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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 397 records · Page 22

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NASA NTRS1991

Progress and recent developments in sodium-metal chloride batteries

Significant strides have been made in the development of high-temperature rechargeable sodium batteries utilizing transition metal chloride cathodes in the last decade, mainly due to the expertise available on Na/S batteries. These systems have already performed attractively in the various feasibility studies and have an excellent safety record. Despite the encouraging figures obtained for specific energies, certain design changes such as modifying the geometry of the beta alumina electrolyte and optimization of the porous cathodes for enhanced electrolyte flow need to be made to achieve high power densities required in applications such as electric vehicles and space. The chemistry of MCl2 cathodes, electrode fabrication, and design options are discussed, and performance data are examined.

Ratnakumar, B. V.↗

NASA NTRS1989

Development of a high power microwave thruster, with a magnetic nozzle, for space applications

This paper describes the current development of a high-power microwave electrothermal thruster (MET) concept at the NASA Lewis Research Center. Such a thruster would be employed in space for applications such as orbit raining, orbit maneuvering, station change, and possibly trans-lunar or trans-planetary propulsion of spacecraft. The MET concept employs low frequency continuous wave (CW) microwave power to create and continuously pump energy into a flowing propellant gas at relative high pressure via a plasma discharge. The propellant is heated to very high bulk temperatures while passing through the plasma discharge region and then is expanded through a throat-nozzle assembly to produce thrust, as in a conventional rocket engine. Apparatus, which is described, is being assembled at NASA Lewis to test the MET concept to CW power levels of 30 kW at a frequency of 915 MHz. The microwave energy is applied in a resonant cavity applicator and is absorbed by a plasma discharge in the flowing propellant. The ignited plasma acts as a lossy load, and with optimal tuning, energy absorption efficiencies over 95 percent (based on the applied microwave power) are expected. Nitrogen, helium, and hydrogen will be tested as propellants in the MET, at discharge chamber pressures to 10 atm.

Power, John L.↗

DOE OSTI2020

Machine learning coupled multi-scale modeling for redox flow batteries

The reaction distribution in macro or device-scale has been studied for redox flow batteries. The reaction distribution on electrode pore-scale structure however is not well understood, lacking especially on how the reaction distribution on the pore-scale may impact the overall performance of a flow battery. This study introduces for the first time a framework of a multi-scale model that provides understanding of the relationship between the pore-scale electrode structure reaction and the device-scale electrochemical reaction uniformity within the flow battery. A reduced order model is constructed based on 128 pore-scale simulations, which provide a quantitative relationship between the battery operation conditions (inlet velocity, current density, inlet concentration) and the surface reaction uniformity for the pore-scale sample. The multi-scale framework upscales this pore-scale surface reaction uniformity to device-scale combined uniformity. Based on the multi-scale model, a time-varying optimization of the inlet velocity is established, leading to significant reduction on pump power consumption with targeted surface reaction uniformity. The multi-scale model establishes the critical link between the micro-structure of a flow battery component and its performance at the macro-scale, therefore providing rationale for further operational or material optimization.

flow batteries, machine learning, multi-scale mode↗

NASA NTRS1981

On variable hydrostatic transmission for road vehicles, powered by supply of fluid at constant pressure

Various hydrostatic power transmission systems for automotive applications with power supply at constant pressure and unrestricted flow and with a Volvo Flygmotor variable displacement motor as the principal unit were investigated. Two most promising concepts were analyzed in detail and their main components optimized for minimum power loss at the EPA Urban Driving Cycle. The best fuel consumption is less than 10 lit. per 100 kM for a 1542 kG vehicle with a hydrostatic motor and a two speed gear box in series (braking power not recovered). Realistic system pressure affects the fuel consumption just slightly, but the package volume/weight drastically. Back pressure increases losses significantly. Special attention was paid to description of the behavior and modeling of the losses of variable displacement hydrostatic machines.

Magi, M.↗

DOE OSTI2021

Wind and Structural Loads on Parabolic Trough Solar Collectors at Nevada Solar One

Wind loading is a main contributor to structural design costs of Concentrating Solar Power (CSP) collectors, such as heliostats and parabolic troughs. These structures must resist the mechanical forces generated by turbulent wind. At the same time, the reflector surfaces must exhibit the necessary rigidity to maintain their optimal optical performance in windy conditions. Over two years, NREL conducted comprehensive field measurements of the atmospheric turbulent wind conditions and the resulting structural wind loads on parabolic troughs at the Nevada Solar One (NSO) plant. The measurement set-up included meteorological masts and structural load sensors on four trough rows. Additionally, we commissioned a lidar scanning the horizontal plane over the trough field. This data set catalogs the high-resolution data set characterizing the complex flow field and resulting structural loads on parabolic trough collectors. By providing this first-of-its-kind data set to the CSP community, we aim to enhance the community's understanding of wind-loading experienced by CSP collector structures. This data set will also help design next-generation solar collectors and photovoltaic trackers.

Array↗

DOE OSTI2023

TEAMER: Experimental performance characterization of a shrouded axial-flow turbine

Sitkana has developed a shrouded hydrokinetic turbine with a modular, low-cost design that can be scaled to meet the needs of remote communities. With technical support from the University of Washington, Sitkana sought to experimentally characterize the mechanical power and structural loads of various 1:3.3 scale rotor geometries. In all, 11 different rotor geometries were characterized with variations in height-to-diameter ratio, blade number, and blade type (foiled versus flat). All tests were conducted in Reynolds-independent flow conditions in the Alice C. Tyler Flume at the University of Washington. Results allow Sitkana to (1) refine the optimal rotor geometry, (2) validate numerical models, and (3) predict power output for a full-scale system. This project is part of the TEAMER RFTS 8 (request for technical support) program.

16 TIDAL AND WAVE POWER↗

NASA NTRS1995

Optimized Coolant-Flow Diverter For Increased Bearing Life

Coolant-flow diverter for rolling-element bearings in cryogenic turbopump designed to enhance cooling power of flow in contact with bearings and thereby reduce bearing wear. Delivers jets of coolant as close as possible to hot spots at points of contact between balls and race. Also imparts swirl that enhances beneficial pumping effect. Used with success in end ball bearing of high-pressure-oxidizer turbopump.

Subbaraman, Maria R.↗

NASA NTRS1993

Two-dimensional thermal-hydraulics analyses of the Pellet Bed Reactor for Nuclear Thermal Propulsion

Thermal-hydraulics design and analyses of the Pellet Bed Reactor for nuclear thermal propulsion are performed using the nuclear propulsion thermal-hydraulic analysis model to determine the 2D steady-state temperature, pressure, and flow fields in the core and optimize the orificing in the hot-frit to avoid hot spots in the core at full power operation. Results show that by properly adjusting the axial porosity profile in the hot frit, hot spots in the core can be essentially eliminated during full power operation. This important accomplishment is achieved at the expense of slightly larger pressure losses in the core because of flow restriction at the hot frit. However, the overall pressure losses is only about 11 percent of the propellant inlet pressure.

Morley, Nicholas J.↗

DOE OSTI2020

Multi-Energy Microgrid Planning Considering Heat Flow Dynamics

In this paper, we present a multi-energy microgrid optimal planning method, considering the intra-hour dynamics of the heating system as constraints of the energy dispatch, and consequently of the sizing of the Combined Heat and Power units. The fixed-mass flow rate method and finite difference technique are applied to linearize the dynamic constraints. Moreover, to determine the values of the mass flow rates, a critical scenario representing the slowest heat dynamic process is put forward. Finally, a realistic microgrid case study is presented to illustrate the effect of considering the heat flow dynamics in the overall solution.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Voltage Stability Constrained Moving Target Defense Against Net Load Redistribution Attacks

Moving target defense (MTD) using distributed flexible AC transmission system (D-FACTS) devices is a promising defense strategy to detect stealthy false data injection (FDI) attacks against the power system state estimation. However, all existing studies myopically perturb the reactance of D-FACTS lines without considering the system voltage stability. In this paper, we first illustrate voltage instability induced by MTDs in a three-bus system. To address this issue, we further propose a novel MTD framework that explicitly considers system voltage stability by using continuation power flow and voltage stability indices. We mathematically derive the sensitivity matrix of voltage stability index to line impedance, on which an optimization problem for maximizing voltage stability index is formulated. This framework is tested on the IEEE 14-bus and the IEEE 118-bus transmission systems, in which net load redistribution attacks are launched by sophisticated attackers. Here, the simulation results show the effectiveness of the proposed framework in circumventing the voltage instability while maintaining the detection effectiveness of MTD. We conduct case studies with and without the proposed framework under different MTD planning and operational methods. The impacts of the proposed two methods on attack detection effectiveness and system economic metrics are also revealed.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Rapid scalable fabrication of roll-to-roll slot-die coated flexible perovskite solar cells using intense pulse light annealing

Perovskite solar cells have achieved high efficiencies at the lab scale using batch processes that often may not be scalable. Processes that can be integrated into a continuous manufacturing platform, such as roll-to-roll, where several processes can be carried out sequentially are necessary to develop a new cost-competitive solar technology. In this work, intense pulsed light thermal post-processing is coupled with scalable slot-die coating and air knife evaporation in a high-speed roll-to-roll process of up to 2 m min –1 . The optimization of IPL energy parameters, web speeds, solution flow rates, and concentration of precursor inks yielded a champion power conversion efficiency of 11.24% for a 1 cm 2 roll-to-roll coated device. The overall processing time for a single layer in this process is reduced from minutes to seconds and the overall footprint of the manufacturing process is decreased. Furthermore, this demonstrates the promising capabilities for intensed pulsed light to reduce manufacturing costs and paves a roadmap for scalable and efficient PSCs on a roll-to-roll platform.

14 SOLAR ENERGY↗

NASA NTRS2006

On the Need for Multidimensional Stirling Analysis

Contents include the following: Dual opposed convertors. High efficiency. Low mass space power. One-dimensional analysis. Fast computation. Design optimizations are easily done. Need for multidimensional modeling. Axisymmetric simulation. Flow characteristics. Low mach number. Laminar, transitional, and turbulent flow. Conjugate heat transfer. Third order analysis. Recent whole engine modeling. Regenerator geometry. Turbulence modeling. Flat head heater not 1-D. Empirical coefficients needed. Experiment design. Flow distribution. Sensor placement. Calibration. Validation.

Dyson, Rodger↗

NASA NTRS1988

Hydrogen turbines for space power systems: A simplified axial flow gas turbine model

Hydrogen cooled, turbine powered space weapon systems require a relatively simple, but reasonably accurate hydrogen gas expansion turbine model. Such a simplified turbine model would require little computational time and allow incorporation into system level computer programs while providing reasonably accurate volume/mass estimates. This model would then allow optimization studies to be performed on multiparameter space power systems and provide improved turbine mass and size estimates for the various operating conditions (when compared to empirical and power law approaches). An axial flow gas expansion turbine model was developed for these reasons and is in use as a comparative bench mark in space power system studies at Sandia. The turbine model is based on fluid dynamic, thermodynamic, and material strength considerations, but is considered simplified because it does not account for design details such as boundary layer effects, shock waves, turbulence, stress concentrations, and seal leakage. Although the basic principles presented here apply to any gas or vapor axial flow turbine, hydrogen turbines are discussed because of their immense importance on space burst power platforms.

Hudson, Steven L.↗

DOE OSTI2024

Joint Management and Optimization of Residential Natural Gas and Electricity Distribution Networks Coupled via Fuel Cells

The interesting properties of natural gas as well as the growing electric power demand worldwide have led to increasing attention to natural-gas-based distributed generation applications in electric distribution systems. This paper goes over the interdependency between a residential natural gas network and an electric distribution network that are coupled via fuel cells. The modeling of the gas network is introduced first, and then the algorithm for gas flow study is presented. The optimal placement and sizing of fuel cell based distributed generation systems are formulated to minimize the losses in both the gas and electric distribution networks, subject to their model constraints. In addition to this, in order to capture the probabilistic nature of the optimization problem under study, the K-means clustering algorithm is applied to the gas and electricity demands to determine hourly load states and their corresponding probabilities. Furthermore, simulation studies are carried out on an integrated system consisting of the IEEE 69-bus distribution feeder and a radial 27-node natural gas network to verify the developed optimization model and the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Joint Management and Optimization of Residential Natural Gas and Electricity Distribution Networks Coupled via Fuel Cells

The attractive features of natural gas as well as the growing electric power demand worldwide have created increasing interest in natural-gas-based distributed generation applications for electric distribution networks. Here, this paper investigates the interdependency between a residential natural gas network and an electric distribution network that are linked together via fuel cells. The modeling of the natural gas network is introduced first, and then the algorithm for gas flow study is presented. The optimal placement and sizing of fuel cell based distributed generation systems are formulated to minimize the losses in both the natural gas network and the electric distribution grid, subject to the constraints imposed by both networks. In addition, a probabilistic model for both gas and electricity demands is developed based on historical electricity and natural gas demand data. A K-means clustering method is used to determine the hourly load states to solve the joint probabilistic optimization problem. Simulation studies are carried out on an integrated system consisting of the IEEE 69-bus distribution network and a radial 27-node natural gas network to verify the developed optimization model and the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

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 OSTI2023

Real Time and Forecasted DLR: Use Cases

This document contains two use cases for the utilization of dynamic line ratings in operational practices. These use cases were developed in support of the Transmission Optimization and Grid Enhancing Technology (TOGETS) task force aimed at facilitating the deployment of dynamic line rating and power flow technologies across the United States. The project included a demonstration of the technology on the Idaho National Laboratory system. The procurement documents, tests scripts, and field-validated results from multiple vendors will be published to improve industry’s familiarity with the products. Because of the urgency in performing this work and INL’s unique test setup, the Task Force identified a need for additional public information on the information exchanges required for operationalizing DLR (i.e. integrating DLR’s within actual system operations). As such, this use case document and an accompanying interoperability profile have been developed with input from the Task Force and various vendors whose systems would ultimately support the functionality described. The use case and interoperability profile support two distinct functionalities with different purposes.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Modeling Subsurface Performance of a Geothermal Reservoir Using Machine Learning

Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells—increasing or decreasing the fluid flow rates across the wells—and drilling new wells at appropriate locations. The latter is expensive, time-consuming, and subject to many engineering constraints, but the former is a viable mechanism for periodic adjustment of the available fluid allocations. In this study, we describe a new approach combining reservoir modeling and machine learning to produce models that enable such a strategy. Our computational approach allows us, first, to translate sets of potential flow rates for the active wells into reservoir-wide estimates of produced energy, and second, to find optimal flow allocations among the studied sets. In our computational experiments, we utilize collections of simulations for a specific reservoir (which capture subsurface characterization and realize history matching) along with machine learning models that predict temperature and pressure timeseries for production wells. We evaluate this approach using an “open-source” reservoir we have constructed that captures many of the characteristics of Brady Hot Springs, a commercially operational geothermal field in Nevada, USA. Selected results from a reservoir model of Brady Hot Springs itself are presented to show successful application to an existing system. In both cases, energy predictions prove to be highly accurate: all observed prediction errors do not exceed 3.68% for temperatures and 4.75% for pressures. In a cumulative energy estimation, we observe prediction errors that are less than 4.04%. A typical reservoir simulation for Brady Hot Springs completes in approximately 4 h, whereas our machine learning models yield accurate 20-year predictions for temperatures, pressures, and produced energy in 0.9 s. This paper aims to demonstrate how the models and techniques from our study can be applied to achieve rapid exploration of controlled parameters and optimization of other geothermal reservoirs.

15 GEOTHERMAL ENERGY↗