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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Prognostication of LED Remaining Useful Life and Color Stability in the Presence of Contamination

The reliability of LED products may be affected by both luminous flux drop and color shift. Previous research on the topic focuses on either luminous maintenance or color shift. However, luminous flux degradation usually takes very long time to observe in LEDs under normal operating conditions. In this paper, the impact of a VOC (volatile organic compound) contaminated luminous flux and color stability are examined. As a result, both luminous degradation and color shift had been recorded in a short time. Test samples are white, phosphorconverted, high-power LED packages. Absolute radiant flux is measured with integrating sphere system to calculate the luminous flux. Luminous flux degradation and color shift distance were plotted versus aging time to show the degradation pattern. A prognostic health management (PHM) method based on the state variables and state estimator have been proposed in this paper. In this PHM framework, unscented kalman filter (UKF) was deployed as the carrier of all states. During the estimation process, third order dynamic transfer function was used to implement the PHM framework. Both of the luminous flux and color shift distance have been used as the state variable with the same PHM framework to exam the robustness of the method. Predicted remaining useful life is calculated at every measurement point to compare with the tested remaining useful life. The result shows that state estimator can be used as the method for the PHM of LED degradation with respect to both luminous flux and color shift distance. The prediction of remaining useful life of LED package, made by the states estimator and data driven approach, falls in the acceptable errorbounds (20%) after a short training of the estimator.

Lall, Pradeep↗
DOE OSTI2016

A Systems Approach to Analyzing Cyber-Physical Threats in the Smart Grid

This paper presents a systems analysis approach to characterizing the risk of a Smart Grid to a load-drop attack. A characterization of the risk is necessary for the design of detection and remediation strategies to address the consequences of such attacks. Using concepts from systems health management and system engineering, this work (a) first identifies metrics that can be used to generate constraints for security features, and (b) lays out an end-to-end integrated methodology using separate network and power simulations to assess system risk. We demonstrate our approach by performing a systems-style analysis of a load-drop attack implemented over the AMI subsystem and targeted at destabilizing the underlying power grid.

Almajali, Anas↗
DOE OSTI2013

Prognostics of damage accural in SSL luminaires and drivers subjected to HTSL accelerated aging

This paper will show an investigation of off-the-shelf luminaires with the focus on the LED electronic drivers, specifically the aluminum electrolytic capacitors (AECs), that have been aged using high temperature shelf life (HTSL) testing of 135°C in order to prognosticate the remaining useful life of the luminaires. Luminaires have the potential of seeing excessive temperatures when being transported across country or being stored in non-climate controlled warehouses. They are also being used in outdoor applications in desert environments that see little or no humidity but will experience extremely high temperatures during the day. This makes it important to increase our understanding of what effects being stored at high temperatures for a prolonged period of time will have on the usability and survivability of these devices. The U.S. Department of Energy has made a long term commitment to advance the efficiency, understanding and development of solid-state lighting (SSL) and is making a strong push for the acceptance and use of SSL products. In this work, the four AECs of three different types inside each LED electronic driver were studied. The change in capacitance and the change in equivalent series resistance (ESR) of the AECs were measured and considered to be a leading indication of failure of the LED system. These indicators were used to make remaining useful life predictions to develop an algorithm to predict the end of life of the AECs. The luminous flux of a pristine downlight module was also monitored using each LED electronic driver that was subjected to HTSL through the progression of the testing to determine a correlation between the light output of the lamp and the failing components of the LED electronic driver. Prognostic and Health Management (PHM) is a useful tool for assessment of the remaining life of electrical components and is demonstrated for AECs in this work.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Apparatus, compositions, and methods for assessment of chronic obstructive pulmonary disease progression among rapid and slow decline conditions

Methods are disclosed for generating and isolating an informative content repository of respiratory related biomarkers to accurately determine whether an individual has normal or abnormal pulmonary function. Specifically, methods are directed to determination of whether individuals have chronic obstructive pulmonary disease, and if so, whether the affected individuals experience rapid long decline or slow lung decline as a result of COPD. Also disclosed is an informative content repository of chronic obstructive pulmonary disease biomarkers, which when linked with other informative content provides a powerful tool for diagnosis, study, therapeutic discovery and development, condition management, health maintenance, and linking chronic obstructive pulmonary disease through pattern of life style, environmental exposure, and genetic susceptibility and inheritance. Disclosed herein is a chronic obstructive pulmonary disease biomarker informative content repository comprising at least one COPD biomarker, apparatus and methods to diagnose, assess, address, and ameliorate related conditions.

Hoidal, John↗
DOE OSTI2016

High Accuracy Signal Validation Framework for Sensor Calibration Assessment in NPPs

Effective and efficient health management of sensing channels and instrumentation supports reliable and accurate process monitoring capacities in any industry. Current practice in the nuclear industry relies on periodic calibration assessment and correction activities. This time based maintenance technique consists of three steps: i) removal of sensor to a test environment, ii) testing and recalibration, and iii) reinstallation of sensor into its working environment. This procedure is highly labor intensive, adds to the outage cost and timeline, and contributes to worker radiation exposure and ALARA requirements. Furthermore, the human element contributes to error factors in all stages of the procedure. The effectiveness of this calibration procedure after sensors are returned to working environmental variables also raises concerns, and the practicability of this periodic approach is uncertain for future reactor designs with longer operating cycles between refueling outages. Studies indicate that periodic calibration assessment find only 10% of sensing instrumentations with calibration issues during a single outage (18- 24 months), meaning at least 90% of sensors are undergoing unnecessary maintenance actions. This provides an opportunity to maintain the current levels of safety and functional integrity with fewer, more targeted maintenance actions and lower economic burden. Performance-based maintenance planning shows much promise over current periodic maintenance approaches. Specifically, online monitoring (OLM) utilizes the continually collected process data to non-intrusively monitor the calibration status of process instrumentation and detect the onset of de-calibration, thereby minimizing the number of recalibration procedures required. Ultimately, this can lead to termination of time based recalibration at NPPs. OLM utilizes the process measurements made for process monitoring and control to evaluate the calibration status of the sensors and instrumentation making the measurements. OLM can detect and differentiate sensor faults and process anomalies, thus providing a valuable tool to suit the industry's and regulatory body's requirements. Though supported by more than a decade of research, OLM for sensor calibration assessment is yet to be implemented in the US fleet due to regulatory requirements and constraints. As shown in Figure 1, OLM utilizes process data to train statistical models that predict normal, error-free process behavior. Measured process values are compared with error-corrected predictions to ascertain the presence of faults. The reliability of OLM is dependent on the quality of its predictions, measured in part by the uncertainty in these predictions. This research develops a framework to accurately quantify the prediction uncertainty based on Bayesian inference techniques to provide the required confidence levels for OLM systems. The expected outcomes include signal validation by high-accuracy, high-confidence uncertainty quantification for variable sensor types and operating ranges. Furthermore, the framework will facilitate fault detection capacities and so-called virtual sensors, a capability to replace faulty sensor measurements with error-corrected values when a sensor fault is detected. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Capturing Historic Reliability Performance Through Graph Databases: A Model Based System Engineering Approach

With the goal of improving the performance and reliability of high dependable technological systems such as nuclear power plants, advanced monitoring and health management systems are employed to inform system engineers on observed degradation processes and anomalous behaviors of assets and components. This information is captured in the form of large amount of data which can be heterogenous in nature (e.g., numeric, textual). Such large data availability poses challenges when system engineers are required to parse and analyze them in order to track historic reliability performance of assets and components. This paper tackles directly this challenge by providing means to organize data in the form of a graph: a knowledge graph. The presented approach distinguish itself from current knowledge graph-based methods by the fact that model-based system engineering (MBSE) models are used to “put data into context”. In particular, MBSE models are used as skeleton of a knowledge graph; numeric and textual data elements, once processed, are associated to MBSE model elements. Thus, a knowledge graph captures both system architecture (though MBSE models) and health/performance data. Such feature opens the door to new data analytics methods designed to identify causal relations between observed phenomena.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Structural health and prognostics management for the enhancement of offshore wind turbine operations and maintenance strategies

Offshore wind turbines are an attractive source for clean and renewable energy for reasons including their proximity to population centers and higher capacity factors. One obstacle to the more widespread installation of offshore wind turbines in the USA, however, is that recent projections of offshore operations and maintenance costs vary from two to five times the land-based costs. One way in which these costs could be reduced is through use of a structural health and prognostics management (SHPM) system as part of a condition-based maintenance paradigm with smart loads management. Our paper contributes to the development of such strategies by developing an initial roadmap for SHPM, with application to the blades. One of the key elements of the approach is a multiscale simulation approach developed to identify how the underlying physics of the system are affected by the presence of damage and how these changes manifest themselves in the operational response of a full turbine. A case study of a trailing edge disbond is analysed to demonstrate the multiscale sensitivity of damage approach and to show the potential life extension and increased energy capture that can be achieved using simple changes in the overall turbine control and loads management strategy. Finally, the integration of health monitoring information, economic considerations such as repair costs versus state of health, and a smart loads management methodology provides an initial roadmap for reducing operations and maintenance costs for offshore wind farms while increasing turbine availability and overall profit.

17 WIND ENERGY↗
DOE OSTI2020

Substation Secondary Asset Health Monitoring and Management System (SSHM)

Electric Power Group, LLC (EPG) was awarded DOE OE0000850 to design, develop, and demonstrate a real-time software application for substation secondary equipment health monitoring and management at host utility American Electric Power (AEP), a cost share partner. This project addresses the need for monitoring substation equipment health and providing operators with tools to identify and take pre-emptive action to avoid catastrophic equipment failure. By monitoring synchrophasor data in real time, data anomalies that indicate potential asset failure can be detected and alerts can be sent to operators in time to take corrective actions. EPG developed two data driven algorithms to identify abnormal equipment signature patterns as well as a method using substation linear state estimation (SLSE). The software has been deployed on hardened PC’s and tested and validated for cost share partner AEP’s substations - 138kV and 765 kV. The SSHM software has been accepted by AEP and final demonstration of DOE - OE0000850 for AEP and DOE was successfully completed on March 17th, 2020. EPG developed the Substation Secondary Asset Health Monitoring (SSHM) Platform to analyze equipment failure signatures in PMU data and alert substation personnel when pre-emptive inspection, repairs and other actions are warranted to prevent potential catastrophic failures. This is the first system that automatically monitors the health of substation secondary assets and alerts users to emerging failures using synchrophasor measurements. SSHM uses high resolution PMU data from PTs, CTs, and CCVTs to analyze equipment signatures and identify anomalies that are precursor indicators of potential equipment failure. When an anomaly is detected, there is a likelihood of potential failure of monitored equipment, the system alerts the user with visual alarms including alarm trend charts and indicator lights on a oneline diagram of the substation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2012

Structural health and prognostics management for offshore wind turbines

Operations and maintenance costs for offshore wind plants are expected to be significantly higher than the current costs for onshore plants. One way in which these costs may be able to be reduced is through the use of a structural health and prognostic management system as part of a condition based maintenance paradigm with smart load management. To facilitate the creation of such a system a multiscale modeling approach has been developed to identify how the underlying physics of the system are affected by the presence of damage and how these changes manifest themselves in the operational response of a full turbine. The developed methodology was used to investigate the effects of a candidate blade damage feature, a trailing edge disbond, on a 5-MW offshore wind turbine and the measurements that demonstrated the highest sensitivity to the damage were the local pitching moments around the disbond. The multiscale method demonstrated that these changes were caused by a local decrease in the blade's torsional stiffness due to the disbond, which also resulted in changes in the blade's local strain field. Full turbine simulations were also used to demonstrate that derating the turbine power by as little as 5% could extend the fatigue life of a blade by as much as a factor of 3. The integration of the health monitoring information, conceptual repair cost versus damage size information, and this load management methodology provides an initial roadmap for reducing operations and maintenance costs for offshore wind farms while increasing turbine availability and overall profit.

Griffith, Daniel Todd↗
DOE OSTI2013

Structural health and prognostics management for offshore wind turbines :

Operations and maintenance costs for offshore wind plants are significantly higher than the current costs for land-based (onshore) wind plants. One way to reduce these costs would be to implement a structural health and prognostic management (SHPM) system as part of a condition based maintenance paradigm with smart load management and utilize a state-based cost model to assess the economics associated with use of the SHPM system. To facilitate the development of such a system a multi-scale modeling approach developed in prior work is used to identify how the underlying physics of the system are affected by the presence of damage and faults, and how these changes manifest themselves in the operational response of a full turbine. This methodology was used to investigate two case studies: (1) the effects of rotor imbalance due to pitch error (aerodynamic imbalance) and mass imbalance and (2) disbond of the shear web; both on a 5-MW offshore wind turbine in the present report. Based on simulations of damage in the turbine model, the operational measurements that demonstrated the highest sensitivity to the damage/faults were the blade tip accelerations and local pitching moments for both imbalance and shear web disbond. The initial cost model provided a great deal of insight into the estimated savings in operations and maintenance costs due to the implementation of an effective SHPM system. The integration of the health monitoring information and O&M cost versus damage/fault severity information provides the initial steps to identify processes to reduce operations and maintenance costs for an offshore wind farm while increasing turbine availability, revenue, and overall profit.

Myrent, Noah J.↗
DOE OSTI2019

Impact of a Low-Intensity Resource Referral Intervention on Patients’ Knowledge, Beliefs, and Use of Community Resources: Results from the CommunityRx Trial

Background: Connecting patients to community-based resources is now a cornerstone of modern healthcare that supports self-management of health. The mechanisms that connect resource information to behavior change, however, remain poorly understood. Objective: To evaluate the impact of CommunityRx, an automated, low-intensity resource referral intervention, on patients' knowledge, beliefs, and use of community resources. Design: Real-world controlled clinical trial at an urban academic medical center in 2015-2016; participants were assigned by alternating week to receive the CommunityRx intervention or usual care. Surveys were administered at baseline, 1 week, 1 month, and 3 months. Participants: Publicly insured adults, ages 45-74 years. Intervention: CommunityRx generated an automated, personalized list of resources, known as HealtheRx, near each participant's home using condition-specific, evidence-based algorithms. Algorithms used patient demographic and health characteristics documented in the electronic health record to identify relevant resources from a comprehensive, regularly updated database of health-related resources in the study area. Main Measures: Using intent-to-treat analysis, we examined the impact of HealtheRx referrals on (1) knowledge of the most commonly referred resource types, including healthy eating classes, individual counseling, mortgage assistance, smoking cessation, stress management, and weight loss classes or groups, and (2) beliefs about having resources in the community to manage health. Key Results: In a real-world controlled trial of 374 adults, intervention recipients improved knowledge (AOR = 2.15; 95% CI, 1.29-3.58) and beliefs (AOR = 1.68; 95% CI, 1.07-2.64) about common resources in the community to manage health, specifically gaining knowledge about smoking cessation (AOR = 2.76; 95% CI, 1.07-7.12) and weight loss resources (AOR = 2.26; 95% CI 1.05-4.84). Positive changes in both knowledge and beliefs about community resources were associated with higher resource use (P = 0.02). Conclusions: In a middle-age and older population with high morbidity, a low-intensity health IT intervention to deliver resource referrals promoted behavior change by increasing knowledge and positive beliefs about community resources for self-management of health. NIH Trial Registry: NCT02435511

60 APPLIED LIFE SCIENCES↗
NASA NTRS1976

Health-care district management information system plan: Review of operations analysis activities during calendar year 1975 and plan for continued research and analysis activities

Operations research activities developed to identify the information required to manage both the efficiency and effectiveness of the Veterans Administration (VA) health services as these services relate to individual patient care are reported. The clinical concerns and management functions that determine this information requirement are discussed conceptually. Investigations of existing VA data for useful management information are recorded, and a diagnostic index is provided. The age-specific characteristics of diseases and lengths of stay are explored, and recommendations for future analysis activities are articulated. The effect of the introduction of new technology to health care is also discussed.

Nielson, G. J.↗
DOE OSTI2014

Structural Health and Prognostics Management for Offshore Wind Turbines: Sensitivity Analysis of Rotor Fault and Blade Damage with O&M Cost Modeling

Operations and maintenance costs for offshore wind plants are significantly higher than the current costs for land-based (onshore) wind plants. One way to reduce these costs would be to implement a structural health and prognostic management (SHPM) system as part of a condition based maintenance paradigm with smart load management and utilize a state-based cost model to assess the economics associated with use of the SHPM system. To facilitate the development of such a system a multi-scale modeling and simulation approach developed in prior work is used to identify how the underlying physics of the system are affected by the presence of damage and faults, and how these changes manifest themselves in the operational response of a full turbine. This methodology was used to investigate two case studies: (1) the effects of rotor imbalance due to pitch error (aerodynamic imbalance) and mass imbalance and (2) disbond of the shear web; both on a 5-MW offshore wind turbine in the present report. Sensitivity analyses were carried out for the detection strategies of rotor imbalance and shear web disbond developed in prior work by evaluating the robustness of key measurement parameters in the presence of varying wind speeds, horizontal shear, and turbulence. Detection strategies were refined for these fault mechanisms and probabilities of detection were calculated. For all three fault mechanisms, the probability of detection was 96% or higher for the optimized wind speed ranges of the laminar, 30% horizontal shear, and 60% horizontal shear wind profiles. The revised cost model provided insight into the estimated savings in operations and maintenance costs as they relate to the characteristics of the SHPM system. The integration of the health monitoring information and O&M cost versus damage/fault severity information provides the initial steps to identify processes to reduce operations and maintenance costs for an offshore wind farm while increasing turbine availability, revenue, and overall profit.

17 WIND ENERGY↗
DOE OSTI2015

Structural Health and Prognostics Management for Offshore Wind Plants (Final Report)

This final report is a compilation of research efforts – funded by the US Department of Energy Wind and Water Power Technologies Office over a four-year period from FY11 through FY14. The goals of this research program were to develop and evaluate technical innovations with promise for maximizing revenues and reducing levelized cost of energy (LCOE) for offshore wind plants – more specifically the goals of the Structural Health and Prognostics Management (SHPM) program were to reduce O&M costs and increase energy capture through use of SHPM-based technologies. A technology roadmap was developed at the start of the project to guide the research efforts. This roadmap identified and outlined six major research thrust areas each having five stages of maturity. Research was conducted in each of these thrust areas, as documented throughout this report, although a major focus was on development of damage detection strategies for the most frequent blade damage conditions and damage mitigation and life-extension strategies via changes in turbine operations (smart loads management). The work summarized in this compilation report is the product of the work of many researchers. A summary of the major findings, status of the SHPM Technology Roadmap and recommendations for future work are also provided.

17 WIND ENERGY↗
DOE OSTI2024

Battery Energy Storage Systems: A Review of Energy Management Systems and Health Metrics

With increasing concerns about climate change, there is a transition from high-carbon-emitting fuels to green energy resources in various applications including household, commercial, transportation, and electric grid applications. Even though renewable energy resources are receiving traction for being carbon-neutral, their availability is intermittent. To address this issue to achieve extensive application, the integration of energy storage systems in conjunction with these resources is becoming a recommended practice. Additionally, in the transportation sector, the increased demand for EVs requires the development of energy storage systems that can deliver energy for rigorous driving cycles, with lithium-ion-based batteries emerging as the superior choice for energy storage due to their high power and energy densities, length of their life cycle, low self-discharge rates, and reasonable cost. As a result, battery energy storage systems (BESSs) are becoming a primary energy storage system. The high-performance demand on these BESS can have severe negative effects on their internal operations such as heating and catching on fire when operating in overcharge or undercharge states. Reduced efficiency and poor charge storage result in the battery operating at higher temperatures. To mitigate early battery degradation, battery management systems (BMSs) have been devised to enhance battery life and ensure normal operation under safe operating conditions. Some BMSs are capable of determining precise state estimations to ensure safe battery operation and reduce hazards. Precise estimation of battery health is computed by evaluating several metrics and is a central factor in effective battery management systems. In this scenario, the accurate estimation of the health indicators (HIs) of the battery becomes even more important within the framework of a BMS. This paper provides a comprehensive review and discussion of battery management systems and different health indicators for BESSs, with suitable classification based on key characteristics.

Nazaralizadeh, Solmaz (ORCID:0009000737004039)↗
DOE OSTI2022

A Population-Level Summary of Health Care Utilization for the Management of Patellar Tendinopathy in the Military Health System

Abstract Patellar tendinopathy (PT) is a common nontraumatic orthopaedic disorder of the knee suffered by many service members. Understanding the make-up of usual care for PT at the system level can better frame current clinical gaps and areas that need improvement. Exercise therapy is recommended as a core treatment for PT, but it is unclear how often it is used as a part of usual care for PT within the Military Health System (MHS). The purpose of the study was to identify interventions used in the management of PT and the timing of these interventions. A secondary purpose was to determine if exercise therapy use was associated with reduced recurrence of knee pain. In total, 4,719 individuals aged 17 to 50 years in the MHS diagnosed with PT between 2010 and 2011 were included. Pharmacological and nonpharmacological interventions, visits to specialty providers, and imaging services were captured. Descriptive statistics were used to report the findings. Interventions were further categorized as being part of initial care (within the first 7 days), the initial episode of care (within the first 60 days), or the 2-year time period after diagnosis. Linear regression assessed the relationship between the number of exercise therapy visits in the initial episode of care and recurrences of knee pain. In total, 50.6% of this cohort had no more than one medical visit total for PT. Exercise therapy (18.2%) and nonsteroidal anti-inflammatory drugs (4.3%) were the two most used interventions in the initial episode of care. Radiographs were ordered for 23.1% of the cohort in the initial episode of care. The number of exercise therapy visits a patient received during the initial episode of care was not associated with recurrences of knee pain. Half of the individuals received no further care beyond an initial visit for the diagnosis of PT. Exercise therapy was the most common intervention used during the initial episode of care, but exercise therapy did not influence the recurrence of knee pain.

Orthopedics↗