SEARCH · Search NASA

Results for “Knowledge acquisition”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 343 records · Page 19

All sources NASA NTRS DOE OSTI

DOE OSTI2023

ET-AL: Entropy-targeted active learning for bias mitigation in materials data

Growing materials data and data-driven informatics drastically promote the discovery and design of materials. While there are significant advancements in data-driven models, the quality of data resources is less studied despite its huge impact on model performance. In this work, we focus on data bias arising from uneven coverage of materials families in existing knowledge. Observing different diversities among crystal systems in common materials databases, we propose an information entropy-based metric for measuring this bias. To mitigate the bias, we develop an entropy-targeted active learning (ET-AL) framework, which guides the acquisition of new data to improve the diversity of underrepresented crystal systems. We demonstrate the capability of ET-AL for bias mitigation and the resulting improvement in downstream machine learning models. This approach is broadly applicable to data-driven materials discovery, including autonomous data acquisition and dataset trimming to reduce bias, as well as data-driven informatics in other scientific domains.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Enhanced Capabilities for Subcritical Experiments (ECSE) Risk Management Plan

Risk is a factor, element, constraint, or course of action that introduces an uncertainty of outcome that could impact project objectives. Risk is an inherent part of all activities, whether the activity is simple and small, or large and complex. Risk management is a process that identifies, evaluates, handles, and monitors risks that have the potential to affect project success. The risk management process spans the entire project, from its initiation to its successful completion and closeout, including both technical and programmatic (non-technical) risks. This Risk Management Plan (RMP) defines the process to be used for identifying, evaluating, handling, and monitoring risks as part of the overall management of the Enhanced Capabilities for Subcritical Experiments (ECSE) ‘Project’. Given the changing nature of the project environment, risk management is essentially an ongoing and iterative process, which applies the best efforts of a knowledgeable project staff to a suite of focused and prioritized concerns. The risk management process itself must be continually applied throughout the project life cycle. This document was prepared in accordance with DOE O 413.3B, Program and Project Management for the Acquisition of Capital Assets, its associated guide for risk management DOE G 413.3-7, Risk Management Guide, and LANL ADPM AP-350-204, Risk and Opportunity Management.

42 ENGINEERING↗

NASA NTRS2011

Crosscutting Development- EVA Tools and Geology Sample Acquisition

Exploration to all destinations has at one time or another involved the acquisition and return of samples and context data. Gathered at the summit of the highest mountain, the floor of the deepest sea, or the ice of a polar surface, samples and their value (both scientific and symbolic) have been a mainstay of Earthly exploration. In manned spaceflight exploration, the gathering of samples and their contextual information has continued. With the extension of collecting activities to spaceflight destinations comes the need for geology tools and equipment uniquely designed for use by suited crew members in radically different environments from conventional field geology. Beginning with the first Apollo Lunar Surface Extravehicular Activity (EVA), EVA Geology Tools were successfully used to enable the exploration and scientific sample gathering objectives of the lunar crew members. These early designs were a step in the evolution of Field Geology equipment, and the evolution continues today. Contemporary efforts seek to build upon and extend the knowledge gained in not only the Apollo program but a wealth of terrestrial field geology methods and hardware that have continued to evolve since the last lunar surface EVA. This paper is presented with intentional focus on documenting the continuing evolution and growing body of knowledge for both engineering and science team members seeking to further the development of EVA Geology. Recent engineering development and field testing efforts of EVA Geology equipment for surface EVA applications are presented, including the 2010 Desert Research and Technology Studies (Desert RATs) field trial. An executive summary of findings will also be presented, detailing efforts recommended for exotic sample acquisition and pre-return curation development regardless of planetary or microgravity destination.

Source record↗

NASA NTRS1995

Acquisition forecast: Fiscal year 1995

This volume includes projections of all anticipated FY95, and beyond, NASA contract actions above $25,000 that small and small disadvantaged businesses may be able to perform under direct contract with the government or as subcontractors. The forecast consolidates anticipated procurements at each NASA center into an agencywide report, with the aim of increasing industries' advance knowledge of NASA requirements and enhancing competition in contracting. Each center forecast report is divided into three principal categories of procurement: research and development, services, and supplies and equipment.

Source record↗

NASA NTRS1989

Imaging infrared: Scene simulation, modeling, and real image tracking; Proceedings of the Meeting, Orlando, FL, Mar. 30, 31, 1989

Various papers on scene simulation, modeling, and real image tracking using IR imaging are presented. Individual topics addressed include: tactical IR scene generator, dynamic FLIR simulation in flight training research, high-speed dynamic scene simulation in UV to IR spectra, development of an IR sensor calibration facility, IR celestial background scene description, transmission measurement of optical components at cryogenic temperatures, diffraction model for a point-source generator, silhouette-based tracking for tactical IR systems, use of knowledge in electrooptical trackers, detection and classification of target formations in IR image sequences, SMPRAD: simplified three-dimensional cloud radiance model, IR target generator, recent advances in testing of thermal imagers, generic IR system models with dynamic image generation, modeling realistic target acquisition using IR sensors in multiple-observer scenarios, and novel concept of scene generation and comprehensive dynamic sensor test.

Triplett, Milton J.↗

NASA NTRS2012

Use of Remote Sensing Data to Enhance NWS Storm Damage Toolkit

In the wake of a natural disaster such as a tornado, the National Weather Service (NWS) is required to provide a very detailed and timely storm damage assessment to local, state and federal homeland security officials. The Post ]Storm Data Acquisition (PSDA) procedure involves the acquisition and assembly of highly perishable data necessary for accurate post ]event analysis and potential integration into a geographic information system (GIS) available to its end users and associated decision makers. Information gained from the process also enables the NWS to increase its knowledge of extreme events, learn how to better use existing equipment, improve NWS warning programs, and provide accurate storm intensity and damage information to the news media and academia. To help collect and manage all of this information, forecasters in NWS Southern Region are currently developing a Storm Damage Assessment Toolkit (SDAT), which incorporates GIS ]capable phones and laptops into the PSDA process by tagging damage photography, location, and storm damage details with GPS coordinates for aggregation within the GIS database. However, this tool alone does not fully integrate radar and ground based storm damage reports nor does it help to identify undetected storm damage regions. In many cases, information on storm damage location (beginning and ending points, swath width, etc.) from ground surveys is incomplete or difficult to obtain. Geographic factors (terrain and limited roads in rural areas), manpower limitations, and other logistical constraints often prevent the gathering of a comprehensive picture of tornado or hail damage, and may allow damage regions to go undetected. Molthan et al. (2011) have shown that high resolution satellite data can provide additional valuable information on storm damage tracks to augment this database. This paper presents initial development to integrate satellitederived damage track information into the SDAT for near real ]time use by forecasters and decision makers.

Jedlove, Gary J.↗

NASA NTRS2022

Hybrid Model Based Approaches for Systems Health Management and Prognostics

This is a previously approved and published presentation. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Present achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision-making. In principle, data-driven approaches can replace expensive experimental test-setups as well as reduce the number of simulations needed to explore, e.g., the parametric space of a multi-parameter model. Nonetheless, the limitations of pure data-driven methods came to light rather quickly, at least for some industries. In many industrial applications, data acquisition is costly, and the volume of data that can be collected does not satisfy the requirements for effective model training and cross-validation. Therefore, some recent works in the area of machine learning is focusing on blending physics with data-driven algorithms, thus mitigating the drawbacks of the two approaches and emphasizing respective advantages. Partial physical knowledge of the problem can aid the learning process by “guiding” the algorithm towards efficient solutions that satisfy the physics driving the system behavior. The result is a hybrid modeling approach combining physical knowledge as well data-driven methods to develop a unified hybrid approach. A hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety-critical systems is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.

Prognostics↗

NASA NTRSDate not supplied

Hybrid Model Based Approaches for Systems Health Management and Prognostics

To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision making. In principle, data driven approaches can replace expensive experimental test-setups as well as reduce the number of simulations needed to explore, e.g., the parametric space of a multi-parameter model. Nonetheless, the limitations of pure data-driven methods came to light rather quickly, at least for some industries. In many industrial applications, data acquisition is costly, and the volume of data that can be collected does not satisfy the requirements for an effective model training and cross-validation. Therefore, some recent works in the area of machine learning is focusing on blending physics with data-driven algorithms, thus mitigating the drawbacks of the two approaches and emphasizing respective advantages. Partial physical knowledge of the problem can aid the learning process by “guiding” the algorithm towards efficient solutions that satisfy the physics driving the system behavior. The result is a hybrid modeling approach combining physical knowledge as well data driven methods to develop a unified hybrid approach. A hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.

Hybrid Modeling↗

NASA NTRSDate not supplied

Hybrid Approaches to Systems Health Management and Prognostics

Systems Health Management↗

NASA NTRS1989

Design of an active helicopter control experiment at the Princeton Rotorcraft Dynamics Laboratory

In an effort to develop an active control technique for reducing helicopter vibrations stemming from the main rotor system, a helicopter model was designed and tested at the Princeton Rotorcraft Dynamics Laboratory (PRDL). A description of this facility, including its latest data acquisition upgrade, are given. The design procedures for the test model and its Froude scaled rotor system are also discussed. The approach for performing active control is based on the idea that rotor states can be identified by instrumenting the rotor blades. Using this knowledge, Individual Blade Control (IBC) or Higher Harmonic Control (HHC) pitch input commands may be used to impact on rotor dynamics in such a way as to reduce rotor vibrations. Discussed here is an instrumentation configuration utilizing miniature accelerometers to measure and estimate first and second out-of-plane bending mode positions and velocities. To verify this technique, the model was tested, and resulting data were used to estimate rotor states as well as flap and bending coefficients, procedures for which are discussed. Overall results show that a cost- and time-effective method for building a useful test model for future active control experiments was developed. With some fine-tuning or slight adjustments in sensor configuration, prospects for obtaining good state estimates look promising.

Marraffa, Andrew M.↗

NASA NTRS2000

Acousto-Optic Imaging Spectrometers for Mars Surface Science

NASA's long term plan for Mars sample collection and return requires a highly streamlined approach for spectrally characterizing a landing site, documenting the mineralogical make-up of the site and guiding the collections of samples which represent the diversity of the site. Ideally, image data should be acquired at hundreds of VIS and IR wavelengths, in order to separately distinguish numerous anticipated species, using principal component analysis and linear unmixing. Cameras with bore-sighted point spectrometers can acquire spectra of isolated scene elements, but it requires 10(exp 2) to 10(exp 2) successive motions and precise relative pointing knowledge in order to create a single data cube which qualifies as a spectral map. These and other competing science objectives have to be accomplished within very short lander/rover operational lifetime (a few sols). True, 2-D imaging spectroscopy greatly speeds up the data acquisition process, since the spectra of all pixels in the scene are collected at once. This task can be accomplished with cameras that use electronically tunable acousto-optic tunable filters (AOTFs) as the optical tuning element. AOTFs made from TeO2 are now a mature technology, and operate at wavelengths from near-UV to about 5 microns. Because of incremental improvements in the last few years, present generation devices are rugged, radiation-hard and operate at temperatures down to at least 150K so they can be safely integrated into the ambient temperature optics of in-situ instruments such as planetary or small-body landers. They have been used for ground-based astronomy, and were also baselined for the ST-4 Champollion IR comet lander experiment (CIRCLE), prior to cancellation of the ST-4 mission last year. AIMS (for Acousto-optic Imaging spectrometer), is a prototype lander instrument which is being built at GSFC with support by the NASA OSS Advanced Technologies and Mission Studies, Mars Instrument Definition and Development Program (MIDP). AIMS is capable of tunable spectroscopic imaging of surface mineralogy, ices and dust between 0.5 and 2.4 microns, at a resolving power (lambda/delta lambda) which is typically several hundred. The design spatial resolution, similar to IMP and SSI, will allow mapping at scales down to about 1 cm.

Glenar, D. A.↗

DOE OSTI2022

Size Ranges of Magnetic Domain States in Tetrataenite

Paleomagnetic studies of meteorites provide unique constraints on the evolution of magnetic fields in the early solar system. These studies rely on the identification of magnetic minerals that can retain stable magnetizations over ≳4.5 billion years (Ga). The ferromagnetic mineral tetrataenite (γ''-Fe 0.5 Ni 0.5 ) is found in iron, stony-iron and chondrite meteorite groups. Nanoscale intergrowths of tetrataenite have been shown to carry records of paleomagnetic fields, although the effect of magnetostatic interactions on their magnetic remanence acquisition remains to be fully understood. Tetrataenite can also occur as isolated, non-interacting, nanoscale grains in many meteorite groups, although the paleomagnetic potential of these grains is particularly poorly understood. Here, we aim to improve our understanding of tetrataenite magnetization to refine our knowledge of existing paleomagnetic analyses and broaden the spectrum of meteorite groups that can be used for future paleomagnetic studies. We present the results of analytical calculations and micromagnetic modeling of isolated tetrataenite grains with various geometries. We find that tetrataenite forms a stable single domain state at grain lengths between 6 and ~160 nm dependent on its elongation. It also possesses a magnetization resistant to viscous remagnetization over the lifetime of the solar system at 293 K. At larger grain sizes, tetrataenite's lowest energy state is a lamellar two-domain state, stable at Ga-scale timescales. Unlike many other magnetic minerals, tetrataenite does not form a single-vortex domain state due to its large uniaxial anisotropy. Our results show that single domain and two-domain tetrataenite grains carry an extremely stable magnetization and therefore are promising for paleomagnetic studies.

58 GEOSCIENCES↗

NASA NTRS2013

The Challenges of Integrating Instrumentation with Inflatable Aerodynamic Decelerators

To realize the National Aeronautics and Space Administration s (NASA) goal of landing humans on Mars, development of technologies to facilitate the landing of heavy payloads are being explored. Current entry, decent, and landing technologies are not practical when utilizing these heavy payloads due to mass and volume constraints dictated by limitations imposed by current launch vehicle fairings. Therefore, past and present technologies are now being considered to provide a mass and volume efficient solution, including Inflatable Aerodynamic Decelerators (IADs) [1]. IAD ground and flight tests are currently being conducted to develop and characterize their performance under flight-like conditions. The integrated instrumentation systems, which are key to the performance characterization in each of these tests, have proven to be a challenge compared to the instrumentation of traditional rigid aeroshells. To overcome these challenges, flexible and embedded sensing systems have been developed, along with improved instrumenting techniques. This development opportunity faces many difficult aspects specific to inflatable structures in extreme environments. These include but are not limited to: physical flexibility, packaging, temperature, structural integration and data acquisition [2]. To better define the instrumentation challenges posed by IAD technology development, a survey was conducted to identify valuable measurements for ground and flight testing. From this survey many sensing technologies were explored, resulting in a down-selection to the most viable prospects. These systems were then iterated upon in design to determine the best integration techniques specific to a 3m and 6m stacked torus IAD. Each sensing system was then integrated and employed to support the IAD testing in the National Full-Scale Aerodynamics Complex 40 x 80 wind tunnel at NASA Ames Research Center in the summer of 2012. Another challenge that has been explored is the data acquisition of IAD sensing technologies. Traditionally all space based sensing systems transmit their data through a wired interface. This limits the amount of sensors able to be integrated within the IAD due to volume and routing restrictions of the supporting signal and excitation wires. To alleviate this situation, multiple wireless data acquisition technologies have been researched and developed through rapid prototyping efforts. The final custom multi-nodal wireless system utilized during the summer 2012 IAD test series consisted of four remote nodes and one receiving base station. The system reliably conditioned and acquired 20+ sensors over the course of the wind tunnel test series. These developments in wireless data acquisition techniques can eliminate the need for structural feedthroughs and reduce system mass associated with wiring and wire harnesses. This makes the utilization of flight instrumentation more attractive to future missions, which would result in further improved characterization of IAD technology, and overall, increased scientific knowledge regarding the response of inflatable structures to extreme entry environments. [

Swanson, Gregory T.↗

NASA NTRS1990

The JPL/KSC telerobotic inspection demonstration

An ASEA IRB90 robotic manipulator with attached inspection cameras was moved through a Space Shuttle Payload Assist Module (PAM) Cradle under computer control. The Operator and Operator Control Station, including graphics simulation, gross-motion spatial planning, and machine vision processing, were located at JPL. The Safety and Support personnel, PAM Cradle, IRB90, and image acquisition system, were stationed at the Kennedy Space Center (KSC). Images captured at KSC were used both for processing by a machine vision system at JPL, and for inspection by the JPL Operator. The system found collision-free paths through the PAM Cradle, demonstrated accurate knowledge of the location of both objects of interest and obstacles, and operated with a communication delay of two seconds. Safe operation of the IRB90 near Shuttle flight hardware was obtained both through the use of a gross-motion spatial planner developed at JPL using artificial intelligence techniques, and infrared beams and pressure sensitive strips mounted to the critical surfaces of the flight hardward at KSC. The Demonstration showed that telerobotics is effective for real tasks, safe for personnel and hardware, and highly productive and reliable for Shuttle payload operations and Space Station external operations.

Mittman, David↗

NASA NTRSDate not supplied

Merging Analytic Collaborative Frameworks with New Observing Strategies Toward a Digital Twin: Earth – Episodic Pulse Event Impacts on Ocean Carbon Cycle as an Example

Virtual representations of the Earth will allow us to address some of the most critical environmental issues of our time. Here, we show the first steps toward representation of riverine, estuarine, and coastal carbon processes to enable scenario driven “what-if” analyses of the carbon system and human footprint. Excess sediment and nutrient runoff from land-based human activities impact water quality and can pose serious threats to coastal and marine ecosystems. Episodic pulse events, such as extreme precipitation events, can increase the amount of nutrients entering estuaries and coastal regions, potentially leading to large phytoplankton blooms followed by anoxic conditions. Consequences of coastal runoff are predicted to increase with the higher intensity and frequency of extreme events. Beyond the threat to coastal ecosystems, recent findings suggest these episodic pulses might play a significant role for biological production influencing regional and global carbon fluxes and budgets. An improved understanding of these events through optimal, dynamic observing strategies will increase our knowledge of the land-ocean continuum and how regional events and nutrient fluxes affect the carbon cycle and ocean ecosystem. This conceptual framework enables focused science investigations by pairing data analytics and artificial intelligence tools (otherwise termed an Analytic Center Framework, ACF) with targeted measurement acquisition through distributed sensing and intelligent asset tasking (or New Observing Strategies, NOS). This NOS and ACF iterative approach acquires and integrates complementary and coincident satellite, in-situ and model data to build a more complete and in-depth picture of science phenomena. Specifically, Apache Science Data Analytic Platform (SDAP) is extended to incorporate relevant datasets for data access, harmonized analysis, and anomaly detection. When conditions are met for a likely pulse event, NASA’s D-SHIELD (Distributed Spacecraft with Heuristic Intelligence to Enable Logistical Decisions) tool is triggered to optimize asset overpass frequency and schedule observations for persistent monitoring. Targeted data is ingested by SDAP for enhanced investigation via iterative analysis until the trigger criteria is no longer met - steps toward a digital twin.

Laura Rogers↗

NASA NTRS2006

Star Tracker Based ATP System Conceptual Design and Pointing Accuracy Estimation

A star tracker based beaconless (a.k.a. non-cooperative beacon) acquisition, tracking and pointing concept for precisely pointing an optical communication beam is presented as an innovative approach to extend the range of high bandwidth (> 100 Mbps) deep space optical communication links throughout the solar system and to remove the need for a ground based high power laser as a beacon source. The basic approach for executing the ATP functions involves the use of stars as the reference sources from which the attitude knowledge is obtained and combined with high bandwidth gyroscopes for propagating the pointing knowledge to the beam pointing mechanism. Details of the conceptual design are presented including selection of an orthogonal telescope configuration and the introduction of an optical metering scheme to reduce misalignment error. Also, estimates are presented that demonstrate that aiming of the communications beam to the Earth based receive terminal can be achieved with a total system pointing accuracy of better than 850 nanoradians (3 sigma) from anywhere in the solar system.

star tracker↗

DOE OSTI2017

Feathermoss and epiphytic Nostoc cooperate differently: expanding the spectrum of plant–cyanobacteria symbiosis

Dinitrogen (N2)-fixation by cyanobacteria in symbiosis with feather mosses represents the main pathway of biological N input into boreal forests. Despite its significance, little is known about the gene repertoire needed for the establishment and maintenance of the symbiosis. To determine gene acquisitions or regulatory rewiring allowing cyanobacteria to form this symbiosis, we compared closely related Nostoc strains that were either symbiosis-competent or non-competent, using a proteogenomics approach and a unique experimental setup allowing for controlled chemical and physical contact between partners. Thirty-two protein families were only in the genomes of competent strains, including some never before associated with symbiosis. We identified conserved orthologs that were differentially expressed in competent strains, including gene families involved in chemotaxis and motility, NO regulation, sulfate/phosphate transport, sugar metabolism, and glycosyl-modifying and oxidative stress-mediating exoenzymes. In contrast to other cyanobacteria-plant symbioses, the moss-cyanobacteria epiphytic symbiosis is distinct, with the symbiont retaining motility and chemotaxis, and not modulating N-fixation, photosynthesis, GS-GOGAT cycle, and heterocyst formation. Our work expands our knowledge of plant cyanobacterial symbioses, provides an interaction model of this ecologically significant symbiosis, and suggests new currencies, namely nitric oxide and aliphatic sulfonates, may be involved in establishing and maintaining this symbiosis.

Environmental Molecular Sciences Laboratory↗

DOE OSTI2015

Nuclear Energy Infrastructure Database Description and User’s Manual

In 2014, the Deputy Assistant Secretary for Science and Technology Innovation initiated the Nuclear Energy (NE)–Infrastructure Management Project by tasking the Nuclear Science User Facilities, formerly the Advanced Test Reactor National Scientific User Facility, to create a searchable and interactive database of all pertinent NE-supported and -related infrastructure. This database, known as the Nuclear Energy Infrastructure Database (NEID), is used for analyses to establish needs, redundancies, efficiencies, distributions, etc., to best understand the utility of NE’s infrastructure and inform the content of infrastructure calls. The Nuclear Science User Facilities developed the database by utilizing data and policy direction from a variety of reports from the U.S. Department of Energy, the National Research Council, the International Atomic Energy Agency, and various other federal and civilian resources. The NEID currently contains data on 802 research and development instruments housed in 377 facilities at 84 institutions in the United States and abroad. The effort to maintain and expand the database is ongoing. Detailed information on many facilities must be gathered from associated institutions and added to complete the database. The data must be validated and kept current to capture facility and instrumentation status as well as to cover new acquisitions and retirements. This document provides a short tutorial on the navigation of the NEID web portal at NSUF-Infrastructure.INL.gov.

42 ENGINEERING↗