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NASA NTRS2018

Autonomous Small Body Mapping and Spacecraft Navigation

Current methods for pose and shape estimation of small bodies, such as comets and asteroids, rely on extensive ground support and signiﬁcant use of radiometric measurements using the Deep Space Network. The Stereo-Photoclinometry (SPC) technique is currently used to provide detailed topological information about a small body as well as its absolute orientation and position. While this technique has produced very accurate estimates, the core algorithm cannot be run in real-time and requires a team of scientists on the ground who must communicate with the spacecraft in order to oversee SPC operations. Autonomous onboard navigation addresses these limitations by eliminating the need for human oversight. In this paper, we present an optimization-based estimation algorithm for navigation that allows the spacecraft to autonomously approach and maneuver around an unknown small body by mapping its geometric shape, estimating its orientation, and simultaneously determining the trajectory of the center of mass of the small body. We show the eﬀectiveness of the proposed algorithm using simulated data from a previous ﬂight mission to Comet 67P.

Bhaskaran, Shyamkumar↗

NASA NTRS2005

Kalman Filter Constraint Tuning for Turbofan Engine Health Estimation

Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints are often neglected because they do not fit easily into the structure of the Kalman filter. Recently published work has shown a new method for incorporating state variable inequality constraints in the Kalman filter, which has been shown to generally improve the filter s estimation accuracy. However, the incorporation of inequality constraints poses some risk to the estimation accuracy as the Kalman filter is theoretically optimal. This paper proposes a way to tune the filter constraints so that the state estimates follow the unconstrained (theoretically optimal) filter when the confidence in the unconstrained filter is high. When confidence in the unconstrained filter is not so high, then we use our heuristic knowledge to constrain the state estimates. The confidence measure is based on the agreement of measurement residuals with their theoretical values. The algorithm is demonstrated on a linearized simulation of a turbofan engine to estimate engine health.

Simon, Dan↗

NASA NTRS2011

Feature and Pose Constrained Visual Aided Inertial Navigation for Computationally Constrained Aerial Vehicles

A Feature and Pose Constrained Extended Kalman Filter (FPC-EKF) is developed for highly dynamic computationally constrained micro aerial vehicles. Vehicle localization is achieved using only a low performance inertial measurement unit and a single camera. The FPC-EKF framework augments the vehicle's state with both previous vehicle poses and critical environmental features, including vertical edges. This filter framework efficiently incorporates measurements from hundreds of opportunistic visual features to constrain the motion estimate, while allowing navigating and sustained tracking with respect to a few persistent features. In addition, vertical features in the environment are opportunistically used to provide global attitude references. Accurate pose estimation is demonstrated on a sequence including fast traversing, where visual features enter and exit the field-of-view quickly, as well as hover and ingress maneuvers where drift free navigation is achieved with respect to the environment.

autonomous operation↗

NASA NTRS2006

Improvement in Visual Target Tracking for a Mobile Robot

In an improvement of the visual-target-tracking software used aboard a mobile robot (rover) of the type used to explore the Martian surface, an affine-matching algorithm has been replaced by a combination of a normalized- cross-correlation (NCC) algorithm and a template-image-magnification algorithm. Although neither NCC nor template-image magnification is new, the use of both of them to increase the degree of reliability with which features can be matched is new. In operation, a template image of a target is obtained from a previous rover position, then the magnification of the template image is based on the estimated change in the target distance from the previous rover position to the current rover position (see figure). For this purpose, the target distance at the previous rover position is determined by stereoscopy, while the target distance at the current rover position is calculated from an estimate of the current pose of the rover. The template image is then magnified by an amount corresponding to the estimated target distance to obtain a best template image to match with the image acquired at the current rover position.

Kim, Won↗

NASA NTRS2009

Estimation of Faults in DC Electrical Power System

This paper demonstrates a novel optimization-based approach to estimating fault states in a DC power system. Potential faults changing the circuit topology are included along with faulty measurements. Our approach can be considered as a relaxation of the mixed estimation problem. We develop a linear model of the circuit and pose a convex problem for estimating the faults and other hidden states. A sparse fault vector solution is computed by using 11 regularization. The solution is computed reliably and efficiently, and gives accurate diagnostics on the faults. We demonstrate a real-time implementation of the approach for an instrumented electrical power system testbed, the ADAPT testbed at NASA ARC. The estimates are computed in milliseconds on a PC. The approach performs well despite unmodeled transients and other modeling uncertainties present in the system.

Gorinevsky, Dimitry↗

NASA NTRS2016

Fast Kalman Filtering for Relative Spacecraft Position and Attitude Estimation for the Raven ISS Hosted Payload

The Raven ISS Hosted Payload will feature several pose measurement sensors on a pan/tilt gimbal which will be used to autonomously track resupply vehicles as they approach and depart the International Space Station. This paper discusses the derivation of a Relative Navigation Filter (RNF) to fuse measurements from the different pose measurement sensors to produce relative position and attitude estimates. The RNF relies on relative translation and orientation kinematics and careful pose sensor modeling to eliminate dependence on orbital position information and associated orbital dynamics models. The filter state is augmented with sensor biases to provide a mechanism for the filter to estimate and mitigate the offset between the measurements from different pose sensors.

estimation↗

NASA NTRS2016

Fast Kalman Filtering for Relative Spacecraft Position and Attitude Estimation for the Raven ISS Hosted Payload

estimation↗

DOE OSTI2024

Uncertainty Quantification and Sensitivity Analysis for Quantitative Risk Assessments of Hydrogen Infrastructure

Typical QRAs provide deterministic estimates and understanding of risks posed but are constructed using significant assumptions and uncertainties due to limited data availability and historical momentum of using nominal estimates. This report presents a hydrogen QRA analysis using HyRAM+ that incorporates uncertainty with Latin hypercube sampling and sensitivity analysis using linear regression.

08 HYDROGEN↗

DOE OSTI2025

Laser Confocal Microscopy Uncertainty Quantification Study

At Los Alamos National Laboratory (LANL), the Storage Safety and Engineering (SSE) team completes annual surveillance on a subset of in-use interim nuclear material storage containers in fulfilment of requirements outlined in DOE Manual M 441.1-1. The containers are selected through several methods, such as subject matter expert judgement, random selection, and trending items. Following these selections, the SSE team has the capacity to complete surveillance on 15-20 containers each fiscal year, composed of a combination of SAVY-4000 and Hagan storage containers. Through previous work, the stainless-steel components of the containers have been identified as life limiting components, with an emphasis on the thin-walled bodies. The team is focused on understanding the extent of general and pitting corrosion, due to observations of extensive corrosion from stored contents and bag-out-bag degradation. Quantifying corrosion effects on the thin-walled stainless steel container bodies, and understanding potential impacts to the respective design release rates and design qualification release rates is paramount to the team. To date, destructive examination (DE) has proven to be the most insightful method for developing an understanding on the extent of corrosion on used containers. To standardize this process, the SSE team developed a destructive examination guide for analyzing stainless steel components of the containers. Corroded containers of interest are identified during surveillance activities and set aside for sectioning and characterization. Following sectioning, a major step in the DE workflow is the utilization of laser confocal microscopy for scanning corroded samples of interest and extracting data on pits, such as count, depth, and equivalent diameter. Adhering to the techniques outlined in the DE guide, analysis has been completed on two Hagans and one SAVY-4000 container, with the maximum pit depth recorded as 139.1 ± 22.82 μm on a 17.5 year old Hagan. The findings from the completed destructive examinations will be utilized to support lifetime extension efforts of the SAVY-4000 as the team can better estimate corrosion rates and effects over time based on stored contents and age. Due to the implications of observing extreme pit depths that approach the nominal container body thickness of .0299 inches (0.759 mm) or minimum container thickness of 0.236” (0.6 mm), high confidence in the LCM measurements is desired. Through testing outlined in, it was concluded that the total error ascribed to the 20x objective when conducting large image mapping on the Keyence VK-X3050 laser confocal microscope (LCM) relative to a 50x objective (reference) is 16.4% (± 8.73%). For shallow features on the order of pristine SAVY surface defects (i.e. 5 μm), this uncertainty is appropriate. However, this conservative estimate of total error poses a fundamental concern for pit depths that approach the thickness of the measured samples. That is, with the measurement uncertainty currently employed on all measurements, the LCM would be unable to resolve if a pit with a depth of 515 μm is through wall. Standard step height samples were procured and used in the present study to assess the resolution and repeatability of height measurements. Understanding the resolution and repeatability of height measurements was the first focus of the team as it relates directly to pit depth, which is of primary concern. Calibration gratings were procured to evaluate the resolution and repeatability of measurements in the X and Y axes of the LCM stage. The results of the depth uncertainty study were conducted first and presented in the subsequent sections. The planar uncertainty study is appended to the depth study with conclusions from both summarized at the end of the report.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Multimodal parameter spaces of a complex multi-channel neuron model

One of the most common types of models that helps us to understand neuron behavior is based on the Hodgkin–Huxley ion channel formulation (HH model). A major challenge with inferring parameters in HH models is non-uniqueness: many different sets of ion channel parameter values produce similar outputs for the same input stimulus. Such phenomena result in an objective function that exhibits multiple modes (i.e., multiple local minima). This non-uniqueness of local optimality poses challenges for parameter estimation with many algorithmic optimization techniques. HH models additionally have severe non-linearities resulting in further challenges for inferring parameters in an algorithmic fashion. To address these challenges with a tractable method in high-dimensional parameter spaces, we propose using a particular Markov chain Monte Carlo (MCMC) algorithm, which has the advantage of inferring parameters in a Bayesian framework. The Bayesian approach is designed to be suitable for multimodal solutions to inverse problems. We introduce and demonstrate the method using a three-channel HH model. We then focus on the inference of nine parameters in an eight-channel HH model, which we analyze in detail. We explore how the MCMC algorithm can uncover complex relationships between inferred parameters using five injected current levels. The MCMC method provides as a result a nine-dimensional posterior distribution, which we analyze visually with solution maps or landscapes of the possible parameter sets. The visualized solution maps show new complex structures of the multimodal posteriors, and they allow for selection of locally and globally optimal value sets, and they visually expose parameter sensitivities and regions of higher model robustness. We envision these solution maps as enabling experimentalists to improve the design of future experiments, increase scientific productivity and improve on model structure and ideation when the MCMC algorithm is applied to experimental data.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Stellar Mass Calibrations for Local Low-mass Galaxies

The stellar masses of galaxies are measured from integrated light via several methods—however, few of these methods were designed for low-mass (M ⋆ ≲ 10 8 M ⊙ ) “dwarf” galaxies, whose properties (e.g., stochastic star formation, low metallicity) pose unique challenges for estimating stellar masses. In this work, we quantify the precision and accuracy at which stellar masses of low-mass galaxies can be recovered using UV/optical/IR photometry. We use mock observations of 469 low-mass galaxies from a variety of models, including both semi-empirical models (GRUMPY and UniverseMachine-SAGA) and cosmological baryonic zoom-in simulations (MARVELous Dwarfs and FIRE-2), to test literature color–M ⋆ /L relations and multiwavelength spectral energy distribution (SED) mass estimators. We identify a list of “best practices” for measuring stellar masses of low-mass galaxies from integrated photometry. We find that literature color–M ⋆ /L relations are often unable to capture the bursty star formation histories (SFHs) of low-mass galaxies, and we develop an updated prescription for stellar mass based on g − r color that is better able to recover stellar masses for the bursty low-mass galaxies in our sample (with ∼0.1 dex precision). SED fitting can also precisely recover stellar masses of low-mass galaxies, but this requires thoughtful choices about the form of the assumed SFH: Parametric SFHs can underestimate stellar mass by as much as ∼0.4 dex, while nonparametric SFHs recover true stellar masses with insignificant offset (−0.03 ± 0.11 dex). Finally, we also caution that noninformative (wide) dust attenuation priors may introduce M ⋆ uncertainties of up to ∼0.6 dex.

de los Reyes, Mithi A. C. [Amherst College, MA (Un↗

NASA NTRS1982

Threat perception while viewing single intruder conflicts on a cockpit display of traffic information

Subjective estimates of the threat posed by a single intruder aircraft were determined by showing pilots photographs of a cockpit display of traffic information. The time the intruder was away from the point of minimum separation was found to be the major determinant of the perception of threat. When asked to choose a maneuver to reduce the conflict, pilots selected maneuvers with a bias toward those that would have kept the intruders in sight had they been visible out the cockpit window.

Ellis, S. R.↗

NASA NTRS1996

NASA Space Missions to Asteroids: Protecting the Earth from NEO Impacts

There is now a general recognition of the hazard of impacts on Earth by comets and asteroids, but there is yet no consensus concerning international actions that should be taken to protect the planet from such impacts. An essential step in the analysis of the situation involves estimating the relative hazard posed by comets and asteroids of different sizes and orbits. All recent studies agree that the larger impacts pose the greater danger, and that our primary concern from the perspective of total risk should be on impacts that are large enough to cause global ecological catastrophe. These global catastrophes are also of special interest, since they (alone among natural disasters) have the potential to destroy civilization. Studies of the sensitivity of the Earth's environment suggest that the energy threshold energy for causing a global catastrophe is at about 1 million megatons, corresponding to impactor diameters of 1.5 to 2 km. This information leads naturally to a strategy of concentrating on the larger NEOs, say those 1 km or more in diameter. This is the rationale for the Spaceguard Survey, which must be the highest priority in mitigation efforts. The second question concerns the value of developing standing defensive systems that could deflect or destroy an incoming NEO. In the case of the asteroids larger than 1 km in diameter, no such system is needed, since there will be ample time (at least several decades) between the discovery of the threatening object by Spaceguard and the requirement to take action against it. In the case of objects smaller than 1 km diameter, development of defensive systems is not cost-effective; there are many greater dangers to persons and property that are much more urgent. Only in the case of large long-period comets is there a rationale for standing defense systems. The question is also raised whether the risks inherent in developing and maintaining a defense system might be greater than the impact risks it is intended to guard against. These and related issues are the focus of much current international debate on defense of the planet against NEO impacts. Meanwhile, the most critical issue remains the expansion of the telescopic search for NEOs.

Morrison, David↗

NASA NTRS2017

Getting to the Heart of Cardiovascular Risk Assessment in Astronauts for Exploration Class Missions

Since the beginning of manned spaceflight, NASA has recognized the potential risk of cardiovascular decrements due to stressors in the space environment. Of particular concern is the effect of space radiation on cardiovascular disease since astronauts will be exposed to higher levels of galactic cosmic rays outside the Earth's protective magnetosphere. To date, only a few studies have examined the effects of heavy ion radiation on cardiovascular disease, and at lower, space-relevant doses, the association between radiation exposure and cardiovascular pathology is more varied and unclear. Furthermore, other spaceflight conditions such as microgravity, circadian shifts, and confinement stress pose unique challenges in estimating the health risks that can be attributed to exposure to ionizing radiations. In this work, we review age, cause of mortality, and radiation exposure amongst early NASA astronauts in selection groups and discuss the limitations of assessing such a cohort when attempting to characterize the risk of space flight, including stressors such as space radiation and microgravity exposure, on cardiovascular health. METHODS: NASA astronauts in selection groups 1-7 were chosen and the comparison population was white men of the same birth cohort as drawn from data from the CDC Wonder Database and CDC National Center for Health Statistics Life Tables. Cause of death information was obtained from the Lifetime Surveillance of Astronaut Health program and deceased astronauts were classified based on ICD-10 codes: ischemic heart disease (IHD), stroke, cancer, acute occupational events, non-NASA accidents, and other/unknown. Expected years of life left and expected age at death were calculated for the cohort. RESULTS AND CONCLUSIONS: There were 32 deaths in this early astronaut population, 12 of which were due to accidents or acute occupational events that impacted lifespan considerably. The average age at death from these causes is 30 years lower than the average expected ~70 years of age in the general population. Remarkably, all 41 living early astronauts outlived our calculated expected age at death for members of their birth cohort; furthermore, 13 of the 20 deceased astronauts who did not die in NASA/non-NASA accidents exceeded this age. There was no difference in IHD between the astronaut cohort and the comparison population; therefore, it is not possible to associate IHD mortality with radiation in that astronaut cohort. As NASA looks toward future exploration-class missions, early astronaut cohorts provide a convenient option for assessing these risks and for developing mitigation strategies. However, many challenges still exist when assessing such limited evidence, including small cohort size, health and lifestyle confounders (such as smoking and drinking), the high accident mortality rate, and the fact that many of these astronauts are still alive, outliving many of their birth-cohort peers. Future analysis should include a longitudinal study, monitoring cases as they occur in the cohort. As this cohort is currently followed-up over time, and as more IHD cases are anticipated in a population of this age, this type of study is not as resource-intensive as would normally be the case.

Elgart, S. R.↗

DOE OSTI2023

Validation of turbulence intensity as simulated by the Weather Research and Forecasting model off the US northeast coast

We report turbulence intensity (TI) is often used to quantify the strength of turbulence in wind energy applications and serves as the basis of standards in wind turbine design. Thus, accurately characterizing the spatiotemporal variability in TI should lead to improved predictions of power production. Nevertheless, turbulence measurements over the ocean are far less prevalent than over land due to challenges in instrumental deployment, maintenance, and operation. Atmospheric models such as mesoscale (weather prediction) and large-eddy simulation (LES) models are commonly used in the wind energy industry to assess the spatial variability of a given site. However, the TI derivation from atmospheric models has not been well examined. An algorithm is proposed in this study to realize online calculation of TI in the Weather Research and Forecasting (WRF) model. Simulated TI is divided into two components depending on scale, including sub-grid (parameterized based on turbulence kinetic energy (TKE)) and grid resolved. The sensitivity of sea surface temperature (SST) on simulated TI is also tested. An assessment is performed by using observations collected during a field campaign conducted from February to June 2020 near the Woods Hole Oceanographic Institution Martha's Vineyard Coastal Observatory. Results show that while simulated TKE is generally smaller than the lidar-observed value, wind speed bias is usually small. Overall, this leads to a slight underestimation in sub-grid-scale estimated TI. Improved SST representation subsequently reduces model biases in atmospheric stability as well as wind speed and sub-grid TI near the hub height. Large TI events in conjunction with mesoscale weather systems observed during the studied period pose a challenge to accurately estimating TI from models. Due to notable uncertainty in accurately simulating those events, this suggests summing up sub-grid and resolved TI may not be an ideal solution. Efforts in further improving skills in simulating mesoscale flow and cloud systems are necessary as the next steps.

17 WIND ENERGY↗

DOE OSTI2023

How reliable is distribution of relaxation times (DRT) analysis? A dual regression-classification perspective on DRT estimation, interpretation, and accuracy

The distribution of relaxation times (DRT) has gained increasing attention and adoption in recent years as a versatile method for analyzing electrochemical impedance spectroscopy (EIS) data obtained from complex devices like fuel cells, electrolyzers, and batteries. The DRT deconvolutes the impedance without a priori specification of a generative model, which is especially useful for interpretation and model selection when the governing principles of the system under study are not fully understood. However, DRT estimation is an ill-posed inversion problem that must be addressed with a subjective choice of regularization and tuning, which leaves substantial risk of misleading interpretations of EIS data. In this work, we suggest a new classification view of the DRT inversion to clarify DRT estimation and interpretation. We introduce a dual regression-classification framework that unifies the classification and regression views of the DRT inversion with wide-reaching implications for DRT analysis. The dual framework is employed to demonstrate a new kind of DRT inversion algorithm and develop novel evaluation metrics that capture previously ignored aspects of DRT accuracy. These approaches are applied to both synthetic data and experimental spectra collected from a protonic ceramic fuel cell and a lithium-ion battery to illustrate their broad utility. The dual inversion algorithm shows promising performance for accurate DRT estimation and autonomous model identification, while the dual evaluation approach produces metrics that meaningfully assess the strengths and risks of DRT algorithms. Here this work provides valuable insight for both practical application of the DRT to experimental data and further development of EIS analysis methods.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Dynamic Power Network State Estimation with Asynchronous Measurements

The operation of distribution networks is becoming increasingly volatile, due to fast variations of renewables and, hence, net-loading conditions. To perform a reliable state estimation under these conditions, this paper considers the case where measurements from meters, phasor measurement units, and distributed energy resources are collected and processed in real time to produce estimates of the state at a fast time scale. Streams of measurements collected in real time and at heterogenous rates render the underlying processing asynchronous, and poses severe strains on workhorse state estimation algorithms. In this work, a real-time state estimation algorithm is proposed, where data are processed on the fly. Starting from a regularized least-squares model, and leveraging appropriate linear models, the proposed scheme boils down to a linear dynamical system where the state is updated based on the previous estimate and on the measurement gathered from a few available sensors. The estimation error is shown to be always bounded under mild condition. Numerical simulations are provided to corroborate the analytical findings.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1995

Results from the Heavy Ions In Space (HIIS) experiment on the ionic charge state of solar energetic particles

It has long been known that low-energy solar energetic particles (SEP's) are partially-ionized. For example, in large, so-called 'gradual' solar energetic particle events, at approximately 1 MeV/nucleon the measured mean ionic charge state, Q, of Fe ions is 14.1 +/- 0.2, corresponding to a plasma temperature of approximately 2 MK in the coronal or solar-wind source material. Recent studies, which have greatly clarified the origin of solar energetic particles and their relation to solar flares, suggest that ions in these SEP events are accelerated not at a flare site, but by shocks propagating through relatively low-density regions in the interplanetary medium. As a result, the partially-ionized states observed at low energies are expected to continue to higher energies. However, up to now there have been no high-energy measurements of ionic charge states to confirm this notion. We report here HIIS observations of Fe-group ions at 50-600 MeV/nucleon, at energies and fluences which cannot be explained by fully-ionized galactic cosmic rays, even in the presence of severe geomagnetic cutoff suppression. Above approximately 200 MeV/nucleon, all features of our data -- fluence, energy spectrum, elemental composition, and arrival directions -- can be explained by the large SEP events of October 1989, provided that the mean ionic charge state at these high energies is comparable to the measured value at approximately 1 MeV/nucleon. By comparing the HIIS observations with measurements in interplanetary space in October 1989, we determine the mean ionic charge state of SEP Fe ions at approximately 200-600 MeV/nucleon to be Q = 13.4 plus or minus 1.0, in good agreement with the observed value at approximately 1 MeV/nucleon. The source of the ions below approximately 200 MeV/nucleon is not yet clear. Partially-ionized ions are less effectively deflected by the Earth's magnetic field than fully-ionized cosmic rays and therefore have greatly enhanced access to low-Earth orbit. Moreover, at the high energies observed in HIIS, these ions can penetrate typical amounts of shielding. We discuss the significance of the HIIS results for estimates of the radiation hazard posed by large SEP events to satellites in low-Earth orbit, including the proposed Space Station orbit. Finally, we comment on previous reports of low-energy below-cutoff Fe-group ions, which some authors have interpreted as evidence for partially-ionized galactic cosmic rays. The LDEF flux levels are much smaller than the corresponding fluxes in these previous reports, implying that the source of these ions has an unusual solar-cycle variation and/or strongly increases with decreasing altitude.

Tylka, Allan J.↗