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

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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Comparison of steady-state analytical wake models implemented in wind farm analysis software

A common set of mathematical wind turbine wake models are implemented in a few, well-adopted computational tools for wind farm wake modelling. Although the referenced mathematical formulations are common, implementation details may lead to differences in results. This study presents a systematic comparison of the implementation of mathematical wake models in open source, Python-based wind turbine wake modelling software, and a set of the models are directly compared. Despite aligning only the mathematical model parameters and retaining the default computational model parameters, good agreement is found across most of the model implementations, and additional agreement is expected upon further parameters alignment.

17 WIND ENERGY↗
DOE OSTI2021

Differentiable programming for online training of a neural artificial viscosity function within a staggered grid Lagrangian hydrodynamics scheme

Lagrangian methods to solve the inviscid Euler equations produce numerical oscillations near shock waves. A common approach to reducing these oscillations is to add artificial viscosity (AV) to the discrete equations. The AV term acts as a dissipative mechanism that attenuates oscillations by smearing the shock across a finite number of computational cells. However, AV introduces several control parameters that are not determined by the underlying physical model, and hence, in practice are tuned to the characteristics of a given problem. We seek to improve the standard quadratic-linear AV form by replacing it with a learned neural function that reduces oscillations relative to exact solutions of the Euler equations, resulting in a hybrid numerical-neural hydrodynamic solver. Because AV is an artificial construct that exists solely to improve the numerical properties of a hydrodynamic code, there is no offline ‘viscosity data’ against which a neural network can be trained before inserting into a numerical simulation, thus requiring online training. We achieve this via differentiable programming, i.e. end-to-end backpropagation or adjoint solution through both the neural and differential equation code, using automatic differentiation of the hybrid code in the Julia programming language to calculate the necessary loss function gradients. A novel offline pre-training step accelerates training by initializing the neural network to the default numerical AV scheme, which can be learned rapidly by space-filling sampling over the AV input space. We find that online training over early time steps of simulation is sufficient to learn a neural AV function that reduces numerical oscillations in long-term hydrodynamic shock simulations. These results offer an early proof-of-principle that online differentiable training of hybrid numerical schemes with novel neural network components can improve certain performance aspects existing in purely numerical schemes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

RhizoVision Explorer: open-source software for root image analysis and measurement standardization

Abstract Roots are central to the function of natural and agricultural ecosystems by driving plant acquisition of soil resources and influencing the carbon cycle. Root characteristics like length, diameter and volume are critical to measure to understand plant and soil functions. RhizoVision Explorer is an open-source software designed to enable researchers interested in roots by providing an easy-to-use interface, fast image processing and reliable measurements. The default broken roots mode is intended for roots sampled from pots and soil cores, washed and typically scanned on a flatbed scanner, and provides measurements like length, diameter and volume. The optional whole root mode for complete root systems or root crowns provides additional measurements such as angles, root depth and convex hull. Both modes support providing measurements grouped by defined diameter ranges, the inclusion of multiple regions of interest and batch analysis. RhizoVision Explorer was successfully validated against ground truth data using a new copper wire image set. In comparison, the current reference software, the commercial WinRhizo™, drastically underestimated volume when wires of different diameters were in the same image. Additionally, measurements were compared with WinRhizo™ and IJ_Rhizo using a simulated root image set, showing general agreement in software measurements, except for root volume. Finally, scanned root image sets acquired in different labs for the crop, herbaceous and tree species were used to compare results from RhizoVision Explorer with WinRhizo™. The two software showed general agreement, except that WinRhizo™ substantially underestimated root volume relative to RhizoVision Explorer. In the current context of rapidly growing interest in root science, RhizoVision Explorer intends to become a reference software, improve the overall accuracy and replicability of root trait measurements and provide a foundation for collaborative improvement and reliable access to all.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Standardizing experimental approaches to investigate interactions between bacteria and ectomycorrhizal fungi

Bacteria and ectomycorrhizal fungi (EcMF) represent two of the most dominant plant root-associated microbial groups on Earth, and their interactions continue to gain recognition as significant factors that shape forest health and resilience. Yet, we currently lack a focused review that explains the state of bacteria-EcMF interaction research in the context of experimental approaches and technological advancements. To these ends, we illustrate the utility of studying bacteria-EcMF interactions, detail outstanding questions, outline research priorities in the field, and provide a suite of approaches that can be used to promote experimental reproducibility, field advancement, and collaboration. Though this review centers on the ecology of bacteria, EcMF, and trees, it by default offers experimental and conceptual insights that can be adapted to various subfields of microbiology and microbial ecology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

SPiRaL: a multiresolution global tomography model of seismic wave speeds and radial anisotropy variations in the crust and mantle

SUMMARY SPiRaL is a joint global-scale model of wave speeds (P and S) and anisotropy (vertical transverse isotropy, VTI) variations in the crust and mantle. The model is comprised of >2.1 million nodes with five parameters at each node that capture velocity variations for P- and S-waves travelling at arbitrary directions in transversely isotropic media with a vertical symmetry axis (VTI). The crust (including ice, water, sediments and crystalline layers) is directly incorporated into the model. The default node spacing is approximately 2° in the lower mantle and 1° in the crust and upper mantle. The grid is refined with ∼0.25° minimum node spacing in highly sampled regions of the crust and upper mantle throughout North America and Eurasia. The data considered in the construction of SPiRaL includes millions of body wave traveltimes (crustal, regional and teleseismic phases with multiples) and surface wave (Rayleigh and Love) dispersion. A multiresolution inversion approach is employed to capture long-wavelength heterogeneities commonly depicted in global-scale tomography images as well as more localized details that are typically resolved in more focused regional-scale studies. Our previous work has demonstrated that such global-scale models with regional-scale detail can accurately predict both teleseismic and regional body wave traveltimes, which is necessary for more accurate location of small seismic events that may have limited signal at teleseismic distances. SPiRaL was constructed to predict traveltimes for event location and long-period waveform dispersion for seismic source inversion applications in regions without sufficiently tuned models. SPiRaL may also serve as a starting model for full-waveform inversion (FWI) with the goal of fitting waves with periods 10–50 s over multiple broad regions (thousands of kilometres) and potentially the globe. To gain insight to this possibility, we simulated waveforms for a small set of events using SPiRaL and independent waveform-based models for comparison. For the events tested, the performance of the traveltime-based SPiRaL model is shown to be generally on par with regional 3-D waveform-based models in three regions (western United States, Middle East, Korean Peninsula) suggesting SPiRaL may serve as a starting model for FWI over broad regions.

58 GEOSCIENCES↗
DOE OSTI2020

Testing dark matter halo properties using self-similarity

ABSTRACT We use self-similarity in N-body simulations of scale-free models to test for resolution dependence in the mass function and two-point correlation functions of dark matter haloes. We use 10243 particle simulations performed with abacus , and compare results obtained with two halo finders: friends-of-friends (fof ), and rockstar . The fof mass functions show a systematic deviation from self-similarity which is explained by resolution dependence of the fof mass assignment previously reported in the literature. Weak evidence for convergence is observed only starting from haloes of several thousand particles, and mass functions are overestimated by at least as much as $20-25{{\ \rm per\ cent}}$ for haloes of 50 particles. The mass function of the default rockstar halo catalogue (with bound virial spherical overdensity mass), on the other hand, shows good convergence of the order of 50 to 100 particles per halo, with no detectable evidence at the few percent level of any systematic dependence for larger particle number. Tests show that the mass unbinding procedure in rockstar is the key factor in obtaining this much improved resolution. Applying the same analysis to the halo–halo two point correlation function, we find again strong evidence for convergence only for rockstar haloes, at separations sufficiently large so that haloes do not overlap. At these separations, we can exclude dependence on resolution at the $5-10{{\ \rm per\ cent}}$ level once haloes have of the order of 50 to 100 particles. At smaller separations results are not converged even at significantly larger particle number, and bigger simulations would be required to establish the resolution required for convergence.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Convolutional neural network identification of galaxy post-mergers in UNIONS using IllustrisTNG

ABSTRACT The Canada–France Imaging Survey (CFIS) will consist of deep, high-resolution r-band imaging over ∼5000 deg2 of the sky, representing a first-rate opportunity to identify recently merged galaxies. Because of the large number of galaxies in CFIS, we investigate the use of a convolutional neural network (CNN) for automated merger classification. Training samples of post-merger and isolated galaxy images are generated from the IllustrisTNG simulation processed with the observational realism code RealSim. The CNN’s overall classification accuracy is 88 per cent, remaining stable over a wide range of intrinsic and environmental parameters. We generate a mock galaxy survey from IllustrisTNG in order to explore the expected purity of post-merger samples identified by the CNN. Despite the CNN’s good performance in training, the intrinsic rarity of post-mergers leads to a sample that is only ∼6 per cent pure when the default decision threshold is used. We investigate trade-offs in purity and completeness with a variable decision threshold and find that we recover the statistical distribution of merger-induced star formation rate enhancements. Finally, the performance of the CNN is compared with both traditional automated methods and human classifiers. The CNN is shown to outperform Gini–M20 and asymmetry methods by an order of magnitude in post-merger sample purity on the mock survey data. Although the CNN outperforms the human classifiers on sample completeness, the purity of the post-merger sample identified by humans is frequently higher, indicating that a hybrid approach to classifications may be an effective solution to merger classifications in large surveys.

Bickley, Robert W.↗
DOE OSTI2022

Constructing high-fidelity halo merger trees in abacussummit

ABSTRACT Tracking the formation and evolution of dark matter haloes is a critical aspect of any analysis of cosmological N-body simulations. In particular, the mass assembly of a halo and its progenitors, encapsulated in the form of its merger tree, serves as a fundamental input for constructing semi-analytic models of galaxy formation and, more generally, for building mock catalogues that emulate galaxy surveys. We present an algorithm for constructing halo merger trees from abacussummit, the largest suite of cosmological N-body simulations performed to date consisting of nearly 60 trillion particles, and which has been designed to meet the Cosmological Simulation Requirements of the Dark Energy Spectroscopic Instrument (DESI) survey. Our method tracks the cores of haloes to determine associations between objects across multiple time slices, yielding lists of halo progenitors and descendants for the several tens of billions of haloes identified across the entire suite. We present an application of these merger trees as a means to enhance the fidelity of abacussummit halo catalogues by flagging and ‘merging’ haloes deemed to exhibit non-monotonic past merger histories. We show that this cleaning technique identifies portions of the halo population that have been deblended due to choices made by the halo finder, but which could have feasibly been part of larger aggregate systems. We demonstrate that by cleaning halo catalogues in this post-processing step, we remove potentially unphysical features in the default halo catalogues, leaving behind a more robust halo population that can be used to create highly accurate mock galaxy realizations from abacussummit.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Comparison of sleep parameters from wrist-worn ActiGraph and Actiwatch devices

Abstract Sleep and physical activity, two important health behaviors, are often studied independently using different accelerometer types and body locations. Understanding whether accelerometers designed for monitoring each behavior can provide similar sleep parameter estimates may help determine whether one device can be used to measure both behaviors. Three hundred and thirty one adults (70.7 ± 13.7 years) from the Baltimore Longitudinal Study of Aging wore the ActiGraph GT9X Link and the Actiwatch 2 simultaneously on the non-dominant wrist for 7.0 ± 1.6 nights. Total sleep time (TST), wake after sleep onset (WASO), sleep efficiency, number of wake bouts, mean wake bout length, and sleep fragmentation index (SFI) were extracted from ActiGraph using the Cole–Kripke algorithm and from Actiwatch using the software default algorithm. These parameters were compared using paired t-tests, Bland–Altman plots, and Deming regression models. Stratified analyses were performed by age, sex, and body mass index (BMI). Compared to the Actiwatch, the ActiGraph estimated comparable TST and sleep efficiency, but fewer wake bouts, longer WASO, longer wake bout length, and higher SFI (all p < .001). Both devices estimated similar 1-min and 1% differences between participants for TST and SFI (β = 0.99, 95% CI: 0.95, 1.03, and 0.91, 1.13, respectively), but not for other parameters. These differences varied by age, sex, and/or BMI. The ActiGraph and the Actiwatch provide comparable absolute and relative estimates of TST, but not other parameters. The discrepancies could result from device differences in movement collection and/or sleep scoring algorithms. Further comparison and calibration is required before these devices can be used interchangeably.

Liu, Fangyu (ORCID:0000000315541478)↗
DOE OSTI2025

Bayesian optimization of PYTHIA 8 tunes

A new tune (set of model parameters) is found for the six most important parameters of the PYTHIA 8 final state parton shower and hadronization model using Bayesian optimization. The tune fits the Large Electron-Positron collider (LEPI) data from ALEPH better than the default tune in PYTHIA 8. To the best of our knowledge, we present the most comprehensive application of Bayesian optimization to the tuning of a parton shower and hadronization model using the LEPI data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

New H erwig7 underlying event tune: From RHIC to LHC energies

We present parameter sets corresponding to new underlying event tunes for the H erwig7.3 Monte Carlo event generator. The existing H erwig tunes are in good agreement with LHC data, however, they are not typically designed for center-of-mass energies below $\sqrt{𝑠}$ = 300 GeV. The tunes presented in this study can describe midrapidity data collected at the nominal RHIC energy of $\sqrt{𝑠}$ = 200 GeV as well as higher center-of-mass energies utilized by experiments at the LHC and Tevatron. The base “New Haven” tune is developed by fitting minimum-bias simulations of proton-proton ($𝑝⁢𝑝$) collisions to midrapidity identified hadron and jet data from the STAR experiment. The “Nashville” tune includes a separate set of parameters developed by tuning to Tevatron proton-antiproton ($𝑝\bar{⁢𝑝}$) data at $\sqrt{𝑠}$ = 300, 900 and 1960 GeV from CDF, and LHC $𝑝⁢𝑝$ measurements from CMS at $\sqrt{𝑠}$ =7 TeV, in addition to the STAR measurements. Both new tunes demonstrate significant improvements over the recommended default tune currently included in the latest version of H erwig for minimum bias production. As such, we advocate using these tunes for future simulation studies at midrapidity by experimental collaborations at RHIC (STAR and sPHENIX) and the LHC (ALICE, ATLAS, and CMS).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Sparse non-Markovian Noise Modeling of Transmon-Based Multi-Qubit Operations

The influence of noise on quantum dynamics is one of the main factors preventing current quantum processors from performing accurate quantum computations. Sufficient noise characterization and modeling can provide key insights into the effect of noise on quantum algorithms and inform the design of targeted error protection protocols. However, constructing effective noise models that are sparse in model parameters, yet predictive can be challenging. In this work, we present an approach for effective noise modeling of multi-qubit operations on transmon-based devices. Through a comprehensive characterization of seven devices offered by the IBM Quantum Platform, we show that the model can capture and predict a wide range of single- and two-qubit behaviors, including non-Markovian effects resulting from spatiotemporally correlated noise sources. The model’s predictive power is further highlighted through multi-qubit dynamical decoupling demonstrations and an implementation of the variational quantum eigensolver. As a training proxy for the hardware, we show that the model can predict expectation values within a relative error of 0.5%; this is a sevenfold improvement over default hardware noise models. Through these demonstrations, we highlight key error sources in superconducting qubits and illustrate the utility of reduced noise models for predicting hardware dynamics.

open quantum systems & decoherence↗
DOE OSTI2023

Realization of flat bands by lattice intercalation in kagome metals

Recently there has been intense interest in kagome metals, which are expected to host flat bands (FBs). However, the observed “FBs” are not flat over the whole two-dimensional Brillouin zone and overlap strongly with other bands. In fact, the FB does not truly exist in a default d-orbital kagome lattice, and the conditions for its existence in kagome metals are unknown. Here, based on tight-binding model analyses of the interplay between orbital and lattice symmetry, we establish such conditions. Additionally, we show that for a single d-orbital kagome lattice assuming large crystal field splitting (CFS), only the d z 2 orbital gives rise to a FB, while d xy , d x 2 -y 2 , d x⁢z , and d yz orbitals can only produce a FB with a rotated d-orbital basis so that they conform with the underlying kagome lattice symmetry. Most importantly, we demonstrate that both conditions of d-orbital rotation and large CFS can be ideally satisfied by intercalating the kagome lattice with a hexagonal sublattice without disrupting the destructive interference of FB wave function. Furthermore, we propose layered metalorganic frameworks as promising candidate kagome metals to realize FBs.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Measurement and modeling of proton-induced reactions on arsenic from 35 to 200 MeV

72 As is a promising positron emitter for diagnostic imaging that can be employed locally using a 72 Se generator. However, current reaction pathways to 72 Se have insufficient nuclear data for efficient production using regional 100–200 MeV high-intensity proton accelerators. In order to address this deficiency, stacked-target irradiations were performed at LBNL, LANL, and BNL to measure the production of the 72 Se/ 72 As positron emission tomography (PET) generator system via 75 As (p, x) between 35 and 200 MeV. This work provides the most well-characterized excitation function for 75 As ( p , 4 n ) 72 Se starting from threshold. Additional focus was given to report the first measurements of 75 As (p, x) 68 Ge and bolster an already robust production capability for the highly valuable 68 Ge/ 68 Ga PET generator. Thick target yield comparisons with prior established formation routes to both generators are made. In total, high-energy proton-induced cross sections are reported for 55 measured residual products from 75 As, nat Cu , and nat Ti targets, where the latter two materials were present as monitor foils. These results were compared with literature data as well as the default theoretical calculations of the nuclear model codes TALYS, COH, EMPIRE, and ALICE. Reaction modeling at these energies is typically unsatisfactory due to few prior published data and many interacting physics models. Therefore, a detailed assessment of the talys code was performed with simultaneous parameter adjustments applied according to a standardized procedure. Particular attention was paid to the formulation of the two-component exciton model in the transition between the compound and preequilibrium regions, with a linked investigation of level density models for nuclei off of stability and their impact on modeling predictive power. This paper merges experimental work and evaluation techniques for high-energy charged-particle isotope production in an extension to an earlier study of this kind.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Investigation of fast and efficient lossless compression algorithms for macromolecular crystallography experiments

Structural biology experiments benefit significantly from state-of-the-art synchrotron data collection. One can acquire macromolecular crystallography (MX) diffraction data on large-area photon-counting pixel-array detectors at framing rates exceeding 1000 frames per second, using 200 Gbps network connectivity, or higher when available. In extreme cases this represents a raw data throughput of about 25 GB s −1 , which is nearly impossible to deliver at reasonable cost without compression. Our field has used lossless compression for decades to make such data collection manageable. Many MX beamlines are now fitted with DECTRIS Eiger detectors, all of which are delivered with optimized compression algorithms by default, and they perform well with current framing rates and typical diffraction data. However, better lossless compression algorithms have been developed and are now available to the research community. Here one of the latest and most promising lossless compression algorithms is investigated on a variety of diffraction data like those routinely acquired at state-of-the-art MX beamlines.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Universal parameters of bulk-solvent masks

The bulk solvent is a major component of biomacromolecular crystals that contributes significantly to the observed diffraction intensities. Accurate modelling of the bulk solvent has been recognized as important for many crystallographic calculations. Owing to its simplicity and modelling power, the flat (mask-based) bulk-solvent model is used by most modern crystallographic software packages to account for disordered solvent. In this model, the bulk-solvent contribution is defined by a binary mask and a scale (scattering) function. The mask is calculated on a regular grid using the atomic model coordinates and their chemical types. The grid step and two radii, solvent and shrinkage, are the three parameters that govern the mask calculation. They are highly correlated and their choice is a compromise between the computer time needed to calculate the mask and the accuracy of the mask. It is demonstrated here that this choice can be optimized using a unique value of 0.6 Å for the grid step irrespective of the data resolution, and the radii values adjusted correspondingly. The improved values were tested on a large sample of Protein Data Bank entries derived from X-ray diffraction data and are now used in the computational crystallography toolbox ( CCTBX ) and in Phenix as the default choice.

36 MATERIALS SCIENCE↗
DOE OSTI2024

UTILITY CONTRIBUTION TO ARC FLASH STUDIES

The utility contribution input to an arc flash study has a significant effect on the output incident energy. Accurate input data can be difficult to obtain from serving utilities or is not consistently available. Defaulting to infinite bus can provide non-conservative results. This focus session poster will discuss the challenges with utility contribution with examples and suggest approaches to calculate conservative incident energy when the utility contribution data is not made available.

Arc flash study, utility contribution data, incide↗
DOE OSTI2022

Methods and Results for Quantum Optimal Pulse Control on Superconducting Qubit Systems

The effective use of current Noisy Intermediate-Scale Quantum (NISQ) devices is often limited by the noise which is caused by interaction with the environment and affects the fidelity of quantum gates. In transmon qubit systems, the quantum gate fidelity can be improved by applying control pulses that can minimize the effects of the environmental noise. In this work, we employ physics-guided quantum optimal control strategies to design optimal pulses driving quantum gates on superconducting qubit systems. We test our results by conducting experiments on the IBM quantum hardware using their OpenPulse API. We compare the performance of our pulse-optimized quantum gates against the default quantum gates and show that the optimized pulses improve the fidelity of the quantum gates, in particular the single-qubit gates. Here we discuss the challenges we encountered in our work and point to possible future improvements.

97 MATHEMATICS AND COMPUTING↗