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DOE OSTI2020

Probing and manipulating magnetic and 2D quantum materials using ultrafast laser and high harmonic sources

The ability to probe the full dynamic response of quantum materials on the length- and time-scales (Å to attoseconds on up) fundamental to charge, spin and phonon interactions is leading to a host of new discoveries. The coupled interactions between charges, spins, orbital and lattice degrees of freedom are key to determining the state of a material, whether metallic, insulating, superconducting or magnetic. Under thermal equilibrium conditions these states can be tuned by varying the temperature, pressure, chemical doping or dimensionality. However, their inherent complexity and rich phase landscape make them challenging to understand or manipulate deterministically. Fortunately, ultrafast light sources have undergone remarkable advances in recent years, achieving what was merely a dream three decades ago, i.e., full coherent control of light fields spanning the THz to the X-ray regions. Here, these new capabilities are providing powerful new tools for coherently manipulating and probing quantum materials using light. Recent advances in high harmonic generation (HHG) have provided new techniques for uncovering new phases and couplings in 2D and magnetic materials, using femtosecond lasers to coherently manipulate and tune the properties and interactions in the material, and HHG as a probe to map out these new phases and couplings. There are several beautiful recent observations of exciting new states in materials using light, but in some cases, the limited experimental data points made it challenging to validate an interpretation. The new ability of ultrafast HHG-based photoemission and magneto-optic spectroscopies to precisely probe multiple phases, electronic and magnetic order parameters, when combined with scanning the laser excitation fluence, is allowing us to map how material phases, magnetic states, and electron-phonon-spin couplings in these delicate materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Electronic spectroscopy and ionization potentials for YbOH and YbOCH 3

The polyatomic molecules YbOH and YbOCH 3 have been recognized as being of potential value for spectroscopic experiments that explore charge-parity and time reversal symmetry violation effects. These measurements require very high precision, which, in turn, will necessitate that the molecules be manipulated at ultra-cold temperatures. Both YbOH and YbOCH 3 have electronic transitions that appear suitable for laser cooling ($\tilde{A}$ 2 Π 1/2 -$\tilde{X}$ 2 Σ + and $\tilde{A}$2E 1/2 -$\tilde{X}$ 2 A 1 , respectively) but the currently available spectroscopic data is not sufficient to determine the extent to which population leaks may compromise the optical cooling processes. A further complication is that the quantum states of interest for these measurements will need to be selectively populated. The $\tilde{A}$-$\tilde{X}$ band systems of both YbOH and YbOCH 3 show evidence of vibronic perturbations, such that there are unassigned vibronic features at energies that are just above the origin bands. Here, in the present study we have recorded spectra for the $\tilde{A}$ 2 Π 1/2 -$\tilde{X}$ 2 Σ + transition of jet-cooled YbOD to facilitate the vibronic assignments. In addition, spectra for the $\tilde{B}$ 2 Σ + - $\tilde{X}$ 2 Σ + transition of YbOH were recorded, establishing the origin band at 20473.8 cm -1 . Previously, the reaction of Yb with CH 3 OH has been used to generate gas-phase YbOCH 3 . As this reaction also yields YbOH, there have been complications in spectroscopic studies of YbOCH 3 due to overlap of the $\tilde{A} -\tilde{X}$ band systems. To identify specific regions of overlap, resonantly enhanced two-photon ionization spectra were recorded using mass-resolved detection of the YbOH + and YbOCH 3 + ions. These data confirmed the overlap of vibronic bands near 17640 and 17680 cm -1 . Two-photon ionization spectroscopy also provided accurate ionization energies of IE(YbOH)=45788(10) and IE(YbOCH 3 )=45283(10) cm -1 . The IE for YbOH is relevant to problems encountered in previous attempts to determine the bond dissociation energy of YbOH + .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Watershed Workflow

Watershed Workflow aims to lower the bar on leveraging open data products in hyperresolution watershed hydrologic models. Integrated, distributed hydrologic models of watersheds require large amounts and complexity of data including meteorological forcing datasets; land cover datasets; watershed geometry, hydrogography, and elevation datasets; and subsurface soil and rock structural datasets. Increasingly open data products meeting this need are available through U.S. governmental and other agencies via APIs and other electronic means, but are not available in the same format, through the same API, or in the same coordinate system as one another, and present other challenges in manipulations across scales. This product automates the discovery, download, curation, and integration of these types of datasets into a common format for use with hydrologic models.

Coon, EthanT [Oak Ridge National Laboratory] (0000↗

DOE OSTI2026

WM26 Paper Multi-Robot Collaboration for Hazardous Environments

Hazardous nuclear and industrial facilities are rarely designed for robots. Work in these domains demand precise manipulation and robust mobility in cluttered, constrained spaces where off-the-shelf platforms struggle and “one-size-fits-all” machines become costly and complex. Idaho National Laboratory (INL) is developing an autonomous, multi-robot inspection system that coordinates task-specific platforms rather than relying on a single omni-tool robot. An electric truck serves as a power and compute hub for a custom manipulator co-developed with Florida International University (FIU), a commercial mini crawler, a pan–tilt–zoom camera, and a Nexxis Argus LiDAR mapping system. Working in concert, these robots generate spatial, radiation, and temperature maps of the pit environments at the Hanford Waste Tank Farms. These systems will capture visual records and environmental telemetry to allow for analysis post inspection. The system architecture uses Robot Operating System 2 (ROS 2) for publish/subscribe integration, NVIDIA Isaac Sim and Unity for simulation and visualization, and algorithms such as NVBlox to fuse data into unified 3D overlays. This robot-agnostic approach reduces operator burden by enabling autonomy across heterogeneous platforms and lets each robot be used where it is strongest. Having autonomous functions means operators don’t have to fully control multiple different components. The ease of use could allow for more widespread adoption of advanced robotics at waste management sites that see continued use. By coordinating simpler, purpose-built mechanisms, the approach lowers design and manufacturing complexity, reduces capital risk in contaminated settings, and improves controllability for complex inspection and manipulation tasks. We present the architecture, early results, and lessons learned from building and deploying this coordinated multi-robot system, with the goal of accelerating safe, cost-effective adoption of advanced robotics at waste-management sites.

42 - ENGINEERING↗

DOE OSTI2023

SPRUCE Climate Warming and Elevated CO2 Rapidly Alter Peatland Soil Carbon Sources and Stability: Supporting Data

This data set reports a suite of complementary biogeochemical analyses of peat samples from the SPRUCE (Spruce and Peatland Responses Under Changing Environments) experiment. Results were collected using quantitative molecular analysis of bulk soil carbon to assess the stability of soil organic carbon following whole-ecosystem warming and exposure to elevated carbon dioxide concentrations (eCO2). Targeted soil organic carbon components include solvent-extractable compounds (alkanoic acids, alkanols, alkanes, steroids, and terpenoids), ester-bound hydrolysable biopolymers (cutin and suberin markers), lignin phenols, and pyrogenic carbon. Bulk peat samples were analysed by Soxhlet extraction and solid phase separation for solvent-extractable compounds, alkaline hydrolysis to extract hydrolysable biopolymers, copper (II) oxide oxidation to extract lignin phenols and benzene polycarboxylic acids (BPCAs) as an approximation of pyrogenic carbon. Samples were analysed by gas chromatography (GC) equipped with a flame ionization detector (GC-FID) and compound identification was performed on GC coupled to mass selective detector (MS) for solvent-extractable compounds, ester-bound hydrolysable biopolymers and lignin phenols, and high-performance liquid chromatograph (HPLC) for pyrogenic carbon. Results are presented in Ofiti et al. (accepted). The experimental work was conducted on samples collected in August 2018 at the SPRUCE climate manipulation experiment in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF). Samples were collected and later analysed in a 10 cm increments over 0 to 50 cm depth and 25 cm intervals from 50 to 75 cm. Samples were analyzed for lignin phenols over 0 to 30 cm depth. This data set contains one file in comma separate (*.csv) format. This dataset contains data used to produce: Ofiti, N.O.E., Schmidt, M.W.I., Abiven, S., Hanson, P.J., Iversen, C.M., Wilson, R.M., Kostka, J.E., Wiesenberg, G.L.B., Malhotra, A. 2023. Climate warming and elevated CO2 rapidly alter peatland soil carbon sources and stability. Nat Commun 14, 7533. https://doi.org/10.1038/s41467-023-43410-z.

SPRUCE experiment, Marcell Experimental Forest, so↗

DOE OSTI2021

Effect of Image Classification Accuracy on Dasymetric Population Estimation

Dasymetric mapping involves the disaggregation of count data, usually relating to population/demographics, from census enumeration areas to smaller target zones with the aid of an ancillary layer related to population density. The ancillary layer is often a binary classification such as developed versus undeveloped, building versus non-building, and residential versus non-residential, in which one class is treated as populated and the other as unpopulated. While dasymetric mapping relies heavily on ancillary data, little research has been done to address the error in ancillary data and its effects on dasymetric mapping accuracy. This chapter reports our research effort to investigate the effect of image classification accuracy on dasymetric population estimates by developing a binomial classification of buildings from high-resolution remote sensor imagery. The classifier was systematically and iteratively manipulated to generate a series of outputs with variegated accuracy characteristics. Lastly, we generated a corresponding series of population estimates based on the mapped building area from each iteration to investigate the relationship between the accuracy of classification and population estimation.

McKee, Jacob↗

DOE OSTI2022

AbacusSummit Cleaned Halo Catalogs

This is a data release from the AbacusSummit suite of cosmological N-body simulations. It contains dark matter halo catalogs and particle samples from those halos. The halo catalogs have been augmented (cleaned) using halo merger tree information. Descriptions of AbacusSummit, the cleaned halo catalogs, and instructions for manipulating these catalogs can be found at the following URL: abacussummit.readthedocs.io/ The halo catalog cleaning is structured as a set of auxiliary files that are ingested by the reader code at runtime. But this release contains both the original catalogs and the auxiliary files, thus forming a self-contained dataset. The files in this release are aggregated by redshift. We define sets of simulations (like all c000 sims or all hugebase sims), and then store one redshift from all simulations per tarball. This is designed to support the use-case where a user wants to analyze multiple simulations at a certain redshift.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

An Accelerated Creep Testing (ACT) Program for Advanced Creep Resistant Alloys for High Temperature Fossil Energy (FE) Applications (Final Report)

The research objective of this study is to develop an accelerated creep testing (ACT) program for advanced creep resistant alloys for high temperature FE applications. This research produced a new ACT for metallic materials based on Time-Temperature-Stress Superposition (TTSSP). In TTSSP, there exists a fundamental relationship between creep resistance, time, temperature, and stress that can be manipulated to reduce test durations. In our study, the stepped isostress method was employed where step increases of load during creep testing accelerated the time-to-rupture. Well-posed constitutive models including sin-hyperbolic and Wilshire-Cano-Stewart where calibrated using the SSM data and employed to predict the conventional creep response of the material. In our best experiments, <100-hour tests on lnconel 718 at 750 deg C produced over a 64x acceleration of data when compared to conventional data from Japan's National Institute of Materials Science. The ACTs enable the rapid screening of candidate materials, where a small test matrix of short duration tests can be employed to determine the creep resistance (minimum-creep-strain-rate, stress-rupture, and creep deformation) of a material across decades.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2021

AutoCCS: automated collision cross-section calculation software for ion mobility spectrometry–mass spectrometry

Abstract Motivation Ion mobility spectrometry (IMS) separations are increasingly used in conjunction with mass spectrometry (MS) for separation and characterization of ionized molecular species. Information obtained from IMS measurements includes the ion’s collision cross section (CCS), which reflects its size and structure and constitutes a descriptor for distinguishing similar species in mixtures that cannot be separated using conventional approaches. Incorporating CCS into MS-based workflows can improve the specificity and confidence of molecular identification. At present, there is no automated, open-source pipeline for determining CCS of analyte ions in both targeted and untargeted fashion, and intensive user-assisted processing with vendor software and manual evaluation is often required. Results We present AutoCCS, an open-source software to rapidly determine CCS values from IMS-MS measurements. We conducted various IMS experiments in different formats to demonstrate the flexibility of AutoCCS for automated CCS calculation: (i) stepped-field methods for drift tube-based IMS (DTIMS), (ii) single-field methods for DTIMS (supporting two calibration methods: a standard and a new enhanced method) and (iii) linear calibration for Bruker timsTOF and non-linear calibration methods for traveling wave based-IMS in Waters Synapt and Structures for Lossless Ion Manipulations. We demonstrated that AutoCCS offers an accurate and reproducible determination of CCS for both standard and unknown analyte ions in various IMS-MS platforms, IMS-field methods, ionization modes and collision gases, without requiring manual processing. Availability and implementation https://github.com/PNNL-Comp-Mass-Spec/AutoCCS. Supplementary information Supplementary data are available at Bioinformatics online. Demo datasets are publicly available at MassIVE (Dataset ID: MSV000085979).

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Smart-DS: Synthetic Models for Advanced, Realistic Testing: Distribution Systems and Scenarios

The explosion of new ideas for distributed energy resources and advanced distribution grid algorithms faces a critical challenge: how can one effectively develop and evaluate these breakthrough technologies without an adequate set of power systems network, load, and resource data to test against? Today's open test systems, particularly for distribution systems, are tiny and incomplete; and though with enough effort, obtaining utility data under NDA can overcome scale challenges, the results can't be openly shared, preventing fair comparison. The Smart-DS project-led by NREL in partnership with MIT, Universidad Pontificia Comillas, CYME, and EDD-is working to overcome this gap by generating multiple large-scale, open, synthetic, distribution systems that are realistic but not real. These datasets go beyond a single medium voltage feeder (~1000 customers) to cover entire metropolitan areas and their surrounds with up to hundreds of feeders and millions of customers, complete with low voltage customer connections and high voltage sub-transmission. This scale allows adequate testing and analysis of not just local controls and advanced DERs, but also multiple substation interactions, optimized switching, full-scale distribution-OPF, and more. To accompany these datasets, the project is also building a rich set of scenario generation tools that can be used for distribution and transmission systems alike. This includes automated, spatially aware access to world-class, high-resolution solar, wind, and weather data: forward looking generation mixes: and highly configurable DER, load, climate, outage, control-scheme, and other scenarios. We will also highlight DiTTo, an exciting open-source, multi-way distribution dataset transformation tool for many-to-many format translation with scenario, merge/split, and many other manipulation capabilities.

DERs↗

DOE OSTI2025

Immersive Digital Twin Laboratory for Engineering Education (CRADA Final Report)

This project aimed to create an immersive digital twin laboratory that incorporates advanced tracking and visualization capabilities. In collaboration with Fort Lewis College, NREL designed a state-of-the-art physical visualization laboratory, developed a software platform to enable interaction with tracked physical objects in the laboratory, and provided proof-of-concept curricula that included manipulating these tracked objects. The project was initiated to address the growing need for innovative educational tools in engineering education. As renewable energy systems, particularly solar installations, become more complex, there is a pressing need to bridge the gap between theoretical knowledge and practical application. Traditional methods of teaching solar engineering concepts often fall short of providing students with a comprehensive, hands-on understanding. This immersive digital twin laboratory was conceived to fill that gap by creating a safe, non-energized setting where students can interact with augmented solar installation objects, gaining valuable insights into system performance, design, and maintenance. The project utilized extended reality (XR) technologies, including head-mounted displays (HMDs) and a whole-room optical motion tracking system, to connect physical objects with their digital twins in real time. The laboratory was equipped with MagicLeap 2 HMDs, supported by a Vicon Vero 2.2 Optical Tracking System, which provided precise 6-degrees-of-freedom (6-DOF) tracking. We developed a software platform to manage the interaction between the tracked physical objects and their virtual counterparts, enabling real-time data synchronization, object recognition, and virtual overlays. We designed the system to be flexible and extendable, allowing for future integration of additional objects and curriculum. This research advances the field of engineering education by demonstrating the potential of immersive digital twin environments. The laboratory provides a dynamic learning space where students can experiment, collaborate, and learn without the risks associated with live experimentation. The ability to simulate and manipulate solar installation objects under various conditions has broad implications for workforce development, particularly in renewable energy. The project also highlights the economic feasibility of using XR technologies in educational settings, offering a cost-effective solution for institutions looking to enhance their curriculum. By fostering a deeper understanding of solar energy systems, this work contributes to the broader goal of supporting the global energy transition and preparing the next generation of engineers and technicians.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Machine learning-based ethylene concentration estimation, real-time optimization and feedback control of an experimental electrochemical reactor

With the increase in electricity supply from clean energy sources, electrochemical reduction of carbon dioxide (CO 2 ) has received increasing attention as an alternative source of carbon-based fuels. As CO 2 reduction is becoming a stronger alternative for the clean production of chemicals, the need to model, optimize and control the electrochemical reduction of the CO 2 process becomes inevitable. However, on one hand, a first-principles model to represent the electrochemical CO 2 reduction has not been fully developed yet because of the complexity of its reaction mechanism, which makes it challenging to define a precise state-space model for the control system. On the other hand, the unavailability of efficient concentration measurement sensors continues to challenge our ability to develop feedback control systems. Gas chromatography (GC) is the most common equipment for monitoring the gas product composition, but it requires a period of time to analyze the sample, which means that GC can provide only delayed measurements during the operation. Moreover, the electrochemical CO 2 reduction process is catalyzed by a fast-deactivating copper catalyst and undergoes a selectivity shift from the product-of-interest at the later stages of experiments, which can pose a challenge for conventional control methods. To this end, machine learning (ML) techniques provide a potential approach to overcome those difficulties due to their demonstrated ability to capture the dynamic behavior of a chemical process from data. Motivated by the above considerations, we propose a machine learning-based modeling methodology that integrates support vector regression and first-principles modeling to capture the dynamic behavior of an experimental electrochemical reactor; this model, together with limited gas chromatography measurements, is employed to predict the evolution of gas-phase ethylene concentration. The model prediction is directly used in a proportional-integral (PI) controller that manipulates the applied potential to regulate the gas-phase ethylene concentration at energy-optimal set-point values computed by a real-time process optimizer (RTO). Specifically, the RTO calculates the operation set-point by solving an optimization problem to maximize the economic benefit of the reactor. Finally, suitable compensation methods are introduced to further account for the experimental uncertainties and handle catalyst deactivation. The proposed modeling, optimization, and control approaches are the first demonstration of active control for a CO 2 electrolyzer and contribute to the automation and scale-up efforts for electrified manufacturing of fuels and chemicals starting from CO 2 .

42 ENGINEERING↗

DOE OSTI2020

Profiles of upcoming HPC Applications and their Impact on Reservation Strategies

With the expected convergence between HPC, BigData and AI, new applications with different profiles are coming to HPC infrastructures. Here, we aim at better understanding the features and needs of these applications in order to be able to run them efficiently on HPC platforms. The approach followed is bottom-up: we study thoroughly an emerging application from the neuroscience community (SLANT) to understand its behavior. Based on these observations, we derive a generic, yet simple, application model (namely, a linear sequence of stochastic jobs). We expect this model to be representative for a large set of upcoming applications that require the computational power of HPC clusters without fitting the typical behavior of large-scale traditional applications. In a second step, we show how one can manipulate this generic model in a scheduling framework. Specifically we consider the problem of making reservations (both time and memory) for an execution on an HPC platform. We derive solutions using the model of the first step of this work. We experimentally show the robustness of the model, even with very few data or with another application, to generate the model, and provide performance gains with regards to standard and more recent approaches used in the neuroscience community.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Properties, Physiological Functions and Involvement of Basidiomycetous Alcohol Oxidase in Wood Degradation

Extensive research efforts have been devoted to describing yeast alcohol oxidase (AO) and its promoter region, which is vastly applied in studies of heterologous gene expression. However, little is known about basidiomycetous AO and its physiological role in wood degradation. This review describes several alcohol oxidases from both white and brown rot fungi, highlighting their physicochemical and kinetic properties. Moreover, the review presents a detailed analysis of available AO-encoding gene promoter regions in basidiomycetous fungi with a discussion of the manipulations of culture conditions in relation to the modification of alcohol oxidase gene expression and changes in enzyme production. The analysis of reactions catalyzed by lignin-modifying enzymes (LME) and certain lignin auxiliary enzymes (LDA) elucidated the possible involvement of alcohol oxidase in the degradation of derivatives of this polymer. Combined data on lignin degradation pathways suggest that basidiomycetous AO is important in secondary reactions during lignin decomposition by wood degrading fungi. With numerous alcoholic substrates, the enzyme is probably engaged in a variety of catalytic reactions leading to the detoxification of compounds produced in lignin degradation processes and their utilization as a carbon source by fungal mycelium.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Efficacy and Costs of Restoring Wetland Breeding Habitat for Imperiled Amphibians in the Southeastern U.S.

Herbaceous isolated wetlands in the North American Southeastern Coastal Plain are important breeding sites for many imperiled amphibians. However, most are degraded from alterations to historic fire disturbance and hydrologic regimes. Without fire, encroaching woody vegetation can transition wetlands to more terrestrial conditions and negatively impact amphibian breeding habitat, yet few studies have experimentally tested the efficacy, cost, or temporal requirement of current methods to restore herbaceous wetland vegetation. Here, we tested the interaction of manipulating wetland canopy and leaf litter/duff to promote herbaceous vegetation within one year (i.e., one breeding season) in degraded herbaceous wetlands in South Carolina. We assessed plant response via herbaceous cover, composition, and species similarity to the wetland seed bank and then related treatment performance to treatment cost. Removing trees combined with burning, disturbing, or removing duff significantly increased herbaceous cover and proportions of wetland plants and graminoids. Removing trees alone did not improve herbaceous cover compared to closed-canopy controls, and manipulating duff alone had limited positive effects on plant cover and composition. The most expensive yet effective treatment was Tree Removal-Duff Removal, while Tree Removal-Duff Disturbance was the most cost-effective. At a minimum, we recommend removing trees and burning to kickstart herbaceous recovery. Promisingly, comparisons of our data with previous seed bank studies from these same wetlands indicate there was limited seed bank attrition during 30 years of woody encroachment. Results from this study should aid practitioners in choosing wetland restoration techniques to better conserve at-risk species in the Southeastern Coastal Plain.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Heat Transfer Experiments of Ribbed, Serpentine Cooling Passages with Supercritical CO2

The results of heat transfer experiments with supercritical CO2 (sCO2) to capture the performance of ribbed, serpentine cooling passages for Reynolds numbers in the range of 100,000 - 400,000 are presented. The oxy-combustion turbine operating in an Allam-Fetvedt cycle has a turbine inlet temperature exceeding 1100°C, necessitating internally cooled turbine blades due to material creep strength limits. Reynolds numbers for sCO2, with its combination of high fluid density and low viscosity, can be up to an order of magnitude higher than comparable internal cooling conditions for an air-breathing engine where the majority of experimental data exists. To improve the prediction of cooling performance through turbulated passages, a test rig was designed and constructed with interchangeable insert capability for operation in sCO2 with heat transfer from a heater outlet flow stream to a lower temperature recuperator outlet flow stream. The inserts included serpentine passage geometry with five passes, one of the inserts including chevron ribs and the other a plain wall. The multi-pass serpentine geometry allowed for the evaluation of the effects 180 deg. tip turns have on the return passage flow characteristics, as they can depart significantly from fully-developed flow characteristics. The test procedure included the use of a modified Wilson plot method, with hot flow stream conditions kept effectively constant so that monitored changes in the overall thermal resistance could be attributed to manipulations in cooling flow stream conditions. Conditions during testing consisted of test section pressures of approximately 180 bar, cooling flow stream temperature of 175°C and hot flow stream temperature of 410°C. Test points at discrete cool flow Reynolds numbers up to 400,000 demonstrated an expected trend of decreased fluid thermal resistance with increasing Reynolds number, while at comparable Reynolds number there was an exhibited lower thermal resistance and higher passage pressure drop for the ribbed insert compared to the plain-walled insert. Processing of test data included establishment of Nusselt number enhancement ratios, so that for different internal cooling passage dimensions in the actual turbine blade at comparable Reynolds number the ratio could be applied to predict cooling performance.

Marshall, Michael↗

DOE OSTI2022

Enhanced convection for higher module and system efficiency (Final Technical Report)

The goal of this work is to develop new solar photovoltaic (PV) modules and solar system-scale designs that promote an increase of the convective heat transfer coefficient of at least 40%, reducing the operating temperature of the solar PV panels, and leading to a boost on the annual energy yield by at least 5%. By achieving this goal, we further foresee decreasing solar panel degradation by +0.3%/year, reducing the LCOE by 2.9-4.5¢/kWh. Currently, this question and/or approach is not considered though it is a relevant factor in performance/efficiency. The technology proposed will be at a mature stage by the end of the project and could be aligned to be proven on a full-field test. PV users, installers and manufacturers will be interested in the technology due to the aforementioned benefits. The work was conducted through a suite of wind tunnel experiments, numerical simulations and field experiments. These were then evaluated through a correlation encompassing the entire data set and implementing findings into NREL SAM. The work resulted in eight peer reviewed publications with three others in preparation. The key results of the project are 1.) Showing the capability of increasing the solar farm power production by increasing the heat transfer coefficient; 2.) Providing strategies for achieving this through large scale arrangement manipulation (heights, spacings, angles), flow deflectors and vortex generators; 3.) Demonstrating scalability of results by comparing numerical simulations, wind tunnel experiments and field experiments; 4.) Providing a correlation to be able to capture the various arrangements while exploiting the heat transfer coefficient; and 5.) Proving the feasibility of such strategies and their capacity through a comprehensive techno-economic analysis. For the heat transfer coefficients, gains of 40% were attained and increases in power in the excess of 5% were observed. For heat mitigation strategies, consideration at the PV array scale were inter-panel spacing, panel height and panel angles while at the module level, wind breaks such as solid walls and selected gaps were evaluated as well as vortex generators on the panel. All proposed strategies saw an increase in heat transfer coefficient. For scalability, results were compared against field experiments and a correlation for the heat transfer quantity was attained leading to a parametric understanding of the variations and impact in the heat transfer coefficient independent of tools implemented (wind tunnel/numerical simulations). The strategies were also further assessed by a technoeconomic analysis finding improvements based on LCOE with respect to location (several states with varies atmospheric conditions/geographic locations) yielded different results. Improvements on this end were also observed especially towards the colder climates and when considering bi-facial modules. The quantitative demonstrations of such conclusions are provided in the main portion of this document with complementary results and their narration. Milestones and go/no-go points were successfully met in the project.

14 SOLAR ENERGY↗

DOE OSTI2021

Measurement of L-shell emission from mid-Z targets under non-LTE conditions using Transmission Grating Spectrometer and DANTE power diagnostics

In this work, we present the measurement of L-band emission from buried Sc/V targets in experiments performed at the OMEGA laser facility. The goal of these experiments was to study non-local thermodynamic equilibrium plasmas and benchmark atomic physics codes. The L-band emission was measured simultaneously by the time resolved DANTE power diagnostic and the recently fielded time integrated Soreq-Transmission Grating Spectrometer (TGS) diagnostic. The TGS measurement was used to support the spectral reconstruction process needed for the unfolding of the DANTE data. The Soreq-TGS diagnostic allows for broadband spectral measurement in the 120 eV–2000 eV spectral band, covering L- and M-shell emission of mid- and high-Z elements, with spectral resolution λ/Δλ = 8–30 and accuracy better than 25%. The Soreq-TGS diagnostic is compatible with ten-inch-manipulator platforms and can be used for a wide variety of high energy density physics, laboratory astrophysics, and inertial confinement fusion experiments.

Fraenkel, M. (ORCID:0000000291939544)↗