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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Numerical modeling and parametric study of a dual purpose underground thermal battery

We report integrating thermal energy storage with building energy systems can enable flexible building electric demands at buildings to help mitigate the mismatch between electricity supply and demand. A novel building heating and cooling system that integrates a dual-source heat pump with hybrid thermal storage named dual-purpose underground thermal battery (DPUTB) has been developed for reshaping building electric demands. The proposed DPUTB integrated geothermal heat pump system is an original innovation that enables Grid-interactive Energy Efficient buildings. This paper focuses on the study of the novel DPUTB. The DPUTB works as both a thermal storage tank (an inner tank) and a ground heat exchanger (an outer tank separated from the inner tank by the insulation material). High fidelity and computationally effective models are needed to predict the performance of the novel DPUTB. This study has developed a simplified dynamic model for the DPUTB according to heat transfer and energy conservation principles and validated it by using experimental data obtained from testing a small-scale DPUTB apparatus. A parametric study was conducted to identify a design that can achieve the target thermal storage performance of load shift and energy efficiency. The parametric study results show that the inner tank shell thermal conductivity and the phase change material's melting point are the two most influencing factors on the performance of the DPUTB. One single full-size DPUTB with the identified design could provide 1-ton cooling (3.51 kW) with the supply temperature lower than 11 °C for 4 hours in summer after being fully charged in 8 hours. The inner tank filled with phase change material is for cooling thermal storage as a latent tank in the design. However, its capacity can be as high as 60 MJ as a sensible water tank for heating storage in winter. In the future study, the DPUTB model will be incorporated into the dual-source heat pump system for evaluating the overall system performance of demand side management in the long term.

25 ENERGY STORAGE↗
DOE OSTI2026

Leveraging large language models to address data scarcity in machine learning for graphene synthesis

Machine learning in experimental materials science faces significant challenges due to the scarcity of data, which are costly and time-consuming to generate, particularly when relying on in-house experiments. Literature data mining offers a potential solution but introduces issues like mixed data quality, inconsistent formats, and non-uniform reporting of synthesis parameters, resulting in partially missing and heterogeneous features across the dataset. Here, we propose data imputation and feature engineering methods that employ pre-trained large language models (LLMs) to enhance machine learning performance on scarce, heterogeneous datasets, demonstrated on graphene CVD synthesis data and the ML-HydPARK hydrogen storage dataset. GPT models perform data imputation via tailored prompting and semantic normalization of inconsistently reported features through embeddings, for example, to harmonize the complex nomenclature of CVD substrates. Beyond yielding more diverse and richer feature representations than traditional methods such as K-nearest neighbors (KNN) and Multivariate Imputation by Chained Equations (MICE), LLM-based data imputation is evaluated against dataset characteristics and prompting strategies. We vary the level of autonomy granted to the LLM, from generic prompting that leverages pre-trained knowledge for autonomous data generation to data-informed prompting that constrains outputs using target-specific information, and demonstrate which level of autonomy yields superior imputation performance across datasets and feature types. The proposed data engineering methods markedly improve downstream performance; for example, in graphene layer number classification using a support vector machine (SVM), binary accuracy increases from 39% to 65% and ternary accuracy from 52% to 72%. Fine-tuning experiments on both datasets show that combining our proposed LLM-based data imputation and feature encoding methods with numerical machine learning predictors outperforms standalone fine-tuned LLM predictors in data-scarce settings. The proposed strategies emphasize data enhancement techniques rather than refining learning architectures or regularizing loss functions, offering a broadly applicable framework for improving machine learning performance on scarce, inhomogeneous datasets.

Chemical vapor deposition↗
DOE OSTI2022

Magnetically Levitated and Constrained Flywheel Energy Storage System

The concept of using linear induction motors to lift, constrain, accelerate, and decelerate a large-scale flywheel is proposed, and some of the advantages are investigated. Calculations for a Magnetically Levitated Energy Storage System (MLES) are performed that compare a single large scale MLES with a current state of the art flywheel energy storage system in order to show the relative differences and advantages of such a system. The system that is used for comparison is a typical Beacon Power flywheel energy system. This is currently one of the state-of-the-art flywheel energy storage systems and so it can be used to provide a basic data set to compare to an MLES system.

VanOsdol, John↗
DOE OSTI2024

Small Hydropower Plant Response Improvement Using Energy Storage

Small hydropower plants contribute significantly to global power generation. However, due to limited storage, these can have low ramping capacity and poor load-frequency regulation. These can prevent small hydropower plants from being used in isolated grids as backup power to critical loads and rural areas. In this paper, a control architecture for frequency control is proposed that facilitates the use of energy storage to improve the response of standalone small hydropower plants. The frequency controller generates power commands using proportional control on frequency deviation and a user-defined power setpoint, and this incorporates with a current controller that facilitates power injection. The distinctive feature of the controller design is that it takes into account frequency thresholds and storage constraints to enable power injections, and it provides the capability to perform automated and manual recharge of the energy storage. Simulations using detailed nonlinear models demonstrate the improved performance of the hydropower with energy storage using the proposed controller. Automated and manual recharge and the impact of the energy storage constraints on the performance of the hydropower plant are demonstrated.

13 HYDRO ENERGY↗
DOE OSTI2024

I/O performance studies of analysis workloads on production and dedicated resources at CERN

The recent evolutions of the analysis frameworks and physics data formats of the LHC experiments provide the opportunity of using central analysis facilities with a strong focus on interactivity and short turnaround times, to complement the more common distributed analysis on the Grid. In order to plan for such facilities, it is essential to know in detail the performance of the combination of a given analysis framework, of a specific analysis and of the installed computing and storage resources. This contribution describes performance studies performed at CERN, using the EOS disk-based storage, either directly or through an XCache instance, from both batch resources and highperformance compute nodes which could be used to build an analysis facility. A variety of benchmarks, both synthetic and based on real-world physics analyses and their corresponding input datasets, are utilized. In particular, the RNTuple format from the ROOT project is put to the test and compared to the latest version of the TTree format, and the impact of caches is assessed. In addition, we assessed the difference in performance between the use of storage system specific protocols, like XRootd, and FUSE. The results of this study are intended to be a valuable input in the design of analysis facilities, at CERN and elsewhere.

Sciabà, Andrea↗
DOE OSTI2026

Africa Battery Energy Storage Systems (BESS) Capacity Building Li-Ion Battery Degradation and Performance [Slides]

This presentation is intended for power system engineers, operators, and planners who work on isolated power systems that have (or may soon have) high levels of power generation coming from wind turbines, solar farms, and battery energy storage, which are collectively referred to as inverter-based resources. It describes the basics of lithium-ion battery energy storage systems and lithium-ion battery degradation. Battery degradation at the cell-level is explained, and then the structure and degradation of battery energy storage systems is also explained. This is intended to help power system engineers, operators, and planners to understand and effectively utilize battery energy storage systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

A Review on Advanced Manufacturing for Hydrogen Storage Applications

Hydrogen is a notoriously difficult substance to store yet has endless energy applications. Thus, the study of long-term hydrogen storage, and high-pressure bulk hydrogen storage have been the subject of much research in the last several years. To create a research path forward, it is important to know what research has already been done, and what is already known about hydrogen storage. In this review, several approaches to hydrogen storage are addressed, including high-pressure storage, cryogenic liquid hydrogen storage, and metal hydride absorption. Challenges and advantages are offered based on reported research findings. Since the project looks closely at advanced manufacturing, techniques for the same are outlined as well. There are seven main categories into which most rapid prototyping styles fall. Each is briefly explained and illustrated as well as some generally accepted advantages and drawbacks to each style. An overview of hydrogen adsorption on metal hydrides, carbon fibers, and carbon nanotubes are presented. The hydrogen storage capacities of these materials are discussed as well as the differing conditions in which the adsorption was performed under. Concepts regarding storage shape and materials accompanied by smaller-scale advanced manufacturing options for hydrogen storage are also presented.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Techno-Economic Analysis of Hydrogen Production and Compressed Air Energy Storage from Variable Renewable Energy

Examines the performance and cost of pairing variable renewable energy (VRE) sources with compressed air energy storage and hydrogen production through PEM electrolysis. Sensitivities were performed on H2 cost, PEM electrolyzer capital cost, and hydrogen cavern capital cost. The analysis shows that the cost of VRE has the most impact on the overall cost results.

Teel, Troy↗
DOE OSTI2022

Low-Carbon District Heating: Performance Modeling of Hybrid Solar, Heat Pump, and Thermal Storage Systems for District Thermal Energy in the United States

District heating requires thermal energy in the temperature range of 40 degrees C - 120 degrees C. Typically, the thermal energy input for these systems has largely been met through fossil energy. However, the temperature range is low enough that it presents an opportunity for low-carbon technologies such as solar thermal and electrified thermal generators like heat pumps to decarbonize the heat generation. In this paper, a heat pump model was applied to estimate the performance and economics of a real-world low-carbon district heating substation. This system is comprised of a flat plate solar collector field paired with a mechanical vapor compression heat pump and hot water thermal storage, augmented by gas-fired boilers. Plant data was used to tune the model and estimate the system's benefits in terms of both standard financial metrics (IRR and payback), and environmental metrics, including avoided CO2 emissions. The model is subsequently employed to estimate the technical and economic potential of solar + heat pump + ther-mal storage hybrid systems as retrofits for district heating systems in eight US Markets.

district heating↗
DOE OSTI2026

Thermoelectric heating and cooling–integrated dishwasher with thermal energy storage

Household dishwashers must address several performance goals: maximize washing and drying performance, while minimizing cycle duration, energy consumption, and water consumption. This study develops and examines a novel thermoelectric heating and cooling (TEHC) system with thermal energy storage applied to a household dishwasher (DW), aiming to improve the energy and drying performance of a commercially-available dishwasher while maintaining its washing performance, water consumption, and cycle duration. Experimental testing conducted on the novel TEHC-DW system demonstrates an 8.7% reduction in total energy consumption, lowering the per-cycle usage to 0.952 kWh, and a 40% reduction in energy consumption for internal water heating. The novel TEHC-DW system also demonstrates better drying performance, shortening the drying time by 42% to reach the same remaining moisture content as a commercially-available system. In addition, a resistance-capacitance network model is developed that predicts total drying time, total energy consumption, and the highest temperature reached in the tub (53.4 °C). The model accuracy is validated with experimental data (within ±1 K), and the model functions as a design tool via a parametric study to evaluate the next-generation design and the effect of the number of thermoelectric modules and thermoelectric driving force (i.e., current). Overall, this study demonstrates the potential for TEHC technology to improve energy efficiency and drying performance in household dishwashers.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Towards a high-performance garnet-based solid-state Li metal battery: A perspective on recent advances

Garnet-based solid-state Li metal batteries have been widely considered one of the most promising next-generation energy storage systems. However, the performance of these batteries is plagued by various limitations caused by the solid-state electrolyte (SSE). The poor wetting of lithium on the garnet surface diminishes the contact between the anode and electrolyte, leading to extremely high anode interfacial resistance. Similarly, the point-to-point contact between the cathode and electrolyte leads to high impedance on the cathode side. Moreover, although the SSE serves a firm barrier separating the anode and cathode, lithium dendrites can still grow through, causing a short circuit. Lastly, the solid/solid interface cannot be well maintained under cycling at high current density and capacity. Recently, remarkable progress has been achieved in garnet electrolyte to resolve these problems towards the aim of a high-performance solid-state Li metal battery. In this perspective, we highlight various recent advances in the field of garnet-based solid-state battery, including improving the anode/electrolyte interface, lithium dendrite detection, reducing cathode impedance, and electrolyte architecture design.

25 ENERGY STORAGE↗
DOE OSTI2024

High-Fidelity and High-Performance Computational Simulations for Rapid Design Optimization of Sulfur Thermal Energy Storage

Industrial process heating (IPH) accounts for approximately 70% of US manufacturing energy use and is primarily produced by fossil fuel combustion. Approximately 1500 TWht (approximately 60%) of IPH demand is in the temperature range of 100-300. Industrial applications in this temperature range include drying, hydrothermal processing, thermal enhanced oil recovery, food and beverage, bioethanol production, etc. Cost-effective thermal energy storage (TES) that increases the utilization of waste and renewable heat (solar, geothermal, etc.) could provide significant energy savings and reliable heat sources, decrease emissions, and increase US manufacturing competitiveness through reductions in fuel consumption. TES development has historically been dominated by technologies suitable for deployment with concentrating solar power (CSP). State-of-the-art thermal storage deployed commercially with power tower CSP plants uses a 60%/40% NaNO3/KNO3 molten salt and operates between temperatures of approximately 280 degrees Celsius and 570 degrees Celsius using a two-tank configuration. However, these nitrate salts are unsuitable for operation outside of this temperature range due to a high freezing point of approximately 220 degrees Celsius, and limits on high-temperature salt stability and corrosion resistance of containment alloys. Other materials being investigated for TES include those based on: (1) sensible energy storage (various molten salt compositions, inert solid particles, rocks or pebble beds, sulfur, water, concrete, graphite, etc.), (2) latent energy storage in materials that undergo solid-liquid phase change at relevant temperatures (organic materials for low-temperature applications, inorganic salts and/or metals for high-temperature applications), or (3) thermochemical energy storage (hydrides, hydroxides, carbonates, metal oxides, etc.). The application temperature and challenges pertaining to storage material and/or containment cost, energy density, long-term thermal and cyclic stability, and charge/discharge heat transfer effectiveness drive material selection for a given IPH or electricity generation application. Sulfur is a cheap commodity at $80/ton compared to $1100 - 1300/ton for conventional salts. When using a metric of storage cost per kWh, sulfur costs around 2-3 $/kWh. Previous sulfur TES development focused on high temperature (>600 degrees) concentrated solar power applications with sulfur encapsulated in pipes and flow of gaseous HTF (air) in the shell side. However, for lower-temperature IPH applications in the range of approximately 100-300 degrees Celsius Element 16 adopted a compact and scalable TES design with molten sulfur in the shell and HTF pipes submerged in the molten sulfur bath. The low-cost molten sulfur TES for dispatchable IPH has deployment potential for broad applications. The spatial and temporal evolution of the HTF and sulfur temperature is critical to the TES system performance, and thus detailed modeling can improve understanding of the performance and facilitate design improvements. Using high performance computing and computational fluid dynamics (CFD) a low-cost molten sulfur thermal energy storage (TES) system for industrial process heating (IPH) applications was developed. The unique challenges in CFD modeling of sulfur TES are the sharp property changes of sulfur relevant to the working temperatures. Above 159, liquid sulfur undergoes polymerization, and the viscosity of sulfur rapidly increases by several orders of magnitude between 159 degrees Celsius and 188 degrees Celsius, followed by a decrease in viscosity beyond 188 degrees Celsius due to thermal bound dissociation. In addition, various concentrations of H2S impurities can also modify sulfur viscosity. This numerical challenge is especially relevant to transient simulation of the sulfur TES charging and discharging processes as the extreme property variations limit the applicability of traditional heat transfer correlations. Transient CFD simulations including the temperature-dependent sulfur properties and geometric complexity of the TES design were used to predict the effect of natural convection during charging and discharging on the heat transfer process, sulfur temperature uniformity, charge/discharge rates, and performance of the storage devices. The CFD model was validated with experimental results for a full charge and discharge cycle. The work will show 3D and 2D simulation comparisons aimed to facilitate rapid design iterations and a machine learning based design optimization approach.

CFD↗
DOE OSTI2025

Eureka: Enabling Fine-Grained Access and Range Queries on Compressed Scientific Data via Data-Index Co-Compression

Handling large-scale scientific data in high-performance computing (HPC) environments poses significant challenges, including excessive I/O, high storage costs, and slow query performance. Traditional approaches often require full data decompression and scans, making them impractical for real-time or interactive analysis. To address these limitations, we introduce Eureka, a unified data-index co-compression framework that enables fine-grained access and efficient range queries on compressed scientific datasets. Eureka integrates spatial domain decomposition with block-wise error-bounded lossy compression to support selective decompression. It constructs a hierarchical AVL-tree index during compression to capture block-level value ranges, enabling fast pruning during query execution. To reduce metadata overhead, the index itself is also compressed while ensuring recall-preserving results. Experiments on six diverse HPC simulation datasets show that Eureka achieves up to 25x data compression and over 300x index compression, surpassing state-of-the-art compressors such as SZ3 and ZFP in rate-distortion performance. Additionally, Eureka delivers over 30x speedup for low-selectivity range queries, making it a scalable and efficient solution for modern scientific data analysis.

Yan, Ning↗
DOE OSTI2022

High-resolution Compton spectroscopy using x-ray microcalorimeters

X-ray Compton spectroscopy is one of the few direct probes of the electron momentum distribution of bulk materials in ambient and operando environments. Herein, we report high-resolution inelastic x-ray scattering experiments with high momentum and energy transfer performed at a storage-ring-based high-energy x-ray light source facility using an x-ray transition-edge sensor (TES) microcalorimeter detector. The performance was compared with a silicon drift detector (SDD), an energy-resolving semiconductor detector, and Compton profiles were measured for lithium and cobalt oxide powders relevant to lithium-ion battery research. Spectroscopic analysis of the measured Compton profiles demonstrates the high-sensitivity to the low- Z elements and oxidation states. The line shape analysis of the measured Compton profiles in comparison with computed Hartree–Fock profiles is usually limited by the resolution of the semiconductor detector. We have characterized an x-ray TES microcalorimeter detector for high-resolution Compton scattering experiments using a bending magnet source at the Advanced Photon Source with a double crystal monochromator, providing monochromatic photon energies near 27.5 keV. The momentum resolution below 0.16 atomic units (a.u.) was measured, yielding an improvement of more than a factor of 7 over a state-of-the-art SDD for the same scattering geometry. Furthermore, the lineshapes of narrow valence and broad core electron profiles of sealed lithium metal were clearly resolved using an x-ray TES compared to smeared and broadened lineshapes observed when using the SDD. High-resolution Compton scattering using the energy-resolving area detector shown here presents new opportunities for spatial imaging of electron momentum distributions for a wide class of materials with applications ranging from electrochemistry to condensed matter physics.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

The Muon g-2 Experiment at Fermilab: Precision Measurements and Nonlinear Beam Dynamics

The Muon g-2 Experiment has achieved a significant milestone by measuring the positive muon anomalous magnetic moment to an unprecedented accuracy of 0.20 ppm, paving the way to a better understanding of particle physics, including beyond-the-Standard-Model possibilities. In the experiment, muons are circulated within a storage ring, and their anomalous precession frequency — the spin precession relative to momentum — is determined from decay positron time and energy data, captured using calorimeters. In support of accurate storage ring simulations, we performed high-order calculations of the field of the experiment's high-voltage quadrupoles. We also carried out accurate, transfer map–based calculations of the storage ring's chromaticity. These calculations are essential for understanding the beam dynamics effects in the Muon g-2 storage ring.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Proton-Mediated and Ir-Catalyzed Iron/Iron-Oxide Redox Kinetics for Enhanced Rechargeability and Durability of Solid Oxide Iron–Air Battery

Long duration energy storage (LDES) is an economically attractive approach to accelerating clean renewable energy deployment. The newly emerged solid oxide iron–air battery (SOIAB) is intrinsically suited for LDES applications due to its excellent low-rate performance (high-capacity with high efficiency) and use of low-cost and sustainable materials. However, rechargeability and durability of SOIAB are critically limited by the slow kinetics in iron/iron-oxide redox couples. Here the use of combined proton-conducting BaZr 0.4 Ce 0.4 Y 0.1 Yb 0.1 O 3 (BZC4YYb) and reduction-promoting catalyst Ir to address the kinetic issues, is reported. It is shown that, benefiting from the facilitated H + diffusion and boosted FeOx-reduction kinetics, the battery operated under 550 °C, 50% Fe-utilization and 0.2 C, exhibits a discharge specific energy density of 601.9 Wh kg –1 -Fe with a round-trip efficiency (RTE) of 82.9% for 250 h of a cycle duration of 2.5 h. Under 500 °C, 50% Fe-utilization and 0.2 C, the same battery exhibits 520 Wh kg –1 -Fe discharge energy density with an RTE of 61.8% for 500 h. This level of energy storage performance promises that SOIAB is a strong candidate for LDES applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Design Tool for Estimating Adsorbent Hydrogen Storage System Characteristics for Light-Duty Fuel Cell Vehicles

This work combines materials development with hydrogen storage technology advancements to address onboard hydrogen storage challenges in light-duty vehicle applications. These systems are comprised of the vehicle requirements design space, balance of plant requirements, storage system components, and materials engineering culminating in the development of an Adsorbent System Design Tool that serves as a preprocessor to the storage system and vehicle-level models created within the Hydrogen Storage Engineering Center of Excellence. Computational and experimental efforts were integrated to evaluate, design, analyze, and scale potential hydrogen storage systems and their supporting components against the Department of Energy 2020 and Ultimate Technical Targets for Hydrogen Storage Systems for Light Duty Vehicles. Ultimately, the Adsorbent System Design Tool was created to assist material developers in assessing initial design parameters that would be required to estimate the performance of the hydrogen storage system once integrated with the full fuel cell system.

08 HYDROGEN↗