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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Reconciling Simulated and Observed Views of Clouds: MODIS, ISCCP, and the Limits of Instrument Simulators in Climate Models

The properties of clouds that may be observed by satellite instruments, such as optical depth and cloud top pressure, are only loosely related to the way clouds are represented in models of the atmosphere. One way to bridge this gap is through "instrument simulators," diagnostic tools that map the model representation to synthetic observations so that differences between simulator output and observations can be interpreted unambiguously as model error. But simulators may themselves be restricted by limited information available from the host model or by internal assumptions. This work examines the extent to which instrument simulators are able to capture essential differences between MODIS and ISCCP, two similar but independent estimates of cloud properties. We focus on the stark differences between MODIS and ISCCP observations of total cloudiness and the distribution of cloud optical thickness can be traced to different approaches to marginal pixels, which MODIS excludes and ISCCP treats as homogeneous. These pixels, which likely contain broken clouds, cover about 15% of the planet and contain almost all of the optically thinnest clouds observed by either instrument. Instrument simulators can not reproduce these differences because the host model does not consider unresolved spatial scales and so can not produce broken pixels. Nonetheless, MODIS and ISCCP observation are consistent for all but the optically-thinnest clouds, and models can be robustly evaluated using instrument simulators by excluding ambiguous observations.

Pincus, Robert↗
DOE OSTI2020

Advancing the science of explosive fragmentation and afterburn fireballs though experiments and simulations at the benchtop scale

Detonation of explosive devices produces extremely hazardous fragments and hot, luminous fireballs. Prior experimental investigations of these post-detonation environments have primarily considered devices containing hundreds of grams of explosives. While relevant to many applications, such large- scale testing also significantly restricts experimental diagnostics and provides limited data for model validation. As an alternative, the current work proposes experiments and simulations of the fragmentation and fireballs from commercial detonators with less than a gram of high explosive. As demonstrated here, reduced experimental hazards and increased optical access significantly expand the viability of advanced imaging and laser diagnostics. Notable developments include the first known validation of MHz-rate optical fragment tracking and the first ever Coherent Anti-Stokes Raman Scattering (CARS) measures of post-detonation fireball temperatures. While certainly not replacing the need for full-scale verification testing, this work demonstrates new opportunities to accelerate developments of diagnostics and predictive models of post-detonation environments.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2022

Diagnostics for Linac Optimization With Machine Learning

The Fermilab Linac delivers 400 MeV H- beam to the rest of the accelerator chain. Providing stable intensity, energy, and emittance is key since it directly affects downstream machines. To counter fluctuations of Linac output due to various effects to be described below we are working on implementing dynamic longitudinal parameter optimization based on Machine Learning (ML). As inputs for the ML model, signals from beam diagnostics have to be well understood and reliable. In this paper we discuss the status and plans for ML-based optimization as well as preliminary results of diagnostics studies.

43 PARTICLE ACCELERATORS↗
DOE OSTI2016

Modeling and Validation of Sodium Plugging for Heat Exchangers in Sodium-cooled Fast Reactor Systems

The project “Modeling and Validation of Sodium Plugging for Heat Exchangers in Sodium-cooled Fast Reactor Systems” was conducted jointly by Westinghouse Electric Company (Westinghouse) and Argonne National Laboratory (ANL), over the period October 1, 2013- March 31, 2016. The project’s motivation was the need to provide designers of Sodium Fast Reactors (SFRs) with a validated, state-of-the-art computational tool for the prediction of sodium oxide (Na 2 O) deposition in small-diameter sodium heat exchanger (HX) channels, such as those in the diffusion bonded HXs proposed for SFRs coupled with a supercritical CO 2 (sCO 2 ) Brayton cycle power conversion system. In SFRs, Na 2 O deposition can potentially occur following accidental air ingress in the intermediate heat transport system (IHTS) sodium and simultaneous failure of the IHTS sodium cold trap. In this scenario, oxygen can travel through the IHTS loop and reach the coldest regions, represented by the cold end of the sodium channels of the HXs, where Na 2 O precipitation may initiate and continue. In addition to deteriorating HX heat transfer and pressure drop performance, Na 2 O deposition can lead to channel plugging especially when the size of the sodium channels is small, which is the case for diffusion bonded HXs whose sodium channel hydraulic diameter is generally below 5 mm. Sodium oxide melts at a high temperature well above the sodium melting temperature such that removal of a solid plug such as through dissolution by pure sodium could take a lengthy time. The Sodium Plugging Phenomena Loop (SPPL) was developed at ANL, prior to this project, for investigating Na 2 O deposition phenomena within sodium channels that are prototypical of the diffusion bonded HX channels envisioned for SFR-sCO 2 systems. In this project, a Computational Fluid Dynamic (CFD) model capable of simulating the thermal-hydraulics of the SPPL test section and provided with Na 2 O deposition prediction capabilities, was developed. This state-of-the-art computational tool incorporates a first-principles Na 2 O deposition model developed by ANL, and combines it with predictive capabilities for the spatial and temporal variation of temperature, velocity, dissolved oxygen concentration, and wall temperature under flowing sodium conditions. The CFD model was validated under no-deposition conditions using experimental data collected with the SPPL, demonstrating the model’s capability to predict the thermal-hydraulics of the SPPL test section within the measurement uncertainty characterizing the SPPL instrumentation. The model’s deposition prediction capability was not, however, validated as the SPPL could not be operated under plugging conditions during the project, resulting in the lack of deposition data with adequate pedigree for a CFD model validation. Two novel diagnostic techniques to detect and characterize Na 2 O deposits, i.e. Ultrasonic Time Domain Reflectometry (UTDR) and Potential Drop (PD) techniques, were developed to ultimately assist in the validation effort under plugging conditions, which can be performed once the SPPL becomes operational. This development effort consisted first in demonstrating, analytically and/or computationally, the capability of these techniques to diagnose Na 2 O deposits inside of small channels (particularly the deposit’s thickness), and subsequently in the fabrication and testing of prototypical UTDR and PD instrumentation. The testing, performed on mockups of the SPPL test section, demonstrated the capability of these techniques to detect and characterize material discontinuities like those induced by sodium oxide deposition on stainless steel channel walls. Because of the mentioned impossibility to run the SPPL in a plugging mode, the developed instrumentation could not be tested in-situ, i.e. at the SPPL while deposits are being formed inside of the SPPL test section. Recommended future work includes a possible enhancement in the CFD modeling technique and installation of the developed UTDR and PD instrumentation on the test section, followed by plugging tests to be conducted with the SPPL. The installation of the UTDR and PD diagnostic instrumentation on the SPPL test section will allow collection of Na 2 O deposition data after the onset of deposition to nearly complete channel plugging, which can ultimately be used for the validation of the CFD model.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

AMPPED LDRD: Advanced Models of the Physics & Phenomena of Electrical Discharge.

This Laboratory Directed Research and Development (LDRD) project aimed at addressing an unmet need for physics-based models that enable prediction of electrical breakdown in the presence of high voltage gradients and real-world environments. This project focused on understanding coupled plasma-surface feedback phenomena critical to electrical discharge processes and design of breakdown voltages, breakdown times, and breakdown paths. New secondary electron emission and coupled plasma-surface measurement methods and models were developed. Highly reproducible discharge experiments were developed to provide current-voltage data as a function of time, and methods were developed to condition electrodes for predictable discharge. To assess plasma-surface feedback mechanisms, new surface physics capabilities, including measurement systems for local and global photoemission yield and ion-induced secondary electron emission yield were developed. Discharge models were developed to incorporate these yields for predicting discharge behavior to understand influence of surface physics on discharge current and time evolution, and methods to accelerate these simulations were demonstrated. A key finding was that the initiation process of a non-vacuum discharge appears highly dependent on photoemission at the cathode. Advanced diagnostics were developed, including spatial electrical field imaging, spectroscopy of plasmas, and high-speed imaging of discharge event s in metal and dielectric environments. These diagnostics and improved electrical models are a step toward enabling quantitative design margins, assurance of safety architectures, and implementation of novel materials and technologies for wide ranging energy and electronics applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Empirical Modeling of Direct Expansion (DX) Cooling System for Multiple Research Use Cases

This study provides a general procedure to generate a direct expansion (DX) cooling coil system for a roof top unit (RTU), which is a typical heating ventilation and air-conditioning (HVAC) system for commercial buildings in the United States. Experimental data from a full-scale unoccupied 2-story commercial building is used for the HVAC modeling. The regression for identifying the model coefficients was carried out with multiple stages, and the results were validated with measured data. The model’s applicability was evaluated with multiple case studies, including a building energy simulation (BES) program validation, model-based predictive control (MPC), and fault diagnostics and detection (FDD).

42 ENGINEERING↗
NASA NTRS1980

Eigenvector analysis of some observed and model-generated Climatological fields

An empirical orthogonal function analysis of monthly mean synoptic fields computed with a general circulation model and the corresponding observed climatological patterns is presented. A computer program was used to compute the principal components of the data matrices representing global maps of various observed and model-generated climatological fields. The variables analyzed were: 500mb geopotential height, 850 mb temperature, and sea level pressure. It is concluded that eigenvector analysis of observed and model-generated synoptic climatological fields is a useful diagnostic aid in the evaluation of global model simulation. The maps of any climatological variables are readily decomposed into a few orthogonal components which account for a large fraction of the total spatial variance, and the observed and model-generated patterns may then be compared in terms of these principal components of the original data matrices.

Dennis, M.↗
NASA NTRS1991

Theoretical H II region models - The effects of stellar atmosphere models

Several grids of theoretical H II region models are computed by photoionization modeling in order to determine the extent to which the choice of the ionizing stellar atmosphere model affects the calibration of emission-line diagnostic diagrams of Evans and Dopita (1985) and the semiempirical H II region abundance sequence calibration of Evans and Dopita. Emission-line diagnostic diagrams are presented and compared for model nebulae ionized by Hummer and Mihalas (1970) unblanketed LTE atmospheres, Kurucz (1979) line-blanketed LTE atmospheres, Mihalas (1972) unblanketed non-LTE, and a truncated blackbody spectrum. The models demonstrate that for solar nebular and atmospheric abundances, there are only minor differences between H II models ionized by the Hummer and Mihalas atmospheres. The unblanketed non-LTE stellar atmosphere models of Mihalas and truncated blackbody spectra are shown to be unsuitable for general H II region modelling.

Evans, I. N.↗
NASA NTRS2020

Metrics for Improved Reanalyses in Polar Regions

Atmospheric reanalyses are widely used for a variety of scientific endeavors in the Arctic and Antarctic. Reanalyses are used as boundary conditions for a regional and process-based models, for climate model validation, and for diagnostic analysis of physical processes, weather and climatic events. However, reanalyses are typically global and often do not account for specific, regional considerations, such as for polar regions. In this work, we provide a brief evaluation of a prototype for a new GMAO reanalysis, which incorporates higher spatial resolution, an updated approach for data assimilation, and a revised atmospheric model. We identify differences in the representation of the Arctic atmosphere in comparison to recent reanalyses. Furthermore, we provide a forum for Arctic scientists to consider the future improvements for reanalyses, and seek feedback for the following questions: 1) What are important performance factors to consider in evaluating new reanalyses? 2) What physical processes should be incorporated into new reanalyses? 3) What spatio-temporal scales should be considered?

Parker, Chelsea L.↗
NASA NTRS1999

Predicting Decade-to-Century Climate Change: Prospects for Improving Models

Recent research has led to a greatly increased understanding of the uncertainties in today's climate models. In attempting to predict the climate of the 21st century, we must confront not only computer limitations on the affordable resolution of global models, but also a lack of physical realism in attempting to model key processes. Until we are able to incorporate adequate treatments of critical elements of the entire biogeophysical climate system, our models will remain subject to these uncertainties, and our scenarios of future climate change, both anthropogenic and natural, will not fully meet the requirements of either policymakers or the public. The areas of most-needed model improvements are thought to include air-sea exchanges, land surface processes, ice and snow physics, hydrologic cycle elements, and especially the role of aerosols and cloud-radiation interactions. Of these areas, cloud-radiation interactions are known to be responsible for much of the inter-model differences in sensitivity to greenhouse gases. Recently, we have diagnostically evaluated several current and proposed model cloud-radiation treatments against extensive field observations. Satellite remote sensing provides an indispensable component of the observational resources. Cloud-radiation parameterizations display a strong sensitivity to vertical resolution, and we find that vertical resolutions typically used in global models are far from convergence. We also find that newly developed advanced parameterization schemes with explicit cloud water budgets and interactive cloud radiative properties are potentially capable of matching observational data closely. However, it is difficult to evaluate the realism of model-produced fields of cloud extinction, cloud emittance, cloud liquid water content and effective cloud droplet radius until high-quality measurements of these quantities become more widely available. Thus, further progress will require a combination of theoretical and modeling research, together with intensified emphasis on both in situ and space-based remote sensing observations.

Somerville, Richard C. J.↗
DOE OSTI2023

Large Ensemble Diagnostic Evaluation of Hydrologic Parameter Uncertainty in the Community Land Model Version 5 (CLM5)

Abstract Land surface models such as the Community Land Model version 5 (CLM5) seek to enhance understanding of terrestrial hydrology and aid in the evaluation of anthropogenic and climate change impacts. However, the effects of parametric uncertainty on CLM5 hydrologic predictions across regions, timescales, and flow regimes have yet to be explored in detail. The common use of the default hydrologic model parameters in CLM5 risks generating streamflow predictions that may lead to incorrect inferences for important dynamics and/or extremes. In this study, we benchmark CLM5 streamflow predictions relative to the commonly employed default hydrologic parameters for 464 headwater basins over the conterminous United States (CONUS). We evaluate baseline CLM5 default parameter performance relative to a large (1,307) Latin Hypercube Sampling‐based diagnostic comparison of streamflow prediction skill using over 20 error measures. We provide a global sensitivity analysis that clarifies the significant spatial variations in parametric controls for CLM5 streamflow predictions across regions, temporal scales, and error metrics of interest. The baseline CLM5 shows relatively moderate to poor streamflow prediction skill in several CONUS regions, especially the arid Southwest and Central U.S. Hydrologic parameter uncertainty strongly affects CLM5 streamflow predictions, but its impacts vary in complex ways across U.S. regions, timescales, and flow regimes. Overall, CLM5's surface runoff and soil water parameters have the largest effects on simulated high flows, while canopy water and evaporation parameters have the most significant effects on the water balance.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Examination of L-Band Brightness Temperature Forecasts in the SMAP Level-4 Soil Moisture Analysis

The NASA Soil Moisture Active Passive (SMAP) mission [4] has been providing L-band (1.4 GHz) passive microwave brightness temperature (Tb) observations since April 2015. By assimilating the Tb observations into the NASA Catchment land surface model [5] using a spatially distributed ensemble Kalman filter, the NASA Global Modeling and Assimilation Office generates the SMAP Level-4 Soil Moisture (L4_SM) product, which provides global, 3-hourly, 9-km resolution estimates of surface (0-5 cm) and root-zone (0-100 cm) soil moisture with ~2.5-day latency for use in research and applications [6]. The L4_SM product also includes estimates of soil temperature, land surface fluxes, and assimilation diagnostics such as the model forecast and observed Tb values [7]. The output from the L4_SM system is routinely monitored by the L4_SM team. Such monitoring provides valuable information; instances of unusually large Tb observation-minus-forecast (O-F) residuals can indicate events during which soil moisture conditions are poorly described in the land modeling system [7,8]. For example, repeated occurrences of very large Tb O-F values in central Australia were traced back to deficiencies in the gauge-based precipitation product used in the land modeling system through L4_SM Version 5; this discovery prompted the use, beginning in Version 6, of satellite- and gauge-based precipitation observations outside of North America [9]. Recently, a statistical analysis of the Tb O-F residuals revealed systematic errors in the “tau-omega” L-band radiative transfer model that converts the land-model simulated soil moisture and temperature into the forecast Tb prior to the L4_SM analysis. The L4_SM analysis is built on the ensemble Kalman filter and assumes unbiased forecast errors. The presence of systematic Tb forecast errors could thus adversely impact the quality of the analyzed soil moisture. In this paper, we examine the Tb O-F residuals of the latest Version 7 L4_SM data (Science Version ID Vv7030 and Vv7032) [10,11,12]. In the L4_SM Version 7 algorithm, key parameters of the L-band radiative transfer model, including soil roughness, scattering albedo, and a (seasonally varying) climatology of vegetation opacity, are obtained from the SMAP Level-2 Radiometer retrieval product (Version 5) [1]. Additionally, we also use ground measurements of surface soil moisture and soil temperature from the SMAP core validation sites as in situ reference of soil conditions [2,3]. As part of the L4_SM system calibration, the seasonally-varying bias between the model forecast Tb and the observed values is removed prior to the assimilation of the SMAP Tb observations [7]. That is, the L4_SM system is designed to only correct errors in synoptic-scale and interannual variations from the long-term mean seasonal cycle while maintaining the model’s (potentially erroneous) climatology. The Tb O-F residuals examined here are thus computed using SMAP Tb observations after they are rescaled to the mean seasonal cycle of Tb from the modeling system without SMAP data assimilation. Consequently, the long-term average of the Tb O-F residuals has a global mean of only 0.13 K and locally small values, ranging from -1 to 3 K. Despite the small time-average values of the Tb O-F residuals, the model forecast Tb was nevertheless found to exhibit undesirable systematic errors. At some locations, the time-average Tb O-F values strongly depend on surface soil moisture (SM). At the Yanco SMAP core validation site, for example, the Tb O-F residuals typically range from 5 to 15 K under dry soil moisture conditions (SM < 0.15 m3 m-3) yet are predominantly negative under wet soil moisture conditions (SM > 0.25 m3 m-3), with values ranging from 0 to -40 K. This results in soil moisture analysis increments that persistently make the soil drier under dry SM conditions and persistently make the soil wetter under wet SM conditions, suggesting an error in the dynamic range of the simulated Tb, soil moisture or soil temperature. In this paper, we describe the higher-order systematic Tb forecast errors in more detail, examine their impact on the L4_SM product quality, and explore potential avenues to further improve the L4_SM algorithm.

Rolf Reichle↗
DOE OSTI2019

Experimental and synthetic measurements of polarized synchrotron emission from runaway electrons in Alcator C-Mod

This paper presents the first experimental analysis of polarized synchrotron emission from relativistic runaway electrons (REs) in a tokamak plasma. Importantly, we show that the polarization information of synchrotron radiation can be used to diagnose spatially-localized RE pitch angle distributions. Synchrotron-producing REs were generated during low density, Ohmic, diverted plasma discharges in the Alcator C-Mod tokamak. The ten-channel Motional Stark Effect diagnostic was used to measure spatial profiles of the polarization angle and the fraction of detected light that was linearly-polarized. Spatial transitions in the polarization angle of 90 degrees---from horizontal to vertical polarization and vice versa---are observed in experimental data and are well-explained by the gyro-motion of REs and high directionality of synchrotron radiation. Polarized synchrotron emission is modeled with the synthetic diagnostic SOFT; its output Green's (or detector response) functions reveal a critical RE pitch angle at which the polarization angle flips by 90 degrees and the polarization fraction is minimal. Using SOFT, we determine the dominant RE pitch angle which reproduces measured polarization angle and fraction values. The spatiotemporal evolutions of the polarization angle and fraction are explored in detail for one C-Mod discharge. For channels viewing REs near the magnetic axis and flux surfaces q = 1 and 4/3, disagreements between synthetic and experimental signals suggest that the sawtooth instability may be influencing RE dynamics. Furthermore, other sources of pitch angle scattering, not considered in this analysis, could help explain discrepancies between simulation and experiment.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Experimental and synthetic measurements of polarized synchrotron emission from runaway electrons in Alcator C-Mod

This paper presents the first experimental analysis of polarized synchrotron emission from relativistic runaway electrons (REs) in a tokamak plasma. Importantly, we show that the polarization information of synchrotron radiation can be used to diagnose spatially-localized RE pitch angle distributions. Synchrotron-producing REs were generated during low density, Ohmic, diverted plasma discharges in the Alcator C-Mod tokamak. The ten-channel motional Stark effect diagnostic was used to measure spatial profiles of the polarization angle θ pol and the fraction f pol of detected light that was linearly-polarized. Spatial transitions in θ pol of 90° —from horizontal to vertical polarization and vice versa—are observed in experimental data and are well-explained by the gyro-motion of REs and high directionality of synchrotron radiation. Here polarized synchrotron emission is modeled with the synthetic diagnostic Soft; its output Green's (or detector response) functions reveal a critical RE pitch angle at which θ pol flips by 90° and f pol is minimal. Using Soft, we determine the dominant RE pitch angle which reproduces measured θ pol and f pol values. The spatiotemporal evolutions of θ pol and f pol are explored in detail for one C-Mod discharge. For channels viewing REs near the magnetic axis and flux surfaces q = 1 and 4/3, disagreements between synthetic and experimental signals suggest that the sawtooth instability may be influencing RE dynamics. Furthermore, other sources of pitch angle scattering, not considered in this analysis, could help explain discrepancies between simulation and experiment.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Effect of higher-order multipole moments on the Stark line shape

Spectral line shapes are sensitive to plasma conditions and are often used to diagnose electron density of laboratory plasmas as well as astrophysical plasmas. Stark line-shape models take into account the perturbation of the radiator’s energy structure due to the Coulomb interaction with the surrounding charged particles. Solving this Coulomb interaction is challenging and is commonly approximated via a multipole expansion. Yet, most models include only up to the second term of the expansion (the dipole term). While there have been studies on the higher-order terms due to one of the species (i.e. either ions or electrons), there is no model that includes the terms beyond dipole from both species. Here, we investigate the importance of the higher-order multipole terms from both species on the Hβ line shape. First, we find that it is important to include higher order terms consistently from both ions and electrons to reproduce measured line-shape asymmetry. Next, we study the line shape convergence with the higher-order terms at 1017, 1018, and 1019 e/cc. We discover that the line shape calculated with the dipole-only approximation becomes inaccurate as density increases. It is necessary to include only up to the third (quadrupole) term to compute the line-shape accurately within 2%. Since most existing models include only the dipole terms, the densities inferred with such models are in question. Finally, we investigate the impact of neglecting the quadrupole terms on density diagnostics. We find that the model without the quadrupole term slightly underestimates the density, and the discrepancy becomes as large as 12% at high densities. Although the case of study is limited to Hβ , we expect similar impact on other lines.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS2012

Estimating Model Error Using Observation Residuals

This presentation discusses an approach to estimate model error using observation residuals. Based on the sequential fixed-lag smoother; we introduce a diagnostic procedure to allow estimating model error over a dense observing system. Optimality considerations are examined in light of the sequential results. The procedure is re-interpreted in the language of variational assimilation, such as 4d-Var. Illustrations of the approach are given by studying both identical-twin and fraternal-twin experimental settings for a system governed by Lorenz-type dynamics. Preliminary results by looking at observation residual statistics for the ECMWF data assimilation system are also shown. The presentation will be part of a series of discussions on issues related to four-dimensional data assimilation under weak-constraint and methodologies to estimate model error.

Todling, Ricardo↗
DOE OSTI2019

A Global Hydrologic Framework to Accelerate Scientific Discovery

With the ability to simulate historical and future global water availability on a monthly time step at a spatial resolution of 0.5 geographic degree, the Python package Xanthos version 1 provided a solid foundation for continuing advancements in global water dynamics science. The goal of Xanthos version 2 was to build upon previous investments by creating a Python framework where core components of the model (potential evapotranspiration (PET), runoff generation, and river routing) could be interchanged or extended without having to start from scratch. Xanthos 2 utilizes a component-style architecture which enables researchers to quickly incorporate and test cutting-edge research in a stable modeling environment prebuilt with diagnostics. Major advancements for Xanthos 2 were also achieved by the creation of a robust default configuration with a calibration module, hydropower modules, and new PET modules, which are now available to the scientific community.

GCAM, Xanthos, global hydrology, modeling↗