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DOE OSTI2025

2032 and 2036 risk enhancement from NEOs in the Taurid stream: Is there a significant coherent component to impact risk?

Impact risk is normally quantified by summing the product of the probability of an event and some measure of its consequences over the set of all possible events. The probability factor is considered to be more objective and is based on the size frequency distribution of Near Earth objects (NEOs) and an implicit assumption of randomness, which can be described as “stochastic risk”. Impact frequency does change with time, however, and there have been episodes in the deep geological past when the flux has been much higher. The hypothesis of “coherent catastrophism” suggests large variations on shorter timescales. It postulates the existence of a “Taurid resonant swarm” (TRS) of debris associated with Comet Encke that is stabilized by Jupiter and in a 7:2 resonance with it. The hypothetical cluster orbits in the broad Taurid stream, which crosses Earth's orbit twice a year at its nodes. Whereas the most extreme and fanciful versions of coherent catastrophism in recent geologic history have been comprehensively refuted, the possibility of a significant component of coherent (time-dependent) risk, associated with non-random correlated events, remains. This paper incorporates recently published data from observational campaigns associated with the Taurid stream. There is no evidence for objects in the Taurid stream that are above the global catastrophe threshold, but the possibility of a few large objects and a significant population of objects the size of the Chelyabinsk or Tunguska bodies has not been eliminated. Eyewitness accounts and comparison of airburst models to ground truth suggest that the Tunguska object was a Beta Taurid. The Tunguska event is probably an outlier when compared to the size frequency distributions under stochastic assumptions, but if there is a significant coherent component it may be representative of events that take place far more frequently, and risk assessments may have underestimated the contribution from airbursts. If so, the Earth will experience increased risk from objects this size, peaking in November 2032 and June 2036. We recommend targeted survey campaigns during these hypothetical TRS node crossings to quantify the population, search for potentially hazardous objects, and identify imminent impactors.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Grass(stage)root movement to ensure future resilience of longleaf pine ecosystems

Recent interest in restoring longleaf pine ecosystems highlights the need for an improved understanding, appreciation, and consideration of longleaf pine’s unique life history compared to other southern pines. Longleaf pine ecosystems are considered more resilient than other southern pine ecosystems and the attributes that confer this resilience may be related to belowground carbon allocation patterns that occur during the seedling stage of its life history where it exists for years in a grass stage. The long residence time spent in the grass stage has impeded adoption of longleaf pine by landowners for decades, which has resulted in efforts to expedite emergence from the grass stage through silviculture, nursery production, and selection breeding techniques; however, expedited emergence may come at the expense of root and belowground carbohydrate storage reserve development —traits that purportedly enhance longleaf pine tree and ecosystem resilience relative to other southern pine species. Furthermore, I caution that efforts to expedite longleaf pine emergence from the grass stage also consider the potential implications on belowground carbon allocation and identify research priorities to help facilitate the improvement of longleaf pine seedling silviculture, nursery production, and breeding in a way that ensures the maintenance of attributes linked to resilience.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Recombination smooths the time-signal disrupted by latency in within-host HIV phylogenies

Within-host HIV evolution involves several features that may disrupt standard phylogenetic reconstruction. One important feature is re-activation of latently integrated provirus, which has the potential to disrupt the temporal signal, leading to variation in the branch lengths and apparent evolutionary rates in a tree. Yet, real within-host HIV phylogenies tend to show clear, ladder-like trees structured by the time of sampling. Another important feature is recombination, which violates the fundamental assumption that evolutionary history can be represented by a single bifurcating tree. Thus, recombination complicates the within-host HIV dynamic by mixing genomes and creating evolutionary loop structures that cannot be represented in bifurcating trees. In this paper, we develop a coalescent-based simulator of within-host HIV evolution that includes latency, recombination, and effective population size dynamics that allows us to study the relationship between the true, complex genealogy of within-host HIV evolution, encoded as an Ancestral Recombination Graph (ARG), and the observed phylogenetic tree. To compare our ARG results to the familiar phylogeny format, we calculate the expected bifurcating tree after decomposing the ARG into all unique site trees, their combined distance matrix, and the overall corresponding bifurcating tree. While latency and recombination separately disrupt the phylogenetic signal, remarkably, we find that recombination recovers the temporal signal of within-host HIV evolution caused by latency by mixing fragments of old, latent genomes into the contemporary population. In effect, recombination averages over extant heterogeneity, whether it stems from mixed time-signals or population bottlenecks. Further, we establish that the signals of latency and recombination can be observed in phylogenetic trees despite being an incorrect representation of the true evolutionary history. Using an Approximate Bayesian Computation method, we develop a set of statistical probes to tune our simulation model to nine longitudinally-sampled within-host HIV phylogenies. Because ARGs are exceedingly difficult to infer from real HIV data, our simulation system allows investigating effects of latency, recombination, and population size bottlenecks by matching decomposed ARGs to real data as observed in standard phylogenies.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Machine learning surrogate of physics-based building-stock simulator for end-use load forecasting

Building energy models are used to simulate heat and mass transfer and estimate end-use load in buildings. With the proliferation of solar photovoltaics on residential and commercial buildings, increasingly, buildings are expected to provide grid services, for which accurate and computationally efficient building energy simulations and end-use load prediction are imperative. Existing building energy simulation tools, however, have significant computational overhead that make them less practical in real-time deployment for optimization, design, uncertainty quantification and control in building energy management systems. Here this article presents a data-driven machine learning model based on light gradient boosting method (LightGBM) as a surrogate for a physics-based simulator for residential buildings to predict end-use load. The machine learning based surrogate model accounts for time-series related variables, seasonality and trend component of end-use load, and history of end-use load. The accuracy of the surrogate model is assessed on the prediction of the load profiles of 100 different houses in Cook County, Illinois, USA. The LightGBM surrogate model is shown to reduce the root-mean-squared error by 53% relative to a reference decision tree (DT) based model reported previously in the literature. Moreover, the model predicts the load spikes and high-ramp rate events throughout the year which are often the Achilles heel of other models in the literature. The machine learning based surrogate model is demonstrated to be computationally efficient, with a ten-fold reduction in the computational time compared to a physics-based building energy simulation, and suitable for uncertainty analysis and real-time control of building characteristics in response to uncertainty.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Cryogenic electronics for noble liquid neutrino detectors

In this paper we present the general features of cryogenic (or “cold”) electronics for noble liquid time projection chambers, with design principles and details for neutrino physics, a brief history of the technology and details of recent research and development that is driving the design of the detectors under construction. Finally, some comments on future R&D envisioned and the impact of this work on other fields is described. “Cold” in the context of this work applies to CMOS devices operated at 77 K and above, at liquids temperatures of LAr (89 K), LKr (125 K) and LXe (165 K), with most of the tests performed in, or at LN 2 (77 K). Additionally, the paper is concentrated on the design of cold electronics for large liquid argon TPCs, those that have been successfully operated, MicroBooNE and ProtoDUNE, and those designed or under construction, such as SBND and DUNE first and second 10 kton modules. The high performance achieved with MicroBooNE and ProtoDUNE – a high signal-to-noise ratio combined with high stability of response – is mainly due to the integral approach to design and construction of sensing electrodes with cold readout electronics in a modular approach with the cryostat signal feed-throughs incorporating warm interface electronics into a Faraday cage with the cryostat. The integral concept is described in some detail in this paper.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

Modeling Ring Current Proton Fluxes Using Artificial Neural Network and Van Allen Probe Measurements

Abstract Terrestrial ring current dynamics are a critical part of the near‐space environment, in that they directly drive geomagnetic field variations that control particle drifts, and define geomagnetic storms. The present study aims to specify a global and time‐varying distribution of ring current proton using geomagnetic indices and solar wind parameters with their history as input. We train an artificial neural network (ANN) model to reproduce proton fluxes measured by the Radiation Belt Storm Probes Ion Composition Experiment instrument onboard Van Allen Probes. By choosing optimal feature parameters and their history length, the model results show a high correlation and a small error between model specifications and satellite measurements. The modeled results well capture energy‐dependent proton dynamics in association with geomagnetic storms, including inward radial diffusion, acceleration and decay. Our ANN model produces proton fluxes with their corresponding 3D spatiotemporal variations, capturing the latitudinal distribution and local time asymmetry that are consistent with observations and that can further inform theory.

Li, Jinxing↗

DOE OSTI2025

Multimodality in the Search for New Physics in Pulsar Timing Data and the Case of Kination-amplified Gravitational-wave Background from Inflation

We investigate the kination-amplified inflationary gravitational-wave background (GWB) interpretation of the signal recently reported by various pulsar timing array (PTA) experiments. Kination is a post-inflationary phase in the expansion history dominated by the kinetic energy of some scalar field, characterized by a stiff equation of state w = 1. Within the inflationary GWB model, we identify two modes that can fit the current data sets (NANOGrav and EPTA) with equal likelihood: the kination-amplification (KA) mode and the ordinary, no-kination-amplification (no-KA) mode. The multimodality of the likelihood motivates a Bayesian analysis with nested sampling. We analyze the free spectra of current PTA data and mock free spectra constructed with higher signal-to-noise ratios using nested sampling. The analysis of the mock spectrum designed to be consistent with the best fit to the NANOGrav 15 yr (NG15) data successfully reveals the expected bimodal posterior for the first time while excluding the reheating mode that appears in the fit to the current NG15 data, making a case for our correct and comprehensive treatment of potential multimodal posteriors arising from future PTA data sets. The resultant Bayes factor is $\mathcal{B}$ $\equiv$ Z no–KA /Z KA = 2.9 ± 1.9, indicating comparable statistical significance between the two modes. Given the theoretical model-building challenges of producing highly blue-tilted primordial tensor spectra, the KA mode has the advantage of requiring less blue primordial spectra, compared with the no-KA mode. The synergy between future cosmic microwave background polarization, pulsar timing, and laser interferometer measurements of gravitational waves will help resolve the ambiguity implied by the multimodal posterior in PTA-only searches.

Cosmology↗

DOE OSTI2023

Optimal Frequency-domain Analysis for Spacecraft Time Series: Introducing the Missing-data Multitaper Power Spectrum Estimator

While the Lomb–Scargle periodogram is foundational to astronomy, it has a significant shortcoming: the variance in the estimated power spectrum does not decrease as more data are acquired. Statisticians have a 60 yr history of developing variance-suppressing power spectrum estimators, but most are not used in astronomy because they are formulated for time series with uniform observing cadence and without seasonal or daily gaps. Here we demonstrate how to apply the missing-data multitaper power spectrum estimator to spacecraft data with uniform time intervals between observations but missing data during thruster fires or momentum dumps. The F-test for harmonic components may be applied to multitaper power spectrum estimates to identify statistically significant oscillations that would not rise above a white noise–based false alarm probability. Multitapering improves the dynamic range of the power spectrum estimate and suppresses spectral window artifacts. We show that the multitaper–F-test combination applied to Kepler observations of KIC 6102338 detects differential rotation without requiring iterative sinusoid fitting and subtraction. Significant signals reside at harmonics of both fundamental rotation frequencies and suggest an antisolar rotation profile. Next we use the missing-data multitaper power spectrum estimator to identify the oscillation modes responsible for the complex "scallop-shell" shape of the K2 light curve of EPIC 203354381. We argue that multitaper power spectrum estimators should be used for all time series with regular observing cadence.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Genetic variation associated with adult migration timing in lineages of Steelhead and Chinook Salmon in the Columbia River

Abstract With the discovery of a major effect region (GREB1L, ROCK1) for adult migration timing in genomes of both Chinook Salmon and Steelhead, several subsequent studies have investigated the effect size and distribution of early and late migration alleles among populations in the Columbia River. Here, we synthesize the results of these studies for the major lineages of Chinook Salmon and Steelhead that include highly distinct groups in the interior Columbia River that exhibit atypical life histories from most coastal lineage populations of these two species. Whole‐genome studies with high marker density have provided extensive insight into SNPs most associated with adult migration timing, and suites of markers for each species have been genotyped in large numbers of individuals to further validate phenotypic effects. For Steelhead, the largest phenotypic effect sizes have been observed in the coastal lineage (36% of variation for passage timing at Bonneville Dam; 43% of variation for tributary arrival timing) compared to the inland lineage (7.5% of variation for passage timing at Bonneville Dam; 8.4% of variation for tributary arrival timing) that overwinter in freshwater prior to spawning. For Chinook Salmon, large effect sizes have been observed in all three lineages for multiple adult migration phenotypes (Coastal lineage: percentage of variation of 27.9% for passage timing at Bonneville Dam, 28.7% for arrival timing for spawning; Interior ocean type: percentage of variation of 47.6% for passage timing at Bonneville Dam, 39.6% for tributary arrival timing, 77.9% for arrival timing for spawning; Interior stream type: percentage of variation of 35.3% for passage at Bonneville Dam, 9.8% for tributary arrival timing, 4.7% for arrival timing for spawning). Together, these results have extended our understanding of genetic variation associated with life history diversity in distinct populations of the Columbia River, however, much research remains necessary to determine the causal mechanism for this major effect region on migration timing in these species.

Narum, Shawn R.↗

DOE OSTI2021

Decreased land use intensity improves surface soil quality on marginal lands

The Conservation Reserve Program (CRP) has been a major factor in land transitions out of intensive row-crop management on marginally productive lands in the central United States. While CRP can protect these more environmentally sensitive lands against erosion and potential nutrient loss, information on how CRP affects soil quality over time is limited. Using a chronosequence with 0–40 yr of CRP conversion history, we evaluated soil quality under different land use intensities (CRP, pasture, row crop) using the Soil Management Assessment Framework (SMAF). Effects of slope classes (higher [14–25%] and lower [2–14%]) and soil depth (0–120 cm) were also evaluated. Our results show that the soils were functioning at 84 and 78% of their theoretical capacity under CRP and row crop, respectively. Conversion to CRP enhanced overall soil quality by increasing soil biological, physical, and chemical attributes, but soil nutrient availability decreased due to the absence of fertilizer application. Increasing soil organic C (SOC) enhanced overall soil quality because of its impact on soil biological, physical, chemical, and nutrient conditions. Conversion to CRP will likely have greater benefits for more environmentally sensitive soils (i.e., higher slope) as demonstrated by structural equation modeling. Land use effects were also depth dependent, with more prominent effects within the 0-to-5-cm than the 5-to-15-cm depth increment. Overall, our methods focused on key soil quality indicators, confirmed ecological benefits of CRP conversion, and provided guidance for improved and simplified land management recommendations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Illitization in the Mt. Simon Sandstone, Illinois Basin, USA: Implications for carbon dioxide storage

Clay mineral cementation is one of the most important controls on sandstone reservoir properties. Here, in this paper, the diagenetic history of the Mt. Simon reservoir complex is studied to reveal the origin, timing, and controls of illitization. Samples of sandstone and shale from Mt. Simon reservoir complex were acquired from the Illinois Basin–Decatur Project (IBDP), a CO 2 storage demonstration project in the central Illinois Basin. Petrographic, SEM, TEM, XRD analyses and K/Ar age dating were completed to identify the major detrital and diagenetic components of the samples and reveal illite to be the major clay component in all samples. Illitic clay coatings in the lower Mt. Simon reservoir are identified as a major control on reservoir properties by inhibiting major precipitation of authigenic quartz during illitization, resulting in highly permeable sandstone, essential for CO 2 storage. The coating box-work morphology and mineralogy are indicative of a detrital smectite origin with subsequent illite growth associated with feldspar dissolution and kaolinite alteration. The mineralogy of bulk material and separate grain size fractions (2–0.6 μm; 0.6–0.2 μm; < 0.2 μm) with illite polytypes 2M 1 , 1M, and 1M d were quantified and age dated via 40 K- 40 Ar methods. The shales or reservoir seals contain the highest proportions of detrital illite with illite in the lower Mt. Simon Sandstone reservoir identified as solely diagenetic. Two major events of illitization are identified throughout the Mt. Simon with more porous reservoir rock exhibiting the older event from approximately 360 to 315 Ma and tighter sandstone units with reservoir properties too low to be considered reservoir exhibiting illite dates from 250 to 220 Ma. This partitioning of illitization is attributed to varied mineralogy controlled by depositional changes and evolution of the greater basin.

58 GEOSCIENCES↗

DOE OSTI2023

The confluence of machine learning and multiscale simulations

Multiscale modeling has a long history of use in structural biology, as computational biologists strive to overcome the time- and length-scale limits of atomistic molecular dynamics. Contemporary machine learning techniques, such as deep learning, have promoted advances in virtually every field of science and engineering and are revitalizing the traditional notions of multiscale modeling. Deep learning has found success in various approaches for distilling information from fine-scale models, such as building surrogate models and guiding the development of coarse-grained potentials. However, perhaps its most powerful use in multiscale modeling is in defining latent spaces that enable efficient exploration of conformational space. In conclusion, this confluence of machine learning and multiscale simulation with modern high-performance computing promises a new era of discovery and innovation in structural biology.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Turning points in the age–metallicity relations – created by late satellite infall and enhanced by radial migration

ABSTRACT The present-day age–metallicity relation (AMR) is a record of the star formation history of galaxies, as this traces the chemical enrichment of the gas over time. We use a zoomed-in cosmological simulation that reproduces key signatures of the Milky Way (MW), g2.79e12 from the NIHAO-UHD project, to examine how stellar migration and satellite infall shape the AMR across the disc. We find in the simulation, similar to the MW, the AMR in small spatial regions (R, z) shows turning points that connect changes in the direction of the relations. The turning points in the AMR in the simulation are a signature of late satellite infall. This satellite infall has a mass radio similar as that of the Sagittarius dwarf to the MW (∼0.001). Stars in the apex of the turning points are young and have nearly not migrated. The late satellite infall creates the turning points via depositing metal-poor gas in the disc, triggering star formation of stars in a narrow metallicity range compared to the overall AMR. The main effect of radial migration on the AMR turning points is to widen the metallicity range of the apex. This can happen when radial migration brings stars born from the infallen gas in other spatial bins, with slightly different metallicities, into the spatial bin of interest. These results indicate that it is possible that the passage of the Sagittarius dwarf galaxy played a role in creating the turning points that we see in the AMR in the Milky Way.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Mini Report: LLMs for Vulnerability Repair in Code

Software vulnerability repair is a notoriously difficult task that is both time consuming and labor intensive. While research into this area has a long history, the recent successes of large language models (LLMs) across many tasks have also spurred efforts to leverage LLM capabilities for automated software vulnerability repair. Currently, there are limitations in the capabilities of LLMs to fix bugs and insufficiently addressed problems in the evaluations of these studies may cause performance to not transfer when they are used in practice. Additionally, most research in the area treats finding and fixing bugs as separate concerns - how to best combine all the subtasks involved in removing vulnerabilities from code remains an open question. In this report, we summarize our findings and opinions on the current state of the art in LLM-assisted code vulnerability repair, highlighting current unresolved problems in the field as well as potential applications and future research.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Gravitational Waves from Black Holes in Merging Ultra-Dwarf Galaxies

The origin of the black-hole:black-hole mergers discovered through gravitational waves with for example the LIGO/Virgo collaboration are a mystery. We investigate the idea that some of these black holes originate from the centers of extremely low-mass ultra-dwarf galaxies that have merged together in the distant past at $z>1$. Extrapolating the central black hole to stellar mass ratio suggests that the black holes in these mergers could arise from galaxies of masses $\sim 10^{5} - 10^{6}$ M$_{\odot}\,$. We investigate whether these galaxies merge enough, or too much, to be consistent with the observed GW rate of $\sim 9.7-101$ Gpc$^{-3}$ yr$^{-1}$ using the latest LIGO/Virgo results. We show that in the nearby universe the merger rate and number densities of ultra-dwarf galaxies are too low, by an order or magnitude, to produce these black hole mergers. However, by considering that the merger fraction, merger-time scales, and the number densities of low-mass galaxies all conspire at $z>1-1.5$ to increase the merger rate for these galaxies at higher redshifts we argue that it is possible that some of the observed GW events arise from BHs in the centers of low-mass galaxies. The major uncertainty in this calculation is the dynamical time-scales for black holes in low-mass galaxies. Our results however suggest a very long BH merger time-scale of 4-7 Gyr, consistent with an extended black hole merger history. Further simulations are needed to verify this possibility, however our theory can be tested by searching for host galaxies of gravitational wave events. Results from these searches would will put limits on dwarf galaxy mergers and/or the presence and formation mechanisms of black holes through PopIII stars in the lowest mass galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Data-driven particle dynamics: Structure-preserving coarse-graining for emergent behavior in non-equilibrium systems

Multiscale systems are ubiquitous in science and technology, but are notoriously challenging to simulate as short spatiotemporal scales must be appropriately linked to emergent bulk physics. When expensive high-dimensional dynamical systems are coarse-grained into low-dimensional models, the entropic loss of information leads to emergent physics which are dissipative, history-dependent, and stochastic. To machine learn coarse-grained dynamics from time-series observations of particle trajectories, we propose a framework using the metriplectic bracket formalism that preserves these properties by construction; most notably, the framework guarantees discrete notions of the first and second laws of thermodynamics, conservation of momentum, and a discrete fluctuation-dissipation balance crucial for capturing non-equilibrium statistics. We introduce the mathematical framework abstractly before specializing to a particle discretization. As labels are generally unavailable for entropic state variables, we introduce a novel self-supervised learning strategy to identify emergent structural variables. We validate the method on benchmark systems and demonstrate its utility on two challenging examples: (1) coarse-graining star polymers at challenging levels of coarse-graining while preserving non-equilibrium statistics, and (2) learning models from high-speed video of colloidal suspensions that capture coupling between local rearrangement events and emergent stochastic dynamics. We provide open-source implementations in both PyTorch and LAMMPS, enabling large-scale inference and extensibility to diverse particle-based systems.

Computational Engineering, Finance, and Science (c↗

DOE OSTI2023

Post Irradiation Examination Results of Irradiated Yttrium Hydride

Department of Energy’s (DOE’s) Microreactor program (MRP) aims to provide the fundamental data to enable the development of microreactors. As such, material property data of critical materials for microreactor technologies are researched. Because substoichiometric yttrium dihydride (YHx, where x<2) is considered as a potential solid neutron moderator, its material property data has been combined in the Advanced Moderator Material Handbook which includes thermodynamic and thermophysical properties of YHx with the exception of irradiated material’s properties due to limited PIE. To fill the knowledge gap for the irradiated YHx, specimens and irradiation capsules were prepared at Los Alamos National Laboratory (LANL). Specimens were irradiated in the Advanced Test Reactor (ATR) at Idaho National Laboratory’s (INL’s). post-irradiation examination (PIE) was performed at INL’s Materials and Fuels Complex (MFC). This report compiles the PIE results of irradiated YHx specimens through fiscal years 2022 and 2023 (FY22-23) . The PIE data will directly be incorporated into the newer version of the Advanced Moderator Material Handbook. The main takeaways include that (i) the geometrical stability and mechanical integrity of YHx was intact with couple exceptions after high-temperature irradiations (600-800°C), (ii) hydrogen content variation due to manufacturing or irradiation in YHx caused visible surface discoloration, that is also related to the microstructural changes, (iii) qualitative comparisons of PIE methods implied that H retention was significantly higher at 600°C as compared to 800°C, (iv) thermal properties included signatures correlated with the H loss or re-gain, (v) importance of manufacturing readiness and initial as-manufactured specimens history was emphasized, (vi) the needs of targeted irradiations focusing on temperature and time parameters and very targeted PIE were specified.

08 HYDROGEN↗

DOE OSTI2023

Report on the Incorporation of Post-Irradiation Examination Results of Yttrium Hydride for Advanced Moderator Handbook

08 HYDROGEN↗