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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 361 records · Page 20

Flash Thermal Diffusivity Measurements and Inspection of Additively Manufactured Ti-6Al-4V Specimens with Varying Process Parameters

Flash thermal diffusivity measurements were obtained on additively manufactured Ti-6Al-4V disk shaped specimens with various process parameters. For additively manufactured metal parts, processing parameters such as laser power and scanning speed are critical to ensure the desired microstructure. For this study, the laser powder bed fusion process parameters were changed at various angular sections on a 21 mm diameter and 3.0 mm thick disk. The measurement of thermal diffusivity was performed by fitting a 1-dimensional thermal model to the data pixel by pixel to produce an inspection image. The image revealed the detection of defects such as lack of fusion porosity and areas of aggregated porosity. The thermal diffusivity imagery was compared to immersion scan ultrasonic and X-ray computed tomography (CT) measurements for validation. Based on these results, additional samples were investigated using a single side thermal inspection technique to detect lack of fusion porosity and near surface voids.

thermal nondestructive evaluation↗

Flash Thermal Diffusivity Measurements and Inspection of Additively Manufactured Ti-6Al-4V Specimens with Varying Process Parameters

Flash thermal diffusivity measurements were obtained on additively manufactured Ti-6Al-4V disk shaped specimens with various process parameters. For additively manufactured metal parts, processing parameters such as laser power and scanning speed are critical to ensure the desired microstructure. For this study, the laser powder bed fusion process parameters were changed at various angular sections on a 21 mm diameter and 3.0 mm thick disk. The measurement of thermal diffusivity was performed by fitting a 1-dimensional thermal model to the data pixel by pixel to produce an inspection image. The image revealed the detection of defects such as lack of fusion porosity and areas of aggregated porosity. The thermal diffusivity imagery was compared to immersion scan ultrasonic and X-ray computed tomography (CT) measurements for validation. Based on these results, additional samples were investigated using a single side thermal inspection technique to detect lack of fusion porosity and near surface voids.

thermal nondestructive evaluation↗

3D Cloud Tomography and Droplet Size Retrieval from Multi-Angle Polarimetric Imaging of Scattered Sunlight from Above

Tomography aims to recover a three-dimensional (3D) density map of a medium or an object. In medical imaging,it is extensively used for diagnostics via X-ray computed tomography (CT). We define and derive a tomographyof cloud droplet distributions via passive remote sensing. We use multi-view polarimetric images to fit a 3Dpolarized radiative transfer (RT) forward model. Our motivation is 3D volumetric probing of vertically-developedconvectively-driven clouds that are ill-served by current methods in operational passive remote sensing. Currenttechniques are indeed based on strictly 1D RT modeling and applied to a single cloudy pixel, where cloud geometrydefaults to that of a plane-parallel slab. Incident unpolarized sunlight, once scattered by cloud droplets, changesits polarization state according to droplet size. Therefore, polarimetric measurements in the rainbow and gloryangular regions can be used to infer the droplet size distribution. This work defines and derives a framework for afull 3D tomography of cloud droplets for both their mass concentration in space and their distribution across arange of sizes. This gridded 3D retrieval of key microphysical properties is made tractable by our novel approachthat involves a restructuring and partial linearization of an open-source polarized 3D RT code to accommodate aspecial two-step iterative optimization technique. Physically-realistic synthetic clouds are used to demonstrate themethodology with rigorous uncertainty quantification, while a real-world cloud imaged by AirMSPI is processedto illustrate the new remote sensing capability

Schechner, Yoav Y.↗

Modeling of Response of Thermoplastic Composites Under High Energy Impact

This work investigates the response of a thermoplastic panel under high energy ballistic impact. The composite material system is a carbon fiber reinforced low melt semi-crystalline resin TC1225 LMPAEK T700G (T700/LMPAEK3). Several high energy dynamic impact tests were performed where an aluminum projectile impacted various panels at different impact velocities. For this work, the test performed at an impact velocity of 73.2 m/s was investigated. The projectile rebounded upon impact, and the damage to the panel was characterized through ultrasonic and CT-scanning. Response of the panel under impact and the associated damage is discussed. Numerical simulation of the impact process was performed using the LS-DYNA® computer code [1] with a new material model MAT_COMPOSITE_DAMAGE_DGD (MAT 299), a modification over MAT 261 material model in terms of an improved representation of damage coupling and additional capability for strain rate effects. Delaminations were modeled using cohesive zone contact formulation in LS-DYNA®, wherein the mixed-mode fracture is captured via the Benzegaggh-Kenane (B-K) mode-dependent fracture energy interpolation law. Simulation of this impact test demonstrates a good match of results in terms of panel deflection and panel-projectile interactions. The overall extent of delaminations was under-predicted by the simulation. This work forms the basis to model tests performed at higher velocities, involving projectile penetration of panel.

Composite Materials↗

Characterization of Low-Velocity Impact Damage in Thermoplastic Laminated Composites

The impact damage response of two thermoplastic material systems were compared over a range of impact energies. Eight-inch-square impact specimens with a 24-ply quasi-isotropic layup were manufactured from TC1225 LMPAEK T700G from Toray Industries and APC AS4D/PEKK-FC from Solvay. The effect of the degree of crystallinity (DOC) on the damage response was also investigated using a third set of specimens from the Toray material manufactured with reduced crystallinity. Using a combination of data obtained from X-ray computed tomography (CT) scans and ultrasonic testing (UT), detailed damage maps were created for every interface and ply for selected specimens. Using these damage maps, the delamination size, shape, and area were evaluated at each interface. The presence of fractured fibers was also identified on each ply. The LMPAEK material was found to have fewer and smaller delaminations than the PEKK specimens for impacts at the same energy. However, the LMPAEK specimens contained a larger number of fiber breaks. A similar trend was observed when comparing the baseline LMPAEK specimens with the low-crystallinity LMPAEK specimens. The low-crystallinity specimens had very little delamination but had a large number of plies with fiber breaks. In addition, the LMPAEK specimens often contained lines of fiber fractures in near-surface plies emanating from the contact region that were not present in the PEKK specimens.

Composite Materials↗

Porosity Area Fraction Analysis of Bonded Borosilicate Specimens From in-Situ Optical Imagery

Image segmentation methods are routinely used to analyze data derived in nondestructive testing scenarios. A typical problem in this area is to estimate porosity from X-ray Computed Tomography (CT) inspections. This investigation aims to understand the effectiveness of open-source image segmentation methods for porosity estimation from optical images in the context of strength analysis of bonded materials and provides a benchmark of performance against a standard commercial software package. The rank ordering of the specimens by porosity area fraction is consistent across both methods.

Porosity area fraction↗

Characterization of Low-Velocity Impact Damage in Thermoplastic Laminated Composites

The impact damage response of two thermoplastic material systems were compared over a range of impact energies. Eight-inch-square impact specimens with a 24-ply quasi-isotropic layup were manufactured from TC1225 LMPAEK T700G from Toray Industries and APC AS4D/PEKK-FC from Solvay. The effect of the degree of crystallinity (DOC) on the damage response was also investigated using a third set of specimens from the Toray material manufactured with reduced crystallinity. Using a combination of data obtained from X-ray computed tomography (CT) scans and ultrasonic testing (UT), detailed damage maps were created for every interface and ply for selected specimens. Using these damage maps, the delamination size, shape, and area were evaluated at each interface. The presence of fractured fibers was also identified on each ply. The LMPAEK material was found to have fewer and smaller delaminations than the PEKK specimens for impacts at the same energy. However, the LMPAEK specimens contained a larger number of fiber breaks. A similar trend was observed when comparing the baseline LMPAEK specimens with the low-crystallinity LMPAEK specimens. The low-crystallinity specimens had very little delamination but had a large number of plies with fiber breaks. In addition, the LMPAEK specimens often contained lines of fiber fractures in near-surface plies emanating from the contact region that were not present in the PEKK specimens.

Composite Materials↗

Electron Beam Welding of Additively Manufactured Niobium Alloy Heat Pipes

Additively manufactured refractory alloy-liquid metal heat pipes are being developed and tested for thermal management systems within nuclear propulsion and power applications. This study investigated electron beam (EB) welded joints on a laser powder bed fusion printed niobium alloy (C-103) and the impact of multiple joined heat pipe sections on working fluid flow and container leak-tightness. Results showed that EB welded joints connecting multiple heat pipe sections do not impact working fluid wicking behavior and the printed C-103 material and the EB welds joining the tubular sections created a leak-tight container. Interestingly, CT data showed an order of magnitude greater number and volume of porosity indications in the ground mating surface weld compared to the as-printed mating surface weld. The work concluded that AM is a viable manufacturing process for niobium alloy heat pipes and provided valuable insights for future AM heat pipe research and development.

Electron beam welding↗

Harnessing Artificial Intelligence for Medical Diagnosis and Treatment During Space Exploration Missions

BACKGROUND The medical capabilities necessary for long-duration exploration missions (LDEMs) will differ tremendously from those currently available to crew medical officers (CMOs) on the International Space Station (ISS). Ground support will be more challenging due to distance-related communication delays and data transmission, and resource utilization must be optimized given limited ability for resupply. Clinical decision support systems (CDSSs) can help mitigate these limitations. The recent launch of generative artificial intelligence (AI) tools based upon large language models (LLM) support the creation of a smart assistant for onboard triage, diagnosis, and guided treatment of medical conditions during these missions. The Informing Mission Planning via Analysis of Complex Tradespaces (IMPACT) tool can help predict which clinical problems and outcomes are likely to occur for a design reference mission (DRM) and assist Medical Operations and systems engineering teams in creating a medical system that may optimally mitigate the predicted risks. The purpose of this study was to identify AI tools currently available or in development for the assistive diagnosis and care of medical conditions predicted for an extended duration Lunar mission. METHODS The 119 medical conditions currently built into the IMPACT suite were categorized into systems, and these diagnoses were used as keywords for our literature search. Using PubMed and Google Scholar, we performed a literature survey of AI tools applicable to these conditions. Article inclusion criteria included publication between the years 2017-2023, as the sentinel paper discussing the “selective attention” driving ChatGPT and other generative transformer models was published in June 2017. Where applicable, we reviewed only the top 1000 research articles (based on relevance) for each of the keywords/phrases. AI tools whose training sets were exclusive to a pediatric patient population were excluded. We also excluded any medical diagnostic tools (such as CT, MRI, mass spectrometry) or procedures (such as endoscopy, surgery) that are unlikely to be available during LDEMs due to mass and volume constraints, CMO knowledge, skills, and abilities, and/or inherent procedural risks. RESULTS Our survey highlighted several AI-driven tools for the triage, diagnosis, and management of those medical conditions highlighted by IMPACT. Selected publications for each medical condition were then screened for inclusion within ten systems-based categories including: general diagnostic tools (25), tools to diagnose and manage respiratory (40), dermatologic (34), neurologic (28), auditory and vestibular (30), ophthalmic (34), musculoskeletal (104), infection-associated (92), and gynecologic (19) conditions, as well as tools that could be deployed in the setting of trauma and emergency (34). CONCLUSIONS Numerous AI-driven tools were highlighted within this literature survey, ranging from chatbot assistants that triage knee pain to vision transformer models for diagnosis of ophthalmic conditions using ocular surface images captured with a mobile phone. Remaining challenges include optimizing connectivity and integration of existing and developing systems into the vehicles or habitats. Notably, findings from this survey could help guide the initial design of an all-encompassing, onboard medical AI assistant for use during future LDEMs.

R A Lacinski↗

Acquisition of and Access to Research Omics Data

Omics data are essential for understanding the myriad and complex effects of space environments on humans. To assure maximum benefit from these kinds of data, the NASA Human Research Program Data Management Plan stipulates that human omics data should be archived within and accessed through the NASA Life Sciences Portal (NLSP). The NLSP has the capability to acquire and provision access to omics (and other kinds of) research results for individual and ad-hoc groups of subjects at the direction of institutional review boards, or other authorizing bodies or individuals, per institutional, program and investigation-specific policies and procedures. However, because some single-subject omics data, like CT scans and other kinds of large, complex biomedical data, could be used to identify heretofore unknown risks to the subject’s health, or, in certain cases, be used to identify a subject, NASA Policy Directive 7170.1 describes various policies regarding the management of and access to “research genetic testing” data, which includes many kinds of omics data. For example, NPD 7170.1 prohibits access to human research genetic data by NASA personnel who make employment decisions for the subjects from whom the data were obtained. To meet the objective of acquiring research omics data for NLSP in compliance with the policies in NPD 7170.1 and other applicable NASA policies, we designed NOMADS (the NLSP Omics Multimodal Acquisition of Data System), a new component that supports the transfer of large research data files, including research genetic testing data, using one of several different transfer mechanisms. The choice of mechanism is made by the submitter of the data, with guiding information from the system, and is likely to often be determined in large part by the nature and source location of the data. For example, for small files where the source data files are not already stored in a cloud storage system, users are likely to prefer to transfer their data to the NLSP via a web browser. Conversely, for large sets of files already organized and stored in a cloud storage system, users may opt for NOMAD’s cloud-to-cloud transfer method. All omics datasets targeted for the NASA Life Sciences Data Archive must pass a variety of quality checks to ensure data integrity and adherence to the standards defined by the LSDA Data Submission Guidelines (DSG) (see https://nlsp.nasa.gov/explore/lsdahome/datasubmit). These include requirements that data are consistent with open standards established by the omics community. Non-compliant data will not be accepted however archivists are available to advise submitters on how to revise data submissions and re-submit until compliance is achieved. Following compliance with the LSDA DSG, omics data next undergo a variety of additional quality checks to ensure the data meet omics community standards. Domain specific Omics data quality control tools and techniques are continually evolving and linked to the advancements in omics assays utilized and thus, the tools and techniques utilized by the LSDA for data quality control and validation will need to be sustained accordingly. All human omics data will be access controlled according to the policies described above, and requiring IRB approval for any additional access grants once the data are acquired (including access for analysis using the NLSP workspace tools).

Omics↗

Research Operations and Integration Flight Session – Always Sweat the Small Stuff

Human research routinely involves elaborate operations with substantial hardware setup, such as functional MRIs, CT scans, ultrasounds, exercise sessions, and cardiac evaluations. These conspicuous operations garner most of our attention and, understandably, resources, but the unsung heroes of spaceflight human research often get by with little fanfare. The collection of human samples and surveys is often just as much of a challenge in terms of both planning and logistics. The samples and surveys are often collected or completed by the crew autonomously, with little to no oversight from science support staff, which puts them the most at risk for data loss. The Research Operations and Integration team will host an interactive session with audience participation to demonstrate the importance of the written communications and instructions that are provided to the astronauts. During this hands-on session, ROI will walk through the challenges faced to ensure astronaut subjects can successfully collect all the various samples (e.g., saliva, fecal, urine, and blood) that the human research community needs. The format will be part lecture and part game show intended to provide both an enlightening and fun session. As we often instruct the crew: “Don’t forget to arrive fasted and bring a list of all the medications you’ve taken in the past week.”

Cherie Morgan Oubre↗

Multiscale Modeling of Reconstructed Tricalcium Silicate using NASA Multiscale Analysis Tool

To study microstructure characteristics of cementitious materials hydrated in space; previously, cement binder formations were processed under microgravity conditions and was further compared against ground-based experiments. For accurate estimation of process-structure-property linkage, particularly on samples hydrated in the microgravity environment, it is desired to have a high-fidelity volumetric representation of the microstructure. However, owing to small sample size and high porosity of the space-returned samples, conventional experimental characterization techniques are not viable. Hence, a deep learning-based reconstruction algorithm was employed to obtain high fidelity 3D volumes from sparse high resolution 2D Scanning Electron Microscopy (SEM) images, as inputs to micromechanics-based modeling. This machine learning-based reconstruction methodology validated against low-order statistical descriptors, captured the microstructural topology of both sample types (ground, 1g and microgravity, μg). Due to the lack of gravity, hydration products of the samples processed in space differed from those processed-on ground. Such AI-generated virtual samples were analyzed in a multiscale recursive micromechanics approach using the NASA Multiscale Analysis Tool (NASMAT). Here, we present a methodology to rapidly integrate and evaluate these AI-generated volumes in NASMAT. The synthesized microstructural volumes are directly employed as Representative Volume Elements (RVEs) to preserve the fidelity (1 pixel = 0.54 m). Invariably, analysis of such largescale problems (5123 voxels) requires huge amount of computational resources. By taking advantage of the NASMAT architecture, we also focused on systematic multiscale integration of these AI-reconstructed virtual volumes to reduce the computational demands. In this work, this methodology is demonstrated on the ground-based, 1g samples. The estimated stiffness value of 15.90 GPa is comparable to experimentally obtained modulus of hydrated tricalcium silicate sample. The workflow presented here paves the way for utilizing the NASMAT tool to perform multiscale analyses of other multi-phase material systems using either 3D virtual datasets synthesized using AI or obtained via micro-CT.

Machine Learning↗

X-Ray Micro- and Nano-Tomography Analysis of Bennu Samples: A Preliminary Report

X-ray tomography (XCT) is an effective technique for obtaining the 3D structures of returned samples. XCT using synchrotron radiation provides high-resolution CT images with quantitative information. The XCT systems at SPring-8, an SR facility in Japan, have been used to analyze samples returned from the asteroids Itokawa and Ryugu. In this study, we plan to apply SR-XCT to samples returned from the asteroid Bennu.

A Tsuchiyama↗

Acquisition of and Access to Research Omics Data

Omics data are essential for understanding the myriad and complex effects of space environments on humans. To assure maximum benefit from these kinds of data, the NASA Human Research Program Data Management Plan stipulates that human omics data should be archived within and accessed through the NASA Life Sciences Portal (NLSP). The NLSP has the capability to acquire and provision access to omics (and other kinds of) research results for individual and ad-hoc groups of subjects at the direction of institutional review boards, or other authorizing bodies or individuals, per institutional, program and investigation-specific policies and procedures. However, because some single-subject omics data, like CT scans and other kinds of large, complex biomedical data, could be used to identify heretofore unknown risks to the subject’s health, or, in certain cases, be used to identify a subject, NASA Policy Directive 7170.1 describes various policies regarding the management of and access to “research genetic testing” data, which includes many kinds of omics data. For example, NPD 7170.1 prohibits access to human research genetic data by NASA personnel who make employment decisions for the subjects from whom the data were obtained. To meet the objective of acquiring research omics data for NLSP in compliance with the policies in NPD 7170.1 and other applicable NASA policies, we designed NOMADS (the NLSP Omics Multimodal Acquisition of Data System), a new component that supports the transfer of large research data files, including research genetic testing data, using one of several different transfer mechanisms. The choice of mechanism is made by the submitter of the data, with guiding information from the system, and is likely to often be determined in large part by the nature and source location of the data. For example, for small files where the source data files are not already stored in a cloud storage system, users are likely to prefer to transfer their data to the NLSP via a web browser. Conversely, for large sets of files already organized and stored in a cloud storage system, users may opt for NOMAD’s cloud-to-cloud transfer method. All omics datasets targeted for the NASA Life Sciences Data Archive must pass a variety of quality checks to ensure data integrity and adherence to the standards defined by the LSDA Data Submission Guidelines (DSG) (see https://nlsp.nasa.gov/explore/lsdahome/datasubmit). These include requirements that data are consistent with open standards established by the omics community. Non-compliant data will not be accepted however archivists are available to advise submitters on how to revise data submissions and re-submit until compliance is achieved. Following compliance with the LSDA DSG, omics data next undergo a variety of additional quality checks to ensure the data meet omics community standards. Domain specific Omics data quality control tools and techniques are continually evolving and linked to the advancements in omics assays utilized and thus, the tools and techniques utilized by the LSDA for data quality control and validation will need to be sustained accordingly. All human omics data will be access controlled according to the policies described above, and requiring IRB approval for any additional access grants once the data are acquired (including access for analysis using the NLSP workspace tools).

Omics↗

The Effect of Impingement Angle on Bipropellant Thruster Plume Degradation of Spacecraft Materials

Unburned and partially combusted liquid propellant present in bipropellant thruster plumes can contaminate and damage external spacecraft materials. Microscopic impact features due to high-speed droplet impacts have been observed on space shuttle flight experiments and International Space Station (ISS) returned flight hardware. Analytical results have shown that particle impingement angle greatly affects surface damage, with normal impacts being the most severe and highly oblique impacts being more benign. The effect of thruster plume impingement angle on material degradation has now been further studied following a bipropellant thruster plume test performed at the high-vacuum plume test facility for chemical thrusters at DLR Göttingen, STG-CT. Several spacecraft material samples were exposed to the freely expanding pulsed thruster plume at a range of impingement angles (from 0 to 75 deg). Results of post-test evaluations and potential spaceflight applications are summarized.

Gateway↗

Emplacement of Shergottites in the Martian Crust Inferred From 3D Petrofabric and Crystal Size Distribution Analyses

Shergottites are mafic to ultramafic igneous rocks that represent a majority of known martian meteorites. They are subdivided into gabbroic, poikilitic, basaltic, and olivine-phyric categories based on differences in mineralogy and textures. Their geologic contexts are unknown so analyses of crystal sizes and preferred orientations have commonly been used to infer where shergottites solidified. Such environments range from subsurface cumulates to shallow intrusives to extrusive lava flows, which all have contrasting implications for interactions with crustal material, cooling histories, and potential in situ exposure at the surface. In this study, we present a novel three-dimensional (3D) approach to better understand the solidification environments of these samples and improve our knowledge of shergottites’ geologic contexts. Shape preferred orientations of most phases and crystal size distributions of late-forming minerals were measured in 3D using X-ray computed tomography (CT) on eight shergottites representing the gabbroic, poikilitic, basaltic, and olivine-phyric categories. Our analyses show that highly anisotropic, rod-like pyroxene crystals are strongly foliated in the gabbroic samples but have a weaker foliation and a mild lineation in the basaltic sample, indicating a directional flow component in the latter. Star volume distribution analyses revealed that most phases (maskelynite, pyroxene, olivine, and oxides/sulfides) preserve a foliated texture with variable strengths, and that the phases within individual samples are strongly to moderately aligned with respect to one another. In combination with relative cooling rates during the final stages of crystallization determined from interstitial oxide/sulfide crystal size distribution analyses, these results indicate that the olivine-phyric samples were emplaced as shallow intrusives (e.g., dikes/sills) and that the gabbroic, poikilitic, and basaltic samples were emplaced in deeper subsurface environments.

Martian meteorites↗

Near Infrared In-situ Measurements for the Detection of Keyhole Porosity in Autogenous Ti-6AL-4V Welds

Certification of additive manufactured metal parts requires nondestructive evaluation (NDE) to ensure build quality. NDE can be performed during the build process or post build. For large parts with complex geometries, post build NDE can be challenging. In-situ NDE potentially provides a way to perform the inspection layer by layer. This work explores the use of a high speed near infrared (NIR) camera that is focused in-line with a laser to obtain high spatial and temporal resolution thermal imagery of the melt pool and associated cooling areas. The thermal data is obtained during a laser melting process using Ti-6AL-4V plate and of particular interest is the detection of keyhole porosity. Keyhole porosity can result from non-optimal build conditions, such as excessive laser power at a given laser scanning speed, that creates an entrapped bubble. The NIR measured melt pool and cooling areas are processed to detect keyhole porosity. The results are compared to X-ray CT results for validation.

additive manufacturing↗

Near Infrared In-situ Measurements for the Detection of Keyhole Porosity in Autogenous Ti-6AL-4V Welds

Certification of additive manufactured metal parts requires nondestructive evaluation (NDE) to ensure build quality. NDE can be performed during the build process or post build. For large parts with complex geometries, post build NDE can be challenging. In-situ NDE potentially provides a way to perform the inspection layer by layer. This work explores the use of a high speed near infrared (NIR) camera that is focused in-line with a laser to obtain high spatial and temporal resolution thermal imagery of the melt pool and associated cooling areas. The thermal data is obtained during a laser melting process using a Ti-6Al-4V plate and of particular interest is the detection of keyhole porosity. Keyhole porosity can result from non-optimal build conditions, such as excessive laser power at a given laser scanning speed, that creates an entrapped bubble. The NIR measured melt pool and cooling areas are processed to detect keyhole porosity. The results are compared to X-ray CT results for validation. Small keyhole pores buried deep were not detectable with this technique, however, some larger subsurface elongated pores along with some open surface pores did show some promise for detectability.

additive manufacturing↗