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LHC hadronic jet generation using convolutional variational autoencoders with normalizing flows

Abstract In high energy physics, one of the most important processes for collider data analysis is the comparison of collected and simulated data. Nowadays the state-of-the-art for data generation is in the form of Monte Carlo (MC) generators. However, because of the upcoming high-luminosity upgrade of the Large Hadron Collider (LHC), there will not be enough computational power or time to match the amount of needed simulated data using MC methods. An alternative approach under study is the usage of machine learning generative methods to fulfill that task. Since the most common final-state objects of high-energy proton collisions are hadronic jets, which are collections of particles collimated in a given region of space, this work aims to develop a convolutional variational autoencoder (ConVAE) for the generation of particle-based LHC hadronic jets. Given the ConVAE’s limitations, a normalizing flow (NF) network is coupled to it in a two-step training process, which shows improvements on the results for the generated jets. The ConVAE+NF network is capable of generating a jet in 18.30 ± 0.04 μ s , making it one of the fastest methods for this task up to now.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The Natural Products Magnetic Resonance Database (NP-MRD) for 2025

The Natural Products Magnetic Resonance Database or NP-MRD (https://np-mrd.org) is a comprehensive, freely accessible, web-based resource for the deposition, distribution, extraction and retrieval of nuclear magnetic resonance (NMR) data on natural products. The NP-MRD was initially established to support compound de-replication and data dissemination for the natural products community. However, that community has now grown to include many users from the metabolomics, microbiomics, foodomics and nutrition science fields. Indeed, since its launch in 2021, the NP-MRD has expanded enormously in size, scope and popularity. The current version of NP-MRD now contains nearly 7X more compounds (281,859 vs. 40,908) and 7X more NMR spectra (5.1 million vs. 817,000) than the first release. More specifically, an additional 4.6 million predicted spectra and another 11,000 spectra simulated from experimental chemical shifts were deposited into the database. Likewise, the number of NMR raw spectral data depositions has grown from a 165 spectra per year to more than 10,000 per year. As a result of this expansion, the number of monthly webpage views has grown from 55 to 20,000 and the number of monthly visitors has increased from 7 to 2500. To address this growth and to better support the expanding needs of its diverse community of users, many additional improvements to the NP-MRD have been made. These include significant enhancements to the data submission process, important improvements to the visualization and display of NMR spectra, notable updates to the database’s spectral search utilities and useful additions to support better NMR spectral analysis/prediction. Significant efforts have also been undertaken to remediate and update many of NP-MRD’s database entries. This manuscript describes these database improvements and expansion efforts, along with how they have been implemented and what future upgrades to the NP-MRD are planned.

Artifical Intelligence↗

Using kernel-based statistical distance to study the dynamics of charged particle beams in particle-based simulation codes

Measures of discrepancy between probability distributions (statistical distance) are widely used in the fields of artificial intelligence and machine learning. We describe how certain measures of statistical distance can be implemented as numerical diagnostics for simulations involving charged-particle beams. Related measures of statistical dependence are also described. The resulting diagnostics provide sensitive measures of dynamical processes important for beams in nonlinear or high-intensity systems, which are otherwise difficult to characterize. Here, the focus is on kernel-based methods such as maximum mean discrepancy, which have a well-developed mathematical foundation and reasonable computational complexity. Several benchmark problems and examples involving intense beams are discussed. While the focus is on charged-particle beams, these methods may also be applied to other many-body systems such as plasmas or gravitational systems.

47 OTHER INSTRUMENTATION↗

Spatiotemporal Automatic Calibration of Infrastructure Lidar, Radar, and Camera with a Global Navigation Satellite System

Robust and accurate perception is important for modern intelligent transportation systems (ITS), which use sensors of various modalities for data fusion to create a digital twin of an intersection. Sensor calibration is an important process that creates a unified coordinate frame for the sensor output data so that it can be used for data fusion. Classical approaches for sensor calibration are time-consuming, require an overlapping field of view for feature matching, and are not feasible for ITS application as they cause disruptions in the flow of traffic. In this paper, we present a spatiotemporal automatic calibration approach to calibrate multiple infrastructure lidar, radar, and cameras installed at a traffic intersection. The approach uses global navigation satellite system (GNSS) positioning information shared by connected vehicles, and when the vehicle is detected by the sensor, we match the sensor detections with the GNSS coordinates. The proposed algorithm is evaluated with a real-world dataset utilizing detections from two radars, cameras, and lidars with a test vehicle instrumented with a post-processing kinematic (PPK)-corrected GNSS driving past the sensors installed at a four-way traffic intersection. The experimental results show that the proposed automatic calibration approach can achieve the transformation with a root mean squared error of less than 0.5 for radar and lidar and less than 2 for camera detections. The ability to rapidly calibrate sensors not only benefits initial installations, but can also be used for system health monitoring, while utilizing available connected vehicle data to test the real-time sensor fidelity and operational status.

ADVANCED PROPULSION SYSTEMS,ENERGY CONSERVATION, C↗

An integrative framework reveals widespread gene flow during the early radiation of oaks and relatives in Quercoideae (Fagaceae)

ABSTRACT Although the frequency of ancient hybridization across the Tree of Life is greater than previously thought, little work has been devoted to uncovering the extent, timeline, and geographic and ecological context of ancient hybridization. Using an expansive new dataset of nuclear and chloroplast DNA sequences, we conducted a multifaceted phylogenomic investigation to identify ancient reticulation in the early evolution of oaks (Quercus). We document extensive nuclear gene tree and cytonuclear discordance among major lineages ofQuercusand relatives in Quercoideae. Our analyses recovered clear signatures of gene flow against a backdrop of rampant incomplete lineage sorting, with gene flow most prevalent among major lineages ofQuercusand relatives in Quercoideae during their initial radiation, dated to the Early‐Middle Eocene. Ancestral reconstructions including fossils suggest ancestors ofCastanea + Castanopsis,Lithocarpus, and the Old World oak clade probably co‐occurred in North America and Eurasia, while the ancestors ofChrysolepis, Notholithocarpus, and the New World oak clade co‐occurred in North America, offering ample opportunity for hybridization in each region. Our study shows that hybridization—perhaps in the form of ancient syngameons like those seen today—has been a common and important process throughout the evolutionary history of oaks and their relatives. Concomitantly, this study provides a methodological framework for detecting ancient hybridization in other groups.

Biochemistry & Molecular Biology↗

Separating Oil-Water Mixtures Using Bump Arrays

Particle separation is an important process step across many fields. One technique being applied for separating solids such as blood components or sand particles from carrier fluids is the use of arrays of aligned posts called deterministic lateral arrays to bump particles to one side in the flow stream to enhance separation. This technique may be useful for separation of deformable particles. The ability to efficiently separate two-phase industrial (oil/water) mixtures is key for future use of valuable resources. Over 1 trillion gallons of petroleum production water could be reclaimed annually for reuse in the drought-ridden western US states. The ability to reclaim this petroleum production water may be critical for the Central High Plains (Colorado, Kansas, Oklahoma, Texas, and New Mexico). Trends in just the High Plains area already lost 20 to 25% of the irrigated farming area due to insufficient ground water storage to irrigate, and farmland losses are expected to grow to 40%. Proving this technology is key to reuse of petroleum production water for crop irrigation or to replace water from currently failing aquifers in rich agricultural lands of the Central High Plains. We conducted experiments applying mesofluidic separation for flowing two-phase (oil/water) mixtures. Experiments were conducted using oils of differing viscosities with water as the carrier fluid; separation was achieved over a range of oil-water concentrations. We describe the results of these experiments in this paper.

oil-water separation, micelle, droplet separation,↗

Novel, active, and uncultured hydrocarbon-degrading microbes in the ocean

ABSTRACT Given the vast quantity of oil and gas input to the marine environment annually, hydrocarbon degradation by marine microorganisms is an essential ecosystem service. Linkages between taxonomy and hydrocarbon degradation capabilities are largely based on cultivation studies, leaving a knowledge gap regarding the intrinsic ability of uncultured marine microbes to degrade hydrocarbons. To address this knowledge gap, metagenomic sequence data from the Deepwater Horizon (DWH) oil spill deep-sea plume was assembled to which metagenomic and metatranscriptomic reads were mapped. Assembly and binning produced new DWH metagenome-assembled genomes that were evaluated along with their close relatives, all of which are from the marine environment (38 total). These analyses revealed globally distributed hydrocarbon-degrading microbes with clade-specific substrate degradation potentials that have not been reported previously. For example, methane oxidation capabilities were identified in all Cycloclasticus . Furthermore, all Bermanella encoded and expressed genes for non-gaseous n -alkane degradation; however, DWH Bermanella encoded alkane hydroxylase, not alkane 1-monooxygenase. All but one previously unrecognized DWH plume member in the SAR324 and UBA11654 have the capacity for aromatic hydrocarbon degradation. In contrast, Colwellia were diverse in the hydrocarbon substrates they could degrade. All clades encoded nutrient acquisition strategies and response to cold temperatures, while sensory and acquisition capabilities were clade specific. These novel insights regarding hydrocarbon degradation by uncultured planktonic microbes provides missing data, allowing for better prediction of the fate of oil and gas when hydrocarbons are input to the ocean, leading to a greater understanding of the ecological consequences to the marine environment. IMPORTANCE Microbial degradation of hydrocarbons is a critically important process promoting ecosystem health, yet much of what is known about this process is based on physiological experiments with a few hydrocarbon substrates and cultured microbes. Thus, the ability to degrade the diversity of hydrocarbons that comprise oil and gas by microbes in the environment, particularly in the ocean, is not well characterized. Therefore, this study aimed to utilize non-cultivation-based ‘omics data to explore novel genomes of uncultured marine microbes involved in degradation of oil and gas. Analyses of newly assembled metagenomic data and previously existing genomes from other marine data sets, with metagenomic and metatranscriptomic read recruitment, revealed globally distributed hydrocarbon-degrading marine microbes with clade-specific substrate degradation potentials that have not been previously reported. This new understanding of oil and gas degradation by uncultured marine microbes suggested that the global ocean harbors a diversity of hydrocarbon-degrading bacteria, which can act as primary agents regulating ecosystem health.

Howe, Kathryn L.↗

Linking impact melt redox with crustal weathering regime

Abstract Impact melting and outgassing of impact melts were important processes shaping the crust and atmosphere of early Earth and Mars. The redox state of impact melts influences the gases they release, but the controls on impact melt redox are not well understood. Here, we present Fe micro–X-ray absorption near edge structure (μ-XANES) measurements of a suite of impact melt glasses from Lonar crater, India. As an impact into continental flood basalts, Lonar crater is an ideal analog for impacts into basaltic crust on early Earth and Mars. The Fe-μ-XANES technique permits robust characterization of the Fe3+/ΣFe ratio and therefore redox conditions in Lonar glasses. We found a range in Fe3+/ΣFe of 0.21–0.49 among Lonar glasses, including substantial intraclast variations. We conclude that a primary factor driving these variations was pre-impact oxidative weathering of target rocks. The coupling between crustal weathering regime and speciation of gases released from impact melts implies that impact melt outgassing could act as a feedback mechanism to reinforce prevailing surface redox conditions.

Geology↗

Characterization of a Low-Temperature Plasma (LTP) Ambient Ionization Source Using Temporally Resolved Monochromatic Imaging Spectrometry

The low-temperature plasma (LTP) probe is a common plasma-based source used for ambient desorption–ionization mass spectrometry (MS). While the LTP probe has been characterized in detail with MS, relatively few studies have used optical spectroscopy. In this paper, two-dimensional (2D) imaging at selected wavelengths is used to visualize important species in the LTP plasma jet. First, 2D steady-state images of the LTP plume for N 2 + (391.2 nm), He I (706.5 nm), and N 2 (337.1 nm) emissions were recorded under selected plasma conditions. Second, time-resolved 2D emission maps of radiative species in the LTP plasma jet were recorded through the use of a 200 ns detection gate and varying gate delays with respect to the LTP trigger pulse. Emission from He I, N 2 + , and N 2 in the plasma jet region was found to show a transient behavior (often referred to as plasma bullets) lasting only a few microseconds. The N 2 + and He I maps were highly correlated in spatial and temporal structure. Further, emission from N 2 showed two maxima in time, one before and one after the maximum emission for N 2 + and He I, due to an initial electronic excitation wave and ion–electron recombination, respectively. Third, the interaction of the LTP probe with a sample substrate and an electrically grounded metallic needle was studied. Emission from a fluorophore on the sample substrate showed an initial photon-induced excitation from plasma-generated photons followed by electronic excitation by other plasma species. The presence of a grounded needle near the plasma jet significantly extended the plasma jet lifetime and also generated a long-lived corona discharge on the needle. The effect of LTP operating parameters on emission spectra was correlated with mass-spectral results including reagent-ion signals. Lastly, five movies provide a side-by-side comparison of the temporal behavior of emitting species and insights into the interactions of the emission clouds with a sample surface as well as an external needle. Temporally and spatially resolved imaging provided insights into important processes in the LTP plasma jet, which will help improve analyte ion sampling in LTP–MS.

Chan, George C. -Y.↗

Water Imbibition and Oil Recovery in Shale: Dynamics and Mechanisms Using Integrated Centimeter-to-Nanometer-Scale Imaging

Water imbibition, and the associated oil displacement, is an important process in shale oil reservoirs after hydraulic fracturing and in water-based enhanced oil recovery (EOR). Current techniques for water imbibition measurement are mostly “black-box”-type methods. A more explicit understanding of the water imbibition/oil recovery dynamics and geological controls is in demand. In this paper, a multiscale imaging technique that covers centimeter to nanometer scale (i.e., core to pore scale), integrating neutron radiography, microcomputed tomography (micro-CT), and scanning electron microscope (SEM) is applied to investigate the water imbibition depth and rate and the cause of heterogeneity of imbibition in shale samples. The dynamic processes of water imbibition in the 1-in. (25.4-mm) core sample were explicitly demonstrated, and the imbibition along the matrix and imbibition through microfractures are distinguished through neutron radiography image analysis. The causes of observed imbibition heterogeneity were further investigated through micro-CT and SEM image analysis for 1.5-mm diameter miniplug samples from different laminas of the 1-in. core samples. Imbibition depth and rate were calculated on the basis of image analysis as well. Estimation of oil recovery through water imbibition in shale matrix was performed for an example shale field. Here this innovative and integrated multiscale imaging technique provides a “white/gray-box” method to understand water imbibition and water-oil displacement in shale. The wide span of the length scale (from centimeter to nanometer) of this technique enables a more comprehensive, accurate, and specific understanding of both the core-scale dynamics and pore-scale mechanisms of water imbibition, oil recovery, and matrix-fracture interaction.

04 OIL SHALES AND TAR SANDS↗

Pore-Scale Study on the Positive Feedback Between Stress and Porosity Caused by Pressure Solution in Porous Media

Pressure solution is an important process in the evolution of sedimentary rocks, which provide storage space for most of our petroleum resources. It directly influences the generation, migration, and storage of petroleum fluids in subsurface sedimentary rocks. Here, in this paper, we develop a pore-scale, mechanochemical model to demonstrate a possible positive feedback between the local porosity and pore surface stress, in which a higher local porosity causes a higher local pore surface stress, thus enhancing pressure solution and consequently further increasing the local porosity. Pore surface stress represents stress on a solid grain adjacent to a pore. Specifically, the pore-scale, mechanochemical model directly simulates the stress distribution over solid and pore surfaces using a finite element model. The dissolution of solids at the solid-pore interfaces under a far-from-equilibrium condition is simulated using a first-order kinetics model that accounts for the local stress distribution. The updated pore geometry, caused by pore surface dissolution, is then used in the stress simulation in the next numerical iteration. Two types of porous media, the Oriskany sandstone and an artificial porous medium with spherical pores, were tested in the mechanochemical simulation. The positive stress-porosity feedback during pressure solution was observed in both samples. In addition, the model quantitatively illustrated the distribution of local mineral dissolution rates on all pore surfaces, as well as its relation to the effective mineral dissolution rate of the entire sample. Based on the comparison between the two porous media, the local mineral dissolution was regulated by pore space distribution, geometry, and coalescence during pressure solution. This work is the first that uses direct, pore-scale numerical simulation to demonstrate the positive stress-porosity feedback during pressure solution, which has the potential to advance the understanding of the mechanical-chemical (MC) coupling in many geological processes that are relevant to subsurface energy systems, such as the recovery of petroleum hydrocarbons and geothermal energy.

CT scanning↗

RAVEN User Manual

RAVEN is a generic software framework to perform parametric and probabilistic analysis based on the response of complex system codes. The initial development was aimed to provide dynamic risk analysis capabilities to the Thermo-Hydraulic code RELAP-7, currently under development at the Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose probabilistic and uncertainty quantification platform, capable to agnostically communicate with any system code. This agnosticism includes providing Application Programming Interfaces (APIs). These APIs are used to allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by inputs files or via python interfaces. RAVEN is capable of investigating the system response, and investigating the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused to- ward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. The development of RAVEN has started in 2012, when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework became stronger. RAVEN principal assignment is to provide the necessary software and algorithms in order to employ the concept developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just the individuation of the frequency of an event potentially leading to a system failure, but the closeness (or not) to key safety-related events. Hence, the approach is interested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. for an important process such as peak pressure in a pipe) is exceeded under certain conditions. The initial development of RAVEN has been focused on providing dynamic risk assessment capability to RELAP-7, currently under development at the INL and, likely, future replacement of the RELAP5-3D code. Most the capabilities that have been implemented having RELAP-7 as principal focus are easily deployable for other system codes. For this reason, several side activates are currently ongoing for coupling RAVEN with soft- ware such as RELAP5-3D, etc. The aim of this document is the explanation of the input requirements, focalizing on the input structure.

97 MATHEMATICS AND COMPUTING↗

Fission Product Yields of 233 U and 239 Pu by Neutron-Induced Fission at Neutron Energies from 0.18-140 MeV [Slides]

Nuclear fission is an important process with applications in astrophysics, nuclear reactors, and stockpile stewardship. Despite having been discovered over 80 years ago, fission is not fully described by a predictive model. This study will show fission product mass yields and total kinetic energies (TKE) across a large range of incident neutron energies for future refinement of fission models. 233U(n,f) data is used to verify features and structures on a previous experiment and compared against fission models. 239Pu(n,f) data will be analyzed to show new data at higher neutron energies using techniques to handle fission in the presence of alphas. 252Cf(sf) data will be used for calibration and benchmarking with a thin-backed target.

07 ISOTOPE AND RADIATION SOURCES↗

Irradiation creep model for α-Fe: Dislocation climb in the presence of stress fields (Final Report)

Irradiation creep is known to be an important process for structural materials in nuclear environments, potentially leading to creep failure at temperatures where thermal creep is generally negligible. While there is a great deal of data for irradiation creep in steels and zirconium alloys in light water reactor conditions, much less is known for first wall materials under fusion energy conditions. Lacking suitable fusion neutron sources for detailed experimentation, modeling, and simulation can help bridge the dose-rate and spectral-effects gap and produce quantifiable expectations for creep deformation of first wall materials under standard fusion conditions. In this work, we present a comprehensive model for irradiation creep created from merging a crystal plasticity representation of the dislocation microstructure and a defect evolution simulator that accounts for the entire cluster dimensionality space. Both approaches are linked by way of a climb velocity that captures dislocation-biased defect absorption and a dislocation strengthening term that reflects the accumulation of defect clusters in the system. We carry out our study in Fe under first wall fusion reactor conditions, characterized by a fusion neutron spectrum at temperatures between 300 and 800°K.

36 MATERIALS SCIENCE↗

Collaborative Research: Parametric Instabilities of Alfven Waves in Low‐beta Plasmas

Alfven waves are of fundamental importance in magnetized plasmas. This project aims to advance our understanding of the basic physics of the parametric instabilities of Alfven waves using advanced computer simulations. The results will have implications for important processes in the heliosphere involving Alfven waves, such as coronal heating and solar wind heating.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Single Primary Heat Extraction and Removal Emulator (SPHERE) Long Duration Testing

For heat-pipe cooled microreactor development, it is essential to understand the characteristics of heat pipes and how they function under a wide range of operating conditions. An important process for heat-pipe cooled microreactor development is the passive heat removal and how the performance may change over long periods of time. Increased experimental data provides additional information to assess the operational lifetime of alkali metal heat pipes. Idaho National Laboratory has completed testing over a long duration of a high-performance sodium filled heat pipe while monitoring axial temperature profile, power supplied by the heaters, and heat removed by a gas-gap calorimeter. The results from this testing can aid in heat pipe validation efforts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Bubble Mass Transport Measurement in the Large-Scale Test Loops at Oak Ridge National Laboratory

Molten salts are complex fluids that incorporate multi-phase behavior depending on the chemistry and the physical properties of the entrained components. These components include the carrier salt, the actinide fuel, and fission, activation, and corrosion products, the concentrations of which depends on the burnup history of the salt. Radionuclide transport from the salt into the cover gas / off-gas system depends on volatility as predicted by thermochemistry, but data from the Molten Salt Reactor Experiment (MSRE) conducted in the late 1960s suggest that bubble formation and transport are also important. Anomalously high fractions of noble metals were found in the off-gas system and were attributed to transportation with parent salt aerosols and their association with rising noble gas bubbles. The prediction of such phenomena requires coupled neutronic, thermal hydraulic, and chemical equilibrium calculations, the framework of which is being developed within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program supported by the US Department of Energy (DOE) Office of Nuclear Energy (NE). However, separate effects tests and models of experiments using tools such as SAM and Thermochimica can guide model developers through important processes. Conversely, model development guides the choice of experiments and systems to provide data that are relevant for validation. This report describes several experiments that tracked gas transport in molten salts, ranging from small-scale systems to large-scale loops. Gas transportation in a molten salt, LiCl-KCl, has been studied using the shadowgraph technique. Sensors such as residual gas analysis, Raman spectroscopy, and laser-induced breakdown spectroscopy have been tested for off-gas measurements. These data were used to interpret how the gases move through the upstream salt / cover gas and the interface between them. Differential pressure measurements were able to detect individual gas bubbles as they popped at the liquid–gas interface. Salt aerosols were collected on a cascade impactor. Their formation was also observed directly via the shadowgraph method, and most of these aerosols were launched ballistically into the cover gas. Fine mists could also be observed. Convection currents through the salt were visualized and can be used to calculate the thermophysical properties of the salt itself. The apparatuses described in this report and in a previous work (McFarlane et al. 2023) have been commissioned and are available for use in making further measurements of salt/surrogate fission product behavior. Novel approaches using neutron imaging are planned for the study of fluoride salts, which cannot be contained in quartz, so shadowgraph visualization is not available. Bubble transport in convective flow and in a slow-moving salt column are planned. The mobile laser-induced breakdown spectroscopy (LIBS) system is available for several applications, including iodine capture in a molten hydroxide scrubber, H2 transport though molten salts to complement Raman analysis, and online tracking of salt aerosol generation, transport, and deposition. This report summarizes the findings from FY24 and the plans for FY25. The work completes milestone M2AT-24OR0702013 of the DOE-NE Advanced Reactor Technology, Molten Salt Reactor Campaign, DOE-NE-5.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗