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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Photometric Analysis in the Kepler Science Operations Center Pipeline

We describe the Photometric Analysis (PA) software component and its context in the Kepler Science Operations Center (SOC) pipeline. The primary tasks of this module are to compute the photometric flux and photocenters (centroids) for over 160,000 long cadence (~thirty minute) and 512 short cadence (~one minute) stellar targets from the calibrated pixels in their respective apertures. We discuss the science algorithms for long and short cadence PA: cosmic ray cleaning; background estimation and removal; aperture photometry; and flux-weighted centroiding. We discuss the end-to-end propagation of uncertainties for the science algorithms. Finally, we present examples of photometric apertures, raw flux light curves, and centroid time series from Kepler flight data. PA light curves, centroid time series, and barycentric timestamp corrections are exported to the Multi-mission Archive at Space Telescope [Science Institute] (MAST) and are made available to the general public in accordance with the NASA/Kepler data release policy.

Twicken, Joseph D.↗
NASA NTRS2010

Robust Mosaicking of Stereo Digital Elevation Models from the Ames Stereo Pipeline

Robust estimation method is proposed to combine multiple observations and create consistent, accurate, dense Digital Elevation Models (DEMs) from lunar orbital imagery. The NASA Ames Intelligent Robotics Group (IRG) aims to produce higher-quality terrain reconstructions of the Moon from Apollo Metric Camera (AMC) data than is currently possible. In particular, IRG makes use of a stereo vision process, the Ames Stereo Pipeline (ASP), to automatically generate DEMs from consecutive AMC image pairs. However, the DEMs currently produced by the ASP often contain errors and inconsistencies due to image noise, shadows, etc. The proposed method addresses this problem by making use of multiple observations and by considering their goodness of fit to improve both the accuracy and robustness of the estimate. The stepwise regression method is applied to estimate the relaxed weight of each observation.

Kim, Tae Min↗
NASA NTRS2005

Video Mosaicking for Inspection of Gas Pipelines

A vision system that includes a specially designed video camera and an image-data-processing computer is under development as a prototype of robotic systems for visual inspection of the interior surfaces of pipes and especially of gas pipelines. The system is capable of providing both forward views and mosaicked radial views that can be displayed in real time or after inspection. To avoid the complexities associated with moving parts and to provide simultaneous forward and radial views, the video camera is equipped with a wide-angle (>165 ) fish-eye lens aimed along the axis of a pipe to be inspected. Nine white-light-emitting diodes (LEDs) placed just outside the field of view of the lens (see Figure 1) provide ample diffuse illumination for a high-contrast image of the interior pipe wall. The video camera contains a 2/3-in. (1.7-cm) charge-coupled-device (CCD) photodetector array and functions according to the National Television Standards Committee (NTSC) standard. The video output of the camera is sent to an off-the-shelf video capture board (frame grabber) by use of a peripheral component interconnect (PCI) interface in the computer, which is of the 400-MHz, Pentium II (or equivalent) class. Prior video-mosaicking techniques are applicable to narrow-field-of-view (low-distortion) images of evenly illuminated, relatively flat surfaces viewed along approximately perpendicular lines by cameras that do not rotate and that move approximately parallel to the viewed surfaces. One such technique for real-time creation of mosaic images of the ocean floor involves the use of visual correspondences based on area correlation, during both the acquisition of separate images of adjacent areas and the consolidation (equivalently, integration) of the separate images into a mosaic image, in order to insure that there are no gaps in the mosaic image. The data-processing technique used for mosaicking in the present system also involves area correlation, but with several notable differences: Because the wide-angle lens introduces considerable distortion, the image data must be processed to effectively unwarp the images (see Figure 2). The computer executes special software that includes an unwarping algorithm that takes explicit account of the cylindrical pipe geometry. To reduce the processing time needed for unwarping, parameters of the geometric mapping between the circular view of a fisheye lens and pipe wall are determined in advance from calibration images and compiled into an electronic lookup table. The software incorporates the assumption that the optical axis of the camera is parallel (rather than perpendicular) to the direction of motion of the camera. The software also compensates for the decrease in illumination with distance from the ring of LEDs.

Magruder, Darby↗
NASA NTRS2013

Ames Stereo Pipeline

Overview presentation of the Ames Stereo Pipeline, which creates Digital Elevation Models from stereo images.

Fong, Terry↗
NASA NTRS2015

Underwater Adhesives Retrofit Pipelines with Advanced Sensors

Houston-based Astro Technology Inc. used a partnership with Johnson Space Center to pioneer an advanced fiber-optic monitoring system for offshore oil pipelines. The company's underwater adhesives allow it to retrofit older deepwater systems in order to measure pressure, temperature, strain, and flow properties, giving energy companies crucial data in real time and significantly decreasing the risk of a catastrophe.

Source record↗
NASA NTRS2012

Riding the Banzai Pipeline at Jupiter: Balancing Low Delta-V and Low Radiation to Reach Europa

Europa's tantalizing allure as a possible haven for life comes cloaked in a myriad of challenges for robotic spacecraft exploration. Not only are the propulsive requirements high and the solar illumination low, but the radiation environment at Jupiter administers its inexorable death sentence on any electronics dispatched to closely examine the satellite. So to the usual trades of mass, delta-V, and cost, we must add radiation dose, which tugs the trajectory solution in a contrary direction. Previous studies have concluded that adding radiation shielding mass is more efficient than using ?V to reduce the exposure time, but that position was recently challenged by a study focusing on delivering simple landers to the Europa surface. During this work, a new trajectory option was found to occupy a strategic location in the delta-V/radiation continuum - we call it the "Banzai pipeline" due to the visual similarity with the end-on view down a breaking wave, as shown in the following figures.

McElrath, Timothy P.↗
NASA NTRS2010

Photometric Analysis in the Kepler Science Operations Center Pipeline

We describe the Photometric Analysis (PA) software component and its context in the Kepler Science Operations Center (SOC) Science Processing Pipeline. The primary tasks of this module are to compute the photometric flux and photocenters (centroids) for over 160,000 long cadence (~thirty minute) and 512 short cadence (~one minute) stellar targets from the calibrated pixels in their respective apertures. We discuss science algorithms for long and short cadence PA: cosmic ray cleaning; background estimation and removal; aperture photometry; and flux-weighted centroiding. We discuss the end-to-end propagation of uncertainties for the science algorithms. Finally, we present examples of photometric apertures, raw flux light curves, and centroid time series from Kepler flight data. PA light curves, centroid time series, and barycentric timestamp corrections are exported to the Multi-mission Archive at Space Telescope [Science Institute] (MAST) and are made available to the general public in accordance with the NASA/Kepler data release policy.

photocenter↗
NASA NTRS2019

Numerical Simulation on Liquid Hydrogen Chill-Down Process of Vertical Pipeline

In order to improve the cryogenic propellant management technologies for a liquid hydrogen rocket with high specific impulse, JAXA, the University of Tokyo, and the NASA Glenn Research Center have jointly organized a multi-agency model validation collaboration project. As part of this project, JAXA's boiling simulation was validated with NASA's experimental data on vertical pipeline chill-down. Simulation results were in good agreement with the experimental data obtained using an improved boiling model to reproduce the spray flow. This activity achieved liquid hydrogen turbo-pump simulation at JAXA for grasping the boiling flow phenomenon from engine cut-off to re-ignition. This joint research resulted in an international cooperative relationship for discussing the cryogenic propellant management technologies necessary to develop next-generation liquid rockets.

Umemura, Yutaka↗
NASA NTRS2019

Surface Biology & Geology Pathfinder Data Analysis Pipeline

NASA's future global orbital mission, currently in development as the Surface Biology and Geology (SBG) Designated Observable study, will acquire relatively high resolution solar-reflected spectroscopy and thermal infrared observations. Innovative processes must be utilized for handling the high volume of data anticipated to be collected, which is anticipated to exceed 100 terabytes/day, greater than NASA's total extant airborne hyperspectral data collection. Collecting, processing/re-processing, disseminating, and exploiting this volume of data presents new challenges. To begin addressing them, NASA is drawing upon the expertise developed from its astrophysics programs to address Earth science and applications. Specifically, NASA is adapting the science processing operations technology developed for the Kepler and TESS planet-hunting missions for imaging spectroscopy data processing. This technology development has been the foundation for the remarkable scientific successes of Kepler and TESS. The Kepler/TESS data processing technology provides a scalable architecture for robust, repeatable, and replicable science and application products while enabling the Earth science community to develop, test, and implement new algorithms. Our effort to leverage this existing capability has begun by ingesting data and applying workflows from the EO-1/Hyperion 17-year mission archive that provides globally sampled visible through shortwave infrared spectra that are representative of SBG data types and volumes. This pathfinding data processing system will help define the solutions to processing SBG data volumes and will enable the scientific community to interact with the data and processing pipeline to create new science products.

Jenkins, Jon↗
NASA NTRSDate not supplied

AstroAmpSeq: Microbial Bioinformatics Education with NASA GeneLab’s Amplicon Pipeline

The prevalence and importance of large sequencing datasets in microbiology has led to a movement to share microbial ecology experimental data through open-access databases. This is particularly true of experiments that are difficult to replicate, such as those conducted in the spaceflight environment and shared via NASA GeneLab. It is now possible and indeed valuable for students to access and re-analyze these shared datasets for educational and research purposes. To provide students with experience utilizing microbial bioinformatics tools, GeneLab for Colleges and Universities (GL4U) has designed AstroAmpSeq, a week-long, virtually implemented project-based learning (PBL) minicourse to instruct undergraduate students on 16S amplicon sequencing. AstroAmpSeq was created to be accessible to students without prior bioinformatics or microbial ecology experience. During the minicourse students work in teams to process, analyze, and visualize a subsample of GeneLab dataset GLDS-280 using GeneLab’s standard amplicon processing pipeline, which is based in R. Students develop a hypothesis related to the dataset then generate and analyze figures to evaluate their hypothesis. Formative assessment of student learning is determined via pre- and post-evaluations, peer feedback, and self-reflection. Project and presentation rubrics serve as a summative assessment of student learning. GL4U AstroAmpSeq not only meets American Society for Microbiology Curriculum Guidelines, but also incites student interest in research by an inquiry-based approach and can be made part of a larger semester-long curriculum. GL4U AstroAmpSeq raises awareness of space microbiology and bioinformatics as a field and career path among undergraduates. Further, by using a GeneLab dataset and nesting microbiology techniques into the real-world application of space biology, AstroAmpSeq enforces deeper and longer-lasting student learning.

microbiology↗
NASA NTRS2022

The Importance of Policies: It’s Not Just A Pipeline Problem

For decades, a leaky pipeline analogy has been used when discussing diversity issues in STEM fields. However, this imagery is overly simplistic and does not capture critical issues that contribute to people leaving the field. It puts distance between structural issues, our actions, and why people leave the field. When we view our research structure as something more complex, we can start taking ownership and frame more impactful solutions instead of misidentifying important issues and providing ineffective short-term solutions. Many of the issues discussed in the "Cultivating a culture of inclusivity in Heliophysics" position paper have counterparts within our policies and our institutions. To fully address and mitigate the current issues within our field, we have identified a need to cultivate a positive, safe, inclusive, and effective environment. However, we need both cultural and programmatic changes. We will try to identify systemic issues that inhibit many from fully participating and potential solutions, as well as groups and fields producing best practices for creating and enabling effective environments where innovation can occur.

A.J. Halford↗
NASA NTRSDate not supplied

Developing a Genetic Variant Calling Pipeline for Quantifying the Complex Mutagenic Load Accumulated in BioNutrients-1 Production Pack Samples

Microorganisms hold great promise for on demand production of labile nutrients and pharmaceuticals as well recycling and in situ resource utilization. The utilization of microorganisms for such tasks on space missions is hindered by the limited data on how microbes respond to spaceflight. For example, the genetic stability of microorganisms, and the genomic engineered traits added to deliver desired functions, over long-term storage in the spacecraft environment is poorly understood. The BioNutrients-1 (BN-1) mission conducted a 5-year study of desiccated storage in Low Earth Orbit (LEO) to evaluate the suitability of eight synthetic biology chassis organisms for long-duration space missions. We are employing high-depth, whole genome sequencing (WGS) to determine the mutagenic load that accumulated during long-term storage. Mutation analysis pipelines are well established for homogenous culture grown from a single colony, but the mutational landscape of the BN-1 samples present a unique analysis challenge, as every cell in the BN-1 samples had a unique genetic journey of DNA damage and repair. Consequently, sequence variants are expected at low allele frequency within samples. To address this genetic complexity, we apply two distinct computational approaches to identify mutations in pre-existing WGS data collected from populations of Chlamydomonas reinhardtii that were exposed to UV mutagenesis and growth in LEO. For reference genome free mutation detection, we utilized DiscoSNP++, which is a de Bruijn graph approach. For reference genome-based mutation detection we utilize GATK for Microbes, which is a Bayesian probabilistic approach. We will benchmark these approaches against the mutations originally identified using CRISP, a method optimized for pooled samples. Ultimately, quantifying the mutation load imposed by storage or growth on the ISS will help identify chassis organisms with both high levels of genome stability and viability, which are desirable traits for implementation of bioproduction in long-duration missions.

SNP↗
DOE OSTI2020

JSONize: A Scalable Machine Learning Pipeline to Model Medical Notes as Semi-structured Documents

The Department of Veteran's Affairs (VA) archives the largest corpora of clinical notes in their corporate data warehouse (CDW) as unstructured text data. Unstructured text easily supports keyword searches and regular expressions. Often these simple searches do not adequately support the complex searches that need to be performed on notes. For example, a researcher may want all notes with a Duke Treadmill Score less than 5 or people that smoke more than 1 pack per day. Range queries like this and more can be supported by modelling text as semi-structured documents. In this paper, we implement a scalable machine learning pipeline that models plain medical text as useful semi-structured documents. We improve on existing models and achieve a F1-score of 0.912 and scale our methods to the entire VA corpus.

Rush III, Everett↗
DOE OSTI2020

Controlling the operating speed of stages of an asynchronous pipeline

An asynchronous pipeline includes a first stage and one or more second stages. A controller provides control signals to the first stage to indicate a modification to an operating speed of the first stage. The modification is determined based on a comparison of a completion status of the first stage to one or more completion statuses of the one or more second stages. In some cases, the controller provides control signals indicating modifications to an operating voltage applied to the first stage and a drive strength of a buffer in the first stage. Modules can be used to determine the completion statuses of the first stage and the one or more second stages based on the monitored output signals generated by the stages, output signals from replica critical paths associated with the stages, or a lookup table that indicates estimated completion times.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Application of the Metabolic Modeling Pipeline in KBase to Categorize Reactions, Predict Essential Genes, and Predict Pathways in an Isolate Genome

The DOE Systems Biology Knowledgebase (KBase) platform offers a range of powerful tools for the reconstruction, refinement, and analysis of genome-scale metabolic models built from microbial isolate genomes. In this chapter, we describe and demonstrate these tools in action with an analysis of isoprene production in the Bacillus subtilis DSM genome. Two different methods are applied to build initial metabolic models for the DSM genome, then the models are gapfilled in three different growth conditions. Next, flux balance analysis (FBA) and flux variability analysis (FVA) techniques are applied to both study the growth of these models in minimal media and classify reactions within each model based on essentiality and functionality. The models are applied with the FBA method to predict essential genes, which are then compared to an updated list of essential genes obtained for B. subtilis 168, a very similar strain to the DSM isolate. The models are also applied to simulate Biolog growth conditions, and these results are compared with Biolog data collected for B. subtilis 168. Finally, the DSM metabolic models are applied to explore the pathways and genes responsible for producing isoprene in this strain. These studies demonstrate the accuracy and utility of models generated from the KBase pipelines, as well as exploring the tools available for analyzing these models.

Allen, Benjamin↗
DOE OSTI2021

IMPECCABLE: Integrated Modeling Pipeline for COVID Cure by Assessing Better Leads

ABSTRACT The drug discovery process currently employed in the pharmaceutical industry typically requires about 10 years and $2-3 billion to deliver one new drug. This is both too expensive and too slow, especially in emergencies like the COVID-19 pandemic. In silico methodologies need to be improved both to select better lead compounds, so as to improve the efficiency of later stages in the drug discovery protocol, and to identify those lead compounds more quickly. No known methodological approach can deliver this combination of higher quality and speed. Here, we describe an Integrated Modeling PipEline for COVID Cure by Assessing Better LEads (IMPECCABLE) that employs multiple methodological innovations to overcome this fundamental limitation. We also describe the computational framework that we have developed to support these innovations at scale, and characterize the performance of this framework in terms of throughput, peak performance, and scientific results. We show that individual workflow components deliver 100× to 1000× improvement over traditional methods, and that the integration of methods, supported by scalable infrastructure, speeds up drug discovery by orders of magnitudes. IMPECCABLE has screened ~10 11 ligands and has been used to discover a promising drug candidate. These capabilities have been used by the US DOE National Virtual Biotechnology Laboratory and the EU Centre of Excellence in Computational Biomedicine.

97 MATHEMATICS AND COMPUTING↗