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At least 145 records · Page 8

The biasing scheme in N-body simulations

A popular prescription for the galaxy formation, i.e., identifying peaks in the linear density field as sites of galaxy formation, is numerically justified under the Cold Dark Matter cosmogony. In particular, the peak-background scheme, originally developed to simplify analytic calculations of peak properties in a Gaussian random density field, is proven to be an excellent prescription for assigning peak tracers in low-resolution N-body simulations through many statistical comparisons. It is found that statistical properties of peak tracers allocated by the peak-background scheme closely resemble those of true peaks when the background smoothing length is about three times the galaxy scale and the correspondence improves as they evolve gravitationally. It is also shown that these peak particles are indeed strongly associated with nonlinear objects that are presently collapsed.

Park, Changbom↗

Effects of simulated turbulence on aircraft handling qualities

The influence of simulated turbulence on aircraft handling qualities is presented. Pilot opinions of the handling qualities of a light general aviation aircraft were evaluated in a motion-base simulator using a simulated turbulence environment. A realistic representation of turbulence disturbances is described in terms of rms intensity and scale length and their random variations with time. The time histories generated by the proposed turbulence models showed characteristics which are more similar to real turbulence than the frequently-used Gaussian turbulence model. The proposed turbulence models flexibly accommodate changes in atmospheric conditions and are easily implemented in flight simulator studies.

Jacobson, I. D.↗

An optimal control approach to the design of moving flight simulators

An abstract flight simulator design problem is formulated in the form of an optimal control problem, which is solved for the linear-quadratic-Gaussian special case using a mathematical model of the vestibular organs. The optimization criterion used is the mean-square difference between the physiological outputs of the vestibular organs of the pilot in the aircraft and the pilot in the simulator. The dynamical equations are linearized, and the output signal is modeled as a random process with rational power spectral density. The method described yields the optimal structure of the simulator's motion generator, or 'washout filter'. A two-degree-of-freedom flight simulator design, including single output simulations, is presented.

Sivan, R.↗

A study of the feasibility of statistical analysis of airport performance simulation

The feasibility of conducting a statistical analysis of simulation experiments to study airport capacity is investigated. First, the form of the distribution of airport capacity is studied. Since the distribution is non-Gaussian, it is important to determine the effect of this distribution on standard analysis of variance techniques and power calculations. Next, power computations are made in order to determine how economic simulation experiments would be if they are designed to detect capacity changes from condition to condition. Many of the conclusions drawn are results of Monte-Carlo techniques.

Myers, R. H.↗

A stochastic differential equation model of diurnal cortisol patterns

Circadian modulation of episodic bursts is recognized as the normal physiological pattern of diurnal variation in plasma cortisol levels. The primary physiological factors underlying these diurnal patterns are the ultradian timing of secretory events, circadian modulation of the amplitude of secretory events, infusion of the hormone from the adrenal gland into the plasma, and clearance of the hormone from the plasma by the liver. Each measured plasma cortisol level has an error arising from the cortisol immunoassay. We demonstrate that all of these three physiological principles can be succinctly summarized in a single stochastic differential equation plus measurement error model and show that physiologically consistent ranges of the model parameters can be determined from published reports. We summarize the model parameters in terms of the multivariate Gaussian probability density and establish the plausibility of the model with a series of simulation studies. Our framework makes possible a sensitivity analysis in which all model parameters are allowed to vary simultaneously. The model offers an approach for simultaneously representing cortisol's ultradian, circadian, and kinetic properties. Our modeling paradigm provides a framework for simulation studies and data analysis that should be readily adaptable to the analysis of other endocrine hormone systems.

NASA Discipline Space Human Factors↗

Deriving Deformable Mirror Performance Requirements in Simulation with Experimental Verification

Coronagraph instruments rely on predictable and stable deformable mirror (DM) surface displacement to achieve the contrast required to detect Earth-sized exoplanets orbiting nearby Solar-type stars. Anomalous DM behavior, such as unstable or pinned actuators, can limit contrast in coronagraphs. Simulating how these undesired behaviors affect the performance of a high contrast imaging architecture is important for developing requirements on their associated hardware. Simulating a vortex coronagraph (VC) with two deformable mirrors, this study quantifies how the number of pinned actuators affect the performance of Focal Plane Wavefront Sensing and Control algorithms using both Grid Search Electric Field Conjugation (EFC) and Planned EFC, which uses Beta-Bumping. The simulation also quantifies how various types of voltage noise such as zero-mean Gaussian noise, zero-mean periodic noise, and drift can affect the contrast of a VC during an observation run. A tolerance of a change in the Mean Normalized Intensity of ${1\times10^{-11}}$ is allocated to both types of error. If Planned EFC is used, only 1 pinned actuator on both DMs can be tolerated. If only pure Grid Search EFC is used the DMs cannot have any pinned actuators. For the case of zero-mean Gaussian noise and zero-mean periodic noise, one can tolerate a noise standard deviation of no more than ${\sigma = 0.45 \text{ mV}}$. For drift, we can only tolerate ${\sigma = 0.30 \text{ mV}}$ or less. These results show that the DM electronics and the DM themselves need to be nearly defect free to avoid having more than 1 pinned actuator. The electronics need to be tested for different types of noise statistics and that both the average and standard deviation of the noise should be measured.

Dean L. Palmer↗

Characterizing Spatiotemporal Uncertainty in Interpolated Meteorological Data

Interpolated meteorological data invariably contain errors. These errors have structure in time and space, particularly autocorrelation, which can cause the effects of errors to compound when model outputs are aggregated temporally or spatially. One way to account for this uncertainty is with a probabilistic model from which samples can be drawn that are coherent with respect to underlying spatial and temporal covariance structure. This work describes a probabilistic method for spatial interpolation of point-wise meteorological time series. Observational data from weather stations are generally sparse in space and dense in time (but sometimes missing). The method works by projecting time series onto orthogonal basis vectors and spatially interpolating each resulting component independently. Under suitable assumptions, and data transformations to better satisfy those assumptions, Gaussian process regression provides a complete description of the joint predictive distribution over a Gaussian random field. Spatiotemporally coherent realizations are generated as the sum of conditional (spatial) simulations of each orthogonal (temporal) component. Data-derived and generic orthogonal bases are considered. In addition to spatial interpolation, imputation of missing observational data is examined. The method is applied using near-surface air temperature over the Western United States and validated by comparing theoretical versus actual coverage of predictive distributions and analyzing the degree to which spatial and temporal covariance structure is reproduced. Computational considerations, relating to conditional simulation of random fields, are also addressed.

Conor T Doherty↗

Passenger ride quality response to an airborne simulator environment

The present study was done aboard a special aircraft able to effect translations through the center of gravity with a minimum of pitch and roll. The aircraft was driven through controlled motions by an on-board analog computer. The input signal was selectively filtered Gaussian noise whose power spectra approximated that of natural turbulence. This input, combined with the maneuvering capabilities of this aircraft, resulted in an extremely realistic simulation of turbulent flight. The test flights also included varying bank angles during turns. Subjects were chosen from among NASA Flight Research Center personnel. They were all volunteers, were given physical examinations, and were queried about their attitudes toward flying before final selection. In profile, they were representative of the general flying public. Data from this study include (1) a basis for comparison with previous commercial flights, that is, motion dominated by vertical acceleration, (2) extension to motion dominated by lateral acceleration, and (3) evaluation of various bank angles.

Wolf, T. D.↗

Estimation of Timing Performance with Pulsed Laser Links for Small Satellite PNT

Satellite constellations are growing in size and in utility for applications as diverse as providing reliable, low-latency internet service to rural areas orEarth science missions.This expansion of satellite constellations brings attention to the need for responsive and reliable satellite communication.Current research in the PrecisionSpace Systems Laboratory at the University of Florida focuses on using pulsed laser communications as the method of relaying time signals instead of the radio frequency (RF)signals.The upcoming CLICK (CubeSat Laser Infrared CrosslinK) missions (Massachusetts Institute of Technology, University of Florida, NASA Ames Research Center) will demonstrate a spacecraft-to-spacecraft laser communication link and time-transfer.For pre-flight technology assessment of missions such as CLICK, a simulation of a spacecraft constellation in Earth orbit has been created to estimate clock synchronization and precision orbit determination based on measured instrumentation performance.We have developed a novel MATLAB-based numerical simulator to model spacecraft-to-spacecraft laser time-transfer and estimate the offset between the spacecraft clocks over time.This simulation includes timing errors associated with laser pulse generation and detection, as well as non-Gaussian clock drift models.The two on-board clocks modeled are a cesium-based Chip-Scale Atomic Clock (CSAC) and a rubidium-based Miniature Atomic Clock (MAC), both produced by Microchip.An example case of two spacecraft in a circular, low-Earth orbit receiving GPS position, GPS timing, and laser pulse time-of-flight measurements is simulated.The positions and velocities of the two spacecraft at a reference epoch and the constant clock model coefficients are estimated.Polynomial models of different orders were used as clock models. The effect of clock model order on the root-mean-square (RMS) of the clock error is apparent in the case using GPS and lasing measurements, showing that the clock model improves with increasing clock model order. Results compare the estimated clock model of a mission operation that only uses GPS measurements and a mission operation that uses both GPS and laser pulse time-of-flight measurements between spacecraft referenced to their on-board CSACs or on-board MACs. Including lasing measurements reduces the RMS clock model error by approximately 80% of the RMS of the cases with only GPS measurements.This simulation tool can be used to optimize the lasing operations schedule based on mission timing performance objectives. During this presentation, I will discuss the details of the simulation and clock model estimation, as well as discuss the results.I will compare the results of incorporating lasing timing measurements to using only GPS measurements and the outcomes of using different orders of polynomials.

Timing Performance↗

Simulation results for an innovative anti-multipath digital receiver

Simulation results are presented for the error rate performance of the recursive digital MAP detector for known M-ary signals in multiplicative and additive Gaussian noise. Plots of detection error rate versus additive signal to noise ratio are given, with multipath interference strength as a parameter. For comparison, the error rates of conventional coherent and noncoherent digital MAP detectors are simultaneously simulated and graphed. It is shown that with nonzero multiplicative noise, the error rates of the conventional detectors saturate at an irreducible level as additive signal to noise ratio increases. The error rate for the innovative detector continues to decrease rapidly with increasing additive signal to noise ratio. In the absence of multiplicative interference, the conventional coherent detector and the innovative detector are shown to exhibit identical performance.-

Painter, J. H.↗

Solution of the stochastic control problem in unbounded domains.

Bellman's dynamic programming equation for the optimal index and control law for stochastic control problems is a parabolic or elliptic partial differential equation frequently defined in an unbounded domain. Existing methods of solution require bounded domain approximations, the application of singular perturbation techniques or Monte Carlo simulation procedures. In this paper, using the fact that Poisson impulse noise tends to a Gaussian process under certain limiting conditions, a method which achieves an arbitrarily good approximate solution to the stochastic control problem is given. The method uses the two iterative techniques of successive approximation and quasi-linearization and is inherently more efficient than existing methods of solution.

Robinson, P.↗

Analytic Confusion Matrix Bounds for Fault Detection and Isolation Using a Sum-of-Squared- Residuals Approach

Given a system which can fail in 1 or n different ways, a fault detection and isolation (FDI) algorithm uses sensor data in order to determine which fault is the most likely to have occurred. The effectiveness of an FDI algorithm can be quantified by a confusion matrix, which i ndicates the probability that each fault is isolated given that each fault has occurred. Confusion matrices are often generated with simulation data, particularly for complex systems. In this paper we perform FDI using sums of squares of sensor residuals (SSRs). We assume that the sensor residuals are Gaussian, which gives the SSRs a chi-squared distribution. We then generate analytic lower and upper bounds on the confusion matrix elements. This allows for the generation of optimal sensor sets without numerical simulations. The confusion matrix bound s are verified with simulated aircraft engine data.

Simon, Dan↗

Near grazing scattering from non-Gaussian ocean surfaces

We investigate the behavior of the scattered electromagnetic waves from non-Gaussian ocean surfaces at near grazing incidence. Even though the scattering mechanisms at moderate incidence angles are relatively well understood, the same is not true for near grazing rough surface scattering. However, from the experimental ocean scattering data, it has been observed that the backscattering cross section of a horizontally polarized wave can be as large as the vertical counterpart at near grazing incidence. In addition, these returns are highly intermittent in time. There have been some suggestions that these unexpected effects may come from shadowing or feature scattering. Using numerical scattering simulations, it can be shown that the horizontal backscattering cannot be larger than the vertical one for the Gaussian surfaces. Our main objective of this study is to gain a clear understanding of scattering mechanisms underlying the near grazing ocean scattering. In order to evaluate the backscattering cross section from ocean surfaces at near grazing incidence, both the hydrodynamic modeling of ocean surfaces and an accurate near grazing scattering theory are required. For the surface modeling, we generate Gaussian surfaces from the ocean surface power spectrum which is derived using several experimental data. Then, weakly nonlinear large scale ocean surfaces are generated following Longuet-Higgins. In addition, the modulation of small waves by large waves is included using the conservation of wave action. For surface scattering, we use MOM (Method of Moments) to calculate the backscattering from scattering patches with the two scale shadowing approximation. The differences between Gaussian and non-Gaussian surface scattering at near grazing incidence are presented.

Kim, Yunjin↗

Pulse Shaped Constant Envelope 8-PSK Modulation Study

This report provides simulation results for constant envelope pulse shaped 8 Level Phase Shift Keying (8 PSK) modulation for end to end system performance. In order to increase bandwidth utilization, pulse shaping is applied to signals before they are modulated. This report provides simulation results of power spectra and measurement of bit errors produced by pulse shaping in a non-linear channel with Additive White Gaussian Noise (AWGN). The pulse shaping filters can placed before (Type B) or after (Type A) signals are modulated. Three kinds of baseband filters, 5th order Butterworth, 3rd order Bessel and Square-Root Raised Cosine with different BTs or roll off factors, are utilized in the simulations. The simulations were performed on a Signal Processing Worksystem (SPW).

Tao, Jianping↗

Algorithmic Detection of Elemental Biosignatures

Machine learning models that classify a sample as indicative or non-indicative of life could play an important role in life-detection missions. Their predictions result from agnostic algorithms and thereby add redundancy to judgements resulting from human expertise. Additionally, their important features can reveal the most informative measurements within the operational constraints of a life-detection mission. The Ladder of Life Detection (Neveu 2018) identifies the need for an understanding of how combinations of multiple biosignatures affect overall confidence. The present work provides a starting point to answer this need, and future work will expand the data types to obtain even more predictive combinations of features. Elemental abundance was chosen as a starting set of features due to its availability in diverse sample types, which are needed to train a generalizable model. A standardized dataset was collected, including 35 non-indicative, e.g., lunar rock, basalt; 19 indicative mixed, e.g., seawater, agricultural soil; 46 indicative non-alive, e.g., coal, chalk; and 10 indicative alive, e.g., biofilm, bacteria. This dataset could be valuable for complementary biosignature research. The samples were standardized to the same limit of detection of a simulated mission scenario. Four classification models were used: k-nearest neighbors (KNN), logistic regression (LR), linear support vector machines (SVM), and Gaussian naïve Bayes (GNB). To obtain feature importances, KNN was run on three principal components of the training data and LR and SVM were run with L1 and L2 regularization. The performances and feature importances of the six model variants on 40:60 train to validation ratios were assessed with Monte Carlo simulations. ROC AUC and mean accuracy scores ranged between 82% - 94%, with sensitivity greater than specificity. For indicative of life predictors, all models had C and Ca as strong and Cl as medium; a majority of models had N, K, and P as medium. For non-indicative of life predictors, all models had Si as strong, and a majority of models had Mg, Al, and Ti as medium. Varied elements were Fe (slightly non-indicative), H (slightly indicative), O (widely varied), Na, Mn, and S. These results serve as a proof of concept and suggest important elemental signals beyond merely the CHNOPS of Earth-based life.

Algorithmic↗

Signal-to-noise ratio estimation in digital computer simulation of lowpass and bandpass systems with applications to analog and digital communications, volume 3

Techniques are developed to estimate power gain, delay, signal-to-noise ratio, and mean square error in digital computer simulations of lowpass and bandpass systems. The techniques are applied to analog and digital communications. The signal-to-noise ratio estimates are shown to be maximum likelihood estimates in additive white Gaussian noise. The methods are seen to be especially useful for digital communication systems where the mapping from the signal-to-noise ratio to the error probability can be obtained. Simulation results show the techniques developed to be accurate and quite versatile in evaluating the performance of many systems through digital computer simulation.

Tranter, W. H.↗

Simulation of separated flow past a bluff body using Navier-Stokes equations

Two-dimensional flow past a bluff body is presently simulated on the basis of an analysis that employs the incompressible, unsteady Navier-Stokes equations in terms of vorticity and stream function. The fully implicit, time-marching, alternating-direction, implicit-block Gaussian elimination used is a direct method with second-order spatial accuracy; this allows it to avoid the introduction of any artificial viscosity. Attention is given to the simulation of flow past a circular cylinder with and without symmetry, requiring the use of either the half or the full cylinder, respectively.

Ghia, K. N.↗