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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
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 OSTI2024

Development Plan for Ultrasonic Pressure Sensors [Slides]

Current light water reactors (LWRs) utilize differential pressure cells, based on strain gauges, which are remotely located from the reactor vessel via impulse lines. These pressure sensors are used to measure liquid level within the vessel and to give a general indication of system health with regard to leaks and flow system fouling. The advanced reactor types currently under development generally operate at higher temperatures than light-water reactors and utilize coolants that may be highly corrosive (i.e., liquid metals). They will use pressure measurements for varied measurands, such as level and flow rate, as well as indications of accident conditions or off-normal operating conditions. More robust pressure sensors are needed to address these more challenging conditions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1988

Real-time space system control with expert systems

Many aspects of space system operations involve continuous control of real time processes. These processes include electrical power system monitoring, prelaunch and ongoing propulsion system health and maintenance, environmental and life support systems, space suit checkout, onboard manufacturing, and vehicle servicing including satellites, shuttles, orbital maneuvering vehicles, orbital transfer vehicles and remote teleoperators. Traditionally, monitoring of these critical real time processes has been done by trained human experts monitoring telemetry data. However, the long duration of future space missions and the high cost of crew time in space creates a powerful economic incentive for the development of highly autonomous knowledge based expert control procedures for these space systems.

Leinweber, David↗
NASA NTRS1993

The development of the human exploration demonstration project (HEDP), a planetary systems testbed

The Human Exploration Demonstration Project (HEDP) is an ongoing task at the National Aeronautics and Space Administration's Ames Research Center to address the advanced technology requirements necessary to implement an integrated working and living environment for a planetary surface habitat. The integrated environment will consist of life support systems, physiological monitoring of project crew, a virtual environment workstation, and centralized data acquisition and habitat systems health monitoring. There will be several robotic systems on a simulated planetary landscape external to the habitat environment to provide representative work loads for the crew. This paper describes the status of the HEDP after one year, the major facilities composing the HEDP, the project's role as an Ames Research Center testbed, and the types of demonstration scenarios that will be run to showcase the technologies.

Chevers, Edward S.↗
NASA NTRS1993

Real-time expert system diagnostics and monitoring for the High Resolution Microwave Survey Targeted Search

An automated monitoring and diagnostics system (MDS) using virtual real-time software was developed for NASA's High Resolution Microwave Survey (HRMS) Targeted Search System (TSS). The four main tasks required of the MDS were monitoring and recording system health, alerting operators of problems, diagnosing poor system performance, and performing an emergency system shutdown. The MDS was implemented using commercial expert system software tools in addition to interface hardware and software developed on site. The expert system used objects, rules, and schematics in its TSS knowledge representation. The MDS was successfully integrated into the HRMS computer environment, and its performance met or exceeded its requirements.

Macalou, A.↗
NASA NTRS2006

ISHM Implementation for Constellation Systems

Integrated System Health Management (ISHM) is a capability that focuses on determining the condition (health) of every element in a complex System (detect anomalies, diagnose causes, prognosis of future anomalies), and provide data, information, and knowledge (DIaK) "not just data" to control systems for safe and effective operation. This capability is currently done by large teams of people, primarily from ground, but needs to be embedded on-board systems to a higher degree to enable NASA's new Exploration Mission (long term travel and stay in space), while increasing safety and decreasing life cycle costs of systems (vehicles; platforms; bases or outposts; and ground test, launch, and processing operations). This viewgraph presentation reviews the use of ISHM for the Constellation system.

Figueroa, Fernando↗
NASA NTRS2007

Smart Sensor Node Development, Testing and Implementation for Rocket Propulsion Systems

Successful design and implementation of an Integrated System Health Management (ISHM) approach for rocket propulsion systems requires the capability improve the reliability of complex systems by detecting and diagnosing problems. One of the critical elements in the ISHM is an intelligent sensor node for data acquisition that meets specific requirements for rocket motor testing including accuracy, sample rate and size/weight. Traditional data acquisition systems are calibrated in a controlled environment and guaranteed to perform bounded by their tested conditions. In a real world ISHM system, the data acquisition and signal conditioning needs to function in an uncontrolled environment. Development and testing of this sensor node focuses on a design with the ability to self check in order to extend calibration times, report internal faults and drifts and notify the overall system when the data acquisition is not performing as it should. All of this will be designed within a system that is flexible, requiring little re-design to be deployed on a wide variety of systems. Progress in this design and initial testing of prototype units will be reported.

Mengers, Timothy R.↗
NASA NTRS2009

Developing Large-Scale Bayesian Networks by Composition: Fault Diagnosis of Electrical Power Systems in Aircraft and Spacecraft

In this paper, we investigate the use of Bayesian networks to construct large-scale diagnostic systems. In particular, we consider the development of large-scale Bayesian networks by composition. This compositional approach reflects how (often redundant) subsystems are architected to form systems such as electrical power systems. We develop high-level specifications, Bayesian networks, clique trees, and arithmetic circuits representing 24 different electrical power systems. The largest among these 24 Bayesian networks contains over 1,000 random variables. Another BN represents the real-world electrical power system ADAPT, which is representative of electrical power systems deployed in aerospace vehicles. In addition to demonstrating the scalability of the compositional approach, we briefly report on experimental results from the diagnostic competition DXC, where the ProADAPT team, using techniques discussed here, obtained the highest scores in both Tier 1 (among 9 international competitors) and Tier 2 (among 6 international competitors) of the industrial track. While we consider diagnosis of power systems specifically, we believe this work is relevant to other system health management problems, in particular in dependable systems such as aircraft and spacecraft. (See CASI ID 20100021910 for supplemental data disk.)

Mengshoel, Ole Jakob↗
NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth independence and autonomy of mission operations. Here we present an overview of AI/ML architecture to support deep space mission goals, developed with leaders in the field. First, we focus on the fundamental biological research that supports our understanding of physiological responses to spaceflight, and we describe current efforts to support AI/ML research including data standardization and data engineering through maximally open and FAIR (findable, accessible, interoperable, reusable) databases and the generation of AI-ready datasets for reuse and analysis. We also discuss remote data management frameworks for research data as well as environmental and health data that are generated during deep space missions. We highlight several research projects that leverage data standardization and management for fundamental biological discovery to uncover the complex effects of space travel on living systems. Next, we provide an overview of cutting-edge AI/ML approaches that can be integrated to support remote monitoring and analysis during deep space missions, including generative models and large language models to learn the underlying biomedical patterns and predict outcomes or answer questions during off world medical scenarios. We also describe current AI/ML methods to support this research and monitoring through automated cloud-based labs which enable limited human intervention and closed-loop experimentation in remote settings. These labs could support mission autonomy by analyzing environmental data streams, and would be facilitated through in situ analytics capabilities to avoid sending large raw data files through low bandwidth communications. Finally, in the context of deep space missions with limited communications or access to medical advice from Earth, we describe a solution for integrated, real-time mission biomonitoring across hierarchical levels from continuous environmental monitoring, to wearables and point-of-care devices, to molecular and physiological monitoring. We introduce a precision space health system that will ensure that the future of space health is predictive, preventative, participatory and personalized.

artificial intelligence↗
NASA NTRS2005

Human Health and Support Systems Capability Roadmap Progress Review

The Human Health and Support Systems Capability Roadmap focuses on research and technology development and demonstration required to ensure the health, habitation, safety, and effectiveness of crews in and beyond low Earth orbit. It contains three distinct sub-capabilities: Human Health and Performance. Life Support and Habitats. Extra-Vehicular Activity.

Grounds, Dennis↗
NASA NTRSDate not supplied

Intelligent Control & Autonomy Branch Research Overview Research

The purpose of the subject presentation is to expose engineering students at Ohio University to ongoing work being performed by the Intelligent Control and Autonomy Branch (ICAB) at the NASA Glenn Research Center in Cleveland, Ohio. The presentation will start with some introductory material about the organization. This will be followed by an overview of Electrified Aircraft Propulsion (EAP) controls research and the ICAB’s support for the Space Launch System (SLS). One aspect of EAP is the integration of electrical motor/generators and other power systems components with turbine engine technology to create propulsion & power systems for single-aisle aircraft that are more fuel efficient and have lower emissions. The presentation will introduce some of the controls, systems health management, and modeling technologies developed by the ICAB to help realize EAP. NASA’s SLS is a super-heavy-lift launch vehicle that provides the foundation for human exploration beyond Earth’s orbit. The presentation will introduce capabilities developed by the ICAB to support the SLS Mission and Fault Management function which includes capabilities for abort, caution and warning, redundancy management, and safing. The presentation will conclude with information about internships with the NASA and the ICAB.

propulsion↗
NASA NTRS2011

Hardware Specific Integration Strategy for Impedance-Based Structural Health Monitoring of Aerospace Systems

The Integrated Vehicle Health Management (IVHM) Project, sponsored by NASA's Aeronautics Research Mission Directorate, is conducting research to advance the state of highly integrated and complex flight-critical health management technologies and systems. An effective IVHM system requires Structural Health Monitoring (SHM). The impedance method is one such SHM technique for detection and monitoring complex structures for damage. This position paper on the impedance method presents the current state of the art, future directions, applications and possible flight test demonstrations.

Owen, Robert B.↗
NASA NTRSDate not supplied

The Exploration Crew Health and Performance System of the Future - A Shared Mental Model

The challenges involved in vehicle/habitat design and operation for long-duration deep space missions are complex, and the needs of a human crew must be considered in the context of all the system trades required to enable such missions. An exploration Crew Health and Performance (CHP) system complements all the other vehicle/habitat systems to achieve one specific and critical endpoint – ensuring that the astronauts can perform the job that they were sent into space to do. This includes accounting for all aspects of the physiological, psychological, medical, and environmental realities that the human crew must face in deep space. Along with this system complexity comes the additional need for increased autonomy of the crew due to the immense distance from Earth. The design of future systems must respect the real human capabilities and limitations within the context of a mission to the Moon or Mars. The NASA Moon to Mars Objectives document outlines the need for advanced CHP system designs: • Develop systems that monitor and maintain crew health and performance throughout all mission phases, including during communication delays to Earth, and in an environment that does not allow emergency evacuation or terrestrial medical assistance. • Evaluate and validate progressively Earth-independent crew health & performance systems and operations with mission durations representative of Mars-class missions. • Validate readiness of systems and operations to support crew health and performance for the initial human Mars exploration campaign. This presentation will outline the initial work that Exploration Medical Capability is leading on the development of a prototype design for an exploration Crew Health and Performance (CHP) system for future NASA human deep space long-duration missions. This effort will require commitment from all stakeholders to a shared mental model of what a future exploration CHP system should look like, one that will address the needs, goals, and objectives of the Agency and help to ensure mission success in deep space.

K R Lehnhardt↗
NASA NTRS1995

Generic Health Management: A System Engineering Process Handbook Overview and Process

Health Management, a System Engineering Process, is one of those processes-techniques-and-technologies used to define, design, analyze, build, verify, and operate a system from the viewpoint of preventing, or minimizing, the effects of failure or degradation. It supports all ground and flight elements during manufacturing, refurbishment, integration, and operation through combined use of hardware, software, and personnel. This document will integrate Health Management Processes (six phases) into five phases in such a manner that it is never a stand alone task/effort which separately defines independent work functions.

Wilson, Moses Lee↗
NASA NTRS1989

NASA/RAE cooperation on a knowlede based flight status monitor

As part of a US/UK cooperative aeronautical research pragram, a joint activity between the Dryden Flight Research Facility of the NASA Ames Research Center (Ames-Dryden) and the Royal Aerospace Establishment (RAE) on Knowledge Based Systems was established. Under the agreement, a Flight Status Monitor Knowledge base developed at Ames-Dryden was implemented using the real-time IKBS toolkit, MUSE, which was developed in the UK under RAE sponsorship. The Flight Status Monitor is designed to provide on-line aid to the flight test engineer in the interpretation of system health and status by storing expert knowledge of system behavior in an easily accessible form. The background to the cooperation is described and the details of the Flight Status Monitor, the MUSE implementation are presented.

Butler, G. F.↗
NASA NTRS2014

Prognostic Analysis System and Methods of Operation

A prognostic analysis system and methods of operating the system are provided. In particular, a prognostic analysis system for the analysis of physical system health applicable to mechanical, electrical, chemical and optical systems and methods of operating the system are described herein.

MacKey, Ryan M. E.↗
NASA NTRS2014

Ultrahigh Temperature Capacitive Pressure Sensor

Robust, miniaturized sensing systems are needed to improve performance, increase efficiency, and track system health status and failure modes of advanced propulsion systems. Because microsensors must operate in extremely harsh environments, there are many technical challenges involved in developing reliable systems. In addition to high temperatures and pressures, sensing systems are exposed to oxidation, corrosion, thermal shock, fatigue, fouling, and abrasive wear. In these harsh conditions, sensors must be able to withstand high flow rates, vibration, jet fuel, and exhaust. In order for existing and future aeropropulsion turbine engines to improve safety and reduce cost and emissions while controlling engine instabilities, more accurate and complete sensor information is necessary. High-temperature (300 to 1,350 C) capacitive pressure sensors are of particular interest due to their high measurement bandwidth and inherent suitability for wireless readout schemes. The objective of this project is to develop a capacitive pressure sensor based on silicon carbon nitride (SiCN), a new class of high-temperature ceramic materials, which possesses excellent mechanical and electric properties at temperatures up to 1,600 C.

Harsh, Kevin↗
NASA NTRS1991

Real-time in-flight engine performance and health monitoring techniques for flight research application

Procedures for real time evaluation of the inflight health and performance of gas turbine engines and related systems were developed to enhance flight test safety and productivity. These techniques include the monitoring of the engine, the engine control system, thrust vectoring control system health, and the detection of engine stalls. Real time performance techniques were developed for the determination and display of inflight thrust and for aeroperformance drag polars. These new methods were successfully shown on various research aircraft at NASA-Dryden. The capability of NASA's Western Aeronautical Test Range and the advanced data acquisition systems were key factors for implementation and real time display of these methods.

Ray, Ronald J.↗