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DOE OSTI2024

Singular Perturbation-Based Large-Signal Order Reduction of Microgrids for Stability and Accuracy Synthesis With Control

The increasing penetration of distributed energy resources (DERs) highlights the growing importance of microgrids (MGs) in enhancing power system reliability. Employing electromagnetic transient (EMT) analysis in MGs becomes crucial for controlling the rapid transients. However, this requires an accurate but high-order model of power electronics and their underlying control loops, complexifying the stability analysis from the viewpoint of a higher control level. To overcome these challenges, this paper proposes a large-signal order reduction (LSOR) method for MGs with considerations of external control inputs and the detailed dynamics of underlying control levels based on singular perturbation theory (SPT). Specially, we innovatively proposed and strictly proved a general stability and accuracy assessment theorem that allows us to analyze the dynamic stability of a full-order nonlinear system by only leveraging our derived reduced-order model (ROM) and boundary layer model (BLM). Furthermore, this theorem furnishes a set of conditions that determine the accuracy of the developed ROM. Lastly, by embedding such a theorem into the SPT, we propose a novel LSOR approach with guaranteed accuracy and stability analysis equivalence. Case studies are conducted on MG systems to show the effectiveness of the proposed approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2013

Discovery of difference in the diffuse scattering from nonstoichiometric Ca{sub 0.87}La{sub 0.13}F{sub 2.13} and Ca{sub 0.92}Er{sub 0.08}F{sub 2.08} crystals with different types of clusters of structural defects

A new approach to application of diffuse scattering (DS) for studying the defect structure of crystals on laboratory radiation sources is implemented. The basic principles of this approach are as follows: (i) choice of crystals with a high concentration of structural defects (highly nonstoichiometric Ca{sub 1-x}R{sub x}F{sub 2+x} phases), (ii) application of intermeasurement minimization method (experimental comparison) to select a weak desired DS signal from a superposition of signals of different nature, and (iii) choice of the basic model proceeding from the reliable information provided by accurate analysis of the contribution of structural defects to Bragg reflections. Significantly different DS diffraction patterns have been recorded for Ca{sub 0.87}La{sub 0.13}F{sub 2.13} and Ca{sub 0.92}Er{sub 0.08}F{sub 2.08} crystals, characterized by different types of structural-defect clusters, determined from the Bragg diffraction data. Experiments performed at 90-100 K proved that DS is caused by clusters with stable atomic configurations rather than cooperative thermal atomic vibrations. A set of methods is proposed which can efficiently be used in diagnostics of nanomaterials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2017

Peakompactons: Peaked compact nonlinear waves

This paper is meant as an accessible introduction to/tutorial on the analytical construction and numerical simulation of a class of nonstandard solitary waves termed peakompactons. We present that these peaked compactly supported waves arise as solutions to nonlinear evolution equations from a hierarchy of nonlinearly dispersive Korteweg–de Vries-type models. Peakompactons, like the now-well-known compactons and unlike the soliton solutions of the Korteweg–de Vries equation, have finite support, i.e., they are of finite wavelength. However, unlike compactons, peakompactons are also peaked, i.e., a higher spatial derivative suffers a jump discontinuity at the wave’s crest. Here, we construct such solutions exactly by reducing the governing partial differential equation to a nonlinear ordinary differential equation and employing a phase-plane analysis. Lastly, a simple, but reliable, finite-difference scheme is also designed and tested for the simulation of collisions of peakompactons. In addition to the peakompacton class of solutions, the general physical features of the so-called K # (n,m) hierarchy of nonlinearly dispersive Korteweg–de Vries-type models are discussed as well.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Sivers extraction with Neural Network

Pseudo-data with simulated experimental errors can be generated to train an ensemble of Artificial Neural Networks (ANN) implemented on a regression to extract Transverse Momentum-dependent Distributions (TMDs). A preliminary analysis is presented on the reliability in extraction of the Sivers function imposed in the pseudo-data given the bounds on the experimental errors, data sparsity, and complexity of phase-space.

Fernando, Ishara↗

DOE OSTI2012

Alternative Fuel for Portland Cement Processing

The production of cement involves a combination of numerous raw materials, strictly monitored system processes, and temperatures on the order of 1500 °C. Immense quantities of fuel are required for the production of cement. Traditionally, energy from fossil fuels was solely relied upon for the production of cement. The overarching project objective is to evaluate the use of alternative fuels to lessen the dependence on non-renewable resources to produce portland cement. The key objective of using alternative fuels is to continue to produce high-quality cement while decreasing the use of non-renewable fuels and minimizing the impact on the environment. Burn characteristics and thermodynamic parameters were evaluated with a laboratory burn simulator under conditions that mimic those in the preheater where the fuels are brought into a cement plant. A drop-tube furnace and visualization method were developed that show potential for evaluating time- and space-resolved temperature distributions for fuel solid particles and liquid droplets undergoing combustion in various combustion atmospheres. Downdraft gasification has been explored as a means to extract chemical energy from poultry litter while limiting the throughput of potentially deleterious components with regards to use in firing a cement kiln. Results have shown that the clinkering is temperature independent, at least within the controllable temperature range. Limestone also had only a slight effect on the fusion when used to coat the pellets. However, limestone addition did display some promise in regards to chlorine capture, as ash analyses showed chlorine concentrations of more than four times greater in the limestone infused ash as compared to raw poultry litter. A reliable and convenient sampling procedure was developed to estimate the combustion quality of broiler litter that is the best compromise between convenience and reliability by means of statistical analysis. Multi-day trial burns were conducted at a full-scale cement plant with alternative fuels to examine their compatibility with the cement production process. Construction and demolition waste, woodchips, and soybean seeds were used as alternative fuels at a full-scale cement production facility. These fuels were co-fired with coal and waste plastics. The alternative fuels used in this trial accounted for 5 to 16 % of the total energy consumed during these burns. The overall performance of the portland cement produced during the various trial burns performed for practical purposes very similar to the cement produced during the control burn. The cement plant was successful in implementing alternative fuels to produce a consistent, high-quality product that increased cement performance while reducing the environmental footprint of the plant. The utilization of construction and demolition waste, woodchips and soybean seeds proved to be viable replacements for traditional fuels. The future use of these fuels depends on local availability, associated costs, and compatibility with a facility's production process.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2018

Sandia National Laboratories

Sandia National Laboratories is a multimission laboratory managed by National Technology & Engineering Solutions of Sandia, LLC a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration. Sandia has a long history of pioneering AM technology development. In the mid 1990s, Sandia developed laser-engineered net shaping (LENS), one of the first direct metal AM technologies, which was commercialized by Optomec. Robocast, an extrusion-based direct-write process for 3D ceramic parts, is another technology developed at Sandia. It was commercialized by Robocast Enterprises, LLC. As of January, 2019, Sandia was conducting AM R&D projects valued at about $25 million, with an emphasis on: 1) analysis-driven design, 2) materials reliability, and 3) multi-material AM.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Comparative Study of TESS Photometry and Radial Velocities on Six Early K-type Contact Binaries with Similar Periods around 0.268 Day

High-precision light curves were extracted from TESScut images. Together with APOGEE and LAMOST medium-resolution spectra, a joint study was made for six early K-type contact binary candidates selected unbiasedly with orbital periods around 0.268 day. It is found that all of them (RV CVn, EK Com, V384 Ser, V1038 Her, EH CVn, and CSS_J125403.7+503945) are W-subtype shallow contact systems, though with different mass ratios (1/q = 0.27–0.62). The effective temperature differences between the binary components are around a few hundred kelvins. The original definitions of the A and W subtypes were compared with the customarily used methods, which rely on the shape or photometric solutions of the light curves. The latter two methods are not always reliable; therefore, the radial velocity analysis is strongly recommended. Through a collection of all available K-type contact binaries with both photometric and spectroscopic measurements, it is found that almost all of them are W-subtype systems, except for a few objects that have nearly identical temperatures for binary components. This W-subtype phenomenon for K-type contact binaries should be further checked with more samples in the future. Finally, the physical parameters of the targets were determined with joint data analysis, and the multiplicity is discussed for these targets. Objects V384 Ser and RV CVn are confirmed to very likely be triple systems from comprehensive analysis, while V1038 Her is a candidate of a triple system based on photometric and spectroscopic solutions.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2018

Residual Stress Distribution in a Hydroformed Advanced High Strength Steel Component: Neutron Diffraction Measurements and Finite Element Simulations

Today’s automotive industry is witnessing increasing applications of advanced high strength steels (AHSS) combined with innovative manufacturing techniques to satisfy fuel economy requirements of stringent environmental regulations. The integration of AHSS in novel automotive structure design has introduced huge advantages in mass reduction while maintaining their structural performances, yet several concerns have been raised for this relatively new family of steels. One of those concerns is their potentially high springback after forming, which can lead to geometrical deviation of the final product from its designed geometry and cause difficulties during assembly. From the perspective of accurate prediction, control and compensation of springback, further understanding on the effect of residual stress in AHSS parts is urged. In this work, the residual stress distribution in a 980GEN3 steel part after hydroforming is investigated via experimental and numerical approaches. A non-destructive neutron diffraction technique is adopted to reveal the residual stress profiles across a 94-degree tube bending radius section of the hydroformed part. The finite element analysis (FEA) is also conducted to simulate the hydroforming and the subsequent unloading processes to predict the residual stress distribution within the same region. The correlation between experimental and simulation results is presented and the effectiveness of the FEA model for residual stress prediction is discussed. Findings in this study set the basis for springback analysis with improved accuracy and reliability.

Huang, Lu↗

DOE OSTI2017

Using depolarization to quantify ice nucleating particle concentrations: a new method

We have developed a new method to determine ice nucleating particle (INP) concentrations observed by the Texas A&M University continuous flow diffusion chamber (CFDC) under a wide range of operating conditions. In this study, we evaluate differences in particle optical properties detected by the Cloud and Aerosol Spectrometer with POLarization (CASPOL) to differentiate between ice crystals, droplets, and aerosols. The depolarization signal from the CASPOL instrument is used to determine the occurrence of water droplet breakthrough (WDBT) conditions in the CFDC. The standard procedure for determining INP concentration is to count all particles that have grown beyond a nominal size cutoff as ice crystals. During WDBT this procedure overestimates INP concentration, because large droplets are miscounted as ice crystals. Here we design a new analysis method based on depolarization ratio that can extend the range of operating conditions of the CFDC. The method agrees reasonably well with the traditional method under non-WDBT conditions with a mean percent error of ±32.1 %. Additionally, a comparison with the Colorado State University CFDC shows that the new analysis method can be used reliably during WDBT conditions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

MODELING AND PARAMETRIC STUDY OF END-GAS AUTOIGNITION TO ALLOW THE REALIZATION OF ULTRA-LOW EMISSIONS, HIGH-EFFICIENCY HEAVY-DUTY SPARK-IGNITED NATURAL GAS ENGINES

Engine knock and misfire are barriers to pathways leading to high-efficiency Spark-Ignited (SI) Natural Gas (NG) engines. The general tendency to knock is highly dependent on engine operating conditions and the fuel reactivity. The problem is further complicated by the low emission limits and the wide range of chemical reactivity in pipeline-quality natural gas. Depending on the region and the source of the natural gas, its reactivity, described by its Methane Number (MN), which is analogous to the Octane Number for liquid SI fuels, can span from 65 to 95. In order to realize diesel-like efficiencies, SI NG engines must be designed to operate at high Brake Mean Effective Pressures (BMEP), near or beyond knock limits, over a wide range of fuel reactivity. This requires a deep understanding of the combustion-engine interactions pertaining to flame propagation and End-Gas Autoignition (EGAI), i.e., the autoignition of the unburned gas (end gas) ahead of the flame front. However, EGAI, if controlled, provides an opportunity to increase SI NG engine efficiency by increasing the combustion rate and the total fraction of burned fuel, mitigating the effects of the slow flame speeds characteristic of natural gas fuels, which generally reduce BMEP and increase unburned hydrocarbon emissions. For this reason, to realize diesel-like efficiencies and ultra-low emissions on SI NG engines, this work proposes the study of the main parameters influencing the modeling and prediction of NG EGAI to allow for its control. In this work, a novel EGAI detection and onset determination method was developed to reliably quantify EGAI for data analysis and engine control. The new method allowed the prediction of EGAI on SI NG engines without the need to use engine- and operating-condition-dependent thresholds and reduced the error in quantifying the fraction of the total energy released by the EGAI event by up to 40%pts. One- and three-dimensional engine models were then developed to study the engine/fuel interactions that lead to NG EGAI and its performance benefits. These models, although having decent agreement with experimental data, showed the need to account for NOx chemistry when predicting NG EGAI due to a consistently later prediction of the EGAI onset (~1.65 crank-angle degrees) and thus, a new reduced chemical mechanism for real NG fuels was developed containing NOx chemistry. The new reduced mechanism improved the EGAI onset prediction agreement to within ±0.5 crank-angle degrees and decreased simulation time during combustion by nearly 50% when using the further reduced AREIS50NOx chemical mechanism. These models were then used to study the role of NG composition on EGAI, evaluate the engine/fuel interactions leading to NG EGAI, and perform engine optimization while leveraging EGAI to increase thermal efficiency. Piston design optimization combined with a Controlled EGAI (C-EGAI) combustion mode allowed a Heavy-Duty (HD) SI NG engine to operate at diesel-like efficiencies, i.e., Brake Thermal Efficiency (BTE) ≥44%. Experimental and modeling data analysis revealed that earlier and faster heat release increases combustion efficiency by an average of 1%pts, increases work transferred to the piston resulting in a decrease in exhaust losses by 50% depending on the engine operating condition while slightly increasing heat losses. Finally, the simulation results revealed an opportunity to further enhance the BTE (up to 50%) by enabling C-EGAI combustion at leaner conditions, λ=1.4-1.6.

Bestel, Diego Bernardi↗

DOE OSTI2025

Precision Measurement of the Neutron Magnetic Form Factor via the Ratio Method at Jefferson Lab Hall A

Protons and neutrons, collectively known as nucleons, are composed of quarks and gluons. The Sachs electromagnetic form factors encode information about the spatial distributions of charge and magnetization in the nucleon, particularly at low momentum transfer. In particular, the neutron magnetic form factor (GMn) provides crucial information about the distribution of magnetization inside the neutron and helps constrain theoretical models of nucleon structure. Quasi-elastic electron scattering from deuterium was measured up to Q^2=13.5 GeV^2 using the Super BigBite Spectrometer in Hall A at Jefferson Lab. In this work, the neutron magnetic form factor GMn was extracted at Q^2 = 3.0 GeV^2 and Q^2=4.5 GeV^2 using the Ratio Method. These results represent a subset of the full dataset collected in this experiment, which extended to significantly higher Q^2. The extracted GMn values agree with the existing global fit within approximately two standard deviations at Q^2=3.0 and show excellent agreement at Q^2=4.5. The measurements achieved systematic uncertainties of about 2% and statistical uncertainties below 0.5%, among the most precise determinations of GMn at these kinematics. These results demonstrate the robustness of the experimental technique and provide an important validation point for future extractions at higher Q^2, where data remain scarce. In addition, the GRINCH heavy gas Cherenkov detector—a key component of the experimental apparatus—was commissioned and achieved an electron detection efficiency of approximately 97%, supporting reliable particle identification. Together, the analysis presented here advances both our understanding of nucleon structure and the validation of the experimental methods and instrumentation used to access it.

Satnik, Maria [College of William and Mary, Willia↗

DOE OSTI2023

Grid-Forming PV Inverter: Technology Development and Microgrid Applications

Presently, excluding residential backup power applications, grid-forming (GFM) inverters are commercially available for battery energy storage system (BESS) and some PV plus battery systems but not yet for stand-alone PV. This tech update investigates the control design for GFM PV inverter, especially the control required to provide active power reserve and to stabilize the dc link voltage. Subsequently, the use cases of GFM PV plants in utility-level microgrids are discussed considering fully inverter-based microgrids (i.e., with PV and BESS) as well as mixed-source microgrids (i.e., with PV and diesel generator). Scenarios where active power up-reserve from GFM PV plants is beneficial are illustrated. Moreover, requirements and specifications for GFM PV plant, especially for its active power reserve function are developed. In addition, stability of an example utility-level microgrid with two GFM PV plants and a diesel generator is analyzed to shed light on the potential unstable interaction between multiple GFM resources and the countermeasures. This research aims to advance GFM PV technology to offer more flexibility in microgrid design. With GFM PV available, depending on the level of reliability required, cost-benefit analysis, etc., the GFM BESS or diesel generator may be sized smaller while leveraging the full potential of PV generation inside the microgrid.

14 SOLAR ENERGY↗

DOE OSTI2016

Comprehensive Solutions for Integration of Solar Resources into Grid Operations

The need for proactive closed-loop integration of uncertainty information into system operations and probability-based controls is widely recognized, but rarely implemented in system operations. Proactive integration for this project means that the information concerning expected uncertainty ranges for net load and balancing requirements, including required balancing capacity, ramping and ramp duration characteristics, will be fed back into the generation commitment and dispatch algorithms to modify their performance so that potential shortages of these characteristics can be prevented. This basic, yet important, premise is the motivating factor for this project. The achieved project goal is to demonstrate the benefit of such a system. The project quantifies future uncertainties, predicts additional system balancing needs including the prediction intervals for capacity and ramping requirements of future dispatch intervals, evaluates the impacts of uncertainties on transmission including the risk of overloads and voltage problems, and explores opportunities for intra-hour generation adjustments helping to provide more flexibility for system operators. The resulting benefits culminate in more reliable grid operation in the face of increased system uncertainty and variability caused by solar power. The project identifies that solar power does not require special separate penetration level restrictions or penalization for its intermittency. Ultimately, the collective consideration of all sources of intermittency distributed over a wide area unified with the comprehensive evaluation of various elements of balancing process, i.e. capacity, ramping, and energy requirements, help system operators more robustly and effectively balance generation against load and interchange. This project showed that doing so can facilitate more solar and other renewable resources on the grid without compromising reliability and control performance. Efforts during the project included developing and integrating advanced probabilistic solar forecasts, including distributed PV forecasts, into closed –loop decision making processes. Additionally, new uncertainty quantifications methods and tools for the direct integration of uncertainty and variability information into grid operations at the transmission and distribution levels were developed and tested. During Phase 1, project work focused heavily on the design, development and demonstration of a set of processes and tools that could reliably and efficiently incorporate solar power into California’s grid operations. In Phase 2, connectivity between the ramping analysis tools and market applications software were completed, multiple dispatch scenarios demonstrated a successful reduction of overall uncertainty and an analysis to quantify increases in system operator reliability, and the transmission and distribution system uncertainty prediction tool was introduced to system operation engineers in a live webinar. The project met its goals, the experiments prove the advancements to methods and tools, when working together, are beneficial to not only the California Independent System Operator, but the benefits are transferable to other system operators in the United States.

14 SOLAR ENERGY↗

DOE OSTI2015

Results of a Demonstration Assessment of Passive System Reliability Utilizing the Reliability Method for Passive Systems (RMPS)

Advanced small modular reactor designs include many advantageous design features such as passively driven safety systems that are arguably more reliable and cost effective relative to conventional active systems. Despite their attractiveness, a reliability assessment of passive systems can be difficult using conventional reliability methods due to the nature of passive systems. Simple deviations in boundary conditions can induce functional failures in a passive system, and intermediate or unexpected operating modes can also occur. As part of an ongoing project, Argonne National Laboratory is investigating various methodologies to address passive system reliability. The Reliability Method for Passive Systems (RMPS), a systematic approach for examining reliability, is one technique chosen for this analysis. This methodology is combined with the Risk-Informed Safety Margin Characterization (RISMC) approach to assess the reliability of a passive system and the impact of its associated uncertainties. For this demonstration problem, an integrated plant model of an advanced small modular pool-type sodium fast reactor with a passive reactor cavity cooling system is subjected to a station blackout using RELAP5-3D. This paper discusses important aspects of the reliability assessment, including deployment of the methodology, the uncertainty identification and quantification process, and identification of key risk metrics.

Bucknor, Matthew↗

DOE OSTI2015

Updated Value of Service Reliability Estimates for Electric Utility Customers in the United States

This report updates the 2009 meta-analysis that provides estimates of the value of service reliability for electricity customers in the United States (U.S.). The meta-dataset now includes 34 different datasets from surveys fielded by 10 different utility companies between 1989 and 2012. Because these studies used nearly identical interruption cost estimation or willingness-to-pay/accept methods, it was possible to integrate their results into a single meta-dataset describing the value of electric service reliability observed in all of them. Once the datasets from the various studies were combined, a two-part regression model was used to estimate customer damage functions that can be generally applied to calculate customer interruption costs per event by season, time of day, day of week, and geographical regions within the U.S. for industrial, commercial, and residential customers. This report focuses on the backwards stepwise selection process that was used to develop the final revised model for all customer classes. Across customer classes, the revised customer interruption cost model has improved significantly because it incorporates more data and does not include the many extraneous variables that were in the original specification from the 2009 meta-analysis. The backwards stepwise selection process led to a more parsimonious model that only included key variables, while still achieving comparable out-of-sample predictive performance. In turn, users of interruption cost estimation tools such as the Interruption Cost Estimate (ICE) Calculator will have less customer characteristics information to provide and the associated inputs page will be far less cumbersome. The upcoming new version of the ICE Calculator is anticipated to be released in 2015.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Business Case Analysis for Artificial Intelligence-Large Language Model Technology Integration

AI-assisted processes are expected to enhance operational efficiency and improve decision-making, supporting the long-term economic viability of nuclear power plants. However, detailed business analyses of AI-generated cost savings are rarely performed. Given the recent industry interest in Large Language Model (LLM), the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program has conducted a comprehensive business case analysis of LLM Artificial Intelligence (AI) implementation in nuclear plant engineering workflows. The research employed three complementary business case approaches to evaluate impact of an LLM, using three representative engineering processes as use-cases: Boric Acid Corrosion (BAC) Evaluations, Maintenance Rule Evaluations, and 10 CFR 50.59 Screenings. Through detailed workload analyses and structured interviews, the study quantified significant efficiency improvements ranging from 11% to 59% across these processes. The research further considers how these efficiency gains could translate into tangible reliability improvements through enhanced engineering capacity. Analysis of historical plant trip data indicates that enabling engineers to focus on proactive reliability activities could provide substantial financial benefits through avoided outages, potentially generating greater value than the direct efficiency improvements alone. By documenting successful applications, implementation challenges, and strategic opportunities, this research provides nuclear utilities with a practical framework for evaluating the value of AI technology to support long-term operations through advanced digital technologies.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Gearbox Reliability Collaborative Phase 3 Gearbox 3 Test

The GRC uses a combined gearbox testing, modeling, and analysis approach disseminating data and results to the industry and facilitating improvement of gearbox reliability. This test data describes the tests of GRC gearbox 3 in the National Wind Technology Center dynamometer and documents any modifications to the original test plan. It serves as a guide to interpret the publicly released data sets with brief analyses to illustrate the data. TDMS viewer and Solidworks software required to view data files. The National Renewable Energy Laboratory (NREL) Gearbox Reliability Collaborative (GRC) was established by the U.S. Department of Energy in 2006; its key goal is to understand the root causes of premature gearbox failures and improve their reliability.

17 WIND ENERGY↗

DOE OSTI2026

Integrated Reliability and Economic Modeling for Transmission Across Large Regions: A Space Odyssey

Power flow modeling and stability analysis are needed to more-comprehensively assess system reliability but the development of the system portfolios and conditions require use of economic models (e.g., production cost). What are the state of art methods for efficiently linking economic and reliability models to enable examination of multiple snapshots and perform detailed nodal analyses?

24 POWER TRANSMISSION AND DISTRIBUTION↗