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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

High-Temperature Mechanical Tensile Testing of Unidirectional Sic/Sic Composites Using A Versatile Lamp Furnace

Silicon carbide (SiC) based ceramic matrix composites (CMCs) are of interest for high-temperature structural applications, including use in turbine engine components. To understand damage mechanisms and predict durability of these systems, in-depth knowledge of their behavior at ambient and high temperatures is necessary. A method for high temperature testing of SiC/SiC minicomposite specimens up to 1500oC in both tensile fast fracture and creep conditions to investigate their thermomechanical behavior will be presented. This method utilizes a novel radiation heat furnace, equipped with infrared lamps with ellipsoidal reflectors, to heat the specimen at the furnace center in user-defined atmospheres. The housing structure of the lamps allows for observation of the specimen during testing using optical methods and for conducting other experimental studies. The goal is to employ nondestructive health monitoring techniques in-situ, including acoustic emission (AE), electrical resistance (ER), and digital image correlation (DIC) to evaluate damage initiation and evolution in the minicomposite specimens during tensile testing. Results from mechanical testing and nondestructive techniques will be presented. Electron microscopy and X-ray micro-computed tomography were used to further characterize specimen damage after testing.

Aeronautics↗
DOE OSTI2023

Limited Role of Absolute Humidity in Intraurban Heat Variability

Abstract Monitoring and understanding the variability of heat within cities is important for urban planning and public health, and the number of studies measuring intraurban temperature variability is growing. Recognizing that the physiological effects of heat depend on humidity as well as temperature, measurement campaigns have included measurements of relative humidity alongside temperature. However, the role the spatial structure in humidity, independent from temperature, plays in intraurban heat variability is unknown. Here we use summer temperature and humidity from networks of stationary sensors in multiple cities in the United States to show spatial variations in the absolute humidity within these cities are weak. This variability in absolute humidity plays an insignificant role in the spatial variability of the heat index and humidity index (humidex), and the spatial variability of the heat metrics is dominated by temperature variability. Thus, results from previous studies that considered only intraurban variability in temperature will carry over to intraurban heat variability. Also, this suggests increases in humidity from green infrastructure interventions designed to reduce temperature will be minimal. In addition, a network of sensors that only measures temperature is sufficient to quantify the spatial variability of heat across these cities when combined with humidity measured at a single location, allowing for lower-cost heat monitoring networks. Significance Statement Monitoring the variability of heat within cities is important for urban planning and public health. While the physiological effects of heat depend on temperature and humidity, it is shown that there are only weak spatial variations in the absolute humidity within nine U.S. cities, and the spatial variability of heat metrics is dominated by temperature variability. This suggests increases in humidity will be minimal resulting from green infrastructure interventions designed to reduce temperature. It also means a network of sensors that only measure temperature is sufficient to quantify the spatial variability of heat across these cities when combined with humidity measured at a single location.

Meteorology & Atmospheric Sciences↗
NASA NTRSDate not supplied

An Oculometric Standard to Assess the Performance of the Ocular System for Long Duration Spaceflight

Changes in the human brain, due to spaceflight, have been a challenge to the space program since its inception; a challenge that is becoming more acute as extended International Space Station (ISS) missions become routine, a return to crewed lunar exploration is about to begin, and a multi-year crewed trip to Mars is being planned. Determining the extent to which neurophysiological adaptations may adversely impact performance in operational tasks, assessing the full-time course of these changes, and identifying/mitigating any potential long-term health consequences are crucial steps required to enable safe crew-autonomous, long-duration, deep-space missions. Vision is the predominant perceptual sense used to guide cognition and motor control in humans. Thus, it is critical for the success of any future, long-duration mission to understand how long-term exposure to microgravity and to other stressors of spaceflight and their interactions, impact visual function. This is an especially challenging task given the small and disparate samples from which we have been and will be able to collect human performance data. NASA has recently been carefully tracking spaceflight-induced ophthalmic changes, driven in large part by the fluid shifts related to microgravity. In particular, a recent study of Optical Coherence Tomography (OCT) postflight measures revealed that more than two-thirds of US crew members experience significant increases in retinal thickness after 6month or longer ISS missions. Space Associated Neuro-ocular Syndrome (SANS) also includes visual acuity decrements and other ocular structural changes that could adversely impact in-flight performance as missions become longer. However, the impact of spaceflight on the visual system is not limited to the retina. Recent comparisons of pre-and post-flight brain images have revealed structural changes throughout the brain that implicate visual, visuomotor, and visual-cognitive pathways, consistent with observed functional impacts (e.g., decreased speed/accuracy/timing of fine goal-oriented movements). Current limitations on inflight testing make it very difficult to determine when and under what conditions SANS and other disruptions of human neurological subsystems arise. Currently, one cannot anticipate the time course and extent of impairment and recovery. This study addresses this knowledge gap by creating an integrated framework of the relevant existing literature on visual and oculomotor function during spaceflight with an eye towards complementing current structural measures of visuomotor impairment with new oculometric standard measures. Using eye-movement based visual function assessment and diagnostics would provide a valuable enhancement of crew health and performance monitoring in support of deepspace exploration.

Vision↗
NASA NTRS2013

Fiber Optics Deliver Real-Time Structural Monitoring

To alter the shape of aircraft wings during flight, researchers at Dryden Flight Research Center worked on a fiber optic sensor system with Austin-based 4DSP LLC. The company has since commercialized a new fiber optic system for monitoring applications in health and medicine, oil and gas, and transportation, increasing company revenues by 60 percent.

Source record↗
NASA NTRSDate not supplied

Enhancing Fault Isolation for Health Monitoring of Electric Aircraft Propulsion by Embedding Failure Mode and Effect Analysis into Bayesian Networks

This paper describes a fault isolation approach for electric powertrains of unmanned aerial vehicles. The approach leverages the combination of failure mode and effect analysis (FMEA) and Bayesian networks, thus introducing depend-ability structures into a diagnostic framework. Faults and failure events from the FMEA are mapped within a Bayesian network, where network edges replicate the links embedded within FMEAs. This framework helps the fault isolation process by identifying the probability of occurrence of specific faults or root causes given evidence observed through sensor signals. The framework is applied to an electric power-train system of a small, rotary-wing unmanned aerial vehicle, demonstrating how a Bayesian network enhanced by FMEA helps disambiguate between root causes of incipient failures, which would otherwise be considered as equally probable.

Fault Isolation↗
DOE OSTI2022

A tailored fast thioacidolysis method incorporating multi-reaction monitoring mode of GC-MS for higher sensitivity on lignin monomer quantification

Abstract Thioacidolysis is widely used for lignin structural characterization by cleaving β-aryl ethers to release syringyl (S), guaiacyl (G), and p -hydroxyphenyl (H) monomers followed by GC analysis. However, the traditional thioacidolysis method requires tedious extraction steps with chlorinated solvent underlying harmful to health, limiting its efficiency and application. Herein, an improved thioacidolysis method with high sensitivity for the quantitation of lignin-derived monomers was developed. The improved protocol used a quick, streamlined procedure to recover the monomeric products using ethyl acetate as extracting solvent and MS detector in multi-reaction monitoring mode to enhance its ability to detect extremely low concentration (0.1 ppb with signal-to-noise higher than 2) of monomeric products. Additionally, a fast GC program was established to speed up the GC quantitation. Several representative lignocellulose samples, including gymnosperm, angiosperm, and poaceae, were used to test this tailored method. The results demonstrated that the ratios of lignin monomer compositions determined by this method were consistent with that of traditional procedure despite the slightly higher monomer yields measured. More importantly, this method uses non-chlorinated solvent for microscale extraction and requires no evaporation step for workup, which is a green and efficient way for the quantification of lignin monomer compositions.

Forestry↗
NASA NTRS2010

Improved Signal Processing Technique Leads to More Robust Self Diagnostic Accelerometer System

The self diagnostic accelerometer (SDA) is a sensor system designed to actively monitor the health of an accelerometer. In this case an accelerometer is considered healthy if it can be determined that it is operating correctly and its measurements may be relied upon. The SDA system accomplishes this by actively monitoring the accelerometer for a variety of failure conditions including accelerometer structural damage, an electrical open circuit, and most importantly accelerometer detachment. In recent testing of the SDA system in emulated engine operating conditions it has been found that a more robust signal processing technique was necessary. An improved accelerometer diagnostic technique and test results of the SDA system utilizing this technique are presented here. Furthermore, the real time, autonomous capability of the SDA system to concurrently compensate for effects from real operating conditions such as temperature changes and mechanical noise, while monitoring the condition of the accelerometer health and attachment, will be demonstrated.

Tokars, Roger↗
NASA NTRS1998

Noncontact Determination of Antisymmetric Plate Wave Velocity in Ceramic Matrix Composites

High-temperature materials are of increasing importance in the development of more efficient engines and components for the aeronautics industry. In particular, ceramic matrix composite (CMC) and metal matrix composite (MMC) structures are under active development for these applications. The acousto-ultrasonic (AU) method has been shown to be useful for assessing mechanical properties in composite structures. In particular, plate wave analysis can characterize composites in terms of their stiffness moduli. It is desirable to monitor changes in mechanical properties that occur during thermomechanical testing and to monitor the health of components whose geometry or position make them hard to reach with conventional ultrasonic probes. In such applications, it would be useful to apply AU without coupling directly to the test surface. For a number of years, lasers have been under investigation as remote ultrasonic input sources and ultrasound detectors. The use of an ultrasonic transducer coupled through an air gap has also been under study. So far at the NASA Lewis Research Center, we have been more successful in using lasers as ultrasonic sources than as output devices. On the other hand, we have been more successful in using an air-coupled piezoelectric transducer as an output device than as an input device. For this reason, we studied the laser in/air-coupled-transducer out combination-using a pulsed NdYAG laser as the ultrasonic source and an air-coupled-transducer as the detector. The present work is focused on one of the AU parameters of interest, the ultrasonic velocity of the antisymmetric plate-wave mode. This easily identified antisymmetric pulse can be used to determine shear and flexure modulus. It was chosen for this initial work because the pulse arrival times are likely to be the most precise. The following schematic illustrates our experimental arrangement for using laser in/air-transducer out on SiC/SiC composite tensile specimens. The NdYAG pulse was directed downward by a 90 infrared prism to the top of the specimen, but at the edge of one end. An energy sensor measured a single pulse at 13 millijoules (mJ) before it passed through the prism, which attenuated 15 percent of its energy. It also provided an output trigger for the waveform time-delay synthesizer.

Kautz, Harold E.↗
NASA NTRS1998

High-Temperature Magnetic Bearings Being Developed for Gas Turbine Engines

Magnetic bearings are the subject of a new NASA Lewis Research Center and U.S. Army thrust with significant industry participation, and cooperation with other Government agencies. The NASA/Army emphasis is on high-temperature applications for future gas turbine engines. Magnetic bearings could increase the reliability and reduce the weight of these engines by eliminating the lubrication system. They could also increase the DN (diameter of bearing times the rpm) limit on engine speed and allow active vibration cancellation systems to be used, resulting in a more efficient, "more electric" engine. Finally, the Integrated High Performance Turbine Engine Technology (IHPTET) program, a joint Department of Defense/industry program, identified a need for a high-temperature (1200 F) magnetic bearing that could be demonstrated in their Phase III engine. This magnetic bearing is similar to an electric motor. It has a laminated rotor and stator made of cobalt steel. Wound around the stator's circumference are a series of electrical wire coils which form a series of electric magnets that exert a force on the rotor. A probe senses the position of the rotor, and a feedback controller keeps it centered in the cavity. The engine rotor, bearings, and casing form a flexible structure with many modes. The bearing feedback controller, which could cause some of these modes to become unstable, could be adapted to varying flight conditions to minimize seal clearances and monitor the health of the system.

Kascak, Albert F.↗
NASA NTRS2017

The Potential for Health Monitoring in Expandable Space Modules: The Bigelow Expandable Activity Module on the ISS

Expandable modules for use in space and on the Moon or Mars offer a great opportunity for volume and mass savings in future space exploration missions. This type of module can be compressed into a relatively small shape on the ground, allowing them to fit into space vehicles with a smaller cargo/fairing size than a traditional solid, metallic structure based module would allow. In April 2016, the Bigelow Expandable Activity Module (BEAM) was berthed to the International Space Station (ISS). BEAM is the first human-rated expandable habitat/module to be deployed and crewed in space. BEAM is a NASA managed ISS payload project in partnership with Bigelow Aerospace. BEAM is intended to stay attached to ISS for an operational period of 2 years to help advance the technology readiness for future expandable modules. BEAM has been instrumented with a suite of space flight certified sensors systems which will help characterize the module's performance for thermal, radiation shielding and impact monitoring against potential Micro Meteoroid/Orbital Debris (MM/OD) providing fundamental information on the BEAM environment for potential health monitoring requirements and capabilities. This paper will provide an overview of how the sensors/instrumentation systems were developed, tested, installed and an overview of the current sensor system operations. It will also discuss how the MM/OD impact detection system referred to as the Distributed Impact Detection System (DIDS) data is being processed and reviewed on the ground by the principle investigators.

Wells, Nathan D.↗
NASA NTRSDate not supplied

Integration of Advanced Structures and Materials Technologies for a Robust Lunar Habitat

NASA’s Artemis program plans to have a sustainable lunar base deployed on the Moon by 2028. The base calls for a foundation surface habitat that can support a crew of four members for a minimum mission duration of 28-days. The lack of a magnetic field and significant lunar atmosphere extends the lifetime of secondary radiation emitted from metallic structures, which is a health hazard for exposed astronauts. Integration of non-metallic structural materials into surface habitat design may alleviate some of these concerns. Additionally, it is favorable for the structure to be collapsible for transportation to optimize payload volume, mass efficiency, and monetary constraints. As a result, inflatable structures are being investigated due to their improved packing efficiency at launch, optimal mass-to-volume ratio, and large surface area that can efficiently disperse structural loads and heat. Currently, only two inflatable airlocks have been deployed in space. Thus, there is a significant need to advance technologies associated with inflatable structures to provide greater options for future missions, i.e., Artemis and beyond. This study focused on the inflatable lunar habitat applications of emerging NASA Langley Research Center (LaRC) technologies and their required development steps to become space qualified. The Bowling Habitat architecture was generated from 13 of these NASA LaRC technologies, five of which were deemed critical, five determined as enhancing technologies, and three were classified as transformational technologies for the Artemis program. To address the payload constraints, the study also considered a tentative timeline that aligned with the current Artemis schedule for transporting the Bowling Habitat to the Moon. Ultimately, the Bowling Habitat mainly addressed the structural needs of an inflatable lunar habitat, meaning that major areas pertaining to the life-style aspects of the habitat must be improved. Areas include, but are not limited to, hard connection points, the monitoring of human health, and extra radiation protection for solar proton events.

Inflatable Habitat↗
NASA NTRS2020

Advancing Methodologies for Applying Machine Learning and Evaluating Spatiotemporal Models of Fine Particulate Matter (PM 2.5 ) Using Satellite Data Over Large Regions

Reconstructing the distribution of fine particulate matter (PM 2.5 ) in space and time, even far from ground monitoring sites, is an important exposure science contribution to epidemiologic analyses of PM 2.5 health impacts. Flexible statistical methods for prediction have demonstrated the integration of satellite observations with other predictors, yet these algorithms are susceptible to overfitting the spatiotemporal structure of the training datasets. We present a new approach for predicting PM 2.5 using machine-learning methods and evaluating prediction models for the goal of making predictions where they were not previously available. We apply extreme gradient boosting (XGBoost) modeling to predict daily PM 2.5 on a 1 x 1 km 2 resolution for a 13 state region in the Northeastern USA for the years 2000–2015 using satellite-derived aerosol optical depth and implement a recursive feature selection to develop a parsimonious model. We demonstrate excellent predictions of withheld observations but also contrast an RMSE of 3.11 μg/m 3 in our spatial cross-validation withholding nearby sites versus an overfit RMSE of 2.10 μg/m 3 using a more conventional random ten-fold splitting of the dataset. As the field of exposure science moves forward with the use of advanced machine-learning approaches for spatiotemporal modeling of air pollutants, our results show the importance of addressing data leakage in training, overfitting to spatiotemporal structure, and the impact of the predominance of ground monitoring sites in dense urban sub-networks on model evaluation. The strengths of our resultant modeling approach for exposure in epidemiologic studies of PM 2.5 include improved efficiency, parsimony, and interpretability with robust validation while still accommodating complex spatiotemporal relationships.

air pollution↗
DOE OSTI2025

Advancing ocean monitoring and knowledge for societal benefit: the urgency to expand Argo to OneArgo by 2030

The ocean plays an essential role in regulating Earth’s climate, influencing weather conditions, providing sustenance for large populations, moderating anthropogenic climate change, encompassing massive biodiversity, and sustaining the global economy. Human activities are changing the oceans, stressing ocean health, threatening the critical services the ocean provides to society, with significant consequences for human well-being and safety, and economic prosperity. Effective and sustainable monitoring of the physical, biogeochemical state and ecosystem structure of the ocean, to enable climate adaptation, carbon management and sustainable marine resource management is urgently needed. The Argo program, a cornerstone of the Global Ocean Observing System (GOOS), has revolutionized ocean observation by providing real-time, freely accessible global temperature and salinity data of the upper 2,000m of the ocean (Core Argo) using cost-effective simple robotics. For the past 25 years, Argo data have underpinned many ocean, climate and weather forecasting services, playing a fundamental role in safeguarding goods and lives. Argo data have enabled clearer assessments of ocean warming, sea level change and underlying driving processes, as well as scientific breakthroughs while supporting public awareness and education. Building on Argo’s success, OneArgo aims to greatly expand Argo’s capabilities by 2030, expanding to full-ocean depth, collecting biogeochemical parameters, and observing the rapidly changing polar regions. Providing a synergistic subsurface and global extension to several key space-based Earth Observation missions and GOOS components, OneArgo will enable biogeochemical and ecosystem forecasting and new long-term climate predictions for which the deep ocean is a key component. Driving forward a revolution in our understanding of marine ecosystems and the poorly-measured polar and deep oceans, OneArgo will be instrumental to assess sea level change, ocean carbon fluxes, acidification and deoxygenation. Emerging OneArgo applications include new views of ocean mixing, ocean bathymetry and sediment transport, and ecosystem resilience assessment. Implementing OneArgo requires about $100 million annually, a significant increase compared to present Argo funding. OneArgo is a strategic and cost-effective investment which will provide decision-makers, in both government and industry, with the critical knowledge needed to navigate the present and future environmental challenges, and safeguard both the ocean and human wellbeing for generations to come.

ARGO↗
NASA NTRS2017

Near Real-Time Probabilistic Damage Diagnosis Using Surrogate Modeling and High Performance Computing

This work investigates novel approaches to probabilistic damage diagnosis that utilize surrogate modeling and high performance computing (HPC) to achieve substantial computational speedup. Motivated by Digital Twin, a structural health management (SHM) paradigm that integrates vehicle-specific characteristics with continual in-situ damage diagnosis and prognosis, the methods studied herein yield near real-time damage assessments that could enable monitoring of a vehicle's health while it is operating (i.e. online SHM). High-fidelity modeling and uncertainty quantification (UQ), both critical to Digital Twin, are incorporated using finite element method simulations and Bayesian inference, respectively. The crux of the proposed Bayesian diagnosis methods, however, is the reformulation of the numerical sampling algorithms (e.g. Markov chain Monte Carlo) used to generate the resulting probabilistic damage estimates. To this end, three distinct methods are demonstrated for rapid sampling that utilize surrogate modeling and exploit various degrees of parallelism for leveraging HPC. The accuracy and computational efficiency of the methods are compared on the problem of strain-based crack identification in thin plates. While each approach has inherent problem-specific strengths and weaknesses, all approaches are shown to provide accurate probabilistic damage diagnoses and several orders of magnitude computational speedup relative to a baseline Bayesian diagnosis implementation.

Warner, James E.↗
NASA NTRSDate not supplied

Thin-Film Embedded Sensors for Battery Health Monitoring

Hybrid or all-electric aircraft are being developed as the next generation of aircraft to both allow new forms of aviation and decrease environmental impact. Since these types of aircraft are based on high-capacity battery technology, safe operation of these batteries becomes increasingly important. In particular, the potential for battery failure due to uncontrolled chemical reactions resulting in thermal runaway, catastrophic failure, and battery fires must be addressed in order for such battery technology to have the level of safety needed for standard aviation implementation. Efforts to ensure battery safety often involve engineering solutions that seek to contain rather than prevent such events by early detection. Such approaches increase the system weight and decrease the power per unit mass provided by the battery system. Existing methods for measuring battery parameters to determine the battery state-of-health are limited. These methods include electrical measurements of the cell current and/or voltage output as well as temperature measurements taken externally on the cell surface. Such external temperature measurements are limited in their ability to provide early warning of impending battery failure. In response, an effort to develop sensors operating internal to battery for health monitoring has been ongoing in the NASA Sensor-based Prognostics to Avoid Runaway Reactions & Catastrophic Ignition (SPARRCI) project. The basic approach associated with this sensor work is the deposition of thin film sensors on the battery separator located between the anode and cathode of the battery. These thin film sensors are then monitored to determine changes in battery parameters and health. Microfabrication techniques are employed to minimize the overall impact of the sensors on battery operation through the implementation of sensors with minimal size, weight, and power consumption. The thickness of the films, which are fabricated through physical vapor deposition (sputtering), are on the order of thousands of angstroms and can have minimal surface area. Thin film sensors for system health management have been implemented for a many decades on complex components for aerospace applications. However, the application of thin films of this type on a battery separator for internal battery monitoring applications has not previously been demonstrated to our knowledge. This paper describes the development of sensors for the internal battery monitoring through the use of thin film sensor technology. Thin metal films were successfully deposited on a battery separator polymer material with good adherence and electrical continuity. Multiple types of sensors have been deposited, as well as lead connections from the sensor to the edge of the separator material. The ability of these thin film sensors immersed in electrolyte to perform multiple types of battery parameter measurements has been demonstrated. For example, a multiparameter sensor system measured multiple properties simultaneously inside of a pouch cell over a wide temperature range. Further, real time measurement of interior temperature changes in a battery pouch cell with an integrated interior temperature sensor was demonstrated. These changes include detecting a fault in the battery (shorting) in situ with rapid response time (less than a minute) corresponding to a more limited response by a temperature sensor mounted externally. Other aspects of monitoring battery health were also explored, such as real-time measurement of simulated dendrite growth/metal deposition by sensor on separator material demonstrated. Future efforts will include improvements in the durability of the sensor structure to allow introduction of the approach into standard battery fabrication techniques. Overall, this work is a step forward in providing a method to prevent catastrophic battery failures and provide a foundation for safer, lighter, and higher energy batteries for the electric aircraft industry.

thin film battery health↗
NASA NTRS1994

Milestone 4: Thrust structure concepts and IHM screening Graphite Composite Primary Structure (GCPS)

The first part of the task was to select up to three promising thrust structure constructions and to select materials for screening tests. Part of the nondestructive evaluation and inspection (NDE/I) and integrated health management (IHM) task is to acquire and develop NDE/I sensor technologies and to integrate those sensors into the full scale test articles which will be produced under the TA2 program. Review of the anticipated fault modes and the available sensor technology data indicates that three sensor technologies should be assessed for the in-situ monitoring of the composite primary structure elements. These are: ultrasonics (dry contact), acoustic emissions, and fiber optics (embedded or attached). In fact, a combination of sensor technologies will be needed to detect and evaluate the fault modes; not only do sensor technology have specific capabilities and applicability, but the three Gr/Ep primary structures being demonstrated under the TA2 effort have differing requirements based on their respective failure modes and designs.

Greenberg, H. S.↗
NASA NTRS1990

A silicon micromachined piezoresistive accelerometer for health and condition monitoring

Silicon micromachining etching techniques were utilized to batch-fabricate hundreds of general purpose microaccelerometers on a single silicon substrate. Piezoresistive sensing elements were aligned to the back-side patterns using an IR mask aligner and then diffused into the areas of maximum stress. Capping of the two-arm cantilever beam structure was achieved using a combination of electrostatic bonding and low temperature glass films. Overrange protection, critical damping, and overall protection from the outside environment are achieved by controlling the cavity depths of the top and bottom covers. Temperature compensation, amplification, and filtering are performed by a companion LSI chip that is interfaced to the accelerometer by conventional wire-bonding techniques.

Walsh, Kevin M.↗
NASA NTRS2009

Optical Diagnostics for High-Temperature Thermal Barrier Coatings

Thermal barrier coatings (TBCs) are typically composed of translucent ceramic oxides that provide thermal protection for metallic components exposed to high-temperature environments, such as in jet turbine engines. Taking advantage of the translucent nature of TBCs, optical diagnostics have been developed that can provide an informed assessment of TBC health that will allow mitigating action to be taken before TBC degradation threatens performance or safety. In particular, rare-earth-doped luminescent sublayers have been integrated into the TBC structure to produce luminescence that monitors TBC erosion, delamination, and temperature gradients. Erosion monitoring of TBC-coated specimens is demonstrated by utilizing visible luminescence that is excited from a sublayer that is exposed by erosion. TBC delamination monitoring is achieved in TBCs with a base rare-earth-doped luminescent sublayer by the reflectance-enhanced increase in luminescence produced in regions containing buried delamination cracks. TBC temperature monitoring is demonstrated using the temperature-dependent decay time for luminescence originating from the specific coating depth associated with a rare-earth-doped luminescent sublayer. The design and implementation of these TBCs with integrated luminescent sublayers is discussed, including co-doping strategies to produce more penetrating near-infrared luminescence. It is demonstrated that integration of the rare-earth-doped sublayers is achieved with no reduction in TBC life. In addition, results for multilayer TBCs designed to also perform as radiation barriers are also presented.

Eldridge, Jeffrey I.↗