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At least 73 records · Page 4

Uncertainty Reduction With Multi-Model Monte Carlo for Crystal Plasticity Simulations of Additively Manufactured Metals

In this work, multi-model Monte Carlo estimators are developed to reduce uncertainty in quantities of interest (QoIs) extracted from crystal plasticity simulations of additively manufactured (AM) metals. A significant concern in AM parts is uncertainty in mechanical properties caused in part by complex microstructures that arise from the AM process. Quantifying uncertainty in microstructure-sensitive behavior using experiments alone is costly, especially when mechanical allowables must be established. Quantitative relationships among microstructure, micromechanical metrics like slip accumulation, crack initiation, and failure are also difficult to capture with limited experiments. Crystal plasticity material models instead enable computational prediction of micromechanical stress and strain fields given a discretized microstructure. However, high-fidelity finely discretized crystal plasticity simulations are computationally expensive, while lower-fidelity models are less accurate and generally biased, making uncertainty quantification and reduction computationally difficult as well. Multi-model Monte Carlo methods leverage correlations between high- and low-fidelity models to produce unbiased estimators for QoIs with reduced uncertainty relative to standard Monte Carlo. Crystal plasticity QoIs considered in this work include yield strength and the mean and extreme values of micromechanical fields that are relevant to crack initiation. Multi-model Monte Carlo estimators are developed for each individual QoI and several groups of QoIs. The results of this work establish relationships among model correlations, sample allocation, and uncertainty reduction for different combinations of QoIs and demonstrate a trend of less uncertainty reduction as QoIs become more sensitive to local microstructure. Limitations from using pilot samples to estimate model covariances and train low-fidelity models are also addressed. The uncertainty reduction achieved by multi-model Monte Carlo is an important step toward using computational mechanics models to predict microstructure-sensitive crack initiation and failure in AM parts.

uncertainty quantification↗

Uncertainty Quantification of Artemis I Space Launch System Integrated Aerodynamics Databases

Accurate prediction of integrated aerodynamic forces and moments is a necessary part of aerospace vehicle development. This accuracy can be quantified in the form of an uncertainty model, which makes the prediction more useful within an integrated vehicle design effort. Aerodynamic force and moment databases were constructed for the Artemis~I mission of the Space Launch System vehicle. These databases reconcile data from multiple sources to yield unified predictions of how NASA's most advanced launch vehicle interacts with Earth's atmosphere as it ascends into orbit. This paper outlines how the uncertainty quantification was performed for these databases to ensure comprehensive and tractable uncertainty source coverage.

Michael W Lee↗

Towards a Satellite Formaldehyde – in situ Hybrid Estimate for Organic Aerosol Abundance

Organic aerosol (OA) is one of the main components of the global particulate burden and intimately links natural and anthropogenic emissions with air quality and climate. It is challenging to accurately represent OA in global models. Direct quantification of global OA abundance is not possible with current remote sensing technology; however, it may be possible to exploit correlations of OA with remotely observable quantities to infer OA spatiotemporal distributions. In particular, formaldehyde (HCHO) and OA share common sources via both primary emissions and secondary production from oxidation of volatile organic compounds (VOCs). Here, we examine OA–HCHO correlations using data from summertime airborne campaigns investigating biogenic (NASA SEAC4RS and DC3), biomass burning (NASA SEAC4RS), and anthropogenic conditions (NOAA CalNex and NASA KORUS-AQ). In situ OA correlates well with HCHO (r=0.59–0.97), and the slope and intercept of this relationship depend on the chemical regime. For biogenic and anthropogenic regions, the OA–HCHO slopes are higher in low NOx conditions, because HCHO yields are lower and aerosol yields are likely higher. The OA–HCHO slope of wildfires is over 9 times higher than that for biogenic and anthropogenic sources. The OA–HCHO slope is higher for highly polluted anthropogenic sources (e.g., KORUS-AQ) than less polluted (e.g., CalNex) anthropogenic sources. Near-surface OAs over the continental US are estimated by combining the observed in situ relationships with HCHO column retrievals from NASA's Ozone Monitoring Instrument (OMI). HCHO vertical profiles used in OA estimates are from climatology a priori profiles in the OMI HCHO retrieval or output of specific period from a newer version of GEOS-Chem. Our OA estimates compare well with US EPA IMPROVE data obtained over summer months (e.g., slope =0.60–0.62, r=0.56 for August 2013), with correlation performance comparable to intensively validated GEOS-Chem (e.g., slope =0.57, r=0.56) with IMPROVE OA and superior to the satellite-derived total aerosol extinction (r=0.41) with IMPROVE OA. This indicates that OA estimates are not very sensitive to these HCHO vertical profiles and that a priori profiles from OMI HCHO retrieval have a similar performance to that of the newer model version in estimating OA. Improving the detection limit of satellite HCHO and expanding in situ airborne HCHO and OA coverage in future missions will improve the quality and spatiotemporal coverage of our OA estimates, potentially enabling constraints on global OA distribution.

anthropogenic emissions↗

Automated quantification of mitral valve regurgitation based on normalized centerline velocity distribution

Previous echocardiographic techniques for quantifying valvular regurgitation are limited by factors including uncertainties for orifice location and a hemispheric convergence assumption that often results in over- and underestimation of flow rate and regurgitant orifice area. Using computational fluid dynamics simulations, these factors were eliminated, allowing a more accurate assessment of regurgitation. A model was developed to allow automated quantification of regurgitant orifice diameter based on the centerline velocity data available from color M-mode echocardiography. The model, validated using in vitro unsteady flow data, demonstrated improved accuracy for orifice diameter (y=0.95x + 0.38, r=0.96) and volume (y=1.18x - 4.72, r=0.93).

NASA Program Biomedical Research and Countermeasur↗

Updates of the KArLE Experiment: New Libs Calibration Under High Vacuum for the Quantification of Potassium in Basalt for In Situ Geochronology

In planetary exploration, in situ absolute geochronology is one of the main important measurements that needs to be accomplished. Until now, on Mars, the age of the surface is only determined by crater density counting, which gives relative ages. These ages can have a lot of uncertainty as they depend on many parameters. More than that, the curves must be ties to absolute ages. Thus far, only the lost lander Beagle 2 was designed to conduct absolute geochronology measurements, though some recent attempts using MSL Curiosity show that this investigation is feasible and should be strongly encouraged for future flight. Experimental: The Potassium (K)-Argon Laser Experiment (KArLE) is being developed at MSFC through the NASA Planetary Instrument Definition and Development Program (PIDDP). The goal of this experiment is to provide in situ geochronology based on the K-Ar method. A laser ablates a rock under high vacuum, creating a plasma which is sensed by an optical spectrometer to do Laser Induced Breakdown Spectroscopy (LIBS). The ablated material frees gases, including radiogenic 40Ar,which is measured by a mass spectrometer (MS). As the potassium is a content and the 40Ar is a quantity, the ablated mass needed in order to relate them. The mass is given by the product of the ablated volume by the density of this material. So we determine the mineralogy of the ablated material with the LIBS spectra and images and calculate its density. The volume of the pit is measured by using microscopy. LIBS measurement of K under high vacuum: Three independant projects [1, 2, 3] including KArLE, are developing geochronological instruments based on this LA-LIBS-MS method. Despite several differences in their setup, all of them have validated the methods with analyses and ages. However, they all described difficulties with the LIBS measurements of K [3,4]. At ambient pressure, the quantification of K by LIBS on geological materials can be accurate [5]. However the protocol of the LA-LIBS-MS experiment required hundreds of shots under high vacuum in order to free enough 40Ar* to be measured by the QMS. This long duration of ablation may induces significant changes in the LIBS spectra. The pressure may increases by orders of magnitudewithin the chamber and the laser pit geometry can change the effectiveness of ablation and intensity of plasma light received. These effects introduce variation between the first and last spectra and so the quantification of K is more complex. The ablation of one crater can give, depending on the protocol of acquisition, from tens to hundreds of spectra. Protocol and results: We are in the process of further characterizing the variation introduced into LIBS spectra by the use of hundreds of laser shots, and definining a protocol that can be used to ensure accuracy and reporoducibility in the results.We are using natural rock powder standards fused in a furnace, as well as mars analog samples with known K content. We will show the result of the calibration and some new statistical approaches in order to apprehend the effects of the long time ablation on rocks under high vacuum.

Devismes, D.↗

Comparison of ISS Power System Telemetry with Analytically Derived Data for Shadowed Cases

Accurate International Space Station (ISS) power prediction requires the quantification of solar array shadowing. Prior papers have discussed the NASA Glenn Research Center (GRC) ISS power system tool SPACE (System Power Analysis for Capability Evaluation) and its integrated shadowing algorithms. On-orbit telemetry has become available that permits the correlation of theoretical shadowing predictions with actual data. This paper documents the comparison of a shadowing metric (total solar array current) as derived from SPACE predictions and on-orbit flight telemetry data for representative significant shadowing cases. Images from flight video recordings and the SPACE computer program graphical output are used to illustrate the comparison. The accuracy of the SPACE shadowing capability is demonstrated for the cases examined.

Fincannon, H. James↗

Airframe Icing Research Gaps: NASA Perspective

qCurrent Airframe Icing Technology Gaps: Development of a full 3D ice accretion simulation model. Development of an improved simulation model for SLD conditions. CFD modeling of stall behavior for ice-contaminated wings/tails. Computational methods for simulation of stability and control parameters. Analysis of thermal ice protection system performance. Quantification of 3D ice shape geometric characteristics Development of accurate ground-based simulation of SLD conditions. Development of scaling methods for SLD conditions. Development of advanced diagnostic techniques for assessment of tunnel cloud conditions. Identification of critical ice shapes for aerodynamic performance degradation. Aerodynamic scaling issues associated with testing scale model ice shape geometries. Development of altitude scaling methods for thermal ice protections systems. Development of accurate parameter identification methods. Measurement of stability and control parameters for an ice-contaminated swept wing aircraft. Creation of control law modifications to prevent loss of control during icing encounters. 3D ice shape geometries. Collection efficiency data for ice shape geometries. SLD ice shape data, in-flight and ground-based, for simulation verification. Aerodynamic performance data for 3D geometries and various icing conditions. Stability and control parameter data for iced aircraft configurations. Thermal ice protection system data for simulation validation.

Potapczuk, Mark↗

The ESA Hera Mission: Detailed Investigation of the NASA Dart Impact Outcome and Characterization of the Binary Asteroid Didymos

The Hera mission is in development in the Space Safety Program of the European Space Agency (ESA) in collaboration with JAXA for launch in October 2024. It will rendezvous with the binary asteroid (65803) Didymos in early 2027 and over the following 6 months will investigate the properties of Didymos and its small moon Dirmorphos, including the effects of the successful impact of the NASA DART probe. DART was launched on 24 November 2021 at 06:21 UTC and successfully impacted at about 6.1 km/s on the 160 meter-size Dimorphos on 26 September 2022 at 23:14 UTC. Two weeks before impact, it deployed the Light Italian Cubesat for Imaging of Asteroids (LICIACube) that provided images during the few minutes following the impact. A campaign of observations from Earth and space provided distant images of the event, which were used to determine a reduction of 33 min in the orbital period of Dimorphos around Didymos. The Hera mission will investigate the outcome of the DART impact in detail. In particular, it will determine the effects of the impact on Dimorphos’ surface, e.g., whether it produced a crater, and if so its properties, and/or whether it led to global reshaping of Dimorphos. It will accurately measure the mass of Dimorphos, which will allow quantification of the momentum enhancement factor, which is a crucial parameter to evaluate the efficiency of the kinetic impactor technique. Hera will also determine in detail the physical, thermal and compositional properties of the asteroid, including first time measurements of the internal properties, which have a critical influence on the impact outcome. With Hera and DART together, we will have a fully documented deflection test and impact experiment that will allow us to verify our numerical impact models, to be able to extrapolate this deflection test to other asteroids and to improve our understanding of the complex geological properties and response of small asteroids. Hera consists of a mother spacecraft and two cubesats. It will perform the first rendezvous with a binary asteroid, arriving at Didymos about 4 years after DART. Hera will not only contribute significantly to the planetary defense effort by documenting entirely the outcome of the DART impact, it will also greatly advance our understanding of processes in the very low gravity regime of a small asteroidv (Dimorphos) as well as our knowledge of binary asteroids and asteroid geophysics. The mission development is progressing nominally, with the Critical Design Review having been passed in Nov. 2022. The various working groups of the Hera Science Team are working intensively to support this development and be best prepared for the surprises that Hera will offer during its visit to Didymos in 2027.

Asteroid deflection↗

Bayesian Symbolic Regression: Addressing Challenges in Estimating Fractional Bayes Factors and Application to Fatigue Crack Growth Modeling

This research pioneers advancements in computational mechanics by integrating Bayesian-based uncertainty quantification into symbolic regression, specifically focusing on the critical task of accurately estimating the fractional Bayes factor for selecting arbitrary equations. In our exploration, we rigorously study two prominent methods—sequential Monte Carlo and the Laplace approximation—employed for computing the fractional Bayes factor. Our findings underscore the limitations of the Laplace approximation, revealing its diminished accuracy in nonlinear and multimodal scenarios. Specifically, the Laplace approximation is shown to underpredict fractional Bayes factor on a wide set of equations associated with a symbolic regression benchmark. This comparative analysis sheds light on the nuanced performance of these techniques, guiding researchers toward more informed choices in uncertainty quantification within symbolic regression. Furthermore, we showcase the practical utility of these enhanced symbolic regression tools through their application to a real-world problem in fatigue crack growth modeling, emphasizing their efficacy in capturing the complexities of mechanical systems.

Geoffrey Bomarito↗

Vagal tone as an index of mental state

The utility of monitoring oscillations in the heart rate pattern as a window to the brain is discussed as an index of general central nervous system status. Quantification of the amplitude of respiratory sinus arrhythmia provides an accurate index of cardiac vagal tone. A number of studies have demonstrated the validity of this measure; the relationship between flight performance and vagal tone has also been studied. In general, the vagal tone index appears to monitor global states of the central nervous system and may be useful in screening the general state of pilots.

Porges, Stephen W.↗

Simulation of Vacuum Chamber Pressure Distribution with Surrogate Modeling and Uncertainty Quantification

A major challenge in understanding differences in electric propulsion performance in ground tests and in space operations concerns the pressure distribution within the test vacuum chamber. The chamber backpressure is much higher than experienced in space, modifying thruster performance and plume dynamics. Numerical simulation is a key element to determining the background conditions in non-ideal vacuum chamber environments. An important parameter for the accurate simulation of chamber backpressure is the probability that an atom will stick to a cryogenic panel used to pump away the plume gases. This quantity can be used to model vacuum pumps in particle-based kinetic numerical methods. In this work, a three-dimensional direct simulation Monte Carlo code is used to model neutral xenon atoms flowing from the anode of the H9 Hall Effect Thruster within the University of Michigan’s Large Vacuum Test Facility. Simulated pressures are compared with ion gauge pressure measurements to infer the effective sticking coefficient of the chamber’s vacuum pumps. A pressure predicting surrogate model is developed for inference of pump sticking coefficients and for uncertainty quantification. This information enables accurate and useful kinetic simulations of electric propulsion thruster plasma plumes in vacuum chambers.

DSMC↗

Estimating Mangrove Aboveground Biomass from Airborne LiDAR Data: a Case Study from the Zambezi River Delta

Mangroves are ecologically and economically important forested wetlands with the highest carbon (C) density of all terrestrial ecosystems. Because of their exceptionally large C stocks and importance as a coastal buffer, their protection and restoration has been proposed as an effective mitigation strategy for climate change. The inclusion of mangroves in mitigation strategies requires the quantification of C stocks (both above and belowground) and changes to accurately calculate emissions and sequestration. A growing number of countries are becoming interested in using mitigation initiatives, such as REDD+ (reducing emissions from deforestation and forest degradation), in these unique coastal forests. However, it is not yet clear how methods to measure C traditionally used for other ecosystems can be modified to estimate biomass in mangroves with the precision and accuracy needed for these initiatives. Airborne Lidar (ALS) data has often been proposed as the most accurate way for larger scale assessments but the application of ALS for coastal wetlands is scarce, primarily due to a lack of contemporaneous ALS and field measurements. Here, we evaluated the variability in field and Lidar-based estimates of aboveground biomass (AGB) through the combination of different local and regional allometric models and standardized height metrics that are comparable across spatial resolutions and sensor types, the end result being a simplified approach for accurately estimating mangrove AGB at large scales and determining the uncertainty by combining multiple allometric models.We then quantified wall-to-wall AGB stocks of a tall mangrove forest in the Zambezi Delta, Mozambique. Our results indicate that the Lidar H100 height metric correlates well with AGB estimates, with R(exp 2) between 0.80 and 0.88 and RMSE of 33% or less. When comparing Lidar H100 AGB derived from three allometric models, mean AGB values range from 192 Mg ha(exp −1) up to 252 Mg ha(exp −1).We suggest the best model to predict AGB was based on the East Africa specific allometry and a power-based regression that used Lidar H100 as the height input with an R(exp 2) of 0.85 and an RMSE of 122 Mg ha(exp −1) or 33%. The total AGB of the Lidar inventoried mangrove area (6654 ha) was 1 350 902 Mg with a mean AGB of 203 Mg ha(exp −1) +/-166 Mg ha(exp −1). Because the allometry suggested here was developed using standardized height metrics, it is recommended that the models can generate AGB estimates using other remote sensing instruments that are more readily accessible over other mangrove ecosystems on a large scale, and as part of future carbon monitoring efforts in mangroves.

Fatoyinbo, Temilola↗

Trajectory Engineering with Modular Patched Conics for Entry Systems and TPS (TEMPEST)

Brief Presenter Biography (35 word limit): Bohdan Wesely is an Aerospace Engineer in the Entry Systems and Technology Division at Ames. He has worked on a variety of projects for NASA including integrated TPS (thermal protection system) flight hardware deliveries and testing services for commercial partners. Introduction: TEMPEST is a new trajectory analysis framework that is designed to fill the gap between dedicated flight mechanics tools and aerothermal and TPS sizing tools. The project started as an SJSU master’s thesis and has since evolved into a general conceptual design tool capable of studying a wide variety of entry problems. Development is ongoing in the Entry Systems and Technology Division at NASA ARC. Why TEMPEST: Space missions involving entry into a planetary atmosphere involve a series of unique requirements across multiple disciplines. Whether it is traditional entry descent and landing (EDL), or aerocapture, the vehicle must navigate to its target landing location or orbit state, and the TPS must protect the payload during entry. The design process typically involves iterative handoffs between various flight mechanics, flow solver, and material response level tools. During the early conceptual phase, a wide variety of feasible trajectories are simulated in a Monte Carlo scenario which broadly satisfy the mission or landing requirements. Next, computational fluid dynamics (CFD), direct simulation Monte Carlo (DSMC), and other flow solver analyses are performed at various key trajectory points to generate an aero-database, heating and TPS design requirements also emerge at this stage. At this point, with updated aerodynamics from the various flow solvers, trajectories can be re-run, this in turn can change the required freestream conditions for the CFD tools, and as a project progresses, these analyses converge, and uncertainty is reduced. However, there is always a “hand-off” occurring between two inherently coupled phenomena. Analysis Description: One of the goals with TEMPEST is to use a variety of first principles estimation methods coupled with an atmosphere model to predict vehicle aerothermodynamics across the entire flight regime while propagating a 3 or 6 degree of freedom (DoF) trajectory. Aerodynamics methods include modified Newtonian, Maxwell and Cercignani- Lampis-Lord (CLL) for continuum, transitional, and free molecular flow regimes. Aerothermodynamics include boundary layer and reference enthalpy methods, and Mutation++ for non-equilibrium chemistry modeling. TEMPEST is also capable of stitching multiple trajectory segments together to study mission scenarios like multi-pass aerocapture and aero-gravity assists. Most of the program is implemented in MATLAB using modern system objects, it relies on several C++ shared libraries for supporting tools like Gmsh, the Global Reference Atmospheric Model (GRAM), and Mutation++. The various first principles aerothermal estimation methods are discretized across either a structured axisymmetric panel mesh or an unstructured tri-mesh generated from an open-source tool such as Gmsh, this allows solutions on the same mesh to be compared across tools such as CB-Aero. CFD Coupling. A physics-aware, gaussian process CFD anchoring scheme is proposed to adjust the various first principles methods as a CFD database is populated. One goal for this anchoring module is to inform the project where CFD should be run. Full knowledge of the entire trajectory, atmosphere, and aerothermodynamics allows for easier identification of high sensitivity areas and uncertainty quantification. While the first principles effects are well known and proven accurate in existing tools such as CB- Aero and Cart3D, a physics aware CFD anchoring scheme increases tool credibility across a project lifecycle. Material Response Modeling. Correct TPS sizing is critical for optimizing mass for science payloads and ensuring mission success. The process typically involves a thermal analysis along the trajectory with surface heating environments as a boundary condition. Several design constraints are maximum bondline temperature and maximum recession with various margining techniques. The material response tool FIAT, developed out of NASA Ames, is currently being integrated into the TEMPEST environment. TPS recession, shape change, mass loss, and mass property alteration are all factors that can perturb an entry trajectory. For missions like Mars 2020, recession was minimal and was safely handled separately as a post process. For missions such as Jupiter Galileo with a high TPS mass fraction or asteroid entries, recession plays a major role. The proposed fully coupled scheme is to use an epoch-based approach where the trajectory integration is halted after a recession threshold, the energy balance and FIAT are solved at each panel, the mesh, aerodynamics, and mass properties are updated, and the trajectory continues. Several computational tradeoffs have been made during the development of TEMPEST to limit the cost of a single trajectory and preserve its utility as a conceptual, rapid iteration tool. Conclusion: Development of TEMPEST is ongoing and the project is still in its infancy. This talk aims to showcase its unique capabilities to support future NASA entry systems missions.

Bohdan O Wesely↗

Uncertainty Quantification of Expected Time-of-Arrival in UAV Flight Trajectory

One of the foremost requirements for accurate in-flight safety monitoring of autonomous unmanned aerial vehicles (UAVs) is tracking of their flight trajectory. Existing UAVs leverage autonomous flight functionalities based on trajectory generation algorithms developed in robotic applications such as polynomial or spline curves in order to facilitate kinematic smoothness, minimum vibrations and fuel efficiency. However in practice, the actual path may be subjected to unexpected local weather conditions, unexpected obstacles along the path or abrupt traffic changes in the low-altitude airspace resulting in large errors of the predicted time-of-arrival at way-points. In this study, an approach to quantify and propagate uncertainty in 4D trajectories is proposed. The paper presents a simple error interval propagation method based on the expected cruise speed of the UAV and its associated uncertainty. The uncertainty is then propagated in time to estimate reasonable confidence intervals on the times-of-arrival of the vehicle at each way-point as well as along the entire flight-path. The uncertainty propagation is demonstrated on a state-of-the-art trajectory generation algorithm based on non-uniform rational B-spline (NURBS) curves. Further, the effect of a stationary wind field is incorporated in the uncertainty propagation approach. The proposed method is implemented on synthetic and real data obtained from flight experiments with a small UAV.

Uncertainty Quantification↗

Development of limb volume measuring system

The mechanisms underlying the reductions in orthostatic tolerance associated with weightlessness are not well established. Contradictory results from measurements of leg volume changes suggest that altered venomotor tone and reduced blood flow may not be the only contributors to orthostatic intolerance. It is felt that a more accurate limb volume system which is insensitive to environmental factors will aid in better quantification of the hemodynamics of the leg. Of the varous limb volume techniques presently available, the ultrasonic limb volume system has proven to be the best choice. The system as described herein is free from environmental effects, safe, simple to operate and causes negligible radio frequency interference problems. The segmental ultrasonic ultrasonic plethysmograph is expected to provide a better measurement of limb volume change since it is based on cross-sectional area measurements.

Bhagat, P. K.↗

Spares quantification for the Space Shuttle Orbiters

A study to determine the numerous factors that must be considered and utilized to accurately quantify the number of spares necessary to support the Orbiter processing is presented. Previously the method used to quantify the requirements for spares was based on a probability of sufficiency (POS) equation. It was found that there are several categories of failures, not only the operating hour dependency type used in POS. Therefore, it was determined that various methods of quantifying spares should be utilized for the different categories of failures. Trending analysis of the failure history was deemed necessary. Also, the working environment was determined to be an important factor in the failure data.

Groh-Hammond, Marcia M.↗

Combined Error and Uncertainty Estimates for CFD Problems

Given input sources of uncertainty, non-intrusive uncertainty propagation methods quantify the uncertainty in output quantities of interest (QoI) by performing a nite number of CFD (Computational Fluid Dynamics) instance realizations needed in the calculation of output statistics. It is well known that this introduces multiple sources of error. CFD codes often utilize finite-dimensional approximation (grids, basis functions, etc.) thus incurring CFD numerical errors often approximately reinterpreted as a statistical bias. Uncertainty propagation methods calculate uncertainty statistics for output quantities of interest using a numerical method (e.g. deterministic quadrature, sampling, etc.) thus incurring UQ (Uncertainty Quantification) numerical errors. Importance of quantifying these errors in large scale scientific computing: How accurate is an output statistic?; How should additional computational resources be invested to further reduce the error in a statistic?

Posteriori↗

Use of microgravity sensors for quantification of space shuttle orbiter vernier reaction control system induced environments

In the modeling of spacecraft dynamics it is important to accurately characterize the environment in which the vehicle operates, including the environments induced by the vehicle itself. On the Space Shuttle these induced environmental factors include reaction control system plume. Knowledge of these environments is necessary for performance of control systems and loads analyses, estimation of disturbances due to thruster firings, and accurate state vector propagation. During the STS-71 mission, while the Orbiter was performing attitude control for the mated Orbiter/Mir stack, it was noted that the autopilot was limit cycling at a rate higher than expected from pre-flight simulations. Investigations during the mission resulted in the conjecture that an unmodelled plume impingement force was acting upon the orbiter elevons. The in-flight investigations were not successful in determining the actual magnitude of the impingement, resulting in several sequential post-flight investigations. Efforts performed to better quantify the vernier reaction control system induced plume impingement environment of the Space Shuttle orbiter are described in this paper, and background detailing circumstances which required the more detailed knowledge of the RCS self impingement forces, as well as a description of the resulting investigations and their results is presented. The investigations described in this paper applied microgravity acceleration data from two shuttle borne microgravity experiments, SAMS and OARE, to the solution of this particular problem. This solution, now used by shuttle analysts and mission planners, results in more accurate propellant consumption and attitude limit cycle estimates in preflight analyses, which are critical for pending International Space Station missions.

Friend, Robert B.↗