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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Model Based Approaches for Fault Detection, Prognostics, Decision Making in Complex Systems

The presentation discusses application of model based approaches to complex systems. The model is composed of physics-derived and empirical equations, integrated with connected networks that are strategically placed within the model to substitute equations that are subject to large uncertainty. Polynomial fit driven by heuristics or empirical observations can be substituted by more flexible networks that can minimize the error between model predictions and observations without being restricted to a predefined functional form. This modeling strategy allows training of networks deep inside the model and unknown parameters in a single learning stage.

Physics Informed↗
NASA NTRS2010

The Value of Identifying and Recovering Lost GN&C Lessons Learned: Aeronautical, Spacecraft, and Launch Vehicle Examples

Within the broad aerospace community the importance of identifying, documenting and widely sharing lessons learned during system development, flight test, operational or research programs/projects is broadly acknowledged. Documenting and sharing lessons learned helps managers and engineers to minimize project risk and improve performance of their systems. Often significant lessons learned on a project fail to get captured even though they are well known 'tribal knowledge' amongst the project team members. The physical act of actually writing down and documenting these lessons learned for the next generation of NASA GN&C engineers fails to happen on some projects for various reasons. In this paper we will first review the importance of capturing lessons learned and then will discuss reasons why some lessons are not documented. A simple proven approach called 'Pause and Learn' will be highlighted as a proven low-impact method of organizational learning that could foster the timely capture of critical lessons learned. Lastly some examples of 'lost' GN&C lessons learned from the aeronautics, spacecraft and launch vehicle domains are briefly highlighted. In the context of this paper 'lost' refers to lessons that have not achieved broad visibility within the NASA-wide GN&C CoP because they are either undocumented, masked or poorly documented in the NASA Lessons Learned Information System (LLIS).

Dennehy, Cornelius J.↗
NASA NTRS1982

IAC control system analysis development

The MultiOptimal Differential Equation Language (MODEL) is described. It provides a means for generating numerical solutions to systems of differential equations using a digital computer. The notation of this language is similar to that usually used in describing physical systems by differential equations. Thus, the learning process is simplified, programming becomes easier, and debugging is more readily accomplished. Programs written in the MultiOptimal Differential Equation Language are machine translated into FORTRAN 4 code which is optimal in several respects. The interactive version of MODEL makes use of interactive system routines so that the user may observe the solution as it is being generated and interact with the program in a manner similar to that associated with analog simulation. The DISCOS-Control version of the MODEL simulation language is used to describe the control system for a plant which is modelled by the DISCOS program. DISCOS plant variables may be referenced in the control system description and all the sensor signals, coupling torques, momentum devices and external loads are automatically linked to the DISCOS plant model.

Frisch, H. P.↗
NASA NTRS1985

Asteroid Collisional Evolution Studies

Understanding asteroid collisional evolution is important for characterizing the physical state of asteroids today and for learning about the processes that acted in this region of the solar system early in its history. The collisional outcome algorithm in the numerical simulation of asteroid evolution was revised to reflect pressure-strengthening. Asteroid collisions are now treated as a distribution of oblique impacts rather than as only head-on collisions. The initial and evolved size distribution of a plausible asteroid population is compared with the observed size distribution. Asteroid accretion times and reconstruction of the primordial solar nebula suggest that there was significantly more mass in this part of the solar system when the asteroids were accreting.

Davis, D. R.↗
NASA NTRS2002

Stellar Occultation Studies of Pluto, Triton, Charon, and Chiron

Bodies inhabiting the outer solar system are of interest because, due to the colder conditions, they exhibit unique physical processes. Also, some of the lessons learned from them can be applied to understanding what occurred in the outer solar system during its formation and early evolution. The thin atmospheres of Pluto and Triton have structure that is not yet understood, and they have been predicted to undergo cataclysmic seasonal changes. Charon may have an atmosphere - we don't know. Chiron exhibits cometary activity so far from the sun (much further than most comets), so that H2O sublimation cannot be the driving mechanism. Probing these bodies from Earth with a spatial resolution of a few kilometers can be accomplished only with the stellar occultation technique. In this program we find and predict stellar occultation events by small outer-solar system bodies and then attempt observations of the ones that can potentially answer interesting questions. We also develop new methods of data analysis for occultations and secure other observations that are necessary for interpretation of the occultation data.

Elliot, James L.↗
NASA NTRS1994

The excitability of plant cells: with a special emphasis on characean internodal cells

This review describes the basic principles of electrophysiology using the generation of an action potential in characean internodal cells as a pedagogical tool. Electrophysiology has proven to be a powerful tool in understanding animal physiology and development, yet it has been virtually neglected in the study of plant physiology and development. This review is, in essence, a written account of my personal journey over the past five years to understand the basic principles of electrophysiology so that I can apply them to the study of plant physiology and development. My formal background is in classical botany and cell biology. I have learned electrophysiology by reading many books on physics written for the lay person and by talking informally with many patient biophysicists. I have written this review for the botanist who is unfamiliar with the basics of membrane biology but would like to know that she or he can become familiar with the latest information without much effort. I also wrote it for the neurophysiologist who is proficient in membrane biology but knows little about plant biology (but may want to teach one lecture on "plant action potentials"). And lastly, I wrote this for people interested in the history of science and how the studies of electrical and chemical communication in physiology and development progressed in the botanical and zoological disciplines.

NASA Discipline Plant Biology↗
NASA NTRS2005

[Stellar Occultation Studies of Small Bodies in the Outer Solar System: Accomplishments, Status, and Plans]

Bodies residing in the outer solar system exhibit unique physical processes, and some of the lessons learned from them can be applied to understanding what occurred in the outer solar system during its formation and early evolution. Pluto, the largest known Kuiper Belt object (KBO), and its near twin Triton--an ex-KBO that has been captured by Neptune--have nitrogen atmospheres that are in vapor-pressure equilibrium with surface ice. These atmospheres are most sensitively probed from Earth by the technique of Stellar occultations, which can provide the temperature and pressure profiles of these atmospheres at a spatial resolution of a few kilometers. Recent results from occultations show that the surface pressure of Triton's atmosphere has been increasing and that the shape of the atmosphere deviates from its expected spherical figure. With the occultation technique we can also learn the sizes of smaller bodies that have formed in the outer solar system: Charon, the Centaurs, and KBOs. Our proposed program involves identifying occultation candidates, predicting occultations, observing occultations, analysis of the data, and synthesis of the occultation results with other data. The main goals for our proposed work are to (i) further observe occultations by Triton with the objectives of understanding its pressure changes, distortion, and enigmatic thermal structure (ii) determine whether the abrupt drop in Pluto's stellar occultation light curve is caused by a sharp thermal gradient near its surface or by atmospheric haze, (iii) further observations to characterize the potential collapse of Pluto's atmosphere as it recedes from the sun (information that should be of interest to the Pluto-Kuiper Express), ( iv ) determine Charon's radius more accurately than can be done with the mutual events to derive a better estimate of Charon's density, and ( v ) directly determine the size (and albedo) of Centaurs with the goal of more accurately estimating the sizes of KBOS.

Elliott, James↗
NASA NTRS2007

Learning Grasp Strategies Composed of Contact Relative Motions

Of central importance to grasp synthesis algorithms are the assumptions made about the object to be grasped and the sensory information that is available. Many approaches avoid the issue of sensing entirely by assuming that complete information is available. In contrast, this paper proposes an approach to grasp synthesis expressed in terms of units of control that simultaneously change the contact configuration and sense information about the object and the relative manipulator-object pose. These units of control, known as contact relative motions (CRMs), allow the grasp synthesis problem to be recast as an optimal control problem where the goal is to find a strategy for executing CRMs that leads to a grasp in the shortest number of steps. An experiment is described that uses Robonaut, the NASA-JSC space humanoid, to show that CRMs are a viable means of synthesizing grasps. However, because of the limited amount of information that a single CRM can sense, the optimal control problem may be partially observable. This paper proposes expressing the problem as a k-order Markov Decision Process (MDP) and solving it using Reinforcement Learning. This approach is tested in a simulation of a two-contact manipulator that learns to grasp an object. Grasp strategies learned in simulation are tested on the physical Robonaut platform and found to lead to grasp configurations consistently.

Platt, Robert, Jr.↗
NASA NTRS2016

Space Launch System Vibration Analysis Support

The ultimate goal for my efforts during this internship was to help prepare for the Space Launch System (SLS) integrated modal test (IMT) with Rodney Rocha. In 2018, the Structural Engineering Loads and Dynamics Team will have 10 days to perform the IMT on the SLS Integrated Launch Vehicle. After that 10 day period, we will have about two months to analyze the test data and determine whether the integrated vehicle modes/frequencies are adequate for launching the vehicle. Because of the time constraints, NASA must have newly developed post-test analysis methods proven well and with technical confidence before testing. NASA civil servants along with help from rotational interns are working with novel techniques developed and applied external to Johnson Space Center (JSC) to uncover issues in applying this technique to much larger scales than ever before. We intend to use modal decoupling methods to separate the entangled vibrations coming from the SLS and its support structure during the IMT. This new approach is still under development. The primary goal of my internship was to learn the basics of structural dynamics and physical vibrations. I was able to accomplish this by working on two experimental test set ups, the Simple Beam and TAURUS-T, and by doing some light analytical and post-processing work. Within the Simple Beam project, my role involves changing the data acquisition system, reconfiguration of the test set up, transducer calibration, data collection, data file recovery, and post-processing analysis. Within the TAURUS-T project, my duties included cataloging and removing the 30+ triaxial accelerometers, coordinating the removal of the structure from the current rolling cart to a sturdy billet for further testing, preparing the accelerometers for remounting, accurately calibrating, mounting, and mapping of all accelerometer channels, and some testing. Hammer and shaker tests will be performed to easily visualize mode shapes at low frequencies. Short analytical projects using MATLAB were also assigned to aid in research efforts. These included integration of acceleration data for comparison to measured displacement data. Laplace and Fourier transforms were also investigated to determine viability as a method of modal decoupling. In addition to these projects, I was also able contribute work that would benefit future interns and the division as a whole. I gave a short presentation and answered questions to aid in the recruitment of subsequent interns and co-ops for the division. I also assisted in revisions and additions to Intern/Co-Op Handbook to provide incoming employees with background information on the organization they are about to work for. I further developed tutorial on Pulse software, which was used for data acquisition for both experiments and will be helpful to interns and engineers that may be unfamiliar to the software. I gained a diverse range of experience throughout my internship. I was introduced to advanced dynamics and analytical techniques. This was through new experience with both hands on experimentation and analytical post processing methods. I was exposed to the benefits of interdepartmental collaboration and developed stronger skills in time management by coordinating two different tests at once. This internship provided an excellent opportunity to see how engineering theories applied to real life scenarios, and an introduction to how NASA/JSC solves technical problems.

Johnson, Katie↗
NASA NTRS2020

The Scientific Value of Returned Samples

Most of the materials in the universe are so distant or inaccessible that the only way we can study them is remotely using various types of telescopes. However, in some cases we can study these materials directly because the samples become physically available to us. Some samples come to us of their own accord in the form of meteorites and cosmic dust. In other cases we have to work hard to carry out sample return missions like Apollo, Stardust, OSIRIS-REx, Hayabusa, and Hayabusa2 to go get the samples ourselves. Once samples are physically available in terrestrial laboratories, we can learn details about their compositions and histories that could never be established by remote observations. As part of this talk, the acquisition of samples in the form of meteorites from Antarctica, cosmic dust from the stratosphere, and comet and asteroid samples from spacecraft missions will be discussed and a few example of the scientific value of such samples will be presented.

Sandford, Scott↗
NASA NTRSDate not supplied

The Unique Scientific Value of Returned Samples

Most of the materials in the universe are so distant or inaccessible that the only way we can study them is remotely using various types of telescopes. However, in some cases we can study these materials directly because the samples become physically available to us. Some samples come to us of their own accord in the form of meteorites and cosmic dust. In other cases we have to work hard to carry out sample return missions like Apollo, Stardust, OSIRIS-REx, Hayabusa, and Hayabusa2 in order to get the samples ourselves. Once samples are physically available in terrestrial laboratories, we can learn details about their compositions and histories that could never be established by remote observations. This talk will highlight some of the unique scientific advances that can be made through the study of extraterrestrial materials, and will describe the various ways in which samples become available for study, with a focus on the acquisition of samples by sample return spacecraft missions. Aspects of NASA’s Stardust comet sample return mission and JAXA’s Hayabusa asteroid sample return mission will be highlighted and scientific highlights of these missions will be discussed. Finally, the presentation will end with an overview of the current status of NASA’s OSIRIS-Rex mission, which will is currently at Asteroid (101955) Bennu and will be returning samples to Earth in 2023.

Extraterrestrial Samples↗
NASA NTRS2023

Toward Physics-informed Neural Networks for 3D Multi-layer Cloud Mask Reconstruction

Three-dimensional (3D) cloud retrievals are critical for understanding their impact on climate and other applications such as aviation safety, weather prediction, and remote sensing. However, obtaining high-resolution and accurate vertical representation of clouds remains unsolved due to the limitations imposed by satellite instrumentation, viewing conditions, and the complexity of cloud dynamics. Cloud masks are essential for comprehending various cloud vertical properties, but deriving accurate 3D cloud masks from 2D satellite imagery data is a challenging task. To tackle these challenges, we introduce a physics-informed loss function for training deep learning models that can extend 2D cloud images into 3D cloud masks. The proposed loss, called CloudMask Loss, is composed of two domain knowledge-informed loss terms: one for evaluating cloud position and thickness, and the other for measuring the number of layers. By combining these loss terms, we improve the trainability of the deep learning models for more accurate and meaningful results. We apply the proposed loss function to different neural networks and demonstrate significant improvements in multi-layer cloud mask reconstruction. Utilizing the same neural network architecture, our proposed loss outperforms standard binary crossentropy loss in terms of multi-layer cloud classification accuracy, number of layers accuracy, and thickness mean absolute error (MAE). The proposed loss function can be readily integrated into various neural network architectures, resulting in substantial performance gains in 3D cloud mask generation.

multi-layer clouds↗
NASA NTRS2006

Lessons from the GP-B Experience for Future Fundamental Physics Missions in Space

Gravity Probe B launched in April 2004 and completed its science data collection in September 2005, with the objective of sub-milliarcsec measurement of two General Relativistic effects on the spin axis orientation of orbiting gyroscopes. Much of the technology required by GP-B has potential application in future missions intended to make precision measurements. The philosophical approach and experiment design principles developed for GP-B are equally adaptable to these mission concepts. This talk will discuss GP-B's experimental approach and the technological and philosophical lessons learned that apply to future experiments in fundamental physics. Measurement of fundamental constants to high precision, probes of short-range forces, searches for equivalence principle violations, and detection of gravitational waves are examples of concepts and missions that will benefit kern GP-B's experience.

Kolodziejczak, Jeffery↗
NASA NTRSDate not supplied

Advancing NASA SatCORPS Global Data Products with Cloud Computing and Machine Learning

Operational satellite imager radiances are valuable for deriving many different physical parameters that can be used for a variety of weather, aviation, and energy applications. The NASA Satellite ClOud and Radiation Property retrieval System (SatCORPS) applies a suite of algorithms to meteorological satellite data to provide cloud properties, radiative fluxes and other parameters on a global scale. The use of cloud computing has enabled recent enhancements to process a constellation of geostationary satellites at higher spatiotemporal resolutions than previously possible that meet low latency and near real-time needs. Data taken from Meteosat-8 and -11, Himawari, GOES-16, and -17 are processed and combined with operational polar orbiting satellite data and composited on a 3-km grid to provide global coverage. To improve the utility of the data products, machine learning and other innovative methods are applied in various ways to help minimize data product uncertainties under the most challenging conditions and to improve their consistency at all times of day. An update on recent SatCORPS enhancements is presented, highlighting the community benefits achieved with the use of cloud computing and machine learning.

William L Smith↗
NASA NTRSDate not supplied

Predicting Melt Properties Using Atomistic Simulations With A Highly Accurate Physically Informed Neural Network Interatomic Potential

The use of a recently developed machine learning (ML) interatomic potential for molecular dynamics simulations of aluminum melt properties will be presented. Such properties are critical for process modeling in additive manufacturing, including the melt pool size, solidification, and formation of solidification microstructures. Direct first-principles modeling of these processes is computationally prohibitive whereas simulations employing ML potentials combine the high accuracy of quantum-mechanical methods with high computational speeds. The physically-informed neural network (PINN) method used herein, integrates a high-dimensional regression implemented by an artificial neural network with a physics-based bond-order interatomic potential. PINN potentials can accurately reproduce many properties of aluminum in both crystalline-solid and liquid phases. We examine the accuracy of a PINN Al potential in predicting the density, self-diffusivity, viscosity, and the tension of the liquid surface and liquid-solid interfaces. Comparison with experimental data and ab initio molecular dynamics calculations shows very good agreement for all properties tested.

molecular dynamics↗
NASA NTRS1990

Growth and properties of Hg-based quantum well structures and superlattices

An overview of the properties of HgTe-CdTe quantum well structures and superlattices (SL) is presented. These new quantum structures are candidates for use as new long wavelength infrared (LWIR) and very long wavelength infrared (VLWIR) detectors, as well as for other optoelectronic applications. Much has been learned within the past two years about the physics of such structures. The valence band offset has been determined to be approx. 350 meV, independent of temperature. The occurrence of electron and hole mobilities in excess of 10(exp 5)cm(exp 2)/V center dot s is now understood on the basis of SL band structure calculations. The in-plane and out-of-plane electron and hole effective masses have been measured and interpreted theoretically for HgTe-CdTe superlattices. Controlled substitutional doping of superlattices has recently been achieved at North Carolina State University (NCSU), and modulation-doped SLs have now been successfully grown and studied. Most recently, a dramatic lowering of the growth temperature of Hg-based quantum well structure and SLs (to approx. 100 C) has been achieved by means of photoassisted molecular beam epitaxy (MBE) at NCSU. A number of new devices have been fabricated from these doped multilayers.

Schetzina, J. F.↗
NASA NTRS1990

Modeling reality

Although powerful computers have allowed complex physical and manmade hardware systems to be modeled successfully, we have encountered persistent problems with the reliability of computer models for systems involving human learning, human action, and human organizations. This is not a misfortune; unlike physical and manmade systems, human systems do not operate under a fixed set of laws. The rules governing the actions allowable in the system can be changed without warning at any moment, and can evolve over time. That the governing laws are inherently unpredictable raises serious questions about the reliability of models when applied to human situations. In these domains, computers are better used, not for prediction and planning, but for aiding humans. Examples are systems that help humans speculate about possible futures, offer advice about possible actions in a domain, systems that gather information from the networks, and systems that track and support work flows in organizations.

Denning, Peter J.↗