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Results for “degradation diagnostics”

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 145 records · Page 8

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NASA NTRS1990

Real-time diagnostics of the reusable rocket engine using on-line system identification

A model-based failure diagnosis system has been proposed for real-time diagnosis of SSME failures. Actuation, sensor, and system degradation failure modes are all considered by the proposed system. In the case of SSME actuation failures, it was shown that real-time identification can effectively be used for failure diagnosis purposes. It is a direct approach since it reduces the detection, isolation, and the estimation of the extent of the failures to the comparison of parameter values before and after the failure. As with any model-based failure detection system, the proposed approach requires a fault model that embodies the essential characteristics of the failure process. The proposed diagnosis approach has the added advantage that it can be used as part of an intelligent control system for failure accommodation purposes.

Guo, T.-H.↗

DOE OSTI2026

Failure Mode and Effects Analysis (FMEA) for Photovoltaic Inverter

Photovoltaic (PV) inverters are critical yet vulnerable components in modern energy systems, often acting as reliability bottlenecks that increase the levelized cost of energy (LCOE). To address this, this paper presents a comprehensive Failure Mode and Effects Analysis (FMEA) tailored for PV inverters. Leveraging field data and literature, we identify failure-prone components, such as capacitors,, and relays, and prioritize their risks based on quantitative Risk Priority Numbers (RPNs). The analysis reveals that surge-induced MOV short circuits, capacitor degradation, and environmental cooling fan failures dominate the risk profile. These findings provide a targeted framework for reliability improvement, guiding future efforts in predictive diagnostics, design optimization, and accelerated life testing strategies.

14 SOLAR ENERGY↗

DOE OSTI2021

Abiotic and Biotic Damage of Microalgae Generate Different Volatile Organic Compounds (VOCs) for Early Diagnosis of Algal Cultures for Biofuel Production

Open microalgal ponds used in industrial biomass production are susceptible to a number of biotic and abiotic environmental stressors (e.g., grazers, pathogens, pH, temperature, etc.) resulting in pond crashes with high economic costs. Identification of signature chemicals to aid in rapid, non-invasive, and accurate identification of the stressors would facilitate targeted and effective treatment to save the algal crop from a catastrophic crash. Specifically, we were interested in identifying volatile organic compounds (VOCs) that can be used to as an early diagnostic for algal crop damage. Cultures of Microchloropsis gaditana were subjected to two forms of algal crop damage: (1) active grazing by the marine rotifer, Brachionus plicatilis, or (2) repeated freeze–thaw cycles. VOCs emitted above the headspace of these algal cultures were collected using fieldable solid phase microextraction (SPME) fibers. An untargeted analysis and identification of VOCs was conducted using gas chromatography-mass spectrometry (GC-MS). Diagnostic VOCs unique to each algal crop damage mechanism were identified. Active rotifer grazing of M. gaditana was characterized by the appearance of carotenoid degradation products, including β-cyclocitral and various alkenes. Freeze–thaw algae produced a different set of VOCs, including palmitoleic acid. Both rotifer grazing and freeze–thawed algae produced β-ionone as a VOC, possibly suggesting a common stress-induced cellular mechanism. Importantly, these identified VOCs were all absent from healthy algal cultures of M. gaditana. Early detection of biotic or abiotic environmental stressors will facilitate early diagnosis and application of targeted treatments to prevent algal pond crashes. Thus, our work further supports the use of VOCs for monitoring the health of algal ponds to ultimately enhance algal crop yields for production of biofuel.

09 BIOMASS FUELS↗

NASA NTRS1992

Design of a solar array simulator for the NASA EOS testbed

The present spacecraft solar array simulator addresses both dc and ac characteristics as well as changes in illumination and temperature and performance degradation over the course of array service life. The computerized control system used allows simulation of a complete orbit cycle, in addition to automated diagnostics. The simulator is currently interfaced with the NASA EOS testbed.

Butler, Steve J.↗

NASA NTRS2024

Single Drop Cytometry Onboard the International Space Station

Real-time lab analysis is needed to support clinical decision making and research on human missions to the Moon and Mars. Powerful laboratory instruments, such as flow cytometers, are generally too cumbersome for spaceflight. Here, we show that scant test samples can be measured in microgravity, by a trained astronaut, using a miniature cytometry-based analyzer, the rHEALTH ONE, modified specifically for spaceflight. The base device addresses critical spaceflight requirements including minimal resource utilization and alignment-free optics for surviving rocket launch. To fully enable reduced gravity operation onboard the space station, we incorporated bubble-free fluidics, electromagnetic shielding, and gravity-independent sample introduction. We show microvolume flow cytometry from 10 μL sample drops, with data from five simultaneous channels using 10 μs bin intervals during each sample run, yielding an average of 72 million raw data points in approximately 2 minutes. We demonstrate the device measures each test sample repeatably, including correct identification of a sample that degraded in transit to the International Space Station. This approach can be utilized to further our understanding of spaceflight biology and provide immediate, actionable diagnostic information for management of astronaut health without the need for Earth-dependent analysis.

Daniel J. Rea↗

NASA NTRS1989

Soft X-ray diagnostics of electron-heated solar flare atmospheres

The dependence of the impulsive-phase Ca XIX w line profile on the form of the flare energy input (assumed to be due to the collisional degradation of a beam of high-energy electrons) is considered. The injected flux spectrum has the form of a power law with a low-energy 'knee', and the effects of varying the total energy flux, spectral index, and knee energy on the w line profile during the impulsive phase have been evaluated. Early in the burst, blueshifts of order 400 km/s are noted, and the peak intensity of the blueshifted component together with spatially unresolved hard X-ray burst spectra can be used to determine the beam filling factor.

Li, Peng↗

DOE OSTI2025

Nanoscopic strain evolution in single-crystal battery positive electrodes

Single-crystal Ni-rich layered oxides (SC-NMC) with a grain-boundary-free configuration have effectively addressed the long-standing cracking issue of conventional polycrystalline Ni-rich materials (PC-NMC) in lithium-ion batteries, prompting a shift in optimization strategies. However, continued reliance on anisotropic lattice volume change—a well-established failure indicator in PC-NMC—as a metric for understanding strain and guiding compositional design for SC-NMC becomes controversial. Here, in this study, by leveraging multiscale diagnostic techniques, we unravelled the distinct nanoscopic strain evolution in SC-NMC during battery operation, challenging the conventional composition-driven strategies and mechanical degradation indicators used for PC-NMC. Through particle-level chemomechanical analysis, we reveal a decoupling between mechanical stability and lattice volume change in SC-NMC, identifying that structural instability in SC materials is primarily driven by multidimensional lattice distortions induced by kinetics-driven reaction heterogeneity and progressively deactivating chemical phases. Using this mechanical failure mode, we redefine the roles of cobalt and manganese in maintaining mechanical stability. Unlike cobalt’s detrimental role in PC-NMC, we find cobalt to be critical in enhancing the longevity of SC-NMC by mitigating localized strain along the extended diffusion pathway, whereas manganese exacerbates mechanical degradation.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Experimental study of high-k turbulence during an energy confinement degradation phase in EAST ohmic plasmas

In this paper, we present experimental studies of both high-k(r) ( cm(-1), and , respectively; ) and high- ( cm(-1), and , respectively; ) turbulence behavior during an ohmic energy confinement degradation phase in experimental advanced superconducting tokamak (EAST). High-k(r) turbulence from density fluctuation at and high- turbulence from density fluctuation at -0.97 were measured by tangential and poloidal CO2 laser collective scattering diagnostics, respectively. Note that k(r), , and are radial wavenumber, poloidal wavenumber, perpendicular wavenumber and ion gyroradius at electron temperature, respectively. Both high-k(r)/ turbulence power and energy confinement time are found to be temporally correlated to line-averaged electron density n(e) in the plasma current flat-top phase (I-p = 0.4 MA): when the n(e) shows continuous increase/decrease, the high-k(r)/ turbulence power increases/decreases correspondingly and the shows corresponding decrease/increase; the stable n(e) is related to stable both and high-k(r)/ turbulence power. Statistical results of high-k(r)/ turbulence power versus further imply that high-k(r)/ turbulence shows a strong correlation with plasma energy confinement degradation in high line-averaged n(e) condition, but high-k(r) and high- turbulence have relatively weak and no dependence on the transition between linear range in low-n(e) condition and energy confinement degradation in the high-n(e) condition, respectively. Moreover, profiles of electron temperature T-e and n(e) as well as their normalized gradients in a part of high- density fluctuation measurement region also have been given to qualitatively explain the enhancement of turbulence power with the increase of line-averaged n(e).

EAST tokamak↗

DOE OSTI2022

Characterization of self-magnetic pinch (SMP) radiographic diode performance on RITS-6 at Sandia National Laboratories. I. Diode dynamics, DC heating to extend radiation pulse

Radiographic diodes focus on an intense electron beam to a small spot size to minimize the source area of energetic photons for radiographic interrogation. The self-magnetic pinch (SMP) diode has been developed as such a source and operated as a load for the six-cavity radiographic integrated test stand (RITS-6) inductive voltage adder driver. While experiments support the generally accepted conclusion that a 1:1 aspect diode (cathode diameter equals anode–cathode gap) delivers optimum SMP performance, such experiments also show that reducing the cathode diameter, while reducing spot size, also results in reduced radiation dose, by as much as 50%, and degraded shot reproducibility. Analysis of the effective electron impingement angle on the anode converter with time made possible by a newly developed dose-rate array diagnostic indicates that fast-developing oscillations of the angle are correlated with early termination of the radiation pulse on many of the smaller-diameter SMP shots. This behavior as a function of relative cathode size persists through experiments with output voltages and currents up to 11.5 MV and 225 kA, respectively, and with spot sizes below approximately few millimeters. Since simulations to date have not predicted such oscillatory behavior, considerable discussion of the angle behavior of SMP shots is made to lend credence to the inference. We report there is clear anecdotal evidence that DC heating of the SMP diode region leads to stabilization of this oscillatory behavior. This is the first of two papers on the performance of the SMP diode on the RITS-6 accelerator.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Characterization of Self-Magnetic Pinch (SMP) radiographic diode performance on RITS-6 at Sandia National Laboratories: 1) Diode Dynamics, DC Heating to extend Radiation Pulse

Radiographic diodes focus an intense electron beam to a small spot size to minimize the source area of energetic photons for radiographic interrogation. The self-magnetic pinch (SMP) diode has been developed as such a source and operated as a load for the RITS-6 Inductive Voltage Adder (IVA) driver. While experiments support the generally accepted conclusion that a 1:1 aspect diode (cathode diameter equals anode-cathode gap) delivers optimum SMP performance, such experiments also show that reducing the cathode diameter, while reducing spot size, also results in reduced radiation dose, by as much as 50%, and degraded shot reproducibility. Analyzation of the effective electron impingement angle on the anode converter with time made possible by a newly developed dose-rate array diagnostic indicates that fast-developing oscillations of the angle are correlated with early termination of the radiation pulse on many of the smaller-diameter SMP shots. This behavior as a function of relative cathode size persists through experiments with output voltages and currents up to 11.5 MV and 225 kA, respectively, and with spot sizes below ~ few mm. Since simulations to date have not predicted such oscillatory behavior, considerable discussion of the angle-behavior of SMP shots is made to lend credence to the inference. There is clear anecdotal evidence that DC heating of the SMP diode region leads to stabilization of this oscillatory behavior. This is the first of two papers on the performance of the SMP diode on the RITS-6 accelerator.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2011

Effect of Whole-Body Vibration on Speech: Effect on Intelligibility - Part 2

The effect on speech intelligibility was measured for speech where talkers reading Diagnostic Rhyme Test material were exposed to 0.7 g whole body vibration to simulate space vehicle launch. Across all talkers, the effect of vibration was to degrade the percentage of correctly transcribed words from 83% to 74%. The magnitude of the effect of vibration on speech communication varies between individuals, for both talkers and listeners. A worst case scenario for intelligibility would be the most sensitive listener hearing the most sensitive talker; one participant s intelligibility was reduced by 26% (97% to 71%) for one of the talkers.

Begault, Durand R.↗

NASA NTRS1973

Development of a standardized battery of performance tests for the assessment of noise stress effects

A set of 36 relatively independent categories of human performance were identified. These categories encompass human performance in the cognitive, perceptual, and psychomotor areas, and include diagnostic measures and sensitive performance metrics. Then a prototype standardized test battery was constructed, and research was conducted to obtain information on the sensitivity of the tests to stress, the sensitivity of selected categories of performance degradation, the time course of stress effects on each of the selected tests, and the learning curves associated with each test. A research project utilizing a three factor partially repeated analysis of covariance design was conducted in which 60 male subjects were exposed to variations in noise level and quality during performance testing. Effects of randomly intermittent noise on performance of the reaction time tests were observed, but most of the other performance tests showed consistent stability. The results of 14 analyses of covariance of the data taken from the performance of the 60 subjects on the prototype standardized test battery provided information which will enable the final development and test of a standardized test battery and the associated development of differential sensitivity metrics and diagnostic classificatory system.

Theologus, G. C.↗

DOE OSTI2020

Nonlinear integrable optics beam dynamics experiment and diagnostics

All present circular particle accelerators are built around linear focusing optics. Un-avoidable nonlinear elements appear in accelerators, such as magnetic aberrations and space-charge effects, which are typically corrected using nonlinear magnets. However, these added nonlinearities degrade particle beam stability, and in most cases, the system becomes non-integrable. The Integrable Optics Test Accelerator (IOTA), at Fermi National Accelerator Laboratory (Fermilab), is a test bed to study beam dynamics in integrable lattices for both electron and proton beams, independently. This work presents experimental results of the nonlinear electron beam dynamics behavior in IOTA using an elliptical nonlinear magnet. The elliptical nonlinear magnet allows for a large betatron tune spread, allowing for a stable high-intensity beam. In a future experimental run, minimally invasive beam instrumentation is needed to study time-dependent collective instabilities, and halo formation in space-chargedominated proton beams. Traditional profile monitors are too destructive to the beam or just measure one dimension of the beam. A gas sheet can be injected perpendicular to theproton beam at an angle. By doing so, a two-dimensional, turn-by-turn, transverse profile measurement can be made, which will preserve the integrity of the beam. The developmentand progress of a gas sheet beam profile monitor will also be presented.

43 PARTICLE ACCELERATORS↗

DOE OSTI2026

Artificial Intelligence Thermostat to Detect Faults

Residential air conditioners and heat pumps often experience faults due to inadequate maintenance, which can severely reduce efficiency or even cause system failure. Common issues include dirty or clogged air filters and refrigerant leaks. These problems degrade performance and increase energy use and operating costs. This study presents a smart thermostat with embedded artificial intelligence to detect such faults and alert homeowners when maintenance is needed. The thermostat uses low-cost measurements—including return-air temperature, relative humidity, supply-air temperature, outdoor-air temperature, and condenser subcooling—to identify abnormal operations. Because different faults produce distinct response patterns, tailored algorithms are developed to recognize characteristic fault signatures. The investigation is built on a detailed co-simulation platform that couples EnergyPlus with the DOE/ORNL Heat Pump Design Model (HPDM). EnergyPlus represents the building’s dynamic environment, while HPDM is a high-fidelity, hardware-based model that can simulate fault-free performance as well as a wide range of faults, including gradual degradation such as minor refrigerant leakage. This platform provides a virtual training and testing environment that helps distinguish fault-induced behavior from normal operation and supports development of robust diagnostic algorithms. Using this framework, a Dynamic Bayesian Network was developed to identify two common faults—gradual refrigerant charge loss and indoor airflow blockage—and the AI-embedded thermostat was verified through annual building simulations.

Shen, Bo [ORNL] (ORCID:0000000336600393)↗

DOE OSTI2021

Outlier classification using autoencoders: application for fluctuation driven flows in fusion plasmas

Understanding the statistics of fluctuation driven flows in the boundary layer of magnetically confined plasmas is desired to accurately model the lifetime of the vacuum vessel components. Mirror Langmuir probes (MLPs) are a novel diagnostic that uniquely allow us to sample the plasma parameters on a time scale shorter than the characteristic time scale of their fluctuations. Sudden large-amplitude fluctuations in the plasma degrade the precision and accuracy of the plasma parameters reported by MLPs for cases in which the probe bias range is of insufficient amplitude. While some data samples can readily be classified as valid and invalid, we find that such a classification may be ambiguous for up to 40% of data sampled for the plasma parameters and bias voltages considered in this study. In this contribution, we employ an autoencoder (AE) to learn a low-dimensional representation of valid data samples. By definition, the coordinates in this space are the features that mostly characterize valid data. Ambiguous data samples are classified in this space using standard classifiers for vectorial data. In this way, we avoid defining complicated threshold rules to identify outliers, which require strong assumptions and introduce biases in the analysis. By removing the outliers that are identified in the latent low-dimensional space of the AE, we find that the average conductive and convective radial heat fluxes are between approximately 5% and 15% lower as when removing outliers identified by threshold values. For contributions to the radial heat flux due to triple correlations, the difference is up to 40%.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2000

Hopanoid Biomarker Preservation In Coniform (Phormidium) Stromatolites in Siliceous Thermal Springs, Yellowstone National Park

The microbial communities that characterize modem hydrothermal ecosystems serve as modern analogs to those thought to have dominated early environments on Earth and possibly Mars. The importance of such hydrothermal systems as targets in exploring for an early biosphere on Mars is well established. Such work provides an important basis for the analysis of Martian samples associated with such environments. The surviving molecular structure and isotopic signature of diagnostic lipid biomarkers found as chemical fossils can provide a link between modern bacterially dominated ecosystems and their ancient counterparts. We are interested in the processes involved in the deposition and/or degradation of organic material in moderately thermal, silicifying microbial mats, particularly as this relates to the potential for preservation of some biomarker components known to be more highly resistant to microbial degradation. Several excellent biomarker molecules are associated with the cyanobacteria that dominate these mats, particularly the 2-methylbacteriohopanepolyols (2-MeBHP). These compounds are ubiquitous on Earth and are not easily degraded in nature, a fact documented by their detection in ancient Earth rocks dating back as far as 2,700 Ma.

Jahnke, Linda L.↗

DOE OSTI2026

Automating Detection and Diagnosis of Faults, Failures, and Underperformance in PV Plants

The project developed hybrid physics-based and machine-learning methods for near-real-time detection of balance-of-system faults (e.g., string, combiner, and tracker outages) in utility-scale Photovoltaic plants, achieving over 50% true positive rates with under 10% false positives and significantly reducing engineering setup time. In the extended phase, the scope expanded to plant-level underperformance analysis and industry benchmarking through the SUPER.epri.com platform. SUPER standardizes data processing and performance metrics across more than 9 GWac and 120+ plants, enabling robust comparisons and insights into loss rates, inverter downtime, and capacity degradation.

14 SOLAR ENERGY↗

NASA NTRS2006

Real-Time Diagnosis of Faults Using a Bank of Kalman Filters

A new robust method of automated real-time diagnosis of faults in an aircraft engine or a similar complex system involves the use of a bank of Kalman filters. In order to be highly reliable, a diagnostic system must be designed to account for the numerous failure conditions that an aircraft engine may encounter in operation. The method achieves this objective though the utilization of multiple Kalman filters, each of which is uniquely designed based on a specific failure hypothesis. A fault-detection-and-isolation (FDI) system, developed based on this method, is able to isolate faults in sensors and actuators while detecting component faults (abrupt degradation in engine component performance). By affording a capability for real-time identification of minor faults before they grow into major ones, the method promises to enhance safety and reduce operating costs. The robustness of this method is further enhanced by incorporating information regarding the aging condition of an engine. In general, real-time fault diagnostic methods use the nominal performance of a "healthy" new engine as a reference condition in the diagnostic process. Such an approach does not account for gradual changes in performance associated with aging of an otherwise healthy engine. By incorporating information on gradual, aging-related changes, the new method makes it possible to retain at least some of the sensitivity and accuracy needed to detect incipient faults while preventing false alarms that could result from erroneous interpretation of symptoms of aging as symptoms of failures. The figure schematically depicts an FDI system according to the new method. The FDI system is integrated with an engine, from which it accepts two sets of input signals: sensor readings and actuator commands. Two main parts of the FDI system are a bank of Kalman filters and a subsystem that implements FDI decision rules. Each Kalman filter is designed to detect a specific sensor or actuator fault. When a sensor or actuator fault occurs, large estimation errors are generated by all filters except the one using the correct hypothesis. By monitoring the residual output of each filter, the specific fault that has occurred can be detected and isolated on the basis of the decision rules. A set of parameters that indicate the performance of the engine components is estimated by the "correct" Kalman filter for use in detecting component faults. To reduce the loss of diagnostic accuracy and sensitivity in the face of aging, the FDI system accepts information from a steady-state-condition-monitoring system. This information is used to update the Kalman filters and a data bank of trim values representative of the current aging condition.

Kobayashi, Takahisa↗