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NASA NTRSDate not supplied

Assessment of Crew Time for Maintenance and Repair Activities for Lunar Surface Missions

NASA is currently evaluating different methods to predict how much time crewmembers will spend conducting repair and maintenance activities on future space missions. As mission scope and spacecraft architectures change, understanding how crew repair and maintenance timelines are impacted by mission operations and technology changes is vital for future mission planning. Past work has been done using historical International Space Station (ISS) data to accurately predict crew habitation and operation timelines, resulting in the development of NASA’s Exploration Crew Time Model (ECTM). However, understanding crew maintenance and repair requirements has posed a unique challenge due to the complexity of available datasets, the probabilistic nature of sub-system failures, and the impacts of reliability growth on failure rates. This paper presents a methodology to collect and condition empirical repair and maintenance time data from available datasets, to extrapolate from that data to estimate projected maintenance and repair times for a lunar Surface Habitat (SH), and to assess how uncertainty in repair time could impact utilization time on the lunar surface. NASA ISS maintenance and crew time data are logged into two central databases: the Maintenance Data Collection (MDC) and the Operations Planning Timeline Integration System (OPTimIS). Separately, each of these two datasets capture only portions of the complete set of data required to generate an accurate assessment of crew time spent on maintenance activities at a sub-system level. To create a more useful crew time estimate for maintenance timelines, the authors developed a methodology to capture relevant data from each set and combine and utilize that data by linking crew time requirements to specific components. The authors compare the failure logs in the MDC to crew activity logs pulled from OPTimIS and then process the data to estimate required repair time for each failure and repair event. The entire maintenance activity dataset is then categorized based on the class of failed component to ensure a significant sample size for each class and accurate crew time estimates for any components lacking relevant data. This resultant component repair time data can be used in the future to generate Mean Time to Repair (MTTR) estimates and confidence intervals for each class of component based on a probabilistic distribution of documented maintenance events. These improved MTTR values can then be applied to candidate element sub-system architectures, along with component Mean Time Between Failure (MTBF) data to generate distributions for potential required system crew repair time estimates for a given mission. The authors applied these modeling methods to a case study of a crewed mission to the planned SH and produced expected corrective maintenance crew time distributions. The results produced an expected corrective maintenance crew time at over 24 hours per mission, and a maintenance crew time distribution that reflects the importance of planning for sufficient maintenance requirements each mission. Repair time distributions can then be used to develop more accurate crew schedules and to assess potential available utilization time.

Crew Time↗

NASA NTRSDate not supplied

Assessment of Crew Time for Maintenance and Repairs Activities for Lunar Surface Missions

NASA is currently evaluating different methods to predict how much time crewmembers will spend conducting repair and maintenance activities on future space missions. As mission scope and spacecraft architectures change, it will be necessary to understand how crew repair and maintenance timelines are impacted by mission operations and technology changes. Past work has been done using historical ISS data to accurately predict crew habitation and operation timelines, resulting in the development of NASA’s Exploration Crew Time Model (ECTM). However, understanding crew maintenance and repair requirements has posed a unique challenge due to the complexity of available datasets, the probabilistic nature of sub-system failures, and the impacts of reliability growth on failure rates. This paper presents a methodology to collect and condition empirical repair and maintenance time data from available data sets, to extrapolate from that data to estimate projected maintenance and repair times for a lunar Surface Habitat, and to assess how uncertainty in repair time could impact utilization time on the lunar surface. NASA International Space Station (ISS) maintenance and crew time data are logged into two central databases, the Maintenance Data Collection (MDC) and the Operations Planning Timeline Integration System (OPTimIS) respectively. Separately, each of these two datasets capture only portions of the complete set of data required to generate an accurate assessment of crew time spent on maintenance activities at a sub-system level. MDC provides a detailed catalog of failure events and an overview of the failure’s required maintenance and OPTimIS provides a description of crew activities and crew time durations dedicated to maintenance. To create a more useful crew time estimate for maintenance timelines, the authors developed a methodology to capture relevant data from each set and combine and utilize that data by linking crew time requirements to specific components. The authors compare the failure logs in the MDC to crew activity logs pulled from OPTimIS and then process the data to estimate required repair times for each failure event. Data is also classified by the outcome of each repair event, whether the failed component was replaced or whether it was repaired in place. The entire maintenance activity dataset is then categorized based on the class of failed component to allow for a statistically significant sample size for each class and to provide accurate crew time estimates for any components lacking relevant data. This resultant component repair time data can be used in the future to generate Mean Time To Repair (MTTR) estimates and confidence intervals for each class of component based on a probabilistic distribution of documented maintenance events. These improved MTTR values can then be applied to candidate element sub-system architectures, along with component Mean Time Between Failure (MTBF) data to generate distributions for potential required system crew repair time estimates for a given mission. Repair time distributions can then be used to develop more accurate crew schedules and to assess potential available utilization time.

Crew Time↗

NASA NTRS2017

Leveraging Terrestrial Industry for Utilization of Space Resources

NASA's Journey to Mars: Pioneering Next Steps in Space Exploration released in October of 2015 states that NASA is working toward the capability to work, operate, and sustainably live safely beyond Earth. To progress from our current "Earth-Reliant" approach to exploration and eventually become "Earth Independent", we need to first identify resources in space and then learn to use and harvest them to minimize logistics from Earth, reduce costs, and enable sustainable and affordable space transportation and surface operations. Known as In Situ Resource Utilization (ISRU), the collection and conversion of space resources into products such as propellants, fuel cell reactants, and life support consumables can greatly reduce the mass, cost, and risk of space exploration. Also, the ability to perform civil engineering, construction, and manufacturing at sites of exploration can also allow for increased crew safety and sustainable growth in critical infrastructure. Much of what NASA wants to do on the Moon and Mars with respect to harnessing and utilizing space resources has been performed and perfected on Earth over the centuries. While minimizing mass and operating in the vacuum of space may be unique challenges to NASA, both terrestrial industry and NASA face many of the same challenges associated with operating in severe environments, minimizing maintenance and logistics, maximizing performance per unit mass and volume, performing remote and autonomous operations, and integrating hardware from many vendors and countries. In the end, both NASA and terrestrial industry need to obtain a return on the investment for the development and deployment of these capabilities. This paper will first examine what is ISRU and what are the space resources of interest. The paper will than discuss what are NASA's approach, life cycle, and economic considerations for implementing ISRU. The paper will outline the site and infrastructure needs associated with a phased implementation of ISRU into human missions to the Moon and Mars. The paper will than assess what technologies and operations from terrestrial industries are relevant and synergistic with ISRU (from prospecting to product storage), and what challenges and similarities between the two can be exploited. Lastly, the paper will end with a discussion on where do we go from here for industry and NASA to collaborate.

Sanders, Gerald B.↗

NASA NTRS1982

Space Operations Center orbit altitude selection strategy

The strategy for the operational altitude selection has to respond to the Space Operation Center's (SOC) maintenance requirements and the logistics demands of the missions to be supported by the SOC. Three orbit strategies are developed: two are constant altitude, and one variable altitude. In order to minimize the effect of atmospheric uncertainty the dynamic altitude method is recommended. In this approach the SOC will operate at the optimum altitude for the prevailing atmospheric conditions and logistics model, provided that mission safety constraints are not violated. Over a typical solar activity cycle this method produces significant savings in the overall logistics cost.

Indrikis, J.↗

DOE OSTI2026

Cross-domain digital twin architecture for predictive maintenance via machine learning and Large Language Models

This research introduces a comprehensive framework for creating and deploying a digital twin platform for continuous monitoring and predictive maintenance within industrial settings. Through utilizing advanced technologies, including Unreal Engine 5, Unity 3D, the Message Queue Telemetry Transport protocol, Random Forest machine learning algorithms, and Large Language Models (LLMs), we establish a platform that digitally reproduces physical equipment and translates digital controls into real-world actions. This facilitates preventive maintenance approaches and improves operational effectiveness. The digital twin platform gathers sensor data from operational equipment, analyzes it using machine learning, and delivers practical insights to prevent potential malfunctions and enhance equipment performance. Furthermore, the incorporation of a web portal enables efficient monitoring and access to historical data, educational materials, and equipment status information. Preliminary findings indicate that digital twins can transform industrial equipment management and maintenance methodologies.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Success Path Method: Conformance with Safety Management Systems

All industrial facilities deal with safety hazards such as equipment failures, chemical and toxic releases, and fires and explosions just to name a few. A disciplined framework for managing the integrity of operating systems and processes that handle hazardous substances by applying good design principles, engineering, and operating practices is called process safety. The goal of such framewoks is to prevent the release of energy or material that could cause harm to people or damage to equipment and/or environment. Process safety covers all aspects of facility operation also including design, maintenance, and human and organizational factors that could possibly have effect on process safety. As it will be seen from the discussion below, process safety is just one of the pieces of the much bigger matter, a safety culture. Many industries have long recognized the importance of safety culture in their day-to-day operation. Although the definition of safety culture can slightly differ from organization to organization, in general, a safety culture is how things are done to demonstrate a commitment to safety by everyone involved. An organization acquires safety culture over time as the product of individual and group values, actions, and behaviors toward overall safety. It is important to note that safety culture should not be viewed as some static state that an organization wants to reach. It is more like a constantly evolving level of “how things are done when nobody is watching.” Safety culture is an inherent characteristic of an organization, it is always present, but the level can range on a continuum from undesirable to desirable or more commonly used, from negative to positive. An example for an undesirable, negative safety culture would be a company in which accidents resulting in harm (physical and/or emotional) of its employees, equipment or surrounding environment and community occur frequently. At the other end of the spectrum would be a company in which such accidents are rare or do not occur at all (desired or positive safety culture). Every company/industry exists somewhere within this spectrum.

42 ENGINEERING↗

NASA NTRS2011

Modular System to Enable Extravehicular Activity

The ability to perform extravehicular activity (EVA), both human and robotic, has been identified as a key component to space missions to support such operations as assembly and maintenance of space system (e.g. construction and maintenance of the International Space Station), and unscheduled activities to repair an element of the transportation and habitation systems that can only be accessed externally and via unpressurized areas. In order to make human transportation beyond lower earth orbit (BLEO) practical, efficiencies must be incorporated into the integrated transportation systems to reduce system mass and operational complexity. Affordability is also a key aspect to be considered in space system development; this could be achieved through commonality, modularity and component reuse. Another key aspect identified for the EVA system was the ability to produce flight worthy hardware quickly to support early missions and near Earth technology demonstrations. This paper details a conceptual architecture for a modular extravehicular activity system (MEVAS) that would meet these stated needs for EVA capability that is affordable, and that could be produced relatively quickly. Operational concepts were developed to elaborate on the defined needs and define the key capabilities, operational and design constraints, and general timelines. The operational concept lead to a high level design concept for a module that interfaces with various space transportation elements and contains the hardware and systems required to support human and telerobotic EVA; the module would not be self-propelled and would rely on an interfacing element for consumable resources. The conceptual architecture was then compared to EVA Systems used in the Shuttle Orbiter, on the International Space Station to develop high level design concepts that incorporate opportunities for cost savings through hardware reuse, and quick production through the use of existing technologies and hardware designs. An upgrade option was included to make use of the developing suitport technologies.

Sargusingh, Miriam J.↗

NASA NTRS2012

Modular System to Enable Extravehicular Activity

The ability to perform extravehicular activity (EVA), both human and robotic, has been identified as a key component to space missions to support such operations as assembly and maintenance of space systems (e.g. construction and maintenance of the International Space Station), and unscheduled activities to repair an element of the transportation and habitation systems that can only be accessed externally and via unpressurized areas. In order to make human transportation beyond lower Earth orbit (LEO) practical, efficiencies must be incorporated into the integrated transportation systems to reduce system mass and operational complexity. Affordability is also a key aspect to be considered in space system development; this could be achieved through commonality, modularity and component reuse. Another key aspect identified for the EVA system was the ability to produce flight worthy hardware quickly to support early missions and near Earth technology demonstrations. This paper details a conceptual architecture for a modular EVA system that would meet these stated needs for EVA capability that is affordable, and that could be produced relatively quickly. Operational concepts were developed to elaborate on the defined needs, and to define the key capabilities, operational and design constraints, and general timelines. The operational concept lead to a high level design concept for a module that interfaces with various space transportation elements and contains the hardware and systems required to support human and telerobotic EVA; the module would not be self-propelled and would rely on an interfacing element for consumable resources. The conceptual architecture was then compared to EVA Systems used in the Space Shuttle Orbiter, on the International Space Station to develop high level design concepts that incorporate opportunities for cost savings through hardware reuse, and quick production through the use of existing technologies and hardware designs. An upgrade option was included to make use of the developing suit port technologies.

Sargusingh, Miriam J.↗

NASA NTRS1991

Background issues for on-line aircraft documentation

Currently, almost all aircraft documentation in commercial aircraft cockpits is presented via hardcopy manuals. Several recent projects are aimed at eliminating all paper documentation in cockpits using electronic libraries. Electronic libraries encompass diverse information bases including aircraft system documentation, operations and procedures, checklists, maintenance logs, minimum equipment lists, maps and charts, and flight management information. These electronic libraries are envisioned to be embedded in the avionics so as to provide real time monitoring and display of information. Background issues are examined (motivation, information retrieval models, and preliminary designs) for the on-line presentation of aircraft systems documentation including operations, procedures, and checklists.

Russell, C. Ray↗

NASA NTRS1993

Soyuz-TM-based interim Assured Crew Return Vehicle (ACRV) for the Space Station Freedom

The concept of using the available Soyuz-TM Assured Crew Return Vehicle (ACRV) spacecraft for the assurance of the safety of the Space Station Freedom (SSF) crew after the departure of the Space Shuttle from SSF was proposed by the NPO Energia and was accepted by NASA in 1992. The ACRV will provide the crew with the capability to evacuate a seriously injured/ill crewmember from the SSF to a ground-based care facility under medically tolerable conditions and with the capability for a safe evacuation from SSF in the events SSF becomes uninhabitable or the Space Shuttle flights are interrupted for a time that exceeds SSF ability for crew support and/or safe operations. This paper presents the main results of studies on Phase A (including studies on the service life of ACRV; spacecraft design and operations; prelaunch processing; mission support; safety, reliability, maintenance and quality and assurance; landing, and search/rescue operations; interfaces with the SSF and with Space Shuttle; crew accommodation; motion of orbital an service modules; and ACRV injection by the Expendable Launch Vehicles), along with the objectives of further work on the Phase B.

Yu P Semenov↗

NASA NTRS2010

Web-Based Requesting and Scheduling Use of Facilities

Automated User's Training Operations Facility Utilization Request (AutoFUR) is prototype software that administers a Web-based system for requesting and allocating facilities and equipment for astronaut-training classes in conjunction with scheduling the classes. AutoFUR also has potential for similar use in such applications as scheduling flight-simulation equipment and instructors in commercial airplane-pilot training, managing preventive- maintenance facilities, and scheduling operating rooms, doctors, nurses, and medical equipment for surgery. Whereas requesting and allocation of facilities was previously a manual process that entailed examination of documents (including paper drawings) from different sources, AutoFUR partly automates the process and makes all of the relevant information available via the requester s computer. By use of AutoFUR, an instructor can fill out a facility-utilization request (FUR) form on line, consult the applicable flight manifest(s) to determine what equipment is needed and where it should be placed in the training facility, reserve the corresponding hardware listed in a training-hardware inventory database, search for alternative hardware if necessary, submit the FUR for processing, and cause paper forms to be printed. Auto-FUR also maintains a searchable archive of prior FURs.

Yeager, Carolyn M.↗

NASA NTRS2023

An Analysis of Barriers Preventing the Widespread Adoption of Predictive and Prescriptive Maintenance in Aviation

The aviation industry has long recognized the potential benefits of predictive maintenance, a maintenance strategy that leverages sensor and operational data to predict the future degradation of components. Prescriptive maintenance takes this a step further and considers the entire aviation ecosystem to schedule maintenance actions optimally. With the ability to reduce maintenance costs by up to 30%, as reported by the Department of Energy, these maintenance strategies have been identified to be an important investment to reduce a airline costs. However, despite great interest and technological advances in areas such as diagnostics, prognostics, sensing, computation, and machine learning, the adoption of predictive and prescriptive maintenance has not been widely applied in aviation. To shed light on this issue, we conducted an analysis of the barriers preventing or limiting the adoption of predictive and prescriptive maintenance in aviation. Through discussions with subject matter experts across industry, academia, standards bodies, and government, we identified five key challenges: complexity of prediction; validation, safety assurance, and regulatory challenges; cost of adoption; difficulty in quantifying impact and informing decisions; and data availability, quality, and ownership challenges. This study provides a detailed overview of these barriers and areas where stakeholders could invest to overcome them, aiming to support the scaled adoption of predictive and prescriptive maintenance in aviation.

Christopher Teubert↗

DOE OSTI2021

FY2021 Status Report on the Computing Systems for the Yucca Mountain Project TSPA-LA Models and Testing of Selected Process Models

Sandia National Laboratories continued evaluation of the total system performance assessment (TSPA) for License Application (LA) computing systems for the previously considered Yucca Mountain Project (YMP). This was done to maintain the operational readiness of the computing infrastructure (computer hardware and software) and knowledge capability for total system performance assessment) type analysis, as directed by the National Nuclear Security Administration (NNSA), DOE 2010. The FY21 task included continued operation of the cluster; maintenance of the TSPA-LA models (with GoldSim 9.60.300); continued assessment of the status of the Infiltration Model; (a process model that feeds the TSP -LA) and preliminary assessments of the Unsaturated Zone Flow Model and the Saturated Zone Flow and Transport Model Abstraction (process models that feed the TSPA-LA). The 2014 cluster and supporting software systems are currently fully operational to support TSPA-LA type analyses.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRSDate not supplied

Autonomous System Operations for Lunar Safe Haven Establishment and Sustainment

To enable a sustainable, permanent human lunar presence, NASA must provide a safe haven shelter to protect astronauts and equipment from radiation, thermal extremes, and micro-meteoroids (MM). Planning and development for a robust Safe Haven includes an examination of NASA activities in site preparation, excavation, regolith transfer, surface operations, autonomous monitoring and maintenance, advanced manufacturing, and in-situ resource utilization (ISRU) for identifying the best approaches when implementing a safe haven shelter. These NASA activities were reviewed as a part of a trade study conducted at NASA Langley to assess technological needs and estimated technology readiness levels (TRL). This paper presents a thorough review of the role and level of autonomy in the establishment and sustainment operations of a Lunar Safe Haven.

Walter J Waltz↗

NASA NTRSDate not supplied

Autonomous System Operations for Lunar Safe Haven Establishment and Sustainment

Walter J Waltz↗

NASA NTRS1988

Large-scale wind turbine structures

The purpose of this presentation is to show how structural technology was applied in the design of modern wind turbines, which were recently brought to an advanced stage of development as sources of renewable power. Wind turbine structures present many difficult problems because they are relatively slender and flexible; subject to vibration and aeroelastic instabilities; acted upon by loads which are often nondeterministic; operated continuously with little maintenance in all weather; and dominated by life-cycle cost considerations. Progress in horizontal-axis wind turbines (HAWT) development was paced by progress in the understanding of structural loads, modeling of structural dynamic response, and designing of innovative structural response. During the past 15 years a series of large HAWTs was developed. This has culminated in the recent completion of the world's largest operating wind turbine, the 3.2 MW Mod-5B power plane installed on the island of Oahu, Hawaii. Some of the applications of structures technology to wind turbine will be illustrated by referring to the Mod-5B design. First, a video overview will be presented to provide familiarization with the Mod-5B project and the important components of the wind turbine system. Next, the structural requirements for large-scale wind turbines will be discussed, emphasizing the difficult fatigue-life requirements. Finally, the procedures used to design the structure will be presented, including the use of the fracture mechanics approach for determining allowable fatigue stresses.

Spera, David A.↗

NASA NTRS2006

A Simulation Based Approach for Contingency Planning for Aircraft Turnaround Operation System Activities in Airline Hubs

Commercial aircraft undergo a significant number of maintenance and logistical activities during the turnaround operation at the departure gate. By analyzing the sequencing of these activities, more effective turnaround contingency plans may be developed for logistical and maintenance disruptions. Turnaround contingency plans are particularly important as any kind of delay in a hub based system may cascade into further delays with subsequent connections. The contingency sequencing of the maintenance and logistical turnaround activities were analyzed using a combined network and computer simulation modeling approach. Experimental analysis of both current and alternative policies provides a framework to aid in more effective tactical decision making.

Adeleye, Sanya↗

DOE OSTI2020

FY19 Status Report on the Computing Systems for the Yucca Mountain Project TSPA-LA Models and Preliminary Testing of a Selected Process Model

Sandia National Laboratories continued evaluation of total system performance assessment (TSPA) computing systems for the previously considered Yucca Mountain Project. This was done to maintain the operational readiness of the computing infrastructure (computer hardware and software) and knowledge capability for total system performance assessment) type analysis, as directed by the National Nuclear Security Administration (NNSA), DOE 2010. The FY19 task included continued operation of the cluster; maintenance of the TSPA-LA models (with Gold Sim 9.60.300); preliminary assessment of the status of the Infiltration Model (a process model that feeds the TSPA-LA). In addition, precautionary actions were needed to extend the life of the cluster hardware. To do that, three new nodes were added to the cluster. In the event any of the original nodes fail they will be replaced with the new nodes, thereby maintaining the core capability. The 2014 cluster and supporting software systems are currently fully operational to support TSPA-LA type analysis.

97 MATHEMATICS AND COMPUTING↗