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DOE OSTI2023

Large-time correlation functions in bosonic lattice field theories

Large-time correlation functions have a pivotal role in extracting particle masses from Euclidean lattice field theory calculations, however little is known about the statistical properties of these quantities. In this work, the asymptotic form of the distributions of the correlation functions at vanishing momentum is determined for bosonic interacting lattice field theories with a unique gapped vacuum. It is demonstrated that the deviations from the asymptotic form at large Euclidean times can be utilized to determine the spectrum of the theory.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Distributed Energy Resource-Cognizant Upgrade Paths to the Traditional Restoration Strategy of Utilities for Improved Load Restoration

Climate change has resulted in increasingly impactful and more frequent occurrences of extreme weather events. This trend poses a significant challenge for distribution utilities and system operators to ensure that there is uninterrupted power supply to critical loads in their networks under fault scenarios; however, currently, utilities deploying the automated fault location, isolation and restoration (FLISR) function in their advanced distribution management system (ADMS) do not take into account the available generation and load-modification capabilities of distributed energy resources present in the disconnected network due to an upstream isolated fault. This results in the network reconfiguration and restoration to result in sub-optimal load restoration. Therefore, this paper presents two approaches that can upgrade the existing FLISR capabilities of distribution utilities to significantly increase the restoration of critical loads. The performance of the proposed approaches is evaluated on a numerical model of a real distribution feeder in Georgia, USA.

DER↗

DOE OSTI2023

Distributed Energy Resource-Cognizant Upgrade Paths to the Traditional Restoration Strategy of Utilities for Improved Load Restoration: Preprint

DER↗

DOE OSTI2022

Exclusive double quarkonium production and generalized TMDs of gluons

Being the “mother distributions” of all types of two-parton correlation functions, generalized transverse momentum dependent parton distributions (GTMDs) have attracted a lot of attention over the last years. We argue that exclusive double production of pseudoscalar quarkonia (η c or η b ) in nucleon-nucleon collisions gives access to GTMDs of gluons.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Enhanced Signal Processing of Distributed Brillouin Fiber Sensors using a Decoupled Radial Basis Function Network

A novel decoupled radial basis function network (D-RBFN) is proposed to accelerate signal processing and address the big data challenges associated with ultra-long distance Brillouin optical time-domain analysis (BOTDA) systems. The proposed frame- work is demonstrated on a dataset measured over a 100 km distance using a bi-directional Raman assisted BOTDA system.

Venketeswaran, Abhishek↗

DOE OSTI2021

Real Time and Distributed Temperature Sensing and Quench Detection Via Multi-Functional Fiber Optic Sensors

Explore the source record for details and available documents.

MANJOORAN, NAVIN↗

DOE OSTI2021

Clarifying remotely-retrieved precipitation of shallow marine clouds from the NSF/NCAR Gulfstream V

Precipitation is a key process within the shallow cloud lifecycle. The Cloud System Evolution in the Trades (CSET) campaign included the first deployment of a 94 GHz Doppler radar and 532 nm lidar. Despite a larger sampling volume, initial mean radar/lidar retrieved rain rates (Schwartz et al. 2019) based on the upward-pointing remote sensor datasets are systematically less than those measured by in-situ precipitation probes in the cumulus regime. Subsequent retrieval improvements produce rainrates that compare better to in-situ values, but still underestimate. Retrieved shallow cumulus drop sizes can remain too small and too few, with an overestimated shape parameter narrowing the raindrop size distribution too much. Three potential causes for the discrepancy are explored: the gamma functional fit to the dropsize distribution, attenuation by rain and cloud water, and an underaccounting of Mie dampening of the reflectivity. A truncated exponential fit may represent the dropsizes below a showering cumulus cloud more realistically, although further work would be needed to fully evaluate the impact of a different dropsize representation upon the retrieval. The rain attenuation is within the measurement uncertainty of the radar. Mie dampening of the reflectivity is shown to be significant, in contrast to previous stratocumulus campaigns with lighter rain rates, and may be difficult to constrain well with the remote measurements. An alternative approach combines an a priori determination of the dropsize distribution width based on the in-situ data with the mean radar Doppler velocity and reflectivity. This can produce realistic retrievals, although a more comprehensive assessment is needed to better characterize the retrieval errors.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Know Your Space: Inlier and Outlier Construction for Calibrating Medical OOD Detectors

This software offers methods and functions for training calibrated out-of-distribution detectors for medical image classification tasks. It includes functionalities for training, synthesizing data augmentations, calibration, and out-of-distribution detection. Developed using PyTorch, this software is compatible with standard neural network architectures used for imaging data. Additionally, it provides capabilities to compute evaluation metrics for assessing the performance and quality of the detectors.

Narayanaswamy, VivekSivaraman↗

DOE OSTI2021

Multimodal Bayesian registration of noisy functions using Hamiltonian Monte Carlo

Functional data registration is a necessary processing step for many applications. The observed data can be inherently noisy, often due to measurement error or natural process uncertainty; which most functional alignment methods cannot handle. A pair of functions can also have multiple optimal alignment solutions, which is not addressed in current literature. In this paper, a flexible Bayesian approach to functional alignment is presented, which appropriately accounts for noise in the data without any pre-smoothing required. Additionally, by running parallel MCMC chains, the method can account for multiple optimal alignments via the multi-modal posterior distribution of the warping functions. To most efficiently sample the warping functions, the approach relies on a modification of the standard Hamiltonian Monte Carlo to be well-defined on the infinite-dimensional Hilbert space. In this work, this flexible Bayesian alignment method is applied to both simulated data and real data sets to show its efficiency in handling noisy functions and successfully accounting for multiple optimal alignments in the posterior; characterizing the uncertainty surrounding the warping functions.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Distribution of Bound and Free Water in Anatomical Fractions of Pine Residues and Corn Stover as a Function of Biological Degradation

Biomass quality is influenced by water’s abundance, distribution, and status in relation to other chemical species within the polymer matrix. Water interacts with polymers that make up the cell walls, and these interactions govern the physical and chemical changes that occur during the storage and preprocessing of biomass feedstocks. Time-domain nuclear magnetic resonance (TD-NMR) was employed to explore variations in the physical constraints of water within the lignocellulosic microstructure in distinct anatomical fractions of biomass and as a function of biological degradation. The Carr–Purcell–Meiboom–Gill sequence, when combined with knowledge of the chemical composition and physical structure of pine residues and corn stover anatomical fractions, gives an accurate measurement of the bound and free water. In this work, the impacts of storage and biological degradation were investigated to elucidate changes in the status and distribution of water within distinct plant tissues. We also investigate how degradation during storage affects water interactions in different pine residues (e.g., bark, branch, and needle) and corn stover (e.g., cob, leaf, and stalk) anatomical fractions using transverse relaxation times (T2). As demonstrated herein, TD-NMR provides quantitative data on lignocellulosic biomass–water interactions within anatomical fractions, which can further aid in the investigation of preprocessing effects on feedstock quality. Our findings suggest that biological heating enhances biomass–water interactions at the cellular and macromolecular scale. In addition, analysis of three-dimensional scanning electron microscopy reconstructions indicates that surface roughness wavelengths align with microscale roughness, suggesting that pine forestry residue and corn stover particles have primarily hydrophobic exterior surfaces. Furthermore, this study offers multiscale insights into understanding the microstructure, wettability, and chemical environment that dictate diffusion, enzyme access, and recalcitrance of lignocellulosic biomass.

09 BIOMASS FUELS↗

DOE OSTI2025

Study of light-meson resonances decaying to K S 0 K π in the B → ( K S 0 K π ) K channels

A study is presented of B + → K S 0 K − π + K + and B + → K S 0 K + π − K + decays based on the analysis of proton-proton collision data collected with the LHCb detector at center-of-mass energies of 7, 8 and 13 TeV, corresponding to an integrated luminosity of 9 fb − 1 . The K S 0 K π invariant-mass distributions of both B + decay modes show, in the m ( K S 0 K π ) < 1.85 GeV mass region, large activity which is resolved using an amplitude analysis. A simple model, where J P C amplitudes are described by multiple Breit-Wigner functions with appropriate angular distributions, provides a good description of the experimental data. In this approach a complex mixture of J P C = 0 − + , 1 + + and 1 + − amplitudes is observed that is dominated by η ( 1405 ) , η ( 1470 ) , η ( 1760 ) , f 1 ( 1285 ) , f 1 ( 1420 ) and h 1 ( 1405 ) resonances. The K S 0 K π Dalitz plots are dominated by asymmetric crossing K * K ¯ bands which are different for the two B + decay modes. This is due to a different interference pattern between the 1 + + and 1 + − amplitudes in the two channels. Branching fractions are measured for each resonant contribution. © 2025 CERN, for the LHCb Collaboration 2025 CERN

Aaij, R. (ORCID:0000000305331952)↗

DOE OSTI2025

Neural chaos: A spectral stochastic neural operator

Building surrogate models for operators with uncertainty quantification capabilities is essential for many engineering applications where randomness–such as variability in material properties, boundary conditions, and initial conditions–is unavoidable. Polynomial Chaos Expansion (PCE) is widely recognized as a go-to method for constructing stochastic surrogates in both intrusive and non-intrusive ways, and it has recently been used in the context of operator learning. However, its application becomes challenging for complex or high-dimensional processes, as achieving accuracy requires higher-order polynomials, which can increase computational demand and/or the risk of overfitting. Furthermore, PCE requires specialized treatments to manage random variables that are not independent, and these treatments may be problem-dependent or may fail with increasing complexity. Here, in this work, we adopt the same formalism as the spectral expansion used in PCE; however, we replace the classical polynomial basis functions with neural network (NN) basis functions to leverage their expressivity. To achieve this, we propose an algorithm that identifies NN-parameterized basis functions in a purely data-driven manner, without any prior assumptions about the joint distribution of the random variables involved, whether independent or dependent, or about their marginal distributions. The proposed algorithm identifies each NN-parameterized basis function sequentially, ensuring they are orthogonal with respect to the data distribution. The basis functions are constructed directly on the joint stochastic variables without requiring a tensor product structure or assuming independence of the random variables. This approach may offer greater flexibility for complex stochastic models, while simplifying implementation compared to the tensor product structures typically used in PCE to handle random vectors. This is particularly advantageous given the current state of open-source packages, where building and training neural networks can be done with just a few lines of code and extensive community support. We demonstrate the effectiveness of the proposed scheme through several numerical examples of varying complexity and provide comparisons with classical PCE.

Polynomial chaos expansion↗

DOE OSTI2021

Scalable/Secure Cooperative Algorithms and Framework for Extremely-high Penetration Solar Integration (SolarExPert) (Final Technical Report)

This SolarExPert project has developed a Sustainable Grid Platform (SGP) with scalable architecture of distributed control and optimization. The SGP consists of the following major functions: 1) an advanced grid architecture with hierarchical and distributed communication and control, combined with the OpenFMB standard and implemented on the Multi-Agent OpenDSS (MA-OpenDSS) platform; 2) an online distributed stochastic optimal power flow; 3) an online distributed system state estimation algorithm; 4) the distributed Volt/VAR optimization and frequency control algorithms; 5) the distributed distribution system restoration strategy. The developed SGP together with advanced functions are tested in 1 million (1M)-node distribution system on the MA-OpenDSS platform. Furthermore, the models and algorithms are tested in 100,000-node system HiL simulation, and also in P-HiL implementation with 100 physical devices. The developed functions haven been validated and tested on the selected actual distribution feeder with the data collected from the field of Maui Meadows in Hawaii. The distributed PV hosting capacities with cooperative Volt/VAR and Volt/VAR/Watt control are estimated and compared to provide recommendations for customers and the utility company.

14 SOLAR ENERGY↗

DOE OSTI2020

Analytical integration of the tractions induced by non-singular dislocations on an arbitrary shaped triangular quadratic element

Here, an analytical model is proposed to evaluate the nodal force induced by a segment of dislocation upon an arbitrary shaped triangular element. This calculation is required in hybrid methods that associate dislocation dynamics to boundary or finite element to solve simultaneously the evolution of large ensembles of dislocations with complex boundary conditions. Nodal forces are defined as the triple integration of the unbalanced traction field induced by a straight dislocation upon the surface of the element. Following our previous approach (Queyreau et al 2014 Modelling Simul. Mater. Sci. Eng. 22 035004) on a simpler geometry and in the case of linear isotropic elasticity, triple integrals are solved by sequences of integration by parts that exhibit recurrence relations. The traction field is defined and finite everywhere even at the core of dislocations, thanks to the use of the non-singular stress expression formulated by Cai et al (2006 J. Mech. Phys. Solids 54 561–587). The nodal force expressions can be used when considering both a single convolution or double convolution of the Green's function with the core distribution. A solution is also proposed for the case of a semi-infinite segment through the study of the asymptotic behavior of the analytical expressions. The proposed approach is exact and very computationally efficient. The choice of an arbitrary shaped triangular element and quadratic shape functions allow the consideration of complex geometries and comply with automatic meshing procedures. These analytical expressions could also be employed to estimate dislocation interactions with interfaces.

42 ENGINEERING↗

DOE OSTI2023

Dynamic Rupture Simulations of the Mw7.2 1992 Landers,California, Earthquake

An important part of the simulation technique implemented in the Recipe is the earthquake rupture characterization based on established empirical scaling relationships between source parameters and seismic moment. The scaling relationships used in the rupture characterization are derived from recorded data and are tested against dynamic and kinematic rupture models of crustal earthquakes. Currently, a revised three-stage source scaling relationship between the source rupture area and seismic moment of inland crustal earthquakes, initially proposed by Irikura and Miyake, is being used. Recent analysis of results obtained with the Recipe for the 2016 M7.1 Kumamoto earthquake performed by several researchers, including the PI, Arben Pitarka, indicate that in order to reproduce the near-fault long-period ground motions and the permanent displacements, observed during surface-rupturing earthquakes, the recipe needs modifications to the kinematic rupture parametrization in the shallow crustal weak zone. In particular, improvements are required in characterizing the slip rate function at shallow depths, above the sesimogenic zone. The main objective of this research project was the development of a dynamic rupture model for the Mw7.2 1992 Landers, California earthquake. The dynamic rupture model was used to derive kinematic rupture parameters, such as slip, slip-rate, rupture time distributions, and slip rate functions in the weak (0-4km) and seismogenic crustal zones. In addition to the knowledge gained from the dynamic rupture modeling of Chi-chi, Ridgecrest, Kumamoto and other crustal earthquakes, studied by the PI, the rupture characterization of the Landers earthquake can be helpful in updating the conventional recipe for broadband ground motion simulations of crustal earthquakes with shallow rupture. The project emphasizes the need for performing physics-based earthquake rupture modeling which ultimately will inform further improvements of rupture characterization. In particular, the modeling of rupture dynamics for recorded earthquakes, and numerical simulations for different rupture scenarios, provides physical constrains on slip evolution in time and space, used in adjustments of empirical source scaling relationships for large crustal earthquakes.

58 GEOSCIENCES↗

DOE OSTI2020

Radiation-Induced Effects on the Extraction Properties of Hexa-n-octylnitrilo-triacetamide (HONTA) Complexes of Americium and Europium

The candidate An(III)/Ln(III) separation ligand hexa-n-octylnitrilo-triacetamide (HONTA) was irradiated under envisioned SELECT (Solvent Extraction from Liquid waste using Extractants of CHON-type for Transmutation) process conditions (n-dodecane/0.1 M HNO 3 ) using a solvent test loop in conjunction with cobalt-60 gamma irradiation. The extent of HONTA radiolysis and complimentary degradation product formation was quantified by HPLC-ESI-MS/MS. Further, the impact of HONTA radiolysis on process performance was evaluated by measuring the change in 243 Am and 154 Eu distribution ratios as a function of absorbed gamma dose. HONTA was found to decay exponentially with increasing dose, affording a dose coefficient of d = (4.48 ± 0.19) × 10 –3 kGy –1 . Multiple degradation products were detected by HPLC-ESI-MS/MS with dioctylamine being the dominant quantifiable species. Both 243 Am and 154 Eu distribution ratios exhibited an induction period of ~70 kGy for extraction (0.1 M HNO 3 ) and back-extraction (4.0 M HNO 3 ) conditions, after which both values decreased with absorbed dose. The decrease in distribution ratios was attributed to a combination of the destruction of HONTA and ingrowth of dioctylamine, which is capable of interfering in metal ion complexation. Furthermore, the loss of HONTA with absorbed gamma dose was predominantly attributed to its reaction with the n-dodecane radical cation (R˙ + ). These R˙ + reaction kinetics were measured for HONTA and its 241 Am and 154 Eu complexes using picosecond pulsed electron radiolysis techniques. All three second-order rate coefficients (k) were essentially diffusion limited in n-dodecane indicating a significant reaction pathway: k(HONTA + R˙ + ) = (7.6 ± 0.8) × 10 9 M –1 s –1 , k(Am(HONTA) 2 + R˙ + ) = (7.1 ± 0.7) × 10 10 M –1 s –1 , and k(Eu(HONTA) 2 + R˙ + ) = (9.5 ± 0.5) × 10 10 M –1 s –1 . HONTA-metal ion complexation afforded an order-of-magnitude increase in rate coefficient. Additional nanosecond time-resolved measurements showed that both direct and indirect HONTA radiolysis yielded the short-lived (< 100 ns) HONTA radical cation and a second long-lived (µs) species identified as the HONTA triplet excited state. The latter was confirmed by a series of oxygen quenching picosecond pulsed electron measurements, affording a quenching rate coefficient of k( 3 [HONTA]* + O 2 ) = 2.2 × 10 8 M –1 s –1 . Overall, both the HONTA radical cation and triplet excited state are important precursors to the suite of measured HONTA degradation products.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2024

Multiplicity dependence of charged-particle intra-jet properties in pp collisions at $\sqrt{s}$ = 13 TeV

The first measurement of the multiplicity dependence of intra-jet properties of leading charged-particle jets in proton–proton (pp) collisions is reported. The mean charged particle multiplicity and jet fragmentation distributions are measured in minimum-bias and high-multiplicity pp collisions at center-of-mass energy $\sqrt{s}$ = 13 TeV using the ALICE detector. Jets are reconstructed from charged particles produced in the midrapidity region (|η| < 0.9) using the sequential recombination anti-k T algorithm with jet resolution parameters R = 0.2, 0.3, and 0.4 for the trans verse momentum (p T ) interval 5–110 GeV/c. The high multiplicity events are selected by the forward V0 scintilla tor detectors. The mean charged-particle multiplicity inside the leading jet cone rises monotonically with increasing jet p T in qualitative agreement with previous measurements at lower energies. The distributions of jet fragmentation function variables z ch and ξ ch are measured for different jet-p T intervals. Jet-p T independent fragmentation of leading jets is observed for wider jets except at high- and low-z ch values. The observed “hump-backed plateau” structure in the ξ ch distribution indicates suppression of low-p T particles. In high-multiplicity events, an enhancement of the fragmen tation probability of low-z ch particles accompanied by a suppression of high-zch particles is observed compared to minimum-bias events. This behavior becomes more promi nent for low-p T jets with larger jet radius. The results are compared with predictions of QCD-inspired event generators, PYTHIA 8 with Monash 2013 tune and EPOS LHC. It is found that PYTHIA 8 qualitatively reproduces the jet modification in high-multiplicity events except at high jet p T . These measurements provide important constraints to models of jet fragmentation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Non-Parametric Statistical Analysis of Current Waveforms through Power System Sensors

The protection, control, and monitoring of the power grid is not possible without accurate measurement devices. As the percentage of renewable energy sources penetrating the existing grid infrastructure increases, so do uncertainties surrounding their effects on the everyday operation of the power system. Many of these devices are sources of high-frequency transients. These transients may be useful for identifying certain events or behaviors otherwise not seen in traditional analysis techniques. Therefore, the ability of sensors to accurately capture these phenomena is paramount. In this work, two commercial-grade power system distribution sensors are investigated in terms of their ability to replicate high-frequency phenomena by studying their responses to three events: a current inrush, a microgrid “close-in”, and a fault on the terminals of a wind turbine. Kernel density estimation is used to derive the non-parametric probability density functions of these error distributions and their adequateness is quantified utilizing the commonly used root mean square error (RMSE) metric. It is demonstrated that both sensors exhibit characteristics in the high harmonic range that go against the assumption that measurement error is normally distributed.

47 OTHER INSTRUMENTATION↗