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At least 1,747 records · Page 97
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Preliminary Introduction of a Free Vortex Wake Method Into OpenFAST

Increasing wind turbine size can have substantial economic benefits. However, increasing wind turbine turbine size requires the use of models that accurately capture the aerodynamic response to large deflections and nonstraight blade geometries. Additionally, the installation of offshore floating turbines requires turbine models that can handle large rotor motion. Free vortex wake (FVW) methods are capable of modeling this type of complex physics while remaining computationally tractable to perform the many simulations necessary for turbine design. In this work, a FVW model is added to the National Renewable Energy Laboratory engineering tool OpenFAST to allow for the aerodynamic modeling of highly flexible turbines along with the aero-hydro-servo-elastic response capabilities of OpenFAST. Code implementation is not complete and thus no results are presented. However, areas of potential modeling improvement are discussed, such as modifications to the circulation calculation and the need for different FVW input model specifications when high-thrust cases are being modeled.

17 WIND ENERGY↗
DOE OSTI2020

Enhancement of Unsteady and 3D Aerodynamics Models using Machine Learning

Unsteady aerodynamics will be an important part of the floating wind turbines of the future operating under high shear across the rotor disk coupled with platform motion and atmospheric turbulence. We develop an unsteady aerodynamics and dynamic stall model using a long short-term memory variant of recurrent neural networks. The neural network model is trained using the oscillating airfoil data set from Ohio State University. The predictions from our machine learning (ML)-based model show good agreement with the experimental data and other state-of-the-art dynamic stall models for a wide range of airfoils, Reynolds numbers and reduced frequencies. In some cases the predictions are better than the Beddoes-Leishman model implementation in OpenFAST, when using the default coefficients. The ML-based model is also able to capture the key physics associated with dynamic stall, such as the precedence of moment stall before lift stall and cycle-to-cycle variations in the aerodynamic response. The new unsteady aerodynamics model is expected to improve prediction of fatigue loads for yaw-based wake-steering control scenarios in actuator-line and actuator-disc simulations of wind farms. Our methodology for training the ML-model provides a pathway for improving design level tools using high-fidelity computational fluid dynamics (CFD) simulations in the future.

17 WIND ENERGY↗
DOE OSTI2020

Comparison of loads from HAWC2 and OpenFAST for the IEA Wind 15 MW Reference Wind Turbine

Reference wind turbines (RWTs) that reflect the state-of-the-art of current wind energy technology are necessary in order to properly evaluate innovative methods in wind turbine design and evaluation. The International Energy Agency (IEA) Wind Technology Collaboration Platform (TCP) Task 37 has recently developed a new RWT geared towards offshore floating-foundation applications: the IEA Wind 15 MW. The model has been implemented in two aeroelastic codes, OpenFAST and HAWC2, based on an underlying common ontology. However, these toolchains result in slightly different structural parameters, and the two codes utilise different structural models. Thus, to increase the utility of the model, it is necessary to compare the aeroelastic responses. This paper compares aeroelastic loads calculated using different fidelities of the blade model in OpenFAST (ElastoDyn and BeamDyn) and HAWC2 (prismatic Timoshenko without torsion and Timoshenko with fully populated stiffness matrix), where both codes use the DTU Basic controller and the same turbulence boxes to reduce discrepancies. The aeroelastic responses to steady wind, step wind and turbulent wind (per IEC 61400-1 wind class IB) are considered. The results indicate a generally good agreement between the loads dominated by aerodynamic thrust and force, especially for the no-torsion blade models. Discrepancies were observed in other load channels, partially due to differences in the asymmetric loading of the rotor and partially due to differing closed-loop dynamics, and they will be the subject of future investigations.

17 WIND ENERGY↗
DOE OSTI2024

Potential for large-scale deployment of offshore wind-to-hydrogen systems in the United States

This study explores the role of producing low-carbon hydrogen using water electrolysis powered by offshore wind in facilitating the United States’ transition to a net-zero emissions economy by 2050. This research introduces an open-source scenario analysis tool for offshore wind-to-hydrogen systems, aiming to assess the impact of technology, regional considerations, and policy incentives on the cost of producing low-carbon hydrogen through offshore wind. Conducting a regional techno-economic analysis at four U.S. coastal sites, the study evaluates two energy transmission configurations and examines associated costs for the years 2025, 2030, and 2035. The results highlight that locations using fixed-bottom technology may achieve cost-competitive water electrolysis hydrogen production by 2030 through leveraging geologic hydrogen storage and federal policy incentives. Furthermore, floating technology locations are expected to see an average 38% reduction in the levelized cost of hydrogen from 2025 to 2035.

17 WIND ENERGY↗
DOE OSTI2017

Stochastic optimization of GeantV code by use of genetic algorithms

GeantV is a complex system based on the interaction of different modules needed for detector simulation, which include transport of particles in fields, physics models simulating their interactions with matter and a geometrical modeler library for describing the detector and locating the particles and computing the path length to the current volume boundary. The GeantV project is recasting the classical simulation approach to get maximum benefit from SIMD/MIMD computational architectures and highly massive parallel systems. This involves finding the appropriate balance between several aspects influencing computational performance (floating-point performance, usage of off-chip memory bandwidth, specification of cache hierarchy, etc.) and handling a large number of program parameters that have to be optimized to achieve the best simulation throughput. This optimization task can be treated as a black-box optimization problem, which requires searching the optimum set of parameters using only point-wise function evaluations. Here, the goal of this study is to provide a mechanism for optimizing complex systems (high energy physics particle transport simulations) with the help of genetic algorithms and evolution strategies as tuning procedures for massive parallel simulations. One of the described approaches is based on introducing a specific multivariate analysis operator that could be used in case of resource expensive or time consuming evaluations of fitness functions, in order to speed-up the convergence of the black-box optimization problem.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Laboratory and testbeam results for thin and epitaxial planar sensors for HL-LHC

The High-Luminosity LHC (HL-LHC) upgrade of the CMS pixel detector will require the development of novel pixel sensors which can withstand the increase in instantaneous luminosity to L = 5 × 10 34 cm –2 s –1 and collect ~ 3000fb –1 of data. The innermost layer of the pixel detector will be exposed to doses of about 10 16 n eq / cm 2 . Hence, new pixel sensors with improved radiation hardness need to be investigated. A variety of silicon materials (Float-zone, Magnetic Czochralski and Epitaxially grown silicon), with thicknesses from 50 μm to 320 μm in p-type and n-type substrates have been fabricated using single-sided processing. The effect of reducing the sensor active thickness to improve radiation hardness by using various techniques (deep diffusion, wafer thinning, or growing epitaxial silicon on a handle wafer) has been studied. Furthermore, the results for electrical characterization, charge collection efficiency, and position resolution of various n-on-p pixel sensors with different substrates and different pixel geometries (different bias dot gaps and pixel implant sizes) will be presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Development of a tagged source of Pb-206 nuclei

There is a particular class of unavoidable backgrounds that plague low-background experiments and rare event searches, particularly those searching for nuclear recoil event signatures: decaying daughters of the 238 U nuclear decay chain, which result from radon plate-out on detector materials. One such daughter isotope, 210 Po, undergoes α-decay and produces a recoiling 103 keV 206 Pb nucleus. In this study, to characterize this important background in the context of noble element detectors, we have implemented a triggered source for these 206 Pb recoils in a dual-phase xenon time projection chamber (Xe TPC) within the Davis Xenon R&D testbed system (DAX). By adhering 210 Po to the surface of a PIN diode and electrically floating the diode on the cathode of the TPC, we tag the α signals produced in the PIN diode and trigger on the correlated nuclear recoils in the liquid xenon (LXe). Lastly, we discuss our methods for 210 Po deposition, electronic readout of the PIN diode signals at high voltage, and analysis methods for event selection.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Selection of the silicon sensor thickness for the Phase-2 upgrade of the CMS Outer Tracker

During the operation of the CMS experiment at the High-Luminosity LHC the silicon sensors of the Phase-2 Outer Tracker will be exposed to radiation levels that could potentially deteriorate their performance. Previous studies had determined that planar float zone silicon with n-doped strips on a p-doped substrate was preferred over p-doped strips on an n-doped substrate. The last step in evaluating the optimal design for the mass production of about 200 m$^{2}$ of silicon sensors was to compare sensors of baseline thickness (about 300 μm) to thinned sensors (about 240 μm), which promised several benefits at high radiation levels because of the higher electric fields at the same bias voltage. This study provides a direct comparison of these two thicknesses in terms of sensor characteristics as well as charge collection and hit efficiency for fluences up to 1.5 × 10$^{15}$ n$_{eq}$/cm$^{2}$. The measurement results demonstrate that sensors with about 300 μm thickness will ensure excellent tracking performance even at the highest considered fluence levels expected for the Phase-2 Outer Tracker.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Estimation of combinatoric background in seaquest using an event-mixing method

All experiments observing dilepton pairs (e.g. e + e -, μ + μ - ) must confront the existence of a combinatoricbackground caused by the combining of tracks not arising from the same physics vertex. Some method must be devised to calculate and remove this background. In this document we describe a particular event-mixing method relying on many of the unique aspects of the SeaQuest spectrometer and data. The method described here calculates the combinatoric background with correct normalization; i.e., there is no need to assign a floating normalization factor that is then determined in a subsequent fitting procedure. Numerous tests are applied to demonstrate the reliability of the method.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

A method to observe field-region oxide charge and inter-electrode isolation from CV-characteristics of n-on-p devices

Abstract N-on-psilicon sensors will be utilized in the Compact Muon Solenoid (CMS) detector's tracker and High Granularity Calorimeter (HGCAL) in the High Luminosity upgrade of the Large Hadron Collider (HL-LHC). Among their several advantages in terms of radiation hardness over the traditionalp-on-nsensors in the extreme radiation environment of the HL-LHC are electron collection instead of holes and overlapping maxima of weighting and electric fields at the charge-collecting electrodes. The disadvantage of the multi-channel SiO 2 -passivatedn-on-psensors is the generation of an inversion layer under the Si/SiO 2 -interface by a positive interface-oxide-charge (N ox ) that at high densities can compromise the position resolution by creating a conduction channel between the electrodes. This issue is typically addressed by including additional isolnts (p-stp,p-spray) between n + -electrodes. Focusing on the guard-ring regions ofn-on-psensors where no isolation implants are applied between the electrodes, a capacitance-voltage (CV) characterization study of both 6-inch wafer test diodes and 8-inch HGCAL prototype and pre-series sensors showed a distinct threshold voltage (V th,iso ) in theCV-characteristics of a biased n + -electrode when its enclosing guard-ring was left floating. When reproduced by simulations, the measuredV th,iso was found to contain information on the field-regionN ox and indicate the threshold where the two electrodes become electrically isolated by the influence of the reverse bias voltage. Together with previous studies on the inter-electrode isolation of irradiatedn-on-psensors, the results indicate that position sensitiven-on-psensors without isolation implants may be feasible in future HEP experiments.

Instruments & Instrumentation↗
DOE OSTI2025

A 28 nm multiply-accumulate ASIC architecture for on-chip data compression in MHz frame rate X-ray and electron pixel detectors

Modern X-ray detector systems urgently require compact, efficient, and fast data compression schemes to handle the transmission of big data from pixel arrays, enabling frame rates in the MHz regime. Here, in this work, a data compression ASIC that implements a streaming fixed-length lossy compression scheme is introduced and analyzed, proving the feasibility and benefits of on-chip compression. The compression scheme utilizes a vector matrix product logic, which performs a number of floating-point multiplications, additions, and accumulations. The logic is verified, synthesized, and shown to fit in the area resource available for the X-ray detector under study, which comprises 192 × 168 pixels each of 12-bit width, and having a total area of 20 mm× 20 mm, about 2 mm× 20 mm of which are available for the digital logic. Several system architectures, precisions, and compression ratios ranging from 100 to 250 were analyzed to pave the way for on-chip fixed-length compression (e.g., principal component analysis, singular value decomposition) and data reduction (e.g., azimuthal integration) for X-ray and electron detectors.

Data compression↗
DOE OSTI2020

Integrating environmental understanding into freshwater floatovoltaic deployment using an effects hierarchy and decision trees

Abstract In an era of looming land scarcity and environmental degradation, the development of low carbon energy systems without adverse impacts on land and land-based resources is a global challenge. ‘Floatovoltaic’ energy systems—comprising floating photovoltaic (PV) panels over water—are an appealing source of low carbon energy as they spare land for other uses and attain greater electricity outputs compared to land-based systems. However, to date little is understood of the impacts of floatovoltaics on the hosting water body. Anticipating changes to water body processes, properties and services owing to floatovoltaic deployment represents a critical knowledge gap that may result in poor societal choices and water body governance. Here, we developed a theoretically-derived hierarchical effects framework for the assessment of floatovoltaic impacts on freshwater water bodies, emphasising ecological interactions. We describe how the presence of floatovoltaic systems may dramatically alter the air-water interface, with subsequent implications for surface meteorology, air-water fluxes and physical, chemical and biological properties of the recipient water body. We apply knowledge from this framework to delineate three response typologies—‘ magnitude’ , those for which the direction and magnitude of effect can be predicted; ‘ direction’ , those for which only the direction of effect can be predicted; and ‘ uncertain’ , those for which the response cannot be predicted—characterised by the relative importance of levels in the effects hierarchy. Illustrative decision trees are developed for an example water body response within each typology, specifically, evaporative water loss, cyanobacterial biomass, and phosphorus release from bed sediments, and implications for ecosystem services, including climate regulation, are discussed. Finally, the potential to use the new understanding of likely ecosystem perturbations to direct floatovoltaic design innovations and identify future research priorities is outlined, showcasing how inter-sectoral collaboration and environmental science can inform and optimise this low carbon, land-sparing renewable energy for ecosystem gains.

Environmental Sciences & Ecology↗
DOE OSTI2017

Modifications to JLab 12 GeV Refrigerator and Wide Range Mix Mode Performance Testing Results

Analysis of data obtained during the spring 2013 commissioning of the new 4.5-K refrigeration system at Jefferson Lab (JLab) for the 12 GeV upgrade indicated a wide capacity range with good efficiency and minimal operator interaction. Testing also showed that the refrigerator required a higher liquid nitrogen (LN) consumption for its pre-cooler than anticipated by the design. This does not affect the capacity of the refrigerator, but it does result in an increased LN utility cost. During the summer of 2015 the modifications were implemented by the cold box manufacturer, according to a design similar to the JLab 12 GeV cold box specification. Subsequently, JLab recommissioned the cold box and performed extensive performance testing, ranging from 20% to 100% of the maximum capacity, and in various modes of operation, ranging from pure refrigeration, pure liquefaction, half-and-half mix mode and at selected design modes. This testing demonstrated the modifications resulted in a LN consumption significantly lower than the expected design for the nominal and maximum capacity modes and equal to the expected design for the pure refrigeration mode (which is the most demanding). The testing also demonstrated that the refrigerator system has a good and fairly constant performance over this wide capacity range and different modes of operation. Also, a pulsed-load test, similar to what is expected for cryogenic systems supporting fusion experiments, was conducted to observe the response using the Floating Pressure ? Ganni Cycle, which was stable and robust. This paper will discuss the results and analysis of this testing pertaining to the LN consumption, the system efficiency over a wide range of capacity and different modes and the behavior of the system to a pulsed load.

Knudsen, P.↗
DOE OSTI2015

HIDING IN PLAIN SIGHT: RECORD-BREAKING COMPACT STELLAR SYSTEMS IN THE SLOAN DIGITAL SKY SURVEY

Motivated by the recent, serendipitous discovery of the densest known galaxy, M60-UCD1, we present two initial findings from a follow-up search, using the Sloan Digital Sky Survey, Subaru/Suprime-Cam, and Hubble Space Telescope imaging, and SOuthern Astrophysical Research (SOAR)/Goodman spectroscopy. The first object discovered, M59-UCD3, has a similar size to M60-UCD1 (half-light radius of r{sub h} ∼ 20 pc) but is 40% more luminous (M{sub V} ∼ −14.6), making it the new densest-known galaxy. The second, M85-HCC1, has a size like a typical globular cluster (GC; r{sub h} ∼ 1.8 pc) but is much more luminous (M{sub V} ∼ −12.5). This hypercompact cluster is by far the densest confirmed free-floating stellar system, and is equivalent to the densest known nuclear star clusters. From spectroscopy, we find that both objects are relatively young (∼9 and ∼3 Gyr, respectively), with metal-abundances that resemble those of galaxy centers. Their host galaxies show clear signs of large-scale disturbances, and we conclude that these dense objects are the remnant nuclei of recently accreted galaxies. M59-UCD3 is an ideal target for follow-up with high-resolution imaging and spectroscopy to search for an overweight central supermassive black hole as was discovered in M60-UCD1. These findings also emphasize the potential value of ultra-compact dwarfs and massive GCs as tracers of the assembly histories of galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Electron spin coherence on a solid neon surface

We report a single electron floating on the surface of a condensed noble-gas liquid or solid can act as a spin qubit with ultralong coherence time, thanks to the extraordinary purity of such systems. Previous studies suggest that the electron spin coherence time on a superfluid helium (He) surface can exceed 100 s. In this paper, we present theoretical studies of the electron spin coherence on a solid neon (Ne) surface, motivated by our recent experimental realization of single-electron charge qubit on solid Ne. The major spin decoherence mechanisms investigated include the fluctuating Ne diamagnetic susceptibility due to thermal phonons, the fluctuating thermal current in normal metal electrodes, and the quasi-statically fluctuating nuclear spins of the 21 Ne ensemble. We find that at a typical experimental temperature about 10 mK in a fully superconducting device, the electron spin decoherence is dominated by the third mechanism via electron–nuclear spin–spin interaction. For natural Ne with 2700 ppm abundance of 21 Ne, the estimated inhomogeneous dephasing time ${T}_{2}^{*}$ is around 0.16 ms, already better than most semiconductor quantum-dot spin qubits. For commercially available, isotopically purified Ne with 1 ppm of 21 Ne, ${T}_{2}^{*}$ can be 0.43 s. Under the application of Hahn echoes, the coherence time T 2 can be improved to 30 ms for natural Ne and 81 s for purified Ne. Therefore, the single-electron spin qubits on solid Ne can serve as promising new spin qubits.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Offshore lightning more active and intense in U.S. East Coast wind areas than in North Sea

Fast winds over open areas off the U.S. East Coast resulted in many offshore areas being opened for wind power deployment. Yet lightning is active in this same general area. Lightning damage has been noted as the leading cause of unplanned downtime of wind farms. Here we use lightning observations from 2020–2022 to quantify lightning activity—U.S. East Coast Wind Lease and Wind Planning areas received about 14-times the lightning strokes and about 18-times the energy transfer compared to the operational wind farms in the North Sea. A strong north-south U.S. gradient of lightning exists : low off the coast of Maine, growing higher off Chesapeake Bay, and high south of Virginia. Very high lightning activity also occurs about 250 km from the U.S. coastline, which is 50–100 km outside currently designated Wind Areas but likely relevant to planning floating wind farms further from shore. International lightning protection standards, such as IEC 614200-24, use lightning stroke density and turbine top-height to estimate damage to wind turbines, but it remains unclear if such standards could protect U.S. offshore wind turbines in active lightning areas where the turbine top-height can be 100 m taller than the next tallest object for tens to hundreds of kilometers. This analysis suggests U.S. East Coast offshore wind farms will be subjected to much higher lightning stroke and lightning energy densities than the North Sea counterparts. Preparing the turbine designs in anticipation of these more active U.S. lightning risks will help foster wind’s growing contribution to a reliable and resilient low-carbon energy future.

lightning↗
DOE OSTI2020

Compressing deep neural networks on FPGAs to binary and ternary precision with hls4ml

We present the implementation of binary and ternary neural networks in the hls4ml library, designed to automatically convert deep neural network models to digital circuits with FPGA firmware. Starting from benchmark models trained with floating point precision, we investigate different strategies to reduce the network's resource consumption by reducing the numerical precision of the network parameters to binary or ternary. We discuss the trade-off between model accuracy and resource consumption. In addition, we show how to balance between latency and accuracy by retaining full precision on a selected subset of network components. As an example, we consider two multiclass classification tasks: handwritten digit recognition with the MNIST data set and jet identification with simulated proton-proton collisions at the CERN Large Hadron Collider. The binary and ternary implementation has similar performance to the higher precision implementation while using drastically fewer FPGA resources.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Lightweight jet reconstruction and identification as an object detection task

We apply object detection techniques based on deep convolutional blocks to end-to-end jet identification and reconstruction tasks encountered at the CERN large hadron collider (LHC). Collision events produced at the LHC and represented as an image composed of calorimeter and tracker cells are given as an input to a Single Shot Detection network. The algorithm, named PFJet-SSD performs simultaneous localization, classification and regression tasks to cluster jets and reconstruct their features. This all-in-one single feed-forward pass gives advantages in terms of execution time and an improved accuracy w.r.t. traditional rule-based methods. A further gain is obtained from network slimming, homogeneous quantization, and optimized runtime for meeting memory and latency constraints of a typical real-time processing environment. We experiment with 8-bit and ternary quantization, benchmarking their accuracy and inference latency against a single-precision floating-point. We show that the ternary network closely matches the performance of its full-precision equivalent and outperforms the state-of-the-art rule-based algorithm. Finally, we report the inference latency on different hardware platforms and discuss future applications.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗