Atomistic modeling of the structure and diffusion processes at Al(110)/Si(001) interphase boundaries obtained by vapor deposition
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Li, Yang (ORCID:0000000311710852)↗
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Radar-Based Bayesian Estimation of Ice Crystal Growth Parameters within a Microphysical Model
The potential for polarimetric Doppler radar measurements to improve predictions of ice microphysical processes within an idealized model–observational framework is examined. In an effort to more rigorously constrain ice growth processes (e.g., vapor deposition) with observations of natural clouds, a novel framework is developed to compare simulated and observed radar measurements, coupling a bulk adaptive-habit model of vapor growth to a polarimetric radar forward model. Bayesian inference on key microphysical model parameters is then used, via a Markov chain Monte Carlo sampler, to estimate the probability distribution of the model parameters. The statistical formalism of this method allows for robust estimates of the optimal parameter values, along with (non-Gaussian) estimates of their uncertainty. To demonstrate this framework, observations from Department of Energy radars in the Arctic during a case of pristine ice precipitation are used to constrain vapor deposition parameters in the adaptive habit model. The resulting parameter probability distributions provide physically plausible changes in ice particle density and aspect ratio during growth. A lack of direct constraint on the number concentration produces a range of possible mean particle sizes, with the mean size inversely correlated to number concentration. Consistency is found between the estimated inherent growth ratio and independent laboratory measurements, increasing confidence in the parameter PDFs and demonstrating the effectiveness of the radar measurements in constraining the parameters. Furthermore, the combined Doppler and polarimetric observations produce the highest-confidence estimates of the parameter PDFs, with the Doppler measurements providing a stronger constraint for this case.
54 ENVIRONMENTAL SCIENCES↗
Predictive Modeling of Electrodeposition in a Single Pore Flow-Through Electrode: From Electronucleation to Coating Thickness Uniformity
The emergence of advanced manufacturing methods capable of producing porous three-dimensional structures has expanded the design space for next-generation functional components. The ability to fabricate ordered 3D foams for use in electrocatalysis reactors has increased the need for controlled deposition of catalytic metals onto porous support materials, such as carbon. However, there is a lack of clear design guidelines for electrodeposition onto 3D substrates, due to the geometric complexity and multi-scale nature of the problem. Furthermore, electro-nucleation phenomena are often overlooked in macro-scale models of current distribution during deposition. Here, a graphite flow-through electrode (FTE) is used as a model system for copper deposition within a single pore. Potential distributions and electro-nucleation phenomena are coupled in a continuum level model by incorporating nucleation size and density as a function of overpotential, determined experimentally using in situ atomic force microscopy (AFM). The model predictions are validated by measuring the coating uniformity in the pore using micro-computed X-ray tomography (μCT). A scaling analysis comprising dimensionless parameters such as the Wagner number is presented. The simplified scaling relationship framework can guide the electrodeposition process and electrode design to optimize plating of porous substrates under fluid flow conditions.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Inhomogeneous energy injection in the 21-cm power spectrum: Sensitivity to dark matter decay
The 21-cm signal provides a novel avenue to measure the thermal state of the Universe during cosmic dawn and reionization (redshifts z ~ 5–30), and thus to probe energy injection from decaying or annihilating dark matter (DM). These DM processes are inherently inhomogeneous: both decay and annihilation are density-dependent, and furthermore, the fraction of injected energy that is deposited at each point depends on the gas ionization and density, leading to further anisotropies in absorption and propagation. In this work, we develop a new framework for modeling the impact of spatially inhomogeneous energy injection and deposition during cosmic dawn, accounting for ionization and baryon density dependence, as well as the attenuation of propagating photons. We showcase how this first completely inhomogeneous treatment affects the predicted 21-cm power spectrum in the presence of exotic sources of energy injection, and forecast the constraints that upcoming HERA measurements of the 21-cm power spectrum will set on DM decays to photons and to electron/positron pairs. These projected constraints considerably surpass those derived from CMB and Lyman-a measurements, and for decays to electron/positron pairs they exceed all existing constraints in the sub-GeV mass range, reaching lifetimes of ~10 28 s. Our analysis demonstrates the unprecedented sensitivity of 21-cm cosmology to exotic sources of energy injection during the cosmic dark ages. Our code, dm21cm, includes all these effects and is publicly available in an accompanying release.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Assessing Metal Ion Assignment Accuracy in Protein Data Bank Models via Elemental Spectroscopy
Accurate representation of metal ions in macromolecular structures is critical for chemical interpretation, computational modeling, and machine-learning methods that rely on Protein Data Bank (PDB) entries. However, the elemental identity of metals modeled in crystallographic structures is often inferred indirectly and rarely validated experimentally. Here, we combine Particle Induced X-ray Emission (PIXE) and X-ray Fluorescence Spectroscopy (XRFS) to determine the elemental composition of protein samples used to generate 70 deposited metalloprotein crystal structures. By analyzing the original protein material employed for crystallization, but before the addition of crystallization buffer solutions, we assess whether the modeled metal ions in deposited structures are consistent with experimentally detectable elemental content. We find that in a majority of cases, the metals modeled in the corresponding PDB entries are inconsistent with the metals present in the protein samples before crystallization, or that additional metals are present but not represented in the structural models. Spectroscopic results were integrated with automated crystallographic validation metrics, including real-space Z-difference (RSZD) analysis and systematic rerefinement, to evaluate atomic-number mismatch at metal sites. PIXE and XRFS show strong agreement for dominant elemental signals and provide complementary, scalable approaches for identifying suspect metal assignments. This work does not address physiological or functional metalation but instead highlights a widespread data integrity issue in deposited macromolecular structures, PDB-wide. These results establish an experimentally corroborated link between elemental identity and crystallographic validation metrics, enabling the large-scale detection of chemically inconsistent annotations in structural databases used for computational modeling and machine learning.
Crystallization↗
Numerical Simulations of Carbon Dioxide Storage Efficiency in Heterogeneous Reservoir Models
The U.S. Department of Energy’s National Energy Technology Laboratory (DOE-NETL) has been developing methods and tools (the online Carbon Dioxide Storage prospeCtive Resource Estimation Excel aNalysis (CO2-SCREEN) tool) to estimate carbon dioxide (CO2) storage potential in subsurface reservoirs. The CO2 storage efficiency terms are input in the tool to calculate storage potential in targeted reservoirs. In this effort, two CO2 storage efficiency terms were evaluated: volumetric displacement ( E V ) and microscopic displacement ( E d ). The first term deals with efficiency of CO2 propagation into an accessible reservoir volume, while the second term evaluates effectiveness of native fluid displacement with CO2. The interpreted well logs and core sample measurements were applied to create the heterogeneous reservoir models including geostatistical realizations of porosity and intrinsic permeability fields. Supercritical CO2 was injected over the course of 30 years into brine-saturated reservoir models for clastics, limestone, and dolomite lithologies and deltaic fluvial, aeolian, shallow marine, and reef depositional environments by means of varying reservoir parameters and injection scenarios. The reservoir models providing vertically heterogeneous petrophysical properties and designated as “layered reservoir models” (with homogeneous parameters along each layer of the model) were not determined to be a transition between the homogeneous and heterogeneous models in respect to storage efficiency. Another finding shows that high-efficiency factors do not necessarily mean increased CO2 storage; they rather indicate that the available volume and pore space are more fully utilized. The CO2 storage efficiency factors were evaluated dynamically at the select time points using P 10 ‐ P 50 ‐ P 90 percentiles. The results of this study show that the P 10 ‐ P 90 distribution for volumetric efficiency is wider when compared to the microscopic efficiency. It was found that where dominant buoyancy forces drive the plume to the top of a target formation, the volumetric efficiency is low. Tighter sandstone and carbonate formations show prevalence of capillary forces and better utilization of reservoir volume.
Myshakin, Evgeniy M.↗
Shock generated vorticity in spark discharges
Spark discharges induce a complex flow field consisting of a shock wave at early times (~ 1 μs), a pair of vortex rings, and a hot gas kernel. The vortex rings entrain ambient gas into the hot gas kernel and control its cooling and expansion. In this work, we investigate the shock wave's contribution in producing the vortex ring vorticity. We analyze high-speed (700 kHz) schlieren images of the shock wave for a range of electrical energies to measure the shock properties and estimate shock velocity and curvature. These measurements are combined with a model to calculate the vorticity generated. The measurements show that the highest vorticity is generated near the peak shock curvature location, and the shock curvature and strength increase with electrical energy deposited. A comparison of the vorticity estimated from the model to vorticity measurements from stereoscopic particle image velocimetry shows the results to be statistically equivalent. Furthermore, this suggests that the shock curvature and velocity contribute to the vortex rings induced by spark discharges.
42 ENGINEERING↗
Towards fast, accurate predictions of RF simulations via data-driven modeling: Forward and lateral models
Three machine learning techniques (multilayer perceptron, random forest, and Gaussian process) provide fast surrogate models for lower hybrid current drive (LHCD) simulations. A single GENRAY/CQL3D simulation without radial diffusion of fast electrons requires several minutes of wall-clock time to complete, which is acceptable for many purposes, but too slow for integrated modeling and real-time control applications. More accurate simulations with fast electron diffusion are even slower, requiring multiple hours of run time with parallel processing. The machine learning models use a database of 16,000+ GEN-RAY/CQL3D simulations for training, validation, and testing. Latin hypercube sampling methods implemented in πScope ensure that the database covers the range of 9 input parameters (n e0 , T e0 , I p , B t , R 0 , n ∥︀ , Z e f f , V loop , P LHCD ) with sufficient density in all regions of parameter space. The surrogate models reduce the computation time from minutes-hours to ms with high accuracy across the input parameter space. Data-driven surrogate models also allow for solving inverse and “lateral” problems. A surrogate model for the inverse problem maps from a desired current drive or power deposition profile to a set of input parameters that would result in such a profile, while a surrogate model for the lateral problem maps from a measured experimental quantity such as hard x-ray emission to a current drive or power deposition profile. In conclusion, the πScope database creation workflow is flexible and applicable to other RF simulation codes such as TORIC.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Dynamics of organic matter molecular composition under aerobic decomposition and their response to the nitrogen addition in grassland soils
Grassland soils store a substantial proportion of the global soil carbon (C) stock. The transformation of C in grassland soils with respect to chemical composition and persistence strongly regulate the predicted terrestrial-atmosphere C flux in global C biogeochemical cycling models. In addition, increasing atmospheric nitrogen (N) deposition alters C chemistry in grassland soils. However, there remains controversy about the importance of mineralogical versus biochemical preservation of soil C, as well as uncertainty regarding how grassland soil C chemistry responds to elevated N. This study used grassland soils with diverse soil organic matter (SOM) chemistries in an 8-month aerobic incubation experiment to evaluate whether the chemical composition of SOM converged across sites over time, and how SOM persistence responded to the N addition. This study demonstrates that over the course of incubation, the richness of labile compounds decreased in soils with less ferrihydrite content, whereas labile compounds were more persistent in ferrihydrite rich soils. In contrast, we found that the richness of more complex compounds increased over the incubation in most sites, independent of soil mineralogy. Moreover, we demonstrate the extent to which the diverse chemical composition of SOM converged among sites in response to microbial decomposition. N fertilization decreased soil respiration and inhibited the convergence of molecular composition across ecosystems by altering N demand for microbial metabolism and chemical interactions between minerals and organic molecules. This study provides original evidence that the decomposition and metabolism of labile organic molecules were largely regulated by soil mineralogy (physicochemical preservation), while the metabolism of more complex organic molecules was controlled by substrate complexity (biochemical preservation) independent to mineral-organic interactions. This study advanced our understanding of the dynamic biogeochemical cycling of C by unveiling that N addition dampened C respiration and diminished the convergence of SOM chemistry across diverse grassland ecosystems.
54 ENVIRONMENTAL SCIENCES↗
Lipid accumulation-induced hepatocyte senescence regulates the activation of hepatic stellate cells through the Nrf2-antioxidant response element pathway
Highlights: • Oxidative stress caused by lipid deposition causes hepatocyte senescence. • Free fatty acid-induced senescent hepatocytes promote hepatic stellate cell activation and development of hepatic fibrosis. • Senescent hepatocytes regulate hepatic fibrosis through the Nrf2-antioxidant response element pathway. Non-alcoholic fatty liver disease (NAFLD) has become the most prevalent chronic liver disease globally. Elderly individuals are at a higher risk of developing NAFLD with severe clinical outcomes. Although NAFLD is closely related to liver aging, the role of hepatocyte senescence in the progression of NAFLD, especially in the development of fibrosis, is still unclear. The early stage of NAFLD is mainly characterized by lipid accumulation in hepatocytes, which could lead to severe oxidative stress, causing cellular senescence. In the present study, hepatocytes cultured in the presence of free fatty acids to induce lipid deposition were used as a hepatocyte senescence model in vitro. Senescent hepatocytes significantly increased the activation of co-cultured primary hepatic stellate cells (HSCs) and the expression of pro-fibrosis molecules. Moreover, the antioxidant regulator nuclear factor erythroid 2-related factor 2 (Nrf2) that was upregulated in senescent hepatocytes was found to be related to the activation of co-cultured HSCs. The Nrf2 agonist sulforaphane, which upregulated the transcriptional activity of the Nrf2-antioxidant response element (ARE) pathway, remarkably inhibited hepatocyte senescence and its activation effect on HSCs. However, the liver tissue obtained from non-alcoholic steatohepatitis (NASH) mice with Nrf2 knockdown showed decreased antioxidation and significant liver senescence and fibrosis. In conclusion, this study confirmed that lipid accumulation induces hepatocyte senescence, which leads to HSC activation and development of hepatic fibrosis. Increasing the activity of the Nrf2-ARE antioxidant pathway in senescent hepatocytes elicited the opposite effect, suggesting that targeting Nrf2 may prevent or delay the progression of aging-related liver fibrosis in NASH.
60 APPLIED LIFE SCIENCES↗
Confocal Raman Microscopy Investigation of Phospholipid Monolayers Deposited on Nitrile-Modified Surfaces in Porous Silica Particles
Phospholipid bilayers deposited on a variety of surfaces offer models for investigation of the lipid membrane structure and supports for biocompatible sensors. Hybrid-supported phospholipid bilayers (HSLBs) are stable membrane models for these investigations, typically prepared by self-assembly of a lipid monolayer over an n-alkane-modified surface. HSLBs have been prepared on n-alkyl chain-modified silica and used for lipophilicity-based chromatographic separations. The structure of these hybrid bilayers differs from vesicle membranes where the lipid head group spacing is greater due to interdigitation of the lipid acyl chains with the underlying n-alkyl chains bound to the silica surface. This interdigitated structure exhibits a broader melting transition at a higher temperature due to strong interactions between the lipid acyl chains and the immobile n-alkyl chains bound to silica. In the present work, we seek to reduce the interactions between a lipid monolayer and its supporting substrate by self-assembly of 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) on porous silica functionalized with nitrile-terminated surface ligands. The frequency of Raman scattering of the surface -C≡N stretching mode at the lipid–nitrile interface is consistent with an n-alkane-like environment and insensitive to lipid head group charge, indicating that the lipid acyl chains are in contact with the surface nitrile groups. The head group area of this lipid monolayer was determined from the within-particle phospholipid concentration and silica specific surface area and found to be 54 ± 2 Å 2 , equivalent to the head group area of a DMPC vesicle bilayer. The structure of these nitrile-supported phospholipid monolayers was characterized below and above their melting transition by confocal Raman microscopy and found to be nearly identical to DMPC vesicle bilayers. Their narrow gel-to-fluid-phase melting transition is equivalent to dispersed DMPC vesicles, indicating that the acyl chain structure on the nitrile support mimics the outer leaflet structure of a vesicle membrane.
36 MATERIALS SCIENCE↗
Improved Mechanical Adhesion Enabled by Bilayer Hole Transport Layers in Perovskite Solar Cells
We investigate buried-interface mechanical integrity in metal-halide perovskite half-cells using carbazole-based self-assembled monolayers (SAMs) and bilayer hole transport layers composed of metal oxide underlayers and SAMs. Combining macroscopic and microscopic characterization, we quantify interfacial fracture energy (Gc) and identify delamination pathways. SAM deposition on NiOx increases Gc by approximately 10-fold compared with ITO, highlighting the importance of oxide underlayer selection. To isolate the effect of removing noncovalently bonded SAM molecules, we use vapor-deposited perovskite as a solvent-free model system, decoupling the rinse step inherent to solution processing. Removing loosely bound SAM molecules increases Gc from 0.94 +- 0.08 J.m-2 to 4.82 +- 0.79 J.m-2. These results show that oxide selection and SAM binding quality are both critical for strengthening buried interfaces and designing mechanically robust perovskite solar cells.
14 SOLAR ENERGY↗
Estimating the CO 2 Fertilization Effect on Extratropical Forest Productivity From Flux‐Tower Observations
Abstract The land sink of anthropogenic carbon emissions, a crucial component of mitigating climate change, is primarily attributed to the CO 2 fertilization effect on global gross primary productivity (GPP). However, direct observational evidence of this effect remains scarce, hampered by challenges in disentangling the CO 2 fertilization effect from other long‐term confounding drivers, particularly climatic changes. Here, we introduce a novel statistical approach to separate the CO 2 fertilization effect on photosynthetic carbon uptake using eddy covariance (EC) records across 38 extratropical forest sites. We find the median stimulation rate of GPP to be 3.2 ± 0.9 gC m −2 yr −1 ppm −1 (or 16.4 ± 4.2% per 100 ppm) under increasing atmospheric CO 2 across these sites, respectively. To validate the robustness of our findings, we test our statistical method using factorial simulations of an ensemble of process‐based land surface models. We address additional factors, including nitrogen deposition and land management, that may impact plant productivity, potentially confounding the attribution to the CO 2 fertilization effect. Assuming these site‐specific effects offset to some extent across sites as random factors, the estimated median value still reflects the strength of the CO 2 fertilization effect. However, disentanglement of these long‐term effects, often inseparable by timescale, requires further causal research. Our study provides direct evidence that the photosynthetic stimulation is maintained under long‐term CO 2 fertilization across multiple EC sites. Such observation‐based quantification is key to constraining the long‐standing uncertainties in the land carbon cycle under rising CO 2 concentrations.
Environmental Sciences & Ecology↗
Performance of microchannel plate based detectors for <25 keV x rays: Monte Carlo simulations and comparisons with experimental results
We present the results of Monte Carlo simulations of the microchannel plate (MCP) response to x rays in the 250 eV to 25 keV energy range as a function of both x-ray energy and impact angle and their comparisons with the experimental results from the X8A beamline at the National Synchrotron Light Source at Brookhaven National Laboratory. Incoming x rays interact with the lead glass of the microchannel plate, producing photoelectrons. Transport of the photoelectrons is neglected in this model, and it is assumed that photoelectrons deposit all their energy at the point they are created. This deposition leads to the generation of many secondary electrons, some fraction of which diffuse to the MCP pore surface where they can initiate secondary electron cascades in the pore under an external voltage bias. X-ray penetration through multiple MCP pore walls is increasingly important above 5 keV, and the effect of this penetration on MCP performance is studied. In agreement with past measurements, we find that the dependence of MCP sensitivity with angle relative to the pore bias changes from a cotangent dependence to angular independence and then proceeds to a secant dependence as the x-ray energy increases. We also find that with the increasing x-ray energy, the MCP gain sensitivity as a function of bias voltage decreases. The simulations also demonstrate that for x rays incident normal to the MCP surface, spatial resolution shows little dependence on the x-ray energy but degrades with the increasing x-ray energy as the angle of incidence relative to the surface normal increases. This agrees with experimental measurements. Simulation studies have also been completed for MCPs gated with a subnanosecond voltage pulse. In this work, we find that the optical gate profile width increases as the x-ray energy is increased above 5 keV, a consequence of increased x-ray penetration at energies >5 keV. Simulations of the pulsed dynamic range show that the dynamic range varies between ~100 and 1000 depending on x-ray energy and peak voltage.
47 OTHER INSTRUMENTATION↗
Quantification of the effect of uncertainty on impurity migration in PISCES-A simulated with GITR
A Bayesian inference strategy has been used to estimate uncertain inputs to global impurity transport code (GITR) modeling predictions of tungsten erosion and migration in the linear plasma device, PISCES-A. This allows quantification of GITR output uncertainty based on the uncertainties in measured PISCES-A plasma electron density and temperature profiles (n e , T e ) used as inputs to GITR. The technique has been applied for comparison to dedicated experiments performed for high (4 × 10 22 m –2 s –1 ) and low (5 × 10 21 m –2 s –1 ) flux 250 eV He–plasma exposed tungsten (W) targets designed to assess the net and gross erosion of tungsten, and corresponding W impurity transport. The W target design and orientation, impurity collector, and diagnostics, have been designed to eliminate complexities associated with tokamak divertor plasma exposures (inclined target, mixed plasma species, re-erosion, etc) to benchmark results against the trace impurity transport model simulated by GITR. The simulated results of the erosion, migration, and re-deposition of W during the experiment from the GITR code coupled to materials response models are presented. Specifically, the modeled and experimental W I emission spectroscopy data for a 429.4 nm line and net erosion through the target and collector mass difference measurements are compared. Furthermore, the methodology provides predictions of observable quantities of interest with quantified uncertainty, allowing estimation of moments, together with the sensitivities to plasma temperature and density.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Demonstration of MELCOR and MACCS Capabilities for Molten Salt Reactor Decay Heat Removal During both Normal Operations and Salt Spill Scenarios
This report provides a demonstration of MELCOR and MELCOR Accident Consequence Code System (MACCS) capabilities to perform a dose assessment for a Molten Salt Reactor (MSR) off-gas system. A primary containment system salt spill is used as the off-normal scenario, along with a normal operation dose assessment for comparison. This report discusses the tools, methods, and information used in this assessment so that it may be utilized as a starting point for future advanced reactor consequence analyses. This report also highlights several gaps, to include the need for reactor inventory information specific to advanced reactors, and the need for specific atmospheric transport models that take into account the unique deposition behaviors of tritium and carbon-14, and makes recommendations for closing these gaps. This report satisfies the DOE NE Milestone M4RD-21SN0601062.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Investigating the Chemical Reactivity of Lithium Silicate Model SEI Layers
Silicon anodes suffer from an unstable solid electrolyte interphase (SEI) layer that contributes to undesirable capacity fade with cycling. A key part to addressing this unstable SEI formation is to examine how certain components of the SEI react with the electrolyte over time. One SEI component that has not been thoroughly studied in the context of the chemical reactivity against the electrolyte is lithiated silicate. Four model silicate thin films with increasing lithium content were deposited by radio frequency (RF) magnetron sputtering to study how the lithiation of the native oxide on a silicon anode affects the chemical stability of the anode surface. SiO2, Li2Si2O5, Li2SiO3, and Li3SiOx films were exposed to 1.2 M LiPF6 in the 3:7 wt% ethylene carbonate/ethyl methyl carbonate (EC/EMC) electrolyte for periods of time that are representative of the amount of time it takes to undergo cell formations. Soaked samples were rinsed, dried, and characterized by a combination of attenuated total reflectance-infrared spectroscopy (ATR-IR), focused ion beam-secondary electron microscopy (FIB-SEM), and X-ray photoelectron spectroscopy (XPS) depth profiling. It was found that the rate of the decrease in film thickness of the silicates exposed to the electrolyte over time increases as a function of the lithium content in the thin film. This reaction involves HF etching and LiPF6 salt degradation leading to silicate loss and fluorination throughout the bulk. Understanding this chemical instability is critical to determining the overall mechanism of SEI degradation over time.
ADVANCED PROPULSION SYSTEMS,ENERGY STORAGE↗
Requirements Description of GAMSOR and GAMSRC
This report presents the modeling and simulation capabilities of Argonne National Laboratory’s GAMSOR and GAMSRC code that is used in present reactor analysis activities. These capabilities will then be used to establish the set of verification tasks necessary to verify GAMSOR for use on commercial projects. A similar approach was taken for the PERSENT, REBUS and DIF3D software packages. The GAMSOR program is a modified version of DIF3D used to obtain the coupled neutron gamma flux distributions for a given reactor system. GAMSOR was first developed in the 1980s and its work has progressed in parallel with DIF3D throughout its various development phases. While GAMSOR is compatible with DIF3D-FD and DIF3D-Nodal, DIF3D-VARIANT is most commonly used today and will be the focus of the present verification effort. As covered in [1], GAMSOR was built to provide more accurate heating distributions by explicitly solving for both the gamma and neutron heating distributions. Without this consideration, gamma heat is normally assumed to be deposited locally at the site of gamma production. This is acceptable for modeling some phenomena because the total energy production is preserved, but it can lead to inaccurate approximations of fluence-dependent behaviors such as fuel performance, swelling, cladding embrittlement, radiation induced creep, and power peaking. The outputs from GAMSOR are contained in multiple intermediate and final output files: FIXSRC, VARSRC, GTFLUX, GHFLUX, PWDINT, NPDINT, and GPDINT. DIF3D normally produces a PWDINT file containing power density results, with the assumption that gamma rays are absorbed where they are emitted (i.e., energy deposition is local with no modeled transport). With GAMSOR, neutron power density (NPDINT) and gamma power density (GPDINT) are both produced, with their summed power densities replacing the results in PWDINT for total heating (i.e., recoverable) power density.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗