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At least 469 records · Page 26

Aircraft System Noise Prediction Uncertainty Quantification for a Hybrid Wing Body Subsonic Transport Concept

Aircraft system level noise prediction for advanced, unconventional concepts has undergone significant improvement over the past two decades. The prediction modeling uncertainty must be quantified so that potential benefits of unconventional configurations, which are outside of the range of empirical models, can be reliably assessed. This paper builds on previous work in an effort to improve estimates of element prediction uncertainties where the prediction methodology has been improved, or new experimental validation data are available, to provide an estimate of the system level uncertainty in the prediction process. In general, the uncertainty of the prediction will be strongly dependent on the aircraft configuration as well as which technologies are integrated. While the quantitative uncertainty values contained here are specific to the hybrid wing body design presented, the underlying process is the same regardless of configuration. A refined process for determining the uncertainty for each element of the noise prediction is detailed in this paper. The system level uncertainty in the prediction of the aircraft noise is determined at the three certification points, using a Monte Carlo method. Comparisons with previous work show a reduction of 1 EPNdB in the 95%coverage interval of the cumulative noise level. The largest impediment for continued reduction in uncertainty for the hybrid wing body concept is the need for improved modeling and validation experiments for fan noise, propulsion airframe aeroacoustic effects, and the Krueger flap, which comprise the bulk of the uncertainty in the cumulative certification noise level.

June, Jason C.↗

Simulation of Liquid Rocket Engine Failure Propagation Using Self-Evolving Scenarios

Traditional probabilistic risk assessment approaches often require failure scenarios to be explicitly defined through event sequences that are then quantified as part of the integrated analysis. This approach becomes difficult when failure propagation paths change as a function of the system operation. Additionally, if the propagation paths represent interactions among even a modest number of components, the scenario count becomes combinatorially intractable. This paper presents an alternate approach for quantifying the probability of failure propagation in such a case. Rather than explicitly defining scenario sequences, simple physical models are created for each of the components. In this way, only the physical states and rules of component interactions must be defined, rather than event sequences for each individual scenario. Initiating failures are introduced into the system, either randomly or as defined by relative likelihood, and the failures cascade through the system via the interaction rules. This process is repeated using Monte Carlo methods and, as a result, the most probable scenarios “self-evolve” in terms of both sequence path and frequency. This approach was applied to failures occurring in the engine compartment of a space launch vehicle with four liquid rocket engines and four high-pressure helium tanks. Each engine was modeled with key components, such as turbomachinery, combustion chamber, propellant lines, and additional support systems. Three test cases were conducted with different high-energy engine failures. End results of interest included an additional engine-out failure and tank burst, which represent the loss-of-mission (LOM) and loss-of-crew (LOC) failure environments, respectively. Observations show that almost every scenario outcome is unique and that many scenarios involve complex chain reactions that are difficult to predict. This validates the usefulness of the modeling approach in assessing the overall risks to the crew during a launch vehicle abort.

Rocket Engine↗

Multilevel Monte Carlo Estimation of Unbiased Expectation via Sample Reuse and the Low Variance Estimation of Asymptotic Rates

A new variant of the multilevel Monte Carlo estimator [5, 3, 9, 12] is presented for the estimation of expectation statistics that utilizes sample reuse in specified levels, explicitly removes approximation error bias associated with numerically computed output quantities of interest that have an asymptotic limit behavior, and permits a low variance estimate of the asymptotic rate of convergence to that limit. In addition, it is shown that this new multilevel Monte Carlo variant can yield a computational cost savings. A review of Monte Carlo and multilevel Monte Carlo estimators is presented that includes analysis of expected value, expected mean squared error, and the calculation of optimized multilevel sample size parameters. The multilevel Monte Carlo estimator produces estimates of expectation for numerically approximated output quantities of interest that are biased by approximation error. When the quantity of interest can be modeled as the asymptotic limit of numerically approximated output quantities of interest, it is theoretically possible to remove this approximation error bias in the multilevel Monte Carlo estimator. In actual implementations, however, this procedure is unreliable due to statistical variability and inaccuracy in estimating the needed asymptotic limit. Analysis and numerical experiment show that the proposed variant of the multilevel Monte Carlo method greatly reduces (in some cases eliminates) the statistical variability in this limit estimation.

Barth, Timothy↗

Development of a Model for the Small-Particle Orbital Debris Population Based on the STS Impact Record

In preparation for the release of the Orbital Debris Engineering Model (ORDEM) version 3.1, the NASA Orbital Debris Program Office (ODPO) revisited how orbiting debris populations of characteristic sizes smaller than 1 cm were modeled. The primary contributor to the population of sub-centimeter debris particles is the surface deterioration or erosion of spacecraft materials exposed to the outer-space environment. Because small particulates are not directly trackable by remote sensing, the primary means of detection is via historical counts of small impact features on flown radiator and window surfaces of the U.S. Space Transportation System (STS, also known as the Space Shuttle) from 1995-2011. Historic NASA studies of high-velocity impact tests have related impact-feature size to particle mass and velocity for certain STS surfaces, so that a corresponding particle size may be inferred from each small-impact feature observed. Micro-debris populations are then estimated by modeling the path and orientation of an STS mission through a simulated debris environment, and the densities of this simulated environment are rescaled to approximate the number of observed STS impact features. Monte-Carlo methods are further employed to gauge the estimation uncertainty of the rescaled environment. A description of the chosen methodologies for estimating and adjusting the micro-debris population model, and the results, are presented.

Seago, J..↗

A Second Look at 12 Candidate Dual AGNs Using BAYMAX

We present an analysis of 12 optically selected dual active galactic nucleus (AGN) candidates at z < 0.34. Each candidate was originally identified via double-peaked [O III] λ5007 emission lines and received follow-up Chandra and Hubble Space Telescope (HST) observations. Because the X-ray data are low-count (<100 counts) with small separations (<1''), a robust analysis is necessary for classifying each source. Pairing long-slit [O III] observations with existing Chandra observations, we re-analyze the X-ray observations with Bayesian AnalYsis of AGNs in X-rays to determine whether the X-ray emission from each system is more likely a single or dual point source. We find that 4 of the 12 sources are likely dual X-ray point-source systems. We examine each point source's spectra via a Monte Carlo method that probabilistically identifies the likely origin of each photon. When doing so, we find that (i) the secondary X-ray point sources in two of the systems have L(X)< 10(exp 40) erg/s, such that we cannot rule out a non-AGN origin, (ii) one source has a secondary with L(X)> 10(exp 40) erg/s but a spectrum that is too soft to definitively preclude being X-ray emitting diffuse gas that was photoionized by the primary AGN, and (iii) one system (SDSS J1126+2944) is a dual AGN. Additionally, using complementary HST observations, we analyze a subsample of systems that are visually identified as merging. Our results suggest that dual AGNs may preferentially reside in mergers with small separations, consistent with both simulations and observations.

Adi Foord↗

FIGS: spectral fitting constraints on the star formation history of massive galaxies since the cosmic noon

We constrain the stellar population properties of a sample of 52 massive galaxies – with stellar mass log (M(s)/M(⊙)) ≳ 10.5 – over the redshift range 0.5 < z < 2 by use of observer-frame optical and near-infrared slitless spectra from Hubble Space Telescope’s ACS and WFC3 grisms. The deep exposures (∼100 ks) allow us to target individual spectra of massive galaxies to F160W = 22.5 AB. Our spectral fitting approach uses a set of six base models adapted to the redshift and spectral resolution of each observation, and fits the weights of the base models, including potential dust attenuation, via a Markov Chain Monte Carlo method. Our sample comprises a mixed distribution of quiescent (19) and star-forming galaxies (33). We quantify the width of the age distribution (Δt) that is found to dominate the variance of the retrieved parameters according to principal component analysis. The population parameters follow the expected trend towards older ages with increasing mass, and Δt appears to weakly anticorrelate with stellar mass, suggesting a more efficient star formation at the massive end. As expected, the redshift dependence of the relative stellar age (measured in units of the age of the Universe at the source) in the quiescent sample rejects the hypothesis of a single burst (aka monolithic collapse). Radial colour gradients within each galaxy are also explored, finding a wider scatter in the star-forming subsample, but no conclusive trend with respect to the population parameters.

Ignacio Ferreras↗

Numerical Results for Polarized Light Scattering in a Spherical Atmosphere

We report numerical results for polarized light reflection from the top of a Rayleigh scattering spherical atmosphere with height-dependent single scattering albedo over a dark surface. Michael Mishchenko considered this scenario back in the 1990’s, for a plane-parallel atmosphere of unit optical thickness (OT), for which radiance errors arising from neglecting polarization reaches their highest values. To further extend Mishchenko’s results, we consider a value of OT = 0.25, for which the effect of atmospheric curvature is pronounced. New results are generated using three state-of-the art radiative transfer (RT) codes. These are: the MYSTIC and MCSSA models, which simulate light scattering in a true- spherical atmosphere using Monte Carlo methods; and the discrete ordinate code VLIDORT, operating with a new multiple-scatter spherical correction designed to deliver reasonable approximations to spherical-medium scattering. In this work, we report results for both single and multiple scattering; this will help to support the validation of existing and future polarized spherical RT codes, especially those using approximative methods to deal with sphericity.

S Korkin↗

Advanced Turboprop Transport Aircraft Modeling for the Electrified Powertrain Flight Demonstration Project

The objective of this study is to establish models for state of the art, representative regional non-electrified turboprop configurations in the 19-50 passenger capability range and assess performance impacts from advanced aircraft technologies. Two of these models will serve as reference baseline configurations for comparison to electrified aircraft propulsion (EAP) demonstrator concepts for the Electrified Powertrain Flight Demonstration (EPFD) project. The other two non-electrified configurations will primarily assess the impacts of advanced technologies on fuel consumption and CO₂ emissions. This paper details an aircraft synthesis and performance analysis approach using the General Aviation Synthesis Program (GASP) which is used to establish baseline performance capabilities, calibrate airplane and engine models using published manufacturer data and conduct technology sensitivity studies. Advanced technologies are selected from the categories of propulsion, aerodynamics, and flight systems. Performance assessments use Monte Carlo method coupled with GASP simulations to obtain performance distributions of the expected fuel burn, propulsive, aerodynamic, and weight benefits on the representative turboprop configurations from the application of advanced technologies. The final paper will present the impact of the advanced technologies on fuel burn and CO₂ emissions.

aircraft performance↗

A Monte Carlo Based Ray Tracing Tool for Evaluating Wolter-Type Prescriptions

Evaluating Wolter-like X-ray mirror prescriptions via ray tracing is useful for selecting and optimizing the right mirror prescriptions for a specified application. Moreover, incorporating real metrology data into a ray trace and simulating point spread functions (PSF) allows for performance predictions representative of real manufacturing errors and tolerances. In fulfillment of an internship project, an X-ray ray trace routine using a Monte-Carlo method has been developed to examine different Wolter-like prescriptions and characterize their theoretical performances over a specified field of view. This routine includes the ability to use real metrology data to evaluate the impact of figure error on imaging performance. As a test case, the Marshall Grazing Incidence X-ray Spectrometer (MaGIXS) Wolter-I mirror prescription and an equivalent Wolter-Schwarzschild prescription were traced and imaging performance of a specified field of view were mapped. Here we present the approach used in this routine, showcase example results, and discuss future goals for expanding the routine to address azimuthally varying figure errors and surface roughness.

X-ray optics↗

Guidance and Control for Laser-Based Non-Cooperative Target Detumbling

Large pieces of orbital debris form a significant risk of fragmentation in case of collision. Such fragmentation would greatly increase the number of trackable and untrackable debris on orbit. This makes them attractive targets for future rendezvous and disposal missions. However, these non-cooperative targets tend to be tumbling and rendezvous with them is a dangerous prospect. To avoid this danger, contactless detumbling through laser ablation has been proposed prior to rendezvous. Existing proposals for contactless laser-based detumbling have yet to include an in-depth study of the problem's guidance, navigation, and control requirements. In this work we develop an attitude and relative motion control scheme for a chaser satellite detumbling a non-cooperative target via laser. We show that detumbling can be achieved with reasonable time and dV budgets. With Monte Carlo methods we explore the impact of laser force on the detumbling operation and reveal some non-intuitive relationships.

Guidance↗

Guidance and Control for Laser-Based Non-Cooperative Target Detumbling

Large pieces of orbital debris form a significant risk of fragmentation in case of collision. Such fragmentation would greatly increase the number of trackable and untrackable debris on orbit. This makes them attractive targets for future rendezvous and disposal missions. However, these non-cooperative targets tend to be tumbling and rendezvous with them is a dangerous prospect. To avoid this danger, contactless detumbling through laser ablation has been proposed prior to rendezvous. Existing proposals for contactless laser-based detumbling have yet to include an in-depth study of the problem's guidance, navigation, and control requirements. In this work we develop an attitude and relative motion control scheme for a chaser satellite detumbling a non-cooperative target via laser. We show that detumbling can be achieved with reasonable time and dV budgets. With Monte Carlo methods we explore the impact of laser force on the detumbling operation and reveal some non-intuitive relationships.

Guidance↗

A Queuing Theory Approach to Pilot-Controller Coordination for m:N Operations

In recent years, attention and interest by industry and researchers has grown in a control paradigm for remotely piloted aircraft termed “m:N operations.” In an m:N operation, a team of m remote pilots in command (RIPCs) collaboratively manage the flights of N aircraft. A consequence of an m:N concept of operations is that the RPICs will have to switch attention from one aircraft to another and from one task to another. Previous research in m:N operations has focused on the workload experienced by an RPIC and their level of situation awareness on their flights. Researchers have found that RPIC workload and situation awareness are generally sensitive to increasing N, although NASA’s Multi-Vehicle (m:N) Working Group has suggested that the driver of workload/situation awareness is the number of exceptions requiring human intervention as opposed to the value of N itself. In any case, a natural antecedent of workload is task load. In this paper, queueing theory is applied to a 1:N Urban Air Mobility (UAM) air taxi operation in order to estimate pilot task load for managing radio communications with air traffic controllers (ATCs) under increasing N. An M/M/1 queueing system is used to model the RIPC’s servicing of calls and clearance requests (e.g., departure, arrival, or airspace transition) to ATC for the N aircraft. Important parameters for the queueing model are the task arrival rate and the average service time for task completion. Radio communication times from past human-in-the-loop simulation studies are used to measure service times for a 1:4 and 1:12 UAM operation and to interpolate service times for 4 < N < 12. A Monte Carlo method is then employed, using the measured and interpolated service times, to estimate arrival rate and related queueing statistics. The paper concludes by considering the estimated queuing statistics, particularly the RPIC’s utilization (i.e., proportion of time actively servicing tasks), the length of the task queue over time, and the implications for task-balanced system design.

task load↗

Sensitivity of Simulated Radiative Emission from Nitrogen Flows to Chemical Parameters

Numerical models of hypersonic flows rely on chemistry data inferred from experiments and quantum calculations. Experiments from NASA's Electric Arc Shock Tube (EAST) measure the spectral emission of strong shocks in pure nitrogen flows. These spectral profiles are only approximately captured by numerical simulations. To address these discrepancies, one wishes to calibrate some of the chemical parameters to better match experiment. Because there are hundreds of parameters in the numerical model, a sensitivity analysis was carried out on the entire chemistry database to determine which parameters are most important to analyze in the future. In order to perform this work it was necessary to generate a consistent chemical database that interfaced with both the CFD and line-by-line radiation solver. Using Monte Carlo methods, the total Sobol index was calculated for important parameters. Twenty parameters were identified as important across the nitrogen system. However, it was noted that in some spectral regions, the parametric uncertainty was unable to bound EAST measurements. Further improvements could be made by increasing the parameter uncertainties or addressing other sources of modeling error.

Kaelan B Hansson↗

Sensitivity of Simulated Radiative Emission from Nitrogen Flows to Chemical Parameters

Numerical models of hypersonic flows rely on chemistry data inferred from experiments and quantum calculations. Experiments from NASA's Electric Arc Shock Tube (EAST) measure the spectral emission of strong shocks in pure nitrogen flows. These spectral profiles are only approximately captured by numerical simulations. To address these discrepancies, one wishes to calibrate some of the chemical parameters to better match experiment. Because there are hundreds of parameters in the numerical model, a sensitivity analysis was carried out on the entire chemistry database to determine which parameters are most important to analyze in the future. In order to perform this work it was necessary to generate a consistent chemical database that interfaced with both the CFD and line-by-line radiation solver. Using Monte Carlo methods, the total Sobol index was calculated for important parameters. Twenty parameters were identified as important across the nitrogen system. However, it was noted that in some spectral regions, the parametric uncertainty was unable to bound EAST measurements. Further improvements could be made by increasing the parameter uncertainties or addressing other sources of modeling error.

Kaelan Hansson↗

Numerical methods for solving the Boltzmann equation (a review)

The methods are reviewed which are utilized in principal attempts to obtain the numerical solution or modeling of the Boltzmann equation over a broad range of Knudsen numbers. The primary methods considered are the Monte Carlo and the discrete velocities methods. The conculsions drawn from the analysis include the following: (1) The Monte Carlo methods are not well suited in the area of small Knudsen numbers. (2) Among the Monte Carlo methods, the Bird method appears to be the most attractive, since it is more directly related to the Boltzmann equation. (3) The deterministic methods, which include the discrete ordinate technique, offer great possibilities but require exceedingly large computer times. (4) The use of approximating equations in combination with the discrete velocities method will possibly improve computation time and reduce the required memory volume.

Limar, Y. F.↗

Monte Carlo Tree Search Methods for the Earth-Observing Satellite Scheduling Problem

This work explores on-board planning for the single spacecraft, multiple ground station Earth-observing satellite scheduling problem through artificial neural network function approximation of state–action value estimates generated by Monte Carlo tree search (MCTS). An extensive hyperparameter search is conducted for MCTS on the basis of performance, safety, and downlink opportunity utilization to determine the best hyperparameter combination for data generation. A hyperparameter search is also conducted on neural network architectures. The learned behavior of each network is explored, and each network architecture’s robustness to orbits and epochs outside of the training distributions is investigated. Furthermore, each algorithm is compared with a genetic algorithm, which serves to provide a baseline for optimality. MCTS is shown to compute near-optimal solutions in comparison to the genetic algorithm. The state–action value networks are shown to match or exceed the performance of MCTS in six orders of magnitude less execution time, showing promise for execution on board spacecraft.

Adam P. Herrmann↗

Monte Carlo simulation of the terrestrial hydrogen exosphere

Methods for Monte Carlo simulation of planetary exospheres have evolved from early work on the lunar atmosphere, where the regolith surface provides a well defined exobase. A major limitation of the successor simulations of the exospheres of Earth and Venus is the use of an exobase surface as an artifice to separate the collisional processes of the thermosphere from a collisionles exosphere. In this paper a new generalized approach to exosphere simulation is described, wherein the exobase is replaced by a barometric depletion of the major constitents of the thermosphere. Exospheric atoms in the thermosphere-exosphere transition region, and in the outer exosphere as well, travel in ballistic trajectories that are interrupted by collisons with the background gas, and by charge exchange interactions with ionospheric particles. The modified simulator has been applied to the terrestrial hydrogen exosphere problem, using velocity dependent differential cross sections to provide statistically correct collisional scattering in H-O and H-H(+) interactions. Global models are presented for both solstice and equinox over the effective solar cycle range of the F(sub 10.7) index (80 to 230). Simulation results show significant differences with previous terrestrial exosphere models, as well as with the H distributions of the MSIS-86 thermosphere model.

Hodges, R. Richard, Jr.↗

Monte Carlo analysis of satellite debris footprint dispersion

A comprehensive study is performed to investigate satellite debris impact point dispersion using a combination of Monte Carlo statistical analysis and parametric methods. The Monte Carlo technique accounts for nonlinearities in the entry point dispersion, which is represented by a covariance matrix of position and velocity errors. Because downrange distance of impact is a monotonic function of debris ballistic coefficient, a parametric method is useful for determining dispersion boundaries. The scheme is applied in the present analysis to estimate the Skylab footprint dispersions for a controlled reentry. A significant increase in the footprint dispersion is noticed for satellite breakup above a 200,000-ft altitude. A general discussion of the method used for analysis is presented together with some typical results obtained for the Skylab deboost mission, which was designed before NASA abandoned plans for a Skylab controlled reentry.

Rao, P. P.↗