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At least 1,387 records · Page 77

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NASA NTRS2011

Fatigue Management in Spaceflight Operations

Sleep loss and fatigue remain an issue for crewmembers working on the International Space Station, and the ground crews who support them. Schedule shifts on the ISS are required for conducting mission operations. These shifts lead to tasks being performed during the biological night, and sleep scheduled during the biological day, for flight crews and the ground teams who support them. Other stressors have been recognized as hindering sleep in space; these include workload, thinking about upcoming tasks, environmental factors, and inadequate day/night cues. It is unknown if and how other factors such as microgravity, carbon dioxide levels, or increased radiation, may also play a part. Efforts are underway to standardize and provide care for crewmembers, ground controllers and other support personnel. Through collaborations between research and operations, evidenced-based clinical practice guidelines are being developed to equip flight surgeons with the tools and processes needed for treating circadian desynchrony (and subsequent sleep loss) caused by jet lag and shift work. The proper implementation of countermeasures such as schedules, lighting protocols, and cognitive behavioral education can hasten phase shifting, enhance sleep and optimize performance. This panel will focus on Fatigue Management in Spaceflight Operations. Speakers will present on research-based recommendations and technologies aimed at mitigating sleep loss, circadian desynchronization and fatigue on-orbit. Gaps in current mitigations and future recommendations will also be discussed.

Whitmire, Alexandra↗

NASA NTRS1997

STS-84 Mission Highlights Resource Tape

The STS-84 mission flight crew, Cmdr. Charles J. Precourt, Pilot Eileen M. Collions, Payload Cmdr. Jean-Francois Clervoy (ESA), Mission Specialists Edward T. Lu, Carlos I. Noriega, Elena V. Kondakova, and Jerry M. Linenger can be seen performing pre-launch activities such as eating the traditional breakfast, crew suit-up, and the ride out to the launch pad. Also, included are various panoramic views of the shuttle on the pad. The crew can be seen being readied in the white room' for their mission. After the closing of the hatch and arm retraction, launch activities are shown including countdown, engine ignition, launch, and the separation of the Solid Rocket Boosters. The rendezvous with the Mir Space Station, along with onboard activities, and landing are included. Also included are shuttle-to-ground transmission between the crew and Mission Control and various earthviews.

Source record↗

NASA NTRS1998

STS-91 Mission Highlights Resource Tape

The crew STS-91 mission, Cmdr. Charles J. Precourt, Pilot Dominic L. Pudwill Gorie and Mission Specialists Wendy B. Lawrence, Franklin R. Chang-Diaz, Janet L. Kavandi, and Valery Victorovitch Ryumin can be seen performing pre-launch activities such as eating the traditional breakfast, crew suit-up, and the ride out to the launch pad. Also, included are various panoramic views of the shuttle on the pad. The crew is readied in the 'white room' for their mission. After the closing of the hatch and arm retraction, launch activities are shown including countdown, engine ignition, launch, and the separation of the Solid Rocket Boosters. Once in orbit, there are various views of the Mir Space Station as the shuttle begins its approach and docks. After the docking the two crews open the entry hatch and greet each other. The astronauts and cosmonauts transfer supplies from the shuttle to Mir. The astronauts prepare for the reentry phase of their mission. The Shuttle separates from the Russian Space Station with a gentle push from springs in the docking mechanism that attaches it to the Space Station. The final view shows the crews' preparations for reentry and landing.

Source record↗

NASA NTRS2003

Development of Novel Methods for the Reduction of Noise and Weight in Helicopter Transmissions

Over the 70-year evolution of the helicopter, man's understanding of vibration control has greatly increased. However, in spite of the increased performance, the extent of helicopter vibration problems has not significantly diminished. Crew vibration and noise remains important factors in the design of all current helicopters. With more complex and critical demands being placed on aircrews, it is essential that vibration and noise not impair their performance. A major source of helicopter cabin noise (which has been measured at a sound pressure level of over 100 dB) is the gearbox. Reduction of this noise has been a goal of NASA and the U.S. Army. Gear mesh noise is typically in the frequency range of 1000 to 3000 Hz, a range important for speech. A requirement for U.S. Army/NASA Advanced Rotorcraft Transmission project has been a 10-dB reduction compared to current designs. A combined analytical/experimental effort has been underway, since the end of the 80's, to study effects of design parameters on noise production. The noise generated by the gear mesh can be transmitted to the surrounding media through the bearings that support the gear shaft. Therefore, the use of fluid film bearings instead of rolling element bearings could reduce the transmission noise by 10 dB. In addition, the fluid film bearings that support the gear shaft can change the dynamics of the gear assembly by providing damping to the system and by being softer than rolling element bearings. Wave bearings can attenuate, and filter, the noise generated by a machine component due to the dynamic stiffness and damping coefficients. The attenuation ratio could be as large as 35-40 dB. The noise components at higher frequencies than a synchronous frequency can be almost eliminated.

Dimofte, Florin↗

NASA NTRS2008

Combustion Devices CFD Team Analyses Review

A variety of CFD simulations performed by the Combustion Devices CFD Team at Marshall Space Flight Center will be presented. These analyses were performed to support Space Shuttle operations and Ares-1 Crew Launch Vehicle design. Results from the analyses will be shown along with pertinent information on the CFD codes and computational resources used to obtain the results. Six analyses will be presented - two related to the Space Shuttle and four related to the Ares I-1 launch vehicle now under development at NASA. First, a CFD analysis of the flow fields around the Space Shuttle during the first six seconds of flight and potential debris trajectories within those flow fields will be discussed. Second, the combusting flows within the Space Shuttle Main Engine's main combustion chamber will be shown. For the Ares I-1, an analysis of the performance of the roll control thrusters during flight will be described. Several studies are discussed related to the J2-X engine to be used on the upper stage of the Ares I-1 vehicle. A parametric study of the propellant flow sequences and mixture ratios within the GOX/GH2 spark igniters on the J2-X is discussed. Transient simulations will be described that predict the asymmetric pressure loads that occur on the rocket nozzle during the engine start as the nozzle fills with combusting gases. Simulations of issues that affect temperature uniformity within the gas generator used to drive the J-2X turbines will described as well, both upstream of the chamber in the injector manifolds and within the combustion chamber itself.

Rocker, Marvin↗

NASA NTRS2016

Capability for Integrated Systems Risk-Reduction Analysis

NASA's Human Research Program (HRP) is working to increase the likelihoods of human health and performance success during long-duration missions, and subsequent crew long-term health. To achieve these goals, there is a need to develop an integrated understanding of how the complex human physiological-socio-technical mission system behaves in spaceflight. This understanding will allow HRP to provide cross-disciplinary spaceflight countermeasures while minimizing resources such as mass, power, and volume. This understanding will also allow development of tools to assess the state of and enhance the resilience of individual crewmembers, teams, and the integrated mission system. We will discuss a set of risk-reduction questions that has been identified to guide the systems approach necessary to meet these needs. In addition, a framework of factors influencing human health and performance in space, called the Contributing Factor Map (CFM), is being applied as the backbone for incorporating information addressing these questions from sources throughout HRP. Using the common language of the CFM, information from sources such as the Human System Risk Board summaries, Integrated Research Plan, and HRP-funded publications has been combined and visualized in ways that allow insight into cross-disciplinary interconnections in a systematic, standardized fashion. We will show examples of these visualizations. We will also discuss applications of the resulting analysis capability that can inform science portfolio decisions, such as areas in which cross-disciplinary solicitations or countermeasure development will potentially be fruitful.

Mindock, J.↗

NASA NTRS2007

Integrating Human Factors into Crew Exploration Vehicle Design

With NASA's new Vision for Exploration to send humans beyond Earth orbit, it is critical to consider the human as a system that demands early and continuous user involvement, and an iterative prototype/test/redesign process. Addressing human-system interface issues early on can be very cost effective even cost reducing when performed early in the design and development cycle. To achieve this goal within Crew Exploration Vehicle (CEV) Project Office, human engineering (HE) team is formed. Key tasks are to apply HE requirements and guidelines to hardware/software, and provide HE design, analysis and evaluation of crew interfaces. Initial activities included many practice-orientated evaluations using low-fidelity CEV mock-ups. What follows is a description of such evaluations that focused on a HE requirement regarding Net Habitable Volume (NHV). NHV is defined as the total remaining pressurized volume available to on-orbit crew after accounting for the loss of volume due to deployed hardware and structural inefficiencies which decrease functional volume. The goal of the NHV evaluations was to develop requirements providing sufficient CEV NHV for crewmembers to live and perform tasks in support of mission goals. Efforts included development of a standard NHV calculation method using computer models and physical mockups, and crew/ stakeholder evaluations. Nine stakeholders and ten crewmembers participated in the unsuited evaluations. Six crewmembers also participated in a suited evaluation. The mock-up was outfitted with volumetric representation of sub-systems such as seats, and stowage bags. Thirteen scenarios were developed to represent mission/crew tasks and considered to be primary volume drivers (e.g., suit donning) for the CEV. Unsuited evaluations included a structured walkthrough of these tasks. Suited evaluations included timed donning of the existing launch and entry suit to simulate a contingency scenario followed by doffing/ stowing of the suits. All mockup evaluations were videotaped. Structured questionnaires were used to document user interface issues and volume impacts of layout configuration. Computer model and physical measures of the NHV agreed within 1 percent. This included measurement of the gross habitable volume, subtraction of intrusive volumes, and other non-habitable spaces. Calculation method developed was validated as a standard means of measuring NHV, and was recommended as a verification method for the NHV requirements. Evaluations confirmed that there was adequate volume for unsuited scenarios and suit donning/ doffing activity. Seats, suit design stowage and waste hygiene system noted to be critical volume drivers. The low-fidelity mock-up evaluations along with human modeling analysis generated discussions that will lead to high-level systems requirements and human-centered design decisions. This approach allowed HE requirements and operational concepts to evolve in parallel with engineering system concepts and design requirements. As the CEV design matures, these evaluations will continue and help with design decisions, and assessment, verification and validation of HE requirements.

Whitmore, Mihriban↗

NASA NTRSDate not supplied

Sleep Obtained by Cabin Crewmembers during a Long-haul Flight

Sleep loss and circadian disruption pose a significant risk in safety-sensitive occupations. In aviation, many studies have demonstrated how inflight rest locations influence alertness and performance among pilots, but few studies have evaluated cabin crew. The purpose of the present study was to evaluate sleep outcomes among cabin crewmembers sleeping in a bunk compared to a jump seat during one long-haul route. Thirty-one (6 male) cabin crewmembers (age M = 30, SD = +/-13) flew the same long-haul route (outbound and return) with a flight duration of 10:41 (± 0:14) hours. Participants were randomly assigned to fly on an aircraft with a bunk or a jump seat for their sleep opportunity. Participants wore an Actiwatch (Phillips-Respironics Spectrum) throughout the entire study and completed a sleep diary at bedtime and upon waking. During flight they completed a nap diary entering the start time of the inflight sleep (if any) and the duration. Sixty-five flights (32 outbound and 33 return) were included in the analyses. Seventy-seven percent of the flights had a bunk and 23% had a jump seat. Crewmembers obtained M = 146.46 (± 67.20) minutes of rest out of which they slept M = 125.33 (± 64.91) minutes in the bunk. While using the jump seat, crewmembers obtained M = 169.53 (± 133.30) minutes of rest out of which they slept M = 142.92 (± 149.72) minutes. When crewmembers slept in the bunk, sleep latency was shorter (M = 13.69 ± 12.64 minutes) and efficiency was better (M = 76.16 ± 16.09 %) compared to the jump seat (sleep onset: M = 16.77 ± 13.89 minutes; sleep efficiency: M = 60.64 ± 17.42 %). We found that cabin crewmembers slept for longer time when they used the jump seat. They fell asleep faster and their sleep efficiency was better when using the bunk compared to the jump seat. Further research is needed to understand how sleep quality and subsequent performance are influenced by sleep opportunity in a bunk compared to a jump seat.

cabin crew↗

NASA NTRS2019

Supporting Crew Autonomy in Deep Space Exploration: Preliminary Onboard Capability Requirements and Proposed Research Questions. Technical Report of the Autonomous Crew Operations Technical Interchange Meeting

Communication delays are a critical challenge posed by long duration deep space exploration. Space missions historically have relied on an ever-present Mission Control Center (MCC) to direct operations in near real-time. As unanticipated anomalies that defeat fault detection and resolution systems do arise, the lack of real-time communication will significantly weaken what the MCC support represents: a reliable safety net for the flight crew through its deep and diverse areas of expertise and investigative resources. As a consequence, future space vehicles and habitats need to be equipped with capabilities to support the flight crew to operate with little or no ground support. Considerations must be given to vehicle and mission designs that will fortify the traditionally ground-centered safety net and forge new support systems, when communication delays exist. In August 2018, NASA’s Human Research Program, through its Human Factors and Behavioral Performance Element, convened a Technical Interchange Meeting (TIM) on Autonomous Crew Operations at NASA Ames Research Center. The goal of the meeting was to gather input from NASA centers, industry, academia, and branches of the Department of Defense (DoD) to address how intelligent technologies can be applied to augment onboard capabilities to support crew anomaly response. The TIM featured 24 presentations by 29 speakers and hosted a total of 59 attendees, including 43 from 5 NASA centers (Ames, Johnson, Langley, Marshall, and Jet Propulsion Lab) and 4 from the DoD (3 from Army Research Lab and 1 from Naval Postgraduate School), with remaining attendees from academia (e.g., UC Davis, CMU) and industry (e.g., IBM, Siemens). Discussions were centered around three themes: standards and guidelines, lessons learned in analog environments, and technologies. To help provide a framework for discussion, a concept matrix describing anomaly response processes was created prior to the TIM (Figure 1, page 6). The matrix captures the steps involved (monitoring and detection, diagnosis, solution development and evaluation, solution implementation and verification, resolution documentation) as well as the resources and capabilities required to support these steps (data, knowledge, analysis, synthesis, resource management). A wallpaper size printout of the matrix was utilized at the TIM to solicit attendee inputs along the three themes; the activity garnered 108 submissions of ideas. Overall, what emerged from TIM discussions was a picture of mismatch between crew anomaly response needs and support that can be provided by existing intelligent technologies. The needs are broad, spanning multiple steps and processes/resources, with many of which lacking support from existing technologies, such as knowledge management throughout the steps of problem solving (especially in resolution documentation) and manpower management. The solutions provided by existing intelligent technologies are specific to the steps/processes that they are designed to support and constrained to solving only problems similar to those that have occurred before. What is lacking from technologies is typically made up by humans, specifically their complex critical thinking, creative problem solving, and domain expertise. In the end, the TIM highlighted the pressing need to support responses to onboard anomalies during autonomous crew operations, particularly those that have eluded the system tests, inspection, and other assurance processes. Such anomalies can potentially threaten crew and vehicle safety, as well as significantly impact overall operations with additional workload. These fairly rare events are difficult to anticipate and prepare for, given the state-of-the-art in intelligent technologies. This is true even for anomalies that stem from “unknown knowns”—cases in which there is sufficient external information to characterize the problem but the overall pattern fails to be recognized by the problem solver, or in which the internal knowledge needed to solve a problem is held tacitly and potentially accessible by the problem solver but not articulated. It follows that the ability to tackle anomalies lies not only with the availability of relevant information and knowledge but also their accessibility in times of need. To that end, we propose research questions along the following three broad themes: • How intelligent technologies can help make relevant knowledge and information available? • How intelligent technologies can help make relevant knowledge and information accessible? • How intelligent technologies can help support the crew operating as a team in anomaly response processes?

autonomous crew operations↗

NASA NTRS1998

STS-90 Day 01 Highlights

On this first day of the STS-90 mission, the flight crew, Cmdr. Richard A. Searfoss, Pilot Scott D. Altman, and Mission Specialists Richard M. Linnehan, Dafydd Rhys Williams and Kathryn P. Hire, and Payload Specialists Jay C. Buckey and James A. Pawelczyk, can be seen performing pre-launch activities such as eating the traditional breakfast, crew suit-up, and the ride out to the launch pad. Also, included are various panoramic views of the shuttle on the pad. The crew is readied in the white room' for their mission. After the closing of the hatch and arm retraction, launch activities are shown including countdown, engine ignition, launch, and the separation of the Solid Rocket Boosters. The shuttle's payload bay doors are then opened in anticipation of the 16-day scientific mission. The astronauts then are seen readying the Spacelab module for various experiments.

Source record↗

NASA NTRS1998

STS-91 Flight Day 1 Highlights and Crew Activities Report

On this first day of the STS-91 mission, the flight crew, Cmdr. Charles J. Precourt, Pilot Dominic L. Pudwill Gorie, and Mission Specialists Franklin R. Chang-Diaz, Janet Lynn Kavandi, Wendy B. Lawrence, Valery Victorovitch Ryumin and Andrew S. W. Thomas, can be seen performing pre-launch activities such as eating the traditional breakfast, crew suit-up, and the ride out to the launch pad. Also, included are various panoramic views of the shuttle on the pad. The crew is readied in the 'white room' for their mission. After the closing of the hatch and arm retraction, launch activities are shown including countdown, engine ignition, launch, and the separation of the Solid Rocket Boosters.

Source record↗

NASA NTRS2017

Flight Crew Survey Responses from the Interval Management (IM) Avionics Phase 2 Flight Test

The Interval Management (IM) Avionics Phase 2 flight test used three aircraft over a nineteen day period to operationally evaluate a prototype IM avionics. Quantitative data were collected on aircraft state data and IM spacing algorithm performance, and qualitative data were collected through end-of-scenario and end-of-day flight crew surveys. The majority of the IM operations met the performance goals established for spacing accuracy at the Achieve-by Point and the Planned Termination Point, however there were operations that did not meet goals for a variety of reasons. While the positive spacing accuracy results demonstrate the prototype IM avionics can contribute to the overall air traffic goal, critical issues were also identified that need to be addressed to enhance IM performance. The first category was those issues that impacted the conduct and results of the flight test, but are not part of the IM concept or procedures. These included the design of arrival and approach procedures was not ideal to support speed as the primary control mechanism, the ground-side of the Air Traffic Management Technology Demonstration (ATD-1) integrated concept of operations was not part of the flight test, and the high workload to manually enter the information required to conduct an IM operation. The second category was issues associated with the IM spacing algorithm or flight crew procedures. These issues include the high frequency of IM speed changes and reversals (accelerations), a mismatch between the deceleration rate used by the spacing algorithm and the actual aircraft performance, and some spacing error calculations were sensitive to normal operational variations in aircraft airspeed or altitude which triggered additional IM speed changes. Once the issues in these two categories are addressed, the future IM avionics should have considerable promise supporting the goals of improving system throughput and aircraft efficiency.

Baxley, Brian T.↗

NASA NTRSDate not supplied

Humans to Mars, but How Many? Using Training Requirements Modeling to Inform Crew Size

Missions to Mars will differ from previous human spaceflight missions in that the onboard crew of astronauts will be required to operate in an Earth-independent manner due to the long communication delays. Without a systematic, repeatable process to determine the number and composition of crew necessary to successfully accomplish these missions, NASA increases the risk that crew sizes may be too small to meet primary mission objectives under nominal conditions and, more consequentially, that crewmembers may not have the expertise needed to successfully respond to unforeseen failures without the real-time expertise of the Mission Control Central (MCC) team NASA currently relies upon. The NASA Engineering and Safety Center (NESC) is developing a methodology for assessing the trade space of factors that affect the number of crew for future missions. This methodology includes the consideration of results from three human performance models developed using the Improved Performance Research and Integration Tool (IMPRINT) modeling platform as well as a custom-built model on expertise trained within the crew. The IMPRINT results will be presented in the modeling and simulation sub-tag. Here we present results of a model based on NASA’s crew qualification and responsibility matrix (CQRM), a tool used to identify the crew qualifications for each area of responsibility (operation, system, and payload) for a mission. The model outputs an optimized allocation of training assignments along with a flight-assigned CQRM that can be used to consider the expertise that can be trained within a crew of a given size. We discuss the CQRM model result implications on the trade space for Mars mission crew size.

Mars↗

NASA NTRSDate not supplied

Humans to Mars, but How Many? Using Training Requirements Modeling to Inform Crew Size

Mars↗

NASA NTRS1997

STS-85 Day 01 Highlights

On this first day of the STS-85 mission, the flight crew, Cmdr. Curtis L. Brown, Jr., Pilot Kent V. Rominger, Payload Cmdr. N. Jan Davis (Ph.D.), Mission Specialists Robert L. Curbeam, Jr., and Stephen K. Robinson (Ph.D.), and Payload Specialist Bjarni V. Tryggvason can be seen performing pre-launch activities such as eating the traditional breakfast, crew suit-up, and the ride out to the launch pad. Also, included are various panoramic views of the shuttle on the pad. The crew can be seen being readied in the 'white room' for their mission. After the closing of the hatch and arm retraction, launch activities are shown including countdown, engine ignition, launch, and the separation of the Solid Rocket Boosters.

Source record↗

DOE OSTI2015

Challenges in leveraging existing human performance data for quantifying the IDHEAS HRA method

Our article documents an exploratory study for collecting and using human performance data to inform human error probability (HEP) estimates for a new human reliability analysis (HRA) method, the IntegrateD Human Event Analysis System (IDHEAS). The method was based on cognitive models and mechanisms underlying human behaviour and employs a framework of 14 crew failure modes (CFMs) to represent human failures typical for human performance in nuclear power plant (NPP) internal, at-power events [1]. A decision tree (DT) was constructed for each CFM to assess the probability of the CFM occurring in different contexts. Data needs for IDHEAS quantification are discussed. Then, the data collection framework and process is described and how the collected data were used to inform HEP estimation is illustrated with two examples. Next, five major technical challenges are identified for leveraging human performance data for IDHEAS quantification. Furthermore, these challenges reflect the data needs specific to IDHEAS. More importantly, they also represent the general issues with current human performance data and can provide insight for a path forward to support HRA data collection, use, and exchange for HRA method development, implementation, and validation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRSDate not supplied

Dust Solution Testing Initiative (DuSTI): Infusing Commercial Off the Shelf Dust Mitigation Technologies with NASA Practices

Dust is one of the most significant hazards to human lunar exploration. However, since the Apollo program concluded, limited research has been performed on lunar dust mitigation technologies. The safety of the crew members and sustainability of habitats, science, and supporting hardware depend on effective dust mitigation techniques and technologies. As NASA pursues a new generation of lunar missions with the Artemis program, the project team will pursue dust mitigation solutions with the Dust Solution Testing Initiative (DuSTI). DuSTI is a lunar dust mitigation effort that involves performing tests on commercial off the shelf (COTS) technologies over FY21. DuSTI will preform component and subsystem tests in dusty environments for up to five technologies with high potential. The specific technologies identified for study were selected based on several factors, including a market analysis of current terrestrial dust mitigation applications, availability of the technology, accessibility of various testing facilities, and cost of procurement. These technologies support the active and passive dust mitigation requirements of filtration systems, electro-mechanical systems, electro-static systems, surface coatings, textiles, and silicone polymers. Technology Readiness Level (TRL) will be increased by validating components in relevant environments. For example, if the COTS technology is at a TRL 9 for terrestrial use but at a 4-5 TRL for use in the lunar environment, we will test that technology in a lunar dust environment to increase the TRL for use on the Moon.

lunar dust↗

NASA NTRSDate not supplied

Introduction to the IMPACT Probabilistic Risk and Tradespace Analysis Tool for Medical System Design

Background: Probabilistic risk analysis (PRA) is a method for estimating risk in complex engineered systems that, at a basic level, focuses on what can go wrong and the likelihood and consequences of those occurrences. NASA has used PRA as an integral component of medical system risk estimation and design for spaceflight. IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces) is a novel tool to meet these goals for exploration missions. Overview: IMPACT performs hundreds of thousands of Monte Carlo simulations of missions to build aggregate pictures of medical risk. These simulations are based on 120 possible medical conditions (the IMPACT Condition List) selected in a consensus-based process because they are of highest likelihood and/or consequence for exploration spaceflight. The conditions are then tied to clinical capabilities which can be used for management (e.g., inserting an IV) and then to over 600 specific resources needed to deliver a capability (e.g., an angiocath or an ultrasound). Different mission profiles can be simulated with user-specified inputs such as mission duration, destination, number of crew and pre-existing medical conditions, and EVA frequency. While the IMPACT evidence base is designed for exploration environments, these user inputs allow the tool to be used across a broad range of missions. IMPACT’s primary outcome metrics include loss of crew life (LOCL, a measure of in-flight mortality due to medical conditions), need for evacuation (RTDC, return to definitive care), and crew disability (TTL, task time lost based on how medical conditions impact the ability to perform over 1000 specific exploration mission crew tasks). In addition to modeling medical risk, IMPACT also accepts user-specified constraints, such as limitations of mass or volume, and will output a recommended clinical capability set and specific medical resources that meet the mission constraints. Discussion: This abstract will provide an introduction to IMPACT and describe the nature of the underlying medical evidence. It will also detail potential use cases for how this tool can be utilized by NASA or commercial spaceflight providers.

Ben Easter↗