SEARCH · Engineering Papers

Results for “Operational reliability”

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 1,225 records · Page 68

All sources NASA NTRS DOE OSTI

DOE OSTI2020

A Review of Machine Learning Applications in Power System Resilience

The integration of power electronics enabled devices and the high penetration of renewable energy drastically increase the complexity of power system operation and control. Power systems are still vulnerable to large-scale blackouts caused by extreme natural events or man-made attacks. With the recent development in artificial intelligence technique, machine learning has shown a processing ability in computational, perceptual and cognitive intelligence. It is an urgent challenge to integrate the advanced machine learning technology and large amount of real-time data from wide area measurement systems and intelligent electronic devices, in order to effectively enhance power system resilience and ensure the reliable and secure operation of power systems. Therefore, this paper aims to systematically review the existing application of machine learning methods on power system resilience enhancement, to expand the interest of researchers and scholars in this topic, and to jointly promote the application of artificial intelligence in the field of power systems.

Deep Learning↗

NASA NTRS1993

Space propulsion

Lewis Research Center is developing broad-based new technologies for space chemical engines to satisfy long-term needs of ETO launch vehicles and other vehicles operating in and beyond Earth orbit. Specific objectives are focused on high performance LO2/LH2 engines providing moderate thrusts of 7,5-200 klb. This effort encompasses research related to design analysis and manufacturing processes needed to apply advanced materials to subcomponents, components, and subsystems of space-based systems and related ground-support equipment. High-performance space-based chemical engines face a number of technical challenges. Liquid hydrogen turbopump impellers are often so large that they cannot be machined from a single piece, yet high stress at the vane/shroud interface makes bonding extremely difficult. Tolerances on fillets are critical on large impellers. Advanced materials and fabricating techniques are needed to address these and other issues of interest. Turbopump bearings are needed which can provide reliable, long life operation at high speed and high load with low friction losses. Hydrostatic bearings provide good performance, but transients during pump starts and stops may be an issue because no pressurized fluid is available unless a separate bearing pressurization system is included. Durable materials and/or coatings are needed that can demonstrate low wear in the harsh LO2/LH2 environment. Advanced materials are also needed to improve the lifetime, reliability and performance of other propulsion system elements such as seals and chambers.

Kazaroff, John M.↗

NASA NTRS1981

Report by the Aerospace Safety Advisory Panel

The process of preparation for the first two shuttle flights was observed and information from both flights was gathered in order to confirm the concept and performance of the major elements of the space transportation system. To achieve truly operational operating safety, regularity, and minimum practical cost, the organization of efforts between the R&D community and any transportation service organization should be clearly separated with the latter organization assuming responsibilities for marketing its services; planning and acquiring prime hardware and spares; maintainance; certification of procedures; training; and creation of requirements for future development. A technical audit of the application of redundancy concepts to shuttle systems is suggested. The state of the art of space transportation hardware suggests that a number of concept changes may improve reliability, costs, and operational safety. For the remaining R&D flights, it is suggested that a redline audit be made of limits that should not be exceeded for ready to launch.

Source record↗

NASA NTRS2011

Cryogenic Behavior of the High Temperature Crystal Oscillator PX-570

Microprocessors, data-acquisition systems, and electronic controllers usually require timing signals for proper and accurate operation. These signals are, in most cases, provided by circuits that utilize crystal oscillators due to availability, cost, ease of operation, and accuracy. Stability of these oscillators, i.e. crystal characteristics, is usually governed, amongst other things, by the ambient temperature. Operation of these devices under extreme temperatures requires, therefore, the implementation of some temperature-compensation mechanism either through the manufacturing process of the oscillator part or in the design of the circuit to maintain stability as well as accuracy. NASA future missions into deep space and planetary exploration necessitate operation of electronic instruments and systems in environments where extreme temperatures along with wide-range thermal swings are countered. Most of the commercial devices are very limited in terms of their specified operational temperature while very few custom-made and military-grade parts have the ability to operate in a slightly wider range of temperature. Thus, it is becomes mandatory to design and develop circuits that are capable of operation efficiently and reliably under the space harsh conditions. This report presents the results obtained on the evaluation of a new (COTS) commercial-off-the-shelf crystal oscillator under extreme temperatures. The device selected for evaluation comprised of a 10 MHz, PX-570-series crystal oscillator. This type of device was recently introduced by Vectron International and is designed as high temperature oscillator [1]. These parts are fabricated using proprietary manufacturing processes designed specifically for high temperature and harsh environment applications [1]. The oscillators have a wide continuous operating temperature range; making them ideal for use in military and aerospace industry, industrial process control, geophysical fields, avionics, and engine control. They exhibit low jitter and phase noise, consume little power, and are suited for high shock and vibration applications. The unique package design of these crystal oscillators offers a small ceramic package footprint, as well as providing both through-hole mounting and surface mount options.

Patterson, Richard↗

NASA NTRS2008

Sensor Selection and Data Validation for Reliable Integrated System Health Management

For new access to space systems with challenging mission requirements, effective implementation of integrated system health management (ISHM) must be available early in the program to support the design of systems that are safe, reliable, highly autonomous. Early ISHM availability is also needed to promote design for affordable operations; increased knowledge of functional health provided by ISHM supports construction of more efficient operations infrastructure. Lack of early ISHM inclusion in the system design process could result in retrofitting health management systems to augment and expand operational and safety requirements; thereby increasing program cost and risk due to increased instrumentation and computational complexity. Having the right sensors generating the required data to perform condition assessment, such as fault detection and isolation, with a high degree of confidence is critical to reliable operation of ISHM. Also, the data being generated by the sensors needs to be qualified to ensure that the assessments made by the ISHM is not based on faulty data. NASA Glenn Research Center has been developing technologies for sensor selection and data validation as part of the FDDR (Fault Detection, Diagnosis, and Response) element of the Upper Stage project of the Ares 1 launch vehicle development. This presentation will provide an overview of the GRC approach to sensor selection and data quality validation and will present recent results from applications that are representative of the complexity of propulsion systems for access to space vehicles. A brief overview of the sensor selection and data quality validation approaches is provided below. The NASA GRC developed Systematic Sensor Selection Strategy (S4) is a model-based procedure for systematically and quantitatively selecting an optimal sensor suite to provide overall health assessment of a host system. S4 can be logically partitioned into three major subdivisions: the knowledge base, the down-select iteration, and the final selection analysis. The knowledge base required for productive use of S4 consists of system design information and heritage experience together with a focus on components with health implications. The sensor suite down-selection is an iterative process for identifying a group of sensors that provide good fault detection and isolation for targeted fault scenarios. In the final selection analysis, a statistical evaluation algorithm provides the final robustness test for each down-selected sensor suite. NASA GRC has developed an approach to sensor data qualification that applies empirical relationships, threshold detection techniques, and Bayesian belief theory to a network of sensors related by physics (i.e., analytical redundancy) in order to identify the failure of a given sensor within the network. This data quality validation approach extends the state-of-the-art, from red-lines and reasonableness checks that flag a sensor after it fails, to include analytical redundancy-based methods that can identify a sensor in the process of failing. The focus of this effort is on understanding the proper application of analytical redundancy-based data qualification methods for onboard use in monitoring Upper Stage sensors.

Garg, Sanjay↗

DOE OSTI2021

Cost Analysis Framework for Comparing AC and DC Design Alternatives for Building Electrical Distribution Systems

In recent years, in response to the changing nature of building load, direct current (DC) distribution systems for buildings have been proposed as alternatives to traditional alternating current (AC) systems. DC distribution offers a closer match to the types of loads and generation sources found in modern buildings, the majority of which use DC electricity internally either natively or as a power conditioning stage. The proposed benefits of DC distribution compared to AC distribution within buildings include higher efficiency, lower installation cost, lower operating cost, higher reliability, improved communication and control, and simplicity. Most recent DC distribution research has focused on quantifying the efficiency advantage of DC distribution over AC distribution. However, energy savings alone do not guarantee cost savings; a more complete cost accounting is required to establish financial benefit. This report provides a framework for cost analysis and comparison of building electrical distribution systems, including common variants for both AC and DC distribution systems. The framework includes all major cost categories, including up-front costs (capital, installation labor, soft costs) and long-term costs (energy, operations and maintenance).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

JGI-Trichoderma v1.0

There is a series of Python and bash scripts to parse genomics datasets used to evaluate the coevolution of gene families and the feature importance of gene families using an SVM classifier. - Cover analysis: takes a list of single-copy genes in a set of genomes, aligns and builds the gene trees to determine if two gene families have a signature of covariation with one another. It parses the files to run phykit cover script described here: https://jlsteenwyk.com/PhyKIT/usage/index.html - SVM-classifier: This Python script is an SVM-based genomic classifier designed for biological data analysis. It combines machine learning with feature selection to identify important genomic markers and classify biological samples. Core Functionality: The script uses Support Vector Machines from scikit-learn to classify genomic data, incorporating SelectKBest for automated feature selection and leave-one-out cross-validation for performance assessment. It operates in multiple modes: feature ranking, optimal combination discovery, and sample prediction. Primary Applications: Genomic sample classification and biomarker discovery Feature importance analysis in high-dimensional biological datasets Prediction of sample categories based on genomic profiles Research applications requiring robust classification of biological data Key Advantages: High-dimensional handling: SVMs excel with genomic data's typical high feature-to-sample ratios Integrated feature selection: Reduces noise and computational overhead while identifying key markers Probability estimation: Provides confidence scores essential for biological interpretation Validation robustness: Leave-one-out cross-validation ensures reliable performance metrics Operational flexibility: Multiple analysis modes support different research phases from exploration to prediction

Stecca Steindorff, Andrei [Lawrence Berkeley Natio↗

DOE OSTI2023

Exploring sustainable electricity system development pathways in South America’s MERCOSUR sub-region

South America has abundant natural water and energy resources, and exploiting these resources to achieve a clean energy future is central to the continent’s economic and sustainable development objectives for the next several decades. Designing pathways to achieving this clean energy future requires better understanding the structural, techno-economic, and policy forces that may influence the future development of the electricity sector in the region. Here, we focus on an interconnected electricity system of five South American countries – Argentina, Brazil, Chile, Paraguay, and Uruguay – which represent major electricity generation, consumption, and trade dynamics in the region. We explore the implications of various forces that could shape the future composition of the power sector in the sub-region, including: evolving renewable energy cost and performance, natural gas prices, cross-border interconnection facilities, early retirement of installed hydropower, and different decarbonization goals. We use a model framework based on a power system planning platform (GridPath) to co-optimize investment and operations of generation, storage, and transmission facilities out to 2050. Our results in a Reference scenario indicate that the electricity system can maintain a relatively clean energy portfolio by leveraging existing hydropower capacity and integrating increasingly cost-competitive wind and solar power. However, dependence on natural gas in the region is likely to remain high. A low-carbon electricity system can cost-effectively be achieved through policy interventions (e.g., renewable portfolio standards) and by diversifying investments in wind, solar, battery storage, and some new hydropower capacity. We also find that existing hydropower is critical for maintaining reliable future grid operations. Enhanced regional electricity trade, mostly based on existing interconnection capacities with nominal investment in new transmission, can significantly benefit the clean energy transition in the region.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS2019

Integrated Refrigeration and Storage of LNG for Compositional Stability

Growing interest in liquefied natural gas (LNG) as a rocket fuel necessitates a greater technical understanding of the compositional changes due to preferential boil-off (or weathering) that occurs during long duration storage. The purity of methane in LNG can range from 90 to 98%, and is subject to preferential boil-off due to its low boiling point compared to other constituents despite the use of high-performance thermal insulation systems. Active heat extraction (i.e. refrigeration) is required to completely eliminate weathering. For future operational safety and reliability, and to better understand the quality and efficiency of the LNG as a cryofuel, a 400-liter Cryostat vessel was designed and constructed to measure the composition and temperatures of the LNG at a number of different liquid levels over long durations. The vessel is the centerpiece of a custom-designed lab-scale integrated refrigeration and storage (IRaS) system employing a pulse tube cryocooler capable of roughly 50 W of lift at 100 K. Instrumentation includes ten temperature sensors mounted on a vertical rake and five liquid sample tubes corresponding to five liquid levels. Two modes of operation are studied. The first is without refrigeration in order to determine a baseline in the change in composition, and to study stratification of the LNG. The second is performed with the cryocooler active to determine the operational parameters of the IRaS system for eliminating the weathering as well as stratification effects in the bulk liquid. The apparatus design and test method, as well as preliminary test results are presented in this paper. As a bonus in cost-saving and operational efficiency, the capability of the IRaS system to provide zero-loss capabilities such as zero boil-off (ZBO) keeping of the LNG and zero-loss filling/transfer operations are also discussed.

Rose, Laura P.↗

NASA NTRS2019

Integrated Refrigeration and Storage of LNG for Compositional Stability

Rose, L.↗

DOE OSTI2022

Bridging Equipment Reliability Data and Robust Decisions in a Plant Operation Context

In order to reduce operation and maintenance (O&M) costs, nuclear power plants (NPPs) are moving from corrective and periodic maintenance to predictive maintenance strategies. Such transition requires changes on the data that needs to be retrieved and on the type of decision processes to be employed. Advanced monitoring and data analysis technologies are essential to support predictive strategies. They can in fact provide precise information about health of a component, track its degradation trends, and provide information of its expected failure time. With such information, maintenance operations for a component can be performed right before its expected failure time. This dynamic context of O&M operations requires new methods to analyze data, propagate component health information from the component to the system level, and optimize plant resources. In this respect, the risk informed asset management (RIAM) project has been tasked to develop and test this new class of methods into a risk analytics toolset. This toolset consists of data analytics tools coupled with reliability methods designed to manage plant assets and performances in a predictive maintenance context. This report shows the latest improvements on such development and the initial testing of our methods on the three main research areas that the RIAM project is focusing on. These areas are the following: equipment reliability data analytics, system reliability modeling, and plant resources optimization methods. We show how the methods developed in these areas can support predictive maintenance strategies by: 1) analyzing equipment reliability data (either in numeric and textual form), 2) assessing component and system health through an innovative margin-based reliability approach, and 3) identifying the most critical components and set optimal maintenance schedule based on plant economic and operational constraints.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Evaluating Resilience of Water Distribution Networks to Operational Failures from Cyber-Physical Attacks

Water cyber-physical systems (CPSs) have gained increasing interest to improve operational efficiency and reliability. However, due to growing exposure to cyber-physical attacks, cybersecurity and resilience against the attacks have become significant concerns. There have been efforts to improve cybersecurity in water CPSs, yet few attempts to investigate resilience against cyber-physical attacks. This study contributes to characterizing resilience of a water CPS and investigating potential resilience strategies. An advanced resilience measure integrating withstanding, absorptive, adaptive, and restorative capability of a system is proposed and applied to the C-town water distribution network (WDN) for 15 failure set scenarios with a pressure-driven hydraulic simulation. The results provide identification of failure sets and unfavorable operational conditions that make the system more vulnerable to the cyber-physical attacks and in turn produce low resilience and capabilities. It is also found that, after recovery of a disrupted component, adjustment of overall operational interactions across system components is needed for complete restoration of disrupted functionality. The findings provide insights on infrastructure investment with resilience strategies in cyber and physical water system domains.

Shin, Sangmin↗

NASA NTRS1988

Launch vehicle operations cost reduction through artificial intelligence techniques

NASA's Kennedy Space Center has attempted to develop AI methods in order to reduce the cost of launch vehicle ground operations as well as to improve the reliability and safety of such operations. Attention is presently given to cost savings estimates for systems involving launch vehicle firing-room software and hardware real-time diagnostics, as well as the nature of configuration control and the real-time autonomous diagnostics of launch-processing systems by these means. Intelligent launch decisions and intelligent weather forecasting are additional applications of AI being considered.

Davis, Tom C., Jr.↗

DOE OSTI2026

SRF cavity instability detection with machine learning at CEBAF

During the operation of the Continuous Electron Beam Accelerator Facility (CEBAF), one or more unstable superconducting radio-frequency (SRF) cavities often cause beam loss trips while the unstable cavities themselves do not necessarily trip off. The present RF controls for the legacy cavities report at only 1 Hz, which is too slow to detectfast transient instabilities during these trip events. These challenges make the identification of an unstable cavity out of the hundreds installed at CEBAF a difficult and time-consuming task. To tackle these issues, a fast data acquisition system (DAQ) for the legacy SRF cavities has been developed, which records the sample at 5 kHz. An unsupervised learning framework has been developed to identify anomalous SRF cavity behavior. We will discuss the present status of the DAQ system and our framework, along with recent successes in detecting anomalous cavity behavior. Overall, our method offers a practical solution for identifying unstable SRF cavities, contributing to increased beam availability and machine reliability.

Accelerator Physics↗

NASA NTRS2003

Magnetic Flux Compression Experiments Using Plasma Armatures

Magnetic flux compression reaction chambers offer considerable promise for controlling the plasma flow associated with various micronuclear/chemical pulse propulsion and power schemes, primarily because they avoid thermalization with wall structures and permit multicycle operation modes. The major physical effects of concern are the diffusion of magnetic flux into the rapidly expanding plasma cloud and the development of Rayleigh-Taylor instabilities at the plasma surface, both of which can severely degrade reactor efficiency and lead to plasma-wall impact. A physical parameter of critical importance to these underlying magnetohydrodynamic (MHD) processes is the magnetic Reynolds number (R(sub m), the value of which depends upon the product of plasma electrical conductivity and velocity. Efficient flux compression requires R(sub m) less than 1, and a thorough understanding of MHD phenomena at high magnetic Reynolds numbers is essential to the reliable design and operation of practical reactors. As a means of improving this understanding, a simplified laboratory experiment has been constructed in which the plasma jet ejected from an ablative pulse plasma gun is used to investigate plasma armature interaction with magnetic fields. As a prelude to intensive study, exploratory experiments were carried out to quantify the magnetic Reynolds number characteristics of the plasma jet source. Jet velocity was deduced from time-of-flight measurements using optical probes, and electrical conductivity was measured using an inductive probing technique. Using air at 27-inHg vacuum, measured velocities approached 4.5 km/s and measured conductivities were in the range of 30 to 40 kS/m.

Turner, M. W.↗

NASA NTRS1994

DSN Co-Observing Operations to Support Space VLBI Missions

Reliable radio astronomy support of Space Very-Long-Baseline- Interferometry missions by ground radio telescopes is mandatory in order to achieve high scientific return from missions, The 70m DSN antennas along with other ground radio telescopes will perform as the ground segment of the Earth-space interferometer. Improvements of radio astronomy VLBI operations at the DSN to achieve higher reliability, efficiency, flexibility, and lower operations costs is a major goal in preparing for radio astronomy support of SVLBI. To help realize this goal, a remote control and monitoring mode for radio astronomy operations at the DSN is being developed.

radio↗

DOE OSTI2022

FFTF Acceptance and Startup Testing for GAIN

The Fast Flux Test Facility (FFTF) is the most recent liquid metal reactor (LMR) to be designed, constructed, and operated by the U.S. Department of Energy (DOE). The 400-MWt sodium-cooled, fast-neutron flux reactor plant was designed for irradiation testing of nuclear reactor fuels and materials for liquid metal fast breeder reactors. Following the demise of the breeder reactor program in the United States, FFTF continued to play a key role in providing a test bed for demonstrating performance of advanced fuel designs and demonstrating operation, maintenance, and safety of advanced liquid metal reactors. FFTF operations ceased in April 1992 after a determination by DOE that no combination of proposed missions was financially feasible over a ten-year period. The reactor is currently deactivated and in a long-term surveillance and maintenance (S&M) mode. This report provides information on the extensive and rigorous process that was used to conduct turnover from construction followed by acceptance and startup testing of the FFTF. This paper is in support of the Gateway for Accelerated Innovation in Nuclear (GAIN), which provides the nuclear energy community with access to the technical, regulatory, and financial support necessary to move new or advanced nuclear reactor designs toward commercialization while ensuring the continued safe, reliable, and economic operation of the existing nuclear fleet. The information obtained from the design, startup, and operation of the FFTF provides valuable insight for follow-on reactor projects, such as the Versatile Test Reactor (VTR), in the areas of plant system and component design, component fabrication, fuel design and performance, prototype testing, site construction, reactor startup and operations, and reactor deactivation and decommissioning (D&D). The focus of this report is on the process used to startup the FFTF and to ensure that operations could be conducted efficiently and safely. A reference section is provided of documents detailing the successful turnover and testing process implemented for startup of the reactor and its supporting systems. The documents listed can be retrieved upon request and are believed useful for future reactor startup endeavors.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS1994

DSN co-observing operations to support space VLBI missions

Reliable radio astronomy support of space very long baseline interferometry (VLBI) missions by ground radio telescopes is mandatory in order to achieve a high scientific return from the missions. The 70 m DSN antennas along with other ground radio telescopes will perform as the ground segment of the earth-space interferometer. Improvements of radio astronomy VLBI operations at the DSN to achieve higher reliability, efficiency, flexibility, and lower operations costs is a major goal in preparing for radio astronomy support of SVLBI. To help realize this goal, a remote control and monitoring mode for radio astronomy operations at the DSN has been developed.

Altunin, Valery I.↗