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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Linear fitting of multi-threshold counting data

The present disclosure provides a system and method for efficiently mining multi-threshold measurements acquired using photon counting pixel-array detectors for spectral imaging and diffraction analyses. Images of X-ray intensity as a function of X-ray energy were recorded on a 6 megapixel X-ray photon counting array detector through linear fitting of the measured counts recorded as a function of counting threshold. An analytical model is disclosed for describing the probability density of detected voltage, utilizing fractional photon counting to account for edge/corner effects from voltage plumes that spread across multiple pixels. Three-parameter fits to the model were independently performed for each pixel in the array for X-ray scattering images acquired for 13.5 keV and 15.0 keV X-ray energies. From the established pixel responses, multi-threshold composite images produced from the sum of 13.5 keV and 15.0 keV data can be analytically separated to recover the monochromatic images through simple linear fitting.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Plant Water Profiler: A Tool for Understanding Water Use, Cost and Savings Potential for Manufacturing Plants

In the 1746 Poor Richard’s Almanack, Benjamin Franklin published “When the well’s dry, we know the worth of water” (Franklin, 1746); industrial water users have begun to see the truth in these words as they examine the potential and reality of water scarcity becoming a significant business risk. Through the authors’ interactions with manufacturers via the U.S. Department of Energy’s Better Plants program and Strategic Analysis projects, they realized that manufacturing facilities often do not fully understand the risks to the water supply and the consequential risks to their business. The authors’ also noticed that many facilities do not know how their water is used (baselining), how they compare with their peers (benchmarking), the actual cost impacts of water use (true cost of water), and potential areas for water savings. This results in a lack of motivation and ability to identify and implement effective water-efficiency measures.The Plant Water Profiler Tool (PWP) was created to help manufacturing plant management address these issues by identifying and accounting for water use in manufacturing operations, helping determine the true cost of water, and providing some high-level estimates for peer comparison. The PWP uses a water mass balance and common engineering equations to estimate water use by each of the facility’s systems (e.g., differentiating process water use from cooling and restroom water use), even when no submetering data is available. This new tool also helps users identify possible areas for water savings and associated water and energy cost savings, making it a potentially useful resource for corporations conducting water assessments. Additionally, governments and private organizations can use the methodology behind this tool to design a survey to help build a database of industrial water use. This paper and corresponding presentation provide an overview of current industrial water use practices and tools, as well as the value of determining the true cost of water. It also briefly describes the methodology behind the tool, then focuses on its functionality through an industrial case study and lessons learned from implementing the case study.

Armstrong, Kristina O.↗
DOE OSTI2017

Development of utility generic functional requirements for electronic work packages and computer-based procedures - 273

The Nuclear Electronic Work Packages - Enterprise Requirements (NEWPER) initiative is a step toward a vision of implementing an eWP framework that includes many types of eWPs. This will enable immediate paper-related cost savings in work management and provide a path to future labor efficiency gains through enhanced integration and process improvement in support of the Nuclear Promise (Nuclear Energy Institute 2016). The NEWPER initiative was organized by the Nuclear Information Technology Strategic Leadership (NITSL) group, which is an organization that brings together leaders from the nuclear utility industry and regulatory agencies to address issues involved with information technology used in nuclear-power utilities. NITSL strives to maintain awareness of industry information technology-related initiatives and events and communicates those events to its membership. NITSL and Light Water Reactor Sustainability Program researchers have been coordinating activities, including joint organization of NEWPER-related meetings and report development. The main goal of the NEWPER initiative was to develop a set of utility generic functional requirements for eWP systems. This set of requirements will support each utility in their process of identifying plant-specific functional and non-functional requirements. The NEWPER initiative has 140 members where the largest group of members consists of 19 commercial U.S. nuclear utilities and eleven of the most prominent vendors of eWP solutions. Through the NEWPER initiative two sets of functional requirements were developed; functional requirements for electronic work packages and functional requirements for computer-based procedures. This paper will describe the development process as well as a summary of the requirements. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Modeling plasticity-mediated void growth at the single crystal scale: A physics-informed machine learning approach

Modeling the evolution of voids during plastic flow as well as their effects on plastic dissipation is critical for both component manufacturing and lifetime estimation purposes. To this end, we propose a rate-dependent constitutive model to homogenize the effects of semi-randomly distributed voids on single crystal plasticity whilst capturing void interaction and plastic anisotropy. Here, this present work focuses on the case of face centered cubic crystals to introduce an anisotropic gauge function applicable within the crystal plasticity formalism. The approach combines analytical methods to describe the micromechanics of the system in combination with symbolic regression to capture analytically intractable mechanisms from data. The hybrid framework uses a physics-informed genetic programming-based symbolic regression algorithm to solve a multiform optimization problem simultaneously producing a new gauge function and a new strain rate equation. This is also a multi-objective optimization problem with many competing objectives. A new search and selection step is introduced to the genetic algorithm that promotes convergence toward a global solution that better satisfies all the objectives. Overall, the symbolic equations produced leverage data-driven methods to achieve greater accuracy than comparable alternatives on an analytically intractable problem while maintaining model transparency.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The Predictive Power of Exact Constraints and Appropriate Norms in Density Functional Theory

Ground-state Kohn-Sham density functional theory provides, in principle, the exact ground-state energy and electronic spin densities of real interacting electrons in a static external potential. In practice, the exact density functional for the exchange-correlation (xc) energy must be approximated in a computationally efficient way. About 20 mathematical properties of the exact xc functional are known. In this work, we review and discuss these known constraints on the xc energy and hole. By analyzing a sequence of increasingly sophisticated density functional approximations (DFAs), we argue that (a) the satisfaction of more exact constraints and appropriate norms makes a functional more predictive over the immense space of many-electron systems and (b) fitting to bonded systems yields an interpolative DFA that may not extrapolate well to systems unlike those in the fitting set. We discuss both how the class of well-described systems has grown along with constraint satisfaction and the possibilities for future functional development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Black hole and galaxy coevolution from continuity equation and abundance matching

We investigate the coevolution of galaxies and hosted supermassive black holes (BHs) throughout the history of the universe by a statistical approach based on the continuity equation and the abundance matching technique. Specifically, we present analytical solutions of the continuity equation without source terms to reconstruct the supermassive BH mass function from the active galactic nucleus (AGN) luminosity functions. Such an approach includes physically motivated AGN light curves tested on independent data sets, which describe the evolution of the Eddington ratio and radiative efficiency from slim- to thin-disk conditions. We nicely reproduce the local estimates of the BH mass function, the AGN duty cycle as a function of mass and redshift, along with the Eddington ratio function and the fraction of galaxies with given stellar mass hosting an AGN with given Eddington ratio. We exploit the same approach to reconstruct the observed stellar mass function at different redshift from the ultraviolet and far-IR luminosity functions associated with star formation in galaxies. These results imply that the build-up of stars and BHs in galaxies occurs via in situ processes, with dry mergers playing a marginal role at least for stellar masses ≲3×10{sup 11} M{sub ⊙} and BH masses ≲10{sup 9} M{sub ⊙}, where the statistical data are more secure and less biased by systematic errors. In addition, we develop an improved abundance matching technique to link the stellar and BH content of galaxies to the gravitationally dominant dark matter (DM) component. The resulting relationships constitute a testbed for galaxy evolution models, highlighting the complementary role of stellar and AGN feedback in the star formation process. In addition, they may be operationally implemented in numerical simulations to populate DM halos or to gauge subgrid physics. Moreover, they may be exploited to investigate the galaxy/AGN clustering as a function of redshift, mass, and/or luminosity. In fact, the clustering properties of BHs and galaxies are found to be in full agreement with current observations, thus further validating our results from the continuity equation. Finally, our analysis highlights that (i) the fraction of AGNs observed in the slim-disk regime, where most of the BH mass is accreted, increases with redshift; and (ii) already at z≳6 a substantial amount of dust must have formed over timescales ≲10{sup 8} yr in strongly star-forming galaxies, making these sources well within the reach of ALMA surveys in (sub)millimeter bands.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Microscopic optical potentials from a Green's function approach

Optical potentials are a standard tool in the study of nuclear reactions, as they describe the interaction between a target nucleus and a projectile. The use of phenomenological optical potentials built using experimental data on stable isotopes is widespread. Although successful in their dedicated domain, it is unclear whether these phenomenological potentials can provide reliable predictions for unstable isotopes. To address this problem, optical potentials based on microscopic nuclear structure input calculations prove to be crucial and are an important current line of research. In this work we present an explicit implementation of the Feshbach formalism for the systematic derivation of optical potentials using input from nuclear structure models. Numerical tools for the derivation of Green's functions associated with nonlocal potentials are presented. In conclusion, the new optical potential, based on the valence shell model, is applied to the calculations of 𝑛 + 24 Mg elastic scattering and yields a close agreement with the experimental data.

Direct reactions↗
DOE OSTI2025

Dynamics-based halo model for large scale structure

Accurate modeling of the one-to-two halo transition has long been difficult to achieve. Here, we demonstrate that physically motivated halo definitions that respect the bimodal phase-space distribution of dark matter particles near halos resolves this difficulty. Specifically, the two phase-space components are overlapping and correspond to (1) particles orbiting the halo and (2) particles infalling into the halo for the first time. Motivated by this decomposition, García et al. [Mon. Not. R. Astron. Soc. 521, 2464 (2023)] advocated for defining halos as the collection of particles orbiting their self-generated potential. This definition identifies the traditional one-halo term of the halo-mass correlation function with the distribution of orbiting particles around a halo, while the two-halo term governs the distribution of infalling particles. We use dark matter simulations to demonstrate that the distribution of orbiting particles is finite and can be characterized by a single physical scale 𝑟 h , which we refer to as the halo radius. The two-halo term is described using a simple yet accurate empirical model based on the Zel’dovich correlation function. We further demonstrate that the halo radius imprints itself on the distribution of infalling particles at small scales. Our final model for the halo-mass correlation function is accurate at the ≈ 2% level for 𝑟∈ [0.1, 50] ℎ −1 Mpc. The Fourier transform of our best-fit model describes the halo-mass power spectrum with comparable accuracy for 𝑘 ∈ [0.06, 6.0] ℎ Mpc −1 .

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Structural basis for auxiliary subunit KCTD16 regulation of the GABA B receptor

Metabotropic GABA B receptors mediate a significant fraction of inhibitory neurotransmission in the brain. Native GABA B receptor complexes contain the principal subunits GABA B1 and GABA B2 , which form an obligate heterodimer, and auxiliary subunits, known as potassium channel tetramerization domain-containing proteins (KCTDs). KCTDs interact with GABA B receptors and modify the kinetics of GABA B receptor signaling. Little is known about the molecular mechanism governing the direct association and functional coupling of GABA B receptors with these auxiliary proteins. Here, we describe the high-resolution structure of the KCTD16 oligomerization domain in complex with part of the GABA B2 receptor. A single GABA B2 C-terminal peptide is bound to the interior of an open pentamer formed by the oligomerization domain of five KCTD16 subunits. Mutation of specific amino acids identified in the structure of the GABA B2 –KCTD16 interface disrupted both the biochemical association and functional modulation of GABA B receptors and G protein-activated inwardly rectifying K + channel (GIRK) channels. These interfacial residues are conserved among KCTDs, suggesting a common mode of KCTD interaction with GABA B receptors. Defining the binding interface of GABA B receptor and KCTD reveals a potential regulatory site for modulating GABA B -receptor function in the brain.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Origin of the Low-Energy Enhancement of the γ-Ray Strength Function

The low-energy enhancement (LEE) in γ-ray strength functions has been experimentally identified in a large number of nuclei during the past two decades; however, the origin of the enhancement is not fully understood. Building on previous theoretical work, we investigate the LEE and its relation to the scissors mode (SM) with an independent theoretical approach. We apply a novel angular-momentum-projected shell-model method that explicitly endows degrees of freedom to describe the scissors motion. Taking the recently measured γ-ray strength functions in Neodymium isotopes as examples, we find that the LEE arises from a quasi-free scissors motion appearing only in weakly-deformed nuclei, which can be viewed as an approximate free-rotation of neutrons with respect to protons. This leads us to propose a new type of collective motion, scissors rotation, to contrast the scissors vibration widely known in well-deformed nuclei. The observed LEE is naturally interpreted as the first evidence for this collective excitation mode.

Collective models↗
DOE OSTI2016

A compact neutron scatter camera for field deployment

Here, we describe a very compact (0.9 m high, 0.4 m diameter, 40 kg) battery operable neutron scatter camera designed for field deployment. Unlike most other systems, the configuration of the sixteen liquid-scintillator detection cells are arranged to provide omnidirectional (4π) imaging with sensitivity comparable to a conventional two-plane system. Although designed primarily to operate as a neutron scatter camera for localizing energetic neutron sources, it also functions as a Compton camera for localizing gamma sources. In addition to describing the radionuclide source localization capabilities of this system, we demonstrate how it provides neutron spectra that can distinguish plutonium metal from plutonium oxide sources, in addition to the easier task of distinguishing AmBe from fission sources.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Development of a Cold Start Fuel Penalty Metric for Evaluating the Impact of Fuel Composition Changes on SI Engine Emissions Control

The U.S. Department of Energy’s Co-Optimization of Fuels and Engines initiative (Co-Optima) aims to simultaneously transform both transportation fuels and engines to maximize performance and energy efficiency. Researchers from across the DOE national laboratories are working within Co-Optima to develop merit functions for evaluating the impact of fuel formulations on the performance of advanced engines. The merit functions relate overall engine efficiency to specific measurable fuel properties and will serve as key tools in the fuel/engine co-optimization process. This work focused on developing a term for the Co-Optima light-duty boosted spark ignition (SI) engine merit function that captures the effects of fuel composition on emissions control system performance. For stoichiometric light-duty SI engines, the majority of NOx, NMOG, and CO emissions occur during cold start, before the three-way catalyst (TWC) has reached its “light-off” temperature. This light-off temperature depends on the exhaust composition, which changes with fuel formulation. Thus, the time to achieve light-off, and therefore the cold start emissions, depends on fuel composition. Since the time to reach light-off must be minimized to meet emissions regulations, modern vehicles employ cold start strategies that intentionally release fuel energy into the engine exhaust to heat the TWC above the light-off temperature as quickly as possible. The fuel penalty associated with catalyst heating during cold start provides a link between fuel properties, emissions performance, and engine efficiency. This paper describes the derivation of the Co-Optima SI engine merit function term for emissions control, which is based on the cold start fuel penalty for catalyst heating and the catalytic light-off temperature for a particular fuel composition. It also discusses the process used for extracting cold start fuel penalties from chassis dynamometer data sets previously collected at ORNL. The form of the merit function term is simple, but it is only intended as a starting point for comparing the potential impacts of changes in fuel formulation on emissions control system performance.

Pihl, Josh↗
DOE OSTI2022

Targeting the Y-box Binding Protein-1 Axis to Overcome Radiochemotherapy Resistance in Solid Tumors

Multifunctional Y-box binding protein-1 (YB-1) is highly expressed in different human solid tumors and is involved in various cellular processes. DNA damage is the major mechanism by which radiochemotherapy (RCT) induces cell death. On induction of DNA damage, a multicomponent signal transduction network, known as the DNA damage response, is activated to induce cell cycle arrest and initiate DNA repair, which protects cells against damage. YB-1 regulates nearly all cancer hallmarks described to date by participating in DNA damage response, gene transcription, mRNA splicing, translation, and tumor stemness. YB-1 lacks kinase activity, and p90 ribosomal S6 kinase and AKT are the key kinases within the RAS/mitogen-activated protein kinase and phosphoinositide 3-kinase pathways that directly activate YB-1. Thus, the molecular targeting of ribosomal S6 kinase and AKT is thought to be the most effective strategy for blocking the cellular function of YB-1 in human solid tumors. In this review, after describing the prosurvival effect of YB-1 with a focus on DNA damage repair and cancer cell stemness, clinical evidence will be provided indicating an inverse correlation between YB-1 expression and the treatment outcome of solid tumors after RCT. In the interest of being concise, YB-1 signaling cascades will be briefly discussed and the current literature on YB-1 posttranslational modifications will be summarized. Finally, the current status of targeting the YB-1 axis, especially in combination with RCT, will be highlighted.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Principal shapes and squeezed limits in the effective field theory of large scale structure

We apply an orthogonalization procedure on the effective field theory of large scale structure (EFT of LSS) shapes, relevant for the angle-averaged bispectrum and non-Gaussian covariance of the matter power spectrum at one loop. Assuming natural-sized EFT parameters, this identifies a linear combination of EFT shapes—referred to as the principal shape—that gives the dominant contribution for the whole kinematic plane, with subdominant combinations suppressed by a few orders of magnitude. For the covariance, our orthogonal transformation is in excellent agreement with a principal component analysis applied to available data. Additionally we find that, for both observables, the coefficients of the principal shapes are well approximated by the EFT coefficients appearing in the squeezed limit, and are thus measurable from power spectrum response functions. Employing data from N-body simulations for the growth-only response, we measure the single EFT coefficient describing the angle-averaged bispectrum with Ο (10%) precision. These methods of shape orthogonalization and measurement of coefficients from response functions are valuable tools for developing the EFT of LSS framework, and can be applied to more general observables.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Resource selection functions based on hierarchical generalized additive models provide new insights into individual animal variation and species distributions

Habitat selection studies are designed to generate predictions of species distributions or inference regarding general habitat associations and individual variation in habitat use. Such studies frequently involve either individually indexed locations gathered across limited spatial extents and analyzed using resource selection functions (RSFs) or spatially extensive locational data without individual resolution typically analyzed using species distribution models. Both analytical methodologies have certain desirable features, but analyses that combine individual- and population-level inference with flexible non-linear functions may provide improved predictions while accounting for individual variation. Here, we describe how RSFs can be fit using hierarchical generalized additive models (HGAMs) using widely available software, providing a means to explore individual variation in habitat associations and to generate species distribution maps. We used GPS tracking data from golden eagles Aquila chrysaetos from across eastern North America with four environmental predictors to generate monthly distribution models. We considered three model structures that assumed different amounts of individual variation in the functional relationship between predictors and habitat use and used k-fold cross-validation to compare model performance. Models accounting for individual variability in shape and smoothness of functional responses performed best. Eagles exhibited the least amount of individual variation in response to land cover variables during winter months, with most individuals more closely adhering to the population-level trend. During the summer months, eagles exhibited more substantial individual variation in shape and smoothness of the functional relationships, suggesting some need to account for individual variation in eagle habitat use for both inferential and predictive purposes, during this time of year. Because they allow users to blend flexible functions with random effects structures and are well-supported by a variety of software platforms, we believe that HGAMs provide a useful addition to the suite of analyses used for modeling habitat associations or predicting species distributions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Stacking disorder in α – RuCl 3 investigated via x-ray three-dimensional difference pair distribution function analysis

The van der Waals layered magnet α-RuCl 3 offers tantalizing prospects for the realization of Majorana quasiparticles. Efforts to understand this are, however, hampered by inconsistent magnetic and thermal transport properties likely coming from the formation of structural disorder during crystal growth, postgrowth processing, or upon cooling through the first order structural transition. Here, we investigate structural disorder in α-RuCl 3 using x-ray diffuse scattering and three-dimensional difference pair distribution function (3D-ΔPDF) analysis. We develop a quantitative model that describes disorder in α-RuCl 3 in terms of rotational twinning and intermixing of the high and low-temperature structural layer stacking. As a result, this disorder may be important to consider when investigating the detailed magnetic and electronic properties of this widely studied material.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Electronic structure of strongly correlated systems: recent developments in multiconfiguration pair-density functional theory and multiconfiguration nonclassical-energy functional theory

Strong electron correlation plays an important role in transition-metal and heavy-metal chemistry, magnetic molecules, bond breaking, biradicals, excited states, and many functional materials, but it provides a significant challenge for modern electronic structure theory. The treatment of strongly correlated systems usually requires a multireference method to adequately describe spin densities and near-degeneracy correlation. However, quantitative computation of dynamic correlation with multireference wave functions is often difficult or impractical. Multiconfiguration pair-density functional theory (MC-PDFT) provides a way to blend multiconfiguration wave function theory and density functional theory to quantitatively treat both near-degeneracy correlation and dynamic correlation in strongly correlated systems; it is more affordable than multireference perturbation theory, multireference configuration interaction, or multireference coupled cluster theory and more accurate for many properties than Kohn–Sham density functional theory. This perspective article provides a brief introduction to strongly correlated systems and previously reviewed progress on MC-PDFT followed by a discussion of several recent developments and applications of MC-PDFT and related methods, including localized-active-space MC-PDFT, generalized active-space MC-PDFT, density-matrix-renormalization-group MC-PDFT, hybrid MC-PDFT, multistate MC-PDFT, spin–orbit coupling, analytic gradients, and dipole moments. We also review the more recently introduced multiconfiguration nonclassical-energy functional theory (MC-NEFT), which is like MC-PDFT but allows for other ingredients in the nonclassical-energy functional. We discuss two new kinds of MC-NEFT methods, namely multiconfiguration density coherence functional theory and machine-learned functionals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Experimental Evaluation of PV Inverter Anti-Islanding with Grid Support Functions in Multi-Inverter Island Scenarios

As PV and other DER systems are connected to the grid at increased penetration levels, island detection may become more challenging for two reasons: 1.) In islands containing many DERs, active inverter-based anti-islanding methods may have more difficulty detecting islands because each individual inverter's efforts to detect the island may be interfered with by the other inverters in the island. 2.) The increasing numbers of DERs are leading to new requirements that DERs ride through grid disturbances and even actively try to regulate grid voltage and frequency back towards nominal operating conditions. These new grid support requirements may directly or indirectly interfere with anti-islanding controls. This report describes a series of tests designed to examine the impacts of both grid support functions and multi-inverter islands on anti-islanding effectiveness. Crucially, the multi-inverter anti-islanding tests described in this report examine scenarios with multiple inverters connected to multiple different points on the grid. While this so-called 'solar subdivision' scenario has been examined to some extent through simulation, this is the first known work to test it using hardware inverters. This was accomplished through the use of power hardware-in-the-loop (PHIL) simulation, which allows the hardware inverters to be connected to a real-time transient simulation of an electric power system that can be easily reconfigured to test various distribution circuit scenarios. The anti-islanding test design was a modified version of the unintentional islanding test in IEEE Standard 1547.1, which creates a balanced, resonant island with the intent of creating a highly challenging condition for island detection. Three common, commercially available single-phase PV inverters from three different manufacturers were tested. The first part of this work examined each inverter individually using a series of pure hardware resistive-inductive-capacitive (RLC) resonant load based anti-islanding tests to determine the worst-case configuration of grid support functions for each inverter. A grid support function is a function an inverter performs to help stabilize the grid or drive the grid back towards its nominal operating point. The four grid support functions examined here were voltage ride-through, frequency ride-through, Volt-VAr control, and frequency-Watt control. The worst-case grid support configuration was defined as the configuration that led to the maximum island duration (or run-on time, ROT) out of 50 tests of each inverter. For each of the three inverters, it was observed that maximum ROT increased when voltage and frequency ride-through were activated. No conclusive evidence was found that Volt-VAr control or frequency-Watt control increased maximum ROT. Over all single-inverter test cases, the maximum ROT was 711 ms, well below the two-second limit currently imposed by IEEE Standard 1547-2003. A subsequent series of 244 experiments tested all three inverters simultaneously in the same island. These tests again used a procedure based on the IEEE 1547.1 unintentional islanding test to create a difficult-to-detect island condition. For these tests, which used the two worst-case grid support function configurations from the single-inverter tests, the inverters were connected to a variety of island circuit topologies designed to represent the variety of multiple-inverter islands that may occur on real distribution circuits. The interconnecting circuits and the resonant island load itself were represented in the real-time PHIL model. PHIL techniques similar to those employed here have been previously used and validated for anti-islanding tests, and the PHIL resonant load model used in this test was successfully validated by comparing single-inverter PHIL tests to conventional tests using an RLC load bank.

24 POWER TRANSMISSION AND DISTRIBUTION↗