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At least 793 records · Page 44

Impacts of Regional Coordination on Transmission Needs for Power System Resource Adequacy [Slides]

Resource adequacy (RA) is an important component of bulk power system reliability that addresses whether there are sufficient resources available to meet electricity demand at all times. RA analysis is used to assess whether the planned power system will provide reliable electricity to consumers while accounting for equipment outages, weather variability, and load uncertainty. Coordination between regions can enable resource sharing to meet RA needs if sufficient transmission capacity exists. Transmission's role in RA coordination can be particularly pronounced for large power systems like the U.S. electricity grid which contains geographically diverse demand and weather-dependent resources. Depending on the level of coordination desired, existing inter-regional transmission capacity may not be sufficient. This study is designed to assess optimal pathways for the development of inter-regional transmission in the U.S. under varying levels of RA coordination. Results can inform long-term grid infrastructure planning and provide insights into potential benefits of greater coordination for generation and transmission planning between regional U.S. power systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

GPS Data Filtration Method for Drive Cycle Analysis Applications

When employing GPS data acquisition systems to capture vehicle drive-cycle information, a number of errors often appear in the raw data samples, such as sudden signal loss, extraneous or outlying data points, speed drifting, and signal white noise, all of which limit the quality of field data for use in downstream applications. Unaddressed, these errors significantly impact the reliability ofsource data and limit the effectiveness of traditional drive-cycle analysis approaches and vehicle simulation software. Without reliable speed and time information, the validity of derived metrics for drive cycles, such as acceleration, power, and distance, become questionable. This study explores some of the common sources of error present in raw onboard GPS data and presents a detailedfiltering process designed to correct for these issues. Test data from both light and medium/heavy duty applications are examined to illustrate the effectiveness of the proposed filtration process across the range of vehicle vocations. Graphical comparisons of raw and filtered cycles are presented, and statistical analyses are performed to determine the effects of the proposed filtration processon raw data. Finally, an evaluation of the overall benefits of data filtration on raw GPS data and present potential areas for continued research is presented.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Optical image analysis of WSe 2 − thresholding for layer detection

The fast and reliable layer identification of two-dimensional transition metal dichalcogenide (TMD), such as WSe 2 , is essential to investigating their thickness-dependent electronic and optical properties. This article presents efficient optical image thresholding methodology designed to segment the mono, bi, and tri-layer regions of WSe 2 flakes mechanically exfoliated onto a SiO 2 /Si substrate. The optical images were first preprocessed to exclude the background effect and analyzed using the pixel medians and interquartile ranges for fundamental color channels—red, green, and blue (RGB). The analysis of red channel pixel intensities yielded three distinct ranges, serving as thresholds for layer segmentation: monolayer (111.0–118.0), bilayer (103.0–110.0), and tri-layer (93.0–103.0). Similarly, thresholds were established for each color channel, facilitating a comparative study of the segmentation performances. Further, the intersection-over-union ($IoU$) calculations revealed that the red and green channels demonstrated greater than 99 % and 90 % accuracy in differentiating each layer, respectively. This approach yields remarkable results without substantial data calibration that utilizes time-intensive heuristic techniques. Moreover, the proposed methodology offers the flexibility to compare performances across different color channels, expanding the applicability for other 2D material systems.

2D Materials↗

Kinetic equilibrium reconstruction and the impact on stability analysis of KSTAR plasmas

High fidelity kinetic plasma equilibrium reconstructions are an essential requirement for accurate stability and disruption prediction analyses to support continuous operation of high beta tokamak plasmas. The present kinetic equilibrium reconstructions of plasmas in the KSTAR device include plasma density and temperature profiles from Thomson scattering and ion temperature from charge exchange spectroscopy diagnostics, and allowance for fast particle pressure. In addition, up to 25 channels of motional Stark effect diagnostic data are used to constrain the magnetic field pitch angle profile in the plasma to produce a reliable computation of the safety factor, q, profile. In this work, H-mode plasmas exhibit clear pedestal characteristics in the reconstructed pressure profile compared to internal transport barrier or L-mode plasmas. The plasma configuration and vertical position of inner strike points are validated by CCD and infrared camera images. Ideal and resistive magnetohydrodynamic (MHD) stability analyses using the DCON and resistive DCON codes utilize these kinetic equilibrium reconstructions to compare to experimental plasma stability. Equilibria with sufficiently low convergence error can provide reliable computation of ideal and resistive MHD stability analysis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

2020 Summer Resource Adequacy in the ERCOT Region

The study looks at the evolution of the Electric Reliability Council of Texas (ERCOT) market across the last decade to provide an understanding of how the market arrived at its current condition. In addition, the study examines four scenarios and utilizes probabilistic dispatch analysis to assess the potential for resource adequacy and reliability concerns under those scenarios. The study finds that under three of the four scenarios, the region will see an increased risk for Energy Emergency Alerts and need for emergency operator actions to ensure the reliable delivery of electricity to the more than 25 million people who ERCOT serves.

2020↗

Fluxomic Analysis Reveals Central Carbon Metabolism Adaptation for Diazotroph Azotobacter vinelandii Ammonium Excretion

Diazotrophic bacteria are an attractive biological alternative to synthetic nitrogen fertilizers due to their remarkable capacity to fix atmospheric nitrogen gas to ammonium via nitrogenase enzymes. However, how diazotrophic bacteria tailor central carbon catabolism to accommodate the energy requirement for nitrogenase activity is largely unknown. In this study, we used Azotobacter vinelandii DJ and an ammonium excreting mutant, AV3 (ΔNifL), to investigate central carbon metabolism fluxes and central cell bioenergetics in response to ammonium availability and nitrogenase activity. Enabled by the powerful and reliable methodology of 13 C-metabolic flux analysis, we show that the respiratory TCA cycle is upregulated in association with increased nitrogenase activity and causes a monotonic decrease in specific growth rate. Whereas the activity of the glycolytic Entner-Doudoroff pathway is positively correlated with the cell growth rate. These new observations are formulated into a 13 C-metabolic flux model which further improves the understanding and interpretation of intracellular bioenergetics. This analysis leads to the conclusion that, under aerobic conditions, respiratory TCA metabolism is responsible for the supply of additional ATP and reducing equivalents required for elevated nitrogenase activity. This study provides a quantitative relationship between central carbon and nitrogen metabolism in an aerobic diazotroph for the first time.

09 BIOMASS FUELS↗

Deciphering Degradation: Machine Learning on Real-World Performance Data (Final Report)

This project addresses a fundamental flaw in solar PV research and solar project financing; the assumed rate of degradation for solar plants. The solar industry currently relies on an out-dated report that observed a 0.5% degradation rate based on a small sample size of systems (~100). While the research conducted at the time was new and innovative, the solar community has not updated this research and universally applies this 0.5% degradation assumption in financial models. Our project updates this assumption by analyzing observed degradation from the industry’s largest dataset of operating solar assets (>10,000 systems) and creating the first machine-learning model based on these observed results to quantify and identify features that drive degradation. There are two strategic goals for this award: reduce the cost of capital (enable solar to attract more capital) and improve the reliability of solar itself. These dual goals are achieved by leveraging an industry dataset to observe system degradation on a large scale, deploying advanced data analysis and machine learning methods to quantify and predict system reliability, and engaging with industry stakeholders to help them accurately price degradation in financial models.

14 SOLAR ENERGY↗

Improving Real-world Measurement-based Phase Identification in Power Distribution Feeders with a Novel Reliability Criteria Assessment

This paper is concerned with solving the phase identification problem in a real-world smart grid project; where there is only a few smart meters available on each of the five power distribution feeders in the test site in Riverside, CA. The main idea is to develop and use two reliability criteria that can identify the most reliable components in a broken-down phase identification analysis; thereby significantly improving the accuracy of phase identification. The proposed method consists of three steps. The results from field implementation reveal the accuracy and consistency of the proposed method in practice, in correctly and reliability identifying the phase connectivity.

Phase identification Data-driven method Sliding wi↗

The IAEA coordinated research programme on HTGR uncertainty analysis: Phase I status and Ex. I-1 prismatic reference results

The quantification of uncertainties in design and safety analysis of reactors is today not only broadly accepted, but in many cases became the preferred way to replace traditional conservative analysis for safety and licensing analysis. The use of a more fundamental methodology is also consistent with the reliable high fidelity physics models and robust, efficient, and accurate codes available today. To facilitate uncertainty analysis applications a comprehensive approach and methodology must be developed and applied, in contrast to the historical approach where sensitivity analysis were performed and uncertainties then determined by a simplified statistical combination of a few important input parameters. New methodologies are currently under development in the OECD/NEA Light Water Reactor (LWR) Uncertainty Analysis in Best-Estimate Modelling (UAM) benchmark activity. High Temperature Gas-cooled Reactor (HTGR) designs require specific treatment of the double heterogeneous fuel design and large graphite quantities at high temperatures. The IAEA has therefore launched a Coordinated Research Project (CRP) on HTGR Uncertainty Analysis in Modelling (UAM) in 2013 to study uncertainty propagation specifically in the HTGR analysis chain. Two benchmark problems are defined, with the prismatic design represented by the General Atomics (GA) MHTGR-350 and a 250 MW modular pebble bed design similar to the Chinese HTR-PM. Work has started on the first phase and the current CRP status is reported in the paper. A comparison of the Serpent and SCALE/KENO-VI reference Monte Carlo results for Ex. I-1 of the MHTGR-350 design is also included. It was observed that the SCALE/KENO-VI Continuous Energy (CE) k ∞ values were 395 pcm (Ex. I-1a) to 803 pcm (Ex. I-1b) higher than the respective Serpent lattice calculations, and that within the set of the SCALE results, the KENO-VI 238 Multi-Group (MG) k ∞ values were up to 800 pcm lower than the KENO-VI CE values. The use of the latest ENDF-B-VII.1 cross section library in Serpent lead to ~180 pcm lower k ∞ values compared to the older ENDF-B-VII.0 dataset, caused by the modified graphite neutron capture cross section. Furthermore, the fourth beta release of SCALE 6.2 likewise produced lower CE k∞ values when compared to SCALE 6.1, and the improved performance of the new 252-group library available in SCALE 6.2 is especially noteworthy. A SCALE/TSUNAMI uncertainty analysis of the Hot Full Power variant for Ex. I-1a furthermore concluded that the 238 U(n,γ) (capture) and 235 U(View the MathML source) cross-section covariance matrices contributed the most to the total k ∞ uncertainty of 0.58%.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Results for Phase I of the IAEA Coordinated Research Program on HTGR Uncertainties

The quantification of uncertainties in design and safety analysis of reactors is today not only broadly accepted, but in many cases became the preferred way to replace traditional conservative analysis for safety and licensing analysis. The use of a more fundamental methodology is also consistent with the reliable high fidelity physics models and robust, efficient, and accurate codes available today. To facilitate uncertainty analysis applications a comprehensive approach and methodology must be developed and applied. High Temperature Gas-cooled Reactors (HTGR) has its own peculiarities, coated particle design, large graphite quantities, different materials and high temperatures that also require other simulation requirements. The IAEA has therefore launched a Coordinated Research Project (CRP) on the HTGR Uncertainty Analysis in Modeling (UAM) in 2013 to study uncertainty propagation specifically in the HTGR analysis chain. Two benchmark problems are defined, with the prismatic design represented by the General Atomics (GA) MHTGR-350 and a 250 MW modular pebble bed design similar to the HTR-PM (INET, China). This report summarizes the contributions of the HTGR Methods Simulation group at Idaho National Laboratory (INL) up to this point of the CRP. The activities at INL have been focused so far on creating the problem specifications for the prismatic design, as well as providing reference solutions for the exercises defined for Phase I. An overview is provided of the HTGR UAM objectives and scope, and the detailed specifications for Exercises I-1, I-2, I-3 and I-4 are also included here for completeness. The main focus of the report is the compilation and discussion of reference results for Phase I (i.e. for input parameters at their nominal or best-estimate values), which is defined as the first step of the uncertainty quantification process. These reference results can be used by other CRP participants for comparison with other codes or their own reference results. The status on the Monte Carlo modeling of the experimental VHTRC facility is also discussed. Reference results were obtained for the neutronics stand-alone cases (Ex. I-1 and Ex. I-2) using the (relatively new) Monte Carlo code Serpent, and comparisons were performed with the more established Monte Carlo codes MCNP and KENO-VI. For the thermal-fluids stand-alone cases (Ex. I-3 and I-4) the commercial CFD code CFX was utilized to obtain reference results that can be compared with lower fidelity tools.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Oakridge Geothermal Resources Assessment

Through the Communities Local Energy Action Program (LEAP), NREL provided technical assistance to a coalition of stakeholders from Oakridge, Oregon. The coalition included community-based non-profit organizations, the city government, the local utility, and others. Technical assistance provides analysis and information to support Oakridge stakeholders with their goals to increase energy reliability and resilience in the community, while promoting economic development. The Geothermal Resource Assessment provides technical analysis related to the geothermal resource in the Oakridge area, possible technology applications, and information related to further geothermal exploration. Technical analysis includes a review of a previous geothermal study conducted for Oakridge, thermal modeling to estimate reservoir temperatures, and technoeconomic simulation of a combined heat and power application in the Oakridge area.

15 GEOTHERMAL ENERGY↗

Dual-angle, self-calibrating Thomson scattering measurements in RFX-MOD

In the multipoint Thomson scattering (TS) system of the RFX-MOD experiment the signals from a few spatial positions can be observed simultaneously under two different scattering angles. In addition the detection system uses optical multiplexing by signal delays in fiber optic cables of different length so that the two sets of TS signals can be observed by the same polychromator. Owing to the dependence of the TS spectrum on the scattering angle, it was then possible to implement self-calibrating TS measurements in which the electron temperature T{sub e}, the electron density n{sub e} and the relative calibration coefficients of spectral channels sensitivity C{sub i} were simultaneously determined by a suitable analysis of the two sets of TS data collected at the two angles. The analysis has shown that, in spite of the small difference in the spectra obtained at the two angles, reliable values of the relative calibration coefficients can be determined by the analysis of good S/N dual‑angle spectra recorded in a few tens of plasma shots. This analysis suggests that in RFX-MOD the calibration of the entire set of TS polychromators by means of the similar, dual-laser (Nd:YAG/Nd:YLF) TS technique, should be feasible.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Hydrogen Compressor Reliability Investigation and Improvement. Cooperative Research and Development Final Report, CRADA Number CRD-13-514

Diaphragm compressors have become the primary source of on-site hydrogen compression for hydrogen fueling stations around the world. NREL and PDC have undertaken two studies aimed at improving hydrogen compressor operation and reducing the cost contribution to dispensed fuel. The first study identified the failure mechanisms associated with mechanical compression to reduce the maintenance and down-time. The second study will investigate novel station configurations to maximize hydrogen usage and compressor lifetime. This partnership will allow for the simulation of operations in the field and a thorough analysis of the component failure to improve the reliability of diaphragm compression.

30 DIRECT ENERGY CONVERSION↗

Structure retrieval from four-dimensional scanning transmission electron microscopy: Statistical analysis of potential pitfalls in high-dimensional data

Four-dimensional (4D) scanning transmission electron microscopy is one of the most rapidly growing modes of electron microscopy imaging. The advent of fast pixelated cameras and the associated data infrastructure have greatly accelerated this process. Yet conversion of the 4D datasets into physically meaningful structure images in real space remains an open issue. In this work, we demonstrate that it is possible to systematically create filters that will affect the apparent resolution or even qualitative features of the real-space structure image, reconstructing artificially generated patterns. As initial efforts, we explore statistical model selection algorithms, aiming for robustness and reliability of estimated filters. This statistical model selection analysis demonstrates the need for regularization and cross validation of inversion methods to robustly recover structure from high-dimensional diffraction datasets.

36 MATERIALS SCIENCE↗

Likelihood-based signal and noise analysis for docking of models into cryo-EM maps

Fast, reliable docking of models into cryo-EM maps requires understanding of the errors in the maps and the models. Likelihood-based approaches to errors have proven to be powerful and adaptable in experimental structural biology, finding applications in both crystallography and cryo-EM. Indeed, previous crystallographic work on the errors in structural models is directly applicable to likelihood targets in cryo-EM. Likelihood targets in Fourier space are derived here to characterize, based on the comparison of half-maps, the direction- and resolution-dependent variation in the strength of both signal and noise in the data. Because the signal depends on local features, the signal and noise are analysed in local regions of the cryo-EM reconstruction. The likelihood analysis extends to prediction of the signal that will be achieved in any docking calculation for a model of specified quality and completeness. A related calculation generalizes a previous measure of the information gained by making the cryo-EM reconstruction.

59 BASIC BIOLOGICAL SCIENCES↗

Segmentation method comparison for residual fiber length measurement across tiled microscopy images

Fiber length distribution (FLD), in part, governs mechanical properties in discontinuous fiber composites, yet manual measurement methods limit the high-throughput characterization needed for materials design optimization. This study compares deep learning segmentation approaches for automated FLD measurement in large-field microscopy, evaluating how method choice affects the microstructural descriptors used in structure-property-processing relationships. A critical challenge is that high-resolution microscopy images (10,000×10,000 pixels) must be tiled for deep learning analysis, fragmenting fibers at boundaries. We demonstrate that segmentation method proves crucial for measurement accuracy. For example, instance segmentation with Slicing Aided Hyper Inference (SAHI) preserves individual fiber integrity across tiles while semantic segmentation prioritizes speed. Comparing against manual measurement of extracted carbon fibers, YOLOv11-SAHI matched manual ground truth (238 μm weighted mean) with 40x speedup (4.5 vs 167 minutes per image). U-Net provides rapid quantification although it is at the cost of reduced accuracy due only reliably measuring stand-alone fibers. Our comparative analysis reveals that instance segmentation with SAHI better preserves length measurements while semantic segmentation prioritizes speed, providing empirical guidance for method selection. The characterization provides essential inputs for mechanical property prediction models and inverse design workflows, accelerating composite materials development cycles.

Additive manufacturing↗

Preparatory Verification of a New Monte Carlo Code cosRMC based on VERA Core Physics Benchmark

To promote nuclear power plant system design and simulation software self-reliance development, DOE of China approved a R and D key project to develop an integrated engine for pressurized water reactor core and system design and analysis, referred as COSINE hereafter. The scope of this code package includes reactor physics, thermal hydraulics, safety analysis, severe accidents, probability safety assessment and etc. Many universities, research institutes and nuclear related corporations in China are involved in the code development, among which the State Nuclear Power Software Development Center (SNPSDC) plays the leading role. With the requirement of accurate three-dimensional modeling of the advanced, special or new complex core in reactor neutronics and shielding analysis, Monte Carlo method is becoming a more powerful tool for reactor analysis. Thus, a new Monte Carlo transport code named cosRMC (abbreviation for COSINE Reactor Monte Carlo) has been developed jointly by SNPSDC and Department of Engineering Physics, Tsinghua University, the main developer of RMC code. The cosRMC now has many functions as criticality calculation, fixed-source calculation, burnup calculation, and etc. Some techniques for geometry treatment, new burnup algorithm, source convergence acceleration, massive tally and parallel calculation have been implemented in cosRMC to improve the efficiency. In order to ensure its reliability, several types of V and V work have been and are being carried out for cosRMC. In this paper, some preparatory verification results based on VERA Core Physics Benchmark are presented. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Tuscaloosa Marine Shale: Seal or Source? Petrophysical Comparative Study of Wells in SE Louisiana and SW Mississippi

The Tuscaloosa Marine Shale (TMS) is a versatile Late Cretaceous shale formation present in central and SE Louisiana and SW Mississippi, which drew attention because of the various roles played within the Tuscaloosa Group. In this paper, it is debated whether the Tuscaloosa Marine Shale can act as a source, reservoir, or seal all throughout the shale play or only in certain areas. Well log and core data from Adams County, Mississippi, are compared to data from East Feliciana Parish in Louisiana. Conclusions were drawn based on the results of well log analysis, X-ray Diffraction (XRD), porosity–permeability measurements, programmed pyrolysis, and fracture analysis. It was shown that the Tuscaloosa Marine Shale interval in SE Louisiana consists of important amounts of calcite, exhibits multiple natural fractures, has porosity values as high as 9.3%, and shows a TOC content of up to 2.8 wt%. On the other hand, samples from a well at the Cranfield field, MS, are characterized by considerably lower TOC values of around 0.88 wt%, porosities between 0.33% and 4%, and no serious fracturing. The formation demonstrates better reservoir and source potential in SE Louisiana and reliable CO2 sealing capacity in SW Mississippi. The analysis presented in this paper represents a holistic approach to the characterization of shale formations, is applicable to other plays around the world, and can be used as an integral part of CO2 sequestration or hydraulic fracturing programs.

04 OIL SHALES AND TAR SANDS↗