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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 1,693 records · Page 94

Comparison of The Dimensional Stability of Kel-F 81 and Neoflon CTFE M400H Polychlorotrifluoroethylenes Used in Valve Seat Application

The dimensional stability of polychlorotrifluoroethylene (PCTFE) valve seats used in oxygen regulator applications was determined by thermomechanical analysis (TMA). Two traceable grades of PCTFE were tested; Kel-F 81 and Neoflon CTFE M400H. For these particular resins, the effect of percent crystallinity, zero strength time (ZST) molecular weight, resin grade, process history (compression-molded versus extruded) on the dimensional stability and annealing behavior was determined. In addition to the traceable Kel-F 81 and Neoflon CTFE M400H grades, actual PCI'PH valve seats of differing geometry and design were tested by TMA. The PCTFE valve seats were of unspecified resin grade, although certain inferences about the grade could be drawn based on knowledge of the valve seat fabrication date. Results consistently revealed dimensional instability of varying magnitude at temperatures ranging from 40 to 70 degrees Celsius. Furthermore, some of the pre- 1 995 seats appeared to be more dimensionally stable than those fabricated after 1995. The TMA results are discussed in the context of several proposed ignition mechanisms; namely, particle impact, presence of contaminant oils and fibers, and localized heating by flow friction and/or resonance. The effect of metal constraint on the dimensional stability of PCTFE is also discussed. Finally, the effect of percent crystallinity, ZST molecular weight, resin grade, process history (compression-molded versus extruded) on the AIT, delta Hc and impact sensitivity of various types of Neoflon CTFE M400H was determined using Kel-F 81 as a control. Results show that the AIT, delta Hc and impact sensitivity were essentially independent of Neoflon CTFE process history and structure.

Waller, Jess M.↗

Modeling Heat-Transfer in Animal Habitats in the Shuttle Orbiter Middeck

A mathematical model has been developed to evaluate the heat transfer characteristics of an Animal Enclosure Module (AEM) in the microgravity environment. The AEM is a spaceflight habitat that provides life support for up to six rodents in the Space Shuttle Middeck. Currently, temperatures within the AEM are recorded in real time using a solid state data recorder; however, the data are only available for analysis post-flight. This temperature information is useful for characterizing the thermal environment of the AEM for researchers, but is unavailable during flight operations. Because animal health in microgravity is directly linked to the thermal environment, the ability to predict internal AEM temperatures is extremely useful to life science researchers. NASA flight crews typically carry hand-held temperature measurement devices which allow them to provide ground researchers with near real time readings of AEM inlet temperature; however, higher priority operations limit the frequency at which these measurements can be made and subsequently downlinked. The mathematical model developed allows users to predict internal cage volume temperatures based on knowledge of the ambient air temperature entering the AEM air intake ports. Additionally, an average convective heat transfer coefficient for the AEM has been determined to provide engineers with the requisite information to facilitate future design improvements and product upgrades. The model has been validated using empirical data from a series of three Space Shuttle missions.

Eodice, Michael T.↗

Issues in Software System Safety: Polly Ann Smith Co. versus Ned I. Ludd

This paper is a work of fiction, but it is fiction with a very real purpose: to stimulate careful thought and friendly discussion about some questions for which thought is often careless and discussion is often unfriendly. To accomplish this purpose, the paper creates a fictional legal case. The most important issue in this fictional case is whether certain proffered expert testimony about software engineering for safety critical systems should be admitted. Resolving this issue requires deciding the extent to which current practices and research in software engineering, especially for safety-critical systems, can rightly be considered based on knowledge, rather than opinion.

Holloway, C. Michael↗

Video-task acquisition in rhesus monkeys (Macaca mulatta) and chimpanzees (Pan troglodytes): a comparative analysis

This study describes video-task acquisition in two nonhuman primate species. The subjects were seven rhesus monkeys (Macaca mulatta) and seven chimpanzees (Pan troglodytes). All subjects were trained to manipulate a joystick which controlled a cursor displayed on a computer monitor. Two criterion levels were used: one based on conceptual knowledge of the task and one based on motor performance. Chimpanzees and rhesus monkeys attained criterion in a comparable number of trials using a conceptually based criterion. However, using a criterion based on motor performance, chimpanzees reached criterion significantly faster than rhesus monkeys. Analysis of error patterns and latency indicated that the rhesus monkeys had a larger asymmetry in response bias and were significantly slower in responding than the chimpanzees. The results are discussed in terms of the relation between object manipulation skills and video-task acquisition.

NASA Discipline Space Human Factors↗

Protein Crystallization

Nucleation, growth and perfection of protein crystals will be overviewed along with crystal mechanical properties. The knowledge is based on experiments using optical and force crystals behave similar to inorganic crystals, though with a difference in orders of magnitude in growing parameters. For example, the low incorporation rate of large biomolecules requires up to 100 times larger supersaturation to grow protein, rather than inorganic crystals. Nucleation is often poorly reproducible, partly because of turbulence accompanying the mixing of precipitant with protein solution. Light scattering reveals fluctuations of molecular cluster size, its growth, surface energies and increased clustering as protein ages. Growth most often occurs layer-by-layer resulting in faceted crystals. New molecular layer on crystal face is terminated by a step where molecular incorporation occurs. Quantitative data on the incorporation rate will be discussed. Rounded crystals with molecularly disordered interfaces will be explained. Defects in crystals compromise the x-ray diffraction resolution crucially needed to find the 3D atomic structure of biomolecules. The defects are immobile so that birth defects stay forever. All lattice defects known for inorganics are revealed in protein crystals. Contribution of molecular conformations to lattice disorder is important, but not studied. This contribution may be enhanced by stress field from other defects. Homologous impurities (e.g., dimers, acetylated molecules) are trapped more willingly by a growing crystal than foreign protein impurities. The trapped impurities induce internal stress eliminated in crystals exceeding a critical size (part of mni for ferritin, lysozyme). Lesser impurities are trapped from stagnant, as compared to the flowing, solution. Freezing may induce much more defects unless quickly amorphysizing intracrystalline water.

Chernov, Alexander A.↗

A Tool for Automatic Verification of Real-Time Expert Systems

The creation of an automated, user-driven tool for expert system development, validation, and verification is curretly onoging at NASA's Jet Propulsion Laboratory. In the new age of faster, better, cheaper missions, there is an increased willingness to utilize embedded expert systems for encapsulating and preserving mission expertise in systems which combine conventional algorithmic processing and artifical intelligence. The once-questioned role of automation in spacecraft monitoring is now becoming one of increasing importance.

real-time expert systems automated utilities knowl↗

Cognitive Bias in Systems Verification

Working definition of cognitive bias: Patterns by which information is sought and interpreted that can lead to systematic errors in decisions. Cognitive bias is used in diverse fields: Economics, Politics, Intelligence, Marketing, to name a few. Attempts to ground cognitive science in physical characteristics of the cognitive apparatus exceed our knowledge. Studies based on correlations; strict cause and effect is difficult to pinpoint. Effects cited in the paper and discussed here have been replicated many times over, and appear sound. Many biases have been described, but it is still unclear whether they are all distinct. There may only be a handful of fundamental biases, which manifest in various ways. Bias can effect system verification in many ways . Overconfidence -> Questionable decisions to deploy. Availability -> Inability to conceive critical tests. Representativeness -> Overinterpretation of results. Positive Test Strategies -> Confirmation bias. Debiasing at individual level very difficult. The potential effect of bias on the verification process can be managed, but not eliminated. Worth considering at key points in the process.

Cognitive bias↗

Determination of Realistic Fire Scenarios in Spacecraft

This paper expands on previous work that examined how large a fire a crew member could successfully survive and extinguish in the confines of a spacecraft. The hazards to the crew and equipment during an accidental fire include excessive pressure rise resulting in a catastrophic rupture of the vehicle skin, excessive temperatures that burn or incapacitate the crew (due to hyperthermia), carbon dioxide build-up or accumulation of other combustion products (e.g. carbon monoxide). The previous work introduced a simplified model that treated the fire primarily as a source of heat and combustion products and sink for oxygen prescribed (input to the model) based on terrestrial standards. The model further treated the spacecraft as a closed system with no capability to vent to the vacuum of space. The model in the present work extends this analysis to more realistically treat the pressure relief system(s) of the spacecraft, include more combustion products (e.g. HF) in the analysis and attempt to predict the fire spread and limiting fire size (based on knowledge of terrestrial fires and the known characteristics of microgravity fires) rather than prescribe them in the analysis. Including the characteristics of vehicle pressure relief systems has a dramatic mitigating effect by eliminating vehicle overpressure for all but very large fires and reducing average gas-phase temperatures.

combustion↗

Integrated Medical Model Overview

The Integrated Medical Model (IMM) Project represents one aspect of NASA's Human Research Program (HRP) to quantitatively assess medical risks to astronauts for existing operational missions as well as missions associated with future exploration and commercial space flight ventures. The IMM takes a probabilistic approach to assessing the likelihood and specific outcomes of one hundred medical conditions within the envelope of accepted space flight standards of care over a selectable range of mission capabilities. A specially developed Integrated Medical Evidence Database (iMED) maintains evidence-based, organizational knowledge across a variety of data sources. Since becoming operational in 2011, version 3.0 of the IMM, the supporting iMED, and the expertise of the IMM project team have contributed to a wide range of decision and informational processes for the space medical and human research community. This presentation provides an overview of the IMM conceptual architecture and range of application through examples of actual space flight community questions posed to the IMM project.

Spae Adaptation Syndrome↗

Dome Degradation Characterization of Wide-Field-of-View Nonscanner Aboard ERBE and Its Reprocessing

Earth Radiation Budget Experiment (ERBE) wide-field-of-view (WFOV) nonscanners aboard ERBS and NOAA- 9/NOAA-10 provided broadband shortwave and longwave irradiances from 1985 to 1999. The previous analysis showed dome degradation in the shortwave nonscanner instruments. The correction was performed with a constant spectral (gray assumption) degradation. We suspect that the gray assumption affected daytime longwave irradiance and led to a day-minus-night longwave flux differences (little change in night time longwave) increase over time. Based on knowledge from the CERES process, we will reprocess entire ERBE nonscanner radiation dataset by characterizing shortwave dome transmissivity with spectral dependent degradation using the solar data observed by these instruments. Once spectral dependent degradation is derived, imager derived cloud fraction and the cloud phase as well as surface type over the FOV of nonscanner instruments will be used to model unfiltering coefficients. This poster primarily explains the reprocessing techniques and includes initial comparison of several months of data processed with existing and our recent methods.

Shrestha, Alok K.↗

Aerodynamic Models for the Low Density Supersonic Decelerator (LDSD) Test Vehicles

An overview of aerodynamic models for the Low Density Supersonic Decelerator (LDSD) Supersonic Flight Dynamics Test (SFDT) campaign test vehicle is presented, with comparisons to reconstructed flight data and discussion of model updates. The SFDT campaign objective is to test Supersonic Inflatable Aerodynamic Decelerator (SIAD) and large supersonic parachute technologies at high altitude Earth conditions relevant to entry, descent, and landing (EDL) at Mars. Nominal SIAD test conditions are attained by lifting a test vehicle (TV) to 36 km altitude with a helium balloon, then accelerating the TV to Mach 4 and 53 km altitude with a solid rocket motor. Test flights conducted in June of 2014 (SFDT-1) and 2015 (SFDT-2) each successfully delivered a 6 meter diameter decelerator (SIAD-R) to test conditions and several seconds of flight, and were successful in demonstrating the SFDT flight system concept and SIAD-R technology. Aerodynamic models and uncertainties developed for the SFDT campaign are presented, including the methods used to generate them and their implementation within an aerodynamic database (ADB) routine for flight simulations. Pre- and post-flight aerodynamic models are compared against reconstructed flight data and model changes based upon knowledge gained from the flights are discussed. The pre-flight powered phase model is shown to have a significant contribution to off-nominal SFDT trajectory lofting, while coast and SIAD phase models behaved much as predicted.

Van Norman, John W.↗

The Geostationary Operational Satellite R Series SpaceWire Based Data System

The Geostationary Operational Environmental Satellite R-Series Program (GOES-R, S, T, and U) mission is a joint program between National Oceanic & Atmospheric Administration (NOAA) and National Aeronautics & Space Administration (NASA) Goddard Space Flight Center (GSFC). SpaceWire was selected as the science data bus as well as command and telemetry for the GOES instruments. GOES-R, S, T, and U spacecraft have a mission data loss requirement for all data transfers between the instruments and spacecraft requiring error detection and correction at the packet level. The GOES-R Reliable Data Delivery Protocol (GRDDP) [1] was developed in house to provide a means of reliably delivering data among various on board sources and sinks. The GRDDP was presented to and accepted by the European Cooperation for Space Standardization (ECSS) and is part of the ECSS Protocol Identification Standard [2]. GOES-R development and integration is complete and the observatory is scheduled for launch November 2016. Now that instrument to spacecraft integration is complete, GOES-R Project reviewed lessons learned to determine how the GRDDP could be revised to improve the integration process. Based on knowledge gained during the instrument to spacecraft integration process the following is presented to help potential GRDDP users improve their system designs and implementation.

Networks↗

Artificial Intelligence (AI) Methods for Augmenting the IMPACT Tool Evidence Library

Development of the Evidence Library for use with the IMPACT probability risk assessment tool took several years and involved a staggering amount of effort from a multi-disciplinary team. A very significant amount of the labor effort to collect, assess and finalize the Clinical Finding Form (CliFF) for each of the 119 medical conditions was provided by physician subject matter experts from the Exploration Medical Capability (ExMC) Element Clinical and Science Team. Many AI tools such as ChatGPT are excellent at summarizing large amounts of information and the current project was initiated to determine how such tools might streamline laborious processes, e.g., review and summarization of many scientific research publications, to execute key steps more efficiently in the process of developing CliFFs. The process for collecting the evidence which is found in the CliFFs is well documented in the Evidence Library Methods document (ELM; HRP-48036*). Using ELM and the CliFF development instructions as a guideline, a team of developers is leveraging Microsoft Azure AI tools and services along with open-source frameworks, to construct an AI-assisted automated pipeline. This pipeline is designed to search, retrieve, and process the necessary data sources, and ultimately help generate the final version of a CliFF. Currently, the large language model evaluates the relevance of each source material to spaceflights, either as direct evidence or as an analog. Additionally, the model assists in extracting keywords and generating brief summaries to enhance augmented retrieval and search processes in later stages of CliFF development. Once the data is ready, the model can perform semantic search and retrieval, generating and extracting valuable information for the CliFF. For instance, it can handle epidemiological statistical data, such as incidence rates and the likelihood of best or worst-case scenarios. The steps that required reading and summarizing articles were viewed as providing the greatest return on investment since large language models are very efficient and accurate in summarizing large amounts of text. Since labor effort to complete the original CliFF was not recorded with sufficient granularity, comparisons with an AI tool-generated CliFF will provide merely an approximation of time saved. Upon completion of the process, the CliFF for the medical condition “appendicitis” generated with the support of AI-based methods will serve as a proof-of-concept and will be compared to the original appendicitis CliFF to determine if use of the tools resulted in content and conclusory similarity. Based upon the results from face validation of the two CliFFs, modifications to the process will be made if necessary and additional condition CliFFs will be evaluated. Ultimately, CliFFs for the entire set of medical conditions will be created with the assistance of AI tools. Depending on the cost savings realized, CliFFs for additional medical conditions can be created to expand the Evidence Library. Future direction includes specifying the characteristics of the reviewer (prompting the AI tools to generate output assuming the reviewer is a sub-specialist physician, or nurse or EMT/medic) to determine if the effects on AI-generated output are different based on knowledge, skills and abilities. *Exploration Medical Capability Evidence Library Methods, HRP-48036 Rev A, July 2022.

Ali Al↗