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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Evaluation of a Head-Worn Display System as an Equivalent Head-Up Display for Low Visibility Commercial Operations

Research, development, test, and evaluation of fight deck interface technologies is being conducted by the National Aeronautics and Space Administration (NASA) to proactively identify, develop, and mature tools, methods, and technologies for improving overall aircraft safety of new and legacy vehicles operating in the Next Generation Air Transportation System (NextGen). One specific area of research was the use of small Head-Worn Displays (HWDs) to serve as a possible equivalent to a Head-Up Display (HUD). A simulation experiment and a fight test were conducted to evaluate if the HWD can provide an equivalent level of performance to a HUD. For the simulation experiment, airline crews conducted simulated approach and landing, taxi, and departure operations during low visibility operations. In a follow-on fight test, highly experienced test pilots evaluated the same HWD during approach and surface operations. The results for both the simulation and fight tests showed that there were no statistical differences in the crews' performance in terms of approach, touchdown and takeoff; but, there are still technical hurdles to be overcome for complete display equivalence including, most notably, the end-to-end latency of the HWD system.

Arthur, Jarvis (Trey) J., III↗
NASA NTRS2018

Development of a Ground Test and Analysis Protocol for NASA's NextSTEP Phase 2 Habitation Concepts

The NASA Next Space Technologies for Exploration Partnerships (NextSTEP) program is a public-private partnership model that seeks commercial development of deep space exploration capabilities to support human spaceflight missions around and beyond cislunar space. NASA first issued the Phase 1 NextSTEP Broad Agency Announcement to U.S. industries in 2014, which called for innovative cislunar habitation concepts that leveraged commercialization plans for low-Earth orbit. These habitats will be part of the Deep Space Gateway (DSG), the cislunar space station planned by NASA for construction in the 2020s. In 2016, Phase 2 of the NextSTEP program selected five commercial partners to develop ground prototypes. A team of NASA research engineers and subject matter experts (SMEs) have been tasked with developing the ground-test protocol that will serve as the primary means by which these Phase 2 prototypes will be evaluated. Since 2008, this core test team has successfully conducted multiple spaceflight analog mission evaluations utilizing a consistent set of operational tools, methods, and metrics to enable the iterative development, testing, analysis, and validation of evolving exploration architectures, operations concepts, and vehicle designs. The purpose of implementing a similar evaluation process for the Phase 2 Habitation Concepts is to consistently evaluate different commercial partner ground prototypes to provide data-driven, actionable recommendations for Phase 3. This paper describes the process by which the ground test protocol was developed and the objectives, methods, and metrics by which the NextSTEP Phase 2 Habitation Concepts will be rigorously and systematically evaluated. The protocol has been developed using both a top-down and bottom-up approach. Top-down development began with the Human Exploration and Operations Mission Directorate (HEOMD) exploration objectives and ISS Exploration Capability Study Team (IECST) candidate flight objectives. Strategic questions and associated rationales, derived from these candidate architectural objectives, provide the framework by which the ground-test protocol will address the DSG stack elements and configurations, systems and subsystems, and habitation, science, and EVA functions. From these strategic questions, high-level functional requirements for the DSG were drafted and associated ground-test objectives and analysis protocols were established. Bottom-up development incorporated objectives from NASA SMEs in autonomy, avionics and software, communication, environmental control and life support systems, exercise, extravehicular activity, exploration medical operations, guidance navigation and control, human factors and behavioral performance, human factors and habitability, logistics, Mission Control Center operations, power, radiation, robotics, safety and mission assurance, science, simulation, structures, thermal, trash management, and vehicle health. Top-down and bottom-up objectives were integrated to form overall functional requirements - ground-test objectives and analysis mapping. From this mapping, ground-test objectives were organized into those that will be evaluated through inspection, demonstration, analysis, subsystem standalone testing, and human-in-the-loop (HITL) testing. For the HITL tests, mission-like timelines, procedures, and flight rules have been developed to directly meet ground test objectives and evaluate specific functional requirements. Data collected from these assessments will be analyzed to determine the acceptability of habitation element configurations and the combinations of capabilities that will result in the best habitation platform to be recommended by the test team for Phase 3.

Gernhardt, Michael L.↗
NASA NTRS2018

Metrology-based Techniques for Optical System Alignment for the OSIRIS-Rx Visual and InfraRed Spectrometer

The alignment, integration, and test group (AI&T) in the optics branch at NASA Goddard Space Flight Center (GSFC) specializes in optical and opto-mechanical alignment and metrology for project ranging from building and testing instrument such as spectrometers and cameras to larger structures such as telescopes to large volume metrology and alignment at the observatory level for spacecraft payloads. One of the projects that involved the support of the AI&T group was the OSIRIS-Rex Visual and Infra-Red Spectrometer (OVIRS) for the Origins-Spectral Interpretation-Resource Identification-Security-Regolith Explorer (OSIRIS-Rex) mission. The purpose of this report is to outline the tools, methods, and approaches to metrology utilized by the AI&T group and how they were applied specifically to the optical alignment of the elements on OVIRS during the ambient I&T phase.

Young, Jerrod↗
NASA NTRS2020

Formal Verification of a Solution to the n-Queens Problem

This report describes a formal verification of a concise algorithm that computes a solution to the n-Queens problem for all natural numbers n, such that n > 3. The formal proof of the algorithm is completed in the Prototype Verification System (PVS) theorem prover. This verification effort serves two purposes. First, it is presented as a pedagogical example for learning a theorem prover, such as PVS, and second, as a candidate benchmark for comparing other formal methods tools to PVS.

Mahyar R Malekpour↗
NASA NTRS2014

TPSAS-NF1676L-18905-DND

Aircraft loss of control is a leading cause of fatal accidents across all transport airplane and operational classes. Aircraft loss-of-control (LOC) accidents are highly complex in that they can result from numerous causal and contributing factors acting alone or (more often) in combination. Hence, there is no single intervention strategy to prevent these accidents. This presentation will define LOC as a dynamics and control problem, summarize LOC accident analysis results, and discuss current NASA research that supports a holistic approach for significantly reducing aircraft LOC accidents for current and future aircraft. The approach includes onboard systems technologies for LOC prevention and recovery, as well as a parallel effort for their validation. The onboard systems technologies provide improved situational awareness, guidance, and control under realistic LOC hazards, and include: hazards effects detection and mitigation; upset detection, prevention and recovery; and multiple hazards mitigation. Validation technologies include analytical, simulation, and experimental methods, tools and testbeds as well as the development of a comprehensive set of realistic LOC test scenarios. Future research directions will also be discussed.

Christine Belcastro↗
NASA NTRS2020

Multibody Based Digital Astronaut Dynamics Simulation

BACKGROUND: This study provides the Software, Robotics, & Simulation Division at the NASA Johnson Space Center with a verification tool for multibody dynamics simulation requiring human motion. The motivation stems from current studies of several Vibration Isolation & Stabilization(VIS)system designs that attenuate the moments and forces which would be transmitted to a spacecraft during an exercise. A multibody dynamics model for a proposed VIS was available previously[1], therefore modeling of the VIS was not needed for this work. The interest here is in creating the multibody dynamics model of an astronaut in motion which may be utilized independently or while attached to a mechanism. An existing simulation [2] that utilizes OpenSim [3,4] and an in-house multibody dynamics package (MBDyn) [5] is used in order to verify the astronaut model. The main advantage this model will have over the existing simulation is that everything will be processed in one tool. METHODS AND RESULTS: Creating the simulation required; estimation of Body Segment Inertial Parameters (BSIP),a multibody model of the human-VIS system, joint acceleration profiles, and input files for MBDyn, which is used for this analysis. The scaling factors provided by Dumas et al. [6] are utilized in estimating the BSIP. Anthropometric data are used for estimating these parameters, the Anthropometric Survey of US Army Personnel (ANSUR II) [7] was the source. The astronaut model consists of 15 bodies, 14 joints and 32 degrees of freedom, with the dynamics topology generated using the center of mass locations and anthropometric data. MBDyn has an option for prescribed joint motion (PJM), which requires joint acceleration data as input. The joint angle data is first obtained from a motion capture system and then processed through code that has been created to generate approximate joint acceleration profiles. The topology tree for the astronaut model begins at the right foot up to the pelvis where there is one branch for going down the left leg and another for the torso. The torso branch leads to branches for the arms and a leaf body for the head/neck segment. For attachment to the VIS, the heel of the right foot is connected to the VIS platform through a fixed joint, resembling a foot restraint. The left foot does not attach to the platform in order to prevent a system with a closed loop. Topology and symmetry of the astronaut model were verified through kinematic analysis. Further verification of the forces and moments transmitted to the VIS were verified against the existing simulation. There was a satisfactory level of agreement when testing a simple motion, for example, rocking back and forth. Full exercise motions are to be tested soon. The main outcome has been a novel application of MBDyn for biomechanics modeling that is now available for dynamic simulations involving human motion. The estimation of BSIP was another useful result of this study, requiring only 15 inputs for generating mass properties of a theoretical astronaut model. Expansion on this work is possible by going through an alternative route in obtaining the joint motion data. Instead of high-tech and often expensive motion capture systems, an individual may watch videos with high focus and at a slow motion for each individual segment in order to determine the initial and final time and angle for that specific degree of freedom. Synthetic trajectories may also be created if there is no video reference available.

F N Matari↗
NASA NTRSDate not supplied

Artificial Neural Networks to Predict Cognitive Impairment of Rodents Subjected to Space Radiation

INTRODUCTION We use artificial neural networks (ANNs) as an example machine learning (ML) tool to predict the cognitive performance impairment of rats induced by irradiation. The experimental data in the analyses is attentional set-shifting (ATSET) test scores from a rodent model exposed to ≤15 cGy of individual galactic cosmic radiation (GCR) ions: 4He, 28Si, or 56Fe, expected for a Lunar or Mars mission [1]. This work investigates rats at a subject-based level and uses applied dose and performance scores taken before irradiation to predict whether a rat will be impaired when irradiated. The results of this study are significant to crewed space missions as they support the potential of predicting an astronaut’s impairment in a specific task before spaceflight through the implementation of appropriately trained ML tools. METHODS Data used in this work are scores from the ATSET, a multi-stage constrained cognitive flexibility test [2]. Our computational model utilizes the number of attempts to reach the criterion to pass a stage as a behavioral performance measure for rats. We use the post-irradiation scores, generate thresholds from cumulative distribution plots of non-irradiated rats, and calculate the percent of irradiated rats whose scores fall below the threshold to infer how each radiation type/dose affects a population. Rats scoring above the threshold are labeled impaired while the others are non-impaired. We then employ ANNs as a typical ML technique, and use each subject’s individual scores taken before radiation along with the applied dose, to predict their personal susceptibility to cognitive impairment due to space radiation exposure. RESULTS AND CONCLUSION A significant finding is the exhibition of a dose-dependent increasing probability of impairment for 1 to 10 cGy of 28Si or 56Fe in the simple discrimination (SD) stage of the ATSET, and for 1 to 10 cGy of 56Fe in the compound discrimination (CD) stage. On a subject-based level, implementing ML classifiers such as ANNs identifies rats that have a higher tendency for impairment after GCR exposure [1]. The receiver operating characteristic (ROC) and the precision-recall (PR) curves of the ML models show a better prediction of impairment when 56Fe is the ion in question in both SD (Figure 1) and CD stages. They, however, do not depict impairment due to 4He in SD (Figure 1) and 28Si in CD, suggesting no dose-dependent impairment response in these cases. In this work, “good” prediction pertains to “better-than-random-chance”, due to the limited sample size and the high inter- and intra-individual variabilities in response to brain stimulation paradigms, as applicable to both animals and humans. More behavioral tests and biomarkers should be investigated on the same subjects, to be fed to the ML models to capture the agents responsible for performance alterations of some individuals versus others.

machine learning↗
NASA NTRSDate not supplied

Machine Learning Models to Predict Cognitive Impairment of Rodents Subjected to Space Radiation

INTRODUCTION We use artificial neural networks (ANNs) as an example machine learning (ML) tool to predict the cognitive performance impairment of rats induced by irradiation. The experimental data in the analyses is attentional set-shifting (ATSET) test scores from a rodent model exposed to ≤15 cGy of individual galactic cosmic radiation (GCR) ions: 4He, 28Si, or 56Fe, expected for a Lunar or Mars mission [1]. This work investigates rats at a subject-based level and uses applied dose and performance scores taken before irradiation to predict whether a rat will be impaired when irradiated. The results of this study are significant to crewed space missions as they support the potential of predicting an astronaut’s impairment in a specific task before spaceflight through the implementation of appropriately trained ML tools. METHODS Data used in this work are scores from the ATSET, a multi-stage constrained cognitive flexibility test [2]. Our computational model utilizes the number of attempts to reach the criterion to pass a stage as a behavioral performance measure for rats. We use the post-irradiation scores, generate thresholds from cumulative distribution plots of non-irradiated rats, and calculate the percent of irradiated rats whose scores fall below the threshold to infer how each radiation type/dose affects a population. Rats scoring above the threshold are labeled impaired while the others are non-impaired. We then employ ANNs as a typical ML technique, and use each subject’s individual scores taken before radiation along with the applied dose, to predict their personal susceptibility to cognitive impairment due to space radiation exposure. RESULTS AND CONCLUSION A significant finding is the exhibition of a dose-dependent increasing probability of impairment for 1 to 10 cGy of 28Si or 56Fe in the simple discrimination (SD) stage of the ATSET, and for 1 to 10 cGy of 56Fe in the compound discrimination (CD) stage. On a subject-based level, implementing ML classifiers such as ANNs identifies rats that have a higher tendency for impairment after GCR exposure [1]. The receiver operating characteristic (ROC) and the precision-recall (PR) curves of the ML models show a better prediction of impairment when 56Fe is the ion in question in both SD (Figure 1) and CD stages. They, however, do not depict impairment due to 4He in SD (Figure 1) and 28Si in CD, suggesting no dose-dependent impairment response in these cases. In this work, “good” prediction pertains to “better-than-random-chance”, due to the limited sample size and the high inter- and intra-individual variabilities in response to brain stimulation paradigms, as applicable to both animals and humans. More behavioral tests and biomarkers should be investigated on the same subjects, to be fed to the ML models to capture the agents responsible for performance alterations of some individuals versus others.

machine learning↗
NASA NTRS2021

Lessons Learned in Remote Participant Concurrent Engineering Concept Development Studies

Team-X was born from a need to perform rapid space mission design for principal investigator-led competed proposals in the mid-1990s. Throughout the last 25 years, Team-X at the Jet Propulsion Laboratory has expanded its application of the collaborative, concurrent study approach into every facet necessary to win competed proposals. The COVID-19 pandemic of 2020 created an immediate and new constraint on these studies – the need to conduct them with remote participants, both on the client side requesting the study, but also on the provider side producing the study. This paper provides lessons learned from dozens of design studies run by Team-X at the Jet Propulsion Laboratory during the COVID-19 pandemic. These lessons span all aspects of the information infrastructure: the people, processes, procedures, methods, tools, and “facilities”. These lessons learned will have applicability post-pandemic, as they have shown how best to incorporate participants, both on the provider side, and on the client side, who cannot travel or otherwise be co-located during collaborative, concurrent study sessions.

Nash, Alfred↗
NASA NTRSDate not supplied

Aerothermodynamic Analyses for the LOFTID Technology Demonstration Mission

On November 10, 2023, the LOFTID flight test successfully demonstrated the aerodynamic and thermal protection system performance of an inflatable aeroshell at conditions relevant to an operational mission. Aerodynamic performance and aeroheating environment databases for this mission were generated using multiple computational tools for the rarefied, hypersonic, and supersonic flow regimes, supplemented by wind tunnel testing to obtain aeroshell boundary-layer transition and wake flow simulation validation data. A detailed discussion of tools, methods and results is presented herein.

Brian R. Hollis↗
NASA NTRSDate not supplied

Aerothermodynamic Analyses for the LOFTID Technology Demonstration Mission

On November 10, 2023, the LOFTID flight test successfully demonstrated the aerodynamic and thermal protection system performance of an inflatable aeroshell at conditions relevant to an operational mission. Aerodynamic performance and aeroheating environment databases for this mission were generated using multiple computational tools for the rarefied, hypersonic, and supersonic flow regimes, supplemented by wind tunnel testing to obtain aeroshell boundary-layer transition and wake flow simulation validation data. A detailed discussion of tools, methods and results is presented herein.

Brian R. Hollis↗
NASA NTRSDate not supplied

Human Systems Risk Network - A Ranking Analysis of Risks

INTRODUCTION The Human Systems Risk Board (HSRB) is responsible for understanding, managing, and mitigating the risks associated with spaceflight. For a particular mission, the HSRB assigns each human system risk a rating on a 5x5 grid assessing its likelihood and consequence, which is ultimately used to compare and rank the risks. The HSRB approaches risk management by primarily establishing the context of each human system risk individually with the understanding that mitigating one risk might affect the likelihood, consequence, and mitigation approaches of another. To support this effort the HSRB, subject matter experts, and risk custodian teams created directed acyclic graphs (DAG), often called a causal graph, for the twenty-nine risks. In this presentation, we propose a new ranking algorithm for the risks which includes the downstream influence of each risk according to the information in the DAGs and provide an application of graph theoretic tools. METHODS In 2014, Mindock and Klaus proposed a taxonomy for human system risk influences which we have adopted to categorize the nodes in each DAG. Analyzing the nodes that correspond to the risks in this taxonomy allows us to analyze and understand how each risk influences the others. We construct an auxiliary network, which we call the Primary Risk Network (PRN), where the nodes are the twenty-nine space flight risks and, a directed edge connects Risk A to Risk B if Risk A has some influence on the likelihood or consequence of Risk B as described in the DAGS. We perform a variety of graph theoretic ranking methods on the nodes (or risks) in the PRN, including Katz centrality. RESULTS We rank the nodes in the PRN using the Katz centrality score. The ten risks with the highest score are pictured in Figure 1, colored (light to dark) according to their score. We analyze other centrality measures like betweenness centrality, eigenvector centrality, and the Estrada index, and provide the meaning of the corresponding rankings in terms of the risks. Future work includes analyzing the other categories in the taxonomy defined by Mindock and Klaus [1]. For example, we are interested in analyzing the nodes that are labeled as countermeasures or capabilities and perform similar analysis to measure their effect on certain medical conditions.

dag↗
NASA NTRS2003

2D and 3D Method of Characteristic Tools for Complex Nozzle Development

This report details the development of a 2D and 3D Method of Characteristic (MOC) tool for the design of complex nozzle geometries. These tools are GUI driven and can be run on most Windows-based platforms. The report provides a user's manual for these tools as well as explains the mathematical algorithms used in the MOC solutions.

Rice, Tharen↗
NASA NTRS1992

A critical evaluation of a three-dimensional Navier-Stokes method as a tool to calculate transonic flows inside a low-aspect-ratio compressor

A numerical study to evaluate a three-dimensional Navier-Stokes method as a tool to predict the detailed flow field inside a low-aspect-ratio compressor at various operating conditions was conducted. The details of the flow structure inside a low aspect ratio compressor (three-dimensional shock structure, shock-boundary layer interaction, and tip leakage vortex) and the overall aerodynamic performance at design and off-design conditions are numerically analyzed and the results are compared with the available experimental data. The flow field inside a state-of-the-art transonic compressor is used for the purpose of the evaluation.

Hah, Chunill↗
NASA NTRS1999

Resin film infusion mold tooling and molding method

A mold apparatus and method for resin film infusion molding including an outer mold tool having a facing sheet adapted to support a resin film and preform assembly. The facing sheet includes attachment features extending therefrom. An inner mold tool is positioned on the facing sheet to enclose the resin film and preform assembly for resin film infusion molding. The inner mold tool includes a plurality of mandrels positioned for engagement with the resin film and preform assembly. Each mandrel includes a slot formed therein. A plurality of locating bars cooperate with the slots and with the attachment features for locating the mandrels longitudinally on the outer mold tool.

Burgess, Roger↗
NASA NTRS1972

Development of gas-pressure bonding process for air-cooled turbine blades

An investigation was conducted on the application of gas-pressure bonding to the joining of components for convectively cooled turbine blades and vanes. A processing procedure was established for joining the fins of Udimet 700 and TD NiCr sheet metal airfoil shells to cast B1900 struts without the use of internal support tooling. Alternative methods employing support tooling were investigated. Testing procedures were developed and employed to determine shear strengths and internal burst pressures of flat and cylindrical bonded finned shell configurations at room temperature and 1750 F. Strength values were determined parallel and transverse to the cooling fin direction. The effect of thermal cycles from 1750 F to room temperature on strength was also investigated.

Meiners, K. E.↗
NASA NTRS1992

Myths and realities: Defining re-engineering for a large organization

This paper describes the background and results of three studies concerning software reverse engineering, re-engineering, and reuse (R3) hosted by the Internal Revenue Service in 1991 and 1992. The situation at the Internal Revenue--aging, piecemeal computer systems and outdated technology maintained by a large staff--is familiar to many institutions, especially among management information systems. The IRS is distinctive for the sheer magnitude and diversity of its problems; the country's tax records are processed using assembly language and COBOL and spread across tape and network DBMS files. How do we proceed with replacing legacy systems? The three software re-engineering studies looked at methods, CASE tool support, and performed a prototype project using re-engineering methods and tools. During the course of these projects, we discovered critical issues broader than the mechanical definitions of methods and tool technology.

Yin, Sandra↗
NASA NTRS2009

Architectural Analysis of Complex Evolving Systems of Systems

The goal of this collaborative project between FC-MD, APL, and GSFC and supported by NASA IV&V Software Assurance Research Program (SARP), was to develop a tool, Dynamic SAVE, or Dyn-SAVE for short, for analyzing architectures of systems of systems. The project team was comprised of the principal investigator (PI) from FC-MD and four other FC-MD scientists (part time) and several FC-MD students (full time), as well as, two APL software architects (part time), and one NASA POC (part time). The PI and FC-MD scientists together with APL architects were responsible for requirements analysis, and for applying and evaluating the Dyn-SAVE tool and method. The PI and a group of FC-MD scientists were responsible for improving the method and conducting outreach activities, while another group of FC-MD scientists were responsible for development and improvement of the tool. Oversight and reporting was conducted by the PI and NASA POC. The project team produced many results including several prototypes of the Dyn-SAVE tool and method, several case studies documenting how the tool and method was applied to APL s software systems, and several published papers in highly respected conferences and journals. Dyn-SAVE as developed and enhanced throughout this research period, is a software tool intended for software developers and architects, software integration testers, and persons who need to analyze software systems from the point of view of how it communicates with other systems. Using the tool, the user specifies the planned communication behavior of the system modeled as a sequence diagram. The user then captures and imports the actual communication behavior of the system, which is then converted and visualized as a sequence diagram by Dyn-SAVE. After mapping the planned to the actual and specifying parameter and timing constraints, Dyn-SAVE detects and highlights deviations between the planned and the actual behavior. Requirements based on the need to analyze two inter-system communication protocols that are representative of protocols used in the Aerospace industry have been specified. The protocols are related: APL s Common Ground System (CGS) as used in the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) and the Radiation Belt Space Probes (RBSP) missions. The analyzed communications were implementations of the Telemetry protocol and the CCSDS File Delivery Protocol (CFDP) protocol. Based on these requirements, three prototypes of Dyn-SAVE were developed and applied to these protocols. The application of Dyn-SAVE to these protocols resulted in the detection of several issues. Dyn-SAVE was also applied to several Testbeds that have previously been used for experimentation earlier on this project, as well as, to other protocols and logs for testing its broader applicability. For example, Dyn-SAVE was used to analyze 1) the communication pattern between a web browser and a web server, 2) the system log of a computer in order to detect offnominal computer shut-down behavior, and 3) the actual test cases of NASA Goddard s Core Flight System (CFS) and automatically generated test cases in order to determine the overlap between the two sets of test cases. In all cases, Dyn-SAVE assisted in providing insightful conclusions about each of the cases identified above.

Lindvall, Mikael↗