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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Exploration Medical Capability Systems Engineering Overview and Update

Long duration Lunar and Martian missions will change the way NASA currently practices medicine. The missions will require more autonomous capability compared to current low Earth orbit operations. For the medical system, lack of consumable resupply, evacuation opportunities, and real-time ground support are key drivers toward greater autonomy. Recognition of the limited mission and vehicle resources available to carry out exploration missions motivates the Exploration Medical Capability (ExMC) Element’s approach to enabling the necessary autonomy. The ExMC Systems Engineering (SE) team’s mission is to “Define, develop, validate, and manage the technical system design needed to implement exploration medical capabilities for Mars and test the design in a progression of proving grounds.” The Element’s work must integrate with the overall exploration mission and vehicle design efforts to successfully provide exploration medical capabilities. ExMC is using Model-Based System Engineering (MBSE) to accomplish its integrative goals. The MBSE approach to medical system design offers a paradigm shift toward greater integration between the vehicle and the medical system, and directly supports the transition of Earth-reliant ISS operations to the Earth-independent operations envisioned for Mars. This talk will provide a high-level overview of what the ExMC SE team has accomplished since the last IWS and what they are focusing on for the upcoming year.

Kerry McGuire↗
NASA NTRSDate not supplied

Presenting Model-Based Systems Engineering Information to Non-Modelers

NASA’s Human Research Program’s (HRP) Exploration Medical Capability (ExMC) Element adopted Systems Engineering (SE) principles and Model Based Systems Engineering (MBSE) tools to capture the system functions, system architecture, requirements, interfaces, and clinical capabilities for a future exploration medical system. There are many different stakeholders who may use the information in the model: systems engineers, clinicians (physicians, nurses, and pharmacists), scientists, and program managers. Many of these individuals do not have access to MBSE modeling tools or have never used these tools. Many of these individuals (clinicians, scientists, even program managers) may have no experience with SE in general let alone interpreting a systems model. The challenge faced by ExMC was how to present the content in the model to non-modelers in a way they could understand with limited to no training in MBSE or the Systems Modeling Language (SysML) without using the modeling tool. Therefore, from the model, ExMC created an HTML report that is accessible to anyone with a browser. When creating the HTML report, the ExMC SE team talked to stakeholders and received their feedback on what content they wanted and how to display this content. Factoring in feedback, the report arranges the content in a way that not only directs readers through the SE process taken to derive the requirements, but also helps them to understand the fundamental steps in an SE approach. The report includes links to source information (i.e., NASA documentation that describes levels of care) and other SE deliverables (e.g., Concept of Operations). These links were provided to aid in the understanding of how the team created this content through methodical SE approach. This paper outlines the process used to develop the model, the data chosen to share with stakeholders, many of the model elements used in the report, the review process stakeholders followed, the comments received from the stakeholders, and the lessons ExMC learned through producing this HTML report.

Jeffrey R. Cohen↗
NASA NTRS1993

DataHub--Knowledge-Based Science Data Management for Exploratory Data Analysis

It is our belief that new modes of research and new tools will be required to handle the massive amount of diverse data that is to be stored, organized, accessed, distributed, visualized, and analyzed. The fundamental innovation required is the integration of three automation technologies, videlicet knowledge-based expert systems, science visualization and science data management. This integration is based on a concept caled the DataHub, which we describe here.

DataHub↗
NASA NTRS1993

DataHub: Science Data Management in Support of Interactive Exploratory Analysis

The DataHub addresses four areas of significant need: scientific visualization and analysis; science data management; interactions in a distributed, heterogeneous environment; and knowledge-based assistance for these functions. The fundamental innovation embedded within the DataHub is the integration of three technologies, videlicet knowledge-based expert systems, science visualization, and science data management. With the DataHub concept, science investigators are able to apply a more complete solution to all nodes of a distributed system.

science↗
NASA NTRS2020

SN 2018fif: The Explosion of a Large Red Supergiant Discovered in its Infancy by the Zwicky Transient Facility

High-cadence transient surveys are able to capture supernovae closer to their first light than ever before. Applying analytical models to such early emission, we can constrain the progenitor stars' properties. In this paper, we present observations of SN 2018fif (ZTF 18abokyfk). The supernova was discovered close to first light and monitored by the Zwicky Transient Facility (ZTF) and the Neil Gehrels Swift Observatory. Early spectroscopic observations suggest that the progenitor of SN 2018fif was surrounded by relatively small amounts of circumstellar material compared to all previous cases. This particularity, coupled with the high-cadence multiple-band coverage, makes it a good candidate to investigate using shock-cooling models. We employ the SOPRANOS code, an implementation of the model by Sapir & Waxman and its extension to early times by Morag et al. Compared with previous implementations, SOPRANOS has the advantage of including a careful account of the limited temporal validity domain of the shock-cooling model as well as allowing usage of the entirety of the early UV data. We find that the progenitor of SN 2018fif was a large red supergiant with a radius of R = 744.0 (sup +183.0) (sub -128.0) R⨀ and an ejected mass of M(sub ej) = 9.3 (sup +0.4)(sub -5.8) M⨀. Our model also gives information on the explosion epoch, the progenitor's inner structure, the shock velocity, and the extinction. The distribution of radii is double-peaked, with smaller radii corresponding to lower values of the extinction, earlier recombination times, and a better match to the early UV data. If these correlations persist in future objects, denser spectroscopic monitoring constraining the time of recombination, as well as accurate UV observations (e.g., with ULTRASAT), will help break the extinction/radius degeneracy and independently determine both.

Supernovae↗
NASA NTRSDate not supplied

Application of Agile for Systems Engineering, Project Management and Modeling and Lessons Learned

The Systems Engineering team within the Human Research Program (HRP) Exploration Medical Capability (ExMC) Element has been transforming its development processes to be more efficient, robust,and responsive to change and to its stakeholders. To these ends, the Systems Engineering team trialed the integration of agile development techniques into existing and new processes. Agile development methods are well understood within the software development community. Outside ofsoftware development, however, how non-software project management (PM) and systems engineering (SE) teams implement agile development techniques is less well understood. In its transformation efforts, the ExMC SE team focused on three main areas: Improving the project communications among subsystem teams and stakeholders by adopting a scrum-like process, Changing the status and reporting mechanisms to improve schedule coordination between the subsystem team, SE leadership, and ExMC Element leadership, and Unifying the model-based SE workflow to improve understanding of Concepts of Operations across projects.This presentation highlights several of these transformations and what the SE team learned while undergoing the transformation.

S Lumpkins↗
NASA NTRSDate not supplied

Implementation of a SysML Model-Based Concept of Operations for Level of Care IV: Long-Duration Lunar Orbital and Surface Operations

One goal of the Human Research Program (HRP) Exploration Medical Capability (ExMC) Element Systems Engineering (SE) team is to define the technical system needed to support crew medical system capabilities for future exploration missions, including orbital and surface operations for long duration lunar missions. This is accomplished through the development of a Medical System Foundation, which communicates medical system requirements, capabilities, conditions, and resources that define a starting point for a medical system that meets the specification for design reference missions and associated Levels of Care (as defined by NASA-STD-3001). The starting point for creating this Medical System Foundation Model is the development of a Concept of Operations (ConOps) that describes the operation of the system from the point of view of the users. It includes a comprehensive and thoroughly vetted list of the users, their specific needs, the goals of the system, key assumptions about the system, and definitions of the system’s operational environments. The use case scenarios included in the ConOps illustrate required medical system capabilities for Level of Care IV and enable the ExMC SE team to develop integrated medical system requirements and identify capabilities required to meet those requirements. For this “Long Duration” Medical System Foundation development effort, ExMC replaced the traditional document-based ConOps with a model-based ConOps using model-based systems engineering. This approach has several advantages, including the facilitation of more efficient understanding of the material through information-dense images with less opportunity for misinterpretation than text alone, the roll-out of changes to the ConOps to stakeholders in real-time as they are approved, and the consolidation of all salient information into one centralized location. This discussion will focus on both how the model represents the ConOps content and how the SE team utilized lessons learned in an agile environment to improve the way this information was created and presented to stakeholders.

M Kaetzer↗
NASA NTRSDate not supplied

Early Systems Integration Strengthens Orion Medical Capabilities

The Orion spacecraft has significant mass and volume constraints, which limits resources that can be provided for medical use. Sharing of resources between vehicle systems is therefore required to meet design requirements. This presentation will illustrate resource sharing within the Orion vehicle using oxygen as a case study.

C Haas↗
NASA NTRS2022

Turning Limitations into Opportunities in the Development of the Orion Medical System: Incorporation of mHealth Devices

INTRODUCTION: Selection of medical devices for the Orion medical system is a complex task which is dependent on the current state of terrestrial technology. In this work we review the interplay between NASA requirements, constraints, and opportunities for synergy during the development of the Orion medical system. METHODS: The “plan to treat” list of conditions, and subsequently the medical resource list for the Orion Artemis II lunar flyby mission was completed using semi-quantitative methods. During this process, some medical resources were excluded to comply with mass and volume limits, while other resources applicable to multiple medical requirements were prioritized for inclusion. Choices were also examined considering NASA level of care standards for the Artemis design reference missions. As a means to optimize capabilities in spite of mass and volume constraints, ideas for integration of multiple devices into a single platform were explored, including a ‘hackathon’ challenge which was conducted to generate and evaluate concepts for combining medical devices into a single app-based mobile device (ultrasound, ECG, etc.). RESULTS: The Orion team identified 128 medical conditions that we “plan to treat”, with 139 unique medical resources to address these conditions, including 5 digital diagnostic devices (ECG, otoscope, stethoscope, pulse oximeter, and blood pressure monitor). During selection of these digital devices the team noted that miniaturized medical devices often use mobile device platforms (mHealth), some displaying and transmitting data exclusively via mobile device. Of the 5 initially selected devices, all are capable of mobile connection, one which cannot function without a mobile device (ECG). Furthermore, only one of these devices connects natively to a Windows platform, which is currently the only operating system available on Orion. DISCUSSION: Significant savings in mass and volume as well as training and usability improvements can be achieved by leveraging mHealth technologies. However, the platform presents significant challenges for deployment within the Artemis Program including lack of internet connectivity, incompatible operating systems, and radiation concerns. Each of these drawbacks are surmountable with investment in the supporting vehicle architecture, which may become necessary to support the technology trends seen in commercially available medical devices today. Objective: Learn about the opportunities and challenges of leveraging mHealth devices in the development of medical capabilities for austere environments. Learn about the constraints of the NASA spaceflight environment with regards to digital medical device integration.

Douglas Ebert↗
NASA NTRSDate not supplied

Implementation of a SysML Model-Based Concept of Operations for Level of Care IV: Long-Duration Lunar Orbital and Surface Operations

One goal of the Human Research Program (HRP) Exploration Medical Capability (ExMC) Element Systems Engineering (SE) team is to define the technical system needed to support crew medical system capabilities for future exploration missions, including orbital and surface operations for long duration lunar missions. This is accomplished through the development of a Medical System Foundation, which communicates medical system requirements, capabilities, conditions, and resources that define a starting point for a medical system that meets the specification for design reference missions and associated Levels of Care (as defined by NASA-STD-3001). The starting point for creating this Medical System Foundation Model is the development of a Concept of Operations (ConOps) that describes the operation of the system from the point of view of the users. It includes a comprehensive and thoroughly vetted list of the users, their specific needs, the goals of the system, key assumptions about the system, and definitions of the system’s operational environments. The use case scenarios included in the ConOps illustrate required medical system capabilities for Level of Care IV and enable the ExMC SE team to develop integrated medical system requirements and identify capabilities required to meet those requirements. For this “Long Duration” Medical System Foundation development effort, ExMC replaced the traditional document-based ConOps with a model-based ConOps using model-based systems engineering. This approach has several advantages, including the facilitation of more efficient understanding of the material through information-dense images with less opportunity for misinterpretation than text alone, the roll-out of changes to the ConOps to stakeholders in real-time as they are approved, and the consolidation of all salient information into one centralized location. This discussion will focus on both how the model represents the ConOps content and how the SE team utilized lessons learned in an agile environment to improve the way this information was created and presented to stakeholders.

Mary Susan Kaetzer↗