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The experience acquired through development, implementation and operation of the KeplerK2 science pipelines can provide lessons learned for the development of science pipelines for other missions such as NASA's Transiting Exoplanet Survey Satellite, and ESA's PLATO mission.
The experience acquired through development, implementation and operation of the Kepler K2 science pipelines can provide lessons learned for the development of science pipelines for other missions such as NASA's Transiting Exoplanet Survey Satellite and ESA's PLATO mission.
The FAIRness of data products, especially findability and accessibility depend on rich metadata which, when extracted, can allow for proper curation. Over the past few years, the Atmospheric Science Data Center (ASDC) suborbital science support team has developed a metadata extraction pipeline to ensure the required metadata can be retrieved systematically, effectively, and efficiently to ensure the data can be used by a broad community. The development of a pipeline has presented many, but necessary, challenges to support archival and distribution of ASDC’s 30+ suborbital missions. Though sufficient metadata is provided by instrument scientists, the metadata may not be readily machine actionable due to different formats and templates. Further complicating metadata extraction, our team has found that the nature of metadata can be quite diverse given the difference in measurement types, instruments, and measurement platforms. A metadata extraction pipeline has been developed to provide an efficient, plugin-in based, method for adding new parsers, a configuration system that lets non-developers customize how files are processed, and a system for identifying and logging metadata quality issues to ensure they are readily found and addressed. The metadata extraction pipeline identifies critical pieces of metadata that are needed to promote data FAIRness, including location, file revision, measurement start/end datetime and can be easily modified to extract further information (such as variables). Given the wide-ranging datasets, the pipeline has been modified to accommodate multiple file formats, including multiple versions of ICARTT (International Consortium for Atmospheric Research on Transport and Transformation), HDF (Hierarchical Data Format), netCDF (network Common Data Form), and multiple versions of the Ames File Format. The pipeline also supports building metadata for file formats that cannot have metadata easily extracted from them, such as PDF (Portable Document Format) and GIF (Graphics Interchange Format). The pipeline has allowed our team to maintain a consistent flow of data and metadata to archival and distribution services, ensuring the ASDC meets the needs of the suborbital science community. This presentation will highlight the ASDC’s suborbital metadata extraction pipeline, its development, how it’s been modified to support data FAIRness, and plans for maintaining the pipeline and adding new features.
Providing ground command software for constellations of spacecraft is a challenging problem. Reliable command delivery requires a feedback loop; for a constellation there will likely be an independent feedback loop for each constellation member. Each command must be sent via the proper Ground Station, which may change from one contact to the next (and may be different for different members). Dynamic configuration of the ground command software is usually required (e.g. directives to configure each member's feedback loop and assign the appropriate Ground Station). For testing purposes, there must be a way to insert command data at any level in the protocol stack. The Pipeline architecture described in this paper can support all these capabilities with a sequence of software modules (the pipeline), and a single self-identifying message format (for all types of command data and configuration directives). The Pipeline architecture is quite simple, yet it can solve some complex problems. The resulting solutions are conceptually simple, and therefore, reliable. They are also modular, and therefore, easy to distribute and extend. We first used the Pipeline architecture to design a CCSDS (Consultative Committee for Space Data Systems) Ground Telecommand system (to command one spacecraft at a time with a fixed Ground Station interface). This pipeline was later extended to include gateways to any of several Ground Stations. The resulting pipeline was then extended to handle a small constellation of spacecraft. The use of the Pipeline architecture allowed us to easily handle the increasing complexity. This paper will describe the Pipeline architecture, show how it was used to solve each of the above commanding situations, and how it can easily be extended to handle larger constellations.
The Lunar South Pole Oxygen Pipeline (LSPOP) Phase I NIAC, is to analyze the feasibility of constructing a pipeline at the Moon’s South Pole for transporting gaseous oxygen from point of generation to point of use. A lunar pipeline has never been pursued and will revolutionize lunar surface operations for the Artemis program and reduce cost and risk. Our starting concept is for a 5 km pipeline to transport oxygen gas from an oxygen production source, for example from our molten regolith electrolysis (MRE, currently at TRL 5, see references[1],[2],[3],[4],[5],[6] for technical discussions of the MRE process) extraction site, or any other source, to an oxygen storage/liquification plant near a lunar base. The pipeline is designed to: 1) be constructed robotically from regolith-derived metals with minimal material transferred from Earth, 2) be repairable robotically, 3) have an oxygen flow rate of ~2 kg/hour, which is commensurate with the NASA initial projected need of 10,000 kg/year, 4) operate with minimal power over the lifetime of the pipeline, with a goal of high operational reliability and the ability to survive in the lunar environment for > 10 years. We compare this concept to a pipeline concept with pipe produced on Earth and then transported to and assembled on the Moon. Both approaches will use earth-based compressors, valves, and fittings which are integrated into the pipeline on the Moon.
The Science Processing Operations Center is in the process of testing and deploying Release 4.0 of the codebase in the March 2019 timeframe. This paper describes the new features of the software and their likely impact on the quality of the TESS science data products. The major goals of Release 4.0 are to improve the extraction of photometry from the pixels in light of the non-uniform pointing performance and the identification of instrumental signatures from the light curves. We also describe modifications to the FFI pipeline to allow the generation of FFI light curves, correction of the instrumental systematics therein, and planet searches, primarily for the purpose of validating the 2-min pipeline against the FFI pipeline, but also to be able to provide cotrending basis vectors (CBVs) derived directly from the FFIs to the public to aid them in their extraction and correction of photometry. We also discuss the improvements in photometric performance of the pipeline and its various components.The lapse in funding experienced between 22 December 2018 and 27 January 2019 significantly delayed our ability to conduct integration testing as planned for late December/early January, delaying the start of V&V by one month to the end of February 2019.The TESS Mission is funded by NASA's Science Mission Directorate as an Astrophysics Explorer Mission.The Science Processing Operations Center is in the process of testing and deplo!"ing Release 4.0 of thecodebase In the March 2019 tlmeframe. This paper describes the new features or the software and theirlikely impact on the quality of the TESS science data products. The major goals or Release 4.0 are to Imtheidentification of instrumental signatures from the light cuNes. We also describe modifications tothe FFI pipeline to allow the generation of FFI light curves, correction of the instrumental systematicstherein, and planet searches, primarily for the purpose of validating the 2-min pipelineagainst the FFI pipeline, but also to be able to provide cotrending basis vectors (C3Vs) ,,.~,.;.derived directly from the FFls to the public to aid them in their extractbn and correction , :-; ~'-'\'.'.of photometry. We also discuss the Improvements In photometric performance• of ~~\":;:•the pipeline and its various components. :,;.-.;The lapse In funding experienced between 22 December 2018 and 27January 2019 significantly delayed our ability to conduct Integrationtesting as planned for late December/early January, delaying thestart of V&V by one month to the end of February 2019.The TESS Mission is funded by NASA's Science Mission Directorateas an Astrophysics Explorer Mission.o.iu.c...,.....~~New Features in SPOC 4.01. Use of quatemions In photometry and centroiding.2. Use of quaternions to Identify high-motion cadences and exclude same.3. Use of the TPS detections to deemphasize pathological cadences ("skyline flattenlng"I.4. Improved CAL calculations for black and smear correction.5. PA brightness metric calculation improvements (induo'e crowding in calrulation)./ • 6. Improved POC spike goodness metric.•~• 7. Improved handling of gaps and momentum duni:>S in POC.8. Improved tuning of POC., 9. Improved attitude tweak correction in PDC.10. Improvements in PDC introduced noise and correlation goodness metrics11. Using the improved spike goodness metric to minimize overlitting in the spikeremover ' • :,''l./ 12. Enable FFI processing through planet search.,,. ,• • "« ,;,,,•.~'A , 13.1 D4.V S mtreinaim-relipnoinrgts d aartcah irveetrdie tvoa Ml aAnSdT p ersistence to database 15. Improved management of jobs on the NAS Pleiadss supercomputer
In many industries, non-Newtonian material, such as oils, lubricants, foods, cosmetics, and solid-liquid suspensions, are passed through pipelines during manufacture, application, or transportation. For the proper design of the pipelines, and evaluation of the flow resistance of the materials when flowing in these pipelines is essential. The pressure loss Δ p , due to a material flowing through a straight pipeline can be expressed as a function of a friction factor, φ, so that Δ p = ( pv 2 )/2 L/D φ where φ is a function of the flow properties of the material v is the mean velocity of the material and can be determined from the mas-flow rate, L is the length and D is the diameters of the pipeline, and p is the density of the material. The purpose of this paper is to present a generalized friction diagram, which can be used to determine φ for any material and flow condition, provided the flow properties of the material and the mean flow velocity in the pipeline are known. In composing this diagram generous use is made of the literature and only parts of the diagram and the presentation can claim originality.
Within the context of NASA's Education Programs, this Workforce Development Pipeline guide describes the goals and objectives of MSFC's Workforce Development Pipeline Program as well as the principles and strategies for guiding implementation. It is designed to support the initiatives described in the NASA Implementation Plan for Education, 1999-2003 (EP-1998-12-383-HQ) and represents the vision of the members of the Education Programs office at MSFC. This document: 1) Outlines NASA s Contribution to National Priorities; 2) Sets the context for the Workforce Development Pipeline Program; 3) Describes Workforce Development Pipeline Program Strategies; 4) Articulates the Workforce Development Pipeline Program Goals and Aims; 5) List the actions to build a unified approach; 6) Outlines the Workforce Development Pipeline Programs guiding Principles; and 7) The results of implementation.
A multinode parallel-processing computer is made up of a plurality of innerconnected, large capacity nodes each including a reconfigurable pipeline of functional units such as Integer Arithmetic Logic Processors, Floating Point Arithmetic Processors, Special Purpose Processors, etc. The reconfigurable pipeline of each node is connected to a multiplane memory by a Memory-ALU switch NETwork (MASNET). The reconfigurable pipeline includes three (3) basic substructures formed from functional units which have been found to be sufficient to perform the bulk of all calculations. The MASNET controls the flow of signals from the memory planes to the reconfigurable pipeline and vice versa. the nodes are connectable together by an internode data router (hyperspace router) so as to form a hypercube configuration. The capability of the nodes to conditionally configure the pipeline at each tick of the clock, without requiring a pipeline flush, permits many powerful algorithms to be implemented directly.
The computer pipelines used to process digital infrared astronomical images from NASA's Spitzer Space Telescope require various input calibration-data files for characterizing the attributes and behaviors of the onboard focal-plane-arrays and their detector pixels, such as operability, dark-current offset, linearity, non- uniformity, muxbleed, droop, and point-response functions. The telescope has three very different science instruments, each with three or four spectral-band-pass channels, depending on the instrument. Moreover, each instrument has various operating modes (e-g., full array or sub-array in one case) and parameters (e.g., integration time). Calibration data that depend on these considerations are needed by pipelines for generating both science products (production pipelines) and higher-level calibration products (calibration pipelines). The calibration files are created in various formats either 'off-line' or by the aforementioned calibration pipelines, depending on the above configuration details. Also, the calibration files are generally applicable to a certain time period and therefore must be selected accordingly for a given raw input image to be correctly processed. All of this complexity in selecting and retrieving calibration files for pipeline processing is handled by a procedural software-program called 'caltrans' . This software, which is implemented in C and interacts with an Informix database, was developed at the Spitzer Science Center (SSC) and is now deployed in SSC daily operations. The software is rule-based, very flexible, and, for efficiency, capable of retrieving multiple calibration files with a single software-execution command.
A preliminary study has shown that the use of a high-strength composite fiber cloth material may greatly reduce fabrication and deployment costs of a subsea offshore pipeline. The problem is to develop an inexpensive submerged pipeline that can safely and economically transport large quantities of fresh water, oil, and natural gas underwater for long distances. Above-water pipelines are often not feasible due to safety, cost, and environmental problems, and present, fixed-wall, submerged pipelines are often very expensive. The solution is to have a submerged, compliant-walled tube that when filled, is lighter than the surrounding medium. Some examples include compliant tubes for transporting fresh water under the ocean, for transporting crude oil underneath salt or fresh water, and for transporting high-pressure natural gas from offshore to onshore. In each case, the fluid transported is lighter than its surrounding fluid, and thus the flexible tube will tend to float. The tube should be ballasted to the ocean floor so as to limit the motion of the tube in the horizontal and vertical directions. The tube should be placed below 100-m depth to minimize biofouling and turbulence from surface storms. The tube may also have periodic pumps to maintain flow without over-pressurizing, or it can have a single pump at the beginning. The tube may have periodic valves that allow sections of the tube to be repaired or maintained. Some examples of tube materials that may be particularly suited for these applications are non-porous composite tubes made of high-performance fibers such as Kevlar, Spectra, PBO, Aramid, carbon fibers, or high-strength glass. Above-ground pipes for transporting water, oil, and natural gas have typically been fabricated from fiber-reinforced plastic or from more costly high-strength steel. Also, previous suggested subsea pipeline designs have only included heavy fixed-wall pipes that can be very expensive initially, and can be difficult and expensive to deploy for long distances. A much less expensive Kevlar pipeline can be coiled up on a ship s deck and deployed in the water as the ship moves. Support ships can be used to drop sand into conduits below the uninflated tube, so that the tube remains in place when more buoyant fresh water later fills the tubes.
The Remote Sensing Project at Michigan State University is using repetitive aerial photography to assess the impact of pipeline construction on coniferous wetlands in central Michigan. Preliminary results indicate that ponding, dieback, windthrow, and vegetation changes are readily detectable on medium-scale aerial photography. It is found that the major effect of the pipeline construction is the alteration of the water level, either by flooding or dessication. The most serious damage generally occurs when pipelines cross seepage and spiring wetland types; specific damage is related to the impoundment of the natural water flow, producing flooding on the upflow side of the pipeline and dessication of these wetlands below the pipeline rights-of-way.
Orchestrator is a software application infrastructure for telemetry monitoring, logging, processing, and distribution. The architecture has been applied to support operations of a variety of planetary rovers. Built in Java with the Eclipse Rich Client Platform, Orchestrator can run on most commonly used operating systems. The pipeline supports configurable parallel processing that can significantly reduce the time needed to process a large volume of data products. Processors in the pipeline implement a simple Java interface and declare their required input from upstream processors. Orchestrator is programmatically constructed by specifying a list of Java processor classes that are initiated at runtime to form the pipeline. Input dependencies are checked at runtime. Fault tolerance can be configured to attempt continuation of processing in the event of an error or failed input dependency if possible, or to abort further processing when an error is detected. This innovation also provides support for Java Message Service broadcasts of telemetry objects to clients and provides a file system and relational database logging of telemetry. Orchestrator supports remote monitoring and control of the pipeline using browser-based JMX controls and provides several integration paths for pre-compiled legacy data processors. At the time of this reporting, the Orchestrator architecture has been used by four NASA customers to build telemetry pipelines to support field operations. Example applications include high-volume stereo image capture and processing, simultaneous data monitoring and logging from multiple vehicles. Example telemetry processors used in field test operations support include vehicle position, attitude, articulation, GPS location, power, and stereo images.
The Kepler mission is designed to continuously monitor up to 170,000 stars at a 30 minute cadence for 3.5 years searching for Earth-size planets. The data are processed at the Science Operations Center (SOC) at NASA Ames Research Center. Because of the large volume of data and the memory and CPU-intensive nature of the analysis, significant computing hardware is required. We have developed generic pipeline framework software that is used to distribute and synchronize the processing across a cluster of CPUs and to manage the resulting products. The framework is written in Java and is therefore platform-independent, and scales from a single, standalone workstation (for development and research on small data sets) to a full cluster of homogeneous or heterogeneous hardware with minimal configuration changes. A plug-in architecture provides customized control of the unit of work without the need to modify the framework itself. Distributed transaction services provide for atomic storage of pipeline products for a unit of work across a relational database and the custom Kepler DB. Generic parameter management and data accountability services are provided to record the parameter values, software versions, and other meta-data used for each pipeline execution. A graphical console allows for the configuration, execution, and monitoring of pipelines. An alert and metrics subsystem is used to monitor the health and performance of the pipeline. The framework was developed for the Kepler project based on Kepler requirements, but the framework itself is generic and could be used for a variety of applications where these features are needed.
The Helioseismic and Magnetic Imager onboard the Solar Dynamics Observatory (SDO/HMI) provides continuous full-disk observations of solar oscillations. We develop a data-analysis pipeline based on the time-distance helioseismology method to measure acoustic travel times using HMI Doppler-shift observations, and infer solar interior properties by inverting these measurements. The pipeline is used for routine production of near-real-time full-disk maps of subsurface wave-speed perturbations and horizontal flow velocities for depths ranging from 0 to 20 Mm, every eight hours. In addition, Carrington synoptic maps for the subsurface properties are made from these full-disk maps. The pipeline can also be used for selected target areas and time periods. We explain details of the pipeline organization and procedures, including processing of the HMI Doppler observations, measurements of the travel times, inversions, and constructions of the full-disk and synoptic maps. Some initial results from the pipeline, including full-disk flow maps, sunspot subsurface flow fields, and the interior rotation and meridional flow speeds, are presented.
This document describes the results of the fourth pixel-level transit injection experiment, which was designed to measure the detection efficiency of both the Kepler pipeline (Jenkins 2002, 2010; Jenkins et al. 2017) and the Robovetter (Coughlin 2017). Previous transit injection experiments are described in Christiansen et al. (2013, 2015a,b, 2016).In order to calculate planet occurrence rates using a given Kepler planet catalogue, produced with a given version of the Kepler pipeline, we need to know the detection efficiency of that pipeline. This can be empirically determined by injecting a suite of simulated transit signals into the Kepler data, processing the data through the pipeline, and examining the distribution of successfully recovered transits. This document describes the results for the pixel-level transit injection experiment performed to accompany the final Q1-Q17 Data Release 25 (DR25) catalogue (Thompson et al. 2017)of the Kepler Objects of Interest. The catalogue was generated using the SOC pipeline version 9.3 and the DR25 Robovetter acting on the uniformly processed Q1-Q17 DR25 light curves (Thompson et al. 2016a) and assuming the Q1-Q17 DR25 Kepler stellar properties (Mathur et al. 2017).
The Surface Biology and Geology (SBG) mission recently passed mission confirmation review and has entered phase A – design and development. SBG will acquire high resolution solar-reflected spectroscopy and thermal infrared observations at a data rate of ~2.5 TB/day and generate products at ~40 TB/day. Given that the per-day volume is greater than NASA’s total extant airborne hyperspectral data collection, collecting, processing, disseminating, and exploiting the SBG data present new challenges. To meet these challenges, we have developed a prototype science pipeline and a full-volume global hyperspectral synthetic data set to help prepare for SBG’s flight (see poster GC42D-0730). Our science pipeline is based on the science processing technology developed for NASA’s Kepler and TESS planet-hunting missions. The pipeline infrastructure, Ziggy, provides a scalable architecture for robust, repeatable, and replicable science and application products that can be run on a range of systems from a laptop to the cloud or a supercomputer. Ziggy is compliant with NASA Procedural Requirement (NPR) 7150.2C, is at a technical readiness level (TRL) of 7 and has been released to github.com/nasa/ziggy. We integrated Ziggy with EO-1/Hyperion workflows to build a prototype pipeline and ingested the 17-year mission archive that provides globally sampled visible through shortwave infrared spectra that are representative of SBG data types and volumes. We fully implemented the first stage and processed the entire 55 TB Hyperion data set from the raw data (Level 0) to top-of-the-atmosphere radiance (Level 1R). We are currently evaluating the ISOFIT atmospheric correction module to convert the L1R data to surface reflectance (Level 2) before reprocessing the full data set to L2. Crosschecks are being performed with RadCalNet as well as with coincident observations by AVIRIS. We are also investigating modern methods for georectifying the Hyperion scenes. Finally, we describe an analysis of the cost to conduct forward processing and reprocessing campaigns for SBG on HECC with dedicated compute and storage resources using the resurrected Hyperion pipeline as a proxy for full-volume SBG data. The analysis demonstrates that SBG L0 data can be processed to L2 on HECC with full reprocessing campaigns every two years for ~$2.6M over a 7-year lifespan. Moreover, 69% of the system capacity would be available for other activities, possibly enabling future open-source science activities, including algorithm development, L3+ processing, .etc.