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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Relativistic Three-Dimensional Lippmann-Schwinger Cross Sections for Space Radiation Applications

Radiation transport codes require accurate nuclear cross sections to compute particle fluences inside shielding materials. The Tripathi semi-empirical reaction cross section, which includes over 60 parameters tuned to nucleon-nucleus (NA) and nucleus-nucleus (AA) data, has been used in many of the world’s best-known transport codes. Although this parameterization fits well to reaction cross section data, the predictive capability of any parameterization is questionable when it is used beyond the range of the data to which it was tuned. Using uncertainty analysis, it is shown that a relativistic Three- Dimensional Lippmann-Schwinger (LS3D) equation model based on Multiple Scatter- ing Theory (MST) that uses 5 parameterizations—3 fundamental parameterizations to nucleon-nucleon (NN) data and 2 nuclear charge density parameterizations—predicts NA and AA reaction cross sections as well as the Tripathi cross section parameterization for reactions in which the kinetic energy of the projectile in the laboratory frame (TLab) is greater than 220 MeV/n. The relativistic LS3D model has the additional advantage of being able to predict highly accurate total and elastic cross sections. Consequently, it is recommended that the relativistic LS3D model be used for space radiation applications in which TLab > 220 MeV/n.

C M Werneth↗
NASA NTRSDate not supplied

Flow Characterization of the NASA Langley Unitary Plan WindTunnel, Test Section 2: Computational Results

Flow in the empty Unitary Planform Wind Tunnel at the NASA Langley Research Center issimulated with computational fluid dynamics methods. The objectives are to assess CFD’s truepredictive capability and to generate flow-field maps upstream of the tunnel’s test section foruse in associated vehicle tests. Multiple CFD solvers, grid adaption methods, and turbulencemodels are used by five teams doing the simulations. The simulation domain is as large aspractical: from the start of the settling chamber, just downstream of the last set of turningvanes, to well downstream of the test section. Simulations are done at three Mach numbers andseveral Reynolds numbers that cover most of the tunnel’s operating range. The sensitivity ofthe CFD solutions to simulation process details, including turbulence model, spatial resolutionand settling-chamber inflow velocity profile, is characterized. Significant sensitivities in somedetails of the predicted test section flow are described. CFD predicts that details of flow inthe settling chamber can affect the flow in the test section. Turning of the flow through thetunnel contraction and past nozzle-block hardware generates streamwise vortices, some ofwhich survive into the core of the test section, principally at low Mach number. Preliminarycomparisons to experimental measurements are given. The major flow characteristics andthe dynamical vortices predicted by CFD exist in the experiment. Several details in CFD andexperiment are observed to differ, including the effects of the vortices and features that appearto be Mach waves in the test section. Sensitivity to grid resolution and turbulence modelingis noted in the vortices; no potential cause for the differences in Mach waves has yet beenidentified in the CFD sensitivity studies.

wind tunnel↗
NASA NTRSDate not supplied

Dissociative Recombination (DR) and Associative Ionization (AI) Cross Section Calculations for the NO+ + e yields N + O (2D+3P, 2P+3P, and 2D+1D) Reaction for Atmospheric Entry Modeling

During entry of a space craft into Earth atmosphere, the flow surrounding the vehicle becomes partially ionized leading to significant cation and free-electron production. Subsequently, electron impact excitation and dissociation form radiating excited state species that contribute to the heat load on the vehicle. While experimental data on selected total cross sections are available, few experiments address the need for accurate AI cross sections for metastable atomic states at the high temperatures realized in atmospheric re-entry. In order to maintain desired safety margins during atmospheric entry of a space vehicle, chemical reaction models need to accurately account for this process. For the present study, we have computed vibrationally resolved cross sections for the DR of NO+ for electron energies between 0.01 to 10 eV and apply microscopic reversibility to obtain the AI cross sections and rate coefficients. For the DR cross section calculations, we use state-of-the-art MRCI potential energy curves. The resulting adiabatic potential curves are transformed to a diabatic representation, which is used in time-dependent wave packet calculations to describe the nuclear motion of the dissociating cation upon collision with an electron. Based on the wave function evolution in time, these calculations provide T-matrix and cross sections for the DR including recombination into the low energy metastable atomic states. The DR and AI rate coefficients are compared with the available experimental data.

Ewa Papajak↗
NASA NTRS2018

New O+CO2 Scattering Cross Sections and Their Impact on Photochemical Atmospheric Escape of Oxygen from Mars

Dissociative recombination of O2+ and CO2+ molecular ions in the upper atmosphere of Mars is a major source of suprathermal (hot) oxygen atoms. A significant fraction of hot O atoms are sufficiently fast to overcome Mars' gravitational potential and escape to space. This mechanism is known as photochemical escape (PE) and found to be one of the major escape mechanisms presently active on Mars. The Mars Atmosphere and Volatile Evolution Mission (MAVEN) can constrain the PE rate from measurements of electron temperature and density and ion temperature and density. Escape probabilities of hot O can then be constructed from in-situ neutral densities and escaping O flux loss due to collisions with atmospheric background gases. Due to CO2 abundance in the upper atmosphere, O+CO2 scattering is the most important sink of the escaping hot O flux that strongly affects estimates of total atomic oxygen escape rate obtained from MAVEN data, as outlined above. New O+CO2 elastic and inelastic cross sections were constructed from first principles for collision energies from 0.01-5 eV. O(3P)+CO2 collisions were described using new 4D electronic potential energy surfaces (PESs) for restricted geometries. Three lowest triplet states of CO2 were considered for symmetric, bending, and asymmetric vibrational modes. The cross sections were determined from close-coupling calculations performed on individual surfaces using vibrating rotor approximations for CO2 molecule. Differential and momentum transfer cross sections, of use in energy transfer atmospheric models, were also constructed. The obtained cross sections are in excellent agreement with published results. Our new elastic cross sections are significantly smaller than assumed in earlier atmospheric escape models, resulting in larger photochemical escape rate of O from Mars, as estimated from a 1D escape model. Our results agree well with estimated hot O flux (about 9 x 10(sup 25) s(sup -1)) derived from altitude profiles of 130.4 nm O emission measured up to ~4,000 km by the Imaging Ultraviolet Spectrograph on MAVEN orbiter.

Atmospheric↗
NASA NTRSDate not supplied

Upwind Buildings Effects on Test Section Performance of the NFAC 80- by 120-Foot Wind Tunnel

In 2013, a new development began that would put multi-story buildings within the exclusion zone of the 80- by 120- Foot Wind Tunnel (80x120) inlet that exceeded the then existing building height restriction. This raised questions concerning whether the tunnel could operate within the acceptable turbulence limits of ≤ 0.5% in the axial direction over 75% area in the wind tunnel test section. The goal of this testing was to determine the validity of this hypothesis. Testing was performed using the 1/50th-scale model of the 80- by 120-FootWind Tunnel within the full-scale facility test section to characterize the model’s test section turbulence levels as a function of wind direction with the presence of the upwind buildings that are currently being constructed. This paper reports the first testing performed to date on the 80x120 inlet as-built under controlled test conditions for wind magnitude and wind onset direction for a variety of buildings in the inlet external flow field, including no buildings (the control case). This testing determined that, at rated operational conditions the upwind blockages caused no increase in turbulence intensity levels measured in the test section and, in some limited cases, caused the turbulence levels to decrease. Lastly, looking at generic rectangular blockages showed that, to have a discernible effect on test section turbulence levels, scaled 100-ft tall blockages need to be within 600 ft of the existing inlet.

Upwind Buildings Effects↗
DOE OSTI2025

Measurement of the inclusive cross sections for W and Z boson production in proton-proton collisions at $\sqrt{\textrm{s}}$ = 5.02 and 13 TeV

Measurements of fiducial and total inclusive cross sections for W and Z boson production are presented in proton-proton collisions at $ \sqrt{s} $ = 5.02 and 13 TeV. Electron and muon decay modes (ℓ = e or μ) are studied in the data collected with the CMS detector in 2017, in dedicated runs with reduced instantaneous luminosity. The data sets correspond to integrated luminosities of 298 ± 6 pb$^{−1}$ at 5.02 TeV and 206 ± 5 pb$^{−1}$ at 13 TeV. Measured values of the products of the total inclusive cross sections and the branching fractions at 5.02 TeV are σ(pp → W + X)$ \mathcal{B} $(W → ℓν) = 7300 ± 10 (stat) ± 60 (syst) ± 140 (lumi) pb, and σ(pp → Z+X)$ \mathcal{B} $(Z → ℓ$^{+}$ℓ$^{−}$) = 669 ± 2 (stat) ± 6 (syst) ± 13 (lumi) pb for the dilepton invariant mass in the range of 60–120 GeV. The corresponding results at 13 TeV are 20480 ± 10 (stat) ± 170 (syst) ± 470 (lumi) pb and 1952 ± 4 (stat) ± 18 (syst) ± 45 (lumi) pb. The measured values agree with cross section calculations at next-to-next-to-leading-order in perturbative quantum chromodynamics. Fiducial and total inclusive cross sections, ratios of cross sections of W$^{+}$ and W$^{−}$ production as well as inclusive W and Z boson production, and ratios of these measurements at 5.02 and 13 TeV are reported.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Inclusive and differential cross section measurements of $ \textrm{t}\overline{\textrm{t}}\textrm{b}\overline{\textrm{b}} $ production in the lepton+jets channel at $ \sqrt{s} $ = 13 TeV

Measurements of inclusive and normalized differential cross sections of the associated production of top quark-antiquark and bottom quark-antiquark pairs, $ \textrm{t}\overline{\textrm{t}}\textrm{b}\overline{\textrm{b}} $, are presented. The results are based on data from proton-proton collisions collected by the CMS detector at a centre-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 138 fb$^{−1}$. The cross sections are measured in the lepton+jets decay channel of the top quark pair, using events containing exactly one isolated electron or muon and at least five jets. Measurements are made in four fiducial phase space regions, targeting different aspects of the $ \textrm{t}\overline{\textrm{t}}\textrm{b}\overline{\textrm{b}} $ process. Distributions are unfolded to the particle level through maximum likelihood fits, and compared with predictions from several event generators. The inclusive cross section measurements of this process in the fiducial phase space regions are the most precise to date. In most cases, the measured inclusive cross sections exceed the predictions with the chosen generator settings. The only exception is when using a particular choice of dynamic renormalization scale, $ {\mu}_{\textrm{R}}=\frac{1}{2}{\prod}_{i=\textrm{t},\overline{\textrm{t}},\textrm{b},\overline{\textrm{b}}}{m}_{\textrm{T},i}^{1/4} $, where $ {m}_{\textrm{T},i}^2={m}_i^2+{p}_{\textrm{T},i}^2 $ are the transverse masses of top and bottom quarks. The differential cross sections show varying degrees of compatibility with the theoretical predictions, and none of the tested generators with the chosen settings simultaneously describe all the measured distributions.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Enhanced Spatial Proteomics and Metabolomics from a Single Tissue Section Using MALDI-MSI and LCM-microPOTS Platforms

Spatially resolved mass spectrometry (MS)-based multi-omics workflows are becoming more utilized for revealing the complex biology that occurs within tissues. However, these approaches commonly require multiple independent tissue sections to analyze the metabolite and protein compositions of these samples. This poses a significant challenge in preserving cell- or region-specific molecular fidelity, as variations between tissue sections can compromise the accurate correlation of molecular data. Here, in this study, we developed workflows for comprehensive multi-omics profiling from a single tissue section (STS) using different MS modalities. We enhanced the functionality of an electrically insulated substrate by employing metal-assisted approaches that enabled both MS-based untargeted spatial metabolomics and proteomics from STS. This allowed metabolite imaging using matrix-assisted laser desorption/ionization-MS imaging (MALDI-MSI), without compromising it for subsequent proteome profiling with laser capture microdissection (LCM)-based technology. Specifically, implementing copper tape as a backing for polyethylene naphthalate (PEN) slides enabled the detection of >140 metabolites across a poplar root tissue section using MALDI-trapped ion mobility spectrometry time of flight (timsTOF)-MS. Afterwards, we detected 6,571 unique proteins from two distinct root regions by leveraging LCM technology coupled to our microdroplet based sample preparation approach. We also developed an alternative workflow utilizing gold-coated PEN substrates for imaging with MALDI-Fourier-transform ion cyclotron resonance (FTICR)-MS, which permitted the profiling of >170 metabolites and the identification of 6,542 unique proteins across a single poplar root tissue section. These results were comparable to using each assay independently without modifications. These approaches offer new opportunities for high-resolution molecular profiling of multiple omics-levels across biological tissues.

Veličković, Marija [Pacific Northwest National Lab↗
DOE OSTI2024

Rovibrationally resolved Rayleigh and Raman scattering cross sections for molecular hydrogen

Accurate Rayleigh and Raman scattering cross sections, tensor components, depolarization ratios, and reversal coefficients for all rovibrational transitions within the X1Σg+ ground electronic state of H2 have been calculated. Raman spectra have been generated using these data. A method for calculating Raman scattering cross sections is formulated that is valid below the ionization threshold and in the region containing resonances, which explicitly accounts for all bound and dissociative vibrational levels of the bound intermediate electronic states and approximately accounts for the ionization continuum. A representative set of cross sections is presented for incident photon energies below 15 eV and compared with existing results in the literature where possible. Convergence of our results with an increasing number of bound intermediate electronic states is demonstrated. The accuracy of the Placzek–Teller approximation is discussed. The effect of accounting for the intermediate ionization continuum is investigated. Local thermal equilibrium cross sections are calculated for Rayleigh and Raman scattering. This work represents the most accurate and complete treatment of Raman scattering for molecular hydrogen to date. A total of 9582 Rayleigh and Raman scattering cross sections have been generated and are openly available on Zenodo under an open-source Creative Commons Attribution license at https://zenodo.org/doi/10.5281/zenodo.13441471.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Form-factor dependence of neutrino-nucleus cross sections using microscopic methods

To achieve its design goals, the next generation of neutrino-oscillation accelerator experiments requires percent-level predictions of neutrino-nucleus cross sections supplemented by robust estimates of the theoretical uncertainties involved. The latter arise from both approximations in solving the nuclear many-body problem and in the determination of the single- and few-nucleon quantities taken as input by many-body methods. To gauge the sensitivity of realistic nuclear many body methods to these few-nucleon quantities, we compute flux-averaged double-differential cross sections using the Green’s function Monte Carlo and spectral function methods as well as different parameterizations of the nucleon axial form factors based on either deuterium bubble-chamber data or lattice quantum chromodynamics calculations. The cross-section results are compared with available experimental data from the MiniBooNE and T2K collaborations. We also discuss the uncertainties associated with N → Δ transition form factors that enter the two-body current operator. We quantify the relations between neutrino-nucleus cross section and nucleon form factor uncertainties. These relations enable us to determine the form factor precision targets required to achieve a given cross-section precision.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Learning nuclear cross sections across the chart of nuclides with graph neural networks

We explore the use of deep learning techniques to learn how nuclear cross sections change as we add or remove protons and neutrons. As a proof of principle, we focus on the neutron-induced reactions in the fast energy regime. Our approach follows a two-stage learning framework. First, we apply representation learning to encode cross section data into a latent space using either variational autoencoders (VAEs) or implicit neural representations (INRs). Then, we train graph neural networks (GNNs) on the resulting embeddings to predict missing values across the nuclear chart by leveraging the topological structure of neighboring isotopes. We demonstrate accurate cross section predictions within a 9 × 9 block of missing nuclei. We also find that the optimal GNN training strategy depends on the type of latent representation used, with VAE embeddings performing best under end-to-end optimization in the original space, while INR embeddings achieve better results when the GNN is trained only in the latent space. Furthermore, using clustering algorithms, we map groups of latent vectors into regions of the nuclear chart and show that VAEs and INRs can discover some of the neutron magic numbers. These findings suggest that deep-learning models based on the representation encoding of cross sections combined with graph neural networks hold significant potential in augmenting nuclear theory models, e.g., by providing reliable estimates of covariances of cross sections, including cross-material covariances.

Machine learning↗
DOE OSTI2024

Measurement of the energy-differential 35 Cl( n, p 0 ) 35 S cross section via the ratio with 6 Li( n, α ) 3 H

Knowledge of the neutron-induced 35 Cl ⁢(n, x) cross sections is vital to the design and certification of molten chloride fast reactors (MCFRs) since the 35 Cl (n, p 0 ) 35 S reaction is believed to be a significant reactor poison. However, recently published measurements are inconsistent with each other and with evaluation. Here, the goal of this work is to measure the 35 Cl (n, p 0 ) reaction cross section using a technique that is different from recent measurements. The experiment was conducted at Lawrence Berkeley National Laboratory's (LBNL) 88-Inch Cyclotron using thick target deuteron breakup from a 14 MeV deuteron beam. Energy-differential 35 Cl (n, p 0 ) 35 S cross sections were obtained via ratio with the 6 Li (n, a)⁢ 3 H reaction using an active target experiment with a Cs 2 ⁢LiYCl 6 (CLYC) scintillator. The 35 Cl (n, p 0 ) reaction cross section was measured from 2.02 to 7.46 MeV. The results are consistent with Kuvin et al., confirming a roughly 50% reduction in magnitude relative to the ENDF/B-VIII.0 evaluation. These data provide new insight into the role of natural Cl as an MCFR poison. The reduction of the 35 Cl (n, p 0 ) reaction cross section compared to evaluation suggests that MCFR criticality is less sensitive to Cl enrichment. This may in turn reduce building and operating costs since isotope separation may not be needed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Measurement of the mass-changing, charge-changing, and production cross sections of 11 C, 11 B, and 10 B nuclei in 12 C + p interactions at 13.5 GeV/𝑐 per nucleon

A good knowledge of nuclear fragmentation cross sections is important to interpret the fluxes of secondary cosmic rays from the Galaxy. Here we report new measurements of nuclear fragmentation with the NA61/SHINE experiment at the CERN SPS. The specific focus is on cross sections important for the production of boron in the Galaxy from the interactions of 12 C nuclei with hydrogen in the interstellar medium, including the contribution from the decay of the short-lived 11 C fragments. The data were taken with the secondary 12 C beam at beam momentum of 13.5 GeV/𝑐per nucleon and two fixed targets, polyethylene (CH 2 ) and graphite (C), from which we derive the cross sections of carbon on hydrogen. We present the measurement of the fragmentation cross sections of 11 C, 11 B, and 10 B as well as the mass- and charge-changing cross sections.

nuclear fragmentation↗
DOE OSTI2025

Efficient Monte Carlo event generation for neutrino-nucleus exclusive cross sections

Modern neutrino-nucleus cross section computations need to incorporate sophisticated nuclear models to achieve greater predictive precision. However, the computational complexity of these advanced models often limits their practicality for experimental analyses. To address this challenge, we introduce a new Monte Carlo method utilizing normalizing flows to generate surrogate cross sections that closely approximate those of the original model while significantly reducing computational overhead. As a case study, we built a Monte Carlo event generator for the neutrino-nucleus cross section model developed by the Ghent group. This model employs a Hartree-Fock procedure to establish a quantum mechanical framework in which both the bound and scattering nucleon states are solutions to the mean-field nuclear potential. The surrogate cross sections generated by our method demonstrate excellent accuracy with a relative effective sample size of more than 98.4%, providing a computationally efficient alternative to traditional Monte Carlo sampling methods for differential cross sections.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Toward virtual thin-beam 𝜈 cross-section measurements: A feasibility study of 𝜈-Ar interaction analysis with DUNE-PRISM

Neutrino-nucleus cross section measurements are critical for future neutrino oscillation analyses. However, our models to describe them require further refinement, and a deeper understanding of the underlying physics is essential for future neutrino oscillation experiments to realize their ambitious physics goals. Current neutrino cross section measurements provide clear deficiencies in neutrino interaction modeling, but almost all are reported averaged over broad neutrino fluxes, rendering their interpretation challenging. Using the concept of deep underground neutrino experiment-precision reaction independent spectrum measurement (DUNE-PRISM)—a movable near detector that samples multiple off axis positions—neutrino interaction measurements can be used to construct narrow virtual fluxes (less than 100 MeV wide). These fluxes can be used to extract charged-current neutrino-nucleus cross sections as functions of outgoing lepton kinematics within specific neutrino energy ranges. Based on a dedicated simulation with realistic event statistics and flux-related systematic uncertainties, but assuming an almost-perfect detector, we run a feasibility study demonstrating how DUNE-PRISM data can be used to measure muon neutrino charged-current integrated and differential cross sections over narrow fluxes. We find that this approach enables a largely model-independent reconstruction of powerful observables, including energy transfer, typically accessible only in electron scattering measurements, but that large exposures may be required for differential cross section measurements with few-percentage statistical uncertainties.

Neutrino interactions↗
DOE OSTI2026

Precise measurement of the tt¯ production cross-section and lepton differential distributions in eμ dilepton events from s=13TeVpp collisions with the ATLAS detector

The inclusive top quark pair (tt¯$$t\bar{t}$$) cross-section σtt¯$$\sigma _{t\bar{t}}$$ has been measured in proton–proton collisions at s=13TeV$$\sqrt{s}=13\,\text {TeV}$$, using 140fb-1$$140\,{\text {fb}^{-1}} $$ of data collected by the ATLAS experiment at the Large Hadron Collider. Using events with an opposite-charge eμ$$e\mu $$ pair and b-tagged jets, the cross-section is measured to be: σtt¯=829.3±1.3(stat)±8.0(syst)±7.3(lumi)±1.9(beam)pb,$$\begin{aligned} \sigma _{t\bar{t}} & = 829.3\pm 1.3\,\mathrm {(stat)}\ \pm 8.0\,\mathrm {(syst)}\ \pm 7.3\,\mathrm {(lumi)}\ \\ & \quad \pm 1.9\,\mathrm {(beam)}\,\textrm{pb}, \end{aligned}$$where the uncertainties reflect the limited size of the data sample, experimental and theoretical systematic effects, the integrated luminosity, and the proton beam energy, giving a total uncertainty of 1.3%. The result is used to determine the top quark pole mass via the dependence of the predicted cross-section on mtpole$${m_{t}^\textrm{pole}}$$, giving mtpole=172.8-1.7+1.5$${m_{t}^\textrm{pole}}=172.8^{+1.5}_{-1.7}$$ GeV$$\text {GeV}$$. The same event sample is used to measure absolute and normalised differential cross-sections for the tt¯→eμνν¯bb¯$$t\bar{t} \rightarrow e\mu u \bar{ u }b\bar{b} $$ process as a function of single-lepton and dilepton kinematic variables. Complementary measurements of eμbb¯$$e\mu b\bar{b} $$ production, treating both tt¯$$t\bar{t}$$ and Wt events as signal, are also provided. Both sets of differential cross-sections are compared to the predictions of various Monte Carlo event generators, demonstrating that the state-of-the-art generators Powheg MiNNLO and Powhegbb4l describe the data better than Powheghvq.

Aad, G↗
DOE OSTI2025

Measurement of the mass-changing, charge-changing, and production cross sections of C 11 , B 11 , and B 10 nuclei in C 12 + p interactions at 13.5 GeV / c per nucleon

A good knowledge of nuclear fragmentation cross sections is important to interpret the fluxes of secondary cosmic rays from the Galaxy. Here we report new measurements of nuclear fragmentation with the NA61/SHINE experiment at the CERN SPS. The specific focus is on cross sections important for the production of boron in the Galaxy from the interactions of C 12 nuclei with hydrogen in the interstellar medium, including the contribution from the decay of the short-lived C 11 fragments. The data were taken with the secondary C 12 beam at beam momentum of 13.5 GeV / c per nucleon and two fixed targets, polyethylene ( CH 2 ) and graphite (C), from which we derive the cross sections of carbon on hydrogen. We present the measurement of the fragmentation cross sections of C 11 , B 11 , and B 10 as well as the mass- and charge-changing cross sections.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

RU Net for Automatic Characterization of TRISO Fuel Cross Sections

TRistructural ISOtropic (TRISO) particle fuel is a type of nuclear fuel known for its high-temperature and high-burnup performance. Each sub-millimeter diameter TRISO particle consists of uranium-oxycarbide (UCO) or UO2 fuel kernel, coated with buffer, inner pyrolytic carbon (IPyC), silicon carbide (SiC), and outer pyrolytic carbon (OPyC) layers. The SiC layer acts as the main containment barrier for the TRISO particle to retain the fission products, while the IPyC and OPyC layers provide additional barriers to the release of fission products, especially fission gases. During irradiation, phenomena like kernel swelling, buffer densification, and IPyC fracture may impact fuel performance. Post-irradiation microscopy on entire compact cross sections or samples of individual particles deconsolidated from compacts is often used to identify these irradiation-induced changes in morphology. However, each fuel compact generally contains thousands of TRISO particles. To get statistical information on these phenomena, it is cumbersome work if done manually. For example, to get information about swelling/densification behaviors of different layers or kernels after irradiation, researchers previously manually measured the perimeter of each TRISO layer in hundreds of particles after four rounds of iterative grinding and polishing encompassing more than 2000 cross-section images for a total of four fuel compacts. To attempt to reduce the subjectivity inherent in that process and accelerate data analysis, we conducted a study on the automatic TRISO layer segmentation on cross-sectional microscopic images using Convolutional Neural Networks (CNNs). CNNs are a class of machine learning algorithms specifically designed for processing structured grid data that have gained popularity in recent years due to their remarkable performance in various computer vision tasks, including image classification, object detection, and image segmentation. In this research, we have generated the large irradiated TRISO layer dataset with more than 2000 cross-section TRISO microscopic images and the corresponding annotated images. Based on these annotated images, we have employed different CNNs for automatic segmentation of different TRISO layers. These include RU-Net (developed in this study), as well as three existing architectures: U-Net, Residual Network (ResNet), and Attention U-Net. The preliminary results show that the model based on RU-Net has the best performance in terms of intersection-over-union (IoU). Through the aid of these CNN models, we can expedite the analysis of TRISO particle cross-sections, significantly reducing the manual labor involved and improving the objectivity of the segmentation results.

Convolutional Neural Networks↗