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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Quantifying Thermal Output of Energetic Materials (LDRD Final Report)

We present the results of an LDRD project, funded by the Nuclear Deterrence IA, to develop capabilities for quantitative assessment of pyrotechnic thermal output. The thermal battery igniter is used as an exemplar system. Experimental methodologies for thermal output evaluation are demonstrated here, which can help designers and engineers better specify pyrotechnic components , provide thermal output guidelines for new formulations, and generate new metrics for assessing component performance and margin given a known failure condition. A heat-transfer analysis confirms that the dominant mode of energy transfer from the pyrotechnic output plume to the heat pellet is conduction via deposition of hot titanium particles. A simple lumped-parameter model of titanium particle heat transfer and a detailed multi-phase model of deposition heat transfer are discussed. Pyrotechnic function, as defined by "go/no-go" standoff testing of a heat pellet, is correlated with experimentally measured igniter plume temperature, titanium metal particle temperature, and energy deposition. Three high-speed thermal diagnostics were developed for this task. A three-color imaging pyrometer, acquiring 100k images per second on three color channels, is deployed for measurement of titanium particle temperatures. Complimentary measurements of the overall igniter plume emission ("color") temperature were conducted using a transmission-grating spectrograph in line-imaging mode. Heat flux and energy deposition to a cold wall at the heat-pellet location were estimated using an eroding thermocouple probe, with a frequency response of ~5 kHz. Ultimate "go/no-go" function in the igniter/heat-pellet system was correlated with quantitative thermal metrics, in particular surface energy deposition and plume color temperature. Titanium metal-particle and plume color temperatures both experience an upper bound approximated by the 3245-K boiling point of TiO 2 . Average metal-particle temperatures remained nearly constant for all standoff distances at T = 2850 K, ± 300 K, while plume color temperature and heat flux decay with standoff—suggesting that heat-pellet failure results from a drop in metal-particle flux and not particle temperature. At 50% likelihood of heat-pellet failure, peak time-resolved plume color temperatures drop well below TiO 2 boiling to ~2000 - 2200 K, near the TiO 2 melting point. Estimates of peak heat flux decline from up to 1 GW/m 2 for near-field standoffs to below 320 MW/m 2 at 50% failure likelihood.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Development of New g-function Data for Simulating a Novel Shallow Bore Ground Heat Exchanger

Geothermal heat pump (GHP), which is also referred as ground source heat pump, is the most energy-efficient technology for space heating and cooling. However, the application of GHP is hindered by its high initial cost, of which approximately 30% is for the ground heat exchanger (GHE). In recent years, researchers have developed different types of shallow bore ground heat exchangers (SBGHE) intending to reduce the cost of drilling. The ability to predict the thermal response of an SBGHE is critical for sizing SBGHE. While g-functions have been commonly used for predicting the thermal response of conventional vertical bore ground heat exchangers (VBGHE), they cannot be directly used for predicting the performance of SBGHE because they did not account for the impacts of the seasonal variation of the soil temperature along with the depth of an SBGHE. In addition, an SBGHE has a larger thermal mass within the borehole than the VBGHE due to the larger borehole diameter of SBGHE. This study develops new g-function data pairs for a new design of SBGHE, which is named Underground Thermal Battery (UTB). Impacts of the seasonal variation of soil temperature on the thermal response of UTB were accounted for by superposing a time-dependent soil temperature onto the g-functions calculated with a numerical model that assumes constant undisturbed soil temperature. The TOUGH program was used to predict the thermal response of several configurations involving multiple UTBs. The results indicate that the proposed methodology is appropriate to generate g-functions for the UTB, and the g-function value of UTB is much lower than that of VBGHE in the time range of 15 min to 1 year due to the large thermal mass and convection heat transfer within the UTB.

Shi, Liang↗
DOE OSTI2021

Performance evaluation of a dynamic wall integrated with active insulation and thermal energy storage systems

Thermal energy storage systems in buildings can store cooling/heating energy during non-peak load hours or when renewable energy sources are available for later use when demanded. Using the building envelope as a thermal battery can help to shave the peak load, reduce the burden in electric grids, and enhance the occupant's thermal comfort. Sensible energy storage on wall systems such as thermally activated building systems can provide an active thermal storage strategy. However, most of the stored energy is used through passive means directed by the thermal lag, which can impede the on-demand release of the stored energy. Integrating active insulation systems with building thermal storage systems can increase the flexibility of charging and discharging time and duration. In this study, a wall system equipped with an active insulation system and thermally activated storage system was designed, and its performance on active cooling energy contribution was studied. The performances of energy storage (charging), release (discharging) of the thermal energy storage energy, and the active insulation system were studied separately and together as an integrated system. Results showed that the thermal properties of the thermal energy storage core material and the pipe spacing of both embedded pipes in the thermal energy storage and hydronic pipes used in the active insulation system affected the wall performance the most out of all the tested wall system parameters. During discharging, the heat flux into the wall was as high as 81.92 W/m 2 . This active insulation system's dynamic R-value varied between less than 1ft 2 •°F•h/BTU (0.18 m 2 •K/W) to 98% of the equally thick foam insulation's R-value.

25 ENERGY STORAGE↗
DOE OSTI2020

Size Effects in the Thermal Conductivity of Amorphous Polymers

Manipulating thermal conductivity through nanoengineering is of critical importance to advance technologies, such as soft robotics, artificial skin, wearable electronics, batteries, thermal insulation, and thermoelectrics. Here, by examining amorphous polymers, including polystyrene, polypropylene, polyethylene, and ethylene vinyl alcohol, using molecular dynamics simulations, we find that the thermal conductivities of amorphous polymers can be reduced below their amorphous limit by size effects. Size-dependent thermal transport in amorphous materials is decomposed into crystalline, crystalline-to-amorphous, and amorphous regimes. In the amorphous regime, the mean free path of propagating heat carriers can range from tens of nanometers to more than 100 nm, contributing 16%–36% of the total thermal conductivity. A two-channel model that combines no size effect (i.e., difusons and locons) and size effect (i.e., propagons) is proposed to account for size-dependent thermal conductivity. We also find that the presence of charged molecules in polymers can significantly affect the thermal conductivity and its size effects due to electrostatic interactions. Overall, this work provides insights into the thermal conductivity of amorphous polymers that will have a broad impact on the nano- and chemical engineering of polymers for various energy-related applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Performance Investigation of High-temperature Latent Heat Storage for Integration with Advanced Nuclear Reactors

Integrating thermal energy storage (TES) with advanced nuclear reactors enhances the flexible use of nuclear energy, facilitating its expansion beyond conventional electricity generation. High-temperature TES, capable of storing heat above 400 degree C, emerges as a vital carbon-free energy solution for decarbonizing industrial sector, especially when combined with low-emission energy sources like advanced nuclear reactors. Idaho National Laboratory (INL) has recently developed a novel design for high-temperature latent heat storage system, called Heat pipe Integrated Thermal Battery (HITB), and efforts are underway to experimentally demonstrate the concept. HITB employs liquid-metal heat pipes to establish thermal linkage between TES and nuclear systems without direct fluid exchange, minimizing the potential risk of the integrated systems such as cross-contamination. HITB is designed to achieve high charging and discharging efficiency as well as high energy storage density by employing metal alloys as Phase Change Material (PCM). Initial proof-of-concept experiments are being undertaken using an aluminum alloy (Al59%-Mg35%-Zn6%). This paper discusses current progress of the HITB project at INL, seeking to develop high-temperature TES for versatile integration with advanced nuclear reactors, and shares insights from the performance evaluations via numerical modeling and analysis.

25 ENERGY STORAGE↗
DOE OSTI2021

Impact of soil model complexity on the long-term thermal performance prediction of a new shallow bore ground heat exchanger

Shallow bore ground heat exchangers have been investigated in recent years because they have the potential to reduce the initial cost of the ground source heat pump system. Correctly modeling the transient heat transfer between the ground heat exchanger and the surrounding soil is essential for predicting a ground heat exchanger's performance. Simplification of the soil model could increase computation speed but sacrifice accuracy. This study investigates the impact of the soil model complexity on the annual performance prediction of a new shallow bore ground heat exchanger, the underground thermal battery (UTB). A simple 1D soil model and a more detailed 2D soil model were implemented, and they were validated against a 3D soil model. Overall, the resulting predictions of the UTB’s response from the 1D and 2D models to a given thermal load in different climates were compared. The results show that the root mean square differences between the hourly temperatures of the UTB during a year predicted using the two soil models range from 1.17°C to 3.39°C. As a result, the difference in the annual power consumption of the heat pump was between 0.7% and 3.4%. Furthermore, the dimensions of the UTB affected its performance, and a longer UTB was less sensitive to the soil models.

42 ENGINEERING↗
DOE OSTI2025

Computational and experimental analysis of structural and Thermophysical properties of LiX-KX (X = chloride, iodide, or bromide) molten salts

Molten salts containing lithium (Li) and potassium (K) halides, including chlorides (Cl), bromides (Br), and iodides (I), are pivotal in advanced technological applications including nuclear reactor technologies, thermal batteries, and industrial pyrochemical processes. Despite their significance, the availability of the temperature-dependent structural and thermophysical properties of these molten salts remain scarce. Here, this study addresses this knowledge gap by predicting and measuring the key properties such as coordination number, radial distribution function, density, heat capacity, and volumetric thermal expansion of molten LiI-KI, LiBr-KBr and LiCl-KCl eutectic mixtures. Utilizing ab initio molecular dynamics (AIMD) simulations, we predict these properties of LiX-KX (X=Br,I, Cl) across various temperatures, with chlorides as a benchmark. Experimental measurements using Archimedes methods and Differential Scanning Calorimetry validate the densities and heat capacities of these molten salts. Our comprehensive analysis of the structural and thermophysical properties provides critical insights into the behavior of these molten salts at various temperatures, enhancing the understanding necessary for their application in advanced technologies.

36 - MATERIALS SCIENCE↗
DOE OSTI2023

Extreme fast charging of commercial Li-ion batteries via combined thermal switching and self-heating approaches

Abstract The mass adoption of electric vehicles is hindered by the inadequate extreme fast charging (XFC) performance (i.e., less than 15 min charging time to reach 80% state of charge) of commercial high-specific-energy (i.e., >200 Wh/kg) lithium-ion batteries (LIBs). Here, to enable the XFC of commercial LIBs, we propose the regulation of the battery’s self-generated heat via active thermal switching. We demonstrate that retaining the heat during XFC with the switch OFF boosts the cell’s kinetics while dissipating the heat after XFC with the switch ON reduces detrimental reactions in the battery. Without modifying cell materials or structures, the proposed XFC approach enables reliable battery operation by applying <15 min of charge and 1 h of discharge. These results are almost identical regarding operativity for the same battery type tested applying a 1 h of charge and 1 h of discharge, thus, meeting the XFC targets set by the United States Department of Energy. Finally, we also demonstrate the feasibility of integrating the XFC approach in a commercial battery thermal management system.

25 ENERGY STORAGE↗
DOE OSTI2020

A novel shallow bore ground heat exchanger for ground source heat pump applications—Model development and validation

A novel ground heat exchanger design, the Underground Thermal Battery (UTB), was proposed as a low-cost alternative to the conventional vertical bore ground heat exchanger (VBGHE) for the application of ground source heat pumps (GSHPs). The UTB is designed to be installed in a shallow borehole (less than 6 m deep) and thus could cost much less than the conventional VBGHE, which usually is installed in vertical bores 60 m deep. By utilizing natural convection of water and phase change materials, the UTB tempers its temperature change in response to thermal loads, which helps improve the efficiency of GSHPs. A one-dimensional (1D) model of the UTB has been developed and validated with the measured performance data of a small-scale UTB, as well as the simulation results of a more detailed three dimensional (3D) numerical model, which accounts for both heat transfer and fluid dynamics in the UTB. Further, this 1D model is computationally much more efficient than the 3D model and thus can simulate the annual performance of the UTB with acceptable computation time. The 1D model has been used to evaluate the performance of the UTB so that it can be compared with the conventional VBGHE.

42 ENGINEERING↗
DOE OSTI2020

Long-Term Vehicle Speed Prediction via Historical Traffic Data Analysis for Improved Energy Efficiency of Connected Electric Vehicles

Connected and automated vehicles (CAVs) are expected to provide enhanced safety, mobility, and energy efficiency. While abundant evidence has been accumulated showing substantial energy saving potentials of CAVs through eco-driving, traffic condition prediction has remained to be the main challenge in capitalizing the gains. The coupled power and thermal subsystems of CAVs necessitate the use of different speed preview windows for effective and integrated power and thermal management. Real-time vehicle-to-infrastructure (V2I) communications can provide an accurate speed prediction over a short prediction horizon (e.g., 30 s to 60 s), but not for a long range (e.g., over 180 s). Therefore, advanced approaches are required to develop detailed speed prediction for robust optimization-based energy management of CAVs. This paper presents an integrated speed prediction framework based on historical traffic data classification and real-time V2I communications for efficient energy management of electrified CAVs. The proposed framework provides multi-range speed predictions with different fidelity over short and long horizons. The proposed multi-range speed prediction is integrated with an economic model predictive control (MPC) strategy for the battery thermal management (BTM) of connected and automated electric vehicles (EVs). The simulation results over real-world urban driving cycles confirm the enhanced prediction performance of the proposed data classification strategy over a long prediction horizon. Despite the uncertainty in long-range CAVs’ speed predictions, the vehicle-level simulation results show that 14% and 19% energy savings can be accumulated sequentially through eco-driving and BTM optimization (eco-cooling), respectively, when compared with normal driving (i.e., human driver) and conventional BTM strategy.

Engineering↗
DOE OSTI2024

Performance evaluation of underground thermal storage integrated dual-source heat pump systems

The increasing demand for electricity stresses the existing electric grids. Buildings consume 73% of all U.S. electricity and are responsible for 30% of U.S. greenhouse gas emissions. Integrating thermal energy storage (TES) in building heating/cooling systems, which consume considerable electricity, can mitigate the challenges to electric grids. Here, this study reports on a novel thermal energy storage device integrated heat pump system to reshape the building electricity demand profile while maintaining thermal comfort. The annual performance of the proposed system has been evaluated through a dynamic system simulation with high fidelity in the Modelica platform. The dynamic model of the novel hybrid component named ‘dual purpose underground thermal battery’ was developed and validated. It was then incorporated into the system model. Given a time-of-use tariff, a rule-based control strategy was designed to shift the electric demand and switch the heat pump source for a typical single-family house in different climate zones of the United States. The system performance of the new TES-integrated dual-source heat pump was compared with that of a conventional air-source heat pump system. The results indicate that the proposed system can reduce the annual HVAC electricity cost by up to 52% while saving 45.2% on electricity consumption. In the Northern areas, the annual peak load of the HVAC system can be reduced by 64.9%. However, this reduction is less in the Southern areas as the system’s higher efficiency in winter dominates the overall energy-saving potential.

25 ENERGY STORAGE↗
DOE OSTI2021

Robust Importance Sampling for Bayesian Model Calibration with Spatio-Temporal Data

This paper addresses two challenges in Bayesian calibration: 1) computational speed of existing sampling algorithms, and 2) calibration with spatio-temporal responses. The commonly used Markov Chain Monte Carlo (MCMC) approaches require many sequential model evaluations making the computational expense prohibitive. This paper proposes an efficient sampling algorithm: iterative importance sampling with genetic algorithm (IISGA). While iterative importance sampling enables computational efficiency, the genetic algorithm enables robustness by preventing sample degeneration and avoids getting stuck in multimodal search spaces. An inflated likelihood further enables robustness in high-dimensional parameter spaces by enlarging the target distribution. Spatio-temporal data complicate both surrogate modeling, which is necessary for expensive computational models, and the likelihood estimation. In this work, singular value decomposition is investigated for reducing the high-dimensional field data to a lower-dimensional space prior to Bayesian calibration. Then the likelihood is formulated and Bayesian inference is performed in the lower-dimension, latent space. An illustrative example is provided to demonstrate IISGA relative to existing sampling methods, and then IISGA is employed to calibrate a thermal battery model with 26 uncertain calibration parameters and spatio-temporal response data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Multi-fidelity information fusion and resource allocation

This project created and demonstrated a framework for the efficient and accurate prediction of complex systems with only a limited amount of highly trusted data. These next generation computational multi-fidelity tools fuse multiple information sources of varying cost and accuracy to reduce the computational and experimental resources needed for designing and assessing complex multi-physics/scale/component systems. These tools have already been used to substantially improve the computational efficiency of simulation aided modeling activities from assessing thermal battery performance to predicting material deformation. This report summarizes the work carried out during a two year LDRD project. Specifically we present our technical accomplishments; project outputs such as publications, presentations and professional leadership activities; and the project’s legacy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

High throughput battery failure experimental platform

Addressing the need to increase the sample set to understand the causes of lithium battery thermal runaway, we conceived of an experimental platform with capability to increase the number of runaway experiments (currently 3-5 per week), while also collecting detailed electrochemical impedance spectroscopy measurements (EIS). Once expanded, the platform would enable data collection on 10s to 100s of cells that all experience runaway, thereby creating a statistical database necessary to identify early indication of risk. A primary containment unit to house cylindrical cells of variety NMC811 and of size 21700 (21 mm diameter by 70 mm length) was designed with features such as debris containment, preloaded cells in an exchangeable port, nitrogen ventilation, and exhaust containment. We performed the first overcharge abuse experiments of several 21700 cells, handpicked because of different initial EIS, and demonstrated that EIS changes dramatically during early stages of overcharge, but in a different manner than previous pouch cell experiments. The abuse experiments also revealed the discharge pattern and debris field created during runaway, as well as the cell temperature control and overheat, that must be considered in the primary containment apparatus. We designed and built a switching relay system to permit measurement of EIS without an active charging circuit, and created instrument control software for charging, EIS, and cell temperature control. The late-start funding was insufficient to fully construct the primary containment unit, but the foundational design and knowhow is available for any future work.

25 ENERGY STORAGE↗
DOE OSTI2025

Electric Vehicle Charging Data Falsification Attacks Utilizing Behavioral Models

A charging station (CS) and its associated electric vehicle supply equipment (EVSE) and charging electric vehicle (EV) interactions are potential targets for data falsification attacks since CSs are typically unmanned public facilities that are connected to the internet and EVs incorporate the vulnerable CAN bus network, which are both susceptible to remote attacks. The research question being addressed is how is the EV owner and CS negatively affected by CAN bus EV battery current sensor and battery temperature sensor data falsification attacks. Negative effects include economic losses from reduced life span of the battery, battery thermal runaway and fire (and potential loss of surrounding structure), and reduced utilization of the CS due to delayed departure time (longer charging times).

25 ENERGY STORAGE↗
DOE OSTI2024

Experimental Study of Underground Heat Storage via Hydraulic Fractures

In this study, we present a laboratory setup to test the energy flow in the form of underground heat storage using hydraulic fractures, a so-called Fracture Thermal Energy Storage (FTES) system. In the experiment, de-ionized water is circulated under high pressure through steel tubing automatically heated to a target temperature. The fluid adjusts to the tubing temperature during its flow before entering a production well drilled into a 250 mm edge length block of Zimbabwe Gabbro. The warm fluid then circulates through a previously created hydraulic fracture at mid-height of the block to a production well drilled at the block periphery. External fracture appearances are sealed using an epoxy resin and the production well by a cork of polydimethylsiloxane. In this cork, tubing to an open outlet is glued. We demonstrated through the results of a preliminary heating experiment that we can transfer nearly all of the heat from the circulating fluid to the block. An efficient charging of the thermal battery is achieved. This first-order demonstration is currently under further improvement and serves as a knowledge basis for the upscaling of mid- to large-scale field implementation of FTES systems.

Möri, Andreas↗
DOE OSTI2023

Anion binding agent lithium salts for battery electrolytes

A method for synthesizing a purified lithium (Li)+ anion binding agent (ABA-F)− salt and the corresponding Li+(ABA-F)− are disclosed. The method includes dissolving a boron-based acid in a polar solvent to form a solution. The solution is refluxed to form an anion binding agent. A stoichiometric amount of a small fluorinated salt, such as LiF, is added to the anion binding agent to form a mixture. The mixture is subsequently crystallized to obtain a substantially pure Li+(ABA-F)− salt. Example purified Li+(ABA-F)− salts include Ox-Li+(ABA-F), m-Li+(ABA-F), and BF3—Li+(ABA-F)−. These purified Li+(ABA-F)− salts provide the benefits of increased battery thermal safety without loss of electrochemical performance.

Orendorff, Christopher↗
DOE OSTI2024

Multi-range vehicle speed prediction using vehicle connectivity for enhanced energy efficiency of vehicles

An integrated speed prediction framework based on historical traffic data mining and real-time V2I communications for CAVs. The present framework provides multi-horizon speed predictions with different fidelity over short and long horizons. The present multi-horizon speed prediction is integrated with an economic model predictive control (MPC) strategy for the battery thermal management (BTM) of connected and automated electric vehicles (EVs) as a case study. The simulation results over real-world urban driving cycles confirm the enhanced prediction performance of the present data mining strategy over long prediction horizons. Despite the uncertainty in long-range CAV speed predictions, the vehicle level simulation results show that 14% and 19% energy savings can be accumulated sequentially through eco-driving and BTM optimization (eco-cooling), respectively, when compared with normal-driving and conventional BTM strategy.

Amini, Mohammad Reza↗