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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 901 records · Page 50
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Evaluating Uncertainties in Marine Biogeochemical Models: Benchmarking Aerosol Precursors

The effort to accurately estimate global radiative forcing has long been hampered by a degree of uncertainty in the tropospheric aerosol contribution. Reducing uncertainty in natural aerosol processes, the baseline of the aerosol budget, thus becomes a fundamental task. The appropriate representation of aerosols in the marine boundary layer (MBL) is essential to reduce uncertainty and provide reliable information on offsets to global warming. We developed an International Ocean Model Benchmarking package to assess marine biogeochemical process representations in Earth System Models (ESMs), and the package was employed to evaluate surface ocean concentrations and the sea–air fluxes of dimethylsulfide (DMS). Model performances were scored based on how well they captured the distribution and variability contained in high-quality observational datasets. Results show that model-data biases increased as DMS enters the MBL, but unfortunately over three-quarters of the models participating in the fifth Coupled Model Intercomparison Project (CMIP5) did not have a dynamic representation of DMS. When it is present, models tend to over-predict sea surface concentrations in the productive region of the eastern tropical Pacific by almost a factor of two, and the sea–air fluxes by a factor of three. Systematic model-data benchmarking as described here will help to identify such deficiencies and subsequently lead to improved subgrid-scale parameterizations and ESM development.

58 GEOSCIENCES↗
NASA NTRS2009

Intra-Seasonal Monthly Oscillations in Stratospheric NCEP Data and Model Results

Intra-seasonal oscillations (ISO) are observed in the zonal-mean of mesospheric wind and temperature measurements-and the numerical spectral model (NSM) generates such oscillations. Relatively large temperature ISO are evident also in stratospheric CPC (NCEP) data at high latitudes, where the NSM produces amplitudes around 3 K at 30 km. Analyzing the NCEP data for the years 1996-2006, we find in Fourier spectra signatures of oscillations with periods between 1.7 and 3 months. With statistical confidence levels exceeding 70%, the spectral features are induced by nonlinear interactions involving the annual and semi-annual variations. The synthesized data show for the 10-year average that the temperature ISO peak in winter, having amplitudes close to 4 K. The synthesized complete spectrum for periods around 2 months produces oscillations, varying from year to year, which can reach peak amplitudes of 15 and 5 K respectively at northern and southern polar latitudes.

Mayr, H. G.↗
NASA NTRS2019

Mars Atmospheric Chemistry Simulations with the GEM-Mars General Circulation Model

General Circulation Models with interactive physical and chemistry processes are the state-of-the-art tools for an integrated view and understanding of the Martian atmosphere and climate system. The GEM-Mars model currently includes 16 tracers for chemical composition and applies a fully online, interactive calculation of the photo- and gas phase chemistry of carbon dioxide (CO2) and water vapor (H2O). These species largely control the chemical composition of the neutral Mars atmosphere through their photolysis products and their subsequent interactions. Water vapor undergoes a complex cycle on Mars as it is transported and interacts with ice reservoirs both at the planet's surface and at water ice clouds, which in turn provide radiative feedbacks. In the photochemical cycles involving CO2 and H2O, the abundances of 5 species have been reported by previous investigations with significant spatio-temporal coverage: CO2, H2O, CO, O3 and H2O2. This paper presents the current status of the atmospheric chemistry simulations in GEM-Mars by comparing them to a selection of these observational datasets as well as to oxygen dayglow emission from O2(a1∆g). The results are consistent with previous model-data comparisons and illustrate that the water cycle and the photochemistry are well implemented in the model. In particular, the simulation of the key reservoir species H2O2 provides a good match to the available data. Model-data biases for ozone columns and oxygen airglow are related to the simulated water vapor vertical profile, as these species have important column contributions from vertical layers at the top of the hygropause.

F Daerden↗
NASA NTRS2001

Assessment of the Contribution of the Atmosphere to Uncertainties in Normalized Water-Leaving Radiance: A Combined Modeling and Data Analysis Approach

Our research for the Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) program has been focused on modeling and simulation studies as well as the development of atmospheric correction algorithms. Based on our original proposal and discussions at the SIMBIOS team meetings and workshops, the objectives of our research can be summarized as follows: (1) Use our radiative transfer model for the coupled atmosphere-ocean system to simulate the radiation field at arbitrary levels and in any desired direction in the atmosphere and ocean so as to provide a firm connection between the signal received by the satellite sensor and by a sensor looking down into the water column just above the surface and just below it; (2) Use the simulations to quantify the influence of atmospheric aerosols on the water-leaving radiance, and to quantify the error in the water-leaving radiance as a function of uncertainties in the aerosol optical properties, mass loading and vertical extent; (3) Use the model simulations in conjunction with validation measurements taken by other SIMBIOS investigators (for satellite overpasses) to assess our understanding of the radiative transfer process in the coupled atmosphere-ocean column, and to examine the extent to which the model provides a realistic prediction of simultaneously measured in situ water-leaving radiance and the radiance received by the satellite sensor; (4) Modify and improve an existing atmospheric correction algorithm, based on the work above, as needed by constructing new look-up tables that include scattering by ocean particles; and (5) Carry out approaches to developing an atmospheric correction algorithm for ocean color imagery with strongly absorbing aerosols.

Stamnes, Knut↗
DOE OSTI2019

Large-Scale Grid Models: Synthetic Data and Co-Simulation

Power grid modernization and wide-spread distributed energy resource (DER) integration are driving an explosion of interest in advanced algorithms and new optimization schemes. However, there has historically been a lack of open-access realistically sized and detailed datasets-particularly for the distribution system-and simulation tools able to model these systems. This talk will present recent advances with very large-scale (>>1M nodes) distribution data sets and the use of co-simulation to tractably model large integrated transmission-distribution grids and their interactions with new controls/optimization.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2012

Empirical Performance Model-Driven Data Layout Optimization and Library Call Selection for Tensor Contraction Expressions

Empirical optimizers like ATLAS have been very effective in optimizing computational kernels in libraries. The best choice of parameters such as tile size and degree of loop unrolling is determined by executing different versions of the computation. In contrast, optimizing compilers use a model-driven approach to program transformation. While the model-driven approach of optimizing compilers is generally orders of magnitude faster than ATLAS-like library generators, its effectiveness can be limited by the accuracy of the performance models used. In this paper, we describe an approach where a class of computations is modeled in terms of constituent operations that are empirically measured, thereby allowing modeling of the overall execution time. The performance model with empirically determined cost components is used to perform data layout optimization together with the selection of library calls and layout transformations in the context of the Tensor Contraction Engine, a compiler for a high-level domain-specific language for expressing computational models in quantum chemistry. The effectiveness of the approach is demonstrated through experimental measurements on representative computations from quantum chemistry.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Modeling Reference Cell Performance Using Measured and Modeled Spectral Data

The performance of several silicon-based reference cells is examined under clear skies on a horizontal and two-axis tracking surface during the winter of 2022. The ratio of the calculated reference cell output to the measured reference cell output is examined. For each reference cell, when using the measured spectral data, the ratio of the estimated to measured output varies by less than +/-0.6% at the P95 level. The analysis was also done using modeled spectral values obtained from the Bird spectrl2 model. The ratio between the estimated reference cell output using the modeled spectral values to the measured reference cell output varies by +/-1.1% at the P95 level.

angle of incidence↗
DOE OSTI2013

Final Report of the Mid-Atlantic Marine Wildlife Surveys, Modeling, and Data

The Wind Program hosted a two-day workshop on July 24-25, 2012 with scientists and regulators engaged in marine ecological survey, modeling, and database efforts pertaining to the waters of the Mid-Atlantic region. The workshop was planned by Federal agency, academic, and private partners to promote collaboration between ongoing offshore ecological survey efforts, and to promote the collaborative development of complementary predictive models and compatible databases. The meeting primarily focused on efforts to establish and predict marine mammal, seabird, and sea turtle abundance, density, and distributions extending from the shoreline to the edge of the Exclusive Economic Zone between Nantucket Sound, Massachusetts and Cape Hatteras, North Carolina.

17 WIND ENERGY↗
NASA NTRS2018

Model-Based Data Integration and Process Standardization Techniques for Fault Management: A Feasibility Study

This paper describes the theory and considerations in the application of model-based techniques to assimilate information from disjoint knowledge sources for performing NASA's Fault Management (FM)-related activities using the TEAMS® toolset. FM consists of the operational mitigation of existing and impending spacecraft failures. NASA's FM directives have both design-phase and operational-phase goals. This paper highlights recent studies by QSI and DST of the capabilities required in the TEAMS® toolset for conducting FM activities with the aim of reducing operating costs, increasing autonomy, and conforming to time schedules. These studies use and extend the analytic capabilities of QSI's TEAMS® toolset to conduct a range of FM activities within a centralized platform.

Haste, Deepak↗
NASA NTRS2004

Calibration, Data Acquisition, and Post Analysis of Turbulent Fluid Flow in a Calibration Jet Using Hot-wire Anemometry

The Turbine Branch concentrates on the following areas: Computational Fluid Dynamics (CFD), and implementing experimental procedures to obtain physical modeling data. Hot-wire Anemometry is a valuable tool for obtaining physical modeling data. Hot-wire Anemometry is likely to remain the principal research tool for most turbulent air/gas flow studies. The Hot-wire anemometer consists of a fine wire heated by electric current. When placed in a fluid stream, the hot-wire loses heat to the fluid by forced convection. In forced convection, energy transfer is due to molecular motion imposed by an extraneous force moving fluid parcels. When the hot-wire is in "equilibrium", the rate of heat input to the wire is equal to the rate of heat loss at the wire ends. The equality between heat input and heat loss is the basis for King s equation, which relates the electrical parameters of the hot-wire to the flow parameters of the fluid. Hot-wire anemometry is based on convective heat transfer from a heated wire element placed in a fluid flow. Any change in the fluid flow condition that affects the heat transfer from the heated element will be detected virtually instantaneously by a constant-temperature Hot-wire anemometry system. The system implemented for this research is the IFA 300. The system is a fully-integrated, thermal anemometer-based system that measures mean and fluctuating velocity components in air, water, and other fluids. It also measures turbulence and makes localized temperature measurements. A constant-temperature anemometer is a bridge and amplifier circuit that controls a tiny wire at constant temperature. As a fluid flow passes over the heated sensor, the amplifier senses the bridge off-balance and adjusts the voltage to the top of the bridge, keeping the bridge in balance. The voltage on top of the bridge can then be related to the velocity of the flow. The bridge voltage is sensitive to temperature as well as velocity and so the built-in thermocouple circuit can be attached to a thermocouple that can measure the fluid temperature. Additional information is included in the original extended abstract.

Moreno, Michelle↗
NASA NTRS2022

L-Band Microwave Satellite Data and Model Simulations Over the Dry Chaco to Estimate Soil Moisture, Soil Temperature, Vegetation and Soil Salinity

The Dry Chaco in South America is a semi-arid ecoregion prone to dryland salinization. In this region, we investigated coarse-scale surface soil moisture (SM), soil temperature, soil salinity and vegetation, using L-band microwave brightness temperature (TB) observations and retrievals from the Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) satellite missions, Catchment Land Surface Model (CLSM) simulations, and in situ measurements within 26 sampled satellite pixels. Across these 26 sampled pixels, the satellite-based SM outperformed CLSM SM compared to field data, and forward L-band TB simulations derived from in situ SM and temperature performed better than those derived from CLSM estimates relative to SMOS TB observations. The surface salinity for the sampled pixels was on average only 4 mg/g and only locally influenced the TB simulations, when including salinity in the dielectric mixing model of the forward radiative transfer model (RTM) simulations. To explore the potential of retrieving salinity together with other RTM parameters to optimize TB simulations over the entire Dry Chaco, the RTM was inverted using 10 years of multi-angular SMOS TB data and constraints of CLSM SM and temperature. However, the latter modeled SM was not sufficiently accurate and factors such as open surface water were missing in the background constraints, so that the salinity retrievals effectively represented a bulk correction of the dielectric constant, rather than salinity per se. However, the retrieval of vegetation, scattering albedo and surface roughness resulted in realistic values.

L-Band↗
DOE OSTI2022

IMoFi - Intelligent Model Fidelity: Physics-Based Data-Driven Grid Modeling to Accelerate Accurate PV Integration (Final Report)

This report summarizes the work performed under a project funded by U.S. DOE Solar Energy Technologies Office (SETO) to use grid edge measurements to calibrate distribution system models for improved planning and grid integration of solar PV. Several physics-based data-driven algorithms are developed to identify inaccuracies in models and to bring increased visibility into distribution system planning. This includes phase identification, secondary system topology and parameter estimation, meter-to-transformer pairing, medium-voltage reconfiguration detection, determination of regulator and capacitor settings, PV system detection, PV parameter and setting estimation, PV dynamic models, and improved load modeling. Each of the algorithms is tested using simulation data and demonstrated on real feeders with our utility partners. The final algorithms demonstrate the potential for future planning and operations of the electric power grid to be more automated and data-driven, with more granularity, higher accuracy, and more comprehensive visibility into the system.

14 SOLAR ENERGY↗
DOE OSTI2022

IMoFi (Intelligent Model Fidelity): Physics-Based Data-Driven Grid Modeling to Accelerate Accurate PV Integration Updated Accomplishments

This report summarizes the work performed under a project funded by U.S. DOE Solar Energy Technologies Office (SETO), including some updates from the previous report SAND2022-0215, to use grid edge measurements to calibrate distribution system models for improved planning and grid integration of solar PV. Several physics-based data-driven algorithms are developed to identify inaccuracies in models and to bring increased visibility into distribution system planning. This includes phase identification, secondary system topology and parameter estimation, meter-to-transformer pairing, medium-voltage reconfiguration detection, determination of regulator and capacitor settings, PV system detection, PV parameter and setting estimation, PV dynamic models, and improved load modeling. Each of the algorithms is tested using simulation data and demonstrated on real feeders with our utility partners. The final algorithms demonstrate the potential for future planning and operations of the electric power grid to be more automated and data-driven, with more granularity, higher accuracy, and more comprehensive visibility into the system.

14 SOLAR ENERGY↗