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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Estimating epistemic uncertainty in soil parameters for nonlinear site response analyses: Introducing the Latin Hypercube Sampling technique

This study quantifies the effects of epistemic uncertainty in soil parameters on nonlinear (NL) site response analysis (SRA) results, validated against the data recorded at a well-instrumented geotechnical downhole array located in Japan. To this end, a one-dimensional soil column model of the Service Hall Array (SHA) near the Kashiwazaki-Kariwa Nuclear Power Plant (KKNPP) is developed using the finite element (FE) program LS-DYNA. The dynamic stress–strain relationship is characterized by a modified two-stage hyperbolic (MTH) NL backbone curve formulation capable of capturing soil behavior at both small- and large-shear strains. The model is then validated against the ground motion recordings to capture the model bias. The uncertainties associated with the shear-wave velocity profile (a small-strain soil property) and soil shear strength (a large-strain soil property) are incorporated in NL SRA to quantify their separate and joint randomization effects on the results. This study proposes using the Latin Hypercube Sampling (LHS) method as an efficient alternative to commonly used methods, such as Standard Monte Carlo (SMC), to account for uncertainty propagation in such reliability analysis. Both low-intensity and design-level records from the recordings at the SHA are applied to study the contribution of the small- and large-strain NL dynamic soil properties. Results from 46,200 NL FE analyses (23,100 per input motion) are presented. Measured and predicted site response, using recorded ground motions at this downhole array, is compared to assess the significance of soil parameter uncertainty on the observed ground motion dispersions. It is demonstrated that increasing the number of soft realizations and implementing higher level earthquake intensity lead to higher ground motion dispersion. Unlike past studies in randomization of Vs profiles with the SMC method, the LHS method is shown to have no significant effect on the predicted median surface response spectra and amplification factors (AFs) for this case study.

Engineering↗
DOE OSTI2024

Processes Associated with Boundary Layer Cloud Ice Phase Precipitation in the High Southern Latitudes (Final Technical Report)

This is a final technical report for DOE Award No. DE-SC0018995. Using data collected during the MARCUS deployment of the 2nd ARM mobile facility, this project sought to address the following scientific questions: 1. What are the conditions that govern phase partitioning in supercooled boundary layer clouds over the high latitude Southern Oceans? 2. To what extent are supercooled mixed phase clouds responsible for the high cloud fractions over the Southern Ocean and do these mixed phase clouds contribute to the model biases in absorbed shortwave radiation? 3. Can the cloud properties and phase partitioning over the Southern Ocean be linked to the underlying aerosol environment? 4. How do the aerosol properties at the surface vary spatially and seasonally over the high latitude Southern Ocean and what processes control these features? 5. How well defined are the atmospheric compositional boundaries between Southern Ocean marine, Antarctic free tropospheric, and Antarctic surface airmasses, and how does this influence the chemistry and physics of the Southern Ocean atmosphere? In this project we published three peer review journal articles that address these questions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Validation of Exploding Wire Tests Using Alegra-NG

Exploding wire tests are used to characterize materials undergoing high voltage loading and to validate computational models in a simple configuration. In this report, the materials emphasized are gold, aluminum, copper and nickel wires. Model validation is presented using the nominal model (no uncertainty) in the form of heat maps (per material) that show model bias across scalar quantities and initial voltage. Mesh convergence and uncertainty quantification is also presented.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Evaluation of interactive and prescribed agricultural ammonia emissions for simulating atmospheric composition in CAM-chem

Abstract. Ammonia (NH3) plays a central role in the chemistry of inorganic secondary aerosols in the atmosphere. The largest emission sector for NH3 is agriculture, where NH3 is volatilized from livestock wastes and fertilized soils. Although the NH3 volatilization from soils is driven by the soil temperature and moisture, many atmospheric chemistry models prescribe the emission using yearly emission inventories and climatological seasonal variations. Here we evaluate an alternative approach where the NH3 emissions from agriculture are simulated interactively using the process model FANv2 (Flow of Agricultural Nitrogen, version 2) coupled to the Community Atmospheric Model with Chemistry (CAM-chem). We run a set of 6-year global simulations using the NH3 emission from FANv2 and three global emission inventories (EDGAR, CEDS and HTAP) and evaluate the model performance using a global set of multi-component (atmospheric NH3 and NH4+, and NH4+ wet deposition) in situ observations. Over East Asia, Europe and North America, the simulations with different emissions perform similarly when compared with the observed geographical patterns. The seasonal distributions of NH3 emissions differ between the inventories, and the comparison to observations suggests that both FANv2 and the inventories would benefit from more realistic timing of fertilizer applications. The largest differences between the simulations occur over data-scarce regions. In Africa, the emissions simulated by FANv2 are 200 %–300 % higher than in the inventories, and the available in situ observations from western and central Africa, as well as NH3 retrievals from the Infrared Atmospheric Sounding Interferometer (IASI) instrument, are consistent with the higher NH3 emissions as simulated by FANv2. Overall, in simulating ammonia and ammonium concentrations over regions with detailed regional emission inventories, the inventories based on these details (HTAP, CEDS) capture the atmospheric concentrations and their seasonal variability the best. However these inventories cannot capture the impact of meteorological variability on the emissions, nor can these inventories couple the emissions to the biogeochemical cycles and their changes with climate drivers. Finally, we show with sensitivity experiments that the simulated time-averaged nitrate concentration in air is sensitive to the temporal resolution of the NH3 emissions. Over the CASTNET monitoring network covering the US, resolving the NH3 emissions hourly instead monthly reduced the positive model bias from approximately 80 % to 60 % of the observed yearly mean nitrate concentration. This suggests that some of the commonly reported overestimation of aerosol nitrate over the US may be related to unresolved temporal variability in the NH3 emissions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Characterization of HRRR-simulated rotor layer wind speeds and clouds along the coast of California

Stratocumulus clouds, with their low cloud base and top, affect the atmospheric boundary layer wind and turbulence profile, thereby modulating wind energy resources. GOES satellite data reveal an abundance of stratocumulus clouds in the late spring and summer months off the coast of northern and central California, where there are active plans to deploy floating offshore wind farms at two lease areas (near Morro Bay and Humboldt). Since the fall of 2020, two buoys equipped with multiple instruments, including Doppler lidar, have been deployed for about 1 year in these wind farm lease areas to assess the rotor layer wind conditions in these locations. The objective of this study is to evaluate how well the High-Resolution Rapid Refresh (HRRR) model represents stratocumulus cloud characteristics and turbine-relevant rotor layer winds (surface to 300 m) by comparing HRRR simulations with buoy and satellite observations. We first find that the HRRR model reproduces the seasonal cycle of cloud top height reasonably well in these regions. However, during the warm season – especially at Morro Bay – the HRRR-simulated stratocumulus clouds tend to have lower tops by about 150 m and exhibit weaker diurnal cycles than satellite observations. Our analysis also shows that rotor layer wind speeds and vertical shear are stronger at Humboldt than at Morro Bay, and both are generally stronger under clear-sky conditions. Finally, the HRRR model bias in rotor layer wind speed is small under cloudy conditions but larger and dependent on observed wind speed under clear skies. Specifically, HRRR underestimates wind speeds at Morro Bay and overestimates them at Humboldt under clear-sky conditions.

17 WIND ENERGY↗
NASA NTRS1977

NASTRAN finite element idealization study

The investigation of the effects of variations of mesh refinement and mesh pattern were conducted using a basic rectangular mesh pattern. When employing the constant strain TRMEM element, the basic rectangular pattern was subdivided into triangles. This subdivision employs two different triangular patterns and allows results to be obtained which demonstrate the effect of modelling bias. Errors in tip deflection, direct stress, and shearing stress as a function of mesh size and element aspect ratio were obtained as well as mid-span stress distributions. All problems were solved on an IBM 360/95 computer using MacNeal-Schwendler Version MSC-38 Rigid Format-1 of the NASTRAN computer program. While NASTRAN uses double precision arithmetic for the solution of the global equations for displacements, subsequent computations to obtain element stresses are carried out in single precision. This suggests that some improvement in stress recovery might be expected when using the higher precision DCD machines.

Case, W. R.↗
NASA NTRS1984

LANDSAT-4 MSS Geometric Correction: Methods and Results

An automated image registration system such as that developed for LANDSAT-4 can produce all of the information needed to verify and calibrate the software and to evaluate system performance. The on-line MSS archive generation process which upgrades systematic correction data to geodetic correction data is described as well as the control point library build subsystem which generates control point chips and support data for on-line upgrade of correction data. The system performance was evaluated for both temporal and geodetic registration. For temporal registration, 90% errors were computed to be .36 IFOV (instantaneous field of view) = 82.7 meters) cross track, and .29 IFOV along track. Also, for actual production runs monitored, the 90% errors were .29 IFOV cross track and .25 IFOV along track. The system specification is .3 IFOV, 90% of the time, both cross and along track. For geodetic registration performance, the model bias was measured by designating control points in the geodetically corrected imagery.

Brooks, J.↗
NASA NTRS1992

Cosmic microwave background probes models of inflation

Inflation creates both scalar (density) and tensor (gravity wave) metric perturbations. We find that the tensor-mode contribution to the cosmic microwave background anisotropy on large-angular scales can only exceed that of the scalar mode in models where the spectrum of perturbations deviates significantly from scale invariance. If the tensor mode dominates at large-angular scales, then the value of DeltaT/T predicted on 1 deg is less than if the scalar mode dominates, and, for cold-dark-matter models, bias factors greater than 1 can be made consistent with Cosmic Background Explorer (COBE) DMR results.

Davis, Richard L.↗
NASA NTRS1992

A redshift survey of IRAS galaxies. V - The acceleration on the Local Group

The acceleration on the Local Group is calculated based on a full-sky redshift survey of 5288 galaxies detected by IRAS. A formalism is developed to compute the distribution function of the IRAS acceleration for a given power spectrum of initial perturbations. The computed acceleration on the Local Group points 18-28 deg from the direction of the Local Group peculiar velocity vector. The data suggest that the CMB dipole is indeed due to the motion of the Local Group, that this motion is gravitationally induced, and that the distribution of IRAS galaxies on large scales is related to that of dark matter by a simple linear biasing model.

Strauss, Michael A.↗
NASA NTRS1992

Clustering, randomness and regularity in cloud fields. I - Theoretical considerations. II - Cumulus cloud fields

The current controversy existing in reference to the regularity vs. clustering in cloud fields is examined by means of analysis and simulation studies based upon nearest-neighbor cumulative distribution statistics. It is shown that the Poisson representation of random point processes is superior to pseudorandom-number-generated models and that pseudorandom-number-generated models bias the observed nearest-neighbor statistics towards regularity. Interpretation of this nearest-neighbor statistics is discussed for many cases of superpositions of clustering, randomness, and regularity. A detailed analysis is carried out of cumulus cloud field spatial distributions based upon Landsat, AVHRR, and Skylab data, showing that, when both large and small clouds are included in the cloud field distributions, the cloud field always has a strong clustering signal.

Weger, R. C.↗
NASA NTRS2001

The Effect of Errors in Snow Assimilation on Land Surface Modeling

The accurate portrayal of the hydrological cycle is extremely important in land surface modeling. Central to this effort is the treatment of snow, as errors in the representation of this quantity can impact practically all other modeled quantities through alterations in the water and energy balances. Although land surface model (LSM) simulations can benefit from the assimilation of snow cover and snow depth observations, they can be negatively impacted if such observations contain errors or if a model bias exists in the simulation of surface or soil temperatures. Both cases may lead to excessive melting or growth of snow packs, and to large alterations in both the energy and water balances. Such problems in the snow assimilation process, made evident by the repeated melting and replenishing of snow pack over significant areas of the United States, exists in the Eta Data Assimilation System and is a product of the EDAS system's direct insertion assimilation of snow data. Occurring on a 24 hour cycle, the repeated melting infuses the soil column with a large quantity of water that upsets the hydrological cycle. In an effort to quantify the impacts of such errors in snow assimilation on water and energy budgets, a series of Mosaic LSM simulations were performed over the 12 month period covering October 1998 to October 1999.

Cosgrove, Brian A.↗
NASA NTRS2001

Recent Developments in DAO's Finite-Volume Data Assimilation System

The Physical-space/Finite-volume Data Assimilation System (fvDAS) is the next generation global atmospheric data assimilation system in development at the Data Assimilation Office at NASA's Goddard Space Flight Center. It is based on a new finite-volume general circulation model jointly developed by NASA and NCAR and on the Physical-Space Statistical Analysis System (PSAS) developed at the DAO. The data assimilation method implemented in CODAS incorporates a simplified version of the model bias estimation and correction algorithm, as described by Dee and da Silva (1998). In this talk we will briefly describe the general system formulation, and focus on the impact of 3 data types recently introduced, namely: 1) cloud tracks winds from the Multi-angle Imaging Spectrometer by the US Air Force, and 3) temperature and moisture information derived from GPS refractivity occultation measurements. The impact of these data types on observation-minus-6hr forecast (O-F) statistics, as well as 5-day forecast skills will be discussed. In addition we will assess the impact of cloud assimilation on top of the atmosphere radiation fields estimated from CERES measurements.

daSilva, Arlindo↗
NASA NTRS2002

Response Surface Modeling of Combined-Cycle Propulsion Components using Computational Fluid Dynamics

Three examples of response surface modeling with CFD are presented for combined cycle propulsion components. The examples include a mixed-compression-inlet during hypersonic flight, a hydrogen-fueled scramjet combustor during hypersonic flight, and a ducted-rocket nozzle during all-rocket flight. Three different experimental strategies were examined, including full factorial, fractionated central-composite, and D-optimal with embedded Plackett-Burman designs. The response variables have been confined to integral data extracted from multidimensional CFD results. Careful attention to uncertainty assessment and modeling bias has been addressed. The importance of automating experimental setup and effectively communicating statistical results are emphasized.

Steffen, C. J., Jr.↗
NASA NTRS2002

On the Issue of Excess Lower Stratospheric Subtropical Transport in GEOS-DAS

In recent years, data assimilation has become an indispensable tool for our understanding of the global features of meteorological variables. However, assessments of transport characteristics using trajectory related methods as well as chemical transport models (CTMs) show that results derived from assimilated (or analyzed) winds exhibit significantly larger mixing and entrainment rates compared to results derived from GCM winds, which are closer to results derived from observations (e.g., Douglass et al., 2002; Schoeberl et al., 2002). This discrepancy presents a serious challenge to our ability to understand and model global trace gas transport and distribution. We use the GEOS-DAS to explore this issue by examining how the process of data assimilation alters the dynamics of the underlying GCM and how this leads to the excess of lower stratospheric mixing and transport in the subtropics. In particular, we show that significant model biases in tropical winds necessitate large analysis increments. These increments directly force large subtropical regions of instability with negative PV gradient on the one hand, and generate excessive noise in the tropical wind fields on the other. The result is an excess of transport in the lower stratospheric subtropics.

Tan, Wei-Wu↗
NASA NTRS2004

Air Mass Factor Formulation for Spectroscopic Measurements from Satellites: Application to Formaldehyde Retrievals from the Global Ozone Monitoring Experiment

We present a new formulation for the air mass factor (AMF) to convert slant column measurements of optically thin atmospheric species from space into total vertical columns. Because of atmospheric scattering, the AMF depends on the vertical distribution of the species. We formulate the AMF as the integral of the relative vertical distribution (shape factor) of the species over the depth of the atmosphere, weighted by altitude-dependent coefficients (scattering weights) computed independently from a radiative transfer model. The scattering weights are readily tabulated, and one can then obtain the AMF for any observation scene by using shape factors from a three dimensional (3-D) atmospheric chemistry model for the period of observation. This approach subsequently allows objective evaluation of the 3-D model with the observed vertical columns, since the shape factor and the vertical column in the model represent two independent pieces of information. We demonstrate the AMF method by using slant column measurements of formaldehyde at 346 nm from the Global Ozone Monitoring Experiment satellite instrument over North America during July 1996. Shape factors are cumputed with the Global Earth Observing System CHEMistry (GEOS-CHEM) global 3-D model and are checked for consistency with the few available aircraft measurements. Scattering weights increase by an order of magnitude from the surface to the upper troposphere. The AMFs are typically 20-40% less over continents than over the oceans and are approximately half the values calculated in the absence of scattering. Model-induced errors in the AMF are estimated to be approximately 10%. The GEOS-CHEM model captures 50% and 60% of the variances in the observed slant and vertical columns, respectively. Comparison of the simulated and observed vertical columns allows assessment of model bias.

Palmer, Paul I.↗
NASA NTRS2010

Observing System Variations Effect on Reanalyses

Reanalyses integrate multitudes of satellite and conventional observations data assimilation and numerical weather prediction. The result is that many disparate observation platforms, discontinuous in space and time, lead to complete and consistent representations the state of the weather. The component also provides physical fields rarely or never observed. However, the numerical model bias is continuously being corrected by the observational analysis, and this bias changes as variations in the observations occur. NASA's Modern Era Retrospective-analysis for Research and Applications (MERRA) sensitivity to variations in the observing systems are explored. Specifically, we will evaluate the water budget and transport processes as they relate to the advent of SSM/I and AMSU-A radiance assimilation, and an additional case of radiosonde station that exhibits a dramatic shift in mean water states. The MERRA input observation data, now available online, is used to explore these variations.

Bosilovich, Michael G.↗
NASA NTRS2012

What Have We Learned from MERRA about Reanalyses of the Stratosphere?

The Modern-Era Retrospective analysis for Research and Applications (MERRA) reanalysis includes a well-resolved middle atmosphere. The upper boundary of the underlying model is in the mesosphere, near 80km, and the input data streams include the Stratospheric Sounding Unit (SSU) and Advanced Microwave Sounding Unit (AMSU) radiance observations. These two datasets provide observational constraints on the deep-layer thermal structure in approximately the 10-2hPa region, the middle to upper stratosphere, which is above the highest range of most radiosonde ascents. This analysis will focus on the difficulties of producing realistic analyses in the middle to upper stratosphere: these arise largely because of vertical averaging inherent in the AMSU and SSU observations, the sensitivity to model biases in this region, the relative biases among the same channels on different instruments, and the orbital sampling of the satellites (morning or afternoon orbits). These issues will be illustrated with examples from MERRA and enhanced by discussions of potential ways of improving the middle atmosphere in future reanalyses.

Pawson, Steven↗