Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “personal”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 559 records · Page 31

Applicability of Public Dose Limits to Individuals on the Nevada National Security Site

Historically all persons working on the Nevada National Security Site (NNSS) were considered subject to worker dose limits when calculations of potential dose from the air pathway were conducted to demonstrate compliance with Title 42 United States Code (USC) Chapter 85, “The Clean Air Act,” and Title 40 Code of Federal Regulations (CFR) Part 61, Subpart H, “National Emission Standards for Hazardous Air Pollutants (NESHAP).” Calculations were also conducted for the all-pathways potential dose to demonstrate compliance with U.S. Department of Energy (DOE) Order DOE O 458.1 Chg. 3, “Radiation Protection of the Public and the Environment.” The need to evaluate environmental air sampling locations and past regulator questions about the existence of persons potentially subject to public dose limits being on the NNSS drove this assessment (letter from EPA [U.S. Environmental Protection Agency] Region 9 to DOE/Nevada Operations Office, dated September 3, 1999). This assessment also supports determining those persons subject to public dose limits from the all pathways perspective. A person that is a member of the public is subject to public dose limits.

61 RADIATION PROTECTION AND DOSIMETRY↗

Radiological Impact of 2023 Operations at the Savannah River Site

This report presents the environmental dose assessment methods and the estimated potential doses to the public from 2023 Savannah River Site (SRS) air and liquid radioactive releases. Also documented are potential doses from special-case exposure scenarios, such as the consumption of wildlife or goat milk. Dose to the Offsite Representative Person The 2023 dose to the offsite representative person from SRS liquid releases was 0.14 mrem and from SRS air releases it was 0.016 mrem. To show compliance with the U. S. Department of Energy (DOE) all pathway dose standard of 100 mrem/yr, SRS conservatively adds these two doses for a total representative person dose of 0.16 mrem which is 0.16% of the DOE standard. Sportsman Doses Onsite Hunter: SRS conducts annual hunts to control onsite deer and feral hog populations. The estimated dose from consuming harvested deer or hog meat is determined for every onsite hunter. During 2023, the maximum potential dose an onsite hunter received was 9.42 mrem, or 9.42% of DOE’s 100 mrem/yr all pathway dose standard. Creek Mouth Fisherman: SRS estimated the maximum potential dose from fish consumption at 0.17 mrem from bass collected at the mouth of Lower Three Runs. This dose is 0.17% of the DOE standard. SRS bases this hypothetical dose on the low probability scenario that, during 2023, a fisherman consumed 24 kg (53 lbs) of bass caught exclusively from the mouth of Lower Three Runs. Release of Material Containing Residual Radioactivity SRS did not release any real property (land or buildings) in 2023. SRS unconditionally released a total of 13,324 items of personal property (such as tools) from radiological areas in 2023. Most of these items did not leave the Site. However, all of these items required no additional radiological controls post-survey as they met DOE Order 458.1 release criteria. Radiation Dose to Aquatic and Terrestrial Biota SRS conducts screening evaluations of plant and animal doses for aquatic and terrestrial ecosystems. For 2023, all SRS aquatic system locations passed the initial (Level 1) screenings and no further assessments were required at those locations. For the land-based systems evaluation, SRS performed initial screenings using concentration data from the five onsite radiological soil sampling locations. Typically, SRS collects and analyzes only one soil sample per year from each location. For 2023, all land-based locations passed their initial (Level 1) pathway screenings.

54 ENVIRONMENTAL SCIENCES↗

Development of Advanced Smart Ventilation Controls for Residential Applications

This study examined the use of zoned ventilation systems using a coupled CONTAM/EnergyPlus model for new California dwellings. Several smart control strategies were developed with a target of halving ventilation-related energy use, largely through reducing dwelling ventilation rates based on zone occupancy. The controls were evaluated based on the annual energy consumption relative to continuously operating non-zoned, code-compliant mechanical ventilation systems. The systems were also evaluated from an indoor air quality perspective using the equivalency approach, where the annual personal concentration of a contaminant for a control strategy is compared to the personal concentration that would have occurred using a continuously operating, non-zoned system. Individual occupant personal concentrations were calculated for the following contaminants of concern: moisture, CO2, particles, and a generic contaminant. Zonal controls that saved energy by reducing outside airflow achieved typical reductions in ventilation-related energy of 10% to 30%, compared to the 7% savings from the unzoned control. However, this was at the expense of increased personal concentrations for some contaminants in most cases. In addition, care is required in the design and evaluation of zonal controls, because control strategies may reduce exposure to some contaminants, while increasing exposure to others.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Package Data for CERF-Data Centers

This dataset contains sample input 100m resolution raster files for running the CERF-DC python package (see https://github.com/IMMM-SFA/cerf_data_centers) at the state level across the CONUS. Due to data availability constraints, some of the items included in this dataset are proxies or assumptions for siting factors used in the model. These are individually noted in the item descriptions and can be exchanged with more detailed information upon availability. Data Descriptions The following raster files are included in the data download: state_siting_region.tif — State areas identified by state FIPS code composite_siting_suitability.tif — Value of 1 indicates suitable siting location, 0 otherwise. The following areas are excluded from siting: Areas within 300m of a federal airport runway Waterbodies Areas with slope >16% Areas susceptible to sinkholes High coastal or inland flood risk areas Local, state, and federal parks, leisure areas, and cemeteries Areas >2 km away from electric substations Areas >5 km away from a municipal water supplier service area Areas >2 km away from high-speed fiber provider service territory Protected Areas Database of the United States (PAD-US) areas Railroads, major roadways, and minor roadways Military areas and training grounds Developed lands Areas >0.8 km (0.5 miles) from developed lands land_value_dollar_per_sqft.tif — USD per square foot (sqft) derived from USDA $/acre land cost personal_property_tax_rate.tif — Personal property tax rate by state. Uses an assumed 0.0125 personal property tax rate for states with personal property tax, 0 for states without personal property tax. real_property_tax_rate.tif — Real property tax rate. Based on county level residential real estate property tax rates. sales_tax_rate.tif — Sales tax rate by state. mechanical_cooling_fraction.tif — Fraction of year (values between 0 and 1, inclusive) that the data center would be cooled through mechanical processes based on local water stress and humidity levels. water_cooling_fraction.tif — Fraction of year (values between 0 and 1, inclusive) that the data center would be cooled through evaporative (water cooled) processes based on local water stress and humidity levels. distance_to_substation.tif — Distance to nearest substation in hundreds of meters (i.e., value of 1 equals a distance of 100m). Offshore areas have a value of 0. industrial_electricity_rates_dollar_per_kwh.tif — USD/kWh industrial electricity rates. Represents the average industrial rate across all utilities that operate within a given county. Values are derived from the US Utility Rate Database. commercial_electricity_rates_dollar_per_kwh.tif — USD/kWh commercial electricity rates. Represents the average commercial rate across all utilities that operate within a given county. Values are derived from the US Utility Rate Database. data_center_market_locations.tif — Grid cells with positive values represent the centroid of existing data center market clusters. The value of non-zero grid cells represents the number of data centers in the market cluster. All other grid cells have a value of 0. Geospatial Metadata CRS: Albers Equal Area Conic (ESRI:102003) Extent: -2415585.0000000023283064,-1441981.2605773280374706 : 2384414.9999999976716936,1708018.7394226719625294 Dimensions: X: 48000 Y: 31500 Bands: 1 Origin: -2415585.0000000023283064,1708018.7394226719625294 Pixel Size: 100,-100 Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License This data is made available under a CCBY4.0 License Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall↗

Package Data for CERF-Data Centers

This dataset contains sample input 100m resolution raster files for running the CERF-DC python package (see https://github.com/IMMM-SFA/cerf_data_centers) at the state level across the CONUS. Due to data availability constraints, some of the items included in this dataset are proxies or assumptions for siting factors used in the model. These are individually noted in the item descriptions and can be exchanged with more detailed information upon availability. Data Descriptions The following raster files are included in the data download: state_siting_region.tif — State areas identified by state FIPS code composite_siting_suitability.tif — Value of 1 indicates suitable siting location, 0 otherwise. The following areas are excluded from siting: Areas within 300 m of a federal airport runway or within an airport area boundary Waterbodies Areas with slope >16% Areas susceptible to sinkholes High coastal or inland flood risk areas Local, state, and federal parks, leisure areas, and cemeteries Areas >2 km away from electric substations Areas >5 km away from a municipal water supplier service area Areas >2 km away from high-speed fiber provider service territory USGS Protected Areas Database of the United States (PAD-US) GAP status 1, 2, or 3 areas US National Parks Wetlands USFWS critical habitats BIA land areas Railroads, major roadways, and minor roadways Military areas and training grounds NLCD developed lands Areas >0.8 km (0.5 miles) from NLCD developed lands land_value_dollar_per_sqft.tif — USD per square foot (sqft) derived from USDA $/acre land cost personal_property_tax_rate.tif — Personal property tax rate by state. Uses an assumed 0.0125 personal property tax rate for states with personal property tax, 0 for states without personal property tax. real_property_tax_rate.tif — Real property tax rate. Based on county level residential real estate property tax rates. sales_tax_rate.tif — Sales tax rate by state. mechanical_cooling_fraction.tif — Fraction of year (values between 0 and 1, inclusive) that the data center would be cooled through mechanical processes based on local water stress and humidity levels. water_cooling_fraction.tif — Fraction of year (values between 0 and 1, inclusive) that the data center would be cooled through evaporative (water cooled) processes based on local water stress and humidity levels. distance_to_substation.tif — Distance to nearest substation in hundreds of meters (i.e., value of 1 equals a distance of 100m). Offshore areas have a value of 0. industrial_electricity_rates_dollar_per_kwh.tif — USD/kWh industrial electricity rates. Represents the average industrial rate across all utilities that operate within a given county. Values are derived from the US Utility Rate Database. commercial_electricity_rates_dollar_per_kwh.tif — USD/kWh commercial electricity rates. Represents the average commercial rate across all utilities that operate within a given county. Values are derived from the US Utility Rate Database. data_center_market_locations.tif — Grid cells with positive values represent the centroid of existing data center market clusters. The value of non-zero grid cells represents the number of data centers in the market cluster. All other grid cells have a value of 0. Geospatial Metadata CRS: Albers Equal Area Conic (ESRI:102003) Extent: -2415585.0000000023283064,-1441981.2605773280374706 : 2384414.9999999976716936,1708018.7394226719625294 Dimensions: X: 48000 Y: 31500 Bands: 1 Origin: -2415585.0000000023283064,1708018.7394226719625294 Pixel Size: 100,-100 Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License This data is made available under a CCBY4.0 License Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall↗

Asynchronous file transfer to IBM PC's

The Asynchronous File Transfer System is used for interactively selecting and tramsmitting text files from the Langley Research Center's Business Data Systems Division (BDSD) host processor to an IBM Personal Computer. The IBM asynchronous communications support package is used for handling the communications on the personal computer. An application program (NATURAL, COBOL, etc.) is used for selecting and formatting the records to be transmitted, and three subroutine modules residing on the BDSD host processor are used for interfacing the application program and the communications software. Each record transmitted to the Personal Computer must be in the standard ASCII format. This record format is directly accessible by BASIC and many of the personal computer software packages provide utility programs for converting them to the format required for the particular package in question.

Hoerger, J.↗

Brainstem response and state-trait variables

A series of investigations are summarized from a personality research program that have relevance for mental state estimation. Of particular concern are those personality variables that are believed to have either a biological or perceptual basis and their relationship to human task performance and psychophysiology. These variables are among the most robust personality measures and include such dimensions as extraversion-introversion, sensation seeking, and impulsiveness. These dimensions also have the most distinct link to performance and psychophysiology. Through the course of many of these investigations two issues have emerged repeatedly: these personality dimensions appear to mediate mental state, and mental state appears to influence measures of performance or psychophysiology.

Gilliland, Kirby↗

Selection for optimal crew performance - Relative impact of selection and training

An empirical study supporting Helmreich's (1986) theoretical work on the distinct manner in which training and selection impact crew coordination is presented. Training is capable of changing attitudes, while selection screens for stable personality characteristics. Training appears least effective for leadership, an area strongly influenced by personality. Selection is least effective for influencing attitudes about personal vulnerability to stress, which appear to be trained in resource management programs. Because personality correlates with attitudes before and after training, it is felt that selection may be necessary even with a leadership-oriented training cirriculum.

Chidester, Thomas R.↗

Degradation of the lunar vacuum by a moon base

Several industrial processes requiring high and ultra-high vacuum similar to the lunar vacuum are outlined. The effects of a 20-person lunar base and a 250-person industrial facility on this vacuum are discussed. It is shown that exhaust from transport spacecraft and leakage from the habitat will be comparable to the daytime gas pressure for the 20-person base, and will degrade the vacuum to the range of 2 x 10 to the -9th torr for the use of 250-person facility. This will result in replacing the mostly nonreactive gases hydrogen, helium, and neon with more reactive gases containing carbon and oxygen. This vacuum is still good enough to perform many important vacuum processes such as plasma-deposition of amorphous silicon for solar cells, but processes such as molecular beam epitaxy or locating an intersecting beam accelerator on the moon will require additional vacuum pumping.

Landis, Geoffrey↗

Validation of astronaut psychological select-in criteria

An optional astronaut selection strategy would select-in individuals on the basis of personality attributes associated with superior performance. Method: A test battery, the Astronaut Personal Characteristics Inventory (ASTROPCI) was developed which assesses positive and negative components of achievement, motivation, and interpersonal orientations and skills. The battery was administered to one hundred three astronaut candidates and sixty-six current U.S. Shuttle astronauts. To determine performance, a series of conceptual areas related to space flight performance were defined. Astronauts rated their peers on each of these dimensions. Ratings were obtained on all eighty-four current astronauts (excluding those selected in 1990). In addition to peer ratings, supervisor assessments of the same dimensions were obtained for each astronaut. Results: Cluster and factor analysis techniques were employed to isolate subgroups of astronauts. Those astronauts with both high achievement needs and interpersonal skills were most often rated among the top five by their peers and least often rated among the lowest five. A number of scales discriminated between astronauts rated high and low on one or more performance dimensions. Conclusions: The results parallel findings from the personality assessment of individuals in other demanding professions, including aircraft pilots and research scientists, suggesting that personality factors are significant determinants to performance in the space environment.

Rose, R. M.↗

Predictors of Behavior and Performance in Extreme Environments: The Antarctic Space Analogue Program

To determine which, if any, characteristics should be incorporated into a select-in approach to screening personnel for long-duration spaceflight, we examined the influence of crewmember social/ demographic characteristics, personality traits, interpersonal needs, and characteristics of station physical environments on performance measures in 657 American men who spent an austral winter in Antarctica between 1963 and 1974. During screening, subjects completed a Personal History Questionnaire which obtained information on social and demographic characteristics, the Deep Freeze Opinion Survey which assessed 5 different personality traits, and the Fundamental Interpersonal Relations Orientation-Behavior (FIRO-B) Scale which measured 6 dimensions of interpersonal needs. Station environment included measures of crew size and severity of physical environment. Performance was assessed on the basis of combined peer-supervisor evaluations of overall performance, peer nominations of fellow crewmembers who made ideal winter-over candidates, and self-reported depressive symptoms. Social/demographic characteristics, personality traits, interpersonal needs, and characteristics of station environments collectively accounted for 9-17% of the variance in performance measures. The following characteristics were significant independent predictors of more than one performance measure: military service, low levels of neuroticism, extraversion and conscientiousness, and a low desire for affection from others. These results represent an important first step in the development of select-in criteria for personnel on long-duration missions in space and other extreme environments. These criteria must take into consideration the characteristics of the environment and the limitations they place on meeting needs for interpersonal relations and task performance, as well as the characteristics of the individuals and groups who live and work in these environments.

Palinkas, Lawrence A.↗

Emotional/Mental Challenges Pre-, In-, and Post-Flight

Dr. Voss has flown aboard the Space Shuttle five times. She knows well her inner concerns, emotions, and mental challenges attending such highly demanding and risky adventures. And she has shared those ideas with her colleagues. She notes that their busy training schedules and fully committed on orbit time allow little time for dwelling on most of these issues. However, they are nonetheless real and may not be ignored with impunity. She thinks that perhaps they are more striking for rookie space farers, but all spacecrew members share them and can profit by assuring proper support and unique solutions for their own specific situation, which could vary with the mission. In her own experience, she found notable benefit from sharing with close members of her family, both before flight and during. The latter has proved of great value to all crew persons in the form of their personal ground contact time with family and friends. In addition, how one arranges and what one provides in the on board personal space and time goes far toward keeping a confident and upbeat view of the big picture. The type and amount of off duty diversions (e.g., music, reading material) are important, as are how one participates in group time. And it is universally agreed that viewing time at the spacecraft windows offers great joy and calm. Dr. Voss conjectures that there could be a difference in how people deal with these matters on busy, short-duration (Shuttle type) missions versus those of longer ones, particularly out of low earth orbit, where the options in the advent of mishap are fewer. Her final opinion is one of optimism and assurance that the human person will do well in coping with this new environment.

Voss, Janice↗

Designing Facilities for Collaborative Operations

A methodology for designing operational facilities for collaboration by multiple experts has begun to take shape as an outgrowth of a project to design such facilities for scientific operations of the planned 2003 Mars Exploration Rover (MER) mission. The methodology could also be applicable to the design of military "situation rooms" and other facilities for terrestrial missions. It was recognized in this project that modern mission operations depend heavily upon the collaborative use of computers. It was further recognized that tests have shown that layout of a facility exerts a dramatic effect on the efficiency and endurance of the operations staff. The facility designs (for example, see figure) and the methodology developed during the project reflect this recognition. One element of the methodology is a metric, called effective capacity, that was created for use in evaluating proposed MER operational facilities and may also be useful for evaluating other collaboration spaces, including meeting rooms and military situation rooms. The effective capacity of a facility is defined as the number of people in the facility who can be meaningfully engaged in its operations. A person is considered to be meaningfully engaged if the person can (1) see, hear, and communicate with everyone else present; (2) see the material under discussion (typically data on a piece of paper, computer monitor, or projection screen); and (3) provide input to the product under development by the group. The effective capacity of a facility is less than the number of people that can physically fit in the facility. For example, a typical office that contains a desktop computer has an effective capacity of .4, while a small conference room that contains a projection screen has an effective capacity of around 10. Little or no benefit would be derived from allowing the number of persons in an operational facility to exceed its effective capacity: At best, the operations staff would be underutilized; at worst, operational performance would deteriorate. Elements of this methodology were applied to the design of three operations facilities for a series of rover field tests. These tests were observed by human-factors researchers and their conclusions are being used to refine and extend the methodology to be used in the final design of the MER operations facility. Further work is underway to evaluate the use of personal digital assistant (PDA) units as portable input interfaces and communication devices in future mission operations facilities. A PDA equipped for wireless communication and Ethernet, Bluetooth, or another networking technology would cost less than a complete computer system, and would enable a collaborator to communicate electronically with computers and with other collaborators while moving freely within the virtual environment created by a shared immersive graphical display.

Norris, Jeffrey↗

Systems and methods for remote long standoff biometric identification using microwave cardiac signals

Systems and methods for remote, long standoff biometric identification using microwave cardiac signals are provided. In one embodiment, the invention relates to a method for remote biometric identification using microwave cardiac signals, the method including generating and directing first microwave energy in a direction of a person, receiving microwave energy reflected from the person, the reflected microwave energy indicative of cardiac characteristics of the person, segmenting a signal indicative of the reflected microwave energy into a waveform including a plurality of heart beats, identifying patterns in the microwave heart beats waveform, and identifying the person based on the identified patterns and a stored microwave heart beats waveform.

McGrath, William R.↗

Artificial Intelligence Software for Assessing Postural Stability

A software package reads and analyzes pressure distributions from sensors mounted under a person's feet. Pressure data from sensors mounted in shoes, or in a platform, can be used to provide a description of postural stability (assessing competence to deficiency) and enables the determination of the person's present activity (running, walking, squatting, falling). This package has three parts: a preprocessing algorithm for reading input from pressure sensors; a Hidden Markov Model (HMM), which is used to determine the person's present activity and level of sensing-motor competence; and a suite of graphical algorithms, which allows visual representation of the person's activity and vestibular function over time.

Lieberman, Erez↗

Replication of Segments of STS-94 as a Lunar Surface Mission

The Artemis program established the goal to land the first woman and first person of color on the Moon, but that is only the beginning of the program. Artemis plans to move towards a sustainable phase, with four crew living on the lunar surface for roughly 30-day annual missions, operating from a Pressurized Rover (PR) and a Surface Habitat (SH). The crew will split up – two living and operating from the PR and the others in the SH, perhaps swapping places halfway through the surface mission. There is a significant degree of maturity surrounding PR operations due to the NASA Desert Research and Technology Studies field tests from 2007-2011. However, there is a degree of uncertainty surrounding activity in the SH, with anecdotal speculation among some Artemis lunar surface engineers that the SH crew might not be fully utilized. Contrary to this belief, there is evidence in US human spaceflight history that the SH crew may instead be extremely busy. In particular, portions of the STS-94 Microgravity Science Lab mission demonstrate a science-based use case for crew activity in the SH. Fifteen Spacelab missions (not including STS-83, which was terminated early due to a fuel cell problem and reflown as STS-94) and eight Spacehab missions used the previously mentioned modules as science labs to expand the science capability of shuttle orbital missions, most flown prior to the assembly of the International Space Station. STS-94 is selected as an example of these flights. STS-94 was a 15.7-day mission with a 7-person crew. The crew operated in split 12-hour shifts, enabling 24-hour science operations. STS-94 used the space shuttle Columbia with the Spacelab module and Extended Duration Orbiter pallet in the cargo bay. The STS-94 physical science investigations were intended to explore various physical aspects of microgravity. These same investigations can be conducted on the Moon to explore 1/6 gravity. The Spacelab module was outfitted with several key facilities to enable this research: Large Isothermal Furnace, Combustion Module-1, Droplet Combustion Experiment, EXPRESS Rack, TEMPUS, Gravity Measurement Devices, and Middeck Glovebox. The current reference concept for the SH is a hybrid inflatable in a vertical orientation. Fairly typical of hybrid inflatables, the SH has an aluminum core pressurized section and a larger inflatable volume, in this case attaching to the top of the core. Two crew will live in the SH at a time, though four can briefly occupy the habitat, such as for contingency or handover activities. This paper will discuss use of the STS-94 physical science equipment in the SH and options for the architectural layout of a resulting physics laboratory. It will also discuss how this laboratory may accompany other science facilities such as biology, human research, and geology. The person hours used by the STS-94 crew to conduct physical science research will be estimated and then mapped to a two-person SH crew, making it possible to determine how many days are required in the SH to complete the lunar gravity physical science investigations at varying levels of crew availability.

STS-94↗

Human Factors and Behavioral Performance Exploration Measures Harmonized Across HERA, NEK, and ISS: Teams Risk

BACKGROUNDThe Human Factors and Behavioral Performance Exploration Measures (HFBP-EM) suite is a set of standardized measures to assess behavioral health and performance risk related to future exploration class missions, and to support reduction of the Human Research Program’s (HRP) Behavioral Medicine (BMed), Team, Sleep, and Human Systems Integration Architecture risks. HFBP-EM were collected during Human Exploration Research Analogs (HERA) campaigns 4 (C4) and 5 (C5), and during SIRIUS 17 and 19 missions in the Russian Ground Based Experiment Complex, NEK, to document the feasibility, flexibility, and acceptability of these measures in analogsof the spaceflight environment. A subset of the HFBP-EM suite was collected during spaceflight as part HRP’s Standard Measures in Spaceflight Project. Whenever possible, the HFBP-EM protocol and measures are kept the same across studies, however, differences across research settings (e.g., experimental manipulations, mission scenarios, mission length) and implementation of the measures require the data are harmonized to ensure comparable views across missions. The purpose of our project is to develop a harmonized database of HFBP-EM data from different settings, and to summarize the trajectory of behavioral health and performance within and between research settings. In this presentation, we will summarize the harmonized dataset and the trajectory of measures related to the Team Risk, including team performance, team cohesion, team processes, and psychological safety, over time and between and within settings.METHODSWe followed best practices for data harmonization. Characteristics of each research setting were assessed for harmonization potential, and we deemed NEK-SIRIUS 17 as inappropriate due to study aims, length, and data quality. Common variables of interest were identified. Study characteristics and key variables with which datafiles could be merged were defined as “meta-data.” HFBP-EM data from all settings were processed under a common format. We then created a harmonized team-level database designed to facilitate analyses that address HRP research gaps related to HRP’s Team risk. In this database, team cohesion, processes, performance, psychological safety, and group living were operationalized as the team mean of the crew responses for each data collection (e.g., on mission day 7). Data collected on the International Space Station (ISS) included a subset of scale items administered to participants. Data collected from ISS team members within +/- 7 days of the first data collection and every following 30 +/-4 days were aggregated to the team level. We generated figures that display the mean and variability of team constructs across research settings. We also generated plots of changes in team constructs with mission day and with percentage of the mission completed. Where possible, we compared data from spaceflight analogs with data from astronauts aboard the ISS. RESULTS AND DISCUSSIONThe team-level harmonized database was structured such that each row represents data for a team on a specific mission day. Team constructs (e.g., team cohesion) were included as columns (i.e., wide format) with repeated measures across mission days given in rows (i.e., long format). The database included data from 18 crews: five, 4-person American crews in HERA C4, four 4-person American crews in HERA C5, one 6-person multinational crew in NEK-SIRIUS 19, and eight, 2–11-person multinational crews aboard the ISS. Results provide insights into mission and campaign differences in team functioning and performance. For example, between campaign differences were observed for team processes—the interdependent team actions that orchestrate taskwork in pursuit of the team’s goals [1]. Greater between-team variability on team processes was detected during HERA C4 than during C5, and a downward trend was observed over the duration of C4, but not C5 or SIRIUS 19. This may be due to the campaign-level differences such as the sleep deprivation implemented during C4. Responses on the subset of team process items administered on the ISS indicate between-crew variability more like those observed in C4 than C5 and NEK, with some, but not all ISS crews demonstrating a downward trend over time. Additional findings will be presented. REFERENCESMarks, M. A., et al (2001) Academy of Management Review, 26(3), 356-376.

S T Bell↗

Watching Without Seeing a Tool to Surveil Astronaut Health Outcomes While Maintaining Astronaut Medical Privacy

BACKGROUND The Privacy Act of 1974 regulates the use a nd disclosure of personally identifiable information by US Federal agencies. The Act applies to biographical, financial, a nd other identity-linked information, a s well a s personal health information (PHI). As such, the use of astronaut PHI is limited to authorized personnel for preapproved uses, with data reporting often limited to aggregated information about groups. These limitations on the use a nd reporting of astronaut PHI complicates surveillance efforts, wherein epidemiologists a t the National Aeronautics and Space Administration (NASA)monitor the incidence of targeted health conditions in the astronaut population, or to discover emerging trends of aging and disease. Stratification on one or more covariates –particularly time-period, sex, a nd mission participation –can lead to extremely small datasets such that the reporting of results is potentially attributable to individuals. An additional challenge is the small size of the astronaut population, both in terms of numbers of individuals a s well a s in terms of density of exposure time. Such small datasets yield volatile rate estimates that are difficult to interpret. To a id the epidemiological surveillance efforts, a surveillance tool is required that can (a) satisfy the need for rapid computation of condition-specific incidence and mortality rates; (b) improve the statistical estimates of these estimated rates; and (c) maintain astronaut privacy. Here we describe a nd demonstrate such a tool. METHODS We devised a system that models incidence a nd mortality rates rather than calculating them directly. This ha s the advantage of using all the available data to derive the estimates, lea ding to rates that a re not attributable to any one individual, a nd a re a s numerically stable a s they can be given the extremely limited data. The system models disease endpoints using a Poisson regression model with exposure density (measured in person-years) a s a n offset term. By doing so the model is estimating event counts per person-year, equivalent to modeling the rates directly. It uses a standard (pre-specified)set of covariates; the system does not engage in “model-building” as model parsimony is not the goa l. Instead, it is explicitly recognized that if a covariate is not statistically significant a nd not a confounder then it will likely have very little effect on the estimate of the incidence a nd mortality rates. Users are able to specify the disease endpoint of interest and the covariates over which they would like to stratify. The system then uses the resulting model to compute the estimated rates for the user-chosen configuration of variables as visualizes those either over an age range within a specified time-period, or over time for astronauts with a specified age range. RESULTS The first iteration of the tool computes incidence a nd mortality rates for cardiovascular conditions and cancers. Code ha s been developed to retrieve the appropriate data from the IMPALA analysis platform, compute the models for incidence a nd mortality, a nd then use those models to generate the corresponding rate curves. A companion graphical user interface allows the user to specify the curves and visualize the results. CONCLUSIONS It is important to note that the rapid surveillance tool described here is neither meant to be a definitive assessment of the incidence or mortality of any particular disease or condition in the astronaut population, nor is it meant to be used for research purposes. Rather, it is meant as an early indicator that in-depth investigation may be warranted. By automating a repetitive process and leveraging carefully curated astronaut health outcomes, the tool makes possible a rapid “first look” into known areas of concern, and, if used judiciously, may surface new areas of concern for long-term astronaut health. This work is supported in part by the Translational Research Institute for Space Health (TRISH) through NASA Cooperative Agreement NNX16AO69A.

R J Reynolds↗