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NASA NTRS1992

Design of an essentially non-oscillatory reconstruction procedure in finite-element type meshes

An essentially non oscillatory reconstruction for functions defined on finite element type meshes is designed. Two related problems are studied: the interpolation of possibly unsmooth multivariate functions on arbitary meshes and the reconstruction of a function from its averages in the control volumes surrounding the nodes of the mesh. Concerning the first problem, the behavior of the highest coefficients of two polynomial interpolations of a function that may admit discontinuities of locally regular curves is studied: the Lagrange interpolation and an approximation such that the mean of the polynomial on any control volume is equal to that of the function to be approximated. This enables the best stencil for the approximation to be chosen. The choice of the smallest possible number of stencils is addressed. Concerning the reconstruction problem, two methods were studied: one based on an adaptation of the so called reconstruction via deconvolution method to irregular meshes and one that lies on the approximation on the mean as defined above. The first method is conservative up to a quadrature formula and the second one is exactly conservative. The two methods have the expected order of accuracy, but the second one is much less expensive than the first one. Some numerical examples are given which demonstrate the efficiency of the reconstruction.

Abgrall, Remi↗

NASA NTRS2007

Anvil Tool in the Advanced Weather Interactive Processing System

Meteorologists from the 45th Weather Squadron (45 WS) and Spaceflight Meteorology Group (SMG) have identified anvil forecasting as one of their most challenging tasks when predicting the probability of violations of the lightning Launch Commit Criteria and Space Shuttle Flight Rules. As a result, the Applied Meteorology Unit (AMU) created a graphical overlay tool for the Meteorological Interactive Data Display Systems (MIDDS) to indicate the threat of thunderstorm anvil clouds, using either observed or model forecast winds as input. In order for the Anvil Tool to remain available to the meteorologists, the AMU was tasked to transition the tool to the Advanced Weather interactive Processing System (AWIPS). This report describes the work done by the AMU to develop the Anvil Tool for AWIPS to create a graphical overlay depicting the threat from thunderstorm anvil clouds. The AWIPS Anvil Tool is based on the previously deployed AMU MIDDS Anvil Tool. SMG and 45 WS forecasters have used the MIDDS Anvil Tool during launch and landing operations. SMG's primary weather analysis and display system is now AWIPS and the 45 WS has plans to replace MIDDS with AWIPS. The Anvil Tool creates a graphic that users can overlay on satellite or radar imagery to depict the potential location of thunderstorm anvils one, two, and three hours into the future. The locations are based on an average of the upper-level observed or forecasted winds. The graphic includes 10 and 20 nm standoff circles centered at the location of interest, in addition to one-, two-, and three-hour arcs in the upwind direction. The arcs extend outward across a 30 degree sector width based on a previous AMU study which determined thunderstorm anvils move in a direction plus or minus 15 degrees of the upper-level (300- to 150-mb) wind direction. This report briefly describes the history of the MIDDS Anvil Tool and then explains how the initial development of the AWIPS Anvil Tool was carried out. After testing was performed by SMG, 45 WS, and AMU, a number of needed improvements were identified. A bug report document was created that showed the status of each bug and desired improvement. This report lists the improvements that were made to increase the accuracy and user-friendliness of the tool. Final testing was carried out and documented and then the final version of the software and Users Guide was provided to SMG and the 45 WS. Several possible future improvements to the tool are identified that would increase the flexibility of the tool. This report contains a brief history of the development of the Anvil Tool in MIDDS, and then describes the transition and development of software to AWIPS.

Barrett, Joe, III↗

DOE OSTI2021

Outlier classification using autoencoders: application for fluctuation driven flows in fusion plasmas

Understanding the statistics of fluctuation driven flows in the boundary layer of magnetically confined plasmas is desired to accurately model the lifetime of the vacuum vessel components. Mirror Langmuir probes (MLPs) are a novel diagnostic that uniquely allow us to sample the plasma parameters on a time scale shorter than the characteristic time scale of their fluctuations. Sudden large-amplitude fluctuations in the plasma degrade the precision and accuracy of the plasma parameters reported by MLPs for cases in which the probe bias range is of insufficient amplitude. While some data samples can readily be classified as valid and invalid, we find that such a classification may be ambiguous for up to 40% of data sampled for the plasma parameters and bias voltages considered in this study. In this contribution, we employ an autoencoder (AE) to learn a low-dimensional representation of valid data samples. By definition, the coordinates in this space are the features that mostly characterize valid data. Ambiguous data samples are classified in this space using standard classifiers for vectorial data. In this way, we avoid defining complicated threshold rules to identify outliers, which require strong assumptions and introduce biases in the analysis. By removing the outliers that are identified in the latent low-dimensional space of the AE, we find that the average conductive and convective radial heat fluxes are between approximately 5% and 15% lower as when removing outliers identified by threshold values. For contributions to the radial heat flux due to triple correlations, the difference is up to 40%.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRSDate not supplied

Large-Eddy Simulations of a Single-Injector Cooling Flow Using the High-Order Flux Reconstruction Method

A single-injector cooling flow into a heated crossflow was used as a validation case for large eddy simulations (LES) from two high-order CFD codes with comparisons to a state-of-the-art Reynolds averaged Navier-Stokes (RANS) turbulence model. The focus of this paper is on the validation of LES for one of the high-order CFD codes, namely the GFR (Glenn Flux Reconstruction) code that is being developed at NASA Glenn Research Center. Fourth-order LES were performed for the single-injector cooling flow configuration at blowing ratios of both 1.0 and 2.0, and a fifth-order LES was also performed with a blowing ratio of 1.0. The GFR simulations agree very well with the experiment mean quantities and reasonably well with the experiment turbulence quantities. The LES solutions from GFR and the other high-order CFD code, FDL3DI, agreed very closely for nearly every flow quantity examined, despite the fact that these two codes use completely different numerical methods, different grid geometries and domains, and different inflow boundary conditions. Finally, both LES show a significant accuracy improvement over RANS turbulence models for flows with large temperature gradients, where the standard gradient diffusion approximation is insufficient for temperature predictions.

Large Eddy Simulations↗

NASA NTRSDate not supplied

Large Eddy Simulations of a Single-Injector Cooling Flow Using the High-Order Flux Reconstruction Method

Large Eddy Simulation↗

NASA NTRS1977

Apparent depth/apparent diameter relation for lunar craters

Photogrammetric measurements from Apollo metric-quality pictures ensure high accuracy of apparent depth (R sub a) and apparent diameter (D sub a) data for fresh lunar craters. R sub a is a direct function of D sub a and the R sub a/D sub a distribution inflects sharply at an apparent diameter of about 15 km. Each of the two resulting subgroups of craters requires two separate least-squares fits. For simple lunar craters (less than 15 km across), the ratio of R sub a to D sub a is about 0.2; the ratio for complex (larger) craters ranges from 0.1 to 0.01. Apparent depth does not exceed 3400 m, regardless of crater size, possibly as a result of isostasy, substrate layering, or curvature of the moon. R sub a/D sub a differences for mare versus terra craters are either absent or are equivocal. The ratio of apparent diameter to rim-crest diameter (D sub a/D sub r) averages 0.83 for smaller craters and 0.86 for larger craters, indicating another simple-to-complex contrast in crater morphology on the moon, and confirms a prediction by R. B. Baldwin for simple craters. Close similarity of D sub a/D sub r for terrestrial experimental craters and simple lunar craters is especially consistent with impact origin for the moon's craters.

Pike, R. J.↗

DOE OSTI2021

StressNet - Deep learning to predict stress with fracture propagation in brittle materials

Abstract Catastrophic failure in brittle materials is often due to the rapid growth and coalescence of cracks aided by high internal stresses. Hence, accurate prediction of maximum internal stress is critical to predicting time to failure and improving the fracture resistance and reliability of materials. Existing high-fidelity methods, such as the Finite-Discrete Element Model (FDEM), are limited by their high computational cost. Therefore, to reduce computational cost while preserving accuracy, a deep learning model, StressNet, is proposed to predict the entire sequence of maximum internal stress based on fracture propagation and the initial stress data. More specifically, the Temporal Independent Convolutional Neural Network (TI-CNN) is designed to capture the spatial features of fractures like fracture path and spall regions, and the Bidirectional Long Short-term Memory (Bi-LSTM) Network is adapted to capture the temporal features. By fusing these features, the evolution in time of the maximum internal stress can be accurately predicted. Moreover, an adaptive loss function is designed by dynamically integrating the Mean Squared Error (MSE) and the Mean Absolute Percentage Error (MAPE), to reflect the fluctuations in maximum internal stress. After training, the proposed model is able to compute accurate multi-step predictions of maximum internal stress in approximately 20 seconds, as compared to the FDEM run time of 4 h, with an average MAPE of 2% relative to test data.

36 MATERIALS SCIENCE↗

DOE OSTI2023

X-ray absorption spectroscopy study of Mn reference compounds for Mn speciation in terrestrial surface environments

Abstract X-ray absorption spectroscopy (XAS) offers great potential to identify and quantify Mn species in surface environments by means of linear combination fit (LCF), fingerprint, and shell-fit analyses of bulk Mn XAS spectra. However, these approaches are complicated by the lack of a comprehensive and accessible spectrum library. Additionally, molecular-level information on Mn coordination in some potentially important Mn species occurring in soils and sediments is missing. Therefore, we investigated a suite of 32 natural and synthetic Mn reference compounds, including Mn oxide, oxyhydroxide, carbonate, phosphate, and silicate minerals, as well as organic and adsorbed Mn species, by Mn K-edge X-ray absorption near edge structure (XANES) and extended X-ray absorption fine structure (EXAFS) spectroscopy. The ability of XAS to infer the average oxidation state (AOS) of Mn was assessed by comparing XANES-derived AOS with the AOS obtained from redox titrations. All reference compounds were studied for their local (<5 Å) Mn coordination environment using EXAFS shell-fit analysis. Statistical analyses were employed to clarify how well and to what extent individual Mn species (groups) can be distinguished by XAS based on spectral uniqueness. Our results show that LCF analysis of normalized XANES spectra can reliably quantify the Mn AOS within ~0.1 v.u. in the range +2 to +4. These spectra are diagnostic for most Mn species investigated, but unsuitable to identify and quantify members of the manganate and Mn(III)-oxyhydroxide groups. First-derivative XANES fingerprinting allows the unique identification of pyrolusite, ramsdellite, and potentially lithiophorite within the manganate group. However, XANES spectra of individual Mn compounds can vary significantly depending on chemical composition and/or crystallinity, which limits the accuracy of XANES-based speciation analyses. In contrast, EXAFS spectra provide a much better discriminatory power to identify and quantify Mn species. Principal component and cluster analyses of k2-weighted EXAFS spectra of Mn reference compounds implied that EXAFS LCF analysis of environmental samples can identify and quantify at least the following primary Mn species groups: (1) Phyllo- and tectomanganates with large tunnel sizes (2 × 2 and larger; hollandite sensu stricto, romanèchite, todorokite); (2) tectomanganates with small tunnel sizes (2 × 2 and smaller; cryptomelane, pyrolusite, ramsdellite); (3) Mn(III)-dominated species (nesosilicates, oxyhydroxides, organic compounds, spinels); (4) Mn(II) species (carbonate, phosphate, and phyllosilicate minerals, adsorbed and organic species); and (5) manganosite. All Mn compounds, except for members of the manganate group (excluding pyrolusite) and adsorbed Mn(II) species, exhibit unique EXAFS spectra that would allow their identification and quantification in mixtures. Therefore, our results highlight the potential of Mn K-edge EXAFS spectroscopy to assess bulk Mn speciation in soils and sediments. A complete XAS-based speciation analysis of bulk Mn in environmental samples should preferably include the determination of Mn valences following the “Combo” method of Manceau et al. (2012), EXAFS LCF analyses based on principal component and target transformation results, as well as EXAFS shell-fit analyses for the validation of LCF results. For this purpose, all 32 XAS reference spectra are provided in the Online Materials1 for further use by the scientific community.

Geochemistry & Geophysics↗

NASA NTRS2016

Uncertainties in Coastal Ocean Color Products: Impacts of Spatial Sampling

With increasing demands for ocean color (OC) products with improved accuracy and well characterized, per-retrieval uncertainty budgets, it is vital to decompose overall estimated errors into their primary components. Amongst various contributing elements (e.g., instrument calibration, atmospheric correction, inversion algorithms) in the uncertainty of an OC observation, less attention has been paid to uncertainties associated with spatial sampling. In this paper, we simulate MODIS (aboard both Aqua and Terra) and VIIRS OC products using 30 m resolution OC products derived from the Operational Land Imager (OLI) aboard Landsat-8, to examine impacts of spatial sampling on both cross-sensor product intercomparisons and in-situ validations of R(sub rs) products in coastal waters. Various OLI OC products representing different productivity levels and in-water spatial features were scanned for one full orbital-repeat cycle of each ocean color satellite. While some view-angle dependent differences in simulated Aqua-MODIS and VIIRS were observed, the average uncertainties (absolute) in product intercomparisons (due to differences in spatial sampling) at regional scales are found to be 1.8%, 1.9%, 2.4%, 4.3%, 2.7%, 1.8%, and 4% for the R(sub rs)(443), R(sub rs)(482), R(sub rs)(561), R(sub rs)(655), Chla, K(sub d)(482), and b(sub bp)(655) products, respectively. It is also found that, depending on in-water spatial variability and the sensor's footprint size, the errors for an in-situ validation station in coastal areas can reach as high as +/- 18%. We conclude that a) expected biases induced by the spatial sampling in product intercomparisons are mitigated when products are averaged over at least 7 km × 7 km areas, b) VIIRS observations, with improved consistency in cross-track spatial sampling, yield more precise calibration/validation statistics than that of MODIS, and c) use of a single pixel centered on in-situ coastal stations provides an optimal sampling size for validation efforts. These findings will have implications for enhancing our understanding of uncertainties in ocean color retrievals and for planning of future ocean color missions and the associated calibration/validation exercises.

Coastal ocean color↗

DOE OSTI2022

Modeling of Cube Array Roughness: RANS, Large Eddy Simulation, and Direct Numerical Simulation

Abstract Flow over arrays of cubes is an extensively studied model problem for rough wall turbulent boundary layers. While considerable research has been performed in computationally investigating these topologies using direct numerical simulation (DNS) and large eddy simulation (LES), the ability of sublayer-resolved Reynolds-averaged Navier–Stokes (RANS) to predict the bulk flow phenomena of these systems is relatively unexplored, especially at low and high packing densities. Here, RANS simulations are conducted on six different packing densities of cubes in aligned and staggered configurations. The packing densities investigated span from what would classically be defined as isolated, up to those in the d-type roughness regime, filling in the gap in the present literature. Three different sublayer-resolved turbulence closure models were tested for each case: a low Reynolds number k–ϵ model, the Menter k–ω SST model, and a full Reynolds stress model. Comparisons of the velocity fields, secondary flow features, and drag coefficients are made between the RANS results and existing LES and DNS results. There is a significant degree of variability in the performance of the various RANS models across all comparison metrics. However, the Reynolds stress model demonstrated the best accuracy in terms of the mean velocity profile as well as drag partition across the range of packing densities.

Engineering↗

DOE OSTI2022

Error analysis of a hybrid control drum worth model

This paper presents a perturbation-based model for control drum worth prediction which employs both physics-based and statistics-based components. Control drums, or control shims, are cylindrical in shape and span the axial length of the core. A portion of the cylinder is coated in neutron absorbing material and the drum can rotate to introduce the absorbing material to the body of the core to reduce reactivity. The model can be expensive to create due to the requirement for full-core Monte Carlo eigenvalue calculations. Therefore, it is important to analyze how the errors in Monte Carlo calculated k{sub eff} used for model training affect model performance. It was found that the error in predicted criticalities could average to 70 pcm in the most complex form of the model and 215 pcm in the simplest form of the model. Furthermore, it was found that the Monte Carlo uncertainty in quantities calculated with Serpent used to train the models had minimal impact on the error observed from the model. Lastly, one of the forms of the hybrid model could be trained in considerably less computational time if the Monte Carlo calculations were run to higher uncertainty in k{sub eff} with a small penalty to model performance.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS2002

Slat Cove Noise Modeling: A Posteriori Analysis of Unsteady RANS Simulations

A companion paper by Khorrami et al demonstrates the feasibility of simulating the (nominally) self-sustained, large-scale unsteadiness within the leading-edge slat-cove region of multi-element airfoils using unsteady Reynolds-Averaged Navier-Stokes (URANS) equations, provided that the turbulence production term in the underlying two-equation turbulence model is switched off within the cove region. In conjunction with a FfowesWilliams-Hawkings solver, the URANS computations were shown to capture the dominant portion of the acoustic spectrum attributed to slat noise, as well as reproducing the increased intensity of slat cove motions (and, correspondingly, far-field noise as well) at the lower angles of attack. This paper examines that simulation database, augmented by additional simulations, with the objective of transitioning this apparent success to aeroacoustic predictions in an engineering context. As a first step towards this goal, the simulated flow and acoustic fields are compared with experiment and simplified analytical model. Rather intense near-field fluctuations in the simulated flow are found to be associated with unsteady separation along the slat bottom surface, relatively close to the slat cusp. Accuracy of the laminar-cove simulations in this near-wall region is raised to be an open issue. The adjoint Green's function approach is also explored in an attempt to identify the most efficient noise source locations.

Choudhari, Meelan↗

NASA NTRS2009

Rare Earth Element Measurements of Melilite and Fassaite in Allende Cai by Nanosims

The rare earth elements (REEs) are concentrated in CAIs by approx. 20 times the chondritic average [e.g., 1]. The REEs in CAIs are important to understand processes of CAI formation including the role of volatilization, condensation, and fractional crystallization [1,2]. REE measurements are a well established application of ion microprobes [e.g., 3]. However the spatial resolution of REE measurements by ion microprobe (approx.20 m) is not adequate to resolve heterogeneous distributions of REEs among/within minerals. We have developed methods for measuring REE with the NanoSIMS 50L at smaller spatial scales. Here we present our initial measurements of REEs in melilite and fassaite in an Allende Type-A CAI with the JSC NanoSIMS 50L. We found that the key parameters for accurate REE abundance measurements differ between the NanoSIMS and conventional SIMS, in particular the oxide-to-element ratios, the relative sensitivity factors, the energy distributions, and requisite energy offset. Our REE abundance measurements of the 100 ppm REE diopside glass standards yielded good reproducibility and accuracy, 0.5-2.5 % and 5-25 %, respectively. We determined abundances and spatial distributions of REEs in core and rim within single crystals of fassaite, and adjacent melilite with 5-10 m spatial resolution. The REE abundances in fassaite core and rim are 20-100 times CI abundance but show a large negative Eu anomaly, exhibiting a well-defined Group III pattern. This is consistent with previous work [4]. On the other hand, adjacent melilite shows modified Group II pattern with no strong depletions of Eu and Yb, and no Tm positive anomaly. REE abundances (2-10 x CI) were lower than that of fassaite. These patterns suggest that fassaite crystallized first followed by a crystallization of melilite from the residual melt. In future work, we will carry out a correlated study of O and Mg isotopes and REEs of the CAI in order to better understand the nature and timescales of its formation process and subsequent metamorphic history.

Ito, M.↗

NASA NTRS2012

Study of MPLNET-Derived Aerosol Climatology over Kanpur, India, and Validation of CALIPSO Level 2 Version 3 Backscatter and Extinction Products

The level 2 aerosol backscatter and extinction profiles from the NASA Micropulse Lidar Network (MPLNET) at Kanpur, India, have been studied from May 2009 to September 2010. Monthly averaged extinction profiles from MPLNET shows high extinction values near the surface during October March. Higher extinction values at altitudes of 24 km are observed from April to June, a period marked by frequent dust episodes. Version 3 level 2 Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) aerosol profile products have been compared with corresponding data from MPLNET over Kanpur for the above-mentioned period. Out of the available backscatter profiles, the16 profiles used in this study have time differences less than 3 h and distances less than 130 km. Among these profiles, four cases show good comparison above 400 m with R2 greater than 0.7. Comparison with AERONET data shows that the aerosol type is properly identified by the CALIOP algorithm. Cloud contamination is a possible source of error in the remaining cases of poor comparison. Another source of error is the improper backscatter-to-extinction ratio, which further affects the accuracy of extinction coefficient retrieval.

extinction profiles↗

NASA NTRS1999

The Geoscience Laser Altimeter System (GLAS) for the ICESAT Mission

Accurate measurements of surface heights and atmospheric backscatter have been demonstrated with the SLA, MOLA and LITE space lidar. Recent MOLA measurements of the Mars surface have 40 cm resolution and have reduced the global uncertainty in Mars topography from a few km to approx. 10 m. GLAS is a next generation lidar being developed as part of NASA's Icesat Mission for Earth orbit . The GLAS design combines a 10 cm precision surface lidar with a sensitive dual wavelength cloud and aerosol lidar. GLAS will precisely measure the heights of the Earth's polar ice sheets, determine the height profiles of the Earth's land topography, and profile the vertical backscatter of clouds and aerosols on a global scale. GLAS will fly on a small dedicated spacecraft in a polar orbit at 598 km altitude with an inclination of 94 degrees. GLAS is scheduled to launch in summer 2001 and to operate continuously for a minimum of 3 years with a goal of 5 years. The primary mission for GLAS is to measure the seasonal and annual changes in the heights of the Greenland and Antarctic ice sheets. GLAS will measure the vertical distance to the ice sheet from orbit with 1064 nm pulses from a Nd:Yag laser at 40 Hz. Each 5 nsec wide laser pulse is used for a single range measurement. When over land GLAS will profile the heights of the topography and vegetation. The GLAS receiver uses a I m diameter telescope and a Si APD detector. The detector signal is sampled by an all digital receiver which records each surface echo waveform with I nsec resolution and a stored echo record lengths of either 200, 400, or 600 samples. Analysis of the echo waveforms within the instrument permits discrimination between cloud and surface echoes. Ground based echo analysis permits precise ranging, determining the roughness or slopes of the surface as well as the vertical distributions of vegetation illuminated by the laser, Errors in knowledge of the laser beam pointing angle can bias height measurements of sloped surfaces. For surfaces with 2 deg. slopes, knowledge of pointing angle of the beam centroid to about 8 urad is required to achieve 10 cm height accuracy. GLAS uses a stellar reference system (SRS) to determine the pointing angle of each laser firing relative to inertial space. The SRS uses a high precision star camera oriented toward local zenith whose measurements are combined with a gyroscope to determine the inertial orientation of the SRS optical bench. The far field pattern of each laser pulse is measured with a laser reference system (LRS). Optically measuring each laser far field pattern relative to the star camera and gyroscope permits the angular offsets of each laser pulse to be determined. GLAS will also determine the vertical distributions of clouds and aerosols by measuring atmospheric backscatter profiles at both 1064 and 532 nm. The 1064 nm measurements use an analog detector and profile the height and vertical structure of thicker clouds. Measurements at 532 nm use new highly sensitive photon counting detectors, and measure the height distributions of very thin clouds and aerosol layers. With averaging these can be used to determine the height of the planetary boundary layer. The instrument design and expected performance will be discussed.

Abshire, James B.↗

NASA NTRS2014

A Method for Obtaining High Time and Spatial Resolution Convective Cloud Top Data for the TTL

A method for obtaining high time and spatial resolution convective cloud top data for the TTL Leonhard Pfister, Eric Jensen, Rei Ueyama, Eliot Atlas, and Maria Navarro Convective systems in the tropics have a maximum in the cloud top altitude distribution of about 13.5 km. However, there is a significant tail to this distribution -- a few percent reach the cold point tropopause (CPT) at 16.5 km, and there has been clear evidence of convective mass deposited as high as 19 km in the tropics. The region between 13.5 km and the cold point tropopause is transitional, between the free tropical troposphere where convective mixing dominates, and the stratosphere where slow upward ascent dominates. In this region (the Tropical Tropopause Layer), convective injection, slow ascent, and mixing from midlatitudes all have similar time scales. So, even though only a few percent of convective systems reach the CPT, convection is important. Space Based Lidar and cloud radar measurements have yielded information about long term average statistical distributions of cloud altitude as a function of location. However, we also need time-dependent cloud top altitude and cloud top potential temperature information, primarily to understand the water vapor and TTL cloud distributions. This is because the effect of convection depends on the local temperature, and on the subsequent temperature history. Time dependent cloud top information is also needed to understand short-lived tracers because cross-isentropic flow is time and space dependent. This paper presents a method of obtaining time and space dependent convective cloud top theta (and altitude) information using 3-hourly geostationary brightness temperature data, coupled with global 3 -hourly rainfall estimates and temperature analyses. We explore different mixing algorithms to obtain the most reasonable agreement with near-simultaneous observations by cloudsat and calipso. Observations of short-lived tracers from ATTREX, coupled with short-term trajectories are used to test the method's accuracy. An important caveat is the ambiguity of evaluating convective cloud top altitudes under from combined cloudsat and calipso measurements.

cold point tropopause (CPT)↗

NASA NTRSDate not supplied

Simulation and Modeling of Hypersonic Turbulent Boundary Layers Subject to Adverse Pressure Gradients due to Concave Streamline Curvature

Direct numerical simulations (DNS) of adverse-pressure-gradient turbulent boundary layers over a planar concave wall are presented for a nominal freestream Mach number of 5, with the objective of assessing the limitations of the currently available Reynolds-averaged Navier-Stokes (RANS) models. The wall geometry and flow conditions of the DNS are representative of the experimental data for a Mach 4.9 turbulent boundary layer that was tested on a two-dimensional planar concave wall model in the high-speed blow-down wind tunnel located at the National Aerothermochemistry Laboratory at Texas A&M University (TAMU). The DNS was validated against the experimental results of TAMU for the same flow conditions and wall geometry. An analysis of the DNS datasets was also conducted to provide an assessment of the validity of Morkovin’s hypothesis and the strong Reynolds analog for turbulence subject to mechanical nonequilibrium. In addition to the DNS results, RANS predictions are obtained by using the Baldwin-Lomax (BL), Spalart-Allmaras (SA), and the k - w SST turbulence models. The comparisons between RANS and DNS showed little impact of an adverse pressure gradient on the accuracy of these models, at least up to an incompressible Clauser pressure gradient parameter of beta(sub inc) 1.22. While the Boussinesq assumption provided reasonable predictions for the Reynolds shear stress, it failed to adequately predict the normal components of the Reynolds stress.

turbulent boundary layers↗

DOE OSTI2026

Bayesian Physics Informed Spatio-Temporal Network for Streamflow Data Imputation

Reliable reconstruction of incomplete streamflow records is critical for improving hydrological forecasting, flood preparedness, and water resource management. However, large observational gaps and uncertainties in governing physical parameters limit the accuracy of traditional statistical and machinelearning imputation frameworks. To address these challenges, we develop a Bayesian Physics-Informed Spatio-Temporal Network (BPI-STNet) that jointly captures spatial and temporal dependencies while enforcing hydrologic consistency through embedded physical constraints. The framework integrates a GraphSAGE-LSTM architecture to model spatial connectivity across gauges and temporal flow dynamics, coupled with a Bayesian update mechanism to estimate uncertain parameters in a simplified water-balance framework. Unlike conventional physics-informed networks that rely on sampling-based posterior estimation, BPI-STNet derives an analytic solution to the inverse problem, allowing closed-form Bayesian updates of uncertain parameters Λ={α,β,k} using Gaussian priors and likelihoods. Applied to daily observations from the Susquehanna River Basin (1980-2022), BPI-STNet achieves substantial improvements over a purely data-driven RGNN baseline, which reduced RMSE by 23 % and MAE by 9 %, and achieving an average NSE values up to 0.96. The results demonstrate that coupling Bayesian inference with physics-informed learning yields physically consistent, uncertainty-aware reconstructions that preserve the temporal persistence and statistical distribution of observed flows. The proposed framework establishes a generalizable paradigm for data-sparse hydrologic systems where both data fidelity and physical interpretability are essential.

Krishnan Kutty Ambika, Anukesh [ORNL] (ORCID:00000↗