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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
NASA NTRS1972

Engine selection for transport and combat aircraft.

Review of the procedures used to select engines for transport and combat aircraft by illustrating the procedures for a long haul CTOL transport, a short haul VTOL transport, a long range SST, and a fighter aircraft. For the CTOL transport, it is shown that advances in noise technology and advanced turbine cooling technology will greatly reduce the airplane performance penalties associated with achieving low noise goals. A remote lift fan powered by a turbofan air generator is considered for the VTOL aircraft. In this case, the lift fan pressure ratio which maximizes payload also comes closest to meeting the noise goal. High turbine temperature in three different engines is considered for the SST. Without noise constraints it leads to an appreciable drop in DOC, but with noise constraints the reduction in DOC is very modest. For the fighter aircraft it is shown how specific excess power requirements play the same role in engine selection as noise constraints for commercial airplanes.

Dugan, J. F., Jr.↗
NASA NTRS2008

Wind Tunnel Testing of Powered Lift, All-Wing STOL Model

Short take-off and landing (STOL) systems can offer significant capabilities to warfighters and, for civil operators thriving on maximizing efficiencies they can improve airspace use while containing noise within airport environments. In order to provide data for next generation systems, a wind tunnel test of an all-wing cruise efficient, short take-off and landing (CE STOL) configuration was conducted in the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC) 14- by 22-foot Subsonic Wind Tunnel. The test s purpose was to mature the aerodynamic aspects of an integrated powered lift system within an advanced mobility configuration capable of CE STOL. The full-span model made use of steady flap blowing and a lifting centerbody to achieve high lift coefficients. The test occurred during April through June of 2007 and included objectives for advancing the state-of-the-art of powered lift testing through gathering force and moment data, on-body pressure data, and off-body flow field measurements during automatically controlled blowing conditions. Data were obtained for variations in model configuration, angles of attack and sideslip, blowing coefficient, and height above ground. The database produced by this effort is being used to advance design techniques and computational tools for developing systems with integrated powered lift technologies.

Collins, Scott W.↗
DOE OSTI2024

Intelligent Partitioning based Fully Parallel AC Security-Constrained Optimal Power Flow

Today’s power grid is becoming more diverse and integrated with high-level distributed energy resources and smart control technologies that is creating a new set of grid management challenges in terms of large-scale, nonlinear, and non-convex problem modeling, complex and time-consuming computation, as well as difficult uncertainty handling. This project focused on solving a challenging multi-period security-constrained generation scheduling problem, which is of great importance for maximizing the social welfare of real-time dispatch, day-ahead market, as well as weekly planning of power systems. Our developed software explored parallel optimization algorithms for complex and realistic power system models, and develop fast, efficient, and robust grid optimization solutions on the high-performance computing platform that will enable increased grid economics, flexibility, resilience, as well as energy security in the United States.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Thermal performance sensitivity to radial power flattening considerations in Nuclear Thermal Propulsion Reactors

Nuclear thermal propulsion is currently being developed for manned Mars and Lunar missions by the National Aeronautics and Space Administration due to its increased specific impulse and significant thrust to reduce the total trip time and cost of deep space missions. To maximize the performance of the engine the exit hydrogen propellant temperature should, ideally, be uniformly distributed among all the fuel elements. Uniform exit temperatures imply that the power must be flattened as much as possible. This paper leverages decoupled neutronic and thermal-hydraulic models to assess the thermal performance and reactivity tradeoffs associated with flattening the radial power distribution by adjusting the fuel kernel loading for each fuel element within the core. The results suggest that a uniform radial power distribution for a single control drum position will not necessarily yield an optimal core design due to the higher variance in power and thus maximum fuel and exit propellant temperature as the control drums rotate out during operation. The results presented here only point to the design characteristics be considered when core-level multi-physics simulations are applied in the context of a specific mission. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

A Hybrid Reinforcement Learning-MPC Approach for Distribution System Critical Load Restoration: Preprint

This paper proposes a hybrid control approach for distribution system critical load restoration, combining deep reinforcement learning (RL) and model predictive control (MPC) aiming at maximizing total restored load following an extreme event. RL determines a policy for quantifying operating reserve requirements, thereby hedging against uncertainty, while MPC models grid operations incorporating RL policy actions, i.e., the reserve requirement, renewable (wind and solar) power predictions, and load demand forecasts. We formulate the reserve requirement determination problem as a sequential decision making problem based on the Markov Decision Process (MDP) and design an RL learning environment based on the OpenAI Gym framework and MPC. The RL agent reward and MPC objective function aim to maximize and monotonically increase total restored load and minimize load shedding and renewable power curtailment. The RL algorithm is trained off-line using historical forecast of renewable generation and load demand. The method is tested using a modified IEEE 13-bus distribution test feeder containing wind turbine, photovoltaic, microturbine and battery. Case studies demonstrated that the proposed method outperforms other operating reserve determination methods.

distribution system↗
DOE OSTI2022

A Hybrid Reinforcement Learning-MPC Approach for Distribution System Critical Load Restoration

This paper proposes a hybrid control approach for distribution system critical load restoration, combining deep reinforcement learning (RL) and model predictive control (MPC) aiming at maximizing total restored load following an extreme event. RL determines a policy for quantifying operating reserve requirements, thereby hedging against uncertainty, while MPC models grid operations incorporating RL policy actions (i.e., reserve requirements), renewable (wind and solar) power predictions, and load demand forecasts. We formulate the reserve requirement determination problem as a sequential decision-making problem based on the Markov Decision Process (MDP) and design an RL learning environment based on the OpenAI Gym framework and MPC simulation. The RL agent reward and MPC objective function aim to maximize and monotonically increase total restored load and minimize load shedding and renewable power curtailment. The RL algorithm is trained offline using a historical forecast of renewable generation and load demand. The method is tested using a modified IEEE 13-bus distribution test feeder containing wind turbine, photovoltaic, microturbine, and battery. Case studies demonstrated that the proposed method outperforms other policies with static operating reserves.

distribution system↗
NASA NTRS2009

A Simple Mechanism for Fractionating Oxygen Isotopes in the Solar Nebula

Lightning in the Solar Nebula is caused by the tribo-electric charging of dust grains carried by massive turbulent flows and driven by the accretion energy in the disk: it has long been one agent assumed responsible for the formation of chondrules. The degree to which charge separation can occur is dependent upon a number of factors, including the concentration of radioactive sources and the total level of ionization in the nebula, and these factors determine the maximum energy likely to be released by a single bolt. While chondrule formation requires a massive discharge, even a small lightning bolt can vaporize grains in the ionized discharge channel. Experimental studies have shown that silica, iron silicate and iron oxide grains formed from a high voltage discharge in hydrogen rich gas containing some oxygen produces solids that are enriched in O-17 and O-18 relative to the composition of the starting gas. Vaporization of silicates produces SiO, metal and free oxygen atoms in each discharge and these species will immediately begin to recondense from the hot plasma. Freshly condensed grains are incrementally enriched in heavy oxygen while the gas is enriched in O-16. Repeated evaporation and condensation of silicates in continuously occurring lightning discharges will monotonically increase the fractionation of oxygen isotopes between the O-17 and O-18 rich dust and the O-16 rich gas. The first mass independently fractionated refractory oxide particles were produced in the lab following the condensation of a flowing gas mixture containing variable amounts of hydrogen, silane, pentacarbonyl iron and oxygen that passed through a high voltage discharge powered by a Tesla coil. While the exact chemical pathway is still uncertain, the most probable reaction mechanisms involve oxidation of the growing refractory clusters by O3, OH or O atoms. This model has some interesting consequences for chemical processes in the early solar nebula. Chemical fractionation of recondensed dust evaporated via lightning discharges should be strongly time dependent. At earlier times, the accretion rate is maximal, thus driving strong turbulence, energetic grain-grain collisions, tribo-electric charging and charge separation, leading to frequent, powerful lightning discharges. As the accretion rate diminishes, turbulence decreases and lightning discharges will become both less powerful and less frequent, thus decreasing the rate of dust-gas fractionation. The most rapid increase in the formation of O-16 poor dust will occur early in nebular history. Generation of fractionated dust should be distributed throughout the inner disk. Once condensed, grain dispersal would average out any significant isotopic anomalies within the inner disk.

Nuth, Joseph A., III↗
DOE OSTI2023

Economic Evaluation of a Coupled Nuclear Power Plant and Hydrogen Production Facility: A Case Study

This study optimized the design sizes and operation of a power-to-hydrogen-to-power integrated energy system to allow a baseload power plant to operate flexibly in the energy market. In collaboration with a utility industry partner, the system, consisting of an electrolyzer, compressors, storage tank, and fuel cell, was optimized under conditions specific to the proposed project at the site of a nuclear power plant. The Design Integration and Synthesis Platform to Advance Tightly Coupled Hybrid Energy Systems (DISPATCHES) maximized net present value by optimizing sizing of components and dispatch decisions. Revenues included sale of electricity, capacity payments typical of the New York Independent System Operator, and the section 45V hydrogen production tax credit of the Inflation Reduction Act of 2022 (the tax credit was assumed to be available to legacy plants in the absence of clear guidance at present). Under default assumptions which excluded many capital expenditures, the base case optimized solution had a net present value of $\$$1.4 million over a 30 year lifetime, with a 0.365 MW fuel cell operating nearly continuously and 85% of revenues supplied by the hydrogen production tax credit (which was counted as a revenue regardless of profit, thus assuming credit monetization or offset of taxes within the larger firm was possible in all years). Beyond the base case, a sensitivity study elucidated drivers of the economics as capacity payment rate and hydrogen production tax credit rate vary. Additional sensitivity studies also extended results to variation of other, previously fixed parameters, including the fuel cell capital cost, and to imposition of further constraints. Optimization was also repeated for the default assumptions but recognizing tax credits upon use of hydrogen rather than upon its production, producing no change in the optimal solution. Most notably, capacity payments above $\$$15/kW-month drove optimal fuel cells multiple times larger than those with the default estimated capacity payment of $\$$2.5/kW-month (approaching 11 vs. 0.365 MW), and these larger fuel cells operated rarely (capacity factors of ~0.03). Furthermore, when the hydrogen production tax credit was provided for only 10 years, under the specific assumptions of this study (e.g., neither site preparation costs nor electrolyzer capital cost counted), the optimal solution avoided economic loss by ceasing system operation after the 10th year. Viewed broadly, this study demonstrated the capabilities of DISPATCHES, which can be user-adapted to serve other industrial case studies.

08 HYDROGEN↗
DOE OSTI2023

Influence on Structural Loading of a Wave Energy Converter by Controlling Variable-Geometry Components and the Power Take-Off

Oceans are harsh environments and can impose significant loads on deployed structures. A wave energy converter (WEC) should be designed to maximize the energy absorbed while ensuring the operating wave condition does not exceed the failure limits of the device itself. Therefore, the loads endured by the support structure are a design constraint for the system. Furthermore, the WEC should be adaptable to different sea states. Herethis work uses a WEC-Sim model of a variable-geometry oscillating wave energy converter (VGOSWEC) mounted on a support structure simulated under different wave scenarios. A VGOSWEC resembles a paddle pitching about a fixed hinge perpendicular to the incoming wave fronts. The geometry of the VGOSWEC is varied by opening a series of controllable flaps on the pitching paddle when the structure experiences threshold loads. It is hypothesized that opening the flaps should result in load shedding at the base of the support structure by reducing the moments about the hinge axis. This work compares the hydrodynamic coefficients, natural periods, and response amplitude operators from completely closed to completely open configurations of the controllable flaps. This work shows that the completely open configuration can reduce the pitch and surge loads on the base of the support structure by as much as 80%. Increased loads at the structure’s natural period can be mitigated by an axial power take-off damping acting as an additional design parameter to control the loads at the WEC’s support structure.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

TEAMER: Results of Investigating Structural Design Concepts and Alternative Materials for a Wave Power System

Included here are materials from a study on the design of a three-body Wave Energy Converter (WEC) utilizing a heave plate, dual Power Take Offs (PTOs), and single point mooring. A material trade study has been conducted to evaluate the effects of introducing various metallic and fiber-reinforced polymer (FRP) elements to the design. The baseline design is C-Power's patented k2 Wave Power System (WPS). This Testing Expertise and Access for Marine Energy Research (TEAMER) Request for Technical Support (RFTS) 9 effort resulted in alternative designs of the WPS center member, the nacelle. The analysis resulting from this study will inform the design of a lightweight structure with lower manufacturing and operating costs that increases energy conversion and power-to-weight ratio of the device. The dataset contains several components: finite element analysis (FEA) data, hand calculations, and CAD models. FEA files includes those used for and generated by finite element simulations. Calculations include hand calculations performed using Microsoft Excel, which assess core laminate properties, buckling, and other structural aspects in accordance with risk management DNV-RP-C201 standards. CAD materials include Solidworks files for parts, assemblies, and drawings of the evaluated models.

16 TIDAL AND WAVE POWER↗
DOE OSTI2023

A Review of Sociotechnical Approaches for Nuclear Power Plant Modernization

The current United States nuclear power plant fleet is in need of transforming the way work is performed to remain competitive with other electricity-generating sources. The use of new digital technologies can be applied to significantly reduce operating and maintenance costs. Recent research by the United States Department of Energy Light Water Reactor Sustainability Program has identified new opportunities to leverage advanced digital technologies to transform the way work is performed at existing plants. However, to ensure that the capabilities of people and advanced digital technologies are jointly optimized, a sociotechnical approach should be considered. This work explores recently introduced sociotechnical approaches to address the function allocation and data visualization considerations in the integration of new digital technologies to ensure safety, reliability, and maximizing the capabilities of proposed technological solutions that ensure the economic viability of the existing United States nuclear power plant fleet.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1998

Effects of Planetary Speed Reduction Ratio on Mean Service Life

Planetary gear transmissions are compact speed reductions which use parallel-load paths to transmit high power. The range of possible reduction ratios is bounded from below and above by limits on the relative size of the planet gears. For a single plane planetary transmission, the speed-reduction ratio must be greater than two for planet gears to exist. As the ratio increase, so does the size of the planets relative to the sizes of the sun and ring. Which ratio is best for a planetary reduction can be resolved by studying a series of optimal designs. In this series, each design is obtained by maximizing the service life for a spur-gear planetary with a fixed size, speed reduction ratio, input speed, power and materials. The planetary gear reduction service life is modeled as a function of the two-parameter Weibull distributed service lives of the ball bearings and spur gears in the reduction. Planet-bearing life strongly influences the optimal reduction lives which point to an optimal planetary reduction ratio in the neighborhood of four to five.

Savage, M.↗
DOE OSTI2024

NSTX-U liquid metal core-edge facility (LMCE)

NSTX-U/LMCE will provide a unique and world-leading research facility to address the primary challenge to delivering economic and timely magnetic fusion energy, namely the need to develop a power and particle exhaust and first-wall system that can withstand very high edge heat fluxes, maximize energy confinement, and avoid the production of large masses of solid eroded first-wall material. The NSTX-U/LMCE facility will assess the ability of liquid metals (LMs) – especially liquid lithium – to provide a new boundary condition for magnetic fusion systems, to extend the lifetime of the plasma facing components (PFCs) and improve core plasma confinement. Such capability is needed to establish the basis for next-step fusion facilities including fusion pilot plants, and to maintain U.S. world leadership in core-edge integration research. NSTX-U/LMCE will leverage the ability to generate very high divertor perpendicular heat flux q⊥ ~ 100MW/m 2 , extensive diagnostics, and liquid-metal-applicable infrastructure of NSTX-U. NSTX-U/LMCE will provide access to a high-confinement plasma core with majority self-driven plasma current, the flexibility to test a range of liquid metal divertor concepts, access to a range of separatrix collisionalities (from high to very low), and the ability to controllably vary the first-wall temperature to vary the plasma- wall interaction physics on liquid lithium components. Further, NSTX-U/LMCE will utilize more reactor-relevant high-Z refractory-metal PFC substrates. With these capabilities the NSTX-U/LMCE facility will explore the full continuum of core-edge solutions ranging from high core radiated power, to conditions with radiative losses concentrated in the scrape-off layer (SOL), and ultimately low recycling conditions. The low collisionality SOL that may be accessible in the low recycling regime is relatively unexplored and will require a kinetic treatment of the edge, which can be addressed theoretically, and with experiments in LTX-β. Additional smaller-scale preparatory R&D facilities will be required to reduce the risk of premature technical/engineering failure of liquid metal systems implemented in NSTX-U. The NSTX-U/LMCE facility aligns very well with recommendations in the FESAC Long-Range Plan and NASEM Pilot Plant reports and the Bold Decadal Vision, will be unique in the world program throughout the next decade, and is garnering private company interest in utilizing NSTX-U/LMCE for development of LM PFCs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Hybrid-RL-MPC4CLR (Hybird-Reinforcement-Learning-Model-Predictive-Control-for-Reserve-Policy-Assisted-Critical-Load-Restoration-in-Distribution-Grids)

Hybrid-RL-MPC4CLR was developed as a hybrid controller for active distribution grid critical load restoration, combining deep reinforcement learning (RL) and model predictive control (MPC) aiming at maximizing total restored load following an extreme event. The RL determines a policy for quantifying operating reserve requirements, thereby hedging against uncertainty, while the MPC models grid operations incorporating the RL policy actions (i.e., reserve requirements), renewable (wind and solar) power predictions, and load demand forecasts. The developers formulated the reserve requirement determination problem as a sequential decision-making problem based on the Markov Decision Process (MDP) and design an RL learning environment based on the OpenAI Gym framework and MPC simulation. The RL agent reward and MPC objective function aim to maximize and monotonically increase total restored load and minimize load shedding and renewable power curtailment. The software is developed using various software packages in Python. The MPC's optimal power flow (OPF) model is implemented using the Pyomo package, the RL simulation environment is implemented using the MPC simulation with various scenarios of renewable energy and load demand profiles and power outage beginning times, based on the OpenAI Gym framework. The RL agent training is performed using the RLlib Ray package. The RL algorithm is trained offline using historical forecasts of renewable generation and load demand profiles. Simulation analysis and performance tests are conducted using a modified IEEE 13-bus distribution test feeder containing wind turbine, photovoltaic, microturbine, and battery.

Eseye, Abinet Tesfaye↗
DOE OSTI2025

CRiSPPy: An advanced hydropower scheduling tool for the Colorado River Storage Project

The Western Area Power Administration (WAPA) plays a vital role in delivering reliable and cost-effective hydroelectric power to millions of customers across the western United States. The Colorado River Storage Project (CRSP) carries out WAPA’s mission in Arizona, Utah, Colorado, New Mexico, Nevada, Wyoming and Texas. Achieving this mission requires effective management of the Colorado River system, and depends on the use of advanced analytical tools and modeling methodologies. For many years, CRSP has relied on the Generation and Transmission Maximization Superlite (GTMax SL) model for its mid-term and long-term hydroscheduling needs. However, the evolving energy market, power system operations, environmental rules, and hydrology conditions, coupled with advancements in computational capabilities, have necessitated the development of a more modern and robust solution. This report introduces the Colorado River Storage Project Python-based (CRiSPPy) model, a new, advanced hydropower scheduling tool developed to address CRSP ever-evolving challenges. CRiSPPy represents a significant leap forward in our ability to model and optimize the operation of the Colorado River system. It incorporates state-of-the-art optimization algorithms, enhanced data management capabilities, and an advanced graphical user interface, providing WAPA CRSP personnel with unprecedented insights and decision-making support. This document details the development, capabilities, and implementation of CRiSPPy. It is intended to serve as a comprehensive resource for WAPA staff, stakeholders, and anyone interested in the future of hydropower scheduling in the Colorado River Basin. We are confident that CRiSPPy will enhance WAPA's mission while adapting to the challenges of a dynamic and increasingly complex environment. The version of CRiSPPy described in this report is the version 2.3. New versions of CRiSPPy will be developed as the tool keeps evolving to address CRSP challenges.

13 HYDRO ENERGY↗
DOE OSTI2022

Atacama Cosmology Telescope: Constraints on prerecombination early dark energy

The early dark energy (EDE) scenario aims to increase the value of the Hubble constant (H0) inferred from cosmic microwave background (CMB) data over that found in the standard cosmological model (Λ CDM ), via the introduction of a new form of energy density in the early Universe. The EDE component briefly accelerates cosmic expansion just prior to recombination, which reduces the physical size of the sound horizon imprinted in the CMB. Previous work has found that nonzero EDE is not preferred by Planck CMB power spectrum data alone, which yield a 95% confidence level (C.L.) upper limit f EDE < 0.087 on the maximal fractional contribution of the EDE field to the cosmic energy budget. In this paper, we fit the EDE model to CMB data from the Atacama Cosmology Telescope (ACT) data release 4. We find that a combination of ACT, large-scale Planck TT (similar to WMAP), Planck CMB lensing, and BAO data prefers the existence of EDE at >99.7 % C .L . : f EDE = 0.091$^{+0.020}_{-0.036}$, with H 0 = 70.9$^{+1.0}_{-2.0}$ km/s/Mpc (both 68% C.L.). From a model-selection standpoint, we find that EDE is favored over Λ CDM by these data at roughly 3 σ significance. In contrast, a joint analysis of the full Planck and ACT data yields no evidence for EDE, as previously found for Planck alone. We show that the preference for EDE in ACT alone is driven by its TE and EE power spectrum data. The tight constraint on EDE from Planck alone is driven by its high-ℓ TT power spectrum data. Understanding whether these differing constraints are physical in nature, due to systematics, or simply a rare statistical fluctuation is of high priority. Here, the best-fit EDE models to ACT and Planck exhibit coherent differences across a wide range of multipoles in TE and EE, indicating that a powerful test of this scenario is anticipated with near-future data from ACT and other ground-based experiments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Hydropower flexibility valuation tool for flow requirement evaluation

Timing of generation is becoming more and more valuable. This creates greater potential tension between environmental and power system objectives since both systems require their own flow patterns. Identifying win–win outcomes in this context requires being able to discuss the value of flexibility across stakeholder groups. This research proposes a two-stage optimization method to understand hydropower flexibility to meet both environmental and power system requirements. The tool simulates the two-settlement market process in the U.S. by maximizing revenues from both the day-ahead and real-time markets, subject to plant operational limits, regulatory flow and ramping requirements, and uncertainties associated with water availability and market prices. The model is formulated as linear programming problems and solved using IBM ILOG CPLEX optimizer. By examining a range of flow requirements, ramping constraints, and storage capacities, the proposed tool shows how to make more informed decisions to weigh the cost of specific flow requirements in the context of the overall license requirements. Results from the case study show that revenue is more sensitive to the ramping constraints than the minimum flow constraints. We also demonstrate that removing flow constraints in a dry month increases monthly revenue by up to 118%, as opposed to only 1% in a wet month. In addition, our results suggest that using a learning-based water flow forecast results in an increase of monthly revenue up to 6.4% compared with persistence forecast.

13 HYDRO ENERGY↗
DOE OSTI2022

Universal signal scaling in microwave impedance microscopy

Microwave impedance microscopy (MIM) is an emerging scanning probe technique that measures the local complex dielectric function using near-field microwave. Although it has made significant impacts in diverse fields, a systematic, quantitative understanding of the signal's dependence on various important design parameters is lacking. Here, we show that for a wide range of MIM implementations, given a complex tip-sample admittance change ΔΥ, the MIM signal—the amplified change in the reflected microwave amplitude—is –G · ΔΥ/2Υ 0 · η 2 · V in , where η is the ratio of the microwave voltage at the probe to the incident microwave amplitude, Y o is the system admittance, and G is the total voltage gain. For linear circuits, η is determined by the circuit design and does not depend on V in . We show that the maximum achievable signal for different designs scales with η 2 or η when limited by input power or sample perturbation, respectively. Furthermore, this universal scaling provides guidance on diverse design goals, including maximizing narrow-band signal for imaging and balancing bandwidth and signal strength for spectroscopy.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗