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At least 289 records · Page 16

Simulation for Prediction of Entry Article Demise (SPEAD): An Analysis Tool for Spacecraft Safety Analysis and Ascent/Reentry Risk Assessment

For the purpose of performing safety analysis and risk assessment for a potential off-nominal atmospheric reentry resulting in vehicle breakup, a synthesis of trajectory propagation coupled with thermal analysis and the evaluation of node failure is required to predict the sequence of events, the timeline, and the progressive demise of spacecraft components. To provide this capability, the Simulation for Prediction of Entry Article Demise (SPEAD) analysis tool was developed. The software and methodology have been validated against actual flights, telemetry data, and validated software, and safety/risk analyses were performed for various programs using SPEAD. This report discusses the capabilities, modeling, validation, and application of the SPEAD analysis tool.

Ling, Lisa↗

The Predicted Growth of the Low Earth Orbit Space Debris Environment: An Assessment of Future Risk for Spacecraft

Space debris is a worldwide-recognized issue concerning the safety of commercial, military, and exploration spacecraft. The space debris environment includes both naturally occuring meteoroids and objects in Earth orbit that are generated by human activity, termed orbital debris. Space agencies around the world are addressing the dangers of debris collisions to both crewed and robotic spacecraft. In the United States, the Orbital Debris Program Office at the NASA Johnson Space Center leads the effort to categorize debris, predict its growth, and formulate mitigation policy for the environment from low Earth orbit (LEO) through geosynchronous orbit (GEO). This paper presents recent results derived from the NASA long-term debris environment model, LEGEND. It includes the revised NASA sodium potassium droplet model, newly corrected for a factor of two over-estimation of the droplet population. The study indicates a LEO environment that is already highly collisionally active among orbital debris larger than 1 cm in size. Most of the modeled collision events are non-catastrophic (i.e., They lead to a cratering of the target, but no large scale fragmentation.). But they are potentially mission-ending, and take place between impactors smaller than 10 cm and targets larger than 10 cm. Given the small size of the impactor these events would likely be undetectable by present-day measurement means. The activity continues into the future as would be expected. Impact rates of about four per year are predicted by the current study within the next 30 years, with the majority of targets being abandoned intacts (spent upper stages and spacecraft). Still, operational spacecraft do show a small collisional activity, one that increases over time as the small fragment population increases.

Krisko, Paula H.↗

Review and developments of dissemination models for airborne carbon fibers

Dissemination prediction models were reviewed to determine their applicability to a risk assessment for airborne carbon fibers. The review showed that the Gaussian prediction models using partial reflection at the ground agreed very closely with a more elaborate diffusion analysis developed for the study. For distances beyond 10,000 m the Gaussian models predicted a slower fall-off in exposure levels than the diffusion models. This resulting level of conservatism was preferred for the carbon fiber risk assessment. The results also showed that the perfect vertical-mixing models developed herein agreed very closely with the diffusion analysis for all except the most stable atmospheric conditions.

Elber, W.↗

New Era, New Opportunity, Is GES DISC Ready for Big Data Challenge?

The new era of Big Data has opened doors for many new opportunities, as well as new challenges, for both Earth science research/application and data communities. As one of the twelve NASA data centers - Goddard Earth Sciences Data and Information Services Center (GES DISC), one of our great challenges has been how to help research/application community efficiently (quickly and properly) accessing, visualizing and analyzing the massive and diverse data in natural hazard research, management, or even prediction. GES DISC has archived over 2000 TB data on premises and distributed over 23,000 TB of data since 2010. Our data has been widely used in every phase of natural hazard management and research, i.e. long term risk assessment and reduction, forecasting and predicting, monitoring and detection, early warning, damage assessment and response. The big data challenge is not just about data storage, but also about data discoverability and accessibility, and even more, about data migration/mirroring in the cloud. This paper is going to demonstrate GES DISC’s efforts and approaches of evolving our overall Web services and powerful Giovanni (Geospatial Interactive Online Visualization ANd aNalysis Infrastructure) tool into further improving data discoverability and accessibility. Prototype works will also be presented.

Li, A.↗

The Challenger Tradgedy was Caused by an Apollo Mistake, Terminating Risk Analysis

NASA’s attitude toward risk changed drastically between the Apollo and Space Shuttle design. [1]Apollo engineers were seriously alarmed about riskbecause of the fatal Apollo 1 fire and the fact that the estimated probability of another fatal accident was extremely high. The predictions were so appalling thatmanagement terminated risk analysis to avoid public apprehension. Because risk analysis was not done, the Space Shuttle design accepted excessively high andunknown risk. The immediate cause of the Challengertragedy was the mistaken decision to launch in coldweather that impaired the O-ring seals, but the fundamental cause was the high risk of the shuttle design. Before Challenger, management asserted that the probability of a fatal accident was 1 in 100,000.Probabilistic Risk Analysis (PRA) found a roughly 1 in 100 chance of a shuttle failure.

Harry W Jones↗

The Extravehicular Suit Impact Load Attenuation Study for Use in Astronaut Bone Fracture Prediction

The NASA Integrated Medical Model (IMM) assesses the risk, including likelihood and impact of occurrence, of all credible in-flight medical conditions. Fracture of the proximal femur is a traumatic injury that would likely result in loss of mission if it were to happen during spaceflight. The low gravity exposure causes decreases in bone mineral density which heightens the concern. Researchers at the NASA Glenn Research Center have quantified bone fracture probability during spaceflight with a probabilistic model. It was assumed that a pressurized extravehicular activity (EVA) suit would attenuate load during a fall, but no supporting data was available. The suit impact load attenuation study was performed to collect analogous data. METHODS: A pressurized EVA suit analog test bed was used to study how the offset, defined as the gap between the suit and the astronaut s body, impact load magnitude and suit operating pressure affects the attenuation of impact load. The attenuation data was incorporated into the probabilistic model of bone fracture as a function of these factors, replacing a load attenuation value based on commercial hip protectors. RESULTS: Load attenuation was more dependent on offset than on pressurization or load magnitude, especially at small offsets. Load attenuation factors for offsets between 0.1 - 1.5 cm were 0.69 +/- 0.15, 0.49 +/- 0.22 and 0.35 +/- 0.18 for mean impact forces of 4827, 6400 and 8467 N, respectively. Load attenuation factors for offsets of 2.8 - 5.3 cm were 0.93 +/- 0.2, 0.94 +/- 0.1 and 0.84 +/- 0.5, for the same mean impact forces. Reductions were observed in the 95th percentile confidence interval of the bone fracture probability predictions. CONCLUSIONS: The reduction in uncertainty and improved confidence in bone fracture predictions increased the fidelity and credibility of the fracture risk model and its benefit to mission design and operational decisions.

Lewandowski, Beth E.↗

HRP's Healthcare Spin-Offs Through Computational Modeling and Simulation Practice Methodologies

Spaceflight missions expose astronauts to novel operational and environmental conditions that pose health risks that are currently not well understood, and perhaps unanticipated. Furthermore, given the limited number of humans that have flown in long duration missions and beyond low Earth-orbit, the amount of research and clinical data necessary to predict and mitigate these health and performance risks are limited. Consequently, NASA's Human Research Program (HRP) conducts research and develops advanced methods and tools to predict, assess, and mitigate potential hazards to the health of astronauts. In this light, NASA has explored the possibility of leveraging computational modeling since the 1970s as a means to elucidate the physiologic risks of spaceflight and develop countermeasures. Since that time, substantial progress has been realized in this arena through a number of HRP funded activates such as the Digital Astronaut Project (DAP) and the Integrated Medical Model (IMM). Much of this success can be attributed to HRP's endeavor to establish rigorous verification, validation, and credibility (VV&C) processes that ensure computational models and simulations (M&S) are sufficiently credible to address issues within their intended scope. This presentation summarizes HRP's activities in credibility of modeling and simulation, in particular through its outreach to the community of modeling and simulation practitioners. METHODS: The HRP requires all M&S that can have moderate to high impact on crew health or mission success must be vetted in accordance to NASA Standard for Models and Simulations, NASA-STD-7009 (7009) [5]. As this standard mostly focuses on engineering systems, the IMM and DAP have invested substantial efforts to adapt the processes established in this standard for their application to biological M&S, which is more prevalent in human health and performance (HHP) and space biomedical research and operations [6,7]. These methods have also generated substantial interest by the broader medical community though institutions like the National Institutes of Health (NIH) and the Food and Drug Administration (FDA) to develop similar standards and guidelines applicable to the larger medical operations and research community. DISCUSSION: Similar to NASA, many leading government agencies, health institutions and medical product developers around the world are recognizing the potential of computational M&S to support clinical research and decision making. In this light, substantial investments are being made in computational medicine and notable discoveries are being realized [8]. However, there is a lack of broadly applicable practice guidance for the development and implementation of M&S in clinical care and research in a manner that instills confidence among medical practitioners and biological researchers [9,10]. In this presentation, we will give an overview on how HRP is working with the NIH's Interagency Modeling and Analysis Group (IMAG), the FDA and the American Society of Mechanical Engineers (ASME) to leverage NASA's biomedical VV&C processes to establish a new regulatory standard for Verification and Validation in Computational Modeling of Medical Devices, and Guidelines for Credible Practice of Computational Modeling and Simulation in Healthcare.

Mulugeta, Lealem↗

Digital Astronaut Project Biomechanical Models: Biomechanical Modeling of Squat, Single-Leg Squat and Heel Raise Exercises on the Hybrid Ultimate Lifting Kit (HULK)

The NASA Digital Astronaut Project (DAP) implements well-vetted computational models to predict and assess spaceflight health and performance risks, and to enhance countermeasure development. The DAP Musculoskeletal Modeling effort is developing computational models to inform exercise countermeasure development and to predict physical performance capabilities after a length of time in space. For example, integrated exercise device-biomechanical models can determine localized loading, which will be used as input to muscle and bone adaptation models to estimate the effectiveness of the exercise countermeasure. In addition, simulations of mission tasks can be used to estimate the astronaut's ability to perform the task after exposure to microgravity and after using various exercise countermeasures. The software package OpenSim (Stanford University, Palo Alto, CA) (Ref. 1) is being used to create the DAP biomechanical models and its built-in muscle model is the starting point for the DAP muscle model. During Exploration missions, such as those to asteroids and Mars, astronauts will be exposed to reduced gravity for extended periods. Therefore, the crew must have access to exercise countermeasures that can maintain their musculoskeletal and aerobic health. Exploration vehicles may have very limited volume and power available to accommodate such capabilities, even more so than the International Space Station (ISS). The exercise devices flown on Exploration missions must be designed to provide sufficient load during the performance of various resistance and aerobic/anaerobic exercises while meeting potential additional requirements of limited mass, volume and power. Given that it is not practical to manufacture and test (ground, analog and/or flight) all candidate devices, nor is it always possible to obtain data such as localized muscle and bone loading empirically, computational modeling can estimate the localized loading during various exercise modalities performed on a given device to help formulate exercise prescriptions and other operational considerations. With this in mind, NASA's Digital Astronaut Project (DAP) is supporting the Advanced Exercise Concepts (AEC) Project, Exercise Physiology and Countermeasures (ExPC) laboratory and NSBRI-funded researchers by developing and implementing well-validated computational models of exercises with advanced exercise device concepts. This report focuses specifically on lower-body resistance exercises performed with the Hybrid Ultimate Lifting Kit (HULK) device as a deliverable to the AEC Project.

health↗

Operational Aspects of Space Radiation

In this session, Session FA4, the discussion focuses on the following topics: Solar Particle Events and the International Space Station; Radiation Environment on Mir and ISS Orbits During the Solar Cycle; New approach to Radiation Risk Assessment; An Industrial Method to Predict Major Solar Flares for a Better Protection of Human Beings in Space; Description of the Space Radiation Control System for the Russian Segment of ISS; Orbit Selection and Its Impact on Radiation Warning Architecture for a Human Mission to Mars; and Space Nuclear Power - Technology, Policy and Risk Considerations in Human Missions to Mars.

Source record↗

Coronary Risk Factor Scoring as a Guide for Counseling

A risk factor scoring system for early detection, possible prediction, and counseling to coronary heart disease patients is discussed. Scoring data include dynamic EKG, cholesterol levels, triglycerine content, total lipid level, total phospolipid levels, and electrophoretic patterns. Results indicate such a system is effective in identifying high risk subjects, but that the ability to predict exceeds the ability to prevent heart disease or its complications.

Robert L. Fleck↗

Plant Responses to Increased UV-B Radiation: A Research Project

Ozone decrease implies more ultraviolet-B (UV-B) radiation reaching the surface of the Earth. Increased UV-B radiation triggers responses by living organisms. Despite the large potential impacts on vegetation, little is known about UV-B effects on terrestrial ecosystems. Long-term ecological studies are needed to quantify the effects of increased UV radiation on terrestrial ecosystems, asses the risks, and produce reliable data for prediction. Screening pigments are part of one of the protective mechanism in plants. Higher concentrations of screening pigments in leaves may be interpreted as a response to increased UV radiation. If the screening effect is not sufficient, important molecules will be disturbed by incoming radiation. Thus, genetics, photosynthesis, growth, plant and leaf shape and size, and pollen grains may be affected. This will have an impact on ecosystem dynamics, structure and productivity. It is necessary to monitor selected terrestrial ecosystems to permit detection and interpretation of changes attributable to global climate change and depleted ozone shield. The objectives of this project are: (1) To identify and measure indicators of the effects of increased solar UV-B radiation on terrestrial plants; (2) to select indicators with the greatest responses to UV-B exposure; (3) to test, adapt or create ecosystem models that use the information gathered by this project for prediction and to enhance our understanding of the effects of increased UV-B radiation on terrestrial ecosystems. As a first step to achieve these objectives we propose a three-year study of forest and steppe vegetation on the North slope of the Brooks Range (within the Arctic circle, in Alaska), in the Saguaro National Monument (near Tucson, Arizona) and in the forests and steppes of Patagonia (Argentina). We selected (1) vegetation north of the Polar Circle because at 70N there is 8% risk of plant damage due to increased UV-B radiation; (2) the foothills of Catalina Mountains because there is anecdotal evidence of plant damage on the saguaros that has been linked to increased UV radiation, and (3) the forests of Nothofagus spp. and the steppe of Patagonia where the risk of plant damage at 35S is 5% and increases to as much as 15% at 55S due to increased UV-B radiation. Measurements of UV-B radiation impinging on the surface at 55S largely exceed the predicted UV-B radiation values at 50 latitude and 0% ozone depletion. Preliminary HPLC analyses of UV-B absorbing compounds in Nothofagus antartica, N. pumilio, N. betuloides and Rumex sp. in natural conditions show species-specific patterns. The spectrum of N. antartica grown at 38S differs significantly from that of N. antartica in natural conditions in Ushuaia (55S). These results suggest that the selected main area (Patagonia) is appropriate for assessing the problem and its magnitude and that Nothofagus is appropriate for our study.

DAntoni, H. L.↗

Quantitative Prediction of Computational Quality (so the S and C Folks will Accept it)

Our choice of title may seem strange but we mean each word. In this talk, we are not going to be concerned with computations made "after the fact", i.e. those for which data are available and which are being conducted for explanation and insight. Here we are interested in preventing S&C design problems by finding them through computation before data are available. For such a computation to have any credibility with those who absorb the risk, it is necessary to quantitatively PREDICT the quality of the computational results.

Hemsch, Michael J.↗

Modeling the effects of exercise during 100% oxygen prebreathe on the risk of hypobaric decompression sickness

BACKGROUND: Several previous studies indicated that exercise during prebreathe with 100% O2 decreased the incidence of hypobaric decompression sickness (DCS). We report a meta-analysis of these investigations combined with a new study in our laboratory to develop a statistical model as a predictive tool for DCS. HYPOTHESIS: Exercise during prebreathe increases N2 elimination in a theoretical 360-min half-time compartment decreasing the incidence of DCS. METHODS: A dose-response probability tissue ratio (TR) model with 95% confidence limits was created for two groups, prebreathe with exercise (n = 113) and resting prebreathe (n = 113), using nonlinear regression analysis with maximum likelihood optimization. RESULTS: The model predicted that prebreathe exercise would reduce the residual N2 in a 360-min half-time compartment to a level analogous to that in a 180-min compartment. This finding supported the hypothesis. The incidence of DCS for the exercise prebreathe group was significantly decreased (Chi-Square = 17.1, p < 0.0001) from the resting prebreathe group. CONCLUSIONS: The results suggested that exercise during prebreathe increases tissue perfusion and N2 elimination approximately 2-fold and markedly lowers the risk of DCS. Based on the model, the prebreathe duration may be reduced from 240 min to a predicted 91 min for the protocol in our study, but this remains to be verified. The model provides a useful planning tool to develop and test appropriate prebreathe exercise protocols and to predict DCS risks for astronauts.

NASA Program Environmental Health↗

Characterizing the 2016 Perseid Meteor Shower Outburst

The Perseid meteor shower has been observed for millennia and known for its visually spectacular meteors and occasional outbursts. The Perseids were expected to outburst in 2016, primarily due to particles released during the 1862 and 1479 revolutions of Comet Swift-Tuttle. NASA's Meteoroid Environment Office predicted the timing, strength and duration of the outburst for spacecraft risk using the MSFC Meteoroid Stream Model. A double peak was predicted, with an outburst displaying a ZHR of 210 +/- 50 at 00:30 UTC Aug 12, and a traditional peak approximately 12 hours later with rates still heightened from the outburst. Video, visual, and radar observations taken worldwide by various entities were used to characterize the shower and compare to predictions.

Blaauw, R. C.↗

Credibility Assessment of Deterministic Computational Models and Simulations for Space Biomedical Research and Operations

Human missions beyond low earth orbit to destinations, such as to Mars and asteroids will expose astronauts to novel operational conditions that may pose health risks that are currently not well understood and perhaps unanticipated. In addition, there are limited clinical and research data to inform development and implementation of health risk countermeasures for these missions. Consequently, NASA's Digital Astronaut Project (DAP) is working to develop and implement computational models and simulations (M&S) to help predict and assess spaceflight health and performance risks, and enhance countermeasure development. In order to effectively accomplish these goals, the DAP evaluates its models and simulations via a rigorous verification, validation and credibility assessment process to ensure that the computational tools are sufficiently reliable to both inform research intended to mitigate potential risk as well as guide countermeasure development. In doing so, DAP works closely with end-users, such as space life science researchers, to establish appropriate M&S credibility thresholds. We will present and demonstrate the process the DAP uses to vet computational M&S for space biomedical analysis using real M&S examples. We will also provide recommendations on how the larger space biomedical community can employ these concepts to enhance the credibility of their M&S codes.

Mulugeta, Lealem↗

Numerical Prediction of Heat Transfer Coefficients during Xenon Tank Fill in Microgravity

NASA’s Gateway will serve as an orbital outpost to enable sustained human lunar exploration and facilitate access to destinations beyond the Moon. To maintain sustainable deep space missions, on-orbit propellant transfer and refueling must be realized. One of Gateway’s critical components, the Power and Propulsion Element (PPE), will use solar electric propulsion to perform attitude control maneuvers and orbit transfers. Xenon will be used as the propellant for the PPE and stored in a composite overwrapped pressure vessel (COPV). During the propellant refueling process, xenon will compress causing the fluid and tank walls to warm. There is concern that the bond between the tank liner and composite may degrade at elevated temperatures, along with the possibility of the tank exceeding design pressure. While on-orbit testing is being proposed, numerical models are being used to predict the thermal response and reduce risk during a refueling operation in microgravity where natural convection is diminished. Accurate numerical models may be used to inform decisions for follow-on testing, or design and operation of refueling architectures. Challenges of modeling xenon tank fill in microgravity include non-ideal gas behavior, operating near the fluid’s critical point, and lack of experimental flight data. This study presents a computational fluid dynamics (CFD) model with conjugate heat transfer that is used to predict averaged heat transfer coefficients during tank filling. At the anticipated injection flow rates, the CFD results showed that forced convection dominates in microgravity. Initial results from a multi-node Thermal Desktop model that assumed a purely conducting fluid (Nu=1) over-predicted the CFD fluid temperature and pressure, while a similar model allowing for natural convection under-predicted. The heat transfer coefficients predicted by CFD were implemented into the multi-node model, and the COPV thermal response from the two computational approaches were compared with good agreement.

Heat Transfer↗

Statistical Prediction of Solar Particle Event Frequency Based on the Measurements of Recent Solar Cycles for Acute Radiation Risk Analysis

Large solar particle events (SPEs) present significant acute radiation risks to the crew members during extra-vehicular activities (EVAs) or in lightly shielded space vehicles for space missions beyond the protection of the Earth's magnetic field. Acute radiation sickness (ARS) can impair performance and result in failure of the mission. Improved forecasting capability and/or early-warning systems and proper shielding solutions are required to stay within NASA's short-term dose limits. Exactly how to make use of observations of SPEs for predicting occurrence and size is a great challenge, because SPE occurrences themselves are random in nature even though the expected frequency of SPEs is strongly influenced by the time position within the solar activity cycle. Therefore, we developed a probabilistic model approach, where a cumulative expected occurrence curve of SPEs for a typical solar cycle was formed from a non-homogeneous Poisson process model fitted to a database of proton fluence measurements of SPEs that occurred during the past 5 solar cycles (19 - 23) and those of large SPEs identified from impulsive nitrate enhancements in polar ice. From the fitted model, the expected frequency of SPEs was estimated at any given proton fluence threshold (Phi(sub E)) with energy (E) >30 MeV during a defined space mission period. Corresponding Phi(sub E) (E=30, 60, and 100 MeV) fluence distributions were simulated with a random draw from a gamma distribution, and applied for SPE ARS risk analysis for a specific mission period. It has been found that the accurate prediction of deep-seated organ doses was more precisely predicted at high energies, Phi(sub 100), than at lower energies such as Phi(sub 30) or Phi(sub 60), because of the high penetration depth of high energy protons. Estimates of ARS are then described for 90th and 95th percentile events for several mission lengths and for several likely organ dose-rates. The ability to accurately measure high energy protons (50-300 MeV) in real-time is shown to be a crucial issue for crew protection.

Myung-Hee, Y. Kim↗

A Hybrid CFD/Engineering Model Tool for Lunar Lander Surface Erosion Prediction

Plume-Surface Interaction (PSI) between lander engine plumes and landing area regolith poses risks to the landers and space exploration missions through view obscuration and high-energy ejecta impacts from eroded particle clouds and vehicle tilting from plume-induced craters. To address these risks, NASA MSFC Fluid Dynamics Branch (ER42) has developed a cascade of predictive simulation capabilities for PSI, including the recent development of a hybrid CFD/engineering model tool that allows for rapid PSI simulations with a descending/ascending vehicle and an eroding surface. The development of this fully-coupled, moving body/eroding surface simulation capability is detailed along with a demonstration of the tool’s capabilities on the Apollo 12 Lunar Module landing. Predictions of eroded mass flow rates as a function of time are verified against Apollo 12 flight data, from which the developed, viscous erosion model has been calibrated.

Plume Surface Interaction↗