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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

First Results from A $Nb_3Sn$-Coated 1.5-Cell 650MHZ SRF Cavity for Cryogen-Free Industrial Accelerators

Fermilab is advancing the development of a compact, high-power electron beam accelerator using superconducting radio frequency (SRF) technology as a non-radioactive alternative to traditional radiological sources. The current design targets continuous-wave (CW) operation at \SI{1.6}{MeV} and \SI{20}{kW}. To ensure suitability for industrial environments, the system is being designed for cryogen-free operation, driving the adoption of a novel Nb$_3$Sn-coated 1.5-cell SRF cavity operating at \SI{650}{MHz}. This contribution reports on the fabrication, surface preparation, and Nb$_3$Sn coating process of the cavity, as well as first results from vertical test stand (VTS) measurements performed in a liquid helium bath. These initial tests mark a key milestone toward demonstrating the viability of conduction-cooled Nb$_3$Sn SRF cavities for industrial-scale deployment.

Tagdulang, Nikki Diala [Fermilab]↗
DOE OSTI2024

Neutronics analysis of Full Size Plate–1 Experiment using MC21

Qualification and testing of Low Enriched Uranium fuel is desired so that it can be used in research reactors instead of High Enriched Uranium. The Full Size Plate - 1 (FSP-1) experiment involves irradiating a low enriched metallic fuel in the Advanced Test Reactor to assist in this general qualification. Prior to irradiation, an in-depth neutronics analysis is needed to ensure the safety requirements of the Advanced Test Reactor are met. To accomplish this, the MC21 software was used to analyze the FSP-1 experiment, which will allow a test run to be performed with this new fuel in the Advanced Test Reactor Critical facility. By verifying and validating the results of the MC21 software with comparisons to other codes and the preliminary irradiation in the Advanced Test Reactor Critical facility, the FSP-1 experiment will be ready to irradiate using the Advanced Test Reactor. This work is concerned with the neutronics analysis of the FSP-1 experiment using the MC21 software.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Nuclear Structural Component Relevant Properties of Nickel-Based Alloys Produced via Additive Manufacturing

Idaho National Laboratory initiated examination of nickel-based alloys manufactured via three different additive manufacturing methods for potential applications in nuclear, high temperature structural components. The three methods analyzed included laser powder bed fusion, blown powder laser directed energy deposition, and wire-fed gas metal arc directed energy deposition. With the rapid push towards additive manufacturing, codes do not exist that definitively define what is or is not tolerable for each process and application, such as with conventional, wrought products. This report contains the initial work to understand possible manufacturing methods for high temperature alloys, and specifically, void formation, microstructure evolution, corrosion, and mechanical properties. To generate mechanical test data, specimens were tested irrespective of voids and microstructures were analyzed to better understand how to negate/improve these issues. The preliminary results showed major decreases in mechanical performance for material tested. Test specimens will continue to be produced to further improve each additive manufacturing processes, quantify void acceptance, and better understand the most suitable high temperature alloys receptive to additive manufacturing and high temperature nuclear applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

AMMT 2025 Milestone

Idaho National Laboratory initiated the examination of nickel-based alloys manufactured laser powder directed energy deposition additive manufacturing for potential applications in nuclear, high temperature structural components. With the rapid push towards additive manufacturing, codes do not exist that definitively define what is or is not tolerable for each process and application, such as with conventional, wrought products. This report contains the initial work to understand possible manufacturing methods for high temperature alloys, and specifically, void formation, microstructure evolution, and mechanical properties. To generate mechanical test data, specimens were tested irrespective of voids and microstructures were analyzed to better understand how to negate/improve these issues. The preliminary results showed major decreases in mechanical performance for material tested. Test specimens will continue to be produced to further improve additive manufacturing processes, quantify void acceptance, and better understand the most suitable high temperature alloys receptive to additive manufacturing and high temperature nuclear applications.

36 - MATERIALS SCIENCE↗
DOE OSTI2026

Qualifying LaBr3:Ce+Sr detector performance for the Mu2e experiment at Fermilab Using the ELBE Accelerator

A LaBr3:Ce+Sr detector will be used to measure the stopped muon captures at the Mu2e experiment at Fermilab. It has been benchmarked in a test beam experiment performed at the ELBE electron accelerator located at the Helmholtz-Zentrum Dresden-Rossendorf, Germany. ELBE’s pulsed bremsstrahlung beam line was set to deliver an average γ -ray energy of between 4–5 MeV. The detector response was mapped to match Mu2e beam conditions, including rates up to 1 Mcps, energy flux, and time structure. A radioactive calibration source was used to mimic the characteristic 1808.7 keV γ -ray, emitted during the atomic muon nuclear capture in the Mu2e aluminum stopping target. The detector energy resolution was measured as a function of the average energy flux: up to 1 TeV/s for 0.34 s, the steady-operation beam-on time and up to 4 TeV/s for 5 ms to get a conservative estimate of the effect of high intensity Mu2e beam fluctuations. The PMT gain variation as a function of the beam spill length and average intensity has been parametrized and corrected for. When a PMT gain correction corresponding to the average beam-spill intensity is applied, the residual effect of beam intensity fluctuations around the average degrades the energy resolution, σ E γ /E γ , at 1808.7 keV from 0.66% to 0.83%.

Huang, Shihua [Purdue U., West Lafayette]↗
DOE OSTI2026

Conformable, Composite Tank for Liquid Hydrogen Storage in Heavy-duty Ground Transportation

Raytheon Technologies Research Center (RTRC), with its partners, Argonne National Labs and University of Dayton Research Institute proposed to design and manufacture a conformable composite tank prototype to store liquid Hydrogen (LH2) for heavy-duty truck applications. A dual-wall tank concept was proposed where an outer shell covers and protects an inner pressure vessel that stores liquid hydrogen. The inner pressure vessel is liner-less and designed with a conformable concept, derived from prior RTRC ARPA-E program where multiple vessels are coalesced into one, maximizing space utilization and reducing surface area for heat leak. The gap between the dual wall is evacuated of air pressure, and filled with multi-layer insulation to minimize radiative heat transfer. Fiber reinforced composites were proposed for light-weighting and conformable shape manufacture. To minimize LH2 leakage, carbon nanotubes-infused composites were proposed, in addition to use of thin plies. The project was divided into two 18-month budget periods (BP), BP1 and BP2, separated by a Go/No-Go gate review. The high-level goal for BP1 was to demonstrate the feasibility of the overall approach, the tank design, material selection, and manufacturing methodology, build and test a prototype tank; and the goal for BP2 was to design and manufacture a conformal tank per DOE requirements (minimum 20 kg of LH2) and perform a successful test of the tank. The program was terminated about two-thirds of the way through BP1. The outcome of this program would have permitted long-haul trucks and construction vehicles to use liquid Hydrogen, reducing the emission of green-house gases. This technology is applicable to other transportation sectors as well.

08 HYDROGEN↗
DOE OSTI2026

Testing and Expertise for Marine Energy (TEAMER) Program Support (CRADA Final Report)

Virginia Tech (VT) had previously developed a 50 kW AC to DC power converter that is specifically designed to improve the performance and efficiency of wave energy converters (WECs). Through this CRADA, NLR will test the VT power converter via a coupled dynamometer and power electronics test platform. The NLR test platform will be comprised of (1) a rotary dynamometer that will drive a VT provided gearbox and generator, (2) one or more DC regenerative power supplies that provide input power to and take power from the VT supplied power electronics, and (3) a data acquisition system for measurement. NLR will work with VT to develop a test plan, set up the test platform and integrate the test article, perform the testing, and assist in the data analysis.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Quasilinear theory and modelling of gyrokinetic turbulent transport in tokamaks

The theory, development, and validation of reduced quasilinear models of gyrokinetic turbulent transport in the closed flux surface core of tokamaks is reviewed. In combination with neoclassical collisional transport, these models are successful in accurately predicting core tokamak plasma temperature, density, rotation, and impurity profiles in a variety of confinement regimes. Refined experimental tests have been performed to validate the predictions of the quasilinear models, probing changes in the dominant gyrokinetic instabilities, as reflected in fluctuation measurements, cross-phases, and transport properties. These tests continue to produce a deeper understanding of the complex mix of instabilities at both electron and ion gyroradius scales.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Experimental Operation of a Prototype 750C Advanced Chloride Molten Salt Bellows Valve

To achieve DOE 2030 SunShot targets that reduce the cost of liquid-based solar by an additional 40% to 70% beyond 2018 costs, a more reliable, highly manufacturable flow valve, capable of achieving operational temperatures of >700°C is required [1]. This paper investigates the development of an innovative high-temperature chloride molten salt valve, with operation up to 750°C. This valve is intended to be employed within Gen 3 CSP liquid-based thermal energy storage (TES) systems as well as Gen 4 modular salt reactor (MSR) technologies. This work details the general design and flow testing of a bellows-seal flow control valve (FCV). This design includes an integrated closed-loop thermal control system to ensure robust design for freeze-thaw cycles. The self-contained thermal management STM system, is unique in the salt valve industry since it is an integrated solution to provide a consistent, repeatable alternative to typical heat tracing. Additionally, the design includes the employment of a novel heat pipe valve stem to facilitate enhanced passive thermal management into the valve assembly. This valve stem heat pipe is designed to facilitate natural circulation within the bonnet to ensure robust operation, during both nominal and transient thermal operation. The valve body and trim will be designed using SS316H, consistent with Flowserve Corporation’s existing product base and is code qualified but will utilize clad material for materials corrosion, manufacturing cost reduction and compatibility to ensure design flexibility. A test campaign was performed in this investigation utilizing a novel 750°C ternary chloride (20%NaCl/40%MgCl2/40%KCl by mol. wt. %) molten salt flow loop. A discussion about the design and installation of the valves within this test bed is provided for this investigation. Valve test results from this study assessed Cv curves as well as multiple actuator cycles, under varying thermodynamic and operational mode conditions, which would be characteristic within a commercial molten salt facility. The results indicate nominal operation for the baseline design, though improved performance and reliability is expected with the full designed FCV.

Armijo, Kenneth (ORCID:0000000346832147)↗
DOE OSTI2024

Chemical signature characterization with hyperspectral imagery: novel deep learning model architectures and physically-motivated data augmentation techniques

The high spectral resolution afforded by Hyperspectral Imaging (HSI) sensors is poised to bring unprecedented advancements to signature characterization applications. Thus far, much of the research in the machine learning field devoted to HSI applications has focused on a few specific tasks like land-use land-cover classification. In land classification tasks, spatial information is very important, and model architectures are often designed to leverage spatial contexts. However, it is unclear how well these spatially-tuned models will translate to tasks where spectral information is critical, like the detection and characterization of chemicals. In this work, we compare spectral models (inputs are 1D spectra) and spatial-spectral models (inputs are 3D cubes) in the context of predicting chemical concentration maps. We find that spatial-spectral models perform the best, though we find a wide range in performance across the different architectures tested. Additionally, we find that model performance is impacted by the availability of training data, particularly in scenarios where the training data doesn't fully capture the true variance of real-world conditions. We find that data augmentation can help mitigate sparse coverage of observed parameter space (e.g., seasonal or geographic variability in ground cover), and present augmentation strategies that are tailored to hyperspectral data.

• Artificial intelligence (AI) / machine learning ↗
DOE OSTI2024

Field-Emission Properties of Vertically Aligned Carbon Nanotube Cathodes of Varying Geometries

This work characterizes the bulk emission properties of carbon nanotube (CNT) forest cathodes fabricated with various geometries. Geometries explored include dense nanotube forests of varying height grown on 5×5 mm silicon (Si) substrates and discrete, patterned CNT pillars fabricated using UV photolithography. Dense forests heights ranged from 526 μ m to 1.41 mm, with packing fraction for dense forest calculated to be 4e10 nanotubes/cm2 based on an average nanotube separation distance of 100 nm for fixed growth dense forests. Patterned sample micro pillar heights ranged from 47 to 393 μ m with pillar widths on tested samples ranging from 250 to 270 μ m . Properties explored include emission current, turn-on field, and emission current performance over time. A parallel plate electron beam diode with a 100- μ m A-K gap and an automated test apparatus were developed to provide a configurable experiment that provides accurate and repeatable measurements for dc, dc sweep, and timed performance testing. Operating voltages for the voltage sweeps spanned from 0 to −350 V. Furthermore, testing has shown evidence of a hysteresis effect on the emission current tied to the applied field history as well as shifting of the turn-on field magnitude throughout the testing period, suggesting a conditioning effect during use. Three separate emission regions in the I–V curves during sweep testing have also been observed. In the geometric study, dense forests and patterned samples were sweep tested up to a peak applied voltage of −250 V, with the taller samples generally performing better. Currents produced in the geometric study from the dense forest emitters ranged from 36.8 to 572.34 μ A , with current densities ranging from 15 to 2.29 mA/cm2. Currents produced from the patterned micropillar emitters ranged from 39.4 to 317.51 μ A , with current densities ranging from 67 to 3 mA/cm2. DC time testing s...

36 MATERIALS SCIENCE↗
DOE OSTI2024

Aligning lithium metal battery research and development across academia and industry

Successful integration of metallic lithium anodes into secondary batteries could enhance energy density and enable new forms of electrified transportation. However, the outlook for widespread lithium metal adoption in energy storage devices remains mixed. This comes in part from existing gaps in our understanding of the relationships connecting the initial state of lithium, its evolution with cycling, and end-of-life state. It remains important to develop standardized protocols for material and cell characterization, cycling performance, safety, and recycling procedures for lithium metal-based batteries. In February 2023 a cohort of scientists and engineers from academia, national laboratories, and industry gathered to converge on a list of critical challenges and action items to provide better understanding of lithium metal evolution and to enhance academic, governmental, and industrial partnerships to address these challenges. Here, we highlight the major discussion topics revolving around the manufacturing of lithium metal, its related metrology and integration into battery form factors, and best practices testing its electrochemical performance relevant to automotive applications. We introduce a power-controlled discharge testing protocol for research and development cells, in alignment between major automotive stakeholders, that may reveal lithium metal battery dynamics closer to practical driving behavior.

25 ENERGY STORAGE↗
DOE OSTI2026

VRN3P: Variational Recurrent Neural Network Based Net-Load Prediction under High Solar Penetration

This is the final technical report for the SETO-funded VRN3P project (PNNL# 76914). The goal of this project, led by Pacific Northwest National Laboratory (PNNL), in collaboration with Lawrence Livermore National Laboratory (LLNL) and Portland General Electric (PGE), was to develop and validate a deep variational recurrent neural network-based net-load prediction (VRN3P) framework for probabilistic time-series forecasting of day-ahead net-load under high solar penetration scenarios. The project team reports successful design of a novel probabilistic net-load forecasting architecture, comprising of a variational autoencoder and a recurrent neural network, which demonstrates 30% improvement in forecast performance, 60% improvement in training time, and consumes 44% less memory, when compared with conventional baseline models. The team tested the VRN3P model performance on GridLAB-D test-cases representing varying BTM solar penetration levels of 20%, 30%, and 50%, with integrated time-series net-load profiles provided by the utility partner (PGE). The VRN3P model demonstrate <2% hourly MAPE (averaged over the year) for day- ahead net-load forecast on the test scenario with 20% BTM solar. Transfer learning extension of the VRN3P model has demonstrated 8.33× speed-up in training, while still achieving acceptable forecast performance of 2.24% hourly MAPE on the 30% BTM solar penetration test-scenario. A preliminary version of the VRN3P GridAPPS-D™has been developed, along with a web-based interactive user-interface (named ‘Forte’) which has made available on GitHub for public use.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Development and performance evaluation of active insulation systems using solid-state thermal switches

Traditional building envelopes have passive insulation systems that cannot respond to dynamic changes in the environment. An Active Insulation System (AIS) consists of Active Insulation Materials (AIMs) that dynamically vary the thermal conductivity of the insulation system. Several researchers have evaluated the impact of AIS on building thermal and energy performance by using simulation tools. Up to 70% savings in annual heating and cooling energy and significant reductions in peak demand have been predicted for some climates with wall systems employing AIS. However, materials and assembly development still need a cost-effective product that achieves the required performance. Here, in this study, we present the process of developing an AIS that we will install in a test hut for its performance evaluation. Minimum performance criteria of the AIS system are developed based on R-low/R-high ratio, required time and efficiency to switch states, and cost estimates. The following steps during this study are creating the concept to meet the requirements, predicting the performance via simulations, developing the experimental setup for bench-scale testing, and finally, constructing a full-scale wall assembly and monitoring the performance when exposed to environmental chamber tests. The selected approach uses off-the-shelf products to create an AIS that can switch R-value between 0.98 ft 2 ·°F·h/BTU (0.173 m 2 ·K/W) and 5.81 ft 2 ·°F·h/BTU (1.02 m 2 ·K/W) and have a switching time of less than one minute between R-high and R-low.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Time projection chamber for GADGET II

The established Gaseous Detector with Germanium Tagging (GADGET) detection system is used to measure weak, low-energy 𝛽-delayed proton decays. It consists of the Gaseous Proton Detector equipped with a MICROMEGAS (MM) readout to detect protons and other charged particles calorimetrically, surrounded by the Segmented Germanium Array (SeGA) for high-resolution detection of prompt 𝛾 rays. To upgrade GADGET's Proton Detector to operate as a compact time projection chamber (TPC) for the detection, three-dimensional imaging and identification of low-energy 𝛽-delayed single- and multiparticle emissions mainly of interest to astrophysical studies. A new high granularity MM board with 1024 pads has been designed, fabricated, installed, and tested. A high-density data acquisition system based on generic electronics for TPCs (GET) has been installed and optimized to record and process the gas avalanche signals collected on the readout pads. The TPC's performance has been tested using a 220 Rn 𝛼-particle source and cosmic-ray muons. In addition, decay events in the TPC have been simulated by adapting the attpcroot data analysis framework. Furthermore, a novel application of two-dimensional convolutional neural networks for GADGET II event classification is introduced. The optimization of data throughput is also addressed. The GADGET II TPC is capable of detecting and identifying 𝛼 particles as well as measuring their track direction, range, and energy. The extracted energy resolution of the GADGET II TPC using P10 gas is about 5.4% at 6.288 MeV ( 220 Rn 𝛼 events), computed using charge integration. Based on a systematic simulation study, we estimated the detection efficiency of the GADGET II TPC for protons and 𝛼 particles, respectively. It has also been demonstrated that the GADGET II TPC is capable of tracking minimum-ionizing particles (i.e., cosmic-ray muons). From these measurements, the electron drift velocity was measured under typical operating conditions. In addition to being one of the first generation of micropattern gaseous detectors (MPGDs) to utilize a resistive anode applied to low-energy nuclear physics, the GADGET II TPC will also be the first TPC surrounded by a high-efficiency array of high-purity germanium 𝛾-ray detectors. As a result, the TPC of GADGET II has been designed, fabricated, and tested and is ready for operation at the Facility for Rare Isotope Beams for radioactive-beam-line experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Topology-Aware Reinforcement Learning for Voltage Control: Centralized and Decentralized Strategies

Volt-VAR control (VVC) methods based on deep reinforcement learning (DRL) can effectively control distribution grid voltage and minimize power loss by implementing corrective and preventive control measures on the reactive power output of inverter-based distributed energy resources (DERs). However, model-free DRL-based VVC approaches usually cannot capture the important topological feature of the power system since they use a fully-connected network (FCN) to deliver the action. Therefore, this paper proposes a graph convolutional network (GCN)-based DRL approach that can employ the topological information of the network to take better control action for regulating the voltage. Our implementation allows for both centralized and decentralized configurations, utilizing a single agent and multiple agents respectively. Although the centralized GCN-based DRL approach has its advantages of minimizing voltage fluctuation and power loss, it is not suitable for large scale power systems due to its challenges in terms of scalability, computation speed and potential single points of failure. Therefore, these problems can be resolved using the decentralized GCN-based DRL approach. Moreover, to ensure the safe operation of the model, our proposed approach incorporates an exponential barrier function while formulating the reward function for each agent. To validate performance of the proposed approaches, the proposed model is tested on modified IEEE test systems and the performances are measured in terms on voltage fluctuation reduction, minimization of power loss and computational speed. Finally, the results show that the proposed topology-aware approach outperforms the FCN-based DRL approach in terms of reducing voltage fluctuation and minimizing power loss of the network. Moreover, it is shown that the decentralized GCN-based DRL has faster computational speed than other approaches.

42 ENGINEERING↗
DOE OSTI2024

Stack Test Summary for TA-59-0001

The Radioactive Air Emissions Management (RAEM) team performed stack flow characterization tests at Technical Area (TA) 59 Building 0001 Exhaust Stack (ES) 8. These tests were completed in accordance with Title 40 of the Code of Federal Regulations (CFR), Part 61, Subpart H and the American National Standards Institute (ANSI) N13.1-1999 required by the Clean Air Act. Subpart H of the regulation is the National Emission Standards for Hazardous Air Pollutants (NESHAP) for radionuclides, which compliance with is maintained by the REAM team.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Strategies for simulating the time evolution of Hamiltonian lattice field theories

Simulating the time evolution of quantum field theories given some Hamiltonian H requires developing algorithms for implementing the unitary operator e -iHt . A variety of techniques exist that accomplish this task, with the most common technique used so far being Trotterization, which is a special case of the application of a product formula. However, other techniques exist that promise better asymptotic scaling in certain parameters of the theory being simulated, the most efficient of which are based on the concept of block encoding. In this work we study the performance of such algorithms in simulating lattice field theories. We derive and compare the asymptotic gate complexities of several commonly used simulation techniques in application to Hamiltonian lattice field theories. Using the scalar $\hat{φ}$ 4 theory as a test, we also perform numerical studies and compare the gate costs required by product formulas and signal-processing-based techniques to simulate time evolution. For the latter, we use the linear combination of unitaries (LCU) construction augmented with the quantum Fourier transform circuit to switch between the field and momentum eigenbases, which leads to immediate order-of-magnitude improvement in the cost of preparing the block encoding. Further, this paper also includes a pedagogical review of the techniques used, in particular product formulas, LCU, qubitization, quantum signal processing, as well as the technique for simulating geometrically-local Hamiltonians developed by Haah, Hastings, Kothari, and Low.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗