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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Improving the Confidence in Retrievals of Vertical Distributions of Cloud Condensation Nuclei Number Concentration from ARM Supported by Aircraft In Situ Observations

Accurate quantification of the vertical distribution of cloud condensation nuclei (CCN) number concentrations is critical for improving our understanding of aerosol–cloud interactions. Ground-based Raman lidars operated by the Atmospheric Radiation Measurement (ARM) program, together with surface CCN measurements, are used to retrieve vertically resolved CCN number concentrations (Retrieved Number concentration of CCN, RNCCN). These retrievals rely on several assumptions, including that aerosol composition is vertically homogeneous. To assess this assumption, we developed and tested a framework to infer the dominant aerosol classes/types at different altitudes. This was done by applying a k-Nearest-Neighbors (kNN) algorithm to lidar ratio and linear depolarization ratio measurements from Raman lidar. We evaluated the framework using aircraft aerosol and CCN measurements from the ARM Holistic Interactions of Shallow Clouds, Aerosols, and Land Ecosystems (HI-SCALE) field campaign. The results show that RNCCN performance degrades as vertical aerosol complexity increases, i.e., RNCCN agrees with the aircraft CCN in vertically homogeneous conditions, but closure decreases in layered aerosol structures. To generalize beyond individual examples, we introduce a metric (heterogeneity index) that quantifies the vertical complexity by assessing the variation of inferred aerosol classes/types. Case-level statistics show a tendency for RNCCN and aircraft differences to increase with this metric. By detecting retrievals that are likely compromised by aerosol vertical heterogeneity, the proposed framework improves the interpretability and effective use of RNCCN used for long-term evaluation of models and aerosol–cloud interactions.

Tian, Jingjing↗
DOE OSTI2024

A robust approach to Gaussian process implementation

Abstract. Gaussian process (GP) regression is a flexible modeling technique used to predict outputs and to capture uncertainty in the predictions. However, the GP regression process becomes computationally intensive when the training spatial dataset has a large number of observations. To address this challenge, we introduce a scalable GP algorithm, termed MuyGPs, which incorporates nearest-neighbor and leave-one-out cross-validation during training. This approach enables the evaluation of large spatial datasets with state-of-the-art accuracy and speed in certain spatial problems. Despite these advantages, conventional quadratic loss functions used in the MuyGPs optimization, such as root mean squared error (RMSE), are highly influenced by outliers. We explore the behavior of MuyGPs in cases involving outlying observations and, subsequently, develop a robust approach to handle and mitigate their impact. Specifically, we introduce a novel leave-one-out loss function based on the pseudo-Huber function (LOOPH) that effectively accounts for outliers in large spatial datasets within the MuyGPs framework. Our simulation study shows that the LOOPH loss method maintains accuracy despite outlying observations, establishing MuyGPs as a powerful tool for mitigating unusual observation impacts in the large data regime. In the analysis of US ozone data, MuyGPs provides accurate predictions and uncertainty quantification, demonstrating its utility in managing data anomalies. Through these efforts, we advance the understanding of GP regression in spatial contexts.

Mukangango, Juliette↗
DOE OSTI2023

Evaluation of native Earth system model output with ESMValTool v2.6.0

Earth system models (ESMs) are state-of-the-art climate models that allow numerical simulations of the past, present-day, and future climate. To extend our understanding of the Earth system and improve climate change projections, the complexity of ESMs heavily increased over the last decades. As a consequence, the amount and volume of data provided by ESMs has increased considerably. Innovative tools for a comprehensive model evaluation and analysis are required to assess the performance of these increasingly complex ESMs against observations or reanalyses. One of these tools is the Earth System Model Evaluation Tool (ESMValTool), a community diagnostic and performance metrics tool for the evaluation of ESMs. Input data for ESMValTool needs to be formatted according to the CMOR (Climate Model Output Rewriter) standard, a process that is usually referred to as “CMORization”. While this is a quasi-standard for large model intercomparison projects like the Coupled Model Intercomparison Project (CMIP), this complicates the application of ESMValTool to non-CMOR-compliant climate model output. In this paper, we describe an extension of ESMValTool introduced in v2.6.0 that allows seamless reading and processing of “native” climate model output, i.e., operational output produced by running the climate model through the standard workflow of the corresponding modeling institute. This is achieved by an extension of ESMValTool's preprocessing pipeline that performs a CMOR-like reformatting of the native model output during runtime. Thus, the rich collection of diagnostics provided by ESMValTool is now fully available for these models. For models that use unstructured grids, a further preprocessing step required to apply many common diagnostics is regridding to a regular latitude–longitude grid. Extensions to ESMValTool's regridding functions described here allow for more flexible interpolation schemes that can be used on unstructured grids. Currently, ESMValTool supports nearest-neighbor, bilinear, and first-order conservative regridding from unstructured grids to regular grids. Example applications of this new native model support are the evaluation of new model setups against predecessor versions, assessing of the performance of different simulations against observations, CMORization of native model data for contributions to model intercomparison projects, and monitoring of running climate model simulations. For the latter, new general-purpose diagnostics have been added to ESMValTool that are able to plot a wide range of variable types. Currently, five climate models are supported: CESM2 (experimental; at the moment, only surface variables are available), EC-Earth3, EMAC, ICON, and IPSL-CM6. As the framework for the CMOR-like reformatting of native model output described here is implemented in a general way, support for other climate models can be easily added.

58 GEOSCIENCES↗
DOE OSTI2023

CRISPR-COPIES: Web Tool

CRISPR/Cas system has emerged as a powerful genome-editing tool for metabolic engineering and human gene therapy. However, the conundrum of where to integrate heterologous genes on the chromosome using the CRISPR/Cas system remains an open question. Selecting a site for gene integration requires incorporation of complex criteria such as factors involved in CRISPR/Cas-mediated integration, genetic stability, and gene expression and therefore, usually requires strenuous characterization of sites on particular or different chromosomal locations. To address these issues, we developed CRISPR-COPIES, a COmputational Pipeline for the Identification of CRISPR/Cas-facilitated intEgration Sites. The tool applies ScaNN, a state-of-the-art model on the embedding-based nearest neighbor search for fast and accurate off-target search and can identify genome-wide intergenic sites for most bacterial and fungal genomes within minutes. This submission contains the code we developed to create a user-friendly web interface for CRISPR-COPIES (https://biofoundry.web.illinois.edu/copies/). We anticipate CRISPR-COPIES will serve as a useful tool for targeted DNA integration and aid in the characterization of synthetic biology toolkits, rapid strain construction to produce valuable biochemicals, and human gene and cell therapy.

Bioinformatics↗
DOE OSTI2022

kasacrgridppi.c1

This datastream is made by kasacrgridppi VAP. It has (time, Y, X) gridded Ka-band PPI radar data, using nearest neighbor algorithm, with calibrated (.b1) input. This datastream is very similar to kasacrgridrhi, with the output grid changed from (time, height, h_distance) to (time, Y, X). output c1 level data use calibrated b1 data as input.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

xsacrgridppi.c0

This datastream is made by xsacrgridppi VAP. It has (time, Y, X) gridded Ka-band PPI radar data, using nearest neighbor algorithm, with uncalibrated (.a1) input.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

xsacrgridppi.c1

This datastream is made by xsacrgridppi VAP. It has (time, Y, X) gridded Ka-band PPI radar data, using nearest neighbor algorithm, with calibrated (.b1) input.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1968

Vacancy relaxations in b.c.c. crystals.

Vacancy relaxations in bcc crystals using energy dependence on radial displacements from defect of nearest neighbor sets, discussing crystal size and shape

Grimes, H. H.↗
NASA NTRS1971

Nonparametric Bayer-risk estimation

Nonparametric Bayes risk estimation for measurement classification, using nearest neighbor error rate and Parzen probability density function estimators

Fralick, S. C.↗
NASA NTRS1971

Surface field analysis of splitting of orbitals of atoms and ions approaching a metal surface.

The splitting of p- and d-orbitals of an atom or an ion which is caused by the locally varying potential near the surface of a realistic metal has been studied for bcc and fcc substrates. A quasi-ionic model is reasonable at close distance, inasmuch as the electron gas does not completely screen the ionic cores. The arrangement of ion cores near the surface causes the potential to vary in three dimensions. Expressions for energy levels were derived for an unsymmetric group using the quasi-ionic model and techniques used in the treatment of crystal field of nearest neighbors. A number of cases involving ions, as well as atoms in the vicinity of a metal substrate were numerically evaluated.

Rao, P. V. S.↗
NASA NTRS1972

Preferential orientation of CO adsorption on Ni as determined by extended Hueckel calculations.

The adsorption of CO on the nickel surface has been calculated using a modified extended Hueckel technique for a number of different orientations of the CO with respect to the nickel surface. The calculations show that double site adsorption with the CO molecule normal to the surface and the carbon atom closest to the metal gives the most stable configuration (2.57 eV). The single site absorbs with an energy of 2.39 eV. However, other configurations also give fairly large bonding energies. The CO normal to the surface with oxygen closest to the metal gives a heat of adsorption of 0.37 eV. Two-center adsorption with the CO axis parallel to the surface and the molecule symmetrically placed between the nearest neighbors gives a chemisorption energy of 1.34 eV. These values compare with an experimental value of 1.98 eV.

Robertson, J. C.↗
NASA NTRS1973

Evaluation of usefulness of Skylab EREP S-190 and S-192 imagery in multistage forest surveys

The author has identified the following significant results. A set of digital interpretation programs have been developed which perform the following tasks: (1) extraction of images for a desired sample unit or combination of sample units by scanner channel and storage of these images on high speed storage devices; (2) extraction of tone and texture information of 8 x 8 pixel interpretation units by channel and storage of these features on a high speed storage device; (3) center of gravity cluster node seeking in higher dimensional space and subsequent nearest neighbor classification, and output of the classification results on a high speed storage device. In all instances the classification results can be related to the original place of subset extraction through the coordinate transformation work previously performed.

Langley, P. G.↗
NASA NTRS1971

The minimum distance approach to classification

The work to advance the state-of-the-art of miminum distance classification is reportd. This is accomplished through a combination of theoretical and comprehensive experimental investigations based on multispectral scanner data. A survey of the literature for suitable distance measures was conducted and the results of this survey are presented. It is shown that minimum distance classification, using density estimators and Kullback-Leibler numbers as the distance measure, is equivalent to a form of maximum likelihood sample classification. It is also shown that for the parametric case, minimum distance classification is equivalent to nearest neighbor classification in the parameter space.

Wacker, A. G.↗
NASA NTRS1973

Use of spatial information in classification of remotely sensed data

The use is discussed of spatial information for improving classification accuracy of remotely sensed data. In particular a simple example (the unanimous four nearest neighbor rule) is discussed and its results are presented. This algorithm results in improved classifications accuracy (one to five percentage points) and costs little in execution time. Other schemes for improving classification accuracy are also discussed.

Vanroony, D. L.↗
NASA NTRS1973

A dimensionality reducing model for distributed filtering.

An approach is made to filtering of two-dimensional steady-state problems based on the notion of nearest neighbor interaction, i.e., at a given point in the spatial grid, the value at the variable of interest can be assumed to depend only on the values at adjacent grid points. It is shown that for linear steady-state problems significant dimensionality reductions can be accomplished. It was possible to achieve the desired results using a small amount of computer time and without getting into stability difficulties.

Angel, E.↗