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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Physics-Guided Deep Learning for Complex System Health Management and Decision Making

The landscape of complex engineered systems is rapidly evolving, from smart manufacturing facilities to next-generation transportation vehicles. As these systems become increasingly sophisticated and interconnected, the need for advanced health management systems grows ever more critical. These systems must go beyond simple monitoring, actively predicting potential failures before they occur. This paradigm shift from fixed maintenance schedules to condition-based predictions is key to optimizing system performance, enhancing safety, and paving the way for autonomous decision-making across various industries. Whether in industrial processes, energy systems, or advanced transportation, the ability to anticipate and prevent failures is becoming a cornerstone of operational excellence. To accurately predict the future health of any complex system, knowledge of its current health state and future operational conditions is essential. Recent advancements in data-driven algorithms have generated growing interest in artificial intelligence for industrial applications. However, the limitations of pure data-driven methods, particularly in industries where data acquisition is costly and limited, have become apparent. This has led to a focus on blending physics with data-driven algorithms, mitigating the drawbacks of both approaches while emphasizing their respective advantages. This research proposes a novel framework for integrating physics-based performance models with deep learning algorithms for the prognostics of complex safety-critical systems. In this approach, physics-based models serve as a blueprint, capturing fundamental system behaviors, while deep learning algorithms, leveraging real-world sensor data, fill in gaps and identify subtle patterns indicative of potential problems. This hybrid methodology, utilizing techniques such as Physics-Informed Neural Networks (PINNs), offers a powerful solution for predicting system health. By fusing domain knowledge with data-driven insights, this approach promises more accurate, adaptable, and reliable models for health prediction. The resulting framework is versatile, applicable across various sectors including aerospace, manufacturing, and energy systems, ultimately contributing to safer, more efficient operations in our increasingly complex technological landscape.

Diagnostics↗
NASA NTRS1991

U.S. Air Force Scientific and Technical Information Program - The STINFO Program

The U.S. Air Force STINFO (Scientific and Technical Information) program has as its main goal the proper use of all available scientific and technical information in the development of programs. The organization of STINFO databases, the use of STINFO in the development and advancement of aerospace science and technology and the acquisition of superior systems at lowest cost, and the application to public and private sectors of technologies developed for military uses are examined. STINFO user training is addressed. A project for aerospace knowledge diffusion is discussed.

Blados, Walter R.↗
DOE OSTI2020

Outer membrane vesicles catabolize lignin-derived aromatic compounds in Pseudomonas putida KT2440

Lignin is an abundant and recalcitrant component of plant cell walls. While lignin degradation in nature is typically attributed to fungi, growing evidence suggests that bacteria also catabolize this complex biopolymer. However, the spatiotemporal mechanisms for lignin catabolism remain unclear. Improved understanding of this biological process would aid in our collective knowledge of both carbon cycling and microbial strategies to valorize lignin to value-added compounds. Here, we examine lignin modifications and the exoproteome of three aromatic–catabolic bacteria: Pseudomonas putida KT2440, Rhodoccocus jostii RHA1, and Amycolatopsis sp. ATCC 39116. P. putida cultivation in lignin-rich media is characterized by an abundant exoproteome that is dynamically and selectively packaged into outer membrane vesicles (OMVs). Interestingly, many enzymes known to exhibit activity toward lignin-derived aromatic compounds are enriched in OMVs from early to late stationary phase, corresponding to the shift from bioavailable carbon to oligomeric lignin as a carbon source. In vivo and in vitro experiments demonstrate that enzymes contained in the OMVs are active and catabolize aromatic compounds. Taken together, this work supports OMV-mediated catabolism of lignin-derived aromatic compounds as an extracellular strategy for nutrient acquisition by soil bacteria and suggests that OMVs could pote

biological funneling↗
DOE OSTI2025

Measurement of Close-in Ground Motion from an Underground Chemical Explosion

Understanding the geophysical response near an underground explosion is crucial for generating insights into the source and emplacement conditions that produce distinct observations in monitoring scenarios occurring at greater distances. Recently, Shot A of the Low Yield Nuclear Monitoring (LYNM) Physics Experiment 1 (PE1) series was conducted at the Nevada National Security Site to provide ground truth for subsurface explosion signal models. This experiment resulted in measuring near-source ground motion at distances ranging from 70 to 1000 m/kt with a 99% success rate, yielding high-fidelity knowledge of the near-field response that can serve as benchmarks for future numerical modeling and experiment planning. However, technical challenges exist in observing near-source phenomena while safeguarding sensitive data acquisition components from the detrimental effects of ground motion in the subsurface. This report outlines tools and techniques to address challenges associated with observing near-source accelerations and within the tunnel drift of the PE1 test bed. Additionally, we describe key systems designed with both modern advancements and legacy guidance to maximize the collection of high-quality ground motion data, which may be applied to constitutive and computational models, leading to new or improved understanding of the near- and far-field signals produced by underground explosions.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
NASA NTRS1994

Adaptive line enhancers for fast acquisition

Three adaptive line enhancer (ALE) algorithms and architectures - namely, conventional ALE, ALE with double filtering, and ALE with coherent accumulation - are investigated for fast carrier acquisition in the time domain. The advantages of these algorithms are their simplicity, flexibility, robustness, and applicability to general situations including the Earth-to-space uplink carrier acquisition and tracking of the spacecraft. In the acquisition mode, these algorithms act as bandpass filters; hence, the carrier-to-noise ratio (CNR) is improved for fast acquisition. In the tracking mode, these algorithms simply act as lowpass filters to improve signal-to-noise ratio; hence, better tracking performance is obtained. It is not necessary to have a priori knowledge of the received signal parameters, such as CNR, Doppler, and carrier sweeping rate. The implementation of these algorithms is in the time domain (as opposed to the frequency domain, such as the fast Fourier transform (FFT)). The carrier frequency estimation can be updated in real time at each time sample (as opposed to the batch processing of the FFT). The carrier frequency to be acquired can be time varying, and the noise can be non-Gaussian, nonstationary, and colored.

Yeh, H.-G.↗
NASA NTRS1994

Airborne differential absorption lidar system for measurements of atmospheric water vapor and aerosols

An airborne differential absorption lidar (DIAL) system has been developed at the NASA Langley Research Center for remote measurements of atmospheric water vapor (H2O) and aerosols. A solid-state alexandrite laser with a 1-pm linewidth and greater than 99.85% spectral purity was used as the on-line transmitter. Solid-state avalanche photodiode detector technology has replaced photomultiplier tubes in the receiver system, providing an average increase by a factor of 1.5-2.5 in the signal-to-noise ratio of the H2O measurement. By incorporating advanced diagnostic and data-acquisition instrumentation into other subsystems, we achieved additional improvements in system operational reliability and measurement accuracy. Laboratory spectroscopic measurements of H2O absorption-line parameters were performed to reduce the uncertainties in our knowledge of the absorption cross sections. Line-center H2O absorption cross sections were determined, with errors of 3-6%, for more than 120 lines in the 720-nm region. Flight tests of the system were conducted during 1989-1991 on the NASA Wallops Flight Facility Electra aircraft, and extensive intercomparison measurements were performed with dew-point hygrometers and H2O radiosondes. The H2O distributions measured with the DIAL system differed by less than 10% from the profiles determined with the in situ probes in a variety of atmospheric conditions.

Carter, Arlen F.↗
NASA NTRS2012

Autonomous Onboard Science Data Analysis for Comet Missions

Coming years will bring several comet rendezvous missions. The Rosetta spacecraft arrives at Comet 67P/Churyumov-Gerasimenko in 2014. Subsequent rendezvous might include a mission such as the proposed Comet Hopper with multiple surface landings, as well as Comet Nucleus Sample Return (CNSR) and Coma Rendezvous and Sample Return (CRSR). These encounters will begin to shed light on a population that, despite several previous flybys, remains mysterious and poorly understood. Scientists still have little direct knowledge of interactions between the nucleus and coma, their variation across different comets or their evolution over time. Activity may change on short timescales so it is challenging to characterize with scripted data acquisition. Here we investigate automatic onboard image analysis that could act faster than round-trip light time to capture unexpected outbursts and plume activity. We describe one edge-based method for detect comet nuclei and plumes, and test the approach on an existing catalog of comet images. Finally, we quantify benefits to specific measurement objectives by simulating a basic plume monitoring campaign.

comets↗
NASA NTRS1984

Prospects for three-dimensional projective and tomographic imaging radar networks

Results of a study demonstrating the feasibility of broadband and speckle-free projective imaging of a complex shaped scattering object in the 6-17 GHz range with centimeter resolution are presented. It is shown how angular, spectral, and polarization diversities can be combined in the data acquisition process with a unique target-derived reference technique to access the three-dimensional Fourier space of the scatterer cost-effectively. Imagea retrieval algorithms, based on the projection slice theorem and knowledge of object symmetry, are utilized in obtaining images of a model aircraft with near optical resolution. The implications for high-resolution three-dimensional tomographic imaging radar networks are discussed.

Farhat, N. H.↗
NASA NTRS2005

Smart Sensors' Role in Integrated System Health Management

During the last decade, there has been a major effort in the aerospace industry to reduce the cost per pond of payload and become competitive in the international market. Competition from Europe, Japan, and China has reduced this cost to almost a third from 1990 to 2000. This cost has leveled in recent years to an average price of around $12,000/pound of payload. One of NASA's goals is to promote the development of technologies to reduce this cost by a factor of 10 or more Exploration of space, specially manned exploration missions, involves very complex launch and flight vehicles, associated ground support systems, and extensive human support during all phases of the mission. When considering the Space Shuttle Program, we can see that vehicle and ground support systems' processing, operation, and maintenance represent a large percentage of the program cost and time. Reducing operating, processing and maintenance costs will greatly reduce the cost of Exploration programs. The Integrated System Health Management (ISHM) concept is one of the technologies that will help reduce these operating, processing and maintenance costs. ISHM is an integrated health monitoring system applicable to both flight and ground systems. It automatically and autonomously acquires information from sensors and actuators and processes that information using the ISHM-embedded knowledge. As a result, it establishes the health of the system based on the acquired information and its prior knowledge. When this concept is fully implemented, ISHM systems shall be able to perform failure prediction and remediation before actual hard failures occurs, preventing its costly consequences. Data sources, sensors, and their associated data acquisition systems, constitute the foundation of the system. A smart sensing architecture is required to support the acquisition of reliable, high quality data, required by the ISHM. A thorough definition of the smart sensor architectures, their embedded diagnostic agents, and communication protocols need to be established and standardized to allow the embedding and exchange of health information among sensors and ISHM. This workshop is aimed to foster the exchange of ideas and lessons learned between government, industry and academia to aid in the establishment of ISHM (and smart sensors) standards and guidelines as well as to identify present technology gaps that will have to be overcome to successfully achieve this goal.

Perotti, Jose M.↗
DOE OSTI2020

HIDES: Hybrid Intrusion Detector for Energy Systems

The establishment of a resilient electric grid accompanied by a secure communications network is an ongoing battle as advanced persistent threats continue to exploit existing vulnerabilities in legacy supervisory control and data acquisition system (SCADA) infrastructure. Traditional intrusion detection systems (IDSs) lack consistent performance because of the continuously evolving attack surface of SCADA systems. These shortcomings can be overcome by integrating logical system behavior, protocol-specific knowledge, and data-based learning to develop a comprehensive IDS solution. In this paper, we present a Hybrid Intrusion Detector for Energy Systems by integrating a network-based IDS, state-of-the-art machine learning-based IDS, and model-based IDS to detect unknown and stealthy cyberattacks targeting the SCADA networks. The proposed IDS uses synchrophasor measurements and cyber logs to learn patterns of different scenarios based on spatiotemporal behaviors of power systems. As a proof of concept, we implement and validate the proposed IDS by leveraging resources available at the National Renewable Energy Laboratory's Energy Systems Integration Facility test bed. Experimental results show promising performance in detecting cyberattacks while providing realtime visualization of power system measurements and cyber logs.

machine-learning intrusion detection system↗
NASA NTRS1989

Effect of earth albedo variation on the performance of spatial acquisition subsystem aboard a planetary spacecraft

Deep-space optical communication systems generally require the use of the sunlit earth as the pointing reference. For simple single-frame spatial acquisition processors, the uncertainties in earth albedo can result in an irreducible error in acquiring the spatial location of the receiver. Multiple frame processing algorithms can be used to estimate the earth albedo. The prior knowledge of the image shape and orientation can then be used to derive the location of the receiver.

Chen, Chien-Chung↗
NASA NTRS1993

CSTI Earth-to-orbit propulsion research and technology program overview

NASA supports a vigorous Earth-to-orbit (ETO) research and technology program as part of its Civil Space Technology Initiative. The purpose of this program is to provide an up-to-date technology base to support future space transportation needs for a new generation of lower cost, operationally efficient, long-lived and highly reliable ETO propulsion systems by enhancing the knowledge, understanding and design methodology applicable to advanced oxygen/hydrogen and oxygen/hydrocarbon ETO propulsion systems. Program areas of interest include analytical models, advanced component technology, instrumentation, and validation/verification testing. Organizationally, the program is divided between technology acquisition and technology verification as follows: (1) technology acquisition; and (2) technology verification.

Gentz, Steven J.↗
NASA NTRS1994

Use of SAR in Regional Methane Exchange Studies

Significant sources of uncertainty in global trace gas budgets are due to lack of knowledge concerning the areal and temporal extent of source and sink areas. Synthetic aperture radar (SAR) is particularly suited to studies of northern ecosystems because of its all-weather operating capability which enables the acquisition of seasonal data. As key controls on methane exchange, the ability to differentiate major vegetation communities, inundation, and leaf area index (LAI) with satellite and airborne SAR data would increase the accuracy and precision of regional and seasonal estimates of methane exchange. The utility of SAR data for monitoring key controls on methane emissions from Arctic and boreal ecosystems is examined.

Morrissey, L. A.↗
NASA NTRS2002

MAP Attitude Control System Design and Flight Performance

The Microwave Anisotropy Probe (MAP) is a follow-on to the Differential Microwave Radiometer (DMR) instrument on the Cosmic Background Explorer (COBE) spacecraft. To make a full-sky map of cosmic microwave background fluctuations, a combination fast spin and slow precession motion will be used that will cover the entire celestial sphere in six months. The spin rate should be an order of magnitude higher than the precession rate, and each rate should be tightly controlled. The sunline angle should be 22.5 +/- 0.25 deg. Sufficient attitude knowledge must be provided to yield instrument pointing to a standard deviation of 1.3 arc-minutes RSS three axes. In addition, the spacecraft must be able to acquire and hold the sunline at initial acquisition, and in the event of a failure. Finally. the spacecraft must be able to slew to the proper burn orientations and to the proper off-sunline attitude to start the compound spin. The design and flight performance of the Attitude Control System on MAP that meets these requirements will be discussed.

Andrews, S. F.↗
NASA NTRS2018

Educación Global

The International Space Station has a unique ability to capture the imaginations of both students and teachers worldwide. The presence of humans aboard the station provides a foundation for numerous educational activities aimed at capturing interest and motivating children towards the study of science, technology, engineering and mathematics (STEM). Projects such as the Amateur Radio on International Space Station (ARISS); Earth Knowledge Acquired by Middle School Students (EarthKAM); and Synchronized Position Hold, Engage, Reorient Experimental Satellites (SPHERES) Zero Robotics competition, among others, have allowed for global student, teacher and public access to space through student image acquisition and radio contacts with crew members. Projects like these and their accompanying educational materials are distributed to students around the world. Through the continued use of the station, we will challenge and inspire the next generation of scientists, engineers, writers, artists, politicians and explorers.

Lopez, Erik↗
NASA NTRS1990

A Thermal Expert System (TEXSYS) development overview - AI-based control of a Space Station prototype thermal bus

A knowledge-based control system for real-time control and fault detection, isolation and recovery (FDIR) of a prototype two-phase Space Station Freedom external thermal control system (TCS) is discussed in this paper. The Thermal Expert System (TEXSYS) has been demonstrated in recent tests to be capable of both fault anticipation and detection and real-time control of the thermal bus. Performance requirements were achieved by using a symbolic control approach, layering model-based expert system software on a conventional numerical data acquisition and control system. The model-based capabilities of TEXSYS were shown to be advantageous during software development and testing. One representative example is given from on-line TCS tests of TEXSYS. The integration and testing of TEXSYS with a live TCS testbed provides some insight on the use of formal software design, development and documentation methodologies to qualify knowledge-based systems for on-line or flight applications.

Glass, B. J.↗
DOE OSTI2025

SANE: strategic autonomous non-smooth exploration for multiple optima discovery in multi-modal and non-differentiable black-box functions

Both computational and experimental material discovery bring forth the challenge of exploring multidimensional and multimodal parameter spaces, such as phase diagrams of Hamiltonians with multiple interactions, composition spaces of combinatorial libraries, material structure image spaces, and molecular embedding spaces. Often these systems are black-boxes and time-consuming to evaluate, which resulted in strong interest towards active learning methods such as Bayesian optimization (BO). However, these systems are often noisy which make the black box function severely multi-modal and non-differentiable, where a vanilla BO can get overly focused near a single or faux optimum, deviating from the broader goal of scientific discovery. To address these limitations, here we developed Strategic Autonomous Non-Smooth Exploration (SANE) to facilitate an intelligent Bayesian optimized navigation with a proposed cost-driven probabilistic acquisition function to find multiple global and local optimal regions, avoiding the tendency to becoming trapped in a single optimum. To distinguish between a true and false optimal region due to noisy experimental measurements, a human (domain) knowledge driven dynamic surrogate gate is integrated with SANE. We implemented the gate-SANE into pre-acquired piezoresponse spectroscopy data of a ferroelectric combinatorial library with high noise levels in specific regions, and piezoresponse force microscopy (PFM) hyperspectral data. SANE demonstrated better performance than classical BO to facilitate the exploration of multiple optimal regions and thereby prioritized learning with higher coverage of scientific values in autonomous experiments. Our work showcases the potential application of this method to real-world experiments, where such combined strategic and human intervening approaches can be critical to unlocking new discoveries in autonomous research.

Biswas, Arpan [University of Tennessee, Knoxville,↗