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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Model-Independent Determination of Nuclear Weak Form Factors and Implications for Standard Model Precision Tests

We analyze the recoil corrections in superallowed beta decays of T = 1, J P = 0 + nuclei by fixing the mean square charged weak radius model independently using the data of multiple charge radii across the nuclear isotriplet. By comparing to model estimations, we argue that the existing theory uncertainty in the statistical rate function f might have been substantially underestimated. Here, we discuss the implications of our proposed strategy for precision tests of the standard model, including a potential alleviation of the first-row CKM unitarity deficit, and motivate new experiments for charge radii measurements.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1978

Accelerated test modeling

Cycle life regression model, cycle life prediction model, and acceleration factors are discussed. A method was presented to: (1) select a mathematical model; (2) determine model coefficients using accelerated test data; (3) test model fit of the accelerated test data; and (4) predict normal packs.

Schwartz, D.↗
NASA NTRS2009

Application of TRMM PR and TMI Measurements to Assess Cloud Microphysical Schemes in the MM5 Model for a Winter Storm

Seen by the human eye, precipitation particles are commonly drops of rain, flakes of snow, or lumps of hail that reach the ground. Remote sensors and numerical models usually deal with information about large collections of rain, snow, and hail (or graupel --also called soft hail ) in a volume of air. Therefore, the size and number of the precipitation particles and how particles interact, evolve, and fall within the volume of air need to be represented using physical laws and mathematical tools, which are often implemented as cloud and precipitation microphysical parameterizations in numerical models. To account for the complexity of the precipitation physical processes, scientists have developed various types of such schemes in models. The accuracy of numerical weather forecasting may vary dramatically when different types of these schemes are employed. Therefore, systematic evaluations of cloud and precipitation schemes are of great importance for improvement of weather forecasts. This study is one such endeavor; it pursues quantitative assessment of all the available cloud and precipitation microphysical schemes in a weather model (MM5) through comparison with the observations obtained by National Aeronautics and Space Administration (NASA) s and Japan Aerospace Exploration Agency (JAXA) s Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and microwave imager (TMI). When satellite sensors (like PR or TMI) detect information from precipitation particles, they cannot directly observe the microphysical quantities (e.g., water species phase, density, size, and amount etc.). Instead, they tell how much radiation is absorbed by rain, reflected away from the sensor by snow or graupel, or reflected back to the satellite. On the other hand, the microphysical quantities in the model are usually well represented in microphysical schemes and can be converted to radiative properties that can be directly compared to the corresponding PR and TMI observations. This study employs this method to evaluate the accuracy of the simulated radiative properties by the MM5 model with different microphysical schemes. It is found that the representations of particle density, size, and mass in the different schemes in the MM5 model determine the model s performance when predicting a winter storm over the eastern Pacific Ocean. Schemes lacking moderate density particles (i.e. graupel), with snow flakes that are too large, or with excessive mass of snow or graupel lead to degraded prediction of the radiative properties as observed by the TRMM satellite. This study demonstrates the uniqueness of the combination of both an active microwave sensor (PR) and passive microwave sensor (TMI) onboard TRMM on assessing the accuracy of numerical weather forecasting. It improves our understanding of the physical and radiative properties of different types of precipitation particles and provides suggestions for better representation of cloud and precipitation processes in numerical models. It would, ultimately, contribute to answering questions like "Why did it not rain when the forecast says it would?"

Han, Mei↗
DOE OSTI2020

Deep Learning Prediction of Interspecies Interactions from Self-organized Spatiotemporal Patterns of Co-evolving Organisms

Microorganisms colonizing natural habits such as soils co-evolve to form specific spatial patterns through interspecies interactions. These self-organized patterns are a key ecological phenotype, which provides critical information on their interaction mechanisms. However, conventional network inference techniques that analyze species population data in bulk have yet to be extended to account for such spatial heterogeneity. Here we proposed supervised deep learning as a new network inference tool for predicting interspecies interactions from spatiotemporal patterns of microbial evolution. Due to lack of biological imaging data that can be used for training deep learning networks, we used in silico data generated from high-fidelity agent-based models to determine model structure and parameters. Even though networks were trained under simple configurations where interaction coefficients are assumed to be spatially invariant, we demonstrated that the resulting model can be utilized to successfully predict spatial variation of interactions in more complex domains (i.e., configured with a context-dependent mixture of interaction coefficients) as well as in simple domains without further training. In the further test against real biological data obtained through imaging experiments of a binary consortium (Pseudomonas fluorescens and a mutant of Escherichia coli), our model also predicted the dramatic shifts in interactions of the two organisms across different environmental contexts. Through various successful demonstrations in this work, the combined use of the agent-based model and machine learning algorithm provides a means to use new type of data - microscopic images - for extracting microbial interactions, therefore presenting itself as a useful tool for the analysis of more complex microbial community interactions.

Lee, Joon-Yong↗
DOE OSTI2025

Sequential Precipitation Input Tagging (SPIT) to Estimate Water Transit Times and Hydrologic Tracer Dynamics Within Water‐Tagging Enabled Hydrologic Models

Determining the age distribution of water exiting a catchment is important for understanding groundwater storage and mixing. New water-tagging capabilities within models track precipitation events as they move through simulated storages, yet forward modeling of individual events may not systematically capture the full transit time distribution (TTD). Here, we present a “sequential precipitation input tagging” (SPIT) framework to tag all input precipitation at regular intervals during extended model simulations. Monthly tags over 7 years were applied at six National Ecological Observatory Network sites to calculate TTDs and derive mean virtual tracer age, $\overline{T_{V}}$, fractions of young water, F yw , and hydrologic tracer concentrations (water isotopes δ 18 O and δ 2 H) within a tagging enabled version of the Weather Research and Forecast hydrologic model (WRF-Hydro). Throughout seven simulation years, the fraction of simulated discharge derived from tagged events, F tag , increased each year, with the final year's F tag ranging from 66% to 100% and highlights the need to apply SPIT over many years to understand TTDs. When the F tag was >75%, simulated $\overline{T_{V}}$ ranged 179–923 days and F yw 0.6%–23.9%, with daily values exhibiting a power-law relationship with precipitation, discharge, and groundwater. Through implementation of SPIT, we find this hydrologic model configuration performs poorly in estimation of $\overline{T_{V}}$ and F yw (root mean squared error of 469 days and 14.4% respectively), suggesting it misrepresents subsurface mixing. Thus, the SPIT framework provides a reproducible approach to calculate watershed transit times within tagging enabled models and thereby assess and improve representation of hydrologic processes.

fraction of young water↗
NASA NTRS1979

SCI model structure determination program (OSR) user's guide

The computer program, OSR (Optimal Subset Regression) which estimates models for rotorcraft body and rotor force and moment coefficients is described. The technique used is based on the subset regression algorithm. Given time histories of aerodynamic coefficients, aerodynamic variables, and control inputs, the program computes correlation between various time histories. The model structure determination is based on these correlations. Inputs and outputs of the program are given.

Source record↗
NASA NTRS1987

Experimental validation of a two-dimensional shear-flow model for determining acoustic impedance

Tests were conducted to validate a two-dimensional shear-flow analytical model for determining the acoustic impedance of a liner test specimen in a grazing-incidence, grazing-flow environment. The tests were limited to a test specimen chosen to exhibit minimal effects of grazing flow so that the results obtained by using the shear-flow analytical model would be expected to match those obtained from normal-incidence impedance measurements. Impedances for both downstream and upstream sound propagation were generally consistent with those from normal-incidence measurements. However, sensitivity of the grazing-incidence impedance to small measurement or systematic errors in propagation constant varied dramatically over the range of test frequencies.

Parrott, Tony L.↗
NASA NTRS2002

Characterization of Low-Frequency Combustion Stability of the Fastrac Engine

A series of tests were conducted to measure the combustion performance of the Fastrac engine thrust chamber. During mainstage, the thrust chamber exhibited no large-amplitude chamber pressure oscillations that could be identified as low-frequency combustion instability or 'chug'. However, during start-up and shutdown, the thrust chamber very briefly exhibited large-amplitude chamber pressure oscillations that were identified as chug. These instabilities during start-up and shutdown were regarded as benign due to their brevity. Linear models of the thrust chamber and the propellant feed systems were formulated for both the thrust chamber component tests and the flight engine tests. These linear models determined the frequency and decay rate of chamber pressure oscillations given the design and operating conditions of the thrust chamber and feed system. The frequency of chamber pressure oscillations determined from the model closely matched the frequency of low-amplitude, low-frequency chamber pressure oscillations exhibited in some of the later thrust chamber mainstage tests. The decay rate of the chamber pressure oscillations determined from the models indicated that these low-frequency oscillations were stable. Likewise, the decay rate, determined from the model of the flight engine tests indicated that the low-frequency chamber pressure oscillations would be stable.

Rocker, Marvin↗
NASA NTRS1991

Mathematical models for determining the protected spaces of the vertical lightning rod

Two mathematical models are presented for determining the protected spaces of the vertical lightning-rod. In the first model there was applied the circular approximation. Through the introduction of the modified striking distance in the second improved approximation there was obtained a new model for the protected space of the lightning-rod. The models are of general type, foreseen for the three-dimensional space and they are simply applied on solving the practical problems.

Mladenovic, I.↗
NASA NTRS1980

A new predictive model for determining solar wind-terrestrial planet interactions

A computational model has been developed for the determination of the gasdynamic and magnetic field properties of the solar wind flow around a magnetic planet, such as the earth, or a nonmagnetic planet, such as Venus. The procedures are based on an established single-fluid, steady, dissipationless, magnetogasdynamic model and are appropriate for the calculation of axisymmetric, supersonic, super-Alfvenic solar wind flow past a planetary magneto/ionosphere. Sample results are reported for a variety of solar wind and planetary conditions. Some of these are new applications; others are included to show that the new procedures produce the same results as previous procedures when applied to the same conditions. The new methods are completely automated and much more efficient and versatile than those employed heretofore.

Spreiter, J. R.↗
NASA NTRS1982

Regionally applicable angular reflectance models

Determination of the angular variation of the reflected radiance field in order to infer the reflected component of the Earth radiation budget from medium or narrow field of view radiometer measurements is discussed. An average angular model applicable at 250 to 1000 km is presented and evaluated. The nature of the convergence of the radiance patterns to the regional means is also discussed. Radiances measured during summer Monex 1979, from Hudson Bay to Saudi Arabia, were averaged and then normalized by multiplying by pi and dividing by the scene-averaged reflected flux density. This casts the model into the inverse of the bidirectional reflectance normalization coefficient, which has the value of unity for an isotropic surface. The reflected component of the Earth's radiation budget is inferred to an accuracy of about 2.5%.

Davis, J. M.↗
NASA NTRS1996

REE Partition Coefficients from Synthetic Diogenite-Like Enstatite and the Implications of Petrogenetic Modeling

Determining the petrogenesis of eucrites (basaltic achondrites) and diogenites (orthopyroxenites) and the possible links between the meteorite types was initiated 30 years ago by Mason. Since then, most investigators have worked on this question. A few contrasting theories have emerged, with the important distinction being whether or not there is a direct genetic link between eucrites and diogenites. One theory suggests that diogenites are cumulates resulting from the fractional crystallization of a parent magma with the eucrites crystallizing, from the residual magma after separation from the diogenite cumulates. Another model proposes that diogenites are cumulates formed from partial melts derived from a source region depleted by the prior generation of eucrite melts. It has also been proposed that the diogenites may not be directly linked to the eucrites and that they are cumulates derived from melts that are more orthopyroxene normative than the eucrites. This last theory has recently received more analytical and experimental support. One of the difficulties with petrogenetic modeling is that it requires appropriate partition coefficients for modeling because they are dependent on temperature, pressure, and composition. For this reason, we set out to determine minor- and trace-element partition coefficients for diogenite-like orthopyroxene. We have accomplished this task and now have enstatite/melt partition coefficients for Al, Cr, Ti, La, Ce, Nd, Sm, Eu, Dy, Er, Yb, and La.

Schwandt, C. S.↗
NASA NTRS2014

Investigating the Sensitivity of Surface-Level Nitrate Seasonality in Antarctica to Primary Sources Using a Global Model

Determining the sources of total nitrate (TNIT NO-3 + HNO3) reaching Antarctica is a long-standing challenge. Here we analyze the monthly sensitivity of surface-level TNIT in Antarctica to primary sources using a global 3-D chemical transport model, GEOS-Chem, and its adjoint. Modeled seasonal variation of TNIT concentrations shows good agreement with several measurement studies, given that the lack of post-depositional processing in the model leads to an expected underestimate of maximum values in November through January. Remote NOx sources have the greatest impact May-July, during when the model background concentrations are sensitive to NOx emissions from fossil fuel combustion, soil, and lightning originating from 25S to 65S. In this season, NOx is transported to Antarctica as TNIT, which is formed above continental source regions at an altitude of 5-11 km. In other seasons, more NOx is transported as a reservoir species (e.g., peroxyacetyl nitrate, PAN) through the free troposphere, transforming into TNIT within a cone of influence that extends to 35S and above 4 km altitude. Photolysis of PAN over Antarctica is the main driver of modeled NOx seasonality. Stratospheric production and loss of tracers are relatively unimportant in monthly sensitivities in GEOS-Chem, driving only a few percent of surface level variability of TNIT. A small peak concentration in August is captured by the model, although some measured values in August fall outside the range of simulated concentrations. Modifications to the model to represent sedimentation of polar stratospheric clouds (PSCs) lead to increased surface level August TNIT concentrations. However, this simple representation does not explicitly account for PSC particle deposition or disappearance of the tropopause in the middle of winter, and thus the influence of stratospheric nitrate sources estimated in this study is likely a lower bound.

stratosphere↗