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The Multi-Mission Earth Entry Vehicle for Sample Return Missions – Past, Present, and Future

The Multi-Mission Earth Entry Vehicle (MMEEV) is an enabling technology developed at NASA’s Langley Research Center (LaRC) over the last two decades for returning samples to Earth across a wide array of space science missions. Currently, the MMEEV is being considered for NASA’s Mars Sample Return (MSR) mission. The original vehicle concept, the Earth Entry Vehicle (EEV), was innovated at LaRC in 1998 as a robust solution to return Mars soil samples to Earth under stringent backward contamination requirements. These backward contamination requirements drove the EEV to have higher reliability than any capsule previously designed for a return-to-Earth sample return mission. The EEV achieved this high reliability by employing a passive (no active systems) vehicle architecture optimized for fault tolerance in a compact, low-mass configuration that is extensible to virtually any sample return mission. The original EEV concept utilized a carbon-carbon primary structure with high-density carbon phenolic thermal protection system. The capsule had a 60-degree sphere-cone forebody and a backshell geometry uniquely tailored to produce aerodynamics that would passively re-orient the vehicle if it entered the atmosphere with an off-nominal attitude. Contrary to every other sample return capsule conceived at the time, the EEV was designed to land without a parachute. The vehicle incorporated an integral energy-absorbing crushable structure that protected the Mars sample for landings on surfaces ranging from soft soil to solid concrete. This paper describes 20 years of technological advancements LaRC has incorporated into the EEV architecture to evolve it from the original, MSR-enabling vehicle, to a true multi-mission capability relevant to any sample return mission. The vehicle’s unique Integrated Composite Stiffener Structure (ICoSS) has been optimized for specific strength - supporting high-G atmospheric entries with steep entry angles that produce precise landing footprints on the ground. The vehicle geometry has been refined through wind tunnel testing and computational fluid dynamics simulations to improve the vehicle’s aerodynamic stability and robustness to off-nominal conditions from hypersonic to subsonic flight. The resulting configuration of the current MMEEV architecture is described, with details provided on its sample carrying capacity and atmospheric entry trajectory capabilities. The upgraded vehicle performance is mapped into current space science objectives, showing how the MMEEV supports future sample return missions and continues to be an enabling technology for NASA’s vision to return samples from Mars.

J M Corliss↗

Thermal Cycle and Capacitance Testing of Mezzo Industries Phase Change Material Heat Capacitor

A phase change material heat capacitor prototype, designed and built under a NASA Small Business Innovation Research grant by Mezzo Technologies, was tested through coolant thermal cycling within the expected flow rates and temperature range of the Orion spacecraft’s propylene glycol-water mixture coolant system. Testing was performed with the phase change material contained under sealed conditions after a degassing procedure and exposed to atmosphere without prior degassing. The useful heat storage capacitance was measured and compared to Orion spacecraft requirements and theoretical N-Pentadecane storage capacity.

Propylene Glycol Water↗

Benchmarking and Testing of Qualcomm Snapdragon System-on-Chip for JPL Space Applications and Missions

As some space missions become more challenging due to new environments, greater distances, or more limited size, weight, and power (SWaP) constraints, spacecraft avionics must adapt to allow the spacecraft to be more autonomous and agile---eliminating the Spacecraft-Earth-Spacecraft feedback loop whenever possible. Prime examples of such missions include Aerobots (such as Ingenuity with extremely low SWaP constraints and demanding signal/image processing during flight) and landers in possibly hostile environments (such as a Europa lander mission, with limited communication capacity, high latency, and constrained power budget). To address these challenges, JPL worked with Qualcomm to demonstrate the use of their Snapdragon 801 system-on-chip (SoC) onboard the Ingenuity Helicopter on Mars. The Qualcomm Snapdragon SoC contains various subsystems, including an ARM cluster, a Graphics processing unit, a Digital Signal Processing subsystem, a Neural Processing Engine, Image Signal Processing subsystem, among others. Since the success of Ingenuity, JPL is continuing to work with Qualcomm to address other applications of the Snapdragon SoC technology. This includes the deployment of two 855 Snapdragon development boards onboard the International Space Station (ISS) for successful in-situ benchmarking of applications in space (beyond those tested on Ingenuity). In this paper, we will examine the performance of various applications that have been identified to benefit from greater onboard computational capability. These applications include (among others): machine vision algorithms that are expected to be critical in autonomous entry-descent-and-landing scenarios and real-time Aerobot flight navigation; Hyperspectral compression algorithms; Synthetic Aperture Radar Processing along with various instrument processing algorithms. We discuss how the infusion of Qualcomm's Snapdragon SoC is capable of enabling missions that may not have been able to achieve their goals with traditional flight computing. In addition, we also show that for some algorithms, the software implementation on the Snapdragon SoC outperforms traditional FPGA implementations.

Cretu, Vlad↗

Testing and Results of Vacuum Swing Adsorption Units for Spacesuit Carbon Dioxide and Humidity Control

A principal concern for extravehicular activity (EVA) space suits is the capability to control carbon dioxide (CO2) and humidity (H2O) for the crewmember. The release of CO2 in a confined or unventilated area is dangerous for human health and leads to asphyxiation; therefore, CO2 and H2O become leading factors in the design and development of the spacesuit. An amine-based CO2 and H2O vapor sorbent for use in pressure-swing re-generable beds has been developed by Hamilton Sundstrand. The application of solid-amine materials with vacuum swing adsorption technology has shown the capacity to concurrently manage CO2 and H2O levels through a fully regenerative cycle eliminating mission constraints imposed with non-regenerative technologies. Two prototype solid amine-based systems, known as rapid cycle amine (RCA), were designed to continuously remove CO2 and H2O vapor from a flowing ventilation stream through the use of a two-bed amine based, vacuum-swing adsorption system. The Engineering and Science Contract Group (ESCG) RCA is the first RCA unit implementing radial flow paths, whereas the Hamilton Sundstrand RCA was designed with linear flow paths. Testing was performed in a sea-level pressure environment and a reduced-pressure environment with simulated human metabolic loads in a closed-loop configuration. This paper presents the experimental results of laboratory testing for a full-size and a sub-scale test article. The testing described here characterized and evaluated the performance of each RCA unit at the required Portable Life Support Subsystem (PLSS) operating conditions. The test points simulated a range of crewmember metabolic rates. The experimental results demonstrate the ability of each RCA unit to sufficiently remove CO2 and H2O from a closed loop ambient or subambient atmosphere.

McMillin, Summer↗

The U.S. Sarsat geosynchronous experiment - Ground processor description and test results

The development of a specialized digital signal processor, the Geosynchronous Signal Processor (GSP), for short beacon burst signal detection and demodulation is described. The processing is based on fast Fourier Transform techniques for detection and message integration on the respective message bursts for demodulation. The GSP is based on array processor technology; it is designed to yield an ultimate capacity of 50-75 simultaneous beacon transmissions within the nominal 20 KHz bandwidth centered at 406.025 MHz.

Flikkema, P. G.↗

Heat Capacity Mapping Mission investigation no. 25 (Tellus project)

The TELLUS pilot project, utilizing 0.5 to 1.1 micron and 10.5 to 12.5 micron day and/or night imagery from the Heat Capacity Mapping Mission, is described. The application of remotely sensed data to synoptic evaluation of evapotranspiration and moisture in agricultural soils was considered. The influence of topography, soils, land use, and meteorology on surface temperature distribution was evaluated. Anthropogenic heat release was investigated. Test areas extended from semi-arid land in southern Italy to polders in the Netherlands, and from vine-growing hills in the Rhineland to grasslands in Buckinghamshire.

Deparatesi, S. G.↗

Regenerable CO2 collection for spacecraft application

The design of the CS-3, a three-person capacity preprototype CO2 collection subsystem, is described. It is noted that the function of the CS-3 is to remove metabolically produced CO2 from the Spacelab cabin to maintain atmospheric pCO2 at 400 Pa or less. Results are presented of an extensive parametric/endurance test program characterizing the subsystem's performance. The results demonstrate the suitability of the electrochemical depolarized CO2 concentration concept for possible use in the Space Operations Center. The CS-3 is found to meet or exceed all Regenerative Life Support Evaluation requirements. Specifically, the 0.13 cu m, 46 kg subsystem is able to remove CO2 at an equivalent rate of 3.4 persons from an air stream having a pCO2 of 400 Pa.

Lance, N., Jr.↗

Solid Surface Combustion Experiment Yields Significant Observations

The spread of a flame over solid fuel is not only a fundamental textbook combustion phenomenon, but also the central element of destructive fires that cause tragic loss of life and property each year. Throughout history, practical measures to prevent and fight fires have been developed, but these have often been based on lessons learned in a costly fire. Since the 1960 s, scientists and engineers have employed powerful tools of scientific research to understand the details of flame spread and how a material can be rendered nonflammable. High-speed computers have enabled complex flame simulations, whereasand lasers have provided measurements of the chemical composition, temperature, and air velocities inside flames. The microgravity environment has emerged as the third great tool for these studies. Spreading flames are complex combinations of chemical reactions and several physical processes including the transport of oxygen and fuel vapor to the flame and the transfer of heat from the flame to fresh fuel and to the surroundings. Depending on its speed, air motion in the vicinity of the flame can affect the flame in substantially different ways. For example, consider the difference between blowing on a campfire and blowing out a match. On Earth, gravity induces air motion because of buoyancy (the familiar rising hot gases); this process cannot be controlled experimentally. For theoreticians, buoyant air motion complicates the problem modeling of flame spread beyond the capacity of modern computers to simulate. The microgravity environment provides experimental control of air motion near spreading flames, with results that can be compared with detailed theory. The Solid Surface Combustion Experiment (SSCE) was designed to obtain benchmark flame spreading data in quiescent test atmospheres--the limiting case of flames spreading. Professor Robert Altenkirch, Vice President for Research at Mississippi State University, proposed the experiment concept, and the NASA Lewis Research Center designed, built, and tested the SSCE hardware. It was the first microgravity science experiment built by Lewis for the space shuttle and the first combustion science experiment flown in space.

Sacksteder, Kurt R.↗

Unitized Regenerative Fuel Cell System Gas Storage-Radiator Development

High-energy-density regenerative fuel cell systems that are used for energy storage require novel approaches to integrating components in order to preserve mass and volume. A lightweight unitized regenerative fuel cell (URFC) energy storage system concept is being developed at the NASA Glenn Research Center. This URFC system minimizes mass by using the surface area of the hydrogen and oxygen storage tanks as radiating heat surfaces for overall thermal control of the system. The waste heat generated by the URFC stack during charging and discharging is transferred from the cell stack to the surface of each tank by loop heat pipes, which are coiled around each tank and covered with a thin layer of thermally conductive carbon composite. The thin layer of carbon composite acts as a fin structure that spreads the heat away from the heat pipe and across the entire tank surface. Two different-sized commercial-grade composite tanks were constructed with integral heat pipes and tested in a thermal vacuum chamber to examine the feasibility of using the storage tanks as system radiators. The storage tank-radiators were subjected to different steady-state heat loads and varying heat load profiles. The surface emissivity and specific heat capacity of each tank were calculated. In the future, the results will be incorporated into a model that simulates the performance of similar radiators using lightweight, spacerated carbon composite tanks.

Burke, Kenneth A.↗

Estimating the Effect of Gypsy Moth Defloiation Using MODIS

The area of North American forests affected by gypsy moth defoliation continues to expand despite efforts to slow the spread. With the increased area of infestation, ecological, environmental and economic concerns about gypsy moth disturbance remain significant, necessitating coordinated, repeatable and comprehensive monitoring of the areas affected. In this study, our primary objective was to estimate the magnitude of defoliation using Moderate Resolution Imaging Spectroradiometer (MODIS) imagery for a gypsy moth outbreak that occurred in the US central Appalachian Mountains in 2000 and 2001. We focused on determining the appropriate spectral MODIS indices and temporal compositing method to best monitor the effects of gypsy moth defoliation. We tested MODIS-based Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Normalized Difference Water Index (NDWI), and two versions of the Normalized Difference Infrared index (NDIIb6 and NDIIb7, using the channels centered on 1640 nm and 2130 nm respectively) for their capacity to map defoliation as estimated by ground observations. In addition, we evaluated three temporal resolutions: daily, 8-day and 16-day data. We validated the results through quantitative comparison to Landsat based defoliation estimates and traditional sketch maps. Our MODIS based defoliation estimates based on NDIIb6 and NDIIb7 closely matched Landsat defoliation estimates derived from field data as well as sketch maps. We conclude that daily MODIS data can be used with confidence to monitor insect defoliation on an annual time scale, at least for larger patches (greater than 0.63 km2). Eight-day and 16-day MODIS composites may be of lesser use due to the ephemeral character of disturbance by the gypsy moth.

deBeurs, K. M.↗

Regolith Advanced Surface Systems Operations Robot (RASSOR)

Regolith is abundant on extra-terrestrial surfaces and is the source of many resources such as oxygen, hydrogen, titanium, aluminum, iron, silica and other valuable materials, which can be used to make rocket propellant, consumables for life support, radiation protection barrier shields, landing pads, blast protection berms, roads, habitats and other structures and devices. Recent data from the Moon also indicates that there are substantial deposits of water ice in permanently shadowed crater regions and possibly under an over burden of regolith. The key to being able to use this regolith and acquire the resources, is being able to manipulate it with robotic excavation and hauling machinery that can survive and operate in these very extreme extra-terrestrial surface environments. In addition, the reduced gravity on the Moon, Mars, comets and asteroids poses a significant challenge in that the necessary reaction force for digging cannot be provided by the robot's weight as is typically done on Earth. Space transportation is expensive and limited in capacity, so small, lightweight payloads are desirable, which means large traditional excavation machines are not a viable option. A novel, compact and lightweight excavation robot prototype for manipulating, excavating, acquiring, hauling and dumping regolith on extra-terrestrial surfaces has been developed and tested. Lessons learned and test results will be presented including digging in a variety of lunar regolith simulant conditions including frozen regolith mixed with water ice.

Mueller, Robert P.↗

The Effects of CDKN1a/p21 on Oxidative Stress and Mitochondrial Function During Long Duration Spaceflight

Broad tissue degeneration and the failure of normal tissue regenerative processes in microgravity because of mechanical unloading are increasing concerns for sustaining life in space as the duration of future flight missions increases. Work in our laboratory has identified normal adult stem cell-based tissue regenerative processes, such as the formation of new bone, cartilage, and immune cells, as being particularly sensitive to the stresses of mechanical unloading in microgravity. Our studies have also identified the inhibition of differentiation of marrow mesenchymal stem cells and activation of CDKN1ap21-mediated cell cycle arrest in proliferative osteoprecursor cells on the bone surface as potential mechanisms for spaceflight-induced skeletal changes. This finding, in combination with the role of CDKN1ap21 as a suppressor of mammalian tissue regeneration, suggests that this gene could be responsible for suppressing stem cell-based tissue regeneration in response to disuse. In this work, we hypothesized that CDKN1ap21 regulates regenerative bone formation in response to alterations in mechanical load and tested this hypothesis by studying the skeletal phenotype and stem cell regenerative ability of juvenile (4-11 weeks old) and adult (18 weeks-12 months old) p21 (--) knockout (KO) mice. Additionally, we analyzed bone micro-architectural properties, bone formation rates and differentiation capacity of bone marrow stem cells (BMSCs) from male and female KO mice exposed to hindlimb unloading (HU) for 15-30 days. We found that juvenile KO mice exhibited increased femoral trabecular and cortical bone formation, whilst three-point bending of the tibias from KO mice showed decreased bone stiffness. Conversely, adult KO mice exhibited no significant differences in micro-architectural properties compared to WT (wild-type) but woven bone structure was indicative of rapid bone remodeling. Furthermore, cortical bone properties showed similar characteristics to aged bone, including increased cross-sectional area and perimeter, whilst three-point bending showed increased stiffness and toughness. Interestingly, in-vitro, KO mice exhibited increased differentiation and mineralized nodule formation in osteoblastogenesis assays compared to WT. Preliminary results from CDKN1ap21 KO mice subjected to HU suggest altered sensitivity to mechanical unloading resulting in decreased cortical thickness compared to WT mice. However, KO mice subjected to short and long-duration HU show increased in-vitro differentiation potential of BMSCs to from form mature, mineral-forming osteoblasts, indicating maintenance of regenerative potential. Analysis of bone formation rates, cell proliferation rates and key genes of interest are currently underway. These results indicate a novel role for CDKN1ap21 in load-dependent osteoprogenitor proliferation and differentiation and that deletion of CDKN1ap21 results in an age-dependent release of osteoblast proliferation inhibition and increased bone formation and turnover.

Stem Cells↗

Development and Evaluation of the Active Response Gravity Offload System as a Lunar and Martian EVA Simulation Environment

In preparation for future exploration missions, NASA seeks the ability to simulate partial-gravity operations for use in ground-based research, crew training, and engineering design evaluations. The Active Response Gravity Offload System (ARGOS) at the Johnson Space Center (JSC) is designed to simulate reduced gravity environments, such as lunar, Martian, or microgravity, using a robotic system similar to an overhead bridge crane. ARGOS continuously offloads a portion of a suited human’s weight during all dynamic motions within the test facility, which can include basic functional movements such as walking, running, and jumping, as well as a wide range of planetary surface activities. This system will be used as part of a metabolic-rate task characterization study to determine the workload associated with partial-gravity extravehicular activity (EVA). Pilot testing was conducted using the MKIII prototype planetary space suit and two gimbal designs to determine the ability of the ARGOS test environment to simulate planetary EVA operations. This paper will describe the lessons learned from the feasibility testing, simulation-environment mockup design, and the results from the pilot tests and their influence into the final study design. Being able to effectively simulate partial-gravity environments and characterize the performance of crewmembers will have an impact on multiple domains including suit design, task design, thermal models, and life-support-system capacity verification plans, among others.

Omar S Bekdash↗

GeoAI advances in specific landform mapping

Landform mapping (also referred to as geomorphology or geomorphometry) can be divided into two domains: general and specific (Evans 2012). Whereas general landform mapping categorizes all elements of the study area into landform classes, such as ridges, valleys, peaks, and depressions, the mapping of specific landforms requires the delineation (even if fuzzy) of individual landforms. The former is mainly driven by physical properties such as elevation, slope, and curvature. The latter, however, must consider the cognitive (human) reasoning that discriminates individual landforms in addition to these physical properties (Arundel and Sinha 2018). Both mapping forms are important. General geomorphometry is needed to understand geological and ecological processes and as boundary layer input to climate and environmental models. Specific geomorphometry supports such activities as disaster management and recovery, emergency response, transportation, and navigation. In the United States, individual landforms of interest are named in the U.S. Geological Survey (USGS) Geographic Names Information System, a point dataset captured specifically to digitize geographic names from the USGS Historical Topographic Map Collection (HTMC). Named landform extent is represented only by the name placement in the HTMC. Recent work has investigated CNN-based deep learning methods to capture these extents in machine-readable form. These studies first relied on physical properties (Arundel et al. 2020) and then included the HTMC as a band in RGB images in limited testing (Arundel et al. 2023). Results from the HTMC dataset surpassed those using just physical properties and using the HTMC alone performed best due to the hillshading and elevation (contour) data incorporated into the topographic maps. However, results fell short of an operational capacity to map all named landforms in the United States. Thus, our current work expands upon past research by focusing on the HTMC and physical information as inputs and the named landform label extents. Specifically, we propose to leverage pre-trained foundation models for segmentation and optical character recognition (OCR) models to jointly map landforms in the United States. Our approach aims to bridge the disparities among the independent information sources to facilitate informed decision-making. The modeling pipeline performs (1) segmentation using the physical information and (2) information extraction using OCR, in parallel. Then a computer vision approach merges the two branches into a labeled segmentation. References: Arundel, Samantha T., Wenwen Li, and Sizhe Wang. 2020. “GeoNat v1.0: A Dataset for Natural Feature Mapping with Artificial Intelligence and Supervised Learning.” Transactions in GIS 24 (3): 556–72. https://doi.org/10.1111/tgis.12633. Arundel, Samantha T, and Gaurav Sinha. 2018. “Validating GEOBIA Based Terrain Segmentation and Classification for Automated Delineation of Cognitively Salient Landforms BT - Proceedings of Workshops and Posters at the 13th International Conference on Spatial Information Theory (COSIT 2017).” In Proceedings of Workshops and Posters at the 13th International Conference on Spatial Information Theory (COSIT 2017), Lecture Notes in Geoinformation and Cartography, edited by Paolo Fogliaroni, Andrea Ballatore, and Eliseo Clementini, 9–14. Cham: Springer International Publishing. Arundel, Samantha T., Gaurav Sinha, Wenwen Li, David P. Martin, Kevin G. McKeehan, and Philip T. Thiem. 2023. “Historical Maps Inform Landform Cognition in Machine Learning.” Abstracts of the ICA 6 (August): 1–2. https://doi.org/10.5194/ica-abs-6-10-2023. Evans, Ian S. 2012. “Geomorphometry and Landform Mapping: What Is a Landform?” Geomorphology 137 (1): 94–106. https://doi.org/10.1016/j.geomorph.2010.09.029.

machine learning↗

GeoAI Advances in Specific Landform Mapping

Landform mapping (also referred to as geomorphology or geomorphometry) can be divided into two domains: general and specific (Evans 2012). Whereas general landform mapping categorizes all elements of the study area into landform classes, such as ridges, valleys, peaks, and depressions, the mapping of specific landforms requires the delineation (even if fuzzy) of individual landforms. The former is mainly driven by physical properties such as elevation, slope, and curvature. The latter, however, must consider the cognitive (human) reasoning that discriminates individual landforms in addition to these physical properties (Arundel and Sinha 2018). Both mapping forms are important. General geomorphometry is needed to understand geological and ecological processes and as boundary layer input to climate and environmental models. Specific geomorphometry supports such activities as disaster management and recovery, emergency response, transportation, and navigation. In the United States, individual landforms of interest are named in the U.S. Geological Survey (USGS) Geographic Names Information System, a point dataset captured specifically to digitize geographic names from the USGS Historical Topographic Map Collection (HTMC). Named landform extent is represented only by the name placement in the HTMC. Recent work has investigated CNN-based deep learning methods to capture these extents in machine-readable form. These studies first relied on physical properties (Arundel et al. 2020) and then included the HTMC as a band in RGB images in limited testing (Arundel et al. 2023). Results from the HTMC dataset surpassed those using just physical properties and using the HTMC alone performed best due to the hillshading and elevation (contour) data incorporated into the topographic maps. However, results fell short of an operational capacity to map all named landforms in the United States. Thus, our current work expands upon past research by focusing on the HTMC and physical information as inputs and the named landform label extents. Specifically, we propose to leverage pre-trained foundation models for segmentation and optical character recognition (OCR) models to jointly map landforms in the United States. Our approach aims to bridge the disparities among the independent information sources to facilitate informed decision-making. The modeling pipeline performs (1) segmentation using the physical information and (2) information extraction using OCR, in parallel. Then a computer vision approach merges the two branches into a labeled segmentation.

machine learning↗

Glenn Extreme Environments Rig (GEER) Facility Users Guide

The Glenn Extreme Environment Rig (GEER) is a large capacity pressure vessel capable of simulating high pressure and temperature conditions with a specified, custom mixture of gas. The chamber is certified for operation in physical and chemical conditions representative of the surface conditions of Venus. It can accommodate large scientific or engineering test articles while maintaining the specified conditions indefinitely. The user-configurable gas supply is capable of handling a mixture of up to nine independent streams for injection directly into the vessel. GEER is supported in part by NASA’s Planetary Science Division under the Science Mission Directorate and is available for use by the commercial, academic, and research communities. GEER was operationally commissioned in November of 2014. At that time, it successfully maintained the temperature, pressure, and chemistry of the Venus surface atmosphere. In the spring of 2015, GEER began operations for engineering and scientific research. Since then, over 20 tests have been successfully conducted in the chamber with a variety of atmospheric test conditions.

Blake W. Beckley↗

Performance of charge-injection-device infrared detector arrays at low and moderate backgrounds

Three 2 x 64 element charge injection device infrared detector arrays were tested at low and moderate background to evaluate their usefulness for space based astronomical observations. Testing was conducted both in the laboratory and in ground based telescope observations. The devices showed an average readout noise level below 200 equivalent electrons, a peak responsivity of 4 A/W, and a noise equivalent power of 3x10 sq root of W/Hz. Array well capacity was measured to be significantly smaller than predicted. The measured sensitivity, which compares well with that of nonintegrating discrete extrinsic silicon photoconductors, shows these arrays to be useful for certain astronomical observations. However, the measured readout efficiency and frequency response represent serious limitations in low background applications.

Mckelvey, M. E.↗

Recent Space Shuttle crew compartment design improvements

Significant design changes to the Space Shuttle waste management system (WMS) and its related personal hygiene support provisions (PHSP) have been made recently to improve overall operational performance and human factors interfaces. The WMS design improvements involve increased urinal flow, individual urinals, and provisions for manually compacting feces and cleanup materials to ensure adequate mission capacity. The basic arrangement and stowage of the PHSP used during waste management operations were extensively changed to better serve habitability concerns and operations needs, and to improve the hygiene of WMS operations. This paper describes these changes and the design, development, and flight test evaluation. In addition, provisions for an eighth crewmember and a new four-tier sleep station are described.

Goodman, Jerry R.↗