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Computer Simulation Results and Analysis for a Root-Raised Cosine Filter Design using Canonical Signed Digits
Filters implemented using Canonical Signed-Digit (CSD) number representation for the coefficients have been studied for many years as an efficient way to increase the speed and reduce the hardware complexity. A simple and very effective method for designing a CSD filter with a specific set of filter parameters has been investigated and its simulation results are presented here. In order to optimize filter coefficients into the corresponding CSD numbers, the Minimum Mean Square Error (MMSE) criterion is used. Furthermore, an attempt is made to improve frequency response of the CSD filter by allocating an extra non-zero digit for normalized coefficients exceeding one-half. Due to limited filter aperture width in examples presented here, the frequency response of CSD filter as the number of non-zero digits in a CSD code increases is not affected much. A root-raised cosine filter model is employed as a base line for this design approach. Finally, the CSD filter simulation results and a hardware complexity comparison with a conventional filter are also shown along with the eye diagrams an Bit-Error-Rate (BER) performance curves.
A Buffet Investigation at High Subsonic Speeds of Wing-Fuselage-Tail Combinations having Sweptback Wings with NACA Four-Digit Thickness Distributions, Fences, and Body Contouring
An investigation has been made to determine the effect of wing fences, fuselage contouring, varying wing sweepback angle from 40 deg. to 45 deg., mounting the horizontal tail on an outboard boom) and wing thickness distribution upon the buffeting response of typical airplane configurations employing sweptback wings of high aspect ratio. The tests were conducted through an angle-of-attack range at Mach numbers varying from 0.60 to 0.92 at a Reynolds number of 2 million. For the combinations with 40 deg. of sweepback, the addition of multiple wing fences usually decreased the buffeting at moderate and high lift coefficients and reduced the erratic variation of buffet intensities with increasing lift coefficient and Mach number. Fuselage contouring also reduced buffeting but was not as effective as the wing fences. At most Mach numbers, buffeting occurred at higher lift coefficients for the combination with the NACA 64A thickness distributions than for the combination with the NACA four-digit thickness distributions. At high subsonic speeds, heavy buffeting was usually indicated at lift coefficients which were lower than the lift coefficients for static-longitudinal instability. The addition of wing fences improved the pitching-moment characteristics but had little effect on the onset of buffeting. For most test conditions and model configurations, the root-mean- square and the maximum values measured for relative buffeting indicated similar effects and trends; however, the maximum buffeting loads were usually two to three times the root-mean-square intensities.
Object Detection in Natural Backgrounds Predicted by Discrimination Performance and Models
In object detection, an observer looks for an object class member in a set of backgrounds. In discrimination, an observer tries to distinguish two images. Discrimination models predict the probability that an observer detects a difference between two images. We compare object detection and image discrimination with the same stimuli by: (1) making stimulus pairs of the same background with and without the target object and (2) either giving many consecutive trials with the same background (discrimination) or intermixing the stimuli (object detection). Six images of a vehicle in a natural setting were altered to remove the vehicle and mixed with the original image in various proportions. Detection observers rated the images for vehicle presence. Discrimination observers rated the images for any difference from the background image. Estimated detectabilities of the vehicles were found by maximizing the likelihood of a Thurstone category scaling model. The pattern of estimated detectabilities is similar for discrimination and object detection, and is accurately predicted by a Cortex Transform discrimination model. Predictions of a Contrast- Sensitivity- Function filter model and a Root-Mean-Square difference metric based on the digital image values are less accurate. The discrimination detectabilities averaged about twice those of object detection.
Exploratory Studies in Generalized Predictive Control for Active Gust Load Alleviation
The results of numerical simulations aimed at assessing the efficacy of Generalized Predictive Control (GPC) for active gust load alleviation using trailing- and leading-edge control surfaces are presented. The equations underlying the method are presented and discussed, including system identification, calculation of control law matrices, and calculation of commands applied to the control effectors. Both embedded and explicit feedforward paths for inclusion of disturbance effects are addressed. Results from two types of simulations are shown. The first used a 3-DOF math model of a mass-spring-dashpot system subject to user-defined external disturbances. The second used open-loop data from a wind-tunnel test in which a wing model was excited by sinusoidal vertical gusts; closed-loop behavior was simulated in post-test calculations. Results obtained from these simulations have been decidedly positive. In particular, results of closed-loop simulations for the wing model showed reductions in root moments by factors as high as 1000, depending on whether the excitation is from a constant- or variable-frequency gust and on the direction of the response.
Model Effects on GLAS-Based Regional Estimates of Forest Biomass and Carbon
ICESat/GLAS waveform data are used to estimate biomass and carbon on a 1.27 million sq km study area. the Province of Quebec, Canada, below treeline. The same input data sets and sampling design are used in conjunction with four different predictive models to estimate total aboveground dry forest biomass and forest carbon. The four models include nonstratified and stratified versions of a multiple linear model where either biomass or (square root of) biomass serves as the dependent variable. The use of different models in Quebec introduces differences in Provincial biomass estimates of up to 0.35 Gt (range 4.942+/-0.28 Gt to 5.29+/-0.36 Gt). The results suggest that if different predictive models are used to estimate regional carbon stocks in different epochs, e.g., y2005, y2015, one might mistakenly infer an apparent aboveground carbon "change" of, in this case, 0.18 Gt, or approximately 7% of the aboveground carbon in Quebec, due solely to the use of different predictive models. These findings argue for model consistency in future, LiDAR-based carbon monitoring programs. Regional biomass estimates from the four GLAS models are compared to ground estimates derived from an extensive network of 16,814 ground plots located in southern Quebec. Stratified models proved to be more accurate and precise than either of the two nonstratified models tested.
Creating Formal Characterizations of Routine Contingency Management in Commercial Aviation
The identification, modelling, and analysis of root causes of accidents and incidents dominate conventional safety management approaches. However, the effect of humans’ safety-producing behavior on the overall resilience of the system is often neglected. Additionally, emerging aviation markets are giving rise to concepts of operation, such as urban air mobility and optionally piloted air cargo operations, that are leading to a shift in locus of control between humans and automation. Without an understanding of the human contribution to safety, it is difficult to assess the effects of these novel role allocations on overall system safety. In this work, safety-producing behaviors are identified and abstracted into resilient performance strategies. Production rules that encapsulate these strategies are then generated and classified in the Soar cognitive architecture. The strategies are then applied to a remotely-operated air cargo example to demonstrate how safe learning is facilitated. The learned rules and strategies are then formally verified.
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.
Tests of Aerodynamically Heated Multiweb Wing Structures in a Free Jet at Mach Number 2: Five Aluminum-Alloy Models of 20-Inch Chord with 0.064-Inch-Thick Skin, 0.025-Inch-Thick Webs, and Various Chordwise Stiffening at 2 deg Angle of Attack
An experimental study was made on five 2024-T3 aluminum-alloy multiweb wing structures (MW-2-(4), MW-4-(3), mw-16, MW-17, and MW-18), at a Mach number of 2 and an angle of attack of 2 deg under simulated supersonic flight conditions. These models, of 20-inch chord and semi-span and 5-percent-thick circular-arc airfoil section, were identical except for the type and amount of chordwise stiffening. One model with no chordwise ribs between root and tip bulkhead fluttered and failed dynamically partway through its test. Another model with no chordwise ribs (and a thinner tip bulkhead) experienced a static bending type of failure while undergoing flutter. The three remaining models with one, two, or three chordwise ribs survived their tests. The test results indicate that the chordwise shear rigidity imparted to the models by the addition of even one chordwise rib precludes flutter and subsequent failure under the imposed test conditions. This paper presents temperature and strain data obtained from the tests and discusses the behavior of the models.
Estimation of coarse dead wood stocks in intact and degraded forests in the Brazilian Amazon using airborne lidar
Coarse dead wood is an important component of forest carbon stocks, but it is rarely measured in Amazon forests and is typically excluded from regional forest carbon budgets. Our study is based on line intercept sampling for fallen coarse dead wood conducted along 103 transects with a total length of 48 km matched with forest inventory plots where standing coarse dead wood was measured in the footprints of larger areas of airborne lidar acquisitions. We developed models to relate lidar metrics and Landsat time series variables to coarse dead wood stocks for intact, logged, burned, or logged and burned forests. Canopy characteristics such as gap area produced significant individual relations for logged forests. For total fallen plus standing coarse dead wood (hereafter defined as total coarse dead wood), the relative root mean square error for models with only lidar metrics ranged from 33 % in logged forest to up to 36 % in burned forests. The addition of historical information improved model performance slightly for intact forests (31 % against 35 % relative root mean square error), not justifying the use of a number of disturbance events from historical satellite images (Landsat) with airborne lidar data. Lidar-derived estimates of total coarse dead wood compared favorably with independent ground-based sampling for areas up to several hundred hectares. The relations found between total coarse dead wood and variables quantifying forest structure derived from airborne lidar highlight the opportunity to quantify this important but rarely measured component of forest carbon over large areas in tropical forests.
CFL3D, FUN3d, and NSU3D Contributions to the Fifth Drag Prediction Workshop
Results presented at the Fifth Drag Prediction Workshop using CFL3D, FUN3D, and NSU3D are described. These are calculations on the workshop provided grids and drag adapted grids. The NSU3D results have been updated to reflect an improvement to skin friction calculation on skewed grids. FUN3D results generated after the workshop are included for custom participant generated grids and a grid from a previous workshop. Uniform grid refinement at the design condition shows a tight grouping in calculated drag, where the variation in the pressure component of drag is larger than the skin friction component. At this design condition, A fine-grid drag value was predicted with a smaller drag adjoint adapted grid via tetrahedral adaption to a metric and mixed-element subdivision. The buffet study produced larger variation than the design case, which is attributed to large differences in the predicted side-of-body separation extent. Various modeling and discretization approaches had a strong impact on predicted side-of-body separation. This large wing root separation bubble was not observed in wind tunnel tests indicating that more work is necessary in modeling wing root juncture flows to predict experiments.
Supersonic aeroelastic instability results for a NASP-like wing model
An experimental study and an analytical study have been conducted to examine static divergence for hypersonic-vehicle wing models at supersonic conditions. A supersonic test in the Langley Unitary Plan Wind Tunnel facility was conducted for two wind-tunnel models. These models were nearly identical with the exception of airfoil shape. One model had a four-percent maximum thickness airfoil and the other model had an eight-percent maximum thickness airfoil. The wing models had low-aspect ratios and highly swept leading edges. The all-movable wing models were supported by a single-pivot mechanism along the wing root. For both of the wind-tunnel models, configuration changes could be made in the wing-pivot location along the wing root and in the wing-pivot pitch stiffness. Three divergence conditions were measured for the four-percent thick airfoil model in the Mach number range of 2.6 to 3.6 and one divergence condition was measured for the eight-percent thick airfoil model at a Mach number of 2.9. Analytical divergence calculations were made for comparison with experimental results and to evaluate the parametric effects of wing-pivot stiffness, wing-pivot location, and airfoil thickness variations. These analyses showed that decreasing airfoil thickness, moving the wing-pivot location upstream, or increasing the pitch-pivot stiffness have the beneficial effect of increasing the divergence dynamic pressures. The calculations predicted the trend of experimental divergence dynamic pressure with Mach number accurately; however, the calculations were approximately 25 percent conservative with respect to dynamic pressure.
Modeling Spectralon's Bidirectional Reflectance for In-flight Calibration of Earth-Orbiting Sensors
The in-flight calibration of the EOS Multi-angle Imaging SpectroRadiometer (MISR) will be achieved, in part, by observing deployable Spectralon panels. This material reflects light diffusely, and allows all cameras to view a near constant radiance field. This is particularly true when a panel is illuminated near the surface normal. To meet the challenging MISR calibration requirements, however, very accurate knowledge of the panel reflectance must be known for all utilized angles of illumination, and for all camera and monitoring photodiode view angles. It is believed that model predictions of the panels Bidirectional Reflectance Distribution Function (BRDF) can be used in conjunction with a measurements program to provide the required characterization. This paper describes the results of a model inversion which was conducted using measured Spectralon BRDF data at several illumination angles. Four physical parameters of the material were retrieved, and are available for use with the model to predict reflectance for any arbitrary illumination or view angle. With these data the root mean square difference between the model and the observations is currently of the order of the noise in the data, at about +/- l%. With this success the model will now be used in a variety of future studies, including the development of a measurements test plan, the validation of these data, and the prediction of a new BRDF profile, should the material degrade in space.
Evaluating the Utility of Remotely-Sensed Soil Moisture Retrievals for Operational Agricultural Drought Monitoring
Soil moisture is a fundamental data source used by the United States Department of Agriculture (USDA) International Production Assessment Division (IPAD) to monitor crop growth stage and condition and subsequently, globally forecast agricultural yields. Currently, the USDA IPAD estimates surface and root-zone soil moisture using a two-layer modified Palmer soil moisture model forced by global precipitation and temperature measurements. However, this approach suffers from well-known errors arising from uncertainty in model forcing data and highly simplified model physics. Here we attempt to correct for these errors by designing and applying an Ensemble Kalman filter (EnKF) data assimilation system to integrate surface soil moisture retrievals from the NASA Advanced Microwave Scanning Radiometer (AMSR-E) into the USDA modified Palmer soil moisture model. An assessment of soil moisture analysis products produced from this assimilation has been completed for a five-year (2002 to 2007) period over the North American continent between 23degN - 50degN and 128degW - 65degW. In particular, a data denial experimental approach is utilized to isolate the added utility of integrating remotely-sensed soil moisture by comparing EnKF soil moisture results obtained using (relatively) low-quality precipitation products obtained from real-time satellite imagery to baseline Palmer model runs forced with higher quality rainfall. An analysis of root-zone anomalies for each model simulation suggests that the assimilation of AMSR-E surface soil moisture retrievals can add significant value to USDA root-zone predictions derived from real-time satellite precipitation products.
Investigation of a 1/4 Scale Model of the Republic F-105 Airplane in the Langley 19 Foot Pressure Tunnel. Longitudinal Stability and Control and Horizontal-Tail Hinge-Moment and Normal-Force Characteristics of the Model Equipped with a Drooped Supersonic-Type Elliptical Wing-Root Inlet
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An Ensemble Neural Network Model for Predicting Rare-Earth Oxide and Silicate Heat Capacities at High Temperature
In this work, a neural network model was developed to predict the constant pressure heat capacity for materials in the rare-earth oxide—silica material space. Several model architectures were trained and tested on heat capacity data generated from first-principles density functional theory calculations. Hyperparameter optimization was performed, and the optimal model was selected for heat capacity predictions. The optimal model architecture was found to have a root-mean-squared error of 5.12 ± 3.37 J/mol-K. The optimal model architecture was then used in a bagging ensemble model trained using the leave-one-group-out method to provide error estimates for model predictions. The out-of-bag score for the ensemble model was 0.997. The predicted heat capacities agree well with the DFT and experimental results and were computed orders of magnitude faster than DFT simulations. Machine learning shows the potential to provide a suitable surrogate model for thermochemical property predictions for candidate environmental barrier coating materials but refining of input material features and model architectures could further improve accuracy for these models.
Density Variations as a Function of Compostion in the Venusian Crust: Implications for Tesserae Formation
The Venusian surface plains are thought to be predominantly basaltic, while tesserae occupy ~ 7 % and are potentially the oldest units preserved [1]. They consist of layered, folded, and eroded rocks [2], potentially giving an insight into what tectonic regimes were present during Venus’ history. Studies of the tesserae have noted lower emissivity measurements compared to the surrounding plains [3]. Several explanations for these lower emissivity values have been proposed, including a more felsic composition for the tesserae [4], that the lower emissivity could be a result of a difference in mineralogy caused by chemical weathering facilitated between the rocks and atmosphere by the lower temperatures at the higher elevations of tesserae [5]. Alternatively, the morphology of some features on tesserae, such as the Ovda Fluctus, are more consistent with a basaltic composition [6]. The presence of significant amounts of felsic igneous compositions could either imply partial melting of hydrous material and hence a higher water content in early Venus [7], or differentiation of basaltic melts [8]. Further, tesserae composition influences the density of the crust with major implications for the stability of crustal roots. Here, we use thermodynamic modeling to compute phase diagrams and extract rock densities for two end-member compositions: a basalt and a granite. We discuss major phase and density changes for each composition and describe the effect of compositional variations along geothermal gradients with implications for the stability of crustal roots with the aim to provide constraints on the composition of tesserae.
A theoretical analysis of the round-off propagation in different Kalman filter implementations
A theoretical analysis is made of the error propagation due to numerical round-off for four different Kalman filter implementations: the conventional Kalman filter, the square root covariance filter, the square root information filter and the Chandrasekhar square root filter. From these error models, new insights about the applicability of the different filters and their sensitivity to round-off, is obtained. It is shown that the CKF may become completely unreliable when the original plant is unstable, and that this is easily circumvented by a number of techniques. The square root filters, often quoted to possess a conditioning or sensitivity that is the square root of that of the CKF, are shown to possess this property only for the computation of the covariance of the filtered signal and not for the computation of the Kalman gain or the filtered estimate. Finally, the Chandrasekhar filter is shown to be numerically unstable.