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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 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Tests characterizing bioprocessor hardware for analytical modeling

The tests outlined in this paper were used to characterize the hardware components of the Salad Machine, a small NASA-developed bioprocessor. The data from these tests are presented, and the methods by which this data can be integrated into system mathematical models are briefly discussed. The subsystems and physical processes discussed include the lighting system, the air loop (condensing heat exchanger and the blower), heat transfer to the surroundings, and leakage. Through this effort it was learned that in the development of a test protocol, care should be taken to order the tests such that environmental parameters, particularly humidity, require as few large adjustments as possible. Sensor calibration and installation take a substantial amount of time, which should be built into the test schedule. Two properties were particularly hard to quantify: the air flow rate and the energy from the lighting system entering into the growth volume. Flow rate can be measured using the appropriate device for the system configuration and airflow. Lighting system radiation level was measured using three methods. The results of these methods varied substantially, putting off conclusive quantification of this value.

Gustavino, S.↗
NASA NTRS1994

Probabilistic Material Strength Degradation Model for Inconel 718 Components Subjected to High Temperature, Mechanical Fatigue, Creep and Thermal Fatigue Effects

This thesis presents the on-going development of methodology for a probabilistic material strength degradation model. The probabilistic model, in the form of a postulated randomized multifactor equation, provides for quantification of uncertainty in the lifetime material strength of aerospace propulsion system components subjected to a number of diverse random effects. This model is embodied in the computer program entitled PROMISS, which can include up to eighteen different effects. Presently, the model includes four effects that typically reduce lifetime strength: high temperature, mechanical fatigue, creep, and thermal fatigue. Statistical analysis was conducted on experimental Inconel 718 data obtained from the open literature. This analysis provided regression parameters for use as the model's empirical material constants, thus calibrating the model specifically for Inconel 718. Model calibration was carried out for four variables, namely, high temperature, mechanical fatigue, creep, and thermal fatigue. Methodology to estimate standard deviations of these material constants for input into the probabilistic material strength model was developed. Using the current version of PROMISS, entitled PROMISS93, a sensitivity study for the combined effects of mechanical fatigue, creep, and thermal fatigue was performed. Results, in the form of cumulative distribution functions, illustrated the sensitivity of lifetime strength to any current value of an effect. In addition, verification studies comparing a combination of mechanical fatigue and high temperature effects by model to the combination by experiment were conducted. Thus, for Inconel 718, the basic model assumption of independence between effects was evaluated. Results from this limited verification study strongly supported this assumption.

Bast, Callie Corinne Scheidt↗
NASA NTRS1995

Probabilistic material strength degradation model for Inconel 718 components subjected to high temperature, high-cycle and low-cycle mechanical fatigue, creep and thermal fatigue effects

This report presents the results of both the fifth and sixth year effort of a research program conducted for NASA-LeRC by The University of Texas at San Antonio (UTSA). The research included on-going development of methodology for a probabilistic material strength degradation model. The probabilistic model, in the form of a postulated randomized multifactor equation, provides for quantification of uncertainty in the lifetime material strength of aerospace propulsion system components subjected to a number of diverse random effects. This model is embodied in the computer program entitled PROMISS, which can include up to eighteen different effects. Presently, the model includes five effects that typically reduce lifetime strength: high temperature, high-cycle mechanical fatigue, low-cycle mechanical fatigue, creep and thermal fatigue. Statistical analysis was conducted on experimental Inconel 718 data obtained from the open literature. This analysis provided regression parameters for use as the model's empirical material constants, thus calibrating the model specifically for Inconel 718. Model calibration was carried out for five variables, namely, high temperature, high-cycle and low-cycle mechanical fatigue, creep and thermal fatigue. Methodology to estimate standard deviations of these material constants for input into the probabilistic material strength model was developed. Using an updated version of PROMISS, entitled PROMISS93, a sensitivity study for the combined effects of high-cycle mechanical fatigue, creep and thermal fatigue was performed. Then using the current version of PROMISS, entitled PROMISS94, a second sensitivity study including the effect of low-cycle mechanical fatigue, as well as, the three previous effects was performed. Results, in the form of cumulative distribution functions, illustrated the sensitivity of lifetime strength to any current value of an effect. In addition, verification studies comparing a combination of high-cycle mechanical fatigue and high temperature effects by model to the combination by experiment were conducted. Thus, for Inconel 718, the basic model assumption of independence between effects was evaluated. Results from this limited verification study strongly supported this assumption.

Bast, Callie C.↗
NASA NTRS2007

RadSTAR L-Band Imaging Scatterometer: Performance Assessment

RadSTAR is an instrument development program aimed at combining a radiometer and a scatterometer system into a highly compact configuration that uses a single, electronically scanned antenna to provide co-located and simultaneous measurements of emission and backscatter for airborne and spaceborne applications [I]. The program was designed to map soil moisture and ocean salinity, both important components of the water cycle, and to map sea ice density and thickness, an important factor in ocean-atmosphere heat exchange in Polar Regions. The accuracy in estimation of these and a number of other Earth science parameters can be greatly enhanced by providing the co-aligned radar/radiometer microwave measurements. For instance, radiometer estimates of soil moisture from soil emission are affected by emission from vegetation, and from the roughness of the surface. Complementary measurements using the scatterometer can be used to evaluate the vegetation and surface roughness effects. Hence, the combined observations can provide an improved estimate. As with soil moisture, the ocean salinity is a function of the microwave emission from the sea surface temperature (SST) and sea roughness. There, the addition of radar backscatter measurements of sea roughness enables the correction of the emissivity and provide more accurate estimates of ocean salinity. Similar arguments can be made for other important Earth science parameters. This paper discusses the RadSTAR program, the radar system design, calibration, and digital beamforming techniques, and presents preliminary analysis of the data collected during the test flights. The data sets obtained during the flights and during the radar calibration in the anechoic chamber are also employed to asses the performance of the radar. The paper also discusses the Digital Beamforming Synthetic Aperture Radar (DBSAR) processor, a real-time processor recently developed for the LIS instrument which enables beam synthesis, fine resolutions, and large swaths.

Rincon, Rafael↗
NASA NTRS2009

Photometric Studies of Orbital Debris at GEO

We report on optical observations of debris at geosynchronous Earth orbit (GEO) using two telescopes simultaneously at the Cerro Tololo Inter-American Observatory (CTIO) in Chile. The University of Michigan s 0.6/0.9-m Schmidt telescope MODEST (for Michigan Orbital DEbris Survey Telescope) was used in survey mode to find objects that potentially could be at GEO. Because GEO objects only appear in this telescope s field of view for an average of 5 minutes, a full six-parameter orbit can not be determined. Interrupting the survey for follow-up observations leads to incompleteness in the survey results. Instead, as objects are detected with MODEST, initial predictions assuming a circular orbit are done for where the object will be for the next hour, and the objects are reacquired as quickly as possible on the CTIO 0.9-m telescope. This second telescope follows-up during the first night and, if possible, over several more nights to obtain the maximum time arc possible, and the best six parameter orbit. Our goal is to obtain an initial orbit and calibrated colors for all detected objects fainter than R = 15th in order to estimate the orbital distribution of objects selected on the basis of two observational criteria: magnitude and angular rate. One objective is to estimate what fraction of objects selected on the basis of angular rate are not at GEO. A second objective is to obtain magnitudes and colors in standard astronomical filters (BVRI) for comparison with reflectance spectra of likely spacecraft materials.

Seitzer, Patrick↗
NASA NTRS2008

Methods of Helium Injection and Removal for Heat Transfer Augmentation

While augmentation of heat transfer from a test article by helium gas at low pressures is well known, the method is rarely employed during space simulation testing because the test objectives are to simulate an orbital thermal environment. Test objectives of cryogenic optical testing at Marshall Space Flight Center's X-ray Calibration Facility (XRCF) have typically not been constrained by orbital environment parameters. As a result, several methods of helium injection have been utilized at the XRCF since 1999 to decrease thermal transition times. A brief synopsis of these injection (and removal) methods including will be presented.

Kegley, Jeffrey↗
NASA NTRS2010

Systems Analyze Water Quality in Real Time

A water analyzer developed under Small Business Innovation Research (SBIR) contracts with Kennedy Space Center now monitors treatment processes at water and wastewater facilities around the world. Originally designed to provide real-time detection of nutrient levels in hydroponic solutions for growing plants in space, the ChemScan analyzer, produced by ASA Analytics Inc., of Waukesha, Wisconsin, utilizes spectrometry and chemometric algorithms to automatically analyze multiple parameters in the water treatment process with little need for maintenance, calibration, or operator intervention. The company has experienced a compound annual growth rate of 40 percent over its 15-year history as a direct result of the technology's success.

Source record↗
NASA NTRS1995

Results of an Automated GPS Tracking System in Support of Topex/Poseidon and GPSMet

A fully automated near real-time GPS tracking system has been developed around JPL's GIPSY/OASIS II software. The system produces <25 cm (3D rms) GPS orbits and one-half nanosecond (15 cm) clock estimates. The process starts automatically when a favorable global distribution of ground data from the IGS network (International GPS Service for Geodynamics) becomes available. Ionospherically corrected phase and pseudorange data are optimally combined to remove satellite and ground receiver clock errors, including selective availability. After the GPS orbits are determined within the data arc, they are then propagated with empirically determined dynamic force models. Real-time <2 meter (3D rms) GPS orbits are always available. As a by-product of this process, other calibration estimates such as station clocks, troposphere estimates, and Earth orientation parameters are also produced. For daily arc fits, the process requires 7-8 hours of CPU time on an HP9000/735 workstation.

GPS↗
NASA NTRSDate not supplied

Uncertainty Quantification and Sensitivity Analysis in Process-Structure-Property Simulations for Laser Powder Bed Fusion Additive Manufacturing

Process variations and process-induced defects like porosity cause significant uncertainty in the microstructure and mechanical behavior of additively manufactured metals. Establishing process-structure-property (PSP) relationships and quantifying uncertainty using experiments alone is costly, especially for structural applications where mechanical allowables must be established for qualification and certification. This work presents a PSP simulation framework for laser powder bed fusion with a focus on uncertainty quantification through probabilistic calibration and multi-fidelity uncertainty propagation. Motivated by phenomenological input parameters related to grain nucleation and growth that are difficult to characterize, a global sensitivity analysis (GSA) is completed. Through GSA, the most important input parameters are identified based on their influence on the statistical distributions of microstructural metrics that influence mechanical behavior, including grain size, morphology, and crystallographic texture. The results provide insight on what experiments are necessary to quantify and control PSP uncertainties, particularly those associated with the more challenging input parameters.

additive manufacturing↗
DOE OSTI2026

Probing the matter-dominated expansion with multi-redshift Lyman-$α$ BAO from DESI DR2

We present a multi-redshift Baryon Acoustic Oscillations (BAO) analysis of the DESI Data Release 2 (DR2) Lyman-$α$ (Ly$α$) forest, splitting the forest auto-correlation and its cross-correlation with quasars into three redshift bins. We obtain BAO measurements at effective redshifts $z_{\rm eff} = 2.13$, $2.40$, and $2.81$ with $\sim2.0$--$2.5\%$ precision per bin in the radial and transverse directions, corresponding to $\sim1.1$--$1.2\%$ precision for the isotropic BAO measurement. Using the same data products and modeling framework as the DESI DR2 Ly$α$ BAO analysis, we validate the pipeline on $400$ synthetic datasets and find unbiased BAO recovery with well-calibrated uncertainties. The measurements show an increase in the isotropic dilation parameter $D_V/r_d$ from $30.26\pm0.39$ to $32.22\pm0.47$ and in the Alcock-Paczyński parameter $D_M/D_H$ from $3.96\pm0.15$ to $5.63^{+0.22}_{-0.24}$. The Hubble distance $D_H/r_d$ decreases from $9.40\pm0.20$ to $7.22\pm0.17$, providing a direct measurement of the expansion history consistent with $Λ$CDM and the expected matter-dominated scaling, with $H(z)\propto(1+z)^n$ giving $n=1.34\pm0.16$. The redshift split also provides a self-consistent measurement of clustering evolution: the Ly$α$ forest bias evolves as $(1+z)^γ$ with $γ_α=3.05\pm0.16$, the RSD parameter has a redshift evolution described by $γ_β=-0.97\pm0.26$, and the quasar bias evolves with $γ_Q=1.56\pm0.23$, consistent with independent quasar clustering measurements. Combining these three-bin BAO measurements with DESI DR2 galaxy and quasar BAO measurements yields cosmological constraints consistent with the single-bin Ly$α$ BAO analysis in flat $Λ$CDM and $w_0w_a$CDM and improves curvature constraints by $\sim12\%$ in $Λ$CDM$+Ω_\mathrm{K}$.

Herrera-Alcantar, Hiram K. [Paris, Inst. Astrophys↗
DOE OSTI2021

Bayesian analysis for estimating statistical parameter distributions of elasto-viscoplastic material models

High temperature design methods rely on constitutive models for inelastic deformation and failure typically calibrated against the mean of experimental data without considering the associated scatter. Variability may arise from the experimental data acquisition process, from heat-to-heat material property variations, or both and need to be accurately captured to predict parameter bounds leading to efficient component design. Applying the Bayesian Markov Chain Monte Carlo (MCMC) method to produce statistical models capturing the underlying uncertainty in the experimental data is an area of ongoing research interest. This work varies aspects of the Bayesian MCMC method and explores their effect on the posterior parameter distributions for a uniaxial elasto-viscoplastic damage model using synthetically generated reference data. From our analysis with the uniaxial inelastic model we determine that an informed prior distribution including different types of test conditions results in more accurate posterior parameter distributions. The parameter posterior distributions, however, do not improve when increasing the number of similar experimental data. Additionally, changing the amount of scatter in the data affects the quality of the posterior distributions, especially for the less sensitive model parameters. Moreover, we perform a sensitivity study of the model parameters against the likelihood function prior to the Bayesian analysis. The results of the sensitivity analysis help to determine the reliability of the posterior distributions and reduce the dimensionality of the problem by fixing the insensitive parameters. The comprehensive study described in this work demonstrates how to efficiently apply the Bayesian MCMC methodology to capture parameter uncertainties in high temperature inelastic material models. Quantifying these uncertainties in inelastic models will improve high temperature engineering design practices and lead to safer, more effective component designs.

42 ENGINEERING↗
DOE OSTI2024

A macro-micro approach for identifying crystal plasticity parameters for necking and failure in nickel-based alloy haynes 282

Here, this work develops a two-scales macro-micro approach to address the challenge in calibrating crystal plasticity microstructural models when samples undergo necking prior to fracture. The crystal plasticity models are crucial for predicting the materials’ plastic deformation and failure at the microstructure level, identifying the materials’ intrinsic properties as well as investigating the microstructure-properties relationships. However, after necking occurs, the experimentally measured stress-strain curves fail to reflect the materials ‘true’ stress-strain behavior and cannot be directly fitted into crystal plasticity models. The proposed macro-micro approach employs a top-down strategy to address this challenge, which has been studied with experimental tests on precipitation-strengthened Ni-based superalloy Haynes® 282®. In this approach, a macro rate-dependent anisotropic plasticity model with Voce-type hardening and Rice-Tracey damage law is first utilized to model the deformation and failure of the tensile bar, and calibrated by matching the stress-strain curves, necking strain, and reduction of area. Especially, to match the testing results under different applied strain rates, the rate-sensitivity parameter m and saturation stress in the elasticity model are modified to incorporate dependence on the local strain rate. Then, the ‘true’ stress-strain behaviors are extracted from the necking zone of the macro-model, which are used to calibrate a micro-model with explicit microstructures and governed by an extended crystal plasticity law. The consistency between the micro-model and macro-model are enforced during calibration. The calibration outcomes from the crystal plasticity model elucidate the materials intrinsic properties for slip, hardening, and failure, which is vital for further investigations into the microstructure-properties relationship and for accurate prediction of the material behavior under various test and service conditions.

36 MATERIALS SCIENCE↗
NASA NTRS1975

Side looking radar calibration study

Calibration of an airborne sidelooking radar is accomplished by the use of a model that relates the radar parameters to the physical mapping situation. Topics discussed include: characteristics of the transmitters; the antennas; target absorption and reradiation; the receiver and map making or radar data processing; and the calibration process.

Edwards, W. D.↗
DOE OSTI2021

Self-calibrating the look-elsewhere effect: fast evaluation of the statistical significance using peak heights

In experiments where one searches a large parameter space for an anomaly, one often finds many spurious noise-induced peaks in the likelihood. This is known as the look-elsewhere effect, and must be corrected for when performing statistical analysis. Here, this paper introduces a method to calibrate the false alarm probability (FAP), or p-value, for a given dataset by considering the heights of the highest peaks in the likelihood. Specifically, we derive an equation relating the global p-value to the rank and height of local maxima. In the simplest form of self-calibration, the look-elsewhere-corrected $\chi^2$ of a physical peak is approximated by the $\chi^2$ of the peak minus the $\chi^2$ of the highest noise-induced peak, with accuracy improved by considering lower peaks. In contrast to alternative methods, this approach has negligible computational cost as peaks in the likelihood are a byproduct of every peak-search analysis. We apply to examples from astronomy, including planet detection, periodograms, and cosmology.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

A framework for feasibility-level validation of high-resolution wave hindcast models

The value of long-term wave hindcasts for investigating wave climates, wave energy resources, and extreme wave conditions has motivated research developing, calibrating and validating wave hindcast models. Past hindcast model validation studies examined the accuracy in modeling bulk wave parameters of overall sea states without considering the dependency of the model's skill within different sea states. In the present study, a framework for wave hindcast model validation is developed by examining the model accuracy for the most frequently occurring sea states, sea states contributing the most energy to total wave power, sea states associated with hurricane events, and those with the largest model error. Here, validations using bulk wave parameters and frequency-directional spectra at these key sea states and extreme wave conditions based on univariate and bivariate-contour methods provide insights to improve model accuracy, identifying the model's strong and weak points, and pathways for improvement, e.g., modeling wave-current interactions and adjusting wind data. This study adds to a growing body of research demonstrating that a carefully calibrated and verified spectral wave hindcast model can be used to estimate key wave energy parameters over a wide range of wave energy climates, as well as their spatial, temporal, frequency, directional, and probabilistic distributions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2014

On-Orbit Performance of MODIS Solar Diffuser Stability Monitor

Moderate Resolution Imaging Spectroradiometer (MODIS) is currently operated on both the Terra and Aqua spacecraft. It collects data in 20 reflective solar bands (RSB) and 16 thermal emissive bands. MODIS RSB calibration is reflectance based via an on-board solar diffuser (SD). On-orbit changes in the SD bidirectional reflectance factor are tracked by an onboard solar diffuser stability monitor (SDSM). The SDSM functions as an independent ratioing radiometer with nine filtered detectors, covering wavelengths in the visible (VIS) and near-infrared (NIR) spectral regions. A brief overview of SDSM design functions, on-orbit operations, and performance for both Terra and Aqua MODIS is provided. In addition to the SD on-orbit degradation at different wavelengths, the changes in SDSM detector responses and their potential impact on tracking SD on-orbit degradation are examined. After more than 12 years of on-orbit operation, Aqua MODIS SD has shown degradation varying from 0.6% at 0.94 microns to 19.0% at 0.41 microns. Due to more frequent solar exposure and longer operation time, the Terra MODIS SD has experienced a much larger degradation, varying from 2.3% at 0.94 microns to 48.0% at 0.41 microns. For both Terra and Aqua MODIS, the SD has experienced more degradation at shorter wavelengths. Meanwhile, the SDSM detector responses have also experienced wavelength-dependent degradation. The largest change in the SDSM detector responses, however, occurred at longer NIR wavelengths. Since launch, the SDSM systems on both Terra and Aqua MODIS have continued their nominal operations, enabling critical parameters to be derived in support of the RSB on-orbit calibration. The calibration strategies developed for and lessons learned from MODIS SDSM operations, and a preliminary performance comparison with the S-NPP VIIRS SDSM are discussed.

MODIS↗
NASA NTRS1997

Tests of a Semi-Analytical Case 1 and Gelbstoff Case 2 SeaWiFS Algorithm with a Global Data Set

A semi-analytical algorithm was tested with a total of 733 points of either unpackaged or packaged-pigment data, with corresponding algorithm parameters for each data type. The 'unpackaged' type consisted of data sets that were generally consistent with the Case 1 CZCS algorithm and other well calibrated data sets. The 'packaged' type consisted of data sets apparently containing somewhat more packaged pigments, requiring modification of the absorption parameters of the model consistent with the CalCOFI study area. This resulted in two equally divided data sets. A more thorough scrutiny of these and other data sets using a semianalytical model requires improved knowledge of the phytoplankton and gelbstoff of the specific environment studied. Since the semi-analytical algorithm is dependent upon 4 spectral channels including the 412 nm channel, while most other algorithms are not, a means of testing data sets for consistency was sought. A numerical filter was developed to classify data sets into the above classes. The filter uses reflectance ratios, which can be determined from space. The sensitivity of such numerical filters to measurement resulting from atmospheric correction and sensor noise errors requires further study. The semi-analytical algorithm performed superbly on each of the data sets after classification, resulting in RMS1 errors of 0.107 and 0.121, respectively, for the unpackaged and packaged data-set classes, with little bias and slopes near 1.0. In combination, the RMS1 performance was 0.114. While these numbers appear rather sterling, one must bear in mind what mis-classification does to the results. Using an average or compromise parameterization on the modified global data set yielded an RMS1 error of 0.171, while using the unpackaged parameterization on the global evaluation data set yielded an RMS1 error of 0.284. So, without classification, the algorithm performs better globally using the average parameters than it does using the unpackaged parameters. Finally, the effects of even more extreme pigment packaging must be examined in order to improve algorithm performance at high latitudes. Note, however, that the North Sea and Mississippi River plume studies contributed data to the packaged and unpackaged classess, respectively, with little effect on algorithm performance. This suggests that gelbstoff-rich Case 2 waters do not seriously degrade performance of the semi-analytical algorithm.

Carder, Kendall L.↗
DOE OSTI2020

Bayesian calibration of a hybrid nuclear collision model using $\textit{p}$₋Pb and Pb-Pb data at energies available at the CERN Large Hadron Collider

Here, we posit a unified hydrodynamic and microscopic description of the quark-gluon plasma (QGP) produced in ultrarelativistic p₋Pb and Pb-Pb collisions at $\sqrt{s}_\text{NN}$ = 5.02 TeV and evaluate our assertion using Bayesian inference. Specifically, we model the dynamics of both collision systems using initial conditions with parametric nucleon substructure, a preequilibrium free streaming stage, event-by-event viscous hydrodynamics, and a microscopic hadronic afterburner. Free parameters of the model, which describe the initial state and QGP medium are then simultaneously calibrated to fit charged-particle yields, mean $p_T$, and flow cumulants. We argue that the global agreement of the calibrated model with the experimental data strongly supports the existence of hydrodynamic flow in small collision systems at ultrarelativistic energies, and that the flow produced develops at length scales smaller than a single proton. Posterior estimates for the model's input parameters are obtained, and new insights into the temperature dependence of the QGP transport coefficients and event-by-event structure of the proton are discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗