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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

SILHIL Replication of Electric Aircraft Powertrain Dynamics and Inner-Loop Control for V&V of System Health Management Routines

Software-in-the-loop and Hardware-in-the-loop testing of failure prognostics and decision making tools for aircraft systems will facilitate more comprehensive and cost-effective testing than what is practical to conduct with flight tests. A framework is described for the offline recreation of dynamic loads on simulated or physical aircraft powertrain components based on a real-time simulation of airframe dynamics running on a flight simulator, an inner-loop flight control policy executed by either an autopilot routine or a human pilot, and a supervisory fault management control policy. The creation of an offline framework for verifying and validating supervisory failure prognostics and decision making routines is described for the example of battery charge depletion failure scenarios onboard a prototype electric unmanned aerial vehicle.

Verification and Validation↗
NASA NTRS2015

Prognostics & Health Management: A NASA Perspective

How can advanced automation techniques developed by NASA to perform Fault Detection, Isolation, and Recovery (FDIR) in space missions be used here on Earth in the Oil & Gas industry? Whether on a Mars orbiter or an oil platform, having an intelligent machine to back up the crew/operators to help monitor and diagnose the systems for possible problems and aid in determining a corrective action/response is an important and useful attribute for multiple industries.

Boyer, Roger L.↗
NASA NTRSDate not supplied

Hybrid Modeling for Complex Systems Health Management

The research work presents application of hybrid physics-informed machine learning to a representative electric powertrain for unmanned aerial vehicles. The model is composed of physics-derived and empirical equations, integrated with connected networks that are strategically placed within the model to substitute equations that are subject to large uncertainty. Polynomial fit driven by heuristics or empirical observations can be substituted by more flexible networks that can minimize the error between model predictions and observations without being restricted to a predefined functional form. This modeling strategy allows training of networks deep inside the model and unknown parameters in a single learning stage. The powertrain model consists of Li-ion batteries, electronic speed controller with pulse-width modulation, and brush-less DC motor with connected propeller. Results obtained from combination of laboratory and simulation tests are discussed in this work.

PINNS↗
NASA NTRS2011

Health Monitor for Multitasking, Safety-Critical, Real-Time Software

Health Manager can detect Bad Health prior to a failure occurring by periodically monitoring the application software by looking for code corruption errors, and sanity-checking each critical data value prior to use. A processor s memory can fail and corrupt the software, or the software can accidentally write to the wrong address and overwrite the executing software. This innovation will continuously calculate a checksum of the software load to detect corrupted code. This will allow a system to detect a failure before it happens. This innovation monitors each software task (thread) so that if any task reports "bad health," or does not report to the Health Manager, the system is declared bad. The Health Manager reports overall system health to the outside world by outputting a square wave signal. If the square wave stops, this indicates that system health is bad or hung and cannot report. Either way, "bad health" can be detected, whether caused by an error, corrupted data, or a hung processor. A separate Health Monitor Task is started and run periodically in a loop that starts and stops pending on a semaphore. Each monitored task registers with the Health Manager, which maintains a count for the task. The registering task must indicate if it will run more or less often than the Health Manager. If the task runs more often than the Health Manager, the monitored task calls a health function that increments the count and verifies it did not go over max-count. When the periodic Health Manager runs, it verifies that the count did not go over the max-count and zeroes it. If the task runs less often than the Health Manager, the periodic Health Manager will increment the count. The monitored task zeroes the count, and both the Health Manager and monitored task verify that the count did not go over the max-count.

Zoerner, Roger↗
DOE OSTI2015

Understanding the perceptions, roles and interactions of stakeholder networks managing health-care waste: A case study of the Gaza Strip

Highlights: • We systematically review scientific literature about health-care waste management. • We identify and discuss gaps, trends, efforts, and key-factors. • We suggest areas for improvement and best practices reported in literature. • We include recommendations for policy makers, practitioners and researchers. • We promote a holistic and harmonized approach to health-care waste management. - Abstract: The sustainable management of waste requires a holistic approach involving a range of stakeholders. What can often be difficult is to understand the manner in which different types of stakeholder networks are composed and work, and how best to enhance their effectiveness. Using social network analysis and stakeholder analysis of healthcare waste management stakeholders in the case study region of the Gaza Strip, this study aimed to understand and examine the manner in which the networks functioned. The Ministry of Health was found to be the most important stakeholder, followed by municipalities and solid waste management councils. Some international agencies were also mentioned, with specific roles, while other local institutions had a limited influence. Finally while health-care facilities had a strong interest in waste management, they were generally poorly informed and had limited links to each other. The manner in which the networks operated was complicated and influenced by differences in perception, sharing of information, access to finance and levels of awareness. The lack of a clear legal framework generated various mistakes about roles and responsibilities in the system, and evidently regulation was not an effective driver for improvement. Finally stakeholders had different priorities according to the waste management issues they were involved with, however segregation at the source was identified as a key requirement by most. Areas for improving the effectiveness of the networks are suggested. The analysis utilized an innovative methodology, which involved a large number of stakeholders. Such an approach served to raise interest and awareness at different levels (public authorities, health providers, supporting actors, others), stimulate the discussion about the adoption of specific policies, and identify the effective way forward.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2005

Design Methods and Practices for Fault Prevention and Management in Spacecraft

Integrated Systems Health Management (ISHM) is intended to become a critical capability for all space, lunar and planetary exploration vehicles and systems at NASA. Monitoring and managing the health state of diverse components, subsystems, and systems is a difficult task that will become more challenging when implemented for long-term, evolving deployments. A key technical challenge will be to ensure that the ISHM technologies are reliable, effective, and low cost, resulting in turn in safe, reliable, and affordable missions. To ensure safety and reliability, ISHM functionality, decisions and knowledge have to be incorporated into the product lifecycle as early as possible, and ISHM must be considered as an essential element of models developed and used in various stages during system design. During early stage design, many decisions and tasks are still open, including sensor and measurement point selection, modeling and model-checking, diagnosis, signature and data fusion schemes, presenting the best opportunity to catch and prevent potential failures and anomalies in a cost-effective way. Using appropriate formal methods during early design, the design teams can systematically explore risks without committing to design decisions too early. However, the nature of ISHM knowledge and data is detailed, relying on high-fidelity, detailed models, whereas the earlier stages of the product lifecycle utilize low-fidelity, high-level models of systems and their functionality. We currently lack the tools and processes necessary for integrating ISHM into the vehicle system/subsystem design. As a result, most existing ISHM-like technologies are retrofits that were done after the system design was completed. It is very expensive, and sometimes futile, to retrofit a system health management capability into existing systems. Last-minute retrofits result in unreliable systems, ineffective solutions, and excessive costs (e.g., Space Shuttle TPS monitoring which was considered only after 110 flights and the Columbia disaster). High false alarm or false negative rates due to substandard implementations hurt the credibility of the ISHM discipline. This paper presents an overview of the current state of ISHM design,and a review of formal design methods to make recommendations about possible approaches to enable the ISHM capabilities to be designed-in at the system-level, from the very beginning of the vehicle design process.

Tumer, Irem Y.↗
NASA NTRS2013

Human Machine Interface Programming and Testing

Human Machine Interface (HMI) Programming and Testing is about creating graphical displays to mimic mission critical ground control systems in order to provide NASA engineers with the ability to monitor the health management of these systems in real time. The Health Management System (HMS) is an online interactive human machine interface system that monitors all Kennedy Ground Control Subsystem (KGCS) hardware in the field. The Health Management System is essential to NASA engineers because it allows remote control and monitoring of the health management systems of all the Programmable Logic Controllers (PLC) and associated field devices. KGCS will have equipment installed at the launch pad, Vehicle Assembly Building, Mobile Launcher, as well as the Multi-Purpose Processing Facility. I am designing graphical displays to monitor and control new modules that will be integrated into the HMS. The design of the display screen will closely mimic the appearance and functionality of the actual modules. There are many different field devices used to monitor health management and each device has its own unique set of health management related data, therefore each display must also have its own unique way to display this data. Once the displays are created, the RSLogix5000 application is used to write software that maps all the required data read from the hardware to the graphical display. Once this data is mapped to its corresponding display item, the graphical display and hardware device will be connected through the same network in order to test all possible scenarios and types of data the graphical display was designed to receive. Test Procedures will be written to thoroughly test out the displays and ensure that they are working correctly before being deployed to the field. Additionally, the Kennedy Ground Controls Subsystem's user manual will be updated to explain to the NASA engineers how to use the new module displays.

Foster, Thomas Garrison↗
NASA NTRS2008

NASA C-17 Usage Overview

The usage and integrated vehicle health management of the NASA C-17. Propulsion health management flight objectives for the aircraft include mapping of the High Pressure Compressor in order to calibrate a Pratt and Whitney engine model and the fusion of data collected from existing sensors and signals to develop models, analysis methods and information fusion algorithms. An additional health manage flight objective is to demonstrate that the Commercial Modular Aero-Propulsion Systems Simulation engine model can successfully execute in real time onboard the C-17 T-1 aircraft using engine and aircraft flight data as inputs. Future work will address aircraft durability and aging, airframe health management, and propulsion health management research in the areas of gas path and engine vibration.

Miller, Christopher R.↗
DOE OSTI2018

Hearst Health Prize for Excellence in Population Health

Sandia National Laboratories (SNL) Employee Health Services (EHS) is committed to promoting healthy, vibrant lives and embracing health. Since 1986, EHS has built a comprehensive, evidence-based program designed to measure and assess health risk prevalence, provide targeted and customizable services to address health risks, incentivize healthy behaviors, improve productivity, enhance quality of life, and lower healthcare costs for participants via collaboration between on-site and community-based providers. This unique partnership provides a broad scope of services that may not be available to employees solely through their health benefit plan, and allows a supportive, convenient approach that has proven enhanced health outcomes. EHS impacts over 12,000 SNL employees in Albuquerque, New Mexico. Corporate wellness is as important as ever as health issues and healthcare costs continue to rise. We use the 8-15-80 model as the foundation for our health program strategy: prevent or improve 8 modifiable behaviors and risks that contribute to 15 chronic health conditions that account for 80% of healthcare spending on chronic illnesses worldwide. We utilize patient-centered, cost-effective, community-connected care by providing free onsite services including the NCQA-recognized/AAAHC-accredited medical clinic, health management, preventive health, behavioral health, physical therapy, medical case management, acute care, emergency medical services, and more. These programs and services are an employer-paid benefit open to all SNL employees. The organization combines best practices, accredited programs, and top health care providers to bring employees the most comprehensive approach to health care.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2011

Autonomous, In-Flight Crew Health Risk Management for Exploration-Class Missions: Leveraging the Integrated Medical Model for the Exploration Medical System Demonstration Project

The Integrated Medical Model (IMM) captures organizational knowledge across the space medicine, training, operations, engineering, and research domains. IMM uses this knowledge in the context of a mission and crew profile to forecast risks to crew health and mission success. The IMM establishes a quantified, statistical relationship among medical conditions, risk factors, available medical resources, and crew health and mission outcomes. These relationships may provide an appropriate foundation for developing an in-flight medical decision support tool that helps optimize the use of medical resources and assists in overall crew health management by an autonomous crew with extremely limited interactions with ground support personnel and no chance of resupply.

Butler, D. J.↗