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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Distributed Aperture Radar Tomographic Sensors (darts) to Map Surface Topography and Vegetation Structure

Distributed Aperture Radar Tomographic Sensors (DARTS)is a mission concept being studied at the NASA Jet PropulsionLaboratory in collaboration with the California Institute ofTechnology to enable global and repeated imaging of surfacetopography and three-dimensional vegetation structure usingsingle-pass tomographic SAR technique. The observing systemconsists of a distributed formation of multiple small syntheticaperture radar platforms deployed in space with variabledistances to achieve look angle diversity and sensitivityto the vertical distribution of vegetation components. Ourgoal is to identify the optimal system configuration startingfrom documented community needs and mature the criticaltechnologies that lead to a viable implementation of DARTS.Here, we provide an overview of DARTS and describe ourapproach for designing and demonstrating single-pass SARtomographic systems as part of an on-going funded NASA Instrument Incubator Program effort.

Chung, Soon-Jo↗
NASA NTRSDate not supplied

DeepONet-Assisted Optimization of Surface Topography for Transition Delay in A Mach 4.5 Boundary Layer

We use deep learning, an ensemble variationaltechnique (EnVar), and direct numerical simulations(DNS) to design an optimal topography for a two-dimensional roughness element that delays the on-set of laminar-turbulent transition in a Mach 4.5 flat-plate boundary layer. Deep operator networks (Deep-ONets), which have the known ability to learn com-plex nonlinear operators within dynamical systems,are used for machine learning. For the baseline config-uration of a smooth flat plate, the second-mode wavesat the DNS inflow cause a quick nonlinear breakdownof the high-speed boundary layer within the computa-tional domain. Results reported in the present studyvalidate the ability of DeepONets to model the tran-sition delay via a given topography of the roughnesselement. The computing cost to optimize the rough-ness element for minimal skin-friction drag is substan-tially lowered by the DeepONets-based reduced-ordermodel. In comparison to the baseline method of EnVaroptimization based on DNS alone, the DeepONets-based EnVar optimizer is able to delay transition pastthe outflow boundary of the computational domainwhile utilizing almost 5–6 times fewer DNS.

Machine Learning↗
NASA NTRSDate not supplied

DeepONet-Assisted Optimization of Surface Topography for Transition Delay in a Mach 4.5 Boundary Layer

We use deep learning, an ensemble variational technique (EnVar), and direct numerical simulations(DNS) to design an optimal topography for a two-dimensional roughness element that delays the on-set of laminar-turbulent transition in a Mach 4.5 flat-plate boundary layer. Deep operator networks (DeepONets), which have the known ability to learn complex nonlinear operators within dynamical systems, are used for machine learning. For the baseline configuration of a smooth flat plate, the second-mode waves at the DNS inflow cause a quick nonlinear breakdown of the high-speed boundary layer within the computational domain. Results reported in the present study validate the ability of DeepONets to model the transition delay via a given topography of the roughness element. The computing cost to optimize the rough-ness element for minimal skin-friction drag is substantially lowered by the DeepONets-based reduced-order model. In comparison to the baseline method of EnVar optimization based on DNS alone, the DeepONets-based EnVar optimizer is able to delay transition past the outflow boundary of the computational domain while utilizing almost 5–6 times fewer DNS.

Machine Learning↗
NASA NTRS1982

Ion-beam-induced topography and surface diffusion

It is pointed out that the development of surface topography along with enhanced surface and bulk diffusion processes accompanying ion bombardment have generated growing interest among users of ion beams and plasmas for thin film or material processing. Interest in these processes stems both from attempts to generate topographic changes for specific studies or applications and from the need to suppress or control undesirable changes. The present investigation provides a summary of the current status of impurity-induced texturing, with emphasis on recent developments. Particular attention is given to the texturing accompanying deposition of an impurity material onto a solid surface while simultaneously etching the surface with an ion beam. A description of experimental considerations is provided, and a thermal-diffusion model is discussed along with the development of sputter cones, and aspects of impact-enhanced surface diffusion.

Robinson, R. S.↗
NASA NTRS1985

Thermomechanical modeling of the Colorado Plateau-Basin and range transition zone

The Colorado Plateau (CP) basin and range (B & R) boundary is marked by a transition zone on the order of 75 to 150 km in width. As one moves westward across this transition from the CP interior to the B & R there is a variation in the surface topography, surface heat flow, Bouguer gravity, seismicity, and crustal structure. This transition extends eastward into the western CP from the Wastach-Hurricane fault line and is largely coincident with the high plateaus of Utah and the Wasatch Mountains. It has been suggested that this transition zone marks a thermal and tectonic encroachment of the CP by the B & R. A simple two dimensional numerical model of the thermal regime for the transition zone was constructed to test the hypothesis that the observed geophysical signatures across the transition are due to lateral heat conduction from steady state uniform extension within the B & R lithosphere. Surface heat flow, uplift due to flexure from thermal buoyant loading, and regional Bouguer gravity are computed for various extension rates, crustal structures, and compensation depths.

Londe, M. D.↗
NASA NTRS1983

Surface topography-connections between lubrication and failure initiation

The characteristics of the initial surface topography is intimately connected to the machining process by which it is produced. Both processes create a near surface region of residual stresses, microstructure and hardness that is different from the bulk. The material properties in this rather undefined region can significantly influence the mode of failure, such as wear, scuffing or fatigue, as well as the degree of failure resistance for a given material. Under full film elastohydrodynamic (EHD) conditions, where shear is accomodated within a relatively thick lubricant film, the normal and shear stresses are distributed uniformly over the near surface region, and the surface topography has little influence on the lubrication or failure process. Under more typical conditions where surface roughness and lubricant film thickness are of the same order of magnitude, the surface topography not only emerges as an important parameter in failure initiation, but it also becomes intimately involved in the lubrication process itself.

Wedeven, L. D.↗
NASA NTRS2016

The Pliocene Model Intercomparison Project (PlioMIP) Phase 2: Scientific Objectives and Experimental Design

The Pliocene Model Intercomparison Project (PlioMIP) is a co-ordinated international climate modelling initiative to study and understand climate and environments of the Late Pliocene, as well as their potential relevance in the context of future climate change. PlioMIP examines the consistency of model predictions in simulating Pliocene climate and their ability to reproduce climate signals preserved by geological climate archives. Here we provide a description of the aim and objectives of the next phase of the model intercomparison project (PlioMIP Phase 2), and we present the experimental design and boundary conditions that will be utilized for climate model experiments in Phase 2. Following on from PlioMIP Phase 1, Phase 2 will continue to be a mechanism for sampling structural uncertainty within climate models. However, Phase 1 demonstrated the requirement to better understand boundary condition uncertainties as well as uncertainty in the methodologies used for data-model comparison. Therefore, our strategy for Phase 2 is to utilize state-of-the-art boundary conditions that have emerged over the last 5 years. These include a new palaeogeographic reconstruction, detailing ocean bathymetry and land-ice surface topography. The ice surface topography is built upon the lessons learned from offline ice sheet modelling studies. Land surface cover has been enhanced by recent additions of Pliocene soils and lakes. Atmospheric reconstructions of palaeo-CO2 are emerging on orbital timescales, and these are also incorporated into PlioMIP Phase 2. New records of surface and sea surface temperature change are being produced that will be more temporally consistent with the boundary conditions and forcings used within models. Finally we have designed a suite of prioritized experiments that tackle issues surrounding the basic understanding of the Pliocene and its relevance in the context of future climate change in a discrete way.

climate models↗