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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Extending XBAER Algorithm to Aerosol and Cloud Condition

The retrieval of cloud optical properties for aerosol contaminated water cloud is challenging because of the complexity of physical processes in such situations. Conventionally, cloud optical data products are typically derived, ignoring the aerosol impacts on radiative transfer in the retrieval process. This is potentially a significant source of error. In this paper, the eXtensible Bremen Aerosol Retrieval (XBAER) algorithm has been optimized for the retrieval of aerosol/cloud properties for the aerosol contaminated cloud (ACC) scenarios. This version of XBAER delivers cloud optical thickness (COT) and cloud effective radius (CER) for ACCs and simultaneously retrieves aerosol optical thickness (AOT). The surface parameterization and aerosol types used in the standard XBAER algorithm have been adapted in this retrieval to account for the ACC conditions. Aerosol types in XBAER for the retrieval of ACC scenarios have been parameterized to comprise weak and strong absorptions. The comparisons of COT, CER, and AOT retrieved using this adapted XBAER algorithm and two new NASA algorithms show good agreements, especially for biomass burning aerosol. The correlation coefficients are >0.9 for AOT, ~0.8 for CER, and ~0.7 for COT. There is also a good agreement for dust plume contaminated cloud scene. The XBAER derived AOT values for dust aerosols are systematically smaller than the NASA retrieval, but both products have the same spatial distribution patterns. The comparison of COT retrieved using the adapted XBAER algorithm and that retrieved from ground-based microwave radiometer (MWR) measurements shows much better agreement for ACC conditions with high AOT.

satellite↗
DOE OSTI2023

Systems and methods for generating a graded lattice structure and their application to additive manufacturing

Systems and methods for generating graded lattice structures that can be used as infill for additively manufactured articles. Tailored sectioning and field-based smoothing are modified polygon, e.g., circle, packing algorithms that adjust the size of the circles based on physical field data to adapt the infill generation process to a field expected to be experienced by the article. Molecular dynamically generated lattice infill is based on force balancing a node distribution instead of a circle packing. Field data can be utilized to adjust the spacing of the node distribution according to a force balance equilibrium model that accounts for the field expected to be experienced by the article being additively manufactured. The resultant non-uniform honeycomb structures from tailored sectioning, field-based smoothing, and force-balancing robustly and efficiently address the connection issues with traditional non-uniform lattice structures.

Kim, Seokpum↗
NASA NTRS1984

Use of the TM tasseled cap transform for interpretation of spectral contrasts in an urban scene

Investigations are being conducted with the objective to develop automated numerical image analysis procedures. In this context, an examination is performed of physically-based multispectral data transforms as a means to incorporate a priori knowledge of land radiance properties in the analysis process. A physically-based transform of TM observations was developed. This transform extends the Landsat MSS Tasseled Cap transform reported by Kauth and Thomas (1976) to TM data observations. The present study has the aim to examine the utility of the TM Tasseled Cap transform as applied to TM data from an urban landscape. The analysis conducted is based on 512 x 512 subset of the Washington, DC November 2, 1982 TM scene, centered on Springfield, VA. It appears that the TM tasseled cap transformation provides a good means to explain land physical attributes of the Washington scene. This result provides a suggestion regarding a direction by which a priori knowledge of landscape spectral patterns may be incorporated into numerical image analysis.

Goward, S. N.↗
DOE OSTI2021

Extraction of the muon signals recorded with the surface detector of the Pierre Auger Observatory using recurrent neural networks

The Pierre Auger Observatory, at present the largest cosmic-ray observatory ever built, is instrumented with a ground array of 1600 water-Cherenkov detectors, known as the Surface Detector (SD). The SD samples the secondary particle content (mostly photons, electrons, positrons and muons) of extensive air showers initiated by cosmic rays with energies ranging from 1017eV up to more than 1020eV. Measuring the independent contribution of the muon component to the total registered signal is crucial to enhance the capability of the Observatory to estimate the mass of the cosmic rays on an event-by-event basis. However, with the current design of the SD, it is difficult to straightforwardly separate the contributions of muons to the SD time traces from those of photons, electrons and positrons. In this paper, we present a method aimed at extracting the muon component of the time traces registered with each individual detector of the SD using Recurrent Neural Networks. We derive the performances of the method by training the neural network on simulations, in which the muon and the electromagnetic components of the traces are known. We conclude this work showing the performance of this method on experimental data of the Pierre Auger Observatory. We find that our predictions agree with the parameterizations obtained by the AGASA collaboration to describe the lateral distributions of the electromagnetic and muonic components of extensive air showers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
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↗
NASA NTRS2012

Chondritic Models of 4 Vesta: Comparison of Predicted Internal Structure and Surface Composition/Mineralogy with Data from the Dawn Mission

Understanding the physical and chemical processes which led to the formation of the terrestrial planets remains one of the principal challenges of the Earth and planetary science communities. However, direct traces of the earliest stages of planet building have generally been wiped out on larger bodies such as the Earth or Mars, obscuring our view of how that process occurred. On the other hand, the planet building process would appear to have been arrested prematurely in the region between Mars and Jupiter, now populated by several hundred thousand compositionally diverse objects that escaped accretion into larger planets. Of these, the asteroid 4 Vesta is of particular interest as it is large (520 km diameter), and known to have a basaltic surface dominated by pyroxenes [1, 2]. Furthermore, visible-IR spectra of Vesta obtained by ground and space-based telescopes are remarkably similar to laboratory spectra measured on meteorites of the Howardite-Eucrite-Diogenite clan (HED), leading to the paradigm that the HEDs came from Vesta [2]. Geochemical and petrological studies of the HEDs confirm the differentiated nature of the near-surface region of their parent body, and imply that crust extraction occurred well within the first 10Ma of solar system history [3]. Vesta is therefore a prime target for studies that aim to constrain the earliest stages of planet building, and for that reason it is currently the subject of the Dawn mission [4].

Toplis, M. J.↗
NASA NTRS2016

Early Spring Post-Fire Snow Albedo Dynamics in High Latitude Boreal Forests Using Landsat-8 OLI Data

Taking advantage of the improved radiometric resolution of Landsat-8 OLI which, unlike previous Landsat sensors, does not saturate over snow, the progress of fire recovery progress at the landscape scale (less than 100 m) is examined. High quality Landsat-8 albedo retrievals can now capture the true reflective and layered character of snow cover over a full range of land surface conditions and vegetation densities. This new capability particularly improves the assessment of post-fire vegetation dynamics across low- to high-burn severity gradients in Arctic and boreal regions in the early spring, when the albedos during recovery show the greatest variation. We use 30 m resolution Landsat-8 surface reflectances with concurrent coarser resolution (500 m) MODIS high quality full inversion surface Bidirectional Reflectance Distribution Functions (BRDF) products to produce higher resolution values of surface albedo. The high resolution full expression shortwave blue sky albedo product performs well with an overall RMSE of 0.0267 between tower and satellite measures under both snow-free and snow-covered conditions. While the importance of post-fire albedo recovery can be discerned from the MODIS albedo product at regional and global scales, our study addresses the particular importance of early spring post-fire albedo recovery at the landscape scale by considering the significant spatial heterogeneity of burn severity, and the impact of snow on the early spring albedo of various vegetation recovery types. We found that variations in early spring albedo within a single MODIS gridded pixel can be larger than 0.6. Since the frequency and severity of wildfires in Arctic and boreal systems is expected to increase in the coming decades, the dynamics of albedo in response to these rapid surface changes will increasingly impact the energy balance and contribute to other climate processes and physical feedback mechanisms. Surface radiation products derived from Landsat-8 data will thus play an important role in characterizing the carbon cycle and ecosystem processes of high latitude systems.

Landsat-8 snow albedo↗
DOE OSTI2025

Meld: A project for exploring how to meet DUNE's framework needs

Existing data-processing frameworks for HEP experiments are largely based on collider-physics concepts, which may be based on rigid, event-based data hierarchies. These data organizations are not always helpful for neutrino experiments, which must sometimes work around such restrictions by manually splitting apart events into constructs that are better suited for neutrino physics. The purpose of Meld is to explore more flexible data organizations by treating a frameworks job as: (1) A graph of data-product sequences connected by (2) User-defined functions that serve as operations to (3) Framework-provided higher-order functions.

Knoepfel, KyleJ. [Fermi National Accelerator Labor↗
NASA NTRS1991

Physical processes in the plasma mantle of Venus

The results are presented of a study, which analyzed data from 10 Pioneer Venus orbits in order to see whether similar wave particle interaction processes also exist in the corresponding region around Venus. The first conclusion is that the apparent physical processes in the mantle are indeed similar around Venus and Mars. The planetary thermal O(+) ions outside the ionopause interact with the shocked solar wind and excite electrostatic waves close to the lower hybrid frequency. These waves propagate inwards, heating first the electron and deeper down in the ionosphere the thermal ion population. The observed superthermal ions are believed to be the product of this wave particle interaction process. It is also concluded that the wave energy transferred to the thermal electrons is of the right magnitude (about 4 x 10 exp 9 eV/sq cm s) to provide the supplemental heat source necessary to reconcile observed and calculated electron temperatures in the ionosphere.

Szego, K.↗
DOE OSTI2021

Feature Extraction: Improving Remote Sensor Classification of Non-Proliferation

This research focuses on developing algorithms for nuclear non-proliferation detection using remote sensor modeling. To improve the performance of classification models, we implemented a data pipeline with feature extraction. This pipeline takes raw data and transforms it into smaller data points called features that still describe the model. Improving this classification works towards the departments of energy’s missions of ensuring American’s security and prosperity by creating technology that addresses nuclear challenges. To conduct this analysis, we used the Python programming language and some key packages, including tsfresh and TSFEL. Originally tsfresh was selected because it has the most statistical features out of all the packages. Later TSFEL was incorporated due to the additional features it can extract from data, such as temporal and spectral. However, feature extraction becomes challenging in the presence of missing values. In this case, two additional Python packages were added to our workflow, NumPy and pandas, allowing for the feature extraction process to handle unknown values. Our data pipeline was tested on data collected from a simulation that describes the process state of a physical example. The results show the pipeline’s capability to consume and extract a total 17 features from tabular data. Future work includes producing classifications using decision tree-based models such as XGBoost and improving data collection by analyzing feature importance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1979

Process feasibility study in support of silicon material, task 1

Analyses of process system properties were continued for materials involved in the alternate processes under consideration for semiconductor silicon. Primary efforts centered on physical and thermodynamic property data for dichlorosilane. The following property data are reported for dichlorosilane which is involved in processing operations for solar cell grade silicon: critical temperature, critical pressure, critical volume, critical density, acentric factor, vapor pressure, heat of vaporization, gas heat capacity, liquid heat capacity and density. Work was initiated on the assembly of a system to prepare binary gas mixtures of known proportions and to measure the thermal conductivity of these mixtures between 30 and 350 C. The binary gas mixtures include silicon source material such as silanes and halogenated silanes which are used in the production of semiconductor silicon.

Li, K. Y.↗
DOE OSTI2022

The LLNL nuclear data infrastructure for the GNDS data format

The next generation of nuclear data infrastructure tools at the Livermore National Laboratory (LLNL) consists of pipeline of codes that read and process nuclear data from evaluated files saved in the new GNDS (Generalised Nuclear Data Structure) nuclear data format. The processing code FUDGE (For Updating Data and Generating Evaluations) is at the front-end of this pipeline as it reads and process the evaluated data for use in downstream transport codes. FUDGE is Python based with C and C++ extensions for computationally intensive tasks. As is the case for the evaluated data, the processed output is also saved in the GNDS format and the GIDI+ API is provided as the interface between the processed data and the transport codes. GIDI+ is a C++ based suite of codes and it includes GIDI (General Interaction Data Interface), a library for reading and writing GNDS data, and MCGIDI which is the cross section lookup, and reaction and product distribution sampling interface between Monte Carlo transport codes and the GNDS data. GIDI provides methods for easy access to the multi-group processed GNDS data and this is demonstrated through its implementation in ARDRA, the LLNL deterministic transport code. The evaluation and sampling methods in MCGIDI are available as both CPU and GPU methods which facilitates the use of MCGIDI in both traditional CPU-based as well as the next generation mixed model computational architectures. This is demonstrated through the GIDI+ implementation in MERCURY, the LLNL Monte Carlo transport code. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2007

Measurement and Simulation of the Variation in Proton-Induced Energy Deposition in Large Silicon Diode Arrays

The proton induced charge deposition in a well characterized silicon P-i-N focal plane array is analyzed with Monte Carlo based simulations. These simulations include all physical processes, together with pile up, to accurately describe the experimental data. Simulation results reveal important high energy events not easily detected through experiment due to low statistics. The effects of each physical mechanism on the device response is shown for a single proton energy as well as a full proton space flux.

Howe, Christina L.↗
DOE OSTI2024

Materials Characterization, Prediction and Control Project: Summary Report on Data Analytics Framework

This report summarizes the activities performed under the data analytics Vertex in the Materials Characterization, Prediction and Control Project funded under laboratory directed research and development at Pacific Northwest National Laboratory. The data analytics Vertex developed models for associating global or local process parameters, microstructural features, and performance properties of friction-stir-processed 316L stainless steel plates. Statistical, machine learning, and deep learning models, as well as generative artificial intelligence approaches, were used to develop the associations between the process-structure-property data streams. These associations formed the basis for predicting global properties of parts manufactured under different process envelopes, providing a basis for predicting performance using data driven as well as physics-informed and physics-constrained approaches. Additionally, the associations were used to predict local process parameters and microstructural features of the product, predictive relationships that have the potential to form the basis of a control framework that could eventually modulate a friction-stir process to maintain product quality.

316L stainless steel↗
NASA NTRS1977

Remote sensing data processing: Two years ago, today, and two years from today

Beginning with a survey of the state-of-the-art of processing remotely sensed data in early 1975, significant developments between that time and the present are chronicled, and technologies for early 1979 are projected. Current technical issues discussed include: training selection and labeling; classification and mensuration; use of satellite indicators to supplement predictions; small scale field structures; physical factors; ancillary data; geometric quality; and the cost of processing.

Holmes, Q. A.↗
NASA NTRS2006

Characterizing diurnal and seasonal cycles in monsoon systems from TRMM and CEOP observations

The CEOP Inter-Monsoon Study (CIMS) is one of the two main science drivers of CEOP that aims to (a) provide better understanding of fundamental physical processes in monsoon regions around the world, and (b) demonstrate the synergy and utility of CEOP data in providing a pathway for model physics evaluation and improvement. As the data collection phase for EOP-3 and EOP-4 is being completed, two full annual cycles (2003-2004) of research-quality data sets from satellites, reference sites, and model output location time series (MOLTS) have been processed and made available for data analyses and model validation studies. This article presents preliminary results of a CIMS study aimed at the characterization and intercomparison of all major monsoon systems. The CEOP reference site data proved its value in such exercises by being a powerful tool to cross-validate the TRMM data, and to intercompare with multi-model results in ongoing work. We use 6 years (1998-2003) of pentad CEOP/TRMM data with 2deg x 2.5deg latitude-longitude grid, over the domain of interests to define the monsoon climatological diurnal and annual cycles for the East Asian Monsoon (EAM), the South Asian Monsoon (SAM), the West Africa Monsoon (WAM), the North America/Mexican Monsoon (NAM), the South American Summer Monsoon (SASM) and the Australian Monsoon (AUM). As noted, the TRMM data used in the study were cross-validated using CEOP reference site data, where applicable. Results show that the observed diurnal cycle of rain peaked around late afternoon over monsoon land, and early morning over the oceans. The diurnal cycles in models tend to peak 2-3 hours earlier than observed. The seasonal cycles of the EAM and SAM show the strongest continentality, i.e, strong control by continental processes away from the ITCZ. The WAM, and the AUM shows the less continentality, i.e, strong control by the oceanic ITCZ.

Lau, William K. M.↗
NASA NTRS2007

Characterizing Diurnal and Seasonal Cycles in Monsoon Systems from TRMM and CEOP Observations

The CEOP Inter-Monsoon Study (CIMS) is one of the two main science drivers of CEOP that aims to (a) provide better understanding of fundamental physical processes in monsoon regions around the world, and (b) demonstrate the synergy and utility of CEOP data in providing a pathway for model physics evaluation and improvement. As the data collection phase for EOP-3 and EOP-4 is being completed, two full annual cycles (2003-2004) of research-quality data sets from satellites, reference sites, and model output location time series (MOLTS) have been processed and made available for data analyses and model validation studies. This article presents preliminary results of a CIMS study aimed at the characterization and intercomparison of all major monsoon systems. The CEOP reference site data proved its value in such exercises by being a powerful tool to cross-validate the TRMM data, and to intercompare with multi-model results in ongoing work. We use 6 years (1998-2003) of pentad CEOP/TRMM data with 2 deg x 2.5 deg. latitude-longitude grid, over the domain of interests to define the monsoon climatological diurnal and annual cycles for the East Asian Monsoon (EAM), the South Asian Monsoon (SAM), the West Africa Monsoon (WAM), the North America/Mexican Monsoon (NAM), the South American Summer Monsoon (SASM) and the Australian Monsoon (AUM). As noted, the TRMM data used in the study were cross-validated using CEOP reference site data, where applicable. Results show that the observed diurnal cycle of rain peaked around late afternoon over monsoon land, and early morning over the oceans. The diurnal cycles in models tend to peak 2-3 hours earlier than observed. The seasonal cycles of the EAM and SAM show the strongest continentality, i.e, strong control by continental processes away from the ITCZ. The WAM, and the AUM shows the less continentality, i.e, strong control by the oceanic ITCZ.

Lau, William K. M.↗