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NASA NTRS2018

Human-Automation Allocations for Current Robotic Space Operations

Within the Human Research Program, one risk delineates the uncertainty surrounding crew working with automation and robotics in spaceflight. The Risk of Inadequate Design of Human and Automation/Robotic Integration (HARI) is concerned with the detrimental effects on crew performance due to ineffective user interfaces, system designs and/or functional task allocation, potentially compromising mission success and safety. Risk arises because we have limited experience with complex automation and robotics. One key gap within HARI, is the gap related to functional allocation. The gap states: We need to evaluate, develop, and validate methods and guidelines for identifying human-automation/robot task information needs, function allocation, and team composition for future long duration, long distance space missions. Allocations determine the human-system performance as it identifies the functions and performance levels required by the automation/robotic system, and in turn, what work the crew is expected to perform and the necessary human performance requirements. Allocations must take into account each of the human, automation, and robotic systems capabilities and limitations. Some functions may be intuitively assigned to the human versus the robot, but to optimize efficiency and effectiveness, purposeful role assignments will be required. The role of automation and robotics will significantly change in future exploration missions, particularly as crew becomes more autonomous from ground controllers. Thus, we must understand the suitability of existing function allocation methods within NASA as well as the existing allocations established by the few robotic systems that are operational in spaceflight. In order to evaluate future methods of robotic allocations, we must first benchmark the allocations and allocation methods that have been used. We will present 1) documentation of human-automation-robotic allocations in existing, operational spaceflight systems; and 2) To gather existing lessons learned and best practices in these role assignments, from spaceflight operational experience of crew and ground teams that may be used to guide development for future systems. NASA and other space agencies have operational spaceflight experience with two key Human-Automation-Robotic (HAR) systems: heavy lift robotic arms and planetary robotic explorers. Additionally, NASA has invested in high-fidelity rover systems that can carry crew, building beyond Apollo's lunar rover. The heavy lift robotic arms reviewed are: Space Station Remote Manipulator System (SSRMS), Japanese Remote Manipulator System (JEMRMS), and the European Robotic Arm (ERA, designed but not deployed in space). The robotic rover systems reviewed are: Mars Exploration Rovers, Mars Science Laboratory rover, and the high-fidelity K10 rovers. Much of the design and operational feedback for these systems have been communicated to flight controllers and robotic design teams. As part of the mitigating the HARI risk for future human spaceflight operations, we must document function allocations between robots and humans that have worked well in practice.

robotic allocation↗

NASA NTRSDate not supplied

Sensorimotor Application of Proposed Methods to Combine the Effects of Multiple Countermeasures for PRisM

Risk associated with human systems is challenging to quantify but is critical for the mission planning and decision making required to enable future Lunar and Martian missions. To address this gap, the Crew Health and Performance-Probabilistic Risk Assessment (CHP-PRA) project is developing an integrated computational model for CHP mission risk. Much like how MEDPRAT is designed to allow medical resource trades informed by medical risk, CHP-PRA will enable analogous trades in human system risks across multiple CHP functions and capabilities. Human performance is one component of the risk intended to be captured by CHP-PRA through the Performance Risk Model (PRisM). The sensorimotor risk area provides a good frame of reference for investigating the structure of a performance model because most tasks that astronauts are expected to perform require input from the sensory system and/or movement/motor control. Additionally, sensorimotor countermeasures are an area of particular concern for NASA’s Human Research Program because of the increased sensorimotor risk associated with surface operations in Lunar and Martian missions. Thus, a tool that can quickly compare risk reductions of potential countermeasures would be beneficial in guiding research and development of effective countermeasures. In this proof of concept, we present a systematic way to combine multiple performance data sets for humans subjected to different countermeasures such that we can predict the countermeasure(s) that optimize astronaut performance on relevant tasks. PRisM assumes that both the tests that are used to measure countermeasure effectiveness (input data) and the tasks we use to represent astronaut performance, can be broken down and represented as a function/vector of the human systems required to perform that test/task. Through mathematical combination, test data are used to predict performance on astronaut tasks that use similar systems. We propose that when combining countermeasures evaluated using the same test, that only one value should be used to represent their combined effectiveness. We start our analysis with the assumption that two countermeasures together will perform better than each countermeasure individually. Our initial implementation of this framework compares various space motion sickness countermeasures and the most up to date analysis will be demonstrated at the IWS.

Caroline R Austin↗

DOE OSTI2026

Ten questions concerning Large Language Models (LLMs) for building applications

Large Language Models (LLMs) are emerging as powerful AI tools capable of transforming how building information is collected, processed, analyzed, and applied across diverse research areas. Their capabilities can help building operators, facility managers and other stakeholders such as designers, architects and engineers by providing actionable insights for decision-making across planning, construction, operations, and maintenance of buildings and facilities. This paper explores ten key questions concerning the role of LLMs in shaping sustainable, intelligent, and human-centric buildings. From fundamental definitions to advanced applications, we examine how LLMs facilitate decision-making across the life cycle of buildings and energy systems. LLMs can enhance life cycle assessments (LCA), building energy simulations, and real-time data integration, empowering more efficient and adaptive human-AI environments. They can also contribute to streamlining regulatory compliance, improving post-occupancy evaluations, and fostering more inclusive and participatory design processes. Additionally, this paper addresses the ethical challenges posed by LLMs, such as bias, data privacy, and environmental impacts, and explores their potentials in advancing intelligent digital twins (DT) for ongoing building operations and maintenance. Built upon our applied research using LLMs and the review of tools, datasets, and research gaps, we provide a forward-looking perspective on how LLMs can drive innovation, collaboration, and productivity in the built environment while supporting ethical and effective implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2008

International Space Station Medical Project

The goals and objectives of the ISS Medical Project (ISSMP) are to: 1) Maximize the utilization the ISS and other spaceflight platforms to assess the effects of longduration spaceflight on human systems; 2) Devise and verify strategies to ensure optimal crew performance; 3) Enable development and validation of a suite of integrated physical (e.g., exercise), pharmacologic and/or nutritional countermeasures against deleterious effects of space flight that may impact mission success or crew health. The ISSMP provides planning, integration, and implementation services for Human Research Program research tasks and evaluation activities requiring access to space or related flight resources on the ISS, Shuttle, Soyuz, Progress, or other spaceflight vehicles and platforms. This includes pre- and postflight activities; 2) ISSMP services include operations and sustaining engineering for HRP flight hardware; experiment integration and operation, including individual research tasks and on-orbit validation of next generation on-orbit equipment; medical operations; procedures development and validation; and crew training tools and processes, as well as operation and sustaining engineering for the Telescience Support Center; and 3) The ISSMP integrates the HRP approved flight activity complement and interfaces with external implementing organizations, such as the ISS Payloads Office and International Partners, to accomplish the HRP's objectives. This effort is led by JSC with Baseline Data Collection support from KSC.

Starkey, Blythe A.↗

NASA NTRS1986

Hybrid routing technique for a fault-tolerant, integrated information network

The evolutionary growth of the space station and the diverse activities onboard are expected to require a hierarchy of integrated, local area networks capable of supporting data, voice, and video communications. In addition, fault-tolerant network operation is necessary to protect communications between critical systems attached to the net and to relieve the valuable human resources onboard the space station of time-critical data system repair tasks. A key issue for the design of the fault-tolerant, integrated network is the development of a robust routing algorithm which dynamically selects the optimum communication paths through the net. A routing technique is described that adapts to topological changes in the network to support fault-tolerant operation and system evolvability.

Meredith, B. D.↗

NASA NTRS2019

Hybrid Transportation System Integrated Trajectory Design and Optimization for Mars Landing Site Accessibility

NASA’s Mars Study Capability Team continues the agency’s efforts to study and refine the nation’s plan to field a sustainable human Mars campaign. One of the primary open issues left unanswered during previous analysis cycles was the uncertainty of the impact to the vehicle performance requirement to deliver crew and cargo to the same landing site across multiple mission opportunities. The Mars Study Capability Team has recently developed an integrated trajectory optimization and system closure model to solve the complex interplanetary trajectory optimization using both low-thrust and high-thrust maneuvers. This paper demonstrates the capability of this new integrated trajectory design and optimization method as it applies to the landing site accessibility problem for the Hybrid transportation architecture. The results showed that the current vehicle is capable of reaching up to +20 degree latitude and down to -20 degree latitude in every mission opportunity from 2033 to 2052. However, reaching latitudes beyond +/- 20 required more propellant than the spacecraft is currently designed to carry for many of the mission opportunities.

Chai, Patrick R.↗

DOE OSTI2025

An Integrated Hydroclimatic Assessment of Future Reservoir and Hydropower Operations in the U.S.

The engineering of rivers by dams is a formative feature of human-nature systems and the interconnectivity of water, energy, and the climate. Sufficient and broad-based representations of dams in large-scale hydrological models prove essential to mapping their extensive regulation of river flow and biogeochemistry and gauging climate-linked provisions, including freshwater supply and hydropower. We present an integrated modeling framework to investigate future streamflow and hydropower generation in the Contiguous U.S. (1990–2075), leveraging an ensemble of six downscaled and bias-corrected General Circulation Models (GCMs) from the high-end SSP585 scenario of the CMIP6. To achieve this, we develop a reservoir operations and parameterization scheme for 1,384 dams in a high-resolution river network, including simulated hydropower generation for 326 dams. For the GCM ensemble mean, we simulate a widespread increase in regulated streamflow into the late-century (11% annual and 17% in winter for the dam median) with region-specific changes in summer streamflow that feature prominent declines in the Northwest (−7%). Mediation by reservoirs is shown to dampen intra-annual streamflow changes, delivering additional summer releases that partially mitigate declining flows. Total hydropower generation is projected to increase modestly (+3%), with boosted generation in the winter (+9%) and spring (+5%) offsetting declined summer generation (−3.4%), suggesting strong adaptation potential for hydropower in the future energy portfolio. Further analysis reveals that the choice of GCM, particularly in western regions, has significant bearing on projected streamflow and hydropower changes.

13 HYDRO ENERGY↗

DOE OSTI2021

Using machine learning to improve land use/cover characterization and projection for scenario-based global modeling

The characterization of the land surface in models is critical for robust estimation of the water cycle and associated extremes. Land use determines water demand, and land cover affects water availability. The interaction between water demand and availability is the key determinant of whether systems are resilient to variability in the overall water cycle. Furthermore, activities such as irrigation and deforestation or afforestation may influence regional to global precipitation patterns, depending on the extent of the activity. Thus this proposed work aims to address the following question: How does integrated land use/cover data and improved land use/cover projection, as informed by machine learning approaches, better resolve human-earth system resilience to water cycle variability and extremes?

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2023

Research and Technology Challenges for Human Data Analysts in Future Safety Management Systems

Enabling new and novel concepts of operations for Advanced Air Mobility poses an important need to evolve current safety management systems (SMS) and is posited to be realized through advances in Machine Learning (ML) Data Sciences and Artificial Intelligence. The “In-time Aviation Safety Management System” (IASMS) concept of operations supports the need to evolve today’s SMS to become more tailorable, scalable, and interoperable in response to forecasted changes expected for the future airspace system. Key to IASMS is integration of proactive and predictive ML algorithms trained to provide “in time” detection and mitigation of hazards and emergent risks through new methods and novel data types. IASMS research and technology development includes human factors design considerations for these systems to include human-system teaming, innovations in human interfaces and management of complex digital data information, human-system interaction/model-based system engineering, and verification and validation for data assurance and trust.

Chad L Stephens↗

DOE OSTI2023

Mobility Energy Productivity and Equity: E-Bike Impacts for Low-Income Essential Workers in Denver

New mobility technologies such as electrified and shared mobility, combined with polices and incentive programs, are emerging to help address sustainability and equity issues in transportation planning. However, it can be difficult to understand the impacts of novel mobility trends and emerging modes on energy-efficient access. This is owing to a lack of (1) open-source tools enabling rapid data collection, and (2) open-source metrics that consider multimodal, multiactivity access and mobility within the contexts of sustainability and equity. Here, this paper addresses the topic of improving evaluation of transportation modes and incentive programs by integrating an open-source platform for tracking human travel data—the Open Platform for Agile Trip Heuristics (OpenPATH)—with a mobility metric that quantifies the efficiency of a region’s transportation system: Mobility Energy Productivity (MEP). Integration is demonstrated in the context of pilot programs in Colorado, where low-income essential workers were provided with electric bikes (e-bikes). OpenPATH-informed MEP calculations showed that several locations in downtown Denver provided comparable time-, cost-, and energy-efficient access to opportunities using e-bikes compared with driving. Additionally, providing e-bikes to low-income essential workers was found to be meaningful, as they utilized e-bikes the most to commute, despite driving still being their most utilized mode and the mode with highest MEP scores in Denver. We show how data collected from open-source tools coupled with robust metrics such as MEP can help evaluate the impacts of emerging mobility options. This could support developing policies to incentivize novel modes to achieve greater levels of sustainable, equitable, and efficient access.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS1993

The implementation of the Human Exploration Demonstration Project (HEDP), a systems technology testbed

The Human Exploration Demonstration Project (HEDP) is an ongoing task at the NASA's Ames Research Center to address the advanced technology requirements necessary to implement an integrated working and living environment for a planetary surface habitat. The integrated environment consists of life support systems, physiological monitoring of project crew, a virtual environment work station, and centralized data acquisition and habitat systems health monitoring. The HEDP is an integrated technology demonstrator, as well as an initial operational testbed. There are several robotic systems operational in a simulated planetary landscape external to the habitat environment, to provide representative work loads for the crew. This paper describes the evolution of the HEDP from initial concept to operational project; the status of the HEDP after two years; the final facilities composing the HEDP; the project's role as a NASA Ames Research Center systems technology testbed; and the interim demonstration scenarios that have been run to feature the developing technologies in 1993.

Rosen, Robert↗

NASA NTRSDate not supplied

Capability Gaps Assessment and Identification of Critical Technology Elements for Mars Transit Habitat

The Habitation Systems Development Office (HP40) at NASA Marshall Space Flight Center supports systems engineering, integration, and project management for next generation space habitats. For in space operations and eventual transport of humans to Mars, NASA will rely on a Mars Transit Habitat (TH). The TH will be designed for an up to 1,200-day Mars mission and will carry all food and supplies needed to support four crew for this duration. In the current concept of operations, Mars TH transfers to near rectilinear halo orbit (NRHO) following launch and docks at Gateway as a visiting vehicle. While there, the TH will complete system shakedown testing and a series of analog missions which will grow from 3 to 6+ months in duration TH also augments Gateway’s habitation capabilities beyond 60-days. Proposed Gateway-TH missions will far exceed the longest duration cislunar human missions to date. These shakedown missions will also be the first operational readiness tests of Mars TH’s long-duration deep space systems, and of the split crew (two crew on the surface, two crew in space) operations that are vital to the approach for the first human Mars mission. Once shakedown missions are complete, Mars TH departs Gateway to aggregate with the Mars propulsion system in NRHO before onboarding the crew and final supplies in Earth orbit via a co-manifested Orion-logistics module. Orion and the LM return to Earth prior to the now aggregated Deep Space Transport vehicle’s journey to Mars. Development of the Mars TH requires significant technology development and maturation. Each year the agency performs a capability gaps assessment, where gaps developed by subject matter experts (SMEs) in various engineering/science disciplines are linked to architectural elements in formulation and prioritized. A gap captures the difference between the current state-of-the-art and the maturity of the capability that is needed to enable or enhance a mission as it is currently envisioned in the government reference architecture. HP40 conducted a gap analysis for Mars TH which will be summarized in this poster. Gaps classified as enabling (which means the mission cannot achieve success without gap closure) were subsequently used to identify critical technology elements (CTEs) for Mars TH. This identification of CTEs was also informed by an examination of the product breakdown structure for Mars TH and focused conversations with SMEs in specific technology areas. CTEs identified for Mars TH to date include the following (note this is not a comprehensive list – CTEs listed represent those in MSFC’s capability areas): inflatable softgoods for habitation; enhanced CO2 recovery; life support systems with greater levels of reliability and maintainability; autonomous guidance, navigation, command and control; and radiators for the Mars TH application. The habitation systems development team is currently delving deeper into each CTE to assess technology approaches being pursued, their maturity, and the degree of difficulty in maturation to meet projected Mars TH timelines. This poster will summarize work to date on the identification of enabling capability gaps linked to Mars TH and provide insight into the associated CTEs and technology maturation efforts.

technology development↗

NASA NTRS2015

An Integrated Hybrid Transportation Architecture for Human Mars Expeditions

NASA's Human Spaceflight Architecture Team is developing a reusable hybrid transportation architecture that uses both chemical and electric propulsion systems on the same vehicle to send crew and cargo to Mars destinations such as Phobos, Deimos, the surface of Mars, and other orbits around Mars. By applying chemical and electrical propulsion where each is most effective, the hybrid architecture enables a series of Mars trajectories that are more fuel-efficient than an all chemical architecture without significant increases in flight times. This paper presents an integrated Hybrid in-space transportation architecture for piloted missions and delivery of cargo. A concept for a Mars campaign including orbital and Mars surface missions is described in detail including a system concept of operations and conceptual design. Specific constraints, margin, and pinch points are identified for the architecture and opportunities for critical path commercial and international collaboration are discussed.

Merrill, Raymond G.↗

NASA NTRS1987

Space Station data management system architecture

Within the Space Station program, the Data Management System (DMS) functions in a dual role. First, it provides the hardware resources and software services which support the data processing, data communications, and data storage functions of the onboard subsystems and payloads. Second, it functions as an integrating entity which provides a common operating environment and human-machine interface for the operation and control of the orbiting Space Station systems and payloads by both the crew and the ground operators. This paper discusses the evolution and derivation of the requirements and issues which have had significant effect on the design of the Space Station DMS, describes the DMS components and services which support system and payload operations, and presents the current architectural view of the system as it exists in October 1986; one-and-a-half years into the Space Station Phase B Definition and Preliminary Design Study.

Mallary, William E.↗

DOE OSTI2023

Alignment among environmental programs in higher education: What Food-Energy-Water Nexus concepts are covered in introductory courses?

Interdisciplinary environmental and sustainability (IES) programs are different from other fields because they focus on a complex integration of humanities, social, and natural sciences concepts centered on the interactions of coupled human and natural systems. The interdisciplinary nature of IES programs does not lend itself to traditional discipline-specific concept inventory frameworks for critically evaluating preconceptions and learning. We discuss the results of the first phase of a research project to develop a next generation concept inventory for evaluating interdisciplinary concepts important for introductory IES courses. Using the Food-Energy-Water (FEW) Nexus (the intersections/interdependencies of food, energy, and water sectors) as our focus, we conducted a content analysis of eight representative college-level introductory environmental course syllabi and course materials (e.g., textbooks, journal articles, print media) to identify common interdisciplinary FEW Nexus concepts taught in introductory IES courses. Results demonstrate that all IES introductory course materials reference the FEW Nexus. Food, energy, and/or water resources as individual elements of the FEW Nexus are frequently described, but connections between these resource systems are included less often. Biology, energy systems, waste and pollution in the natural environment, agriculture, earth sciences and geology, climate change, behavioral social sciences, and economics concepts are most associated with FEW concepts, hinting at commonalities across IES topics that anchor systems thinking. Despite differences in IES programs, there appears to be some alignment between core concepts being taught at the FEW Nexus in introductory courses.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1987

Development of a comprehensive software engineering environment

The generation of a set of tools for software lifecycle is a recurring theme in the software engineering literature. The development of such tools and their integration into a software development environment is a difficult task because of the magnitude (number of variables) and the complexity (combinatorics) of the software lifecycle process. An initial development of a global approach was initiated in 1982 as the Software Development Workbench (SDW). Continuing efforts focus on tool development, tool integration, human interfacing, data dictionaries, and testing algorithms. Current efforts are emphasizing natural language interfaces, expert system software development associates and distributed environments with Ada as the target language. The current implementation of the SDW is on a VAX-11/780. Other software development tools are being networked through engineering workstations.

Hartrum, Thomas C.↗

NASA NTRS1987

Habitability in long-term space missions

The research (both in progress and completed) conducted for the U.S. Space Station in relation to the crew habitability and crew productivity is discussed. Methods and tasks designed to increase the data base of the man/system information are described. The particular research areas discussed in this paper include human productivity, on-orbit maintenance, vewing requirements, fastener types, and crew quarters. This information (along with data obtained on human interaction with command/control work station, anthropometic factors, crew equipment, galley/wardroom, restraint systems, etc) will be integrated into the common data base for the purpose of assisting the design of the Space Station and other future manned space missions.

Mount, Frances E.↗

NASA NTRS1991

Analysis of Issues for Project Scheduling by Multiple, Dispersed Schedulers (distributed Scheduling) and Requirements for Manual Protocols and Computer-based Support

Although computerized operations have significant gains realized in many areas, one area, scheduling, has enjoyed few benefits from automation. The traditional methods of industrial engineering and operations research have not proven robust enough to handle the complexities associated with the scheduling of realistic problems. To address this need, NASA has developed the computer-aided scheduling system (COMPASS), a sophisticated, interactive scheduling tool that is in wide-spread use within NASA and the contractor community. Therefore, COMPASS provides no explicit support for the large class of problems in which several people, perhaps at various locations, build separate schedules that share a common pool of resources. This research examines the issue of distributing scheduling, as applied to application domains characterized by the partial ordering of tasks, limited resources, and time restrictions. The focus of this research is on identifying issues related to distributed scheduling, locating applicable problem domains within NASA, and suggesting areas for ongoing research. The issues that this research identifies are goals, rescheduling requirements, database support, the need for communication and coordination among individual schedulers, the potential for expert system support for scheduling, and the possibility of integrating artificially intelligent schedulers into a network of human schedulers.

Richards, Stephen F.↗