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DOE OSTI2022

Hierarchical Model-Free Transactional Control of Building Loads to Support Grid Services

A transition from generation on demand to consumption on demand is one of the solutions to overcome the many limitations associated with the higher penetration of renewable energy sources. Such a transition, however, requires a considerable amount of load flexibility in the demand side. Demand response (DR) programs can reveal and utilize this demand flexibility by enabling the participation of a large number of grid-interactive efficient buildings (GEB). Existing approaches on DR require significant modelling or training efforts, are computationally expensive, and do not guarantee the satisfaction of end users. To address the aforementioned limitations, this software code considers a scalable hierarchical model-free transactional control approach that incorporates elements of virtual battery, game theory, and model-free control (MFC) mechanisms. The developed approach separates the control mechanism into upper and lower levels. The MFC modulates the flexible GEB in the lower level with guaranteed thermal comfort of end users in response to the optimal pricing and power signals determined in the upper layer using a Stackelberg game integrated with aggregate virtual battery constraints. Additionally, the usage of MFC necessitates less burdensome computational and communication requirements, thus, it is easily deployable even on small, embedded devices. This software code enables the use of residential and small-size commercial buildings to offer a potentially substantial source of ancillary grid services that are currently underutilized. A hierarchical, model-free transactive building control provides a smooth interface between the grid service requests of utilities and the reliable control required by participating buildings. Model-free control, which supports distributed control architecture, will be a more scalable solution that can be deployed in neighborhood-size systems as well as individual buildings. The proposed approach contributes to the body of knowledge on two main aspects. First, it couples the MFC with the game-theoretic control and proposes a scalable model-free transactive control approach. MFC does not require any modeling effort or model training for the various building loads. This is very beneficial since deriving an accurate model for every single unit participating in DR programs and obtaining all the parameters about the units (e.g., thermal coefficients, standby losses) are infeasible. Also, MFC is computationally efficient, easily deployable even on small, embedded devices, and can be implemented in real time. Second, it integrates the concept of virtual battery into DR via the Stackelberg game. The concept of virtual battery enables efficient coordination and aggregation of a large number of flexible GEB with guaranteed thermal comfort of end users.

Olama, Mohammed [Oak Ridge National Lab. (ORNL), O↗

NASA NTRS2016

International Research Results and Accomplishments From the International Space Station - A New Compilation

In 2016, the International Space Station (ISS) partnership published the first-ever compilation of international ISS research publications resulting from research performed on the ISS through 2011 (Expeditions 0 through 30). International Space Station Research Accomplishments: An Analysis of Results. From 2000-2011 is a collection of over 1,200 journal publications that describe ISS research in the areas of biology and biotechnology; Earth and space science; educational activities and outreach; human research; physical sciences; technology development and demonstration; and, results from ISS operations. This paper will summarize the ISS results publications obtained through 2011 on behalf of the ISS Program Science Forum that is made up of senior science representatives across the international partnership. NASA's ISS Program Science office maintains an online experiment database (www.nasa.gov/iss- science) that tracks and communicates ISS research activities across the entire ISS partnership, and it is continuously updated by cooperation and linking with the results tracking activities of each partner. It captures ISS experiment summaries and results and includes citations to the journals, conference proceedings, and patents as they become available. This content is obtained through extensive and regular journal and patent database searches, and input provided by the ISS international partners ISS scientists themselves. The International Space Station Research Accomplishments: An Analysis of Results From 2000-2011 is a testament to the research that was underway even as the ISS laboratory was being built. It rejects the scientific knowledge gained from ISS research, and how it impact the fields of science in both space and traditional science disciplines on Earth. Now, during a time when utilization is at its busiest, and with extension of the ISS through at least 2024, the ISS partners work together to track the accomplishments and the new knowledge gained in a way that will impact humanity like no laboratory on Earth. Examples of the highest pro le publications to date from each discipline will also be presented. As ISS research activities and operations continue, scientific data derived from earlier experiments will continuously be re-examined, refined, and assembled with new data and findings, including data from other fields never considered. New results will be produced, allowing breakthroughs in new areas of research and innovative solutions to problems on Earth. The ISS Program Science Forum will continue to capture and report on these results in the form of journal publications, conference proceedings, and patents. We anticipate that successful ISS research will continue to contribute to the science literature in a way that helps to formulate new hypotheses and conclusions that will enable science advancements across a wide range of scientific disciplines both in space and on Earth.

Ruttley, Tara↗

NASA NTRS1990

NASA ground terminal communication equipment automated fault isolation expert systems

The prototype expert systems are described that diagnose the Distribution and Switching System I and II (DSS1 and DSS2), Statistical Multiplexers (SM), and Multiplexer and Demultiplexer systems (MDM) at the NASA Ground Terminal (NGT). A system level fault isolation expert system monitors the activities of a selected data stream, verifies that the fault exists in the NGT and identifies the faulty equipment. Equipment level fault isolation expert systems are invoked to isolate the fault to a Line Replaceable Unit (LRU) level. Input and sometimes output data stream activities for the equipment are available. The system level fault isolation expert system compares the equipment input and output status for a data stream and performs loopback tests (if necessary) to isolate the faulty equipment. The equipment level fault isolation system utilizes the process of elimination and/or the maintenance personnel's fault isolation experience stored in its knowledge base. The DSS1, DSS2 and SM fault isolation systems, using the knowledge of the current equipment configuration and the equipment circuitry issues a set of test connections according to the predefined rules. The faulty component or board can be identified by the expert system by analyzing the test results. The MDM fault isolation system correlates the failure symptoms with the faulty component based on maintenance personnel experience. The faulty component can be determined by knowing the failure symptoms. The DSS1, DSS2, SM, and MDM equipment simulators are implemented in PASCAL. The DSS1 fault isolation expert system was converted to C language from VP-Expert and integrated into the NGT automation software for offline switch diagnoses. Potentially, the NGT fault isolation algorithms can be used for the DSS1, SM, amd MDM located at Goddard Space Flight Center (GSFC).

Tang, Y. K.↗

NASA NTRS2001

Shift changes, updates, and the on-call architecture in space shuttle mission control

In domains such as nuclear power, industrial process control, and space shuttle mission control, there is increased interest in reducing personnel during nominal operations. An essential element in maintaining safe operations in high risk environments with this 'on-call' organizational architecture is to understand how to bring called-in practitioners up to speed quickly during escalating situations. Targeted field observations were conducted to investigate what it means to update a supervisory controller on the status of a continuous, anomaly-driven process in a complex, distributed environment. Sixteen shift changes, or handovers, at the NASA Johnson Space Center were observed during the STS-76 Space Shuttle mission. The findings from this observational study highlight the importance of prior knowledge in the updates and demonstrate how missing updates can leave flight controllers vulnerable to being unprepared. Implications for mitigating risk in the transition to 'on-call' architectures are discussed.

Non-NASA Center↗

DOE OSTI2022

Cyber-Resilient Distributed Autonomous Energy Grid

The aim of Cyber-Resilient Distributed Autonomous Grid research initiative is to advance fundamental science and engineering approaches for cyber-resilient design, control, and operation of a distributed, highly interconnected, and autonomous energy grid of the future. From increasing penetration of DERs, smart homes and building with highly controllable loads at the distribution layer, to the interconnection of bulk renewables at the transmission layer the fundamental nature of the energy grid is changing, and these changes are enabled by rapid increase in dependence on the communication infrastructure and independent third parties for control and operation of the grid. NREL's Integrated Energy Pathways critical objective correctly identifies that there are fundamental cyber-resilience challenges inherent in the grid's evolution, and this effort is establishing strong and novel integrated cyber-resilience framework and approaches to address these new and fundamental challenges.

controls↗

DOE OSTI2021

The Role of Mobility Data Hubs in an Integrated Decarbonized Transportation Future

The landscape for connected mobility ecosystems is evolving rapidly as information and communication technologies lower the cost and complexity of connecting people to places, integrating transportation modes and collecting data regarding such movements. These developments have been key to unlocking new business opportunities, particularly through mobility services. While the mechanisms for data collection, processing, and transfer have made significant advances in the past decade, the broader landscape of mobility data architectures and data users remains largely unresolved. It is unclear as to whether the result will converge towards a framework that resembles a coherent quilt or a disjointed patchwork of competing visions. Initial approaches to mobility data collection and provisioning have been largely siloed - by mode or software - or held for exclusive use, however several key players are quickly realizing the need and opportunities enabled through integrated mobility data eco-systems, or mobility data hubs as referred to in this paper. As the business case for hosting mobility data hubs evolves, there is great uncertainty regarding their impact to either advance or exacerbate sustainable mobility (e.g., seamless connectivity across modes, decreased energy consumption and greenhouse gas emissions, etc.). Groups such as the United Nations and World Bank have identified data platforms as a key enabler of realizing environmental and social benefits. If designed with decarbonization in mind, we hypothesize that enhanced observability provided by these ever-expanding mobility data hubs can facilitate energy and emissions reductions that are otherwise limited by transactional barriers and knowledge asymmetry that is inherent to a more siloed approach. In this sense, integration of mobility data can help to create a competitive playing field where value is not determined by exclusivity of data, but rather the quality and uniqueness of a given service. The goals of this paper are to 1) identify key players and data architectures that are emerging in a service-based mobility market, 2) explore several use cases where mobility data hubs have enabled greater sustainability outcomes, and 3) discuss key issues that will need to be resolved to fully leverage emerging mobility data hubs towards a sustainable transportation future.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗

NASA NTRSDate not supplied

Using Open Innovation in Reducing Risk to Crews

In the exploration of destinations outside of Earth's neighborhood, specifically Mars, scientific and engineering inquiries have occurred by two means; observations from satellites and observations by landed spacecraft. Satellite observations (Mariner, MRO, Mars Odyssey, provide global-scale spatial and temporal data while landed spacecraft (Viking, Mars Pathfinder, Spirit, Opportunity, Phoenix Mars Lander) investigate highly localized areas of the surface of the planet. In preparation for human exploration, extensive knowledge of the surface and atmospheric environments should be known before the first human leaves Earth. The primary goal of performing reconnaissance on Mars on a sub-global scale is to know as much as possible about the environment to which crews will be subjected. At the current rate of launching and landing probes to Mars, it will take a very long time to understand the surface and atmospheric conditions associated with the regions where prospective crews may land. Meanwhile electronics and electrical systems are rapidly getting smaller. One can argue that to acquire the knowledge of the region, one must take hundreds, maybe thousands of measurements simultaneously. One means to perform such a task is to deploy a swarm of sensors. Such a swarm would perform an in-situ assessment of the region. Imagine a close flyby mission to Mars for example, where mini- to micro-sensors are deposited into the atmosphere over half an orbit or more. The sensors, captured by the atmospheric drag and Martian gravity slowly descend buffeted about by Martian winds and weather until they settle on the surface a great time later (think of how long dust takes to settle). As they descend they communicate a vast array of data; temperature, chemistry, pressure, radiation dose, electric or magnetic properties from a region of the planet and an individual sensor need not measure the same quantity as its neighbors. Initially, they could move at the whim of the environment but later versions could have locomotion or propulsion mechanisms. Humans wouldn't need to decide where the sensors go, the sensors do that for themselves. This is a key strength of a sensor swarm. The intelligence relies on the group not on a decision maker on earth. Real time sensor inputs direct what the swarm considers most interesting to investigate resulting in emergent behavior. We issued a $20,000 challenge to the global innovators to provide solutions as to how such a swarm could be initialized and by what protocols and methodologies by which they operate. Over 400 innovators from 49 countries took a look at the problem, with three receiving partial awards for solutions.

Mel Ferebee↗

DOE OSTI2019

Short-Term Forecasting Across a Network for the Autonomous Wind Farm: Preprint

In an autonomous wind farm, turbines will use information from nearby turbines to achieve wind farm-level objectives such as optimizing the overall performance of a wind farm, ensuring resiliency when other sensors fail, and adapting to changing local conditions. In this paper, the wind farm can be modeled as a network within which turbines (nodes) share information across designated communication channels, with a focus on turbines at the outside of the wind farm capturing local effects and sharing that information with downstream turbines. Understanding of varied inflow conditions can be especially important in complex terrain. This information can be used to monitor turbines, self-organize turbines into groups, and predict the power performance of a wind farm. In particular, this paper describes an autonomous wind farm that incorporates information from local sensors in real time to predict wind speed and wind direction at each turbine over a short-term horizon. Results indicate that the estimate of wind direction can be used to improve the knowledge of the wind speed and direction over the persistence method on a 10- 15-minute time horizon. These short-term forecasts can also be used to facilitate advanced control methods such as feedforward control within a wind farm.

17 WIND ENERGY↗

DOE OSTI2019

Short-Term Forecasting Across a Network for the Autonomous Wind Farm

In an autonomous wind farm, turbines will use information from nearby turbines to achieve wind farm-level objectives such as optimizing the overall performance of a wind farm, ensuring resiliency when other sensors fail, and adapting to changing local conditions. In this paper, the wind farm can be modeled as a network within which turbines (nodes) share information across designated communication channels, with a focus on turbines at the outside of the wind farm capturing local effects and sharing that information with downstream turbines. Understanding of varied inflow conditions can be especially important in complex terrain. This information can be used to monitor turbines, self-organize turbines into groups, and predict the power performance of a wind farm. In particular, this paper describes an autonomous wind farm that incorporates information from local sensors in real time to predict wind speed and wind direction at each turbine over a short-term horizon. Results indicate that the estimate of wind direction can be used to improve the knowledge of the wind speed and direction over the persistence method on a 10-15-minute time horizon. These short-term forecasts can also be used to facilitate advanced control methods such as feedforward control within a wind farm.

17 WIND ENERGY↗

NASA NTRS1978

Use of radio equipment for Space Shuttle navigation

Space Shuttle navigation is defined, in a narrow sense, as the task of maintaining adequate knowledge of vehicle position and velocity. The state of the Orbiter in terms of this goal is described by a vector of at least six elements, three for position and three for velocity, at a given time. These are referred to as the 'state vector' or simply as the state. Shuttle navigation will relay on a blend of ground-based and onboard systems. The onboard systems will be capable of state propagation at all times and will perform state determination during the latter part of the entry from orbit. The ground-based system will be capable of accurate state propagation for free-flight phases. Radio communication will be necessary in order for the ground and onboard capabilities to work as a coordinated system. The use of radio equipment for state determination is discussed for the ascent, orbit, rendezvous, descent, and abort phases of Shuttle missions.

Schiesser, E. R.↗

NASA NTRS1994

Coordinating complex decision support activities across distributed applications

Knowledge-based technologies have been applied successfully to automate planning and scheduling in many problem domains. Automation of decision support can be increased further by integrating task-specific applications with supporting database systems, and by coordinating interactions between such tools to facilitate collaborative activities. Unfortunately, the technical obstacles that must be overcome to achieve this vision of transparent, cooperative problem-solving are daunting. Intelligent decision support tools are typically developed for standalone use, rely on incompatible, task-specific representational models and application programming interfaces (API's), and run on heterogeneous computing platforms. Getting such applications to interact freely calls for platform independent capabilities for distributed communication, as well as tools for mapping information across disparate representations. Symbiotics is developing a layered set of software tools (called NetWorks! for integrating and coordinating heterogeneous distributed applications. he top layer of tools consists of an extensible set of generic, programmable coordination services. Developers access these services via high-level API's to implement the desired interactions between distributed applications.

Adler, Richard M.↗

NASA NTRS2009

Human Factors in Training - Space Flight Resource Management Training

Accidents and incidents show that high workload-induced stress and poor teamwork skills lead to performance decrements and errors. Research on teamwork shows that effective teams are able to adapt to stressful situations, and to reduce workload by using successful strategies for communication and decision making, and through dynamic redistribution of tasks among team members. Furthermore, superior teams are able to recognize signs and symptoms of workload-induced stress early, and to adapt their coordination and communication strategies to the high workload, or stress conditions. Mission Control Center (MCC) teams often face demanding situations in which they must operate as an effective team to solve problems with crew and vehicle during onorbit operations. To be successful as a team, flight controllers (FCers) must learn effective teamwork strategies. Such strategies are the focus of Space Flight Resource Management (SFRM) training. SFRM training in MOD has been structured to include some classroom presentations of basic concepts and case studies, with the assumption that skill development happens in mission simulation. Integrated mission simulations do provide excellent opportunities for FCers to practice teamwork, but also require extensive technical knowledge of vehicle systems, mission operations, and crew actions. Such technical knowledge requires lengthy training. When SFRM training is relegated to integrated simulations, FCers can only practice SFRM after they have already mastered the technical knowledge necessary for these simulations. Given the centrality of teamwork to the success of MCC, holding SFRM training till late in the flow is inefficient. But to be able to train SFRM earlier in the flow, the training cannot rely on extensive mission-specific technical knowledge. Hence, the need for a generic SFRM training framework that would allow FCers to develop basic teamwork skills which are mission relevant, but without the required mission knowledge. Work on SFRM training has been conducted in collaboration with the Expedition Vehicle Division at the Mission Operations Directorate (MOD) and with United Space Alliance (USA) which provides training to Flight Controllers. The space flight resource management training work is part of the Human Factors in Training Directed Research Project (DRP) of the Space Human Factors Engineering (SHFE) Project under the Space Human Factors and Habitability (SHFH) Element of the Human Research Program (HRP). Human factors researchers at the Ames Research Center have been investigating team work and distributed decision making processes to develop a generic SFRM training framework for flight controllers. The work proposed for FY10 continues to build on this strong collaboration with MOD and the USA Training Group as well as previous research in relevant domains such as aviation. In FY10, the work focuses on documenting and analyzing problem solving strategies and decision making processes used in MCC by experienced FCers.

Bryne, Vicky↗

DOE OSTI2021

A HPC Theory-Guided Machine Learning Cyberinfrastructure for Communicating Hydrometeorological Data Across Scales

High-resolution predictions of hydrometeorological variables are critical for supporting hydropower generation decisions and flood control at hydroelectric power plants. Traditional climate and hydrologic models rely on the numerical simulation of detailed physical processes. Therefore, running these simulations is time-, labor-, and computation-intensive. Improving the spatial and temporal resolution in these modeling outputs could lead to cubic increases in both the simulation time and computational demands, rendering high-resolution hydrometeorological predictions expensive and impractical. Many past studies apply the super resolution (SR) technique to downscale climate models using deep learners. However, deep learners are deemed “black-boxes,” as their derivation processes from low-resolution outputs to high-resolution outputs are often hidden. Their results are difficult for domain scientists to interpret and validate. Thus, there is a need for an exploratory machine learning approach that can partially integrate domain-specific theory and knowledge into the data-driven mapping process between simulation outputs of different spatial scales. The domain-specific theory and knowledge can be incorporated into the data model through an inductive approach in which process-related environmental variables are used and analyzed as key drivers (i.e., environmental surrogates) to reflect the complex physical processes. Many of these variables, such as land use land cover, soil types, topography, digital elevation, air temperature, and various watershed characteristics, can be directly measured through sensors or remote sensing techniques. Additionally, SR applications that can downscale hydrological and hydrodynamics models to efficiently produce high-resolution (1 m) flood depth grids are still rare. Since the flood depth grid can be used to support critical decisions for flood control operation at hydroelectric power plants, it is crucial to enable an SR-based capability for interpolating high-resolution flood inundation maps.

13 HYDRO ENERGY↗

NASA NTRS2003

Java Library for Input and Output of Image Data and Metadata

A Java-language library supports input and output (I/O) of image data and metadata (label data) in the format of the Video Image Communication and Retrieval (VICAR) image-processing software and in several similar formats, including a subset of the Planetary Data System (PDS) image file format. The library does the following: It provides low-level, direct access layer, enabling an application subprogram to read and write specific image files, lines, or pixels, and manipulate metadata directly. Two coding/decoding subprograms ("codecs" for short) based on the Java Advanced Imaging (JAI) software provide access to VICAR and PDS images in a file-format-independent manner. The VICAR and PDS codecs enable any program that conforms to the specification of the JAI codec to use VICAR or PDS images automatically, without specific knowledge of the VICAR or PDS format. The library also includes Image I/O plugin subprograms for VICAR and PDS formats. Application programs that conform to the Image I/O specification of Java version 1.4 can utilize any image format for which such a plug-in subprogram exists, without specific knowledge of the format itself. Like the aforementioned codecs, the VICAR and PDS Image I/O plug-in subprograms support reading and writing of metadata.

Deen, Robert↗

NASA NTRS2018

Updated Benefits for Humanity from the International Space Station

Final document is attached. In 2018, the International Space Station (ISS) [Figure 1] partnership completed a revision for the third edition of the International Space Station Benefits for Humanity, a compilation of case studies of benefits being realized from ISS activities in the areas of human health, Earth observations and disaster response, innovative technology, global education, and economic development of space. The revision included new assessments of economic value and scientific value with more detail than the second edition. The third edition contains updated statistics on the impacts of the benefits as well as new benefits that have developed since the previous publication. This presentation will summarize the updates on behalf of the ISS Program Science Forum, which consists of senior science representatives across the ISS international partnership. An independent consultant determined the economic valuation (EV) of ISS research benefits case studies and the third edition contains the results. The process involved a preliminary assessment of economic, social, and innovation factors. A more detailed assessment followed, which included factors such as addressable market, market penetration, revenue generation, ability to leverage across other applications or customer groups, quality of life improvements, health benefits, environmental benefits, cultural and community cohesion, inspiration, new knowledge, novel approaches, creation of a unique market niche, and research leadership. Because of the unique microgravity environment of the ISS laboratory, the multidisciplinary and international nature of the research, and the significance of the investment in its development, analyzing ISS scientific impacts is an exceptional challenge. As a result, the ISS partnership determined the scientific valuation (SV) of ISS research using a combination of citation analyses, bibliometrics, and narratives of important ISS utilization results. Approximately 2,100 ISS results publications comprised of scientific journal articles, conference proceedings, and gray literature, representing over 5,000 authors and co-authors on Earth were used in this evaluation to enable the communication of impacts of ISS research on various science and technology fields across many countries. The publication also updates and expands the previously described benefits of research results in the areas of space commerce, technology development, human health, environmental change and disaster response, and education activities. Distinct benefits return to Earth from the only orbiting multidisciplinary laboratory of its kind. The ISS is a stepping-stone for future space exploration while also providing findings that develop low Earth orbit as a place for sustained human activity and improve life on our planet.

research↗

NASA NTRS2018

Updated Benefits for Humanity, Third Edition (B4H3), from the International Space Station (ISS)

In 2018, the International Space Station (ISS) [Figure 1] partnership completed a revision for the third edition of the International Space Station Benefits for Humanity, a compilation of case studies of benefits being realized from ISS activities in the areas of human health, Earth observations and disaster response, innovative technology, global education, and economic development of space. The revision included new assessments of economic value and scientific value with more detail than the second edition. The third edition contains updated statistics on the impacts of the benefits as well as new benefits that have developed since the previous publication. This presentation will summarize the updates on behalf of the ISS Program Science Forum, which consists of senior science representatives across the ISS international partnership. An independent consultant determined the economic valuation (EV) of ISS research benefits case studies and the third edition contains the results. The process involved a preliminary assessment of economic, social, and innovation factors. A more detailed assessment followed, which included factors such as addressable market, market penetration, revenue generation, ability to leverage across other applications or customer groups, quality of life improvements, health benefits, environmental benefits, cultural and community cohesion, inspiration, new knowledge, novel approaches, creation of a unique market niche, and research leadership. Because of the unique microgravity environment of the ISS laboratory, the multidisciplinary and international nature of the research, and the significance of the investment in its development, analyzing ISS scientific impacts is an exceptional challenge. As a result, the ISS partnership determined the scientific valuation (SV) of ISS research using a combination of citation analyses, bibliometrics, and narratives of important ISS utilization results. Approximately 2,100 ISS results publications comprised of scientific journal articles, conference proceedings, and gray literature, representing over 5,000 authors and co-authors on Earth were used in this evaluation to enable the communication of impacts of ISS research on various science and technology fields across many countries. The publication also updates and expands the previously described benefits of research results in the areas of space commerce, technology development, human health, environmental change and disaster response, and education activities. Distinct benefits return to Earth from the only orbiting multidisciplinary laboratory of its kind. The ISS is a stepping-stone for future space exploration while also providing findings that develop low Earth orbit as a place for sustained human activity and improve life on our planet.

ISS↗

NASA NTRSDate not supplied

Planetary Surface Operations and Utilization: How ISS and Artemis Missions Can Be Used to Model Human Exploration of Mars

As NASA moves forward with plans to send astronauts to the Moon under Artemis missions and prepare for human exploration of Mars, the Agency is developing a set of high-level objectives for human spaceflight, identifying 50 points falling into four overarching categories of exploration. An element in NASA’s overall process of achieving these objectives is to leverage its assets and missions – such as the many crew increments sent to the International Space Station and future Artemis expeditions sent to the Moon – to develop more robust spaceflight systems and build a culture of interplanetary human exploration. This paper describes several examples of how NASA is exercising a process to achieve these objectives for future human Mars surface missions; both (a) building on lessons learned from ISS missions and maturing plans for Artemis missions, and (b) using human Mars mission planning to inform the plans for future ISS and Artemis missions so that the knowledge gained will reduce uncertainty and risk for Mars. One focal point for this two-way interaction between ISS and Artemis with future human Mars missions is a document titled “Reference Surface Activities for Crewed Mars Mission Systems and Utilization” (HEOMD-415), which describes the systems and operations of the crew thought necessary for the first human Mars surface mission. The details described in this paper will address three specific aspects of HEOMD-415 that have been influenced by ISS and where HEOMD-415 is influencing plans in ISS, Artemis, research and technology development, and other related aspects: (1) crew (activity planning and medical), (2) Mars surface infrastructure, and (3) communication and navigation support. The paper will close by describing near-term opportunities for tests and analogs relevant to these aspects of HEOMD-415.

Mars↗

NASA NTRSDate not supplied

PLANETARY SURFACE OPERATIONS AND UTILIZATION: HOW ISS AND ARTEMIS MISSIONS CAN BE USED TO MODEL HUMAN EXPLORATION OF MARS

Mars↗