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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Scheduling and Estimating the Cost of Crew Time

In a previous paper, Theory and Application of the Equivalent System Mass Metric, Julie Levri, David Vaccari, and Alan Drysdale developed a method for computing the Equivalent System Mass (ESM) of crew time. ESM is an analog of cost. The suggested approach has been applied but seems to impose too high a cost for small additional requirements for crew time. The proposed method is based on the minimum average cost of crew time. In this work, the scheduling of crew time is examined in more detail, using suggested crew time allocations and daily work schedules. Crew tasks are typically assigned using priorities, which can also be used to construct a crew time demand curve mapping the value or cost per hour versus the total number of hours worked. The cost of additional crew time can be estimated by considering the intersection and shapes of the demand and supply curves. If e assume a mathematical form for the demand curve, a revised method can be developed for computing the cost or ESM of crew time. This method indicates a low cost per hour for small additional requirements for crew time and an increasing cost per hour for larger requirements.

Jones, Harry↗
NASA NTRS2018

Predicting Crew Time Allocations for Lunar Orbital Missions Based on Historical ISS Operational Activities

As the National Aeronautics and Space Administration continues to define candidate architectures for the planned lunar “Gateway”, it will be necessary to have a detailed understanding of how the crew will inhabit, operate, and maintain the spacecraft. The nature of the Gateway vehicle systems configuration and operations will have a direct impact on the scope of work activities required of the crew. Crew work schedules are sensitive to variations in spacecraft architecture, visiting vehicle activities, and logistics operations – particularly within short duration missions as initially planned for the lunar Gateway. These system and operational configurations must be taken into account when planning for crew time availability to conduct science activities on Gateway missions. This paper presents a methodology that is used to predict crew time distributions for lunar Gateway missions, as applied in NASA’s Exploration Crew Time Model (ECTM). The process utilized for evaluating crew time distributions is based on the categorization of all crew activities into a standardized ontology. Historical ISS daily crew timeline data from July 20, 2011 (post STS retirement) to present day was captured via the Operational Planning Timeline Integration System (OPTimIS) database and characterized according to the standardized ontology. This process enabled correlation and statistical analysis of the ISS data according to common mission parameters such as crew size, ECLSS system design, vehicle traffic operations, and logistics delivery operations. The results of the statistical analysis are a set of crew time distributions for each activity category. These distributions are then utilized within the ECTM to examine crew time allocations based on mission parameter inputs, which serve to characterize the Gateway mission configurations. Results for predicted crew time allocations for representative short duration Gateway missions are presented. These results can be used to evaluate crew schedule availability for science and utilization activities. Variations in expected mission architectures and mission operations are accounted for to correct crew time predictions. The analysis is being leveraged to plan utilization capability objectives that are achievable on the Gateway missions, as well as inform the viability of various mission architecture options.

Stromgren, Chel↗
NASA NTRSDate not supplied

Crew Time Requirements in Future Space Greenhouses - What Can We Infer from Current Analog and Space Missions?

Efficient crop production will be required to advance humanity’s presence in space, and for this, accurate predictions of crew time in future space greenhouse modules will be crucial to design and operate these plant growth systems, and schedule crop production. Crew time estimates will also be critical for deciding priorities of automating different aspects of space crop production. Because it is difficult to capture in operational environments, crew time for plant cultivation has only been sporadically recorded in past analog and space missions. We propose a methodology for efficient categorizing and reporting of crew time in space plant growth systems: first identify the different tasks needed to operate the greenhouse module, second define a representative time period for data collection, third accurately report crew time for individual tasks - and their occurrence, and fourth use collected data to improve greenhouse modules and plant growth system designs. Using data from various analog facilities and from the Veggie hardware on ISS, and assumptions for different mission scenarios, we discuss how crew time for plant cultivation can be reduced with adequate choices of crops, automation, artificial intelligence (AI) and virtual assistants, and sufficient crew training. This has major implications for the design of future space greenhouse modules. For example, missions on future space stations or during interplanetary travel would save significant crew time by including leafy greens and microgreens for astronaut’s diet supplement, with automated watering, health and environmental checks, as well as AI managing maintenance schedules, and a virtual assistant for repair activities. This work was funded by NASA Space Biology through NASA postdoctoral program / USRA, by NASA’s Space Biology and Human Research Programs, and by the European Union Horizon 2020 program via the COMPET-07-2014 - Space exploration – Life-support subprogram (reference number: 636501).

Lucie Poulet↗
NASA NTRSDate not supplied

Crew Time Requirements in Future Space Greenhouses: What Can We Infer from Current Analog and Space Missions?

Efficient crop production will be required to advance humanity’s presence in space, and for this, accurate predictions of crew time in future space greenhouse modules will be crucial to design and operate these plant growth systems, and schedule crop production. Crew time estimates will also be critical for deciding priorities of automating different aspects of space crop production. Because it is difficult to capture in operational environments, crew time for plant cultivation has only been sporadically recorded in past analog and space missions. We propose a methodology for efficient categorizing and reporting of crew time in space plant growth systems: first identify the different tasks needed to operate the greenhouse module, second define a representative time period for data collection, third accurately report crew time for individual tasks - and their occurrence, and fourth use collected data to improve greenhouse modules and plant growth system designs. Using data from various analog facilities and from the Veggie hardware on ISS, and assumptions for different mission scenarios, we discuss how crew time for plant cultivation can be reduced with adequate choices of crops, automation, artificial intelligence (AI) and virtual assistants, and sufficient crew training. This has major implications for the design of future space greenhouse modules. For example, missions on future space stations or during interplanetary travel would save significant crew time by including leafy greens and microgreens for astronaut’s diet supplement, with automated watering, health and environmental checks, as well as AI managing maintenance schedules, and a virtual assistant for repair activities. This work was funded by NASA Space Biology through NASA postdoctoral program / USRA, by NASA’s Space Biology and Human Research Programs, and by the European Union Horizon 2020 program via the COMPET-07-2014 - Space exploration – Life-support subprogram (reference number: 636501).

Veggie↗
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

A Historical Review of Logistics Mass and Crew Time Demands for ISS Operations

Following over 20 years of continuously crewed operations on the International Space Station (ISS), NASA is planning to return to the Moon and eventually send humans to Mars. ISS operations provide vital data to inform mission analysts as NASA prepares for longer and more complex missions with increased mission endurance. Endurance, defined as crewed operating time between cargo deliveries (or crew launch and return to Earth), is an important metric when analyzing mission needs. NASA is developing architectures to support sustained deep-space habitats in cislunar space, the lunar surface, Mars transit, and the surface of Mars. Unlike the ISS, these systems will not be continuously crewed, and unlike the Space Shuttle, these systems will not return to Earth for regular refurbishment between missions. Lunar systems will routinely go through long uncrewed periods between crewed missions. The systems on board will need to survive these dormancy periods with no crew present to provide maintenance. Mars systems will experience significantly longer endurance than past experience. Additionally, the inability to have quick aborts to return to Earth increases the need for system reliability, redundancy, and maintainability, as well as plans for contingency operations. This paper examines the historical logistics and crew time demand for ISS operations and mission objectives and provides an overview of missions to the ISS over its operating history, the mass and items delivered with the missions, and the crew time spent during missions. These parameters provide insight and valuable data to inform logistics and crew time estimates for future long-endurance crewed exploration missions.

Crew Logistics↗
NASA NTRSDate not supplied

A Historical Review of Logistics Mass and Crew Time Demands for ISS Operations

Following over 20 years of continuously crewed operations on the International Space Station (ISS), NASA is planning to return to the Moon and eventually send humans to Mars. ISS operations provide vital data to inform mission analysts as NASA prepares for longer and more complex missions with increased mission endurance. Endurance, defined as crewed operating time between cargo deliveries (or crew launch and return to Earth), is an important metric when analyzing mission needs. NASA is developing architectures to support sustained deep-space habitats in cislunar space, the lunar surface, Mars transit, and the surface of Mars. Unlike the ISS, these systems will not be continuously crewed, and unlike the Space Shuttle, these systems will not return to Earth for regular refurbishment between missions. Lunar systems will routinely go through long uncrewed periods between crewed missions. The systems on board will need to survive these dormancy periods with no crew present to provide maintenance. Mars systems will experience significantly longer endurance than past experience. Additionally, the inability to have quick aborts to return to Earth increases the need for system reliability, redundancy, and maintainability, as well as plans for contingency operations. This paper examines the historical logistics and crew time demand for ISS operations and mission objectives and provides an overview of missions to the ISS over its operating history, the mass and items delivered with the missions, and the crew time spent during missions. These parameters provide insight and valuable data to inform logistics and crew time estimates for future long-endurance crewed exploration missions.

Crew Logistics↗
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 NTRS1990

Space Station Freedom on-orbit crew time availability - A limited resource

Because of the enormity, complexity, and duration of the Space Station Freedom (SSF) project, the available crew time is at a premium. This paper discusses the methodology for determining, early in the program, estimates of crew time which will be available within pressurized areas of intravehicular activity, from the First Element Launch (FEL) throughout the lifetime of the SSF. The methodology utilizes the baseline assembly sequence (November 1989) as a guideline. The total hours provided are categorized by periods, where a period is comprised of the time between two major SSF Program assembly milestones; e.g., FEL to Man Tended Capability (MTS), MTS to Permanently Manned Capability (PMC), or PMC to Assembly Complete (AC). After AC, total available crew time is presented on a yearly basis.

Garegnani, Jerry J.↗
NASA NTRS2015

Developing a Crew Time Model for Human Exploration Missions to Mars

Candidate human missions to Mars require mission lengths that could extend beyond those that have previously been demonstrated during crewed Lunar (Apollo) and International Space Station (ISS) missions. The nature of the architectures required for deep space human exploration will likely necessitate major changes in how crews operate and maintain the spacecraft. The uncertainties associated with these shifts in mission constructs - including changes to habitation systems, transit durations, and system operations - raise concerns as to the ability of the crew to complete required overhead activities while still having time to conduct a set of robust exploration activities. This paper will present an initial assessment of crew operational requirements for human missions to the Mars surface. The presented results integrate assessments of crew habitation, system maintenance, and utilization to present a comprehensive analysis of potential crew time usage. Destination operations were assessed for a short (approx. 50 day) and long duration (approx. 500 day) surface habitation case. Crew time allocations are broken out by mission segment, and the availability of utilization opportunities was evaluated throughout the entire mission progression. To support this assessment, the integrated crew operations model (ICOM) was developed. ICOM was used to parse overhead, maintenance and system repair, and destination operations requirements within each mission segment - outbound transit, Mars surface duration, and return transit - to develop a comprehensive estimation of exploration crew time allocations. Overhead operational requirements included daily crew operations, health maintenance activities, and down time. Maintenance and repair operational allocations are derived using the Exploration Maintainability and Analysis Tool (EMAT) to develop a probabilistic estimation of crew repair time necessary to maintain systems functionality throughout the mission.

Battfeld, Bryan↗
NASA NTRS2017

Development of a Novel Space Flight Plan to Monitor Female Mice Fertility Using Reduced Crew Time

Ovarian estrogen impacts the normal homeostatic and metabolic processes of all tissues and organ systems within the body: particularly, but not limited to canonical space-flight impacted systems: bone, muscle, immune, wound repair, and cardiovascular. Effects of space flight on the ovarian estrogen production are therefore critical to our understanding of all space flight experiments using female mice, the current paradigm being used on the International Space Station (ISS). Recently, we demonstrated that vaginal wall histology could be used to determine the stage of the estrous cycle in female mice at the time of sacrifice in space. Moreover, this robust technique was completed following two post-flight freezethaw procedures of the carcasses (RR1 experiment). Thus, this technique represents a viable mechanism to determine the estrous cycle status of the female at the time of sacrifice and can be completed in a manner that does not impact primary experimental objectives. We propose that vaginal wall histology become a standard procedure completed on all mice sacrificed in space and that the individual estrous status of each animal be shared with all investigators. While evidence of estrous cyclicity was present in long-term (33 day) RR1 mice, fertility of female mice exposed to weightlessness remains unknown. In preparation for an upcoming funded NASA flight investigating the effects of long duration spaceflight on female fertility, we have refined our experimental design to minimize crew flight time and to accommodate the duration of Dragon capsule berth. These refinements maintain all our proposed primary and secondary experimental objectives. Briefly, in order to evaluate fertility, we will super ovulate mice using standard procedures (PMSG hCG), followed by collection of reproductive tract after follicular stimulation alone (PMSG) or following ovulation (hCG). Ovarian folliculogenesis and ovulation rate will be determined in fixed tissues following return in order to determine fertility. Ovarian and uterine tissues will also be evaluated by hormonal and gene expression profiling using quantitative approaches (radioimmunoassays, western blots, digital droplet PCR). Comparisons will be made to contemporary vivarium and Rodent Research Hardware Transporter and Habitat housed animals maintained on earth. Supported by NNX15AB48G to JST.

Christenson, Lane↗
NASA NTRS1994

Automation and crew time saving in the space experiment

We describe preliminary results of the feasibility study of automation and crew workload saving in space experiments on the space station. Some functions have been studied that can be automated within a single rack and without major impact to the development process and costs. In addition, we assume the following premises: (1) applicable as the second generation apparatuses; (2) maximum reduction of the crew workload; and (3) automation between racks including storage. Four apparatuses have been selected as the study case; results for three are summarized.

Matsumoto, Kohtaro↗
NASA NTRS1990

Vehicle processing operations database

The Vehicle Processing Operations Data base (VPOD) has been designed and constructed to enable the collection and preliminary analysis of data relative to the processing of planetary exploration vehicles in low Earth orbit. VPOD has the capability to hierarchically store the events, assemblies, and equipment data needed for performing vehicle processing analysis, to whatever level of detail available. This permits some analysis to be performed even during the very early phases of vehicle and mission design. As more data about the events, assemblies, or equipment become available, the analysis can then be refined using the increased level of detail. VPOD output is based on a mission defined by selecting from the VPOD Events data base the events that are required to perform the desired tasks. The outputs available include total crew time, crew skill requirements, equipment needed, assemblies worked per event, to any available level of detail. The VPOD design is structured to interface with an operations simulation capability which is currently in the requirements definition phase. The simulator will use information from the VPOD to perform operations analysis for missions being conducted in low Earth orbit. VPOD information, along with information from the science missions operations data base and a Space Station configuration data base, will be used by the simulator to provide a capability to study total system operations and resources requirements.

Ganoe, George G.↗
NASA NTRS2016

Analog Testing of Operations Concepts for Mitigation of Communication Latency During Human Space Exploration

OBJECTIVES: NASA Extreme Environment Mission Operations (NEEMO) is an underwater spaceflight analog that allows a true mission‐like operational environment and uses buoyancy effects and added weight to simulate different gravity levels. Three missions were undertaken from 2014‐2015, NEEMO's 18‐20. All missions were performed at the Aquarius undersea research habitat. During each mission, the effects of varying operations concepts and tasks type and complexity on representative communication latencies associated with Mars missions were studied. METHODS: 12 subjects (4 per mission) were weighed out to simulate near‐zero or partial gravity extravehicular activity (EVA) and evaluated different operations concepts for integration and management of a simulated Earth‐based science backroom team (SBT) to provide input and direction during exploration activities. Exploration traverses were planned in advance based on precursor data collected. Subjects completed science‐related tasks including presampling surveys, geologic‐based sampling, and marine‐based sampling as a portion of their tasks on saturation dives up to 4 hours in duration that were to simulate extravehicular activity (EVA) on Mars or the moons of Mars. One‐way communication latencies, 5 and 10 minutes between space and mission control, were simulated throughout the missions. Objective data included task completion times, total EVA times, crew idle time, translation time, SBT assimilation time (defined as time available for SBT to discuss data/imagery after it has been collected, in addition to the time taken to watch imagery streaming over latency). Subjective data included acceptability, simulation quality, capability assessment ratings, and comments. RESULTS: Precursor data can be used effectively to plan and execute exploration traverse EVAs (plans included detailed location of science sites, high‐fidelity imagery of the sites, and directions to landmarks of interest within a site). Operations concepts that allow for presampling surveys enable efficient traverse execution and meaningful Mission Control Center (MCC) interaction across long communication latencies and can be done with minimal crew idle time. Imagery and information from the EVA crew that is transmitted real‐time to the intravehicular (IV) crewmember(s) can be used to verify that exploration traverse plans are being executed correctly. That same data can be effectively used by MCC (across comm latency) to provide further instructions to the crew from a SBT on sampling priorities, additional tasks, and changes to the plan. Text / data capabilities are preferred over voice capabilities between MCC and IV when executing exploration traverse plans over communication latency. Autonomous crew planning tools can be effective at modifying existing plans if the objectives and constraints are clearly defined.

Chappell, Steven P.↗
NASA NTRS2016

NEEMO 18-20: Analog Testing for Mitigation of Communication Latency During Human Space Exploration

NASA Extreme Environment Mission Operations (NEEMO) is an underwater spaceflight analog that allows a true mission-like operational environment and uses buoyancy effects and added weight to simulate different gravity levels. Three missions were undertaken from 2014-2015, NEEMO's 18-20. All missions were performed at the Aquarius undersea research habitat. During each mission, the effects of communication latencies on operations concepts, timelines, and tasks were studied. METHODS: Twelve subjects (4 per mission) were weighed out to simulate near-zero or partial gravity extravehicular activity (EVA) and evaluated different operations concepts for integration and management of a simulated Earth-based science team (ST) to provide input and direction during exploration activities. Exploration traverses were preplanned based on precursor data. Subjects completed science-related tasks including pre-sampling surveys, geologic-based sampling, and marine-based sampling as a portion of their tasks on saturation dives up to 4 hours in duration that were designed to simulate extravehicular activity (EVA) on Mars or the moons of Mars. One-way communication latencies, 5 and 10 minutes between space and mission control, were simulated throughout the missions. Objective data included task completion times, total EVA times, crew idle time, translation time, ST assimilation time (defined as time available for ST to discuss data/imagery after data acquisition). Subjective data included acceptability, simulation quality, capability assessment ratings, and comments. RESULTS: Precursor data can be used effectively to plan and execute exploration traverse EVAs (plans included detailed location of science sites, high-fidelity imagery of the sites, and directions to landmarks of interest within a site). Operations concepts that allow for pre-sampling surveys enable efficient traverse execution and meaningful Mission Control Center (MCC) interaction across communication latencies and can be done with minimal crew idle time. Imagery and contextual information from the EVA crew that is transmitted real-time to the intravehicular (IV) crewmember(s) can be used to verify that exploration traverse plans are being executed correctly. That same data can be effectively used by MCC (across comm latency) to provide meaningful feedback and instruction to the crew regarding sampling priorities, additional tasks, and changes to the EVA timeline. Text / data capabilities are preferred over voice capabilities between MCC and IV when executing exploration traverse plans over communication latency.

Chappell, Steven P.↗