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NASA NTRS1990

Enforcing compatibility and constraint conditions and information retrieval at the design action

The design of complex entities is a multidisciplinary process involving several interacting groups and disciplines. There is a need to integrate the data in such environments to enhance the collaboration between these groups and to enforce compatibility between dependent data entities. This paper discusses the implementation of a workstation based CAD system that is integrated with a DBMS and an expert system, CLIPS, (both implemented on a mini computer) to provide such collaborative and compatibility enforcement capabilities. The current implementation allows for a three way link between the CAD system, the DBMS and CLIPS. The engineering design process associated with the design and fabrication of sheet metal housing for computers in a large computer manufacturing facility provides the basis for this prototype system.

Woodruff, George W.↗

DOE OSTI2017

PECAN: library-free peptide detection for data-independent acquisition tandem mass spectrometry data

Data-independent acquisition (DIA) is an emerging mass spectrometry (MS)-based technique for unbiased and reproducible measurement of protein mixtures. DIA tandem mass spectrometry spectra are often highly multiplexed, containing product ions from multiple cofragmenting precursors. Detecting peptides directly from DIA data is therefore challenging; most DIA data analyses require spectral libraries. Here we present PECECAN (http://pecan.maccosslab.org), a library-free, peptide-centric tool that robustly and accurately detects peptides directly from DIA data. PECECAN reports evidence of detection based on product ion scoring, which enables detection of low-abundance analytes with poor precursor ion signal. We demonstrate the chromatographic peak picking accuracy and peptide detection capability of PECECAN, and we further validate its detection with data-dependent acquisition and targeted analyses. Lastly, we used PECECAN to build a plasma proteome library from DIA data and to query known sequence variants.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

NASA NTRS1989

Parallel processing of real-time dynamic systems simulation on OSCAR (Optimally SCheduled Advanced multiprocessoR)

Parallel processing of real-time dynamic systems simulation on a multiprocessor system named OSCAR is presented. In the simulation of dynamic systems, generally, the same calculation are repeated every time step. However, we cannot apply to Do-all or the Do-across techniques for parallel processing of the simulation since there exist data dependencies from the end of an iteration to the beginning of the next iteration and furthermore data-input and data-output are required every sampling time period. Therefore, parallelism inside the calculation required for a single time step, or a large basic block which consists of arithmetic assignment statements, must be used. In the proposed method, near fine grain tasks, each of which consists of one or more floating point operations, are generated to extract the parallelism from the calculation and assigned to processors by using optimal static scheduling at compile time in order to reduce large run time overhead caused by the use of near fine grain tasks. The practicality of the scheme is demonstrated on OSCAR (Optimally SCheduled Advanced multiprocessoR) which has been developed to extract advantageous features of static scheduling algorithms to the maximum extent.

Kasahara, Hironori↗

NASA NTRS2010

A Framework for Propagation of Uncertainties in the Kepler Data Analysis Pipeline

The Kepler space telescope is designed to detect Earth-like planets around Sun-like stars using transit photometry by simultaneously observing 100,000 stellar targets nearly continuously over a three and a half year period. The 96-megapixel focal plane consists of 42 charge-coupled devices (CCD) each containing two 1024 x 1100 pixel arrays. Cross-correlations between calibrated pixels are introduced by common calibrations performed on each CCD requiring downstream data products access to the calibrated pixel covariance matrix in order to properly estimate uncertainties. The prohibitively large covariance matrices corresponding to the ~75,000 calibrated pixels per CCD preclude calculating and storing the covariance in standard lock-step fashion. We present a novel framework used to implement standard propagation of uncertainties (POU) in the Kepler Science Operations Center (SOC) data processing pipeline. The POU framework captures the variance of the raw pixel data and the kernel of each subsequent calibration transformation allowing the full covariance matrix of any subset of calibrated pixels to be recalled on-the-fly at any step in the calibration process. Singular value decomposition (SVD) is used to compress and low-pass filter the raw uncertainty data as well as any data dependent kernels. The combination of POU framework and SVD compression provide downstream consumers of the calibrated pixel data access to the full covariance matrix of any subset of the calibrated pixels traceable to pixel level measurement uncertainties without having to store, retrieve and operate on prohibitively large covariance matrices. We describe the POU Framework and SVD compression scheme and its implementation in the Kepler SOC pipeline.

Clarke, Bruce D.↗

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↗

NASA NTRS2005

Channel alignment and radiometry in hyperspectral atmospheric infrared sounders

The Atmospheric Infrared Sounder (AIRS) is a hyper-spectral infrared sounder which covers the 3.7 to 15,4 micron region with 2378 spectral channels. The AIRS instrument specification called for spatial co-registration of all channels to better than 2% of the field of view. Pre-launch testing confirmed that this requirement was met, since the standard deviations in the centroids was about 1% of the 13.5 km IFOV in scan and 3% in track. Detailed analysis of global AIRS data show that the typical scene gradient in 10 micron window channels is about I .3K/km rms. The way these gradients, which are predominantly caused by clouds, manifest themselves in the data depends on the details of the instrument design and the way the spectral channels are used in the data analysis, AIRS temperature and moisture retrievals use 328 of the 2378 channels from 17 independent arrays. As a result, the effect of the boresight misalignment averages to zero mean. Any increase in the effective noise is less than 0.2K. Also, there is no discernable performance degradation of products at the 45 km spatial resolution in the presence of partially cloudy scenes with up to 80% cloudiness. Single pixel radiometric differences between channels with boresight alignment differences can be appreciable and can affect scientific investigations on a single 15km footprint scale, particularly near coastlines, thunderstorms and surface emissivity inhomogeneities.

sounders↗

NASA NTRSDate not supplied

Data Sharing in Radiobiology; Towards FAIR

The value of scientific data depends on their findability, accessibility, integrability and reusability according to the FAIR principles. Together with the sustainability of data preservation and access, these principles underpin the long term benefits of scientific research. Within the domain of radiobiology we have a huge array of data types, themes and complexities which make standardisation of metadata, data structure and data integration very challenging. Moreover, it is clear that, for example, in the area of disaster preparedness, the ready discovery and availability of multiple types of data, for example on biological effects of exposure, climatology, ecology, human behavioural and attitudinal studies, is important for an integrated scientific approach. Because these data are spread over many databases, journal supplementary information resources and even the computers of the investigators, their discovery and reuse can be challenging. Despite exhortations from funding agencies and scientific institutions over the past two decades there is still a serious deficit in the willingness and in some cases the ability of investigators to share data, and although much may not be formally „Public domain“, information about the existence of the data, their metadata, and how to obtain them should always be available. We report the progress of work on three databases, the STORE and the NASA GeneLab and LSDA repositories to leverage the Radiation Biology Ontology (RBO), a structured terminology for metadata that can be used by all radiation biology-relevant databases to unite federated and automated data searches across multiple databases, for example using web services, and through semantic web technologies supporting data discovery. The initial primary use-cases for RBO were archiving data in the STORE database (https://www.storedb.org/), the repository used for the RadoNorm and Pianoforte Projects among others, and in the NASA Open Science Data Repository (https://osdr.nasa.gov/bio). The scope of radiobiology research ranges from basic physics to radiation oncology to sociolegal studies; no existing ontology had the necessary breadth or depth to fulfill this need. In addition, a formal ontology has the advantage of being usable for machine learning and, importantly, for tasks like data integration, knowledge extraction from the scientific literature and for query extension and data classification. Standardisation of metadata is one of the primary objectives of the FAIR principles for open data; RBO is an important landmark for FAIR-compliant radiation biology data sharing. The RBO is developed using the open-source tools of GitHub and the OBO Foundry-led Ontology Development Kit, and published through GitHub and the NIH/NCBI BioPortal website. This initial phase of concept modeling has yielded an ontology that has more than 300 declared concepts, with more than 3500 additional concepts imported from other OBO Foundry ontologies with relevance to radiation biology (for example, concepts from the ISO standard Basic Formal Ontology, the Environment Ontology and the Gene Ontology). We welcome input into the development of RBO and encourage its adoption.

ontologies↗

NASA NTRS2023

Data Sharing in Radiation Biology: Towards FAIR

The value of scientific data depends on their findability, accessibility, integrability and reusability according to the FAIR principles. Together with the sustainability of data preservation and access, these principles underpin the long term benefits of scientific research. Within the domain of radiobiology we have a huge array of data types, themes and complexities which make standardisation of metadata, data structure and data integration very challenging. Moreover, it is clear that, for example, in the area of disaster preparedness, the ready discovery and availability of multiple types of data, for example on biological effects of exposure, climatology, ecology, human behavioural and attitudinal studies, is important for an integrated scientific approach. Because these data are spread over many databases, journal supplementary information resources and even the computers of the investigators, their discovery and reuse can be challenging. Despite exhortations from funding agencies and scientific institutions over the past two decades there is still a serious deficit in the willingness and in some cases the ability of investigators to share data, and although much may not be formally "Public domain“, information about the existence of the data, their metadata, and how to obtain them should always be available. We report the progress of work on three databases, the STORE and the NASA GeneLab and LSDA repositories to leverage the Radiation Biology Ontology (RBO), a structured terminology for metadata that can be used by all radiation biology-relevant databases to unite federated and automated data searches across multiple databases, for example using web services, and through semantic web technologies supporting data discovery. The initial primary use-cases for RBO were archiving data in the STORE database (https://www.storedb.org/), the repository used for the RadoNorm and Pianoforte Projects among others, and in the NASA Open Science Data Repository (https://osdr.nasa.gov/bio). The scope of radiobiology research ranges from basic physics to radiation oncology to sociolegal studies; no existing ontology had the necessary breadth or depth to fulfill this need. In addition, a formal ontology has the advantage of being usable for machine learning and, importantly, for tasks like data integration, knowledge extraction from the scientific literature and for query extension and data classification. Standardisation of metadata is one of the primary objectives of the FAIR principles for open data; RBO is an important landmark for FAIR-compliant radiation biology data sharing. The RBO is developed using the open-source tools of GitHub and the OBO Foundry-led Ontology Development Kit, and published through GitHub and the NIH/NCBI BioPortal website. This initial phase of concept modeling has yielded an ontology that has more than 300 declared concepts, with more than 3500 additional concepts imported from other OBO Foundry ontologies with relevance to radiation biology (for example, concepts from the ISO standard Basic Formal Ontology, the Environment Ontology and the Gene Ontology). We welcome input into the development of RBO and encourage its adoption.

ontologies↗

NASA NTRS1992

Long Duration Exposure Facility (LDEF) attitude measurements of the interplanetary dust experiment

The Long Duration Exposure Facility (LDEF) Interplanetary Dust Experiment (IDE) was unique in providing a time history of impacts of micron-sized particles on six orthogonal faces of LDEF during the first year in orbit. The value of this time resolved data depended on and was enhanced by the proper operation of some basic LDEF systems. Thus, the value of the data is greatly enhanced when the location and orientation of LDEF is known for each time of impact. The location and velocity of LDEF as a function of time can be calculated from the 'two-line elements' published by GSFC during the first year of the LDEF mission. The attitude of LDEF was passively stabilized in a gravity-gradient mode and a magnetically anchored viscous damper was used to dissipate roll, pitch, and yaw motions. Finally, the IDE used a standard LDEF Experiment Power and Data System (EPDS) to collect and store data and also to provide a crystal derived clock pulse (1 count every 13.1072 seconds) for all IDE time measurements. All that remained for the IDE was to provide a system to calibrate the clock, eliminating accumulative errors, and also verify the attitude of LDEF. The IDE used solar cells on six orthogonal faces to observe the LDEF sunrise and provide data about the LDEF attitude. The data was recorded by the EPDS about 10 times per day for the first 345 days of the LDEF mission. This data consist of the number of IDE counts since the last LDEF sunrise and the status of the six solar cells (light or dark) at the time of the last IDE count. The EPDS determined the time that data was recorded and includes, with each record, the master EPDS clock counter (1 count every 1.6384 seconds) that provided the range and resolution for time measurements. The IDE solar cells provided data for an excellent clock calibration, meeting their primary purpose, and the time resolved LDEF attitude measurements that can be gleaned from this data are presented.

Kassel, Philip C., Jr.↗

NASA NTRS2011

Effects of Data Quality on the Characterization of Aerosol Properties from Multiple Sensors

Cross-comparison of aerosol properties between ground-based and spaceborne measurements is an important validation technique that helps to investigate the uncertainties of aerosol products acquired using spaceborne sensors. However, it has been shown that even minor differences in the cross-characterization procedure may significantly impact the results of such validation. Of particular consideration is the quality assurance I quality control (QA/QC) information - an auxiliary data indicating a "confidence" level (e.g., Bad, Fair, Good, Excellent, etc.) conferred by the retrieval algorithms on the produced data. Depending on the treatment of available QA/QC information, a cross-characterization procedure has the potential of filtering out invalid data points, such as uncertain or erroneous retrievals, which tend to reduce the credibility of such comparisons. However, under certain circumstances, even high QA/QC values may not fully guarantee the quality of the data. For example, retrievals in proximity of a cloud might be particularly perplexing for an aerosol retrieval algorithm, resulting in an invalid data that, nonetheless, could be assigned a high QA/QC confidence. In this presentation, we will study the effects of several QA/QC parameters on cross-characterization of aerosol properties between the data acquired by multiple spaceborne sensors. We will utilize the Multi-sensor Aerosol Products Sampling System (MAPSS) that provides a consistent platform for multi-sensor comparison, including collocation with measurements acquired by the ground-based Aerosol Robotic Network (AERONET), The multi-sensor spaceborne data analyzed include those acquired by the Terra-MODIS, Aqua-MODIS, Terra-MISR, Aura-OMI, Parasol-POLDER, and CalipsoCALIOP satellite instruments.

Petrenko, Maksym↗

DOE OSTI2012

Recommended Parameter Values for GENII Modeling of Radionuclides in Routine Air and Water Releases

The GENII v2 code is used to estimate dose to individuals or populations from the release of radioactive materials into air or water. Numerous parameter values are required for input into this code. User-defined parameters cover the spectrum from chemical data, meteorological data, agricultural data, and behavioral data. This document is a summary of parameter values that reflect conditions in the United States. Reasonable regional and age-dependent data is summarized. Data availability and quality varies. The set of parameters described address scenarios for chronic air emissions or chronic releases to public waterways. Considerations for the special tritium and carbon-14 models are briefly addressed. GENIIv2.10.0 is the current software version that this document supports.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1989

Unique signatures of synoptic features in Tiros N satellite data

The application of satellite data to the study of synoptic characteristics is analyzed. A radiative transfer model is used to generate a database of satellite information on synoptic features. Canonical discriminant analysis is employed to reveal the differences among synoptic sounding classes; and the fine structures within each sounding class are examined with rotated factor analysis. Diagrams of wind and frontal inversions are presented. It is noted that the applicability of satellite data depends on the method used to analyze it and multivariable statistical techniques may be useful for deriving additional information from satellite data.

White, G. A., III↗

DOE OSTI2017

Mercat

Mercat is a highly scalable property software package for robust of analysis of features in next-generation sequencing data and observed unique peptides from metaproteomic data. Mercat is offered in python 3.5/anaconda3, is multiparellel and is easily installed using bioconda/conda recipes. Mercat inputs include assembled contigs, raw sequence reads from any platform, and unique peptide files obtained from proteomics with feature abundance counts tables. Mercat is the only software available that allows for direct analysis of data properties without a data-dependent search tools such as BLAST or diamond for compositional analysis of whole community shotgun sequencing (e.g. metagenomes and/or metatranscriptomes) or metaproteomic data.

Source record↗

DOE OSTI2017

Mercat

Source record↗

DOE OSTI2018

pnnl/ZebrafishBMD

ZebrafishBMD: A software tool to perform benchmark dose calculations using toxicity screening data of high-throughput zebrafish assays. High-content imaging of larval zebrafish behavior can be used as a screening approach to rapidly evaluate the relative potential for chemicals to cause toxicity. However, most statistical methods applied to these data transform movement values to incidence-based “hits” and calculate lowest effect levels (LELs), which loses individual fish resolution of behavior and defies hazard ranking due to reliance on applied dose levels. We developed a parallelizable workflow to calculate benchmark dose (BMD) values from dynamic, high-content zebrafish behavior data that scales for high throughput chemical screening. To capture the zebrafish movement response from light to dark stimulus, we summarized time-dependent data using both area under the curve and the immediate change at the transition point into two novel metrics that characterized abnormal behavior as a function of chemical concentration. The BMD workflow was applied to calculate BMD10 values of 1,060 ToxCast chemicals for 24 zebrafish endpoints, including behavior, mortality and morphology. ZebrafishBMD implements the BMD workflow and provides Matlab scripts to read the data (stored in a specific structure) from a .mat file, to calculate the behavioral endpoint values from movement versus time data, to construct concentrationresponse curves, to perform curve-fitting, and to calculate BMD10 values.

Thomas, Dennis↗

DOE OSTI2024

Data Efficiency Assessment of Generative Adversarial Networks for Critical Heat Flux Synthetic Data Generation

This study investigates the application of generative artificial intelligence techniques, particularly conditional generative adversarial networks (cGAN), in real-world engineering contexts, with a specific focus on synthetic data generation for critical heat flux (CHF). Utilizing a dataset comprising more than 20,000 real experimental CHF measurements, we conduct a series of experiments to examine cGAN’s behavior. These experiments encompass varying sizes of the training dataset, training cGAN on data from diverse experimental sources to generate new data on unseen experimental setups, and assessing the impact of excluding various input features on cGAN’s data generation accuracy. Our findings underscore the pronounced data dependency of cGAN for reliable performance, with decreased efficacy observed with smaller training dataset sizes. Notably, cGAN exhibits varying performance when trained on data from different experiments, with superior predictive capabilities observed for certain experiment sources compared to others. For instance, when cGAN was trained on data from Smolin et al.’s experiments or Zenkevich et al., it exhibited relatively good performance in generating the data from Becker et al., Kirillov et al., and Alekseev et al. experiments. In contrast, when trained with Alekseev et al.’s data and tasked with generating other experimental setups, cGAN showed notably poor performance. In both scenarios, cGAN’s performance was inferior compared to training on samples from all experiments concurrently. A feature importance analysis highlights the significant influence of parameters such as mass flux and heated length on accurate CHF generation, while other parameters like diameter and pressure have less impact. Inlet temperature is identified as a moderating factor by cGAN.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2013

MEASURING THE COOLING OF THE NEUTRON STAR IN CASSIOPEIA A WITH ALL CHANDRA X-RAY OBSERVATORY DETECTORS

The thermal evolution of young neutron stars (NSs) reflects the neutrino emission properties of their cores. Heinke and Ho measured a 3.6% ± 0.6% decay in the surface temperature of the Cassiopeia A (Cas A) NS between 2000 and 2009, using archival data from the Chandra X-ray Observatory ACIS-S detector in Graded mode. Page et al. and Shternin et al. attributed this decay to enhanced neutrino emission from a superfluid neutron transition in the core. Here we test this decline, combining analysis of the Cas A NS using all Chandra X-ray detectors and modes (HRC-S, HRC-I, ACIS-I, ACIS-S in Faint mode, and ACIS-S in Graded mode) and adding a 2012 May ACIS-S Graded mode observation, using the most current calibrations (CALDB 4.5.5.1). We measure the temperature changes from each detector separately and test for systematic effects due to the nearby filaments of the supernova remnant. We find a 0.92%-2.0% decay over 10 yr in the effective temperature, inferred from HRC-S data, depending on the choice of source and background extraction regions, with a best-fit decay of 1.0% ± 0.7%. In comparison, the ACIS-S Graded data indicate a temperature decay of 3.1%-5.0% over 10 yr, with a best-fit decay of 3.5% ± 0.4%. Shallower observations using the other detectors yield temperature decays of 2.6% ± 1.9% (ACIS-I), 2.1% ± 1.0% (HRC-I), and 2.1% ± 1.9% (ACIS-S Faint mode) over 10 yr. Our best estimate indicates a decline of 2.9% ± 0.5%{sub stat} ± 1.0{sub sys}% over 10 yr. The complexity of the bright and varying supernova remnant background makes a definitive interpretation of archival Cas A Chandra observations difficult. A temperature decline of 1%-3.5% over 10 yr would indicate extraordinarily fast cooling of the NS that can be regulated by superfluidity of nucleons in the stellar core.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2013

AGC-1 Specimen Post Irradiation Data Report

Here we report the results of the Post Irradiation Examination (PIE) of the creep, control, and piggyback specimens from the irradiation creep capsule AGC-1. This is the first (prototype) of a series of six capsules planned as part of the Advanced Graphite Creep (AGC) experiment to fully characterize the neutron irradiation effects and radiation creep behavior of current nuclear graphites. The data reported include: specimen dimensions and hence the dimensional change upon irradiation (a comparison of these data for specimen matched pairs will yield the creep strain); mass and volume, hence density; elastic constants (Young’s modulus, shear modulus and Poisson’s ratio) from ultrasonic time of flight (TOF) and velocity measurements; Young’s modulus from the fundamental frequency of vibration; electrical resistivity; and thermal expansion from 100-550°C (hence coefficient of thermal expansion). Over 8500 individual physical measurement have been made and the data are reduced and reported here. The AGC-1 capsule was irradiated in the Advanced Test Reactor (ATR) at INL at approximately 700°C and to a peak dose of 7 dpa (displacements per atom). The specimen’s final dose, temperature and stress conditions have been reported by INL and are also tabulated here. Additionally the analysis of the SiC temperature monitors is reported. These temperature monitors were located along the center of the AGC-1 capsule and provide an independent assessment of the capsules final irradiation temperature. While all the PIE testing is reported (with the exception of the glued-end tensile strength specimens) additional analysis of the AGC data will be required to allow: 1. Improved fits to the existing models of graphite irradiation induced creep strain. 2. With the eventual advent of temperature dependency data from the additional AGC series of capsules, and microstructural data from piggy back specimens in AGC capsules, the development of new and improved models for the development of irradiation induced creep strain in graphite are anticipated. 3. An Investigation into the effects of creep strain on the physical properties of irradiated graphite.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗