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At least 541 records · Page 30

Working Fluid Trade Study for a Two-Phase Mechanically Pumped Loop Thermal Control System

NASA Jet Propulsion Laboratory is investigating a two-phase mechanically pumped fluid loop (MPFL) technology for spacecraft thermal control for future planetary space science mission concepts. The two-phase technology combines the potential of single-phase MPFL and the passive two-phase heat pipe systems. Previous two-phase MPFL studies at JPL have identified an evaporator system with a separated flow architecture as providing a robust light mass thermal control system with very high spatial and temporal thermal stability required by the science instruments on these missions. These studies have further identified the thermophysical properties of the working fluid to be key to the performance of a two-phase fluid loop. This paper describes the methodology used in the selection of the working fluids for optimizing the performance of the two-phase MPFL. A high level model was developed that includes the constraints and boundaries driven by the system components. The performance of fluids from the REFPROP database are investigated and rated for this system. The working fluid attributes such as cost, hazardous properties, and heritage were taken into account in this selection. A typical spacecraft dissipating 1000 W and a fluid loop consisting of an evaporator, accumulator, radiator, and associated tubing components is used as an example in this study.

Daimaru, Takuro↗

Working Fluid Trade Study for a Two-Phase Mechanically Pumped Loop Thermal Control System

NASA Jet Propulsion Laboratory is investigating a two-phase mechanically pumped fluid loop (MPFL) technology for spacecraft thermal control for future planetary space science mission concepts. The two-phase technology combines the potential of single-phase MPFL and the passive two-phase heat pipe systems. Previous two-phase MPFL studies4,5 at JPL have identified an evaporator system with a separated flow architecture as providing a robust light mass thermal control system with very high spatial and temporal thermal stability required by the science instruments on these missions. These studies have further identified the thermophysical properties of the working fluid to be key to the performance of a two-phase fluid loop. This paper describes the methodology used in the selection of the working fluids for optimizing the performance of the two-phase MPFL. A high level model was developed that includes the constraints and boundaries driven by the system components. The performance of fluids from the REFPROP database were investigated and rated for this system. The working fluid attributes such as cost, hazardous properties, and heritage were taken into account in this selection. A typical spacecraft dissipating 1000 W and a fluid loop consisting of an evaporator, accumulator, radiator, and associated tubing components was used as an example in this study.

Daimaru, Takuro↗

Machine Learning Algorithms for Aerosol and Cloud Detection Using CATS on the ISS

Clouds and aerosols are one of the largest uncertainties in understanding and forecasting the Earth’s changing climate system. The type and height of aerosols are important factors in determining the top-of-atmosphere (TOA) radiation budget, either direct reflection of solar radiation back to space and/or absorption of solar radiation. In addition to their impact on the Earth’s climate system, aerosols near the surface from wildfires, man-made pollution events, and dust storms are hazardous to human health. The phase and height of clouds also play a critical role in determining the role of clouds in the Earth’s climate system. Cirrus clouds in the upper troposphere can induce a significant daytime TOA warming effect, while liquid water clouds near the surface cause a large corresponding cooling effect. Lidar measurements provide accurate vertically resolved information about clouds and aerosols, including complex multi-layer scenes where passive sensors are challenged and at night, when passive sensors are unable to measure cloud and aerosol properties. The Cloud-Aerosol Transport System (CATS) is a lidar instrument that operated for 33 months on the International Space Station (ISS) at the 1064 nm wavelength to measure attenuated total backscatter and depolarization ratio. These fundamental measurements are used to derive “vertical feature mask” cloud and aerosol products, including layer top/base heights, layer geometrical thickness, aerosol type, and cloud phase. While space-based lidar systems like CATS provide cloud and aerosol vertical distributions that improve our understanding of the climate system, averaging of the daytime data from these sensors is required, at the expense of spatial resolution, to improve the daytime signal-to noise (SNR) and thus atmospheric layer detection. This presentation shows results from machine learning (ML) techniques that, when applied to CATS data: 1. improve the 1064 nm SNR 2. enable detection of atmospheric features during daytime with a horizontal resolution of 350 m or 5 km (compared to the 60 km required for standard CATS data products) 3. increase the number of atmospheric layers detected in the CATS data. A Convolutional Neural Network (CNN) trained using CATS standard data products also demonstrated the potential for improved cloud-aerosol discrimination, cloud phase, and aerosol typing compared to the operational CATS algorithms for cloud edges and complex near-surface scenes during daytime. The ML tools described in this paper can facilitate the development of smaller, low-cost lidar systems in the future and enable real-time accessibility of lidar data products from future lidar systems for monitoring and forecasting of hazardous events.

John Yorks↗

Fiber-Optic Coupled Lidar Receiver System to Measure Stratospheric Ozone

The measurement of ozone in the atmosphere has become increasingly important over the past two decades. Significant increases of ozone concentrations in the lower atmosphere, or troposphere, and decreases in the upper atmosphere, or stratosphere, have been attributed to man-made causes. High ozone concentrations in the troposphere pose a health hazard to plants and animals and can add to global warming. On the other hand, ozone in the stratosphere serves as a protective barrier against strong ultraviolet (UV) radiation from the sun. Man-made CFC's (chlorofluorocarbons) act as a catalyst with a free oxygen atom and an ozone molecule to produce two oxygen molecules therefore depleting the protective layer of ozone in the stratosphere. The beneficial and harmful effects of ozone require the study of ozone creation and destruction processes in the atmosphere. Therefore, to provide an accurate model of these processes, an ozone lidar system must be able to be used frequently with as large a measurement range as possible. Various methods can be used to measure atmospheric ozone concentrations. These include different airborne and balloon measurements, solar occulation satellite techniques, and the use of lasers in lidar (high detection and ranging,) systems to probe the atmosphere. Typical devices such as weather balloons can only measure within the direct vicinity of the instrument and are therefore used infrequently. Satellites use solar occulation techniques that yield low horizontal and vertical resolution column densities of ozone.

Harper, David Brent↗

Open Science for Life in Space: Data Sharing and Tools for Knowledge Discovery

The next era in human space exploration is rapidly approaching and will require the use of countermeasures to deep space health hazards. The development of countermeasures (or, there-purposing of existing agents) will be highly dependent on our understanding of basic biological responses to space stressors (e.g. ionizing radiation, altered gravitational fields, altered day-night cycles, confinement, isolation, hostile-closed environments, distance-duration from Earth, exposure to celestial regolith, etc.). The fast-growing array of space biological data, which in the past was simply archived after minimal analysis, holds great potential if it can be reorganized and formatted for Open Science. Organizing the data for such analysis is a challenge because of its diverse nature (molecular, cellular, tissue, imaging, whole organism and behavior). We will discuss here several strategies that NASA's Biological and Physical Science Division has put in place to maximize the return on investment for spaceflight bioscience data. Open Science, as a scientific philosophy, is the concept that the more people who have access to the data, the more knowledge will be gained from it. This guiding principle led NASA to develop GeneLab in 2015. GeneLab houses spaceflight and relevant ground-based multi-omics data, and has grown to ~400 transcriptomatic, proteomic, metabolomic and epigenomic datasets from plant, rodent, small animal, and microbial space experiments. GeneLab provides users with various tools for data analysis and a visualization portal that allows users to interact with gene expression data from space-related 'omics experiments. Open Science is also about building scientific communities, and with this spirit in mind, GeneLab has spawned several Analysis Working Groups (AWGs), comprised of more than 200 volunteer scientists. The AWGs initially provided feedback on the processing pipeline and metadata 'omics standards for GeneLab. Over the last few years, they have become a community-driven science enterprise, engaging in large meta-analysis of GeneLab datasets, resulting in 10 publications (beyond the originally submitted research). Overall, the Open Science nature of GeneLab has resulted in a high degree of data-use, resulting in 40 enabled publications by open data. The enormous success and knowledge gained from GeneLab has led to a collection of sister NASA "Open Science Data Repositories (OSDR)" and research support groups. These include the NASA Ames Life Sciences Data Archive (ALSDA), the NASA Biological Institutional Scientific Collection (NBISC), and the Biospecimen Sharing Program (BSP). All are adopting the GeneLab data architecture system to maximize open-access, find-ability, accessibility, interoperability, and reusability (FAIR). ALSDA collects and curates phenotypic-physiological bioimaging-behavioral data from space and space-relevant non-human experiments, oftentimes coming from the same omics-associated experimental datasets found in GeneLab. Since 2021, a community of ~100 researchers have rallied around ALSDA, to provide feedback in a new ALSDA AWG focused on phenotypic-physiological investigation-sample-assay metadata standards (e.g., Micro-Computed Tomography, Light/Flourescence Microscopy, Western Blot, Flow Cytometry, Novel Object Recognition, Elevated Plus Maze, etc. of ~50 assays collected). These standards are part of a new single point-of-entry data submission portal for all non-human Space Biology and Human Research Program principal investigators, to submit, curate, and share their research data. With open-access space biological data now collected and curated together with rich metadata, and with the potential for linkage to "big data" from the international biological and medical communities (NIH, EBI, etc.), the artificial intelligence and machine learning (AI/ML) era has started for Space Biology.

omics↗

Ballistic limit of 6061 T6 aluminum and threat to surface coatings for use with orbiting space station space suit materials

In recent years orbiting satellites, spent components, collisions and explosions have populated the near earth orbit with debris potentially more hazardous than the average meteoroid debris. This new debris has an average density of aluminum (2.78 g/cc) and an average encounter velocity of 10 km/sec. The space station will require many hours of work in this environment and there is concern over hazard to the assembly personnel. A proposed hard suit design utilizes 6061-T6 Aluminum for most of its exposed area. The aluminum surface will be treated for thermal and radiation control. The basic thickness of this suit will be on the order of 1.78 mm (0.070 inches). The selection of 6061-T6 Aluminum for space suits for use on the space station would appear to be worthwhile. The relatively ductile behavior of 6061-T6 aluminum is better than a choice of a more brittle material.

Fish, D.↗

Results in orbital evolution of objects in the geosynchronous region

The orbital evolution of objects at or near geosynchronous orbit (GEO) has been simulated to investigate possible hazards to working geosynchronous satellites. Orbits of both large satellites and small particles have been simulated, subject to perturbations by nonspherical geopotential terms, lunar and solar gravity, and solar radiation pressure. Large satellites in initially circular orbits show an expected cycle of inclination change driven by lunar and solar gravity, but very little altitude change. They thus have little chance of colliding with objects at other altitudes. However, if such a satellite is disrupted, debris can reach thousands of kilometers above or below the initial satellite altitude. Small particles in GEO experience two cycles driven by solar radiation: an expected eccentricity cycle and an inclination cycle not expected. Particles generated by GEO insertion stage solid rocket motors typically hit the earth or escape promptly; a small fraction appear to remain in persistent orbits.

Friesen, Larry Jay↗

Interactions Between Asian Air Pollution and Monsoon System: South Asia (ROSES-2014 ACMAP)

Asia's rapid economic growth over the past several decades has brought a remarkable increase in air pollution levels in that region. High concentrations of aerosols (also known as particulate matter or PM) from pollution sources pose major health hazards to half of the world population in Asia including South Asia. How do pollution and dust aerosols regulate the monsoon circulation and rainfall via scattering and absorbing solar radiation, changing the atmospheric heating rates, and modifying the cloud properties? We conducted a series of regional model experiments with NASA-Unified Weather Research and Forecast (NUWRF) regional model with coupled aerosol-chemistry-radiation-microphysics processes over South Asia for winter, pre-monsoon, and monsoon seasons to address this question. This study investigates the worsening air quality problem in South Asia by focusing on the interactions between pollution and South Asian monsoon, not merely focusing on the increase of pollutant emissions.

regional model experiments with NASA-Unified Weath↗

Performances of the Heat Melt Compactor System in Various Operational Scenarios

The Heat Melt Compactor (HMC) system has been developed to manage the waste generated on board spacecraft during long-duration missions. The quantity and composition of spacecraft trash depends upon the mission and can have a very high daily variability. This requires a flexible system able to manage extreme waste scenarios. Most missions will generate on average about one kilograms of trash per astronaut per day, derived mainly from the spacecraft logistics supplies and consisting of clothing, food & beverage residues, packaging, paper, plastic, hygiene wipes, and many other personal or scientific items used and discarded by the crew. Uncontained and unprocessed waste is a health hazard and a habitat storage problem. However, trash also contains valuable resources such as water. HMC is designed to provide volume reduction, microbial safening and stabilization, water recovery, and radiation shielding material. The final byproduct generated by HMC is a sterilized tile with the consistency of hard plastic that can be safely handled, easily stored, and used for radiation protection. This paper provides the summary of an extensive campaign of testing performed using the HMC system to simulate different nominal and extreme operational scenarios and to generate the data necessary to finalize requirements for proto-flight hardware to be deployed to an International Space Station (ISS) EXPRESS Rack.

HMC↗

Open Science for Life in Space: Data Sharing and Tools for Knowledge Discovery

The next era in human space exploration is rapidly approaching and will require the use of countermeasures to deep space health hazards. The development of countermeasures (or, the re-purposing of existing agents) will be highly dependent on our understanding of basic biological responses to space stressors (e.g. ionizing radiation, altered gravitational fields, altered day-night cycles, confinement, isolation, hostile-closed environments, distance-duration from Earth, exposure to celestial regolith, etc.). The fast-growing array of space biological data, which in the past was simply archived after minimal analysis, holds great potential if it can be reorganized and formatted for Open Science. Organizing the data for such analysis is a challenge because of its diverse nature (molecular, cellular, tissue, imaging, whole organism and behavior). We will discuss here several strategies that NASA’s Biological and Physical Science Division has put in place to maximize the return on investment for spaceflight bioscience data. Open Science, as a scientific philosophy, is the concept that the more people who have access to the data, the more knowledge will be gained from it. This guiding principle led NASA to develop GeneLab in 2015. GeneLab houses spaceflight and relevant ground-based multi-omics data, and has grown to ~400 transcriptomic, proteomic, metabolomic and epigenomic datasets from plant, rodent, small animal, and microbial space experiments. GeneLab provides users with various tools for data analysis and a visualization portal that allows users to interact with gene expression data from space-related ‘omics experiments. Open Science is also about building scientific communities, and with this spirit in mind, GeneLab has spawned several Analysis Working Groups (AWGs), comprised of more than 200 volunteer scientists. The AWGs initially provided feedback on the processing pipeline and metadata ‘omics standards for GeneLab. Over the last few years, they have become a community-driven science enterprise, engaging in large meta-analysis of GeneLab datasets, resulting in 10 publications (beyond the originally submitted research). Overall, the Open Science nature of GeneLab has resulted in a high degree of data re-use, resulting in 38 additional publications derived from the original 67 publication over the past four years. The enormous success and knowledge gained from GeneLab has led to a collection of sister NASA “Open Science Data Repositories (OSDR)” and research support groups. These include the NASA Ames Life Sciences Data Archive (ALSDA), the NASA Biological Institutional Scientific Collection (NBISC), and the Biospecimen Sharing Program (BSP). All are adopting the GeneLab data architecture system to maximize open-access, find-ability, accessibility, interoperability, and reusability (FAIR). ALSDA collects and curates phenotypic-physiological bioimaging-behavioral data from space and space-relevant non-human experiments, oftentimes coming from the same omics-associated experimental datasets found in GeneLab. Since 2021, a community of ~100 researchers have rallied around ALSDA, to provide feedback in a new ALSDA AWG focused on phenotypic-physiological investigation-sample-assay metadata standards (e.g., Micro-Computed Tomography, Light/Fluorescence Microscopy, Western Blot, Flow Cytometry, Novel Object Recognition, Elevated Plus Maze, etc. of ~50 assays collected). These standards are part of a new single point-of-entry data submission portal for all non-human Space Biology and Human Research Program principal investigators, to submit, curate, and share their research data. With open-access space biological data now collected and curated together with rich metadata, and with the potential for linkage to “big data” from the international biological and medical communities (NIH, EBI, etc.), the artificial intelligence and machine learning (AI/ML) era has started for Space Biology. Several other talks will cover these topics in this conference.

life sciences↗

NASA Open Science Data Repository: Maximizing Spaceflight Bioscience Data

The next era in human space exploration is rapidly approaching and will require the use of countermeasures to deep space health hazards. The development of countermeasures (or, the re-purposing of existing agents) will be highly dependent on our understanding of basic biological responses to space stressors (e.g. ionizing radiation, altered gravitational fields, altered day-night cycles, confinement, isolation, hostile-closed environments, distance-duration from Earth, exposure to celestial regolith, etc.). The fast-growing array of space biological data, which in the past was simply archived after minimal analysis, holds great potential if it can be reorganized and formatted for data re-analysis and re-use via Open Science. Organizing the data for such analysis is a challenge because of its diverse nature (molecular, cellular, tissue, imaging, whole organism and behavior). To address the challenges posed by gaining new knowledge from a vast and diverse amount of biological, health and environmental data in space, the NASA Open Science Data Repository (OSDR - osdr.nasa.gov/bio) plays a crucial role in curating and openly publishing biological data from space-related experiments. Its design incorporates successes and lessons from NASA GeneLab, encompassing not only high-throughput sequencing data but also physiological, phenotypic, and telemetry data. The OSDR makes space biological data FAIR (findable, accessible, interoperable, reusable), and facilitates effective data ingestion, dissemination, and Open Science collaborations. The OSDR also has the capability to integrate human astronaut data with state-of-the-art security and accessibility procedures. We will discuss here several strategies that NASA’s Biological and Physical Science Division have put in place to maximize the return on investment for spaceflight bioscience data.

space biology↗

BioSentinel: An Adaptable Platform for Studying the Biological Effects of Deep Space Radiation

NASA's BioSentinel mission is a 6U nanosatellite with autonomous life support that will utilize the budding yeast Saccharomyces cerevisiae to study the DNA damage response to the deep space radiation environment. BioSentinel is planned to launch in 2019 as a secondary payload on the Space Launch System's first Exploration Mission (EM-1), and will undergo a lunar fly-by and enter heliocentric orbit after deployment. As the first biological mission beyond Low Earth Orbit (LEO) in nearly half a century, this mission will help fill critical gaps in knowledge about the effects of uniquely composed, chronic, low-flux deep space radiation on biological systems. Yeast is well-suited for this mission due to its desiccation tolerance and space-flight heritage. As a eukaryotic model organism, it also serves as a robust analog for human cells. Data gathered on this mission will thus inform us of the hazards involved in long-duration human exploration in deep space, and the protections necessary to mitigate them. Due to its low-cost, flexible and advanced technology, the 4U BioSensor payload contained within the nanosatellite is adaptable to other model microorganisms, exploration platforms and environments relevant to human exploration, such as the ISS, the Lunar Orbital Platform - Gateway and future lunar landers. In order to query the DNA damage response to deep space radiation, BioSentinel contains a wild type yeast strain as a positive control, and a radiation sensitive rad51 mutant strain that is defective for DNA repair. Yeast cells are desiccated in microfluidic cards, and rehydrated with growth medium and metabolic indicator dye at the desired time points during the mission. A thermal control system supports these stasis and growth states, and an optical system continuously measures cell growth and metabolism. An onboard radiation spectrometer and dosimeter allows us to correlate the dose, energy and particle-type of deep space radiation to the biological response. Data received from the deep space biosensor will be compared to control payloads on Earth and the ISS. Ongoing science testing for the BioSentinel project includes optimization for cell viability, desiccation tolerance, and long-term biocompatibility, as well as radiation experiments to understand the sensitivity and responsiveness of cells to varying radiation doses and particle types.

BioSentinel↗

Concept, Simulation, and Instrumentation for Radiometric Inflight Icing Detection

The multi-agency Flight in Icing Remote Sensing Team (FIRST), a consortium of the National Aeronautics and Space Administration (NASA), the Federal Aviation Administration (FAA), the National Center for Atmospheric Research (NCAR), the National Oceanographic and Atmospheric Administration (NOAA), and the Army Corps of Engineers (USACE), has developed technologies for remotely detecting hazardous inflight icing conditions. The USACE Cold Regions Research and Engineering Laboratory (CRREL) assessed the potential of onboard passive microwave radiometers for remotely detecting icing conditions ahead of aircraft. The dual wavelength system differences the brightness temperature of Space and clouds, with greater differences potentially indicating closer and higher magnitude cloud liquid water content (LWC). The Air Force RADiative TRANsfer model (RADTRAN) was enhanced to assess the flight track sensing concept, and a 'flying' RADTRAN was developed to simulate a radiometer system flying through simulated clouds. Neural network techniques were developed to invert brightness temperatures and obtain integrated cloud liquid water. In addition, a dual wavelength Direct-Detection Polarimeter Radiometer (DDPR) system was built for detecting hazardous drizzle drops. This paper reviews technology development to date and addresses initial polarimeter performance.

Ryerson, Charles↗

Atmospheric reentry of the in-core thermionic SP-100 reactor system

Presumed end-of-life atmospheric reentry of the GA SP-100 system was studied to assess dispersal feasibility and associated hazards. Reentry was studied by sequential use of an orbital trajectory and a heat analysis computer program. Two heating models were used. The first model assumed a thermal equilibrium condition between the stagnation point aerodynamic heating and the radiative cooling of the skin material surface. The second model allowed for infinite conductivity of the skin material. Four reentering configurations were studied representing stages of increased SP-100 breakup: (1) radiator, shield and reactor, (2) shield and reactor, (3) reactor with control drums, and (4) reactor without control drums. Each reentering configuration was started from a circular orbit at 116 km having an inertial velocity near Mach 25. The assumed failing criterion was the attainment of melting temperature of a critical system component. The reentry analysis revealed breakup of the vessel in the neighborhood of 61 km altitude and scattering of the fuel elements. Subsequent breakup of the fuel elements was not predicted. Oxidation of the niobium skin material was calculated to cause an increase in surface temperature of less than ten percent. The concept of thermite analogs for enhancing reactor reentry dispersal was assessed and found to be feasible in principle. A conservative worst-case hazards analysis was performed for radioactive and nonradioactive toxic SP-100 materials assumed to be dispersed during end-of-life reentry. The hazards associated with this phase of the SP-100 mission were calculated to be insignificant.

Stamatelatos, M. G.↗

Aerospect operations criteria for Mercury thresholds

The hazards anticipated from a large scale mercury spill during a possible failure in the preflight and early flight stages of the Space Shuttle were studied. Toxicity thresholds were investigated as well as other consequences of mercury interacting with the environment. Three sites of mercury spill were investigated: land, water, and atmosphere. A laboratory study of interactions between mercury vapor and ozone in a low pressure, high ultraviolet radiation environment approximated the conditions of a mercury vapor release in the ozone layer region of the stratosphere. Clear evidence of an interaction leading to the destruction of ozone by conversion to oxygen was obtained. The impact of a spill on the Earth's environment and methods of early detection of a developing hazard wave of primary concern in the study.

Katz, S.↗

Biological CubeSats: What Have We Learned so Far and What Is Next?

Since Apollo 17 in 1972, NASA has sent no humans or other biological organisms outside of Earth's protective magnetosphere. Recently, NASA has set its sights on human exploration in deep space, with an ambitous plan to put astronauts back on the Moon by 2024 and to eventually land human missions on Mars. Such missions will require significant countermeasures, likely both technological and biomedical, to protect biology from chronic radiation exposure. CubeSats can inform these countermeasures by querying relevant space environments with model organisms.NASA has launched five biological CubeSat missions into low-Earth orbit (LEO). GeneSat-1 was launched in 2006 to study gene expression and increase our knowledge of how spaceflight affects microbes. Similar life-support technologies were then used in PharmaSat and O/OREOS, which launched in 2009 and 2010, respectively. PharmaSat contained optical systems to examine how yeast cells responded to an antifungal treatment. One of O/OREOS payloads, SESLO (Space Environment Survivability of Living Organisms), housed dormant microorganisms, which were rehydrated on orbit to track alterations to growth and metabolism induced by microgravity and radiation. In 2014, NASA launched SporeSat to study the mechanisms of plant cell gravity sensing using lab-on-a-chip devices. Most recently, in 2017, NASA launched EcAMSat (E. coli AntiMicrobial Satellite), which investigated the effects of microgravity on antibiotic resistance of a pathogenic bacterium. Each one of these missions increased our understanding of the biological effects of spaceflight in LEO, while refining technologies and imparting valuable lessons to the next generation of CubeSats.CubeSats housing translational biological models are therefore ideal for defining the hazards of deep space travel, as they can provide critical data over relevant durations. BioSentinel, a next-generation deep-space CubeSat, is planned to launch as a secondary payload on Artemis 1 in 2020. BioSentinel will study the DNA damage response to deep space radiation in yeast.

Santa Maria, Sergio R.↗

Kennedy Space Center environmental health program

The Kennedy Space Center's environmental health organization is responsible for programs which assure its employees a healthful workplace under diverse and varied working conditions. These programs encompass the disciplines of industrial hygiene, radiation protection (health physics), and environmental sanitation/pollution control. Activities range from the routine, such as normal office work, to the highly specialized, such as the processing of highly toxic and hazardous materials.

Marmaro, G. M.↗

The Value of Biomedical Simulation Environments to Future Human Space Flight Missions

Mars and NEO missions will expose astronaut to extended durations of reduced reduced gravity, isolation and higher radiation. These new operation conditions pose health risks that are not well understood and perhaps unanticipated. Advanced computational simulation environments can beneficially augment research to predict, assess and mitigate potential hazards to astronaut health. The NASA Digital Astronaut Project (DAP), within the NASA Human Research Program, strives to achieve this goal.

Mulugeta,Lealem↗