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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

High-Temperature Active Magnetic Bearing Development for Supercritical CO 2 Machinery Applications

Hermetic machinery utilizing gas bearings for MW-scale supercritical CO 2 (sCO 2 ) machinery applications can have significantly lower power loss and enable improved cycle efficiency compared to conventional machinery with oil-lubricated bearings. Active magnetic bearings (AMBs) are another option anticipated to have similar power loss and load capacity to gas bearings as well as offering larger mechanical tolerances, the ability to tune properties, and high reliability due to lack of mechanical wear. AMBs also have proven commercial experience at MW-scale, though environments for high-temperature sCO 2 power cycle machinery conditions are novel. Besides the potential impact of AMBs for sCO 2 turbomachinery, the technology also offers promising benefits for steam and gas turbines for power generation, compressors and expanders for industrial heat and power, and in other oil and gas and space applications. The goals of this project were to conceptual design an AMB and perform material testing. Conceptual designs for radial and thrust AMBs were produced based on a hermetically-sealed sCO 2 machinery waste-heat recovery (WHR) application for sizing and loads, and choosing a target design temperature of 540°C useful for high-temperature sCO 2 turbines for concentrating solar power (CSP) applications. Conceptual designs were initially developed for multiple radial and thrust AMBs with spreadsheet-based calculations before selecting one of each to develop further using higher-fidelity design methods for magnetic and structural performance. It was found that the radial AMB at 540°C was feasible, but the thrust AMB needed to be limited to 315°C for high-speed operation. The decision for a reduced-temperature thrust AMB was the result of several significant conclusions: 1) Hiperco 50A, originally chosen for good magnetic performance at high temperature, had insufficient strength for high-speed operation, so it was replaced with 17-4 PH. 2) The reduced magnetic performance from 17-4 PH yielded a larger bearing size, reducing the strength margin. 3) This ultimately led to a creative design implementing a more-compact E-core topology, compared to the original (conventional) C-core, and an integral shaft-disk with Hirth joint connection. These conceptual designs are unique for the size and temperature in CO 2 , relevant for MW-scale CSP applications. Long term, high temperature test data was generated for several materials, filling a void in the current body of literature. Corrosion and magnetic performance measurements were produced for PM materials (Alnico 5-7C, Alnico 9C, and SmCo) with and without nickel-coating for environments of high-temperature CO 2 up to 550°C at atmospheric pressure and 450°C at 103 bar for up to 6,000 hours. Corrosion measurements were also produced for Hiperco 50, a SM material relevant for AMB laminations, with and without C5 coating. Comparisons were also made for 450°C and 550°C, atmospheric pressure air exposures up to 5,000 hours. Results generally show that coatings can be effective at improving oxidation resistance of the bare materials, and Alnicos generally outperformed SmCo after high-temperature exposure. In addition to technical feasibility demonstrated by the design, economic feasibility was demonstrated by updating the TEA from the reference machine, re-evaluating it with CAPEX and OPEX to reflect estimated changes from process-lubricated bearings to AMBs. AMBs were shown to be comparable in performance to process-lubricated bearings, still showing a notable improvement over conventional machinery architecture with oil-lubricated bearings.

42 ENGINEERING↗
DOE OSTI2022

ECAR-6330 Rev 0 Computational Fluid Dynamics Evaluation of Core Pressure Drop for the Primary Coolant Apparatus Test

PCAT is a thermal-hydraulic test loop for MARVEL reactor. The design gap thickness between the heater rods of PCAT core is 1.0 mm. The heater elements were manufactured within a straightness tolerance for the designed gap thickness, but several elements have been distorted out of tolerance during the welding process. The distortion of heater rods could lead to flow maldistribution and excessive hotspot temperature when the gap between two heater rods is too narrow. Wire-wraps are the spacer devices widely used in the sodium cooled fast reactor system to maintain the design fuel pitch. Generally, a wire spacer can enhance the turbulent heat transfer, but it increases the pressure drop, which is not desirable for a natural-circulation system like PCAT. Therefore, three short wire-wrap spacers per heater have been proposed to contain the core pressure drops and keep the heater-to-heater gap in an acceptable range. The objectives of this ECAR is to evaluate the PCAR core pressure drop with short wire spacers to confirm that the additional pressure drop due to the wire spacer will not disturb the natural circulation of the PCAT.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2023

Testing of fiber optic based sensors for advanced reactors in the Texas A&M University TRIGA reactor

An Optical Fiber Based Gamma Thermometer has been developed and tested at the Texas A&M University reactor as well as the Ohio State Research Reactor. This sensor technology provides temperature measurement of a thermal mass undergoing gamma heating, from which the gamma flux along the length of the sensor may be calculated. The gamma flux data from an array of OFBGTs could allow the determination of local power density within a nuclear reactor core in three dimensions. The design of the sensor makes use of optical fiber as a truly distributed temperature sensor with a spatial resolution less than 1mm and temperature accuracy of ±1°C. The testing program showed that the system provided the expected temperature data for each location. Overall, this sensor technology shows promise for current Light Water Reactors as well as advanced nuclear reactors by providing an unparalleled level of precision in reactor power measurement.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Energy impact of human health and wellness lighting recommendations for office and classroom applications

The goal of this investigation was to evaluate potential energy impacts of circadian lighting design recommendations gaining attention in a variety of common applications such as offices and classrooms. The renewed focus on health along with advances in SSL technology capabilities has underscored that there is still much to learn regarding the relationship between light and human physiology. The energy implications of designing to address these possible physiological effects are not yet fully understood. Beyond the fact that the basic metric of luminous efficacy (lumens per watt) does not cover these other effects, the emerging science seems to indicate that addressing a holistic view of the human needs in most applications may mean a need for increased light and associated energy use by electric lighting systems. Within the two applications considered, lumen output, spectral characteristics, surface reflectance distribution and desk orientation were varied to explore the magnitude of potential effects. Meeting current IES illuminance recommendations did not satisfy existing EML and CS recommendations for any of the simulations. In some cases, satisfying circadian metric recommendations required average illuminance that was more than double IES recommendations, which may negatively impact lighting quality as well. Using results from 45 unique simulation conditions, it was estimated that lighting energy use may increase between 10% and 100% due to increased luminaire light levels used to meet circadian lighting design recommendations listed in current building standards such as WELL v2 Q2 2019, UL Design Guideline 24480, and CHPS Core Criteria 3.0.

circadian lighting, lighting simulation, solid sta↗
DOE OSTI2024

Highly-detailed neutronic and thermal-hydraulic coupled calculations for OPAL reactor using diverse codes and approaches

The industry-standard approach for designing and operating research reactors cores relies on well-established methodologies that consider uncoupled neutronic calculations and a subchannel analysis of the Thermal-Hydraulic (TH) associated problem. Advancements in computing power and codes allow detailed Multiphysics approaches to be implemented, thereby reducing conservatism. In this study, a comparative analysis of results from diverse detailed neutronic-TH coupled core approaches is developed. To address a realistic application case, the comparison is made for a reported critical configuration from the Open Pool Australian Lightwater research reactor (OPAL) at Hot Full Power (HFP) and low burnup. Both cell-core and stochastic methodologies for neutronics are evaluated, whereas two different subchannel codes are considered for TH. In conclusion, the convergence of the coupled schemes, and the consistency of the main parameters are discussed, showing the compatibility of the alternative methods and their ability to offer critical insights not captured by standard practices.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Better understanding and prediction of antiviral peptides through primary and secondary structure feature importance

The emergence of viral epidemics throughout the world is of concern due to the scarcity of available effective antiviral therapeutics. The discovery of new antiviral therapies is imperative to address this challenge, and antiviral peptides (AVPs) represent a valuable resource for the development of novel therapies to combat viral infection. We present a new machine learning model to distinguish AVPs from non-AVPs using the most informative features derived from the physicochemical and structural properties of their amino acid sequences. To focus on those features that are most likely to contribute to antiviral performance, we filter potential features based on their importance for classification. These feature selection analyses suggest that secondary structure is the most important peptide sequence feature for predicting AVPs. Our Feature-Informed Reduced Machine Learning for Antiviral Peptide Prediction (FIRM-AVP) approach achieves a higher accuracy than either the model with all features or current state-of-the-art single classifiers. Understanding the features that are associated with AVP activity is a core need to identify and design new AVPs in novel systems. The FIRM-AVP code and standalone software package are available at https://github.com/pmartR/FIRM-AVP with an accompanying web application at https://msc-viz.emsl.pnnl.gov/AVPR.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Highly efficient semi-hydrogenation in strained ultrathin PdCu shell and the atomic deciphering for the unlocking of activity-selectivity

Excellent ethylene selectivity in acetylene semi-hydrogenation is often obtained at the expense of activity. To break the activity-selectivity trade-off, precise control and in-depth understanding of the three-dimensional atomic structure of surfacial active sites are crucial. Here, we designed a novel Au@PdCu core–shell nanocatalyst featuring diluted and stretched Pd sites on the ultrathin shell (1.6 nm), which showed excellent reactivity and selectivity, with 100% acetylene conversion and 92.4% ethylene selectivity at 122 °C, and the corresponding activity was 3.3 times higher than that of the PdCu alloy. The atomic three-dimensional decoding for the activity-selectivity balance was revealed by combining pair distribution function (PDF) and reverse Monte Carlo simulation (RMC). The results demonstrate that a large number of active sites with a low coordination number of Pd–Pd pairs and an average 3.25% tensile strain are distributed on the surface of the nanocatalyst, which perform a pivotal function in the simultaneous improvement of hydrogenation activity and ethylene selectivity. Our work not only develops a novel strategy for unlocking the linear scaling relation in heterogeneous catalysis but also provides a paradigm for atomic 3D understanding of lattice strain in core–shell nanocatalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Investigation of Various Transformer Topologies for HF Isolation Applications

High-frequency (HF) transformers are an essential part of many power electronic devices. The performance and behavior of HF transformers can greatly affect the efficiency and performance of all systems, particularly, from a parasitic parameter point of view. In this article, HF transformers' parasitic parameters, such as leakage inductances and parasitic capacitances, are analyzed using a novel analytical method, finite element method (FEM), and experimental measurements of different structures and winding arrangements. Also, the magnetic field, electric field, electric displacement field, and electric potential distribution within the transformers are simulated and analyzed. Four different HF transformers with E and U cores with different windings are designed and analyzed. Investigation outcomes help to classify structures according to the trade-off between leakage inductances and series parasitic capacitances. This information can later be used for the optimal selection and design of transformers as a function of their operating frequency for any power rating and voltage level. Moreover, 3-D FEM and experimental results validate the proposed methodology to be used for designing HF transformers in high-voltage/power applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

ModuleOT

ModuleOT is an open hardware security platform which provides all features necessary for securing remote energy resources. The platform consists of a physical bump in-the wire device which runs a custom-built application built with Go and Python and leverages AES-NI Instruction set available on modern hardware for cryptographic acceleration. By combining these features, ModuleOT acts as an all-in-one low-cost solution to enable cryptographically secured communications to any critical remote servers or devices. Because the software application has been built using Golang, this source can be easily compiled for different hardware platforms. The module is designed to provide the following core features: (1) encrypted communications across an untrusted network, (2) certificate-based authentication with secure storage, (3) hardware cryptographic acceleration, (4) IP-based whitelisting, (5) local firewall management, and (6) legacy (RS485) device support.

Hasandka, Adarsh↗
DOE OSTI2025

Analyzing and Exploring Training Recipes for Large-Scale Transformer-Based Weather Prediction

Abstract The rapid rise of deep learning (DL) in numerical weather prediction (NWP) has led to a proliferation of models which forecast atmospheric variables with comparable or superior skill than traditional physics-based NWP. However, among these leading DL models, there is a wide variance in both the training settings and architecture used. Further, the lack of thorough ablation studies makes it hard to discern which components are most critical to success. In this work, we show that it is possible to attain high forecast skill even with relatively off-the-shelf architectures, simple training procedures, and moderate compute budgets. Specifically, we train a minimally modified Swin Transformer V2 (SwinV2) on ERA5 data and find that it attains superior skill in terms of mean-square errors of deterministic forecasts when compared against the European Centre for Medium-Range Weather Forecasts’ Integrated Forecasting System (IFS). Almost all DL–NWP systems share a core set of hyperparameters and design decisions. To aid and expedite future DL–NWP research, we present an in-depth, systematic exploration of different loss functions, model sizes and depths, patch sizes, and multistep training objectives. We also examine the model performance with metrics beyond the typical accuracy (ACC) and RMSE and investigate how the performance scales with model size. Through our open-source code, scoring pipelines, and models, we share our findings on key aspects of the training pipeline. These ablations reduce the necessity for expensive hyperparameter tuning and lower the barrier to entry for future DL–NWP research. Significance Statement This study investigates the potential of using large-scale transformer-based models for weather prediction, showing that it is possible to achieve high forecast accuracy with simpler, off-the-shelf architectures. By training a minimally modified SwinV2 transformer on ERA5 data, we show that the model achieves competitive forecast skill in terms of mean-square error for key variables, outperforming the European Centre for Medium-Range Weather Forecasts’ Integrated Forecasting System (IFS) at all lead times. Our findings suggest that effective training strategies, such as multistep fine-tuning and channel-weighted losses, significantly enhance the model’s performance. However, we also highlight that these improvements come with trade-offs in other areas, such as ensemble spread and high-frequency spatial detail. This work highlights the promise of deep learning in improving weather forecasts, which could lead to better preparedness and response to weather events, ultimately benefiting society by providing more reliable weather predictions.

Willard, Jared D. [Lawrence Berkeley National Labo↗
DOE OSTI2021

Flattop Benchmark CED-2 (IER-423)

The final design for the Flattop HEU Core Benchmark is presented in this report. Physical measurements will be performed on Flattop components using modern instruments and techniques to define uncertainties necessary to meet contemporary ICSBEP standards. A preliminary re-evaluation of ICSBEP HMF-0028 (Flattop HEU Core) led to the development of IER-423 CED-1, wherein total relative uncertainties in $k_{eff}$ were provided based on a new detailed model. The estimated uncertainty on the total uncertainty is +100%/-0%, given a lack of documented uncertainties on mass, dimensions, and densities of predominantly the natural uranium (NU) and highly enriched uranium (HEU) components.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Design, Modeling, and Testing of a Novel Inductor for Electric Vehicles: Iron Nitride Soft Magnetic Composites

New technology for electric vehicles (EVs) must meet the requirements of higher energy usage, lower costs, and more sustainable source materials. One promising material for EV power system components is iron nitride (IN) soft magnetic composites (SMCs) because of their competitive magnetic properties and high abundance of the source materials. As part of an ongoing program at Sandia National Laboratories, this project focused on using computer modeling to optimize the prototyping process for an iron nitride SMC toroidal inductor to reach a target inductance of 600 μH. Four inductors with different combinations of wiring (26 AWG and 20 AWG) and vol% loading of iron nitride (65 vol% and 50 vol%) were fabricated at Cal Poly and characterized using an LCR meter. These inductors were also modeled using COMSOL Multiphysics™ with the Magnetic Fields module. The inductance data from the experiment and the model show that the 65 vol% IN prototypes and models agree with about 8% difference, while the 50 vol% IN samples show about a 9% difference between the prototype and the model. These results suggest that the model can predict inductance with both accuracy and precision with low confidence for the given sample size of four. An additional parameter of AC resistance is studied but the AC resistance results from the inductors and from the model generally do not agree closely, suggesting that the current model used in the project does not fully capture the mechanisms behind AC resistance of the inductor. With the focus of the project on inductance, the percent difference results of less than 9% across the four inductors that were tested increases confidence in the model’s predictive capabilities for inductance only. Using the inductance results from both the model and experiment, the final suggested inductor design is a 65 vol% core with 150 windings of 20 AWG wire that is 8 cm across and 1.5 cm tall to reach the inductance goal of 600 μH based on analysis using the optimized COMSOLTM model.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Rapid-cycling HTS magnet for muon acceleration

A very wide range of operational temperatures of the HTS (YBCO) superconductor makes it suitable for the construction of rapid-cycling magnets required for the muon acceleration. The measured [3] very low power loss of the 0.4 T magnet operating at 300 T/s suggested a realistic possibility of the HTS-based accelerator magnet with much higher magnetic field and ramp rate. The magnet core and the HTS cable designs for the 2 T field in the 30 mm beam gap are presented. The simulation of the HTS cable hysteresis power loss for the 1000 T/s ramp rate is discussed in terms of the operational temperatures and required cryogenic power.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

TREAT Slide Decks for Alabama A&M

Slides to introduce TREAT and two senior design projects to a professor and senior engineering students at Alabama A&M. Slide Deck 1 is an overview of the TREAT Reactor and its mission. Use for Space Nuclear Thermal Propulsion Testing is mentioned, but no details of space reactor fuel are included. Review for unlimited release is requested. Slide deck 2 presents technical background for neutron radiography, with contrast to x-radiography, and then presents the application of TREAT for Flash Radiography. Slide Deck 3 describes the background behind the second senior design project, which is to design powered actuators for TREAT core clamps. Slide Deck 3 includes photos of different sides of the TREAT reactor and sketches of internal components associated with the core clamping system. These were presented via Teams on October 5, but we want to provide the slidedeck files to the university for student reference.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Strain‐Enhanced Metallic Intermixing in Shape‐Controlled Multilayered Core–Shell Nanostructures: Toward Shaped Intermetallics

Abstract Controlling the surface composition of shaped bimetallic nanoparticles could offer precise tunability of geometric and electronic surface structure for new nanocatalysts. To achieve this goal, a platform for studying the intermixing process in a shaped nanoparticle was designed, using multilayered Pd‐Ni‐Pt core–shell nanocubes as precursors. Under mild conditions, the intermixing between Ni and Pt could be tuned by changing layer thickness and number, triggering intermixing while preserving nanoparticle shape. Intermixing of the two metals is monitored using transmission electron microscopy. The surface structure evolution is characterized using electrochemical methanol oxidation. DFT calculations suggest that the low‐temperature mixing is enhanced by shorter diffusion lengths and strain introduced by the layered structure. The platform and insights presented are an advance toward the realization of shape‐controlled multimetallic nanoparticles tailored to each potential application.

Williams, Benjamin P.↗
DOE OSTI2020

Federal Best Practices: Core Principles of Sustainable Fleet Management

This document is designed to help agency fleet managers understand and implement optimal petroleum reduction strategies for each fleet location by evaluating the most appropriate combination of the four core principles of sustainable fleet management: Right-sizing the fleet to agency mission by implementing a vehicle allocation methodology study; Minimizing vehicle miles traveled; Increasing fleet fuel efficiency by replacing inefficient vehicles with more fuel-efficient vehicles, maintaining vehicles, driving more efficiently, and avoiding excessive idling; Optimizing cost-effective alternative fuel use, including maximizing utilization of existing alternative fuel infrastructure, installing alternative fuel infrastructure where practical (including electric vehicle charging stations), and aligning deployment of alternative fuel vehicles with fueling infrastructure.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

PWR loading pattern optimization with reinforcement learning

The core loading pattern optimization problem belongs to the class of combinatorial optimization problem and has been studied since the dawn of commercial nuclear energy industry. It is characterized by multiple objectives and constraints, with a very high number of candidate patterns, which makes it impossible to solve explicitly. Stochastic optimization methodologies including Genetic Algorithms and Simulated Annealing are used by different nuclear utilities and vendors to perform fuel cycle reload design. Nevertheless, hand-designed solutions continue to be the prevalent method in the industry. To improve the state-of-the-art core reload patterns, we aim to create a method as scalable as possible, that agrees with the designer's goal of performance and safety. To help in this task Deep Reinforcement Learning (DRL), in particular Proximal Policy Optimization is leveraged. DRL has recently experienced a strong impetus from its successes applied to games, sometimes even reaching 'super-human' performances. This paper lays out the foundation of this method and proposes to study the behavior of several hyper-parameters that influence the DRL algorithm. The algorithm is highly dependent on multiple factors such as an exploration/exploitation trade-off that manifests through different parameters such as the number of loading patterns seen and the number of samples collected before a policy update, but also the shape of the objective function derived for the core design. Experimental results also demonstrate the effectiveness of the method in finding high-quality solutions from scratch within a reasonable amount of time. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Instrumentation for the In-Core Real-Time Mechanical Testing of Structural Materials (INCREASE) Project

Idaho National Laboratory (INL), in collaboration with the Electric Power Research Institute (EPRI), the Nuclear Regulatory Commission (NRC), the French Atomic and Alternative Energies Commission (CEA), the Joint Research Center (JRC), the Nuclear Research and Consultancy Group (NRG), and the Research Center Rez (CVR), started a Joint Experimental Program (JEEP) project that operates within the Nuclear Energy Agency’s Framework for Irradiation Experiments (FIDES II) program in order to develop capabilities for the in-core real-time mechanical testing of structural materials. This effort will focus on designing a shared capsule capable of housing a variety of in-core mechanical testing instrumentation allowing enhanced experiments for the material science community. The outcome of the project would be high-priority, stress relaxation data for stainless-steel-based materials provided by EPRI and CEA. Stress relaxation is a major phenomenon that contributes to material degradation in nuclear reactor components. Currently, nuclear material stress relaxation is assessed both before and after irradiation, using complex and costly post-irradiation examination (PIE) activities. In-situ data would support the development of precision modeling and simulation of this degradation phenomena and would provide validation and benchmarking for existing models using the PIE data. As part of the U.S. Department of Energy Advanced Sensor and Instrumentation (ASI) program, INL has fabricated and tested out-of-core mechanical test instrumentation. This instrumentation was designed for easy adaptation to the irradiation capsule proposed under this JEEP, and can be deployed to measure real-time stress relaxation under pressurized-water reactor (PWR) conditions. This initial effort will partially serve to replace the testing capabilities lost because of shutting down the Halden Boiling Water Reactor (HBWR). The project would provide these capabilities to the international community via a shared capsule design that is easily adaptable to additional material test reactors. The design features will incorporate expansion to PWR and non-light-water reactor (LWR) environments that will be developed in future work. The capsule and instrumentation will be demonstrated in the Massachusetts Institute of Technology Reactor (MITR) for phase I and the Petten High Flux Reactor (HFR) for phase II irradiations to deliver real-time stress relaxation data on high priority stainless steel structural materials.

36 MATERIALS SCIENCE↗