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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2015

Adaptive State Predictor Based Human Operator Modeling on Longitudinal and Lateral Control

Control-theoretic modeling of the human operator dynamic behavior in manual control tasks has a long and rich history. In the last two decades, there has been a renewed interest in modeling the human operator. There has also been significant work on techniques used to identify the pilot model of a given structure. The purpose of this research is to attempt to go beyond pilot identification based on collected experimental data and to develop a predictor of pilot behavior. An experiment was conducted to categorize these interactions of the pilot with an adaptive controller compensating during control surface failures. A general linear in-parameter model structure is used to represent a pilot. Three different estimation methods are explored. A gradient descent estimator (GDE), a least squares estimator with exponential forgetting (LSEEF), and a least squares estimator with bounded gain forgetting (LSEBGF) used the experiment data to predict pilot stick input. Previous results have found that the GDE and LSEEF methods are fairly accurate in predicting longitudinal stick input from commanded pitch. This paper discusses the accuracy of each of the three methods - GDE, LSEEF, and LSEBGF - to predict both pilot longitudinal and lateral stick input from the flight director's commanded pitch and bank attitudes.

Trujillo, Anna C.↗
NASA NTRS2016

Encke-Beta Predictor for Orion Burn Targeting and Guidance

The state vector prediction algorithm selected for Orion on-board targeting and guidance is known as the Encke-Beta method. Encke-Beta uses a universal anomaly (beta) as the independent variable, valid for circular, elliptical, parabolic, and hyperbolic orbits. The variable, related to the change in eccentric anomaly, results in integration steps that cover smaller arcs of the trajectory at or near perigee, when velocity is higher. Some burns in the EM-1 and EM-2 mission plans are much longer than burns executed with the Apollo and Space Shuttle vehicles. Burn length, as well as hyperbolic trajectories, has driven the use of the Encke-Beta numerical predictor by the predictor/corrector guidance algorithm in place of legacy analytic thrust and gravity integrals.

Robinson, Shane↗
NASA NTRS2015

Random Predictor Models for Rigorous Uncertainty Quantification: Part 2

This and a companion paper propose techniques for constructing parametric mathematical models describing key features of the distribution of an output variable given input-output data. By contrast to standard models, which yield a single output value at each value of the input, Random Predictors Models (RPMs) yield a random variable at each value of the input. Optimization-based strategies for calculating RPMs having a polynomial dependency on the input and a linear dependency on the parameters are proposed. These formulations yield RPMs having various levels of fidelity in which the mean, the variance, and the range of the model's parameter, thus of the output, are prescribed. As such they encompass all RPMs conforming to these prescriptions. The RPMs are optimal in the sense that they yield the tightest predictions for which all (or, depending on the formulation, most) of the observations are less than a fixed number of standard deviations from the mean prediction. When the data satisfies mild stochastic assumptions, and the optimization problem(s) used to calculate the RPM is convex (or, when its solution coincides with the solution to an auxiliary convex problem), the model's reliability, which is the probability that a future observation would be within the predicted ranges, is bounded rigorously.

Crespo, Luis G.↗
NASA NTRS2015

Random Predictor Models for Rigorous Uncertainty Quantification: Part 1

This and a companion paper propose techniques for constructing parametric mathematical models describing key features of the distribution of an output variable given input-output data. By contrast to standard models, which yield a single output value at each value of the input, Random Predictors Models (RPMs) yield a random variable at each value of the input. Optimization-based strategies for calculating RPMs having a polynomial dependency on the input and a linear dependency on the parameters are proposed. These formulations yield RPMs having various levels of fidelity in which the mean and the variance of the model's parameters, thus of the predicted output, are prescribed. As such they encompass all RPMs conforming to these prescriptions. The RPMs are optimal in the sense that they yield the tightest predictions for which all (or, depending on the formulation, most) of the observations are less than a fixed number of standard deviations from the mean prediction. When the data satisfies mild stochastic assumptions, and the optimization problem(s) used to calculate the RPM is convex (or, when its solution coincides with the solution to an auxiliary convex problem), the model's reliability, which is the probability that a future observation would be within the predicted ranges, can be bounded tightly and rigorously.

Crespo, Luis G.↗
NASA NTRS2016

Application of Interval Predictor Models to Space Radiation Shielding

This paper develops techniques for predicting the uncertainty range of an output variable given input-output data. These models are called Interval Predictor Models (IPM) because they yield an interval valued function of the input. This paper develops IPMs having a radial basis structure. This structure enables the formal description of (i) the uncertainty in the models parameters, (ii) the predicted output interval, and (iii) the probability that a future observation would fall in such an interval. In contrast to other metamodeling techniques, this probabilistic certi cate of correctness does not require making any assumptions on the structure of the mechanism from which data are drawn. Optimization-based strategies for calculating IPMs having minimal spread while containing all the data are developed. Constraints for bounding the minimum interval spread over the continuum of inputs, regulating the IPMs variation/oscillation, and centering its spread about a target point, are used to prevent data over tting. Furthermore, we develop an approach for using expert opinion during extrapolation. This metamodeling technique is illustrated using a radiation shielding application for space exploration. In this application, we use IPMs to describe the error incurred in predicting the ux of particles resulting from the interaction between a high-energy incident beam and a target.

Crespo, Luis G.↗
NASA NTRS2016

Photospheric Current Spikes as Possible Predictors of Flares

Flares involve generation of the largest current densities in the solar atmosphere. This suggests the hypothesis that prior to a large (M,X) flare there are related time dependent changes in the photospheric current distribution, and hence in the resistive heating rate in neutral line regions (NLRs). If this is true, these changes might be useful predictors of flares. Evidence supporting this hypothesis is presented. Results from a data driven, near photospheric, 3D magnetohydrodynamic type model suggest the model might be useful for predicting M and X flares several hours to several days in advance. The model takes as input the photospheric magnetic field observed by the Helioseismic & Magnetic Imager (HMI) on the Solar Dynamics Observatory (SDO) satellite. The model computes quantities in every active region (AR) pixel for 14 ARs, with spurious Doppler periods due to SDO orbital motion filtered out of the time series of the magnetic field for each pixel. Spikes in the NLR resistive heating rate Q, appearing as increases by orders of magnitude above background values in the time series of Q are found to occur, and appear to be correlated with the occurrence of M or X flares a few hours to a few days later. The subset of spikes analyzed at the pixel level are found to occur on HMI and granulation scales of 1 arcsec and 12 minutes. Spikes are found in NLRs with and without M or X flares, and outside as well as inside NLRs, but the largest spikes are localized in the NLRs of ARs with M or X flares, and associated with horizontal magnetic field strengths several hG, and vertical magnetic field strengths several orders of magnitude smaller, suggesting that the spikes are associated with current sheets.

Goodman, Michael L.↗
NASA NTRS2016

Photospheric Current Spikes as Possible Predictors of Flares

Flares involve generation of the largest current densities in the solar atmosphere. This suggests the hypothesis that prior to a large (M,X) flare there are related time dependent changes in the photospheric current distribution, and hence in the resistive heating rate in neutral line regions (NLRs). If this is true, these changes might be useful predictors of flares. Preliminary evidence supporting this hypothesis is presented. Results from a data driven, near photospheric, 3D magnetohydrodynamic type model suggest the model might be useful for predicting M and X flares several hours to several days in advance. The model takes as input the photospheric magnetic field observed by the Helioseismic and Magnetic Imager (HMI) on the Solar Dynamics Observatory (SDO) satellite. The model computes quantities in every active region (AR) pixel for 14 ARs, with spurious Doppler periods due to SDO orbital motion filtered out of the time series of the magnetic field for each pixel. Spikes in the NLR resistive heating rate Q, appearing as increases by orders of magnitude above background values in the time series of Q are found to occur, and appear to be correlated with the occurrence of M or X flares a few hours to a few days later. The subset of spikes analyzed at the pixel level are found to occur on HMI and granulation scales of 1 arcsec and 12 minutes. Spikes are found in NLRs with and without M or X flares, and outside as well as inside NLRs, but the largest spikes are localized in the NLRs of ARs with M or X flares, and associated with horizontal magnetic field strengths approximately several hG, and vertical magnetic field strengths several orders of magnitude smaller. The spikes may be signatures of horizontal current sheets associated with emerging magnetic flux.

Goodman, Michael L.↗
NASA NTRS2017

Interval Predictor Models for Data with Measurement Uncertainty

An interval predictor model (IPM) is a computational model that predicts the range of an output variable given input-output data. This paper proposes strategies for constructing IPMs based on semidefinite programming and sum of squares (SOS). The models are optimal in the sense that they yield an interval valued function of minimal spread containing all the observations. Two different scenarios are considered. The first one is applicable to situations where the data is measured precisely whereas the second one is applicable to data subject to known biases and measurement error. In the latter case, the IPMs are designed to fully contain regions in the input-output space where the data is expected to fall. Moreover, we propose a strategy for reducing the computational cost associated with generating IPMs as well as means to simulate them. Numerical examples illustrate the usage and performance of the proposed formulations.

Lacerda, Marcio J.↗
NASA NTRS2019

Pterodactyl: An Uncoupled Range Control Approach to Fully Numerical Predictor-Corrector Entry Guidance

Entry, descent, and landing (EDL) has been identified as a core area of investment in NASA's Strategic Technology Investment Plan (NASA STIP). STIP lists the space technologies needed to help achieve NASA's science, technology, and exploration goals across the agency. Within the EDL core area, deployable hypersonic decelerators, also known as deployable entry vehicles (DEVs), have been identified as an area of investment, due to its potential to revolutionize payload delivery methods to Earth and other planets. These vehicles, which can deploy their heat shields or alter their shape before entry, exploit an increased and more effective drag ratio by using less mass than traditional blunt body vehicles with rigid aeroshells. DEVs like Adaptive Deployable Entry and Placement Technology (ADEPT) and Hypersonic Inflatable Aerodynamic Decelerator (HIAD) have demonstrated the capability of transporting the equivalent science payloads of blunt body rigid aeroshells, while using a significantly smaller diameter when stowed within a launch vehicle. While DEVs' increased energy dissipation for less mass is an attractive feature, their ability to contract and expand would require advancements in the current state-of-the-art guidance and control (G&C) architectures used by traditional rigid vehicles. Pterodactyl, a project funded by NASA's Space Technology Mission Directorate (STMD), aims to provide feasible integrated G&C solutions for DEVs, complete with optimized vehicle designs and packaging analyses. Structural and aerodynamic analyses for the explored control systems suggested a need for a bank angle guidance algorithm, a heritage guidance approach that has been used in many entry precision targeting vehicles, as well as an additional need for the development of a non-bank angle guidance. For this reason, Pterodactyl will consider four different G&C configurations during its design phase: i) a reaction control system for bank (sigma) control, ii) a mass movement system for angle of attack (alpha) sideslip (beta) control, iii) flaps for alpha - beta control, and iv) flaps for sigma control. To increase the applicability of each proposed integrated G&C architecture, an 11 km/s lunar return demonstration mission is selected to stress the developed technology capability. The Lifting Nano-ADEPT (LNA) vehicle is chosen as the DEV to demonstrate the integrated solutions. This paper will detail the trajectory design for a lunar return mission, using the validated bank control guidance algorithm Fully Numerical Predictor-Corrector Entry Guidance (FNPEG) and a newly developed guidance algorithm: FNPEG Uncoupled Range Control (URC). FNPEG-URC diverges from traditional bank angle guidances by producing alpha and beta commands to thereby decouple downrange and crossrange control. This presentation will discuss the development and overall performance of FNPEG and FNPEG-URC for each of the four G&C configurations. Successful G&C configurations are defined as those that can deliver payloads to the intended descent and landing site while abiding by trajectory constraints in the face of dispersions.

Johnson, Breanna↗
NASA NTRS2020

Development of a Numeric Predictor-Corrector Aerocapture Guidance for Direct Force Control

Direct force control, where the angle of attack and sideslip angle are modulated, has been proposed as an alternative to bank angle control for aero-assist maneuvers. This paper reimplements the current state-of-the-art aerocapture guidance for bank angle control, Fully Numeric Predictor-corrector Aerocapture Guidance (FNPAG), for direct force control. The optimal control theory underlying the structure of FNPAG is shown to not be applicable to the direct force control approach. Several solution structures for the longitudinal channel are compared by simulating dispersed three-degree-of-freedom trajectories for a reference mission consisting of a low lift-to-drag vehicle and a highly elliptical, 1-sol target orbit around Mars. The equations of motion for the lateral channel are derived, and a controller is designed to target a specified orbital plane. Finally, a Monte Carlo is used to demonstrate the performance of the new guidance.

Matz, Daniel A.↗
NASA NTRSDate not supplied

Numerical Predictor-Corrector Based Guidance Scheme For Aero-Gravity Assist at Titan For Enceladus Missions

Aero-gravity assist is a spacecraft maneuver than can enable a vehicle to insert into an orbit of one planetary body using the atmosphere and gravity field of a secondary body, reducing the required propellant mass relative to a fully-propulsive orbit insertion. The Fully Numerical Predictor-Corrector Aerocapture Guidance algorithm was modified to work with a direct force control blunt body vehicle, executing an aero-gravity assist at Titan to enter a Saturnian orbit and conduct fly-by at Enceladus. Additionally, a proportional-integral-derivative controller was implemented to command sideslip angles for control of the orbital inclination. Numerical simulation showed the developed guidance scheme was capable of minimizing the energy and inclination error at atmospheric exit, allowing Saturnian moon tour trajectories and Enceladus exploration at a small delta-V cost, on the order of 100 m/s, in the nominal case.

Daniel Louis Engel↗
NASA NTRSDate not supplied

Numerical Predictor-Corrector Based Guidance Scheme For Aero-Gravity Assist at Titan For Enceladus Missions

Aero-gravity assist is a spacecraft maneuver than can enable a vehicle to insert into an orbit of one planetary body using the atmosphere and gravity field of a secondary body, reducing the required propellant mass relative to a fully-propulsive orbit insertion. The Fully Numerical Predictor-Corrector Aerocapture Guidance algorithm was modified to work with a direct force control blunt body vehicle, executing an aero-gravity assist at Titan to enter a Saturnian orbit and conduct fly-by at Enceladus. Additionally, a proportional-integral-derivative controller was implemented to command sideslip angles for control of the orbital inclination. Numerical simulation showed the developed guidance scheme was capable of minimizing the energy and inclination error at atmospheric exit, allowing Saturnian moon tour trajectories and Enceladus exploration at a small delta-V cost, on the order of 100 m/s, in the nominal case.

Daniel L. Engel↗
NASA NTRSDate not supplied

Genomic and Phenotypic Predictors of Human Ex Vivo Sensitivity to Simulated Deep Space Radiation

High-linear energy transfer (LET) ionizing radiation is a major health hazard for astronauts who will be exposed to galactic cosmic rays during upcoming lunar and Mars missions. Predicting and mitigating this risk requires understanding the factors underlying individual radiation sensitivity. We started to address this challenge by identifying the genomic and phenotypic associations with sensitivity to low and high-LET ionizing radiation ex vivo in over 750 healthy human donors. We exposed primary human blood mononuclear cells to simulated galactic cosmic ray components: 350 MeV/n 28Si, 350 MeV/n 40Ar and 600 MeV/n 56Fe particles, at 1.1 and 3 particles/100 sq.m fluences, as well as 0.1 Gy and 1 Gy doses of gamma rays, and analyzed the outcomes at 4 and 24 hours post-irradiation. We quantified DNA damage and repair responses based on 53BP1+ radiation-induced foci formation, together with oxidative stress and changes in secreted factors including immune cytokines and exosomes. We also analyzed phenotypic associations with spontaneous DNA repair foci at baseline prior to irradiation. We identified an increase in spontaneous DNA repair associated with age and latent viral infection, and observed that human spontaneous DNA repair foci at baseline can serve as a negative predictor of DNA repair and immunoregulatory cytokine production after irradiation. Furthermore, we observed a wide variability of subject- and LET-dependent radiation responses, with radiation-induced DNA repair foci increasing by dose and LET, and high-LET particle radiation resulting in more residual DNA damage compared to low-LET particles and gamma rays. We have developed multiple metrics to quantify human radiosensitivity across the spectrum of conditions. Here we present their dependence on radiation quality and phenotypic variables, including an age-dependent decrease in DNA repair after irradiation, and genomic associations with radiosensitivity based on low-coverage whole genome sequencing. We anticipate that our work will pave the way for understanding the spectrum of human radiosensitivity and identifying targets for countermeasure development to reduce DNA and cellular damage and radiation carcinogenesis during deep space exploration.

GWAS↗
NASA NTRSDate not supplied

Genomic and phenotypic predictors of human ex vivo sensitivity to simulated deep space radiation

High-linear energy transfer (LET) ionizing radiation is a major health hazard for astronauts who will be exposed to galactic cosmic rays during upcoming lunar and Mars missions. Predicting and mitigating this risk requires understanding the factors underlying individual radiation sensitivity. We started to address this challenge by identifying the genomic and phenotypic associations with sensitivity to low and high-LET ionizing radiation ex vivo in over 750 healthy human donors. We exposed primary human blood mononuclear cells to simulated galactic cosmic ray components: 350MeV/n (28)Si, 350MeV/n (40)Ar and 600MeV/n (56)Fe particles, at 1.1 and 3 particles/100µm^(2) fluences, as well as 0.1 Gy and 1 Gy doses of gamma rays, and analyzed the outcomes at 4 and 24 hours post-irradiation. We quantified DNA damage and repair responses based on 53BP1^(+) radiation-induced foci formation, together with oxidative stress and changes in secreted factors including immune cytokines and exosomes. We also analyzed phenotypic associations with spontaneous DNA repair foci at baseline prior to irradiation. We identified an increase in spontaneous DNA repair associated with age and latent viral infection, and observed that human spontaneous DNA repair foci at baseline can serve as a negative predictor of DNA repair and immunoregulatory cytokine production after irradiation. Furthermore, we observed a wide variability of subject- and LET-dependent radiation responses, with radiation-induced DNA repair foci increasing by dose and LET, and high-LET particle radiation resulting in more residual DNA damage compared to low-LET particles and gamma rays. We have developed multiple metrics to quantify human radiosensitivity across the spectrum of conditions. Here we present their dependence on radiation quality and phenotypic variables, including an age-dependent decrease in DNA repair after irradiation, and genomic associations with radiosensitivity based on low-coverage whole genome sequencing. We anticipate that our work will pave the way for understanding the spectrum of human radiosensitivity and identifying targets for countermeasure development to reduce DNA and cellular damage and radiation carcinogenesis during deep space exploration.

GWAS↗
NASA NTRS2013

Bulk Insolation Models as Predictors for Locations for High Lunar Hydrogen Concentrations

In this study we consider the bulk effects of surface illumination on topography (insolation) and the possible thermodynamic effects on the Moon's hydrogen budget. Insolation is important as one of the dominant loss processes governing distributions of hydrogen volatiles on the Earth, Mars and most recently Mercury. We evaluated three types of high latitude > 65 deg., illumination models that were derived from the Lunar Observing Laser Altimetry (LOLA) digital elevation models (DEM)'s. These models reflect varying accounts of solar flux interactions with the Moon's near-surface. We correlate these models with orbital collimated epithermal neutron measurements made by the Lunar Exploration Neutron Detector (LEND). LEND's measurements derive the Moon's spatial distributions of hydrogen concentration. To perform this analysis we transformed the topographic model into an insolation model described by two variables as each pixels 1) slope and 2) slope angular orientation with respect to the pole. We then decomposed the illumination models and epithermal maps as a function of the insolation model and correlate the datasets.

Hydrogen Concentrations↗