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NASA NTRSDate not supplied

Summary of Technical Interchange Meetings (TIMs) Designed to Enable Earth Independent Medical Operations (EIMO)

The Exploration Medical Capability Element (ExMC) in NASA’s Human Research Program hosted a series of TIMs in 2023-2024 designed to stimulate discussion around specific topics with the goal of enabling EIMO. In context of the thematic constituent elements of EIMO, namely pre-mission planning, acute/emergent/prolonged medical decision making, supply/resource management and task load management, subject matter experts from industry, academia and government (NASA and other Agencies) provided valuable and actionable guidance and recommendations. Earth-based medical experts will remain indispensable for pre-mission planning, however, management of acute/emergent medical contingencies will require a gradual transition of medical care and decision making from terrestrial to space-based assets to enable support of astronaut health and performance and reduce overall mission risk. Key to achieving these enhancements is providing an integrated data system platform capable of utilizing multiple data streams in concert with a variety of on-board databases and passive monitoring of video and wearable sensors to enable a multi-modal, agentic AI-based clinical decision support system (CDSS) to support crew medical officer (CMO) medical decision-making. The EIMO series of TIMs (I-V) have proven to be instructive and portend a significant paradigm shift will be necessary to maintain crew health and performance on exploration class missions. Importantly, since the expected paradigm shift will be significantly different from the methods of operation that have been employed for the majority of missions from the inception of human spaceflight to date, any proposed methods must be deployed in the setting of ongoing operations early and be “tested, reviewed and practiced” while reliable back-up is available to facilitate an Enterprise-wide level of comfort and acceptance. Serious constraints on data transmission coupled with a large and expanding universe of on-board medical informatics data streams will necessitate implementation of a CDSS to supplant the current reliance on support provided by ground-based SMEs. Establishment of trust in the system by CMO/crew and the ground-based medical support team will be essential. Co-development of a CDSS with industry partners will assure that state of the art tools can be employed, and industry efficiencies can be leveraged. Training regimens, materials and tools must evolve to be responsive (just-in-time training) and facilitate autonomous execution of procedures. Proficiency metrics should be established and be based on validated competencies or milestones as opposed to a prescribed number of training hours. Training should be prioritized for broad, translatable skills that have universal application across a variety of medical conditions. Repetition was deemed to be the key to achieving proficiency and emphasis should lie in procedural training which is known to extinguish more rapidly than diagnostic skills. Advanced tools, e.g., extended reality, can provide more realistic and effective training. Use of advanced probabilistic risk assessment tools will be essential to optimize the medical system capability while carefully balancing risk relative to mass/power/volume limitations. Importance of factoring use-life of medical supplies and maintaining awareness of redundancy and opportunity to re-purpose under off nominal situations was emphasized. Consideration of adopting optimized performance standards vs. “good-enough” performance thresholds is warranted. The use of legacy systems as opposed to creating new systems may be preferable. Managing task load and associated cognitive load will be essential to maintain operational safety and behavioral health. ExMC aspires to create a shared EIMO paradigm and strategic vision for advancing medical system design through novel technologies, training, protocols, and support capabilities, built upon the spirit of successful strategies and innovations over the past six decades of space medicine operations.

Jay Lemery↗
NASA NTRS2023

State-of-the-Art: Small Spacecraft Technology

When the first edition of NASA’s Small Spacecraft Technology State-of-the-art report was published in 2013, 247 CubeSats and 105 other non-CubeSat small spacecraft under 50 kilograms (kg) had been launched worldwide, representing less than 2% of launched mass into orbit over multiple years. In 2013 alone, around 60% of the total spacecraft launched had a mass under 600 kg, and of those under 600 kg, 83% were under 200 kg and 37% were nanosatellites (1). Of the total 1,849 spacecraft launched in 2021, 94% were small spacecraft with an overall mass under 600 kg, and of those under 600 kg, 40% were under 200 kg, and 11% were nanosatellites (1). Since 2013, the fight heritage for small spacecraft has increased by over 30% and has become the primary source to space access for commercial, government, private, and academic institutions. The total number of spacecraft launched in the past 10 years is 5,681 and 45% of those had a mass. As with all previous editions of this report, the 2022 edition captures and distills a wealth of new information available on small spacecraft systems from NASA and other publicly available sources. This report is limited to publicly available information and cannot reflect major advances in development that are not publicly disclosed. We encourage any opportunity to publish mission outcomes and technology development milestones (e.g., via conference papers, press releases, company website) so they can be reflected in this report. Overall, this report is a survey of small spacecraft technologies sourced from open literature; it does not endeavor to be an original source, and only considers literature in the public domain to identify and classify devices. Commonly used sources for data include manufacturer datasheets, press releases, conference papers, journal papers, public filings with government agencies, news articles, presentations, the compendium of databases accessed via NASA’s Small Spacecraft Systems Virtual Institute (S3VI) Information Search, and engagement with companies. Data not appropriate for public dissemination, such as proprietary, export controlled, or otherwise restricted data, are not considered. As a result, this report includes many dedicated hours of desk research performed by subject matter experts reviewing resources noted above. Content in this 2022 edition is based on data available by October 2022. This report should not be considered as a comprehensive overview of all the technologies but a great reference for the current state-of-the-art SmallSat technologies. The organizational approach for each chapter is relatively consistent with previous editions and includes an introduction of the technology, current development status of the technology’s procurable systems, and summary tables of technologies surveyed. The content in each chapter is uniquely organized to present a mini-stand-alone report on spacecraft subsystems. As in previous years, chapters include information from previous editions but are updated with new and maturating technologies and reference missions. Tables in each section provide a convenient summary of the technologies discussed, with explanations and references in the body text. The authors have attempted to isolate trends in the small spacecraft industry to point out which technologies have been adopted after successful demonstration missions. Lastly, the authors tried to use the terms “SmallSat,” “microsatellite,” “nanosatellite,” and “CubeSat” in a consistent manner, even as these terms are often used interchangeably in the space industry. Every subsystem chapter contains updated information to reflect the growth in the small spacecraft market. Significant changes are included in several chapters. The “Complete Spacecraft Platforms” chapter now includes information on the two main market options, hosted payload services and dedicated buses. The “Power” chapter provides information on the development of solid-state batteries with significantly higher energy than the current state-of-theart lithium-ion batteries. A large effort was made to update the “Communications” chapter to appropriately capture the recent technology maturation of optical communications for SmallSats. The “Ground Data Systems and Mission Operations” chapter was updated to reflect the recent establishment of the Near Space Network and influx of SmallSat Optical Ground Stations. The “Guidance, Navigation and Control” chapter was updated to include Lidar sensor technology. The “Deorbit Systems” chapter includes a discussion of recently proposed changes by the Federal Communications Commission (FCC) to limit a spacecraft’s lifetime to no longer than 5 years after end-of-mission. The “Identification and Tracking” Chapter includes updated information on the progress of SmallSat tracking. Finally, this report now encompasses technology funded by NASA’s Small Spacecraft Technology (SST) program’s SmallSat Technology Partnerships (STP) initiative which is described further in this Introduction. The reader can find the included SST technology in the “On the Horizon” section of the “Thermal Systems”, “Communications”, and “Guidance, Navigation, and Control” chapters. A central element of this report is to list state-of-the-art technologies by NASA standard Technology Readiness Level (TRL) as defined by the 2020 NASA Engineering Handbook, found in NASA NPR 7123.1C NASA Systems Engineering Processes and Requirements. The authors have endeavored to independently verify the TRL value of each technology by reviewing and citing published test results or publicly available data to the best of their ability. Where test results and data disagree with vendors’ own advertised TRL, the authors have attempted to engage the vendors to discuss the discrepancy. Readers are strongly encouraged to follow the references cited in the literature describing the full performance range and capabilities of each technology. Readers of this report should reach out to individual companies to further clarify information. It is important to note that this report takes a broad system-level view. To attain a high TRL, the subsystem must be in a flight-ready configuration with all supporting infrastructure—such as mounting points, power conversion, and control algorithms—in an integrated unit. An accurate TRL assessment requires a high degree of technical knowledge on a subject device, and an in-depth understanding of the mission (including interfaces and environment) on which the device was flown. There is variability in TRL values depending on design factors for a specific technology. For example, differences in TRL assessment based on the operating environment may result from the thermal environment, mechanical loads, mission duration, or radiation exposure. If a technology has flown on a mission without success, or without providing valid confirmation to the operator, such claimed “flight heritage” was discounted. The authors believe TRLs are most accurately determined when assessed within the context of a program’s unique requirements. While the overall capability of small spacecraft has matured since the 2021 edition of this report, technologies are still being developed to make deep space SmallSat missions more routine and more cost effective. Future editions of this report may include content dedicated to the rapidly growing fields of assembly, integration, and testing services, and mission modeling and simulation–all of which are now extensively represented at small spacecraft conferences. Many of these subsystems and services are still in their infancy, but as they evolve and reliable conventions and standards emerge, the next iteration of this report may also evolve to include additional chapters.

Bruce Yost↗
NASA NTRS2019

The Subseasonal Experiment (SubX): A Multi-Model Subseasonal Prediction Experiment

SubX is a multi-model subseasonal prediction experiment designed around operational requirements with the goal of improving subseasonal forecasts. Seven global models have produced seventeen years of retrospective (re-) forecasts and more than a year of weekly real-time forecasts. The re-forecasts and forecasts are archived at the Data Library of the International Research Institute for Climate and Society, Columbia University, providing a comprehensive database for research on subseasonal to seasonal predictability and predictions. The SubX models show skill for temperature and precipitation three weeks ahead of time in specific regions. The SubX multi-model ensemble mean is more skillful than any individual model overall. Skill in simulating the Madden-Julian Oscillation (MJO) and the North Atlantic Oscillation (NAO), two sources of subseasonal predictability, is also evaluated with skillful predictions of the MJO four weeks in advance and of the NAO 2 weeks in advance. SubX is also able to make useful contributions to operational forecast guidance at the Climate Prediction Center. Additionally, SubX provides information on the potential for extreme precipitation associated with tropical cyclones which can help emergency management and aid organizations to plan for disasters. (Capsule Summary) A research to operations project in service of developing better operational subseasonal forecasts.

Precipitation↗
NASA NTRSDate not supplied

Genesis Solar Wind Sample Curation Documentation

Introduction: A scientist with experience as a sample science analyst, provider of flight hardware for multiple missions, and senior engineer in an ISO 2000-rated manufacturing plant has described the timeline of key participants in any PI-led sample return mission, the breadth of the organizations involved [1,2], and, of interest to this meeting, choosing the types of data to preserve and issues of future data accessibility. This work broadens that perspective by giving similar lessons from Genesis sample curation point-of-view. Curation participation regarding data gathering was part of the mission review process from the beginning. Genesis’ story illustrates outcome of several choices about types of data to record and preserve. Precision analysis of solar wind atoms captured in pure, ultraclean substrates is the driving science goal; therefore, detailed documentation was captured from all mission and curation phases and from investigator laboratories because these processes affect the final analytical results [3]. Pre-flight: Design and fabrication of the spacecraft. Like many modern small sample return missions, Genesis was a tightly managed team integrated across science, engineering and curation. Communication across the team was excellent, and, for the most part, the hands-on engineering technicians understood the impacts of “small choices” they routinely make, and the eyes-on oversight of manufacturing processes by scientists was mindful of details. The payload was designed by the Jet Propulsion Laboratory and the spacecraft by Lockheed Martin. Solar wind collectors and instruments were fabricated by multiple vendors and laboratories. The main portion of the payload was assembled at JSC. Fabrication procedures and contamination-control data (with witness coupons) were stored primarily at JSC. The original composition, dimensions and configuration of components, results of thermal testing, etc. are still needed for interpretation of analytical data. At times, these must be estimated from secondary information acquired pre-flight. Moreover, some files (e.g., original 3-D models and early Powerpoint) cannot be opened using software. Archived curation data includes 2-D drawings, material usage lists, QA documentation and analyses of consumables used during fabrication. Important chemical information still resides in archived hardware, paints and lubricants, material coupons, cleaning coupons, environmental witness plates and reference materials from manufacturing facilities. Purity and cleanliness of collector substrates. Semi-conductor vendors provided surface cleanliness data and some purity data. Purity for specific elements of interest was verified by science team members in their laboratories [4]. Curation archived procurement and shipping records, analysis reports, and non-proprietary fabrication data. A physical archive of flight collector reference materials is maintained for future use so additional data can be collected as analytical techniques improve. These are of increased value due to the hard landing upon re-entry. Cleaning and cleanliness assessments of flight hardware. Cleaning of the science canister payload was performed at JSC in a dedicated ISO 4 cleanroom using ultrapure water (UPW). The cleanliness of this UPW was monitored throughout processing. The archive for the clean lab also includes airborne particle counts, airborne molecular and inorganic contamination measurements as well as cleanroom construction material coupons and witness coupons. Hardware cleanliness was assessed by particle counts in rinse water batches. This information is recorded in batch cleaning forms and logbooks, and are, perhaps, of decreased value due to the hard landing. Post-flight: Curation-generated data. The curation handling history of each Genesis sample is documented in a typical astromaterials sample database which captures sample location, physical description and characterization data. Samples have a “shelf life”. Crucial to the preservation of samples is ongoing documentation of the sample environment, initially under curatorial control but is now a separate facility function with requires coordination. PI-generated data. Data on sample characterization and cleaning techniques continues to be generated by sample users [5]. These are often captured in LPSC abstracts, but these “engineering” results often are not publishable as stand-alone papers. We are actively looking for ways to make this information more accessible to users. Ion implants into samples have aided science return and can be shared among investigators. These (and similar) materials should be added to the curatorial collection with appropriate process and characterization data generated externally. Summary: Complete data archives for returned astromaterial samples must be broad in types and formats, and inclusive of environmental monitoring.

Genesis↗
NASA NTRS2009

The Lunar Sample Compendium

The Lunar Sample Compendium is a succinct summary of the data obtained from 40 years of study of Apollo and Luna samples of the Moon. Basic petrographic, chemical and age information is compiled, sample-by-sample, in the form of an advanced catalog in order to provide a basic description of each sample. The LSC can be found online using Google. The initial allocation of lunar samples was done sparingly, because it was realized that scientific techniques would improve over the years and new questions would be formulated. The LSC is important because it enables scientists to select samples within the context of the work that has already been done and facilitates better review of proposed allocations. It also provides back up material for public displays, captures information found only in abstracts, grey literature and curatorial databases and serves as a ready access to the now-vast scientific literature.

Meyer, Charles↗
NASA NTRS1990

Summary of JAYGO mixing and FSM-1 application of castable inhibitor and liner

Two JAYGO planetary mixers (12 and 42 gallon) are being qualified to mix STW5-3224 liner and STW5-3223 castable inhibitor. These mixers are an integral part of a mix process which allows for safe addition of the asbestos component. An essential part of the engineering evaluation (ETP-0347) of these mixers is the generation of static test fire data. Ultimately, these results will help confirm the adequacy of these mixers for production mixing of liner and inhibitor. (These data are not required for qualification of the Certification Test Plan CTP-0125). The details on the mixing, inhibiting, and sling-lining of JAYGO-mixed castable inhibitor and liner which were applied to the FSM-1 segments are presented. The objectives are the following: (1) to document processing events surrounding the JAYO mixing of castable inhibitor and liner, and the subsequent inhibiting and sling lining onto the FSM-1 segments; and (2) to substantiate the measured properties of these JAYGO-mixed materials (rheological and mechanical) and compare these properties to existing production database.

Evans, Kurt B.↗
NASA NTRS2015

Common Cause Failure Modeling

Common Cause Failures (CCFs) are a known and documented phenomenon that defeats system redundancy. CCFS are a set of dependent type of failures that can be caused by: system environments; manufacturing; transportation; storage; maintenance; and assembly, as examples. Since there are many factors that contribute to CCFs, the effects can be reduced, but they are difficult to eliminate entirely. Furthermore, failure databases sometimes fail to differentiate between independent and CCF (dependent) failure and data is limited, especially for launch vehicles. The Probabilistic Risk Assessment (PRA) of NASA's Safety and Mission Assurance Directorate at Marshall Space Flight Center (MFSC) is using generic data from the Nuclear Regulatory Commission's database of common cause failures at nuclear power plants to estimate CCF due to the lack of a more appropriate data source. There remains uncertainty in the actual magnitude of the common cause risk estimates for different systems at this stage of the design. Given the limited data about launch vehicle CCF and that launch vehicles are a highly redundant system by design, it is important to make design decisions to account for a range of values for independent and CCFs. When investigating the design of the one-out-of-two component redundant system for launch vehicles, a response surface was constructed to represent the impact of the independent failure rate versus a common cause beta factor effect on a system's failure probability. This presentation will define a CCF and review estimation calculations. It gives a summary of reduction methodologies and a review of examples of historical CCFs. Finally, it presents the response surface and discusses the results of the different CCFs on the reliability of a one-out-of-two system.

Hark, Frank↗
NASA NTRS2016

Common Cause Failure Modeling

Common Cause Failures (CCFs) are a known and documented phenomenon that defeats system redundancy. CCFS are a set of dependent type of failures that can be caused by: system environments; manufacturing; transportation; storage; maintenance; and assembly, as examples. Since there are many factors that contribute to CCFs, the effects can be reduced, but they are difficult to eliminate entirely. Furthermore, failure databases sometimes fail to differentiate between independent and CCF (dependent) failure and data is limited, especially for launch vehicles. The Probabilistic Risk Assessment (PRA) of NASA's Safety and Mission Assurance Directorate at Marshal Space Flight Center (MFSC) is using generic data from the Nuclear Regulatory Commission's database of common cause failures at nuclear power plants to estimate CCF due to the lack of a more appropriate data source. There remains uncertainty in the actual magnitude of the common cause risk estimates for different systems at this stage of the design. Given the limited data about launch vehicle CCF and that launch vehicles are a highly redundant system by design, it is important to make design decisions to account for a range of values for independent and CCFs. When investigating the design of the one-out-of-two component redundant system for launch vehicles, a response surface was constructed to represent the impact of the independent failure rate versus a common cause beta factor effect on a system's failure probability. This presentation will define a CCF and review estimation calculations. It gives a summary of reduction methodologies and a review of examples of historical CCFs. Finally, it presents the response surface and discusses the results of the different CCFs on the reliability of a one-out-of-two system.

Hark, Frank↗
NASA NTRS2019

In Situ Observation of Growth Dynamics in DECLIC Directional Solidification Insert Onboard ISS: DSI-R Flight Campaign

The study of solidification microstructure formation is of utmost importance for materials design and processing, as solid-liquid interface patterns largely govern mechanical and physical properties. Pattern selection occurs under dynamic conditions of growth in which the initial morphological instability evolves nonlinearly and undergoes a reorganization process. The dynamic and nonlinear nature of this instability renders in situ observation of the interface an invaluable tool to gain knowledge on the time-evolution of the interface pattern. Transparent organic analogs, which solidify like metallic alloys, allow direct visualization of interface dynamics. Extensive ground-based studies of both metallic and organic bulk samples have established the presence of significant convection during solidification processes that alters the formation of interfacial microstructures. A reduced-gravity environment is therefore mandatory for fluid flow elimination in bulk samples. In the framework of the CNES project MISOL3D (MIcrostrutures de SOLidification 3D) and the NASA projects DSIP (Dynamical Selection of 3D Interface Patterns), SPADES (SPAtiotemporal Evolution of three-dimensional DEndritic array Structures) and CAMUS (ComputAtional Studies of MicrostrUcture Formation During Alloy Solidification in Microgravity), we participated in the development of the Directional Solidification Insert (DSI) of the DEvice for the study of Critical Liquids and Crystallization (DECLIC). The DECLIC-DSI is dedicated to in situ and real-time characterization of solid-liquid interface patterns during directional solidification of transparent alloys in diffusive transport regime. Between April 2010 and March 2011, the first ISS campaign (DSI) explored the entire range of microstructures resulting in unprecedented observations. A second campaign (DSI-R), performed between October 2017 and December 2018, in which the insert contained an alloy of higher solute concentration, allowed to complete the benchmark database. The increase of solute concentration resulted in well-developed dendritic patterns at lower velocities (lower interface curvature and larger tip radius). The microstructure resulting from dendritic growth is dominant in metallurgy so that it is fundamental to understand the mechanisms of its formation. The main aims of this experimental campaign are to understand: the mechanisms of the cell to dendrite transition, the fundamental mechanisms of sidebranching formation, the dependence of dendrite tip shapes on growth conditions, the interaction of primary array and secondary sidebranches, and the influence of subgrain boundaries on the spatiotemporal organization of the array structure. Preparation, analysis and interpretation of the experiments performed onboard ISS are considerably enhanced by experiments performed on ground using thin-samples (Pr. Trivedi’s group) and phase-field simulations of microstructure formation in a diffuse growth regime (Pr. Karma’s group). In this summary, we will present an initial assessment of the results obtained during the DSI-R campaign. Nomenclature Vp: pulling velocity G: thermal gradient L: solidified length rtip: tip curvature radius Acronyms/Abbreviations CADMOS: Centre d'Aide au Développement des activités en Micro-pesanteur et des Opérations Spatiales CNES: Centre National d’Études Spatiales DECLIC: Device for the study of Critical LIquids and Crystallization DSI: Directional Solidification Insert DSI-R: Directional Solidification Insert - Refurbish ISS: International Space Station NASA: National Aeronautics and Space Administration PF: phase-field SCN: Succinonitrile 3D: three-dimensional

Mota, F.L.↗
NASA NTRS1997

Issues in Defining Software Architectures in a GIS Environment

The primary mission of the Pan-American Center for Earth and Environmental Studies (PACES) is to advance the research areas that are relevant to NASA's Mission to Planet Earth program. One of the activities at PACES is the establishment of a repository for geographical, geological and environmental information that covers various regions of Mexico and the southwest region of the U.S. and that is acquired from NASA and other sources through remote sensing, ground studies or paper-based maps. The center will be providing access of this information to other government entities in the U.S. and Mexico, and research groups from universities, national laboratories and industry. Geographical Information Systems(GIS) provide the means to manage, manipulate, analyze and display geographically referenced information that will be managed by PACES. Excellent off-the-shelf software exists for a complete GIS as well as software for storing and managing spatial databases, processing images, networking and viewing maps with layered information. This allows the user flexibility in combining systems to create a GIS or to mix these software packages with custom-built application programs. Software architectural languages provide the ability to specify the computational components and interactions among these components, an important topic in the domain of GIS because of the need to integrate numerous software packages. This paper discusses the characteristics that architectural languages address with respect to the issues relating to the data that must be communicated between software systems and components when systems interact. The paper presents a background on GIS in section 2. Section 3 gives an overview of software architecture and architectural languages. Section 4 suggests issues that may be of concern when defining the software architecture of a GIS. The last section discusses the future research effort and finishes with a summary.

Acosta, Jesus↗
NASA NTRS2008

The NASA MSFC Earth Global Reference Atmospheric Model-2007 Version

Reference or standard atmospheric models have long been used for design and mission planning of various aerospace systems. The NASA/Marshall Space Flight Center (MSFC) Global Reference Atmospheric Model (GRAM) was developed in response to the need for a design reference atmosphere that provides complete global geographical variability, and complete altitude coverage (surface to orbital altitudes) as well as complete seasonal and monthly variability of the thermodynamic variables and wind components. A unique feature of GRAM is that, addition to providing the geographical, height, and monthly variation of the mean atmospheric state, it includes the ability to simulate spatial and temporal perturbations in these atmospheric parameters (e.g. fluctuations due to turbulence and other atmospheric perturbation phenomena). A summary comparing GRAM features to characteristics and features of other reference or standard atmospheric models, can be found Guide to Reference and Standard Atmosphere Models. The original GRAM has undergone a series of improvements over the years with recent additions and changes. The software program is called Earth-GRAM2007 to distinguish it from similar programs for other bodies (e.g. Mars, Venus, Neptune, and Titan). However, in order to make this Technical Memorandum (TM) more readable, the software will be referred to simply as GRAM07 or GRAM unless additional clarity is needed. Section 1 provides an overview of the basic features of GRAM07 including the newly added features. Section 2 provides a more detailed description of GRAM07 and how the model output generated. Section 3 presents sample results. Appendices A and B describe the Global Upper Air Climatic Atlas (GUACA) data and the Global Gridded Air Statistics (GGUAS) database. Appendix C provides instructions for compiling and running GRAM07. Appendix D gives a description of the required NAMELIST format input. Appendix E gives sample output. Appendix F provides a list of available parameters to enable the user to generate special output. Appendix G gives an example and guidance on incorporating GRAM07 as a subroutine in other programs such as trajectory codes or orbital propagation routines.

Leslie, F.W.↗
NASA NTRS2004

Intern Summary Reports

Topics covered include: Probe Station Antenna Range; LERCIP 2004 Summary; L.E.R.C.I.P. Internship Summary; Hubble Space Telescope Bi-Stem Thermal Shield Analyses; GRABER - the Duct Tape of Space and JIMO Heat Conducting Foam; CDF and PDF Comparison Between Humacao, Puerto Rico and Florida; Development of the On-board Aircraft Network; Development of the Planar Inlet Design and Analysis Process (PINDAP); An Overview of My 2004 Summer Internship [Non-destructive Evaluation]; My Summer Experience as an Administrative Officer Assistant [in the Safety and Assurance Directorate Office]; Programming an Experiment Control System; Reducing the Cation Exchange Capacity of Lithium Clay to Form Better Dispersed; Polymer-Clay Nanocomposites; Feasibility of EB Welded Hastelloy X and Combination of Refractory Metals; My Work in the NASA Glenn History Office and Records Management Office; Education, Technology, and Media: A Peak into My Summer Internship at NASA Glenn Research Center in Cleveland, Ohio; [The Engineering and Technical Services Directorate at the Glenn Research Center]; Drinking Water Database; Design of an EXB Probe; and Texturing Carbon-carbon Composite Radiator Surfaces Utilizing Atomic Oxygen.

Source record↗
NASA NTRS1998

Real Gas/Blunt Cone

In this chapter recent activity in real-gas database definition and code validation will be summarized. In the Phase I report of the Working Group (WG) 181, aerothermodynamic problems were classified, for purpose of discussion, into seven types: aerodynamic parameters, viscous/shock interaction, boundary-layer transition, forebody-heating/heat-transfer, radiation and ablation, lee and base-region flow, and low-density flow. Several of these problem types were the subject of various chapters of the Phase 1 report describing real-gas effects and ground test facility issues. In this chapter some background and objectives outlined in the real-Gas effects Chapter V of the Phase 1 report will be reviewed. The results of the blunt cone test campaign developed under the auspices of the WG18 activity to study real-gas phenomena will be summarized, including the experimental and computational programs, issues and questions, and recommendations. Further, recent progress in other real-gas areas beyond the blunt cone test campaign will be discussed. Finally, a summary in which the present status of our understanding of real-gas issues will be presented.

George S. Delwert↗
NASA NTRS2019

NASA GeneLab Platform Utilized for Space Radiation Dosimetry Biological Response Compared to Radiation Ground Studies

Ionizing radiation from Galactic Cosmic Rays (GCR) is one of the major risk factors factor that will impact health of astronauts on extended missions outside the protective effects of the Earth's magnetic field. Currently there are gaps in our knowledge of the health risks associated with chronic low dose, low dose rate ionizing radiation, specifically ions associated with high (H) atomic number (Z) and energy (E). The NASA GeneLab project (genelab.nasa.gov) aims to provide a detailed library of Omics datasets associated with biological samples exposed to HZE. The GeneLab Data System (GLDS) includes datasets from both spaceflight and ground-based studies, a majority of which involved exposure to ionizing radiation. Recently GeneLab has also assessed radiation dosimetry data with omics datasets associated with samples flown to the International Space Station (ISS). The combination of the detailed information on radiation exposure for ground-based studies and curated dosimetry information for spaceflight experiments allows GeneLab to be the first comprehensive Omics database for space related research from which an investigator can generate hypotheses to direct future experiments utilizing both ground and space biological radiation data. We demonstrate the usefulness of these datasets by analyzing multiple GeneLab datasets associated with both radiation ground-based studies and spaceflight studies. The radiation ground based studies we analyzed includes both in vivo and in vitro work with a range ions from protons to iron particles with doses from 0.1Gy to 2Gy. These datasets were compared to both in vivo and in vitro datasets from samples flown to the ISS and on shorter shuttle missions with total doses of 0.1 mGy to 30 mGys. From this analysis we were able to associate distinct biological signatures associating specific ions to specific biological response to radiation exposure in space. For example, we discovered radiation biological response related to cardiovascular effects from proton ground studies are the dominating response for samples related to cardiovascular effects on the ISS. With this work we will provide a summary of how different ions will impact different biological response in space and how this can be used in future studies to assess optimal ground experiments to simulate space radiation.

Beheshti, Afshin↗
NASA NTRS1993

Opening remarks: Current and future activities

It is our custom to present the Propagation Program's recent accomplishments and future plans at the onset of a NAPEX meeting. A summary is presented. The data analysis phase of the U.S. Olympus Campaign is nearing its end. The final report will be published by Virginia Tech by midsummer 1993. The report will comprise measurement analysis for 12 months. It will include monthly and annual attenuation statistics and statistics on scintillation effects. A number of prediction models will be presented. The ACTS propagation experiment preparations are moving forward as expected. The mobile/personal channel characterization efforts continued during the last year. Data collected by the University of Texas in 1992 are being analyzed and will become available by September 1993. We have recently started a study to characterize LEO mobile/personal channels. Topics such as indoor reception, tree shadowing, blockage, and delay spread will be investigated. These results will become available in one to two years from now. We have also collected Ka-band mobile data using Olympus 20 GHz beacon transmissions. The University of Texas has already collected five years of low-elevation angle, 11GHz propagation data. The work on database for propagation models has progressed very well. The first release is ready, and the participants of this meeting will receive a copy of the software. We had an active year where CCIR is concerned. An input document on land mobile satellite system (LMSS) propagation models was submitted to the U.S. national committee and was approved and sent to Geneva.

Davarian, Faramaz↗
NASA NTRS1999

A New Compendium of Unsteady Aerodynamic Test Cases for CFD: Summary of AVT WG-003 Activities

With the continuous progress in hardware and numerical schemes, Computational Unsteady Aerodynamics (CUA), that is, the application of Computational Fluid Dynamics (CFD) to unsteady flowfields, is slowly finding its way as a useful and reliable tool (turbulence and transition modeling permitting) in the aircraft, helicopter, engine and missile design and development process. Before a specific code may be used with confidence it is essential to validate its capability to describe the physics of the flow correctly, or at least to the level of approximation required, for which purpose a comparison with accurate experimental data is needed. Unsteady wind tunnel testing is difficult and expensive; two factors which dramatically limit the number of organizations with the capability and/or resources to perform it. Thus, unsteady experimental data is scarce, often classified and scattered in diverse documents. Additionally, access to the reports does not necessarily assure access to the data itself. The collaborative effort described in this paper was conceived with the aim of collecting into a single easily accessible document as much quality data as possible. The idea is not new. In the early 80's NATO's AGARD (Advisory Group for Aerospace Research & Development) Structures and Material Panel (SMP) produced AGARD Report No. 702 "Compendium of Unsteady Aerodynamic Measurements", which has found and continues to find extensive use within the CUA Community. In 1995 AGARD's Fluid Dynamics Panel (FDP) decided to update and expand the former database with new geometries and physical phenomena, and launched Working Group WG-22 on "Validation Data for Computational Unsteady Aerodynamic Codes". Shortly afterwards AGARD was reorganized as the RTO (Research and Technology Organization) and the WG was renamed as AVT (Applied Vehicle Technolology) WG-003. Contributions were received from AEDC, BAe, DLR, DERA, Glasgow University, IAR, NAL, NASA, NLR, and ONERA. The final publication with the results of the exercise is expected in the second part of 1999. The aim of the present paper is to announce and present the new database to the Aeroelasticity community. It is also intended to identify, together with one of the groups of end users it targets, deficiencies in the compendium that should be addressed by means of new wind tunnel tests or by obtaining access to additionally existing data.

Ruiz-Calavera, Luis P.↗
NASA NTRS2011

Methodology and Results of the Near-Earth Object (NEO) Human Space Flight (HSF) Accessible Targets Study (NHATS)

Near-Earth Asteroids (NEAs) have been identified by the current administration as potential destinations for human explorers during the mid-2020s. While the close proximity of these objects' orbits to Earth's orbit creates a risk of highly damaging or catastrophic impacts, it also makes some of these objects particularly accessible to spacecraft departing Earth, and this presents unique opportunities for solar system science and humanity's first ventures beyond cislunar space. Planning such ambitious missions first requires the selection of potentially accessible targets from the growing population of nearly 7,800 NEAs. To accomplish this, NASA is conducting the Near-Earth Object (NEO) Human Space Flight (HSF) Accessible Targets Study (NHATS). Phase I of the NHATS was executed during September of 2010, and Phase II was completed by early March of 2011. The study is ongoing because previously undetected NEAs are being discovered constantly, which has motivated an effort to automate the analysis algorithms in order to provide continuous monitoring of NEA accessibility. The NHATS analysis process consists of a trajectory filter and a minimum maximum estimated size criterion. The trajectory filter employs the method of embedded trajectory grids to compute all possible ballistic round-trip mission trajectories to every NEA in the Jet Propulsion Laboratory (JPL) Small-Body Database (SBDB) and stores all solutions that satisfy the trajectory filter criteria. An NEA must offer at least one qualifying trajectory solution to pass the trajectory filter. The Phase II NHATS filter criteria were purposely chosen to be highly inclusive, requiring Earth departure date between January 1st, 2015 and December 31st, 2040, total round-trip flight time <= 450 days, stay time at the NEA >= 8 days, Earth departure C(sub 3) energy <= 60 km(exp 2)/s(exp 2), total mission delta-v <= 12 km/s (including an Earth departure maneuver from a 400 km altitude circular parking orbit), and a maximum atmospheric re-entry speed of 12 km/s. After determining which NEAs offer at least one trajectory solution meeting the criteria, the estimated size constraint is then imposed whereby those NEAs may only be considered NHATS- qualifying NEAs if their maximum estimated size is >= 30 m. This corresponds to an absolute magnitude H <= 26.5 with an assumed albedo p = 0:05. The following is a brief high-level summary of the Phase II study results. Of the 7,665 NEAs in the SBDB as of February 3rd, 2011, 765 NEAs passed the trajectory filter and yielded a total of 79,157,604 trajectory solutions. The trajectory solutions for each NEA are post-processed into Pork Chop Contour (PCC) plots which show total mission delta-v as a function of Earth departure date and total mission duration. Although the PCC plots necessarily compress a very multi-dimensional design space into a two-dimensional plot, they permit rapid assessment of the breadth and quality of an NEA's available Earth departure season and clearly indicate the regions of the trajectory design space which warrant further analysis and optimization. The PCC plot for the NEA with the greatest number of NHATS-qualifying trajectory solutions, 2000 SG-344, is shown. Of the 765 NEAs which passed the Phase II trajectory filter, a total of 590 NEAs also satisfied the further constraint of maximum estimated size >= 30 m. The distributions of osculating heliocentric orbital semi-major axis (a), eccentricity (e), and inclination (i), for those 590 NEAs are shown. Note that the semi-latus rectum used is equal to alpha (1-e(exp 2)). To further our understanding of round-trip trajectory accessibility dynamics, it is instructive to examine the distribution of the NHATS-Qualifying NEAs according to orbit classification. NEAs are grouped into four orbit families: Atiras (aphelion < 0.983 AU), Atens (aphelion > 0.983 AU, alpha < 1.0 AU), Apollos (perihelion < 1.017 AU, alpha > 1.0 AU), and Amors (1.017 < perihelion < 1.3 AU). Of the 765 NEAhich satisfied the NHATS trajectory criteria, none are Atiras, 193 are Atens (31% of known Atens), 456 are Apollos (11% of known Apollos), and 116 are Amors (4% of known Amors). While Apollos comprise 60% of the NEAs which pass the NHATS trajectory filter and Atens comprise only 25%, the percentages according to orbit family are perhaps more relevant. Note that only 11% of known Apollos passed the trajectory filter while 31% of known Atens passed. These simple statistics alone strongly suggest that Aten orbits possess features which tend to enhance their round-trip trajectory accessibility as compared to Apollos or Amors. This is significant because Atens' orbits cause them to spend considerable time in Earth's daytime sky, making them difficult to discover and track using ground-based observing assets. In this paper we will detail the NHATS analysis algorithms, present and analyze all NHATS results to date, and discuss aspects of HSF mission architecture design for future NEA missions.

Barbee, Brent↗
NASA NTRS2019

Predictive Modeling for Differential Diagnosis and Mortality Risk Assessment

The prevalence of electronic health record (EHR) systems has brought prodigious biomedical informatics opportunity. Automated machine learning methods can effectively utilize such data and have become common tools for healthcare predictive modeling. Researches in medical informatics have explored the potential of deep learning and classical models in emergent care scenarios. In particular, predicting differential diagnoses for admissions have proven useful in decreasing unnecessary lab tests and improving inpatient triage decision-making. Moreover, identification of high-risk patients for in-hospital mortality is vitally important to maximize allocation of medical resources.The Medical Information Mart for Intensive Care (MIMIC-III) database, containing de-identified critical care inpatient was used in our study. This data set captures hospital patient laboratory measurements, pharmacologic prescriptions, diagnostic data and procedure event recordings. When considering adult patients and discounting admissions with ICU length of stay less than 24 hours, there were 37,787 unique admissions and 30,414 total patients. We examined the top 25 most prevalent ICD-9 group-level disease specificities in MIMIC-III using a multi-label classification model. In-hospital mortality was modeled as binary classification with 4,155 (13%) adult patients that expired, of which 3,138 (75.5%) were in the ICU setting. The metrics AUC, F1 score, sensitivity and specificity values calculated for each disease label measured prediction performance.The usage of ICD-9 group codes reduced feature dimension from 14,567 to 942 and greatly improved distribution of patient diagnostic categories. Disease temporal patterns were captured by considering the most frequently sampled 6 vital signs and 13 laboratory values. Missing data were imputed at each time-stamp. Time-series raw hourly average values were converted into 5 summary features (mean, standard deviation, number of observations, min & max values). Patient demographic variables such as age, gender, marital status and ethnicity were also factored into the modeling. Choi et al showed that contextual embedding of medical data, diagnostic and procedural codes alone can predict future diagnoses with sensitivity as high as 0.79. We utilized an embedding technique called word2vec which allowed sparse representations of medical history to be transformed into dense word vectors. The mappings captured contextual information by treating each admission as a sentence and learning the most likely neighboring words in a sliding window fashion. Binary and multi-label classification was achieved via collapse models, which do not consider temporal information, as well as recurrent neural networks with regularization, Softmax output layer activation together with categorical cross-entropy as the loss function.

US Army collaboration↗