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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

NASA GeneLab RNASeq Consensus Pipeline: A Nextflow Implementation

The NASA GeneLab project (genelab.nasa.gov) seeks to accelerate space biology research through cataloging and democratizing omics data. Since raw omics data is largely inaccessible to non-bioinformaticians, GeneLab works with the scientific community to develop standard processing pipelines to generate and publish processed data. Unlike raw data, processed data has greater immediate value to a wide range of users with varying technical backgrounds and computational capabilities. Standardizing processing workflows is essential to match the pace of raw data generation, ensure reproducibility, and enable standardized processed data for comparison across datasets. Previously, GeneLab developed a standardized pipeline for processing RNAseq data, referred to as the ‘GeneLab RNAseq Consensus Pipeline (RCP)’, in collaboration with GeneLab’s Analysis Working Groups. The work presented here is a Nextflow implementation of GeneLab’s RCP that automates and accelerates data processing of RNASeq datasets hosted on GeneLab. In addition to the core data processing, the workflow also includes staging of GeneLab raw data and a robust verification and validation (V&V) program that runs after each processing step to identify errors in real-time, stop additional downstream computation, and preserve computational resources. The workflow, including the staging and V&V functionality, is open source for others to reuse and modify at https://github.com/nasa/GeneLab_Data_Processing/tree/master/RNAseq.

Jonathan Dejesus Oribello↗

NASA GeneLab RNASeq Consensus Pipeline: A Nextflow Implementation

The NASA GeneLab project (genelab.nasa.gov) seeks to accelerate space biology research through cataloging and democratizing omics data. Since raw omics data is largely inaccessible to non-bioinformaticians, GeneLab works with the scientific community to develop standard processing pipelines to generate and publish processed data. Unlike raw data, processed data has greater immediate value to a wide range of users with varying technical backgrounds and computational capabilities. Standardizing processing workflows is essential to match the pace of raw data generation, ensure reproducibility, and enable standardized processed data for comparison across datasets. Previously, GeneLab developed a standardized pipeline for processing RNAseq data, referred to as the ‘GeneLab RNAseq Consensus Pipeline (RCP)’, in collaboration with GeneLab’s Analysis Working Groups. The work presented here is a Nextflow implementation of GeneLab’s RCP that automates and accelerates data processing of RNASeq datasets hosted on GeneLab. In addition to the core data processing, the workflow also includes staging of GeneLab raw data and a robust verification and validation (V&V) program that runs after each processing step to identify errors in real-time, stop additional downstream computation, and preserve computational resources. The workflow, including the staging and V&V functionality, is open source for others to reuse and modify at https://github.com/nasa/GeneLab_Data_Processing/tree/master/RNAseq.

Jonathan D Oribello↗

Transcriptomics Processing Pipelines for Space Biology: An Open Source and Consensus-Driven Approach

Transcriptomics holds significant value in elucidating the relationship between gene expression, experimental factors, biological factors, and various types of omics data. Enhancing our understanding of these connections is paramount for foundational biology, which plays a pivotal role in devising solutions for challenges pertinent to both space travel and terrestrial life. The NASA GeneLab project, part of the Open Science Data Repository (OSDR.nasa.gov), seeks to accelerate space biology research through cataloging and democratizing ‘omics data, including transcriptomics. Since raw omics data are largely inaccessible to non-bioinformaticians, GeneLab works with the scientific community via the Open Science Analysis Working Groups (AWGs) to develop standard processing pipelines to generate and publish processed data. Unlike raw data, processed data have greater immediate value to diverse users with varying technical backgrounds and computational capabilities. Standardizing processing workflows is essential to match the pace of raw data generation, ensure reproducibility, and enable standardized processed data for comparison across datasets. As of June 2023, transcriptomics studies comprise over half of GeneLab datasets hosted on the OSDR, including data from bulk RNA-seq and Affymetrix or Agilent 1-Channel DNA microarray assays. In collaboration with the AWGs, GeneLab developed consensus processing pipelines for these transcriptomics data types that includes quality control, background correction (microarray only), data normalization and quantification, culminating in the detection and annotation of differentially expressed genes. The work presented here describes Nextflow implementations of GeneLab’s consensus transcriptomics pipelines that automates and accelerates processing of these datasets. In addition to the core data processing, these workflows also include raw data staging and a robust verification and validation program to identify errors in real-time, stop additional downstream computation, and preserve computational resources. These workflows are used to generate GeneLab processed data hosted on the OSDR, and are publicly available as open source software for others to use at: https://github.com/nasa/GeneLab_Data_Processing.

Jonathan Oribello↗

Sensor and transmitter system for communication in pipelines

A system for sensing and communicating in a pipeline that contains a fluid. An acoustic signal containing information about a property of the fluid is produced in the pipeline. The signal is transmitted through the pipeline. The signal is received with the information and used by a control.

47 OTHER INSTRUMENTATION↗

Implementing the LSST Software Stack for DESGW processing and the Integration of Convolutional Neural Networks into the DESGW Pipeline

The Dark Energy Survey Gravitational Wave (DESGW) group strives to understand thelargescale structure of the universe and galaxies by looking for electromagnetic signatures intelescope images following gravitational wave detections. The DESGW group uses a processing pipeline to perform difference imaging to look for potential candidates. In order to perform these searches more effectively, we first explored using an alternative processing pipeline, the LSST Software Stack to analyze the telescope images. Because the LSST software stack is currently transitioning between its generation 2 and generation 3 system, we decided that while the software will be usable in the future once generation 3 is complete, at the moment its incompleteness makes it impractical to use. We then decided to work on improving the current pipeline by developing a module that integrates a Convolutional Neural Network (CNN) to test difference imaging products for bad subtractions due to misalignment.

Navarro, Alexander↗

A Data Processing Pipeline for Adversarial Socio-Technical Network Analysis

With the rapid adoption of emerging technologies, there is a need to catalog and model sociotechnical interdependencies that have been historically used to influence the operation of Critical Infrastructure networks including the impacts of mergers and acquisitions, hostile takeovers, and foreign investment. Our research intends to address this need with two primary contributions. First, we have developed a data curation and processing pipeline to generate sociotechnical networks extracted from a variety of data sources including SEC filings and infrastructure asset databases. The pipeline, implemented in Apache Airflow, extracts and normalizes the representation of entities and relations, specified within ontologies. Our intent is to provide an extensible, machine-actionable approach to quickly communicate such models, reproduce previous results, and adapt them to new, unanticipated situations. Second, networks produced by our pipeline enable the development of graph-theoretic metrics that consider the properties of network components in addition to its topology. Metadata associated with network components---whether semantic, temporal, or geospatial---affects the alignment of generated networks with assumptions underlying complexity metrics. Validation of generated networks relative to component types defined by an ontology, may allow the research community to adapt metrics to the semantics of the domains being studied. Generated networks may be processed as knowledge, dynamic, or spatial graphs and enables a variety of analyses including automated reasoning and measures of network complexity. Automated reasoning views extracted entities and relations as a knowledge graph; this enables application of inference rules that represent historically-attested adversarial business methods and applies that behavior to a specific geographic context. Measures of network complexity, including degree distribution, reachability analyses, temporal analysis, and community detection can be adapted to indicate adversarial organizational influence.

97 MATHEMATICS AND COMPUTING↗

Utilizing the Shift Technical Engineer Pipeline to Develop the Next Generation of Engineers - 17354

As the liquid waste contractor for the U.S. Department of Energy's (DOE) Savannah River Site (SRS), Savannah River Remediation (SRR) is responsible for safely treating and dispositioning approximately 35 million gallons of liquid waste stored at SRS. To achieve this mission, SRR manages and operates several complex nuclear facilities. These nuclear facilities include the H and F Tank Farms, the Defense Waste Processing Facility (DWPF), and the Saltstone Processing and Disposal Facility. To support the operations of these complex nuclear facilities, a Shift Technical Engineer (STE) is stationed for every shift. The STE is the sole Engineering Organization representative on-shift and serves as a direct technical resource for operations, including safety basis interpretation, process monitoring and prompt troubleshooting support. The training and qualification for an STE is more intensive than for typical technical staff personnel at SRR, involving additional classes, under-instruction watches, demonstration of practical factors, and culminating in an intense oral board examination. Like many other contractors in the DOE complex, SRR faces the challenge of preparing a significant number of new generation engineers to take the place of an aging workforce. Beyond the traditional training to establish minimum technical qualifications, SRR has established a number of initiatives aimed at accelerating the process of preparing early career engineers to replace experienced senior engineers. These initiatives include an internal rotational program, technical exchange activities with companies at other DOE sites, and an STE pipeline. The STE role provides a unique mechanism for select, early career engineers to gain in-depth knowledge and significant responsibility normally not achieved until much later in their careers. Once qualification is complete, the engineers perform the STE duties, providing technical support for nuclear facility operations. In addition, creating an STE pipeline, where promising young engineers are continually being qualified to replace the on-shift STEs, provides the company with a source of experienced engineers with in-depth technical knowledge as well as valuable experience interfacing with operations and other facility support groups. This paper will discuss the STE position, the qualification process, and how SRR is using the STE qualification pipeline to benefit both the company and the individual engineer. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Evaluation of NETL’s Self-Healing Metallic Coating for Internal Corrosion Protection of Natural Gas Pipelines: Field Test

Steel pipelines are a safe, reliable, and affordable way to transport natural gas. However, the presence of impurities (e.g., water, carbon dioxide, and hydrogen sulfide) in the natural gas can cause internal corrosion, which can lead to pipeline leaks and failure. This paper reports on field tests of an innovative self-healing, corrosion-resistant, metallic coating developed at the National Energy Technology Laboratory (NETL) for protecting the interior surfaces of pipelines.

carbon dioxide (CO2)↗

Fatigue-Crack-Growth Behavior of Two Pipeline Steels

This paper focuses on studying the fatigue-crack-growth behavior of two types of pipeline steels, and investigating their microstructural differences, which could influence the fatigue behavior. For fatigue experiments, compact-tension (CT) specimens are employed. These two kinds of base pipeline steels are Alloy B [Fe-0.05C-1.52Mn-0.12Si-0.092Nb, weight percent (wt.%)] and Alloy C [(Fe- 0.04C-1.61Mn-0.14Si-0.096Nb, wt.%)]. They have been tested at various frequencies (10 Hz, 1 Hz, and 0.1 Hz) and different R ratios (0.1 and 0.5, R = P min. /P max. where P min. is the minimum applied load, and P max. is the maximum applied load) in air. The effects of frequencies and R ratios on crackpropagation behavior are compared. The microstructures of fracture surfaces are investigated, using both scanning-electron microscopy (SEM) and transmission-electron microscopy (TEM). It is concluded that higher R ratios lead to faster crack-growth rates, while frequency does not have much influence on the fatigue-crack-growth rates. Moreover, Alloy B (Fe-0.05C-1.52Mn-0.12Si-0.092Nb, wt.%) tends to have better fatigue resistance than Alloy C (Fe-0.04C-1.61Mn-0.14Si-0.096Nb, wt.%) under various test conditions in air.

36 MATERIALS SCIENCE↗

Automated Radiology Report Summarization Using an Open-Source Natural Language Processing Pipeline

Diagnostic radiologists are expected to review and assimilate findings from prior studies when constructing their overall assessment of the current study. Radiology information systems facilitate this process by presenting the radiologist with a subset of prior studies that are more likely to be relevant to the current study, usually by comparing anatomic coverage of both the current and prior studies. It is incumbent on the radiologist to review the full text report and/or images from those prior studies, a process that is time-consuming and confers substantial risk of overlooking a relevant prior study or finding. This risk is compounded when patients have dozens or even hundreds of prior imaging studies. Our goal is to assess the feasibility of natural language processing techniques to automatically extract asserted and negated disease entities from free-text radiology reports as a step towards automated report summarization. We compared automatically extracted disease mentions to a gold-standard set of manual annotations for 50 radiology reports from CT abdomen and pelvis examinations. The automated report summarization pipeline found perfect or overlapping partial matches for 86% of the manually annotated disease mentions (sensitivity 0.86, precision 0.66, accuracy 0.59, F1 score 0.74). The performance of the automated pipeline was good, and the overall accuracy was similar to the interobserver agreement between the two manual annotators.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

A Combined Experimental-Computational Confirmation of the Seismic Stability of the Branched Pipelines of Systems of Nuclear Power Stations

The increase in the extent and degree of complication of the geometry of the branched pipelines of nuclear power stations has led to the appearance of natural forms of vibrations with frequencies that cannot be determined by the traditional combined experimental-computational method. This has made it necessary to develop new approaches to the experimental determination of the dynamic characteristics and to the selection of the boundaries of the design plans. Through use of the proposed correction to the technique and algorithm used in the estimation of the seismic stability of pipelines it has been possible to increase the precision with which the lowest frequencies of the natural vibrations are determined and, in certain cases, to also reduce the volume of operations through “targeted” testing performed at sites of expected maximal amplitudes of the lowest forms of vibrations.

42 ENGINEERING↗

Quantifying impact reduction due to avoidance, minimization and restoration for a natural gas pipeline in the Peruvian Andes

We present monitoring methods and quantitative biodiversity data to document components of the mitigation hierarchy. We estimated avoidance, minimization, restoration and impact reduction in quality hectares for the 25 m wide right of way of a 408 km natural gas buried pipeline that crosses 14 Ecological Landscape Units (ELUs) in the tropical Andes of Peru. We found that applying the mitigation hierarchy as part of a comprehensive biodiversity action plan substantially reduced impacts on biodiversity in all habitats studied. Avoidance and right of way minimization contributed to significant impact reduction. We quantified impact reduction during construction and operation on the right of way of the pipeline over a five-year period and found that restoration was the greatest contributor to reducing impacts. We documented that most ELUs have a positive restoration trajectory. We also documented how monitoring over large scale spatial scales, in combination with site-specific monitoring, generated data for management to determine restoration priorities and impact mitigation. A biodiversity action plan that incorporated the mitigation hierarchy and a science-based biodiversity monitoring and assessment program contributed to biodiversity management of the project and played an important role in minimizing and managing impacts. - Highlights: •Quantitative data for mitigation hierarchy components are presented. •Application of the mitigation hierarchy reduced impacts on biodiversity. •A biodiversity monitoring program provided data to reduce impacts.

03 NATURAL GAS↗

Modeling and optimization of steady flow of natural gas and hydrogen mixtures in pipeline networks

Here, we extend the canonical problems of simulation and optimization of steady-state gas flows in pipeline networks with compressors to the transport of mixtures of highly heterogeneous gases injected throughout a network. Our study is motivated by proposed projects to blend hydrogen generated using clean energy into existing natural gas pipeline systems as part of efforts to reduce the reliance of energy systems on fossil fuels. Flow in a pipe is related to endpoint pressures by a basic Weymouth equation model, with an ideal gas equation of state, where the wave speed depends on the hydrogen concentration. At vertices, in addition to mass balance, we also consider mixing of incoming flows of varying hydrogen concentrations. The problems of interest are the heterogeneous gas flow simulation (HGFS), which determines system pressures and flows given fixed boundary conditions and compressor settings, as well as the heterogeneous gas flow optimization (HGFO), which extremizes an objective by determining optimal boundary conditions and compressor settings. We examine conditions for uniqueness of solutions to the HGFS, as well as compare and contrast mixed-integer and continuous nonlinear programming formulations for the HGFO. We develop computational methods to solve both problems, and examine their performance using four test networks of increasing complexity.

08 HYDROGEN↗

Microstructure and properties of pipeline steel with a ferrite/martensite dual-phase microstructure

In order to satisfy the transportation of the crude oil and gas in severe environmental conditions, a ferrite/martensite dual-phase pipeline steel has been developed. After a forming process and double submerged arc welding, the microstructure of the base metal, heat affected zone and weld metal was characterized using scanning electron microscopy and transmission electron microscopy. The pipe showed good deformability and an excellent combination of high strength and toughness, which is suitable for a pipeline subjected to the progressive and abrupt ground movement. The base metal having a ferrite/martensite dual-phase microstructure exhibited excellent mechanical properties in terms of uniform elongation of 7.5%, yield ratio of 0.78, strain hardening exponent of 0.145, an impact energy of 286 J at - 10 deg. C and a shear area of 98% at 0 deg. C in the drop weight tear test. The tensile strength and impact energy of the weld metal didn't significantly reduce, because of the intragranularly nucleated acicular ferrites microstructure, leading to high strength and toughness in weld metal. The heat affected zone contained complete quenching zone and incomplete quenching zone, which exhibited excellent low temperature toughness of 239 J at - 10 deg. C. - Research Highlights: {yields}The pipe with ferrite/martensite microstructure shows high deformability. {yields}The base metal of the pipe consists of ferrite and martensite. {yields}Heat affected zone shows excellent low temperature toughness. {yields}Weld metal mainly consists of intragranularly nucleated acicular ferrites. {yields}Weld metal shows excellent low temperature toughness and high strength.

36 MATERIALS SCIENCE↗

Calibration and field deployment of low-cost sensor network to monitor underground pipeline leakage

Recent technological advances in methane detection have improved leak detection and repair. However, current methods to reliably measure methane concentrations rely on expensive instruments or demand significant labor input. There is interest in using affordable methane sensors that are responsive to ppmv level changes in methane concentrations in both urban and rural environments for monitoring underground natural gas pipeline leaks. This is especially relevant for situations where potentially significant leaks cannot be repaired immediately or smaller leaks that require long-term monitoring and further evaluation. In this work, a low-cost sensor unit, equipped with a metal oxide sensor, was designed, built, and calibrated over a wide range of methane concentrations and environmental conditions in preparation for field application. A network of these sensors was then installed at the test site and used to measure methane concentrations at ground level above known sub-surface natural gas emissions which emulated underground gas pipeline leaks. This low-cost sensor network measured over 4 days total for the two different known leakage rates. Results demonstrate that the sensors can continuously measure relative methane variability for extended periods but require calibration for a wide range of temperature and humidity conditions to properly determine absolute gas (i.e., methane) concentrations. Furthermore, when a regression analysis was conducted to evaluate the effects of meteorological parameters on methane concentration, air temperature and wind speed have strong impacts on the concentration. Overall, the network approach allows improved identification of leak location and monitoring of underground natural gas leaks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Toward practical 3D radiography of pipeline girth welds

Digital radiography has made its way into in-the-field girth weld testing. With recent generations of detectors and x-ray tubes it is possible to reach the image quality desired in standards as well as the speed of inspection desired to be competitive with film radiography and automated ultrasonic testing. This paper will show the application of these technologies in the RTD Rayscan system. The method for achieving an image quality that complies with or even exceeds prevailing industrial standards will be presented, as well as the application on pipeline girth welds with CRA layers. A next step in development will be to also achieve a measurement of weld flaw height to allow for performing an Engineering Critical Assessment on the weld. This will allow for similar acceptance limits as currently used with Automated Ultrasonic Testing of pipeline girth welds. Although a sufficient sizing accuracy was already demonstrated and qualified in the TomoCAR system, testing in some applications is restricted to time limits. The paper will present some experiments that were performed to achieve flaw height approximation within these time limits.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

SIMBAD : a sequence-independent molecular-replacement pipeline

The conventional approach to finding structurally similar search models for use in molecular replacement (MR) is to use the sequence of the target to search against those of a set of known structures. Sequence similarity often correlates with structure similarity. Given sufficient similarity, a known structure correctly positioned in the target cell by the MR process can provide an approximation to the unknown phases of the target. An alternative approach to identifying homologous structures suitable for MR is to exploit the measured data directly, comparing the lattice parameters or the experimentally derived structure-factor amplitudes with those of known structures. Here, SIMBAD , a new sequence-independent MR pipeline which implements these approaches, is presented. SIMBAD can identify cases of contaminant crystallization and other mishaps such as mistaken identity (swapped crystallization trays), as well as solving unsequenced targets and providing a brute-force approach where sequence-dependent search-model identification may be nontrivial, for example because of conformational diversity among identifiable homologues. The program implements a three-step pipeline to efficiently identify a suitable search model in a database of known structures. The first step performs a lattice-parameter search against the entire Protein Data Bank (PDB), rapidly determining whether or not a homologue exists in the same crystal form. The second step is designed to screen the target data for the presence of a crystallized contaminant, a not uncommon occurrence in macromolecular crystallography. Solving structures with MR in such cases can remain problematic for many years, since the search models, which are assumed to be similar to the structure of interest, are not necessarily related to the structures that have actually crystallized. To cater for this eventuality, SIMBAD rapidly screens the data against a database of known contaminant structures. Where the first two steps fail to yield a solution, a final step in SIMBAD can be invoked to perform a brute-force search of a nonredundant PDB database provided by the MoRDa MR software. Through early-access usage of SIMBAD , this approach has solved novel cases that have otherwise proved difficult to solve.

59 BASIC BIOLOGICAL SCIENCES↗

Understanding performance variability in standard and pipelined parallel Krylov solvers

In this work, we collect data from runs of Krylov subspace methods and pipelined Krylov algorithms in an effort to understand and model the impact of machine noise and other sources of variability on performance. We find large variability of Krylov iterations between compute nodes for standard methods that is reduced in pipelined algorithms, directly supporting conjecture, as well as large variation between statistical distributions of runtimes across iterations. Based on these results, we improve upon a previously introduced nondeterministic performance model by allowing iterations to fluctuate over time. We present our data from runs of various Krylov algorithms across multiple platforms as well as our updated non-stationary model that provides good agreement with observations. We also suggest how it can be used as a predictive tool.

97 MATHEMATICS AND COMPUTING↗