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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
DOE OSTI2026

CFD Modeling of an 81" Single Slope Barrier Wall Drainage Window for on Grade and Sag Conditions

The main goal of this study is to design a drainage window in an 81" single slope barrier wall for on-grade and sag conditions that could replace the standard ODOT I-3 barrier catch basin. The ODOT design guidelines are as follows: a) Examine configurations of the opening to the flume behind the wall under the wall section to maximize conveyance of flow to a roadside ditch section. b) Examine window lengths and configurations to maximize hydraulic efficiency on a grade up to an absolute maximum window length of 20 ft. c) Use a minimum opening height of 4 in. and consider tapering to an increased height at the outlet to the flume to reduce the potential for debris clogging beneath the barrier section. On-grade locations are analyzed for longitudinal slope up to 5% and spread up to 10 ft. Sag locations, represented by pavement at zero longitudinal slope, are analyzed for water depths up to 18 in. The roadway cross section consists of a 10-ft shoulder at a 4.0% cross slope and pavement at a 1.6% cross slope. All surfaces are represented with Manning’s n = 0.015. Computational fluid dynamics (CFD) is used to perform the analysis. The modeling approach follows previous studies by the authors. The new design is similar to a slotted inlet: a rectangular opening cut into the bottom of a barrier (e.g., a temporary barrier or single slope barrier wall), which typically has a uniform cross section. Findings from laboratory tests of flow under Florida DOT barrier walls were used for additional validation of the modeling approach used in this study.

42 ENGINEERING↗
DOE OSTI2025

Factors That Influence Variability in Stress-Drop Measurements Using Spectral Decomposition and Spectral-Ratio Methods for the 2019 Ridgecrest Earthquake Sequence

Stress drop is a fundamental parameter related to earthquake source physics, but is hard to measure accurately. To better understand how different factors influence stress-drop measurements, we compare two different methods using the Ridgecrest stress-drop validation data set: spectral decomposition (SD) and spectral ratio (SR), each with different processing options. Here, we also examine the influence of spectral complexity on source parameter measurement. Applying the SD method, we find that frequency bandwidth and time-window length could influence spectral magnitude calibration, while depth-dependent attenuation is important to correctly map stress-drop variations. For the SR method, we find that the selected source model has limited influence on the measurements; however, the Boatwright model tends to produce smaller standard deviation and larger magnitude dependence than the Brune model. Variance reduction threshold, frequency bandwidth, and time-window length, if chosen within an appropriate parameter range, have limited influence on source parameter measurement. For both methods, wave type, attenuation correction, and spectral complexity strongly influence the result. The scale factor that quantifies the magnitude dependence of stress drop show large variations with different processing options, and earthquakes with complex source spectra deviating from the Brune-type source models tend to have larger scale factor than earthquakes without complexity. Based on these detailed comparisons, we make a few specific suggestions for data processing workflows that could help future studies of source parameters and interpretations.

58 GEOSCIENCES↗
NASA NTRS1994

A note on windowing for the waveform relaxation

The technique of windowing has been often used in the implementation of the waveform relaxations for solving ODE's or time dependent PDE's. Its efficiency depends upon problem stiffness and operator splitting. Using model problems, the estimates for window length and convergence rate are derived. The electiveness of windowing is then investigated for non-stiff and stiff cases respectively. lt concludes that for the former, windowing is highly recommended when a large discrepancy exists between the convergence rate on a time interval and the ones on its subintervals. For the latter, windowing does not provide any computational advantage if machine features are disregarded. The discussion is supported by experimental results.

Zhang, Hong↗
DOE OSTI2023

Analytical estimation of the signal to noise ratio efficiency in axion dark matter searches using a Savitzky-Golay filter

The signal to noise ratio efficiency ϵ SNR in axion dark matter searches has been estimated using large-statistic simulation data reflecting the background information and the expected axion signal power obtained from a real experiment. This usually requires a lot of computing time even with the assistance of powerful computing resources. Employing a Savitzky-Golay filter for background subtraction, in this work, we estimated a fully analytical ϵ SNR without relying on large-statistic simulation data, but only with an arbitrary axion mass and the relevant signal shape information. Hence, our work can provide ϵ SNR using minimal computing time and resources prior to the acquisition of experimental data, without the detailed information that has to be obtained from real experiments. Axion haloscope searches have been observing the coincidence that the frequency independent scale factor ξ is approximately consistent with the ϵ SNR . This was confirmed analytically in this work, when the window length of the Savitzky-Golay filter is reasonably wide enough, i.e., at least 5 times the signal window.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Identification of hot water end-use process of electric water heaters from energy measurements

This paper presents an algorithm for the identification of parameters for a stochastic hot water end-use process that drives a homogeneous population of thermostatically controlled electric water heaters (EWH). Usually, only metered interval consumption data (kWh) is collected and the hot water end-use process is unobservable to utility and aggregators. However, the availability of EWHs for demand response (DR) is closely coupled with the hot water end-use process. In this context, the hot water end-use process is modeled as a two-state Markov chain (Use / No use), which causes the thermostatic ON-OFF switching process to behave as a Markov renewal process (MRP). A set of first passage-time problems is developed to obtain the moments of the transition probability densities of the MRP. These problems are addressed by establishing a system of coupled partial differential equations characterizing the temperature evolution of the EWH population. A key quantity in the methodology for estimating the parameters is the total time an EWH is ON within a period of interest. It is referred to as the total busy time. Total busy time in this approach is a random variable for which analytical expressions of the moments are developed as a function of the metered window length. The latter expressions become the basis of a hot water demand model identification algorithm which is validated using agent-based simulations of EWHs.

42 ENGINEERING↗
DOE OSTI2025

Adaptive Algebraic Derivative Estimation for Battery Electric Buses Energy Consumption Forecasting

The limited service life of onboard batteries for EVs is a challenge, underscoring the need for real-time battery usage prediction. This paper proposes an adaptive Algebraic Derivative Estimation (ADE) approach for forecasting the energy consumption of battery electric buses. By dynamically adjusting the sliding window length, the adaptive ADE retains the fixed-length ADE’s key advantage—namely, operating online without reliance on extensive historical datasets—while substantially bolstering forecast accuracy by actively trading estimation bias off estimation variance. Comparative experiments against both the conventional ADE with a fixed length and a representative machine learning algorithm, XGBoost, were conducted, with performance evaluated via root mean square error, mean absolute error, and the coefficient of determination. The results demonstrate that the proposed approach significantly outperforms baseline methods.

Cui, Tianyang [The University of Texas at Dallas]↗
DOE OSTI2020

Lightning Interferometry Uncertainty, Beam Steering Interferometry, and Evidence of Lightning Being Ignited by a Cosmic Ray Shower

Abstract We present an uncertainty analysis on correlation‐based time delay estimate, the basis for broadband lightning interferometry. A normal interferometry would yield much higher uncertainties than the theoretically predicted lower bound due to finite correlation window lengths. However, if the signals are aligned in time, the uncertainties approach the lower bound and can be used to indicate the interferometric uncertainties. Based on this, we introduce a beam steering interferometry technique. It first estimates a direction centroid for the lightning sources with a normal interferometry and computes the time delays among the signals. It then shifts the raw data with the time delays to align the signals roughly in time and reprocess the aligned signals. It finally pushes the reprocessed results to their correct positions, based on the time delays estimated in the first step. We apply this technique on a fast positive breakdown (FPB) process that started a normal intracloud lightning. The FPB process is shown to have a much more complex structure and development than a normal interferometry would provide. More importantly, from both interferometric and polarization analyses, the FPB appears to be ignited by a cosmic ray shower (CRS). We estimate the radio frequency strength and frequency content related to a presumed CRS in a thunderstorm electric field and find that they are in agreement with the observations. We examine the electric field effect of the CRS front and find that it could raise the field above the threshold for positive breakdown and is capable of igniting the FPB (and the lightning).

Shao, Xuan‐Min↗
DOE OSTI2024

Robustness of topological persistence in knowledge distillation for wearable sensor data

Topological data analysis (TDA) has shown great success in various applications involving wearable sensor data. However, there are difficulties in leveraging topological features in machine learning and wearable sensors because of the large time consumption and computational resources required to extract the features. To address this problem, knowledge distillation (KD) is utilized to generate a small model and accommodate topological features with persistence image (PI) representations from the raw time series data. Deploying topological knowledge in KD enables the student to achieve better performance compared to the one trained solely on raw time series data. However, it is not yet known if there are coherent characteristics for topological features in PI, which can aid in improving the performance during KD. In this paper, we investigate the suitability and challenges of utilizing topological features in KD for wearable sensor data, thereby contributing to the advancement of the field. Our study explores the impact of transferred topological features by comparing the Teacher-to-Student framework with Multiple Teachers-to-Student where teachers utilize both time series data and persistence images obtained by TDA as inputs. Additionally, we conduct a rigorous examination of topological knowledge effects by testing under various corruptions, knowledge types, and learning strategies in the context of human activity recognition tasks. Our analysis of topological features in KD presents the optimal strategy for incorporating these features. This study includes datasets of varying scales, window lengths, and activity classes, providing a comprehensive evaluation. Our results demonstrate that leveraging topological features in KD to enhance performance across databases.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1983

Non-intrusive parameter identification procedure user's guide

Written in standard FORTRAN, NAS is capable of identifying linear as well as nonlinear relations between input and output parameters; the only restriction is that the input/output relation be linear with respect to the unknown coefficients of the estimation equations. The output of the identification algorithm can be specified to be in either the time domain (i.e., the estimation equation coefficients) or in the frequency domain (i.e., a frequency response of the estimation equation). The frame length ("window") over which the identification procedure is to take place can be specified to be any portion of the input time history, thereby allowing the freedom to start and stop the identification procedure within a time history. There also is an option which allows a sliding window, which gives a moving average over the time history. The NAS software also includes the ability to identify several assumed solutions simultaneously for the same or different input data.

Hanson, G. D.↗
NASA NTRS1983

Review of correlation techniques

Correlation analysis in MST radar to determine the scattered power, Doppler frequency and correlation time for a noisy signal is examined. It is assumed that coherent detection was employed, with two accurately balanced quadrature receiving channels and that coherent integration is performed with a window length significantly less than the correlation time of the signal.

Bowhill, S. A.↗
NASA NTRS2012

Evidence for Widespread Cooling in an Active Region Observed with the SDO Atmospheric Imaging Assembly

A well known behavior of EUV light curves of discrete coronal loops is that the peak intensities of cooler channels or spectral lines are reached at progressively later times. This time lag is understood to be the result of hot coronal loop plasma cooling through these lower respective temperatures. However, loops typically comprise only a minority of the total emission in active regions. Is this cooling pattern a common property of active region coronal plasma, or does it only occur in unique circumstances, locations, and times? The new SDO/AIA data provide a wonderful opportunity to answer this question systematically for an entire active region. We measure the time lag between pairs of SDO/AIA EUV channels using 24 hours of images of AR 11082 observed on 19 June 2010. We find that there is a time-lag signal consistent with cooling plasma, just as is usually found for loops, throughout the active region including the diffuse emission between loops for the entire 24 hour duration. The pattern persists consistently for all channel pairs and choice of window length within the 24 hour time period, giving us confidence that the plasma is cooling from temperatures of greater than 3 MK, and sometimes exceeding 7 MK, down to temperatures lower than approx. 0.8 MK. This suggests that the bulk of the emitting coronal plasma in this active region is not steady; rather, it is dynamic and constantly evolving. These measurements provide crucial constraints on any model which seeks to describe coronal heating.

Viall, Nicholeen M.↗
NASA NTRS2019

Space Launch System and Missions to Near Rectilinear Halo Orbits

The first major evolution of NASA’s Space Launch System (SLS) will begin its flights starting in the mid-2020’s. This new configuration, called Block 1B, replaces the Interim Cryogenic Propulsion Stage with a larger Exploration Upper Stage (EUS). The additional capability provided by the new upper stage will allow SLS to send heavier payloads into deep space. One destination of interest to the SLS program is called a Near Rectilinear Halo Orbit (NRHO). This is a type of lunar orbit with multiple advantages for deep space exploration. These benefits include Earth/lunar access, low station-keeping requirements, and high communication potential with Earth. Therefore, it is a leading candidate for the proposed Lunar Orbital Platform-Gateway (LOP-G). This paper will provide a detailed assessment of the SLS Block 1B requirements and capabilities for sending payloads to an NRHO. Analysts at Marshall Space Flight Center are producing a multi-year mission availability scan for the SLS Block 1B configuration to a predefined NRHO orbit. The analysis produces an optimized trajectory for each day of the scan window. A maximized payload and minimized propellant requirement are determined for each day. All maneuvers from launch to the end of the Trans-Lunar-Injection (TLI) are being modeled as finite burns. Injections into an NRHO are being modeled as impulsive maneuvers. The payload element is arbitrary, but includes sufficient mass to represent a large habitat or propulsion module. The resulting parameters of payload capability, delta-v requirements, and launch windows length vary over the course of the scan. Many launch days in the scan are eliminated in post-processing as they violate mission constraints such as payload mass and propellant usage to insert into an NRHO. Based off previous one-year scan results for the SLS Block 1B Design Analysis Cycle 2 (DAC-2), it is expected that there will be one to three days per week where the payload is able to insert into an NRHO within SLS constraints objectives. This scan provides results for longer than one-year, allowing analysts to better understand the launch availability and energy requirements of SLS Block 1B over time. The in-space mission design and scans utilize Copernicus, an n-body trajectory optimization tool originally developed out of the University of Texas at Austin with further development at Johnson Space Center in Houston, TX. To seed the in-space trajectory, Copernicus uses a plugin to call a database of SLS ascent trajectories optimized in the Program to Simulate Optimized Trajectories II (POST2). The ascent trajectories are developed using a framework that parametrizes payload mass and LEO inclination, and targets a 100 nmi (nautical mile) altitude circular parking orbit. Though this analysis is specific to the SLS program, it will provide a summary of mission design benefits and constraints associated with generic NRHO access, and may be applied to other programs or concepts that will utilize this orbit.

Statham, T. L.↗
NASA NTRSDate not supplied

Wind Tunnel to Full Scale Mapping of Winds and Loads for Launch-Vehicle Ground Wind Loads

A launch vehicle ground-wind-loads program was conducted at the NASA Langley Transonic Dynamics Tunnel. The objectives were to quantify key aerodynamic and structural characteristics that impact the occurrence of large wind-induced oscillations of a launch vehicle when exposed to ground winds prior to launch. Of particular interest is the dynamic response of a launch vehicle when a von Kármán vortex street forms in the wake of the vehicle resulting in quasiperiodic lift and drag forces.Vehicle response to these quasiperiodic forces can become quite large when the frequency of vortex shedding nears that of a lowly-damped structural mode thereby exciting a resonant response. The study of ground-wind-loads presents unique challenges to quantify significant characteristics of the approaching wind and to relate the wind-tunnel acquired static, dynamic, and gravitational loads to full-scale vehicles. This paper will explain the correlation process between model-scale and full-scale wind characteristics and resulting structural loads. Characterization of the wind at a launch site requires knowledge of the vehicle dynamics and the anemometer performance. Vehicle dynamics dictate the frequency range of interest in characterization of the atmospheric turbulence, and in defining the required data window-length to model dynamic oscillation build-up during wind-gust analysis. Knowledge of the anemometer performance is required to infer peak wind magnitudes since most anemometers cannot directly measure instantaneous peak values. Following proper wind-speed correlation, static and dynamic wind-tunnel loads must be converted to full-scale equivalent values to derive design and operational guidance. In addition to the direct computation of full-scale equivalent loads using relevant scaling parameters, the corrections applied to dynamic loads accounting for differences in structural damping will also be discussed. Furthermore, a phenomenon that manifests in many slender and flexible launch vehicles is a load magnification due to gravity resulting from mass offset under deflection. A method for scaling this contribution from model-scale to full-scale is presented. Finally, a comparison of wind-tunnel derived loads using the described methodologies to launch vehicle measured loads is presented.

ground wind loads↗
NASA NTRSDate not supplied

Wind-Tunnel to Full-Scale Mapping of Winds and Loads for Launch-Vehicle Ground Wind Loads

A launch vehicle ground-wind-loads program was conducted at the NASA Langley Transonic Dynamics Tunnel. The objectives were to quantify key aerodynamic and structural characteristics that impact the occurrence of large wind-induced oscillations of a launch vehicle when exposed to ground winds prior to launch. Of particular interest is the dynamic response of a launch vehicle when a von Kármán vortex street forms in the wake of the vehicle resulting in quasiperiodic lift and drag forces. Vehicle response to these quasiperiodic forces can become quite large when the frequency of vortex shedding nears that of a lowly-damped structural mode thereby exciting a resonant response. The study of ground-wind-loads presents unique challenges to quantify significant characteristics of the approaching wind and to relate the wind-tunnel acquired static, dynamic, and gravitational loads to full-scale vehicles. This paper will explain the correlation process between model-scale and full-scale wind characteristics and resulting structural loads. Characterization of the wind at a launch site requires knowledge of the vehicle dynamics and the anemometer performance. Vehicle dynamics dictate the frequency range of interest in characterization of the atmospheric turbulence, and in defining the required data window-length to model dynamic oscillation build-up during wind-gust analysis. Knowledge of the anemometer performance is required to infer peak wind magnitudes since most anemometers cannot directly measure instantaneous peak values. Following proper wind-speed correlation, static and dynamic wind-tunnel loads must be converted to full-scale equivalent values to derive design and operational guidance. In addition to the direct computation of full-scale equivalent loads using relevant scaling parameters, the corrections applied to dynamic loads accounting for differences in structural damping will also be discussed. Furthermore, a phenomenon that manifests in many slender and flexible launch vehicles is a load magnification due to gravity resulting from mass offset under deflection. A method for scaling this contribution from model-scale to full-scale is presented. Finally, a comparison of wind-tunnel derived loads using the described methodologies to launch vehicle measured loads is presented.

Ground wind loads↗
NASA NTRS2011

Strategic Implications of Human Exploration of Near-Earth Asteroids

The current United States Space Policy [1] as articulated by the White House and later confirmed by the Congress [2] calls for [t]he extension of the human presence from low-Earth orbit to other regions of space beyond low-Earth orbit will enable missions to the surface of the Moon and missions to deep space destinations such as near-Earth asteroids and Mars. Human exploration of the Moon and Mars has been the focus of numerous exhaustive studies and planning, but missions to Near-Earth Asteroids (NEAs) has, by comparison, garnered relatively little attention in terms of mission and systems planning. This paper examines the strategic implications of human exploration of NEAs and how they can fit into the overall exploration strategy. This paper specifically addresses how accessible NEAs are in terms of mission duration, technologies required, and overall architecture construct. Example mission architectures utilizing different propulsion technologies such as chemical, nuclear thermal, and solar electric propulsion were formulated to determine resulting figures of merit including number of NEAs accessible, time of flight, mission mass, number of departure windows, and length of the launch windows. These data, in conjunction with what we currently know about these potential exploration targets (or need to know in the future), provide key insights necessary for future mission and strategic planning.

Drake, Bret G.↗
DOE OSTI2021

Noise suppression for MHD characterization with electron cyclotron emission imaging 1D technique

Significant noise suppression for magnetohydrodynamics (MHD) mode characterization in the spatial and spectral domain is achieved by processing two-dimensional (2D) electron cyclotron emission imaging (ECEI) data with a one-dimensional (1D) ECEI technique using a short time window ($1\;{\text{ms}}$). The technique is applied to detect toroidal Alfven eigenmodes (TAEs) in the temporal spectrum and fit their radial envelope using the data from the DIII-D tokamak W-band 2D ECEI system. Using the data length (time window) of only 1 ${\text{ms}}$, the 1D ECEI can clearly detect the TAEs (~100 ${\text{kHz}}$) on the spectrum, while similar spectrum quality requires ~10 ${\text{ms}}$ data length with the cross power spectrum between two midplane ECEI channels. The 1D ECEI technique also effectively avoids biased fitting when resolving the fine structure of the TAE's radial envelope. The radially spatial resolution of 1D ECEI is constrained by the finite ECE radiation volume of the ECEI receiver. Here, with forward radiation modeling, we find the DIII-D ECEI system can sensitively measure the even parity MHD activities, for which the mode width is >15 mm, and tearing modes (odd parity MHD activities), for which the island full width is >30 mm.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Non-Stationary Power System Forced Oscillation Analysis using Synchrosqueezing Transform

Non-stationary forced oscillations (FOs) have been observed in power system operations. However, most detection methods assume that the frequency of FOs is stationary. In this paper, we present a methodology for the analysis of nonstationary FOs. Firstly, Fourier synchrosqueezing transform (FSST) is used to provide a concentrated time-frequency representation of the signals that allows identification and retrieval of non-stationary signal components. To continue, the Dissipating Energy Flow (DEF) method is applied to the extracted components to locate the source of forced oscillations. The methodology is tested using simulated as well as real PMU data. In conclusion, the results show that the proposed FSST-based signal decomposition provides a systematic framework for the application of DEF Method to non-stationary FOs.

42 ENGINEERING↗