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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Corrosion resistance of functionally graded TiN/Ti coatings for proton exchange membrane fuel cells

Bipolar Plates (BPP) are important components of proton exchange membrane fuel cell (PEMFC) stacks. In the development of innovative fuel cell designs, it is advantageous to use aluminum for these applications, however, this material lacks the necessary corrosion resistance. Since the performance of PEMFC stacks depends on BPP properties, in particular, corrosion resistance, depositing titanium nitride (TiN) thin films onto aluminum substrates may improve their efficiency and durability. Present work focuses on improving corrosion resistance and hydrophobicity of TiN/Ti by using N graded films deposited onto aluminum substrates (AA-1100) by grid-assisted magnetron sputtering (GAMS). Electrochemical impedance spectroscopy (EIS) with potentiodynamic and potentiostatic polarization are used to investigate the performance of the substrate/film system at room temperature and 70 oC, thus simulating a prototypic PEMFC electrolyte environment. Electrochemical test results showed that graded TiN films improved corrosion resistance when compared with both the homogeneous films and the AA1100 uncoated substrate. Furthermore, contact angle results reveal improved hydrophobicity for both homogeneous and graded TiN coatings when compared with the AA1100 substrate.

25 ENERGY STORAGE↗
DOE OSTI2024

Photovoltaic Analysis and Response Support (PARS) Platform for Solar Situational Awareness and Resiliency Services

The project's primary objective is to develop a digital-twin based Photovoltaic (PV) Analysis and Response Support (PARS) platform, which aims to provide real-time situational awareness and optimal response plans. This platform is designed to enhance the performance of hybrid PV systems, making them competitive with or even superior to conventional generation resources. The PARS platform enabled the project team to develop and evaluate an extensive suite of grid support functionalities for the hybrid PV systems to enhance grid performance, across key areas including visibility, dispatchability, security, resilience, and reliability. Given the global push toward achieving 100% clean energy by 2035, there is a significant increase in the integration of inverter-based resources (IBRs) throughout the energy grid. Effectively managing the inherent variability and uncertainty associated with IBRs is crucial for ensuring cost-effectiveness, reliability, and security in both the main grid and islanded microgrids. Constrained to a limited array of IEEE test systems or standard feeder models, traditional IBR modeling struggles to assimilate new field data, accurately reflect system dynamics, and adapt to the evolving energy landscape. In our project, we embraced a Digital Twin (DT) strategy for crafting the PARS platform. A digital twin acts as a precise virtual counterpart of a physical system, built on historical data and continuously honed with real-time insights. This enables the high-fidelity DT to accurately mirror current system operations and forecast future scenarios. Consequently, the PARS platform becomes an ideal environment for testing and refining monitoring, control, power, and energy management algorithms designed to boost hybrid PV system performance. The defining feature of the PARS platform, distinguishing it from other advanced simulation tools, is its exceptional adaptability. This is achieved by employing actual network topologies and utilizing real-time field data for fine-tuning and calibration, ensuring a close emulation of real-world conditions. The project deliverables include: 1) High-fidelity IBR models and tools for real-time parameterization, utilizing real-time field measurements to refine IBR models for enhanced accuracy and performance; 2) Grid-forming and Grid-following capabilities to deliver resilience services, including blackstart, voltage and frequency support, cold-load pick-up, power reserves, and three-phase load balancing across grid-connected and microgrid settings; 3) Machine learning-based forecasting tools and methods for generating synthetic data and topologies, creating diverse and realistic simulation environments for evaluating varied operational scenarios; 4) Advanced microgrid power and energy management algorithms for optimizing the integration and operation of PV, storage, and demand response resources within both feeder and community scales. The power grid data sets are provided by four utility companies in North Carolina and the New York Power Administration. Acting as industry advisors, our industry partners communicated stakeholder needs and regulatory standards to the research teams, aiding technology transfer by incorporating the developed methodologies into their daily operations. This collaboration ensures that the PARS platform, functioning as a power system digital twin, enhances our understanding of IBR dynamic behaviors and enables the development and evaluation of IBR control functions that match or exceed the capabilities of conventional synchronous generators.

14 SOLAR ENERGY↗
DOE OSTI2025

Does class matter? Understanding differential pandemic recovery via a building typology

This study investigates the recovery of building-level footfall from the COVID-19 pandemic using privacy-preserving mobile devices-based footfall data within 60 downtown areas in the USA and Canada. Using clustering, we identify five distinct building typologies based on their characteristics, including rent, quality and recovery rates. The results reveal significant variation of recovery rates by building features. We find negative relationships with footfall recovery for both the percentage of office and remote work tenants and building quality. In contrast, buildings with traditional work tenants and retail functions achieve higher recovery rates. We also test the ‘flight to quality’ hypothesis via on our typology results. High-quality office buildings (Class A+) continue to have high rents but experience low physical footfall recovery, which suggests that this class is not as resilient as portrayed. The findings thus suggest the importance of considering both economic and footfall resilience in evaluating the performance of office buildings.

Covid-19↗
DOE OSTI2025

Let’s Stick Together: Interplay of Moisture, Particle Size, and Anatomical Fraction in the Flowability of Corn Stover Crumbles

Handling of agricultural waste biomass feedstocks (such as corn stover) is a persistent challenge in the production of biofuels and chemicals at integrated biorefineries. Inconsistent flowability and high feedstock variability creates equipment downtime and processing challenges. This work investigates the influence of anatomical fractionation and moisture content on the bulk solids handling behavior of corn stover crumbles. A combination of rotational shear testing, tribological measurements, and surface and sorption characterization techniques (inverse gas chromatography (IGC), dynamic vapor sorption (DVS), and electron microscopy) were used to evaluate the contributions of particle composition, size, and surface properties to flow behavior. Shear and frictional testing revealed that moisture content has the greatest effect on flowability, significantly increasing unconfined yield strength (ƒ c ) and reducing the flow function coefficient (F F C), regardless of anatomical fraction. While differences in surface energy were observed between fractions, particularly in polar contributions (γ AB ), these did not correspond to meaningful differences in flow behavior. Coarser 6 mm particles exhibited poorer flow performance than 4 mm crumbles, likely due to broader particle size distributions and increased particle interlocking. Taken together, these results suggest that anatomical fractionation provides minimal benefit from a bulk handling perspective. Moisture content and particle size heterogeneity dominate handling behavior, reinforcing the utility of unfractionated corn stover in processing environments. These insights can inform the design of more efficient and reliable feedstock processing systems for agricultural biomass in integrated biorefineries.

09 BIOMASS FUELS↗
DOE OSTI2024

Startup Physics Testing of Advanced Reactors

This report documents the startup physics testing from initial fuel loading through ascension to full power for past advanced reactor startup physics testing programs. The review includes an assessment of what nuclear physics data was measured, why this data was measured, how was the measurement made, and the agreement with predictive reactor performance calculations of that time. The purpose of this review is to establish historical precedence for test inclusion for future advanced reactors planned for demonstration at the National Reactor Innovation Center (NRIC). The historical review includes reactor designs considered to be significantly different from current light-water reactor designs, or use simplified, inherent, passive, or other innovative means to accomplish their safety functions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Correlated Trajectory Uncertainty for Adaptive Sequential Decision Making

One of the great challenges with decision making tasks on real world systems is the fact that data is sparse and acquiring additional data is expensive. In these cases, it is often crucial to make a model of the environment to assist in making decisions. At the same time, limited data means that learned models are erroneous, making it just as important to equip the model with good predictive uncertainties. In the context of learning sequential decision making policies, these uncertainties can prove useful for informing which data to collect for the greatest improvement in policy performance \citep{mehta2021experimental, mehta2022exploration} or informing the policy about unsure regions of state and action space to avoid during test time \citep{yu2020mopo}. Additionally, assuming that realistic samples of the environment can be drawn, an adaptable policy can be trained that attempts to make optimal decisions for any given possible instance of the environment \citep{ghosh2022offline, chen2021offline}. In this work, we examine the so-called ``probabilistic neural network'' (PNN) model that is ubiquitous in model-based reinforcement learning (MBRL) works. We argue that while PNN models may have good marginal uncertainties, they form a distribution of non-smooth transition functions. Not only are these samples unrealistic and may hamper adaptability, but we also assert that this leads to poor uncertainty estimates when predicting multiple step trajectory estimates. To address this issue, we propose a simple sampling method that can be implemented on top of pre-existing models.We evaluate our sampling technique on a number of environments, including a realistic nuclear fusion task, and find that, not only do smooth transition function samples produce more calibrated uncertainties, but they also lead to better downstream performance for an adaptive policy.

Offline Reinforcement Learning↗
DOE OSTI2023

Impact of Pendent Ammonium Groups on Solubility and Cycling Charge Carrier Performance in Nonaqueous Redox Flow Batteries

The synthesis, characterization, electrochemical performance, and theoretical modeling of two base-metal charge carrier complexes incorporating a pendent quaternary ammonium group, [Ni(bppn-Me3)][BF4], 3′, and [Fe(PyTRENMe)][OTf]3, 4’, are described. Both complexes were produced in high yield and fully characterized using NMR, IR, and UV–vis spectroscopies as well as elemental analysis and single-crystal X-ray crystallography. The solubility of 3′ in acetonitrile showed a 283% improvement over its neutral precursor, whereas the solubility of complex 4’ was effectively unchanged. Cyclic voltammetry indicates an ∼0.1 V positive shift for all waves, with some changes in reversibility depending on the wave. Bulk electrochemical cycling demonstrates that both 3′ and 4’ can utilize the second more negative wave to a degree, whereas 4’ ceases to have a reversible positive wave. Flow cell testing of 3′ and 4’ with Fc as the posolyte reveals little improvement to the cycling performance of 3′ compared with its parent complex, whereas 4’ exhibits reductions in capacity decay when cycling either negative wave. Postcycling CVs indicate that crossover is the likely source of capacity loss in complexes 3, 3′, and 4’ because there is little change in the CV trace. Density functional theory calculations indicate that the ammonium group lowers the HOMO energy in 3′ and 4’, which may impart stability to cycling negative waves while making positive waves less accessible. The incorporation of a positively charged species can improve solubility, stored electron density, and capacity decay depending on the complex, features critical to high energy density redox flow battery performance.

25 ENERGY STORAGE↗
DOE OSTI2020

A critical examination of compound stability predictions from machine-learned formation energies

Machine learning has emerged as a novel tool for the efficient prediction of material properties, and claims have been made that machine-learned models for the formation energy of compounds can approach the accuracy of Density Functional Theory (DFT). The models tested in this work include five recently published compositional models, a baseline model using stoichiometry alone, and a structural model. By testing seven machine learning models for formation energy on stability predictions using the Materials Project database of DFT calculations for 85,014 unique chemical compositions, we show that while formation energies can indeed be predicted well, all compositional models perform poorly on predicting the stability of compounds, making them considerably less useful than DFT for the discovery and design of new solids. Most critically, in sparse chemical spaces where few stoichiometries have stable compounds, only the structural model is capable of efficiently detecting which materials are stable. The nonincremental improvement of structural models compared with compositional models is noteworthy and encourages the use of structural models for materials discovery, with the constraint that for any new composition, the ground-state structure is not known a priori. This work demonstrates that accurate predictions of formation energy do not imply accurate predictions of stability, emphasizing the importance of assessing model performance on stability predictions, for which we provide a set of publicly available tests.

36 MATERIALS SCIENCE↗
DOE OSTI2020

CONTROLLED END GAS AUTO IGNITION WITH EXHAUST GAS RECIRCULATION ON A STOICHIOMETRIC, SPARK IGNITED, NATURAL GAS ENGINE

The goal of this study is to address fundamental limitations to achieving diesel-like efficiencies in heavy duty on-highway natural gas (NG) engines. Engine knock and misfire are barriers to pathways leading to higher efficiency engines. This study explores enabling technologies for development of high efficiency stoichiometric, spark ignited, natural gas engines. These include design strategies for fast and stable combustion and higher dilution tolerance. Additionally, advanced control methodologies are implemented to maintain stable operation between knock and misfire limits. To implement controlled end- gas autoignition (C-EGAI) strategies a Combustion Intensity Metric (CIM) is used for ignition control with the use of a Woodward large engine control module (LECM). Tests were conducted using a single cylinder, variable compression ratio, cooperative fuel research (CFR) engine with baseline conditions of 900 RPM, engine load of 800 kPa indicated mean effective pressure (IMEP), and stoichiometric air/fuel ratio. Exhaust gas recirculation (EGR) tests were performed using a custom EGR system that simulates a high pressure EGR loop and can provide a range of EGR rates from 0 to 40%. The experimental measurements included the variance of EGR rate, compression ratio, engine speed, IMEP, and CIM. These five variables were optimized through a Modified Box- Benken design Surface Response Method (RSM), with brake efficiency as the merit function. A positive linear correlation between CIM and f-EGAI was identified. Consequently, CIM was used as the feedback control parameter for C-EGAI. As such, implementation of C-EGAI effectively allowed for the utilization of high EGR rates and CRs, controlling combustion between a narrower gap between knock and lean limits. The change from fixed to parametric ignition timing with CIM targeted select values of f-EGAI with an average coefficient of variance (COV) of peak pressure of 5.4. The RSM efficiency optimization concluded with operational conditions of 1080 RPM, 1150 kPa IMEP, 10.55:1 compression ratio, and 17.8% EGR rate with a brake efficiency of 21.3%. At this optimized point of peak performance, a f-EGAI for C-EGAI was observed at 34.1% heat release due to auto ignition, a knock onset crank angle value of 10.3° aTDC and ignition timing of - 24.7° aTDC. This work has demonstrated that combustion at a fixed f-EGAI can be maintained through advanced ignition control of CIM without experiencing heavy knocking events.

Cooperative Fuel Research Engine, Auto Ignition, E↗
DOE OSTI2023

Real Time and Forecasted DLR: Use Cases

This document contains two use cases for the utilization of dynamic line ratings in operational practices. These use cases were developed in support of the Transmission Optimization and Grid Enhancing Technology (TOGETS) task force aimed at facilitating the deployment of dynamic line rating and power flow technologies across the United States. The project included a demonstration of the technology on the Idaho National Laboratory system. The procurement documents, tests scripts, and field-validated results from multiple vendors will be published to improve industry’s familiarity with the products. Because of the urgency in performing this work and INL’s unique test setup, the Task Force identified a need for additional public information on the information exchanges required for operationalizing DLR (i.e. integrating DLR’s within actual system operations). As such, this use case document and an accompanying interoperability profile have been developed with input from the Task Force and various vendors whose systems would ultimately support the functionality described. The use case and interoperability profile support two distinct functionalities with different purposes.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

First evaluation of the tracking performance of the ARCADIA Fully Depleted MAPS with 120 GeV proton beam

This work presents test beam characterization of the ARCADIA Main Demonstrator 3, a 200 $μ$m thick Fully Depleted MAPS developed using a custom LFoundry 110 nm CIS process on a high-resistivity substrate. Measurements using a 120 GeV proton beam demonstrate a detection efficiency exceeding 99% and a spatial resolution down to 3.8 $μ$m. The study evaluates cluster size, spatial resolution, and efficiency as a function of the threshold, front-end currents, and backside bias voltage.

Rignanese, M. [Padua U.; INFN, Padua]↗
DOE OSTI2020

Analysis of Air-Purifying Respirator (APR) and Powered Air-Purifying Respirator (PAPR) Cartridge Performance Testing on Hanford Tanks BY-108 and BY-110 Volume 2: Raw Analytical Data

As the Tank Operations Contractor for U.S. Department of Energy operations at the Hanford site in Washington State, Washington River Protection Solutions (WRPS) is responsible for managing highly radioactive wastes stored in tanks at Hanford. WRPS tests air-purifying respirator (APR) and powered air-purifying respirator (PAPR) chemical cartridges commonly used by workers at Hanford Tank Farms to determine the period of time that the cartridges would provide adequate performance for APRs and PAPRs used to protect workers when exposed to a mixture of Chemicals of Potential Concern (COPC) from any vapors exiting headspaces in the storage tanks. The Occupational Safety and Health Administration (OSHA) Standard promulgated in Title 29 of the Code of the Federal Regulations (CFR) 1910.134(d)(3)(iii)(b)(2) specifies that for protection against gases and vapors, employers shall implement a schedule for cartridges to ensure that change-outs occur before the end of service life. The change schedule can be based on objective information or data that ensures cartridge change-outs occur before the end of their service life. The primary function of the WRPS Cartridge Test Program is to obtain objective data to determine service lives for the APR and PAPR cartridges used at Hanford Tank Farms. WRPS contracted with Pacific Northwest National Laboratory to analyze the test data and offer an independent analysis and any recommendations. This report summarizes data analysis of APR and PAPR cartridge testing on BY-110 and BY-108 headspace vapors, respectively. Two different APR cartridges from SCOTT Safety (Monroe, North Carolina) were assessed for the BY-110 headspace vapors, and two different PAPR cartridges—one from MSA Safety Inc. (Pittsburgh, Pennsylvania) and another from 3M (Maplewood, Minnesota)—were assessed for the BY-108 headspace vapors. Volume 1 of this report documents the testing, data analysis, results, conclusions, and recommendations resulting from the cartridge testing of vapors from the BY-110 and BY-108 headspaces. Volume 2 provides an introduction to the raw data, including analytical laboratory analysis results that supported the analysis and conclusions documented in Volume 1.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Nondestructive Evaluation (NDE) of Cable Anomalies using Frequency Domain Reflectometry (FDR) and Spread Spectrum Time Domain Reflectometry (SSTDR)

This report presents a comparative assessment of the performance of frequency domain reflectometry (FDR) and spread spectrum time domain reflectometry (SSTDR) in detecting a wide range of electrical cable anomalies. All tests and results reported herein were performed at the PNNL Accelerated and Real-Time Environmental Nodal Assessment (ARENA) cable and motor test bed. The primary objective of this work was to evaluate the effectiveness of SSTDR, a fledgling cable monitoring technique that shows promise for application in online monitoring of energized cable systems, against FDR, an offline technique widely employed in the nuclear power plant (NPP) industry. FDR tests are becoming more widely used in nuclear power plant cable aging management and test programs – particularly for low voltage cables. FDR capabilities for these kinds of tests have been reported by PNNL and others. The FDR test is performed on de-energized cables by connecting the FDR instrument to two of the cable conductors, or one conductor and the shield. A broad band low voltage (< 5 V) chirp is introduced in the cable, and any reflected response is captured in the frequency domain. The captured reflection is then processed by performing an inverse Fourier transform to a time domain response which can then be converted to a distance response based on the cable velocity of propagation (VoP). SSTDR measurements are functionally similar to FDR measurements in that a broad-band voltage signal composed of a square or sine wave modulated pseudo-random sequence of chips (< 5 volts), is injected onto one of the cable conductors. The injected signal will experience partial energy reflection and transmission at each impedance discontinuity along the transmission line. Any reflected response is detected by computing a cross-correlation between the reflected signals and a delayed copy of the incident SSTDR signal. the time delay for the reflected signal to experience the best matched correlation with the incident signal, indicates the travel time for the signal to reach a change in impedance. By knowing this time delay and velocity of propagation (VoP) of the signal, one can compute the physical distance. A big advantage that SSTDR measurements have over other methods is the ability to be connected to energized or live wires (currently up to 1kV) thereby enabling online monitoring of cables. SSTDR has been used successfully in several applications, e.g., aircraft, rail, and photovoltaic systems. In this work FDR and SSTDR cable assessment techniques were used to characterize a variety of cable anomalies and faults including: (1) Presence or absence of a motor; (2) Ground faults and short circuit faults; (3) Moist environments and water ingress faults; (4) Accelerated thermal aging. Both shielded and non-shielded cables were evaluated in this report. Offline measurements were made using FDR and online measurements were made by SSTDR for a range of test scenarios. Based on the results across all cable anomalies evaluated in this study, FDR displayed high sensitivity towards cable condition assessment, while SSTDR showed promise for future application in monitoring NPP cable systems. However, further developments are suggested to improve the resolution and sensitivity of SSTDR towards faults and anomalies in low voltage cables.rt presents a comparative

42 ENGINEERING↗
DOE OSTI2020

SympNets: Intrinsic structure-preserving symplectic networks for identifying Hamiltonian systems

Here, we propose new symplectic networks (SympNets) for identifying Hamiltonian systems from data based on a composition of linear, activation and gradient modules. In particular, we define two classes of SympNets: the LA-SympNets composed of linear and activation modules, and the G-SympNets composed of gradient modules. Correspondingly, we prove two new universal approximation theorems that demonstrate that SympNets can approximate arbitrary symplectic maps based on appropriate activation functions. We then perform several experiments including the pendulum, double pendulum and three-body problems to investigate the expressivity and the generalization ability of SympNets. The simulation results show that even very small size SympNets can generalize well, and are able to handle both separable and non-separable Hamiltonian systems with data points resulting from short or long time steps. In all the test cases, SympNets outperform the baseline models, and are much faster in training and prediction. We also develop an extended version of SympNets to learn the dynamics from irregularly sampled data. This extended version of SympNets can be thought of as a universal model representing the solution to an arbitrary Hamiltonian system.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Semi-transparent p-type barium copper sulfide as a back contact interface layer for cadmium telluride solar cells

Optically transparent p-type materials play a critical role in transparent electronics including photovoltaic (PV) devices. P-type sulfide materials offer an alternative to oxides for PV application due to improved hole transport properties. Here, we report the solution-based synthesis of earth-abundant p-type transparent conducting barium copper sulfide (α-BaCu 4 S 3 , BCS) thin films. These films were characterized using scanning electron microscopy, X-ray diffraction, UV–Vis–NIR spectrophotometry, Raman spectroscopy, and spectroscopic ellipsometry. BCS films of ~100 nm thickness transmit >70% of visible light. We report on tests of the hole transport properties of these BCS films for cadmium telluride (CdTe) photovoltaics, finding that the BCS deposition process forms a beneficial tellurium (Te) rich surface on CdTe by selectively removing Cd from the surface. Based on our study, the BCS interface layer plays dual functions for CdTe PV devices as a hole transport material and as an etchant, enhancing the resulting device performance. We observed a significant increase in open-circuit voltage of CdTe solar cells with the BCS buffer layer. Furthermore, we discuss semitransparent CdTe solar cells with BCS as a hole transport layer and indium tin oxide as a finishing electrode. Semitransparent CdTe solar cells shows 13.3% conversion efficiency for the front side illumination and 1.2% efficiency for back side illumination, indicating high recombination of charge carriers generated close to the rear CdTe/BCS/ITO contact.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Defining a Use Case for the ADMS Test Bed: Fault Location, Isolation, and Service Restoration with Distributed Energy Resources

Advanced distribution management systems (ADMS) integrate multiple enterprise-level functions into a single platform and offer advanced applications such as fault location, isolation, and service restoration (FLISR), to utilities to meet their operational needs for a modernized grid. These applications need to operate reliably even as distributed energy resource (DER) penetration increases on distribution systems. The ADMS test bed at the National Renewable Energy Laboratory offers utilities and vendors the opportunity to evaluate the performance of such advanced applications on distribution feeders of the future and to understand their potential benefits for a specific utility. This is done through defining use cases that address specific questions. This paper presents the definition of a use case on the performance of a commercially-available FLISR application on a feeder of an electric cooperative with DERs. After experiments are completed, results from this use case will be disseminated to the electric utility and research community to improve understanding of the challenges and benefits that DERs present to ADMS applications and the operation of a modernized grid.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

The Dark Energy Spectrographic Instrument (DESI) Guide-Focus Assembly

The specific research of the DESI project is to study in detail the expansion history of the Universe over the past 10 billion years. In order to do this, the project designed, fabricated, tested and commissioned the DESI instrument which has been deployed at the Mayall Telescope at the Kitt Peak National Observatory near Tucson, Arizona. The DESI project was conducted by approximately 30 US and foreign national laboratories. Our CRADA with the The Institut de Física d’Altes Energies (IFAE) in Barcelona (Spain) involved both research planning for eventual observing on the DESI telescope; and in providing hardware jointly designed by LBNL and IFAE; ten guide and focus sensor systems (GFAs) that either provide feedback to the Mayall telescope tracking system or provide focus position information to the DESI corrector hexapod. The key major goals of this CRADA were achieved.For survey planning, Drs. Fernandez, Fosalba, Garcia-Bellido, and Gaztañaga were all important contributors to the working groups to which they were assigned. Their application of redshift techniques, development of simulations to support target selection, exploration of the use of alternative observables to extract cosmological information like AP and void statistics, and the use of PAU data to assist in the optimization of targeting selections have been vital in the early planning for targets during commissioning. The major role in the project involved Drs. Castander, Miquel, Padilla, and Sànchez. They were all directly involved with the development of the Guide-Focus Assembly (GFA) hardware, software and filter validation. In order to accomplish the goals of the DESI Project, the Mayall telescope must track DESI targeted galaxies for up to 15 minutes and the DESI corrector must be repositioned on its hexapod system for different telescope orientations. The guide and focus assemblies (GFA) provide in this information. There are ten GFA modules on the focal plane, six providing tracking information and four providing focus information. A common GFA design supports both functions by a simple switching of its operating mode. IFAE designed, fabricated, tested and delivered twelve GFAs. Once received at LBNL, the GFAs were integrated with the focal plane. This was an iterative process as the GFA’s were delivered as they were made. Our working relationship with the IFAE scientists and engineers was remarkable given the distance and time zone issues. The GFAs have performed extremely well during the commissioning phase of the instrument.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Defining a Use Case for the ADMS Test Bed: Fault Location, Isolation, and Service Restoration with Distributed Energy Resources: Preprint

Advanced distribution management systems (ADMS) integrate multiple enterprise-level functions into a single platform and offer advanced applications such as fault location, isolation, and service restoration (FLISR), to utilities to meet their operational needs for a modernized grid. These applications need to operate reliably even as distributed energy resource (DER) penetration increases on distribution systems. The ADMS test bed at the National Renewable Energy Laboratory offers utilities and vendors the opportunity to evaluate the performance of such advanced applications on distribution feeders of the future and to understand their potential benefits for a specific utility. This is done through defining use cases that address specific questions. This paper presents the definition of a use case on the performance of a commercially-available FLISR application on a feeder of an electric cooperative with DERs. Results from this use case will be disseminated to the electric utility and research community to improve understanding of the challenges and benefits that DERs present to ADMS applications and the operation of a modernized grid.

61 RADIATION PROTECTION AND DOSIMETRY↗