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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.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Evaluation of the maximum cross-correlation method of estimating sea surface velocities from sequential satellite images

The maximum cross correlation (MCC) method of Leese et al. (1971) for estimating sea surface velocities from sequences of satellite images is evaluated by comparing the MCC fields obtained from sequences of AVHRR and CZCS with in situ data and velocity fields calculated with a high-resolution quasi-geostrophic model. The rms differences and vector correlations between the velocity field produced by the MCC method and the model's field are presented. It is shown that much of the difference between the MCC fields and either the in situ data or the model velocity fields can be accounted for by considering physical and biological processes not included in the MCC method. The conditions under which the method is likely to be most successful are discussed.

Tokmakian, Robin↗
NASA NTRS1994

Infrared algorithm development for ocean observations with EOS/MODIS

Efforts continue under this contract to develop algorithms for the computation of sea surface temperature (SST) from MODIS infrared retrievals. This effort includes radiative transfer modeling, comparison of in situ and satellite observations, development and evaluation of processing and networking methodologies for algorithm computation and data accession, evaluation of surface validation approaches for IR radiances, and participation in MODIS (project) related activities. Efforts in this contract period have focused on radiative transfer modeling and evaluation of atmospheric path radiance efforts on SST estimation, exploration of involvement in ongoing field studies, evaluation of new computer networking strategies, and objective analysis approaches.

Brown, Otis B.↗
NASA NTRS1995

Infrared algorithm development for ocean observations

Efforts continue under this contract to develop algorithms for the computation of sea surface temperature (SST) from MODIS infrared retrievals. This effort includes radiative transfer modeling, comparison of in situ and satellite observations, development and evaluation of processing and networking methodologies for algorithm computation and data accession, evaluation of surface validation approaches for IR radiances, and participation in MODIS (project) related activities. Efforts in this contract period have focused on radiative transfer modeling, evaluation of atmospheric correction methodologies, involvement in field studies, production and evaluation of new computer networking strategies, and objective analysis approaches.

Brown, Otis B.↗
NASA NTRS1997

Infrared Algorithm Development for Ocean Observations with EOS/MODIS

Efforts continue under this contract to develop algorithms for the computation of sea surface temperature (SST) from MODIS infrared measurements. This effort includes radiative transfer modeling, comparison of in situ and satellite observations, development and evaluation of processing and networking methodologies for algorithm computation and data accession, evaluation of surface validation approaches for IR radiances, development of experimental instrumentation, and participation in MODIS (project) related activities. Activities in this contract period have focused on radiative transfer modeling, evaluation of atmospheric correction methodologies, undertake field campaigns, analysis of field data, and participation in MODIS meetings.

Brown, Otis B.↗
NASA NTRS2000

Case Study Analyses of the Success DC-8 Scanning Lidar Database

Under project SUCCESS (Subsonic Aircraft Contrail and Cloud Effects Special Study) funded by the Atmospheric Effects of Aviation Program, SRI International (SRI) developed an angular scanning back'scatter lidar for operation on the NASA DC-8 research aircraft and deployed the scanning lidar during the SUCCESS field campaign. The primary purpose of the lidar was to generate real-time video displays of clouds and contrails above, ahead of, and below the DC-8 as a means to help position the aircraft for optimum cloud and contrail sampling by onboard in situ sensors, and to help extend the geometrical domain of the in situ sampling records. A large, relatively complex lidar database was collected and several data examples were processed to illustrate the value of the lidar data for interpreting the other data records collected during SUCCESS. These data examples were used to develop a journal publication for the special SUCCESS Geophysical Research Letters issue (reprint presented as Appendix A). The data examples justified data analyses of a larger part of the DC-8 lidar database and is the objective of the current study.

Uthe, Edward E.↗
NASA NTRS2004

Structural Health Management for Future Aerospace Vehicles

Structural Health Management (SHM) will be of critical importance to provide the safety, reliability and affordability necessary for the future long duration space missions described in America's Vision for Space Exploration. Long duration missions to the Moon, Mars and beyond cannot be accomplished with the current paradigm of periodic, ground based structural integrity inspections. As evidenced by the Columbia tragedy, this approach is also inadequate for the current Shuttle fleet, thus leading to its initial implementation of on-board SHM sensing for impact detection as part of the return to flight effort. However, future space systems, to include both vehicles as well as structures such as habitation modules, will require an integrated array of onboard in-situ sensing systems. In addition, advanced data systems architectures will be necessary to communicate, store and process massive amounts of SHM data from large numbers of diverse sensors. Further, improved structural analysis and design algorithms will be necessary to incorporate SHM sensing into the design and construction of aerospace structures, as well as to fully utilize these sensing systems to provide both diagnosis and prognosis of structural integrity. Ultimately, structural integrity information will feed into an Integrated Vehicle Health Management (IVHM) system that will provide real-time knowledge of structural, propulsion, thermal protection and other critical systems for optimal vehicle management and mission control. This paper will provide an overview of NASA research and development in the area of SHM as well as to highlight areas of technology improvement necessary to meet these future mission requirements.

Prosser, W. H.↗
NASA NTRS2011

Radiation Induced Chemistry of Icy Surfaces: Laboratory Simulations

We will discuss laboratory experiments designed to enhance our understanding the chemical processes on icy solar system bodies, enable interpretation of in-situ and remote-sensing data, and help future missions to icy solar system bodies, such as comets, Europa, Ganymede, Enceladus etc.

radiation↗
NASA NTRS2019

Vicarious Calibration of GOCI for the SeaDAS Ocean Color Retrieval

A key on-orbit calibration step for satellite remote sensing of ocean color is the vicarious calibration. This establishes the final gains for each spectral band on the sensor that minimize bias in the retrieved ocean color signal. The vicarious calibration is specific to the instrument and the atmospheric correction algorithm. The vicarious calibration gains for the Geostationary Ocean Color Imager (GOCI) are presented here, which were derived to optimize the performance ofNASA's standard atmospheric correction algorithm as implemented in the l2gen code and distributed through the SeaDAS open-source software package. Following NASA's protocols, the near-infrared(NIR) bands were calibrated first, and the visible bands were then calibrated relative to this fixed NIR calibration. The gain for the 745-nm NIR band was derived using a fixed aerosol model, which waschosen based on the Angstrom Coefficients derived from MODIS onAqua (MODISA). For the vicarious gains of the visible bands, twosources for the target water-leaving radiances were tested: matchupsfrom MODISA and climatological data from SeaWiFS. A validation analysis using AERONET-OC data shows an improvement in sensor performance when compared with results using the current vicarious gains and results using no vicarious calibration. Good agreement was found in vicarious gains derived using both concurrent MODISA and climatological SeaWiFS as vicarious calibration data sources. These results support the use of a concurrent sensor for the vicarious calibration when in situ data are not available and demonstrate that using climatology from a well-calibrated sensor like SeaWiFSfor the vicarious calibration is a valid alternative when it is not possible to use a concurrent sensor or in situ data. We recommend using the gains derived from concurrent GOCI matchups with MODISA for GOCI processing in SeaDAS/l2gen.

Concha, Javier↗
DOE OSTI2023

Self-supervised learning of spatiotemporal thermal signatures in additive manufacturing using reduced order physics models and transformers

Microstructure control via additive manufacturing has enormous potential as manufacturers, materials scientists, and designers alike seek to exploit novel fabrication technologies to improve component performance. Recent works have demonstrated the feasibility of producing materials with controlled microstructures across various length scales. However, the experimental approach towards exploring the process-structure space can be laborious and costly. This is particularly true if also considering scan pattern optimization which is well suited for processes such as powder bed fusion electron beam melting. In this work we propose an approach for encoding additive manufacturing layer-wise thermal response signatures using self-supervised representation learning. Thermal simulations from a reduced order model are utilized to estimate the spatiotemporal response during printing. A machine learning framework, using video-transformers, is utilized to efficiently distill spatiotemporal patterns into a compact latent space representation. This latent state representation encodes the relevant physics which is then utilized to establish a data-driven process-structure model for an additively manufactured Ni-based superalloy. In conclusion, the proposed methodology could potentially be used towards in-situ process monitoring, scan pattern experimental design, and component qualification.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Accelerating Scientific Workflows on HPC Platforms with In Situ Processing

Scientific workflows drive most modern large-scale science breakthroughs by allowing scientists to define their computations as a set of jobs executed in a given order based on their data dependencies. Workflow management systems (WMSs) have become key to automating scientific workflows-executing computational jobs and orchestrating data transfers between those jobs running on complex high-performance computing (HPC) platforms. Traditionally, WMSs use files to communicate between jobs: a job writes out files that are read by other jobs. However, HPC machines face a growing gap between their storage and compute capabilities. To address that concern, the scientific community has adopted a new approach called in situ, which bypasses costly parallel filesystem I/O operations with faster in-memory or in-network communications. When using in situ approaches, communication and computations can be interleaved. In this work, we leverage the Decaf in situ dataflow framework to accelerate task-based scientific workflows managed by the Pegasus WMS, by replacing file communications with faster MPI messaging. We propose a new execution engine that uses Decaf to manage communications within a sub-workflow (i.e., set of jobs) to optimize inter-job communications. We consider two workflows in this study: (i) a synthetic workflow that benchmarks and compares file- and MPI-based communication; and (ii) a realistic bioinformatics workflow that computes mu-tational overlaps in the human genome. Experiments show that in situ communication can improve the bioinformatics workflow execution time by 22% to 30% compared with file communication. Our results motivate further opportunities and challenges for bridging traditional WMSs with in situ frameworks.

Decaf↗
DOE OSTI2024

Review—In Situ X-ray and Infrared Spectroscopic Studies of Electrochemical Systems

Despite of intense research and a wealth of data, the phenomena occurring during electrocatalysis are still a major obstacle in many chemical processes. Molecular analysis of the electrode/electrolyte interface is needed to correctly describe the reaction through identifying the species involved, their interaction with the environment and kinetics in situ, i.e. while the reaction is taking place. That can be done by coupling the electrochemical system with complementary non-electrochemical techniques. Particularly revealing are in situ X-ray spectroscopic techniques to analyze the electrode itself, providing the information on the changes in the catalyst during the reaction. The synergy of the traditional electrochemical techniques with the complementary spectroscopic methodologies offer understanding of the electrode/electrolyte interface above and beyond traditional experimental mainframe. Here we demonstrate how in situ X-ray absorption spectroscopy (XAS), in situ infrared reflection/absorption spectroscopy (IRRAS), and traditional voltammetric studies can increase our understanding of electrochemical processes during oxidation of ethanol. The results show the pronounced role of electrode surface in determining reaction kineticks and revealed the selectivity of the catalyst to complete oxidation pathway. They further provide understanding of the parameters that enhance its oxidation for future designing catalysts for alcohol oxidation fuel cells.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

In-Situ Detection and Prediction of WAAM Cross Feature Geometry

Abstract Wire arc additive manufacturing (WAAM) is increasingly used by manufacturers due to its relatively low cost and high deposition rate compared to other metal AM methods, but the parts produced by WAAM can be subject to localized variations in part quality. One such variation is the cross-feature defect, whereby a localized part height increase occurs due to the crossing of deposition toolpaths. Mitigation of this defect is typically achieved using manual path planning strategies, but closed-loop control is underutilized. Since the nature of this defect and of the WAAM process is such that the previous layer’s geometry influences that of the subsequent layer’s, the cross-feature defect geometry changes throughout the deposition. Therefore, any closed-loop control strategy will need to incorporate the dynamic trait of this defect. The present work seeks to implement an in-situ process modeling approach where a regression model can be continuously updated to predict the defect geometry of the subsequent deposition layer based on the historical process data. Several multi-layer cross-feature geometries are deposited and current, voltage, and optical camera data is taken for each layer. The resulting cross-feature geometries are characterized using 3D scanning and the performance and accuracy of the in-situ modeling approach is evaluated.

Thien, Austen↗
DOE OSTI2025

A Performance Model of In-Situ Techniques

The computational capacity of High-Performance Computing (HPC) systems increases continuously with the rapid development of central processing units (CPUs) and graphic processing units (GPUs), while the in-/output (IO) subsystem develops relatively slowly and storage capacity is also limited. Data-intensive applications, which are designed to leverage the high computational capacity of HPC resources, typically generate a considerable amount of data for post-processing visualizations and data analytics. The limited IO speed and storage space could lead to constraints in the actual performance of these applications and, therefore, scientific discovery. In-situ techniques, where data is visualized/analysed while still in memory rather than through disk, can contribute to alleviating these problems as they can reduce or even fully avoid data writing/reading through the IO subsystem to/from storage. However, the overall efficiency of insitu techniques crucially depends on the characteristics of both the in-situ tasks and the applications, and the resource distribution among them. Therefore, choosing the right in-situ approach (synchronous, asynchronous, or hybrid) and resource allocation is essential to minimize overhead and maximize the benefits of concurrent execution. In this paper, we present a performance model of in-situ techniques to find the most beneficial in-situ approach and the preferred resource configuration. We verify the high accuracy of our approach with over 6800 measurements and provide use cases with different applications.

Ju, Yi [Max Planck Computing and Data Facility, Ga↗
NASA NTRS2018

Toward Long-Term Aquatic Science Products from Heritage Landsat Missions

This paper aims at generating a long-term consistent record of Landsat-derived remote sensing reflectance (Rrs) products, which are central for producing downstream aquatic science products (e.g., concentrations of total suspended solids). The products are derived from Landsat-5 and Landsat-7 observations leading to Landsat-8 era to enable retrospective analyses of inland and nearshore coastal waters. In doing so, the data processing was built into the SeaWiFS Data Analysis System (SeaDAS) followed by vicariously calibrating Landsat-7 and -5 data using reference in situ measurements and near-concurrent ocean color products, respectively. The derived Rrs products are then validated using (a) matchups using the Aerosol Robotic Network (AERONET) data measured by in situ radiometers, i.e., AERONET-OC, and (b) ocean color products at select sites in North America. Following the vicarious calibration adjustments, it is found that the overall biases in Rrs products are significantly reduced. The root-mean-square errors (RMSE), however, indicate noticeable uncertainties due to random and systematic noise. Long-term (since 1984) seasonal Rrs composites over 12 coastal and inland systems are further evaluated to explore the utility of Landsat archive processed via SeaDAS. With all the qualitative and quantitative assessments, it is concluded that with careful algorithm developments, it is possible to discern natural variability in historic water quality conditions using heritage Landsat missions. This requires the changes in Rrs exceed maximum expected uncertainties, i.e., 0.0015 [1/sr], estimated from mean RMSEs associated with the matchups and intercomparison analyses. It is also anticipated that Landsat-5 products will be less susceptible to uncertainties in turbid waters with Rrs(660) > 0.004 [1/sr], which is equivalent of ~1.2% reflectance. Overall, end-users may utilize heritage Rrs products with "fitness-for-purpose" concept in mind, i.e., products could be valuable for one application but may not be viable for another. Further research should be dedicated to enhancing atmospheric correction to account for non-negligible near-infrared reflectance in CDOM-rich and extremely turbid waters.

Pahlevan, Nima↗
DOE OSTI2021

Out-of-equilibrium processes in crystallization of organic-inorganic perovskites during spin coating

Complex phenomena are prevalent during the formation of materials, which affect their processing-structure-function relationships. Thin films of methylammonium lead iodide (CH 3 NH 3 PbI 3 , MAPI) are processed by spin coating, antisolvent drop, and annealing of colloidal precursors. The structure and properties of transient and stable phases formed during the process are reported, and the mechanistic insights of the underlying transitions are revealed by combining in situ data from grazing-incidence wide-angle X-ray scattering and photoluminescence spectroscopy. Here, we report the detailed insights on the embryonic stages of organic-inorganic perovskite formation. The physicochemical evolution during the conversion proceeds in four steps: i) An instant nucleation of polydisperse MAPI nanocrystals on antisolvent drop, ii) the instantaneous partial conversion of metastable nanocrystals into orthorhombic solvent-complex by cluster coalescence, iii) the thermal decomposition (dissolution) of the stable solvent-complex into plumboiodide fragments upon evaporation of solvent from the complex and iv) the formation (recrystallization) of cubic MAPI crystals in thin film.

36 MATERIALS SCIENCE↗
NASA NTRS2011

Laboratory for Atmospheres: Instrument Systems Report

Studies of the atmospheres of our solar system's planets including our own require a comprehensive set of observations, relying on instruments on spacecraft, aircraft, balloons, and on the surface. Laboratory personnel define requirements, conceive concepts, and develop instrument systems for spaceflight missions, and for balloon, aircraft, and ground-based observations. Laboratory scientists also participate in the design of data processing algorithms, calibration techniques, and data processing systems. The instrument sections of this report are organized by measurement technique: lidar, passive, in situ and microwave. A number of instruments in various stages of development or modification are also described. This report will be updated as instruments evolve.

Source record↗
NASA NTRSDate not supplied

Relative Detectability of Iron-Bearing Phases for the Mars 2020 Sherloc Deep UV Raman Instrument: 1. Focusing on Carbonates

A deep ultraviolet (DUV) Raman and fluorescence instrument is a surface standoff instrument mounted on the robotic arm of the Mars 2020 (M2020) rover Perseverance, and it is a key element of the Scanning Habitable Environments with Luminescence for Organics and Chemicals (SHERLOC) investigation [1]. Measurement and science objectives include mineralogical and organic images (~100 μm/pixel) that map sub-millimeter spatial distributions and characterization of primary and secondary minerals, potential organics, and their interaction/alteration products. The results of data analysis pertain to understanding igneous and alteration processes on Mars through time, assessing habitability, evidencing in situ biosignatures, and, along with results from other Perseverance instruments, selecting samples to cache for Mars sample return. Acceptance of the SHERLOC investigation for the NASA M2020 mission [2] created a need for Mars-relevant DUV Raman spectra, particularly for inorganic materials [e.g., 3, 4]. As reported previously [e.g., 4, 5], phases with Fe cations as essential elements (e.g., siderite (FeCO3) and ankerite (FeCa(CO3)2) for carbonates) significantly hinder detection by DUV Raman because of intense absorption of incident and scattered DUV laser radiation by Fe cations. We report here the relative detectability of carbonates (Mg,Ca,Fe,Mn)CO3 by DUV Raman using a SHERLOC analog laboratory instrument.

R V Morris↗
DOE OSTI2024

Bayesian stability and force modeling for uncertain machining processes

Accurately simulating machining operations requires knowledge of the cutting force model and system frequency response. However, this data is collected using specialized instruments in an ex-situ manner. Bayesian statistical methods instead learn the system parameters using cutting test data, but to date, these approaches have only considered milling stability. This paper presents a physics-based Bayesian framework which incorporates both spindle power and milling stability. Initial probabilistic descriptions of the system parameters are propagated through a set of physics functions to form probabilistic predictions about the milling process. The system parameters are then updated using automatically selected cutting tests to reduce parameter uncertainty and identify more productive cutting conditions, where spindle power measurements are used to learn the cutting force model. The framework is demonstrated through both numerical and experimental case studies. Results show that the approach accurately identifies both the system natural frequency and cutting force model.

42 ENGINEERING↗