Development of Slat-gap and Slat-cove Filler Treatments for Noise Reduction Assessment on the High-Lift Common Research Model in the NASA LaRC 14x22
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Introduction: Sleep inertia refers the transient neurobehavioral impairments experienced immediately after waking from sleep. This period of reduced alertness and performance poses a significant safety risk to on-call workers who may be required to perform a safety-critical task immediately after waking (e.g., emergency services, health care, and military). In these operations, the need for a rapid return to full alertness is critical to mission safety and success. Several factors may exacerbate sleep inertia, resulting in greater impairment upon waking, including: waking from deep sleep, (i.e., slow wave sleep, SWS), waking at night, and waking following prior sleep loss. Awakenings under these conditions are common for on-call and extended shift workers who may need to perform safety-critical tasks soon after waking from unprotected sleep opportunities. Therefore, there is a need for evidence-based reactive countermeasures (i.e., used upon waking) to the cognitive consequences sleep inertia. Specifically, countermeasures that can rapidly restore alertness and performance immediately following sleep. A recent review of the literature on reactive countermeasures highlighted several research gaps and promising candidates for further investigation. The review also emphasized the need for countermeasures that are operationally viable and readily deployed in occupational settings. This study aims to address the identified gaps and limitations by assessing the efficacy of exposure to two known acute alerting stimuli - blue-enriched light and peppermint odor - to improve cognitive performance, alertness, and mood immediately after waking from SWS at night. Materials and Methods: Twelve participants completed a two-week within-subject, randomized, cross-over intervention study including two in-laboratory overnight visits. During each experimental week, the subjects experienced one intervention (light or peppermint) and a control condition upon awakening from SWS at night. The presentation order of the two conditions (intervention or control) at wake-up and the order of intervention (light or peppermint) by week was randomized by sex. Prior to each in-laboratory visit, participants maintained a sleep schedule of 8.5 h for 5 nights and 5 h for one night. Compliance with this sleep schedule was confirmed by actigraphy. In the laboratory, participants went to bed at their habitual bedtime and were monitored by standard polysomnography. After at least five minutes of continuous SWS, participants were awoken and exposed, in a randomized order, to either the control or intervention condition. During the hour after awakening from SWS (at 2, 17, 32, and 47 minutes after waking), participants completed a battery of tasks including a 5-minute psychomotor vigilance task (PVT), a subjective scale of alertness (Karolinska Sleepiness Scale, KSS), and visual analogue scales (VAS) of mood. Following this sleep inertia measurement period, all lights were turned off and participants were allowed to return to sleep. They were then awoken again from their subsequent SWS period and exposed to the alternative condition (control or intervention). Following this second awakening, participants were allowed to sleep until their habitual wake time and were then released from the laboratory. Participants then followed the at-home sleep schedule and returned to the laboratory for the second intervention (light or peppermint) following the procedures described above. The light intervention involved exposure to a blue-enriched light canvas illuminated for 1 hour at a distance of ~56 cm from the participant (~200 lux and ~60 melanopic lux at angle of gaze). For the peppermint intervention, peppermint oil was pipetted onto a mask, and participants inhaled the odor with the mask covering the nose and mouth for 1 minute. The control condition for both weeks involved a dim, red ambient light (<1 lux). An odorless mask, without any oil pipetted onto the mask, was also worn in the peppermint control condition. Results: Compared to the control condition, participants exposed to blue-enriched light had fewer PVT lapses (χ2 = 5.285, p = .022), reported feeling more alert (KSS: F1,77 = 4.955, p = .029; VASalert: F1,77 = 8.226, p = .005), and had improved mood (VAScheerful: F1,77 = 8.615, p = .004; VASdepressed: F1,77 = 4.649, p = .034; VASlethargic: F1,77 = 5.652, p = .020). Exposure to peppermint oil did not improve any outcome measures on any of the tasks compared to control condition (p > .05). Conclusions: We found that participants had fewer lapses of attention upon awakening when exposed to blue-enriched light compared to dim, red light. In addition, participants reported feeling more alert, more cheerful, less depressed, and less lethargic in the blue-enriched light condition. Brief exposure to a peppermint odor, however, did not appear to improve performance, alertness, or mood under the experimental conditions. Our null results in the peppermint condition may have been due to methodological limitations such as the duration and method of administration. Given the need to mitigate the potential impact of sleep inertia on safety-critical tasks in on-call operations, our findings suggest that blue-enriched light exposure upon awakening may help to improve performance and alertness during the sleep inertia period following awakening from deep, nocturnal sleep. We are currently exploring the potential mechanisms for the effect of light on cognitive performance upon awakening as well as investigating its application in real-world settings to explore the translational efficacy of this countermeasure to occupational environments. Continued exploration into light and other reactive countermeasures, and potentially their combination, is needed in order to provide evidence-based guidance on effective sleep inertia countermeasures to improve the alertness and performance of those required to perform safety-critical tasks soon after waking.
In an effort to determine the gap between the actual performance and the necessary performance of employees for the effective and efficient accomplishment of an organization's mission and goals, an organization-wide Training Needs Assessment must be conducted. The purpose of this work was to conduct a training needs analysis and prepare a NASA Langley Catalog of On-Site Training programs. The work included developing a Training Needs Assessment Survey, implementing the survey, analyzing and researching the training needs, identifying the courses to meet the needs, and preparing and designing an On-Site Training Catalog. This needs analysis attempted to identify performance weaknesses and deficits; seek out and provide opportunities for improved performance; anticipate and avoid future problems; enhance and create new strengths. The end product is a user-friendly catalog of on-site training available. The results include: top-down approach to needs assessment; improved communication with training coordinators; 98 percent return rate of the Training Needs Assessment survey; complete, newly designed, user-friendly catalog; 167 catalog descriptions advertised; 82 new courses advertised; training logo; and request for the training application form.
The reliance on CFD simulations to develop, design, and optimize scramjet systems (or components) has become commonplace. This reliance inevitably hinges on the ability of the computational analyst to quantify the level of confidence in their computational results. Unfortunately, nearly all the measured data available for this assessment comes from antiquated experimental datasets, or from tests that focused on the extraction of scramjet system (or component) performance. The objective of a CFD validation experiment is to quantify the predictive accuracy of one or more of the CFD physics submodels, implying that other uncertainties related to replicating the facility flow environment (e.g., knowledge of boundary conditions) must be minimized to the extent possible. This inevitably places stringent requirements on the quality and quantity of measurements taken to accurately specify inflow, outflow, and surface conditions for the CFD simulations; in addition to the measurements taken for the validation of physics submodels. This places additional demands on the experimental process above and beyond those for test article performance assessment. A recent high speed code credibility workshop series sponsored by AFRL identified a gap in existing validation data for fundamental assessments of turbulent mixing and combustion CFD closure models at scramjet engine relevant conditions. To address this gap, engineers at AFRL have designed a coaxial jet flame configuration that will be tested at two facilities (Research Cell 19 at the Air Force Research Lab, and at Purdue University). The effort described here documents pretest simulations of this validation experiment with the goal of fleshing out the extent of the facility flowpath that must be included to adequately reproduce the facility test section flow environment. The findings indicate that the flow around the support structure for the fuel injection centerbody upstream of the facility nozzle generates disturbances that persist throughout the nozzle expansion process; corrupting the azimuthal symmetry that was desired in the fuel/air mixing region of the test section. Simulations without this support structure maintained a high degree of azimuthal symmetry up until the fuel injection plane. However, even in this scenario the azimuthal symmetry was not maintained once the centerbody boundary layer transitioned to a wake flow downstream of the fuel injection plane.
The reliance on CFD simulations to develop, design, and optimize scramjet systems (or components) has become commonplace. This reliance inevitably hinges on the ability of the computational analyst to quantify the level of confidence in their computational results. Unfortunately, nearly all the measured data available for this assessment comes from antiquated experimental datasets, or from tests that focused on the extraction of scramjet system (or component) performance. The objective of a CFD validation experiment is to quantify the predictive accuracy of one or more of the CFD physics submodels, implying that other uncertainties related to replicating the facility flow environment (e.g., knowledge of boundary conditions) must be minimized to the extent possible. This inevitably places stringent requirements on the quality and quantity of measurements taken to accurately specify inflow, outflow, and surface conditions for the CFD simulations; in addition to the measurements taken for the validation of physics submodels. This places additional demands on the experimental process above and beyond those for test article performance assessment. A recent high speed code credibility workshop series sponsored by AFRL identified a gap in existing validation data for fundamental assessments of turbulent mixing and combustion CFD closure models at scramjet engine relevant conditions. To address this gap, engineers at AFRL have designed a coaxial jet flame configuration that will be tested at two facilities (Research Cell 19 at the Air Force Research Lab, and at Purdue University). The effort described here documents pretest simulations of this validation experiment with the goal of fleshing out the extent of the facility flowpath that must be included to adequately reproduce the facility test section flow environment. The findings indicate that the flow around the support structure for the fuel injection centerbody upstream of the facility nozzle generates disturbances that persist throughout the nozzle expansion process; corrupting the azimuthal symmetry that was desired in the fuel/air mixing region of the test section. Simulations without this support structure maintained a high degree of azimuthal symmetry up until the fuel injection plane. However, even in this scenario the azimuthal symmetry was not maintained once the centerbody boundary layer transitioned to a wake flow downstream of the fuel injection plane.
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The accuracy of PBL height simulation is a key issue in many applications including forecasting near surface meteorology and air quality, however, it is a very challenging problem due to the lack of not only comprehensive, global Planetary Boundary Layer (PBL) observations but also a strategy and infrastructure to utilize PBL height data from a variety of sensors. Following the designation of PBL as an incubation class observable in the 2017 Decadal Survey, the PBL Incubation Study Team Report [14] made clear that “a future global PBL observing system requires modeling and data assimilation as essential components.” There is an urgent need for global modeling development in order to utilize Program of Record (POR) observations, assess their impacts, and identify gaps to be filled by future PBL missions. Our overall objective is to develop PBL data assimilation capabilities in the NASA Global Earth Observing System (GEOS), focusing on PBL height from multiple observing systems, to support the assessment and use of future PBL observations. The NASA GEOS system is composed of the GEOS global atmospheric general circulation model (AGCM) and the atmospheric data assimilation system (ADAS). The PBL parameterizations include the “Lock” K-profile scheme driven by surface and cloud-top buoyancy fluxes ([4]), and the “Louis” local scheme for stable conditions based on the Richardson number ([5]). Above the mixed layer defined by the Lock surface plume, shallow cumulus convection is represented by the mass flux scheme of [9]. Additional parameterizations are summarized in [1]. The ADAS employs the hybrid 4D Ensemble- Variational (EnVar) configuration ([15]), with the ensemble providing flow-dependent background error covariance information. The resultant analysis increments are fed back to the forecast model through the 4D incremental analysis update (IAU) approach ([11]). In this study, PBL height data are being or have been generated from radiosondes, GNSS RO, satellite (CATS, CALIPSO and ICESat-2) and ground-based (MPLNET) lidars, and wind profiler. Investigations have been conducted to specify quality marks for PBL height retrievals for the data assimilation purpose. These PBL height data have different strengths and weaknesses ([2], [3], [6], [7], [8], [10]), and the satellite PBL height data provide better global coverage and complement in-situ PBL height data. Radiosondes offer high accuracy and in situ measurement of temperature and humidity profiles, but with poor spatio-temporal sampling. The in-situ observing systems like MPLNET and wind profiler provide long history of PBL height records at each station. The GNSS RO based PBL height is retrieved based on the sharp gradients in refractivity profile that represent the fine vertical structure of temperature and moisture changes above the PBL. However, not all RO refractivity profiles reach the surface depending on location and regime, and RO refractivity retrievals can be negatively biased below 2km. The PBL height data from satellite lidars provide high resolution along track PBL height retrievals, but over land they are affected by previous day convective PBL aerosol and strongly associated with mixing layer and retrievals cannot be made below thick, attenuating clouds. A successful assimilation of PBL height data requires a thorough understanding of the observing method and the retrieval algorithm for each observing system in order to use the PBL height data from multiple observing systems properly. Due to the sensitivity of PBL height data to the observing method and choice of algorithm, it is important to use a model definition appropriate for each observation type to compute differences between PBL height data and model PBL height (OmFs). The GEOS model currently includes two PBL height definitions suitable for direct comparison with observed PBL height, and additional definitions are being added in this study. Evaluation of different model PBL height definitions is underway. Meanwhile, efforts have been made in the GEOS data assimilation system to develop PBL height data assimilation capability. PBL height data can be assimilated using two different approaches. The traditional approach is to construct an observation operator and its tangent linear and adjoint, which link control variables to PBL height data from each observing system. This observation operator can be very complicated, e.g., the lidar-based PBL height observation operator includes the backscatter lidar forward observation operator, the algorithm to derive PBL height from attenuated total backscatter, interpolation, and calculations handling the mismatch between observed and model scales. The other approach is to augment PBL height to the control variable vector, and it is adopted in this study. The latter approach was also used in previous studies, e.g., the assimilation of PBL height data from radiosonde and aircraft in the Real Time Mesoscale Analysis (RTMA) system for a dispersion modelling study ([13]); the PBL height assimilation study using lidar PBL height data at Greensburg, Kansas for a field campaign ([12]). The PBL height assimilation from multiple observing systems in this study allows us to take advantage of the diverse PBL height data that provide much better global coverage collectively under different meteorological conditions and with different temporal and spatial scales. As all the PBL heights are tightly coupled with the PBL thermodynamic variables, the strong correlations, which are provided by the 4D ensemble forecast, enable PBL height data from various sources to interact and combine coherently and provide additional information for PBL temperature and moisture fields. The results of comparisons among PBL height data from different sources and the evaluation of the model PBL height definitions with the PBL height data will be presented, and the PBL height data synergy strategies and preliminary results will also be discussed at the conference.
The leading edge slat of a high-lift system is one of the main contributors to airframe noise during approach. In a previous experimental study, we assessed the performance of an impermeable slat gap filler as a passive flow control device to reduce the slat noise associated with a two-dimensional, three-element high-lift airfoil. The present paper, the first of two parts,represents a follow-on investigation to assess the relative efficacy of permeable gap fillers thatallow successively higher amounts of flow to pass through the gap. To evaluate the influence of this passive flow control device on the acoustics generated by the unsteady flow near the slat, experiments are conducted in an anechoic wind tunnel by mounting a gap filler to the slat element of the two-dimensional 30P30N high-lift configuration. Measurements are performed at a single geometric angle of attack (𝛼𝑘=8◦) and three different flow speeds that correspond to Reynolds numbers of𝑅𝑒𝑐=1.2𝑒6,1.5𝑒6, and1.71𝑒6, respectively. Steady surface pressure measurements are used to gauge the influence of the permeable gap filler treatments on the overall lift. The effect of each treatment on the radiated noise is analyzed via acoustic array measurements, followed by delay-and-sum beamforming to locate the slat noise sources and to provide the integrated acoustic spectra. The porous gap fillers are found to eliminate the narrowband peaks in the acoustic spectra and, also, to yield a 10 dB reduction in the broadband noise in comparison with the baseline case with no gap filler. The porous gap filler with thelowest permeability acts similar to the impermeable gap filler examined previously. However, the aerodynamics and noise reduction both degrade with increasing permeability. An accompanying abstract describes the particle image velocimetry measurements of the flowfield within the slat cove and on either side of the permeable gap f
Mars Aerocapture Systems Study (MASS) is a detailed study of the application of aerocapture to a large Mars robotic orbiter to assess and identify key technology gaps. This study addressed use of an Opposition class return segment for use in the Mars Sample Return architecture. Study addressed mission architecture issues as well as system design. Key trade studies focused on design of aerocapture aeroshell, spacecraft design and packaging, guidance, navigation and control with simulation, computational fluid dynamics, and thermal protection system sizing. Detailed master equipment lists are included as well as a cursory cost assessment.
NASA has long used Probabilistic Risk Assessment (PRA) when high-stakes decisions need to be made about complex systems. For spaceflight medical risk, the Human Research Program’s Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) is a significant step towards robustly quantifying the risk to crew health during exploration missions. However, there remains a significant gap in the ability to comprehensively characterize and assess risk across the disparate functionalities and capabilities which comprise the entire Crew Health and Performance (CHP) system. To fill this gap, the Crew Health and Performance – Probabilistic Risk Assessment (CHP-PRA) project aims to perform risk characterization for the CHP system by assessing performance risk in addition to medical risk. This effort also includes quantifying Long-Term Health (LTH) risk in addition to in-mission risk outcomes within the CHP-PRA results. LTH risk encompasses the timeframe from immediately post-flight, through the rest of an astronaut’s career, through retirement, and until death. A proof-of-concept LTH risk metric is based on medical condition end-state, as defined by the Evidence Library, capturing the spaceflight specific medical impacts persisting into post-flight[1]. Condition outcomes in the Evidence Library progress through three Clinical Phases (CP): the diagnostic phase (CP1), the treatment/convalescent phase (CP2), and the end-state phase (CP3) which represents the detrimental effects of the condition after the crew member has recovered to the maximal extent. Each CP has an associated Task Impairment (TI), defined as the degree of crew incapacity due to experiencing the condition, and is quantified with a 0-1 range. Conditions with an associated CP3 (e.g. Sepsis, Traumatic Hypovolemic Shock, Sudden Cardiac Arrest, etc.) typically have serious consequences that can cause an astronaut to be fully or partially debilitated throughout the remainder of the mission. Consequently, the Cumulative CP3 TI End-of-Mission Health Status Metric is developed by CHP-PRA to quantify the cumulative effects of all conditions which progressed to the CP3 state throughout the entirety of the mission. Hence, this End-of-Mission Health Status Metric attempts to serve as an indicator of an astronaut’s health state at the time of landing. The severity of the lingering effects of in-mission medical events are dependent on mission activities and the level of available in-mission medical care. This allows the associated cumulative TI metric to be used in comparison with the crew’s end of mission health status for different levels of in-mission resources. This presentation provides the strategy for using CP3 as an LTH metric component, as well as a proof-of-concept demonstration of LTH risk characterization using this component.
The Space Crop Production (SCP) Program at the NASA Kennedy Space Center (KSC) is aimed at achieving nutrient supplementation and moving towards caloric independence from Earth by growing crops for astronauts. However, growing crops outside of Earth’s orbit creates many new challenges. The KCS SCP Project Scientists have developed a method of organizing these challenges, called the Gaps List. This Gaps List is a dynamic, taxonomically arranged list of missing knowledge and technologies needed to reach production goals. The purpose of this evaluation was to assess the effectiveness and current research coverage of the Gaps List by using it to document KSC SCP Program research. It was determined that there are several needs within the SCP Program that are not being met, as well as, many deficiencies within the Gaps List. Gaps involving hardware were largely unrecognized by both the KSC researchers and the funding sources that would typically support them. The KSC SCP Project will require more engineering and physical sciences support to fill those gaps. The Gaps List was found to be out of date and in need of rearrangement. A recommendation from this review was that the Gaps List be reassessed at regular intervals to ensure all gaps, and relevant research topics are included. To better understand the gaps within the list, any assessment needs to include a measure of priority, dependency, and breadth. These measures may be included within or alongside the current taxonomical arrangement of the Gaps List.
The Space Crop Production (SCP) Program at the NASA Kennedy Space Center (KSC) is aimed at achieving nutrient supplementation and moving towards caloric independence from Earth by growing crops for astronauts. However, growing crops outside of Earth’s orbit creates many new challenges. The KCS SCP Project Scientists have developed a method of organizing these challenges, called the Gaps List. This Gaps List is a dynamic, taxonomically arranged list of missing knowledge and technologies needed to reach production goals. The purpose of this evaluation was to assess the effectiveness and current research coverage of the Gaps List by using it to document KSC SCP Program research. It was determined that there are several needs within the SCP Program that are not being met, as well as, many deficiencies within the Gaps List. Gaps involving hardware were largely unrecognized by both the KSC researchers and the funding sources that would typically support them. The KSC SCP Project will require more engineering and physical sciences support to fill those gaps. The Gaps List was found to be out of date and in need of rearrangement. A recommendation from this review was that the Gaps List be reassessed at regular intervals to ensure all gaps, and relevant research topics are included. To better understand the gaps within the list, any assessment needs to include a measure of priority, dependency, and breadth. These measures may be included within or alongside the current taxonomical arrangement of the Gaps List.
The Space Crop Production (SCP) at the NASA Kennedy Space Center (KSC) is aimed at achieving nutrient supplementation and moving towards caloric independence from Earth by growing crops for astronauts. However, growing crops outside of Earth’s orbit creates many new challenges. The KCS SCP Project Scientists have developed a method of organizing these challenges, called the Gaps List. This Gaps List is a dynamic, taxonomically arranged list of missing knowledge and technologies needed to reach production goals. The purpose of this evaluation was to assess the effectiveness and current research coverage of the Gaps List by using it to document the KSC SCP Program research. In evaluating the research, it was determined that several needs within the SCP Program that are not being met, and many deficiencies within the Gaps List were encountered. Gaps involving hardware were largely unrecognized by the KSC researchers and the funding sources that would typically support them. The KSC SCP Project will require more engineering and physical sciences support to close those gaps. The Gaps List was found to be out of date and in need of rearrangement. A recommendation from this review was that the Gaps List be reassessed at regular intervals to ensure all gaps and relevant research topics are included. In order to better understand the gaps within the list, any assessment needs to include a measure of priority, dependency and breadth. These measures may be included within or along side the current taxonomical arrangement of the Gaps List.
Performance of Extra-Vehicular Activities (EVA) has been and will continue to be a critical capability for human space flight. Human exploration missions beyond LEO will require EVA capability for either contingency or nominal activities to support mission objectives and reduce mission risk. EVA systems encompass a wide array of products across pressure suits, life support systems, EVA tools and unique spacecraft interface hardware (i.e. EVA Translation Paths and EVA Worksites). In a fiscally limited environment with evolving transportation and habitation options, it is paramount that the EVA community's strategic planning and architecture integration products be reviewed and vetted for traceability between the mission needs far into the future to the known technology and knowledge gaps to the current investments across EVA systems. To ascertain EVA technology and knowledge gaps many things need to be brought together, assessed and analyzed. This includes an understanding of the destination environments, various mission concept of operations, current state of the art of EVA systems, EVA operational lessons learned, and reference advanced capabilities. A combined assessment of these inputs should result in well-defined list of gaps. This list can then be prioritized depending on the mission need dates and time scale of the technology or knowledge gap closure plan. This paper will summarize the current state of EVA related technology and knowledge gaps derived from NASA's Exploration EVA Reference Architecture and Operations Concept products. By linking these products and articulating NASA's approach to strategic development for EVA across all credible destinations an EVA could be done in, the identification of these gaps is then used to illustrate the tactical and strategic planning for the EVA technology development portfolio. Finally, this paper illustrates the various "touch points" with other human exploration risk identification areas including human health and performance.
The NASA engineering community utilizes event-driven and fault-tree probabilistic techniques to classify risks in the space environment by taking advantage of the inherent knowledge of complex spaceflight system design and testing to quantify failure risk. In harmonizing the risk of human space flight, answering the question of ‘How do we balance health, performance and resource risks with other engineering risks on long duration space missions?’ remains a deeply challenging and largely qualitative practice. The Human Research Program’s Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) was a significant step forward in efforts to robustly quantify the risk to crew health for exploration missions. However, there remains a significant gap in the ability to comprehensively assess and characterize risk across the disparate functionalities and capabilities which comprise the Crew Health and Performance (CHP) system. The Crew Health and Performance – Probabilistic Risk Assessment (CHP-PRA) project seeks to characterize CHP risks by expanding beyond the foundation established by its PRA predecessors like IMM and MEDPRAT, that simulate medical risk metrics like loss of crew life and evacuations. One of the new risk measures in the CHP-PRA system is embodied in our Performance Risk Model (PRisM). PRisM provides a novel way of assessing crew performance on mission tasks, using a generalized framework which relates back to NASA-STD-3001. This approach allows PRisM to capture and integrate data from a variety of different domains into a single, unified, reproducible representation of astronaut performance. In this presentation, we discuss the motivation for the CHP-PRA work and give a high level overview of the goals of the project, outline the forward work for PRisM, and discuss collaboration opportunities for the community who might explore if their domain knowledge and data could be represented, integrated, and quantified with these tools, whose outcomes are metrics useful for supporting operational mission planning and decision making.
Spaceflight requires tremendous amounts of energy to achieve Earth orbit and to attain escape velocity for interplanetary missions. Although the majority of the energy is managed in such a way as to limit the accelerations on the crew, several mission phases may result in crew exposure to dynamic loads. In the automotive industry, risk of serious injury can be tolerated because the probability of a crash is remote each time a person enters a vehicle, resulting in a low total risk of injury. For spaceflight, the level of acceptable injury risk must be lower to achieve a low total risk of injury because the dynamic loads are expected on each flight. To mitigate the risk of injury due to dynamic loads, the NASA Human Research Program has developed a research plan to inform the knowledge gaps and develop relevant tools for assessing injury risk. The risk of injury due to dynamic loads can be further subdivided into extrinsic and intrinsic risk factors. Extrinsic risk factors include the vehicle dynamic profile, seat and restraint design, and spacesuit design. Human tolerance to loads varies considerably depending on the direction, amplitude, and rise-time of acceleration therefore the orientation of the body to the dynamic vector is critical to determining crew risk of injury. Although a particular vehicle dynamic profile may be safe for a particular design, the seat, restraint, and suit designs can affect the risk of injury due to localized effects. In addition, characteristics intrinsic to the crewmember may also contribute to the risk of injury, such as crewmember sex, age, anthropometry, and deconditioning due to spaceflight, and each astronaut may have a different risk profile because of these factors. The purpose of the research plan is to address any knowledge gaps in the risk factors to mitigate injury risk. Methods for assessing injury risk have been well documented in other analogous industries and include human volunteer testing, human exposure to dynamic environments, post-mortem human subject (PMHS) testing, animal testing, anthropomorphic test devices (ATD), dynamic models of the human, numerical models of ATDs, and numerical models of the human. Each has inherent strengths and limitations. For example, human volunteer testing is advantageous because a population can be selected that is similar to the astronaut corps; however, because of the inherent ethical limitations, only sub-injurious conditions can be tested. PMHSs can be tested in a variety of conditions including injurious levels, but the responses are not completely analogous to living human subjects. In addition, it is exceedingly difficult to select a PMHS population that is similar to the astronaut corps. ATDs are currently widely used in the automotive industry and military because they are highly repeatable and durable. Unfortunately, because they are mechanical models of the human body, the biofidelity of the responses are limited to dynamic conditions used to validate the ATD. Numerical models of the ATD, in addition to the strengths and limitations for ATDs, are easy to use for a variety of designs before a design is fabricated, but also have additional limitations for ATDs, are easy to use for a variety of designs before a design is fabricated, but also have additional uncertainty. Dynamic models are simple and easy to use, but do not account for localized effects of the seat and suit. Finally, numerical models of the human have the potential to have the most advantages; however, the current models are not validated for the conditions expected during spaceflight. To properly assess spaceflight conditions with numerical human models, human data would be needed to optimize the model responses for those conditions. Using the appropriate assessment method with the knowledge gained for each risk factor, an appropriate approach for mitigating the risk of injury due to dynamic loads can be developed ensuring crew safety in future NASA vehicles.
In the commercial aviation domain, large volumes of data are collected and analyzed on the failures and errors that result in infrequent incidents and accidents, but in the absence of data on behaviors that contribute to routine successful outcomes, safety management and system design decisions are based on a small sample of non- representative safety data. Analysis of aviation accident data suggests that human error is implicated in up to 80% of accidents, which has been used to justify future visions for aviation in which the roles of human operators are greatly diminished or eliminated in the interest of creating a safer aviation system. However, failure to fully consider the human contributions to successful system performance in civil aviation represents a significant and largely unrecognized risk when making policy decisions about human roles and responsibilities. Opportunities exist to leverage the vast amount of data that has already been collected, or could be easily obtained, to increase our understanding of human contributions to “things going right” in commercial aviation. The principal focus of this assessment was to identify current gaps and explore methods for identifying human “success” data generated by the aviation system, from personnel and within the supporting infrastructure.
The objectives of the Technology Watch process are to identify emerging, high-impact technologies that augment current ExMC development efforts, and to work with academia, industry, and other government agencies to accelerate the development of medical care and research capabilities for the mitigation of potential health issues that could occur during space exploration missions. The establishment of collaborations with these entities is beneficial to technology development, assessment and/or insertion. Such collaborations also further NASA s goal to provide a safe and healthy environment for human exploration. The Tech Watch project addresses requirements and capabilities identified by knowledge and technology gaps that are derived from a discrete set of medical conditions that are most likely to occur on exploration missions. These gaps are addressed through technology readiness level assessments, market surveys, collaborations and distributed innovation opportunities. Ultimately, these gaps need to be closed with respect to exploration missions, and may be achieved through technology development projects. Information management is a key aspect to this process where Tech Watch related meetings, research articles, collaborations and partnerships are tracked by the HRP s Exploration Medical Capabilities (ExMC) Element. In 2011, ExMC will be introducing the Tech Watch external website and evidence wiki that will provide access to ExMC technology and knowledge gaps, technology needs and requirements documents.