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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Multiscale Computational Model for Particle Size Evolution during Coprecipitation of Li-Ion Battery Cathode Precursors

Next generation lithium ion batteries require higher energy and power density, which can be achieved by tailoring the cathode particle morphology, such as particle size, size distribution, and internal porosity. All these morphological features are determined during the cathode synthesis process, which consists of two steps, (i) coprecipitation and (ii) calcination. Transition metal hydroxide precursors are synthesized during the coprecipitation process, whereas their oxidation and lithiation occur during calcination. The size and size distribution of crystalline primary and aggregated secondary particles and their internal porosity are determined during coprecipitation. Operating conditions of the chemical reactor, such as solution pH, ammonia concentration, and stirring speed control the final morphological features. Here, a multiscale computational model has been developed to capture the nucleation and growth of crystalline primary particles and their aggregation into secondary transition metal hydroxide precursor particles. The simulations indicate that increasing solution pH and decreasing ammonia concentration lead to smaller sizes of the secondary particles. Finally, a phase map has been developed that can help identify the synthesis conditions needed for a specified particle size and size distribution.

25 ENERGY STORAGE↗
DOE OSTI2026

Josephson dynamics in two-dimensional ring-shaped condensates

We investigate Josephson transport in a fully closed, two-dimensional superfluid circuit formed by a ring-shaped 87 Rb Bose-Einstein condensate that contains two optical barriers acting as movable weak links. Translating these barriers at controlled speeds imposes a steady bias current, enabling direct mapping of the current-chemical-potential (𝐼−Δ⁢𝜇) characteristics. For narrow junctions (𝑤 ≈ 1µ⁢m), the circuit exhibits a pronounced dc branch that terminates at a critical current 𝐼 𝑐 = 9⁢(1) × 10 3 s −1 ; above this threshold, the system switches to an ac, resistive regime. Classical-field simulations that include the moving barriers quantitatively reproduce both the nonlinear 𝐼−Δ⁢𝜇 curve and the measured 𝐼 𝑐 , validating the underlying microscopic picture. Analysis of the ensuing phase dynamics shows that dissipation is mediated by the nucleation and traversal of vortex-antivortex pairs through the junctions, while the bulk condensate remains globally phase locked—direct evidence of the ring's topological constraint enforcing quantized circulation. These results establish a cold-atom analog of a superconducting quantum interference device in which Josephson dynamics can be resolved at the single-vortex level, providing a versatile platform for atomtronic circuit elements, nonreciprocal Josephson devices, and on-chip Sagnac interferometers for multiaxis rotation sensing.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Using Machine Learning Tools to Predict Compressor Stall

Clean energy has become an increasingly important consideration in today’s power systems. As the push for clean energy continues, many coal-fired power plants are being decommissioned in favor of renewable power sources such as wind and solar. However, the intermittent nature of renewables means that dynamic load following traditional power systems is crucial to grid stability. With high flexibility and fast response at a wide range of operating conditions, gas turbine systems are poised to become the main load following component in the power grid. Yet, rapid changes in load can lead to fluid flow instabilities in gas turbine power systems. These instabilities often lead to compressor surge and stall, which are some of the most critical problems facing the safe and efficient operation of compressors in turbomachinery today. Although the topic of compressor surge and stall has been extensively researched, no methods for early prediction have been proven effective. This study explores the utilization of machine learning tools to predict compressor stall. The long short-term memory (LSTM) model, a form of recurrent neural network (RNN), was trained using real compressor stall datasets from a 100 kW recuperated gas turbine power system designed for hybrid configuration. Two variations of the LSTM model, classification and regression, were tested to determine optimal performance. The regression scheme was determined to be the most accurate approach, and a tool for predicting compressor stall was developed using this configuration. Overall, results show that the tool is capable of predicting stalls 5–20 ms before they occur. With a high-speed controller capable of 5 ms time-steps, mitigating action could be taken to prevent compressor stall before it occurs.

42 ENGINEERING↗
DOE OSTI2022

Calculation of Nuclear Reactor Cooling Tower Performance With Limited Data Streams

Monitoring of cooling tower performance in a nuclear reactor facility is necessary to ensure safe operation; however, instrumentation for measuring performance characteristics can be difficult to install and may malfunction or break down over long duration experiments. This paper describes employing a thermodynamic approach to quantify cooling tower performance, the Merkel model, which requires only five parameters, namely, inlet water temperature, outlet water temperature, liquid mass flowrate, gas mass flowrate, and wet bulb temperature. Using this model, a general method to determine cooling tower operation for a nuclear reactor was developed in situations when neither the outlet water temperature nor gas mass flowrate are available, the former being a critical piece of information to bound the Merkel integral. Furthermore, when multiple cooling tower cells are used in parallel (as would be in the case of large-scale cooling operations), only the average outlet temperature of the cooling system is used as feedback for fan speed control, increasing the difficulty of obtaining the outlet water temperature for each cell. To address these shortcomings, this paper describes a method to obtain individual cell outlet water temperatures for mechanical forced-air cooling towers via parametric analysis and optimization. In this method, the outlet water temperature for an individual cooling tower cell is acquired as a function of the liquid-to-gas ratio (L/G). Leveraging the tight tolerance on the average outlet water temperature, an error function is generated to describe the deviation of the parameterized L/G to the highly controlled average outlet temperature. The method was able to determine the gas flowrate at rated conditions to be within 3.9% from that obtained from the manufacturer’s specification, while the average error for the four individual cooling cell outlet water temperatures were 1.6 °C, -0.5 °C, -1.0 °C, and 0.3 °C.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

WBG-Enabled Current-Source Inverters for Integrated PM Motor Drives

This project takes advantage of the special capabilities of wide-bandgap (WBG) power semiconductor devices to develop innovative power electronics in the form of new current-source inverters (CSIs) that offer promising advantages over the dominant voltage-source inverter (VSI) topology. These CSIs, in turn, are extremely well-suited for integration into the housings of permanent magnet synchronous machines (PMSMs) to form integrated motor drives (IMDs). These new IMDs offer great promise for achieving major energy savings in a wide variety of applications that benefit from adjustable-speed control, including air conditioners, laundry appliances, industrial pumps/compressors, electric vehicles, and aerospace drives. WBG devices play a critical enabling role in these new IMDs because of their transformative features including much higher switching frequencies, lower losses, and compatibility with high operating temperatures. When incorporated into new CSI-based IMDs with PM machines, these WBG switches open the door to achieving major increases in power density, drive system efficiency, and fault tolerance, as well as substantial reductions in electromagnetic interference (EMI), manufacturing cost, and temperature-induced failures. The higher operating temperature capability of WBG devices compared to conventional silicon power devices is very appealing in IMD applications because the power electronics is mounted in close proximity to the motors which typically operate at temperatures well above the maximum limits of today’s silicon-based power electronics. This project has succeeded in designing, building, and testing multiple prototype versions of this CSI-IMD that have overcome many technical challenges in order to demonstrate the impressive performance improvements that can be achieved by the WBG-enabled CSI-IMD. The preliminary demo and bench-top versions of the current-source inverter developed during the first two years of the project were critical to laying the technical foundations for the 3 kW prototype CSI-IMD unit that was successfully built and tested during the third year. This prototype CSI-IMD unit was designed to fit within the housing envelope of the original permanent magnet (PM) synchronous machine in order to meet the demanding power density requirements that were set at the beginning of the project. All of the remaining performance objectives set for the prototype CSI-IMD unit including efficiency and electromagnetic interference (EMI) were also met. The last 18 months of the project were devoted to developing further enhancements of the WBG-enabled CSI-IMD technology that better prepare it for commercial production. More specifically, an upgraded version of the prototype CSI-IMD unit was developed that moved the power electronics into the same machine housing chamber as the motor, substantially raising the thermal demands on the power electronics. Tests with five different combinations of motor enclosure types and air cooling configurations were evaluated. Importantly, this work confirmed that the power electronics can deliver its full rated power and still operate well within its maximum temperature limits even for worst-case conditions when the housing is “totally-enclosed” without any openings for air to enter or exit the enclosure, and no blower/fan is provided to blow air over the outside surface of the enclosure. Reaching the full performance and energy-savings potential of this disruptive CSI-IMD motor drive technology is highly consistent with ARPA-E’s stated mission to “enhance the economic and energy security of the United States” while also supporting its commitment to “ensure that the U.S. maintains a technological lead in developing and deploying advanced energy technologies”. Follow-on projects are under way to explore the scalability of WBG-enabled CSI-IMD technology to 100 kW (peak) electric vehicle traction drives and fault-tolerant modular motor drives for future electrified aircraft propulsion applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Adaptively Learned Modeling for a Digital Twin of Hydropower Turbines with Application to a Pilot Testing System

In the development of a digital twin (DT) for hydropower turbines, dynamic modeling of the system (e.g., penstock, turbine, speed control) is crucial, along with all the necessary data interface, virtualization, and dashboard designs. Since the DT must mimic the actual dynamics of the hydropower turbine accurately, adaptive learning is required to train these dynamic models online so that the models in the DT can effectively follow the representation of the actual hydropower turbine dynamics accurately and reliably. This study presents an adaptive learning method for obtaining the hydropower turbine models for DT development of hydropower systems using the recursive least squares algorithm. To simplify the formulation, the hydropower turbine under consideration was assumed to operate near a fixed operating point, where the system dynamics can be well represented by a set of linear differential equations with constant parameters. In this context, the well-known six-coefficient model for the Francis turbine was formulated as the starting point to obtain input and output models for the turbine. Then, an adaptive learning mechanism was developed to learn model parameters using real-time data from a hydropower turbine testing system. This led to semi-physical modeling, in which first principles and data-driven modeling are integrated to produce dynamic models for DT development. Applications to a pilot system at the Norwegian University of Science and Technology (NTNU) were made, and the models learned adaptively using the data collected from the university’s pilot system. Desired modeling and validation results were obtained.

13 HYDRO ENERGY↗
NASA NTRS1971

Brushless DC motor with dual windings

Motor has high starting torque and high running speeds. Control system consists of Hall effect generator/resolver and associated electronic amplifiers and switches. Motor operation is described.

Auclair, G. F.↗
NASA NTRS1972

Electro-chemical grinding

Electro-chemical grinding technique has rotation speed control, constant feed rates, and contour control. Hypersonic engine parts of nickel alloys can be almost 100% machined, keeping tool pressure at virtual zero. Technique eliminates galling and permits constant surface finish and burr-free interrupted cutting.

Feagans, P. L.↗
NASA NTRS1971

Cold startup and low temperature performance of the Brayton cycle electrical subsystem

Cold performance tests and startup tests were conducted on the Brayton-cycle inverter, motor-driven pump, dc supply, speed control with parasitic load resistor and the Brayton control system. These tests were performed with the components in a vacuum and mounted on coldplates. A temperature range of ?25 to -50 C was used for the tests. No failures occurred, and component performance gave no indication that there would be any problem with the safe operation of the Brayton power generating system.

Vrancik, J. E.↗
NASA NTRS1972

The Goddard helical tape recorder

A spacecraft recorder was developed with the objective of functioning continuously for 5 years. The resulting design employed a metallic tape wound in a 200-turn helix. A direct drive, brushless dc torquer and servo speed control drove the recorder at 3 rpm for recording and 54 rpm for playback.

Martin, F. T.↗
NASA NTRS1971

Magnetic tape recorder for long operating life in space.

Magnetic tape recorders have long been used on satellites and spacecraft for onboard storage of large quantities of data. As satellites enter into commercial service, long operating life at high reliability becomes important. Also, the presently planned long-duration space flights to the outer planets require long-life tape recorders. Past satellite tape recorders have achieved a less than satisfactory performance record and the operating life of other spacecraft tape recorders has been relatively short and unpredictable. Most failures have resulted from malfunctions of the mechanical tape transport. Recent advances in electric motors and static memories have allowed the development of a new tape recorder which uses a very simple tape transport with few possible failure modes. It consists only of two brushless dc motors, two tape guides, and the recording heads. Relatively low tape tension, wide torque capability, and precise speed control facilitate design for mechanical reliability to match that of tape-recorder electronics.

Bahm, E. J.↗