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At least 397 records · Page 22

Air Conditioning Systems Fault Detection and Diagnosis-Based Sensing and Data-Driven Approaches

The air conditioning (AC) system is the primary building end-use contributor to the peak demand for energy. The energy consumed by this system has grown as fast as it has in the last few decades, not only in the residential section but also in the industry and transport sectors. Therefore, to combat energy crises, urgent actions on energy efficiency should be taken to support energy security. Consequently, the faults in AC system components increase energy consumption due to the degradation of the system’s performance and the losses in the energy conversion procedure. In this work, AC system fault detection and diagnosis (FDD) methods are investigated to propose analytic tools to identify faults and provide solutions to those problems. The analysis of existing work shows that data-driven approaches are more accurate for both soft and hard fault detection and diagnosis in AC systems. Therefore, the proposed methods are not accurate for simultaneous fault detection, while in some works, authors tested the method with several faults separately without investigating scenarios that combine more than one fault. Moreover, this study shows that integrating data-driven approaches requires deploying an optimal sensing and measurement architecture that can detect a maximum number of faults with minimally deployed sensors. The new sensing, information, and communication technologies are discussed for their integration in AC system monitoring in order to optimize system operation and detect faults.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Technical Language Processing of Nuclear Power Plants Equipment Reliability Data

Operating nuclear power plants (NPPs) generate and collect large amounts of equipment reliability (ER) element data that contain information about the status of components, assets, and systems. Some of this information is in textual form where the occurrence of abnormal events or maintenance activities are described. Analyses of NPP textual data via natural language processing (NLP) methods have expanded in the last decade, and only recently the true potential of such analyses has emerged. So far, applications of NLP methods have been mostly limited to classification and prediction in order to identify the nature of the given textual element (e.g., safety or non-safety relevant). In this paper, we target a more complex problem: the automatic generation of knowledge based on a textual element in order to assist system engineers in assessing an asset’s historical health performance. The goal is to assist system engineers in the identification of anomalous behaviors, cause–effect relations between events, and their potential consequences, and to support decision-making such as the planning and scheduling of maintenance activities. “Knowledge extraction” is a very broad concept whose definition may vary depending on the application context. In our particular context, it refers to the process of examining an ER textual element to identify the systems or assets it mentions and the type of event it describes (e.g., component failure or maintenance activity). In addition, we wish to identify details such as measured quantities and temporal or cause–effect relations between events. This paper describes how ER textual data elements are first preprocessed to handle typos, acronyms, and abbreviations, then machine learning (ML) and rule-based algorithms are employed to identify physical entities (e.g., systems, assets, and components) and specific phenomena (e.g., failure or degradation). A few applications relevant from an NPP ER point of view are presented as well.

97 MATHEMATICS AND COMPUTING↗

Combustion system processes leading to corrosive deposits

Degradation of turbine engine hot gas path components by high temperature corrosion can usually be associated with deposits even though other factors may also play a significant role. The origins of the corrosive deposits are traceable to chemical reactions which take place during the combustion process. In the case of hot corrosion/sulfidation, sodium sulfate was established as the deposited corrosive agent even when none of this salt enters the engine directly. The sodium sulfate is formed during the combustion and deposition processes from compounds of sulfur contained in the fuel as low level impurities and sodium compounds, such as sodium chloride, ingested with intake air. In other turbine and power generation situations, corrosive and/or fouling deposits can result from such metals as potassium, iron, calcium, vanadium, magnesium, and silicon.

Stearns, C. A.↗

Combustion system processes leading to corrosive deposits

Degradation of turbine engine hot gas path components by high temperature corrosion can usually be associated with deposits even though other factors may also play a significant role. The origins of the corrosive deposits are traceable to chemical reactions which take place during the combustion process. In the case of hot corrosion/sulfidation, sodium sulfate was established as the deposited corrosive agent even when none of this salt enters the engine directly. The sodium sulfate is formed during the combustion and deposition processes from compounds of sulfur contained in the fuel as low level impurities and sodium compounds, such as sodium chloride, ingested with intake air. In other turbine and power generation situations, corrosive and/or fouling deposits can result from such metals as potassium, iron, calcium, vanadium, magnesium, anad silicon. Previously announced in STAR as N81-23243

Stearns, C. A.↗

Incorporation of a progressive failure analysis method in the CSM testbed software system

Analysis of the postbuckling behavior of composite shell structures pose many difficult and challenging problems in the field of structural mechanics. Current analysis methods perform well for most cases in predicting the postbuckling response of undamaged components. To predict component behavior accurately at higher load levels, the analysis must include the effects of local material failures. The CSM testbed software system is a highly modular structural analysis system currently under development at Langley Research Center. One of the primary goals of the CSM testbed is to provide a software environment for the development of advanced structural analysis methods and modern numerical methods which will exploit advanced computer architecture such as parallel-vector processors. Development of a progressive failure analysis method consists of the design and implementation of a processor which will perform the ply-level progressive failure analysis and the development of a geometrically nonlinear analysis procedure which incorporates the progressive failure processor. Regarding the development of the progressive failure processor, two components are required: failure criteria and a degradation model. For the initial implementation, the failure criteria of Hashin will be used. For a matrix failure which typically indicates the development of transverse matrix cracks, the ply properties will be degraded. Work to date includes the design of the progressive failure analysis processor and initial plans for the controlling geometrically nonlinear analysis procedure. The implementation of the progressive failure analysis has begun. Access to the model database and the Hashin failure criteria are completed. Work is in progress on the input/output operations for the processor related data and the finite element model updating procedures. In total the progressive failure processor is approximately one-third complete.

Arenburg, Robert T.↗

Vacuum deposited optical coatings experiment (AO 138-4)

The aim of this experiment was to test the optical behavior of 20 components and coatings subjected to space exposure. Most of them are commonly used for their reflective or transmittive properties in spaceborne optics. They consist in several kind of metallic and dielectric mirrors designed for the 0.12 to 10 microns spectrum, UV, and NIR bandpass filters, visible, and IR antireflecting coatings, visible/IR dichroic beam splitters, and visible beam splitter. The coatings were deposited on various substrates such as glasses, germanium, magnesium fluoride, quartz, zinc selenide, and kanigened aluminum. Several coating materials were used such as Al, Ag, Au, MgF2, LaF3, ThF3, ThF4, SiO2, TiO2, ZrO2, Al2O3, MgO, Ge, and ZnSe. Five samples of each component were manufactured. Two flight samples were mounted in such a way that one was directly exposed to space and the other looking backwards. The same arrangement was used for the spare samples stored on ground in a box identical to the flight one and they were kept under vacuum during the LDEF mission. Finally, one set of reference components was stocked in a sealed box under a dry nitrogen atmosphere. By comparing the preflight and postflight optical performances of the five samples of each component, it is possible to detect the degradations due to the space exposure.

Charlier, Jean↗

Probabilistic material degradation model for aerospace materials subjected to high temperature, mechanical and thermal fatigue, and creep

A probabilistic general material strength degradation model has been developed for structural components of aerospace propulsion systems subjected to diverse random effects. The model has been implemented in two FORTRAN programs, PROMISS (Probabilistic Material Strength Simulator) and PROMISC (Probabilistic Material Strength Calibrator). PROMISS calculates the random lifetime strength of an aerospace propulsion component due to as many as eighteen diverse random effects. Results are presented in the form of probability density functions and cumulative distribution functions of lifetime strength. PROMISC calibrates the model by calculating the values of empirical material constants.

Boyce, L.↗

SNR degradation in square-wave subcarrier downconversion

This article presents a study of signal-to-noise ratio (SNR) degradation in the process of square-wave subcarrier downconversion. The study shows three factors that contribute to the SNR degradation: the cutoff of the higher frequency components in the data, the approximation of a square wave with a finite number of harmonics, and nonideal filtering. Both analytical and simulation results are presented.

Feria, Y.↗

EnKF OSSE Experiments Assessing the Impact of HIRAD Wind Speed and HIWRAP Radial Velocity Data on Analysis of Hurricane Karl (2010)

Previous studies (e.g., Zhang et al. 2009, Weng et al. 2011) have shown that radial velocity data from airborne and ground-based radars can be assimilated into ensemble Kalman filter (EnKF) systems to produce accurate analyses of tropical cyclone vortices, which can reduce forecast intensity error. Recently, wind speed data from SFMR technology has also been assimilated into the same types of systems and has been shown to improve the forecast intensity of mature tropical cyclones. Two instruments that measure these properties were present during the NASA Genesis and Rapid Intensification Processes (GRIP) field experiment in 2010 which sampled Hurricane Karl, and will next be co-located on the same aircraft for the subsequent NASA HS3 experiment. The High Altitude Wind and Rain Profiling Radar (HIWRAP) is a conically scanning Doppler radar mounted upon NASAs Global Hawk unmanned aerial vehicle, and the usefulness of its radial velocity data for assimilation has not been previously examined. Since the radar scans from above with a fairly large fixed elevation angle, it observes a large component of the vertical wind, which could degrade EnKF analyses compared to analyses with data taken from lesser elevation angles. The NASA Hurricane Imaging Radiometer (HIRAD) is a passive microwave radiometer similar to SFMR, and measures emissivity and retrieves hurricane surface wind speeds and rain rates over a much wider swath. Thus, this study examines the impact of assimilating simulated HIWRAP radial velocity data into an EnKF system, simulated HIRAD wind speed, and HIWRAP+HIRAD with the Weather Research and Forecasting (WRF) model and compares the results to no data assimilation and also to the Truth from which the data was simulated for both instruments.

Albers, Cerese↗

CMAS Interactions with Advanced Environmental Barrier Coatings Deposited via Plasma Spray- Physical Vapor Deposition

Materials for advanced turbine engines are expected to have temperature capabilities in the range of 1370-1500C. At these temperatures the ingestion of sand and dust particulate can result in the formation of corrosive glass deposits referred to as CMAS. The presence of this glass can both thermomechanically and thermochemically significantly degrade protective coatings on metallic and ceramic components. Plasma Spray- Physical Vapor Deposition (PS-PVD) was used to deposit advanced environmental barrier coating (EBC) systems for investigation on their interaction with CMAS compositions. Coatings were exposed to CMAS and furnace tested in air from 1 to 50 hours at temperatures ranging from 1200-1500C. Coating composition and crystal structure were tracked with X-ray diffraction and microstructure with electron microscopy.

Coatings↗

Lunar Simulant Deposition Technique for Dust Tolerance Studies

A renewed interest in lunar exploration has spawned an array of development efforts for lunar surface assets. These systems depend on the reliable operation of mechanisms and components that may be susceptible to performance degradations or failure due to dust. The Uniform Dust Deposition System was developed at the NASA Glenn Research Center to provide repeatable, uniform, and automated deposition of simulants on surfaces of interest for dust mitigation testing. The system is capable of depositing simulants on test articles up to 60 cm in diameter and 15 cm high in a dry air environment with less than 1 percent relative humidity while keeping users safe from aerosolized dust. The automation of the system allows for high testing throughput while not sacrificing test quality and allows the user to reduce data in parallel. The additional development of a simulant preparation technique complements the repeatability of the deposition physics during testing. The system includes an imaging subsystem that leverages the power of machine learning to count simulant particles and measure their size, thereby allowing for accurate predictions of surface deposition densities (coefficient of determination R^(2) = 0.93) from images alone. The coverage of dust on a surface was shown to be uniform (coefficient of variation CV < 0.11), allowing developers to accurately evaluate the performance of their technology with a prescribed amount of lunar simulant, information that can be used to develop and refine models. The accuracy of the system is currently less than desired for a single deposition run, with a standard deviation (SD) ranging from 18 to 24 mg, or 0.839 to 1.184 mg/sq. cm , for a 5-cm-diameter area. However, the accuracy can be improved by performing multiple deposition runs to build dust to a desired level. Testing has shown that a SD of 0.2 to 0.6 mg, or 0.076 to 0.227 mg/sq. cm, can be achieved for a 5-cm-diameter area using this technique.

Stephen Gerdts↗

SPACE-Gateway: Modeling the Electrical Performance of the Gateway Power & Propulsion Element (PPE) Solar Arrays

The System Power Analysis for Capability Evaluation (SPACE) computer model was originally developed in 1988 at NASA Glenn Research Center to model the International Space Station (ISS) electrical power system (EPS). Since then, SPACE development has continued with the rise of new NASA human spaceflight missions. Today, SPACE’s uniquely complex and robust solar array model is being leveraged to model the solar arrays on the Gateway Power & Propulsion Element (PPE) for NASA's Artemis Program. This presentation will discuss the model’s integrated features, including its solar cell current-voltage (IV) curve, degradation, temperature, and on-orbit shadowing components. The presentation will also discuss recent SPACE advancements to meet the needs of NASA's latest spaceflight missions.

SPACE↗

A Circularity Assessment for Silicon Solar Panels Based on Dynamic Material Flow Analysis

Solar photovoltaics (PV) are the fastest growing renewable energy technology for clean, inexpensive, and sustainable electricity generation. Along with numerous technical roadmaps to improve system cost, performance and reliability, the PV industry should also plan to handle large volumes of silicon panel waste, which is initially estimated to be ~13 million metric tons (MT) by 2050 in the U.S. alone. Understanding the magnitude of material needs and how material flows throughout the PV panel life cycle could respond to design, operational and different end-of-life (EOL) circular pathways will help transition into a circular, resource-conserving economy. Herein, we introduce a dynamic material flow analysis (DMFA) framework based on electricity generation to quantify time-series stocks and flows of bulk PV materials (e.g., solar glass and aluminum frames) throughout the life cycles of utility-scale silicon PV systems in the U.S. in the period 2000-2100. We apply the model to a range of scenarios to understand how material demands depend on selected PV-related parameters, different material circularity strategies, and recent module design trends (e.g., bifacial, frameless). We found that float glass and aluminum in PV installations would likely reach 100 million MT and 12 million MT by 2100, respectively, in the baseline scenario. The most influential parameters for PV installation and subsequent waste reduction are found to be module lifetime, module efficiency, annual degradation, and material reduction. Module recycling and component remanufacturing were found to be the most effective material circularity strategies for waste minimization. Panel reuse has negligible savings on waste under current module efficiencies compared to replacements with newer generations with higher efficiency. Ongoing trends to produce larger power frameless modules could save 10 million MT of glass and ~9 million MT of aluminum. Our results enable advanced planning for future materials needs and provide insight into potential opportunities to minimize waste.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A Circularity Assessment for Silicon Solar Panels Based on Dynamic Material Flow Analysis: Preprint

Solar photovoltaics (PV) are the fastest growing renewable energy technology for clean, inexpensive, and sustainable electricity generation. Along with numerous technical roadmaps to improve system cost, performance and reliability, the PV industry should also plan to handle large volumes of silicon panel waste, which is initially estimated to be ~13 million metric tons (MT) by 2050 in the U.S. alone. Understanding the magnitude of material needs and how material flows throughout the PV panel life cycle could respond to design, operational and different end-of-life (EOL) circular pathways will help transition into a circular, resource-conserving economy. Herein, we introduce a dynamic material flow analysis (DMFA) framework based on electricity generation to quantify time-series stocks and flows of bulk PV materials (e.g., solar glass and aluminum frames) throughout the life cycles of utility-scale silicon PV systems in the U.S. in the period 2000-2100. We apply the model to a range of scenarios to understand how material demands depend on selected PV-related parameters, different material circularity strategies, and recent module design trends (e.g., bifacial, frameless). We found that float glass and aluminum in PV installations would likely reach 100 million MT and 12 million MT by 2100, respectively, in the baseline scenario. The most influential parameters for PV installation and subsequent waste reduction are found to be module lifetime, module efficiency, annual degradation, and material reduction. Module recycling and component remanufacturing were found to be the most effective material circularity strategies for waste minimization. Panel reuse has negligible savings on waste under current module efficiencies compared to replacements with newer generations with higher efficiency. Ongoing trends to produce larger power frameless modules could save 10 million MT of glass and ~9 million MT of aluminum. Our results enable advanced planning for future materials needs and provide insight into potential opportunities to minimize waste.

circular economy↗

Self-Learning Kinetic Monte Carlo Simulations of Radiation Damage in Nuclear Fuels

Understanding how irradiation affects the thermo-physical and mechanical properties of nuclear materials, such as thermal conductivity degradation in fuels and embrittlement of structural components, is critical to the safety and efficiency of nuclear reactors. These effects are largely governed by the formation and evolution of atomic-scale point defects and defect clusters. Due to their small sizes, however, these defects are invisible under high-resolution scanning transmission electron microscopy. This project aims to fill this experimental knowledge gap by integrating density functional theory (DFT), machine learning interatomic potential (MLIP), and kinetic Monte Carlo (KMC) techniques to predict longtime evolution of irradiation-induced defects in nuclear fuels.

36 - MATERIALS SCIENCE↗

On the Effects of a Spacecraft Subcarrier Unbalanced Modulator

This paper presents mathematical models with associated analysis of the deleterious effects which a spacecraft's subcarrier unbalanced modulator has on the performance of a phase-modulated residual carrier communications link. The undesired spectral components produced by the phase and amplitude imbalances in the subcarrier modulator can cause (1) potential interference to the carrier tracking and (2) degradation in the telemetry bit signal-to-noise ratio (SNR). A suitable model for the unbalanced modulator is developed and the threshold levels of undesired components that fall into the carrier tracking loop are determined. The distribution of the carrier phase error caused by the additive White Gaussian noise (AWGN) and undesired component at the residual RF carrier is derived for the limiting cases. Further, this paper analyses the telemetry bit signal-to-noise ratio degradations due to undesirable spectral components as well as the carrier tracking phase error induced by phase and amplitude imbalances. Numerical results which indicate the sensitivity of the carrier tracking loop and the telemetry symbol-error rate (SER) to various parameters of the models are also provided as a tool in the design of the subcarrier balanced modulator.

Nguyen, Tien Manh↗

The Center for Performance and Design of Nuclear Waste Forms and Containers (WastePD) Energy Frontier Research Center (Final Report)

The DOE Office of Environmental Management is responsible for high level nuclear waste that must be safely isolated from humans and the environment for extremely long periods. The waste forms and containers are made of glass, ceramics, and metals. Verified safe disposal requires understanding the fundamental mechanisms of waste form degradation and the design of new waste forms with improved performance, which comprise the goals of the Energy Frontier Research Center known as the Center for the Performance and Design of Nuclear Waste Forms and Containers, WastePD. WastePD was constructed to develop innovative approaches and solutions to those goals through the synergistic interactions of individuals who are experts in the degradation behavior, modeling, and design of glasses, ceramics and metal alloys. WastePD is the first center ever created to address this diverse group of materials in a comprehensive and coordinated manner. The science goals are grouped into three common topics: corrosion mechanisms via advanced characterization, environmental impacts, and materials design. Synergistic interactions in these areas were a key component of WastePD. The fundamental understanding of the degradation mechanisms of the waste forms and containers as well as the development of new materials with improved properties will allow DOE to prevent environmental contamination and to explore totally new repository concepts. WastePD was operational from August 2016 through July 2022, but the DOE support was drastically reduced for the last two years. This final technical report covers the full period of performance. However, much of what was accomplished in the first four years is nicely summarized in a review paper published in 2021, which is appended to this report. Therefore, this final report focuses on the technical findings from the last two years of WastePD activities. Considerable progress was made in the areas of a) the environmental and compositional impacts on the corrosion of borosilicate and aluminosilicate glasses, b) the mechanism of glass corrosion and the structure and evolution of the surface alteration layer, c) the effects of environment and composition on the corrosion of pyrochlore, perovskite, hollandite, and other oxide ceramics, d) the corrosion mechanism of multi-principal element metallic alloys, and e) a new framework for understanding the pitting corrosion of metals.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Thin Film Multilayer Conductor/Ferroelectric Tunable Microwave Components for Communication Applications

High Temperature Superconductor/Ferroelectric (HTS/FE ) thin film multilayered structures deposited onto dielectric substrates are currently being investigated for use in low loss, tunable microwave components for satellite and ground based communications. The main goal for this technology is to achieve maximum tunability while keeping the microwave losses as low as possible, so as to avoid performance degradation when replacing conventional technology (e.g., filters and oscillators) with HTS/FE components. Therefore, for HTS/FE components to be successfully integrated into current working systems, full optimization of the material and electrical properties of the ferroelectric films, without degrading those of the HTS film; is required. Hence, aspects such as the appropriate type of ferroelectric and optimization of the deposition conditions (e.g., deposition temperature) should be carefully considered. The tunability range as well as the microwave losses of the desired varactor (i.e., tunable component) are also dependent on the geometry chosen (e.g., parallel plate capacitor, interdigital capacitor, coplanar waveguide, etc.). In addition, the performance of the circuit is dependent on the location of the varactor in the circuit and the biasing circuitry. In this paper, we will present our results on the study of the SrTiO3/YBa2Cu3O(7-delta)/LaAl03 (STO/YBCO/LAO) and the Ba(x)Sr(1-x)TiO3/YBa2Cu3O(7-delta)/LaAl03(BSTO/YBCO/ILAO) HTS/FE multilayered structures. We have observed that the amount of variation of the dielectric constant upon the application of a dc electric field is closely related to the microstructure of the film. The largest tuning of the STO/YBCO/LAO structure corresponded to single-phased, epitaxial STO films deposited at 800 C and with a thickness of 500 nm. Higher temperatures resulted in interfacial degradation and poor film quality, while lower deposition temperatures resulted in films with lower dielectric constants, lower tunabilities, and higher losses. For STO/LAO multilayer structures having STO film of similar quality we have observed that interdigital capacitor configurations allow for higher tunabilities and lower losses than parallel plate configurations, but required higher dc voltage. Results on the use of these geometries in working microwave components such as filters and stabilizing resonators for local oscillators (LO) will be discussed.

Miranda, Felix A.↗