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NASA NTRS2017

Micrometeoroid and Orbital Debris Risk Assessment With Bumper 3

The Bumper 3 computer code is the primary tool used by NASA for micrometeoroid and orbital debris (MMOD) risk analysis. Bumper 3 (and its predecessors) have been used to analyze a variety of manned and unmanned spacecraft. The code uses NASA's latest micrometeoroid (MEM-R2) and orbital debris (ORDEM 3.0) environment definition models and is updated frequently with ballistic limit equations that describe the hypervelocity impact performance of spacecraft materials. The Bumper 3 program uses these inputs along with a finite element representation of spacecraft geometry to provide a deterministic calculation of the expected number of failures. The Bumper 3 software is configuration controlled by the NASA/JSC Hypervelocity Impact Technology (HVIT) Group. This paper will demonstrate MMOD risk assessment techniques with Bumper 3 used by NASA's HVIT Group. The Permanent Multipurpose Module (PMM) was added to the International Space Station in 2011. A Bumper 3 MMOD risk assessment of this module will show techniques used to create the input model and assign the property IDs. The methodology used to optimize the MMOD shielding for minimum mass while still meeting structural penetration requirements will also be demonstrated.

Hyde, J.↗

NASA NTRSDate not supplied

Interface Consistency: Phase I Results & Phase II Status

Future exploration missions will rely on designing and developing vehicles and complex systems from within NASA and through multiple external commercial partners to meet mission goals. Despite existing consistency-related agency requirements, NASA’s approach to commercial spaceflight development encourages providers’ flexibility and innovation. This strategy is resulting in significant design diversity across Artemis vehicles. Design best practices and guidelines champion interface consistency to promote mental model development and knowledge transfer. However, research investigating the benefits of consistency is mixed, and little is known about its role in complex systems. Determining the level of risk that system diversity presents is difficult, as there is no established method for quantifying the degree of consistency within and across interfaces, nor is there information about the differential impacts of different types of inconsistency. Phase I of this project (Characterization and Measurement) served as a starting point to better understand the construct of consistency, its application, and the range of studies and methods for measuring it. The project team created a taxonomy of consistency to apply to interfaces as a framework to guide the development of tools to assess intersystem consistency. Checklist and cognitive walkthrough methods were developed for use by human factors (HF) and human-computer interaction (HCI) experts. The Intersystem Consistency Scale (ICS) was developed for interface evaluations with crew. A pilot study evaluated the methods’ ability to distinguish differences between Artemis-like prototype pairs exhibiting either high or low design consistency. In addition, click errors and time on task were collected within the ICS (crew-like) group. Results from our exploratory analysis and lessons learned from the pilot study will be discussed. The project team will also present the status of Phase II (Risk Assessment, Standards and Guidelines). This includes incorporating feedback to redesign the assessment tools, and inputs from displays and training Subject Matter Experts to update tasks and prototype designs. The team will present the risk assessment study design to identify the types and levels of inconsistency that pose the greatest risk to performance. Plans to apply these results toward agency standards and guideline recommendations will also be discussed.

Human-Computer Interaction↗

NASA NTRS1999

Aerospace Systems Design in NASA's Collaborative Engineering Environment

Past designs of complex aerospace systems involved an environment consisting of collocated design teams with project managers, technical discipline experts, and other experts (e.g. manufacturing and systems operations). These experts were generally qualified only on the basis of past design experience and typically had access to a limited set of integrated analysis tools. These environments provided less than desirable design fidelity, often lead to the inability of assessing critical programmatic and technical issues (e.g., cost risk, technical impacts), and generally derived a design that was not necessarily optimized across the entire system. The continually changing, modern aerospace industry demands systems design processes that involve the best talent available (no matter where it resides) and access to the best design and analysis tools. A solution to these demands involves a design environment referred to as collaborative engineering. The collaborative engineering environment evolving within the National Aeronautics and Space Administration (NASA) is a capability that enables the Agency's engineering infrastructure to interact and use the best state-of-the-art tools and data across organizational boundaries. Using collaborative engineering, the collocated team is replaced with an interactive team structure where the team members are geographically distributed and the best engineering talent can be applied to the design effort regardless of physical location. In addition, a more efficient, higher quality design product is delivered by bringing together the best engineering talent with more up-to-date design and analysis tools. These tools are focused on interactive, multidisciplinary design and analysis with emphasis on the complete life cycle of the system, and they include nontraditional, integrated tools for life cycle cost estimation and risk assessment. NASA has made substantial progress during the last two years in developing a collaborative engineering environment. NASA is planning to use this collaborative engineering infrastructure to provide better aerospace systems life cycle design and analysis, which includes analytical assessment of the technical and programmatic aspects of a system from "cradle to grave." This paper describes the recent NASA developments in the area of collaborative engineering, the benefits (realized and anticipated) of using the developed capability, and the long-term plans for implementing this capability across the Agency.

Monell, Donald W.↗

NASA NTRS2000

Aerospace Systems Design in NASA's Collaborative Engineering Environment

Past designs of complex aerospace systems involved an environment consisting of collocated design teams with project managers, technical discipline experts, and other experts (e.g., manufacturing and systems operation). These experts were generally qualified only on the basis of past design experience and typically had access to a limited set of integrated analysis tools. These environments provided less than desirable design fidelity, often lead to the inability of assessing critical programmatic and technical issues (e.g., cost, risk, technical impacts), and generally derived a design that was not necessarily optimized across the entire system. The continually changing, modern aerospace industry demands systems design processes that involve the best talent available (no matter where it resides) and access to the the best design and analysis tools. A solution to these demands involves a design environment referred to as collaborative engineering. The collaborative engineering environment evolving within the National Aeronautics and Space Administration (NASA) is a capability that enables the Agency's engineering infrastructure to interact and use the best state-of-the-art tools and data across organizational boundaries. Using collaborative engineering, the collocated team is replaced with an interactive team structure where the team members are geographical distributed and the best engineering talent can be applied to the design effort regardless of physical location. In addition, a more efficient, higher quality design product is delivered by bringing together the best engineering talent with more up-to-date design and analysis tools. These tools are focused on interactive, multidisciplinary design and analysis with emphasis on the complete life cycle of the system, and they include nontraditional, integrated tools for life cycle cost estimation and risk assessment. NASA has made substantial progress during the last two years in developing a collaborative engineering environment. NASA is planning to use this collaborative engineering engineering infrastructure to provide better aerospace systems life cycle design and analysis, which includes analytical assessment of the technical and programmatic aspects of a system from "cradle to grave." This paper describes the recent NASA developments in the area of collaborative engineering, the benefits (realized and anticipated) of using the developed capability, and the long-term plans for implementing this capability across Agency.

Monell, Donald W.↗

NASA NTRSDate not supplied

Unlocking the Microbiome of the International Space Station

With the start of human occupation more than 22 years ago, the microbiome of International Space Station (ISS) has been monitored to assess risk to both crew and craft. Historically, this monitoring has been achieved through onboard culture and ground-based analyses. Data spanning this timeframe are descriptive of a semi-closed, human occupied environment with associations to crew changes and process escapes within the environmental control and life support systems. While this approach has served to provide alerts to anomalies and overall confidence in the controls in place, the data are limited to the media type and growth conditions used. The bias toward the detection of culturable organisms has depicted an overall lack in biodiversity. As NASA leaves the ISS to focus on exploration, it is critical to fully understand its microbiome and its possible association to the noted positive influence on crew and vehicle health. The implementation of culture-independent, nanopore sequencing-based studies, both onboard the ISS and with returned ground samples, is revealing a more thorough depiction of the microbiome. As noted with pervious culture-based data, there is a common core microbiome across time and location, but key distinct areas of greater diversity exist. Through further investigation, these areas are emerging as unique ecological niches, potentially resulting in environmentally driven microbial selection. Moreover, the presence of some noted taxa within these unique locations has implications for crew health, planetary protection, and controls used in future spacecraft systems. The ability to perform in situ profiling of the ISS microbiome is transforming how NASA assesses risk and is a critical tool towards monitoring the establishment of the environmental microbiome in exploration spacecraft.

Sarah Stahl-Rommel↗

NASA NTRSDate not supplied

Usability of Pre-Flight Planning Interfaces for Supplemental Data Service Provider Tools to Support Uncrewed Aircraft System Traffic Management

Small uncrewed aircraft systems (sUASs) operate in low-altitude, uncontrolled airspace – where support services for their operators (UASOs) are not currently provided. NASA’s System-Wide Safety (SWS) project is identifying the potential risks and hazards to sUAS operations to provide, inform, and improve the designs of In-time Aviation Safety Management Systems (IASMS). The IASMS will include a suite of data-driven tools that compile and analyze data collected from aviation systems and environmental sources to predict hazards, and provide information to allow operators to mitigate these risks (Young et al., 2020). These risk and hazard services can be run and displayed to operators on graphical user interfaces (GUIs), as they relate to a vehicle(s)’ route of flight. These interfaces offer both a means to present hazard service output and offer an opportunity to test user understanding of the information, user decision making, and the best ways to present such data to an operator. Based on these future technologies and intended missions, it is important to investigate interface requirements and evaluate how operators might use these tools. Presenting salient and meaningful risk assessment information to operators is necessary to increase situation awareness and ultimately safety. Building on previous research (Feldman et al., 2022), a usability study comparing two GUIs was conducted to explore how individuals interacted with different styles of information displays. A series of pre-flight hazard and risk-assessment tasks were developed to evaluate participant performance using the Supplemental Data Service Provider Consolidated Dashboard and the Human Automation Team Interface System interfaces. Participants were trained to use both GUIs and their performance was analysed across different scenarios involving multiple sUASs. Performance on simple tasks and the System Usability Scale scores were reported by Feldman et al., 2023. Additional analyses and evaluations on more complex tasks (e.g., risk assessment, prioritization), workload and response times are examined in this paper.

sUAV interfaces↗

NASA NTRSDate not supplied

Usability of Pre-flight Planning Interfaces for Supplemental Data Service Provider Tools to Support Uncrewed Aircraft System Traffic Management

sUAV interfaces↗

NASA NTRS2018

Exploration Medical System Trade Study Tools Overview

ExMC is creating an ecosystem of tools to enable well-informed medical system trade studies. The suite of tools address important system implementation aspects of the space medical capabilities trade space and are being built using knowledge from the medical community regarding the unique aspects of space flight. Two integrating models, a systems engineering model and a medical risk analysis model, tie the tools together to produce an integrated assessment of the medical system and its ability to achieve medical system target requirements. This presentation will provide an overview of the various tools that are a part of the tool ecosystem. Initially, the presentation's focus will address the tools that supply the foundational information to the ecosystem. Specifically, the talk will describe how information that describes how medicine will be practiced is captured and categorized for efficient utilization in the tool suite. For example, the talk will include capturing what conditions will be planned for in-mission treatment, planned medical activities (e.g., periodic physical exam), required medical capabilities (e.g., provide imaging), and options to implement the capabilities (e.g., an ultrasound device). Database storage and configuration management will also be discussed. The presentation will include an overview of how these information tools will be tied to parameters in a Systems Modeling Language (SysML) model, allowing traceability to system behavioral, structural, and requirements content. The discussion will also describe an HRP-led enhanced risk assessment model developed to provide quantitative insight into each capability's contribution to mission success. Key outputs from these various tools, to be shared with the space medical and exploration mission development communities, will be assessments of medical system implementation option satisfaction of requirements and per-capability contributions toward achieving requirements.

Mindock, J.↗

NASA NTRSDate not supplied

Performance Risk Model (PRisM) Proof-of-Concept: An Operational Decision Support Tool to Predict Crew Performance in Space from Available Performance Tests

The Crew Health and Performance-Probabilistic Risk Assessment (CHP-PRA) team at NASA Glenn Research Center has developed a range of tools to evaluate astronaut health during spaceflight and to optimize the medical set required for missions. Among these, the Performance Risk Model (PRisM) represents a novel advancement, extending CHP-PRA’s focus beyond medical systems into the domain of human performance. Such tool could be pivotal in optimizing astronaut capabilities during space travel, thereby enhancing overall mission success. PRisM leverages data from well-established performance assessments conducted during previous crewed space missions and Earth analogs to strategically predict outcomes for planned tasks, even when direct performance testing has not been conducted for those specific tasks. To evaluate performance, PRisM references the various metrics outlined in NASA-STD-3001 and employs a methodology to integrate different performance scales. This framework analyzes the contribution of various human system task categories (HSTCs) to task execution and compares these contributions to the HSTCs’ involvement in other known tests. The model further employs a Monte Carlo simulation to sample performance scores from their distribution in operationally relevant tests such as those in Mulavara et al. (2018) and, by leveraging similarities in HSTC involvement, transfers this knowledge to actual mission tasks, such as those outlined in the "Human Exploration of Mars: Preliminary List of Crew Tasks”. The current PRisM proof-of-concept includes analyses of the impact of exercise and specific medications on astronauts’ performance, with provisions to incorporate additional countermeasures as data becomes available. Furthermore, the tool is customizable to include any system necessary to fully encompass the domain of human systems and can be adapted to evaluate performance for any spaceflight activities as requested by operational stakeholders. PRisM has the potential to assist the Human Research Program in exploring the capabilities trade space for optimized crew performance.

performance modeling↗

NASA NTRS2011

The Use of the Integrated Medical Model for Forecasting and Mitigating Medical Risks for a Near-Earth Asteroid Mission

Introduction The Integrated Medical Model (IMM) is a decision support tool that is useful to space flight mission managers and medical system designers in assessing risks and optimizing medical systems. The IMM employs an evidence-based, probabilistic risk assessment (PRA) approach within the operational constraints of space flight. Methods Stochastic computational methods are used to forecast probability distributions of medical events, crew health metrics, medical resource utilization, and probability estimates of medical evacuation and loss of crew life. The IMM can also optimize medical kits within the constraints of mass and volume for specified missions. The IMM was used to forecast medical evacuation and loss of crew life probabilities, as well as crew health metrics for a near-earth asteroid (NEA) mission. An optimized medical kit for this mission was proposed based on the IMM simulation. Discussion The IMM can provide information to the space program regarding medical risks, including crew medical impairment, medical evacuation and loss of crew life. This information is valuable to mission managers and the space medicine community in assessing risk and developing mitigation strategies. Exploration missions such as NEA missions will have significant mass and volume constraints applied to the medical system. Appropriate allocation of medical resources will be critical to mission success. The IMM capability of optimizing medical systems based on specific crew and mission profiles will be advantageous to medical system designers. Conclusion The IMM is a decision support tool that can provide estimates of the impact of medical events on human space flight missions, such as crew impairment, evacuation, and loss of crew life. It can be used to support the development of mitigation strategies and to propose optimized medical systems for specified space flight missions. Learning Objectives The audience will learn how an evidence-based decision support tool can be used to help assess risk, develop mitigation strategies, and optimize medical systems for exploration space flight missions.

Kerstman, Eric↗

NASA NTRSDate not supplied

Future Improvements to Impact for Long Duration Exploration Spaceflight

BACKGROUND: While NASA currently uses the Integrated Medical Model (IMM) to model spaceflight medical risk for Low Earth Orbit missions, IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces) was created to improve the fidelity of medical risk analysis for exploration missions involving the Lunar surface and beyond. OVERVIEW: While completion work continues on the initial version of the IMPACT tool, work has already begun to investigate ways to further enhance the fidelity of the model and its utility to stakeholders. DISCUSSION: Future additions leveraging the more robust and flexible IMPACT architecture include analyzing mission segments to account for segment-specific environments (ie. Lunar surface or microgravity), clinically tracible outcomes based on partial treatment of conditions, the ability to model mission outcomes based on provider Knowledge, Skills, and Abilities (KSAs), and the ability to affect the incidence of conditions based on the occurrence of related conditions (e.g. UTI progressing to sepsis). IMPACT also enables the addition of new conditions to its database as required to meet future risk assessment needs. Ultimately, the desire is to broaden IMPACT from a tool that models/trades medical risk to one that does so for all crew health and performance relevant systems (e.g., food, exercise, etc.).

E Stratton↗

NASA NTRS2019

New York City Panel on Climate Change 2019 Report Chapter 1: Introduction

While urban areas like New York City and its surrounding metropolitan region are key drivers of climate change through emissions of greenhouse gases, cities are also significantly impacted by climate shifts, both chronic changes and extreme events. These are already affecting the New York metropolitan region, including the five boroughs of New York City through higher temperatures, more intense precipitation, and higher sea levels, and will increasingly do so in the coming decades. The City of New York has embarked on a flexible adaptation pathway (i.e., strategies that can evolve through time as climate risk assessment, evaluation of adaptation strategies, and monitoring continues) to respond to climate change challenges. This entails significant programs to develop resilience in communities and critical infrastructure to observed and projected changes in temperature, precipitation, and sea level. The first NPCC Report laid out the risk management framing for the city and region via flexible adaptation pathways. The second New York City Panel on Climate Change Report (NPCC2) developed the “climate projections of record” that are currently being used by the City of New York in its resilience programs . The NPCC3 2019 Report co-generates new tools and methods for the next generation of climate risk assessments and implementation of region-wide resilience. Co-generation is an interactive process by which stakeholders and scientists work together to produce climate change information that is targeted to decision-making needs. These tools and methods can be used to observe, project, and map climate extremes; monitor risks and responses; and engage with communities to develop effective programs. They are especially important at “transformation points” in the adaptation process when large changes in the structure and function of physical, ecological, and social systems of the city and region are undertaken.

Rosenzweig, Cynthia↗

NASA NTRS2001

Advanced Finite Element Modeling of Low Cycle Fatigue Crack Growth

This document (a viewgraph presentation) assumes a crack-like defect of a size which may be missed in inspection will exist in most critical location of any critical structure or component. Flaw existence assumption is usually, but not always, conservative based on past experiences in NASA and knowledge of manufacturing processes. Cyclic, environmental, and sustained loads used to generate stresses on models. Fracture Mechanics analysis used to predict crack growth and residual strength. Must show that defective structure will still provide four times required mission lifetime. Special exemptions cover redundant structures, low risk parts, etc. Assessments require specialized software tools, experienced analysts, and reliable material crack growth rate test database.

Gregg, Wayne↗

NASA NTRS2005

Enhancing the Design Process for Complex Space Systems through Early Integration of Risk and Variable-Fidelity Modeling

An important enabler of the new national Vision for Space Exploration is the ability to rapidly and efficiently develop optimized concepts for the manifold future space missions that this effort calls for. The design of such complex systems requires a tight integration of all the engineering disciplines involved, in an environment that fosters interaction and collaboration. The research performed under this grant explored areas where the space systems design process can be enhanced: by integrating risk models into the early stages of the design process, and by including rapid-turnaround variable-fidelity tools for key disciplines. Enabling early assessment of mission risk will allow designers to perform trades between risk and design performance during the initial design space exploration. Entry into planetary atmospheres will require an increased emphasis of the critical disciplines of aero- and thermodynamics. This necessitates the pulling forward of EDL disciplinary expertise into the early stage of the design process. Radiation can have a large potential impact on overall mission designs, in particular for the planned nuclear-powered robotic missions under Project Prometheus and for long-duration manned missions to the Moon, Mars and beyond under Project Constellation. This requires that radiation and associated risk and hazards be assessed and mitigated at the earliest stages of the design process. Hence, RPS is another discipline needed to enhance the engineering competencies of conceptual design teams. Researchers collaborated closely with NASA experts in those disciplines, and in overall space systems design, at Langley Research Center and at the Jet Propulsion Laboratory. This report documents the results of this initial effort.

Mavris, Dimitri↗

NASA NTRS2010

The Multispectral Microscopic Imager: Integrating Microimaging with Spectroscopy for the In-Situ Exploration of the Moon

To maximize the scientific return, future robotic and human missions to the Moon will need to have in-situ capabilities to enable the selection of the highest value samples for returning to Earth, or a lunar base for analysis. In order to accomplish this task efficiently, samples will need to be characterized using a suite of robotic instruments that can provide crucial information about elemental composition, mineralogy, volatiles and ices. Such spatially-correlated data sets, which place mineralogy into a microtextural context, are considered crucial for correct petrogenetic interpretations. . Combining microscopic imaging with visible= nearinfrared reflectance spectroscopy, provides a powerful in-situ approach for obtaining mineralogy within a microtextural context. The approach is non-destructive and requires minimal mechanical sample preparation. This approach provides data sets that are comparable to what geologists routinely acquire in the field, using a hand lens and in the lab using thin section petrography, and provide essential information for interpreting the primary formational processes in rocks and soils as well as the effects of secondary (diagenetic) alteration processes. Such observations lay a foundation for inferring geologic histories and provide "ground truth" for similar instruments on orbiting satellites; they support astronaut EVA activities and provide basic information about the physical properties of soils required for assessing associated health risks, and are basic tools in the exploration for in-situ resources to support human exploration of the Moon.

Nunez, J. I.↗

NASA NTRS2013

NASA Human Research Program Space Radiation Program Element

The goal of the NASA Human Research Program's Space Radiation Program Element is to ensure that crews can safely live and work in the space radiation environment. Current work is focused on developing the knowledge base and tools required for accurate assessment of health risks resulting from space radiation exposure including cancer and circulatory and central nervous system diseases, as well as acute risks from solar particle events. Division of Space Life Sciences (DSLS) Space Radiation Team scientists work at multiple levels to advance this goal, with major projects in biological risk research; epidemiology; and physical, biophysical, and biological modeling.

Chappell, Lori↗

NASA NTRS2014

Mixed-field GCR Simulations for Radiobiological Research Using Ground Based Accelerators

Space radiation is comprised of a large number of particle types and energies, which have differential ionization power from high energy protons to high charge and energy (HZE) particles and secondary neutrons produced by galactic cosmic rays (GCR). Ground based accelerators such as the NASA Space Radiation Laboratory (NSRL) at Brookhaven National Laboratory (BNL) are used to simulate space radiation for radiobiology research and dosimetry, electronics parts, and shielding testing using mono-energetic beams for single ion species. As a tool to support research on new risk assessment models, we have developed a stochastic model of heavy ion beams and space radiation effects, the GCR Event-based Risk Model computer code (GERMcode). For radiobiological research on mixed-field space radiation, a new GCR simulator at NSRL is proposed. The NSRL-GCR simulator, which implements the rapid switching mode and the higher energy beam extraction to 1.5 GeV/u, can integrate multiple ions into a single simulation to create GCR Z-spectrum in major energy bins. After considering the GCR environment and energy limitations of NSRL, a GCR reference field is proposed after extensive simulation studies using the GERMcode. The GCR reference field is shown to reproduce the Z and LET spectra of GCR behind shielding within 20% accuracy compared to simulated full GCR environments behind shielding. A major challenge for space radiobiology research is to consider chronic GCR exposure of up to 3-years in relation to simulations with cell and animal models of human risks. We discuss possible approaches to map important biological time scales in experimental models using ground-based simulation with extended exposure of up to a few weeks and fractionation approaches at a GCR simulator.

Kim, Myung-Hee Y.↗

NASA NTRS2018

The Growth of Mass and Reliability Source Database and Me

Mass and Reliability Source (MaRS) is a database which draws together information from multiple other sources and databases (MADS, VMDB, ISS PART, Bayesian PowerPoint, etc.). Information such as mass, operating hours, and failure data are compiled to create a tool for the building of probabilistic Risk Assessment (PRA) models. MaRS also has great potential for deep space mission planning. Understanding the lowest point of failure within an ORU helps to inform the efficient selection of spare parts necessary for a journey where mass and volume are at a premium and resupply is not possible.

George, Cory A.↗