Results for “Variational inference” — Page 7

NASA NTRS2021

Pretest Computational Assessment of Boundary Layer Transition in the NASA Juncture Flow Model with an NACA 0015-Based Wing

The first two phases of the NASA Juncture Flow experiment were carried out on a DLR-F6 swept-wing model and were designed to provide “CFD validation-quality” data toward the assessment and improvement of existing CFD turbulence models in predicting onset and extent of three-dimensional separated flow near the wing-juncture trailing-edge region. The next phase of experiments will involve an NACA 0015-based swept wing, as prior risk reduction experiments had indicated that this wing shape resulted in reduced separation near the juncture region than the DLR-F6 wing, thus providing a better option to evaluate the ability of CFD models to predict incipient turbulent separation. The NACA 0015 measurements will also include IR thermography to infer the variation of transition front with respect to an increasing angle of attack. The primary objective of this work is to computationally make a preliminary assessment of the transition front on both surfaces of the NACA 0015 wing at a crank-chord-based Reynolds number of 2.4 x 106 for four different angles of attack, (0°, 2.5°, 5°, and 7.5°) and to determine the dominant mechanisms responsible for transition. This assessment includes both RANS-based transition models from NASA’s OVERFLOW 2.3b flow solver and linear parabolized stability equations (PSE) stability analysis based on the Langley Stability and Transition Analysis code, LASTRAC. Linear PSE results indicate that the upper surface of the wing is dominated by Tollmien- Schlichting (TS) instabilities, and that the laminar flow region shrinks from about 50% chord to a very small region just downstream of the attachment line as the angle of attack is increased from 0° to 7.5°. Consequently, the transition fronts predicted by the Spalart- Allmaras-based amplification factor transport (AFT-2017b) equation model (which accounts for the TS instabilities alone) and the Menter’s shear-stress transport equation (SST2003)- based Langtry-Menter transition model with ability to account for both TS and crossflow effects (LM2015) compare well with those predicted using linear PSE. On the lower surface of the wing, stationary crossflow (CF) instabilities begin to appear on the inboard portion of the wing in addition to the TS-instabilities for the larger angles of attack (5° and 7.5°), further reducing the laminar flow extent within the inboard region. The LM2015 model that accounts for CF effects is able to replicate this trend but appears to predict a slightly earlier transition. The outcome of this effort will inform the experiment and, when the actual experimental data become available, provide further opportunity to assess and improve the various transition models.

CFD modeling↗

NASA NTRS2021

Pretest Computational Assessment of Boundary Layer Transition in the NASA Juncture Flow Model with an NACA 0015-Based Wing

The first two phases of the NASA Juncture Flow experiment were carried out on a DLR-F6 swept-wing model and were designed to provide “CFD validation-quality” data toward the assessment and improvement of existing CFD turbulence models in predicting onset and extent of three-dimensional separated flow near the wing-juncture trailing-edge region. The next phase of experiments will involve an NACA 0015-based swept wing, as prior risk reduction experiments had indicated that this wing shape resulted in reduced separation near the juncture region than the DLR-F6 wing, thus providing a better option to evaluate the ability of CFD models to predict incipient turbulent separation. The NACA 0015 measurements will also include IR thermography to infer the variation of transition front with respect to an increasing angle of attack. The primary objective of this work is to computationally make a preliminary assessment of the transition front on both surfaces of the NACA 0015 wing at a crank-chord-based Reynolds number of 2.4 x 106 for four different angles of attack, (0°, 2.5°, 5°, and 7.5°) and to determine the dominant mechanisms responsible for transition. This assessment includes both RANS-based transition models from NASA’s OVERFLOW 2.3b flow solver and linear parabolized stability equations (PSE) stability analysis based on the Langley Stability and Transition Analysis code, LASTRAC. Linear PSE results indicate that the upper surface of the wing is dominated by Tollmien- Schlichting (TS) instabilities, and that the laminar flow region shrinks from about 50% chord to a very small region just downstream of the attachment line as the angle of attack is increased from 0° to 7.5°. Consequently, the transition fronts predicted by the Spalart- Allmaras-based amplification factor transport (AFT-2017b) equation model (which accounts for the TS instabilities alone) and the Menter’s shear-stress transport equation (SST2003)- based Langtry-Menter transition model with ability to account for both TS and crossflow effects (LM2015) compare well with those predicted using linear PSE. On the lower surface of the wing, stationary crossflow (CF) instabilities begin to appear on the inboard portion of the wing in addition to the TS-instabilities for the larger angles of attack (5° and 7.5°), further reducing the laminar flow extent within the inboard region. The LM2015 model that accounts for CF effects is able to replicate this trend but appears to predict a slightly earlier transition. The outcome of this effort will inform the experiment and, when the actual experimental data become available, provide further opportunity to assess and improve the various transition models.

CFD modeling↗

DOE OSTI2025

Aided Active Learning (AAL) for Enhanced Critical Heat Flux Prediction

Accurate prediction of critical heat flux (CHF) is crucial for the safe and efficient operation of nuclear reactors. Traditional CHF modeling methods often require extensive experimental data, which are hard to obtain. This study introduces the Aided Active Learning (AAL) framework, which strategically minimizes data requirements without sacrificing model accuracy. Unlike conventional Active Learning (AL), AAL introduces an additional step of randomly selecting a subset from the sample pool before applying the query strategy. To evaluate the performance of AAL, two query strategies—uncertainty-based sampling and error-reduction sampling—were evaluated across the following models: random forest (RF), feedforward neural network (FNN), and variational feedforward neural network (vFNN). The proposed framework demonstrated that AAL effectively reduces the number of training samples needed to achieve comparable predictive accuracy. For the RF model, AL required only 710 samples to achieve an R2 score of 0.98, as compared to the 4,785 samples needed by random sampling. Similarly, the FNN model achieved the same R2 score with just 355 samples when using AL, a significant improvement over the 825 samples required by random sampling. In case of uncertainty-based sampling strategy, vFNN attained an R2 of 0.98 with 3,420 samples, reducing the sample requirement by 47% relative to the 6,440 samples needed for random sampling. Its performance suggests that larger training data are required to fully leverage its uncertainty quantification capabilities.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1994

The solar cycle variation of ozone in the stratosphere inferred from Nimbus 7 and NOAA 11 satellites

The combined Nimbus 7 solar backscattered ultraviolet (SBUV) and NOAA 11 SBUV/2 ozone data, covering a period of more than a solar cycle (about 15 years), are used to study the UV response of ozone in the stratosphere. The study shows that about 2% change in total column ozone and about 5-7% change in ozone mixing ratio in the upper stratosphere (0.7 to 2 hPa) may be attributed to the change in the solar UV flux over a solar cycle. In the upper stratosphere, where photochemical processes are expected to play a major role, the measured solar cycle variation of ozone is significantly larger than inferred either from the photochemical models or from the ozone response to the 27-day solar UV modulation. For example, the observed solar cycle related change in ozone mixing ratio at 2 hPa is about 1% for 1% change in the solar UV flux near 200 nm. The inferred change in ozone from either the photochemical models or from the 27-day ozone-UV response is about a factor of 2-3 lower than this value.

Chandra, S.↗

NASA NTRS1976

Diurnal and seasonal variations in atomic and molecular oxygen inferred from Atmosphere Explorer-C

Mass-spectrometer measurements of O and N2, obtained with the Atmosphere Explorer-C satellite during December 1974 and January 1975, are used to derive the O2 concentration near 250 km from several ionization reactions. In order to separate temperature effects from diffusion effects, the measured O and inferred O2 concentrations are employed to determine, under the assumption of diffusive equilibrium, the O/N2 and O2/N2 ratios at 120 km. It is found that the latitudinal and diurnal variations in the O concentration at 120 km are consistent with previous results obtained with OGO 6 and that the O2 concentration in the Northern (winter) Hemisphere is about twice as high as that in the Southern (summer) Hemisphere. The possible importance of photodissociation in the diurnal O2 variations is discussed.

Mayr, H. G.↗

NASA NTRS1991

Crustal magnetization and temperature at depth beneath the Yilgarn block, Western Australia inferred from Magsat data

Variations in crustal magnetization along a seismic section across the Archean Yilgarn block of Western Australia inferred from Magsat data are interpreted as a subtle thermal effect arising from variations in depth to the Curie isotherm. The isotherm lies deep within the mantle of the eastern part of the province, but transects the crust-mantle transition and rises well into the crust on the western side. The model is consistent with heat flow variations along the section line. The mean crustal magnetization implied by the model is approximately 2 A/m. The temperature variation implied by the model is consistent with the hypothesis that the crust-mantle transition seen seismically corresponds to the mafic granulite-eclogite phase transition within a zone of igneous crustal underplating.

Mayhew, M. A.↗

NASA NTRS2005

Constraining Hydrological and Cryospheric Mass Flux in Southeastern Alaska using Space-Based Gravity Measurements

Watersheds draining into the Gulf of Alaska (GoA) experience large seasonal and inter-annual variations of water in the form of rain, snow, and ice, but accurate constraints on these variations have been difficult to obtain. Over larger geographic regions, water variations can be inferred directly from the Gravity Recovery and Climate Experiment (GRACE) data. However, because GoA variations occur over such a small region, the inferred average value of water flux increases as the applied smoothing of the GRACE data decreases. We use this observed scaling together with scaling results obtained from forward models to infer a seasonal amplitude of 115 plus or minus 20 cubic kilometers of water and an average contribution to sea level rise over the two years of data of 0.31 plus or minus 0.09 millimeters per year. These results suggest that accelerated melting that began in the late 1990s, as inferred from altimetry, continues unabated.

Tamisiea, M. E.↗

NASA NTRS1989

The effects of viewing angle on the inference of magnetic shear in preflare active regions

Analytic models for nonpotential force-free fields representative of preflaring active regions have been used to determine the degree of magnetic shear along the magnetic neutral line of these fields as a function of location and orientation of the active region on the solar disk. The results indicate that, with the exception of regions close to the disk center, the position of the inferred neutral line differs significantly from the actual neutral line. It is suggested that the significant variation of the inferred degree of shear with the position and orientation of the region is due to such factors as geometric projection effects, the shift of the inferred neutral line relative to its true position, and the variations in the reference potential field.

Wilkinson, Ladye Kathryn↗

DOE OSTI2025

Global variation in vegetation carbon use efficiency inferred from eddy covariance observations

Not provided.

Environmental Sciences & Ecology↗

NASA NTRS1972

Variations in the stratospheric ozone field inferred from Nimbus satellite observations

The ultraviolet earth radiance data from the Backscatter Ultraviolet Experiment on Nimbus 4 have been inverted to infer ozone profiles using a single Rayleigh scattering model. Two methods of solution give essentially the same results. Comparisons of these profiles with simultaneous rocket sounding data shows satisfactory agreement at low and middle latitudes. Vertical cross sections of ozone mixing ratio along the orbital tracks indicate that while the gross characteristics of the ozone field above 10 mb are under photochemical control, the influence of atmospheric motions can be found up to the 4 mb level.

Krueger, A. J.↗

NASA NTRS1973

Variations in the stratospheric ozone field inferred from Nimbus satellite observations.

The ultraviolet earth radiance data from the backscatter ultraviolet experiment on Nimbus 4 have been inverted to infer ozone profiles using a single Rayleigh scattering model. Two methods of solution give essentially the same results. Comparison of these profiles with simultaneous rocket sounding data shows satisfactory agreement at low and middle latitudes. Vertical cross-sections of ozone mixing ratio along the orbital tracks indicate that while the gross characteristics of the ozone field above 10 mb are under photochemical control, the influence of atmospheric motions can be found up to the 4 mb level.

Krueger, A. J.↗

NASA NTRS1985

The seasonal variation of the D region as inferred from propagation characteristics of LF radio waves

The propagation data of JG2AS 40 kHz (Japanese Standard Frequency), Loran C 100 kHz radio waves, and meteorological data were analyzed to study the association of propagation characteristics of LF radio waves with the atmospheric circulation in the mesosphere. The monthly averaged electric fields were depicted on the complex plane for typical summer and winter months, June and November. The locus traced out by the electric field vector during daytime is nearly circular. This is because during daytime the amplitude of the sky wave remains nearly constant while its phase changes in accord with the height change of the reflection layer, and thus the electric field vector traces out a circular locus with its center at the tip of the supposed ground wave vector. The locus has a loop during the sunrise or sunset period, which seems to arise from interference of two waves reflected by two different layers. In June the amplitude of the sky wave decreases rapidly before the dawn or increases after the dusk. In November such rapid change is not observed. During nighttime, the sky wave phase changes in such a way as to suggest that the reflection height moves upwards with time before midnight or lowers after midnight in November. In June it changes similarly before midnight, but after midnight it varies erratically. These characteristics are closely related to the structure of the D region, which is clearly shown by simulating the loci traced out by electric fields.

Ishimine, T.↗

NASA NTRS1985

Variation of tidal winds in the ionosphere inferred from geomagnetic SQ field

The geomagnetic Sq field is mainly generated by the dynamo action of tidal winds in the ionosphere, and therefore some information can be derived from the variation of the Sq field. The geomagnetic Sq field was analyzed during March 1 to 18, 1980, when the geomagnetic activity was exceptionally low, and the equivalent Sq currents calculated every 2 hours by using the spherical harmonics method. Then additional Sq currents were extracted by subtracting the currents averaged through all days in the period from the original currents at each UT. The change of the instantaneous Sq current system by the above-mentioned method is discussed.

Takeda, M.↗

NASA NTRS1984

Latitudinal and altitudinal variation of size distribution of stratospheric aerosols inferred from SAGE aerosol extinction coefficient measurements at two wavelengths

A method of retrieving aerosol size distribution from the measured extinction of solar radiation at wavelengths of 0.45 microns and 1.0 microns has recently been proposed. This method is utilized to obtain latitudinal and altitudinal variations of size distributions of stratospheric aerosols from the Stratospheric Aerosol and Gas Experiment data for March 1979. Small particles are found in the lower stratosphere of the tropical region, and large particles are found at higher altitudes and latitudes in both hemispheres. Results of this study are consistent with the suggestion that the upper troposphere in tropical regions is a source of condensation nuclei in the stratosphere, and they become mature as they move to higher altitudes and latitude.

Yue, G. K.↗

DOE OSTI2021

Optimal Bayesian supervised domain adaptation for RNA sequencing data

Abstract Motivation When learning to subtype complex disease based on next-generation sequencing data, the amount of available data is often limited. Recent works have tried to leverage data from other domains to design better predictors in the target domain of interest with varying degrees of success. But they are either limited to the cases requiring the outcome label correspondence across domains or cannot leverage the label information at all. Moreover, the existing methods cannot usually benefit from other information available a priori such as gene interaction networks. Results In this article, we develop a generative optimal Bayesian supervised domain adaptation (OBSDA) model that can integrate RNA sequencing (RNA-Seq) data from different domains along with their labels for improving prediction accuracy in the target domain. Our model can be applied in cases where different domains share the same labels or have different ones. OBSDA is based on a hierarchical Bayesian negative binomial model with parameter factorization, for which the optimal predictor can be derived by marginalization of likelihood over the posterior of the parameters. We first provide an efficient Gibbs sampler for parameter inference in OBSDA. Then, we leverage the gene-gene network prior information and construct an informed and flexible variational family to infer the posterior distributions of model parameters. Comprehensive experiments on real-world RNA-Seq data demonstrate the superior performance of OBSDA, in terms of accuracy in identifying cancer subtypes by utilizing data from different domains. Moreover, we show that by taking advantage of the prior network information we can further improve the performance. Availability and implementation The source code for implementations of OBSDA and SI-OBSDA are available at the following link. https://github.com/SHBLK/BSDA. Supplementary information Supplementary data are available at Bioinformatics online.

Biochemistry & Molecular Biology↗

NASA NTRS1999

A Combined Length-of-Day Series Spanning 1832-1997

The Earth's rotation is not constant but exhibits minute changes on all observable time scales ranging from subdaily to secular. This rich spectrum of observed Earth rotation changes reflects the rich variety of astronomical and geophysical phenomena that are causing the Earth's rotation to change, including, but not limited to, ocean and solid body tides, atmospheric wind and pressure changes, oceanic current and sea level height changes, post-glacial rebound, and torques acting at the core-mantle boundary. In particular, the decadal-scale variations of the Earth's rotation are thought to be largely caused by interactions between the Earth's outer core and mantle. Comparing the inferred Earth rotation variations caused by the various core-mantle interactions to observed variations requires Earth rotation observations spanning decades, if not centuries. During the past century many different techniques have been used to observe the Earth's rotation. By combining the individual Earth rotation series determined by each of these techniques, a series of the Earth's rotation can be obtained that is based upon independent measurements spanning the greatest possible time interval. In this study, independent observations of the Earth's rotation are combined to generate a length-of-day series spanning 1832-1997. The observations combined include lunar occultation measurements spanning 1832-1955, optical astrometric measurements spanning 1956-1982, lunar laser ranging measurements spanning 1970-1997, and very long baseline interferometric measurements spanning 1978-1998. These series are combined using a Kalman filter developed at JPL for just this purpose. The resulting combined length-of-day series will be presented and compared with other available length-of-day series of similar duration.

Gross, Richard S.↗

DOE OSTI2022

Monitoring Seasonal Shear Wave Velocity Changes in the Top 6 m at Garner Valley in Southern California With Borehole Data

Abstract Subsurface structures play important roles in seismic ground motion, crustal hydrology, stability of the built environment, and more. Constraining temporal changes of subsurface shear wave velocity ( V S ) can provide useful information to all these topics and the growing field of hydrological monitoring with seismic velocity. Using borehole records at Garner Valley, CA, we estimate seasonal subsurface V S variations from impulse response functions (IRFs) of earthquake data (2005–2018) along with IRFs and cross‐correlation of cross‐hole experiment data (2015–2018). The inferred V S variations are up to ∼25% in the top 6 m and ∼10% at 2–5 m in depth. The V S variations correlate strongly with the water table depth changes, suggesting that the changes are mostly due to fluctuations of pore pressure in the shallow material. The shallow velocity changes alter the near‐surface conditions, can affect seismic hazard estimation, and may be improperly attributed to deeper processes without careful analysis.

58 GEOSCIENCES↗

DOE OSTI2020

Spatiotemporal variations of albedo in managed agricultural landscapes: inferences to global warming impacts (GWI)

Albedo can be used to quantify ecosystem and landscape contributions to local and global climate. Such contributions are conventionally expressed as radiative forcing (RF) and global warming impact (GWI). We contextualize our results within landscape carbon production and storage to highlight the importance of changes in albedo for landscape GWI from multiple causes, including net ecosystem production (NEP) and greenhouse gas (GHG) emissions. Objective To examine the spatiotemporal changes in albedo (Δα) in contrasting managed landscapes through calculations of albedo-induced RF (RF Δα ) and GWI (GWI Δα ) under different climatic conditions. Methods We selected five contrasting landscapes within the Kalamazoo River watershed in southern Michigan USA as proof of concept. The daily MCD43A3 MODIS (V006) product was used to analyze the inter- and intra-annual variations of growing season albedo. In addition, the variations of RF Δα and GWI Δα were computed based on landscape composition and climate. Results The RF Δα (-5.6 W m -2 ) and GWI Δα (-1.3 CO 2eq ha -1 year -1 ) were high in forest-dominated landscapes, indicating cooling effects and CO 2eq mitigation impacts similar to crops. The CO 2eq mitigation of cropland-dominated landscapes was on average 52% stronger than forest-dominated landscapes. In the landscape with the highest proportion of forest, under dry and wet conditions CO 2eq mitigation was reduced by up to 24% and ~ 30%, respectively; in one cropland-dominated landscape wet conditions reduced CO 2eq mitigation by 23%. Conclusions Findings demonstrate that quantifying spatiotemporal changes in albedo in managed landscapes and under different climatic conditions is essential to understand how landscape modification affects RF Δα and GWI Δα and thereby contributes to ecosystem-level GWI.

54 ENVIRONMENTAL SCIENCES↗