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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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The Upper Atmosphere Research Satellite Microwave Limb Sounder has obserced small- and meso-scale temperature fluctuations with its 63 GHz saturated radiances in 30-80 km altitudes.
The absence of an economy of scale in spaceflight hardware makes additive manufacturing an immensely attractive option for propulsion components. As additive manufacturing techniques are increasingly adopted by government and industry to produce propulsion hardware in human‐rated systems, significant development efforts are needed to establish these methods as reliable alternatives to conventional subtractive manufacturing. One of the critical challenges facing powder bed fusion techniques in this application is variability between machines used to perform builds. Even with implementation of robust process controls, it is possible for two machines operating at identical parameters with equivalent base materials to produce specimens with slightly different material properties. The machine variability study presented here evaluates 60 specimens of identical geometry built using the same parameters. 30 samples were produced on machine 1 (M1) and the other 30 samples were built on machine 2 (M2). Each of the 30‐sample sets were further subdivided into three subsets (with 10 specimens in each subset) to assess the effect of progressive heat treatment on machine variability. The three categories for post‐processing were: stress relief, stress relief followed by hot isostatic press (HIP), and stress relief followed by HIP followed by heat treatment per AMS 5664. Each specimen (a round, smooth tensile) was mechanically tested per ASTM E8. Two formal statistical techniques, hypothesis testing for equivalency of means and one‐way analysis of variance (ANOVA), were applied to characterize the impact of machine variability and heat treatment on six material properties: tensile stress, yield stress, modulus of elasticity, fracture elongation, and reduction of area. This work represents the type of development effort that is critical as NASA, academia, and the industrial base work collaboratively to establish a path to certification for additively manufactured parts. For future flight programs, NASA and its commercial partners will procure parts from vendors who will use a diverse range of machines to produce parts and, as such, it is essential that the AM community develop a sound understanding of the degree to which machine variability impacts material properties.
Tunable laser based illumination sources have been adopted by a number of recent hyperspectral instruments for pre-launch spectral radiometric calibration. Some of these sources use mode-locked cavity configurations, which produce a pulse train and create an undesirable fluctuation in the radiometric source at the mode locking frequency. Although typically this frequency is several orders of magnitude higher than the instrument response, care must be taken to ensure the resultant calibration is not biased due to detector or electronic saturation effects. The temporal averaging properties of an integrating sphere can be used to reduce high frequency fluctuations to an acceptable level. In this work, the time resolved output of an integrating sphere coupled with a mode-locked source was measured. A 76 cm diameter sphere with 30 cm output aperture was illuminated using a mode-locked pulse train at 76 MHz, with single pulse durations of 12 ps. The time constant of the sphere was found to be 36 ns, and the resultant temporal averaging of pulses produced a maximum time varying irradiance at the output of 20% of the mean. The form of this time variance is a sawtooth pattern, with a sharp rise during the introduction of each pulse into the sphere followed by a slower decay between pulses. A comparison of instrument calibration data generated with this integrating sphere using both a mode locked source and a continuous wave source is also given. .
The purpose of this study is to seek observational evidence for diurnal, vertically propagating inertia-gravity waves (IGWs) in the mesosphere and lower thermosphere (MLT). Numerical modeling studies indicate that vertically propagating IGWs excited by tropical heating provide a significant source of momentum for the semiannual oscillation (SAO) in the equatorial zonal mean winds. The power spectrum of these waves has a strong diurnal component. We analyze global patterns of ascending and descending node differences in MLT satellite temperatures, which are assumed in this study to be proxies for waves of diurnal period. Juxtaposed upon the planetary-scale features are localized variations with longitudinal wavelengths ranging from 25 deg to 50 deg, and with vertical wavelengths between 13 and 25 km. These intermediate-scale variations are spatially coherent, and persist for several weeks. Their amplitudes generally increase with altitude, while their phase structures suggest both eastward and westward propagation. The variance of wave numbers 9-17 in the MLT is examined in relation to the underlying stratospheric zonal mean zonal gradient winds. Stronger variances generally coincide with periods where the underlying zonal mean winds are relatively light, or unidirectional. The weak inverse association between variance strength and zonal wind magnitude is suggestive of a wave filtering mechanism.
We describe and analyze a variance reduction approach for Monte Carlo (MC) sampling that accelerates the estimation of statistics of computationally expensive simulation models using an ensemble of models with lower cost. These lower cost models — which are typically lower fidelity with unknown statistics — are used to reduce the variance in statistical estimators relative to a MC estimator with equivalent cost. We derive the conditions under which our proposed approximate control variate framework recovers existing multifidelity variance reduction schemes as special cases. We demonstrate that existing recursive/nested strategies are suboptimal because they use the additional low-fidelity models only to efficiently estimate the unknown mean of the first low-fidelity model. As a result, they cannot achieve variance reduction beyond that of a control variate estimator that uses a single low-fidelity model with known mean. However, there often exists about an order-of-magnitude gap between the maximum achievable variance reduction using all low-fidelity models and that achieved by a single low-fidelity model with known mean. We show that our proposed approach can exploit this gap to achieve greater variance reduction by using non-recursive sampling schemes. The proposed strategy reduces the total cost of accurately estimating statistics, especially in cases where only low-fidelity simulation models are accessible for additional evaluations. Several analytic examples and an example with a hyperbolic PDE describing elastic wave propagation in heterogeneous media are used to illustrate the main features of the methodology.
In recent years, the Engine Combustion Network (ECN) has developed as a worldwide reference for understanding and describing engine combustion processes, successfully bringing together experimental and numerical efforts. Since experiments and numerical simulations both target the same boundary conditions, an accurate characterization of the stratified environment that is inevitably present in experimental facilities is required. The difference between the core-, and pressure-derived bulk-temperature of pre-burn combustion vessels has been addressed in various previous publications. Additionally, thermocouple measurements have provided initial data on the boundary layer close to the injector nozzle, showing a transition to reduced ambient temperatures. The conditions at the start of fuel injection influence physicochemical properties of a fuel spray, including near nozzle mixing, heat release computations, and combustion parameters. To address the temperature stratification in more detail, thermocouple measurements at larger distances from the spray axis have been conducted. Both the temperature field prior to the pre-combustion event that preconditions the high-temperature, high-pressure ambient, as well as the stratification at the moment of fuel injection were studied. To reveal the cold boundary layer near the injector with a better spatial resolution, Rayleigh scattering experiments and thermocouple measurements at various distances close to the nozzle have been carried out. The impact of the boundary layers and temperature stratification are illustrated and quantified using numerical simulations at Spray A conditions. Next to a reference simulation with a uniform temperature field, six different stratified temperature distributions have been generated. These distributions were based on the mean experimental temperature superimposed by a randomized variance, again derived from the experiments. The results showed that an asymmetric flame structure arises in the computed results when the temperature stratification input is used. In these predictions, first-stage ignition is advanced by 24 $\mu$s , while second-stage ignition is delayed by 11 $\mu$s. At the same time a lift-off length difference between the top and the bottom of up to 1.1 mm is observed. Furthermore, the lift-off length is less stable over time. Given the shown dependency, the temperature data is made available along with the vessel geometry data as a recommended basis for future numerical simulations.
Natural Gas (NG) Internal Combustion Engines (ICE) are a promising alternative to diesel engines for on-road heavy-duty applications to reduce greenhouse gas and harmful pollutant emissions. NG engines have not been widely adopted due to the lower thermal efficiency compared with diesel engine counterparts. To develop the base knowledge required to reach the desired efficiency, a Single Cylinder Engine (SCE) is the most effective platform to acquire reliable and repeatable data. A SCE test cell was developed using a Cummins 15-liter six-cylinder heavy-duty engine block modified to fire one cylinder (2.5-liter displacement). A Woodward Large Engine Control Module (LECM) is integrated to permit implementation of real-time advanced combustion control. Intake and exhaust characteristics, fuel composition, and exhaust gas recirculated substitution rate (EGR) are fully adjustable. A high-speed data acquisition system acquires in-cylinder, intake, and exhaust pressure for combustion analysis. The baseline testing shows reliable and consistent results for engine thermal efficiency, indicated mean effective pressure (IMEP), and coefficient of variance of the IMEP over a wide range of operating conditions while achieving effective control of all engine control and operation variables. This test cell will be used to conduct a research program to develop new and innovative control algorithms and CFD optimized combustion chamber designs, allowing ultra-high efficiency and low emissions for NG ICE heavy-duty on-road applications.
This paper examines the robustness of a Bayes estimator with respect to the assigned prior distribution. A Bayesian analysis for a stochastic scale parameter of a Weibull failure model is summarized in which the natural conjugate is assigned as the prior distribution of the random parameter. The sensitivity analysis is carried out by the Monte Carlo method in which, although an inverted gamma is the assigned prior, realizations are generated using distribution functions of varying shape. For several distributional forms and even for some fixed values of the parameter, simulated mean squared errors of Bayes and minimum variance unbiased estimators are determined and compared. Results indicate that the Bayes estimator remains squared-error superior and appears to be largely robust to the form of the assigned prior distribution.
Transient phenomena and target acquisition modes associated with interrupted observations during ground-to-air AA tracking were investigated. Using a two-axes control stick, the subjects tracked a computer-generated airplane image on a CRT display. The airplane image excuted a low-level straight pass. At certain pseudo-random times during each 25-second run, the screen was blanked for a period of one second. When the target image reappeared, the subjects reacquired it and continued tracking, attempting to minimize vector RMS error for the entire run (including the blanked period). The results reveal an increase both in tracking error and in error variance during the blanked period, only when the target disappears while in the crossover region. Blanking at other times effected increased variance but had no effect on the mean error. A blanking period just before crossover produced an increase lag while a blanking just after crossover resulted in a lead and thus made the error curve more symmetric.
It is demonstrated that (tangential) discontinuities in the magnetic field direction can support MHD surface waves. The surface waves are similar to the usual Alfven wave, but there are seven important differences. The first is that the surface waves exhibit a low-frequency cutoff; the second is that the velocity and magnetic field fluctuations are elliptically, and sometimes circularly, polarized. It is noted that they may account for the solar wind helicity spectrum. The third difference is that the surface waves are compressive, although there are special cases where they are noncompressive. The fourth is that the wave vector k, the local normals to the surfaces of constant phase, and the magnetic minimum variance direction do not all coincide. The fifth is that there is a tendency for the minimum variance direction to align itself with the mean magnetic field direction. The sixth difference is that the waves can be intrinsically nonplanar, and the seventh is that equipartition between magnetic and kinetic energies is not obeyed locally. These properties of the surface waves are interpreted to mean that surface waves may be common in the solar wind.
The Samarkand extensive air showers (EAS) array was used to measure the mean and individual lateral distribution functions (LDF) of EAS Cerenkov light. The analysis of the individual parameters b showed that the mean depth of EAS maximum and the variance of the depth distribution of maxima of EAS with energies of approx. 2x10 to the 15th power eV can properly be described in terms of Kaidalov-Martirosyan quark-gluon string model (QGSM).
In the source-free mantle/frozen-flux core magnetic earth model, the non-linear inverse steady motional induction problem was solved using the method presented in Part 1B. How that method was applied to estimate steady, broad-scale fluid velocity fields near the top of Earth's core that induce the secular change indicated by the Definitive Geomagnetic Reference Field (DGRF) models from 1945 to 1980 are described. Special attention is given to the derivation of weight matrices for the DGRF models because the weights determine the apparent significance of the residual secular change. The derived weight matrices also enable estimation of the secular change signal-to-noise ratio characterizing the DGRF models. Two types of weights were derived in 1987-88: radial field weights for fitting the evolution of the broad-scale portion of the radial geomagnetic field component at Earth's surface implied by the DGRF's, and general weights for fitting the evolution of the broad-scale portion of the scalar potential specified by these models. The difference is non-trivial because not all the geomagnetic data represented by the DGRF's constrain the radial field component. For radial field weights (or general weights), a quantitatively acceptable explication of broad-scale secular change relative to the 1980 Magsat epoch must account for 99.94271 percent (or 99.98784 percent) of the total weighted variance accumulated therein. Tolerable normalized root-mean-square weighted residuals of 2.394 percent (or 1.103 percent) are less than the 7 percent errors expected in the source-free mantle/frozen-flux core approximation.
Temperature and ozone data from the Microwave Limb Sounder (MLS) instrument on Upper Atmosphere Research Satellite (UARS) are used to analyze the variability of Kelvin wave activity during the first two years of the UARS mission. The analysis is carried out using the asynoptic mapping technique. Time frequency plots for zonal wavenumbers 1 and 2, at two heights representing the middle stratosphere and the stratopause, respectively, are used to analyze the temporal variability of the waves, and its possible relationship to the equatorial quasi-biennial oscillation (QBO) and semiannual oscillation (SAO). Kelvin wave activity reaches a maximum during the solstice seasons and almost disappears during the equinoxes, in agreement with previous studies. Eastward propagating variance is estimated for wave periods from 4 to 20 days, at all UARS pressure surfaces currently available for MLS. The semiannual modulation of variance is observed to extend down to the lower limits of the height ranges of the temperature and ozone retrievals. Furthermore, a superposed QBO modulation is detected up to the stratopause. Comparison between the variance in eastward propagating waves and the mean zonal wind shows a possible participation of kelvin waves in the forcing of the QBO. At the stratopause the role of Kelvin waves in forcing the SAO appears to be limited, in agreement with previous results. Between the 21-hPa and 4.6-hPa surfaces there appears to be a transition zone where there is no clear relationship between Kelvin wave activity and mean zonal flow acceleration.
This paper presents a review and comparison of the engineering and physiological optics literature on defocus detection. The equivalence of spatial frequency based detectors and the edge-based hypothesis, and variance-based detectors and the contrast- difference hypothesis is argued. Finally, variance-invariant transforms are introduced as a means of experimentally differentiating the hypotheses.
The absence of an economy of scale in spaceflight hardware makes additive manufacturing an immensely attractive option for propulsion components. As additive manufacturing techniques are increasingly adopted by government and industry to produce propulsion hardware in human-rated systems, significant development efforts are needed to establish these methods as reliable alternatives to conventional subtractive manufacturing. One of the critical challenges facing powder bed fusion techniques in this application is variability between machines used to perform builds. Even with implementation of robust process controls, it is possible for two machines operating at identical parameters with equivalent base materials to produce specimens with slightly different material properties. The machine variability study presented here evaluates 60 specimens of identical geometry built using the same parameters. 30 samples were produced on machine 1 (M1) and the other 30 samples were built on machine 2 (M2). Each of the 30-sample sets were further subdivided into three subsets (with 10 specimens in each subset) to assess the effect of progressive heat treatment on machine variability. The three categories for post-processing were: stress relief, stress relief followed by hot isostatic press (HIP), and stress relief followed by HIP followed by heat treatment per AMS 5664. Each specimen (a round, smooth tensile) was mechanically tested per ASTM E8. Two formal statistical techniques, hypothesis testing for equivalency of means and one-way analysis of variance (ANOVA), were applied to characterize the impact of machine variability and heat treatment on six material properties: tensile stress, yield stress, modulus of elasticity, fracture elongation, and reduction of area. This work represents the type of development effort that is critical as NASA, academia, and the industrial base work collaboratively to establish a path to certification for additively manufactured parts. For future flight programs, NASA and its commercial partners will procure parts from vendors who will use a diverse range of machines to produce parts and, as such, it is essential that the AM community develop a sound understanding of the degree to which machine variability impacts material properties.
Understanding the relationship between remotely sensed snow disappearance and seasonal water supply may become vital in coming years to supplement limited ground based, in situ measurements of snow in a changing climate. For the period 2001–2019, we investigated the relationship between satellite derived Day of Snow Disappearance (DSD)—the date at which snow has completely disappeared—and the seasonal water supply, i.e., the April—July total streamflow volume, for 15 snow dominated basins across the western U.S. A Monte Carlo framework was applied, using linear regression models to evaluate the predictive skill—defined here as a model’s ability to accurately predict seasonal flow volumes—of varied predictors, including DSD and in situ snow water equivalent (SWE), across a range of spring forecast dates. In all basins there is a statistically significant relationship between mean DSD and seasonal water supply (p ≤ 0.05), with mean DSD explaining roughly half of the variance. Satellite-based model skill improves later in the forecast season, surpassing the skill of in-situ-based (SWE) models in skill in 10 of the 15 basins by the latest forecast date. We found little to no correlation between model error and basin characteristics such as elevation and the ratio of snow water equivalent to total precipitation. Despite a relatively short data record, this exploratory analysis shows promise for improving seasonal water supply prediction, in particular for snow dominated basins lacking in situ observations.
Differential predation was observed in a population of 59 translocated juvenile Desert Tortoises (Gopherus agassizii) of known sex during a juvenile translocation survival study between September 2012 and November 2017. The main source of mortality (77%; 24 of 31 deaths) was attributed to Coyote (Canis latrans) and Kit Fox (Vulpes macrotis) predation. Predation was skewed with 71% (n = 17) female mortality versus 29% (n = 7) male mortality. We tested the hypothesis that juvenile females smell different than males which leads to increased canid predation. We also explored differences in chemical signatures of resident adult female and male Desert Tortoises. We collected oral, cloacal and chin/forelimb swabs from translocated juvenile and resident adult female and male tortoises during fall 2015 and fall 2017 and analyzed them using headspace gas chromatography/mass spectrometry to determine potential differences in the chemical signatures among the four groups. Standardized chromatographic peak responses were subjected to repeated analyses of variance (ANOVA). For development of artificial scents, mean responses were calculated for each juvenile tortoise from standardized responses representing all collections (i.e., oral, cloacal, and chin/forelimb swabs) and grand means were determined for males and females. Repeated measures ANOVAs clearly demonstrated that the collections of volatiles differed according to age and/or sex depending on the body location of collection. Among the plausibly endogenous volatiles that differed by age, many of them are alcohols. Two field trials using captive Coyotes and one field trial partially within the translocation area were conducted to test if Coyotes showed a preference for female or bias against male synthesized scent. No consistent preference or bias was shown, suggesting that no innate preference for female odor was evident.
Abstract Regional‐scale estimations of sorghum biomass production allow identification of optimum genotype×environment×management (G×E×M) combinations for bioenergy generation. The objective of this study was to determine the degree of contributions of G, E, and M toward variability in sorghum biomass in the United States. Using the Agricultural Production Systems sIMulator in a grid computing platform, biomass was simulated for irrigated and rainfed conditions for 30 years across the United States for four sorghum varietal types (grain—GS, sudangrass—SS, photosensitive—PS, and photo‐insensitive—PI). Simulated biomass was assessed by environments clustered using the sum of intercepted solar radiation ( ir ), mean of temperature stress factor ( tp ) and water stress factor ( sw ). Simulated biomass ranged from 5.8 t ha −1 (GS‐rainfed) to 27.5 t ha −1 (PI‐irrigated). Under high‐temperature environments (mean annual temperature = 25°C), rainfed biomass between 40 and 80 days after planting (DAP) was strongly correlated with sw ( r = 0.64–0.86) and irrigated biomass with ir ( r = 0.68–0.81). Under low‐temperature environments (mean annual temperature = 18°C) after 40 DAP, tp and ir had greater effects than sw ( r = 0.55–0.82). Biomass variance was mainly explained by varietal type (50%–76%) in all environments×irrigation combinations, except in the high‐ and mid‐temperature environments under rainfed conditions where rainfall had the major effect (25%–45%). However, when mean temperature during the growing season decreased from 25°C (high environments) to 18°C (low environments), the contribution of mean temperature to biomass variance increased from 7% to 34% (rainfed) and from 4% to 36% (irrigated). Varietal type had the larger interactions with other factors independently of the environment and irrigation. We demonstrated a need to quantify (i) the main G×E×M drivers of biomass variability based on environmental stress factors and (ii) the variance contribution of these drivers on sorghum biomass. Our regional‐scale estimations are key inputs for future robust biomass projections of energy sorghum genotypes integrating G×E×M under climate change scenarios.