Results for “human systems performance” — Page 45

NASA NTRS1991

ALLY: An operator's associate for satellite ground control systems

The key characteristics of an intelligent advisory system is explored. A central feature is that human-machine cooperation should be based on a metaphor of human-to-human cooperation. ALLY, a computer-based operator's associate which is based on a preliminary theory of human-to-human cooperation, is discussed. ALLY assists the operator in carrying out the supervisory control functions for a simulated NASA ground control system. Experimental evaluation of ALLY indicates that operators using ALLY performed at least as well as they did when using a human associate and in some cases even better.

Bushman, J. B.↗

NASA NTRS1992

1991 NASA Life Support Systems Analysis workshop

The 1991 Life Support Systems Analysis Workshop was sponsored by NASA Headquarters' Office of Aeronautics and Space Technology (OAST) to foster communication among NASA, industrial, and academic specialists, and to integrate their inputs and disseminate information to them. The overall objective of systems analysis within the Life Support Technology Program of OAST is to identify, guide the development of, and verify designs which will increase the performance of the life support systems on component, subsystem, and system levels for future human space missions. The specific goals of this workshop were to report on the status of systems analysis capabilities, to integrate the chemical processing industry technologies, and to integrate recommendations for future technology developments related to systems analysis for life support systems. The workshop included technical presentations, discussions, and interactive planning, with time allocated for discussion of both technology status and time-phased technology development recommendations. Key personnel from NASA, industry, and academia delivered inputs and presentations on the status and priorities of current and future systems analysis methods and requirements.

Evanich, Peggy L.↗

NASA NTRS2006

Integrated Human-Robotic Missions to the Moon and Mars: Mission Operations Design Implications

For most of the history of space exploration, human and robotic programs have been independent, and have responded to distinct requirements. The NASA Vision for Space Exploration calls for the return of humans to the Moon, and the eventual human exploration of Mars; the complexity of this range of missions will require an unprecedented use of automation and robotics in support of human crews. The challenges of human Mars missions, including roundtrip communications time delays of 6 to 40 minutes, interplanetary transit times of many months, and the need to manage lifecycle costs, will require the evolution of a new mission operations paradigm far less dependent on real-time monitoring and response by an Earthbound operations team. Robotic systems and automation will augment human capability, increase human safety by providing means to perform many tasks without requiring immediate human presence, and enable the transfer of traditional mission control tasks from the ground to crews. Developing and validating the new paradigm and its associated infrastructure may place requirements on operations design for nearer-term lunar missions. The authors, representing both the human and robotic mission operations communities, assess human lunar and Mars mission challenges, and consider how human-robot operations may be integrated to enable efficient joint operations, with the eventual emergence of a unified exploration operations culture.

Korth, David↗

NASA NTRS2007

Upgrades to the NESS (Nuclear Engine System Simulation) Code

In support of the President's Vision for Space Exploration, the Nuclear Thermal Rocket (NTR) concept is being evaluated as a potential propulsion technology for human expeditions to the moon and Mars. The need for exceptional propulsion system performance in these missions has been documented in numerous studies, and was the primary focus of a considerable effort undertaken during the 1960's and 1970's. The NASA Glenn Research Center is leveraging this past NTR investment in their vehicle concepts and mission analysis studies with the aid of the Nuclear Engine System Simulation (NESS) code. This paper presents the additional capabilities and upgrades made to this code in order to perform higher fidelity NTR propulsion system analysis and design.

Fittje, James E.↗

NASA NTRS2007

Integrated Human-Robotic Missions to the Moon and Mars: Mission Operations Design Implications

For most of the history of space exploration, human and robotic programs have been independent, and have responded to distinct requirements. The NASA Vision for Space Exploration calls for the return of humans to the Moon, and the eventual human exploration of Mars; the complexity of this range of missions will require an unprecedented use of automation and robotics in support of human crews. The challenges of human Mars missions, including roundtrip communications time delays of 6 to 40 minutes, interplanetary transit times of many months, and the need to manage lifecycle costs, will require the evolution of a new mission operations paradigm far less dependent on real-time monitoring and response by an Earthbound operations team. Robotic systems and automation will augment human capability, increase human safety by providing means to perform many tasks without requiring immediate human presence, and enable the transfer of traditional mission control tasks from the ground to crews. Developing and validating the new paradigm and its associated infrastructure may place requirements on operations design for nearer-term lunar missions. The authors, representing both the human and robotic mission operations communities, assess human lunar and Mars mission challenges, and consider how human-robot operations may be integrated to enable efficient joint operations, with the eventual emergence of a unified exploration operations culture.

human robotic missions↗

NASA NTRS2012

Application of System Operational Effectiveness Methodology to Space Launch Vehicle Development and Operations

The Department of Defense (DoD) defined System Operational Effectiveness (SOE) model provides an exceptional framework for an affordable approach to the development and operation of space launch vehicles and their supporting infrastructure. The SOE model provides a focal point from which to direct and measure technical effectiveness and process efficiencies of space launch vehicles. The application of the SOE model to a space launch vehicle's development and operation effort leads to very specific approaches and measures that require consideration during the design phase. This paper provides a mapping of the SOE model to the development of space launch vehicles for human exploration by addressing the SOE model key points of measurement including System Performance, System Availability, Technical Effectiveness, Process Efficiency, System Effectiveness, Life Cycle Cost, and Affordable Operational Effectiveness. In addition, the application of the SOE model to the launch vehicle development process is defined providing the unique aspects of space launch vehicle production and operations in lieu of the traditional broader SOE context that examines large quantities of fielded systems. The tailoring and application of the SOE model to space launch vehicles provides some key insights into the operational design drivers, capability phasing, and operational support systems.

Watson, Michael D.↗

NASA NTRS2012

Cognitive Systems Modeling and Analysis of Command and Control Systems

Military operations, counter-terrorism operations and emergency response often oblige operators and commanders to operate within distributed organizations and systems for safe and effective mission accomplishment. Tactical commanders and operators frequently encounter violent threats and critical demands on cognitive capacity and reaction time. In the future they will make decisions in situations where operational and system characteristics are highly dynamic and non-linear, i.e. minor events, decisions or actions may have serious and irreversible consequences for the entire mission. Commanders and other decision makers must manage true real time properties at all levels; individual operators, stand-alone technical systems, higher-order integrated human-machine systems and joint operations forces alike. Coping with these conditions in performance assessment, system development and operational testing is a challenge for both practitioners and researchers. This paper reports on research from which the results led to a breakthrough: An integrated approach to information-centered systems analysis to support future command and control systems research development. This approach integrates several areas of research into a coherent framework, Action Control Theory (ACT). It comprises measurement techniques and methodological advances that facilitate a more accurate and deeper understanding of the operational environment, its agents, actors and effectors, generating new and updated models. This in turn generates theoretical advances. Some good examples of successful approaches are found in the research areas of cognitive systems engineering, systems theory, and psychophysiology, and in the fields of dynamic, distributed decision making and naturalistic decision making.

Norlander, Arne↗

NASA NTRS2016

Modeling Relationships Between Flight Crew Demographics and Perceptions of Interval Management

The Interval Management Alternative Clearances (IMAC) human-in-the-loop simulation experiment was conducted to assess interval management system performance and participants' acceptability and workload while performing three interval management clearance types. Twenty-four subject pilots and eight subject controllers flew ten high-density arrival scenarios into Denver International Airport during two weeks of data collection. This analysis examined the possible relationships between subject pilot demographics on reported perceptions of interval management in IMAC. Multiple linear regression models were created with a new software tool to predict subject pilot questionnaire item responses from demographic information. General patterns were noted across models that may indicate flight crew demographics influence perceptions of interval management.

Remy, Benjamin↗

NASA NTRS2006

Integrated human-robotic missions to the Moon and Mars : mission operations design implications

For most of the history of space exploration, human and robotic programs have been independent, and have responded to distinct requirements. The NASA Vision for Space Exploration calls for the return of humans to the Moon, and the eventual human exploration of Mars; the complexity of this range of missions will require an unprecedented use of automation and robotics in support of human crews. The challenges of human Mars missions, including roundtrip communications time delays of 6 to 40 minutes, interplanetary transit times of many months, and the need to manage lifecycle costs, will require the evolution of a new mission operations paradigm far less dependent on real-time monitoring and response by an Earthbound operations team. Robotic systems and automation will augment human capability, increase human safety by providing means to perform many tasks without requiring immediate human presence, and enable the transfer of traditional mission control tasks from the ground to crews. Developing and validating the new paradigm and its associated infrastructure may place requirements on operations design for nearer-term lunar missions. The authors, representing both the human and robotic mission operations communities, assess human lunar and Mars mission challenges, and consider how human-robot operations may be integrated to enable efficient joint operations, with the eventual emergence of a unified exploration operations culture.

Lee, Young↗

NASA NTRSDate not supplied

Human Systems Integration: Capturing the Human Element in Technology Development

Provide a high-level awareness of the Human Systems Integration(HSI) process and the human readiness complement of technology readiness level(TRL) to manage and maximizing system performance.

George Salazar↗

NASA NTRS2024

Navigation Performance Overview of Gateway During a Lunar Lander Mission

Starting with Artemis IV, the human lander system (HLS) missions will utilize the Gateway as a staging point in a near rectilinear halo orbit (NRHO) between cislunar space and the lunar surface. The presence of a crew, Orion, and HLS will cause significant perturbations from docking and venting, while attitude requirements on Gateway can cause structural antenna blockage. The HLS mission timeline and perturbations are simulated considering antenna blockage to ground stations. Simulated DSN tracking data is generated and processed to produce a navigation state estimate for orbit maintenance maneuver (OMM) targeting. The starting epoch is varied to adjust tracking availability, and the volume of tracking data processed is reduced. Separately, the observability of perturbations in the NRHO with two-way tracking data is analyzed. The mission is simulated with imperfect knowledge of venting perturbations, and finally the estimation errors from propagating an estimated state from data cutoff (DCO) to maneuvers are investigated.

Clark P Newman↗

NASA NTRS2024

Key Considerations When Developing Avionics for Safety-Critical Systems

Multiple human spaceflight programs are underway at NASA including Orion, Space Launch System, Gateway, Human Landing System, and EVA and Lunar Surface Mobility programs. Achieving success in these programs requires NASA to collaborate with a variety of commercial partners, including both new spaceflight companies and robotic spaceflight companies pursuing crewed spaceflight for the first time. It is not always clear to these organizations how to show their systems are safe for human spaceflight. This is particularly true for avionics systems, which are responsible for performing some of a crewed spacecraft’s most critical functions. NASA recently published guidance describing how to show the design of an avionic system meets safety requirements for crewed missions.

Safety-Critical Systems↗

DOE OSTI2020

Artificial Intelligence Application to D and D - 20492

As aging facilities across the DOE complex await decommissioning, there is an ongoing need to understand any changes in the structural conditions. Many of these facilities were built over 50 years ago and, in some cases, these facilities have gone beyond the expected operational lifetime. Many facilities have been placed in a state of 'cold and dark,' sitting unused and awaiting decommissioning. Especially challenging are the aging facilities that provide unique operational/production capabilities to support critical DOE missions and cannot be shut down. In any of these scenarios, the structural integrity of these facilities may become compromised as time passes. It is critical that adequate inspections be performed on a continual basis and that the data collected undergoes sufficient analysis to support timely identification of any new or worsening structural issues as well as prompt needed maintenance and repairs to maintain the facilities in a safe condition. In recent days, Artificial Intelligence (AI) [1] and its application to various domains are growing at fast speed. FIU is performing research in this area and exploring the associated technologies to solve nuclear decommissioning problems. Artificial intelligence refers to the capability of a program to autonomously act, react and adapt to the working environment. AI enables the machine to behave like humans and perform the cognitive functions such as 'learning' and 'problem solving'. AI systems gradually moving from traditional approaches (algorithms and expert systems) towards more efficient and advanced technologies (machine learning [1] and deep learning [2] [3]). AI is the study of algorithms and statistical models that is being used by computers to perform specific tasks without using explicit instructions. FIU is working to develop a pilot-scale infrastructure to implement structural health monitoring using AI technologies with focus on machine learning, deep learning. This research is focused on Computer Vision/Image Classification area of AI applications. This can also be expanded to other areas of AI related to Object Recognition and Character Recognition in images. In addition to utilizing existing data sets, FIU will collect and investigate image and video data using FIU test-bed mockups to monitor structural health of the facility. Resulting data will be processed and analyzed using machine learning/deep learning technologies. The proposed pilot system is intended to serve as a starting point to engage the DOE field sites on related data sets and their decision making needs. It is anticipated that proposed machine learning/deep learning technologies can be effectively employed using anomaly detection to solve EM challenges in surveillance and maintenance of the D and D facilities. FIU will work with research stakeholders to identify applications at various sites and other DOE facilities. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS2014

NASA Extreme Environment Mission Operations: Science Operations Development for Human Exploration

The purpose of NASA Extreme Environment Mission Operations (NEEMO) mission 16 in 2012 was to evaluate and compare the performance of a defined series of representative near-Earth asteroid (NEA) extravehicular activity (EVA) tasks under different conditions and combinations of work systems, constraints, and assumptions considered for future human NEA exploration missions. NEEMO 16 followed NASA's 2011 Desert Research and Technology Studies (D-RATS), the primary focus of which was understanding the implications of communication latency, crew size, and work system combinations with respect to scientific data quality, data management, crew workload, and crew/mission control interactions. The 1-g environment precluded meaningful evaluation of NEA EVA translation, worksite stabilization, sampling, or instrument deployment techniques. Thus, NEEMO missions were designed to provide an opportunity to perform a preliminary evaluation of these important factors for each of the conditions being considered. NEEMO 15 also took place in 2011 and provided a first look at many of the factors, but the mission was cut short due to a hurricane threat before all objectives were completed. ARES Directorate (KX) personnel consulted with JSC engineers to ensure that high-fidelity planetary science protocols were incorporated into NEEMO mission architectures. ARES has been collaborating with NEEMO mission planners since NEEMO 9 in 2006, successively building upon previous developments to refine science operations concepts within engineering constraints; it is expected to continue the collaboration as NASA's human exploration mission plans evolve.

Bell, Mary S.↗

NASA NTRSDate not supplied

Trajectory Shaping of Lunar Descent Approach Phase for Human Landing Systems

NASA’s Artemis program will have many mission phases but perhaps the most dangerous and dynamic is the powered descent and landing phase. NASA’s HLS Program has developed a candidate lunar approach concept of operations to address the needs of both hazard detection sensors and crew visibility of the landing site. The descent trajectory is shaped such that the approach phase is initiated at a steep trajectory path angle for hazard map generation then transitions to a shallow trajectory path angle to facilitate crew landing site visibility. The results show this tailored approach concept is a viable option to reduce risk during landing with minimal performance impacts.

Trajectory Optimization↗

NASA NTRS2016

Design of Photovoltaic Power System for a Precursor Mission for Human Exploration of Mars

This project analyzed the viability of a photovoltaic power source for technology demonstration mission to demonstrate Mars in-situ resource utilization (ISRU) to produce propellant for a future human mission, based on technology available within the next ten years. For this assessment, we performed a power-system design study for a scaled ISRU demonstrator lander on the Mars surface based on existing solar array technologies.

solar cells↗

NASA NTRSDate not supplied

Cryogenic Insulation Solutions for the Surface of Mars with Its Unique Environments

The surface of Mars provides unique challenges for cryogenic insulation systems and for cryogenic spacecraft traveling there. In order to store cryogenic fluids for propulsion, life support, and other applications on the surface of Mars one must protect the insulation from the array of unique environmental factors that are present. Travel to Mars is a very energy intensive endeavor and landing on the surface requires launching over 200 kg of propellant and spacecraft per kilogram landed. As such, high performance, lightweight insulations are needed for cryogenic systems to be used on the surface. Traditional spacecraft use multilayer insulation that works well in a vacuum, but Mars has an atmospheric of pressure approximately 7 torr, consisting of approximately 95 % carbon dioxide. Based on analysis and trade studies NASA has shown that the mass savings from the higher performance of multilayer insulation with a vacuum jacket saved several hundred kilograms of mass for a typical human Mars ascent stage. Thus NASA, along with several contractors, have been developing a lightweight vacuum jacketed system for the 7 torr environment. This lightweight vacuum jacketed system must survive launch from earth, travel to Mars, and on the surface for several years. On the surface, it must be able to survive landing, natural environmental occurrences such as dust storms, and temperature cycling with minimal if any human maintenance. The insulation systems under development have been exposed to an array of tests to demonstrate their capability to survive these environments while still providing the high performance required to meet mission needs.

Cryogenic Fluid Management↗

DOE OSTI2026

From Rules to Reasoning: A Survey of Large Language Model-Based Approaches to Scientific Hypothesis and Idea Generation

Scientific hypothesis generation represents a fundamental challenge in contemporary research due to exponentially expanding literature volumes and increasing disciplinary specialization. Large language models (LLMs) have emerged as transformative tools for automated scientific discovery, moving beyond traditional rule-based and literature-mining approaches. Four paradigmatic approaches define current LLM-driven hypothesis generation: direct prompting and fine-tuning methods, knowledge-enhanced frameworks integrating retrieval-augmented generation (RAG), multi-agent collaborative systems simulating research teams, and reasoning-focused approaches implementing cognitive architectures. Domain-specific applications demonstrate statistical equivalence to human expert performance in social psychology, experimental validation in biomedical research, and near-expert quality in astronomy. Evaluation methodologies encompass human expert assessment, LLM-as-judge frameworks, and comprehensive benchmarking systems. Technical challenges include hallucination management, knowledge integration limitations, and balancing novelty with feasibility. Future directions emphasize hybrid neural-symbolic architectures and sophisticated human-AI collaboration models for responsible scientific discovery acceleration.

AI-driven discovery↗