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At least 271 records · Page 15

Monitoring of Liquid Metal Reactor Heater Zones with Recurrent Neural Network Learning of Temperature Time Series

Advanced high-temperature fluid reactors (ARs), such as sodium fast reactors (SFRs) and molten salt cooled reactors (MSCRs) utilize high-temperature fluids at ambient pressure. To melt the fluid during reactor startup and prevent fluid freezing during cooldown, the thermal–hydraulic systems of such ARs include heater zones consisting of specific heaters with controllers, temperature sensors, and thermal insulation. The failure of heater zones due to insulation material degradation or improper installation, resulting in parasitic heat losses, can lead to fluid freezing. The detection of faults using a heat-transfer model is difficult because of a lack of knowledge of the experimental details. Data-driven machine learning of heater zone temperature time series offers a viable alternative. In this study, we benchmarked the performance of recurrent neural networks (RNNs) in an analysis of heat-up transient temperature time series of heater zones installed on a liquid sodium vessel. The RNN models include long short-term memory (LSTM) and gated recurrent unit (GRU) networks, as well as their bi-directional variants, BiLSTM and BiGRU. Anomalous temperature points were designated using a percentile-based threshold applied to residual fluctuations in the detrended temperature time series. Additionally, the impact of the exponentially weighted moving average (EWMA) method on detection accuracy was examined. The RNN models’ performance was assessed using precision, recall, and F 1 score metrics. Results demonstrated that RNN models effectively detect anomalies in temperature time series with the best models for each heater zone achieving F 1 scores of over 93%. To explain the variations in RNN model performance across different heater zones, we used Kullback–Leibler (KL) divergence to quantify the relative entropy between training and testing data, and the Detrended Fluctuation Analysis (DFA) to assess long-range temporal correlations. For datasets with strong long-range correlations and minimal relative entropy between training and testing data, GRU is the best-performing model. When the data exhibits weaker long-term correlations and a significant relative entropy between training and testing distributions, BiGRU shows the best performance. For the data sets with intermediate values of both KL divergence and DFA, the best performance is obtained with LSTM and BiLSTM, respectively.

gated recurrent unit↗

Long-Term Surveillance and Maintenance Plan for the Salmon, Mississippi, Site

The U.S. Department of Energy (DOE) Office of Legacy Management (LM) prepared this Long-Term Surveillance and Maintenance Plan (LTS&M Plan) for the Salmon, Mississippi, Site (the Salmon site) to describe LM’s plan and policy for future site activities. The Salmon site consists of 1470 acres in Lamar County, Mississippi, approximately 10 miles west of Purvis, Mississippi, and about 21 miles southwest of Hattiesburg, Mississippi. The site is located over a large subsurface salt formation referred to as the Tatum Salt Dome. Two nuclear tests (Project Dribble) and two gas explosive tests (Project Miracle Play) were conducted in the salt dome between 1964 and 1970. Salmon, the first nuclear test, was conducted on October 22, 1964, and created a cavity approximately 2700 feet (ft) below ground surface (bgs). The second nuclear test, Sterling, was conducted on December 3, 1966. The Sterling test and the two gas explosions—Diode Tube on February 2, 1969, and Humid Water on April 19, 1970—were all conducted in the cavity created by the Salmon test. The four explosions were conducted as part of the U.S. Atomic Energy Commission’s (AEC’s) Vela Uniform program. Testing at the site ended in 1970 after the second gas detonation. The tests resulted in residual contamination and postdetonation features that require long-term oversight.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Re-Additization of Commercial Biodiesel Blends During Long-Term Storage

Commercial biodiesel blends representative of the U.S. market were aged following procedure ASTM D4625, Standard Test Method for Middle Distillate Fuel Storage Stability at 43°C (110°F), with periodic monitoring of fuel properties indicative of oxidation. The oxidation stability—or oxidation reserve expressed as Rancimat induction period (IP)—gradually decreased from its initial value, as expected. At a predetermined IP threshold, an antioxidant was used to restore IP to the ASTM D7467 specification minimum of 6 six hours, referred to as re-additization. At lower IP values, the amount of antioxidant required increased significantly, and the effectiveness tended to be reduced. Once IP fell to essentially zero, the acid content increased to above the allowable limit. Insoluble material was detectable after the acid number increased out of specification. Storage life was increased with re-additization relative to the as-received fuels, as evidenced by longer time to produce acids. Experience in the field may vary based on storage conditions; however, these results indicate re-additization can significantly increase the storage life of biodiesel blends when used with regular monitoring of IP and acid number. An assessment of property changes during long-term storage showed the initial IP did not predict storage behavior, although fuels above the specification minimum remained stable for greater than 12 weeks of D4625 accelerated aging (1 one year simulated).

09 BIOMASS FUELS↗

CO2 Electrolyzer to Produce Formic Acid at Industry Relevant Current Density

Electrochemical CO2 reduction reaction (CO2RR) to produce formic acid has attracted great interest recently since formic acid can be used as a feedstock for biorefineries. Over the past decade, much effort has been devoted to the prospects of electrochemical CO2 conversion to formic acid. However, issues including low current density, low selectivity, low energy efficiency, poor long-term stability, and production of formate salts instead of formic acid remain as the great challenges for the development and commercialization of this technology. Recently, Dioxide Materials (DM) has developed an electrolyzer technology that can directly convert CO2 to pure formic acid with a three-compartment CO2 electrolyzer. In this work, DM will present our recent effort on improving the electrolyzer performance operating at industry relevant current density (200 mA/cm2). We have demonstrated 200 mA/cm² with 80% Faradaic efficiency for 1000 hours of operation. The effects of CO2 concentration and impurities in the flue gas on the electrolyzer performance will be discussed, as will ongoing efforts to test the device at a coal fired power plant. The long-term (1000 h) performance of the electrolyzer will also be presented.

Yang, Hongzhou↗

The suitability of differentiable, physics-informed machine learning hydrologic models for ungauged regions and climate change impact assessment

As a genre of physics-informed machine learning, differentiable process-based hydrologic models (abbreviated as δ or delta models) with regionalized deep-network-based parameterization pipelines were recently shown to provide daily streamflow prediction performance closely approaching that of state-of-the-art long short-term memory (LSTM) deep networks. Meanwhile, δ models provide a full suite of diagnostic physical variables and guaranteed mass conservation. Here, we ran experiments to test (1) their ability to extrapolate to regions far from streamflow gauges and (2) their ability to make credible predictions of long-term (decadal-scale) change trends. We evaluated the models based on daily hydrograph metrics (Nash–Sutcliffe model efficiency coefficient, etc.) and predicted decadal streamflow trends. For prediction in ungauged basins (PUB; randomly sampled ungauged basins representing spatial interpolation), δ models either approached or surpassed the performance of LSTM in daily hydrograph metrics, depending on the meteorological forcing data used. They presented a comparable trend performance to LSTM for annual mean flow and high flow but worse trends for low flow. For prediction in ungauged regions (PUR; regional holdout test representing spatial extrapolation in a highly data-sparse scenario), δ models surpassed LSTM in daily hydrograph metrics, and their advantages in mean and high flow trends became prominent. In addition, an untrained variable, evapotranspiration, retained good seasonality even for extrapolated cases. The δ models' deep-network-based parameterization pipeline produced parameter fields that maintain remarkably stable spatial patterns even in highly data-scarce scenarios, which explains their robustness. Combined with their interpretability and ability to assimilate multi-source observations, the δ models are strong candidates for regional and global-scale hydrologic simulations and climate change impact assessment.

54 ENVIRONMENTAL SCIENCES↗

Impact of environmental variables on the degradation of photovoltaic components and perspectives for the reliability assessment methodology

Backsheet cracking has been a major issue observed in the field; however, standardized qualification tests, such as IEC61215, are inadequate to reliably identify such failures of PV modules due to the lack of the critical weathering factors applied sequentially or in combination, such as those found in the service environments. To address this problem, in this work we investigated the effects of various environmental variables on the degradation and failure behaviors of the polyamide-based backsheet in PV modules retrieved from five different locations, encompassing a variety of climates, including humid subtropical, hot-summer Mediterranean, tropical savanna climate and hot arid. The correlations between the degradation indicators and the weathering variables were further demonstrated by principle components analysis (PCA). We found strong relationships between: carbonyl formation and reflected solar radiation; hydroxyl formation and module temperature; yellowness and NO2 concentration, while no simple correlation could be found between a specific weathering factor and cracking. By introducing additional stress factors to the aged polyamide-based backsheet films with the novel 'fragmentation test', we successfully reproduced the field cracking behaviour. This study has demonstrated that different degradation modes of PV components respond differently to the environmental stresses encountered in service. Thereby, any accelerated laboratory test based on a single set condition or lacking key environmental variables would be inadequate to assess the long-term performance of PV modules and components. A new reliability-based methodology is proposed to quantitatively link laboratory testing with field results for the service life prediction of PV materials.

14 SOLAR ENERGY↗

HEPA Filter Age Evaluation Report

In 2020, PNNL completed a literature search for high-efficiency particulate air (HEPA) filter age information. HEPA filters are used in many operations to remove particulate matter from effluent exhaust streams. They are thought to degrade over time both during proper storage and during normal operational service; however, the rate at which the filters degrade remains unknown. This brings into question if age is an adequate indicator of HEPA filter performance. Data from six previous reports were obtained from the literature search and combined to create a data set of 1600 operating filters. Filter usage was identified from multiple facilities. The various types of filters (e.g., axial flow, self-contained, and standard 24 x 24 x 11.5 inches; and both separator and separatorless) reported were constructed to the requirements Section FC (HEPA Filters) or Section FK (Special HEPA Filters) of the American Society of Mechanical Engineers AG-1 code. Filters were presumed to have continuously met the operational criteria and in particular passed both annual efficiency tests and annual DP measurements. The environmental conditions within the exhaust system were also assumed adequate for long-term filter operation. The data, by the nature of the reports, excludes rejected filters from quality assurance evaluations, intake, or installation testing. The collective data set shows over half of were operating past the current 10-year Department of Energy (DOE) limit. Data was evaluated for age lifetime using a linear trendline, survival function, probability functions, and failure rate; financial impacts were also addressed. This report supports the notion that HEPA filters can operate safely and efficiently under proper maintenance well past the 10-year lifetime established by DOE. Using the results of the four age evaluation approaches, they collectively point to the reasonableness of an operating HEPA filter lifetime of 20 years. The results are not necessarily definitive, but nevertheless, they are promising. The analysis provides reasonable assurance that when implemented using a graded approach with well-defined performance and operational requirements, extending the service life for HEPA filters beyond 10 years is low risk.

42 ENGINEERING↗

Design and Initial Verification Testing of an In Situ Load Retention Aging Fixture

Load retention is a key metric used to evaluate long-term mechanical functionality of polymeric materials. Its measurement currently requires periodically removing the aging fixtures from the ovens, removing the specimens from the fixtures, and performing load testing on the specimens. The ability to perform load measurement in situ (i.e., without having to remove the specimens from the fixtures, and possibly even the ovens) would facilitate data acquisition/analysis, improve data quality, and enable uninterrupted compression of specimens which is more representative of the actual application.

36 MATERIALS SCIENCE↗

Technology Development for Dry Storage of Aluminum-Clad Spent Nuclear Fuel - 20490

A candidate disposition pathway for the > 13 MTHM of aluminum-clad spent nuclear fuel (ASNF), owned and managed by the U.S. Department of Energy, is the drying and placement of the SNF into sealed-canister dry storage, with the ASNF-in- canisters 'road-ready' for transportation to and final direct disposal in a repository waste package. Technical information gaps in fuel drying, and fuel dry storage behavior, have previously challenged the declaration of technology readiness for drying and placement of this fuel into the DOE Standard Canister design for > 50 years of safe dry storage. The principal technical information gaps included: i) characterization and thermal dehydration behavior of aluminum (oxy)hydroxide films attendant on the cladding due to film formation during reactor operation and during post-discharge up to long-term wet storage histories; and ii) G-value data to enable estimation of the radiolytic gas generation from the cladding with its (oxy)hydroxide films. Thus, the oxide films on the ASNF challenged the safety of a sealed storage canister with thermal and radiolytic decomposition of the waters on the films that can lead to corrosion, pressurization, and flammability issues. These gaps in the technical information base have largely been closed. This paper discusses the investigations at the Idaho National Laboratory (INL) and the Savannah River National laboratory (SRNL), and outlines the pending technology development work for input to an engineering design to enable a road-ready dry storage system for ASNF. The ASNF inventory considered for road-ready dry storage is stored at the Savannah River Site (SRS) and at the Idaho Nuclear Technology and Engineering Center (INTEC) at the INL. The ASNF inventory in the SRS L Basin is from foreign and domestic research reactors (FRR and DRR), and is diverse in terms of design, irradiation, and post-reactor-discharge storage conditions; these factors yield a range of characteristics of cladding oxide films on ASNF. Mixed aluminum (oxy)hydroxide (boehmite and bayerite/gibbsite) films, non-uniform in thicknesses up to a maximum local thickness bounded by 25 μm, were observed on ASNF materials removed from wet storage in the L Basin and in non-sealed dry storage at the SRS following reactor service and a long-term (up to 40+ years) interim storage history. The ASNF inventory at INTEC, in both wet and vented dry storage, is predominantly from the Advanced Test Reactor (ATR), but it also includes DRR and FRR fuel. To address a profound behavior of these films, radiolysis testing of aluminum specimens with mixed type boehmite/bayerite oxide films was performed to develop basic data on G-values for production of radiolytic hydrogen under dry storage conditions with nominal relative humidity, temperature, and cover gas. Modeling and simulation of canister internal environments with postulated inventories of oxide films provides estimation of the evolution of the conditions of the canister loaded with ASNF. Simultaneous Thermal Analysis (TGA/DSC) of hydrated oxide powders, and laboratory-scale aluminum specimens with a bayerite film (∼10 μm) using TGA methods, inform drying time/temperature conditions to be used for the ASNF. A demonstration project is recommended for Verification and Validation of the drying and storage of the ASNF. Remaining major tasks leading up to the hot demonstration include scale-up radiolysis testing and scale-up drying testing. Engineering design with the information from the technology program will establish the safety basis and enable long-term (> 50 years) dry storage compatibility with ASNF in the DOE Standard Canister pending its transportation to and disposal in a repository. This full capability would show the ASNF-in-canister storage system to be road-ready. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Assessment of Accelerated Stress Testing Data for Silicon Photovoltaics Using Tensor Decomposition Methods

The photovoltaic (PV) industry is simultaneously targeting long warranties and new materials/designs for high-energy-yield modules, requiring an advanced methodology to forecast long-term durability of products with un-proven materials combinations. Extended, sequential, and combined stress testing methods are gaining popularity for assessing durability of PV modules/materials beyond the early-stage mortalities. Importantly, multiple degradation mechanisms can proceed simultaneously, and their separate contributions to the overall power loss should ideally be quantified. This work examines the use of data-driven tools towards developing a strategy for faster learning cycles in accelerated stress testing.

accelerated stress testing↗

Microstructural Coarsening Kinetics and Mechanical Property Changes in Long-Term Aged Sn–Pb–Sb Solder Joints

Tin-lead-antimony (50Sn–47Pb–3Sb wt.%) soldered assemblies were mechanically tested approximately 30 years after initial production and found to have solder joints of reduced strength. The microstructure of this solder alloy exhibits a ternary eutectic structure with Sn-rich, Pb-rich, and SnSb phases. Accelerated aging was performed to evaluate solder microstructural coarsening and associated strength of laboratory solder joints to correlate these properties to the “naturally aged” solder joints. Isothermal aging was conducted at room temperature, 55, 70, 100, and 135 °C and aging times that ranged from 0.1 to 365 days. The coarsening kinetics of the Pb-rich phase were determined through optical microscopy and image analysis methods established in previous studies on binary Sn–Pb solder. A kinetic equation was developed with time exponent n of 0.43 and activation energy of 24000 J/mol, suggesting grain boundary diffusion or other fast diffusion pathways controlling the microstructural evolution. Compression testing and Vickers microhardness showed significant strength loss within the first 20–30 days after soldering; then, the microstructure and mechanical properties changed more slowly over long periods of time. Further, by combining accelerated aging data and the microstructure-based kinetics, strength predictions were made that match well with the properties of the actual soldered assemblies naturally aged for 30 years. However, aging at the highest temperature of 135 °C produced anomalous behavior suggesting that extraneous aging mechanisms are active. Therefore, data obtained at this temperature or higher should not be used. Overall, the combined microstructural and mechanical property methods used in this study confirmed that the observed reduction in strength of ~ 30-year-old solder joints can be accounted for by the microstructural coarsening that takes place during long-term solid-state aging.

36 MATERIALS SCIENCE↗

Sulfur poisoning mechanism of LSCF cathode material in the presence of SO 2 : a computational and experimental study

Aiming at the comprehensive understanding of the single sulfur poisoning effect and, eventually, the multiple impurities poisoning phenomena on the SOFC (Solid Oxide Fuel Cell) cathode materials, the sulfur poisoning effect on the (La 0.6 Sr 0.4 ) 0.95 Co 0.2 Fe 0.8 O 3 (LSCF-6428) has been investigated in the presence of 10 ppm SO 2 at 800, 900, and 1000°C, respectively, with a combined computational and experimental approach. The good agreement between the CALPHAD (Computer Coupling of Phase Diagrams and Thermochemistry) simulations and the XRD (X-Ray Diffraction), SEM (Scanning Electron Microscopy), and TEM (Transmission Electron Microscopy) characterization results support the reliability of the CALPHAD approach in the SOFC field. Furthermore, comprehensive simulations were made to understand the impact of temperature, P(SO 2 ), P(O 2 ), and Sr concentration on the threshold of SrSO 4 stability. Results showed that the formation of SrSO4 is thermodynamically favored at lower temperatures, higher P(SO 2 ), higher P(O 2 ), and higher Sr concentration. Finally, comparisons were also made between LSCF-6428 and LSM20 (La 0.8 Sr 0.2 MnO 3 ) using simulations, which confirmed that LSCF-6428 is a poor sulfur-tolerant cathode, in agreement with the literature.

36 MATERIALS SCIENCE↗

Versatile Remediation Module Final Operational Testing Results

Oak Ridge National Laboratory (ORNL) successfully demonstrated the Versatile Remediation Module (VRM), a prototype module designed and built by ORNL for performing the on-site remote repair of welded stainless-steel storage containers for spent nuclear fuel and high-level radioactive waste. This report describes the VRM prototype and its design features, components, qualification tests, operational procedures, and demonstration results to support continued long-term storage or off-site transportation of spent nuclear fuel and high-level radioactive waste currently stored in storage containers. A remote (i.e., 100 ft away from the simulated radiative environment) demonstration of the VRM was successfully performed on a full-scale mock-up welded stainless-steel canister. The VRM is designed with features to accommodate remediation techniques beyond those currently selected and described in this report. Therefore, many of the VRM’s features could benefit other remote nuclear or nonnuclear applications. The VRM is envisioned to serve as a development center to facilitate and enhance the further development of new remediation technologies.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Collaborative R&D with REEL Solar Inc (REEL) to Understand and Overcome Performance Limitations in CdTe Solar Cells: Cooperative Research and Development (Final Report)

This CRADA will focus on processing, advanced characterization, and testing of photovoltaic materials and devices to understand and improve REEL CdTe solar technology. This will include examining process variations and different buffer, absorber, and contact layers from REEL and NLR to maximize performance. The unique and diverse advanced characterization tools at NLR, such as time-resolved photoluminescence, capacitance-voltage measurements, electron beam scattered diffraction, cathodoluminescence, electron microscopy, TOF-SIMS, and other measurements will be applied to characterize REEL processing to improve understanding and guide experimental directions. Accelerated stability and potential induced degradation tests will be used to analyze metastability, short-and-long term degradation, and improve bankability. A second and major thrust this period will be joint development of Si/CdTe tandem solar cells to overcome industry wide terrestrial solar efficiency limits with the two lowest cost and manufacturable solar materials today. This will include developing novel transparent back contacts that can be incorporated into tandem structures and other novel solar applications, detailed analysis of designs and configurations for CdTe/Si tandem modules, and prototyping REEL CdTe Technology with Si bottom cells in tandem structures.

14 SOLAR ENERGY↗

Wells of Opportunity: An Assessment of Idle Geothermal Wells in Nevada

Geothermal energy is poised to play an increasing role in the energy transition over the coming decades. At the same time, idled and inactive geothermal wells represent both an opportunity for increased geothermal energy production but also an environmental risk. However, it is unclear how many geothermal wells are idled or inactive, making it difficult to identify pathways to redeploy these wells or prioritize them for additional monitoring, maintenance, or abandonment. Through a comparison of state well databases, this study develops an inventory of all existing large-bore wells at geothermal fields in Nevada to identify idled wells and their characteristics. The results show that at least 91 production or injection wells may be idled (inactive for 7 or more years), representing 21% of inventoried wells across all fields. This idled rate is significantly below the national rate for oil and gas wells (69%), though there are an additional 92 geothermal wells with an unknown status. The average age and length of inactivity for potentially idled geothermal wells is 26 and 23 years respectively, and active generation fields comprise most of the inventory (83%). Idled well incidence varies significantly across active fields, with 6 of the 17 fields having idled rates of 20%-50% and/or more than 5 idled wells, while 3 fields have no idled wells and the remaining fields have rates below 20%. Younger or more recently idled wells at these active fields likely present the best opportunities for future use or enhanced geothermal systems technology testing. However, a significant proportion of the older and long-term idled wells will likely require additional monitoring or eventual abandonment.

geothermal↗

Integrated Disposal Facility FY2011 Glass Testing Summary Report [Erratum]

Pacific Northwest National Laboratory was contracted by Washington River Protection Solutions, LLC to provide the technical basis for estimating radionuclide release from the engineered portion of the disposal facility (e.g., source term). Vitrifying the low-activity waste at Hanford is expected to generate over 1.6 x 10 5 m 3 of glass (Certa and Wells 2010). The volume of immobilized low-activity waste (ILAW) at Hanford is the largest in the DOE complex and is one of the largest inventories (approximately 8.9 x 10 14 Bq total activity) of long-lived radionuclides, principally 99 Tc (t 1/2 = 2.1 x 10 5 ), planned for disposal in a low-level waste (LLW) facility. Before the ILAW can be disposed, DOE must conduct a performance assessment (PA) for the Integrated Disposal Facility (IDF) that describes the long-term impacts of the disposal facility on public health and environmental resources. As part of the ILAW glass testing program PNNL is implementing a strategy, consisting of experimentation and modeling, in order to provide the technical basis for estimating radionuclide release from the glass waste form in support of future IDF PAs. The purpose of this report is to summarize the progress made in fiscal year (FY) 2011 toward implementing the strategy with the goal of developing an understanding of the long-term corrosion behavior of low-activity waste glasses.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Developing Accelerated Test Protocols and Tuning Microstructures of the Common Materials to Improve Robustness, Reliability, and Endurance of SOFC Cells

This work is built on our prior work where we found that phase transformation in praseodymium nickelates, e.g. Pr 2 NiO 4 (PNO) and (Pr 1-x Nd x ) 2 NiO 4 (PNNO), can be electrochemically driven, and is substantially faster when compared to thermal annealing studies. The first task aims at an attempt to further accelerate the phase transformation in the oxygen electrode by alternating the current input in the cells, which lead to the development of accelerated test protocols (ATPs). ATPs showed up to 60x faster phase transformation and up to 10x faster performance degradation in (Pr 0.50 Nd 0.50 ) 2 NiO 4 electrodes, when compared to long-term operation under constant current density. Furthermore, the phase stable Nd 2 NiO 4 and (La 0.6 Sr 0.4 )(Co 0.8 Fe 0.2 )O 3 (LSCF6482) electrodes were tested in full cells under ATPs, and showed up to 10x faster performance degradation within 1,100 hours in a comparison with long-term thermal annealing studies and electrochemical operation under constant current density. The second task aims at the quantification of the contributions of cell components to the total impedance of a solid oxide fuel cell (SOFC) using electrochemical impedance spectroscopy (EIS) and distribution of relaxation times (DRT). Specifically, the role of gas composition at both anode and cathode was systematically studied, aiming at deconvoluting, identifying and quantifying the contributions of different electrode processes. This was achieved by first tuning the partial pressure of H 2 at the anode and subsequently varying the partial pressure of O 2 at the cathode. The results suggest that, while DRT offers a viable way of deconvoluting different times distributions, additional attention is needed before assigning a peak to a specific electrode process due to the significant overlap of the contributions from the cathode and the anode. Density function theory studies show that both Pr-vacancies and O-defects play a key role on the activity and stability for nickelates towards oxygen reduction reaction. The resident O-interstitials and oxygen ions in the PrO layer form peroxide (O 2 2- ) nearby Pr vacancies. The O 2 2- limits oxygen-ion transport due to the required additional energy to break its O-O bond. We further calculated the formation and segregation energies for different Ln ions (La, Pr, Nd, Pm, Sm, Gd, Tb, Dy, and Ho) in PNO and CeO 2 (111) surfaces. In addition to Nd, Pm and La are suggested as potential dopants in PNO to enhance it stability without decomposition due to their more negative formation energies, lower diffusion energies, and positive separation energies.

01 COAL, LIGNITE, AND PEAT↗

Wavelet and Deep-Learning-Based Approach for Generation System Problematic Parameters Identification and Calibration

Accurate models of generation systems are critical for maintaining reliable and secure grid operations. In this paper, a novel and systematic approach is proposed to identify and calibrate the generation system problematic parameters using continuous wavelet transform (CWT) and advanced deep-learning technology. The phasor measurement unit (PMU) data are used through “event playback” to check whether the parameter calibration is required, and if yes, a group of suspicious parameters will be identified as the primary problematic parameter candidates (PPCs). These primary PPCs are randomly perturbed to generate the event playback simulation data, which are used by the CWT and convolutional neural networks (CNNs) to further narrow down the primary PPCs into a smaller set of candidates. Then, the identified candidates are perturbed again to generate massive event playback simulation data for training a parameter calibration neural network. Here, we designed a multi-output neural network structure to find the mappings between the perturbed parameters and the simulation data using both CNN and long short-term memory (LSTM) models. Finally, the well-trained and tested CNN-LSTM model is used to estimate the accurate value of the suspicious parameters with actual PMU measurements. The proposed CNN-LSTM network can accurately and reliably estimate the generation-system problematic parameters, and has better performance when compared to other machine-learning methods, such as the multilayer perceptron network and the conditional variational autoencoder method. The accuracy and effectiveness of the proposed approach have been validated through simulation and real-world data.

24 POWER TRANSMISSION AND DISTRIBUTION↗