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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1965

Factors Relating to the Airport-Community Noise Problem

Factors relating to the airport-community noise problem are discussed herein. The noise problems are associated with aircraft landing approaches, take-offs, and climbouts in communities near commercial airports. The main objectives are to identify the significant factors involved in the problem, to define some of their interrelationships, and to present recent related research information from NASA in-house and contract studies. Changes in the types of aircraft power plants, the aircraft operating procedures, and the community itself are all judged to be important; however, these changes should not be made without understanding the associated human-response implications.

Hubbard, Harvey H.↗
DOE OSTI2025

Investigation of the Performance and Explainability Tradeoffs for Machine-Learning Models for Predictive Maintenance of Circulating Water Systems in Nuclear Power Plants

Predictive maintenance (PdM) has shown great potential for achieving substantial cost savings and enhancing the economic competitiveness of nuclear power plants (NPPs) in today's energy market. Among the different modeling approaches that exist, machine learning (ML) tools in particular have a demonstrated ability to handle high dimensional and multivariate data and to extract hidden relationships within data in industrial environments. While ML methods show great potential, their lack of explainability---especially for black-box models---is a major hurdle to their adoption. Moreover, considering the supposed trade-off between explainability and performance challenges, careful consideration must be made as to which of these quality aspects takes precedence in light of multiple modeling options, resource availability, and domain characteristics. The present work evaluates the performance of six ML models, each with a different degree of explainability, in classifying the conditions of circulating water pumps (CWPs) by utilizing sensor data from nuclear power plants. To determine the drivers behind the trade-offs presented by this array of models, this work also tests different combinations of CWP units as the training and testing data, degrees of data imbalance, and objective functions for hyperparameter tuning. It was found that black-box models tend to afford superior performance in cases where there are far more instances of one type of labeled data than of any other type. It is recommended that a guided procedure be followed for designing and delivering an ML system that is sufficiently explainable to all involved stakeholders.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

System Modeling Frameworks for Wind Turbines and Plants: Review and Requirements Specifications

System modeling frameworks for wind turbines and plants are used by research groups and industry to design wind energy systems that take into account key trade-offs across performance, cost, and reliability at both the turbine and plant level. The frameworks are exercised using a variety of multi-disciplinary design, analysis and optimization (MDAO) methods. To improve inter-operability and foster collaboration, this report proposes a classification system for the frameworks along dimensions of model fidelity and scope. The classification system is first motivated with reviews the state-of-the-art in the development of software frameworks for integrated wind turbine and plant simulation. Within each major wind turbine and power plant subsystem, a matrix is developed for the disciplines used and the fidelity levels with which each discipline can be modeled. The existing frameworks are then classified according to the matrix. Next, an ontology is proposed that will allow for standardizing how data is transferred between the most common discipline-fidelity combinations used in the frameworks. A common representation of data creates the ability to 1) share system descriptions and analysis results, supporting more transparent benchmarks and comparison, and 2) integrate models together into workflows within and across organizations for improving the efficiency and performance of wind turbine and power plant design processes. Ultimately, this integration leads to better overall wind energy system designs with high performance and low costs.

17 WIND ENERGY↗
NASA NTRS1994

Lean spacecraft avionics trade study

Spacecraft design is generally an exercise in design trade-offs: fuel vs. weight, power vs. solar cell area, radiation exposure vs. shield weight, etc. Proper analysis of these trades is critical in the development of lightweight, efficient, 'lean' satellites. The modification of the launch plans for the Magnetosphere Imager (MI) to a Taurus launcher from the much more powerful Delta has forced a reduction in spacecraft weight availability into the mission orbit from 1300 kg to less than 500 kg. With weight now a driving factor it is imperative that the satellite design be extremely efficient and lean. The accuracy of engineering trades now takes on an added importance. An understanding of spacecraft subsystem interactions is critical in the development of a good spacecraft design, yet it is a challenge to define these interactions while the design is immature. This is currently an issue in the development of the preliminary design of the MI. The interaction and interfaces between this spacecraft and the instruments it carries are currently unclear since the mission instruments are still under development. It is imperative, however, to define these interfaces so that avionics requirements ideally suited to the mission's needs can be determined.

Main, John A.↗
NASA NTRS2005

Comet/Asteroid Protection System: Concept Study Executive Summary

Many of the major issues have been identified for a futuristic capability to protect against impacting comets and asteroids, and a preliminary space-based concept has been envisioned. Some of the basic concept elements, approaches, methodologies, and features have been identified. When contemplating the ability to monitor comets and asteroids continuously, there are many trade-offs between orbiting observatories and detection systems on planetary bodies without an atmosphere. Future orbit modification techniques have the potential for rapid and controlled alteration of NEO orbits, provided that high-power, compatible thermal management systems are developed. Much additional work and analysis are required to identify a final system concept, and many trade studies need to be performed to select the best mix of system capability, reliability, maintainability, and cost. Finally, it is fully appreciated that at the present time space systems are much more costly than terrestrial-based systems. Hopefully, this will change in the future. Regardless, understanding what it would take to defend against a much wider range of the impact threat will foster ideas, innovations, and technologies that could one day enable the development of such a system. This understanding is vital to provide ways of reducing the costs and quantifying the benefits that are achievable with a system like CAPS.

Mazanek, Daniel D.↗
DOE OSTI2023

Torrefaction of almond shell as a renewable reinforcing agent for plastics: techno-economic analyses and comparison to bioethanol process

Abstract In 2016, the US state of California alone produced nearly 3.5 billion kilograms of almonds, accounting for approximately 84% of the world’s almond production. This generated about 2.58 million metric tons (MTs) of almond residues. Almond shells are currently either burned to generate power or disposed of in landfill. Valorizing almond shells and hulls provides an opportunity to replace petroleum-derived products and divert organic material from landfill. Here we demonstrate a detailed techno-economic analysis (TEA) of an almond shell torrefaction process capable of utilizing the 520 000 MTs of almond shells produced annually in California. Our process also includes preprocessing the torrefied biomass to exploit it as a reinforcing agent for plastics. We further compared the revenue generated from the torrefied biomass and bioethanol derived from the same quantity of almond shells. We considered three different torrefaction facility scales to evaluate trade-offs between economies of scale at the facility and trucking costs to deliver almond shells. A facility that takes in 200 000 MT yr –1 of almond shells results in lower per-unit-output basis capital and operating cost relative to other smaller-scale torrefaction facilities, including 10 000 MT yr –1 and 50 000 MT yr –1 , considered for analysis in this study. The large-sale facility results in a minimum selling price (MSP) of the torrefied biomass of $311.4 MT –1 . An analogous TEA on converting almond residues into bioethanol is also investigated. The MSP of almond shell derived ethanol ($1.71 kg −1 ) is higher than that of corn ($0.48 kg −1 ) or cellulosic biomass ($0.88 kg −1 ) derived ethanol. Compared with the bioethanol route, the torrefied almond shells result in three times more revenue if utilized as a reinforcing agent for plastics.

Liu, Dupeng (ORCID:0000000269514064)↗
DOE OSTI2025

A Framework for Assessing Economic and Environmental Trade-offs of Internalized Emission Costs in ERCOT Grid Planning

The power grid is on the cusp of a massive transition driven by three major areas: 1) the growth in demand for electricity, 2) efforts to decarbonize the United States economy, and 3) a desire to mitigate social disparities from the impact of electricity generation on local populations. However, most studies of the electricity sector do not include equity impacts in their models. This study seeks to do so by developing a comprehensive and generalizable model tailored to the Electric Reliability Council of Texas (ERCOT) grid, designed to incorporate the equity impacts of electricity generation in a decarbonized and resilient framework. To integrate equity into our research, we incorporate environmental externalities into our capacity expansion model of ERCOT. Specifically, we factor in intermediate-level local marginal damages of precursor pollutants (NH3, NOx, primary PM2.5, SO2, and VOC) and global pollutant CO2 into the cost of generating electricity. We do this by taking into account county population, county ambient pollution concentration, and generator emission rates. Leveraging open-source modeling tools, such as PowerGenome, pyGRETA, and GenX we construct a county-level model to account for these costs. We integrate these marginal damages into the variable operations and maintenance costs of generators, for both existing and potential future builds. This study’s findings suggest that the value of a dynamic social cost of carbon (SSC) will cover criteria pollutant marginal damages within the ERCOT grid and solar and wind is expected to increase out to 2035. Key metrics evaluated within this research include fuel mix distribution across technologies, transmission and grid infrastructure costs, CO2 emissions, local pollutants marginal damages, and the variation in generation capacity built by the model. These results and framework can be used to support grid decisions that explicitly include distributional and procedural equity within a decarbonized and sustainable grid framework.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRSDate not supplied

Energy-Optimized Path Planning for Uas in Varying Winds Via Reinforcement Learning

In this paper we propose a reinforcement learning (RL) algorithm for path planning of Unmanned Aviation Vehicles (UAVs) under varying wind conditions. Solutions to UAV path planning problems are becoming increasingly necessary as autonomous UAVs continue to enter commercial and government spaces. Path-planning is inherently challenging, as UAVs need to account for dynamically changing flying conditions such as weather, obstacle or no-fly zones, degraded vehicle health, and off-nominal battery power consumption. Machine learning methods such as reinforcement learning (RL) have the potential to revolutionize how vehicles navigate in such uncertain environments. In this study, we compute UAV trajectories from a pre-determined starting position to a target cell within a 7X7 grid environment by optimizing parameters for mission assurance and safety limits in addition to the energy consumption and operation time. The UAV navigates the grid by taking actions to move in any of the eight cardinal and inter-cardinal directions, under constant thrust profile. The resultant UAV state is sampled from a probability distribution which accounts for the UAV’s action, local wind velocity, and the presence of obstacles or boundaries. As the unmanned airspace gets more complex due to multiple vehicles and environmental uncertainties, trade-offs between energy consumption, operation time, risk tolerance, and mission assurance need to be made. Our Markov Decision Process (MDP) environment model can capture any combination of these in the optimization objective, making it novel compared to other work in the field.

trajectory planning↗
DOE OSTI2022

Parameter inference with non-linear galaxy clustering: accounting for theoretical uncertainties

ABSTRACT We implement euclidemulator (version 1), an emulator for the non-linear correction of the matter power spectrum, into the Markov chain Monte Carlo forecasting code montepython. We compare the performance of halofit, hmcode, and euclidemulator1, both at the level of power spectrum prediction and at the level of posterior probability distributions of the cosmological parameters, for different cosmological models and different galaxy power spectrum wavenumber cut-offs. We confirm that the choice of the power spectrum predictor has a non-negligible effect on the computed sensitivities when doing cosmological parameter forecasting, even for a conservative wavenumber cut-off of $0.2\, h\, {\rm Mpc}^{-1}$. We find that euclidemulator1 is on average up to 17 per cent more sensitive to the cosmological parameters than the other two codes, with the most significant improvements being for the Hubble parameter of up to 42 per cent and the equation of state of dark energy of up to 26 per cent, depending on the case. In addition, we point out that the choice of the power spectrum predictor contributes to the risk of computing a significantly biased mean cosmology when doing parameter estimations. For the four tested scenarios we find biases, averaged over the cosmological parameters, of between 0.5σ and 2σ (from below 1σ up to 6σ for individual parameters). This paper provides a proof of concept that this risk can be mitigated by taking a well-tailored theoretical uncertainty into account as this allows to reduce the bias by a factor of 2 to 5, depending on the case under consideration, while keeping posterior credibility contours small: the standard deviations are amplified by a factor of ≤1.4 in all cases.

Astronomy & Astrophysics↗
DOE OSTI2021

Investigations into Balancing Peak-to-Average Power Ratio and Mean Power Extraction for a Two-Body Point-Absorber Wave Energy Converter

The power harnessed by wave energy converters (WECs) in oceans is highly variable and, therefore, has a high peak-to-average power (PTAP) ratio. To minimize the cost of a WEC power take off (PTO) system, it is desirable to reduce the PTAP ratio while maximizing the mean power extracted by WECs. The important issue of how PTAP ratio reduction measures (such as adding an inertia element) can affect the mean power extracted in a reference model has not been thoroughly addressed in the literature. To investigate this correlation, this study focuses on the integration of the U.S. Department of Energy’s Reference Model 3, a two-body point absorber, with a slider-crank WEC for linear-to-rotational conversion. In the first phase of this study, a full-scale numerical model was developed that predicts how PTO system parameters, along with an advanced control algorithm, can potentially affect the proposed WEC’s PTAP ratio as well as the mean power extracted. In the second phase, an appropriate scaled-down model was developed, and extracted power results were successfully validated against the full-scale model. Finally, numerical and hardware-in-the-loop (HIL) simulations based on the scaled-down model were designed and conducted to optimize or make trade-offs between the operational performance and PTAP ratio. The initial results with numerical and HIL simulations reveal that gear ratio, crank radius, and generator parameters substantially impact the PTAP ratio and mean power extracted.

16 TIDAL AND WAVE POWER↗
NASA NTRSDate not supplied

Systems Health Monitoring: Integrating FMEA into Bayesian Networks

The foreseeable high traffic density suggests that a large number of electric propulsion systems will enter the airspace, and that they will also operate at high frequency, e.g., large number of take offs and landings per unit time. The reliability of such critical systems is therefore key to ensure high safety standards in the low-altitude airspace. Diagnostic systems, which aim at identifying incipient faults, can mitigate unexpected failures or lower-than-expected reliability by performing early fault detection by monitoring the systems. A key element of fault diagnosis is fault detection and isolation (FDI), which complexity increases with the complexity of the system itself, namely the number of subsystems and components, interactions among sub-systems, and the number of sensors available. The proposed approach leverages combination of failure mode and effect analysis (FMEA) integrated with Bayesian networks, thus introducing dependability structures into a diagnostic framework to aid FDI. Faults and failure events from the FMEA are mapped within a Bayesian network, where network edges replicate the links embedded within FMEAs. The integrated framework enables the fault isolation process by identifying the probability of occurrence of specific faults or root causes given evidence observed through sensor signals. In this work, sub systems of Urban Air Mobility (UAM) type vehicle like avionics, structures, power-train etc. are taken into account to show the approach at the system level. This work integrates early design phase in the development of UAM type vehicles with diagnostic tools, which are often developed later in the product life-cycle, or retrofitted at a later time on systems. Failure mode and effect analysis (FMEA) derived for the system in the design phase is embedded within a Bayesian network (BN).

UAM↗
NASA NTRSDate not supplied

Markov Decision Process based Trajectory Planning for UAVs under Uncertain Wind Conditions

In this paper we propose a Markov Decision Process (MDP) algorithm for path-planning of Unmanned Aviation Vehicles (UAVs) under varying wind conditions. Solutions to path-planning for UAVs are becoming increasingly necessary as autonomous UAVs continue to enter commercial and government spaces. Path-planning is inherently challenging, as UAVs needs to account for dynamically changing flying conditions such as weather, obstacle or no-fly zones, degraded vehicle health and off-nominal battery power consumption. Machine learning methods such as Markov Decision Process (MDPs) have the potential to revolutionize how vehicles navigate in such uncertain environments. Previous papers have demonstrated the use of MDPs to optimize UAV path-planning for energy consumption under time-varying wind distribution. In this study, UAV trajectories from a pre-determined waypoint to target cell, will be computed on a 7X7 grid environment by optimizing parameters for mission assurance and safety limits in addition to the energy consumption, and operation time. The UAV navigates the grid by taking actions to move in either of the eight cardinal and intercardinal directions, under constant thrust profile. The next state of the UAV is calculated by considering its action, transition probability, obstacle cells and the wind speed magnitude and direction. Both constant and stochastic wind will be considered in this paper, the parameters being extracted from real wind measurements in proximity to an experimental UAV flight. One of the studies to be demonstrated in this paper is that as the unmanned airspace gets more complex with multiple vehicles and environmental uncertainties, trade-offs between energy consumption, operation time, risk tolerance, and mission assurance needs to be made. Further, MDPs are capable of fast computation of UAV trajectories under varying wind, hence making them suitable for in-flight path planners.

decision-making↗
NASA NTRS2021

PEM Fuel Cell MODEL for Conceptual Design of Hydrogen eVTOL Aircraft

A model and software for design and analysis of a Proton Exchange Membrane fuel cell (PEMFC) system are developed for hydrogen eVTOL aircraft. Examples are provided of stacks designed for 80 kWe and 500 kWe net electrical power. Examples are provided of eVTOL designed for 250 and 400 lb payload. The trade-offs included stack characteristics, hydrogen storage characteristics, and aircraft payload and range. The objectives were to identify the key technology drivers of a hydrogen rotorcraft, establish technology targets for a viable aircraft, and recommend research to address the fundamental pre-competitive barriers. The current U.S. infrastructure on hydrogen informed the targets and recommendations. The key conclusion is that the advances made in cell electrochemical power density over the last decade might allow a PEMFC system to meet, or even beat, piston engine powered light-utility rotorcraft. The development must focus on the key drivers of a hydrogen eVTOL. The drivers are ultra-light stack cooling and short-term hydrogen storage. A stack system of net electrical power 100−150 kWe with specific power 1.1 kWe/kg including air, cooling, and electrical subsystems, and a tank storage of 15% weight fraction hydrogen are the minimum targets to meet the performance of a modern piston-engine rotorcraft, with a range of 180 nautical miles, payload of 400 lb, and gross weight of about 1400 lb. This is defined as the objective aircraft. If only one target is met, an aircraft of half the range could be produced, with a 30% greater gross take-off weight. This is defined as an intermediate aircraft. Because definitive conclusions are premature without weights and loads data on a flight-worthy stack system, it is recommended that a fuel cell powered hydrogen eVTOL demonstrator be built and flown. The existing hydrogen infrastructure for cars provide ample opportunity to create a pilot program. About 12 metric tons of retail hydrogen are available for cars every day in California, which is less than 0.05% of the yearly hydrogen production in the U.S.. A hypothetical fleet of 100 aircraft, operating 3 flights a day, would increase the demand by 2.25 tons per day and require 140 MWh of renewable electricity for green hydrogen.

PEM↗
NASA NTRS1961

Flight Tests of a 1/6-Scale Model of the Hawker P 1127 Jet VTOL Airplane

An experimental investigation has been made to determine the dynamic stability and control characteristics of a 1/6-scale flying model of the Hawker P lIP7 jet vertical-take-off-and-landing (VTOL) airplane in hovering and transition flight. The model was powered by a counter-rotating ducted fan driven by compressed-air jets at the tips of the fan blades. In hovering flight the model was controlled by jet-reaction controls which consisted of yaw and pitch jets at the extremities of the fuselage and a roll jet on each wing tip. In forward flight the model was controlled by conventional ailerons and rudder and an all-movable horizontal tail. In hovering flight the model could be flown smoothly and easily, but the roll control was considered too weak for rapid maneuvering or hovering in gusty air. Transitions from hovering to normal forward flight and back to hovering could be made smoothly and consistently and with only moderate changes in longitudinal trim. The model had a static longitudinal instability or pitch-up tendency throughout the transition range, but the rate of divergence in the pitch-up was moderate and the model could be controlled easily provided the angle of attack was not allowed to become too high. In both the transition and normal forward flight conditions the lateral motions of the model were difficult to control at high angles of attack, apparently because of low directional stability at small angles of sideslip. The longitudinal stability of the model in normal forward flight was generally satisfactory, but there was a decided pitch-up tendency for the flap-down condition at high angles of attack. In the VTOL landing approach condition, with the jets directed straight down or slightly forward, the nose-down pitch trim required was greater than in the transitions from hovering to forward flight, but the longitudinal instability was about the same. Take-offs and landings in still air could be made smoothly although there was a slight unfavorable ground effect on lift and a nose-down change in pitch trim near the ground. Short take-offs and landings could be made smoothly and consistently although the model experienced a decided nose-up change in pitching moment as it climbed out of ground effect.

Smith, Charles C., Jr.↗