SEARCH · Engineering Papers

Results for “data quality analysis”

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.

SourceResearch connectionFrom yearThrough year

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

At least 1,117 records · Page 62

All sources NASA NTRS DOE OSTI

DOE OSTI2024

From soil to sequence: filling the critical gap in genome-resolved metagenomics is essential to the future of soil microbial ecology

Abstract Soil microbiomes are heterogeneous, complex microbial communities. Metagenomic analysis is generating vast amounts of data, creating immense challenges in sequence assembly and analysis. Although advances in technology have resulted in the ability to easily collect large amounts of sequence data, soil samples containing thousands of unique taxa are often poorly characterized. These challenges reduce the usefulness of genome-resolved metagenomic (GRM) analysis seen in other fields of microbiology, such as the creation of high quality metagenomic assembled genomes and the adoption of genome scale modeling approaches. The absence of these resources restricts the scale of future research, limiting hypothesis generation and the predictive modeling of microbial communities. Creating publicly available databases of soil MAGs, similar to databases produced for other microbiomes, has the potential to transform scientific insights about soil microbiomes without requiring the computational resources and domain expertise for assembly and binning.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Analysis of Tank 38H (HTF-38-22-91, -92) and Tank 43H (HTF-43-22-93, -94) Samples for Support of the Enrichment Control and Corrosion Control Programs

SRNL analyzed samples from Tank 38H and Tank 43H to support ECP and CCP. The results indicate the concentrations of most soluble species in the Tank 38H surface sample increased slightly from the previous surface sample. The Tank 38H sub-surface sample shows changes in concentration for soluble species in the solution with some increasing and some decreasing. The current Tank 38H sub-surface sample contains more sludge solids than the previous sample based on visual appearance. The small differences in the concentrations of major components between the Tank 38H surface and sub-surface samples indicate only minimal stratification of solution species within the tank. The Tank 43H surface and sub-surface samples are similar in composition to the previous samples. The similar solution compositions measured in the Tank 43H surface and sub-surface samples indicate a minimal stratification within the tank. The total uranium and plutonium in the current Tank 38H surface sample remains similar to the previous analysis. The Tank 38H sub-surface sample shows an increase in uranium and plutonium concentrations compared to the previous sample likely because of an increase in sludge solids in the current sample. The total uranium concentration in the two Tank 43H samples is essentially unchanged from previous sample results. The plutonium concentration in the Tank 43H surface sample is similar to the previous sample results while the plutonium in the Tank 43H sub-surface sample increased relative to the previous analysis. The sum of the major cations versus the sum of the major anions shows a difference of <10% for both samples from Tank 38H and for both samples from Tank 43H providing an indication of good data quality for the non-radioactive analytes in the samples. The silicon concentrations measured in the Tank 38H sub-surface sample increased compared with the previous sample results likely due to the presence of more sludge solids in the current sample. The Tank 38H surface sample silicon concentrations is similar to the previous sample results. The Tank 43H surface and sub-surface sample silicon concentrations both increased compared to the previous sample results. The samples analyzed from Tanks 38H and 43H show silicon concentrations ranging from 61.5 to 97.3 mg/L.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS1980

The operational use of Landsat for lake quality assessment

A cooperative program between the Wisconsin Department of Natural Resources and the University of Wisconsin for the assessment, with Landsat data, of the trophic status of all the significant inland lakes in Wisconsin is described. The analysis technique is a semiautomatic data acquisition and handling system which, in conjunction with an analytical categorization scheme, can be used for classifying inland lakes into one of seven categories of eutrophication and one of four problem types.

Scarpace, F. L.↗

NASA NTRS1978

Buckling tests of structural elements applicable to large erectable space trusses

Detailed data on columns and center a joint for completeness is presented. Buckling data for a tripod arrangement of these columns using a cluster joint is also presented. The objectives of these test are: (1) to gain insight into joint requirements for truss structure; (2) to assess the structural qualities of the column and center joint designs; (3) to investigate the restraint provided by octetruss core members (tripod) to the cluster joints; (4) to provide insight into the level of analysis required to predict buckling behavior of Gr/E nestable columns both as simple columns and in a tripod arrangement; and (5) to provide a data base for Gr/E nestable columns.

Heard, W. L., Jr.↗

NASA NTRS2003

Fractals and Spatial Methods for Mining Remote Sensing Imagery

The rapid increase in digital remote sensing and GIS data raises a critical problem -- how can such an enormous amount of data be handled and analyzed so that useful information can be derived quickly? Efficient handling and analysis of large spatial data sets is central to environmental research, particularly in global change studies that employ time series. Advances in large-scale environmental monitoring and modeling require not only high-quality data, but also reliable tools to analyze the various types of data. A major difficulty facing geographers and environmental scientists in environmental assessment and monitoring is that spatial analytical tools are not easily accessible. Although many spatial techniques have been described recently in the literature, they are typically presented in an analytical form and are difficult to transform to a numerical algorithm. Moreover, these spatial techniques are not necessarily designed for remote sensing and GIS applications, and research must be conducted to examine their applicability and effectiveness in different types of environmental applications. This poses a chicken-and-egg problem: on one hand we need more research to examine the usability of the newer techniques and tools, yet on the other hand, this type of research is difficult to conduct if the tools to be explored are not accessible. Another problem that is fundamental to environmental research are issues related to spatial scale. The scale issue is especially acute in the context of global change studies because of the need to integrate remote-sensing and other spatial data that are collected at different scales and resolutions. Extrapolation of results across broad spatial scales remains the most difficult problem in global environmental research. There is a need for basic characterization of the effects of scale on image data, and the techniques used to measure these effects must be developed and implemented to allow for a multiple scale assessment of the data before any useful process-oriented modeling involving scale-dependent data can be conducted. Through the support of research grants from NASA, we have developed a software module called ICAMS (Image Characterization And Modeling System) to address the need to develop innovative spatial techniques and make them available to the broader scientific communities. ICAMS provides new spatial techniques, such as fractal analysis, geostatistical functions, and multiscale analysis that are not easily available in commercial GIS/image processing software. By bundling newer spatial methods in a user-friendly software module, researchers can begin to test and experiment with the new spatial analysis methods and they can gauge scale effects using a variety of remote sensing imagery. In the following, we describe briefly the development of ICAMS and present application examples.

Lam, Nina↗

NASA NTRS2006

Use of the JPL Electronic Nose to detect leaks and spills in an enclosed environment

An electronic nose to be used as an air quality monitor in human habitats in space has been developed at the Jet Propulsion Laboratory. This device is capable of detecting, identifying and quantifying several organic and inorganic chemical species which might be present as contaminants in spacecraft air. The complete portable device, including sensors, electronics, and software for data analysis, has been extensively tested.

environmental monitoring↗

DOE OSTI2021

INGENIOUS Thermal Conductivity Measurement Source Categorization

Thermal conductivity (TC) data taken for different wells at a specified drill depth. This is an abridged version of the complete SMU heat flow database, downloaded from the SMU node of the NGDS at the beginning of INGENIOUS (approximately April 2021), and filtered to the INGENIOUS study area. This National Geothermal Data System (NGDS) project aggregates geothermal data collected and curated by the SMU Geothermal Laboratory and its partner organizations. All columns in this database are the same as the SMU database, except for 2 additions associated with this project. Repeated columns are for data correlation purposes. Column descriptions and data types are the same as previous iterations of the SMU database. The new values that are the addition are two new columns developed as part of the INGENIOUS project: INGENIOUS TC Value | INGENIOUS notes INGENIOUS notes are individual notes that were written for specific data points during the analysis process. There are not always notes associated with each input value. INGENIOUS TC Value includes 4 values: 1. Assumed Measured These are values that are assumed to be measured thermal conductivity values, either within a specific well or within the same study region. Many of these have either a published reference, a reported standard deviation, or a unique thermal conductivity value. 2. Data release - assumed measured These are values in the SMU database that are from proprietary data that were added to the SMU database and are labeled as data release for their reference. These values were searched for in person at the SMU Geothermal Laboratory as well as virtual examination of data available on the NGDS. For many of these, there are reported thermal conductivity values associated with the heat flow data in the database, but no specific table or reference to measurements in the original data release files. 3. Known measured These are values that have a reported measurement, either as an original file in the SMU data files on the NGDS or a reported table in a publication. In the rare circumstances, Maria Richards or David Blackwell confirmed measurement. Confirmation of measurement would be written in the INGENIOUS notes column. 4. Unmeasured Unmeasured values are those that are known to be unmeasured, either estimated from another report or no information given. In the SMU database, there are wells that have a heat flow but no thermal conductivity. These are categorized as unmeasured. There are also heat flow values that are stated to have estimated or generalized average thermal conductivity values for the region and rock type. Because these are known to be unmeasured, they are categorized as such. 5. Blank Blank values are either A quality or X quality. These quality values are stated in the INGENIOUS notes. These values were not going to change associated with the heat flow analysis, so these were not examined.

15 GEOTHERMAL ENERGY↗

NASA NTRS2001

Sun and Sky Radiance Measurements and Data Analysis Protocols

This chapter is concerned with two types of radiometric measurements essential to verify atmospheric correction algorithms and to calibrate vicariously satellite ocean color sensors. The first type is a photometric measurement of the direct solar beam to determine the optical thickness of the atmosphere. The intensity of the solar beam can be measured directly, or obtained indirectly from measurements of diffuse global upper hemispheric irradiance. The second type is a measurement of the solar aureole and sky radiance distribution using a CCD camera, or a scanning radiometer viewing in and perpendicular to the solar principal plane. From the two types of measurements, the optical properties of aerosols, highly variable in space and time, can be derived. Because of the high variability, the aerosol properties should be known at the time of satellite overpass. Atmospheric optics measurements, however, are not easy to perform at sea, from a ship or any platform. This complicates the measurement protocols and data analysis. Some instrumentation cannot be deployed at sea, and is limited to island and coastal sites. In the following, measurement protocols are described for radiometers commonly used to measure direct atmospheric transmittance and sky radiance, namely standard sun photometers, fast-rotating shadow-band radiometers, automated sky scanning systems, and CCD cameras. Methods and procedures to analyze and quality control the data are discussed, as well as proper measurement strategies for evaluation of atmospheric correction algorithms and satellite-derived ocean color.

Frouin, Robert↗

DOE OSTI2024

Quantile regression-enriched event modeling framework for dropout analysis in high-temperature superconductor manufacturing

High-temperature superconductor (HTS) tapes have shown promising characteristics of high critical current, which are prerequisites for applications in high-field magnets. Due to the unstable growth conditions in the HTS manufacturing process, however, the frequent occurrences of dropouts in the critical current impede the consistent performance of HTS tapes. To manufacture HTS tapes with large scale, high yield, and uniform performance, it is essential to develop novel data analysis approaches for modeling the dropouts and identifying the related important process parameters. Conventional methods for modeling recurrent events, such as the point process, require the extraction of events from quality measurements. As the critical current is a continuous process, it may not comprehensively represent the drop patterns by transforming the time-series measurements into a set of events. Here, to solve this issue, we develop a novel quantile regression-enriched event modeling (QREM) framework that integrates the non-homogeneous Poisson process for modeling the occurrence of dropouts and the quantile regression for capturing the drop patterns. By incorporating the feature selection and regularization, the proposed framework identifies a set of significant process parameters that can potentially cause the dropouts of HTS tapes. The proposed method is tested on real HTS tapes produced using an advanced manufacturing process, successfully identifying important parameters that influence dropout events including the substrate temperature and voltage. The results demonstrate that the proposed QREM method outperforms the standard point process in predicting the occurrence of dropouts.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Private, public, and bottled drinking water: Shared contaminant-mixture exposures and effects challenge

Background: Humans are primary drivers of environmental–contaminant exposures worldwide, including in drinking-water (DW). In the United States, point-of-use DW (POU–DW) is supplied via private tapwater (TW), public-supply TW, and bottled water (BW). Differences in management, monitoring, and messaging and lack of directly–intercomparable exposure data influence the actual and perceived quality and safety of different DW supplies and directly impact consumer decision–making. Objectives: The purpose of this paper is to provide a meta-analysis (quantitative synthesis) of POU–DW contaminant–mixture exposures and corresponding potential human–health effects of private-TW, public-TW, and BW by aggregating exposure results and harmonizing apical–health–benchmark–weighted and bioactivity–weighted effects predictions across previous studies by this research group. Discussion: Simultaneous exposures to multiple inorganic and organic contaminants of known or suspected human-health concern are common across all three DW supplies, with substantial variability observed in each and no systematic difference in predicted cumulative risk between supplies. Differences in contaminant or contaminant–class exposures, with important implications for DW–quality improvements, were observed and attributed to corresponding differences in regulation and compliance monitoring. Conclusion: The results indicate that human-health risks from contaminant exposures are common to and comparable in all three DW–supplies, including BW. Importantly, this study’s target analytical coverage, which exceeds that currently feasible for water purveyors or homeowners, nevertheless is a substantial underestimation of the breadth of contaminant mixtures in the environment and potentially present in DW. Thus, the results emphasize the need for improved understanding of the adverse human-health implications of long-term exposures to low–level inorganic–/organic–contaminant mixtures across all three distribution pipelines and do not support commercial messaging of BW as a systematically safer alternative to public-TW. Regardless of the supply, increased public engagement in source-water protection and drinking–water treatment is necessary to reduce risks associated with long-term DW–contaminant exposures, especially in vulnerable populations, and to reduce environmental waste and plastics contamination.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Entropy and Boundary Based Adversarial Learning for Large Scale Unsupervised Domain Adaptation

Supervised semantic segmentation methods provide state-of-the-art performance, but their performance is limited by the amount of quality labeled data they need for training. Scarcity of labeled data and non-transferablity of models, due to cross-domain discrepancy makes it a bigger challenge for remote sensing imagery analysis. In this work, we approach this problem through adversarial learning, driven by entropy and boundary of region-of-interest for unsupervised domain adaptation. This concept helps with better boundary prediction and encourages target domain entropy maps (probability/uncertainty maps) to be similar to source domains. In particular, we showed that deriving informative entropy through the adversarial learning is essential to enable the adaptation. We used a large scale cross country building extraction dataset to validate the framework. The experimental results show the usefulness of considering boundary and entropy driven adversarial learning for adaptation.

Makkar, Nikhil↗

DOE OSTI2022

Aerosol and Cloud Optical Properties from the ARM Raman Lidars: The Feature Detection and Extinction (RLPROF-FEX) Value-Added Product

Aerosols and their interactions and influence on clouds are among the main sources of uncertainties in radiative direct and indirect forcing (IPCC 2013). Continuous height-resolved measurements of cloud and aerosol optical properties are needed to reduce these uncertainties. Here we describe the Raman Lidar Profiles – Feature detection and Extinction (RLPROF-FEX) Value-Added Product (VAP) derived using Raman lidar data at multiple U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility sites. RLPROF-FEX provides estimates of extinction, backscatter, and depolarization using the algorithm described by Thorsen et al. 2015 and Thorsen and Fu 2015. This document provides a description of the FEX algorithm, its input and output data, and related details about the Raman lidar (RL) system.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Agricultural Ice Nuclei at Southern Great Plains (AGINSGP) Field Campaign Report

The Agricultural Ice Nuclei at Southern Great Plains (AGINSGP) field campaign was conducted from April 4 to April 29, 2022, at the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) SGP site in Oklahoma. The goal of this campaign was to improve understanding of the sources and variability of ice-nucleating particles (INPs) at the SGP site. To this end, the key objectives of the campaign were (1) to produce a high-quality data set including measurements of atmospheric INP concentrations and aerosol particle properties relevant to the sources of INPs; and (2) to conduct a residual characterization experiment including offline and online analysis of the physical and chemical characteristics of INPs sampled in ambient air at SGP.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Precision Plant Biomass Characterization in Agriculture: Harnessing Machine Learning and Hyperspectral Imaging [Slides]

Efficient Biomass Separation Object detection of anatomical parts (Cob, Stalk, Husk) in IR images enables precise separation, improving preprocessing (e.g., drying, grinding) for biofuel production. Detailed Biomass Characterization with Hyperspectral Data Hyperspectral imaging captures spectral signatures of biomass, allowing for the identification of specific traits like moisture content, lignin levels, and nutrient composition, leading to optimized treatments for each biomass part. Enhanced Feedstock Quality By leveraging hyperspectral data, feedstock can be processed based on its chemical composition, improving conversion efficiency and biofuel yield. Automation for Large-Scale Operations Automated object detection and hyperspectral data analysis reduce manual labor, ensuring accurate sorting and faster processing, making large-scale biofuel production more efficient. Maximized Biomass Utilization Accurate identification of biomass properties minimizes waste and ensures that each part is processed according to its highest biofuel potential.

09 BIOMASS FUELS↗

NASA NTRS1987

A review of computer aided interpretation technology for the evaluation of radiographs of aluminum welds

Industrial radiography is a well established, reliable means of providing nondestructive structural integrity information. The majority of industrial radiographs are interpreted by trained human eyes using transmitted light and various visual aids. Hundreds of miles of radiographic information are evaluated, documented and archived annually. In many instances, there are serious considerations in terms of interpreter fatigue, subjectivity and limited archival space. Quite often it is difficult to quickly retrieve radiographic information for further analysis or investigation. Methods of improving the quality and efficiency of the radiographic process are being explored, developed and incorporated whenever feasible. High resolution cameras, digital image processing, and mass digital data storage offer interesting possibilities for improving the industrial radiographic process. A review is presented of computer aided radiographic interpretation technology in terms of how it could be used to enhance the radiographic interpretation process in evaluating radiographs of aluminum welds.

Lloyd, J. F., Sr.↗

NASA NTRS1990

Ground-based laser DIAL system for long-term measurements of stratospheric ozone

A ground-based differential absorption lidar system has been implemented to make long-term, precise measurements of stratospheric ozone concentration profiles from about 20 to 50 km altitude. This lidar is located at an elevation of 2300 m in the San Gabriel Mountains, Southern California, and has been in operation since January 1988. A high power (100-W) excimer laser system and a 90-cm diam telescope are used to achieve the desired performance levels. This paper describes the implementation of the system and its operation including the procedures for data analysis. Examples of ozone profiles measured, and intercomparisons with measurements made by other instruments, are presented which show that the lidar, in its present configuration, is capable of producing high quality ozone measurements from 20 km up to at least 45 km.

Mcdermid, Stuart I.↗

NASA NTRS1998

Effects of Weightlessness on Vestibular Development: Summary of Research on NIH.R1

In our original application we proposed to investigate the effects of gravity on the formation of connections between the gravity receptors of the ear and the brain in rat pups raised in space beginning at an age before these connections are made until near the time of birth, when they are to some extent functional. We used the neuronal tracer, Dil, which could be applied to tissue obtained immediately after landing of the space shuttle, thus minimizing changes due to the earth's gravity. We hoped to determine whether the vestibular system develops in two phases, as do other sensory systems (such as the visual system). In these other systems the first phase of development is controlled genetically and the second phase is controlled by environmental stimulation. Our data collected strongly supports the idea that the vestibular system has these same two phases of development. The tissue obtained from the NIH.R1 experiment was of exceptionally high quality for our analysis. Therefore, we expanded our investigation into the ultrastructural effects of microgravity on vestibular development. For the sake of clarity we will subdivide our summary into two categories: (1) analysis of the branching pattern of axons between the vestibular nerve and the gravistatic receptors of the ear in flight and control animals, and (2) analysis of the branching pattern of axons between the vestibular nerve and the brain in flight and control animals.

Fritzsch, Bernd↗

NASA NTRS1969

Biosatellite II mission

Biosatellite B was launched from Cape Kennedy, Florida, on a two-stage DELTA launch vehicle at 6:04 p.m. on 7 September, 1967. Approximately nine minutes later the 435 kg spacecraft biological laboratory was placed into a satisfactory 315 km near-circular earth orbit, successfully separated from the launch vehicle's second stage and was designated Biosatellite II. The scientific payload consisting of thirteen selected general biology and radiation experiments were subjected to planned, carefully controlled environmental conditions during 45 hours of earth-orbital flight. The decision was made to abbreviate the scheduled 3-day mission by approximately one day because of a threatening tropical storm in the recovery area, and a problem of communication with the spacecraft from the tracking stations. Highest priority was placed on recovery which was essential to obtain the scientific results on all the experiments. The operational phase of the mission came to a successful conclusion with the deorbit of the recovery capsule, deployment of the parachute system and air recovery by the United States Air Force. The 127 kg recovery capsule was returned to biology laboratories at Hickam Air Force Base, Hawaii, for disassembly and immediate inspection and analysis of the biological materials by the experimenters. It was evident immediately that the quality of the biology was excellent and this fact gave promise of a high return of scientific data. The environmental conditions provided to the experimental material in the spacecraft, provisions for experimental controls, and operational considerations are presented as they relate to interpretation of the experimental results.

Biosatellite 2 Project↗