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Results for “Process Scaling”

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 1,693 records · Page 94
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

The development of methods for predicting and measuring distribution patterns of aerial sprays

The capability of conducting scale model experiments which involve the ejection of small particles into the wake of an aircraft close to the ground is developed. A set of relationships used to scale small-sized dispersion studies to full-size results are experimentally verified and, with some qualifications, basic deposition patterns are presented. In the process of validating these scaling laws, the basic experimental techniques used in conducting such studies, both with and without an operational propeller, were developed. The procedures that evolved are outlined. The envelope of test conditions that can be accommodated in the Langley Vortex Research Facility, which were developed theoretically, are verified using a series of vortex trajectory experiments that help to define the limitations due to wall interference effects for models of different sizes.

Ormsbee, A. I.↗
NASA NTRS2021

The Search for Lunar Mantle Rocks Exposed on the Surface of the Moon

The lunar surface is ancient and well-preserved, recording Solar System history and planetary evolution processes. Ancient basin-scale impacts excavated lunar mantle rocks, which are still expected to be present on the surface. Sampling these rocks would provide insight into fundamental planetary processes, including differentiation and magmatic evolution. There is contention among lunar scientists as to what lithologies make up the upper lunar mantle, and where they may have been exposed on the surface. We review dynamical models of lunar differentiation in the context of recent experiments and spacecraft data, assessing candidate lithologies, their distribution, and implications for lunar evolution.

Geochemistry↗
DOE OSTI2025

Femtosecond x-ray photon correlation spectroscopy enables direct observations of atomic-scale relaxations of glass forming liquids

Glass-forming liquids exhibit structural relaxation behaviors, reflecting underlying atomic rearrangements on a wide range of timescales and playing a crucial role in determining material properties. However, the relaxation processes on the atomic scale are not well-understood due to the experimental difficulties in directly characterizing the evolving correlations of atomic-scale order in disordered systems. Here, in this study, we harness the coherence and ultrashort pulse characteristics of an x-ray free electron laser to directly probe atomic-scale ultrafast relaxation dynamics in the model system Ge 15 Te 85 . We demonstrate an analysis strategy for determining the intermediate scattering function by extracting the contrast decay of summed scattering patterns from two rapidly successive, nearly identical femtosecond x-ray pulses generated by a split-delay system. The result indicates a full decorrelation of atomic-scale order on the sub-picosecond timescale, supporting the argument for a high-fluidity fragile state of liquid Ge 15 Te 85 above its dynamic crossover temperature. The demonstrated strategy opens an avenue for experimental studies of relaxation dynamics in liquids, glasses, and other highly disordered systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Upscaling Reactive Transport and Clogging in Shale Microcracks by Deep Learning

Fracture networks in shales exhibit multiscale features. A rock system may contain a few main fractures and thousands of microcracks, whose length and aperture are orders of magnitude smaller than the former. It is computationally prohibitive to resolve all the fractures explicitly for such multiscale fracture networks. One traditional approach is to model the small-scale features (e.g., microcracks in shales) as an effective medium. Although this fracture-matrix conceptualization significantly reduces the problem complexity, there are classes of physical processes that cannot be accurately upscaled by effective medium approximations, e.g., microcrack clogging during mineral reactions. Here, we employ deep learning in place of effective medium theory to upscale physical processes in small-scale features. Specifically, we consider reactive transport in a fracture-microcrack network where microcracks can be clogged by precipitation. A deep learning multiscale algorithm is developed, in which the microcracks are upscaled as a wall boundary condition of the main fractures. The wall boundary condition is constructed by recurrent neural networks, which take concentration histories as input and predict the solute transport from main fractures to microcracks. The deep learning multiscale algorithm is firstly employed in specific scenarios, then a general model is developed which can work under various conditions. The new approach is validated against fully resolved simulations and an analytical solution, providing a reliable and efficient solution for problems that cannot be upscaled by effective medium models.

58 GEOSCIENCES↗
DOE OSTI2024

Climate-invariant machine learning

Projecting climate change is a generalization problem: We extrapolate the recent past using physical models across past, present, and future climates. Current climate models require representations of processes that occur at scales smaller than model grid size, which have been the main source of model projection uncertainty. Recent machine learning (ML) algorithms hold promise to improve such process representations but tend to extrapolate poorly to climate regimes that they were not trained on. To get the best of the physical and statistical worlds, we propose a framework, termed “climate-invariant” ML, incorporating knowledge of climate processes into ML algorithms, and show that it can maintain high offline accuracy across a wide range of climate conditions and configurations in three distinct atmospheric models. Our results suggest that explicitly incorporating physical knowledge into data-driven models of Earth system processes can improve their consistency, data efficiency, and generalizability across climate regimes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Scaling Arctic landscape and permafrost features improves active layer depth modeling

Tundra ecosystems in the Arctic store up to 40% of global below-ground organic carbon but are exposed to the fastest climate warming on Earth. However, accurately monitoring landscape changes in the Arctic is challenging due to the complex interactions among permafrost, micro-topography, climate, vegetation, and disturbance. This complexity results in high spatiotemporal variability in permafrost distribution and active layer depth (ALD). Moreover, these key tundra processes interact at different scales, and an observational mismatch can limit our understanding of intrinsic connections and dynamics between above and below-ground processes. Consequently, this could limit our ability to model and anticipate how ALD will respond to climate change and disturbances across tundra ecosystems. In this paper, we studied the fine-scale heterogeneity of ALD and its connections with land surface characteristics across spatial and spectral scales using a combination of ground, unoccupied aerial system, airborne, and satellite observations. We showed that airborne sensors such as AVIRIS-NG and medium-resolution satellite Earth observation systems like Sentinel-2 can capture the average ALD at the landscape scale. We found that the best observational scale for ALD modeling is heavily influenced by the vegetation and landform patterns occurring on the landscape. Landscapes characterized by small-scale permafrost features such as polygon tussock tundra require high-resolution observations to capture the intrinsic connections between permafrost and small-scale land surface and disturbance patterns. Conversely, in landscapes dominated by water tracks and shrubs, permafrost features manifest at a larger scale and our model results indicate the best performance at medium resolution (5 m), outperforming both higher (0.4 m) and lower resolution (10 m) models. This transcends our study to show that permafrost response to climate change may vary across dominant ecosystem types, driven by different above- and below-ground connections and the scales at which these connections are happening. We thus recommend tailoring observational scales based on landforms and characteristics for modeling permafrost distribution, thereby mitigating the influences of spatial-scale mismatches and improving the understanding of vegetation and permafrost changes for the Arctic region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Improved CO 2 Capture Performance of Electrochemically Mediated Amine Regeneration Processes with Ionic Surfactant Additives

For the effective reduction of global CO 2 emissions, it is essential to develop and deploy efficient and cost-effective technologies for CO 2 capture, especially from large point sources. We recently developed an electrochemically mediated amine regeneration (EMAR) system to replace traditional thermal desorption for the capture of CO 2 from post-combustion flue gases. Despite EMAR effectiveness on a laboratory scale, concerns regarding the high gas-to-liquid ratio in the electrochemical cell and long-term instability of the electrodes need to be addressed before further scale-up of the process to a pilot plant and beyond can be entertained. Accordingly, we investigated the effect of using sodium dodecyl sulfate (SDS) as an anionic surfactant and dodecyltrimethylammonium bromide (DTAB) as a cationic surfactant on the process operation. It was found that it is advantageous to use an anionic surfactant for a system such as EMAR that contains hydrophilic electrodes and a positively charged electrochemically active species. The overall cell resistance was notably reduced when SDS anionic surfactant was used. The precipitation of copper particles observed in the anode outlet when no surfactant was used was effectively avoided when SDS was added to the electrolyte, resulting in electrode stability. In addition, smaller gas bubbles were produced in the presence of the SDS surfactant, which resulted in less blockage of the electrode by the gas with a resultant lower cell potential under constant current conditions, driving more efficient CO 2 desorption. This led to an ~25% reduction in the electrochemical energy requirement, the lowest ever achieved experimentally for the EMAR process. Altogether, the addition of a very low concentration of SDS resulted in the successful circumvention of the important problems faced by the EMAR system regarding further scale-up.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Impact of magnetic and electric fields on the free energy to form a calcium carbonate ion-pair

Electromagnetic fields are used in water treatment and desalination to regulate scale formation and extend the lifetime of membranes. External electric and magnetic fields can promote or suppress mineral nucleation and growth. However, the molecular-scale mechanisms of such processes remain unknown. Computing the free energies needed to form ion pairs under external fields provides important insights into understanding the elemental steps during the initial formation of mineral scales. In this paper, we used molecular dynamics combined with metadynamics simulations to investigate the free energies of forming the [Ca–CO 3 ] 0 ion pair, a fundamental building block of carbonate scales, under a range of magnetic (up to 10 T) and electric (up to 10 V m −1 ) fields in water. The presence of constant magnetic or electric fields favored the ion pairing reaction and lowered the free energies by up to 3% to 6%. The internal energy and entropic components of the free energy showed significant changes and exhibited non-linear behavior with increasing field strength. The [Ca–CO 3 ] 0 ion pairing is an entropy-driven process in the absence of an external field, but the mechanism shifts to an internal energy-driven process under selected external fields, suggesting possible changes in the nucleation pathways.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Hydrological analysis in watersheds with a variable-resolution global climate model (VR-CESM)

Traditionally, watershed-scale hydrology is simulated by distributed hydrological models with offline meteorological forcing data, or by regional regional climate models that link atmospheric and land hydrology interactions. Global climate models (GCMs) are rarely used to study watershed-scale hydrology due to the relatively coarse grid resolution, computationally expensive downscaling, and simplified physical processes. Recently, however, watershed-scale hydrology analysis has become possible in GCMs due to the development of variable-resolution GCMs that dynamically couple the hydrological processes between atmosphere and land systems at fine resolutions in selected regions and coarse resolution elsewhere. In this study, we used the variable-resolution Community Earth System Model (VR-CESM) with refined-resolution (14 km) in the western U.S. and eastern China to evaluate watershed-scale hydrology. Furthermore, we compared the historical VR-CESM outputs with gauge measurements and other hydrological models (e.g., National Water Model in the U.S.) and calibrated the subsurface runoff capacities in four mountainous watersheds. An RCP8.5 projection from 2007 to 2050 is used to estimate the impact of changing precipitation and snow climatology on watershed hydrology. We also analyzed the long-term runoff variability and the possibility of extreme runoff events as simulated by the VR-CESM. Although calibration is not possible in larger-scale watersheds, VR-CESM simulates the long-term annual variability of watersheds and provides insights on climate change impacts on hydrology. We conclude that refined-resolution VR-CESM can be used for watershed-scale hydrology analysis to understand water resources and water balance, in addition to traditional watershed-scale hydrological models. It enables hydrological analysis at multiple watersheds in one simulation and can help understand the two-way dynamics between land surface hydrology and atmospheric processes, and is especially practical for projecting climate change impacts. However, it is challenging to apply VR-CESM for hydrologic analysis in regulated watersheds as human factors (e.g., pumping, irrigation, water diversion) have not been fully addressed in VR-CESM.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1991

Relaxation processes in a low-order three-dimensional magnetohydrodynamics model

The time asymptotic behavior of a Galerkin model of 3D magnetohydrodynamics (MHD) has been interpreted using the selective decay and dynamic alignment relaxation theories. A large number of simulations has been performed that scan a parameter space defined by the rugged ideal invariants, including energy, cross helicity, and magnetic helicity. It is concluded that time asymptotic state can be interpreted as a relaxation to minimum energy. A simple decay model, based on absolute equilibrium theory, is found to predict a mapping of initial onto time asymptotic states, and to accurately describe the long time behavior of the runs when magnetic helicity is present. Attention is also given to two processes, operating on time scales shorter than selective decay and dynamic alignment, in which the ratio of kinetic to magnetic energy relaxes to values 0(1). The faster of the two processes takes states initially dominant in magnetic energy to a state of near-equipartition between kinetic and magnetic energy through power law growth of kinetic energy. The other process takes states initially dominant in kinetic energy to the near-equipartitioned state through exponential growth of magnetic energy.

Stribling, Troy↗
DOE OSTI2024

The atomic gas sequence and mass–metallicity relation from dwarfs to massive galaxies

Galaxy scaling relations provide insights into the processes that drive galaxy evolution. The extension of these scaling relations into the dwarf galaxy regime is of particular interest. This is because dwarf galaxies represent a crucial stage in galaxy evolution, and understanding them could also shed light on their role in reionizing the early Universe. There is currently no consensus on the processes that dominate the evolution of dwarfs. In this work, we constrain the atomic gas sequence (stellar mass versus atomic gas fraction) and mass–metallicity relation (stellar mass versus gas-phase metallicity) from dwarf (⁠10 6.5 M ⊙ ⁠) to massive (⁠10 11.5 M ⊙ ) galaxies in the local Universe. The combined optical and 21-cm spectroscopic observations of the Dark Energy Spectroscopic Instrument and Arecibo Legacy Fast ALFA surveys allow us to constrain both scaling relations simultaneously. We find a slope change of the atomic gas sequence at a stellar mass of ~10 9 M ⊙ ⁠. We also find that the shape and scatter of the atomic gas sequence and mass–metallicity relation are strongly linked for both dwarfs and more massive galaxies. Consequently, the low-mass slope change of the atomic gas sequence is imprinted onto the mass–metallicity relation of dwarf galaxies. The mass scale of the measured slope change is consistent with a predicted escape velocity threshold below which low-mass galaxies experience significant supernova-driven gas loss, as well as with a reduction in cold gas accretion onto more massive galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Spatial Atomic Layer Deposition to Scale Manufacturing of Robust Catalysts for Biomass Conversion Applications: Cooperative Research and Development Final Report, CRADA Number CRD-17-715

This CRADA will facilitate technology maturation for NREL-developed ALD-coated catalyst materials that are tailored for durability during harsh biomass conversion chemistries. This project will address optimizing process parameters for scale-up of Al2O3 ALD-coated catalysts, demonstrating ALD-coated catalyst performance for muconic acid hydrogenation, and validating economic models that project significant cost benefits for ALD-enhanced catalytic processes. This work will strengthen private-public partnerships in the area of advanced catalyst manufacturing for energy-related technology. Critical information will be collected to elevate the Technology Readiness Level and increase our competitiveness for cooperative R&D agreements and licensing. Success of this work will be crosscutting as it can facilitate advanced catalyst development for both renewable and conventional processes.

09 BIOMASS FUELS↗
NASA NTRS1992

Composite intermediate case manufacturing scale-up for advanced engines

This Manufacturing Technology for Propulsion Program developed a process to produce a composite intermediate case for advanced gas turbine engines. The method selected to manufacture this large, complex part uses hard tooling for surfaces in the airflow path and trapped rubber to force the composite against the mold. Subelements were manufactured and tested to verify the selected design, tools, and processes. The most significant subelement produced was a half-scale version of a composite intermediate case. The half-scale subelement maintained the geometry and key dimensions of the full-scale case, allowing relevant process development and structural verification testing to be performed on the subelement before manufacturing the first full-scale case.

Ecklund, Rowena H.↗
DOE OSTI2020

There’s plenty of room at the top

Richard Feynman’s famous words, “there’s plenty of room at the bottom,” referred to the opportunities for revolutionizing the electronics industry by developing the science and technology of how to manufacture very small components (sub-micron to nanometer sized features). In additive manufacturing (AM), the opposite may be true: There’s plenty of room at the top. AM’s strength is in the low volume production of complex components, which is demanded in big industries such as oil and gas, construction, tooling, wind and water turbines, and infrastructure. Is AM’s ‘big’ future in the manufacture of large structures? Here, this special issue surveys the technical challenges and enormous opportunities associated with large scale additive manufacturing while discussing the materials, processes and applications that are enabled by scaling to much larger structures, much faster speeds and lower manufacturing costs. The authors believe that, if Professor Feynman was alive, he’d say “There’s plenty of room at the top.”

36 MATERIALS SCIENCE↗
NASA NTRS1992

Dimension scaling effects on the yield sensitivity of HEMT digital circuits

In our previous works, using a graphical tool, yield factor histograms, we studied the yield sensitivity of High Electron Mobility Transistors (HEMT) and HEMT circuit performance with the variation of process parameters. This work studies the scaling effects of process parameters on yield sensitivity of HEMT digital circuits. The results from two HEMT circuits are presented.

Sarker, Jogendra C.↗
NASA NTRS2003

Optimal Observations for Variational Data Assimilation

An important aspect of Ocean state estimation is the design of an observing system that allows the efficient study of climate aspects in the ocean. A solution of the design problem is presented here in terms of optimal observations that emerge as nondimensionalized singular vectors of the modified data resolution matrix. The actual computation is feasible only for scalar quantities in the limit of large observational errors. In the framework of a lo resolution North Atlantic primitive equation model it is demonstrated that such optimal observations when applied to determining the strength of the volume and heat transport across the Greenland-Scotland ridge, perform significantly better than traditional section data. On seasonal to inter-annual time-scales optimal observations are located primarily along the continental shelf and information about heat-transport, wind stress and stratification is being communicated via boundary waves and advective processes. On time-scales of about a month, sea surface height observations appear to be more efficient in reconstructing the cross-ridge heat transport than hydrographic observations. Optimal observations also provide a tool for understanding how the ocean state is effected by anomalies of integral quantities such as meridional heat transport.

Koehl, Armin↗
NASA NTRS2004

Granular Materials and the Risks They Pose for Success on the Moon and Mars

Working with soil, sand, powders, ores, cement and sintered bricks, excavating, grading construction sites, driving off-road, transporting granules in chutes and pipes, sifting gravel, separating solids from gases, and using hoppers are so routine that it seems straightforward to do it on the Moon and Mars as we do it on Earth. This paper brings to the fore how little these processes are understood and the millennia-long trial-and-error practices that lead to today's massive over-design, high failure rate, and extensive incremental scaling up of industrial processes because of the inadequate predictive tools for design. We present a number of pragmatic scenarios where granular materials play a role, the risks involved, and what understanding is needed to greatly reduce the risks.

Wilkinson, R. Allen↗