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At least 361 records · Page 20

Complete Tem-Tomography: 3D Structure of Gems Cluster

GEMS (glass with embedded metal and sulfide) grains in interplanetary dust particles (IDPs) are considered to be one of the ubiquitous and fundamental building blocks of solids in the Solar System. They have been considered to be interstellar silicate dust that survived various metamorphism or alteration processes in the protoplanetary disk but the elemental and isotopic composition measurements suggest that most of them have been formed in the protoplanetary disk as condensates from high temperature gas. This formation model is also supported by the formation of GEMS-like grains with respect to the size, mineral assemblage, texture and infrared spectrum by condensation experiments from mean GEMS composition materials. Previous GEMS studies were performed only with 2D observation by transmission electron microscopy (TEM) or scanning TEM (STEM). However, the 3D shape and structure of GEMS grains and the spatial distribution of Fe/FeS's has critical information about their formation and origin. Recently, the 3D structure of GEMS grains in ultrathin sections of cluster IDPs was revealed by electron tomography using a TEM/STEM (JEM-2100F, JEOL). However, CT images of thin sections mounted on Cu grids acquired by conventional TEM-tomography are limited to low tilt angles (e. g., less than absolute value of 75 deg. In fact, previous 3D TEM observations of GEMS were affected by some artifacts related to the limited tilt range in the TEM used. Complete tomographic images should be acquired by rotating the sample tilt angle over a range of more than absolute value of 80 deg otherwise the CT images lose their correct structures. In order to constrain the origin and formation process of GEMS grains more clearly, we performed complete electron tomography for GEMS grains. Here we report the sample preparation method we have developed for this study, and the preliminary results.

Matsuno, J.↗

Co-developing a SAR for Disasters Reference Guide for the International Applications Community

Synthetic Aperture Radar (SAR) data are widely applicable for disaster monitoring, especially in Central and South America where atmospheric effects are a frequent obstacle for disaster monitoring. There is a growing interest in the application of SAR data to diverse disasters, ranging from landslides to volcanic eruptions and floods. With this interest comes a growing need for user-friendly guides that facilitate the integration of SAR into existing workflows. A joint effort between AmeriGEO, university networks in the Americas, NASA SERVIR’s Science Coordination Office (SCO), and the NASA Earth Science Disasters Program, culminated in the “SAR for Disasters” Guide. The guide is modeled after the one-page informational sheets created for SERVIR’s SAR Handbook, with the aim to succinctly communicate the key considerations needed to apply relevant analyses using SAR. Developed with contributors from diverse backgrounds, this guide is designed to be a useful reference for experienced technical users and beginners alike.

SAR↗

A Holding Function for Conflict Probe Appiications

Conflict Alerts for aircraft in holding patterns are often missed or in error due to fact that holding trajectories are not modeled in Conflict Alert or Conflict Probe logic. In addition, a controller in one sector may not know when aircraft are holding in a neighboring sector. These factors can lead to an increased potential for loss of separation while aircraft are flying in holding patterns. A holding function for conflict probe applications has been developed and tested with air traffic data from Fort Worth Center. The holding function automatically determines when an aircraft enters a holding pattern, builds a holding region around the pattern and then probes the region for conflict with other traffic. The operational concept of use assumes that air traffic controllers are very busy during periods when aircraft are in holding and therefore don't have time to manually enter information which defines a holding pattern and activates conflict probing. For this reason, it is important the holding function automatically detect aircraft in holding and compute a holding region for conflict analysis. The controller is then alerted if other aircraft are predicted to fly through the holding region at the holding altitude.

McNally, Dave↗

Predictive Modeling of Carbon Ablators

Efforts to build a Predictive Material Modeling (PMM) framework from the micro-scale to the macro-scale are presented in this abstract. To reduce the need for extensive testing, accelerate the design cycle process, and reduce uncertainty margins applied to final designs, NASA is developing simulation and modeling tools that enable characterization of material properties and response to high-enthalpy environments. The Porous Microstructure Analysis (PuMA) code has been developed for computing macroscale (volume averaged) properties of porous materials using microscale images from micro-computed tomography (micro-CT). Microscale modeling requires a realistic representation of a material microstructure; these are obtained either synthetically during the design of the material or through X-ray micro-CT. Volume averaged properties are then used to inform macroscale material response models, such as those implemented in the Porous-material Analysis Toolbox based on OpenFOAM (PATO) software, also actively developed by NASA. The computational model in PATO is a generic heat and mass transfer model for porous reactive materials containing several solid phases and a single gas phase. The detailed chemical interactions occurring between the solid phases and the gas phase are modeled at the pore scale assuming local thermal equilibrium. These tools were developed to efficiently interface with other pre-existing codes such as SPARTA (direct simulation Monte Carlo), DPLR (hypersonic CFD), NEQAIR (radiative transport) and DAKOTA (uncertainty quantification and optimization). Detailed flight data (Mars Science Laboratory [MSL] Entry Descent and Landing Instrument [MEDLI]) is critical for validating these computational tools for NASA applications. Examples of modeling ablative material response using these codes will be presented including 3D simulations of the full-scale heatshield of the MSL capsule. The simulations demonstrate the ability of the modern material response code, PATO, to handle the material response of geometrically complex and large domains, through the use of massively parallel computations.

Thermal Protection Systems↗

Predictive Modeling of Carbon Ablators Using Micro and Macro-Scale Modeling

Efforts to build a Predictive Material Modeling (PMM) framework from the micro-scale to the macro-scale are presented in this abstract. To reduce the need for extensive testing, accelerate the design cycle process, and reduce uncertainty margins applied to final designs, NASA is developing simulation and modeling tools that enable characterization of material properties and response to high-enthalpy environments. The Porous Microstructure Analysis (PuMA) code has been developed for computing macroscale (volume averaged) properties of porous materials using microscale images from micro-computed tomography (micro-CT). Microscale modeling requires a realistic representation of a material microstructure; these are obtained either synthetically during the design of the material or through X-ray micro-CT. Volume averaged properties are then used to inform macroscale material response models, such as those implemented in the Porous-material Analysis Toolbox based on OpenFOAM (PATO) software, also actively developed by NASA. The computational model in PATO is a generic heat and mass transfer model for porous reactive materials containing several solid phases and a single gas phase. The detailed chemical interactions occurring between the solid phases and the gas phase are modeled at the pore scale assuming local thermal equilibrium. These tools were developed to efficiently interface with other pre-existing codes such as SPARTA (direct simulation Monte Carlo), DPLR (hypersonic CFD), NEQAIR (radiative transport) and DAKOTA (uncertainty quantification and optimization). Detailed flight data (Mars Science Laboratory [MSL] Entry Descent and Landing Instrument [MEDLI]) is critical for validating these computational tools for NASA applications. Examples of modeling ablative material response using these codes will be presented including 3D simulations of the full-scale heatshield of the MSL capsule. The simulations demonstrate the ability of the modern material response code, PATO, to handle the material response of geometrically complex and large domains, through the use of massively parallel computations.

Thermal Protection Systems↗

Assessing Urban Heat in the Cincinnati and Covington Area to Inform Local Decision-Makers and Environmental Justice Initiatives

The Urban Heat Island effect is a phenomenon characterized by urban areas experiencing temperatures that are, on average, warmer than surrounding suburban and rural regions. Urban Heat Islands are fueled by expansive impervious surfaces, vehicle emissions, and insufficient urban green space. Densely populated urban centers like the Cincinnati, Ohio and Covington, Kentucky area can experience negative health impacts due to the Urban Heat Island. NASA DEVELOP partnered with Groundwork USA and Groundwork Ohio River Valley to combine environmental education and outreach with technical capacity building in NASA Earth observations. The DEVELOP team used Landsat 5 TM and ISS ECOSTRESS to calculate daytime and nighttime land surface temperature anomalies. The team found that the Cincinnati and Covington area was 8.32°F warmer during the day and 4.97°F warmer at night compared to non-urban areas. The team also ran the Natural Capital Project InVEST Urban Cooling Model to map a heat mitigation index for the study area. The heat mitigation index models the cooling capacity of each pixel and the effect of green spaces on the pixel’s ability to mitigate heat. Results show which communities are most vulnerable to impacts of increased urban heat. The team also assessed alternative tree canopy scenarios with the InVEST model to better understand the effectiveness of potential heat mitigation strategies. Increasing tree canopy cover by 25% in urbanized land cover types was found to reduce mean temperature across the study area by 0.87°F. Combining these results with work from Groundwork’s Climate Safe Neighborhoods program highlights the relationship between extreme heat and historical-race based housing practices in the region. Results provide partners at Groundwork with refined methodologies to support future education and outreach, as well as increase future capacity to NASA Earth observations.

Celeste Gambino↗

Planetary Surface Operations and Utilization: How ISS and Artemis Missions Can Be Used to Model Human Exploration of Mars

As NASA moves forward with plans to send astronauts to the Moon under Artemis missions and prepare for human exploration of Mars, the Agency is developing a set of high-level objectives for human spaceflight, identifying 50 points falling into four overarching categories of exploration. An element in NASA’s overall process of achieving these objectives is to leverage its assets and missions – such as the many crew increments sent to the International Space Station and future Artemis expeditions sent to the Moon – to develop more robust spaceflight systems and build a culture of interplanetary human exploration. This paper describes several examples of how NASA is exercising a process to achieve these objectives for future human Mars surface missions; both (a) building on lessons learned from ISS missions and maturing plans for Artemis missions, and (b) using human Mars mission planning to inform the plans for future ISS and Artemis missions so that the knowledge gained will reduce uncertainty and risk for Mars. One focal point for this two-way interaction between ISS and Artemis with future human Mars missions is a document titled “Reference Surface Activities for Crewed Mars Mission Systems and Utilization” (HEOMD-415), which describes the systems and operations of the crew thought necessary for the first human Mars surface mission. The details described in this paper will address three specific aspects of HEOMD-415 that have been influenced by ISS and where HEOMD-415 is influencing plans in ISS, Artemis, research and technology development, and other related aspects: (1) crew (activity planning and medical), (2) Mars surface infrastructure, and (3) communication and navigation support. The paper will close by describing near-term opportunities for tests and analogs relevant to these aspects of HEOMD-415.

Mars↗

PLANETARY SURFACE OPERATIONS AND UTILIZATION: HOW ISS AND ARTEMIS MISSIONS CAN BE USED TO MODEL HUMAN EXPLORATION OF MARS

As NASA moves forward with plans to send astronauts to the Moon under Artemis missions and prepare for human exploration of Mars, the Agency is developing a set of high-level objectives for human spaceflight, identifying 50 points falling into four overarching categories of exploration. An element in NASA’s overall process of achieving these objectives is to leverage its assets and missions – such as the many crew increments sent to the International Space Station and future Artemis expeditions sent to the Moon – to develop more robust spaceflight systems and build a culture of interplanetary human exploration. This paper describes several examples of how NASA is exercising a process to achieve these objectives for future human Mars surface missions; both (a) building on lessons learned from ISS missions and maturing plans for Artemis missions, and (b) using human Mars mission planning to inform the plans for future ISS and Artemis missions so that the knowledge gained will reduce uncertainty and risk for Mars. One focal point for this two-way interaction between ISS and Artemis with future human Mars missions is a document titled “Reference Surface Activities for Crewed Mars Mission Systems and Utilization” (HEOMD-415), which describes the systems and operations of the crew thought necessary for the first human Mars surface mission. The details described in this paper will address three specific aspects of HEOMD-415 that have been influenced by ISS and where HEOMD-415 is influencing plans in ISS, Artemis, research and technology development, and other related aspects: (1) crew (activity planning and medical), (2) Mars surface infrastructure, and (3) communication and navigation support. The paper will close by describing near-term opportunities for tests and analogs relevant to these aspects of HEOMD-415.

Mars↗

Kalman Orbit Optimized Loop Tracking

Under certain conditions of low signal power and/or high noise, there is insufficient signal to noise ratio (SNR) to close tracking loops with individual signals on orbiting Global Navigation Satellite System (GNSS) receivers. In addition, the processing power available from flight computers is not great enough to implement a conventional ultra-tight coupling tracking loop. This work provides a method to track GNSS signals at very low SNR without the penalty of requiring very high processor throughput to calculate the loop parameters. The Kalman Orbit-Optimized Loop (KOOL) tracking approach constitutes a filter with a dynamic model and using the aggregate of information from all tracked GNSS signals to close the tracking loop for each signal. For applications where there is not a good dynamic model, such as very low orbits where atmospheric drag models may not be adequate to achieve the required accuracy, aiding from an IMU (inertial measurement unit) or other sensor will be added. The KOOL approach is based on research JPL has done to allow signal recovery from weak and scintillating signals observed during the use of GPS signals for limb sounding of the Earth s atmosphere. That approach uses the onboard PVT (position, velocity, time) solution to generate predictions for the range, range rate, and acceleration of the low-SNR signal. The low- SNR signal data are captured by a directed open loop. KOOL builds on the previous open loop tracking by including feedback and observable generation from the weak-signal channels so that the MSR receiver will continue to track and provide PVT, range, and Doppler data, even when all channels have low SNR.

Young, Lawrence E.↗

Design Under Uncertainty for Conceptual Aircraft Design Leveraging Analytical Gradients

The purpose of this paper is to extend previously demonstrated methodologies for design under uncertainty, leveraging analytical gradients to higher fidelity analysis for use in conceptual aircraft design. Previous work developed methods to generate analytical derivatives through polynomial chaos expansion, eliminating the need to estimate derivatives via complex step or finite difference. In this research, the authors build upon the methods to include physics-based aircraft design codes for aircraft design under uncertainty. This extends the previous work’s case study, which employed analytical aerodynamics and Breguet range estimations for wing design, to a higher fidelity level. In addition, this work extends previous work on interface development between the Uncertainty Quantification with Polynomial Chaos Expansion (UQPCE) software and Model-Based Systems Analysis and Engineering (MBSA&E) frameworks. This paper will discuss the development work necessary to perform multidisciplinary design under uncertainty as well as demonstrate the mechanics of interfacing UQPCE and conceptual aircraft design tools such as NASA’s Aviary code. In a case study, a conceptual aircraft design under uncertainty was conducted and compared against a traditional deterministic design. When given information about the uncertainty space from UQPCE, the optimizer was able to shape the output distribution and produce a more robust design

UQ↗

Design Under Uncertainty for Conceptual Aircraft Design Leveraging Analytical Gradients

The purpose of this paper is to extend previously demonstrated methodologies for design under uncertainty, leveraging analytical gradients to higher fidelity analysis for use in conceptual aircraft design. Previous work developed methods to generate analytical derivatives through polynomial chaos expansion, eliminating the need to estimate derivatives via complex step or finite difference. In this research, the authors build upon the methods to include physics-based aircraft design codes for aircraft design under uncertainty. This extends the previous work’s case study, which employed analytical aerodynamics and Breguet range estimations for wing design, to a higher fidelity level. In addition, this work extends previous work on interface development between the Uncertainty Quantification with Polynomial Chaos Expansion (UQPCE) software and Model-Based Systems Analysis and Engineering (MBSA&E) frameworks. This paper will discuss the development work necessary to perform multidisciplinary design under uncertainty as well as demonstrate the mechanics of interfacing UQPCE and conceptual aircraft design tools such as NASA’s Aviary code. In a case study, a conceptual aircraft design under uncertainty was conducted and compared against a traditional deterministic design. When given information about the uncertainty space from UQPCE, the optimizer was able to shape the output distribution and produce a more robust design.

UQ↗

Environmental Public Health Surveillance for Exposure to Respiratory Health Hazards: A Joint NASA/CDC Project to Use Remote Sensing Data for Estimating Airborne Particulate Matter Over the Atlanta, Georgia Metropolitan Area

As part of the National Environmental Public Health Tracking Network (EPHTN) the National Center for Environmental Health (NCEH) at the Centers for Disease Control and Prevention (CDC) is leading a project called Health and Environment Linked for Information Exchange (HELiX-Atlanta). The goal of developing the National Environmental Public Health Tracking Network is to improve the health of communities. Currently, few systems exist at the state or national level to concurrently track many of the exposures and health effects that might be associated with environmental hazards. An additional challenge is estimating exposure to environmental hazards such as particulate matter whose aerodynamic diameter is less than or equal to 2.5 micrometers (PM2.5). HELIX-Atlanta's goal is to examine the feasibility of building an integrated electronic health and environmental data network in five counties of Metropolitan Atlanta, GA. NASA Marshall Space Flight Center (NASA/MSFC) is collaborating with CDC to combine NASA earth science satellite observations related to air quality and environmental monitoring data to model surface estimates of PM2.5 concentrations that can be linked with clinic visits for asthma. While use of the Air Quality System (AQS) PM2.5 data alone could meet HELIX-Atlanta specifications, there are only five AQS sites in the Atlanta area, thus the spatial coverage is not ideal. We are using NASA Moderate Resolution Imaging Spectroradiometer (MODIS) satellite Aerosol Optical Depth (AOD) data for estimating daily ground level PM2.5 at 10 km resolution over the metropolitan Atlanta area supplementing the AQS ground observations and filling their spatial and temporal gaps.

Quattrochi, Dale A.↗

Exploration Systems Development (ESD) Approach to Enterprise Risk Management

The National Aeronautics and Space Administration (NASA) Exploration Systems Development (ESD) Division has implemented an innovative approach to Enterprise Risk Management under a unique governance structure and streamlined integration model. ESD's mission is to design and build the capability to extend human existence to deep space. The Enterprise consists of three Programs: Space Launch System (SLS), Orion, and Ground Systems Development and Operations (GSDO). The SLS is a rocket and launch system that will be capable of powering humans, habitats, and support systems to deep space. Orion will be the first spacecraft in history capable of taking humans to multiple destinations within deep space. GSDO is modernizing Kennedy's spaceport to launch spacecraft built and designed by both NASA and private industry. ESD's approach to Enterprise Risk Management is commensurate with affordability and a streamlined management philosophy. ESD Enterprise Risk Management leverages off of the primary mechanisms for integration within the Enterprise. The Enterprise integration approach emphasizes delegation of authority to manage and execute the majority of cross-program activities and products to the individual Programs, while maintaining the overall responsibility for all cross-program activities at the Division. The intent of the ESD Enterprise Risk Management approach is to improve risk communication, to avoid replication and/or contradictory strategies, and to minimize overhead process burden. This is accomplished by the facilitation and integration of risk information within ESD. The ESD Division risks, Orion risks, SLS risks, and GSDO risks are owned and managed by the applicable Program. When the Programs have shared risks with multiple consequences, they are jointly owned and managed. When a risk is associated with the integrated system that involves more than one Program in condition, consequence, or mitigation plan, it is considered an Exploration Systems Integration (ESI) Risk. An ESI risk may require visibility and risk handling by multiple organizations. The Integrated Risk Working Group (IRWG) is a small team of Risk experts that are responsible for collaborating and communicating best practices. In addition, the forum facilitates proper integration of risks across the Enterprise. The IRWG uses a Continuous Risk Management approach for facilitating the identification, analysis, planning, tracking, and controlling of ESI Risks. The ESD Division, Programs, and Integrated Task Teams identify ESI Risks. The IRWG maintains a set of metrics for understanding Enterprise Risk process and the overall Risk Posture. The team is also actively involved in the modeling of risk for Enterprise Performance Management. With the Enterprise being constrained in Schedule and Budget, and with significant technical complexity, the appropriate use of Risk Management techniques is crucial to the success of the Enterprise. The IRWG achieves this through the modified approach, providing a forum for collaboration on risks that cross boundaries between the separate entities.

Bauder, Stephen P.↗

The Numerical Propulsion System Simulation: A Multidisciplinary Design System for Aerospace Vehicles

Advances in computational technology and in physics-based modeling are making large scale, detailed simulations of complex systems possible within the design environment. For example, the integration of computing, communications, and aerodynamics has reduced the time required to analyze ma or propulsion system components from days and weeks to minutes and hours. This breakthrough has enabled the detailed simulation of major propulsion system components to become a routine part of design process and to provide the designer with critical information about the components early in the design process. This paper describes the development of the Numerical Propulsion System Simulation (NPSS), a multidisciplinary system of analysis tools that is focussed on extending the simulation capability from components to the full system. This will provide the product developer with a "virtual wind tunnel" that will reduce the number of hardware builds and tests required during the development of advanced aerospace propulsion systems.

Lytle, John K.↗

Application of Machine Learning to Rotorcraft Health Monitoring

Machine learning is a powerful tool for data exploration and model building with large data sets. This project aimed to use machine learning techniques to explore the inherent structure of data from rotorcraft gear tests, relationships between features and damage states, and to build a system for predicting gear health for future rotorcraft transmission applications. Classical machine learning techniques are difficult, if not irresponsible to apply to time series data because many make the assumption of independence between samples. To overcome this, Hidden Markov Models were used to create a binary classifier for identifying scuffing transitions and Recurrent Neural Networks were used to leverage long distance relationships in predicting discrete damage states. When combined in a workflow, where the binary classifier acted as a filter for the fatigue monitor, the system was able to demonstrate accuracy in damage state prediction and scuffing identification. The time dependent nature of the data restricted data exploration to collecting and analyzing data from the model selection process. The limited amount of available data was unable to give useful information, and the division of training and testing sets tended to heavily influence the scores of the models across combinations of features and hyper-parameters. This work built a framework for tracking scuffing and fatigue on streaming data and demonstrates that machine learning has much to offer rotorcraft health monitoring by using Bayesian learning and deep learning methods to capture the time dependent nature of the data. Suggested future work is to implement the framework developed in this project using a larger variety of data sets to test the generalization capabilities of the models and allow for data exploration.

machine learning↗

LANDSAT-4 MSS Geometric Correction: Methods and Results

An automated image registration system such as that developed for LANDSAT-4 can produce all of the information needed to verify and calibrate the software and to evaluate system performance. The on-line MSS archive generation process which upgrades systematic correction data to geodetic correction data is described as well as the control point library build subsystem which generates control point chips and support data for on-line upgrade of correction data. The system performance was evaluated for both temporal and geodetic registration. For temporal registration, 90% errors were computed to be .36 IFOV (instantaneous field of view) = 82.7 meters) cross track, and .29 IFOV along track. Also, for actual production runs monitored, the 90% errors were .29 IFOV cross track and .25 IFOV along track. The system specification is .3 IFOV, 90% of the time, both cross and along track. For geodetic registration performance, the model bias was measured by designating control points in the geodetically corrected imagery.

Brooks, J.↗

Development of Testing Station for Prototype Rover Thermal Subsystem

In order to successfully and efficiently explore the moon or other planets, a vehicle must be built to assist astronauts as they travel across the surface. One concept created to meet this need is NASA's Space Exploration Vehicle (SEV). The SEV, a small pressurized cabin integrated onto a 12-wheeled chassis, can support two astronauts up to 14 days. Engineers are currently developing the second generation of the SEV, with the goal of being faster, more robust, and able to carry a heavier payload. In order to function properly, the rover must dissipate heat produced during operation and maintain an appropriate temperature profile inside the rover. If these activities do not occur, components of the rover will start to break down, eventually leading to the failure of the rover. On the rover, these requirements are the responsibility of the thermal subsystem. My project for the summer was to design and build a testing station to facilitate the design and testing of the new thermal subsystem. As the rover develops, initial low fidelity parts can be interchanged for the high fidelity parts used on the rover. Based on a schematic of the proposed thermal system, I sized and selected parts for each of the components in the thermal subsystem. For the components in the system that produced heat but had not yet been finalized or fabricated, I used power resistors to model their load patterns. I also selected all of the fittings to put the system together and a mounting platform to support the testing station. Finally, I implemented sensors at various points in the system to measure the temperature, pressure, and flow rate, and a data acquisition system to collect this information. In the future, the information from these sensors will be used to study the behavior of the subsystem under different conditions and select the best part for the rover.

Burlingame, Kaitlin↗

A Historical Overview of International Space Station Extravehicular Activity Meteoroid and Orbital Debris Risk

Nearly 300 spacewalks have been conducted over the last 25 years to help build and maintain the International Space Station (ISS). During the nearly 2,000 hours of extra-vehicular activity (EVA), crew members wear extra-vehicular mobility unit (EMU) “spacesuits” to mitigate hazards of the space environment including impacts from meteoroid and orbital debris (MMOD) particles. NASA includes detailed EMU MMOD risk analyses as part of the ISS EVA review and approval process. This paper provides a general historical overview of the ISS EVA MMOD risks and the associated risk assessment process. The NASA Johnson Space Center (JSC) Hypervelocity Impact Technology (HVIT) Team produces the ISS EVA MMOD risk analyses using the Bumper3 MMOD risk analysis code in conjunction with detailed information about the EVA including crew-member EVA work sites, crew translation paths, suit orientation, and duration. Detailed physical models of the EMU spacesuits and the ISS are included and tailored for each EVA analysis. Two types of MMOD risk are included: (1) Penetration, and (2) Catastrophic. Penetration risk is for any size leak in the EMU suit. Catastrophic risk is a subset of Penetration Risk and only includes penetrations that cause a 4mm diameter hole (or larger) in the inner “bladder” layer of the EMU suit. This size hole will exceed the ability of the EMU suit to compensate. The MMOD risk analyses also utilize the latest orbital debris environment and meteoroid environment models including additional transient factors to account for recent satellite break-ups and annual meteor storms. These additional factors and the associated increase in EVA MMOD risk are considered when scheduling an EVA to reduce EMU MMOD risk.

Dana M. Lear↗