount, necessitating data driven models to be developed in line with existing codes and standards, as well as considering potential future guidelines for advanced reactors - Explainability and transparency in ML/AI models are essential for developing operator trust and regulatory review, including methods that enhance the interpretability of complex data-driven predictions - Condition monitoring programs must be evaluated for their effectiveness in reducing maintenance-preventable function failures (MPFF) and aligning with plant performance criteria - The deployment of advanced technologies for condition monitoring could lead to a transition from periodic to continuous monitoring, thereby optimizing maintenance schedules - Collaborative efforts between industry stakeholders, regulatory bodies, and technology developers are crucial for the successful adoption of advanced technologies for condition monitoring systems in nuclear facilities In summary, the introduction of advanced technologies into condition monitoring programs represents a significant leap forward in the domain of NPP maintenance. By harnessing the capabilities of advanced sensors, data analytics, and ML/AI, NPP operators can transition from a time-based to a condition-based maintenance approach. This shift can potentially enhance the reliability and safety of critical plant components while optimizing maintenance efforts and minimizing unnecessary outages. The NRC is continuing to explore the regulatory aspects of advanced technologies as part of inservice inspection and inservice testing (ISI and IST) programs by pursuing additional research in this technical area.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Anomaly Detection for Online Monitoring of Thermocouple Sensors in the Advanced Test Reactor

This study explores data-driven anomaly detection methods to analyze sensor fail- ures in the Advanced Gas Reactor (AGR) nuclear fuel irradiation experiments. Specifically, we examine failures of thermocouples (TCs), which are critical for mon- itoring and controlling in-reactor temperatures during operation. Failures were pri- marily observed during abrupt power transitions and manifested as sensor drop-outs, drifts, or unexplained behavior. We applied three time-series analysis techniques— rolling mean smoothing, matrix profile, and vector auto-regression (VAR)—to de- tect anomalies in TC data prior to failure events. The rolling mean method effec- tively highlighted deviations aligned with reported failures, while the matrix profile provided partial early warning but sometimes flagged normal fluctuations during power-down periods. VAR shows potential in capturing multivariate dependencies but requires further calibration. A rare case of TC drift was also documented, which did not result in failure, underscoring the challenge of building predictive models with sparse positive examples. Our findings demonstrate that traditional statistical tools can aid anomaly detection but have limited predictive power without richer training data. We propose future directions including synthetic data generation, real- time surrogate modeling, and multi-modal feature integration. This work provides a foundation for applying robust anomaly detection frameworks to mission-critical sensor systems in experimental settings.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Nature of quantum criticality in the Ising ferromagnet TbV 6 Sn 6

TbV 6 Sn 6 is a topological metal where ferromagnetic Tb ions with strong uniaxial magnetic anisotropy interact with V kagome layers. Inelastic neutron scattering (INS) measurements show that the Tb ions adopt an Ising doublet ground state. Here, we consider whether a transverse magnetic field can drive TbV 6 Sn 6 toward a quantum critical point, providing a rare example of transverse-field Ising criticality in a metallic compound. High-field magnetization measurements reveal a first-order-like spin-reorientation transition at 25.6 T. Our INS-based magnetic model finds that this is caused by an avoided crossing of an excited-state singlet with the ground-state doublet. Surprisingly, our model predicts that quantum critical and tricritical points are accessible within the range of experimentally determined model parameters and may be reached by varying the direction of an applied magnetic field.

36 MATERIALS SCIENCE↗
DOE OSTI2025

The Emergence and Promise of Functional Chemogeography of Organic Matter

Organisms in ecosystems continuously release a myriad of organic matter molecules that undergo microbial and abiotic transformation, processes that critically influence carbon storage and climate feedbacks. Yet, a systematic understanding of what determines the transformation and persistence of organic matter across spatiotemporal scales remains elusive. We propose an emerging framework, termed “functional chemogeography,” to understand transformation and persistence of organic matter based on the chemical traits of molecules. This framework extends beyond a sole focus on intrinsic traits, which remain relatively constant across spatiotemporal scales, to emphasize extrinsic traits such as biochemical transformations and environmental responses, which vary spatiotemporally and are shaped by both intrinsic traits and the environment. When upscaled to the assemblage level using functional diversity indices, these extrinsic traits reveal a significant, and in some cases superior, capacity than intrinsic traits to explain biogeochemical processes, as demonstrated through a case study of dissolved organic matter in China's lakes. In conclusion, by integrating trait-based perspectives into predictive models, this framework helps bridge chemical complexity with ecosystem biogeochemistry, thereby advancing our ability to predict the fate of global organic carbon under environmental change.

chemical traits↗
DOE OSTI2025

Simplified Model and Approach to Transform Infrared Surface Temperature to Film Effectiveness in a Conjugate Heat Transfer Experiment

In the pursuit of more efficient gas turbines, film cooling is a critical technology. This article describes a simplified engineering model based on a one-dimensional thermal resistance network. The model is used to relate film-cooling effectiveness and heat transfer augmentation to local overall cooling effectiveness in a conjugate flat plate experiment. Here, this article presents experimental proof-of-concept data to demonstrate the potential for this model. In contrast to previous approaches, neither the wall heat flux nor the adiabatic wall temperature is required to estimate the local film-cooling performance parameters. The model predicts surface temperatures that are within the experimental uncertainties over the range for which the model is trained and to within five percent when the model is extrapolated to higher coolant channel Reynolds numbers. This article is relevant to conjugate test rigs that can measure the hot-surface temperature distribution with and without film cooling. This information may also be relevant to designers as a method to approximate surface temperatures or used as an approximate heat transfer model for optimization studies.

advanced turbines↗
DOE OSTI2024

Towards engineering the growth morphology of anisotropic bicrystals

Eutectic alloys, such as Pb-free Bi-Sn-Ag or Sn-Ag-Cu, are essential for their low melting points in solder joints but suffer from brittle intermetallic phases, reducing reliability. Traditional solder design relies on equilibrium phase diagrams, often neglecting the kinetic influence of crystalline anisotropy during solidification. This study hypothesizes that the energetics at the solid-solid-liquid trijunction dictate crystalline facet selection. Using the Al-Al 3 Ni alloy as a model, this project combines atomistic simulations and experimental methods to understand interfacial energies and develop predictive models. This approach aims to mitigate the negative effects of intermetallics, enhancing component reliability in electronic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Simplified Model and Approach to Transform Infrared Surface Temperature to Film Effectiveness in a Conjugate Heat Transfer Experiment

This paper describes a simplified engineering model based on a one-dimensional thermal resistance network. The model is used to develop a new method to relate film cooling effectiveness and heat transfer augmentation to local overall cooling effectiveness in a conjugate flat plate experiment. This paper presents experimental proof-of-concept data to demonstrate the potential for this model. In contrast to previous approaches, neither the wall heat flux nor the adiabatic wall temperature is required to estimate the local film cooling performance parameters. The model predicts surface temperatures that are within the experimental uncertainties over the range for which the model is trained, and to within five percent when the model is extrapolated to higher coolant channel Reynolds numbers. This paper is relevant to conjugate test rigs that can measure the hot surface temperature distribution with and without film cooling. This information may also be relevant to designers as a method to approximate surface temperatures or used as an approximate heat transfer model for optimization studies.

advanced gas turbines↗
DOE OSTI2025

Study of same-sign W boson scattering and anomalous couplings in events with one tau lepton from pp collisions at $\sqrt{s}=13$ TeV

A first study is presented of the cross section for the scattering of same-sign W boson pairs via the detection of a τ lepton. The data from proton-proton collisions at the center-of-mass energy of 13 TeV were collected by the CMS detector at the LHC, and correspond to an integrated luminosity of 138 fb −1 . Events were selected that contain two jets with large pseudorapidity and large invariant mass, one τ lepton, one light lepton (e or μ), and significant missing transverse momentum. The measured cross section for electroweak same-sign WW scattering is $1.44^{+0.63}_{-0.56}$ times the standard model prediction. In addition, a search is presented for the indirect effects of processes beyond the standard model via the effective field theory framework, in terms of dimension-6 and dimension-8 operators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Trajectory Shaper: A Solution for Disrupted Cooperative Adaptive Cruise Control

Cooperative adaptive cruise control (CACC) can effectively reduce energy consumption, alleviate traffic congestion, and enhance safety. However, communication-related constraints and uncooperative vehicle users can disrupt CACC during real-world operations, significantly undermining the putative benefits of CACC. To alleviate the negative impacts of disrupted CACC, this study develops the trajectory shaper (TS) methods as backup solutions for two scenarios: (i) communication between vehicles is infeasible, and vehicles execute adaptive cruise control (ACC) using local sensor measurements; (ii) follower vehicles reject forming a cooperative platoon and execute their local distributed controllers using the information attained via communication. When communication is infeasible, a distributed TS is devised on each vehicle to modify the sensor measurements, enabling safe and efficient ACC operations. When communication is available but uncooperative agents are involved, the lead vehicle of the platoon executes a centralized TS to modify the information shared with uncooperative agents, achieving optimal platoon-level performance. The centralized and distributed TSs are implemented based on the model predictive control algorithms to yield optimal modifications on input information. Robustness is also factored to tackle model uncertainties during TS operations to ensure safety and efficiency. Numerical experiments validate the control performance of the proposed TSs.

Zhou, Anye [ORNL] (ORCID:0000000301455579)↗
DOE OSTI2024

Experimental methods to test photoionized plasma models in emission

The expanding foil photoionized plasma platform was developed on the Z-machine at Sandia National Laboratories to produce terrestrial photoionized plasmas at some of the same conditions as those observed in astrophysical black hole accretion disks. The specific scientific goals of the platform are motivated by long-standing astrophysical puzzles related to accreting black hole systems. Ultimately, the experimental goal is to inform the supersolar Fe abundance problem by testing photoionized plasma models in emission with at-parameter laboratory data. High quality high resolution emission data with absolute intensity calibration from a laboratory photoionized plasma have never been collected prior to the experiments described here, providing broader motivation. A robust test of the model predictions requires the successful production of a laboratory photoionized plasma along with measurements of the supporting model inputs including the radiation drive spectrum used to create the photoionized plasma, the electron density, and the temperature. The measured absolute spectral radiance in emission collected from the independently diagnosed plasma can be compared against model calculations performed using the measured inputs. In this paper, we focus on the experimental platform and the model inputs, specifically detailing the methodology used to measure the plasma conditions. The moderate electron temperature of ∼41 eV ± 15 eV and electron density of ∼1e19 ± 1.6e18 e−/cm3 and the ∼3e12 W/cm2 x-ray irradiance at the sample confirm that photoionization dominates the plasma ionization and spectra.

Cho, P. B. (ORCID:0000000291632905)↗
DOE OSTI2025

Direct Air Capture Using Aqueous Amino Acid Solvents in a Crossflow Absorber

Carbon dioxide (CO 2 ) is the most abundant of all greenhouse gases (GHGs). CO 2 levels in the atmosphere are 50% higher than in the preindustrial era, trapping heat. CO 2 removal from the atmosphere by direct air capture (DAC) is needed to achieve the internationally agreed global temperature goals. The most common CO 2 capture technology is absorption by aminebased solvents in packed columns. Amino acid solutions have recently gained attention due to their advantages over traditional amine solvents. To be implemented effectively, DAC industrial processes need to handle large airflow rates in separation absorbers. The large air and solvent flow rates preclude the use of countercurrent columns due to high-pressure drops and the occurrence of flooding. Crossflow air−liquid absorbers are used to handle large air and liquid volumes due to their lower-pressure drop. The objective of this work is to study the influence of crossflow absorber geometric parameters and operating conditions on product formation and process efficiency. An already derived theoretical model for countercurrent absorbers has been modified to simulate the operation of a crossflow DAC absorber. The predictive model was implemented into a computer code that was used to study the efficiency of the processes as geometric equipment dimensions and operating parameters vary. Practical suggestions are made to design more efficient DAC processes.

Absorption↗
DOE OSTI2024

Large spatiotemporal variability in aerosol properties over central Argentina during the CACTI field campaign

Abstract. Few field campaigns with extensive aerosol measurements have been conducted over continental areas in the Southern Hemisphere. To address this data gap and better understand the interactions of convective clouds and the surrounding environment, extensive in situ and remote sensing measurements were collected during the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign conducted between October 2018 and April 2019 over the Sierras de Córdoba range of central Argentina. This study describes measurements of aerosol number, size, composition, mixing state, and cloud condensation nuclei (CCN) collected on the ground and from a research aircraft during 7 weeks of the campaign. Large spatial and multiday variations in aerosol number, size, composition, and CCN were observed due to transport from upwind sources controlled by mesoscale to synoptic-scale meteorological conditions. Large vertical wind shears, back trajectories, single-particle measurements, and chemical transport model predictions indicate that different types of emissions and source regions, including biogenic emissions and biomass burning from the Amazon and anthropogenic emissions from Chile and eastern Argentina, contribute to aerosols observed during CACTI. Repeated aircraft measurements near the boundary layer top reveal strong spatial and temporal variations in CCN and demonstrate that understanding the complex co-variability of aerosol properties and clouds is critical to quantify the impact of aerosol–cloud interactions. In addition to quantifying aerosol properties in this data-sparse region, these measurements will be valuable to evaluate predictions over the midlatitudes of South America and improve parameterized aerosol processes in local, regional, and global models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Cloud Feedback Uncertainty in the Equatorial Pacific Across CMIP6 Models

Cloud feedback is the largest uncertainty in estimating Equilibrium Climate Sensitivity. In this study we focus on the equatorial Pacific, where CMIP6 model cloud feedback spread is notably large. Cloud radiative effects in this region are relevant for the global climate. Our findings show that models predict a consistent shift towards the ascent regime in response to El Nino-like sea surface warming. Models diverge in terms of the radiative impact due to differences in cloud characteristics in ascent and subsidence regimes. Using the observed relationship between circulation regime and cloud radiative effect, we find a reduction in the regional mean cloud feedback estimate from 0.77 to 0.22 W m -2 K -1 , though this does not substantially lessen the model spread in total feedback. Pathways to reduce this spread include: improving confidence in the regional ocean warming pattern, and using observations and models to understand cloud type and circulation interactions.

CMIP6↗
DOE OSTI2026

EASY-SHIFT v Alpha

The software is a generic, price- and load-responsive control algorithm integrating heat pumps with thermal energy storage. The algorithm leverages simple models of the system and easily accessible data to schedule operation of heat pumps and thermal energy storage in ways that minimize the cost of operating the heating/cooling system. This tool is specifically designed to be easy to interact with, and something that industry partners are able to adopt. There are two current state of the art approaches. Industry tends to develop very simple algorithms, with predetermined schedules that are not capable of changing operation in response to changes in operating environment. For example, a control designed to avoid high-price electricity from 5-8 PM will not be able to adapt if the high-price period changes to 4-9 PM. Academia commonly develops algorithms called Model predictive control (MPC). MPC requires extensive data and highly trained staff to develop a specific type of simulation model of the building, connect the building to optimization algorithms, and leverage powerful computers. Industry, with limited time/finance budgets for any project, is resistant to adopting MPC due to the associated high complexity and cost.

Grant, Peter [Lawrence Berkeley National Laborator↗
DOE OSTI2024

From soil to sequence: filling the critical gap in genome-resolved metagenomics is essential to the future of soil microbial ecology

Abstract Soil microbiomes are heterogeneous, complex microbial communities. Metagenomic analysis is generating vast amounts of data, creating immense challenges in sequence assembly and analysis. Although advances in technology have resulted in the ability to easily collect large amounts of sequence data, soil samples containing thousands of unique taxa are often poorly characterized. These challenges reduce the usefulness of genome-resolved metagenomic (GRM) analysis seen in other fields of microbiology, such as the creation of high quality metagenomic assembled genomes and the adoption of genome scale modeling approaches. The absence of these resources restricts the scale of future research, limiting hypothesis generation and the predictive modeling of microbial communities. Creating publicly available databases of soil MAGs, similar to databases produced for other microbiomes, has the potential to transform scientific insights about soil microbiomes without requiring the computational resources and domain expertise for assembly and binning.

59 BASIC BIOLOGICAL SCIENCES↗