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At least 307 records · Page 17

Physical Correlations and Predictions Emerging from Modern Core-collapse Supernova Theory

Abstract In this paper, we derive correlations between core-collapse supernova observables and progenitor core structures that emerge from our suite of 20 state-of-the-art 3D core-collapse supernova simulations carried to late times. This is the largest such collection of 3D supernova models ever generated and allows one to witness and derive testable patterns that might otherwise be obscured when studying one or a few models in isolation. From this panoramic perspective, we have discovered correlations between explosion energy, neutron star gravitational birth masses, 56 Ni and α -rich freezeout yields, and pulsar kicks and theoretically important correlations with the compactness parameter of progenitor structure. We find a correlation between explosion energy and progenitor mantle binding energy, suggesting that such explosions are self-regulating. We also find a testable correlation between explosion energy and measures of explosion asymmetry, such as the ejecta energy and mass dipoles. While the correlations between two observables are roughly independent of the progenitor zero-age main-sequence (ZAMS) mass, the many correlations we derive with compactness cannot unambiguously be tied to a particular progenitor ZAMS mass. This relationship depends on the compactness/ZAMS mass mapping associated with the massive star progenitor models employed. Therefore, our derived correlations between compactness and observables may be more robust than with ZAMS mass but can nevertheless be used in the future once massive star modeling has converged.

Astronomy & Astrophysics↗

A compact furnace to support in situ neutron imaging of hydrogen dynamics in yttrium hydride moderators

A compact, nuclear microreactor that utilizes low-enriched uranium fuel is a promising solution to meet U.S. energy demands in nonconventional nuclear markets such as remote and decentralized energy grids. Yttrium hydride (YHx) is a potential moderator material for a microreactor design that reduces the amount of required fuel and provides superior retention of hydrogen at high reactor operating temperatures. Hydrogen diffusion properties in YHx are highly sought after for computer model validation and reactor prototyping. To characterize hydrogen diffusion, a compact dual-zone furnace was developed at Los Alamos National Laboratory and analyzed via neutron imaging at the Los Alamos Neutron Science Center (LANSCE). The goal of these measurements is to assess hydrogen diffusion in YHx samples as a function of applied temperature gradients. Included herein is recent progress in technique and furnace developments as well as initial results from concentration- and temperature-gradient measurements at LANSCE.

Torres, James↗

Glassy carbon formation from pyrolysis of polymeric coatings on fiber-optic sensors

Deploying fiber-optic sensors in nuclear reactors requires a detailed understanding of radiation effects on the fiber materials and the transmitted signals. Previous work has shown large wavelength shifts in the reflected spectra obtained from polymer-coated fiber-optic temperature sensors exposed to high neutron fluences. The sensor drift resulting from these wavelength shifts cannot be explained by radiation effects on fused silica glass. These shifts are hypothesized to be caused by the conversion of the polymeric fiber coating to a glassy carbon via radiolysis and/or pyrolysis and subsequent radiation-induced compaction. Here, thermal degradation of these polymeric coatings was studied to provide insight into the potential origins of the sensor drift phenomenon. Acrylate- and polyimide-coated fibers were heated under various temperatures (250–1300 °C) and environments (oxidative and inert), and the resulting coating products were characterized via mass-loss data, scanning electron microscope imaging, and Raman spectroscopy. Results suggest that the polymer decomposition product of both coating types, at least under inert conditions, is indeed a glassy carbon. Analytical models that account for radiation-induced glassy carbon coating compaction show significant compressive fiber strains and predicted wavelength shifts that agree well with experimental measurements, providing additional evidence that supports the hypothesized origins of the sensor drift.

36 MATERIALS SCIENCE↗

Material Control & Accounting Modeling Developments for a Generic TRISO Fuel Fabrication Facility

The Material Protection, Accounting, and Control Technologies (MPACT) program utilizes modeling and simulation to assess Material Control and Accountability (MC&A) concerns for a variety of nuclear facilities. The Sandia National Laboratories (SNL)-developed Fissile Facility Flow Modeler (F3M) and the Material Accountancy Performance Indicator Toolkit (MAPIT) have historically provided MPACT with the capability to analyze MC&A approaches for nuclear facilities to determine that these facilities meet regulatory requirements. In FY25, improvements on the application of the F3M and MAPIT tools to simulate a generic TRi-structural ISOtropic (TRISO) fuel fabrication facility were successfully completed. The generic TRISO fuel fabrication F3M model captures the entire TRISO fuel fabrication process and is adaptable to any final TRISO fuel form, including spherical pebbles and cylindrical compacts loaded into graphite prismatic blocks. Comprehensive F3M/MAPIT functionality for the generic TRISO fuel fabrication model has been demonstrated. This modeling framework can be applied to support the U.S. Department of Energy and domestic nuclear industry stakeholders in developing MC&A approaches for advanced fuel fabrication facilities via statistical tests that demonstrate compliance to regulatory requirements.

97 MATHEMATICS AND COMPUTING↗

FEA-aided investigation of the effective thermal conductivity in a medium with embedded spheres

For multiple applications in nuclear energy, the ability to accurately represent material behavior with a simplified model is important to facilitate practical engineering-scale simulations. Here, we focus on the homogenized thermal response of a medium containing spherical inclusions, similar to a fuel form (compact or pebble) containing (TRISO) particles. A review on effective thermal conductivity (ETC) modeling is performed considering a random distribution of mono-sized spherical inclusions in a continuous matrix, with a primary focus on the analytical models. Finite element simulations are performed to evaluate each analytical model in varying material conditions. The model predictions are compared with the expected results obtained from the finite element predictions in addition to the Wiener and Hashin-Shtrikman bounds. Lastly, we included a practical discussion on the homogenization applied to a TRISO fuel pebble.

42 ENGINEERING↗

In situ probing the origin of interfacial instability of Na metal anode

The unstable and fragile solid electrolyte interphase (SEI) has restricted the application of Na metal anodes. Despite numerous research efforts being put into understanding its chemical composition and physical properties, direct observation of its formation remains a challenge due to the lack of temporal and spatial resolution. Here, through combined in situ probing techniques, we exhibit two pivotal stages associated with SEI instability during the often -neglected formation process. It is revealed that Na metal that is not uniformly passivated at the initial (passivating) stage will trigger unrestricted electrolyte decomposition and homogeneous components distribution during the subsequent (growing) stage. SEI with homogenously distributed components is found to have higher solubility than that with a layered structure evolved from a compact passivation layer. Furthermore, through demonstrating an SEI dissolution model that is closely related to its formation process and compositional distribution, this work sheds light on an uncharted territory of Na metal batteries.

25 ENERGY STORAGE↗

Modeling Flow in a Microreactor Core: From High-Fidelity CFD to Subchannel Analysis

The accurate prediction of pressure drop in tightly packed, low–Reynolds number (Re) bare rod bundles is essential for the thermal-hydraulic design of the Microreactor Applications Research Validation and EvaLuation (MARVEL) reactor and other microreactor concepts. However, existing friction factor correlations, particularly the upgraded Cheng-Todreas (UCTD) correlation, have limited validation for the small pitch-to-diameter ratios (P/Ds) and transitional flow conditions characteristic of these systems. In this work, we perform high-fidelity large-eddy simulations (LESs) of both an infinite bare rod bundle and a finite bare 37-pin scalloped rod bundle across the range 1000≤ 𝑅𝑒 ≤5500. The simulations reveal strong gap vortex–driven transitional behavior and indicate that the UCTD may underpredict the friction factor by up to 28% at 𝑃/𝐷 = 1.05. Using the LES-calculated pressure drops, we formulate a new friction factor correlation that follows the Cheng-Todreas functional form but is calibrated for low-Re and tightly packed geometries representative of a MARVEL-like reactor. The correlation is implemented in the MOOSE (Multiphysics Object-Oriented Simulation Environment) subchannel module and compared against both the LES and UCTD predictions. Across all subchannel types, the proposed model reduces the streamwise velocity differences from as high as 44% (UCTD) to below 9%, and decreases the pressure gradient differences from 13% to 25% (UCTD) to 0.7% to 7% relative to the LES results. These results suggest that the new correlation has the potential to improve the pressure drop and flow field predictions for such geometries, highlighting the importance of high-fidelity simulations in supporting microreactor thermal-hydraulic model development and motivating future pressure drop experiments for compact rod bundles to further validate these findings.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

A mini-TGA protein modulates gene expression through heterogeneous association with transcription factors

Abstract TGA (TGACG-binding) transcription factors, which bind their target DNA through a conserved basic region leucine zipper (bZIP) domain, are vital regulators of gene expression in salicylic acid (SA)-mediated plant immunity. Here, we investigated the role of StTGA2.1, a potato (Solanum tuberosum) TGA lacking the full bZIP, which we named a mini-TGA. Such truncated proteins have been widely assigned as loss-of-function mutants. We, however, confirmed that StTGA2.1 overexpression compensates for SA-deficiency, indicating a distinct mechanism of action compared with model plant species. To understand the underlying mechanisms, we showed that StTGA2.1 can physically interact with StTGA2.2 and StTGA2.3, while its interaction with DNA was not detected. We investigated the changes in transcriptional regulation due to StTGA2.1 overexpression, identifying direct and indirect target genes. Using in planta transactivation assays, we confirmed that StTGA2.1 interacts with StTGA2.3 to activate StPRX07, a member of class III peroxidases (StPRX), which are known to play role in immune response. Finally, via structural modeling and molecular dynamics simulations, we hypothesized that the compact molecular architecture of StTGA2.1 distorts DNA conformation upon heterodimer binding to enable transcriptional activation. This study demonstrates how protein truncation can lead to distinct functions and that such events should be studied carefully in other protein families.

59 BASIC BIOLOGICAL SCIENCES↗

Isolated Single-stage Three-phase AC/DC Converter using Bidirectional Switches

The advent of the SiC Bidirectional FET (BiDFET), a monolithic 1.2 kV bidirectional switch, has rendered the single-stage three-phase AC/DC converter topology a promising approach for implementing AC/DC converters. This topology, which integrates a full-bridge converter with a single-phase to three-phase matrix converter via a high-frequency transformer, is particularly suitable for applications requiring galvanic isolation, buck-boost functionality, and bidirectional power flow. The single-stage design eliminates the need for bulky and unreliable electrolytic capacitors, and utilizes a single magnetic component for power transfer. In the matrix converter, bidirectional switches, which were traditionally implemented using combinations of multiple semiconductor devices such as MOSFETs, IGBTs, and diodes, can now be realized using the single-chip solution, BiDFET. This advancement leads to a lower switch count, compact converter implementation, with lower inductance commutation cells, thereby enhancing the overall efficiency and compactness of the system. The paper presents a unified model of the converter, considering all control parameters, including the duty cycles and phase shift of transformer voltages. Detailed expressions for power transfer, transformer currents, and currents at AC and DC ports are provided. Additionally, the paper outlines the conditions necessary for soft-switching of all switches and the commutation schemes required for the practical implementation of the matrix converter modulation scheme. A hardware prototype of a 10 kW, 480 VRMS, LL/ 800 V AC/DC system has been developed, and experimental results are presented to demonstrate its performance.

BiDFET↗

Nuclear Criticality Safety Assessment of Criticality Control Containers without Moderation Control at the Waste Isolation Pilot Plant

The Waste Isolation Pilot Plant (WIPP) provides for safe, permanent disposal of government-owned transuranic (TRU) and TRU mixed wastes. Receipt and disposal of waste at the WIPP site began in March 1999. The Sandia report, Consideration of Nuclear Criticality When Disposing of Transuranic Waste at the Waste Isolation Pilot Plant, addressed potential nuclear criticality safety issues based on the projected inventory characteristics known at the time [1]. As designs for inventory, waste forms, and disposal packages have changed, new analyses have been performed, and updates have been made to address any potential effects to the WIPP safety basis. New analyses performed include Saylor 2017 [2] and Brickner 2019 [3], which address certain waste containers with specified loadings under post-closure conditions. Both examined several hypothetical scenarios and included analyses to bound (from a criticality potential standpoint) credible configurations that could occur at WIPP during the repository regulatory post-closure disposal time period for feature, event, and process (FEP) considerations—10,000 years. During this post-closure period at WIPP, the screening of FEPs is governed by the risk-based standards and implementing regulations of the US Environmental Protection Agency (EPA) (i.e., 40 CFR 191 and 40 CFR 194, respectively) [4,5]. An FEP screening can be based on either a low-consequence or low-probability rationale. A low-probability rationale includes either (a) a qualitative rationale that the FEP is not credible or (b) a quantitative demonstration that the probability is less than 10-4 in 104 years. In this evaluation, a qualitative lowprobability rationale of not credible is used by demonstrating that bounding configurations of the waste are not critical. The demonstration of subcriticality is through quantitative calculations, but a probability of criticality is not evaluated. Rather, the rationale for this evaluation is that bounding configurations with an effective neutron multiplication factor (keff) well below the upper subcriticality limit (USL) make criticality incredible. Reference [2] documented a nuclear criticality assessment of the WIPP repository for disposal of dilute surplus plutonium materials using the Dilute and Dispose Approach and packaging in criticality control overpacks (CCOs). The CCO is the waste disposal container recently designed to allow for up to 380 fissile gram equivalent (FGE) 239 Pu per drum, which is a higher fissile loading than typical waste containers. The CCO consists of a criticality control container (CCC) positioned by upper and lower plywood spacers within a standard 55 gal drum. The CCC is used to establish a geometry control for fissile materials during transportation and WIPP emplacement operations. The current WIPP waste acceptance criteria for CCO payloads limit beryllium to less than or equal to 1% by weight of the waste contents and require the waste form to be non-machine compacted. Reference [2] considered two scenario progressions—room closure from salt creep, hereafter referred to as the reconfigured dry scenario, and flooding with brine, hereafter referred to as the reconfigured wet scenario. The subsequent drying out of the reconfigured wet scenarios was also considered. For all scenarios, subcriticality was maintained when 50 g of B 4 C (acting as a neutron absorber) per CCC was intermixed within the plutonium disposition waste form. The analysis used a waste form description that limits the amount of moderation that could be present within the waste form (i.e., it limits the amount of water and polyethylene that could be present based on planned processing conditions). This analysis to evaluate increased limits on the amount of moderation that could be present was performed as a companion to Reference [2] to address concerns associated with verifying moisture and/or plastic contents of waste materials following packaging of dilute surplus plutonium in the CCO. To that end, this analysis used the models and methods from Reference [2] to evaluate a more generic base waste form consisting of water and polyethylene that is more similar (and nearly identical) to the generic waste forms utilized in other models/analyses supporting the TRU Package Transporter Model II (TRUPACTII) safety analysis [6] (all are without moderation controls). The waste form in this analysis uses a base mixture of 75% water and 25% polyethylene, the total amount of which is varied to determine the optimum moderation to fissile material (H/Pu) ratio. The fissile loading is maintained at up to 380 FGE 239 Pu (modeled as PuO 2 ) per CCO with an additional 545 g of beryllium (to bound the 1% by weight contents restriction) and 50 g of B 4 C intermixed per CCO. The beryllium content (1% by weight) is based on the total allowed waste weight (this does not include packaging and container weights). Figures ES-1 and ES-2 display summary results, showing that with this model including 50 g of B 4 C per CCO, the system keff remains under 0.85 for all moderator amounts and provides a significant margin against post-closure criticality under postulated bounding conditions for compaction. Figure ES-1 compares an infinite model with a room model at the initial emplacement spacing and under full radial compaction. Full radial compaction places each CCC in direct contact and does not credit any anticipated spacing associated with current post-closure geomechanical modeling of the repository [7]. The effects of variations in the H/Pu ratio were evaluated by varying the amount of the water/polyethylene component of the waste model, with fissile loading maintained at 380 239 Pu FGE. Similarly, Figure ES-2 illustrates how various amounts of B 4 C per CCO influence k eff at different radial compactions, all at the H/Pu ratio of 200 (in the room array model). Therefore, while the results from Saylor 2017 [2] modeled more realistic process limits associated with packaging of dilute surplus plutonium, this analysis demonstrates that limits on moderation (plastic and water content) are not necessary to ensure subcriticality in the WIPP repository, provided the requisite B 4 C absorber is present.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Simulations of Criticality Control Overpack Container Compaction at the Waste Isolation Pilot Plant

Criticality Control Overpack (CCO) containers are being considered for the disposal of defense-related nuclear waste at the Waste Isolation Pilot Plant (WIPP). At WIPP, these containers would be placed in underground disposal rooms, which will naturally close and compact the containers closer to one another over several centuries. This report details simulations to predict the final container configuration as an input to nuclear criticality assessments. Each container was discretely modeled, including the plywood and stainless steel pipe inside the 55-gallon drum, in order to capture its complex mechanical behavior. Although these high-fidelity simulations were computationally intensive, several different material models were considered in an attempt to reasonably bound the horizontal and vertical compaction percentages. When exceptionally strong materials were used for the containers, the horizontal and vertical closure respectively stabilized at 43:9 % and 93:7 %. At the other extreme, when the containers completely degraded and the clay seams between the salt layers were glued, the horizontal and vertical closure reached respective final values of 48:6 % and 100 %.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Analytical homogenization techniques applied to the Fickian diffusion: Effective diffusivity coefficient

For multiple applications in nuclear energy, the ability to accurately represent material behavior with a simplified model is important to facilitate practical engineering-scale simulations. In this work, we focus on the homogenized thermal response of a medium containing spherical inclusions, similar to a fuel form (compact or pebble) containing TRISO particles. An extensive survey on effective thermal conductivity modeling was performed in our previous study, considering a random distribution of mono-sized spherical inclusions in a continuous matrix. Using the analogy between heat conduction and the simplified Fickian diffusion (or fission product species conservation), we can use the same analytical homogenization methods to obtain ETC as for the effective diffusivity coefficient (EDC). We performed several numerical experiments at varying conditions to assess the validity of our hypothesis for EDC calculations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Artificial Intelligence for Event Reconstruction and Higgs Physics at CMS and Future Colliders

This dissertation charts a trajectory in which advances in artificial intelligence (AI) play a central role in pushing the high-energy physics frontier, complementing progress driven by higher collision energies and larger colliders. The discovery potential of the LHC and future colliders relies on accurate reconstruction of increasingly complex particle collision events. In the CMS experiment, this task is performed by the particle-flow (PF) algorithm. This dissertation presents the first implementation of a machine-learning-based particle-flow (MLPF) reconstruction in the CMS detector based on transformer architectures. In simulated top quark--antiquark pair (ttbar) events under LHC Run~3 (2023--2024) conditions, MLPF improves jet energy resolution by 10--20\% compared to standard PF for jets with transverse momentum between 30--100\GeV. Runtime performance is evaluated using simulated multijet events, with a median inference time of 20\unit{ms} per event on an NVIDIA L4 GPU, compa red to approximately 110\unit{ms} for standard PF. The MLPF algorithm is also validated on Run~3 collision data, representing the first data-validated ML-based reconstruction pipeline at any LHC experiment. We then extend MLPF toward future electron--positron colliders and introduce the first full-simulation cross-detector transfer learning workflow for PF reconstruction. The model is pre-trained on simulated events from the Compact Linear Collider detector (CLICdet) and fine-tuned on the CLIC-like detector (CLD) proposed for the Future Circular Collider (FCC). This approach achieves up to a 40\% improvement in jet energy resolution over rule-based reconstruction while reducing the required training dataset size by an order of magnitude, demonstrating the potential of AI to accelerate detector development and optimization. This dissertation also demonstrates how modern AI techniques enhance the sensitivity of LHC physics analyses. A CMS search for highly Lorentz-boosted Higgs bosons decaying to \textrm{W} boson pairs is presented, focusing on the single-lepton final state. A dedicated fine-tuning strategy for \ParT yields an approximately 70\% increase in expected sensitivity relative to the baseline model. The analysis uses proton--proton collision data at a center-of-mass energy of \ensuremath{\sqrt{s}=13\TeV} collected by CMS between 2016 and 2018, corresponding to an integrated luminosity of 138\ensuremath{\ \mathrm{fb}^{-1}}. The expected significance of the search is $1.86\sigma$, with an observed signal strength of $-0.19^{+0.48}_{-0.46}$. Finally, explainable AI techniques are applied to the MLPF and \ParticleNet algorithms using layerwise relevance propagation, showing that both models base their predictions on physically meaningful features consistent with our physics intuition. Together, these results demonstrate how advanced AI methods can enhance reconstruction, analysis sensitivity, and interpretability, shaping the next era of experimental parti cle physics.

Mokhtar, Farouk [UC, San Diego]↗

Ultracompact hybrid stars consistent with multimessenger astrophysics

In this work, we consider the consequences of phase transition in dense QCD on the properties of compact stars and implications for the observational program in gravitational wave and x-ray astrophysics. The key underlying assumption of our modeling is a strong first-order phase transition past the point where the hadronic branch of compact stars reaches the two-solar mass limit. Furthermore, our analysis predicts ultracompact stars with very small radii—in the range of 6–9 km—living on compact star sequences that are entirely consistent with the current multimessenger data. We show that sequences featuring two-solar mass hadronic stars consistent with radio-pulsar observations are also consistent with the inferences of large radii for massive neutron stars by NICER x-ray observations of neutron stars and the small radii predicted by gravitational waves analysis of the binary neutron star inspiral event GW170817 for our models that feature a strong first-order QCD phase transition.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Charges in the UV completion of neutral electrodynamics

A theory with a non-compact form-symmetry is described by two closed form fields of degrees k and d – k. Effective theory examples are non-linear electrodynamics, a photon field coupled to a neutron field, and a low energy Goldstone boson. We show these models cannot be completed in the UV without breaking the non-compact form-symmetry down to a compact one. This amounts to the existence of electric or magnetic charges. A theory with an unbroken non-compact k-form symmetry is massless and free.

't Hooft and Polyakov loops↗

Modeling the dynamic response of rock masses with multiple compliant fluid saturated joint sets—Part I: Mesoscale simulations

Recently a mesoscale model was developed that includes thermomechanically consistent constitutive equations with dissipation due to porous compaction, inelastic distortional deformation rate, and slipping on persistent dry joint surfaces. In this Part I of a two-part paper, we describe enhancements of the mesoscale model which include: normal compliance with hysteresis, non-persistent joints with finite area, joint sets with angular deviation, and the weakening effect of fluid pressure in the joints. Examples study the influences of these effects on average strength. These computationally expensive simulations are used to inspire functional forms in a continuum model, described in Part II, which is needed for large scale simulations of real applications.

42 ENGINEERING↗

Towards Compact Neural Networks via End-to-End Training: A Bayesian Tensor Approach with Automatic Rank Determination

Post-training model compression can reduce the inference costs of deep neural networks, but uncompressed training still consumes enormous hardware resources and energy. To enable low-energy training on edge devices, it is highly desirable to directly train a compact neural network from scratch with a low memory cost. Low-rank tensor decomposition is an effective approach to reduce the memory and computing costs of large neural networks. However, directly training low-rank tensorized neural networks is a very challenging task because it is hard to determine a proper tensor rank a priori, and the tensor rank controls both model complexity and accuracy. Here, this paper presents a novel end-to-end framework for low-rank tensorized training. We first develop a Bayesian model that supports various low-rank tensor formats (e.g., CANDECOMP/PARAFAC, Tucker, tensor-train, and tensor-train matrix) and reduces neural network parameters with automatic rank determination during training. Then we develop a customized Bayesian solver to train large-scale tensorized neural networks. Our training methods shows orders-of-magnitude parameter reduction and little accuracy loss (or even better accuracy) in the experiments. On a very large deep learning recommendation system with over 4.2 ×10 9 model parameters, our method can reduce the parameter number to 1.6 ×10 5 automatically in the training process (i.e., by 2.6 ×10 4 times) while achieving almost the same accuracy. Code is available at https://github.com/colehawkins/bayesian-tensor-rank-determination.

compact neural networks↗

More Realistic Intermediate Depth Dry Firn Densification in the Energy Exascale Earth System Model (E3SM)

Abstract Earth system models account for seasonal snow cover, but many do not accommodate the deeper snowpack on ice sheets (aka firn) that slowly transforms to ice under accumulating snowfall. To accommodate and resolve firn depths of up to 60 m in the Energy Exascale Earth System Model's land surface model (ELM), we add 11 layers to its snowpack and evaluate three dry snow compaction equations in multi‐century simulations. After comparing results from ELM simulations (forced with atmospheric reanalysis) with empirical data, we find that implementing into ELM a two‐stage firn densification model produces more accurate dry firn densities at intermediate depths of 20–60 m. Compared to modeling firn using the equations in the (12 layer) Community Land Model (version 5), switching to the two‐stage firn densification model (with 16 layers) significantly decreases root‐mean‐square errors in upper 60 m dry firn densities by an average of 41 kg m −3 (31%). Simulations with three different firn density parameterizations show that the two‐stage firn densification model should be used for applications that prioritize accurate upper 60 m firn air content (FAC) in regions where the mean annual surface temperature is greater than roughly −31°C. Because snow metamorphism, firn density, and FAC are major components in modeling ice sheet surface albedo, melt water retention, and climatic mass balance, these developments advance broader efforts to simulate the response of land ice to atmospheric forcing in Earth system models.

58 GEOSCIENCES↗