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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Analysis of pumped thermal energy storage using particle media integrated with concentrating solar power

Pumped Thermal Energy Storage (PTES) is an electricity storage system that converts electricity into thermal energy which is stored and later transformed back into electricity. Previous work has illustrated that particles have low capital costs and can be operated over a wide range of temperatures. PTES with particle storage achieves higher round-trip efficiency and specific power output than when molten salt thermal energy storage is used. This article explores hybrid systems that combine PTES with Concentrating Solar Power (CSP). Hybrid systems share the majority of components thereby reducing costs compared to two stand-alone devices. In addition, hybrid systems can provide multiple services (such as renewable power generation and electricity storage services). Using particle thermal storage in these hybrid concepts provides freedom in choosing the design conditions, since a wide range of operating temperatures is allowable, therefore making it possible to identify hybrid system designs that have good performance. In this article, two concepts for hybrid PTES-CSP are introduced. Thermodynamic models are developed and these are used to evaluate the performance of two hybrid systems. These models account for turbomachinery efficiency, and approach temperature and pressure loss in heat exchangers, as well as other sources of inefficiency, such as motor-generator losses, and air fan power. The “Solar Top-Up” Concept uses CSP to increase the temperature delivered by the charging heat pump. The discharging system uses a topping gas cycle and a bottoming steam cycle to fully exploit the available energy. Using solar heat to increase the maximum temperature from 750 K to 1100 K increases the round-trip efficiency from 41 % to 62 % and the specific work output from 88 kJ/kg to 301 kJ/kg. The second concept is a “Dual-Mode” device which provides both electricity storage and solar electricity generation with the same set of components. The PTES-mode and CSP-mode performance are optimized at different design values but careful parameter selection leads to good performance of both modes: one design produces PTES round-trip efficiency > 60 %, CSP heat engine efficiency > 40 %, and specific work outputs > 150 kJ/kg (for both cycles), when the particle receiver temperature is > 1200 K and maximum heat pump temperature is 1100 K.

14 SOLAR ENERGY↗
DOE OSTI2025

Control-Agnostic Beam Instrumentation with Redis at the Core

Redis isn’t a database — it’s our protocol. Fermilab’s RedisAdapter provides a high-performance, control-system-agnostic bridge between digitized beam data and downstream consumers such as ACNET and EPICS. It forms the foundation of three new software components deployed across MicroTCA-based digitizers: GMMDM, a runtime for memory-mapped data movement from Zynq-based platforms; GRAFE, a front end for Redis-to-ACNET presentation; and GREFE, an EPICS IOC front end. Together, these tools enable modular, standardized instrumentation pipelines. Precision timing is handled via White Rabbit PPS distribution, allowing nanosecond-scale synchronization across crates. This architecture, originally prototyped in Booster BPM systems, is now deployed on modern hardware and designed to meet the performance, modularity, and scalability requirements of the PIP-II era.

Steinkamp, Derek [Fermilab] (ORCID:000900027228626↗
DOE OSTI2024

Component-to-Optimization Workflow Demonstration

This report aims to demonstrate workflow-generating algorithms for optimizing dispatch across a broad range of Integrated Energy System applications using the Framework for Optimization of Resources and Economics (FORCE) tool suite. The optimization is performed at two different time scales. In the coarse time scale, the optimization focuses on a class of energy sources and consumers and aims to find the optimal combinations and flows of energy based on real-time price data information. In the fine time scale, the optimization focuses on a specific thermal energy delivery system and aims to find the optimal setpoints of components in order to meet the energy demands from coarse-time-scale optimizations. In this demonstration, the coarse-scale optimization is implemented using the newly developed Dispatch Optimization Variable Engine (DOVE), while the fine-scale optimization used Optimization of Real-Time Capacity Allocation (ORCA).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Uncovering Structure–Conductivity Relationships in Anion Exchange Membranes (AEMs) Using Interpretable Machine Learning

Anion exchange membranes (AEMs) play a vital role in the performance of water electrolyzers and fuel cells, yet their discovery and optimization remain challenging due to the complexity of structure–property relationships. In this study, we introduce a machine learning framework that leverages conditional graph neural networks (cGNNs) and descriptor-based models and a hybrid graph neural network (HGARE) to predict and interpret ionic conductivity. The descriptor-based pipeline employs principal component analysis (PCA), ablation, and SHAP analysis to identify factors governing anion conductivity, revealing electronic, topological, and compositional descriptors as key contributors. Beyond prediction, dimensionality reduction and clustering are performed by employing t-SNE and KMeans as well as SOM, which reveal distinct membranes clusters, some of which were enriched with high anion conductivity. Among graph-based approaches, the graph convolutional (GCN) achieved strong predictive performance, while the Hybrid Graph Autoencoder-Regressor Ensemble (HGARE) achieved the highest accuracy. Additionally, atom-level saliency maps from GCN provide spatial explanations for conductive behavior, revealing the importance of polarizable and flexible regions. This work contributes to the accelerated and data-driven design of high-performance AEMs.

Naghshnejad, Pegah [Department of Chemical Enginee↗
DOE OSTI2024

Development of a Griffin model of the advanced test reactor

In the pursuit of a higher fidelity deterministic simulation capability of the Advanced Test Reactor, it is important to have a fast yet accurate deterministic neutronics model. Here, to achieve this, we employed an advanced two-step method. The first step involves generating homogenized cross sections using OpenMC, a cutting-edge Monte Carlo neutron transport code. OpenMC offers excellent modular capabilities, allowing for easy component integration and flexibility in incorporating new designs into the model. The second step involves deterministic transport calculations, which are performed using Griffin, a reactor physics application based on the Multiphysics Object-Oriented Simulation Environment (MOOSE). To ensure the accurate spatial resolution and assignment of material cross sections, a Cubit-generated mesh for the Advanced Test Reactor is utilized as an intermediate step between the OpenMC and Griffin models; Griffin utilizes the mesh for its finite element solution, while OpenMC material identifications are written to the mesh file to be used in Griffin material assignments. Additionally, a Python-based script converts the cross sections generated by OpenMC into the ISOXML format required by Griffin. Initial comparisons using the Griffin diffusion solver indicated good agreement between the neutron multiplication factors obtained from the standalone OpenMC model and the Griffin model, with differences of less than 10 pcm in the 2D geometry configuration; it was later determined that this agreement was likely due to compensating effect and was more likely on the order of –700 pcm relative to the OpenMC solution. However, in three-dimensional calculations, an unacceptably large error (almost 8,000 pcm) was found in the Griffin solution with the diffusion solver. Subsequent calculations using Griffin’s discrete ordinates solver demonstrated substantially improved agreement, within 116 pcm of the OpenMC solution used to generate the cross sections for Griffin. Building on this capability, future work will seek to perform more detailed validation calculations. The ultimate goal is to evaluate both transient and multiphysics simulations of the reactor.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Genetic algorithm optimization of nuclear criticality experiment for reduction of intermediate-energy 239 Pu nuclear data uncertainties

Nuclear criticality experiments are conducted to investigate specific nuclear data important for safe handling and storage of fissile materials, reactor design and operation, and the validation of radiation transport codes. Incorrect or uncertain nuclear data can prohibitively impact operational safety limits, reactor licensing, and predictive simulation capability; therefore, integral measurements from criticality experiments are necessary and should be performed frequently. To maximize the impact of the integral measurements, it is important to consider experiment geometry, material selection, and component dimensions. When taking these considerations into account, the experiment design process becomes iterative and very time intensive. This work utilizes a genetic algorithm to efficiently explore potential nuclear criticality experiment designs for the Laboratory Directed Research & Development project PARADIGM (PARallel Approach of Differential and InteGral Measurements) at Los Alamos National Laboratory. In this paper, the building blocks of the genetic algorithm are discussed in detail, the genetic algorithm methodology is verified, and the genetic algorithm is used to produce three candidate experiment models for the final PARADIGM design. The three candidate models produced by the genetic algorithm consist of copper-reflected assemblies containing 14 repeating units of alumina, graphite, boron, and plutonium plates. Furthermore, in addition to the optimization results, final design considerations are also discussed for designs with a height and/or weight very close to or slightly above assembly machine operational limits.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Quantifying market volume sensitivity to material property modifications in polyhydroxybutyrate: A parametric analysis approach

Polyhydroxybutyrate (PHB), a biodegradable biopolymer, represents a promising alternative to petroleum-based thermoplastics. However, despite consistent market growth, PHB faces persistent commercialization challenges that limit widespread adoption. Existing research has focused predominantly on optimizing PHB production processes, leaving a critical gap in understanding which material property modifications would most effectively enhance market competitiveness. This study addresses this gap by systematically analyzing the relationship between polymer material properties and market performance using U.S. market data from 2008 to 2021 for 21 thermoplastic polymers across 19 material properties. We employed principal component regression to identify property modifications that could maximize market volume while reducing CO 2 emissions. Our parametric analysis revealed that two specific material properties – Hardness Shore A and Sheet Extrusion Temperature – significantly influence PHB marketability across different price points. Market simulations demonstrated that a 10% increase in Hardness Shore A could increase PHB market volume by 431.5 million kg while reducing emissions by 188.7 kg CO 2 . A similar 10% increase to Sheet Extrusion Temperature could yield a 297.5 million kg volume increase and a 99.2 kg CO 2 reduction in emissions. Critically, this approach is agnostic to the specific methods required to achieve these property changes, instead providing material scientists with quantitative, data-driven targets for R&D prioritization. Here, this framework offers a novel methodology for evaluating biopolymer competitiveness and supporting strategic decisions to accelerate PHB market adoption and contribute to decarbonization of the plastics industry.

09 BIOMASS FUELS↗
DOE OSTI2026

Understanding failure in austenitic steels: Key considerations for molten salt storage in CSP applications

Owing to their excellent properties, austenitic stainless steels are extensively used in boilers, furnaces, molten salt tanks, and other applications that are subjected to extreme mechanical loads and high-temperature conditions. Their high corrosion and creep resistance make them suitable for high-temperature operating environments. Additionally, good fatigue resistance and favorable mechanical and visual properties are essential. However, the premature failure of several components at elevated temperatures has been previously reported. Although the failure analysis of components in service is complex, processes such as cold work and welding have been identified as contributing factors to the performance degradation of these steels. This study aims to analyze the various documented failure modes and mechanisms in austenitic steels, including creep, cracking, stress relaxation cracking, and fatigue, to better understand the multi-objective design requirements for these alloys as structural materials for high-temperature molten salt tanks in Concentrating Solar Power (CSP) plants. Stabilized austenitic grades, such as AISI 347H, demonstrate superior resistance to creep and corrosion-related degradation when compared to non-stabilized grades like AISI 316L at temperatures relevant to concentrated solar power (CSP) applications. In contrast, nickel-based alloys offer enhanced corrosion resistance, albeit at a higher cost. This review underscores that creep, stress relaxation cracking, and thermo-mechanical fatigue are the predominant long-term failure risks in CSP hot tanks.

14 SOLAR ENERGY↗
DOE OSTI2024

Dynamic Modeling and Simulation of a Subcritical Coal-Fired Power Plant under Load-Following Conditions

Dynamic models for power plants that capture realistic general process trends and effects of manipulated variables are needed to improve load-following, while minimizing carbon footprint. In this work, a dynamic modeling approach and simulation results for subcritical coal-fired power plant components are presented. These encompass simulation of the dynamics in the fireside, including the effects of fuel, air combustion, and the dynamics of the entire waterside and power generation sections. This model development enables the simulation and analysis of the important short and long-time scale dynamics of components such as heaters, evaporative loop, and power generation units. Furthermore, additional variables in the power generation section are introduced to improve model accuracy, extending the prediction capability of subcritical power plant models and opening new opportunities for research in operator training, optimization, and advanced model-based controller design that are based on these models. The change in process gain for different ramp rates associated with disturbance signals that affect process variables is also explored and a correlation developed. This provides opportunities to study disturbance rejection control implementation and adaptation for scenarios with such variations in ramp rates. The prediction capabilities of selected components are compared to data available in literature, with the obtained root mean squared error ranges that reflect the model performance and quality of predictions.

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

A high-density and high-confinement tokamak plasma regime for fusion energy

The tokamak approach, utilizing a toroidal magnetic field configuration to confine a hot plasma, is one of the most promising designs for developing reactors that can exploit nuclear fusion to generate electrical energy. To reach the goal of an economical reactor, most tokamak reactor designs simultaneously require reaching a plasma line-averaged density above an empirical limit—the so-called Greenwald density and attaining an energy confinement quality better than the standard high-confinement mode. However, such an operating regime has never been verified in experiments. In addition, a long-standing challenge in the high-confinement mode has been the compatibility between a high-performance core and avoiding large, transient edge perturbations that can cause very high heat loads on the plasma-facing-components in tokamaks. Here we report the demonstration of stable tokamak plasmas with a line-averaged density approximately 20% above the Greenwald density and an energy confinement quality of approximately 50% better than the standard high-confinement mode, which was realized by taking advantage of the enhanced suppression of turbulent transport granted by high density-gradients in the high-poloidal-beta scenario. Furthermore, our experimental results show an integration of very low edge transient perturbations with the high normalized density and confinement core. The operating regime we report supports some critical requirements in many fusion reactor designs all over the world and opens a potential avenue to an operating point for producing economically attractive fusion energy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Accelerated Fuel Qualification of Fast Modular Reactor Fuel in a Thermal Reactor: Modeling and Simulation Paired with Irradiation Testing

The accelerated fuel qualification (AFQ) methodology is applied by simulating accelerated fuel tests of the General Atomics Electromagnetic Systems’ fuel system for its 44-MW(electric) gas-cooled, fast-spectrum fast modular reactor (FMR). This fuel is comprised of UO 2 pellets in SiGA® cladding, a silicon carbide ceramic matrix composite. Fast reactors, like the FMR, offer many benefits, including high fuel utilization and flexibility, but may require a lengthy material design process if tests are performed using fast neutron irradiation alone. A thermal neutron irradiation can instead be used to rapidly test how well key components of the current material models extend to high burnup. Thermal neutrons produce a different radial power distribution within the pin than fast neutrons. However, the temperature and burnup values for the two neutron types are comparable, and the differences between the simulated fuel responses are relatively small, demonstrating the weak sensitivity of the physics-based fuel model calculations on the neutron type and the irradiation rate. Furthermore, the deformation of the SiGA cladding saturates after about 1 displacement per atom for both neutron spectra. In an accelerated fuel test, the irradiation time required to reach the target fuel burnup can be reduced by a factor of 3 by using a small rodlet with a 45% smaller pellet diameter while maintaining the same linear power. Therefore, the time for data collection up to high burnup can be significantly reduced while maintaining the same temperature profile, which largely determines the material response. Tests of fuel rodlets of standard and compact size will be carried out in the Idaho National Laboratory’s Advanced Test Reactor (ATR), including full size and compact rodlets with varying gap sizes. By applying physics-based mechanistic modeling and simulation in accordance with the AFQ methodology, this type of compact rodlet testing in a thermal test reactor captures the necessary phenomena to test fuel material models up to high burnup and to simulate the expected impact of fast neutron radiation on the fuel in FMR operations. Finally, this approach to testing fast reactor fuels in existing thermal test reactors, paired with advanced physics-based mechanistic modeling and simulation, is expected to be applicable to a range of advanced fuels and will decrease the overall fuel qualification timeframe from decades to years.

Advanced test reactor (ATR)↗
DOE OSTI2024

Precise relative magnitude measurement improves fracture characterization during hydraulic fracturing

SUMMARY Microseismic monitoring is an important technique to obtain detailed knowledge of in-situ fracture size and orientation during stimulation to maximize fluid flow throughout the rock volume and optimize production. Furthermore, considering that the frequency of earthquake magnitudes empirically follows a power law (i.e. Gutenberg–Richter), the accuracy of microseismic event magnitude distributions is potentially crucial for seismic risk management. In this study, we analyse microseismicity observed during four hydraulic fracture treatments of the legacy Cotton Valley experiment in 1997 at the Carthage gas field of East Texas, where fractures were activated at the base of the sand-shale Upper Cotton Valley formation. We perform waveform cross-correlation to detect similar event clusters, measure relative amplitude from aligned waveform pairs with a principal component analysis, then measure precise relative magnitudes. The new magnitudes significantly reduce the deviations between magnitude differences and relative amplitudes of event pairs. This subsequently reduces the magnitude differences between clusters located at different depths. Reduction in magnitude differences between clusters suggests that some attenuation-related biases could be effectively mitigated with relative magnitude measurements. The maximum likelihood method is applied to understand the magnitude frequency distributions and quantify the seismogenic index of the clusters. Statistical analyses with new magnitudes suggest that fractures that are more favourably oriented for shear failure have lower b-value and higher seismogenic index, suggesting higher potential for relatively larger earthquakes, rather than fractures subparallel to maximum horizontal principal stress orientation.

58 GEOSCIENCES↗
DOE OSTI2024

Accelerated Lifetime Testing of Main Shaft Seals for Tidal Turbine Rotors

This document will briefly discuss the observations and results from an NREL conducted accelerated lifetime testing of the main shaft seal for the Verdant Power fifth generation Gen5 underwater Tidal Energy Converter (TEC) turbine, which successfully performed at the RITE project in 2020-2021. In order to evaluate a 5-year Service Interval ( SI) for this component, testing at NREL operated the main shaft seal nearly continuously for over 135 (text says 130 days on page 5 and 125 days on page 7 and 137 days on page 11) days at a rotational velocity of 160 rpm while the test stand recorded water pressure, barrier fluid pressure, temperature, and number of cycles., representing ~ 40% of the SI. An additional separate test was conducted to measure the aging behavior of the rubber drive rings. The water pressure reservoir was held constant as 29 psi. Barrier fluid pressure remained relatively constant throughout the duration of the test but was seen to sink to as low as 10.1 psi. No barrier fluid leakage was observed throughout the test. A sudden failure occurred within the seal after the power to test machine was interrupted for a scheduled building maintenance procedure. Upon restarting, the main shaft seal lost all ability to prevent water ingress. The exact cause is not known but is believed to be either a seal assembly issue or a change in the alignment of the seal components during or following the power outage. Following seal disassembly, significant wear was seen on one of the graphite sealing rings. Based on these results it is recommended that a follow-on TEAMER be conducted to rectify protocol and assembly issues to further evaluate SI of this component. The support and participation of Verdant Power Inc, Dovetail Solutions LLC and Garlock Manufacturing Inc were instrumental in understanding the results. NREL thanks them for their significant effort.

13 HYDRO ENERGY↗
DOE OSTI2024

Leveraging Existing Assets for Long Duration Energy Storage

Increased renewables penetration to electrical grid is necessary to reduce overall emissions from the electrical power generation sector. Nonetheless, its integration creates challenges to grid operators who must match the power being generated by intermittent renewables and other traditional energy sources with the demand from consumers, while ensuring the reliability and power quality for the entire system. Energy storage has been proposed as an alternative to natural gas peaking plants and a form to deliver excess renewable energy generation at times of peak demand. For energy storage to provide benefits to end customers (energy consumers), it must be reliable, efficient, and cost effective. The Illinois Sustainable Technology Center (ISTC), one of the surveys that integrate the Prairie Research Institute (PRI), aims to develop a Center for Energy Storage at Existing Assets (CESEA) at UIUC with the participation of Waste Pressure Corp and Ecotek Engineering USA LLC. CESEA will focus on LDES systems that can integrate to existing infrastructure in a manner that reduces the initial capital expenditure and demonstrates the ability to repurpose fossil assets that would otherwise become stranded, to serve the energy transition. CESEA aims to leverage UIUC’s unique facilities to validate LDES systems performance at a relevant operating environment. UIUC’s facilities include a 85-MW combined heat and power (CHP) power plant, two (2) solar PV plants totaling over 18 MWdc of installed capacity, an electrical grid along with a substation at transmission and distribution voltages, a 22-mile gas pipeline network operating at two pressure levels, along with steam and chilled water distribution networks. The new LDES systems will connect to the existing UIUC grid through a new test electrical station, which will have the capacity to accommodate additional connections to test new devices and technologies as part of future CESEA R&D activities. The test electrical station will contain meters, instrumentation, and controls to accurately capture data and allow optimization of control algorithms. CESEA will initially focus on technologies that: i) utilize existing equipment or facilities to perform at least one of the process steps in LDES (charging, storage, or discharging), ii) leverage mature or commercially available components or controls, iii) show potential for cost-leadership in 10+ hour storage at a commercial scale. Initial technologies that were identified to meet these criteria include Compressed Gas Energy Storage (CGES), and TES. CGES stores electricity by raising the pressure of a compressible gas inside a control volume and converting the stored energy to electricity via expansion-generation. CGES is a generalization of CAES that covers any working gas (not just air). A successful CGES demo will help to circumvent many challenges faced by CAES (long development times due to site prospecting, high cost of compression and storage, heat recovery management, etc.) by: 1) utilizing existing infrastructure (compressors, pipelines, underground storage or pressure vessels) used in the transportation and storage of industrial gases for LDES charging and storage; 2) deploying over sites already-developed for industrial applications with minor additional work; 3) leveraging the price structure of commercial industrial gas to cover the costs of electricity used during charging. A previous DOE-sponsored conceptual study (DE-FE-0032018) estimated the levelized cost of energy of a 1.1 MW / 17 MWh CGES system at $0.08/kWh, with a commercial 10x scale system cost estimated at <$0.04/kWh (Giardinella, 2022). The pilot-sized system was estimated to avoid up to 2693 tons of CO2/year.

25 ENERGY STORAGE↗
DOE OSTI2024

Considerations in Proliferation Resistance Optimization of Medical Isotope Facilities

The U.S. Proliferation Resistance and Optimization (PRO-X) program provides a framework for design optimization of a system, component, or feature of a nuclear facility to minimize potential Special Nuclear Material production and diversion pathways while optimizing system performance for peaceful, asintended missions.

Groden, Nicholas D.↗
DOE OSTI2025

Electronics Free Laser Sensing Technology for Minerals and Technology Elements

This presentation presents an electronics free laser sensing technique and its ongoing and potential applications. A laser-based technique, popularly known as laser-induced breakdown spectroscopy has been prototyped for the determination of high-tech elements including rare earth elements and other elements in solid as well as aqueous sources. All optical unit without any electronics has been designed in such a way that it can be installed in the source environment and connected to other required components for controlling and data acquisition from the workstation. Measurement methods and results obtained for selected elemental species and overall performance of the developed prototype will be presented.

HCM Sensor↗
DOE OSTI2024

Standard Analysis Report INV-SAR-79, Revision 0 Chemical and Cement Components 2023 Inventory Estimates

This standard analysis report provides the estimates for the chemical (oxyanions and complexing agents) and cement components with a data collection cut-off date of December 31, 2023. These estimates will be included in a Performance Assessment Inventory Report developed for the U.S. Department of Energy (DOE) performance assessment (PA) for the 2026 Compliance Recertification Application (CRA).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Powdermet CRADA for VELOCITI Voucher (CRADA Final Report)

NLR shall develop a model of an electric thermal energy storage (ETES) system in the System Advisor Model (SAM) framework that uses a salt and particle slurry developed by PowderMet as the thermal energy storage medium. The ETES shall consist of a recuperated sCO 2 Brayton cycle using 2-tank indirect thermal energy storage and an electric heater for heat input. The salt slurry uses chloride salt and operates at a maximum temperature of 500-720°C. The ETES uses dry air cooling. The salt slurry will be modeled as a sensible heat storage medium and as a latent heat storage medium. NLR will use the model to do parametric analysis of the factors affecting the performance (ex., round trip efficiency) of the ETES system. NLR will work with PowderMet to estimate the costs of system components and total system costs, with the levelized cost of electricity (LCOE) as the primary cost metric.

14 SOLAR ENERGY↗