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NASA NTRS2017

Informal Statistics Help Desk

Back by popular demand, the JSC Biostatistics Laboratory and LSAH statisticians are offering an opportunity to discuss your statistical challenges and needs. Take the opportunity to meet the individuals offering expert statistical support to the JSC community. Join us for an informal conversation about any questions you may have encountered with issues of experimental design, analysis, or data visualization. Get answers to common questions about sample size, repeated measures, statistical assumptions, missing data, multiple testing, time-to-event data, and when to trust the results of your analyses.

Young, M.↗
NASA NTRS2017

Determination of the Risk of Radiation-Associated Circulatory and Cancer Disease Mortality in a NASA Early Astronaut Cohort

Of the many possible health challenges posed during extended exploratory missions to space, the effects of space radiation on cardiovascular disease and cancer are of particular concern. There are unique challenges to estimating those radiation risks; care and appropriate and rigorous methodology should be applied when considering small cohorts such as the NASA astronaut population. The objective of this work was to determine if there was sufficient evidence for excess risk of cardiovascular disease and cancer in early NASA astronaut cohorts. NASA astronauts in selection groups 1-7 were chosen; this relatively homogeneous cohort consists of 73 white males, who unlike today's astronauts, maintained similar smoking and drinking habits to the general US population, and have published radiation doses. The participants flew in space on missions Mercury through Shuttle and received space radiation doses between 0-74.1 milligrays. Cause of death information was obtained from the Lifetime Surveillance of Astronaut Health (LSAH) program at NASA Johnson Space Center. Mortality was compared with the US male population. Trends of mortality with dose were assessed using a logistic model, fitted by maximum likelihood. Only 32 (43.84 percent) of the 73 early astronauts have died. Standard mortality ratios (SMRs) for cancer (n=7, SMR=43.4, 95 percent CI 17.8, 84.9), all circulatory disease (n=7, SMR=33.2, 95 percent CI 13.7, 65.0), and ischemic heart disease (IHD) (n=5, SMR=40.1, 95 percent CI 13.2, 89.4) were significantly lower than for the US white male population. For cerebrovascular disease, the upper confidence interval for SMR included 100, indicating it was not significantly different from the US population (n=2, SMR = 77.0, 95 percent CI 9.4, 268.2). The power of the study is low and remains below 10 percent even when risks 10 times those reported in the literature are assumed. Due to small sample size, there is currently insufficient statistical power to evaluate space radiation exposure effects on mortality in NASA astronauts. In addition to a comprehensive longitudinal study of NASA astronauts, a research strategy of low dose epidemiology data integration with cell and animal studies should be utilized for space radiation risk assessment in the astronauts.

Elgart, S. R.↗
NASA NTRS2017

Recent Radiation Test Results for Trench Power MOSFETs

Single-event effect (SEE) radiation test results are presented for various trench-gate power MOSFETs. The heavy-ion response of the first (and only) radiation-hardened trench-gate power MOSFET is evaluated: the manufacturer SEE response curve is verified and importantly, no localized dosing effects are measured, distinguishing it from other, non-hardened trench-gate power MOSFETs. Evaluations are made of n-type commercial and both n- and p-type automotive grade trench-gate device using ions comparable to of those on the low linear energy transfer (LET) side of the iron knee of the galactic cosmic ray spectrum, to explore suitability of these parts for missions with higher risk tolerance and shorter duration, such as CubeSats. Part-to-part variability of SEE threshold suggests testing with larger sample sizes and applying more aggressive derating to avoid on-orbit failures. The n-type devices yielded expected localized dosing effects including when irradiated in an unbiased (0-V) configuration, adding to the challenge of inserting these parts into space flight missions.

Schottky Diodes↗
NASA NTRS2018

Realistic Covariance Generation for the GPM Spacecraft

We present several different methods for generating realistic predictive covariance, including Monte-Carlo simulations and more direct linear methods which require the addition of process noise. The Monte-Carlo simulation starts with an epoch uncertainty sample basis and propagates each trial to a time of interest in the future. The variance-covariance of the state elements as well as other higher order sample statistics can be readily computed from the propagated sample. While this method preserves the nonlinear effects on the propagated uncertainty, it is computationally intensive as a statistically significant sample size must be considered in the propagation process. Moreover, if the epoch covariance is optimistic, this can result in an underestimation of the prediction error. Another method is to propagate a state sensitivity matrix simultaneously with the satellite state, which allows the epoch covariances to be propagated forward in a linear fashion. This method does not preserve the non-linearity of the satellite state uncertainty but is much less computationally intensive. The propagated state covariance is the scaled to represent the realistic level of GPM state uncertainty via a "e-tuning process." The tuning process generates an inflation factor based on the observed error statistics of the predictive satellite trajectories when compared to the definitive ones. Difference tuning strategies are considered and compared via Goodness-of-Fit method testing for the Gaussian properties of the scaled covariance.

prediction error↗
NASA NTRS2018

An Analysis of the Lightning Jump Algorithm Using Geostationary Lightning Mapper Flashes

This project aims to implement the two-sigma lightning jump algorithm (LJA) developed using Lightning Mapping Arrays (LMAs), with GOES-16 Geostationary Lightning Mapper (GLM) flashes, evaluate its performance, and identify any needed adjustments to the algorithm to optimize operational skill. The GLM is projected to have lower detection efficiency (DE) (70-90 percent) than operational LMAs (95-99 percent). The reduced GLM DE coupled with the coarser spatial resolution of the GLM could have impacts on flash rates and trends that could affect the LJA in various ways. Deep dives are conducted on four separate cases. Three of four cases show LMAs seeing two to three times as many flashes as the GLM. Only fifteen of twenty five GLM jumps saw increases in radar intensity while fourteen of nineteen LMA jumps did. These results suggest a larger sample sized study must be conducted to determine how to implement the LJA with the GLM.

Curtis, Nathan↗
NASA NTRS2018

Lyman-Alpha Comes of Age

The Lyman-alpha (Lyα) line is the strongest recombination line of hydrogen, which constitutes the dominant share of normal matter in the Universe. Fifty-one years ago, it was predicted that Lyα emission should appear prominently in the spectra of young primordial galaxies. For the next 30 years, this prediction was tested by many surveys, but none found the predicted galaxies at the predicted luminosities. The blame for these non-detections was squarely cast on the resonant nature of the Lyα line, which requires Lyα photons to scatter off many hydrogen atoms before escaping from a galaxy. This can hugely increase the path that they traverse, and consequently also the probability that they will be absorbed by dust. This remained the dominant explanation of the missing high-redshift lines for decades, despite some dissenting opinions about the effect of dust. The spectra of nearby galaxies from the International Ultraviolet Explorer are inconclusive about what allows galaxies to be Lyα emitters. The ‘missing’ lines were finally detected 20 years ago, at flux levels much below the original predictions - a difference that we understand to be predominantly due to the hierarchical growth of galaxies, such that star-forming objects at high redshift are much less massive than anticipated in the original prediction. The discovery and study of Lyα galaxies has blossomed into an invaluable method for understanding the youngest stages of galaxy formation, the circumgalactic medium, and ultimately the epoch of reionization. The high equivalent widths of Lyα galaxies from the earliest high-redshift surveys show that they are low-mass galaxies dominated by young stellar populations. The Sakura CLAW workshop (which used the Twitter hashtag #SakuraCLAW) gathered more than 110 participants (Fig. 1) who showcased progress that pushed the frontiers of Lyα galaxy science in sample size, sensitivity, redshifts and physical understanding..

Malhotra, Sangeeta↗
NASA NTRS2019

Characterizing the System Impulse Response Function from Photon-Counting LiDAR Data

NASA's Multiple Altimeter Beam Experimental LiDAR (MABEL) is an aircraft-based photon-counting laser altimeter designed as a simulator to test measurement techniques and algorithms for Advanced Topographic Laser Altimeter System (ATLAS), the sole instrument on NASA's Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) mission. By measuring the time of flight, pointing angle, and absolute position for individual photons, ICESat-2 provides detailed elevation measurements of earth's surface. Calculating accurate and precise elevations requires an understanding of how photons interact with surfaces, and characterization of the photon distribution after returning from surfaces. Neither MABEL nor ATLAS records the transmitted laser pulse shape, relying instead on aggregating several pulses worth of photons, often using histograms, to characterize the pulse shape. In this paper, we assess the limitations of using histograms and propose a more robust method to describe MABEL's system impulse-response function using an exponentially modified Gaussian distribution. We also provide standard error estimates for the arithmetic mean and standard deviation calculations, and for exponentially modified Gaussian parameters using a Monte Carlo sensitivity analysis. We apply this method to photon returns from a sea ice lead and from a dry salt lake bed as case studies for estimating the standard error associated with sample size for the arithmetic mean and standard deviation, and for the exponentially modified Gaussian parameters. We use these standard errors to calculate the minimum number of photons required to find both Gaussian and exponentially modified Gaussian distribution parameters within 3 cm of their parent population values.

photoncounting↗
NASA NTRS2019

Challenges in Qualification of Thermal Protection Systems in Extreme Entry Environments

Planetary entry vehicles employ ablative TPS materials to shield the aeroshell from entry aeroheating environments. To ensure mission success, it must be demonstrated that the heat shield system, including local features such as seams, does not fail at conditions that are suitably margined beyond those expected in flight. Furthermore, its thermal response must be predictable, with acceptable fidelity, by computational tools used in heat shield design. Mission assurance is accomplished through a combination of ground testing and material response modelling. A material's robustness to failure is verified through arcjet testing while its thermal response is predicted by analytical tools that are verified against experimental data. Due to limitations in flight-like ground testing capability and lack of validated high-fidelity computational models, qualification of heat shield materials is often achieved by piecing together evidence from multiple ground tests and analytical simulations, none of which fully bound the flight conditions and vehicle configuration. Extreme heating environments (>2000 W/sq. cm heat flux and >2 atm pressure), experienced during entries at Venus, Saturn and Ice Giants, further stretch the current testing and modelling capabilities for applicable TPS materials. Fully-dense Carbon Phenolic was the material of choice for these applications; however, since heritage raw materials are no longer available, future uses of re-created Carbon Phenolic will require re-qualification. To address this sustainability challenge, NASA is developing a new dual-layer material based on 3D weaving technology called Heat shield for Extreme Entry Environments (HEEET). Regardless of TPS material, extreme environments pose additional certification challenges beyond what has been typical in recent NASA missions. Scope of this presentation: This presentation will give an overview of challenges faced in verifying TPS performance at extreme heating conditions. Examples include: (1) Bounding aeroheating parameters (heat flux, pressure, shear and enthalpy) in ground facilities. How to certify TPS if environments can't be bounded or aeroheating parameters can't be simultaneously achieved. (2) Higher uncertainties in ground test environments (facility calibration and analytical predictions) at extreme conditions. (3) Testing in flows similar to planetary atmosphere composition (H2/He for Gas and Ice Giants). (4) Test sample size limitations for qualifying seam designs. (5) Lack of computational tools capable of simulating all significant aspects of TPS performance (including initiation and propagation of failures). This presentation will provide recommendations on how the EDL community can address these challenges and mitigate some of the risks involved in flying TPS materials at extreme conditions. Examples include: (1) Dedicated activity to understanding TPS failure modes. Develop computational tools capable of modelling fluid interaction with material's thermostructural response. Validate these tools through failure testing. A better understanding of failure mechanisms may eliminate the need to fully bound all aeroheating parameters in ground testing. (2) Enhancements to current testing facilities to simulate flight-like ablation mechanism (ex. testing in Nitrogen at Ames Interaction Heating Facility to limit oxidation in favor of more sublimation). (3) Improved characterization of test conditions with new diagnostic methods and determination of environment uncertainty through rigorous statistical analysis of available data. (4) Design margin policies that are directly tied to uncertainties in ground test environments and modelling fidelity

Mahzari, Milad↗
NASA NTRS2019

Multilevel Monte Carlo Estimation of Unbiased Expectation via Sample Reuse and the Low Variance Estimation of Asymptotic Rates

A new variant of the multilevel Monte Carlo estimator [5, 3, 9, 12] is presented for the estimation of expectation statistics that utilizes sample reuse in specified levels, explicitly removes approximation error bias associated with numerically computed output quantities of interest that have an asymptotic limit behavior, and permits a low variance estimate of the asymptotic rate of convergence to that limit. In addition, it is shown that this new multilevel Monte Carlo variant can yield a computational cost savings. A review of Monte Carlo and multilevel Monte Carlo estimators is presented that includes analysis of expected value, expected mean squared error, and the calculation of optimized multilevel sample size parameters. The multilevel Monte Carlo estimator produces estimates of expectation for numerically approximated output quantities of interest that are biased by approximation error. When the quantity of interest can be modeled as the asymptotic limit of numerically approximated output quantities of interest, it is theoretically possible to remove this approximation error bias in the multilevel Monte Carlo estimator. In actual implementations, however, this procedure is unreliable due to statistical variability and inaccuracy in estimating the needed asymptotic limit. Analysis and numerical experiment show that the proposed variant of the multilevel Monte Carlo method greatly reduces (in some cases eliminates) the statistical variability in this limit estimation.

Barth, Timothy↗
NASA NTRS2019

Investigating Neuro-Consequences of Spaceflight Using Drosophila Melanogaster

Research on human acclimation to spaceflight, including the recent NASA's Twin Study, reports complex effects of the spaceflight environment on health, with both acute and prolonged changes in multiple tissues. Spaceflight includes multiple factors such as microgravity, ionizing radiation, physiological stress, and disrupted circadian rhythms, that have been shown to contribute to pathophysiological responses that target immunity, bone and muscle integrity, cardiovascular and nervous systems. In this study, we used a well-established spaceflight model organism, Drosophila melanogaster, to assess spaceflight-associated changes on the nervous system. With 75% disease gene orthology to humans, short generation time, large sample size and ease of genetic, neuronal and behavioral studies, Drosophila is an excellent model to study nervous system dysfunction. Here, we present results from MVP-Fly-01 spaceflight mission that was launched on SpaceX CRS-14. The MVP hardware (developed by Techshot) used in this mission enabled us to have an in-flight 1g centrifuge, to distinguish the changes resulting from gravity versus those induced by other environmental factors associated with spaceflight. We observe behavioral impairments (p<0.001) and synaptic deficits, including decreased synaptic connections (p<0.05), in 3rd instar larvae which were developed in space. Furthermore, space-grown microgravity adults show a decrease in neuronal (p<0.05) and dendritic field (p<0.01) in adult brains coupled with an increased number of apoptotic cells (p<0.001) compared to in-flight 1g controls, suggesting increased neuronal loss under spaceflight conditions. In summary, we observe that altered gravity leads to gross neurological deficits. To better understand the long-term effects of spaceflight on the nervous system, longitudinal and multigenerational changes were also identified. This study will help elucidate the different approaches to prevent nervous system dysfunction in astronauts during spaceflight, while also contributing to a better understanding of the pathways that are related to some CNS disorders on Earth.

Iyer, Janani↗
NASA NTRS2020

NASA Ames Thermophysics Ground Test Facilities Supporting Future Planetary Atmospheric Entry

A review of the current facility capabilities for testing Thermal Protection Systems and quantifying their entry environments at NASA Ames Research Center is presented based on the expected targets of interest to the Planetary Science and Astrobiology communities. While the operational capabilities of these facilities are generally considered sufficient for supporting future missions to targets of interest, expanded ground test capabilities such as larger sample sizes, flight-relevant gas mixtures, dusty environments, and flight-relevant shear/pressure combinations would reduce future entry vehicle design uncertainties and applied margins. These reduced uncertainties may translate into reduced entry vehicle masses, increased robustness, and decreased operational risks during entry phases for science missions. Expanded ground test capabilities would also offer the ability to study material failure modes in environments even more representative of flight than are currently achievable. A list of desired future test capabilities is presented along with suggestions of possible methods of achieving each. The main recommendation of this paper is the undertaking of a detailed study of the benefits and associated costs of each of these expanded capabilities to determine the best future path.

arc jet↗
NASA NTRS2020

Investigating the Effect of Galaxy Interactions on the Enhancement of Active Galactic Nuclei at 0.5<z<3.0

Galaxy interactions and mergers are thought to play an important role in the evolution of galaxies. Studies in the nearby universe show a higher fraction of active galactic nuclei(AGNs)in interacting and merging galaxies than in their isolated counterparts, indicating that such interactions are important contributors to black hole growth. To investigate the evolution of this role at higher redshifts, we have compiled the largest known sample of major spectroscopic galaxy pairs(2381 withΔV<5000 km s−1)at 0.5<z<3.0 from observations in the COSMOS and CANDELS surveys. We identify X-ray and IR AGNs among this kinematic pair sample, a visually identified sample of mergers and interactions, and a mass-, redshift-, and environment-matched control sample for each in order to calculate AGN fractions and the level of AGN enhancement as a function of relative velocity, redshift, and X-ray luminosity. While we see a slight increase in AGN fraction with decreasing projected separation, overall, we find no significant enhancement relative to the control sample at any separation. In the closest projected separation bin(<25 kpc,ΔV<1000 km s−1),we find enhancements of a factor of-+0.940.160.21and-+1.000.310.58for X-ray and IR-selected AGNs, respectively. While we conclude that galaxy interactions do not significantly enhance AGN activity on average over 0.5<z<3.0 at these separations, given the errors and the small sample size at the closest projected separations, our results would be consistent with the presence of low-level AGN enhancement

Ekta A. Shah↗
NASA NTRS2021

Is the Last Inflight Rest Break Really the Best?

As pilots experienced in augmented long-haul flights know, current FAA regulations limit options for scheduling in-flight rest periods, such that on many long-haul operations the landing pilot needs to use the final bunk period, closest to top of descent (TOD). However, the logistics of a particular flight (e.g., timing of the flight, timing of passenger service) and the pilot’s own physiology may mean that the last rest break isn’t always the best. To study this, we conducted a large survey of pilots flying these operations. Pilots completed the survey after eligible flights and provided us with information on which rest break they used, how much sleep they received, factors that disrupted sleep and ratings on the quality of their sleep, and they also provided fatigue and alertness ratings at top-of-descent. Pilots from another US-based carrier were also surveyed, in collaboration with our research partners at Washington State University, to increase the sample size and gather insights between operations.

in-flight rest↗
NASA NTRSDate not supplied

Marangoni effect and its potential utilization in supporting lunar habitats and other extraterrestrial endeavors

Tears of wine is a phenomenon frequently observed as a ring of wine formed near the top of the glass generates droplets that fall back into the wine. This phenomenon can be explained by the Marangoni effect driven by the surface tension created via gradient on concentration and temperature along with the interface between two phases. Besides being observed while drinking wine, the Marangoni effect is crucial for welding metals, manufacturing integrated circuits, and growing crystals; the Marangoni effect might be also crucial in supporting lunar habitats and other extraterrestrial endeavors as vacuum and reduced gravity are expected to augment the Marangoni effect on extraterrestrial molten soil leading to sustainable extraterrestrial in-situ resources utilization (ISRU). Preliminary Marangoni effect assessment on molten lunar regolith was conducted via JSC-1A lunar regolith simulant under vacuum yielding a spontaneous upwards migration of a uniform molten thin-film front that climbed the crucible wall covering the entire wall’s surface and reaching the crucible’s top end. A temperature gradient within the melt’s bulk and along the crucible’s wall generates a surface tension large enough not only to form a meniscus within the three-phase junction (crucible’s wall, bulk melt, and vacuum) but also to supersede the gravitational force to create the upwards migration of a thin film front originated on the meniscus. The observed extensive wettability of the melt with the crucible surface, an additional key factor besides surface tension necessary to sustain upwards migration, is atypical to what it has been witnessed on molten JSC-1A lunar regolith simulant under non-vacuum conditions and smaller sample sizes. The unique formation and self-migration of a thin-film front could enable key ISRU processes such as thin-film coating, crystal growth, and feedstock generation for additive 3D printing. Further assessment on the higher-temperature vacuum-driven decomposition of the uniform thin-film front as it climbed the crucible’s wall revealed a significant decomposition of various simulant’s metal-oxide components into their respective oxygen and metal elements strengthening the feasibility of extraterrestrial generation and fractional separation of oxygen and metals/alloys with none or minimal need for terrestrial precursors. The Marangoni effect assessment on molten JSC-1A lunar regolith simulant clearly opens novel pathways in future extraterrestrial ISRU endeavors including manufacturing and mining. Extraterrestrial mining will require an operational approach completely different from the terrestrial one that heavily relies on not only mechanical excavation and transportation but also post-processing; an in-situ all-in-one process might be feasible via these two coupled phenomena, self-migration and decomposition.

J A Dominguez↗
NASA NTRS2020

Toward Complete Characterization: Prospects for Directly Imaging Transiting Exoplanets

High-contrast direct imaging of exoplanets can provide many important observables, including measurements of the orbit, spectra that probe the lower layers of the atmosphere, and phase variations of the planet, but cannot directly measure planet radius or mass. Our future understanding of directly imaged exoplanets will therefore rely on extrapolated models of planetary atmospheres and bulk composition, which need robust calibration. We estimate the population of extrasolar planets that could serve as calibrators for these models. Critically, this population of "standard planets" must be accessible to both direct imaging and the transit method, allowing for radius measurement. We show that the search volume of a direct imaging mission eventually overcomes the transit probability falloff with semimajor axis, so that as long as cold planets are not exceedingly rare, the population of transiting planets and directly imageable planets overlaps. Using current extrapolations of Kepler occurrence rates, we estimate that ~8 standard planets could be characterized shortward of 800 nm with an ambitious future direct imaging mission like LUVOIR-A and several dozen could be detected at the V band. We show the design space that would expand the sample size and discuss the extent to which ground- and space-based surveys could detect this small but crucial population of planets.

Christopher C. Stark↗
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 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↗