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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Seasonal performance evaluation of zero-superheat active refrigerant charge control for variable-speed heat pumps

Heat pumps account for a significant portion of electricity consumption in buildings, making their energy efficiency a critical area of research. Control optimization is recognized as an effective approach for enhancing the efficiency of building HVAC systems. Specifically, since the efficiency of heat pumps increases with reduced superheat and the optimal refrigerant charge level varies with operating conditions, zero-superheat active charge control is a promising strategy to maximize the system’s COP. However, due to its complexity, this control strategy remains in the research phase and has only been tested under limited operating conditions. This paper proposes a methodology to evaluate the seasonal performance improvement of zero-superheat active charge control across a full range of heating conditions in buildings. The methodology includes the development of an optimal controller that utilizes an accumulator to store excess refrigerant and manages the active charge level at zero superheat through subcooling control, as well as the creation of a detailed physics-based heat pump model. Targeted a 3-ton variable-speed heat pump with R410A refrigerant, we selected ten U.S. cities representing different climate regions for seasonal performance evaluation. Our simulations indicate that, depending on the climate conditions, the optimal control strategy could achieve energy savings ranging from 5.8 % to 8.0 % over the entire heating season. These results suggest that zero-superheat active charge control, combined with coordinated compressor and fan speeds, could substantially improve the energy efficiency of heat pump systems while maintaining the required heating capacity.

Guo, Fangzhou↗
DOE OSTI2021

Forecasting Solar-Thermal Systems Performance under Transient Operation Using a Data-Driven Machine Learning Approach Based on the Deep Operator Network Architecture

Modeling and prediction of the dynamic behavior of thermal systems operating under intermittent energy input and variable load requirements represent one of the greatest challenges in the development of efficient and reliable renewable-based power generation technologies. In this work, a data-driven machine learning modeling framework was developed based on a modified version of the Deep Operator Network architecture where the time coordinate in the trunk net is replaced with historical data of the predicting quantity. The modeling framework can be used to accurately predict the performance of renewable-based energy conversion technologies including wind- and solar-based power plants. This novel framework was applied on a solar-thermal system that consists of a solar collection loop using a flat plate collector, a power generation loop comprising an Organic Rankine Cycle, and a thermal energy storage tank connecting both loops. Variable solar irradiance, air temperature, and power load profiles were used by the Deep Operator Network to predict the State-of-Charge and the efficiency of the thermal system for several days. The results were compared with the State-of-Charge and efficiency functions calculated using a physics-based model. For a simple operation scenario, characterized by a clear sky solar irradiance profile and constant load, the standard deviation in the State-of-Charge prediction by Deep Operator Network is below 0.9% during a seven-day prediction time horizon. For the most realistic operation scenario that considers real solar irradiance and a rough load profile, the maximum standard deviation in the predictions for the State-of-Charge and efficiency are below 6.8% and 2.5%, respectively. A comparison between Deep Operator Network and Long Short Term Memory network was also performed. In general, both networks predict very well the State-of-Charge for different data density conditions; however, a higher accuracy, with a standard deviation below 2.0%, is obtained by the Deep Operator Network during three and half days using sparser training data of 20-minute points. The same accuracy for the State-of-Charge prediction with the Long Short Term Memory network is achieved only for 14 h. Average standard deviations for the State-of-Charge prediction of 1.1% with the Deep Operator Network and 1.5% with the Long Short Term Memory network are obtained for a four-day prediction time using a denser training data of 5-minute points.

DeepONet↗
DOE OSTI2025

Large eddy simulation of wind farm performance in horizontally and vertically staggered layouts

This numerical investigation employs Large Eddy Simulation (LES) coupled with Actuator Disk Model (ADM) to evaluate wind farm layout optimization strategies. The study presents a systematic analysis of aligned, horizontal staggering, vertical staggering, and mixed (combination of horizontal and vertical) staggering configurations, aiming to establish optimal design parameters for enhanced power production. The investigation examines key performance metrics including mean velocity distributions, turbulence intensity characteristics, and power generation efficiency. Results demonstrate better performance of both horizontal and vertical staggering patterns compared to conventional aligned configurations, with horizontal staggering exhibiting notably higher power output than vertical arrangements. Our findings also suggest that mixed configurations, incorporating both horizontal and vertical staggering, can offer optimal performance characteristics. As a result, this research advances the understanding of wake interactions in complex wind farm layouts and provides design guidelines for maximizing wind farm power generation efficiency through strategic turbine positioning.

17 WIND ENERGY↗
DOE OSTI2022

Achieving low-temperature hydrothermal relithiation by redox mediation for direct recycling of spent lithium-ion battery cathodes

Lithium-ion battery (LIB) recycling is an urgent need to address the massive generation of spent LIBs from portable devices and electrical vehicles. However, the large-scale recycling is hampered by economic and safety issues associated with today's recycling processes. In this study, we demonstrate a safe and energy efficient direct regeneration process based on low-temperature hydrothermal relithiation (LTHR) at low pressure for spent LiNi x Co y Mn z O 2 (0 < x,y,z <1, x + y + z = 1, or NCM) cathode materials. A low concentration of low-cost redox mediator is employed to improve the relithiation kinetics of spent NCM materials, enabling full relithiation temperature to be reduced from 220 °C to 100 °C or below. Correspondingly, the pressure incurred in the relithiation process can be reduced from ~25 bar to 1 bar, offering significantly improved operation safety. Specifically, three NCM materials, including chemically delithiated NCM111, cycled (degraded) NCM111, and cycled NCM622, were successfully regenerated with complete recovery of composition, crystal structure, and electrochemical performance, achieving the same effectiveness as that achieved at high temperature process. Meanwhile, the total energy consumption of spent cell recycling and the greenhouse gas emission is also reduced. This work provides a facile and scalable way to more sustainable LIB recycling with high economic return, high operation safety and low cost.

25 ENERGY STORAGE↗
DOE OSTI2024

Low concentration electrolyte: A new approach for achieving high performance lithium batteries

The conventional perspective suggests that low-concentration electrolytes (LCEs) face challenges in achieving stable charge/discharge properties due to the decreased ionic conductivity resulting from lower Li + concentrations. However, the successful utilization of LCEs in lithium/sodium-ion batteries has brought them into the forefront of consideration for high performance battery systems. It is possible to achieve improved interface stability and ion transport performance for LCEs through adjusting electrolyte components, such as salts, solvents, and additives. This review provides timely update of the recent research progress, design strategies and remaining challenges of LCEs to answer several questions: i) What is the key factor for designing LCEs? ii) How to balance the low salt concentration and good ionic conductivity? iii) What is the interphasial mechanism of anode/cathode in LCEs? Firstly, the development of LCEs is discussed with typical examples. Subsequently, effectiveness of solvents on overall performances of LCEs is comprehensively summarized in detail. Finally, the challenges and possible research direction of LCEs are discussed. This review provides critical guidance for designing novel electrolytes for secondary batteries.

25 ENERGY STORAGE↗
DOE OSTI2023

Interaction of methanol with a layered α-Sn(IV) phosphate on its surface: A solid-state NMR study

Here, a layered crystalline phosphate, α-Sn(HPO 4 ) 2 ·H 2 O, treated with CD 3 OD was characterized by the 31 P, 119 Sn, 1 H and 2 H solid-state NMR techniques. The 2 H solid-echo MAS NMR spectra of the product have unexpectedly revealed deuterated hydronium ions on the surface of this material instead of intercalated methanol. According to the 13 C NMR and GC–MS studies, these ions are formed by water molecules following a dehydration of the methanol-d 4 to yield deuterated dimethyl ether.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Improved multiline HVDC circuit breakers with asymmetric conducting branches

Here, this paper proposes two improved multiline HVDC circuit breakers (DCBs) for HVDC grid applications, including type-1 improved multiline DCB and type-2 improved multiline DCB. The two improved DCBs draw on the core idea of extended H-bridge. m adjacent DC transmission lines share a single main breaker (MB) and surge arrester. Due to the extended H-bridge design, bidirectional current flow can be achieved by a unidirectional MB. An upper conducting branch and a lower conducting branch are connected to a DC line. The upper and lower conducting branches in the two improved multiline DCBs are asymmetric. The upper conducting branch of both two improved DCBs is formed by a load commutation switch (LCS) and an ultra-fast disconnector (UFD). The lower conducting branch of the type-1 improved scheme is composed of a diode and a UFD; and of the type-2 improved scheme is made up of diode stack. Compared with other DCBs, the proposed type-1 DCB and type-2 DCB are more cost effective. Among the five DCBs, the type-2 improved scheme requires the least number of individual switching actions. The effectiveness and feasibility of the proposed schemes are verified through simulation of a bipolar three-terminal HVDC grid in PSCAD/EMTDC.

42 ENGINEERING↗
DOE OSTI2025

A sequential Attacker-Defender game for distribution systems resilience enhancement against extreme weather events

Improving distribution system resilience against frequent extreme weather events is important for reliable power system operations. Especially when dealing with events such as hurricanes that have short-term predictions, proactive pre-event preparedness plays a vital role in system resilience performance. In this paper, we propose a novel approach to construct pre-event resource allocation plans for system operators to cope with upcoming threats through a sequential attacker-defender game framework. The sequential attacker-defender game is designed to model the interaction between the extreme weather and the system operator. In each round of the game, the attacker and the defender sequentially update their current strategies by accounting for the opponent’s action set. The attacker model is formulated as a bi-level problem to identify the severe outage scenarios, and the defender model is formulated as a two-stage optimization problem to determine the allocation of restoration resources including mobile responsive resources and repair crews. Two scale-reduction strategies are proposed to ensure the scalability of the game scheme. Finally, case studies on the IEEE 33-bus and a 7149-node practical utility system validate the effectiveness of the proposed sequential game and the efficiency of the scale-reduction strategies.

24 POWER TRANSMISSION AND DISTRIBUTION↗