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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 OSTI2022

Qualitative trend analysis based on a mixed-integer representation

Shape constrained spline fitting is a useful method to impose prior knowledge onto flexible semi-parametric models during parameter estimation. Most typically, the function shape is imposed through order restrictions on the regression coefficients. The intended shape is considered known or selected based on heuristic rules. In this study, we present a method to estimate the optimal set of order restrictions to segment a univariate data series into episodes with distinct shapes. This is also known as the qualitative trend analysis (QTA) problem. The obtained solution uses a trade-off between lack-of-fit and model complexity. Further, our practical implementation takes inspiration from the generalized order restricted information criterion (GORIC) for inequality-constrained model selection. From this, one learns (a) that QTA can be formulated as a mixed-integer quadratic program (MIQP) and (b) that the newly proposed mixed order restricted information criterion (MORIC) enables optimal segmentation. This is illustrated through didactic case studies.

42 ENGINEERING↗
NASA NTRS1977

Global correlation of topographic heights and gravity anomalies

The short wavelength features were obtained by subtracting a calculated 24th-degree-and-order field from observed data written in 1 deg x 1 deg squares. The correlation between the two residual fields was examined by a program of linear regression. When run on a worldwide scale over oceans and continents separately, the program did not exhibit any correlation; this can be explained by the fact that the worldwide autocorrelation function for residual gravity anomalies falls off much faster as a function of distance than does that for residual topographic heights. The situation was different when the program was used in restricted areas, of the order of 5 deg x 5 deg square. For 30% of the world,fair-to-good correlations were observed, mostly over continents. The slopes of the regression lines are proportional to apparent densities, which offer a large spectrum of values that are being interpreted in terms of features in the upper mantle consistent with available heat-flow, gravity, and seismic data.

Roufosse, M. C.↗
DOE OSTI2022

Photometry on Structured Backgrounds: Local Pixel-wise Infilling by Regression

Photometric pipelines struggle to estimate both the flux and flux uncertainty for stars in the presence of structured backgrounds such as filaments or clouds. However, it is exactly stars in these complex regions that are critical to understanding star formation and the structure of the interstellar medium. We develop a method, similar to Gaussian process regression, which we term local pixel-wise infilling (LPI). Using a local covariance estimate, we predict the background behind each star and the uncertainty of that prediction in order to improve estimates of flux and flux uncertainty. We show the validity of our model on synthetic data and real dust fields. We further demonstrate that the method is stable even in the crowded field limit. While we focus on optical-IR photometry, this method is not restricted to those wavelengths. We apply this technique to the 34 billion detections in the second data release of the Dark Energy Camera Plane Survey. In addition to removing many >3σ outliers and improving uncertainty estimates by a factor of ~2–3 on nebulous fields, we also show that our method is well behaved on uncrowded fields. The entirely post-processing nature of our implementation of LPI photometry allows it to easily improve the flux and flux uncertainty estimates of past as well as future surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Impacts of COVID-19 related stay-at-home restrictions on residential electricity use and implications for future grid stability

“Stay-at-home” orders and other health precautions enacted during the COVID-19 pandemic have led to substantial changes in residential electricity usage. Here, we conduct a case study to analyze data from 390 apartments in New York City (NYC) to examine the impacts of two key drivers of residential electricity usage: COVID-19 case-loads and the outdoor temperature. We develop a series of regression models to predict two characteristics of residential electricity usage on weekdays: The average occupied apartment’s consumption (kWh) over a 9am-5pm window and the hourly peak demand (Watt) over a 12pm-5pm window. Via a Monte Carlo simulation, we forecast the two usage characteristics under a possible scenario in which stay-at-home orders in NYC, or a similar metropolitan region, coincide with warm summer weather. Under the scenario, the 9am-5pm residential electricity usage on weekdays is predicted to be 15% – 24% higher than under prior, pre-pandemic conditions. This could lead to substantially higher utility costs for residents. Additionally, we predict that the residential hourly peak demand between 12pm and 5pm on weekdays could be 35% – 53% higher than that under pre-pandemic conditions. We conclude that the projected increase in peak demand - which might arise if stay-at-home guidelines coincided with hot weather conditions - could pose grid management challenges, especially for residential feeders. We also note that, if there is a longer lasting shift towards work and study-from-home, utilities will have to rethink load profile considerations. The applications of our predictive models to managing future smart-grid technology are also highlighted.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Toward the Analytic Bootstrap of Energy Correlators

In this paper, we present a framework for the analytic bootstrap of three-point energy correlators, a crucial observable in N = 4 N=4 super Yang-Mills theory and quantum chromodynamics (QCD). Our approach combines spherical contour techniques, general physical constraints such as pole cancellations, and power correction data in the singular limits to determine its analytic expression. In contrast to previous bootstrap studies restricted to scattering amplitudes for supersymmetric theories, our framework makes use of the properties of Feynman integrals, marking a significant step toward bootstrapping realistic QCD observables. Using this method, we derive analytic expressions for leading-order three-point energy correlators with equal and unequal energy weights, where the latter are crucial ingredients for projected N N-point energy correlators. We also apply the recently developed technique of analytic regression with lattice reduction as a way to bypass needing explicit expressions for the singular limits. Bridging theoretical advances in scattering amplitudes with the renewed interest in weighted cross-sections, our work opens the door to precision tests of QCD dynamics through analytic event-shape predictions.

Gong, Jianyu [State Key Laboratory]↗
DOE OSTI2026

Toward the analytic bootstrap of energy correlators

In this paper, we present a framework for the analytic bootstrap of three-point energy correlators, a crucial observable in $\mathcal{N}$ = 4 super Yang-Mills theory and quantum chromodynamics (QCD). Our approach combines spherical contour techniques, general physical constraints such as pole cancellations, and power correction data in the singular limits to determine its analytic expression. In contrast to previous bootstrap studies restricted to scattering amplitudes for supersymmetric theories, our framework makes use of the properties of Feynman integrals, marking a significant step toward bootstrapping realistic QCD observables. Using this method, we derive analytic expressions for leading-order three-point energy correlators in the multi-collinear limit with equal and unequal energy weights, where the latter are crucial ingredients for projected N -point energy correlators. We also apply the recently developed technique of analytic regression with lattice reduction as a way to bypass needing explicit expressions for the singular limits. Bridging theoretical advances in scattering amplitudes with the renewed interest in weighted cross-sections, our work opens the door to precision tests of QCD dynamics through analytic event-shape predictions.

jet substructure↗
NASA NTRS2018

Evaluation of the Danish Aerospace Corporation Portable Pulmonary Function System

A research project designed to investigate changes in maximal oxygen consumption (VO2max) during and following long duration flight on the International Space Station (ISS) has recently been completed. The device used to measure VO2 on board ISS, the Portable Pulmonary Function System (PPFS) manufactured by the Danish Aerospace Corporation (DAC), is based on previous-generation devices manufactured by DAC, but the PPFS has not been validated for analyzing metabolic gases or measuring cardiac output (Qc). The purpose of the present evaluation is to compare PPFS metabolic gas analysis measurements to measurements obtained using a clinically-validated system (ParvoMedics TrueOne(c) 2400 system; Parvo). In addition, Qc data collected with the PPFS were compared to Qc measurements from echocardiography. METHODS: Ten subjects completed three cycle exercise tests to maximal exertion. The first test was conducted to determine each subject's VO2max and set the work rates for the second and third (comparison) tests. The protocol for the two comparison tests consisted of three 5-minute stages designed to elicit 25%, 50%, and 75% VO2max (based upon results from the initial test), followed by 1-minute stages of increasing work rate (25 watt/minute) until the subject reached maximal effort. During one of the two comparison tests, metabolic gases and Qc were assessed with the PPFS; metabolic gases and Qc were assessed with the Parvo and by echocardiography, respectively, during the other test. The order of the comparison tests was counterbalanced. VO2max and maximal work rate during the comparison tests were compared using t tests. Mixed-effects regression modeling was used to analyze submaximal data. RESULTS: All of the data were within normal physiological ranges. The PPFS-measured values for VO2max were 6% lower than values obtained with the Parvo (PPFS: 3.11 +/- 0.75 L/min; Parvo: 3.32 +/- 0.87 L/min; mean +/- standard deviation; P = 0.02); this difference is probably due to flow restriction imposed by the PPFS Qc accessories. Submaximal VO2 values were slightly lower when measured with the PPFS, although differences were not physiologically relevant. The PPFS-measured values of submaximal carbon dioxide production (VCO2) were lower than the data obtained from Parvo, which could be attributed to lower fractions of expired carbon dioxide measured by the PPFS. The PPFS Qc values tended to be lower than echocardiography-derived values. CONCLUSIONS: The results of the present study indicate a need to further examine the PPFS and to better quantify its reproducibility; however, none of the findings of the current evaluation indicate that the PPFS needs to be replaced or modified.

Portable Pulmonary Function System (PPFS)↗
DOE OSTI2022

Cost function for low-dimensional manifold topology assessment

Abstract In reduced-order modeling, complex systems that exhibit high state-space dimensionality are described and evolved using a small number of parameters. These parameters can be obtained in a data-driven way, where a high-dimensional dataset is projected onto a lower-dimensional basis. A complex system is then restricted to states on a low-dimensional manifold where it can be efficiently modeled. While this approach brings computational benefits, obtaining a good quality of the manifold topology becomes a crucial aspect when models, such as nonlinear regression, are built on top of the manifold. Here, we present a quantitative metric for characterizing manifold topologies. Our metric pays attention to non-uniqueness and spatial gradients in physical quantities of interest, and can be applied to manifolds of arbitrary dimensionality. Using the metric as a cost function in optimization algorithms, we show that optimized low-dimensional projections can be found. We delineate a few applications of the cost function to datasets representing argon plasma, reacting flows and atmospheric pollutant dispersion. We demonstrate how the cost function can assess various dimensionality reduction and manifold learning techniques as well as data preprocessing strategies in their capacity to yield quality low-dimensional projections. We show that improved manifold topologies can facilitate building nonlinear regression models.

42 ENGINEERING↗
NASA NTRS2008

On the Response of Halogen Occultation Experiment (HALOE) Stratospheric Oxone and Temperature to the 11-yr Solar Cycle Forcing

Results are presented on responses in 14-yr time series of stratospheric ozone and temperature from the Halogen Occultation Experiment (HALOE) of the Upper Atmosphere Research Satellite (UARS) to a solar cycle (SC-like) variation. The ozone time series are for ten, 20-degree wide, latitude bins from 45S to 45N and for thirteen "half-Umkehr" layers of about 2.5 km thickness and extending from 63 hPa to 0.7 hPa. The temperature time series analyses were restricted to pressure levels in the range of 2 hPa to 0.7 hPa. Multiple linear regression (MLR) techniques were applied to each of the 130 time series of zonally-averaged, sunrise plus sunset ozone points over that latitude/pressure domain. A simple, 11-yr periodic term and a linear trend term were added to the final MLR models after their seasonal and interannual terms had been determined. Where the amplitudes of the 11-yr terms were significant, they were in-phase with those of the more standard proxies for the solar uv-flux. The max minus min response for ozone is of order 2 to 3% from about 2 to 5 hPa and for the latitudes of 45S to 45N. There is also a significant max minus min response of order 1 K for temperature between 15S and 15N and from 2 to 0.7 hPa. The associated linear trends for ozone are near zero in the upper stratosphere. Negative ozone trends of 4 to 6%/decade were found at 10 to 20 hPa across the low to middle latitudes of both hemispheres. It is concluded that the analyzed responses from the HALOE data are of good quality and can be used to evaluate the responses of climate/chemistry models to a solar cycle forcing.

Remsberg, E. E.↗
NASA NTRS1995

Integrated design and manufacturing for the high speed civil transport (a combined aerodynamics/propulsion optimization study)

This report documents the efforts of a Georgia Tech High Speed Civil Transport (HSCT) aerospace student design team in completing a design methodology demonstration under NASA's Advanced Design Program (ADP). Aerodynamic and propulsion analyses are integrated into the synthesis code FLOPS in order to improve its prediction accuracy. Executing the integrated product and process development (IPPD) methodology proposed at the Aerospace Systems Design Laboratory (ASDL), an improved sizing process is described followed by a combined aero-propulsion optimization, where the objective function, average yield per revenue passenger mile ($/RPM), is constrained by flight stability, noise, approach speed, and field length restrictions. Primary goals include successful demonstration of the application of the response surface methodolgy (RSM) to parameter design, introduction to higher fidelity disciplinary analysis than normally feasible at the conceptual and early preliminary level, and investigations of relationships between aerodynamic and propulsion design parameters and their effect on the objective function, $/RPM. A unique approach to aircraft synthesis is developed in which statistical methods, specifically design of experiments and the RSM, are used to more efficiently search the design space for optimum configurations. In particular, two uses of these techniques are demonstrated. First, response model equations are formed which represent complex analysis in the form of a regression polynomial. Next, a second regression equation is constructed, not for modeling purposes, but instead for the purpose of optimization at the system level. Such an optimization problem with the given tools normally would be difficult due to the need for hard connections between the various complex codes involved. The statistical methodology presents an alternative and is demonstrated via an example of aerodynamic modeling and planform optimization for a HSCT.

Baecher, Juergen↗