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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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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Neural Networks to Find the Optimal Forcing for Offsetting the Anthropogenic Climate Change Effects

Abstract Of great relevance to climate engineering is the systematic relationship between the radiative forcing to the climate system and the response of the system, a relationship often represented by the linear response function (LRF) of the system. However, estimating the LRF often becomes an ill-posed inverse problem due to high-dimensionality and nonunique relationships between the forcing and response. Recent advances in machine learning make it possible to address the ill-posed inverse problem through regularization and sparse system fitting. Here, we develop a convolutional neural network (CNN) for regularized inversion. The CNN is trained using the surface temperature responses from a set of Green’s function perturbation experiments as imagery input data together with data sample densification. The resulting CNN model can infer the forcing pattern responsible for the temperature response from out-of-sample forcing scenarios. This promising proof of concept suggests a possible strategy for estimating the optimal forcing to negate certain undesirable effects of climate change. The limited success of this effort underscores the challenges of solving an inverse problem for a climate system with inherent nonlinearity. Significance Statement Predicting the climate response for a given climate forcing is a direct problem, while inferring the forcing for a given desired climate response is often an inverse, ill-posed, problem, posing a new challenge to the climate community. This study makes the first attempt to infer the radiative forcing for a given target pattern of global surface temperature response using a deep learning approach. The resulting deeply trained convolutional neural network inversion model shows promise in capturing the forcing pattern corresponding to a given surface temperature response, with a significant implication on the design of an optimal solar radiation management strategy for curbing global warming. This study also highlights the technical challenges that future research should prioritize in seeking feasible solutions to the inverse climate problem.

Ren, Huiying↗
NASA NTRS1976

Physiologic and anti-G suit performance data from YF-16 flight tests

Biomedical data were collected during high-G portions of 11 YF-16 test flights. Test pilots monitored revealed increased respiratory rate and volume, decreased tidal volume, and increased heart rate at higher G levels, with one pilot exhibiting various cardiac arrhythmias. Anti-G suit inflation and pressurization lags varied inversely with G-onset rate, and suit pressurization slope was near the design value.

Gillingham, K. K.↗
NASA NTRS1982

High-Lift Separated Flow About Airfoils

TRANSEP Calculates flow field about low-speed single-element airfoil at high-angle-of-attack and high-lift conditions with massive boundary-layer separation. TRANSEP includes effects of weak viscous interactions and can be used for subsonic/transonic airfoil design and analysis. The approach used in TRANSEP is based on direct-inverse method and its ability to use either displacement surface or pressure as airfoil boundary condition.

Carlson, L. A.↗
NASA NTRS1987

Recursive Robot-Arm Dynamics via Filtering and Smoothing

Forward and inverse dynamics solved using Kalman filtering and Bryson-Frazier smoothing. Dynamics of serial-link robot arm solved by using recursive techniques from linear filtering and smoothing theory. Solutions of dynamical equations give forces, moments, and accelerations at joints between links, and multilink inertia matrix and its inverse. Theoretical developments lay foundation for use of filtering and smoothing techniques in design of robot controls.

Rodriguez, Guillermo↗
NASA NTRS1987

A hybrid algorithm for transonic airfoil and wing design

The present method for the design of transonic airfoils and wings employs a predictor/corrector approach in which an analysis code calculates the flowfield for an initial geometry, then modifies it on the basis of the difference between calculated and target pressures. This allows the design method to be straightforwardly coupled with any existing analysis code, as presently undertaken with several two- and three-dimensional potential flow codes. The results obtained indicate that the method is robust and accurate, even in the cases of airfoils with strongly supercritical flow and shocks. The design codes are noted to require computational resources typical of current pure-inverse methods.

Campbell, Richard L.↗
NASA NTRS2010

Implementation and Evaluation of Multiple Adaptive Control Technologies for a Generic Transport Aircraft Simulation

Presented here is the evaluation of multiple adaptive control technologies for a generic transport aircraft simulation. For this study, seven model reference adaptive control (MRAC) based technologies were considered. Each technology was integrated into an identical dynamic-inversion control architecture and tuned using a methodology based on metrics and specific design requirements. Simulation tests were then performed to evaluate each technology s sensitivity to time-delay, flight condition, model uncertainty, and artificially induced cross-coupling. The resulting robustness and performance characteristics were used to identify potential strengths, weaknesses, and integration challenges of the individual adaptive control technologies

Campbell, Stefan F.↗
NASA NTRSDate not supplied

Examination of Unified Control Incorporating Generalized Control Allocation

Hybrid vehicles which combine vertical take off and landing with cruise configurations pose a unique challenge for control design and implementation. For this class of vehicle, successful control designs have historically broken the flight envelope into phases of flight and modified the control approach for each phase. This research approaches control in a unified way across the entire envelope utilizing a robust optimal design which provides effect or weighting then implemented in a generalized Affine Generalized Inverse control allocation algorithm. System performance for a Lift plus Cruise class vehicle is presented.

Unified Control,Control Allocation↗
DOE OSTI2024

Physics-Based Machine Learning Methods for U-235 Forensics Signatures

Signatures of low-intensity U-235 sources have been recently studied by utilizing a variety of machine learning (ML) classifiers using features derived from gamma spectral measurements collectedunder structured campaigns. Several ML classifiers, such as ensemble of tress and classification trees, revealed misleadingly-optimistic training error due to over-fitting, and furthermore,their performance is not directly relatable to the physical properties due to their data-driven, opaque designs. We present a regression-based ML method that first estimates the inverse distanceto the source and then utilizes a threshold to infer its presence, by representing the background as a source located at an infinite distance. For the inverse distance estimation, we study the ensembleof trees and Gaussian process regression methods, and a hyper parameter auto-tuning and selection method that employs five regression estimators. These methods avoid the over-fittingobserved in several ML classifiers, while providing the classification error nearly comparable to them based on independent test data. Their error is directly related to estimates of the inversephysical distance to source, and the precision of error determines the seperability property that determines the false alarm and missed detection rates. The property of monotonic decrease of thesource strength with increasing detector distance combined with Poisson distribution of measurements is utilized to analytically validate these methods by deriving the generalization equations ofunderlying regression methods.

Rao, Nageswara↗
DOE OSTI2024

Physics-Based Machine Learning Methods for U-235 Forensics Signatures

Signatures of low-intensity U-235 sources have been recently studied by utilizing a variety of machine learning (ML) classifiers using features derived from gamma spectral measurements collected under structured campaigns. Several ML classifiers, such as ensemble of tress and classification trees, revealed misleadingly-optimistic training error due to over-fitting, and furthermore, their performance is not directly relatable to the physical properties due to their data-driven, opaque designs. We present a regression-based ML method that first estimates the inverse distance to the source and then utilizes a threshold to infer its presence, by representing the background as a source located at an infinite distance. For the inverse distance estimation, we study the ensemble of trees and Gaussian process regression methods, and a hyper parameter auto-tuning and selection method that employs five regression estimators. These methods avoid the over-fitting observed in several ML classifiers, while providing the classification error nearly comparable to them based on independent test data. Their error is directly related to estimates of the inverse physical distance to source, and the precision of error determines the seperability property that determines the false alarm and missed detection rates. The property of monotonic decrease of the source strength with increasing detector distance combined with Poisson distribution of measurements is utilized to analytically validate these methods by deriving the generalization equations of underlying regression methods.

Rao, Nageswara↗
NASA NTRS2021

Computational Inference of Vibratory System with Incomplete Modal Information Using Parallel, Interactive and Adaptive Markov Chains

Inverse analysis of vibratory system is an important subject in fault identification, model updating, and robust design and control. It is challenging subject because 1) the problem is oftentimes underdetermined while the measurements are limited and/or incomplete; 2) many combinations of parameters may yield results that are similar with respect to actual response measurements; and 3) uncertainties inevitably exist. The aim of this research is to leverage upon computational intelligence through statistical inference to facilitate an enhanced, probabilistic framework using incomplete modal response measurement. This new framework is built upon efficient inverse identification through optimization, whereas Bayesian inference is employed to account for the effect of uncertainties. To overcome the computational cost barrier, we adopt Markov chain Monte Carlo (MCMC) to characterize the target function/distribution. Instead of using single Markov chain in conventional Bayesian approach, we develop a new sampling theory with multiple parallel, interactive and adaptive Markov chains and incorporate it into Bayesian inference. This can harness the collective power of these Markov chains to realize the concurrent search of multiple local optima. The number of required Markov chains and their respective initial model parameters are automatically determined via Monte Carlo simulation-based sample pre-screening followed by K-means clustering analysis. These enhancements can effectively address the aforementioned challenges in finite element inverse analysis. The validity of this framework is systematically demonstrated through case studies.

K Zhou↗
NASA NTRS1986

Inverse kinematic solution for near-simple robots and its application to robot calibration

This paper provides an inverse kinematic solution for a class of robot manipulators called near-simple manipulators. The kinematics of these manipulators differ from those of simple-robots by small parameter variations. Although most robots are by design simple, in practice, due to manufacturing tolerances, every robot is near-simple. The method in this paper gives an approximate inverse kinematics solution for real time applications based on the nominal solution for these robots. The validity of the results are tested both by a simulation study and by applying the algorithm to a PUMA robot.

Hayati, Samad A.↗
NASA NTRS1988

Development of automation and robotics for space via computer graphic simulation methods

A robot simulation system, has been developed to perform automation and robotics system design studies. The system uses a procedure-oriented solid modeling language to produce a model of the robotic mechanism. The simulator generates the kinematics, inverse kinematics, dynamics, control, and real-time graphic simulations needed to evaluate the performance of the model. Simulation examples are presented, including simulation of the Space Station and the design of telerobotics for the Orbital Maneuvering Vehicle.

Fernandez, Ken↗
NASA NTRS2012

Improving the Automatic Inversion of Digital Alouette/ISIS Ionogram Reflection Traces into Topside Electron Density Profiles

The topside sounders of the International Satellites for Ionospheric Studies (ISIS) program were designed as analog systems. The resulting ionograms were displayed on 35 mm film for analysis by visual inspection. Each of these satellites, launched between 1962 and 1971, produced data for 10 to 20 years. A number of the original telemetry tapes from this large data set have been converted directly into digital records. Software, known as the Topside Ionogram Scalar With True-Height (TOPIST) algorithm, has been produced and used for the automatic inversion of the ionogram reflection traces on more than 100,000 ISIS-2 digital topside ionograms into topside vertical electron density profiles Ne(h). Here we present some topside ionospheric solar cycle variations deduced from the TOPIST database to illustrate the scientific benefit of improving and expanding the topside ionospheric Ne(h) database. The profile improvements will be based on improvements in the TOPIST software motivated by direct comparisons between TOPIST profiles and profiles produced by manual scaling in the early days of the ISIS program. The database expansion will be based on new software designed to overcome limitations in the original digital topside ionogram database caused by difficulties encountered during the analog-to-digital conversion process in the detection of the ionogram frame sync pulse and/or the frequency markers. This improved and expanded TOPIST topside Ne(h) database will greatly enhance investigations into both short- and long-term ionospheric changes, e.g., the observed topside ionospheric responses to magnetic storms, induced by interplanetary magnetic clouds, and solar cycle variations, respectively.

Benson, Robert F.↗
NASA NTRS2003

Enhanced Mixing in a Rectangular Duct

An experimental investigation of the mixing of non-reacting opposed rows of jets injected normal to a confined rectangular crossflow has been conducted. Planar Mie-scattering was used to measure the time-average concentration distribution of the jet fluid in planes perpendicular to the duct axis. Particular emphasis was placed on the study of closely spaced orifice configurations applicable to the mixing zone of an RQL combustor. Baseline studies were performed of mixing under "ideal" conditions, i.e., plenum fed jets injecting into a crossflow uniform in velocity and turbulence intensity. In addition, more practical ("non-ideal") issues encountered during hardware design were also studied. As in other studies, mixing effectiveness, determined using a spatial unmixedness parameter based on the variance of mean jet concentration distributions, was found to be optimum when the spacing-to-duct-height ratio was inversely proportional to the square root of the jet-to-mainstream momentum-flux ratio. This relationship is suitable for design under ideal flow conditions. Inlet flow boundary conditions of the jet and approach flow (mainstream) were found to strongly influence mixing performance, but no attempt was made to determine optimum performance under non-ideal conditions. The tests performed do offer some guidance as to expected mixing behavior for several common variables likely to be imposed by hardware constraints. Additionally, in this study it was found that for rows of orifices with opposite centerlines inline, mixing was similar for blockages up to 89 percent (previous crossflow mixing studies concerned with dilution zone configurations, blockages were typically less than 50 percent). Lower levels of unmixedness were obtained as a function of downstream location when axial injection length was minimized. Mixing may be enhanced if orifice centerlines of opposed rows are staggered, but blockage must be =50 percent in this configuration. Round hole and "square" orifice shapes had similar performance. Other variations in orifice shape did not substantially augment overall mixing performance. Furthermore an isothermal mixing data set was generated and used by CFDRC as input to a NO(x) inference code.

Liscinsky, D. S.↗
NASA NTRS1984

A robust pseudo-inverse spectral filter applied to the Earth Radiation Budget Experiment (ERBE) scanning channels

Computer simulations of a least squares estimator operating on the ERBE scanning channels are discussed. The estimator is designed to minimize the errors produced by nonideal spectral response to spectrally varying and uncertain radiant input. The three ERBE scanning channels cover a shortwave band a longwave band and a ""total'' band from which the pseudo inverse spectral filter estimates the radiance components in the shortwave band and a longwave band. The radiance estimator draws on instantaneous field of view (IFOV) scene type information supplied by another algorithm of the ERBE software, and on a priori probabilistic models of the responses of the scanning channels to the IFOV scene types for given Sun scene spacecraft geometry. It is found that the pseudoinverse spectral filter is stable, tolerant of errors in scene identification and in channel response modeling, and, in the absence of such errors, yields minimum variance and essentially unbiased radiance estimates.

Avis, L. M.↗
DOE OSTI2024

Absolute band-edge energies are over-emphasized in the design of photoelectrochemical materials

The absolute band-edge potentials of semiconductors, i.e., the conduction-band minimum, valence-band maximum, and their relative positions to solution redox potentials, are often invoked as design principles for photoelectrochemical (PEC) devices, especially for particulate photocatalysts. Here we show that reliance on these criteria is not necessary and limits the exploration of materials that will advance the fields of photoelectrochemistry, photochemistry, and photocatalysis. We discuss how i) band-edge energies are not singular parameters and instead shift with pH, electrolyte type, and surface chemistry; ii) the free energy of electrons and holes in comparison to that of solution redox couples dictates overall reaction spontaneity and thus reactivity; and iii) favorable charge-transfer kinetics can occur even when the relevant electrolyte redox potential(s) appear ‘outside’ the bandgap, enabled by the inversion or accumulation of electronic charge at the semiconductor surface. As a result, this discussion informs design principles for photocatalyst systems engineering for both one-electron redox reactions as well as for more complex multi-electron transfer reactions (e.g, H 2 evolution, H 2 O oxidation, CO 2 reduction).

14 SOLAR ENERGY↗
NASA NTRS1985

Geodesy and gravity experiment in earth orbit using a superconducting gravity gradiometer

A superconducting gravity gradiometer is under development with NASA support for space application. It is planned that a sensitive three-axis gravity gradiometer will be flown in a low-altitude (about 160 km) polar orbit in the 1990's for the purpose of obtaining a high-resolution gravity map of the earth. The large twice-an-orbit term in the harmonic expansion of gravity coming from the oblateness of the earth can be analyzed to obtain a precision test of the inverse square law at a distance of 100-1000 km. In this paper, the design, operating principle, and performance of the superconducting gravity gradiometer are described. The concept of a gravity-gradiometer mission (GGM), which is in an initial stage of development is discussed. In particular, requirements that such a mission imposes on the design of the cryogenic spacecraft will be addressed.

Paik, H. J.↗