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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

AGES OF 70 DWARFS OF THREE POPULATIONS IN THE SOLAR NEIGHBORHOOD: CONSIDERING O AND C ABUNDANCES IN STELLAR MODELS

Oxygen and carbon are important elements in stellar populations. Their behavior refers to the formation history of the stellar populations. C and O abundances would also obviously influence stellar opacities and the overall metal abundance Z . With observed high-quality spectroscopic properties, we construct stellar models with C and O elements to give more accurate ages for 70 metal-poor dwarfs, which have been determined to be high- α halo, low- α halo, and thick-disk stars. Our results show that high- α halo stars are somewhat older than low- α halo stars by around 2.0 Gyr. The thick-disk population has an age range in between the two halo populations. The age distribution profiles indicate that high- α halo and low- α halo stars match the in situ accretion simulation by Zolotov et al., and the thick-disk stars might be formed in a relatively quiescent and long-lasting process. We also note that stellar ages are very sensitive to O abundance, since the ages clearly increase with increasing [O/Fe] values. Additionally, we obtain several stars with peculiar ages, including 2 young thick-disk stars and 12 stars older than the universe age.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Multiscale Electricity Modeling for Evaluating Carbon Capture and Sequestration Technologies (Final Report)

Carbon capture and sequestration (CCS) technologies that can operate with a high degree of operating flexibility could provide necessary electric grid flexibility in a system with high shares of variable renewables. This project examines the deployment and dispatch potential of twelve unique flexible CCS (FLECCS) technologies that encompass post-combustion carbon dioxide (CO 2 ) capture designs, concepts using a storage media to enable energy arbitrage, and hybrid processes that integrate CCS with direct air capture (DAC) for flexibility with net zero or negative CO 2 emissions. FLECCS technology potential is explored with a multi-model, multi-scale framework including the Regional Energy Deployment System (ReEDS) electric sector capacity expansion model (CEM) and the PLEXOS production cost model (PCM). Innovative methods were developed to represent FLECCS technology operating modes, performance, and cost in the two models. ReEDS was then used to simulate nine scenarios for each FLECCS technology, three CO 2 emissions price futures reaching $\$$150, $\$$225, and $\$$300/tCO 2 in 2050; and three scenarios for FLECCS technology deployment favorability relative to competing technologies. For each CO 2 price and reference FLECCS favorability, the 2050 infrastructures from ReEDS model are downscaled and implemented in PLEXOS to examine hourly dispatch under detailed operational constraints that are not included in ReEDS. FLECCS technologies exhibited a wide range of deployment potential ranging from none to several hundred gigawatts of capacity, with outcomes highly sensitive to input cost and performance parameters that are inherently highly uncertain. When deployed, FLECCS tended to displace a combination of wind, solar, and natural gas-based technologies rather than supporting increased renewable deployment. As a result, CO 2 emissions reductions facilitated by FLECCS deployment tended to come with higher overall system costs and electricity prices. When economically competitive, FLECCS technologies can contribute significant flexible generation and firm capacity to the grid, but continued technology development and an expanded analytical scope are necessary to fully understand FLECCS deployment potential its impact on the electric power sector. Follow-on analysis incorporating captured CO 2 tax credit value from the Inflation Reduction Act (IRA) and other potential policy scenarios could be particularly valuable, as this policy can substantially change the relative competitiveness of FLECCS technologies.

03 NATURAL GAS↗
DOE OSTI2022

Comparisons of Nodal diffusion and whole-core transport methods for multiple cycles of a small Light water reacto

As part of a cooperative research and development agreement between the US department of Energy's Oak Ridge National Laboratory and Holtec International subsidiary SMR LLC, core simulator models of the SMR-160, a light water-cooled and -moderated, natural circulation, small modular reactor, were developed and compared. The model results indicate pin-by-pin power histories, critical boron concentration, and other key performance indicators useful for developing multi-cycle core loading patterns. One model uses industry standard nodal methods with a simple thermal-hydraulics solution, and the other uses an advanced deterministic neutronics solver with a coupled subchannel calculation. The goals of the comparison are to provide the reactor designer with a detailed and coupled core physics reference solution, inform the reactor designer of nodal model best practices based on the code-to-code comparison, and set up a workflow for performing subsequent detailed core simulator calculations. The results of this work will be used in the development of coupled neutronic, thermal hydraulic, and fuel performance models for advanced analysis of the SMR-160. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Evaluating performance of different generative adversarial networks for large-scale building power demand prediction

We report as an unsupervised-learning data-driven model, Generative Adversarial Networks (GANs) have recently attracted a lot of attention for various applications. There is potential to apply GANs for large-scale building power demand prediction, which is needed for power grid operation. However, there are many GAN variations and it is unclear which GAN is suitable for this application. To answer this question, this paper identifies five promising GANs (Original GAN, cGAN, SGAN, InfoGAN, and ACGAN) and evaluates their performance for predicting building power demand at a large scale. Physics-based building energy models are developed to generate training and reference data. A new evaluation indicator that combines accuracy and reproducibility is proposed to evaluate the performance of different GANs in predicting building power demand. The results show that SGAN and InfoGAN are not suitable because they cannot control the number of generated building samples for different building types. The prediction performance among the Original GAN, cGAN, and ACGAN can vary depending on training sample sizes and number of building types. If the training sample size is sufficiently large, Original GAN and cGAN can predict building power demand more accurately than ACGAN with the same number of samples. If training samples are limited, Original GAN provides better accuracy than cGAN and ACGAN. When the number of building types increase, the prediction accuracy increases for cGAN, decreases for ACGAN, and remains the same for Original GAN. As a result, cGAN and Original GAN are recommended for large-scale building power demand prediction.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Production Facility Simulations for Annular LEU Targets

Eden Radioisotopes, LLC is designing a new molybdenum-99 (Mo-99) production facility based on a TRIGA-sized reactor with a core composed of low enriched uranium (LEU) targets. Reactor production is designed to exceed U.S. demand for Mo-99 using the fission processes. The nominal operational power is 1.8MW (less than 2.0MW, to satisfy the “non-power” reactor requirement) and desired irradiation scenarios include 7, 14, or 21 days of the irradiation for each target element. Safety limits for reactor operating margins are associated with such physical phenomena as fission gas release, fuel swelling, and stress cracking. As shown in the literature, one of the critical parameters defining safety margins for metallic uranium fuel is swelling. In its turn the fuel operational temperature is the main parameter impacting the swelling rate. This report documents the results of consecutive studies of reactor criticality, fission energy depositions, and cooling conditions for the target. The maximum temperature calculated for the LEU targets allows us to choose appropriate modeling approximation of the swelling. All obtained results refer to the preliminary targets and core designs provided by Eden. A criticality analysis was performed, and the results are listed mainly to cross-check Eden’s safety report and assume maximal neutron field disturbance for maximal reactivity. A brief description of the metallic uranium swelling model is provided in the Appendix.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2022

Updated Economic Model for Estimation of GDP Losses in the MACCS Offsite Consequence Analysis Code RDEIM Model Report for MACCS v4.2

This report updates the Regional Disruption Economic Impact Model (RDEIM) GDP-based model described in Bixler et al. (2020) used in the MACCS accident consequence analysis code. MACCS is the U.S. Nuclear Regulatory Commission (NRC) used to perform probabilistic health and economic consequence assessments for atmospheric releases of radionuclides. It is also used by international organizations, both reactor owners and regulators. It is intended and most commonly used for hypothetical accidents that could potentially occur in the future rather than to evaluate past accidents or to provide emergency response during an ongoing accident. It is designed to support probabilistic risk and consequence analyses and is used by the NRC, U.S. nuclear licensees, the Department of Energy, and international vendors, licensees, and regulators. The update of the RDEIM model in version 4.2 expresses the national recovery calculation explicitly, rather than implicitly as in the previous version. The calculation of the total national GDP losses remains unchanged. However, anticipated gains from recovery are now allocated across all the GDP loss types – direct, indirect, and induced – whereas in version 4.1, all recovery gains were accounted for in the indirect loss type. To achieve this, we’ve introduced new methodology to streamline and simplify the calculation of all types of losses and recovery. In addition, RDEIM includes other kinds of losses, including tangible wealth. This includes loss of tangible assets (e.g., depreciation) and accident expenditures (e.g., decontamination). This document describes the updated RDEIM economic model and provides examples of loss and recovery calculation, results analysis, and presentation. Changes to the tangible cost calculation and accident expenditures are described in section 2.2. The updates to the RDEIM input-output (I-O) model are not expected to affect the final benchmark results Bixler et al. (2020), as the RDEIM calculation for the total national GDP losses remains unchanged. The reader is referred to the MACCS revision history for other cost modelling changes since version 4.0 that may affect the benchmark. RDEIM has its roots in a code developed by Sandia National Laboratories for the Department of Homeland Security to estimate short-term losses from natural and manmade accidents, called the Regional Economic Accounting analysis tool (REAcct). This model was adapted and modified for MACCS. It is based on I-O theory, which is widely used in economic modeling. It accounts for direct losses to a disrupted region affected by an accident, indirect losses to the national economy due to disruption of the supply chain, and induced losses from reduced spending by displaced workers. RDEIM differs from REAcct in in its treatment and estimation of indirect loss multipliers, elimination of double-counting associated with inter-industry trade in the affected area, and that it is intended to be used for extended periods that can occur from a major nuclear reactor accident, such as the one that occurred at the Fukushima Daiichi site in Japan. Most input-output models do not account for economic adaptation and recovery, and in this regard RDEIM differs from its parent, REAcct, because it allows for a user-definable national recovery period. Implementation of a recovery period was one of several recommendations made by an independent peer review panel to ensure that RDEIM is state-of-practice. For this and several other reasons, RDEIM differs from REAcct.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Transferability of data-driven, many-body models for CO 2 simulations in the vapor and liquid phases

Here, extending on the previous work by Riera et al. [J. Chem. Theory Comput. 16, 2246–2257 (2020)], we introduce a second generation family of data-driven many-body MB-nrg models for CO 2 and systematically assess how the strength and anisotropy of the CO 2 –CO 2 interactions affect the models’ ability to predict vapor, liquid, and vapor–liquid equilibrium properties. Building upon the many-body expansion formalism, we construct a series of MB-nrg models by fitting one-body and two-body reference energies calculated at the coupled cluster level of theory for large monomer and dimer training sets. Advancing from the first generation models, we employ the charge model 5 scheme to determine the atomic charges and systematically scale the two-body energies to obtain more accurate descriptions of vapor, liquid, and vapor–liquid equilibrium properties. Challenges in model construction arise due to the anisotropic nature and small magnitude of the interaction energies in CO 2 , calling for the necessity of highly accurate descriptions of the multidimensional energy landscape of liquid CO 2 . These findings emphasize the key role played by the training set quality in the development of transferable, data-driven models, which, accurately representing high-dimensional many-body effects, can enable predictive computer simulations of molecular fluids across the entire phase diagram.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

CMIP6-based Multi-model Streamflow Projections over the Conterminous US

This dataset presents an ensemble of streamflow projections based on the hydroclimate projections dataset supporting the SECURE Water Act Section 9505 Assessment for the US Department of Energy (DOE) Water Power Technologies Office (WPTO). The six-member General Climate Model (GCM) ensemble from the Coupled Models Intercomparison Project phase 6 (CMIP6) downscaled using statistical (i.e., DBCCA) and dynamical (i.e., RegCM) and bias-corrected using two meteorological reference observations (Daymet & Livneh) are driven through two calibrated hydrologic models (VIC & PRMS) to simulate projected future hydrologic responses. This leads to the production of an ensemble of hydroclimate projections, including total runoff (surface runoff and baseflow) for 1980–2019 baseline and 2020–2059 near-term future periods under multiple emission scenarios at 1/24° (~4 km) spatial resolution across the CONUS. The total runoff projections are routed through the Routing Application for Parallel computatIon of Discharge (RAPID) routing model to produce an ensemble of streamflow projections for both periods across 2.7 million NHDPlusV2 stream reaches in the CONUS.

13 HYDRO ENERGY↗
DOE OSTI2021

Artificial spin ice: Paths forward

Artificial spin ice systems are lithographically prepared arrays of interacting nanoscale magnetic moments with collective behavior resulting from the chosen array geometry. These many-body systems are unusual in that their simple constituent elements can be configured to design their interactions with exquisite control. They can then be probed experimentally over a remarkably large range of time scales and length scales, including imaging of the individual moments. The study of artificial spin ice has broadened well beyond the original focus on systems with connection to spin ice and ice models, and now the term is used in reference to many other structures that exhibit a much wider range of physical phenomena. Here in this perspective, we review progress in the field of artificial spin ice since its inception more than a decade ago. We then discuss prospects for future directions – continuing the exploration of nanomagnetism, statistical spin models, and the potential for technological devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Industry Level Feasibility of LiDAR Data into Fire Modeling Using Fire Risk Investigation in 3D (FRI3D)

Many evaluation, assessment, and modeling tasks at nuclear power plants require spatial information this often requires physical visits to locations within the facility because the 2D or 3D schematics and current models do not contain enough detail or do not capture as-built and real-world conditions. These visits require extensive manual labor for not only the requesting party, but support groups such as security. LIDAR mapping is trying to solve that problem by providing very detailed 3D models for low costs. However, the use of these models can be very limited because either component reference information is missing and too costly to add, or there is no way to extract specific spatial data needed for other tools. This report presents Idaho National Lab's work with Environmental Intellect (Ei) covering two main efforts. First, to reduce the effort of "tagging" data in large 3D models. By using both existing plant database information, and artificial intelligence (AI) to find and read equipment labels. This research explores the ability of to provide a simple way for the user to tag items and verify plant data, capturing both the speed of AI and human verification. The second part of the work is the development of an interface for importing pieces needed for Modeling & Simulation. Analysis work such as that for fire, flood, or physical security all require spatial or 3D models in various levels of detail. This interface will allow for the retrieval of item location or boundaries, enabling the auto generation of models for varying tools. The application program interface (API) of the fire risk investigation in 3D (FRI3D) was used to test feasibility of exporting the LiDAR tagged spatial information. Outcomes from this work provide preliminary data to determine if the tools and methods could provide substantial industry benefit if fully matured.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Equation of State Model Quality Study for Ti and Ti64.

Titanium and the titanium alloy Ti64 (6% aluminum, 4% vanadium and the balance ti- tanium) are materials used in many technologically important applications. To be able to computationally investigate and design these applications, accurate Equations of State (EOS) are needed and in many cases also additional constitutive relations. This report describes what data is available for constructing EOS for these two materials, and also describes some references giving data for stress-strain constitutive models. We also give some suggestions for projects to achieve improved EOS and constitutive models. In an appendix, we present a study of the 'cloud formation' issue observed in the ALEGRA code. This issue was one of the motivating factors for this literature search of available data for constructing improved EOS for Ti and Ti64. However, the study shows that the cloud formation issue is only marginally connected to the quality of the EOS, and, in fact, is a physical behavior of the system in question. We give some suggestions for settings in, and improvements of, the ALEGRA code to address this computational di culty.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

The International Experimental Thermal Hydraulic Systems database – TIETHYS: A new NEA validation tool

Nuclear reactor codes require validation with appropriate data representing the plant for specific scenarios. The thermal-hydraulic data is scattered in different locations and in different formats. Some of the data is in danger of being lost. A relational database is being developed to organize the international thermal hydraulic test data for various reactor concepts and different scenarios. At the reactor system level, that data is organized to include separate effect tests and integral effect tests for specific scenarios and corresponding phenomena. The database relies on the phenomena identification sections of expert developed PIRTs. The database will provide a summary of appropriate data, review of facility information, test description, instrumentation, references for the experimental data and some examples of application of the data for validation. The current database platform includes scenarios for PWR, BWR, VVER, and specific benchmarks for CFD modelling data and is to be expanded to include references for molten salt reactors. There are place holders for high temperature gas cooled reactors, CANDU and liquid metal reactors. This relational database is called The International Experimental Thermal Hydraulic Systems (TIETHYS) database and currently resides at Nuclear Energy Agency (NEA) of the OECD and is freely open to public access. Going forward the database will be extended to include additional links and data as they become available. https://www.oecd-nea.org/tiethysweb/

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Advanced Multiphysics Thermal-Hydraulics Models for the High Flux Isotope Reactor

Engineering design studies to determine the feasibility of converting the High Flux Isotope Reactor (HFIR) from using highly enriched uranium (HEU) to low-enriched uranium (LEU) fuel are ongoing at Oak Ridge National Laboratory (ORNL). This work is part of an effort sponsored by the US Department of Energy (DOE) Reactor Conversion Program. HFIR is a very high flux pressurized light-water-cooled and moderated flux-trap type research reactor. HFIR s current missions are to support neutron scattering experiments, isotope production, and materials irradiation, including neutron activation analysis. Advanced three-dimensional multiphysics models of HFIR fuel were developed in COMSOL software for safety basis (worst case) operating conditions. Several types of physics including multilayer heat conduction, conjugate heat transfer, turbulent flows (RANS model) and structural mechanics were combined and solved for HFIR s inner and outer fuel elements. Alternate design features of the new LEU fuel were evaluated using these multiphysics models. This work led to a new, preliminary reference LEU design that combines a permanent absorber in the lower unfueled region of all of the fuel plates, a burnable absorber in the inner element side plates, and a relocated and reshaped (but still radially contoured) fuel zone. Preliminary results of estimated thermal safety margins are presented. Fuel design studies and model enhancement continue.

COMSOL↗
DOE OSTI2013

Inverse Modeling of Hydrologic Parameters Using Surface Flux and Runoff Observations in the Community Land Model

This study demonstrates the possibility of inverting hydrologic parameters using surface flux and runoff observations in version 4 of the Community Land Model (CLM4). Previous studies showed that surface flux and runoff calculations are sensitive to major hydrologic parameters in CLM4 over different watersheds, and illustrated the necessity and possibility of parameter calibration. Two inversion strategies, the deterministic least-square fitting and stochastic Markov-Chain Monte-Carlo (MCMC) - Bayesian inversion approaches, are evaluated by applying them to CLM4 at selected sites. The unknowns to be estimated include surface and subsurface runoff generation parameters and vadose zone soil water parameters. We find that using model parameters calibrated by the least-square fitting provides little improvements in the model simulations but the sampling-based stochastic inversion approaches are consistent - as more information comes in, the predictive intervals of the calibrated parameters become narrower and the misfits between the calculated and observed responses decrease. In general, parameters that are identified to be significant through sensitivity analyses and statistical tests are better calibrated than those with weak or nonlinear impacts on flux or runoff observations. Temporal resolution of observations has larger impacts on the results of inverse modeling using heat flux data than runoff data. Soil and vegetation cover have important impacts on parameter sensitivities, leading to the different patterns of posterior distributions of parameters at different sites. Overall, the MCMC-Bayesian inversion approach effectively and reliably improves the simulation of CLM under different climates and environmental conditions. Bayesian model averaging of the posterior estimates with different reference acceptance probabilities can smooth the posterior distribution and provide more reliable parameter estimates, but at the expense of wider uncertainty bounds.

inverse, modeling, hydrologic, parameters, flux, r↗
DOE OSTI2018

Improved Nested Sampling and Surrogate-Enabled Comparison With Other Marginal Likelihood Estimators

Estimating marginal likelihood is of central importance to Bayesian model selection and/or model averaging. The nested sampling method has been recently used together with the Metropolis-Hasting (M-H) sampling algorithm for estimating marginal likelihood. This study develops a new implementation of nested sampling by using the DiffeRential Evolution Adaptive Metropolis (DREAMzs) sampling algorithm. The two implementations of nested sampling are evaluated for four models of a synthetic groundwater flow modeling. The DREAMzs-based nested sampling outperforms the M-H-based nested sampling in terms of their accuracy, convergence, efficiency, and stability, which is attributed to the fact that DREAMzs is more robust than M-H for parameter sampling. The nested sampling method is also compared with four other methods (arithmetic mean, harmonic mean, stabilized harmonic mean, and thermodynamic integration) commonly used for estimating marginal likelihood and posterior probability of the four groundwater models. The comparative study requires hundreds of millions of model executions, which would not be possible without using surrogate models to replace the original models. Using the arithmetic mean estimator as the reference, the comparison reveals that thermodynamic integration outperforms nested sampling in terms of accuracy and stability, whereas nested sampling is more computationally efficient to reach to convergence. Here, the harmonic mean and stabilized harmonic mean methods give the worst marginal likelihood estimation. Accurate marginal likelihood estimation is important for accurate estimation of posterior model probability and better predictive performance of Bayesian model averaging.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Bottom Fixed Platform Dynamics Models Assessing Surface Ice Interactions for Transitional Depth Structures in the Great Lakes: FAST8 – IceDyn

To create long-term solutions for offshore wind turbines in a variety of environmental conditions, CAE tools are needed to model the design-driving loads that interact with an offshore wind turbine system during operation. This report describes our efforts in augmenting existing CAE tools used for offshore wind turbine analysis with a new module that can provide simulation capabilities for ice loading on the system. This augmentation was accomplished by creating an ice-loading module coupled to FAST8, the CAE tool maintained by the NREL for simulating land-based and offshore wind turbine dynamics. The new module includes both static and dynamic ice loading that can be applied during a dynamic simulation of the response of an offshore wind turbine. The ice forces can be prescribed, or influenced by the structure’s compliant response, or by the dynamics of both the structure and the ice floe. The new module covers ice failure modes of spalling, buckling, crushing, splitting, and bending. The supporting structure of wind turbines can be modeled as a vertical or sloping form at the waterline. The Inward Battered Guide Structure (IBGS) foundation designed by Keystone Engineering for the Great Lakes was used to study the ice models coupled to FAST8. The IBGS foundation ice loading simulations in FAST8 were compared to the baseline simulation case without ice loading. The ice conditions reflecting those from Lake Huron at Port Huron and Lake Michigan at North Manitou were studied under near rated wind speed of 12 m/s for the NREL 5-MW reference turbine. Simulations were performed on ice loading models 1 through 4 and ice model 6 with their respective sub-models. The purpose of ice model 5 is to investigate ice loading on sloping structures such as ice-cones on a monopile and is not suitable for multi-membered jacketed structures like the IBGS foundation. The key response parameters from the simulations, shear forces and moments from the tower base and IBGS foundation base, were compared. Ice models 1 and 6 do not significantly affect the tower fore-aft shear and moment. However, ice model 2 (dynamic analyses), model 3 (random ice loading), and model 4 (multiple ice failure zone loading) show increased effect on the tower fore-aft shear and moment with significant effect from ice model 3.1. In general ice loading creates large reaction forces and moments at the base of the IBGS foundation; the largest occurred in model 1.1 (steady creep ice indentation loading) followed by model 3.1 (random creep ice indentation loading). In general the power production from the ice loading cases had little deviation from the baseline case without ice loading. For ultimate limit state (ULS), ice model 1.1 ice and 3.1 appear to be the ice most critical models to consider at an early stage of design. Ice model 4 is an important tool for assessing structural fatigue.

17 WIND ENERGY↗
DOE OSTI2015

Genome-wide mapping of histone H3 lysine 4 trimethylation in Eucalyptus grandis developing xylem

Background: Histone modifications play an integral role in plant development, but have been poorly studied in woody plants. Investigating chromatin organization in wood-forming tissue and its role in regulating gene expression allows us to understand the mechanisms underlying cellular differentiation during xylogenesis (wood formation) and identify novel functional regions in plant genomes. However, woody tissue poses unique challenges for using high-throughput chromatin immunoprecipitation (ChIP) techniques for studying genome-wide histone modifications in vivo. We investigated the role of the modified histone H3K4me3 (trimethylated lysine 4 of histone H3) in gene expression during the early stages of wood formation using ChIP-seq in Eucalyptus grandis, a woody biomass model. Results: Plant chromatin fixation and isolation protocols were optimized for developing xylem tissue collected from field-grown E. grandis trees. A “nano-ChIP-seq” procedure was employed for ChIP DNA amplification. Over 9 million H3K4me3 ChIP-seq and 18 million control paired-end reads were mapped to the E. grandis reference genome for peak-calling using Model-based Analysis of ChIP-Seq. The 12,177 significant H3K4me3 peaks identified covered ~1.5% of the genome and overlapped some 9,623 protein-coding genes and 38 noncoding RNAs. H3K4me3 library coverage, peaking ~600 - 700 bp downstream of the transcription start site, was highly correlated with gene expression levels measured with RNA-seq. Overall, H3K4me3-enriched genes tended to be less tissue-specific than unenriched genes and were overrepresented for general cellular metabolism and development gene ontology terms. Relative expression of H3K4me3-enriched genes in developing secondary xylem was higher than unenriched genes, however, and highly expressed secondary cell wall-related genes were enriched for H3K4me3 as validated using ChIP-qPCR. Conclusions: In this first genome-wide analysis of a modified histone in a woody tissue, we optimized a ChIP-seq procedure suitable for field-collected samples. In developing E. grandis xylem, H3K4me3 enrichment is an indicator of active transcription, consistent with its known role in sustaining pre-initiation complex formation in yeast. The H3K4me3 ChIP-seq data from this study paves the way to understanding the chromatin landscape and epigenomic architecture of xylogenesis in plants, and complements RNA-seq evidence of gene expression for the future improvement of the E. grandis genome annotation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

An Evaluation of Representation Learning Methods in Particle Physics Foundation Models

We present a systematic evaluation of representation learning objectives for particle physics within a unified framework. Our study employs a shared transformer-based particle-cloud encoder with standardized preprocessing, matched sampling, and a consistent evaluation protocol on a jet classification dataset. We compare contrastive (supervised and self-supervised), masked particle modeling, and generative reconstruction objectives under a common training regimen. In addition, we introduce targeted supervised architectural modifications that achieve state-of-the-art performance on benchmark evaluations. This controlled comparison isolates the contributions of the learning objective, highlights their respective strengths and limitations, and provides reproducible baselines. We position this work as a reference point for the future development of foundation models in particle physics, enabling more transparent and robust progress across the community.

Chen, Michael [Caltech]↗