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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 19 records

2025 Peregrine in-situ monitoring and training dataset for laser powder bed fusion and binder jet printers

Peregrine, a software tool developed at Oak Ridge National Laboratory (ORNL), was used to collect and analyze in-situ monitoring (ISM) data from a Concept Laser M2 (Colibrium Additive) laser powder bed fusion (L-PBF) printer and an ExOne Innovent (Desktop Metal) binder jet printer. Data for four builds (print jobs) were saved to HDF5 (high performance data) files for release. Additionally, process anomalies were annotated by the authors across 37 image stacks (i.e., print layers) and are also provided as HDF5 files.

36 MATERIALS SCIENCE↗

Intraspecific evolutionary relationships among peregrine falcons in western North American high latitudes

Subspecies relationships within the peregrine falcon (Falco peregrinus) have been long debated because of the polytypic nature of melanin-based plumage characteristics used in subspecies designations and potential differentiation of local subpopulations due to philopatry. In North America, understanding the evolutionary relationships among subspecies may have been further complicated by the introduction of captive bred peregrines originating from non-native stock, as part of recovery efforts associated with mid 20th century population declines resulting from organochloride pollution. Alaska hosts all three nominal subspecies of North American peregrine falcons–F. p. tundrius, anatum, and pealei–for which distributions in Alaska are broadly associated with nesting locales within Arctic, boreal, and south coastal maritime habitats, respectively. Unlike elsewhere, populations of peregrine falcon in Alaska were not augmented by captive-bred birds during the late 20th century recovery efforts. Population genetic differentiation analyses of peregrine populations in Alaska, based on sequence data from the mitochondrial DNA control region and fragment data from microsatellite loci, failed to uncover genetic distinction between populations of peregrines occupying Arctic and boreal Alaskan locales. However, the maritime subspecies, pealei, was genetically differentiated from Arctic and boreal populations, and substructured into eastern and western populations. Levels of interpopulational gene flow between anatum and tundrius were generally higher than between pealei and either anatum or tundrius. Estimates based on both marker types revealed gene flow between augmented Canadian populations and unaugmented Alaskan populations. While we make no attempt at formal taxonomic revision, our data suggest that peregrine falcons occupying habitats in Alaska and the North Pacific coast of North America belong to two distinct regional groupings–a coastal grouping (pealei) and a boreal/Arctic grouping (currently anatum and tundrius)– each comprised of discrete populations that are variously intra-regionally connected.

60 APPLIED LIFE SCIENCES↗

Supplementary Feeding, Plumage Documentation and Early Season Prey of Peregrine Falcons at the New Mexico Alpha Eyrie

A review of what is known about avian physiology and the biological effects of DDE suggests that some benefit to peregrine falcon egg condition could be attained by artificially feeding DDE free prey to the female from the time of her arrival on the nesting grounds until completion of egg laying; the magnitude of potential benefit is unknown. Sporadic efforts in the past demonstrated the need for precision methods of prey delivery. Two methods were developed and tried; providing dead prey items by dropping them in a day perch, and delivery of live prey by remotely controlled release from compartments positioned at the top of the cliff occupied by the falcons. Maintaining quail in the day perch for 21 days resulted in at least one and probably two meals for the female peregrine. Of 16 live birds released (mostly pigeons) 13 were pursued and three caught. Blinding the pigeons with tape proved to be necessary to enable capture. Also, some reluctance of the male peregrine to attack pigeons was observed, and problems with equipment, visibility, and the proximity of the falcons to the release box were encountered. Manpower was the most significant resource requirement. Baiting of great-horned owls, possibly leading to owl attack on the falcons, is judged to be the largest detrimental effect of supplemental feeding. It is recommended that supplemental feeding be reserved for falcons or eyries where complete reproductive failure is expected. Plumage documentation photography was successfully conducted by a remotely controlled camera as an aid to identification of individual falcons. American robin, red-winged blackbird, starling, white-throated swift, bluebird, and mourning dove were among natural prey consumed by the peregrines before completion of egg laying. All activities in close proximity to the cliff were conducted at night to preclude direct disturbance of the falcons.

54 ENVIRONMENTAL SCIENCES↗

Peregrine Software Development: Report on the Code Conversion From Python to C++

This work package seeks to convert the Peregrine software tool from its original Python implementation to a production version based on the C++ language. Peregrine is a powerful research platform with a multitude of advanced data analytics and data visualization functionalities. Developed by scientists to explore multimodal and multidimensional data related to the production of components using powder bed additive manufacturing processes, the tool implements state-of-the-art algorithms to assist machine users in making build or part quality determinations. Given that Peregrine is data-intensive, the goal of this conversion is to enhance the tool’s flexibility and interactivity and reduce the number of code dependencies to facilitate its deployment as part of the ongoing technology transfer campaign. This brief document provides an overview of Peregrine’s functionalities and capabilities, along with a detailed description of the core functionalities that have been implemented to date in the new C++ version. This document serves as a development update at the end of the first year of the ongoing conversion and will be regularly updated as progress continues.

97 MATHEMATICS AND COMPUTING↗

Peregrine 100-km Sounding Rocket Project

The Peregrine Sounding Rocket Program is a joint basic research program of NASA Ames Research Center, NASA Wallops, Stanford University, and the Space Propulsion Group, Inc. (SPG). The goal is to determine the applicability of this technology to a small launch system. The approach is to design, build, and fly a stable, efficient liquefying fuel hybrid rocket vehicle to an altitude of 100 km. The program was kicked off in October of 2006 and has seen considerable progress in the subsequent 18 months. This research group began studying liquifying hybrid rocket fuel technology more than a decade ago. The overall goal of the research was to gain a better understanding of the fundamental physics of the liquid layer entrainment process responsible for the large increase in regression rate observed in these fuels, and to demonstrate the effect of increased regression rate on hybrid rocket motor performance. At the time of this reporting, more than 400 motor tests were conducted with a variety of oxidizers (N2O, GOx, LOx) at ever increasing scales with thrust levels from 5 to over 15,000 pounds (22 N to over 66 kN) in order to move this technology from the laboratory to practical applications. The Peregrine program is the natural next step in this development. A number of small sounding rockets with diameters of 3, 4, and 6 in. (7.6, 10.2, and 15.2 cm) have been flown, but Peregrine at a diameter of 15 in. (38.1 cm) and 14,000-lb (62.3-kN) thrust is by far the largest system ever attempted and will be one of the largest hybrids ever flown. Successful Peregrine flights will set the stage for a wide range of applications of this technology.

Zilliac, Gregory↗

Challenges of Designing a Passive Thermal Control System for the Astrobotic Peregrine Lunar Lander

The Astrobotic Peregrine is a lunar lander currently undergoing design by Astrobotic Technology with help from NASA through the Lunar Cargo Transportation and Landing by Soft Touchdown (Lunar CATALYST) program. This paper will discuss the challenges of designing a passive thermal control system for the lander, and how the design has evolved from the initial passive concept. These challenges include drastically varying worst hot and worst cold case thermal environments, narrow temperature limits of critical components, limited available locations for spacecraft component mounting, and unexpected changes causing significant thermal impacts. The initial thermal control strategy was to cold bias the spacecraft by thermally coupling all spacecraft components to one mounting deck, which also doubled as a radiator, and using heaters to maintain each component’s temperature above its lower temperature limit when in the cold environments. As the design evolved, this strategy alone became inadequate. As heat dissipations increased and became more varying with the addition of components, the thermal design was changed and additional thermal control technologies added. Thermal control strategies incorporated into the design include dictating the lander orientation in demanding environments, defining locations for critical spacecraft components, limiting component operation when possible, and using technology to create variable thermal contacts. Additional design changes will occur as the design continues to evolve to optimize the most effective thermal control system. The thermal design of Peregrine is still in progress, with Critical Design Review (CDR) scheduled for December 2019.

Mauro, Stephanie↗

The Peregrine Ion Trap Mass Spectrometer (PITMS) Investigation Development and Pre-Flight Planning

The Peregrine Ion Trap Mass Spectrometer (PITMS) is a mass spectrometer instrument that operated during the Astrobotic Peregrine Mission-1 as part of the NASA Commercial Lunar Payload Services (CLPS) initiative. This paper describes the instrument and investigation design, development, and planning conducted by the PITMS team consisting of a successful partnership between NASA Goddard Space Flight Center (GSFC), The Open University (OU), NASA, and ESA. PITMS was designed to measure the abundance and temporal variability of volatile species in the near-surface lunar exosphere from a landed platform on the lunar surface. The PITMS instrument consisted of an ESA-provided Exospheric Mass Spectrometer (EMS; including sensor, electronics, controller, power supply boards) and a GSFC wrapper that provided structural elements, thermal control, and a deployable dust cover. PITMS was designed to operate as a passive sampler, where ambient gases would enter PITMS through an aperture, diffuse around the mass analyzer cavity, become ionized by electron impact and trapped in a radiofrequency field, then sequentially released to a detector to build a mass spectrum. PITMS was capable of measuring species with a massto-charge ratio (m/z) from 10 to 150 Da, with a mass resolution of approximately 0.5 amu. The PITMS science investigation was planned to be operated by GSFC with an international team of scientists. Though the mission did not achieve its lunar landing, information about the PITMS instrument and planning is provided to be able to understand and effectively use data that will be forthcoming from the investigation.

Barbara Cohen↗

Layer-wise Imaging Dataset from Powder Bed Additive Manufacturing Processes for Machine Learning Applications (Peregrine v2021-03)

This dataset contains layer-wise powder bed images from three different powder bed printing technologies – laser powder bed fusion, electron beam powder bed fusion, and binder jetting. This dataset was collected and annotated using the internally-developed Peregrine software tool and is designed primarily to facilitate research into anomaly defect detection using image segmentation or similar techniques. A total of 20 layers are provided for each printing technology, with each layer of data consisting of one or more calibrated images and an annotation file containing pixel-wise ground truth labels. The ground truths were labeled by domain experts, typically printer technicians. Data in this release were collected at Oak Ridge National Laboratory between 2016 and 2020 and were compiled in March 2021.

36 MATERIALS SCIENCE↗

A Co-Registered In-Situ and Ex-Situ Dataset from an Electron Beam Powder Bed Fusion Additive Manufacturing Process (Peregrine v2023-09)

This release contains a co-registered in-situ and ex-situ Peregrine dataset from a single Arcam Q10 Electron Beam Powder Bed Fusion (EB-PBF) Inconel 738 build. These data were collected at the Manufacturing Demonstration Facility (MDF) located at Oak Ridge National Laboratory (ORNL). The dataset includes layer-wise Near Infrared (NIR) in-situ imaging data, in-situ temporal sensor data, ex-situ X-Ray Computed Tomography (X-CT) scans, and the target part geometries. Additionally, anomaly detections produced by a trained Dynamic Segmentation Convolutional Neural Network (DSCNN) are provided.

36 MATERIALS SCIENCE↗

A Co-Registered In-Situ and Ex-Situ Tensile Properties Dataset from a Laser Powder Bed Fusion Additive Manufacturing Process (Peregrine v2023-11)

This release contains a co-registered in-situ and ex-situ Peregrine dataset from five Concept Laser M2 Laser Powder Bed Fusion (L-PBF) stainless steel 316L builds containing 6,299 SS-J3 individually tracked tensile coupons. These data were collected at the Manufacturing Demonstration Facility (MDF) located at Oak Ridge National Laboratory (ORNL). The dataset includes layer-wise visible-light in-situ imaging data, the laser scan paths and parameters, in-situ temporal sensor data, room-temperature static tensile test results, and the target part geometries. Additionally, anomaly detections produced by a modified Dynamic Segmentation Convolutional Neural Network (DSCNN) are provided.

36 MATERIALS SCIENCE↗

A Co-Registered In-Situ and Ex-Situ Dataset from a Laser Powder Bed Fusion Additive Manufacturing Process (Peregrine v2023-10)

This release contains a co-registered in-situ and ex-situ Peregrine dataset from a single Concept Laser M2 Laser Powder Bed Fusion (L-PBF) stainless steel 316L build. These data were collected at the Manufacturing Demonstration Facility (MDF) located at Oak Ridge National Laboratory (ORNL). The dataset includes layer-wise visible-light in-situ imaging data, the laser scan paths and parameters, in-situ temporal sensor data, X-Ray Computed Tomography (X-CT) scans, pycnometry and tensile test results, etched micrographs from selected locations, and the target part geometries. Additionally, anomaly detections produced by a modified Dynamic Segmentation Convolutional Neural Network (DSCNN) are provided.

36 MATERIALS SCIENCE↗

Status Update Report for the Peregrine 100km Sounding Rocket Project

The Peregrine Sounding Rocket Program is a joint basic research program of NASA Ames Research Center, NASA Wallops, Stanford University and the Space Propulsion Group, Inc. (SPG). The goal is to determine the applicability of liquifying hybrid technology to a small launch system. The approach is to design, build, test and y a stable, efficient liquefying fuel hybrid rocket vehicle to an altitude of 100 km. The program was kicked o in October of 2006 and has seen considerable progress in the subsequent 18 months. Two virtually identical vehicles will be constructed and own out of the NASA Sounding Rocket Facility at Wallops Island. This paper presents the current status of the project as of June 2008. For background on the project, the reader is referred to last year's paper.

Dyer, Jonny↗

Peregrine Sustainer Motor Development

The Peregrine sounding rocket is an in-house NASA design that provides approximately 15 percent better performance than the motor it replaces. The design utilizes common materials and well-characterized architecture to reduce flight issues encountered with the current motors. It engages NASA design, analysts, test engineers and technicians, ballisticians, and systems engineers. The in-house work and collaboration within the government provides flexibility to efficiently accommodate design and program changes as the design matures and enhances the ability to meet schedule milestones. It provides a valuable tool to compare industry costs, develop contracts, and it develops foundational knowledge for the next generation of NASA engineers.

Brodell, Chuck↗

Peregrine Hybrid Rocket Ground Test Video

The attached edited and compressed video shows the final ground test of the Peregrine hybrid rocketflight-weight motor that took place at NASA Ames on March 15, 2017.

Zilliac, Gregory↗

Peregrine

The purpose of “Peregrine” is to perform in-situ quality control of the additive manufacturing process in powder bed systems. The software is an AI-based method to automatically detect and map multiple classes of defects present in the top layer of a powder bed system, either after material deposition, i.e. raking, or after printing the layer. Relying on image data or sensing modalities that can be converted into image data, the code allows for: (1) various steps of pre-processing of the data (registration, distortion correction, etc), (2) annotation of training datasets, (3) processing of data inline or offline, (4) creating 3D rendering of the defect map, and (5) implementation of corrective actions if allowed by the manufacturing platform.

Paquit, Vincent C↗

Layer-wise Imaging Dataset from Powder Bed Additive Manufacturing Processes for Machine Learning Applications (Peregrine v2022-10)

This release consists of six datasets which together include multi-modal layer-wise powder bed images from two different powder bed printing technologies. These datasets are designed primarily to facilitate the development and testing of new computer vision and machine learning based anomaly and defect detection algorithms. The authors provide both training data with corresponding ground truth pixel masks and evaluation data with corresponding baseline prediction pixel masks made by a trained neural network. The laser powder bed fusion (L-PBF) datasets are sourced from EOS M290 and AddUp FormUp 350 printers and the binder jet (BJ) dataset is sourced from an ExOne M-Flex printer. The materials represented in these datasets include 17-4 PH Stainless Steel, DMREF, Inconel 718, Maraging Steel, and H13 Steel. The sensor imaging modalities represented include visible-light (VL), temporally-integrated (i.e., long duration exposure) near-infrared (TI-NIR), and wide-band infrared (IR).

36 MATERIALS SCIENCE↗

Layer-wise Imaging Dataset from Powder Bed Additive Manufacturing Processes for Machine Learning Applications (Peregrine v2022-10.1)

This release consists of six datasets which together include multi-modal layer-wise powder bed images from two different powder bed printing technologies. These datasets are designed primarily to facilitate the development and testing of new computer vision and machine learning based anomaly and defect detection algorithms. The authors provide both training data with corresponding ground truth pixel masks and evaluation data with corresponding baseline prediction pixel masks made by a trained neural network. The laser powder bed fusion (L-PBF) datasets are sourced from EOS M290 and AddUp FormUp 350 printers and the binder jet (BJ) dataset is sourced from an ExOne M-Flex printer. The materials represented in these datasets include 17-4 PH Stainless Steel, GammaPrint-700, Inconel 718, Maraging Steel, and H13 Steel. The sensor imaging modalities represented include visible-light (VL), temporally-integrated (i.e., long duration exposure) near-infrared (TI-NIR), and wide-band infrared (IR). To download the dataset: (1) Create a Globus account. (2) Create a Globus Endpoint on your computer. (3) Transfer the dataset from the OLCF DOI-DOWNLOADS Collection to your Collection. Common troubleshooting steps: (a) Confirm that the transfer is going from OLCF DOI-DOWNLOADS to your Collection. (b) Create an exception for Globus in your antivirus software so that it can create an Endpoint. (c) Manually create a Globus access directory (where the data will be downloaded) by going to the Preferences > Access tab.

36 MATERIALS SCIENCE↗