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At least 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Mars2020 Entry, Descent, and Landing Instrumentation (MEDLI2): Science Objectives and Instrument Requirements

NASAs exploration and technology roadmaps call for capability advancements in Mars entry, descent, and landing (EDL) systems to enable increased landed mass, a higher landing precision, and a wider planetary access. It is also recognized that these ambitious EDL performance goals must be met while maintaining a low mission risk in order to pave the way for future human missions. As NASA is engaged in developing new EDL systems and technologies via testing at Earth, instrumentation of existing Mars missions is providing valuable engineering data for performance improvement, risk reduction, and an improved definition of entry loads and environment. The most notable recent example is the Mars Entry, Descent and Landing Instrument (MEDLI) suite hosted by Mars Science Laboratory for its entry in Aug 2012. The MEDLI suite provided a comprehensive dataset for Mars entry aerodynamics, aerothermodynamics and thermal protection system (TPS) performance. MEDLI data has since been used for unprecedented reconstruction of aerodynamic drag, vehicle attitude, in-situ atmospheric density, aerothermal heating, and transition to turbulence, in-depth TPS performance and TPS ablation. [1,2] In addition to validating predictive models, MEDLI data has demonstrated extra margin available in the MSL forebody TPS, which can potentially be used to reduce vehicle parasitic mass. The presentation will introduce a follow-on MEDLI instrumentation suite (called MEDLI2) that is being developed for Mars-2020 mission. MEDLI2 has an enhanced scope that includes backshell instrumentation, a wider forebody coverage, and instruments that specifically target supersonic aerodynamics. Similar to MEDLI, MEDLI2 uses thermal plugs with embedded thermocouples and ports through the TPS to measure surface pressure. MEDLI2, however, also includes heat flux sensors in the backshell and a low range pressure transducer to measure afterbody pressure.

Aerothermodynamics↗
NASA NTRS2010

Excavator Design Validation

The Excavator Design Validation tool verifies excavator designs by automatically generating control systems and modeling their performance in an accurate simulation of their expected environment. Part of this software design includes interfacing with human operations that can be included in simulation-based studies and validation. This is essential for assessing productivity, versatility, and reliability. This software combines automatic control system generation from CAD (computer-aided design) models, rapid validation of complex mechanism designs, and detailed models of the environment including soil, dust, temperature, remote supervision, and communication latency to create a system of high value. Unique algorithms have been created for controlling and simulating complex robotic mechanisms automatically from just a CAD description. These algorithms are implemented as a commercial cross-platform C++ software toolkit that is configurable using the Extensible Markup Language (XML). The algorithms work with virtually any mobile robotic mechanisms using module descriptions that adhere to the XML standard. In addition, high-fidelity, real-time physics-based simulation algorithms have also been developed that include models of internal forces and the forces produced when a mechanism interacts with the outside world. This capability is combined with an innovative organization for simulation algorithms, new regolith simulation methods, and a unique control and study architecture to make powerful tools with the potential to transform the way NASA verifies and compares excavator designs. Energid's Actin software has been leveraged for this design validation. The architecture includes parametric and Monte Carlo studies tailored for validation of excavator designs and their control by remote human operators. It also includes the ability to interface with third-party software and human-input devices. Two types of simulation models have been adapted: high-fidelity discrete element models and fast analytical models. By using the first to establish parameters for the second, a system has been created that can be executed in real time, or faster than real time, on a desktop PC. This allows Monte Carlo simulations to be performed on a computer platform available to all researchers, and it allows human interaction to be included in a real-time simulation process. Metrics on excavator performance are established that work with the simulation architecture. Both static and dynamic metrics are included.

Pholsiri, Chalongrath↗
NASA NTRS1996

NASA's Advanced Life Support Systems Human-Rated Test Facility

Future NASA missions to explore the solar system will be long-duration missions, requiring human life support systems which must operate with very high reliability over long periods of time. Such systems must be highly regenerative, requiring minimum resupply, to enable the crews to be largely self-sufficient. These regenerative life support systems will use a combination of higher plants, microorganisms, and physicochemical processes to recycle air and water, produce food, and process wastes. A key step in the development of these systems is establishment of a human-rated test facility specifically tailored to evaluation of closed, regenerative life supports systems--one in which long-duration, large-scale testing involving human test crews can be performed. Construction of such a facility, the Advanced Life Support Program's (ALS) Human-Rated Test Facility (HRTF), has begun at NASA's Johnson Space Center, and definition of systems and development of initial outfitting concepts for the facility are underway. This paper will provide an overview of the HRTF project plan, an explanation of baseline configurations, and descriptive illustrations of facility outfitting concepts.

NASA Discipline Number 61-10↗
NASA NTRSDate not supplied

Earth-Independent Medical Operations (EIMO) Concept of Operations

In contrast to the current crew health paradigm for low-Earth orbit and Lunar missions, which depends on real-time communication with Mission Control, deep-space exploration missions will require a significant shift in medical operations. This shift is driven by the constraints of operating at a considerable distance from Earth, such as resource limitations—lack of resupply, restricted mass, power, volume, and data—as well as communication delays and the inability to evacuate back to Earth during emergencies. To move toward a more self-reliant medical model, a strategy is needed to gradually increase space-based crew autonomy and reduce risks to mission success in the challenging environment of deep space. This transformative change, known as "Earth-Independent Medical Operations" (EIMO), explores the gradual transfer of medical care and decision-making from Earth-based support to space-based systems. The goal of this transition is to enhance astronaut health and performance while minimizing mission risks. EIMO requires the development of a medical system that integrates seamlessly with mission planning, vehicle and spacesuit design, and data architecture. This integration is crucial for building a robust medical infrastructure that not only safeguards astronaut well-being but also ensures overall mission success. The Human Research Program (HRP) Exploration Medical Capability (ExMC) Element has revised the EIMO model-based Concept of Operations (ConOps) which outlines an initial vision for EIMO. The ConOps, which is built on the stakeholders’ need, system goals, and objectives (NGOs), presents an array of in-mission scenarios that span a wide range of medical conditions demonstrating the system’s capabilities from basic to complex events. Developed by a multidisciplinary team of systems engineers, scientists, and clinicians within ExMC, the ConOps revision includes two new scenarios(Barotrauma and Self-Medical Management and Behavioral Health and Chronic Medical Care), and implementation of findings from EIMO technical interchange meetings that focused on data and training. The envisioned EIMO Medical System (MS) operates as a system of systems, gathering data from various sources such as reference databases, real-time wearable sensors, point-of-care diagnostics, and environmental controls. The MS also incorporates advanced training tools to support autonomous medical care, assisting the Crew Medical Officer (CMO) during medical events where Ground Support is either unavailable or communication-delayed beyond practicality. Furthermore, MS functions and capabilities were decomposed from the scenarios to establish foundational requirements for EIMO and traced to the NASA Spaceflight Human-System Standard(NASA-STD-3001, Volumes 1 and 2). These traces were performed to gain insights on the alignment of EIMO requirements with the NASA standard. This work serves as an initial recommendation to increase crew autonomy gradually and safely for Mars missions and future deep-space exploration.

medical system↗
NASA NTRS2016

Modifying a Commercial Centrifuge to Reduce Electromagnetic Interference and Evaluating Functionality of Ultrasound Equipment

The Project Management and Engineering Branch (SF4) supports the Human Health and Performance Directorate (HH&P) and is responsible for developing and supporting human systems hardware for the International Space Station (ISS). When a principal investigator's (PI) medical research project on the ISS is accepted, SF4 develops the necessary hardware and software to transport to the ISS. The two projects I primarily worked on were the centrifuge and ultrasound projects. Centrifuge: One concern with spacecraft such as the ISS is electromagnetic interference (EMI) from onboard equipment, typically from radio waves (frequencies of ~3 kHz to ~300 GHz), which can negatively affect nearby circuitry. Standard commercial centrifuges produce EMI above safety limits, so my task was to help reduce EMI production from this equipment. Two centrifuges were tested: one unmodified as a control and one modified. To reduce EMI below safety limits, one centrifuge was modified to become a Faraday shield, in which significant electrical contact was made between all regions of the centrifuge housing. This included removing non-conductive paint, applying conductive fabric to the lid and foam sealer, adding a 10,000 μF decoupling capacitor across the power supply, and adding copper adhesive-mount gaskets to the housing interior. EMI testing of both centrifuges was performed in the EMI/EMC Control Test and Measurement Facility. EMI for both centrifuges was below safety limits for frequencies between 10 MHz and 15 GHz (pass); however, between 14 kHz and 10 MHz, EMI for the unmodified centrifuge exceeded safety limits (fail) as expected. Alternatively, for the modified centrifuge with the Faraday shield, EMI was below the safely limit of 55 dBμV/m for electromagnetic frequencies between 14 kHz and 10 MHz. This result indicates our modifications were successful. The successful EMI test allowed us to communicate with the vendor what modifications they needed to make to their commercial unit to meet our specifications and to understand what needs to be done in lab to the new centrifuge. Our modifications will provide a standard for readying centrifuges for future missions. Once the new modified centrifuge arrives by the vendor, it will need to undergo EMI testing again for validation. The centrifuge is also in the process of compatibility testing with a custom stowage drawer, which is an ongoing project in SF4. Both of these items will be payloads on future missions to the ISS for various research purposes. Ultrasound: ISS currently has an onboard ultrasound (Ultrasound 2 system) for research and medical purposes. Every piece of medical flight hardware has an equivalent ground-unit so instrumentation can be routinely evaluated and transported to the ISS if necessary. The ground-unit ultrasound equipment must be evaluated every six months using a task performance sheet (TPS). A TPS is a document, written by the appropriate scientists and engineers, which describes how to run equipment and is written in such a way that astronauts with unspecialized training can follow the tasks. I was responsible for performing six TPSs on a combination of three ultrasounds and two video power converters (VPCs). Performing a TPS involves checking out and computationally documenting each piece of equipment removed from storage locations, setting up hardware and software, performing tasks to verify functionality, returning equipment, and logging items back into the computerized system. My work revealed all ground-unit ultrasounds were functioning properly. Because of proper function, a discrepancy report (DR) did not have to be opened. The TPS was then passed along to the Quality Engineering (QE) for review and ultimately given to Quality Assurance (QA). Other projects: In addition to my main projects, I participated in other tasks including troubleshooting an EEG headband, volunteering for an ultrasound training research study, and conformal coating printed circuit boards. My internship at SF4 has helped me understand how space systems hardware development for the ISS fits into NASA's mission and vision.

Greening, Gage J.↗
DOE OSTI2020

Cognition at the Point of Sensing

Over the last 15 years, compressive sensing techniques have been developed which have the potential to greatly reduce the amount of data collected by systems while preserving the amount of information obtained. A cost of this efficiency is that a computationally-intensive optimization routine must be used to put the sensed data into a form that a person can interpret. At the same time, machine learning techniques have experienced tremendous growth as well. Machines have demonstrated the ability learn how to effectively perform tasks such as detection and classification at speeds much faster than humanly possible. Our goal in this project was to study the feasibility of using compressive sensing systems "at the edge." That is, how can compressive sensing sensors be deployed such that information is created at the remote sensor rather than sending raw data to a central processing location? Studies were performed to analyze whether machine learning could be done on the compressively sensed data in its raw form. If a machine is performing the task, is it possible to do so without putting the data into a human interpretable form? We show that this is possible for some systems, in particular a compressive sensing snapshot imaging spectrometer. Machine learning tasks were demonstrated to be more effective and more robust to noise when the machine learning algorithm worked on data in its raw form. This system is shown to outperform a traditional spectrometer. Techniques for reducing the complexity of the reconstruction routine were also analyzed. Techniques for such as data regularization, deep neural networks, and matrix completion were studied and shown to have benefits over traditional reconstruction techniques. In this project we showed that compressive sensing sensors are indeed feasible at the edge. As always, sensors and algorithms must be carefully tuned to work in the constrained environment. In this project we developed tools and techniques to enable those analyses.

47 OTHER INSTRUMENTATION↗
NASA NTRS1972

A performance measure for manual control systems

A new performance measure is introduced for multivariable closed loop experiments with a human operator. The essential feature of the phase margin performance measure (PMPM) is that the performance of each control loop can be determined independently, with prescribed disturbance and error levels. A variable filter parameter is used as the PMPM within the loop and it assures a high workload at the same time. There is a straightforward relationship between the PMPM and the inner loop feedback augmentation that can be utilized in trade-off studies. An adjustment scheme that seeks the PMPM automatically is described as employed in a single loop control task. This task applies directly to the experimental study of displays for helicopters and VTOL aircraft.

Dukes, T. A.↗
NASA NTRS1984

Automation effects in a stereotypical multiloop manual control system

The increasing reliance of state-of-the art, high performance aircraft on high authority stability and command augmentation systems, in order to obtain satisfactory performance and handling qualities, has made critical the achievement of a better understanding of human capabilities, limitations, and preferences during interactions with complex dynamic systems that involve task allocation between man and machine. An analytical and experimental study has been undertaken to investigate human interaction with a simple, multiloop dynamic system in which human activity was systematically varied by changing the levels of automation. Task definition has led to a control loop structure which parallels that for any multiloop manual control system, and may therefore be considered a stereotype.

Hess, R. A.↗
NASA NTRS1991

Recent technology products from Space Human Factors research

The goals of the NASA Space Human Factors program and the research carried out concerning human factors are discussed with emphasis given to the development of human performance models, data, and tools. The major products from this program are described, which include the Laser Anthropometric Mapping System; a model of the human body for evaluating the kinematics and dynamics of human motion and strength in microgravity environment; an operational experience data base for verifying and validating the data repository of manned space flights; the Operational Experience Database Taxonomy; and a human-computer interaction laboratory whose products are the display softaware and requirements and the guideline documents and standards for applications on human-computer interaction. Special attention is given to the 'Convoltron', a prototype version of a signal processor for synthesizing the head-related transfer functions.

Jenkins, James P.↗
NASA NTRS1990

NASA Center for Intelligent Robotic Systems for Space Exploration

NASA's program for the civilian exploration of space is a challenge to scientists and engineers to help maintain and further develop the United States' position of leadership in a focused sphere of space activity. Such an ambitious plan requires the contribution and further development of many scientific and technological fields. One research area essential for the success of these space exploration programs is Intelligent Robotic Systems. These systems represent a class of autonomous and semi-autonomous machines that can perform human-like functions with or without human interaction. They are fundamental for activities too hazardous for humans or too distant or complex for remote telemanipulation. To meet this challenge, Rensselaer Polytechnic Institute (RPI) has established an Engineering Research Center for Intelligent Robotic Systems for Space Exploration (CIRSSE). The Center was created with a five year $5.5 million grant from NASA submitted by a team of the Robotics and Automation Laboratories. The Robotics and Automation Laboratories of RPI are the result of the merger of the Robotics and Automation Laboratory of the Department of Electrical, Computer, and Systems Engineering (ECSE) and the Research Laboratory for Kinematics and Robotic Mechanisms of the Department of Mechanical Engineering, Aeronautical Engineering, and Mechanics (ME,AE,&M), in 1987. This report is an examination of the activities that are centered at CIRSSE.

Source record↗
NASA NTRSDate not supplied

A Decision Support System for Extravehicular Operations Under Significant Communication Latency

Within the next few decades, humanity hopes to perform extravehicular activities (EVAs) on the surface of Mars; however, several technical and operational challenges must first be overcome. Foremost among these challenges is managing a significant two-way communication latency between Earth and Mars. Current and historical paradigms of EVA operations have required near-real-time communication between the crewmember(s) performing an EVA and an Earth-based mission control. Next-generation operational paradigms for supporting deep space exploration will necessitate a distributed decision authority system, including delayed Earth-based mission control, the on-planet extravehicular crewmember(s), and intermediate mission support from intravehicular crewmember(s) within real-time communication range. This latter group is of particular interest: they must provide operations support without the plentiful resources available to mission control on Earth. For this purpose, NASA is developing the Personalized EVA Informatics and Decision Support (PersEIDS) software platform. PersEIDS is designed to bolster operator situational awareness and offload operator workload by automating the tracking and projection of consumables usage over an EVA timeline, providing real-time probabilistic safety assessments of an EVA timeline given consumables constraints, and recommending alternative EVA timeline(s) when the active timeline is not expected to be completed under consumables limits. The PersEIDS concept of operations, use cases, and models will be presented. A limited version of PersEIDS was demonstrated during a three-day-long study where each day a roughly four-hour-long simulated Martian EVA was performed in virtual reality at the NASA Johnson Space Center. The first day was a control trial without PersEIDS support; the second and third days represented different levels of decision support provided by PersEIDS to the intravehicular crewmember acting as mission control. With PersEIDS support, the IV crewmember was able to manage the mission to completion faster and with more remaining consumables; however, additional testing is required to understand confounding factors, e.g. training bias.

Mars↗
DOE OSTI2022

A Methodology to Support the Development of a New State Vision for the U.S. Nuclear Industry

Recent changes in natural gas prices combined with reduced capital costs for solar and wind systems has created challenges for the continued operation of existing nuclear power plants (NPPs) in the United States. A new strategy in the way in which U.S. NPPs are operated, maintained, and supported is needed. One such strategy is to transform the NPP operating model through a business-driven approach that leverages technology to enable new capabilities that improve performance and reduce costs. This paper presents a methodology for developing an achievable yet transformative new state vision that ensures the continued safe and efficient operations of the U.S. NPP fleet. Here this work builds on existing guidance and leverages previous research to comprehensively address both utility needs and high-level human factors engineering design principles when developing a new state vision. The proposed methodology is intended to provide industry-wide guidance for developing a new state vision that leverages both the selected vendor’s capabilities in a way that meets the utility’s modernization goals while ensuring state-of-the-art systems engineering and human factors engineering principles are applied that promote overall plant safety, performance, and efficiency.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRSDate not supplied

Neo – Mars Adaptive Training Integrative Knowledge System (MATRIKS) to Improve Operational Performance and its Neural Basis for Spaceflight

With prolonged mission durations, spaceflight crews will become increasingly dependent on onboard technologies for knowledge acquisition and maintenance. It is expected that not all skills and knowledge required for these missions can be retained and retrieved based on pre-mission training alone. Limited and delayed communication will significantly constrain support from Mission Control and crews will increasingly rely on autonomous onboard technologies to successfully perform post-landing operations. With the present project we will target NASA’s particular interest in developing and assessing an adaptive, just-in-time countermeasure that will consolidate and improve skills that are most relevant to space flight operations. To achieve this aim, NASA established a Virtual NASA Specialized Center of Research (VNSCOR)referred to as “Mars Adaptive Training Integrative Knowledge System (MATRIKS)”, comprising the following three projects: (1) “Trinity–Multi-Environment Virtual Training for Long Duration Exploration Missions”, PI: A. Anderson (UC Boulder); (2) “Morpheus–A Haptic Sensory Supplement to Optimize In-Flight Adaptive Training for Human Control of Spacecraft Robotic Arms”, PI: S. Robinson, UC Davis); and the present project “Neo–Adaptive Training integrative knowledge System to Improve Operational Performance and its Neural Basis for Spaceflight” (UPenn, PI: A.C. Stahn). Neo leverages a validated workstation called 6DF that simulates a rendezvous and docking maneuver using real spacecraft flight dynamics. It is designed to (1) train and improve sensorimotor skills relevant for inflight and post-landing operational tasks; (2) feature an autonomous and adaptive training approach that does not rely on feedback from flight operations on the ground; (3) maximize the transfer of mission-relevant motor skills; (4) allow the assessment of the neural circuitry underlying the task; and (5) deliver the training in a motivating and meaningful way to astronauts. Neocomprises two overarching aims: First, we will identify the neural circuitry underlying spaceflight relevant tasks by performing a subset of the 6DFtaskduring functional magnetic resonance imaging (MRI)in a total of up to N=30 subjects with varying levels of 6DF training experience. Second, as part of the above-mentioned VNSCOR MATRIKS the proposed 6DF autonomous intelligent tutor system will be integrated in an additive manner with a haptic feedback intervention (Morpheus), and a multi-environment virtual trainer(Trinity).It is expected that Neo, Morpheus and Trinity mutually complement each other to facilitate an effective countermeasure tool to acquire and retain operational skills that are critical for exploration class missions. To assess the efficacy of this combined effort, the VNSCOR MATRIKS will collect data inN=16 crew members in one HERA campaign of 45 days duration with N=16 crew members(four missions with N=4 crew member seach).The primary goal is to identify changes in operational performance as assessed by NASA’s simulator of Canadarm2 operations, i.e., Robotic On-board Trainer (ROBoT-r) in response to MATRIKS. As part of Neo we will also identify if, and to what extent MATRIKS will promote transfer to general cognitive performance (Cognition battery), distinctive visuo-spatial tasks critical for telerobotic tasks (Spatial Cognition battery), and affect brain structural changes and the neural circuitry of key brain networks expected to be relevant for spaceflight-related performance. At the conclusion of the research, we will have defined and demonstrated the use of a neuroscience-based, adaptive training integrative knowledge system to potentially mitigate visuo-spatial and sensorimotor brain changes associated with prolonged isolation and confinement to reduce the likelihood or impact of potential decrements in human performance capabilities during long-duration space missions. The expected significance of this 4-year project relates to its relevance for facilitating effective countermeasure tools to acquire and retain operational skills that are critical for exploration class missions. This will support the development of necessary countermeasures and technologies in support of human space exploration, focusing on mitigating operational performance risks.

A C Stahn↗
NASA NTRS1977

Study to design and develop remote manipulator systems

A description is given of part of a continuing effort both to develop models for and to augment the performance of humans controlling remote manipulators. The project plan calls for the performance of several standard tasks with a number of different manipulators, controls, and viewing conditions, using an automated performance measuring system; in addition, the project plan calls for the development of a force-reflecting joystick and supervisory display system.

Hill, J. W.↗
NASA NTRS1977

Fully automated urban traffic system

The replacement of the driver with an automatic system which could perform the functions of guiding and routing a vehicle with a human's capability of responding to changing traffic demands was discussed. The problem was divided into four technological areas; guidance, routing, computing, and communications. It was determined that the latter three areas being developed independent of any need for fully automated urban traffic. A guidance system that would meet system requirements was not being developed but was technically feasible.

Dobrotin, B. M.↗
NASA NTRS2007

The Naturalistic Flight Deck System: An Integrated System Concept for Improved Single-Pilot Operations

This paper reviews current and emerging operational experiences, technologies, and human-machine interaction theories to develop an integrated flight system concept designed to increase the safety, reliability, and performance of single-pilot operations in an increasingly accommodating but stringent national airspace system. This concept, know as the Naturalistic Flight Deck (NFD), uses a form of human-centered automation known as complementary-automation (or complemation) to structure the relationship between the human operator and the aircraft as independent, collaborative agents having complimentary capabilities. The human provides commonsense knowledge, general intelligence, and creative thinking, while the machine contributes specialized intelligence and control, extreme vigilance, resistance to fatigue, and encyclopedic memory. To support the development of the NFD, an initial Concept of Operations has been created and selected normal and non-normal scenarios are presented in this document.

Schutte, Paul C.↗
NASA NTRS2000

Multi-Agent Diagnosis and Control of an Air Revitalization System for Life Support in Space

An architecture of interoperating agents has been developed to provide control and fault management for advanced life support systems in space. In this adjustable autonomy architecture, software agents coordinate with human agents and provide support in novel fault management situations. This architecture combines the Livingstone model-based mode identification and reconfiguration (MIR) system with the 3T architecture for autonomous flexible command and control. The MIR software agent performs model-based state identification and diagnosis. MIR identifies novel recovery configurations and the set of commands required for the recovery. The AZT procedural executive and the human operator use the diagnoses and recovery recommendations, and provide command sequencing. User interface extensions have been developed to support human monitoring of both AZT and MIR data and activities. This architecture has been demonstrated performing control and fault management for an oxygen production system for air revitalization in space. The software operates in a dynamic simulation testbed.

Malin, Jane T.↗