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NASA NTRS2022

Shape Servoing of Deformable Objects using Adaptive Deformation Model Estimation

In this paper, we propose an adaptive shape servoing method to deform a soft object into a desired 3-D shape. The high dimensional representation and the unknown deformation properties of the soft object pose a challenge to actively manipulate its shape. To address this issue, we develop a method to compute the deformation Jacobian matrix in real-time. The Jacobian is estimated using a set of basis functions and its corresponding parameters to capture the dynamics of the system and relate the applied input motion to changes in the soft object's shape. An integral concurrent learning (ICL) based adaptive update law is derived using Lyapunov analysis to estimate the deformation parameters and prove its convergence. A physics-based simulation is used to validate the proposed method and controller by performing manipulation tasks with different desired configurations. The performance is compared with a standard gradient update law to demonstrate the accuracy and robustness of our approach.

Vrithik Raj Guthikonda↗

NASA NTRS1979

Fundamental mechanisms that influence the estimate of heat transfer to gas turbine blades

Estimates of the heat transfer from the gas to stationary (vanes) or rotating blades poses a major uncertainty due to the complexity of the heat transfer processes. The gas flow through these blade rows is three dimensional with complex secondary viscous flow patterns that interact with the endwalls and blade surfaces. In addition, upstream disturbances, stagnation flow, curvature effects, and flow acceleration complicate the thermal transport mechanisms in the boundary layers. Some of these fundamental heat transfer effects are discussed. The chief purpose of the discussion is to acquaint those in the heat transfer community, not directly involved in gas turbines, of the seriousness of the problem and to recommend some basic research that would improve the capability for predicting gas-side heat transfer on turbine blades and vanes.

Graham, R. W.↗

NASA NTRS1986

Vela X-1 pulse timing. I - Determination of the neutron star orbit

Analysis and interpretation of observations of the pulsed X-ray emission from Vela X-1 are presented. The interrelated tasks of determining the neutron-star orbit and calculating pulse emission times in the rest frame of the source are considered, with the underlying motivation to utilize this time series for analysis of fluctuations in the pulse emission frequency, which are interpreted as noise in the neutron-star rotation rate. However, the redness and strength of this noise in Vela X-1 pose a nontrivial complication, because the parameters of the neutron-star orbit are estimated by pulse timing and hence are themselves affected by fluctuations in the pulse emission frequency. A second challenge is presented by substantial fluctuations in the Vela X-1 pulse shape that, if ignored, would significantly reduce both the precision of the orbital solution and the ability to study fluctuations in the rotation rate. The report emphasizes the analysis techniques that have been developed to obtain the most precise orbital solution possible in the face of these difficulties. These techniques are general and may be applied to other pulsars that exhibit substantial fluctuations in pulse shape and frequency, such as Her X-1 and Cen X-3.

Boynton, P. E.↗

NASA NTRSDate not supplied

Vision-Based Distributed Sensing at Vertiports for Advanced Air Mobility and Urban Air Mobility Approach and Landing

Advanced Air Mobility (AAM) encompasses a broad vision for air transportation, including Urban Air Mobility (UAM) as a subset. AAM aims to create a more connected and efficient transportation network across various geographical settings. However, navigating AAM aircraft in GPS-denied or degraded environments during approach and landing is challenging. Traditional vision aids like glideslopes and localizers are limited in vertiport environments due to narrow beam constraints and reduced landing angle options. This paper addresses the need for accurate navigation solutions at vertiports by proposing a vision-based distributed sensing (VIDIS) system utilizing cameras with bundle adjustment to assist incoming AAM aircraft during approach and landing while monitoring surface movements to enhance safety and efficiency. Key focus areas for current and future vertiport developers include identifying suitable sensor types and infrastructure standards to support AAM operations and including vertiport markings as vision-based navigation aids. The proposed system offers a novel approach to overcoming navigation challenges in AAM operations, particularly in urban settings where traditional aids may be insufficient. Preliminary simulation results with distributed cameras demonstrate promising outcomes for implementing bundle adjustment techniques to enhance vision-based navigation solutions at vertiports. Generating waypoint-based trajectories via waypoint integration using explicit guidance synthesis (WINGS) creates smooth AAM trajectories for landing at vertiports by using the current waypoint's terminal conditions as the initial conditions for the next waypoint. Combining bundle adjustment's ground-based solution of vertiport features with WINGS, Coplanar Pose from Orthography and Scaling with Iterations (COPOSIT), and an extended Kalman filter (EKF) estimates the state of an incoming aircraft during approach and landing at vertiports. Future work includes testing VIDIS in a high-fidelity simulation and with real-world data.

Distributed sensing↗

NASA NTRSDate not supplied

Vision-Based Distributed Sensing at Vertiports for Advanced Air Mobility and Urban Air Mobility Approach and Landing

Distributed sensing↗

NASA NTRS1986

The ill-posed nature of the satellite temperature retrieval problem and the limits of retrievability

The inverse problem of satellite temperature profile retrieval is well known to be ill-posed. This means that not only is a vertical temperature profile solution not unique, but that two solutions can be very different from each other. A set of atmosphere-like, and true atmospheric examples of significantly dissimilar inverse solutions, were sought and found, using an 11-channel simulated HIRS sounding radiometer. Using the Riemann-Lebesgue Lemma for guidance, it is shown that simultaneous, numerical solutions of an atmospheric character may differ by as much as 10 K between 10-1000 mb. However, an empirical search for dissimilar solutions in the natural atmosphere reveals an extremely low probability of finding two significantly different RAOBs which produce radiance measurements whose differences cannot be resolved by the satellite radiometer. The empirical results are used to derive a first estimate of the limits of retrievability, analogous to the limits of predictability derivable from the ill-posed nature of the numerical weather prediction problem.

Thompson, Owen E.↗

NASA NTRS2015

Raven: An On-Orbit Relative Navigation Demonstration Using International Space Station Visiting Vehicles

Since the last Hubble Servicing Mission five years ago, the Satellite Servicing Capabilities Office (SSCO) at the NASA Goddard Space Flight Center (GSFC) has been focusing on maturing the technologies necessary to robotically service orbiting legacy assets-spacecraft not necessarily designed for in-flight service. Raven, SSCO's next orbital experiment to the International Space Station (ISS), is a real-time autonomous non-cooperative relative navigation system that will mature the estimation algorithms required for rendezvous and proximity operations for a satellite-servicing mission. Raven will fly as a hosted payload as part of the Space Test Program's STP-H5 mission, which will be mounted on an external ExPRESS Logistics Carrier (ELC) and will image the many visiting vehicles arriving and departing from the ISS as targets for observation. Raven will host multiple sensors: a visible camera with a variable field of view lens, a long-wave infrared camera, and a short-wave flash lidar. This sensor suite can be pointed via a two-axis gimbal to provide a wide field of regard to track the visiting vehicles as they make their approach. Various real-time vision processing algorithms will produce range, bearing, and six degree of freedom pose measurements that will be processed in a relative navigation filter to produce an optimal relative state estimate. In this overview paper, we will cover top-level requirements, experimental concept of operations, system design, and the status of Raven integration and test activities.

Rendezvous↗

NASA NTRS1990

On three dimensional object recognition and pose-determination: An abstraction based approach

A method of computing reliable Gaussian and mean curvature sign-map descriptors from the polynomial approximation of surfaces was demonstrated. Such descriptors which are invariant under perspective variation are suitable for hypothesis generation. A means for determining the pose of constructed geometric forms whose algebraic surface descriptors are nonlinear in terms of their orienting parameters was developed. This was done by means of linear functions which are capable of approximating nonlinear forms and determining their parameters. It was shown that biquadratic surfaces are suitable companion linear forms for cylindrical approximation and parameter estimation. The estimates provided the initial parametric approximations necessary for a nonlinear regression stage to fine tune the estimates by fitting the actual nonlinear form to the data. A hypothesis-based split-merge algorithm for extraction and pose determination of cylinders and planes which merge smoothly into other surfaces was developed. It was shown that all split-merge algorithms are hypothesis-based. A finite-state algorithm for the extraction of the boundaries of run-length regions was developed. The computation takes advantage of the run list topology and boundary direction constraints implicit in the run-length encoding.

Quek, Kok How Francis↗

NASA NTRS2006

Attenuating Stereo Pixel-Locking via Affine Window Adaptation

For real-time stereo vision systems, the standard method for estimating sub-pixel stereo disparity given an initial integer disparity map involves fitting parabolas to a matching cost function aggregated over rectangular windows. This results in a phenomenon known as 'pixel-locking,' which produces artificially-peaked histograms of sub-pixel disparity. These peaks correspond to the introduction of erroneous ripples or waves in the 3D reconstruction of truly Rat surfaces. Since stereo vision is a common input modality for autonomous vehicles, these inaccuracies can pose a problem for safe, reliable navigation. This paper proposes a new method for sub-pixel stereo disparity estimation, based on ideas from Lucas-Kanade tracking and optical flow, which substantially reduces the pixel-locking effect. In addition, it has the ability to correct much larger initial disparity errors than previous approaches and is more general as it applies not only to the ground plane.

pixel locking effect↗

NASA NTRSDate not supplied

Using Machine Learning to Estimate Surface-Level SO2 Concentrations from Satellite-Based Measurements

Sulfur dioxide (SO2) is a criteria air pollutant due to its contributions to aerosol formation, rainfall acidification, and harm to human health. The placement of air quality monitoring sites is typically biased towards urban areas, leaving large areas with very limited monitoring data. The Ozone Monitoring Instrument (OMI) has been used to provide estimates of SO2 vertical column densities (VCDs) globally at spatial resolution of 10s of kms once per day. OMI SO2 VCDs have been previously used to estimate surface SO2 concentrations using chemical transport model (CTM) simulations. The CTMs use estimated emissions and assimilated meteorological data, and simulate the chemical and physical processes that determine the vertical profile of SO2, which can be used to derive a ratio between the surface concentrations and VCDs. These models are complex, computationally expensive, and have large uncertainties in the simulated surface-to-VCD ratio due to biases in emissions and relatively coarse resolution. Machine learning techniques are comparatively easier to use, much less computationally expensive to use after training, and can produce more accurate estimations of surface concentrations than the CTM-based method. The interpretation of machine learning models often poses challenges, and in some cases, non-physical variables unrelated to SO2 are used as predictors. In this work, we create an artificial neural network (ANN) to relate OMI retrievals and archived GEOS-FP boundary layer heights to surface SO2 concentrations from the ChinaHighAirPollutants ChinaHighSO2 dataset (CHAP; Wei et al., 2023) on a seasonal average timescale from 2013-2018. Our model only utilizes five variables that are directly relevant to the satellite retrieval, lifetime, and spatial distribution of SO2. The model was trained on 16 seasons (four of each) with independent validation (one of each season) and testing datasets (one of each season) to avoid overfitting. Our ANN generates surface SO2 concentrations that are sensitive (slope = 0.51) and consistent (r = 0.74) with the CHAP data, but are underpredicted by an average of 1.2 ppbv with a mean absolute error of 2.2 ppbv. These results are better than recent studies utilizing the CTM method. To our knowledge, this is the best performing machine learning model that only uses physical variables to predict surface SO2. Our work demonstrates that a carefully constructed, simple ML model can accurately estimate surface-based SO2 concentrations from satellite VCD measurements, and this technique has future promise to expend to newer, higher resolution satellites and other air pollutants.

SO2, air quality, OMI, machine learning↗

NASA NTRS1991

Inverse problems and optimal experiment design in unsteady heat transfer processes identification

Experimental-computational methods for estimating characteristics of unsteady heat transfer processes are analyzed. The methods are based on the principles of distributed parameter system identification. The theoretical basis of such methods is the numerical solution of nonlinear ill-posed inverse heat transfer problems and optimal experiment design problems. Numerical techniques for solving problems are briefly reviewed. The results of the practical application of identification methods are demonstrated when estimating effective thermophysical characteristics of composite materials and thermal contact resistance in two-layer systems.

Artyukhin, Eugene A.↗

NASA NTRS2012

Characterization of New Hard X-ray Cataclysmic Variables

Aims. We aim at characterizing a sample of nine new hard X-ray selected Cataclysmic Variable (CVs), to unambiguously identify them as magnetic systems of the Intermediate Polar (IP) type. Methods. We performed detailed timing and spectral analysis by using X-ray, and simultaneous UV and optical data collected by XMM−Newton, complemented with hard X-ray data provided by INTEGRAL and Swift. The pulse arrival time were used to estimate the orbital periods. The broad band X-ray spectra were fitted using composite models consisting of different absorbing columns and emission components. Results. Strong X-ray pulses at the White Dwarf (WD) spin period are detected and found to decrease with energy. Most sources are spin-dominated systems in the X-rays, though four are beat dominated at optical wavelengths. We estimated the orbital period in all system (except for IGR J16500-3307), providing the first estimate for IGRJ08390-4833, IGRJ18308-1232, and IGR J18173-2509. All X-ray spectra are multi-temperature. V2069 Cyg and RX J0636+3535 poses a soft X-ray optically thick component at kT approx. 80 eV. An intense K (sub alpha) Fe line at 6.4 keV is detected in all sources. An absorption edge at 0.76 keV from OVII is detected in IGR J08390-4833. The WD masses and lower limits to the accretion rates are also estimated. Conclusions. We found all sources to be IPs. IGR J08390-4833, V2069 Cyg, and IGR J16500-3307 are pure disc accretors, while IGR J18308-1232, IGR J1509-6649, IGR J17195-4100, and RX J0636+3535 display a disc-overflow accretion mode. All sources show a temperature gradient in the post-shock regions and a highly absorbed emission from material located in the pre-shock flow which is also responsible for the X-ray pulsations. Reflection at the WD surface is likely the origin of the fluorescent iron line. There is an increasing evidence for the presence of a warm absorber in IPs, a feature that needs future exploration. The addition of two systems to the subgroup of soft X-ray IPs confirms a relatively large (∼ 30%) incidence.

hard X-ray↗

NASA NTRSDate not supplied

Lunar Regolith Trajectories as a Result of Plume Surface Interactions

Lunar regolith is ejected from the impingement points of descent engine plumes. Such particles pose potential risks to surface operations, sites of scientific and historical interest, and orbiting spacecraft. Consequently, determining the resultant trajectories of these particles is necessary in order to estimate and mitigate risk. Here we present the ranges, impact latitudes, times of flight, and maximum altitudes for particles accelerated by a plume surface interaction at the lunar south pole. Using launch angles determined from observations and simulations, and for velocities <1:6 km/s, particles pose little risk. However, above 1:6 km/s the risks increase, and the results become highly sensitive to the initial angle. In addition, gravitational and non-gravitational processes will introduce perturbations to high-velocity trajectories resulting in a reduction in precision. Therefore, while local topography or artificial berms may mitigate trajectories with low initial angles, it remains important to place tight constraints on the potential launch angles of particles accelerated by plume surface interactions through simulations and experimentation. If these angles are indeed constrained to within a few degrees of the horizon, the risks posed by accelerated regolith particles at any velocity will be minimal.

Daniel Batcheldor↗

NASA NTRS2021

Unsupervised Deep Persistent Monocular Visual Odometry and Depth Estimation in Extreme Environments

In recent years, unsupervised deep learning ap-proaches have received a significant attention to estimate depthand visual odometry (VO) from unlabelled monocular imagesequences. However, their performance is limited in challengingenvironments due to perceptual degradation, occlusions andrapid motions. Moreover, the existing unsupervised methodssuffer from the lack of scale-consistency constraints acrossframes, which causes that the VO estimators fail to providepersistent trajectories over long sequences. In this study, wepropose a unsupervised monocular deep VO framework thatpredicts 6 degrees-of-freedom pose camera motion and depthmap of the scene from unlabelled RGB image sequences.We provide detailed quantitative and qualitative evaluationsof the proposed framework on a) a challenging dataset col-lected during the DARPA Subterranean challenge1; and b)the benchmark KITTI and Cityscapes datasets. The proposedapproach outperforms both traditional and state-of-the-artunsupervised deep VO methods providing better results for bothpose estimation and depth recovery. The presented approach ispart of the solution used by the COSTAR team participatingat the DARPA Subterranean Challenge

Agha-mohammadi, Ali-akbar↗

NASA NTRS2010

New Evidence for a Black Hole in the Compact Binary Cygnus X-3

The bright and highly variable X-ray and radio source known as Cygnus X-3 was among the first X-ray sources discovered, yet it remains in many ways an enigma. Its known to consist of a massive. Wolf-Rayet primary in an extremely tight orbit with a compact object. Yet one of the most basic of pa.ranietern the mass of the compact object - is not known. Nor is it even clear whether its is a neutron star or a black hole. In this Paper we present our analysis of the broad-band high-energy continua covering a substantial range in luminosity and spectral morphology. We apply these results to a recently identified scaling relationship which has been demonstrated to provide reliable estimates of the compact object mass in a number of accretion powered binaries. This analysis leads us to conclude that the compact object in Cygnus X-3 has a mass greater than 4.2 solar mass thus clearly indicative of a black hole and as such resolving a longstanding issue. The full range of uncertainty in our analysis and from using a. range of recently published distance estimates constrains the compact object mass to lie between 4.2 solar mass and 14.4 solar mass. Our favored estimate, based on a 9.0 kpc distance estimate is approx. l0 solar mass, with the. error margin of 3.2 solar masses. This result may thus pose challenges to shared-envelope evolutionary models of compact binaries. as well as establishing Cygnus X-3 as the first confirmed accretion-powered galactic gamma: ray source.

Shrader, Chris R.↗

NASA NTRS2000

Aerosol Climate Effects: Local Radiative Forcing and Column Closure Experiments

In an effort to reduce uncertainties in climate change predictions, experiments are being planned and conducted to measure anthropogenic aerosol properties and effects, including effects on radiative fields. The global average, direct anthropogenic aerosol effect on upwelling shortwave fluxes is estimated to be about +1/2 W/sq m, whereas errors in flux changes measured with airborne and spaceborne radiometers are 2 to 8 W/sq m or larger. This poses the question of whether flux changes expected in field experiments will be large enough to measure accurately. This paper obtains a new expression for the aerosol-induced change in upwelling flux, compares it to two-stream and adding-doubling (AD) results, and uses all three methods to estimate expected flux changes. The new expression accounts for the solar zenith angle dependences of aerosol transmission and reflection, as well as of surface albedo, all of which can have a strong effect in determining flux changes measured in field experiments. Despite its relative simplicity, the new expression gives results similar to previous two-stream results. Relative to AD results, it agrees within a few watts per square meter for the intermediate solar elevation angles where the flux changes peak (roughly 10 to 30 degrees), but it has negative errors for higher Sun and positive errors for lower Sun. All three techniques yield aerosol-induced changes in upwelling flux of +8 to +50 W/sq m for aerosol midvisible optical depths of 0.1 to 0.5. Because such aerosol optical depths occur frequently off the U.S. and European Atlantic coasts in summer, the flux changes they induce should be measurable by airborne, and possibly by spaceborne, radiometers, provided sufficient care is taken in experiment design (including measurements to separate aerosol radiative effects from those of absorbing gases). The expected flux changes are about 15 to 100 times larger than the global average flux change expected for the global average anthropogenic sulfate optical depth of 0.04. Reasons for the larger flux changes include the larger optical depths considered here (factor 2.5 to 12), plus restricting the measurements to cloud-free, daytime conditions over the ocean (factor 5 to 9).

Russell, P. B.↗

NASA NTRS2002

Sudden ionospheric delay decorrelation and its impact on WAAS

We report a methodology for assessing the impact on WAAS posed by a sudden increase in the level of ionospheric disturbance. The methodology is based upon the forming an estimate of the probability P(D) that a WAAS user will confront a sudden increase in the level of ionospheric disturbance following a period of relative calm. By restricting the tabulation of fit residuals to only those fits where the spatial coverage of the fit points is sufficiently good, we have determined a limiting upper bound of P(D) to be 2x10(sup -6).

ionosphere WAAS GPS↗

NASA NTRS2017

Real-Time Prediction of Safety Margins in the National Airspace

Underlying all operations in the National Airspace System (NAS) is the concept of safety. Safety, as defined by acceptable levels of risk, is to be maintained at all times. The real-time safety monitoring (RTSM) framework is under development to provide an automated system to quantify safety in the NAS, estimate the current level of safety, and predict the future evolution of safety and the occurrence of events that pose an increased risk to flights so that these occurrences can be managed strategically rather than mitigated reactively. This paper presents the mathematical framework, the models, and the monitoring and prediction algorithms used to achieve this. RTSM computes safety as expressed through a set of safety margins based on user-defined safety metrics, thresolds, and events. Sources of uncertainty are modeled and propagated through the predictions in order to compute the probabilistic evolution of safety and the probability of events that introduce increased risk to operations. A prototype implementation is discussed and results demonstrating feasibility are presented. The results highlight the kinds of predictions that can be computed and the fidelity that is currently achieved.

national airspace system↗