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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 163 records · Page 9

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DOE OSTI2024

Improving North American Wildfire Prediction by Integrating a Machine-Learning Fire Model in a Land Surface Model

Wildfires have shown increasing trends in both frequency and severity across the Contiguous United States (CONUS). However, process-based fire models have difficulties in accurately simulating the burned area over the CONUS due to a simplification of the physical process and cannot capture the interplay among fire, ignition, climate, and human activities. The deficiency of burned area simulation deteriorates the description of fire impact on energy balance, water budget, and carbon fluxes in the Earth System Models (ESMs). Alternatively, machine learning (ML) based fire models, which capture statistical relationships between the burned area and environmental factors, have shown promising burned area predictions and corresponding fire impact simulation. We develop a hybrid framework (ML4Fire-XGB) that integrates a pretrained eXtreme Gradient Boosting (XGBoost) wildfire model with the Energy Exascale Earth System Model (E3SM) land model (ELM) version 2.1. A Fortran-C-Python deep learning bridge is adapted to support online communication between ELM and the ML fire model. Specifically, the burned area predicted by the ML-based wildfire model is directly passed to ELM to adjust the carbon pool and vegetation dynamics after disturbance, which are then used as predictors in the ML-based fire model in the next time step. Evaluated against the historical burned area from Global Fire Emissions Database 5 from 2001-2020, the ML4Fire-XGB model outperforms process-based fire models in terms of spatial distribution and seasonal variations. Sensitivity analysis confirms that the ML4Fire-XGB well captures the responses of the burned area to rising temperatures. The ML4Fire-XGB model has proved to be a new tool for studying vegetation-fire interactions, and more importantly, enables seamless exploration of climate-fire feedback, working as an active component in E3SM.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Simulated wildfire burned area over the CONUS during 2001-2020

Wildfires have shown increasing trends in both frequency and severity across the Contiguous United States (CONUS). However, process-based fire models have difficulties in accurately simulating the burned area over the CONUS due to a simplification of the physical process and cannot capture the interplay among fire, ignition, climate, and human activities. The deficiency of burned area simulation deteriorates the description of fire impact on energy balance, water budget, and carbon fluxes in the Earth System Models (ESMs). Alternatively, machine learning (ML) based fire models, which capture statistical relationships between the burned area and environmental factors, have shown promising burned area predictions and corresponding fire impact simulation. We develop a hybrid framework (ML4Fire-XGB) that integrates a pretrained eXtreme Gradient Boosting (XGBoost) wildfire model with the Energy Exascale Earth System Model (E3SM) land model (ELM). A Fortran-C-Python deep learning bridge is adapted to support online communication between ELM and the ML fire model. Specifically, the burned area predicted by the ML-based wildfire model is directly passed to ELM to adjust the carbon pool and vegetation dynamics after disturbance, which are then used as predictors in the ML-based fire model in the next time step. Evaluated against the historical burned area from Global Fire Emissions Database 5 from 2001-2020, the ML4Fire-XGB model outperforms process-based fire models in terms of spatial distribution and seasonal variations. Sensitivity analysis confirms that the ML4Fire-XGB well captures the responses of the burned area to rising temperatures. The ML4Fire-XGB model has proved to be a new tool for studying vegetation-fire interactions, and more importantly, enables seamless exploration of climate-fire feedback, working as an active component in E3SM.

Liu, Ye↗

NASA NTRS2007

Baffin Bay Ice Drift and Export: 2002-2007

Multiyear estimates of sea ice drift in Baffin Bay and Davis Strait are derived for the first time from the 89 GHz channel of the AMSR-E instrument. Uncertainties in the drift estimates, assessed with Envisat ice motion, are approximately 2-3 km/day. A persistent atmospheric trough, between the coast of Greenland and Baffin Island, drives the prevailing southward drift pattern with average daily displacements in excess of 18-20 km during winter. Over the 5-year record, the ice export ranges between 360 and 675 x 10(exp 3) km(exp 2), with an average of 530 x 10(exp 3) km(exp 2). Sea ice area inflow from the Nares Strait, Lancaster Sound and Jones Sound potentially contribute up to a third of the net area outflow while ice production at the North Water Polynya contributes the balance. Rough estimates of annual volume export give approximately 500-800 km(exp 3). Comparatively, these are approximately 70% and approximately 30% of the annual area and Strait.

remote sensing↗

NASA NTRS1961

The Effect on Thrust Minus Base Drag of Exchanging Base Area for Nozzle Expansion in Supersonic Nozzles at Transonic Mach Numbers

A wind-tunnel investigation to determine the effect on thrust minus base drag of exchanging base area for nozzle overexpansion on a cylindrical afterbody with a single supersonic nozzle has been conducted a t Mach numbers from 0.9 t o 1.4. The throat-to-base diameter ratio has been varied from 0.320 to 0.550; the jet-to-base diameter ratio has been varied from 0.320 to 1, resulting in a jet Mach number variation of 1.0 to 3.897. The jet total-pressure ratio ranged from 2 to approximately 22. The results indicated that a proper balance between nozzle over-expansion and base area exists, which will produce the maximum afterbody net-thrust factor over a given operating range. For a given Mach number and throat-to-base diameter ratio, the optimum values of jet-to-base diameter ratio corresponding to the peak values of the net-thrust factor are, in general, larger than the values at the jet design pressure ratio and tend to increase with increasing j e t total-pressure ratio in a manner similar to the design values. Also, for given values of throat-to-base diameter ratio and jet total-pressure ratio, the optimum value of jet-to-base diameter ratio changed as the free-stream Mach number was varied from transonic to low supersonic speeds. The magnitude of the changes varied with jet total-pressure ratio and throat-to-base diameter ratio.

Slocumb, Travis H.↗

DOE OSTI2025

ELM2.1-XGBfire1.0: improving wildfire prediction by integrating a machine learning fire model in a land surface model

Wildfires have shown increasing trends in both frequency and severity across the contiguous United States (CONUS). However, process-based fire models have difficulties in accurately simulating the burned area over the CONUS due to a simplification of the physical process and cannot capture the interplay among fire, ignition, climate, and human activities. The deficiency of burned area simulation deteriorates the description of fire impact on energy balance, water budget, and carbon fluxes in the Earth system models (ESMs). Alternatively, fire models based on machine learning (ML), which capture statistical relationships between the burned area and environmental factors, have shown promising burned area predictions and corresponding fire impact simulation. We develop a hybrid framework (ELM2.1-XGBFire1.0) that integrates an eXtreme Gradient Boosting (XGBoost) wildfire model with the Energy Exascale Earth System Model (E3SM) land model (ELM) version 2.1. A Fortran–C–Python deep learning bridge is adapted to support online communication between ELM and the ML fire model. Specifically, the burned area predicted by the ML-based wildfire model is directly passed to ELM to adjust the carbon pool and vegetation dynamics after disturbance, which are then used as predictors in the ML-based fire model in the next time step. Evaluated against the historical burned area from Global Fire Emissions Database 5 from 2001–2019, the ELM2.1-XGBFire1.0 outperforms process-based fire models in terms of spatial distribution and seasonal variations. The ELM2.1-XGBFire1.0 has proven to be a new tool for studying vegetation–fire interactions and, more importantly, enables seamless exploration of climate–fire feedback, working as an active component of E3SM.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Favorable morphology and electronic conductivity of functional sublayers for highly efficient water splitting electrodes

Low electronic conductivities and improper morphologies of anode electrodes greatly limit the reaction area, catalyst utilization and efficiency in proton exchange membrane water electrolyzers. In this study, conductive sublayers with different conductivities and morphologies were introduced into anode electrodes in membrane-based water electrolyzers. In-situ and ex-situ investigation results showed that conductive sublayers (Au mesh and carbon nanotube (CNT) film) augmented the sheet conductivity of anode electrodes by up to 4000 times (from 2000 to 0.5 ohm square -1 ), and the ohmic resistance of water electrolyzers was reduced to 1/3 when inserting conductive sublayers. In addition, CNT film provided a higher electrochemical active area than Au mesh, because of favorable morphologies (large porosity and surface area) of CNT fibers on CNT films. Therefore, the current density of water splitting was increased by 3 times (from 4.55 mA cm -2 to 14.83 mA cm -2 ) at 2.5 V compared to a conventional anode electrode. Visualizations on bubble dynamics showed improved performances with conductive sublayers; this was mainly due to greatly increased number of reaction sites, highly spread reaction area (from 50 to 1000 um), and reduced activation overpotential. Therefore, a balance between high electronic conductivity and nanoporous morphology is essential to the anode electrode for larger reaction sites and areas in highly efficient water electrolyzers.

25 ENERGY STORAGE↗

DOE OSTI2024

Effect of Wettability Gradient on the Scale Formation in Falling Film Flow

Mitigation of scale formation and performance degradation remains a vital challenge for falling film evaporators in various industries. In this work, an experimental study of falling film flow on a horizontal tube is conducted to investigate the effects of wettability gradients on thermal, hydraulic, and fouling behavior. It is revealed that certain hydrophobic coating patterns, such as strip, ring, and grid patterns, lead to unwetted heat transfer area, which results in decreased heat transfer compared to fully wetted plain tube. By adjusting the geometry and position of the wettability gradient, the hybrid coating demonstrates improved heat transfer performance. Based on the characteristics of horizontal tube falling film flow, impinging jet, thin film flow, and liquid retention at the tube bottom, a hybrid coating pattern is developed to improve surface wetting and mitigate the scaling coverage. It is revealed that scale deposition is regulated by wettability gradient. Crystals tend to be dense and compact in hydrophilic areas, while they appear scattered or even absent in hydrophobic regions, depending on the dimension of the hydrophobic area. While at the hydrophilic/hydrophobic boundary, a noticeable scale thickness step is observed, which raises the potential for self-cleaning. Furthermore, the balance of minimization of scaling layer coverage and maximization of wetting area requires an optimal design in coating dimensions, for which a systemic study of both flow dynamics and fouling characteristics on the falling film is necessary in the future.

42 ENGINEERING↗

NASA NTRS2004

Spatially Complete Surface Albedo Data Sets: Value-Added Products Derived from Terra MODIS Land Products

Moody, E. G.↗

NASA NTRS2011

What do We Know the Snow Darkening Effect Over Himalayan Glaciers?

The atmospheric absorbing aerosols such as dust, black carbon (BC), organic carbon (OC) are now well known warming factors in the atmosphere. However, when these aerosols deposit onto the snow surface, it causes darkening of snow and thereby absorbing more energy at the snow surface leading to the accelerated melting of snow. If this happens over Himalayan glacier surface, the glacier meltings are expected and may contribute the mass balance changes though the mass balance itself is more complicated issue. Glacier has mainly two parts: ablation and accumulation zones. Those are separated by the Equilibrium Line Altitude (ELA). Above and below ELA, snow accumulation and melting are dominant, respectively. The change of ELA will influence the glacier disappearance in future. In the Himalayan region, many glacier are debris covered glacier at the terminus (i.e., in the ablation zone). Debris is pieces of rock from local land and the debris covered parts are probably not affected by any deposition of the absorbing aerosols because the snow surface is already covered by debris (the debris covered parts have different mechanism of melting). Hence, the contribution of the snow darkening effect is considered to be most important "over non debris covered part" of the Himalayan glacier (i.e., over the snow or ice surface area). To discuss the whole glacier retreat, mass balance of each glacier is most important including the discussion on glacier flow, vertical compaction of glacier, melting amount, etc. The contribution of the snow darkening is mostly associated with "the snow/ice surface melting". Note that the surface melting itself is not always directly related to glacier retreats because sometimes melt water refreezes inside of the glacier. We should discuss glacier retreats in terms of not only the snow darkening but also other contributions to the mass balance.

Yasunari, T. J.↗

NASA NTRS2012

Jet Exit Rig Six Component Force Balance

A new six axis air balance was delivered to the NASA Glenn Research Center. This air balance has an axial force capability of 800 pounds, primary airflow of 10 pounds per second, and a secondary airflow of 3 pounds per second. Its primary use was for the NASA Glenn Jet Exit Rig, a wind tunnel model used to test both low-speed, and high-speed nozzle concepts in a wind tunnel. This report outlines the installation of the balance in the Jet Exit Rig, and the results from an ASME calibration nozzle with an exit area of 8 square-inches. The results demonstrated the stability of the force balance for axial measurements and the repeatability of measurements better than 0.20 percent.

Castner, Raymond↗

NASA NTRS1981

Numerical studies of the energy balance in coronal loops

A numerical method is applied to treat the energy balance of quasi-static solar coronal loops, which have been observed to persist for periods much greater than the radiative cooling time. The quasi-static loop model employed takes into account gravity, density-, temperature- or position-dependent energy input, an accurate form of the radiative losses and variable loop cross-sectional area, under assumptions of energy input by coronal heating balanced by radiative and conductive losses, an optically thin plasma, energy conduction along the field lines only and hydrostatic equilibrium. Computations of an emission measure function for various distributions of the energy input and loop geometries are then presented which show that little information on the location of the energy input may be gained from spectral line intensity measurements integrated over a single loop.

Underwood, J. H.↗

DOE OSTI2022

Creating Functional Oxynitride–Silicon Interfaces and SrNbO 2 N Thin Films for Photoelectrochemical Applications

Photoelectrochemical performance dependence upon absorption length, carrier diffusion length, and surface area of an oxynitride photoabsorber is investigated. How best to fabricate optical-quality thin films of bandgap-tunable oxynitrides is also discussed. We targeted the stoichiometric compound SrNbO 2 N as an optimal wide-bandgap photoabsorber (1.9 eV) for use with silicon (1.1 eV) in a tandem structure photoelectrochemical cell. Preparation of perovskite oxynitrides at high-temperature as isolated powders is often straightforward, but it is difficult to integrate them as thin films in tandem junction devices with low-temperature materials. Here we develop the first method to prepare optical-quality SrNbO 2 N thin-films of tunable thickness and roughness on single-crystal silicon substrate. This achievement required an interfacial layer of ultra-thin TaN to be used as a barrier to reduce the inter-diffusion of silicon and oxygen during oxynitride syn-thesis. We produced a variety of SrNbO 2 N film thicknesses (20-440 nm) on n + -Si(100) surfaces. Roughness factor (0.14-21) scaled with thickness. The intrinsic photoelectrochemical activity of these devices was evaluated using a low-barrier sacrificial electron donor. Photocurrent density and photovoltage revealed a significant (and non-linear) dependence on film thickness and roughness. Furthermore, absorption length, carrier diffusion length, and surface area were each found to play key roles. Balancing these is required for optimally performing devices.

08 HYDROGEN↗

DOE OSTI2023

Smart Preprocessing & Robust Integration Emulator

To achieve the desired particle size of biomass feedstocks during preprocessing for trouble-free handling and conversion to produce biofuels and bioproducts, the raw materials must undergo a crucial milling process. The particle size of biomass plays a critical role in subsequent biofuel manufacturing, where a larger area-to-volume ratio facilitates efficient synthesis while balancing the impact of moisture on biomass storage. To optimize biofuel production efficiency and overcome these challenges, it is imperative to accurately predict the particle size distribution (PSD) of the biomass in the design of efficient preprocessing systems. The population balance model (PBM), upon empirical calibration and validation, can provide rapid prediction of post-milling PSD of granular biomass. However, PSD has limitations related to mass conservation and the absence of moisture considerations. To overcome these drawbacks, a deep learning model called the enhanced deep neural operator (DNO+) is implemented in the code. This model not only retains the capabilities of the PBM in handling complex mapping functions but also incorporates additional factors influencing the system. By considering various experimental conditions such as sieve size and moisture content, the trained DNO+ model can effectively predict the PSD after milling for any given feed PSD. To further reduce the reliance on experimental data, the PBM is integrated into the DNO+ model, resulting in a physics-informed DNO+ (PIDNO+). The PIDNO+ model addresses the non-conservation of quality exhibited by the PBM while inheriting the advantages of the DNO+ model in considering multiple influencing factors. Moreover, the PIDNO+ model significantly reduces the amount of data required for model training. Both deep learning models, i.e., DNO+ and PIDNO+, are excellent in predictive performance, offering swift and accurate machine learning-based predictions. The use of this code that contains these models will assist in guiding the proper milling equipment selection and operational conditions to achieve the desired biomass particle sizes, ensuring the efficiency of subsequent biofuel and bioproduct production processes.

Xia, Yidong [Idaho National Laboratory (INL), Idah↗

NASA NTRS1987

Active vehicle charging measurements in sounding rocket and space shuttle orbiter environments at Low Earth Orbit (LEO) altitude

It was concluded that for electron beam emission up to 100mA, vehicle charging is not a significant problem with the Space Shuttle Orbiter. Similarly, sounding rocket payloads have no serious charging problems up to this level of beam current, provided that the maximum amount of the rocket skin is available to collect ionospheric electrons from the LEO altitude range. However, sounding rockets are marginal in their collecting area capability and other effects may occur to balance the beam current when operated at lower altitudes during the night.

Raitt, W. J.↗

NASA NTRS1987

Orbital transfer vehicle concept definition and system analysis study, 1986. Volume 9: Study extension results

The purpose of this extension to the OTV Concept Definition and Systems Analysis Study was to improve the definition of the OTV Program that will be most beneficial to the nation in the 1995 to 2010 timeframe. The implications of the defined mission and defined launch vehicle are investigated. The key mission requirements identified for the Space Transportation Architecture Study (STAS) were established and reflect a need for early capability and more ambitious capability growth. The key technical objectives and related issues addressed are summarized. The analyses of selected areas including aerobrake design, proximity operations, and the balance of EVA and IVA operations used in the support of the OTV at the space-base were enhanced. Sensitivity studies were conducted to establish how the OTV program should be tailored to meet changing circumstances.

Kofal, Allen E.↗

NASA NTRS1994

An update on the Department of Energy's photovoltaic program

Funding for the terrestrial photovoltaic's program is $78 million in 1994. This is more than double the minimum level reached in 1989 and runs counter to the general trend of decreasing budgets for Department of Energy (DOE) programs. During the past five years, the program has expanded its mission from research and development to also address manufacturing technology and commercialization assistance. These new activities are directed toward revitalizing the market to reinstate the rapid rate of sales growth needed to attract investment. The program is approaching balance among efforts in each of the three areas. This translates to a reduction in some of the R & D activities of most relevance to the space power community. On the other hand, some of the advancements in manufacturing may finally bring thin-film technologies to reality for space arrays. This talk will describe the status and direction of DOE program with an eye toward highlighting its impact on technology of interest for space.

Benner, John P.↗

NASA NTRS2004

Spatially Complete Surface Albedo Data Sets: Value-Added Products Derived from Terra MODIS Land Products

Moody, Eric G.↗

NASA NTRS2004

Spatially Complete Global Surface Albedos Derived from Terra/MODIS Data

Spectral land surface albedo is an important parameter for describing the radiative properties of the Earth. Accordingly it reflects the consequences of natural and human interactions, such as anthropogenic, meteorological, and phenological effects, on global and local climatological trends. Consequently, albedos are integral parts in a variety of research areas, such as general circulation models (GCMs), energy balance studies, modeling of land use and land use change, and biophysical, oceanographic, and meteorological studies. Recent production of land surface anisotropy, diffuse bihemispherical (white-sky) albedo and direct beam directional hemispherical (black-sky) albedo from observations acquired by the MODIS instruments aboard NASA s Terra and Aqua satellite platforms have provided researchers with unprecedented spatial, spectral, and temporal information on the land surface's radiative characteristics. Cloud cover, which cutails retrievals, and the presence of ephemeral and seasonal snow limit the snow-free data to approximately half the global land surfaces on an annual equal-angle basis. This precludes the MOD43B3 albedo products from being used in some remote sensing and ground-based applications, climate models, and global change research projects. An ecosystem-dependent temporal interpolation technique is described that has been developed to fill missing or seasonally snow-covered data in the official MOD43B3 albedo product. The method imposes pixel-level and local regional ecosystem-dependent phenological behavior onto retrieved pixel temporal data in such a way as to maintain pixel-level spatial and spectral detail and integrity. The phenological curves are derived from statistics based on the MODIS MOD12Q1 IGBP land cover classification product geolocated with the MOD43B3 data. The resulting snow-free value-added products provide the scientific community with spatially and temporally complete global white- and black-sky surface albedo maps and statistics. These products are stored on 1'(approximately 10 km) and coarser resolution equal-angle grids, and are computed for the first seven MODIS wavelengths, ranging from 0.47 through 2.1 microns, and for three broadband wavelengths, 0.3-0.7,0.3-5.0 and 0.7-5.0 microns.

King, Michael D.↗