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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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104 records · Page 6

Establishing and Monitoring an Aseptic Workspace for Building the MOMA Mass Spectrometer

Mars Organic Molecule Analyzer (MOMA) is an instrument suite on the European Space Agency (ESA) ExoMars 2020 Rover, and the Mass Spectrometer (MOMA-MS) is being built at Goddard Space Flight Center (GSFC). MOMA-MS is a life-detection instrument and thus falls in the most stringent category of Planetary Protection (PP) biological cleanliness requirements. Less than 0.03 spore/m2 are allowed in the instrument sample path. In order to meet these PP requirements, MOMA-MS must be built and maintained in a low bioburden environment. The MOMA-MS project at GSFC maintains three clean rooms with varying levels of bioburden control. The Aseptic Assembly Clean room has the highest level of control, applying three different bioburden reducing methods: 70% Isopropyl Alcohol (IPA), 7.5% Hydrogen Peroxide, and Ultra-Violet C (UVC) light. The three methods are used in rotation and each kills microorganisms by a different mechanism, reducing the likelihood of microorganisms developing resistance to all three. The Integration and Mars Chamber Clean rooms use less biocidal cleaning, with the option to deploy extra techniques as necessary. To support the monitoring of clean rooms and verification that MOMA-MS hardware meets PP requirements, a new Planetary Protection lab was established that currently has the capabilities of standard growth assays for spore or vegetative bacteria, rapid bioburden analysis that detects Adenosine Triphosphate (ATP), plus autoclave and Dry Heat microbial Reduction (DHMR) verification. The clean rooms are monitored for vegetative microorganisms and by rapid ATP assay, and a clear difference in bioburden is observed between the aseptic and other clean room.

Contamination Control Engineering↗

CisLunar Habitat Internal Architecture Design Criteria

BACKGROUND: In preparation for human exploration to Mars, there is a need to define the development and test program that will validate deep space operations and systems. In that context, a Proving Grounds CisLunar habitat spacecraft is being defined as the next step towards this goal. This spacecraft will operate differently from the ISS or other spacecraft in human history. The performance envelope of this spacecraft (mass, volume, power, specifications, etc.) is being defined by the Future Capabilities Study Team. This team has recognized the need for a human-centered approach for the internal architecture of this spacecraft and has commissioned a CisLunar Phase-1 Habitat Internal Architecture Study Team to develop a NASA reference configuration, providing the Agency with a "smart buyer" approach for future acquisition. THE CISLUNAR HABITAT INTERNAL ARCHITECTURE STUDY: Overall, the CisLunar Habitat Internal Architecture study will address the most significant questions and risks in the current CisLunar architecture, habitation, and operations concept development. This effort is achieved through definition of design criteria, evaluation criteria and process, design of the CisLunar Habitat Phase-1 internal architecture, and the development and fabrication of internal architecture concepts combined with rigorous and methodical Human-in-the-Loop (HITL) evaluations and testing of the conceptual innovations in a controlled test environment. The vision of the CisLunar Habitat Internal Architecture Study is to design, build, and test a CisLunar Phase-1 Habitat Internal Architecture that will be used for habitation (e.g. habitability and human factors) evaluations. The evaluations will mature CisLunar habitat evaluation tools, guidelines, and standards, and will interface with other projects such as the Advanced Exploration Systems (AES) Program integrated Power, Avionics, Software (iPAS), and Logistics for integrated human-in-the-loop testing. The mission of the CisLunar Habitat Internal Architecture Study is to become a forcing function to establish a common understanding of CisLunar Phase-1 Habitation Internal Architecture design criteria, processes, and tools. The scope of the CisLunar Habitat Internal Architecture study is to design, develop, demonstrate, and evaluate a Phase-1 CisLunar Habitat common module internal architecture based on design criteria agreed to by NASA, the International Partners, and Commercial Exploration teams. This task is to define the CisLunar Phase-1 Internal Architecture Government Reference Design, assist NASA in becoming a "smart buyer" for Phase-1 Habitat Concepts, and ultimately to derive standards and requirements from the Internal Architecture Design Process. The first step was to define a Habitat Internal Architecture Design Criteria and create a structured philosophy to be used by design teams as a filter by which critical aspects of consideration would be identified for the purpose of organizing and utilizing interior spaces. With design criteria in place, the team will develop a series of iterative internal architecture concept designs which will be assessed by means of an evaluation criteria and process. These assessments will successively drive and refine the design, leading to the combination and down-selection of design concepts. A single refined reference design configuration will be developed into in a medium-to-high fidelity mockup. A multi-day human-in-the-loop mission test will fully evaluate the reference design and validate its configuration. Lessons learned from the design and evaluation will enable the team to identify appropriate standards for Phase-1 CisLunar Habitat Internal Architecture and will enable NASA to develop derived requirements in support of maturing CisLunar Habitation capabilities. This paper will describe the criteria definition process, workshop event, and resulting CisLunar Phase-1 Habitat Internal Architecture Design Criteria.

Jones, R.↗

Medical Data Architecture (MDA) Project Status

The Medical Data Architecture (MDA) project supports the Exploration Medical Capability (ExMC) risk to minimize or reduce the risk of adverse health outcomes and decrements in performance due to in-flight medical capabilities on human exploration missions. To mitigate this risk, the ExMC MDA project addresses the technical limitations identified in ExMC Gap Med 07: We do not have the capability to comprehensively process medically-relevant information to support medical operations during exploration missions. This gap identifies that the current in-flight medical data management includes a combination of data collection and distribution methods that are minimally integrated with on-board medical devices and systems. Furthermore, there are a variety of data sources and methods of data collection. For an exploration mission, the seamless management of such data will enable a more medically autonomous crew than the current paradigm. The medical system requirements are being developed in parallel with the exploration mission architecture and vehicle design. ExMC has recognized that in order to make informed decisions about a medical data architecture framework, current methods for medical data management must not only be understood, but an architecture must also be identified that provides the crew with actionable insight to medical conditions. This medical data architecture will provide the necessary functionality to address the challenges of executing a self-contained medical system that approaches crew health care delivery without assistance from ground support. Hence, the products supported by current prototype development will directly inform exploration medical system requirements.In fiscal year 2018, the MDA project developed Test Bed 2, the second iteration in a series of prototypes with functionality focused on data security through role-based access control and encryption, integration with One Portal exercise software and ingestion of an ultrasound Digital Imaging and Communications in Medicine (DICOM) file and image display. Test Bed 2 advances the medical data system architecture framework by providing these functionalities in a scalable system that maintained a layered, modular design. The architecture framework uses a data services approach with role-based access to data in a customized medical record system suitable for space exploration. These functionalities were demonstrated as part of the Next Space Technologies for Exploration Partnerships (NextSTEP) ground test demonstrated at the NASA Johnson Space Center Integrated Power, Avionics and Software (iPAS) facility. Interfacing to a Core Flight Software (CFS) system, the MDA system, using Consultative Committee for Space Data Systems (CCSDS) protocol, transferred an exercise file from the simulated flight MDA system to a mirrored MDA system on the ground through the CFS system. The selection of data sources and demonstrations enabled the team to address stakeholder concerns throughout the development process. In the next iteration, the MDA team will work with stakeholders to identify additional relevant functionalities to further advance system data models, standards and principles that will inform the medical system requirements development.

medical data architecture↗

Pterodactyl: Control System Demonstrator Development for Integrated Control Design of a Mechanically Deployed Entry Vehicle

The NASA-funded Pterodactyl project is a design, test, and build capability to (i) advance the current state of the art for Deployable Entry Vehicle (DEV) guidance and control (G&C), and (ii) determine the feasibility of control system integration for various entry vehicle types including those without aeroshells. This capability is currently being used to develop control systems for one such unconventional entry vehicle, the Lifting Nano-ADEPT (LNA) vehicle. ADEPT offers the possibility of integrating control systems directly onto the mechanically deployed structure and building hardware demonstrators will help assess integration and design challenges. Control systems based on aerodynamic control surfaces, mass movement, and reaction control systems (RCS) are currently being investigated for a down-select to the most suitable control architecture for the LNA.To that effect, in this submission, we detail the efforts of the Pterodactyl project to develop a series of hardware demonstrators for the different LNA control systems. Rapid prototypes, for a set of quarter- model or eighth-model vehicle segments, will be developed for all three architectures to validate mechanical design assumptions, and hardware-in-the-loop (HIWL) control approaches. A ground test control system demonstrator will be designed and built after the trade study is complete. The industrial-grade demonstrator will be designed so that it can be incorporated into a HWIL simulation to further validate the findings of the initial trade study. The HWIL simulation will leverage the iPAS environment developed at NASA's Johnson Space Center which facilitates integration testing to support technology maturation and risk reduction, necessary elements for the hardware demonstration development detailed in this paper.

Margolis, Benjamin W.↗

Medical Data Architecture Platform and Recommended Requirements for a Medical Data System for Exploration Missions

The Medical Data Architecture (MDA) project supports the Exploration Medical Capability (ExMC) risk to minimize or reduce the risk of adverse health outcomes and decrements in performance due to in-flight medical capabilities on human exploration missions. To mitigate this risk, the ExMC MDA project addresses the technical limitations identified in ExMC Gap Med 07: We do not have the capability to comprehensively process medically- relevant information to support medical operations during exploration missions. This gap identifies that the current in-flight medical data management includes a combination of data collection and distribution methods that are minimally integrated with on-board medical devices and systems. Furthermore, there are a variety of data sources and methods of data collection. For an exploration mission, the seamless management of such data will enable a more medically autonomous crew than the current paradigm of medical data management on the International Space Station. ExMC has recognized that in order to make informed decisions about a medical data architecture framework, current methods for medical data management must not only be understood, but an architecture must also be identified that provides the crew with actionable insight to medical conditions. This medical data architecture will provide the necessary functionality to address the challenges of executing a self-contained medical system that approaches crew health care delivery without assistance from ground support. Hence, the products derived from the third MDA prototype development will directly inform exploration medical system requirements for Level of Care IV in Gateway missions. In fiscal year 2019, the MDA project developed Test Bed 3, the third iteration in a series of prototypes, that featured integrations with cognition tool data, ultrasound image analytics and core Flight Software (cFS). Maintaining a layered architecture design, the framework implemented a plug-in, modular approach in the integration of these external data sources. An early version of MDA Test Bed 3 software was deployed and operated in a simulated analog environment that was part of the Next Space Technologies for Exploration Partnerships (NextSTEP) Gateway tests of multiple habitat prototypes. In addition, the MDA team participated in the Gateway Test and Verification Demonstration, where the MDA cFS applications was integrated with Gateway-in-a-Box software to send and receive medically relevant data over a simulated vehicle network. This software demonstration was given to ExMC and Gateway Program stakeholders at the NASA Johnson Space Center Integrated Power, Avionics and Software (iPAS) facility. Also, the integrated prototypes served as a vehicle to provide Level 5 requirements for the Crew Health and Performance Habitat Data System for Gateway Missions (Medical Level of Care IV). In the upcoming fiscal year, the MDA project will continue to provide systems engineering and vertical prototypes to refine requirements for medical Level of Care IV and inform requirements for Level of Care V.

Krihak, M.↗

Medical Data Architecture Platform and Recommended Requirements for A Medical Data System for Exploration Missions

Minimize or reduce the risk of adverse health outcomes and decrements in performance due to in-flight medical capabilities on human exploration missions. To mitigate this risk, the ExMC MDA project addresses the technical limitations identified in ExMC Gap Med 07: We do not have the capability to comprehensively process medically relevant information to support medical operations during exploration missions. This gap identifies that the current in-flight medical data management includes a combination of data collection and distribution methods that are minimally integrated with on-board medical devices and systems. Furthermore, there are a variety of data sources and methods of data collection. For an exploration mission, the seamless management of such data will enable a more medically autonomous crew than the current paradigm of medical data management on the International Space Station. ExMC has recognized that in order to make informed decisions about a medical data architecture framework, current methods for medical data management must not only be understood, but an architecture must also be identified that provides the crew with actionable insight to medical conditions. This medical data architecture will provide the necessary functionality to address the challenges of executing a self-contained medical system that approaches crew health care delivery without assistance from ground support. Hence, the products derived from the third MDA prototype development will directly inform exploration medical system requirements for Level of Care IV in Gateway missions.In fiscal year 2019, the MDA project developed Test Bed 3, the third iteration in a series of prototypes, that featured integrations with cognition tool data, ultrasound image analytics and core Flight Software (cFS). Maintaining a layered architecture design, the framework implemented a plug-in, modular approach in the integration of these external data sources. An early version of MDA Test Bed 3 software was deployed and operated in a simulated analog environment that was part of the Next Space Technologies for Exploration Partnerships (NextSTEP) Gateway tests of multiple habitat prototypes. In addition, the MDA team participated in the Gateway Test and Verification Demonstration, where the MDA cFS applications was integrated with Gateway-in-a-Box software to send and receive medically relevant data over a simulated vehicle network. This software demonstration was given to ExMC and Gateway Program stakeholders at the NASA Johnson Space Center Integrated Power, Avionics and Software (iPAS) facility. Also, the integrated prototypes served as a vehicle to provide Level 5 requirements for the Crew Health and Performance Habitat Data System for Gateway Missions (Medical Level of Care IV). In the upcoming fiscal year, the MDA project will continue to provide systems engineering and vertical prototypes to refine requirements for medical Level of Care IV and inform requirements for Level of Care V.

Krihak, M.↗

IROSA 2B/4B EVA Robotics

The MAGIK Robotic analysis team provides kinematic feasibility assessments and robotic visualizations for the ISS. This animation was created with configurations provided by the CX Team and showcases the robotics for the IROSA install 2B and 4B EVAs. The ExtraVehicular Activities (EVAs) shown include the extraction of the two ISS Roll-Out Solar Arrays (IROSAs) from the ISS Power Augmentation (IPA) carrier by an astronaut on the end of the Space Station Remote Manipulator System (SSRMS) and subsequent handoff to a second astronaut on the ISS port side truss. Extravehicular activities not shown will complete the install of the IROSAs.

Alexander Radford Fryer↗

Looking into Ocular Risks of Spaceflight through the Mouse Retina

Ocular alterations have been observed at anatomical levels in astronauts on long duration spaceflight missions, such as what would be required for missions to Mars. These alterations cause an array of signs which together constitute the Spaceflight-Associated Neuro-ocular Syndrome (SANS), one of the top risk priorities of the NASA Human Research Program. Not much is known about SANS at the cellular and molecular level, but studies in mice and rats have recently begun to yield observations on how the spaceflight environment might affect the eye’s biology. Preliminary data from shuttle mouse experiments, and more recently experiments on ISS, have shown changes in retinal physiology via histology and gene expression analysis. This study utilizes samples from the CASIS sponsored Rodent Research 8 Experiment (RRRM-1) tissue sharing opportunity, delivered to the ISS by SpaceX CRS-16 on 12/08/2018. Female BALB/cAnNTac mice were on the ISS for 45 days, while ground controls consisted ofa standard vivarium group and spaceflight habitat group. Here we investigate the molecular response of the mouse retina to identify genes and pathways affected by spaceflight conditions using histology and transcriptomic RNAseq data. This Differentially Expressed Gene (DEG) data was used for pathway analysis with Galaxy (Genelab) and Ingenuity Pathway Analysis (IPA). We identified pathways related to neuronal differentiation, cellular transport/movement, and wound healing. Some of the top DEGs have known relation to ophthalmic diseases. Though there were DEGs throughout the comparisons we tested, there was no clear effect of spaceflight. This could be due to sample processing, which required mice to be returned to Earth about a day before they were sacrificed, possibly allowing for readaptation affecting the retinal transcriptome. However, there was a clear effect of age, between the young (10-12 weeks) and old (32 weeks) groups, and between the baseline and end of experiment, about 46 days.

SANS↗

Exploration Helmet Permanent Anti-fog Study

For the current Extravehicular Mobility Unit (EMU) spacesuit, an astronaut applies an anti-fog solution to the interior of the helmet bubble before each EVA. However, the anti-fog solution has been reported to cause eye discomfort during at least seven EMU EVAs when the anti-fog solution contacted the crew member’s eyes. During STS-100, astronaut Chris Hadfield reported the eye irritation temporarily blinded him during his spacewalk. In addition, the wipe on anti-fog solution is a consumable that needs to be accounted for and a supply launched for missions. To solve this, the Exploration EMU (xEMU) pressure bubble investigated using a permanent anti-fog coating during Design Verification and Test (DVT) human in the loop (HITL) events. Chosen for previous use in Constellation Space Suit develop, HTAF-601, a water based permanent anti-fog solution, was tested. However, major issues have arisen with further HITL testing with the coating. Cleaning the helmet has been a challenge to avoid damaging the permanent anti-fog coating. NASA has completed a set of different methods for cleaning the anti-fog to try to document a preferred method. It was found isopropyl alcohol (IPA) cannot be used to clean the interior of the helmet because it will strip and delaminate the permanent anti-fog coating. Even with using a very gentle cleaning method of flushing with distilled or DI water and dabbing at facial oils, the permanent anti-fog starts to delaminate consistently after 50 hours manned pressurized time (MPT). Finally, the HTAF-601 coating is being discontinued by the vendor. Due to these issues, further investigation is being completed evaluating two solvent based anti-fog solutions: Exxene’s HCF-100 and FSI’s Visgard 106-94. Each coating will be evaluated on polycarbonate samples for application consistency, steam cycles (mimicking breath cycles), cleaning durability, haze, and light transmission. This study will determine if either coating is a viable option to pursue as a permanent anti-fog for spacesuit helmet applications.

spacesuit↗

Defining Pupil Knowledge Requirements for Roman Space Telescope Integrated Payload Assembly Testing

This thesis examines the use of phase retrieval to characterize an optical system under testing conditions with pupil knowledge error. The purpose of this research is to define pupil knowledge requirements for the integrated payload testing of the Roman Space Telescope (RST). I have conducted a Monte Carlo study to determine how uncertainty in the location of the ground support equipment relative to the payload will affect the ability to use image-based wavefront sensing during the test to characterize system alignment. This test will be conducted in the Space Environment Simulator (SES) with the presence of Wavefront Error (WFE) due to gravity sag on the primary mirror. In this study, I incrementally decentered a piece of ground support equipment, the SubAperture Metrology System (SAMS), and evaluated how the phase retrieval algorithm attempted to fit the wavefront with the pupil mismatch. The results of this study are a factor in the overall Integrated Payload Assembly (IPA) testing WFE budget.

Roman Space Telescope↗

IROSA 3A EVA Robotics

The MAGIK Robotic analysis team provides kinematic feasibility assessments and robotic visualizations for the ISS. This animation was created with configurations provided by the CX Team and showcases the robotics for the IROSA 3A EVA install. The ExtraVehicular Activity (EVA) shown include the extraction of one ISS Roll-Out Solar Array (IROSA) from the ISS Power Augmentation (IPA) carrier by an astronaut on the end of the Space Station Remote Manipulator System (SSRMS) and subsequent install on the ISS starboard side truss. Operations during the EVA not shown will complete the install of the IROSA.

ISS↗

Anti-Fog Coatings For Spacesuit Helmets

A permanent and robust anti-fog coating was developed that is applied to the interior of polycarbonate spacesuit helmets. The coating is a mechanically resilient and permanent superhydrophilic (SHPL) layer produced by a two-step process consisting of a plasma processing pre-etch followed by the deposition of an optically transparent Diamond Like Carbon (DLC) coating to achieve an anti-fog, SHPL-DLC layer with Water Contact Angle (WCA) < 10°. The all-dry vacuum process consists of an oxygen plasma etching to engineer the surface of the polycarbonate, creating a well-controlled nanotextured morphology, which is key to the superhydrophilic properties, followed by vacuum deposited Plasma Enhanced Chemical Vapor Deposition (PECVD) DLC coating with high surface energy. The process is carried out at low temperatures compatible with polycarbonate materials and the two steps are performed back-to-back without breaking vacuum between steps. The process is readily scalable and compatible with large scale production volumes. The SHPL-DLC coating was tested for > 200 hours exposure using a breath simulator with no detrimental effect on the coating performance. The coating was also tested for exposure to cleaning fluids, IPA chemical exposure, adhesion testing per ASTM D3359, and abrasion resistance per MIL-E-12397 with no detrimental effects.

Spacesuit↗

Crowdsourcing the Frontier: Advancing Hybrid Physics‐ML Climate Simulation via a $\$$50,000 Kaggle Competition

Subgrid machine-learning (machine learning [ML]) parameterizations have the potential to introduce a new generation of climate models that incorporate the effects of higher-resolution physics without incurring the prohibitive computational cost associated with more explicit physics-based simulations. However, important issues, ranging from online instability to inconsistent online performance, have limited their operational use for long-term climate projections. To more rapidly drive progress in solving these issues, domain scientists and ML researchers opened up the offline aspect of this problem to the broader ML and data science community with the release of ClimSim, a NeurIPS Data sets and Benchmarks publication, and an associated Kaggle competition. This paper reports on the downstream results of the Kaggle competition by coupling emulators inspired by the winning teams' architectures to an interactive climate model (including full cloud microphysics, a regime historically prone to online instability) and systematically evaluating their online performance. Our results demonstrate that online stability in the low-resolution real-geography setting is reproducible across multiple diverse architectures, which we consider a key milestone. All tested architectures exhibit strikingly similar offline and online biases, though their responses to architecture-agnostic design choices (e.g., expanding the list of input variables) can differ significantly. Multiple Kaggle-inspired architectures achieve state-of-the-art results on certain metrics such as zonal mean bias patterns and global Root Mean Squared Error, indicating that crowdsourcing the essence of the offline problem is one path to improving online performance in hybrid physics-AI climate simulation.

Environmental sciences↗