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DOE OSTI2025

Classifying thermodynamic cloud phase using machine learning models

Vertically resolved thermodynamic cloud-phase classifications are essential for studies of atmospheric cloud and precipitation processes. The Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Thermodynamic Cloud Phase (THERMOCLDPHASE) value-added product (VAP) uses a multi-sensor approach to classify the thermodynamic cloud phase by combining lidar backscatter and depolarization, radar reflectivity, Doppler velocity, spectral width, microwave-radiometer-derived liquid water path, and radiosonde temperature measurements. The measured pixels are classified as ice, snow, mixed phase, liquid (cloud water), drizzle, rain, and liq_driz (liquid+drizzle). We use this product as the ground truth to train three machine learning (ML) models to predict the thermodynamic cloud phase from multi-sensor remote sensing measurements taken at the ARM North Slope of Alaska (NSA) observatory: a random forest (RF), a multi-layer perceptron (MLP), and a convolutional neural network (CNN) with a U-Net architecture. Evaluations against the outputs of the THERMOCLDPHASE VAP with 1 year of data show that the CNN outperforms the other two models, achieving the highest test accuracy, F1 score, and mean intersection over union (IOU). Analysis of ML confidence scores shows that ice, rain, and snow have higher confidence scores, followed by liquid, while mixed, drizzle, and liq_driz have lower scores. Feature importance analysis reveals that the mean Doppler velocity and vertically resolved temperature are the most influential data streams for ML thermodynamic cloud-phase predictions. Lidar measurements exhibit lower feature importance due to rapid signal attenuation caused by the frequent presence of persistent low-level clouds at the NSA site. The ML models' generalization capacity is further evaluated by applying them at another Arctic ARM site in Norway using data taken during the ARM Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) field campaign. The models demonstrated similar performance to that observed at the NSA site. Finally, we evaluate the ML models' response to simulated instrument outages and signal degradation and show that a CNN U-Net model trained with input channel dropouts performs better when input fields are missing.

ARM Aerial Facility↗

DOE OSTI2024

A parallel and performance portable implementation of a full-field crystal plasticity model

We have developed a parallel implementation of an Elasto-Viscoplastic Fast Fourier Transform-based (EVPFFT) micromechanical solver to enable computationally efficient crystal plasticity modeling for polycrystalline materials. Our primary focus lies in achieving performance portability, allowing a single EVPFFT implementation to run optimally on various homogeneous architectures, including multi-core Central Processing Units (CPUs), as well as on heterogeneous computer architectures comprising multi-core CPUs and Graphics Processing Units (GPUs) from different vendors. To accomplish this goal, we have leveraged MATAR, a C++ software library that simplifies the creation and utilization of multidimensional dense or sparse matrix and array data structures. These data structures are designed to be portable across diverse architectures through the use of Kokkos, a performance-portable library. Additionally, we have employed the Message Passing Interface (MPI) to efficiently distribute the computational workload among processors. The heFFTe (Highly Efficient FFT for Exascale) library is used to facilitate the performance portability of the fast Fourier transforms (FFTs) computation. The computational performance of EVPFFT is evaluated and presented in terms of parallel scalability and simulation runtime on different high-performance computing (HPC) architectures. As a result, the utility of the developed framework to efficiently simulate the micro-mechanical fields in polycrystalline microstructures in engineering applications is discussed.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Zero-Field NMR and Millitesla-SLIC Spectra for >200 Molecules from Density Functional Theory and Spin Dynamics

NMR is usually performed at magnetic fields of 1 T and above to obtain sufficient sensitivity and spectral dispersion to identify chemicals based on chemical shifts and J couplings. At lower fields, the advent of hyperpolarization technologies and sensitive detectors can address sensitivity concerns. However, it remains disputed whether spectral signatures at zero and ultra-low fields are sufficient for chemical identification. Here, we report an all–electron DFT-based batch calculation of J-coupling constants, which are used to generate J coupling NMR spectra at zero field and 6.5 mT for over 200 small molecules. In the developed computational tool chain, we first used the all-electron FHI-aims code to calculate the molecular J couplings and chemical shifts. We then fed the calculated NMR parameters into the NMR simulation package SPINACH to simulate both heteronuclear J coupling spectra at zero-field, and homonuclear J coupling spectra as spin-lock induced crossing (SLIC) spectra at ultra-low field (6.5 mT). The resulting spectra demonstrate that zero and ultra-low field NMR spectra can represent unique identifiers of chemical structure for small molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Can the United States Maintain Its Leadership in High-Performance Computing? - A report from the ASCAC Subcommittee on American Competitiveness and Innovation to the ASCR Office

The United States (U.S.) is no longer the unambiguous leader in the vitally important field of high performance computing (HPC). Japan, the European Union (EU), and China have fielded systems that are on par with our fastest supercomputers. The supply chain for everything from semiconductors to scientific software is globally distributed. Yet our economic future and security depend critically on our ability to innovate faster than our competitors, and the speed of innovation depends increasingly on large-scale computational science and engineering and thus HPC. How should the United States respond to this challenge? This report seeks to initiate a new and potentially transformative national discussion on this vital question. The Department of Energy’s (DOE) Advanced Scientific Computing Research (ASCR) program is well-positioned to make informed, targeted decisions about where the United States should cooperate and where it should compete in the global market for scientific exploration and discovery. By setting its sights on problems critical to our nation and the world, by establishing productive new collaborations, and by making strategic investments, ASCR can restore and maintain U.S. scientific leadership in the critical areas described in this report while strengthening our research infrastructure and training a large, diverse cohort of scientists. In doing so, ASCR and its scientists will pave the way for a secure and prosperous future for America. For more than 30 years, the ASCR program has provided the HPC and networking capabilities and expertise needed to support DOE’s mission to advance the national, economic, and energy security of the United States. The program now faces the challenge of developing and deploying the next generation of HPC systems and technologies, as well as supporting the application of HPC and artificial intelligence (AI) technologies to a wide range of scientific and engineering research problems. Through its research and development efforts, the ASCR program must also advance the state of the art in HPC and accelerate the pace of scientific discovery and technological innovation. Fulfilling this promise will require significantly increased investments, as well as innovative policies and programs. This subcommittee is aware that we are making recommendations and calls for action at a time when federal resources are limited. We understand that a wide range of competing priorities must be balanced by the nation’s leaders and that there is a need to leverage resources in new ways and seek efficiencies in facilities and operations. However, we must not let these realities limit our imagination or silence our advocacy. The ASCR program is a key part of the U.S. research infrastructure and an important component of economic growth and U.S. competitiveness. ASCR has a responsibility to pursue its mission, including advanced scientific computing, applications of AI technologies, and the required advanced research facilities, with determination and enthusiasm. To fulfill the scientific enterprise’s responsibility to the nation, the ASCR program must not only develop and publish a clear vision with an associated list of goals, priorities, and recommendations but also demonstrate scientific leadership by consistently securing long-term funding. This will allow the program to build on its achievements to date, to realize its ambitious vision, and to make lasting contributions to the field.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Modular Multi-family Construction: A Field Study of Energy Code Compliance and Performance through Offsite Prefabrication

Prefabrication in a controlled, factory setting may improve the energy code compliance and energy performance of modular buildings compared to traditional site-built buildings. To test this premise, the work detailed in this DOE-funded commercial field study (EE0009082) compares the energy code compliance of 25 modular and 30 site-built multifamily buildings under construction in Los Angeles, San Francisco, Philadelphia and Seattle representing climate zones 3B, 3C, 4A and 4C respectively. This dataset includes full data on 20 modular and site-built buildings and partial data on 35 modular and site-built buildings that had started prior to or were completed after the 18-month data collection period. This study also compares the post-occupancy energy performance or energy use intensity (EUI) of an additional 23 modular multifamily buildings and 128 site-built multifamily buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Hollow plasma structure during the breakdown phase of nanosecond pulsed pin–pin discharges generated with overvoltage

Atmospheric pressure nanosecond repetitive pulsed discharges are of interest for applications in combustion, material processing, plasma medicine and gas treatment. Here, the observation of a hollow structure at the ignition stage of such discharge in a pin–pin geometry is reported. Plasma images show that the phenomenon occurs in a variety of gases (helium, humid helium, argon and air) suggesting that it is in first approximation non-species specific. The phenomenon is investigated in detail in pure helium discharges for peak applied voltages between 3 and 6 kV and 200 ns voltage pulse duration by performing time-resolved optical emission spectroscopy measurements of electron density, gas temperature and electric field. All the measurements were performed at the mid-gap during the early stages of the discharge, near the breakdown. The transition from a homogeneous filament to a hollow structure occurs between 4 and 5 kV in helium. Electron density measurements by Stark broadening of the He I line at 492.2 nm show no significant difference in electron densities for the applied voltage between 3 and 6 kV. In all cases, a maximum electron density of about 3.5 × 10 21 m –3 was found. Electric field measurements performed by Stark polarization spectroscopy of the He I transition at 492.2 nm and of its forbidden counterpart show electric field strengths higher than the DC breakdown field of helium at atmospheric pressure consistent with the generation of the discharges with overvoltage. Moreover, a correlation between electric field values and the appearance of the hollow structure is observed and, remarkably, the phenomenon is not sensitive to the pre-ionization level (memory effect). Possible mechanisms for the phenomenon are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Reliability of tandem solar cells and modules: what's next?

Hybrid tandem photovoltaic (PV) technology development has gained momentum in the last few years. This has been motivated by a need to push module efficiencies beyond what is theoretically capable with single-junction technologies to further accelerate total global PV deployment. Significant advances have been made with multiple material systems achieving tandem efficiencies over 30% in the last decade. All of the highest record efficiencies have been from laboratory-scale devices, with areas of 1 cm2 or less. Interestingly, there are multiple material combinations and terminal configurations that have demonstrated promising results. Despite these high laboratory efficiencies, reasonable service lifetimes (a useful operating lifetime of at least 25 years) are needed for tandems to compete with the levelized cost of energy (LCOE) of traditional single junction PV technologies. Existing commercial Si PV products have demonstrated performance in the field with an average of less than 1% relative annual degradation in module and system performance, and many manufacturers now provide 30 year warranties on their products.

14 SOLAR ENERGY↗

DOE OSTI2021

Modeling and Measuring the Stress Distribution in Soft Magnetic Cores due to Epoxy Impregnation and Curing

Understanding the effects of viscoelastic relaxation of stresses is critical in electric motor and inductor applications, where the magnetic material is fully or partially comprised of an amorphous phase and impregnated in an epoxy. Magnetic Amorphous Nanocomposites (MANCs) are a class of recently developed high-frequency magnetic materials that exhibit low magnetic hysteresis, high saturation flux density and very low AC magnetic losses. MANCs are formed as long, thin ribbons, a shape factor that minimizes eddy current-induced self-heating. This feature, in addition to their 1 GPa strength, and makes them attractive candidates for high-speed, high-power density, electric motors. MANCs are used in the form of tape-wound cores (TWCs). During the manufacturing process, the cores are impregnated with liquid epoxy between each layer of ribbon. Validated knowledge of the stresses imposed by the manufacturing process and during operation is necessary to understand motor performance limitations with respect to strength. Magnetostriction, the strain imposed by reversal of the magnetic field, also affects performance. When the epoxy cures, it contracts volumetrically by 8%, imposing radial and circumferential stresses that vary along the radial direction. To date, these stresses have received little attention in the literature. Here, we model the stress distribution throughout a TWC due to epoxy curing. Strain gauge measurements reported here indicate substantially lower tangential strain than model values, which is beneficial and which we attribute to viscoelastic relaxation of the epoxy layers. We will incorporate a constitutive model of this viscoelastic relaxation, and conduct more detailed strain measurements to understand how this takes

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Energy performance evaluation of the ASHRAE Guideline 36 control and reinforcement learning–based control using field measurements

This study evaluates the energy performance of ASHRAE Guideline 36–compliant control (ASHRAE 36 control) and reinforcement learning (RL)–based control through experimental field tests and a simulation study. Three field tests were conducted at Oak Ridge National Laboratory’s commercial building test facility in Oak Ridge, Tennessee: a baseline with a baseline conventional control, a test with ASHRAE 36 control, and a test with RL-based control. The selected ASHRAE 36 controls were trim and respond control, as well as variable air volume (VAV) box control. We compared the measured supply air temperature of the rooftop unit, VAV box supply air temperature, and VAV box supply airflow rate across the three test cases. The field data indicated that ASHRAE 36 controls operated as specified by ASHRAE Guideline 36. Based on these data, ASHRAE 36 control achieved a 45 % reduction in hourly averaged HVAC energy consumption compared with the baseline, and RL-based control achieved a 66 % reduction. These potential annual energy savings were confirmed using a calibrated whole-building energy model. Compared with the baseline, ASHRAE 36 control reduced HVAC energy consumption by 42 %, and RL-based control achieved a 54 % reduction. Furthermore, RL-based control reduced total HVAC energy consumption by 21 % more than ASHRAE 36 control.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Toroidal magnetic field ripple in the presence of misaligned toroidal field coils on the COMPASS-U tokamak

Homogeneity of the toroidal magnetic field is a critical aspect of the tokamak fusion device. It is affected by the design of toroidal magnetic field coils and their manufacturing and assembly misalignments. The magnetic field of the COMPASS-U project is analysed using toroidal field ripple quantity. Here ANSYS modelling of bitter-plate-designed toroidal field coils is performed to prepare an accurate simplistic representation of the coils using a virtual current line. Toroidal field ripple is analysed using a Gaussian distribution of possible misalignments. The worst-case toroidal field ripple corresponding to the technical drawings only slightly exceeds the chosen limit of 0.5%.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Thermomechanical and sequential stress performance of photovoltaic backsheets

Photovoltaic backsheet technology is utilized to protect the interior components of solar modules from environmental stress as well as provide electrical insulation to the module. The growing demand for solar energy and longer module service life requirements have brought backsheet performance into focus. Despite being a protective packaging material, many backsheets have exhibited failure in the field, limiting the performance and service life of entire modules. Most backsheets consist of multiple polymeric layers laminated together using adhesives. A new backsheet, with a high performance polyamide structure, has been developed as the solution to module failure. Primarily, it contains a unique polyamide-ionomer alloy targeted at improved weather resistance. In this study, several photovoltaic industry standard backsheets, and the novel polyamide compositions of multilayered backsheets fabricated from the coextrusion process, were examined using thermomechanical analysis (TMA). The coefficient of thermal expansion (CTE) for entire backsheets and their constituent layers was used to model the thermomechanical behavior of various backsheet constructions. Subsequently, thermal cycling was performed in the TMA to examine the intrinsic thermal behavior of the backsheets. Thermal cycling in the TMA indicates the resilience and dimensional stability in the coextruded structures as opposed to the laminated structures. Lastly, results from a Module Accelerated Sequential Testing (MAST), are included to show the mechanical integrity of these backsheets after sequential exposure to stressors including damp heat, ultra-violet (UV) light radiation, and thermal cycling. The laminate backsheets deteriorated extensively after sequential exposure to these stressors, while the novel coextruded structures retained their physical properties.

14 SOLAR ENERGY↗

DOE OSTI2026

Topographic Characterization of Niobium Films on Copper for SRF Applications

Niobium films on copper substrates are being actively developed as a low-cost alternative to bulk niobium for superconducting radio-frequency (SRF) cavities, offering superior thermal conductivity, reduced material cost, and the potential for scalable cavity fabrication. The performance of such films can be limited by imperfect surfaces that reduce the peak achievable magnetic field. Nb films deposited under varied electron cyclotron resonance conditions were characterized via atomic force microscopy. The films exhibit a corrugated surface morphology which can be characterized by the depth of the corrugation, slope angle, and standard roughness parameters. The influence of this surface roughness on field limitations is examined within the framework of London theory. These measurements and models aid in understanding how ECR deposition conditions influence the nanometer-scale roughness of Nb films on Cu and its impact on high-field SRF cavity performance.

Redman, Brandi [Old Dominion Univ., Norfolk, VA (U↗

DOE OSTI2025

Spin State Modulation via Magnetic Fields in Fe Single Atom Catalysts for High-Performance Aqueous Zinc–Sulfur Batteries

Aqueous zinc–sulfur battery has garnered significant attention as a high-energy, low-cost, and safe energy storage system. However, the multielectron transfer kinetics of sulfur cathodes are relatively slow, presenting challenges such as limited sulfur utilization and lower discharge voltage, which significantly hinder their practical applications. Here, in this study, we explored a comprehensive design approach for high-performance, long-cycle aqueous zinc–sulfur batteries. The simultaneous introduction of ZnI 2 and Fe single atoms (Fe-SAs) as catalytically active agents decouples the redox reactions, effectively facilitating ZnS oxidation and S reduction separately. The application of an external magnetic field regulates the spin state of Fe-SAs, further enhancing their catalytic activity and electron transfer capability. Electrochemical tests demonstrate that the S@Fe-NC HS/ZnI 2 cathode assembled under a magnetic field exhibits excellent rate performance, achieving an impressive specific capacity of 1399 mAh g –1 at a high current density of 5 A g –1 and good cycling stability over 300 cycles, representing the highest reported high-current discharge capacity to date. This study provides a comprehensive design framework for optimizing zinc–sulfur (Zn–S) battery performance and elucidates the influence of magnetic field-induced spin state modulation on catalytic behavior.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Comprehensive assessment of metrology techniques for heliostat efficiency and performance evaluation

Concentrating solar power plants, specifically central receiver type systems and their heliostat field, are struggling with negative reputation in the USA, due to perceived underperformance and reliability issues. This is in part due to a lack of standards for performance assessment as well as overly simplified techno-economical models. A better understanding of influences and losses along the solar radiation path from the sun, across the solar collector to the receiver, increases the fidelity of heliostat efficiency assessment as well as solar field performance predictions. Such data are currently scarce and require a complete set of metrology capabilities to evaluate direct solar irradiance, sun shape, atmospheric attenuation, reflectance, collector shape, slope errors and total beam dispersion. In preparation for establishing a 3rd party metrology platform in collaboration with Sandia National Labs, NLR conducted a scoping study on available metrology. We present an extensive overview of techniques and commercial systems for each category. Our work includes an analysis to increase understanding of strengths and limitations of the many techniques used for surface shape and slope measurement. This applies to a controlled, indoor or outdoor laboratory environment assessing a single heliostat.

14 SOLAR ENERGY↗

DOE OSTI2021

Investigation of Scale-Dependent Groundwater/Surface-water Exchange in Rivers by Gradient Self-Potential Logging: Numerical Modeling and Field Experiments

Exchanges of groundwater and surface-water are fundamental to a wide range of water-supply and water-quality management issues but challenging to map beyond the reach scale. Waterborne gradient self-potential (SP) measurements are directly sensitive to water flow through riverbed sediments and can be used to infer exchange locations, direction (gain versus loss), scale, and relative changes, but to date applications to river corridor hydrology are limited. Numerical modeling and field experiments were therefore performed herein, each emphasizing waterborne gradient SP logging for identifying and locating focused vertical groundwater discharge (surface-water gain) and recharge (surface-water loss) in a river. Two and three-dimensional numerical models were constructed to simulate the polarities, appearances, and peak amplitudes of streaming-potential and electric-field anomalies on a riverbed and in the surface-water that were attributable to steady-state vertical fluxes of groundwater through high-permeability conduits in the riverbed. Effects of varied hydraulic length-scale of exchange and surface-water depth were tested through numerical modeling. Modeling results aided in data acquisition and interpretation for three repeated field experiments performed along a 1.5–2.0 km reach of the Quashnet River in Cape Cod, Massachusetts, where focused, meter-scale groundwater discharges occur at discrete locations within otherwise ubiquitous and more diffuse groundwater upwelling conditions. Strong gradient SP anomalies were repeatedly measured in the Quashnet River at previously confirmed locations of focused groundwater discharge, showing the efficacy of waterborne gradient SP logging in identifying and characterizing groundwater/surface water exchange dynamics at multiple river network scales.

Engineering↗

DOE OSTI2022

Energy Northwest - Horn Rapids Solar and Storage: An Assessment of Battery Technical Performance

Chartered in 1957 as a joint action agency of the state, Energy Northwest (ENW) is a consortium of 27 public utility districts and municipalities across Washington state. ENW takes advantage of economies of scale and shared services to help utilities run their operations more efficiently and at lower cost, to the benefit of more than 1.5 million customers. ENW develops, owns, and operates a diverse mix of electricity generating resources, including hydro, solar, and wind projects – and the Northwest’s only active nuclear energy facility. These projects provide enough reliable, affordable, and environmentally responsible energy to power more than a million homes each year, and that carbon-free electricity is provided at the cost of generation. The agency continually explores new generation projects to meet its members’ needs. In 2017, as part of the second round of funding from the Washington state Clean Energy Fund, the Washington State Department of Commerce granted up to $3 million in matching funds to develop an estimated $6.5 million project that deployed a 4-MW, 20-acre solar generating array of photovoltaic (PV) panels coupled with a 1 MW/5.5 MWh lithium-iron-phosphate battery energy storage system (BESS) in Richland, Washington. The combination of PV and BESS will provide a predictable, renewable generating source and will also serve as a training ground for solar and battery technicians throughout the nation. The City of Richland will purchase the power from the project and utilize the benefits of the energy storage. The project provides Washington state with its first opportunity to integrate a large-scale solar and storage facility into its clean mix of hydro, nuclear, and wind resources. This first-of-its-kind facility combines solar generation with battery storage and technician training. In 2019, Pacific Northwest National Laboratory (PNNL) worked with ENW to assess the integrated PV and BESS in representative use cases that could benefit the City of Richland. Between March and May 2022, extensive testing was conducted, and the results were used to assess the technical performance of the BESS subjected to actual field operations. Both reference performance and use case tests were performed: (A) Reference performance tests assess the general technical capabilities of the BESS, such as energy capacity, round-trip efficiency (RTE), ramp rate, and signal tracking capability. These are the first tests performed (baseline), and they are repeated after use case tests (post cycle). A standardized U.S. Department of Energy (DOE) energy storage performance protocol was used to characterize the BESS, including representative duty cycle profiles, test procedure guidance, and calculation guidance for determining key characteristics. (B) Use case tests examine the performance of the BESS for specific use cases using duty cycles developed by PNNL in collaboration with ENW. Five use cases were selected for testing: 1) demand charge reduction, 2) load shaping, 3) transmission charge reduction, 4) Volt-VAR service, and 5) outage mitigation. The use case duty cycles were developed based on utility and site-specific characteristics in addition to the technical characteristics and physical capabilities of the BESS. Use case tests were performed between the baseline and post cycle tests. This report describes the BESS and its components, presents testing and performance analysis results, and shares key insights and lessons learned from this project. Outcomes of the tests and analyses will help ENW understand the performance of the Horn Rapids BESS in its current state and design appropriate operational strategies for this and other BESSs over the long term.

14 SOLAR ENERGY↗

DOE OSTI2022

OPALCO - Decatur Island Solar and Energy Storage Project: An Assessment of Battery Technical Performance

Orcas Power & Light Cooperative (OPALCO) is a member-owned, nonprofit cooperative utility that provides energy services to approximately 11,200 customers across 20 islands in San Juan County, Washington. OPALCO’s mostly hydroelectric power is generated by Bonneville Power Administration and delivered to the islands by submarine cables. In 2016, as part of the second round of funding from the Washington state Clean Energy Fund, OPALCO received a $1 million matching grant to support a project that deployed a 504-kW LG community photovoltaic (PV) system in combination with a 1 MW/2 MWh lithium-iron-phosphate battery energy storage system (BESS) on Decatur Island, Washington. The Decatur Island Substation is essential to ensuring reliable energy for the residents of the San Juan Islands as it is the point of interconnection with the mainland transmission system. The BESS, in combination with the community solar array, will deliver an innovative method to both defer the costly upgrade of the transmission system and allow for other high-value applications intended to benefit the utility and its customers. In 2018, Pacific Northwest National Laboratory (PNNL) completed a preliminary economic assessment for several identified use cases in collaboration with OPALCO. Between August 2021 and May 2022, extensive testing was conducted, and the results were used to assess the technical performance of the BESS subjected to actual field operations. Both reference performance and use case tests were performed: (a) Reference performance tests assess the general technical capabilities of the BESS, such as energy capacity, round-trip efficiency (RTE), ramp rate, and signal tracking capability. These are the first tests performed (baseline) and are repeated after use case tests (post cycle). A standardized U.S. Department of Energy (DOE) energy storage performance protocol was used to characterize the BESS, including representative duty cycle profiles, test procedure guidance, and calculation guidance for determining key characteristics. (b) Use case tests examine the performance of the BESS for specific use cases using duty cycles developed by PNNL in collaboration with OPALCO. Four use cases were selected for testing: 1) demand charge reduction, 2) load shaping, 3) outage mitigation, and 4) transmission deferral. The use case duty cycles were developed based on utility and site-specific characteristics in addition to the technical characteristics and physical capabilities of the BESS. Use case tests were performed between the baseline and post cycle tests. This report describes the BESS and its components, presents testing and performance analysis results, and shares key insights and lessons learned from this project. Outcomes of the tests and analyses will help OPALCO understand the performance of the Decatur Island BESS in its current state and design appropriate operational strategies for this and other BESSs over the long term.

14 SOLAR ENERGY↗

DOE OSTI2022

The CMS Magnetic Field Measuring and Monitoring Systems

This review article describes the performance of the magnetic field measuring and monitoring systems for the Compact Muon Solenoid (CMS) detector. To cross-check the magnetic flux distribution obtained with the CMS magnet model, four systems for measuring the magnetic flux density in the detector volume were used. The magnetic induction inside the 6 m diameter superconducting solenoid was measured and is currently monitored by four nuclear magnetic resonance (NMR) probes installed using special tubes outside the barrel hadron calorimeter. Two more NRM probes were installed at the faces of the tracking system. The field inside the superconducting solenoid was precisely measured in 2006 in a cylindrical volume of 3.448 m in diameter and 7 m in length using 10 three-dimensional (3D) B-sensors based on the Hall effect. These B-sensors were installed on each of the two propeller arms of an automated field-mapping machine. In addition to these measurement systems, a system for monitoring the magnetic field during the CMS detector operation has been developed. Inside the solenoid in the horizontal plane, 4 3D B-sensors were installed at the faces of the tracking detector. Twelve 3D B-sensors were installed on the surfaces of the flux-return yoke nose disks. Seventy 3D B-sensors were installed in the air gaps of the CMS magnet yoke. A specially developed flux loop technique was used for the most complex measurements of the magnetic flux density inside the steel blocks of the CMS magnet yoke. The flux loops are installed in 22 sections of the flux-return yoke blocks. The areas enclosed by these coils varied from 0.3 to 1.59 m$^{2}$ in the blocks of the barrel wheels and from 0.5 to 1.12 m$^{2}$ in the blocks of the yoke endcap disks. The development of these systems and the results of the magnetic flux density measurements across the CMS magnet are presented and discussed in this review article.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗