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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Reduced-order CFD modeling of cryogenic hydrogen isotope extrusion for pellet fueling

This study presents a reduced-order model (ROM) for computational fluid dynamics (CFD) simulations of cryogenic hydrogen isotope extrusions, focusing on protium (H₂) and deuterium (D₂) piston extruders. Using a 2D axisymmetric ROM in ANSYS-Polyflow, significant computational savings were achieved (runtime reduced from 9∼24 h to 3∼5 min), with extrusion force discrepancies between the 2D ROM and 3D models being on the order of 1%. Parametric studies identified optimal cutoff shear rates in the viscosity model (0.01/s for H₂ and 0.001/s for D₂), providing recommendations for future simulations. Finally, a comprehensive comparison of ROM results with experimental data was performed across varying geometries, cryogenic materials, temperatures, extrusion lengths, and piston velocities. Predictions at low extrusion temperatures met the objective of providing quick and efficient solutions with an acceptable extrusion force error of approximately 10% or less, validating the effectiveness of the 2D ROM approach. However, at high temperatures closer to the triple point, extrusion force error grows, which necessitates developing an improved model that accounts for temperature effects, e.g. melting. Nevertheless, the findings still represent a significant improvement in efficiency of CFD modeling of cryogenic hydrogenic extrusion. The ROM framework can also be extended to tritium (T2) and screw extruders, which will ultimately provide a fast and effective tool for optimizing pellet injector design for ITER and future reactor systems.

Fan, Joy [ORNL] (ORCID:0000000229751735)↗
DOE OSTI2025

An experimental and computational study of thin-layer Rayleigh–Taylor instability development during deceleration with and without an externally applied magnetic field

The importance of mitigating the Rayleigh–Taylor instability (RTI) in inertial confinement fusion (ICF) is critical to successfully achieve high gain fusion yield. Consequently, understanding the seed mechanisms of RTI and the potential evolution of RTI in ICF relevant conditions is crucial. Single feature perturbations consistently demonstrate non-linear RTI evolution, for which an experimental platform on OMEGA-EP is developed. Manufacturing defects introduced into the target design require exploration of unanticipated changes to RTI development and an identification of targets that will still render quantifiable physics results. Consequently, it is presented that the inherent 3D nature of experimental targets necessitates 3D modeling for accurate design work and predictive modeling of experimental targets, especially when high resolution imaging diagnostics, like Fresnel Zone Plates, are utilized. A study of the morphology of the RTI evolution due to changing initial conditions and the presence of an externally applied magnetic field are also explored. Experimental data show thin-layer RTI morphology comparable to resistive magneto hydrodynamic 3D results. A discussion on the impacts of an externally applied magnetic field makes the case for continued efforts to observe a magnetic field's impact on RTI morphology.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Representativity error scaling of models of the high temperature test facility

Error scaling is a critical step toward the validation of modeling capabilities for high-temperature gas-cooled reactors (HTGRs). Extensive effort is being made to bring HTGRs into the validation basis of numerous thermal-hydraulics codes. Here, this paper demonstrates how systems-level codes can be leveraged to perform error scaling analyses between an experimental facility and a plant-to-be facility. Specifically, we focus on two conduction cooldown experiments from the High Temperature Test Facility (HTTF) and the General Atomics 350 MW th modular high-temperature gas-cooled reactor (MHTGR-350). The error scaling methodology employed in this study is representativity, which in the context of this work was used to quantify how well experiments captured the physics of the plant facility by comparing sensitivity vectors between the two facilities. In addition, two different RELAP5–3D models of the HTTF were included in the comparison to determine if modeling methodologies notably impact the representativity results. The key figures of merit are the maximum block temperature and the coolant outlet temperature. The time-dependent maximum block temperature had a low representativity of below 0.1 for both models across both transients. The coolant outlet temperature had a higher representativity of around 0.6 for both models during the pressurized conduction cooldown, but it was below 0.2 for the depressurized conduction cooldown. Overall, the HTTF experiments were not representative of the transients in the MHTGR-350. However, these results can play a significant role in informing future potential experiments for HTGR systems that iterate on what the HTTF accomplished.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

X-ray Micro-Computed Tomography for Structural Analysis of All-Solid-State Battery at Pouch Cell Level

Characterizing the microstructure of all-solid-state batteries (ASSBs) during fabrication and operation is vital for their advancement, particularly as scaling to pouch cell levels introduces challenges in probing large-scale microstructural evolution. This work highlights the potential of synchrotron X-ray micro-computed tomography (sXCT) as a nondestructive, rapid (<30 min), and high-resolution technique for visualizing and quantifying key microstructural features, including overhang, porosity, contact loss, active surface area, and tortuosity, in all-solid-state pouch cells. The large field of view (up to millimeters) of sXCT enables detailed analysis at an industry-relevant scale, bridging the gap between laboratory research and commercial applications. Furthermore, integrating realistic sXCT-derived 3D models into multiphysics simulations could provide insights into chemo-mechanical degradation, particularly at the edges of the pouch cells, offering a pathway for designing robust, high-performance ASSBs. This perspective establishes sXCT as an indispensable tool for advancing both the understanding and the engineering of next-generation energy storage systems.

25 ENERGY STORAGE↗
DOE OSTI2025

A Machine Learning Framework for Predicting Microphysical Properties of Ice Crystals From Cloud Particle Imagery

The microphysical properties of ice crystals are important because they significantly alter the radiative properties and spatiotemporal distributions of clouds, which in turn strongly affect Earth's climate. However, it is challenging to measure key properties of ice crystals, such as mass or morphological features. Here, we present a proof-of-concept framework for predicting three-dimensional (3D) microphysical properties of ice crystals from in situ two-dimensional (2D) imagery. First, we computationally generated synthetic ice crystals using 3D modeling software along with geometric parameters estimated from the 2021 Ice Cryo-Encapsulation Balloon (ICEBall) field campaign. Then, we used synthetic crystals to train machine learning (ML) models to predict effective density ($ρ_e$), effective surface area ($A_e$), and number of bullets ($N_b$) from synthetic rosette imagery. On unseen synthetic images, our ML models accurately predicted ice crystal properties. ResNet-18 performed best, achieving $R^2$ values of 0.99 and 0.98 for $ρ_e$ and $A_e$, respectively, and MAE of 0.10 for mathematical equation in single view tasks. Stereo view ResNet-18 further reduced RMSE by 40% for $ρ_e$ and $A_e$ and reduced MAE by 0.08 for $N_b$. This work provides a novel ML-driven framework for estimating ice microphysical properties from in situ imagery, which will allow for downstream constraints on microphysical parameterizations, such as the mass-size relationship.

Ko, J. [Columbia Univ., New York, NY (United State↗
DOE OSTI2025

Viroid-like “obelisk” agents are widespread in the ocean and exceed the abundance of RNA viruses in the prokaryotic fraction

Abstract “Obelisks” are recently discovered ribonucleic acid (RNA) viroid-like elements present in diverse environments with no phylogenetic similarity to any known biological agent. obelisks were first identified in the human gut and in a commensal bacterium acting as a replicative host. They have a circular ∼1 kb RNA genome, rod-like secondary structures, and the encoding of a protein superfamily called “Oblins”. We performed a large-scale search of obelisks in the ocean using the Pebblescout program and the transcriptomic Sequence Archive Read databases, revealing the biogeography and abundance of these viroid-like RNA elements. We detected 55 obelisk genomes resulting in 35 marine clusters at the species level. These obelisks were detected in the prokaryotic fraction and to a lesser extent in the eukaryotic fraction, and distributed across all the oceans from surface to mesopelagic including the Arctic, and even in the coldest seawater of Earth beneath the Antarctic Ross Ice Shelf. The obelisk hallmark protein Oblin-1 confirmed by 3D models was found in various marine samples. Some of the detected marine obelisks harbor hammerhead self-cleaving ribozymes in both polarities. In the prokaryotic, but not the eukaryotic, fraction of the Tara Ocean dataset, relative abundance of obelisks calculated by transcriptomic fragment recruitment indicated that they are abundant in marine samples, reaching or even exceeding the relative abundance of the previously discovered uncultured RNA viruses. In conclusion, obelisks are abundant and widespread viroid-like elements that should be included in ocean biogeochemical models.

Environmental Sciences & Ecology↗
DOE OSTI2025

A Misalignment Tolerant Magnetic Coupler Design and Implementation for Wireless Charging of Unmanned Aerial Vehicles (UAVs)

Wireless power transfer technology is getting more attention these days as a part of expanded battery charging infrastructure and network at a wide range of power levels. Charging Unmanned aerial vehicles (UAVs) is one wireless charging application, and charging their batteries can be challenging because they have short flight times and are frequently charged. For wireless charging of UAVs, the misalignment performance of the magnetic coupler pads is critical because landing on a charging pad at a perfectly aligned position is difficult and can be time-consuming. Different coil shapes and system structures have been proposed in the literature to overcome this challenge. A new design with a high misalignment tolerance is needed; therefore, to fill this gap, a wireless power transfer system has been designed for a 250 W UAV battery charging system with a new magnetic coupler design. A 3D model of the proposed design was created, and finite element simulations were performed. To prove the proposed design, the magnetic coupler prototypes were developed, and experimental results are presented herein. The misalignment tolerance of the proposed system was observed for various rotational positions of the secondary coil, from 0° to 360°. The results demonstrate that DC–DC efficiency varies between 80% and 85% within full 360° rotation of the receiver coil. This result enables the proposed system to address the misalignment problem for wireless charging of UAVs.

UAVs↗
DOE OSTI2024

Aerial Inspection Planner

SAND2025-04581O Aerial Inspection Planner is a software tool that creates aerial trajectories for full coverage of a 3D object at minimum cost. It can be used for inspection of aircraft, buildings, ships, wind turbines, etc. It uses a 3D model of the object, and given the coverage constraints, outputs an efficient flight path for a UAV to follow.Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Moon, Brady↗
DOE OSTI2025

Fitness for Service Assessment of a Corroded Heat Exchanger

Fermilab s Main Injector Accelerator has used shell & tube heat exchangers to cool various beamline components since its construction in the late 1990s. Many of the heat exchangers still around today are original to the machine. Untreated pond water has been used to exchange heat with the Low Conductivity Water. Throughout the lifetime of Fermilab s heat exchangers, they have undergone significant material degradation in the carbon steel end channels due to corrosion. Wall thickness measurements (per API 510) of each heat exchanger were used to generate a 3D model of the corroded surfaces. In order to continue their safe and reliable operation, ASME FFS-1/API 579 (Fitness-For-Service) was implemented to address their integrity. The assessments consisted of finite element analysis techniques outlined in ASME Section VIII Div. 2 (design by analysis methods for pressure vessels), in accordance with the requirements of ASME FFS-1 Part 4: General Metal Loss, Part 5: Local Metal Loss, and Part 9: Crack Like Flaws. The assessments concluded that each heat exchanger is coined Fit For Service . The Fitness-For-Service standard offers a unique opportunity to facilities and institutions within the DOE National Lab complex to properly and safely assess the integrity of aging equipment necessary to conduct science and research. This poster demonstrates the assessment process and techniques used to determine the heat exchangers are fit for service.

Humenik, Alex [Fermilab]↗
DOE OSTI2024

Quantitative Analysis of Rhodobacter sphaeroides Storage Organelles via Cryo-Electron Tomography and Light Microscopy

Bacterial cytoplasmic organelles are diverse and serve many varied purposes. Here, we employed Rhodobacter sphaeroides to investigate the accumulation of carbon and inorganic phosphate in the storage organelles, polyhydroxybutyrate (PHB) and polyphosphate (PP), respectively. Using cryo-electron tomography (cryo-ET), these organelles were observed to increase in size and abundance when growth was arrested by chloramphenicol treatment. The accumulation of PHB and PP was quantified from three-dimensional (3D) segmentations in cryo-tomograms and the analysis of these 3D models. The quantification of PHB using both segmentation analysis and liquid chromatography and mass spectrometry (LCMS) each demonstrated an over 10- to 20-fold accumulation of PHB. The cytoplasmic location of PHB in cells was assessed with fluorescence light microscopy using a PhaP-mNeonGreen fusion-protein construct. The subcellular location and enumeration of these organelles were correlated by comparing the cryo-ET and fluorescence microscopy data. A potential link between PHB and PP localization and possible explanations for co-localization are discussed. Finally, the study of PHB and PP granules, and their accumulation, is discussed in the context of advancing fundamental knowledge about bacterial stress response, the study of renewable sources of bioplastics, and highly energetic compounds.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Machine Learning for Additive Manufacturing of Functionally Graded Materials

Additive Manufacturing (AM) is a transformative manufacturing technology enabling direct fabrication of complex parts layer-by-layer from 3D modeling data. Among AM applications, the fabrication of Functionally Graded Materials (FGMs) has significant importance due to the potential to enhance component performance across several industries. FGMs are manufactured with a gradient composition transition between dissimilar materials, enabling the design of new materials with location-dependent mechanical and physical properties. This study presents a comprehensive review of published literature pertaining to the implementation of Machine Learning (ML) techniques in AM, with an emphasis on ML-based methods for optimizing FGMs fabrication processes. Through an extensive survey of the literature, this review article explores the role of ML in addressing the inherent challenges in FGMs fabrication and encompasses parameter optimization, defect detection, and real-time monitoring. The article also provides a discussion of future research directions and challenges in employing ML-based methods in the AM fabrication of FGMs.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

Design and Demonstration of a NH3-Fueled Two-Stroke Uniflow Engine for Greenhouse Gas Reduction

The maritime shipping industry is growing increasingly interested in both low and non-carbon-containing fuels to meet future greenhouse gas emission targets. Specifically of interest is ammonia, as it has a relatively high volumetric energy density compared to other future fuels, such as hydrogen, making it more economical to transport. The robust engine architecture of low-speed two-stroke marine engines makes them an ideal candidate for ammonia fuel, overcoming many of the issues surrounding its poor ignitability and low flame speed. If emissions and fueling system challenges can be addressed, retrofits of current low-speed two-stroke dual-fuel engines represent a viable pathway for bringing ammonia engines to market. This study explores these technical hurdles by describing the design, analysis, and experimental validation of a single cylinder research engine converted to operate on ammonia fuel. The engine is a reduced-scale uniflow two-stroke marine engine with two previous hardware configurations available – diesel and high-pressure CNG dual-fuel. A concept study was used to evaluate possible ammonia-fueled engine architectures and the associated tradeoffs and design considerations. With the chosen architecture, low-pressure dual fuel, 1D and 3D analysis tools were used to inform hardware selection and to determine hardware configurations which minimized ammonia-slip. In addition to these considerations the hardware and engine configuration were designed to provide a versatile and robust testing platform. This includes options to test both gaseous and liquid ammonia injection, as well as a wide range of performance parameters such as AFR, swirl, valve timing, SOI, and many others. Design constraints imposed by the existing engine hardware necessitated an iterative loop between design and analysis toolsets, ultimately converging on a final design for the ammonia-conversion hardware. The engine was rebuilt with the new hardware and evaluated in an engine test cell. A new control strategy developed and flashed onto a prototyping electronic control unit allowed for full control over all engine parameters. An initial calibration was developed, providing test data for validation of the engine 1D and 3D models. The impact of the design choices on engine operability and the ability to meet program targets is discussed as well as opportunities for further optimization of the ammonia-conversion hardware, informed by the validated models.

Kaul, Brian [ORNL] (ORCID:0000000184813620)↗
DOE OSTI2025

Evaluating FRI3D for Cost Savings in Fire Hazard Analysis at DOE Sites

A fire hazard analysis, required for many U.S. Department of Energy (DOE) facilities, is a complex, cumbersome, and costly process. Fire hazard analyses may be viewed as a checkbox, but ideally and in spirit with the DOE-STD-1066, the fire hazard analysis (FHA) should be a part of the workflow and used to help in modifications, maintenance, and improving operational safety. With current FHA development processes, it is both time and cost prohibitive for true integration. A tool called Fire Risk Investigation in 3D or FRI3D was developed under the DOE Light Water Reactor Sustainability program to simplify and automate many aspects of a fire probabilistic risk analysis for existing nuclear power plants. The FRI3D tool automates fire scenarios by combining approved fire simulation codes, U.S. Nuclear Regulatory Commission fire calculations methods, 3D modeling and visualization, and probabilistic risk analysis models into a single workflow supported with a user interface. FRI3D was initially designed for used in combination with a PRA, this case study, evaluated using FRI3D for a plant modification, determined the benefits that detailed fire modeling can have for U.S. Department of Energy facilities with or without a PRA model. It also looked at what tasks from DOE requirements could be reduced using the tool and what is needed to integrate fire hazard analysis into site workflow.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2025

2025 Intern Poster - Abbigail Short

The OSCC Coupling Shaft Handling Fixture, known as the "Puppy Dog Tool," was originally designed by hand in 1976. The initial design was difficult to read and replicate, lacking 3D modeling for simulations and testing. To modernize the tool, the original drawings were reviewed and recreated in Autodesk Inventor with increased spacing for clarity. Key improvements included adding a hook, modifying the top plate and main body connection, and introducing a guiding wall for the clamp. These changes enhanced durability and usability, preventing bending and facilitating easier assembly. The updated design preserved the tool's functionality while making it more robust and user-friendly for high-precision operations.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Modeling Electrodeposition in 3D Porous Architectures for Solid-State Li-Metal Batteries

Li-metal storage in three-dimensional (3D) electrodes is considered a potential dendrite-mitigation strategy. The large surface area and high porosity of these electrodes result in reduced local Li-plating current densities. The porous topology provides a scaffold for Li-deposition and stripping, maintaining both mechanical integrity and Li accessibility. The goal of this study is to understand how characteristics, such as geometry and material properties, affect the current distribution and deposition pattern. To this end, we developed a computational method to track material growth driven by electrodeposition within a complex geometry. This method ensures that the finite-element discretization remains conforming to the moving boundary while preserving an adequate mesh quality, and thus maintains solution accuracy. Using this new computational tool, we analyze the conditions under which porous anode architectures effectively expand the surface area of the charge-transfer interface, and self-regulate current density and dendrite growth.

3D electrode architectures↗
DOE OSTI2024

Utilizing 3D Mechanical Earth Models for Calibration and Validation in a Large-Scale Carbon Capture and Storage Project in North Dakota

Conference paper presented at 17th International Conference on Greenhouse Gas Control Technologies (GHGT-17), Calgary, Alberta, Canada, October 20–24, 2024. Three-dimensional (3D) mechanical earth models (MEMs) are pivotal in assessing geological sites for carbon dioxide (CO 2 ) storage and mitigating potential risks associated with storage and injection. The Energy & Environmental Research Center is exploring innovative carbon storage monitoring techniques at a CO 2 storage site near Beulah, North Dakota. These methods aim to provide lower-impact, faster feedback for commercial carbon capture and storage (CCS) projects. The research includes monitoring CO 2 injection using various approaches: 1) an automated, integrated modular monitoring station; 2) time-lapse electromagnetic (EM) field surveys; 3) drone-based surveillance; 4) time-lapse seismic techniques; and 5) advanced wellbore monitoring.

02 PETROLEUM↗
DOE OSTI2024

Temporal and spatial resolution of magnetosome degradation at the subcellular level in a 3D lung carcinoma model

Magnetic nanoparticles offer many exciting possibilities in biomedicine, from cell imaging to cancer treatment. One of the currently researched nanoparticles are magnetosomes, magnetite nanoparticles of high chemical purity synthesized by magnetotactic bacteria. Despite their therapeutic potential, very little is known about their degradation in human cells, and even less so of their degradation within tumours. In an effort to explore the potential of magnetosomes for cancer treatment, we have explored their degradation process in a 3D human lung carcinoma model at the subcellular level and with nanometre scale resolution. We have used state of the art hard X-ray probes (nano-XANES and nano-XRF), which allow for identification of distinct iron phases in each region of the cell. Our results reveal the progression of magnetite oxidation to maghemite within magnetosomes, and the biosynthesis of magnetite and ferrihydrite by ferritin.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Learning a general model of single phase flow in complex 3D porous media

Modeling effective transport properties of 3D porous media, such as permeability, at multiple scales is challenging as a result of the combined complexity of the pore structures and fluid physics—in particular, confinement effects which vary across the nanoscale to the microscale. While numerical simulation is possible, the computational cost is prohibitive for realistic domains, which are large and complex. Although machine learning (ML) models have been proposed to circumvent simulation, none so far has simultaneously accounted for heterogeneous 3D structures, fluid confinement effects, and multiple simulation resolutions. By utilizing numerous computer science techniques to improve the scalability of training, we have for the first time developed a general flow model that accounts for the pore-structure and corresponding physical phenomena at scales from Angstrom to the micrometer. Using synthetic computational domains for training, our ML model exhibits strong performance (R 2 = 0.9) when tested on extremely diverse real domains at multiple scales.

36 MATERIALS SCIENCE↗