Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “in situ data processing”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Direct mechanistic connection between acoustic signals and melt pool morphology during laser powder bed fusion

Various nondestructive diagnostic techniques have been proposed for in situ process monitoring of laser powder bed fusion (LPBF), including melt pool pyrometry, whole-layer optical imaging, acoustic emission, atomic emission spectroscopy, high speed melt pool imaging, and thermionic emission. Correlations between these in situ monitoring signals and defect formation have been demonstrated with acoustic signals having been shown to predict pore formation with especially high confidence in recent machine learning studies. Here, in this work, time-resolved acoustic data are collected in both the conduction and keyhole welding regimes of LPBF-processed Ti-6Al-4V alloy. A non-dimensionalized Strouhal number analysis, used in whistle aeroacoustics, is applied to demonstrate that the acoustic signals recorded in the keyhole regimes can be directly associated with the vapor depression morphology. This mechanistic understanding developed from whistle aeroacoustics shows that acoustic monitoring during the LPBF process can provide a direct probe into the vapor depression dynamics and defect occurrence, especially in the keyhole regimes relevant to printing and defect formation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Modeling of deposit formation in mesoporous substrates via atomic layer deposition: Insights from pore‐scale simulation

Atomic layer deposition (ALD) has been a promising technique in fabricating membranes and tuning their properties with a precision at the atomic level. Fabrication of zeolitic imidazolate framework (ZIF) membranes using the ligand-induced permselectivation (LIPS) method starts with the formation of an oxide in a mesoporous substrate by ALD and is followed by the transformation of this oxide to ZIF using imidazolate vapor treatment. The objective of the ALD step is to block the mesopores with a thin deposit, that is, one with small penetration depth and small thickness on the top surface of the substrate. Unlike typical ALD on nonporous substrates, where all available sites react per ALD cycle, thin deposit formation in a mesoporous substrate requires that only a small fraction of the available deposition sites (i.e., close to the substrate surface) is subjected to ALD. Consequently, reactant dosing and duration of pulses are important process variables which, together with diffusion and reaction kinetics determine the deposit structure. Quantitative understanding of the interplay of these variables and phenomena can enable the rational design of ALD within mesoporous substrates. Here, we extend our earlier modeling effort considering the coexistence of ALD both inside the pores and on the external surface of the substrate. Finite-volume based models were developed and validated to simulate the two distinct modes of deposition cycle by cycle. The total mass uptake of the substrate with ALD cycles can be predicted using the combined surface deposition and pore reaction–diffusion models as affirmed by in situ quartz crystal microbalance experimental data. The ALD reactor model combined with the deposition model can accurately capture the number of ALD cycles needed to block the pores of the substrate. Based on the model, we designed a modified ALD process and examined the performance of the corresponding LIPS membranes. Furthermore, the present modeling work provides a new understanding of the deposit formation via ALD within mesoporous substrates for a variety of membrane applications.

atomic layer deposition↗
DOE OSTI2021

Interpretable Deep Learning for the Earth System with Fractal Nets

Focal Area 3: Explainable AI Our confidence in the projections made by Earth System Models (ESMs) depends on understanding them to be, in some important respects, faithful representations of the Earth system. Here we present an “explainable Artificial Intelligence (AI)” method that allows us to uncover the dynamical structure of the observed and modeled Earth system, discover hidden links across wide spatiotemporal scales, target model development efforts at poorly-represented dynamics, and optimize observed or modeled data collection to maximize predictive information. Science Challenge: Dynamical system science for the Earth system poses unique challenges given the large degree of internal climate variability. Thus, tools that help us understand how ESMs succeed and fail at representing these dynamics are crucial, particularly in relation to the observed system. Furthermore, the computational and memory constraints on ESM data output motivate in situ analysis of ESM dynamics, including automatic detection of dynamical shifts. Also, of key importance are procedures that leverage ESMs to optimize observational campaigns for improving process representation, reducing structural uncertainty and improving model skill.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Hydropower Biological Evaluation Toolset Best Practice Guide

Field studies using live fish are necessary for the evaluation of turbine biological performance, but they cannot determine the specific hydraulic conditions or physical stresses experienced by the fish, the locations where deleterious conditions occur, or the specific causes of the biological response. Using the Sensor Fish (SF) sensing technology, this deficiency can be overcome because the SF can be released independently or concurrently with live fish directly into operating infrastructure, and it takes high-frequency measurements of hydraulic conditions such as pressure, acceleration, and rotation acting on a body in situ during downstream passage. The Hydropower Biological Evaluation Tools (HBET; Hou et al. 2018) software package, developed by Pacific Northwest National Laboratory (PNNL), is designed to assemble, organize, and process data collected by the PNNL-developed SF and by live fish. HBET was developed specifically to design SF field studies, process the raw data, and analyze the processed data efficiently and scientifically. Its objectives are to facilitate SF studies focused on characterizing hydraulic conditions and to apply SF data for evaluating the impacts on fish from passage through hydro-structures. HBET allows users to design new studies, analyze data, perform statistical analyses, and evaluate predicted biological responses. It can be used by researchers, turbine designers, hydropower operators, and regulators to evaluate hydro-structures to enhance environmental sustainability in a cost-effective manner.

13 HYDRO ENERGY↗
NASA NTRS2006

Progress in the Development of Practical Remote Detection of Icing Conditions

The NASA Icing Remote Sensing System (NIRSS) has been under definition and development at NASA Glenn Research Center since 1997. The goal of this development activity is to produce and demonstrate the required sensing and data processing technologies required to accurately remotely detect and measure icing conditions aloft. As part of that effort NASA has teamed with NCAR to develop software to fuse data from multiple instruments into a single detected icing condition product. The multiple instrument approach utilizes a X-band vertical staring radar, a multifrequency microwave, and a lidar ceilometer. The radar data determine cloud boundaries, the radiometer determines the sub-freezing temperature heights and total liquid water content, and the ceilometer refines the lower cloud boundary. Data is post-processed with a LabVIEW program with a resultant supercooled liquid water profile and aircraft hazard depiction. Ground-based, remotely-sensed measurements and in-situ measurements from research aircraft were gathered during the international 2003-2004 Alliance Icing Research Study (AIRS II). Comparisons between the remote sensing system s fused icing product and the aircraft measurements are reviewed here. While there are areas where improvement can be made, the cases examined suggest that the fused sensor remote sensing technique appears to be a valid approach.

Reehorst, Andrew↗
NASA NTRS2017

Chlorine in Lunar Basalts

In the context of the lunar magma ocean (LMO) model, it is anticipated that chlorine (and other volatiles) should have been concentrated in the late-stage LMO residual melts (i.e., the dregs enriched in incompatible elements such as K, REEs, and P, collectively called KREEP, and in its primitive form - urKREEP, [1]), given its incompatibility in mafic minerals like olivine and pyroxene, which were the dominant phases that crystallized early in the cumulate pile of the LMO (e.g., [2]). When compared to chondritic meteorites and terrestrial rocks (e.g., [3-4]), lunar samples often display heavy chlorine isotope compositions [5-9]. Boyce et al. [8] found a correlation between delta Cl-37 (sub Ap) and bulk-rock incompatible trace elements (ITEs) in lunar basalts, and used this to propose that early degassing of Cl (likely as metal chlorides) from the LMO led to progressive enrichment in remaining LMO melt in Cl-37over Cl-35- the early degassing model. Barnes et al. [9] suggested that relatively late degassing of chlorine from urKREEP (to yield delta Cl-37 (sub urKREEP greater than +25 per mille) followed by variable mixing between KREEPy melts and mantle cumulates (characterized by delta Cl-37~0 per mille) could explain the majority of Cl isotope data from igneous lunar samples. In order to better understand the processes involved in giving rise to the heavy chlorine isotope compositions of lunar samples, we have performed an in situ study of chlorine isotopes and abundances of volatiles in lunar apatite from a diverse suite of lunar basalts spanning a range of geochemical types.

Barnes, J. J.↗
NASA NTRS2015

Evidence for a Dynamic Nanodust Cloud Enveloping the Moon

The exospheres that surround airless bodies such as the Moon are tenuous, atmosphere-like layers whose constituent particles rarely collide with one another. Some particles contained within such exospheres are the product of direct interactions between airless bodies and the space environment, and offer insights into space weathering processes. NASAs Lunar Atmosphere and Dust Environment Explorer (LADEE) mission studied the Moons exospheric constituents in situ and detected a permanent dust exosphere1 of particles with radii as small as 300 nm. Here we present evidence from LADEE spectral data for an additional fluctuating nanodust exosphere at the Moon containing a population of particles sufficiently dense to be detectable via scattered sunlight. We compare two anti-Sun spectral observations: one near the peak of the Quadrantidmeteoroid stream, the other during a period of comparativelyweak stream activity. The former shows a negative spectralslope consistent with backscattering of sunlight by nanodustgrains with radii less than 20 to 30 nm; the latter has a flatterspectral slope. We hypothesize that a spatially and temporallyvariable nanodust exosphere may exist at the Moon, and thatit is modulated by changes in meteoroid impact rates, suchas during encounters with meteoroid streams. The findingssuggest that similar nanodust exospheresand the particle ejection and transport processes that form themmay occurat other airless bodies.

Moon↗
NASA NTRS2007

A New Source of Space Weather Data

The twin STEREO spacecraft were launched on October 26,2006 and, after spending several weeks in alignment orbits, became operational in heliocentric orbits on January 2 1,2007. The spacecraft are now in orbits similar to Earth's and are separating from each other at a rate of about 45 degrees per year as viewed from the sun. The STEREO spacecraft are each equipped with a complement of EUV, and white light imagers as well as particles and fields in situ instruments and a radio burst tracker. In addition to full resolution data downloaded once per day, each spacecraft broadcasts a real time telemetry 'beacon' stream containing compressed images and typically one minute averages of solar wind measurements and radio intensities. These real time data streams are received by a mix of NOAA and NASA-managed tracking stations and the data is transmitted by these stations to the STEREO Science Center at NASA Goddard Space Flight Center where they are processed into useable parameters with a latency of less than five minutes from receipt. As the two spacecraft recede from the sun-Earth line, triangulation of the imaging and radio measurements should allow better estimate of the speed and direction of coronal mass ejections, allowing a more precise estimate of their arrival at Earth. In situ particles and fields measurements, particularly for the spacecraft (Behind) trailing Earth in its orbit, will sample the solar wind that will eventually co-rotate around to the sun-Earth line. Late in the prime mission when the spacecraft are very far (>90 degrees) from the sun-Earth line, observations from the Behind spacecraft, will be particularly valuable for providing a preview of active regions well beyond the sun's East limb (as seen from Earth). Continually updated STEREO space weather data can be viewed and downloaded at http:/lstereo-ssc.nascom.nasa.govldata/beacon/.

Kaiser, Michael L.↗
DOE OSTI2021

Modeling Ti–6Al–4V using crystal plasticity, calibrated with multi-scale experiments, to understand the effect of the orientation and morphology of the α and β phases on time dependent cyclic loading

Classically, crystal plasticity modeling has used a range of constitutive equations, in which the incorporation of additional physics-based relationships typically results in additional model parameters. These additional parameters need to be reliably calibrated, which often necessitates the use of a range of experimental data acquired at multiple length scales. In this work, a crystal plasticity based finite element (CPFE) model for a dual-phase Titanium alloy, Ti–6Al–4V, is developed. The α and β phases of the microstructure are explicitly modeled. The model is calibrated using a systematic optimization routine and experimental data that consist of macroscopic stress-strain curves coupled with lattice strains on different crystallographic planes for the two phases. These experimental data were obtained from in situ high energy X-ray diffraction experiments for multiple material pedigrees, with varying crystallographic orientation distribution and β volume fractions. Depending on the thermomechanical-processing route and the heat treatment used to manufacture the alloy, Ti–6Al–4V can exist in a wide number of microstructural forms, which often results in the α and β phases either having well aligned slip systems (following the Burgers orientation relationship (BOR)) or possessing no alignment of the slip systems across the interphase boundary (not following the BOR). In this study, the fully-calibrated CPFE model is used to gain a comprehensive understanding of the deformation behavior of Ti–6Al–4V, specifically, the effect of microstructures that follow the BOR (or not) on time-dependent cyclic loading (including the effects of dwell hold times).

36 MATERIALS SCIENCE↗
DOE OSTI2020

Data product development for cold cloud and precipitation process analysis/Snow regime classifications from the NSA snow product

This grant funded work focused first on developing a data product for cold-cloud precipitation and second, under a continuation, on examining distinct snowfall regimes occurring at the North Slope Alaska (NSA) facility. The overarching goal under the first phase was to provide a data product that quantifies the vertically- and temporally-resolved properties of cold, precipitating clouds and that will enable future analyses of the processes that control their formation and evolution. The data product derives from observations at the NSA Utqiagvik (BRW) and Oliktok Point (OLI) sites, its algorithm utilizing radar observations supplemented with in situ and other collocated remote sensing measurements to constrain an optimal estimation retrieval.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Refining Principal Stress Measurements in Reservoir Underburden in Regions of Induced Seismicity through Seismological Tools, Laboratory Experiments - Final Technical Report

This project developed methodologies to measure the in-situ principal stress in the deep subsurface through use of multiple independent, but complementary, seismic methods, laboratory verification, and development of theoretical frameworks. By leveraging existing regional and local datasets we developed, tested, and refined a set of diagnostic tools for determining the in-situ stress state with reduced uncertainty at and below reservoir depths (1.5-6 km). A set of novel tools was produced that are scale independent, such that their utility is equivalent on regional, field scale, and near borehole monitoring of principal stresses in reservoir underburden for carbon storage projects. During a 4-year Department of Energy (DOE) and Southern Company funded project, carried out by the Electric Power Research Institute (EPRI), Lawrence Livermore National Laboratory (LLNL), the University of Oklahoma (OU), and the U.S. Geological Survey (USGS), the project team developed methodologies to measure the far-field in-situ principal stress in the deep subsurface, leveraging induced seismicity data from waste-water disposal projects. These methodologies consisted in the use of well-established and technically advanced seismic processing methods, such as virtual seismometer method-moment tensor (VSM-MT) and shear wave splitting (SWS), that are adept at recovering the stress orientation and certain components of the stress tensor. These methods were applied to robust seismicity catalogs created with matched filter techniques near sites of active fluid disposal—a proxy for carbon storage sites where such datasets are more limited. Estimates of the stress orientation made with seismic processing tools were considered along with laboratory acoustic emission experiments conducted on rock samples from the region of interest. Stress orientations in the studied region do not vary significantly across distances of ~100 km, nor are they found to rotate through time as a consequence of local wastewater disposal, as previously speculated. Finally, the project team investigated the trade-offs among the different seismic methods and evaluated the range of uncertainty that is generated with these methodologies, which led to a practical use and refinement of the VSM-MT technique when it is applied to field datasets. Understanding the trade-offs between these different methods highlighted the potential benefits of improved quantification of uncertainties on stress field estimations.

58 GEOSCIENCES↗
NASA NTRS1976

A high-sensitivity torsional pendulum for polymeric films and fibres

A free oscillation torsion pendulum is described, which has been designed to measure accurately the dynamic shear modulus and logarithmic decrement of polymeric thin films and fibers, at frequencies of 0.1 to 10 Hz and a temperature range of 4.2 to 450 K. The instrument can also provide in situ tensile deformations of up to 5%. The specimen geometry necessary to obtain reliable modulus measurements with thin films is discussed, and typical data are presented which exhibit hitherto unreported relaxation processes, discernible by this instrument.

Aghili-Kermani, H.↗
NASA NTRS1988

The interaction of the solar wind with Comet Halley - Upwind and downwind

The interaction between Comet Halley and solar wind is examined using in situ data collected in 1986, computer modeling, and data from 1910, when the earth passed through the comet's tail. An overview of the nature of comets is given, presenting specific physical processes occurring in comets. The range of scientific tools and data available for studying comets is discussed. Data from observation of the comet are compared to expectations from theory and computer modeling. The data from 1910 show that the cometary tail was well developed 24 million km downstream from the nucleus with a wake about 6 million km wide.

Russell, C. T.↗
NASA NTRS1995

Validation of Global Climatologies of Trace Gases Using NASA Global Tropospheric Experiment (GTE) Data

Methane is an important trace gas because it is a greenhouse gas that affects the oxidative capacity of the atmosphere. It is produced from biological and anthropogenic sources, and is increasing globally at a rate of approximately 0.6% per year [Climate Change 1992, IPCC]. By using National Oceanic and Atmospheric Administration/Climate Monitoring and Diagnostics Laboratory (NOAA/CMDL) ground station data, a global climatology of methane values was produced. Unfortunately, because the NOAA/CMDL ground stations are so sparse, the global climatology is low resolution. In order to compensate for this low resolution data, it was compared to in-situ flight data obtained from the NASA Global Tropospheric Experiment (GTE). The smoothed ground station data correlated well with the flight data. Thus, for the first time it is shown that the smoothing process used to make global contours of methane using the ground stations is a plausible way to approximate global atmospheric concentrations of the gas. These verified climatologies can be used for testing large-scale models of chemical production, destruction, and transport. This project develops the groundwork for further research in building global climatologies from sparse ground station data and studying the transport and distribution of trace gases.

Courchaine, Brian↗
NASA NTRS2006

Quantifying the Seasonal and Interannual Variability of North American Isoprene Emissions Using Satellite Observations of the Formaldehyde Column

Quantifying isoprene emissions using satellite observations of the formaldehyde (HCHO) columns is subject to errors involving the column retrieval and the assumed relationship between HCHO columns and isoprene emissions, taken here from the GEOS-CHEM chemical transport model. Here we use a 6-year (1996-2001) HCHO column data set from the Global Ozone Monitoring Experiment (GOME) satellite instrument to (1) quantify these errors, (2) evaluate GOME-derived isoprene emissions with in situ flux measurements and a process-based emission inventory (Model of Emissions of Gases and Aerosols from Nature, MEGAN), and (3) investigate the factors driving the seasonal and interannual variability of North American isoprene emissions. The error in the GOME HCHO column retrieval is estimated to be 40%. We use the Master Chemical Mechanism (MCM) to quantify the time-dependent HCHO production from isoprene, alpha- and beta-pinenes, and methylbutenol and show that only emissions of isoprene are detectable by GOME. The time-dependent HCHO yield from isoprene oxidation calculated by MCM is 20-30% larger than in GEOS-CHEM. GOME-derived isoprene fluxes track the observed seasonal variation of in situ measurements at a Michigan forest site with a -30% bias. The seasonal variation of North American isoprene emissions during 2001 inferred from GOME is similar to MEGAN, with GOME emissions typically 25% higher (lower) at the beginning (end) of the growing season. GOME and MEGAN both show a maximum over the southeastern United States, but they differ in the precise location. The observed interannual variability of this maximum is 20-30%, depending on month. The MEGAN isoprene emission dependence on surface air temperature explains 75% of the month-to-month variability in GOME-derived isoprene emissions over the southeastern United States during May-September 1996-2001.

Palmer, Paul I.↗
DOE OSTI2021

In Situ Inference for Earth System Predictability

An understanding of future evolution in precipitation extremes is critical to numerous DOE mission questions. Extreme events are by nature short time-scale events that are difficult to diagnose in available model data. Accurate modeling of extreme events necessarily requires high spatial resolution at the storm scale locally. However, the environment in which storms grow is dependent on global, remote, processes. These complex spatiotemporal relationships are impossible to diagnose at resolutions required to accurately model storms responsible for extreme precipitation. At exascale, climate simulations will produce results at fine enough resolution to investigate these relationships. However, the resulting data from these simulations will be far too large to save for post-simulation analysis. We advocate for fitting statistical models inside the simulations as they run, a context known as in situ, which will facilitate scientific investigations using the full fine-scale data stream. Figure 1 shows an example of the type of model we could consider, a Bayesian hierarchical spatial regression model. Precipitation extremes at each grid cell are modeled using extreme value distributions. Since extremes are rare, fitting models to individual grid cells can result in high variance and poor estimates. Instead, the model can be made more robust by smoothing the parameters of the extreme value model across space. Additionally, the parameters themselves can be functionally linked to other variables elsewhere in the simulation. Thus, we can use the fine-scale data to build more robust models for extremes that link extreme behavior to other climate patterns.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2026

High Temperature Dielectric Properties and Differential Scanning Calorimetry of Lunar Simulants

To guide development of microwave process technology that could be used during in situ construction on the Moon, we measured the high-temperature basic dielectric properties (εʹ and εʺ) of 17 lunar simulants and related materials. In order to confidently use these data one needs to understand the data’s strengths and weaknesses. Therefore, a goal of this publication is to provide insights into the comparative effects of sample composition, pre-treatments, experimental variables, high temperatures, and other factors on the measured response. The dielectric measurements were performed using the cavity perturbation method over a temperature range between room temperature to 1000 °C, or higher, and provided the real and imaginary components of permittivity at six frequencies. The utility of the original values was limited by the varying density of the pellets used in the measurement. Therefore, all of the εʹ and εʺ measurements at the frequency of 2466 MHz have been scaled to a constant density, 1.75 g/cm 3 . Here the data are presented as graphs chosen to aid analysis within and across simulant groups. To gain additional insight into the processes happening at the elevated temperatures in the dielectric measurements, heat capacity data was obtained using differential scanning calorimetry (DSC) on several of the simulant materials. Our data show that over the frequency range 397 MHz – 2985 MHz a material’s behavior does not greatly change, as compared to the scale of differences observed between lunar mare and highland simulants at high temperatures. For example at 1000 °C, the mare simulant JSC-1A absorbs 10 times more power than the highland simulant NUW-LHT-5M. We observe that as melting temperatures are reached both permittivity and dielectric loss rise non-linearly, helping to explain thermal runaway during microware heating. Our data show that even less than a few weight % of many non-lunar minerals, and the use of mixtures in simulants can affect the dielectric behavior at higher temperatures. A comparison of our results with published dielectric data for Apollo samples and with remote sensing of the Moon supports the conclusion the simulants and lunar material at room temperature have very similar dielectric values.

Differential Scanning Calorimetry↗
DOE OSTI2021

Shear-free mixing to achieve accurate temporospatial nanoscale kinetics through scanning-SAXS: ion-induced phase transition of dispersed cellulose nanocrystals

Time-resolved in situ characterization of well-defined mixing processes using small-angle X-ray scattering (SAXS) is usually challenging, especially if the process involves changes of material viscoelasticity. In specific, it can be difficult to create a continuous mixing experiment without shearing the material of interest; a desirable situation since shear flow both affects nanoscale structures and flow stability as well as resulting in unreliable time-resolved data. Here, we demonstrate a flow-focusing mixing device for in situ nanostructural characterization using scanning-SAXS. Given the interfacial tension and viscosity ratio between core and sheath fluids, the core material confined by sheath flows is completely detached from the walls and forms a zero-shear plug flow at the channel center, allowing for a trivial conversion of spatial coordinates to mixing times. With this technique, the time-resolved gel formation of dispersed cellulose nanocrystals (CNCs) was studied by mixing with a sodium chloride solution. It is observed how locally ordered regions, so called tactoids, are disrupted when the added monovalent ions affect the electrostatic interactions, which in turn leads to a loss of CNC alignment through enhanced rotary diffusion. The demonstrated flow-focusing scanning-SAXS technique can be used to unveil important kinetics during structural formation of nanocellulosic materials. However, the same technique is also applicable in many soft matter systems to provide new insights into the nanoscale dynamics during mixing.

36 MATERIALS SCIENCE↗