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DOE OSTI2025

Hydrogen Transportation and Distributed Energy Systems Seismic Risk Assessment for Cascadia Subduction Zone Airport Facilities

Portland International Airport in Oregon is exploring operating a fleet of 28 fuel cell electric buses to support airport operations and possibly provide backup power during outages. In this report, we evaluate the risk of hydrogen deployment at an airport considering the potential for seismic activity. We present a seismic risk assessment for pressurized piping for a generic hydrogen refueling station at the airport. Only pressurized piping was considered in the risk analysis because of its vulnerability and availability of fragility information unlike the other components. Seismic capacity of other components should be included as more information becomes available. To characterize the seismic hazard, we considered the initiating event frequency of a Cascadia Subduction Zone earthquake event based on data from the literature. Seismic stressors that translate to the site from an earthquake event are expressed as peak ground acceleration. Site disturbance is characterized as a function of soil conditions, represented by different shear wave velocity values, which affect how seismic waves propagate and impact structures. Pipe fragility curves as a function of seismic capacity were used to correlate ground acceleration and failure probability. These fragility characteristics were combined with site-specific soil conditions to calculate the probability of pipe rupture during a seismic event. It should be noted that multiple simultaneous failures due to an earthquake event as a common cause are not considered. Some epistemic uncertainties such as self-exciting shocks, aftershocks, and the time variant nature of the ground motion are not considered either.

08 HYDROGEN↗

DOE OSTI2025

24.1.3.4 Upgraded Fixed Energy Response Function Analysis with Multiple Efficiencies (FRAM) Software for U/Pu/MOX Mass Measurements

Fixed-energy Response-function Analysis with Multiple efficiency (FRAM) is a software code designed primarily for plutonium and uranium isotopic analysis. It is widely used in both the domestic and international safeguards community. FRAM can quickly and accurately determine the isotopic compositions of plutonium, uranium, and mixed oxides (MOX) when measuring with a high-purity germanium (HPGe), cadmium zinc telluride (CZT), or lanthanum bromide (LaBr 3 ) detector. The capabilities of FRAM have been enhanced to analyze the data of the pixelated CZT detector (made by H3D) and to measure the mass of plutonium, uranium, and MOX. Both the isotopic composition and mass of the item can be quickly determined with one measurement using a gamma detector with FRAM v.7.1.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Nuclear DFT analysis of electromagnetic moments in odd near doubly magic nuclei

We use the nuclear density functional theory to determine nuclear electric quadrupole and magnetic dipole moments in all one-particle and one-hole neighbours of eight doubly magic nuclei. We align angular momenta along the intrinsic axial-symmetry axis with broken time-reversal symmetry, which allows us to explore fully the self-consistent charge, spin, and current polarisation. Spectroscopic moments are determined for symmetry-restored wave functions and compared with available experimental data. We find that the obtained polarisations do not call for using quadrupole- or dipole-moment operators with effective charges or effective g-factors.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

The Single Event Error (SEE) test and analysis of the CMS Endcap Timing Layer readout chip

The ETROC2, the first full size and full functionality prototype chip for the CMS Endcap Timing Layer readout, is strategically designed to meet the SEE immunity requirements of detector operation with the low power constraint. The triplicated periphery and pixel I2C configuration registers are designed with self-correction feature. The pixel readout control is centralized in the global readout and fully triplicated. The pixel readout is not triplicated, instead protected with power-efficient one-bit correction Hamming code. The TMR protection of the on-pixel threshold calibration can be turned off allowing the detection of the beam spot during the beam test by checking the bit-flips of the internal memory cells. In the initial proton beam test in January 2024, the chip readout process did not hang throughout the tests. The Hamming code correction strategy works because the error corrected TDC data were observed in the data frames. The error-injection simulation is performed to analy ze the small number of bit-flips in the configuration registers. We also performed SEE testing with a heavy ion beam in April and the data analysis is ongoing. The detailed design on the SEE immunity and the testing as well as simulation results will be presented, including follow-up SEE testing results in May and June 2024.

Gong, Datao↗

DOE OSTI2023

Snekmer: a scalable pipeline for protein sequence fingerprinting based on amino acid recoding

Abstract Motivation The vast expansion of sequence data generated from single organisms and microbiomes has precipitated the need for faster and more sensitive methods to assess evolutionary and functional relationships between proteins. Representing proteins as sets of short peptide sequences (kmers) has been used for rapid, accurate classification of proteins into functional categories; however, this approach employs an exact-match methodology and thus may be limited in terms of sensitivity and coverage. We have previously used similarity groupings, based on the chemical properties of amino acids, to form reduced character sets and recode proteins. This amino acid recoding (AAR) approach simplifies the construction of protein representations in the form of kmer vectors, which can link sequences with distant sequence similarity and provide accurate classification of problematic protein families. Results Here, we describe Snekmer, a software tool for recoding proteins into AAR kmer vectors and performing either (i) construction of supervised classification models trained on input protein families or (ii) clustering for de novo determination of protein families. We provide examples of the operation of the tool against a set of nitrogen cycling families originally collected using both standard hidden Markov models and a larger set of proteins from Uniprot and demonstrate that our method accurately differentiates these sequences in both operation modes. Availability and implementation Snekmer is written in Python using Snakemake. Code and data used in this article, along with tutorial notebooks, are available at http://github.com/PNNL-CompBio/Snekmer under an open-source BSD-3 license. Supplementary information Supplementary data are available at Bioinformatics Advances online.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Measurement of $t\overline{t}$ production in association with additional b -jets in the eμ final state in proton–proton collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

This paper presents measurements of top-antitop quark pair ($t\overline{t}$) production in association with additional b-jets. The analysis utilises 140 fb -1 of proton–proton collision data collected with the ATLAS detector at the Large Hadron Collider at a centre-of-mass energy of 13 TeV. Fiducial cross-sections are extracted in a final state featuring one electron and one muon, with at least three or four b-jets. Results are presented at the particle level for both integrated cross-sections and normalised differential cross-sections, as functions of global event properties, jet kinematics, and b-jet pair properties. Observable quantities characterising b-jets originating from the top quark decay and additional b-jets are also measured at the particle level, after correcting for detector effects. The measured integrated fiducial cross sections are consistent with $t\overline{t}$$b\overline{b}$ predictions from various next-to-leading-order matrix element calculations matched to a parton shower within the uncertainties of the predictions. State of-the-art theoretical predictions are compared with the differential measurements; none of them simultaneously describes all observables. Differences between any two predictions are smaller than the measurement uncertainties for most observables.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

The molten salt tritium transport experiment: A pumped fluoride salt loop for hydrogen isotope experimentation

Molten salt reactors (MSRs) and fusion reactors propose to use molten salts as coolants and breeder blanket materials, respectively. Tritium, however, poses safety concerns in both reactor types due to its ability to permeate through reactor materials and potential for environmental release. This manuscript addresses the tritium transport phenomena in molten salts and presents the design and analysis of the Molten Salt Tritium Transport Experiment (MSTTE). MSTTE is a forced-convection fluoride salt loop intended to measure hydrogen isotope permeation through structural materials in a flowing salt system. In the first phase, MSTTE will use FLiNaK salt and deuterium as surrogates for FLiBe and tritium, with future plans to utilize tritium and FLiBe. MSTTE couples a Copenhagen Atomics pumped salt loop with an external test section that introduces hydrogen isotopes into the loop and measures transport phenomena. The Hydrogen Injection System (HIS) controls hydrogen isotope introduction into the molten salt loop. Here, the permeation test section measures the permeation rate through stainless steel tubing in contact with flowing salt. Computational fluid dynamics (CFD) analysis ensures fully developed salt flow in the permeation test section. MSTTE is modeled with MELCOR-TMAP to predict the permeation rate as a function of experimental variables such as source term, salt flow rate, and salt temperature. Results indicate that the source term is the only parameter with a significant effect on the permeation rate. Pressure drop analysis suggests that the loop should operate below 200 LPM to maintain a pressure drop below 200 kPa. Additionally, finite-element analysis assesses thermal stress during loop operation to ensure the experiment's safe design. MSTTE will provide semi-integral data on tritium transport phenomena in molten salts and serve as a testbed for advancing molten salt technology.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Adipose-specific knockout of Protein Kinase D1 suppresses de novo lipogenesis in mice via SREBP1c-dependent signaling

Highlights: • Protein Kinase D1 is a functional regulator in adipocyte and white adipose tissue. • PKD1 drives de novo lipogenesis in adipocyte. • SREBP1c signaling regulates lipogenesis in adipocyte. • PKD1-mediated de novo lipogenesis relies on SREBP1c. Having healthy adipose tissue is essential for metabolic health, as excessive adipose tissue in the body can cause its dysregulation and driving chronic metabolic diseases. Protein kinase D1 (PKD1) is considered to be a key kinase in signal transduction, which regulates multiple cellular functions, but its physiological functions in adipose are still not fully understood. This study aimed at elucidating the function of adipocyte PKD1 on lipogenesis. From RNA-Sequencing data, we found that the fatty acid biosynthesis pathway in white adipose tissue lacking PKD1 was significantly affected. Critical rate-limiting enzymes for de novo lipogenesis in adipocytes, such as FASN, ACCα, and SCD1, were significantly repressed after deleting PKD1 in vivo and in vitro. Further studies revealed that blockade of PKD1 significantly increased phosphorylation of SREBP1c at serine 372 site. Co-immunoprecipitation analysis showed that PKD1 interacts with SREBP1c in vitro and in vivo. Importantly, overexpression of SREBP1c reversed the inhibition of FASN and ACCα expression caused by PKD1 silencing. Together, adipocyte PKD1 promotes de novo lipogenesis via SREBP1c-dependent manner in visceral white adipose tissue and might provide a new target for the development of anti-obesity therapies.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Kinetic Study of Polyvinyl Chloride Pyrolysis with Characterization of Dehydrochlorinated PVC

In this paper, we study the kinetics of polyvinyl chloride (PVC) decomposition using a combination of experimental and computational approaches. Here, we develop a simplified kinetic model that contains only two steps: dehydrochlorination of PVC and further decomposition of the PVC residue. The model is consistent with density functional theory (DFT) calculations and experimental data. Dehydrochlorination is an autocatalytic reaction that starts with a tertiary chloride (Cl) and generates hydrogen chloride (HCl) and benzene as the main products. Benzene and HCl formation rates showed similar trends, indicating that HCl likely catalyzes a homolytic carbon-carbon (C-C) bond cleavage, which gives rise to benzene and an aliphatic fragment. We characterized the structure of dehydrochlorinated PVC (PVC residue) by using thermal gravimetric analysis (TGA), Fourier-transform infrared spectroscopy (FTIR), and nuclear magnetic resonance spectroscopy (NMR). FTIR and NMR results indicate that the PVC residue contains 20% quaternary carbon content, indicating a high concentration of cross-linked molecules. We predict that the most probable structure in the cross-linked centers of the PVC residue is cyclohexadiene, which is supported by DFT calculations, FTIR, and NMR.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Task 12 PV Sustainability - Life Cycle Assessment of Crystalline Silicon Photovoltaic Module Delamination with Hot Knife Technology

The objective of this study is to complete a life cycle assessment (LCA) of a novel technology that separates the crystalline silicon (c-Si) photovoltaic (PV) module front glass from the backsheet using hot knife technology. This is known to be the most challenging step in module recycling, where the choice of delamination approach can determine the process selection for the next steps of the recycling process, the economic value of the recovered materials, and environmental performance. The life cycle inventory (LCI) reported here is based on primary data from the technology manufacturer. Different LCIs are established following the cut-off approach and the end-of-life (EOL) approach. The environmental impacts of the hot knife delamination process are analysed based on six indicators, and the main contributors to delamination efforts are identified. For the EOL approach, the potential environmental benefits from the recovered materials are compared to the environmental impacts caused by the delamination process. The functional unit of this analysis is the delamination of 1 kg of used framed c-Si PV modules at the place of installation.

14 SOLAR ENERGY↗

DOE OSTI2021

A novel measurement of initial-state gluon radiation in hadron collisions using Drell-Yan events

A study of initial-state gluon radiation (ISR) in hadron collisions is presented using Drell-Yan (DY) events produced in proton-antiproton collisions by the Tevatron collider at a center-of-mass energy of 1.96 TeV. This paper adopts a novel approach which uses the mean value of the Z/$\gamma^*$ transverse momentum $ $ in DY events as a powerful observable to characterize the effect of ISR. In a data sample corresponding to an integrated luminosity of 9.4 fb$^{-1}$ collected with the CDF Run II detector, $ $ is measured as a function of the Z/$\gamma^*$ invariant mass. It is found that these two observables have a dependence, $ = -8 + 2.2 \ln m_{DY}^2$ [GeV/c], where $m_{DY}$ is the value of the Z/$\gamma^*$ mass measured in units of GeV/$c^2$. This linear dependence is observed for the first time in this analysis. It may be exploited to model the effect of ISR and constrain its impact in other processes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

First Measurement Of Charged-current 1 Muon 2 Proton 0 Pion Single Differential Cross-sections On Argon-40 At 0.8 Gev Average Neutrino Energy With The MicroBooNE Detector

Constraining systematic uncertainties that arise from neutrino-nucleon cross-section modeling is critical for upcoming neutrino oscillation experiments. Neutrino interactions that lead to the ejection of 2 particles from the target nucleus, leaving the nucleus with 2 holes, are one cross-section of interest. These instances, known as 2-particle 2-hole (2p2h) states, can be produced either by neutrino interaction modes or from the influence of nuclear physics on the neutrino interaction. While there are many theoretical models that attempt to describe the nature of 2p2h states, very few experimental measurements of this process exist, making it difficult to benchmark theoretical calculations. Furthermore, no high statistic cross-section measurements of 2p2h states exist on $^{40}$Ar, the target nucleus of many current and next generation neutrino oscillation experiments. This analysis aims to address this issue by providing the first high-statistic single differential cross-section me asurements of 2p2h states. Using data collected from the first 3 years of running of the MicroBooNE experiment, we select $\nu_\mu$ charged-current interaction events that produce a single muon, 2 protons, and no pions in the final state (CC1$\mu$2p0$\pi$). The single differential cross-section is then extracted as a function of a variety of physics variables and compared to theoretical predictions from several event generator model sets.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Equivalence Ratio Scans in a Rotating Detonation Engine

Published data for run times exceeding a few seconds in rotating detonation engines (RDEs) is rare, but long duration tests are necessary to understand both transient and persistent phenomena in RDE operation. Previous work has noted different detonation wave modes at different equivalence ratios. In the current study, multiple long-duration runs with constant air flow rate and variable equivalence ratio are conducted in a hydrogen-fueled, water-cooled RDE. Analysis of the capillary tube averaged pressure (CTAP) data reveals a strong correlation with equivalence ratio as well as a small time dependency due to transient thermal processes. Ion probe measurements are used to analyze detonation wave frequencies and modes, both of which are strongly dependent on the equivalence ratio. Mode transitions are observed to occur consistently as the equivalence ratio is traversed between 0.55 and 0.60. These transitions are also found to be a function of the direction of changing equivalence ratio (ascending or descending) and time.

Boyette, Wesley R.↗

DOE OSTI2024

Equivalence Ratio Scans in a Rotating Detonation Engine

Boyette, Wesley R.↗

DOE OSTI2025

Large Area Airborne Contamination Monitoring

The individual components of a Large Area Airborne Contamination Monitoring (LAACM) system have been demonstrated as functional and the concept of a low-cost, rapidly deployable, and rapidly expandable system has been validated. All components of a previously demonstrated system were re-evaluated. Based on this evaluation, recommendations were made for air collection equipment, scintillating material was synthesized and optimized for application, and improved images were acquired. A preliminary concept of operations was developed, outlining the need for an automated scintillation application system and software for data acquisition and analysis. The work conducted under this program in FY24 has raised the Technology Readiness Level (TRL) of the LAACM from TRL 3 to TRL 4.

Whiteside, Tad S. [Savannah River National Laborat↗

DOE OSTI2022

Fraction of broad absorption line quasars in different radio morphologies

ABSTRACT In this study, we investigated the orientation model of Broad Absorption Line (BAL) quasars using a sample of sources that are common in Sloan Digital Sky Survey (SDSS) Data Release (DR)-16 quasar catalogue and Very Large Array (VLA)-Faint Images of the Radio Sky at Twenty Centimeters (FIRST) survey. Using the radio cut-out images from the FIRST survey, we first designed a deep-learning model using convolutional neural networks (CNN) to classify the quasar radio morphologies into the core-only, young jet, single lobe, or triples. These radio morphologies are further sub-classified into core-dominated and lobe-dominated sources. The CNN models can classify the sources with a high precision of >98 ${{\ \rm per\ cent}}$ for all the morphological sub-classes. The average BAL fraction in the resolved core, core-dominated, and lobe-dominated quasars are consistent with the BAL fraction inferred from radio and infrared surveys. We also present the distribution of BAL quasars as a function of quasar orientation by using the radio core-dominance as an orientation indicator. A similar analysis is performed for HiBALs, LoBALs, and FeLoBALs. All the radio morphological sub-classes and BAL sub-classes show an increase in BAL fraction at high orientation angles of the jets with respect to the line of sight. Our analysis suggests that BAL quasars are more likely to be found in viewing angles close to the equatorial plane of the quasar. However, a pure orientation model is inadequate, and a combination of orientation and evolution is probably the best way to explain the complete BAL phenomena.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

An adjoint-based optimization method for jointly inverting heterogeneous material properties and fault slip from earthquake surface deformation data

SUMMARY Analysis of tectonic and earthquake-cycle associated deformation of the crust can provide valuable insights into the underlying deformation processes including fault slip. How those processes are expressed at the surface depends on the lateral and depth variations of rock properties. The effect of such variations is often tested by forward models based on a priori geological or geophysical information. Here, we first develop a novel technique based on an open-source finite-element computational framework to invert geodetic constraints directly for heterogeneous media properties. We focus on the elastic, coseismic problem and seek to constrain variations in shear modulus and Poisson’s ratio, proxies for the effects of lithology and/or temperature and porous flow, respectively. The corresponding nonlinear inversion is implemented using adjoint-based optimization that efficiently reduces the cost function that includes the misfit between the calculated and observed displacements and a penalty term. We then extend our theoretical and numerical framework to simultaneously infer both heterogeneous Earth’s structure and fault slip from surface deformation. Based on a range of 2-D synthetic cases, we find that both model parameters can be satisfactorily estimated for the megathrust setting-inspired test problems considered. Within limits, this is the case even in the presence of noise and if the fault geometry is not perfectly known. Our method lays the foundation for a future reassessment of the information contained in increasingly data-rich settings, for example, geodetic GNSS constraints for large earthquakes such as the 2011 Tohoku-oki M9 event, or distributed deformation along plate boundaries as constrained from InSAR.

Geochemistry & Geophysics↗

DOE OSTI2022

A comprehensive and fair comparison of two neural operators (with practical extensions) based on $\mathrm{FAIR}$ data

Neural operators can learn nonlinear mappings between function spaces and offer a new simulation paradigm for real-time prediction of complex dynamics for realistic diverse applications as well as for system identification in science and engineering. Herein, we investigate the performance of two neural operators, which have shown promising results so far, and we develop new practical extensions that will make them more accurate and robust and importantly more suitable for industrial-complexity applications. The first neural operator, DeepONet, was published in 2019 (Lu et al., 2019), and its original architecture was based on the universal approximation theorem of Chen & Chen (1995). The second one, named Fourier Neural Operator or FNO, was published in 2020, and it is based on parameterizing the integral kernel in the Fourier space. DeepONet is represented by a summation of products of neural networks (NNs), corresponding to the branch NN for the input function and the trunk NN for the output function; both NNs are general architectures, e.g., the branch NN can be replaced with a CNN or a ResNet. According to Kovachki et al. (2021), FNO in its continuous form can be viewed conceptually as a DeepONet with a specific architecture of the branch NN and a trunk NN represented by a trigonometric basis. In order to compare FNO with DeepONet computationally for realistic setups, we develop several extensions of FNO that can deal with complex geometric domains as well as mappings where the input and output function spaces are of different dimensions. We also develop an extended DeepONet with special features that provide inductive bias and accelerate training, and we present a faster implementation of DeepONet with cost comparable to the computational cost of FNO, which is based on the Fast Fourier Transform. Here we consider 16 different benchmarks to demonstrate the relative performance of the two neural operators, including instability wave analysis in hypersonic boundary layers, prediction of the vorticity field of a flapping airfoil, porous media simulations in complex-geometry domains, etc. We follow the guiding principles of FAIR (Findability, Accessibility, Interoperability, and Reusability) for scientific data management and stewardship. The performance of DeepONet and FNO is comparable for relatively simple settings, but for complex geometries the performance of FNO deteriorates greatly. We also compare theoretically the two neural operators and obtain similar error estimates for DeepONet and FNO under the same regularity assumptions.

42 ENGINEERING↗