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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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All sources NASA NTRS DOE OSTI

DOE OSTI2021

Development of a compressive failure model for carbon fiber composites and associated uncertainties.

An approach to increase the value of carbon fiber for wind turbines blades, and other compressive strength driven designs, is to identify pathways to increase its cost-specific compressive strength. A finite element model has been developed to evaluate the predictiveness of current finite element methods and to lay groundwork for future studies that focus on improving the cost-specific compressive strength. Parametric studies are conducted to understand which uncertainties in the model inputs have the greatest impact on compressive strength predictions. Furthermore, a statistical approach is also presented that enables the micromechanical model, which is deterministic, to efficiently account for statistical variability in the fiber misalignment present in composite materials; especially if the results from the hexagonal and square pack models are averaged. The model was found to agree well with experimental results for a Zoltek PX-35 pultrusion. The sensitivity studies suggest that the fiber packing and the interface shear strength have the greatest impact on compressive strength prediction for the fiber reinforced polymer studied here. Based on the performance of the modeling approach presented in this work, it is deemed sufficient for future work which will seek to identify carbon fiber composites with improved cost-specific compressive strength.

36 MATERIALS SCIENCE↗

DOE OSTI2020

A low-complexity non-intrusive approach to predict the energy demand of buildings over short-term horizons

Reliable, non-intrusive, short-term (of up to 12 hours ahead) prediction of a building's energy demand is a critical component of intelligent energy management applications. A number of such approaches have been proposed over time, utilizing various statistical and, more recently, machine learning techniques, such as decision trees, neural networks and support vector machines. Importantly, all of these works barely outperform simple seasonal auto-regressive integrated moving average models, while their complexity is significantly higher. Here, we propose a novel low-complexity non-intrusive approach that improves the predictive accuracy of the state-of-the-art by up to ~10%. The backbone of our approach is a K-nearest neighbours search method, that exploits the demand pattern of the most similar historical days, and incorporates appropriate time-series pre-processing and easing. In the context of this work, we evaluate our approach against state-of-the-art methods and provide insights on their performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Reliable photometric membership (RPM) of galaxies in clusters – I. A machine learning method and its performance in the local universe

ABSTRACT We introduce a new method to determine galaxy cluster membership based solely on photometric properties. We adopt a machine learning approach to recover a cluster membership probability from galaxy photometric parameters and finally derive a membership classification. After testing several machine learning techniques (such as stochastic gradient boosting, model averaged neural network and k-nearest neighbours), we found the support vector machine algorithm to perform better when applied to our data. Our training and validation data are from the Sloan Digital Sky Survey main sample. Hence, to be complete to $M_r^* + 3$, we limit our work to 30 clusters with $z$phot-cl ≤ 0.045. Masses (M200) are larger than $\sim 0.6\times 10^{14} \, \mathrm{M}_{\odot }$ (most above $3\times 10^{14} \, \mathrm{M}_{\odot }$). Our results are derived taking in account all galaxies in the line of sight of each cluster, with no photometric redshift cuts or background corrections. Our method is non-parametric, making no assumptions on the number density or luminosity profiles of galaxies in clusters. Our approach delivers extremely accurate results (completeness, C $\sim 92{\rm{ per\ cent}}$ and purity, P $\sim 87{\rm{ per\ cent}}$) within R200, so that we named our code reliable photometric membership. We discuss possible dependencies on magnitude, colour, and cluster mass. Finally, we present some applications of our method, stressing its impact to galaxy evolution and cosmological studies based on future large-scale surveys, such as eROSITA, EUCLID, and LSST.

Lopes, Paulo A. A.↗

DOE OSTI2020

Stellar mass as a galaxy cluster mass proxy: application to the Dark Energy Survey redMaPPer clusters

Abstract We introduce a galaxy cluster mass observable, μ⋆, based on the stellar masses of cluster members, and we present results for the Dark Energy Survey (DES) Year 1 (Y1) observations. Stellar masses are computed using a Bayesian model averaging method, and are validated for DES data using simulations and COSMOS data. We show that μ⋆ works as a promising mass proxy by comparing our predictions to X-ray measurements. We measure the X-ray temperature–μ⋆ relation for a total of 129 clusters matched between the wide-field DES Y1 redMaPPer catalogue and Chandra and XMM archival observations, spanning the redshift range 0.1 < $z$ < 0.7. For a scaling relation that is linear in logarithmic space, we find a slope of α = 0.488 ± 0.043 and a scatter in the X-ray temperature at fixed μ⋆ of $\sigma _{{\rm ln} T_\mathrm{ X}|\mu _\star }= 0.266^{+0.019}_{-0.020}$ for the joint sample. By using the halo mass scaling relations of the X-ray temperature from the Weighing the Giants program, we further derive the μ⋆-conditioned scatter in mass, finding $\sigma _{{\rm ln} M|\mu _\star }= 0.26^{+ 0.15}_{- 0.10}$. These results are competitive with well-established cluster mass proxies used for cosmological analyses, showing that μ⋆ can be used as a reliable and physically motivated mass proxy to derive cosmological constraints.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Accessing the gluon momentum fraction of nucleons through the gradient flow

We calculate the gluon momentum fraction of the nucleon using lattice QCD, with a nonperturbative renormalization technique based on the gradient flow. The gluon momentum fraction is determined on a single Wilson-clover ensemble using 𝑁 𝑓 =2 +1 flavors with pion mass 358 MeV and lattice spacing 0.094 fm. We employ the variational method to reduce excited-state contamination and apply the distillation framework to ensure a large operator basis. To reduce systematic uncertainties, we apply Bayesian model averaging to all fit procedures. We apply matching coefficients to the flow-time dependent lattice results to recover the gluon momentum fraction in the $\overline{MS}$-scheme at 2 GeV. Our final result is ⟨𝑥⟩ 𝑔 ⁢(𝜇 =2 GeV) =0.482⁢(35), where we quote only statistical uncertainties.

Lattice QCD↗

DOE OSTI2026

Third moments of nucleon unpolarized, polarized, and transversity parton distribution functions from physical-point lattice QCD

Using forward matrix elements of local leading-twist operators, we present a determination of the isovector third Mellin moments ⟨𝑥 2 ⟩ of nucleon unpolarized, polarized, and transversity parton distribution functions. Two lattice QCD ensembles at the physical pion mass are used, which were generated using a tree-level Symanzik-improved gauge action and 2+1 flavor tree-level improved Wilson Clover fermions coupling via 2-level HEX-smearing. Leveraging a wide set of operators, two extraction methods for the matrix elements, and the automatic inclusion of model uncertainties via bootstrapped model averages, we extract values of the third Mellin moments. Furthermore, this is the first direct calculation of these observables performed at the physical pion mass.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Light-quark connected intermediate-window contributions to the muon 𝑔 − 2 hadronic vacuum polarization from lattice QCD

We present a lattice-QCD calculation of the light-quark connected contribution to window observables associated with the leading-order hadronic vacuum polarization contribution to the anomalous magnetic moment of the muon, $a^{HVP,LO}_μ$. We employ the MILC Collaboration’s isospin-symmetric QCD gauge-field ensembles, which contain four flavors of dynamical highly improved staggered quarks with four lattice spacings between $a ≈ 0.06-0.15$ fm and close-to-physical quark masses. We consider several effective-field-theory-based schemes for finite volume and other lattice corrections and combine the results via Bayesian model averaging to obtain robust estimates of the associated systematic uncertainties. After unblinding, our final results for the intermediate and "W2" windows are $a^{U,W}_μ$(conn) = 206.6(1.0) x 10 -10 and $a^{U,W2}_μ$ (conn) = 100.7(3.2) x 10 -10 , respectively

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Hadronic vacuum polarization for the muon 𝑔 − 2 from lattice QCD: Complete short and intermediate windows

We present complete results for the hadronic vacuum polarization (HVP) contribution to the muon anomalous magnetic moment 𝑎 𝜇 in the short- and intermediate-distance window regions, which account for roughly 10% and 35% of the total HVP contribution to 𝑎 𝜇 , respectively. In particular, we perform lattice-QCD calculations for the isospin-symmetric connected and disconnected contributions, as well as corrections due to strong-isospin breaking. For the short-distance window observables, we investigate the so-called log-enhancement effects as well as the significant oscillations associated with staggered quarks in this region. For the dominant, isospin-symmetric light-quark-connected contribution, we obtain 𝑎$^{𝑙⁢𝑙,SD}_{𝜇⁡}$(conn) = 48.139⁢(11) stat ⁢(91) syst ⁢[92] total × 10 −10 and 𝑎$^{𝑙⁢𝑙,W}_{𝜇}$⁡(conn) = 206.90⁢(14) stat ⁢(61) syst ⁢[63] total × 10 −10 . We use Bayesian model averaging to fully estimate the covariance matrix between the individual contributions. Our determinations of the complete window contributions are 𝑎$^{SD}_{𝜇}$ = 69.05⁢(1) stat⁢ (21) syst ⁢[21] total × 10 −10 and 𝑎$^{W}_{𝜇}$ = 236.45⁢(17) stat⁢ (83) syst ⁢[85] total × 10 −10 . This work is part of our ongoing effort to compute all contributions to HVP with an overall uncertainty at the few-permille level.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Grid-Forming Control Using TAPAS Software Defined Inverters

Here, this paper discusses the design and hardware implementation aspects of state-feedback primary control for grid forming inverters. The primary control consists of two tracking control laws: voltage tracking and frequency/angle tracking. The voltage tracking control requires voltage and current at the inverter's switch terminal (i.e. before the filter). The fundamental component of switch terminal voltage is estimated using the inverter's average model while the switch terminal current is estimated using an observer, thus obviating the need for sensors at the switch terminals. The measurements of frequency and angle(s) needed for frequency/angle tracking are noisy due to measurement noises and inherent delays in the phase locked loop (PLL). Conditioning of these feedback signals is discussed in detail, and the corresponding changes in the control design are provided to better attenuate the impact of noises. Effectiveness of the proposed design and implementation is demonstrated by the implementation results from TAPAS software defined inverter (SDI).

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Investigating Multi-Microgrid Black Start Methods Using Grid-Forming Inverters

This paper examines state-of-the-art microgrid (MG) black-start technologies with grid-forming (GFM) inverter-based resources (IBRs) and proposes black start and interconnection methods for 100% inverter-based MGs. A multiple-MG approach is proposed and compared to the existing methods in a 4-bus, 12-GFM inverter simulation test setup. This investigation involves intelligent synchronization units that enable the autonomous synchronization of multiple MGs based on their terminal measurements. MGs in this setup are held at different loading levels and comprise averaged models of GFM inverters. The results of the black-start techniques are compared, and conclusions are drawn to better prepare MG planners and distribution system operators for next-generation, multi-MG, GFM inverter-based, black-start procedures.

black start↗

DOE OSTI2023

Low Energy Analysis of NuclEar Reactions v0.0.1

This is a lightweight, easy to use Python analysis package for analyzing public low-energy nuclear reaction data relevant to understanding basic nuclear processes, often of relevance to Solar Fusion, to improve our theoretical understanding of them, and enable connections with input from lattice QCD. It performs the analysis in a Bayesian Framework and supports Bayesian Model Averaging to provide a robust uncertainty quantification.

Walker-Loud, André↗

DOE OSTI2023

Assessment of the 3430 Building Filtered Exhaust Stack Sampling Probe Location: Stack Verification Following Fan and Air Blender Additions

The velocity uniformity and flow angle results from the 3430 stack verification tests, performed in April 2023, demonstrated that the CFD model results may be used to support the qualification of the stack sampling location. The measured velocity uniformity verification test result was 2.1 %COV. This value is well within the uniformity criterion, which is that the velocity uniformity be =20 %COV. Additionally, this value is well within the criterion that the actual stack measurement must be within 5% of the surrogate stack (i.e., CFD modeled stack); in this case the CFD modeled average result of 2.85 %COV for the nominal operating range of 22,800 cfm to 62,400 cfm. Additionally, the measured average flow angle at the 3430 stack monitor location was 5.6 degrees. The result is =20 degrees, so the criterion is met.

3430 Building↗

DOE OSTI2025

How Inverter-Based Resources (IBRs) Affect Protection Relay Elements

Inverter-based resources (IBRs) exhibit fault responses that differ significantly from those of synchronous generators, which can challenge the reliable operation of many commonly used power system protection elements. The fault response of IBRs is primarily influenced by their control algorithms and configurations, but the impact of these controls on protection relays is not yet fully understood. This presentation provides a comprehensive study of how IBR modeling and controls affect transmission line protection. Key modeling and control aspects include the DC source, inverter model, power level control, current control, and current limiting. The study reveals that certain aspects - such as the type of DC source (battery, PV, or hybrid), inverter model (average vs. switching), and power level control methods (PQ dispatch vs. Vdc-Vac control for grid-following IBRs, and droop vs. VSM for grid-forming IBRs) - do not significantly affect relay response. However, faster control loops, such as current control and current limiting, do influence the relay behavior. Additionally, the study explores the effects of other factors, including momentary cessation, operating points, fast/slow current responses, and grid strength on relay performance. Finally, the study offers recommendations for both IBR and protection engineers to improve IBR fault response and enhance the reliability of protection systems.

14 SOLAR ENERGY↗

DOE OSTI2025

A Comprehensive Study of the Impact of Inverter-Based Resource (IBR) Modeling and Control on Protection Relay Elements

14 SOLAR ENERGY↗

DOE OSTI2024

Improved Statistical Analysis for the Neutrinoless Double-Beta Decay Matrix Element of 136Xe

Neutrinoless double beta decay nuclear matrix element (M0ν) for 136Xe was recently analyzed using a statistical approach (Phys. Rev. C 107, 045501 (2023)). In the analysis, three initial shell model effective Hamiltonians were randomly altered, and their results for 23 measured observables were used to infer credibility for the M0ν nuclear matrix element (NME) based on a Bayesian Model Averaging approach. In that analysis, a reasonable Gamow-Teller quenching factor of 0.7 was assumed for each starting effective Hamiltonian. Given that the result of the statistical analysis was sensible to this choice, we are here improving that analysis by assuming that the Gamow-Teller quenching factor is also randomly chosen within reasonabe limits for all three starting Hamiltonians. The outcomes are slightly higher expectation values and uncertainties for the M0ν NME.

Astronomy & Astrophysics↗

DOE OSTI2020

Potential Vorticity Mixing in a Tangled Magnetic Field

A theory of potential vorticity (PV) mixing in a disordered (tangled) magnetic field is introduced. The analysis is in the context of β -plane MHD, with a special focus on the physics of momentum transport in the stably stratified, quasi-2D solar tachocline. A physical picture of mean PV evolution by vorticity advection and tilting of magnetic fields is proposed. In the case of weak field perturbations, quasi-linear theory predicts that the Reynolds and magnetic stresses balance as turbulence Alfvénizes for a larger mean magnetic field. Jet formation is explored quantitatively in the mean field–resistivity parameter space. However, since even a modest mean magnetic field leads to large magnetic perturbations for large magnetic Reynolds number, the physically relevant case is that of a strong but disordered field. We show that numerical calculations indicate that the Reynolds stress is modified well before Alfvénization—i.e., before fluid and magnetic energies balance. To understand these trends, a double-average model of PV mixing in a stochastic magnetic field is developed. Calculations indicate that mean-square fields strongly modify Reynolds stress phase coherence and also induce a magnetic drag on zonal flows. The physics of transport reduction by tangled fields is elucidated and linked to the related quench of turbulent resistivity. We propose here a physical picture of the system as a resisto-elastic medium threaded by a tangled magnetic network. Applications of the theory to momentum transport in the tachocline and other systems are discussed in detail.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Development of a Machine-Learned Cruise Guide Indicator for Rotorcraft

This paper presents a machine-learned virtual cruise guide indicator (vCGI) for Chinook helicopters. Two temporal neural networks were trained and evaluated on measured data from 55 flight tests, one for the fore rotor and another for the aft rotor, to predict a vCGI value, which protects 23 components from fatigue damage during steady-state conditions. Three different classes of machine learning architectures were evaluated for prediction of the vCGI from time sequences: a temporal convolutional neural network with 1D dilated causal convolutions, a long short-term memory recurrent neural network, and an attention-based transformer architecture. The final average model accuracy on unseen flight data is currently greater than 93% for CGI values which could result in fatigue damage and 90% for normal operation CGI values. Model accuracy was improved through a series of advancements in:(1) selection of optimal training data using temporal collective variables and unsupervised learning, (2) dataset augmentation with maximum-entropy temporal collective variables, and (3) implementation of a mixture-of-experts classification- regression approach using an adversarial classification approach to assign maneuver labels. The results are presented for each advancement in model development along with lessons learned in training machine learning models on real- world, time-dependent rotorcraft data.

Boyer, Mathew↗

DOE OSTI2025

Hadronic vacuum polarization for the muon g - 2 from lattice QCD: Complete short and intermediate windows

We present complete results for the hadronic vacuum polarization (HVP) contribution to the muon anomalous magnetic moment a μ in the short- and intermediate-distance window regions, which account for roughly 10% and 35% of the total HVP contribution to a μ , respectively. In particular, we perform lattice-QCD calculations for the isospin-symmetric connected and disconnected contributions, as well as corrections due to strong-isospin breaking. For the short-distance window observables, we investigate the so-called log-enhancement effects as well as the significant oscillations associated with staggered quarks in this region. For the dominant, isospin-symmetric light-quark-connected contribution, we obtain a μ l l , SD ( conn ) = 48.139 ( 11 ) stat ( 91 ) syst [ 92 ] total × 10 - 10 and a μ l l , W ( conn ) = 206.90 ( 14 ) stat ( 61 ) syst [ 63 ] total × 10 - 10 . We use Bayesian model averaging to fully estimate the covariance matrix between the individual contributions. Our determinations of the complete window contributions are a μ SD = 69.05 ( 1 ) stat ( 21 ) syst [ 21 ] total × 10 - 10 and a μ W = 236.45 ( 17 ) stat ( 83 ) syst [ 85 ] total × 10 - 10 . This work is part of our ongoing effort to compute all contributions to HVP with an overall uncertainty at the few-permille level.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗