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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Accuracy considerations in the computational analysis of jet noise

The application of computational fluid dynamics methods to the analysis of problems in aerodynamic noise has resulted in the extension and adaptation of conventional CFD to the discipline now referred to as computational aeroacoustics (CAA). In the analysis of jet noise accurate resolution of a wide range of spatial and temporal scales in the flow field is essential if the acoustic far field is to be predicted. The numerical simulation of unsteady jet flow has been successfully demonstrated and many flow features have been computed with reasonable accuracy. Grid refinement and increased solution time are discussed as means of improving accuracy of Navier-Stokes solutions of unsteady jet flow. In addition various properties of different numerical procedures which influence accuracy are examined with particular emphasis on dispersion and dissipation characteristics. These properties are investigated by using selected schemes to solve model problems for the propagation of a shock wave and a sinusoidal disturbance. The results are compared for the different schemes.

Scott, James N.↗
DOE OSTI2020

Reduced-Order Parameterized Short-Circuit Current Model of Inverter-Interfaced Distributed Generators

The short-circuit response of inverter-interfaced distributed generators (IIDGs) is not adequately represented in many conventional protection studies. This paper presents an in-depth analysis of IIDG behavior during grid faults and proposes a more accurate reduced-order parameterized short-circuit current (RPSC) model of inverters. Typical inverter components are thoroughly investigated to identify those that play dominant roles during faults. The paper shows that the current limiter is the dominant factor for the steady-state fault-current of inverter; while the inverter filter along with the severity of the voltage disturbance largely determine the initial transient spike of inverter fault current. The proposed model is low-order and can be used in large scale simulations. The parameters of the proposed RPSC model can be extracted from laboratory experiments without requiring proprietary manufacturer information. The proposed fault-current model is analogous to the well-known synchronous machine model that segregates the inverter fault current into subtransient, transient, and steady-state fault currents. Finally, experimental and simulation tests are presented to validate the model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Wideband Impedance Passivation of MMCs for Suppressing Harmonic Oscillations

Harmonic instability and associated oscillation events have become one of the main concerns in MMC-based HVdc systems. These oscillations can appear in the range from a few hundred hertz to several kilohertz, and the root cause is identified as delay-induced negative damping of MMC impedance appearing at the system resonance frequency. Here, this paper introduces a wideband impedance reshaping method through MMC control to eliminate such negative damping for both grid-following (GFL) and grid-forming (GFM) MMCs, which makes the MMC impedance completely passive from the second harmonic frequency upward, thus preventing all harmonic oscillations. First, simplified impedance models of MMCs are derived for the harmonic stability analysis and the impedance reshaping control design. Next, a passivity-based impedance reshaping method is presented, as well as practical considerations for its implementation. In addition, to maintain the MMC's disturbance ride-through capability, an adaptive activation scheme is developed, which enables the wideband impedance reshaping control only in the presence of harmonic oscillation events. The effectiveness of the proposed method is validated by frequency domain analysis and by electromagnetic transient (EMT) simulations of two typical MMC-based power systems.

17 WIND ENERGY↗
NASA NTRS2003

Living with a Star: New Opportunities in Sun-Climate Research

Living With a Star is a NASA initiative employing the combination of dedicated spacecraft with targeted research and modeling efforts to improve what we know of solar effects of all kinds on the Earth and its surrounding space environment, with particular emphasis on those that have significant practical impacts on life and society. The highest priority among these concerns is the subject of this report: the potential effects of solar variability on regional and global climate, including the extent to which solar variability has contributed to the well-documented warming of the Earth in the last 100 years. Understanding how the climate system reacts to external forcing from the Sun will also greatly improve our knowledge of how climate will respond to other climate drivers, including those of anthropogenic origin. A parallel element of the LWS program addresses solar effects on space weather : the impulsive emissions of charged particles, short-wave electromagnetic radiation and magnetic disturbances in the upper atmosphere and near-Earth environment that also affect life and society. These include a wide variety of solar impacts on aeronautics, astronautics, electric power transmission, and national defense. Specific examples are (1) the impacts of potentially- damaging high energy radiation and atomic particles of solar origin on satellites and satellite operations, spacecraft electronics systems and components, electronic communications, electric power distribution grids, navigational and GPS systems, and high altitude aircraft; and (2) the threat of sporadic, high-energy solar radiation to astronauts and high altitude aircraft passengers and crews. Elements of the LWS program include an array of dedicated spacecraft in near- Earth and near-Sun orbits that will closely study and observe both the Sun itself and the impacts of its variations on the Earth's radiation belts and magnetosphere, the upper atmosphere, and ionosphere. These spacecraft, positioned to study and monitor changing conditions in the Sun-Earth neighborhood, will also serve as sentinels of solar storms and impulsive events.

Source record↗
NASA NTRS2015

20-mN Variable Specific Impulse (Isp) Colloid Thruster

Busek Company, Inc., has designed and manufactured an electrospray emitter capable of generating 20 mN in a compact package (7x7x1.7 in). The thruster consists of nine porous-surface emitters operating in parallel from a common propellant supply. Each emitter is capable of supporting over 70,000 electrospray emission sites with the plume from each emitter being accelerated through a single aperture, eliminating the need for individual emission site alignment to an extraction grid. The total number of emission sites during operation is expected to approach 700,000. This Phase II project optimized and characterized the thruster fabricated during the Phase I effort. Additional porous emitters also were fabricated for full-scale testing. Propellant is supplied to the thruster via existing feed-system and microvalve technology previously developed by Busek, under the NASA Space Technology 7's Disturbance Reduction System (ST7-DRS) mission and via follow-on electric propulsion programs. This project investigated methods for extending thruster life beyond the previously demonstrated 450 hours. The life-extending capabilities will be demonstrated on a subscale version of the thruster.

Demmons, Nathaniel↗
DOE OSTI2021

Tropical Cyclone Frequency

Abstract The frequency with which tropical cyclones (TCs) occur controls all other aspects of tropical cyclone risk since a storm that does not occur can do no harm. Yet this frequency is poorly understood. There is no accepted theory that explains the average number of TCs that occur each year on the Earth, nor how that number will change with global warming. Arguments based on global budgets of heat or moisture do not yet appear helpful, nor does a detailed understanding of the physical processes of TC genesis. Empirical indices that predict TC frequency as a function of large‐scale environmental variables can explain some of its relative variations in space and time, but not its absolute value. Global numerical models with horizontal grid spacings on the order of 25–50 km have allowed much improved simulations of TC activity, however. Many such models project a decrease in frequency with warming, but some project an increase. Idealized simulations, including those at higher resolutions, offer promise by allowing a systematic, deductive investigation of the roles of individual environmental factors. In addition to the larger‐scale environmental modulation of genesis likelihood, precursor disturbances, or “seeds”, may exert an independent influence on TC frequency.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1987

Spring-to-summer transitions of global circulations during May-July 1979

Gridded datasets produced for May-July 1979 from the FGGE data by the Goddard Laboratory for Atmospheres were used to study the characteristics of a well-documented seasonal transition, as revealed by weekly averages, from spring to summer in the Northern Hemisphere and from fall to winter in the Southern Hemisphere. Analysis of the weekly departures from the seasonal averages (i.e., anomalies) reveals an eastward-propagating divergence disturbance with wave-number one. The passage of this pulse over Central America appears to trigger the displacement of negative outgoing long-wave radiation (OLR) anomalies northward from the South American winter location. The center of maximum divergence is found over Asia during the onset of the summer monsoon and is also found in conjunction with strengthening of the negative OLR anomalies over this region.

Nogues-Paegle, Julia↗
NASA NTRS2008

Pre-Stall Behavior of a Transonic Axial Compressor Stage via Time-Accurate Numerical Simulation

CFD calculations using high-performance parallel computing were conducted to simulate the pre-stall flow of a transonic compressor stage, NASA compressor Stage 35. The simulations were run with a full-annulus grid that models the 3D, viscous, unsteady blade row interaction without the need for an artificial inlet distortion to induce stall. The simulation demonstrates the development of the rotating stall from the growth of instabilities. Pressure-rise performance and pressure traces are compared with published experimental data before the study of flow evolution prior to the rotating stall. Spatial FFT analysis of the flow indicates a rotating long-length disturbance of one rotor circumference, which is followed by a spike-type breakdown. The analysis also links the long-length wave disturbance with the initiation of the spike inception. The spike instabilities occur when the trajectory of the tip clearance flow becomes perpendicular to the axial direction. When approaching stall, the passage shock changes from a single oblique shock to a dual-shock, which distorts the perpendicular trajectory of the tip clearance vortex but shows no evidence of flow separation that may contribute to stall.

Chen, Jen-Ping↗
DOE OSTI2025

A Reinforcement Learning Approach to Augment Conventional PID Control in Nuclear Power Plant Transient Operation

The ability of nuclear reactors to operate their power conversion cycles more flexibly will enhance their value to energy grids with variable pricing. Current nuclear control systems are typically classical controllers that are often based on proportional-integral-derivative (PID) control. This paper presents a method of augmenting the existing PID control for difficult transient operations in nuclear power plants using a reinforcement learning–derived feedforward signal applied in real time. The agents, which are trained on a test thermal load-following problem, are designed to improve steam generator outlet temperature control for a range of fast load-following scenarios covering ramp rates from 9%/min to 15%/min. Several reinforcement learning algorithms were initially investigated for the training of the feedforward agents with deep Q-learning (DQN) and proximal policy optimization (PPO) networks, which were found to be the most promising. The DQN controllers utilize discrete actions, giving them a better disturbance rejection at steady state but inconsistent response to initial temperature deviations. In contrast, PPO-trained agents, which take continuous actions except for a dead zone around zero, were shown to have the best combination of high disturbance rejection at steady state and good tracking of the desired temperature value. The ability of the PPO agent was also examined, with the average time of decision making found to be on the order of 1 ms. The fault properties of the controller under the loss of the reinforcement learning agent feedforward signal were also examined. The controller showed strong performance in situations of “no-signal” faults. but was less good at handling “stuck-at” faults, where the feedforward signal remains at a set value. In both cases, however, the PID was able to successfully maintain stability, eventually returning the system to a steady state. It is hoped that this work will allow for the proposed control architecture to be examined for more difficult control problems such that it may eventually be used to adapt existing nuclear plants for more aggressive load-following on grids of the future.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Data and scripts associated with a manuscript analyzing ELM-FATES parameter sensitivity under pre-fire and postfire scenarios using machine learning

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript “Fire Severity-Dependent Shifts in Vegetation Parameter Sensitivity: A Pre- and Post-Fire Analysis Using ELM-FATES and Explainable AI” submitted to Journal of Advances in Modeling Earth Systems (Zahura et al. 2026). The study examines vegetation physiological parameters controlling pre-fire and post-fire vegetation dynamics. To support this analysis, 73 vegetation parameters in Functionally Assembled Terrestrial Ecosystem Simulator (FATES) (Fisher et al., 2018) , which is coupled with E3SM (Energy Exascale Earth System Model) land model (ELM, ELM-FATES), were perturbed using a Sobol sequence to generate 1,024 ensemble members for two plant functional types: needleleaf evergreen extratropical trees (NEET) and C3 grass. Simulations were conducted for the pre-fire period (2016) and post-fire period (2018–2023). Burn severity was represented by modifying the Nesterov index in FATES to 75,000, 150,000, and 300,000 for low, moderate, and high severity, respectively. A no-fire scenario was also included. Simulations were performed for 16 grid cells in the American River Watershed across different burn severities and plant functional types. XGBoost (eXtreme Gradient Boosting) models were trained using the parameter ensembles and ELM-FATES-simulated outputs, including leaf area index (LAI), gross primary productivity (GPP), aboveground biomass, vegetation evaporation, transpiration, and soil evaporation. Models were trained separately for each year and burn severity, followed by SHAP (SHapley Additive exPlanations) analysis to identify changes in dominant parameters after fire disturbance. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. The data package contains the ELM-FATES simulation data. The scripts and data related to the analysis will be added later. The inputs and outputs from ELM-FATES are inside the “FATES” folder. “FATES_domain_surface” contains the domain and surface netcdfs that were used to run ELM-FATES in the study area. “FATES_parameters” contains the 1024 ensembles that were generated using Sobol sequence. “FATES_outputs” folder contains ELM-FATES simulated variables. All files are .csv and .nc (NetCDF).

Aboveground biomass↗
NASA NTRS1997

Global Analysis of Empirical Relationships Between Annual Climate and Seasonality of NDVI

This paper describes the use of satellite data to calibrate a new climate-vegetation greenness relationship for global change studies. We examined statistical relationships between annual climate indexes (temperature, precipitation, and surface radiation) and seasonal attributes If the AVHRR Normalized Difference Vegetation Index (NDVI) time series for the mid-1980's in order to refine our understanding of intra-annual patterns and global abiotic controls on natural vegetation dynamics. Multiple linear regression results using global 1o gridded data sets suggest that three climate indexes: degree days (growing/chilling), annual precipitation total, and an annual moisture index together can account to 70-80 percent of the geographic variation in the NDVI seasonal extremes (maximum and minimum values) for the calibration year 1984. Inclusion of the same annual climate index values from the previous year explains no substantial additional portion of the global scale variation in NDVI seasonal extremes. The monthly timing of NDVI extremes is closely associated with seasonal patterns in maximum and minimum temperature and rainfall, with lag times of 1 to 2 months. We separated well-drained areas from lo grid cells mapped as greater than 25 percent inundated coverage for estimation of both the magnitude and timing of seasonal NDVI maximum values. Predicted monthly NDVI, derived from our climate-based regression equations and Fourier smoothing algorithms, shows good agreement with observed NDVI for several different years at a series of ecosystem test locations from around the globe. Regions in which NDVI seasonal extremes are not accurately predicted are mainly high latitude zones, mixed and disturbed vegetation types, and other remote locations where climate station data are sparse.

Potter, C. S.↗
DOE OSTI2024

A Distributed Model Identification Algorithm for Multi-Agent Systems: Preprint

In this study, we investigate agent-based approach for system model identification with emphasis on power distribution system applications. Departing from conventional practices of relying on historical data for offline model identification, we adopt online update approach utilizing real-time data by employing the latest data points for gradient computation. This methodology offers advantages including a large reduction in the communication network's bandwidth requirements by minimizing the data exchanged at each iteration and enabling the model to adapt in real-time to disturbances. Furthermore, we extend our model identification process from linear frameworks to more complex non-linear convex models. This extension is validated through numerical studies demonstrating improved control performance for a synthetic IEEE test case.

data-driven control↗
NASA NTRS2008

Space Weather: What is it, and Why Should a Meteorologist Care?

"Space weather" is a term coined almost 15 years ago to describe environmental conditions ABOVE Earth's atmosphere that affect satellites and astronauts. As society has become more dependent on technology, we nave found that space weather conditions increasingly affect numerous commercial and infrastructure sectors: airline operations, the precision positioning industry, and the electric power grid, to name a few. Similar to meteorology where "weather" often refers to severe conditions, "space weather" includes geomagnetic storms, radiation storms, and radio blackouts. But almost all space weather conditions begin at the Sun--our middle-age, magnetically-variable star. At NASA, the science behind space weather takes place in the Heliophysics Division. The Space Weather Prediction Center in Boulder, Colorado, is manned jointly by NCAA and US Air Force personnel, and it provides space weather alerts and warnings for disturbances that can affect people and equipment working in space and on Earth. Organizationally, it resides in NOAA's National Weather Service as one of the National Centers for Environmental Prediction. In this seminar we hope to give the audience a brief introduction to the causes of space weather, discuss some of the effects, and describe the state of the art in forecasting. Our goal is to highlight that meteorologists are increasingly becoming the "first responders" to questions about space weather causes and effects.

SaintCyr, Chris↗
DOE OSTI2022

Exceedance Probabilities and Recurrence Intervals for Extended Power Outages in the United States

Power outages cause significant economic and societal impacts. An increasing likelihood of extreme weather coupled with aging grid infrastructure is leading to a higher prevalence of extended power outages, which can leave customers without power for multiple days or even weeks. Planners at the facility, local, state, and federal levels are interested in resilience solutions to reduce the impacts of extended power outages. Resilience solutions—such as installing backup systems, integrating microgrid solutions, weatherizing buildings, and hardening distribution and transmission components—can reduce the consequences of extended power outages, but these solutions come with increased capital costs. Conducting cost-benefit analyses is important for determining which steps to take to mitigate the impact of power outages without investing in ineffective and cost-prohibitive resilience solutions. The expected benefits of resilience investments depend on the frequency of power outages of various durations, particularly extended outages lasting several hours, days, or weeks. A significant barrier to resilience planning is the lack of publicly available data on the frequency and duration of extended power outages. The absence of outage duration information severely limits the ability to conduct quantitative cost-benefit analyses of resilience investments. This report provides estimates of recurrence intervals and conditional exceedance probabilities for major power outages by U.S. region between 2015 and 2021. Additionally, we provide estimates for grid management, particularly outages caused by California’s public safety power shutoffs (PSPS), and for natural outages caused by major hurricanes. Outage recurrence intervals are the average number of years between outage events, and conditional exceedance probabilities are the likelihoods that a customer who experiences a major power outage will experience an outage exceeding a given duration. Major outage events are those that affect 10,000 or more customers, as defined by the U.S. Department of Energy’s (DOE’s) Electric Emergency Incident and Disturbance Report, called OE-417 (DOE 2020). These results can be applied to determine the likelihood of experiencing long-duration outages, which can be integrated into cost-benefit analyses of resilience solutions and broader energy resilience studies. We developed a methodology to estimate customer outage durations for extended outage events using publicly available data on customer outages. Shorter-duration power outages are relatively common, with customers experiencing on average more than one power outage each year lasting fewer than 12 hours. An outage event lasting between 1 day and 1 week is expected to occur between once every 16 years and once every 42 years, depending on the region, with an average recurrence rate of once every 32 years across the contiguous United States.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Exceedance Probabilities and Recurrence Intervals for Extended Power Outages in the United States

This report provides estimates of recurrence intervals and conditional exceedance probabilities for major power outages by U.S. region between 2015 and 2021. Additionally, we provide estimates for grid management, particularly outages caused by California’s public safety power shutoffs (PSPS), and for natural outages caused by major hurricanes. Outage recurrence intervals are the average number of years between outage events, and conditional exceedance probabilities are the likelihoods that a customer who experiences a major power outage will experience an outage exceeding a given duration. Major outage events are those that affect 10,000 or more customers, as defined by the U.S. Department of Energy’s (DOE’s) Electric Emergency Incident and Disturbance Report, called OE-417 (DOE 2020). These results can be applied to determine the likelihood of experiencing long-duration outages, which can be integrated into cost-benefit analyses of resilience solutions and broader energy resilience studies.

Ericson, Sean↗
NASA NTRS1990

Delivery and application of precise timing for a traveling wave powerline fault locator system

The Bonneville Power Administration (BPA) has successfully operated an in-house developed powerline fault locator system since 1986. The BPA fault locator system consists of remotes installed at cardinal power transmission line system nodes and a central master which polls the remotes for traveling wave time-of-arrival data. A power line fault produces a fast rise-time traveling wave which emanates from the fault point and propagates throughout the power grid. The remotes time-tag the traveling wave leading edge as it passes through the power system cardinal substation nodes. A synchronizing pulse transmitted via the BPA analog microwave system on a wideband channel sychronizes the time-tagging counters in the remote units to a different accuracy of better than one microsecond. The remote units correct the raw time tags for synchronizing pulse propagation delay and return these corrected values to the fault locator master. The master then calculates the power system disturbance source using the collected time tags. The system design objective is a fault location accuracy of 300 meters. BPA's fault locator system operation, error producing phenomena, and method of distributing precise timing are described.

Street, Michael A.↗
NASA NTRS1995

Scalability of Parallel Spatial Direct Numerical Simulations on Intel Hypercube and IBM SP1 and SP2

The implementation and performance of a parallel spatial direct numerical simulation (PSDNS) approach on the Intel iPSC/860 hypercube and IBM SP1 and SP2 parallel computers is documented. Spatially evolving disturbances associated with the laminar-to-turbulent transition in boundary-layer flows are computed with the PSDNS code. The feasibility of using the PSDNS to perform transition studies on these computers is examined. The results indicate that PSDNS approach can effectively be parallelized on a distributed-memory parallel machine by remapping the distributed data structure during the course of the calculation. Scalability information is provided to estimate computational costs to match the actual costs relative to changes in the number of grid points. By increasing the number of processors, slower than linear speedups are achieved with optimized (machine-dependent library) routines. This slower than linear speedup results because the computational cost is dominated by FFT routine, which yields less than ideal speedups. By using appropriate compile options and optimized library routines on the SP1, the serial code achieves 52-56 M ops on a single node of the SP1 (45 percent of theoretical peak performance). The actual performance of the PSDNS code on the SP1 is evaluated with a "real world" simulation that consists of 1.7 million grid points. One time step of this simulation is calculated on eight nodes of the SP1 in the same time as required by a Cray Y/MP supercomputer. For the same simulation, 32-nodes of the SP1 and SP2 are required to reach the performance of a Cray C-90. A 32 node SP1 (SP2) configuration is 2.9 (4.6) times faster than a Cray Y/MP for this simulation, while the hypercube is roughly 2 times slower than the Y/MP for this application. KEY WORDS: Spatial direct numerical simulations; incompressible viscous flows; spectral methods; finite differences; parallel computing.

Joslin, Ronald D.↗