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At least 559 records · Page 31

Data Needs for Modeling Low-Temperature Non-Equilibrium Plasmas: The LXCat Project, History, Perspectives and a Tutorial

Technologies based on non-equilibrium, low-temperature plasmas are ubiquitous in today’s society. Plasma modeling plays an essential role in their understanding, development and optimization. An accurate description of electron and ion collisions with neutrals and their transport is required to correctly describe plasma properties as a function of external parameters. LXCat is an open-access, web-based platform for storing, exchanging and manipulating data needed for modeling the electron and ion components of non-equilibrium, low-temperature plasmas. The data types supported by LXCat are electron- and ion-scattering cross-sections with neutrals (total and differential), interaction potentials, oscillator strengths, and electron- and ion-swarm/transport parameters. Online tools allow users to identify and compare the data through plotting routines, and use the data to generate swarm parameters and reaction rates with the integrated electron Boltzmann solver. In this review, the historical evolution of the project and some perspectives on its future are discussed together with a tutorial review for using data from LXCat.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Vibrationally resolved cross sections for proton collisions with hydrogen molecules

The semi-classical molecular convergent close-coupling approach has been applied to proton collisions with molecular hydrogen in the ground electronic and vibrational state. Cross sections for electron loss and electron capture agree well with the experimental data in the intermediate energy range where coupling between electronic reaction channels is strong and previously available calculations produce inconsistent results. Results for elastic scattering and total excitation are compared with effective one-electron coupled-channel calculations, showing that accurate target structure makes an important difference to these cross sections at intermediate energies. The excitation cross sections are calculated using both the fixed-nuclei and adiabatic-nuclei approximations for transitions from the $X^1Σ^+_{\textrm{g}}$ state to the $B^1Σ^+_{\textrm{u}}$, $B'$$^1Σ^+_{\textrm{u}}$, $B''$$^1Σ^+_{\textrm{u}}$, $EF$$^1Σ^+_{\textrm{g}}$, $GK$$^1Σ^+_{\textrm{g}}$, $H$$^1Σ^+_{\textrm{g}}$, $C$$^1Π_{\textrm{u}}$, $D$$^1Π_{\textrm{u}}$, $D'$$^1Π_{\textrm{u}}$, $I$$^1Π_{\textrm{u}}$, and $J$$^1Δ_{\textrm{g}}$ states for proton energies from to keV. We find significant differences between the present ab initio calculations and the equivelocity scaled electron-scattering data that is currently used for collisional-radiative modelling. Furthermore, the adiabatic-nuclei calculations enable us to resolve the final vibrational level after excitation, producing a complete set of cross sections for excitation of ground-state molecular hydrogen for all electronic states up to $n = 3$, where $n$ is the united-atoms-limit principle quantum number.

74 ATOMIC AND MOLECULAR PHYSICS↗

Absolute photoionization cross sections of brominated organics and determination of an effective C—Br bond cross section

For this work, absolute photoionization cross sections for five brominated species were measured using multiplexed synchrotron photoionization mass spectrometry at the Advanced Light Source (Lawrence Berkeley National Laboratory). These data enable reliable detection of bromine-containing compounds and estimation of C—Br bond photoionization cross sections. Complementary electronic-structure calculations provided adiabatic ionization energies in good agreement with experiment, while thermochemical appearance energies were measured directly. Bond dissociation energies for key fragmentation pathways of the neutral parent molecules were also analyzed. At 11 eV, cross sections were 53.8 ± 7.50 Mb (sp 2 C—Br) and 48.8 ± 7.70 Mb (sp 3 C—Br).

Brominated compounds↗

Determination of the titanium spectral function from ($e,e'p$) data

The E12-14-012 experiment, performed in Jefferson Lab Hall A, has measured the (e, e'p) cross section in parallel kinematics using a natural titanium target. In this paper, we report the analysis of the dataset obtained in different kinematics for our solid natural titanium target. Data were obtained in a range of missing momentum and missing energy between 15 ≲ p m ≲ 250 MeV / c and 12 ≲ E m ≲ 80 MeV, respectively, and using an electron beam energy of 2.2 GeV. We measured the reduced cross section with ~7% accuracy as a function of both missing momentum and missing energy. Furthermore, our Monte Carlo simulation, including both a model spectral function and the effects of final-state interactions, satisfactorily reproduces the data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Updates to Improve the Evaluated Nuclear Data of Copper Isotopes in the Resolved and Unresolved Resonance Regions

The evaluated nuclear data of the 63,65 Cu isotopes have been updated in the resolved and unresolved resonance energy regions with the goal of improving the fidelity between calculated and measured critical benchmarks. Particular focus was devoted to the 63 Cu(n, γ) cross sections because of their large sensitivity to the reactivity in the benchmark calculations. By focusing on these cross sections, the set of parameters in both resolved and unresolved resonance regions were fitted to available experimental data. The newly updated evaluations were compared to the currently available ENDF/B-VIII.0 evaluations in reactivity calculations for copper-sensitive integral benchmarks. An initial study of the sensitivity of the benchmarks to the angular distributions was performed, finding it necessary to describe the angular distributions more accurately above 100 keV. This investigation uncovered the need for more accurate data for the 63 Cu(n, γ) cross section above 100 keV. An increase in the capture cross section was found to improve agreement for the considered benchmarks.

07 ISOTOPE AND RADIATION SOURCES↗

Measurement of muon antineutrino charged current - 0 meson scattering, using the NOvA Near Detector

Antineutrino interaction cross sections are, at present, poorly constrained, particularly regarding the role of multi-nucleon processes such as 2-particle 2-hole (2p2h) interactions. The associated crosssection systematic uncertainties represent a significant challenge for precision oscillation measurements, especially for the next generation of neutrino experiments such as DUNE. We present a new measurement of the muon antineutrino charged-current cross section without mesons in the final state, using the high-statistics data set of the NOvA Near Detector. The analysis employs a cut-based selection enhanced by machine learning techniques to isolate a high-purity sample dominated by quasielastic (QE) and 2p2h interactions. We present the cross section as a function of the kinetic energy and scattering angle of the outgoing muon. We also present measurements of more model-dependent kinematic variables such as the neutrino energy and momentum transfer, to better probe the underlying nuclear physics. The results are compared against various neutrino event generators to test the robustness of current interaction models.

Vockerodt, Kevin John [Ohio State U.; Queen Mary, ↗

Application of machine learning in the determination of impact parameter in the 132 Sn+ 124 Sn system

Here, 132 Sn + 124 Sn collisions at a beam energy of 270 MeV/nucleon were performed at the Radioactive Isotope Beam Factory (RIBF) in RIKEN to investigate the nuclear equation of state. Reconstructing the impact parameter is one of the important tasks in the experiment as it relates to many observable. In this work, we employ three commonly used algorithms in machine learning, the artificial neural network (ANN), the convolutional neural network (CNN), and the light gradient boosting machine (LightGBM), to determine the impact parameter by analyzing either the charged particle spectra or several features simulated with events from the ultrarelativistic quantum molecular dynamics (UrQMD) model. To closely imitate experimental data and investigate the generalizability of the trained machine learning algorithms, incompressibility of nuclear equation of state and the in-medium nucleon-nucleon cross sections are varied in the UrQMD model to generate the training data. The mean absolute error Δb between the true and the predicted impact parameter is smaller than 0.45 fm if training and testing sets are sampled from the UrQMD model with the same parameter set. However, if training and testing sets are sampled with different parameter sets, Δb would increase to 0.8 fm. The generalizability of the trained machine learning algorithms suggests that these machine learning algorithms can be used reliably to reconstruct the impact parameter in experiment.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A new way to unravel the $^{12}$C($\alpha $,$\gamma $)$^{16}$O cross section components using neural networks

The $^{12}$C($\alpha $,$\gamma $)$^{16}$O reaction rate is crucial in determining the carbon-to-oxygen abundance ratio in stellar nucleosynthesis. Measuring this reaction’s cross section at stellar energies is challenging due to its extremely small value, approximately 10 -17 barn at E c.m. = 300 keV. To address this, R-matrix calculations are employed to extrapolate data to lower energies, requiring a comprehensive understanding of each contribution to the cross section. The dominant contributions to the cross section at stellar energies arise from electric dipole (E1) and electric quadrupole (E2) transitions to the ground state of 16 O, along with a significant cascade contribution. Traditionally, these contributions have been separated using the γ-ray angular distribution. In this work, we propose a novel technique using the energy distribution of the 16 O recoils at the focal plane. This method involves a neural network trained on detailed Monte Carlo simulations of the energy distribution of recoils transported through the recoil mass separator ERNA. This approach enables the simultaneous determination of all three contributions with errors around 10% in the energy range E c.m. = 1.0–2.2 MeV. In conclusion, by employing this new technique, we aim to significantly improve the accuracy of determining the cross section of the $^{12}$C($\alpha $,$\gamma $)$^{16}$O reaction at astrophysical energies.

Astrochemistry↗

Characterization of uncertainties in electron-argon collision cross sections

Abstract The predictive capability of a plasma discharge model depends on accurate representations of electron-impact collision cross sections, which determine the corresponding reaction rates and electron transport properties. The values of cross sections can be known only approximately either through experiments or simulations and are thus subject to uncertainties. Quantifying the uncertainties in plasma simulations allows us to assess the reliability of simulations and to provide a basis for interpreting discrepancies between simulations and experiments. For such uncertainty quantification of plasma simulations, it is essential to quantify the uncertainties of the underlying cross sections. Although much effort has been committed to calibrate the cross section values, their uncertainties are not well investigated. We characterize uncertainties in electron-argon atom collision cross sections using a Bayesian framework. Six collision processes—elastic momentum transfer, ionization, and four excitations—are characterized with semi-empirical models, which effectively capture the features important to the macroscopic properties of the plasma. A probability model for the uncertain parameters of these semi-empirical models is developed. Specifically, a Gaussian-process likelihood model is proposed to capture discrepancies among data sets, as well as the model-form inadequacies of the semi-empirical models. Two other likelihood models are compared with the proposed Gaussian-process model, to illustrate the importance of the choice of the likelihood model. The cross section models are calibrated using the electron-beam experiments and ab-inito quantum simulations. The resulting calibrated uncertainties capture well the scattering among the data sets. The calibrated cross section models are further validated against swarm-parameter experiments and zero-dimensional Boltzmann equation simulations of widely used cross section datasets.

Chung, Seung Whan (ORCID:0000000302501549)↗

Measurement of 𝑑 2⁢ 𝜎/𝑑⁢|$\vec{q}$|⁢𝑑⁢𝐸 avail in charged current 𝜈 𝜇 -nucleus interactions at ⟨𝐸 𝜈 ⟩=1.86 GeV using the NOvA Near Detector

Double- and single-differential cross sections for inclusive charged-current 𝜈 𝜇 -nucleus scattering are reported for the kinematic domain 0 to 2 GeV/𝑐 in three-momentum transfer and 0 to 2 GeV in available energy, at a mean 𝜈 𝜇 energy of 1.86 GeV. The measurements are based on an estimated 995,760 𝜈 𝜇 charged-current (CC) interactions in the scintillator medium of the NOvA Near Detector. The subdomain populated by 2-particle-2-hole (2p2h) reactions is identified by the cross section excess relative to predictions for 𝜈 𝜇 -nucleus scattering that are constrained by a data control sample. Models for 2-particle-2-hole processes are rated by 𝜒 2 comparisons of the predicted-versus-measured 𝜈 𝜇 CC inclusive cross section over the full phase space and in the restricted subdomain. Shortfalls are observed in neutrino generator predictions obtained using the theory-based València and SuSAv2 2p2h models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Bottom quark energy loss and hadronization with B + and ${\textrm{B}}_{\textrm{s}}^0$ nuclear modification factors using pp and PbPb collisions at $\sqrt{s_{\textrm{NN}}}$ = 5.02 TeV

The production cross sections of $ {\textrm{B}}_{\textrm{s}}^0 $ and B$^{+}$ mesons are reported in proton-proton (pp) collisions recorded by the CMS experiment at the CERN LHC with a center-of-mass energy of 5.02 TeV. The data sample corresponds to an integrated luminosity of 302 pb$^{−1}$. The cross sections are based on measurements of the $ {\textrm{B}}_{\textrm{s}}^0 $→ J/ψ(μ$^{+}$μ$^{−}$)ϕ(1020)(K$^{+}$K$^{−}$) and B$^{+}$→ J/ψ(μ$^{+}$μ$^{−}$)K$^{+}$ decay channels. Results are presented in the transverse momentum (p$_{T}$) range 7–50 GeV/c and the rapidity interval |y| < 2.4 for the B mesons. The measured p$_{T}$-differential cross sections of B$^{+}$ and $ {\textrm{B}}_{\textrm{s}}^0 $ in pp collisions are well described by fixed-order plus next-to-leading logarithm perturbative quantum chromodynamics calculations. Using previous PbPb collision measurements at the same nucleon-nucleon center-of-mass energy, the nuclear modification factors, R$_{AA}$, of the B mesons are determined. For p$_{T}$> 10 GeV/c, both mesons are found to be suppressed in PbPb collisions (with R$_{AA}$ values significantly below unity), with less suppression observed for the $ {\textrm{B}}_{\textrm{s}}^0 $ mesons. In this p$_{T}$ range, the R$_{AA}$ values for the B$^{+}$ mesons are consistent with those for inclusive charged hadrons and D$^{0}$ mesons. Below 10 GeV/c, both B$^{+}$ and $ {\textrm{B}}_{\textrm{s}}^0 $ are found to be less suppressed than either inclusive charged hadrons or D$^{0}$ mesons, with the $ {\textrm{B}}_{\textrm{s}}^0 $R$_{AA}$ value consistent with unity. The R$_{AA}$ values found for the B$^{+}$ and $ {\textrm{B}}_{\textrm{s}}^0 $ are compared to theoretical calculations, providing constraints on the mechanism of bottom quark energy loss and hadronization in the quark-gluon plasma, the hot and dense matter created in ultrarelativistic heavy ion collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Deep Learning for Multigroup Cross-Section Representation in Two-Step Core Calculations

Here we investigate using deep learning, a type of machine-learning algorithm employing multiple layers of artificial neurons, for the mathematical representation of multigroup cross sections for use in the Griffin reactor multiphysics code for two-step deterministic neutronics calculations. A three-dimensional fuel element typical of a high-temperature gas reactor as well as a two-dimensional sodium-cooled fast reactor lattice are modeled using the Serpent Monte Carlo code, and multigroup macroscopic cross sections are generated for various state parameters to produce a training data set and a separate validation data set. A fully connected, feedforward neural network is trained using the open-source PyTorch machine-learning framework, and its accuracy is compared against the standard piecewise linear interpolation model. Additionally, we provide in this work a generic technique for propagating the cross-section model errors up to the k eff using sensitivity coefficients with the first-order uncertainty propagation rule. Quantifying the eigenvalue error due to the cross-section regression errors is especially practical for appropriately selecting the mathematical representation of the cross sections. We demonstrate that the artificial neural network model produces lower errors and therefore enables better accuracy relative to the piecewise linear model when the cross sections exhibit nonlinear dependencies; especially when a coarse grid is employed, where the errors can be halved by the artificial neural network. However, for linearly dependent multigroup cross sections as found for the sodium-cooled fast reactor case, a simpler linear regression outperforms deeper networks.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Benchmarking fast-neutron response of 7 Li-enriched C 7 LYC scintillators: Simulations and experiment

New insights into the fast neutron response of 7 Li-enriched C 7 LYC scintillators have been obtained through detailed Geant4 simulations of 35 Cl(n,p) and 35 Cl(n, α) reactions that are primarily responsible for the fast neutron response of C 7 LYC. The light output of a 1” x1” C 7 LYC detector was simulated using the Birks equation for light quenching in scintillators. The simulations were benchmarked against neutron scattering data from a 12 C target obtained with a white neutron beam at the Los Alamos LANSCE facility and fourteen 1”x1” C 7 LYC detectors. Incident neutron energies extracted from time-of-flight measurements, and appropriate recoil corrections for the different detector angles were used to map the response of C 7 LYC to mono-energetic neutrons. Resonances in the 35 Cl(n,p) reaction cross-section below 3 MeV incident neutron energy were directly observed in C 7 LYC. The experimental data and simulations are compared with ENDF databases, as well as recent direct cross-section measurements of neutrons scattered from a 35 Cl target. In conclusion, the results suggest a scrutiny of the 35 Cl(n,p) and 35 Cl(n, α) cross sections at low energy in the ENDF library.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Evaluated Nuclear Data Requirements in Support of Fission and Fusion Applications [Slides]

This presentation touches on thermal scattering cross section and scattering lengths including criticality benchmarks (fission). Secondly, development and completeness of charged ­particle libraries: criticality benchmarks (fission), neutron source (fission/fusion), simulation benchmarks and light elements generation (fusion). Additionally, this presentation details on the covariances (methodology and completeness) with adjustment and optimization of nuclear data libraries (fission/fusion). Finally nuclear data reproducibility and conclusions are discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Ring Pull Strain Analysis

Ring Pull Strain Analysis (RPSA) is a framework for analysis of Digital Image Correlation (DIC) data of gaugeless ring pull testing. It is meant for analysis of rings cut from tube cross sections and pulled in a displacement-controlled tensile test. This code takes load frame data, images take during testing, and csv files from the DIC analysis of those images and allows the user to analyze and plot data from the test. Some important features of the software include getting the strain values as a function of radial distance and angle, plotting of the strain around the ring, and stress-strain analysis of the load frame data.

Beck, Peter↗

Ring Pull Strain Analysis

Ring Pull Strain Analysis (RPSA) is a framework for analysis of Digital Image Correlation (DIC) data of gaugeless ring pull testing. It is meant for analysis of rings cut from tube cross sections and pulled in a displacement-controlled tensile test. This code takes load frame data, images take during testing, and csv files from the DIC analysis of those images and allows the user to analyze and plot data from the test. Some important features of the software include getting the strain values as a function of radial distance and angle, plotting of the strain around the ring, and stress-strain analysis of the load frame data. Additional capability is included with Ring Pull Coating Analysis (RPCA, also part of the software). Additional images are taken of samples with an outer coating and are used to correlate failure of the coating with strain values measured with DIC.

Beck, Peter↗

Constraining the impact of chlorine as a neutron absorber in next-gen fast reactor designs

The role of chlorine as a neutron poison and as a seed for producing radioactive waste in nuclear systems has driven a renewed interest to improve its nuclear data uncertainties. Additionally, basic and applied science programs that use CLYC (Cs 2 LiYCl 6 :Ce) detectors for neutron spectroscopy and monitoring are also very sensitive to any change in chlorine nuclear data for simulations of the detector response. In this work, sensitivities relevant for these different applications are addressed through simulations of the efficiency of CLYC detectors in a fast fission spectrum when applying new chlorine nuclear data as input. These simulations are validated by an experimental measurement using CLYC detectors coupled to an ionization chamber loaded with a 252 Cf spontaneous fission source. The results are then used to obtain the first reliable direct measurement of the 35 Cl(n,p 0 ) and summed Cl(n,p+n,α) fission spectrum average cross sections, found to be 54.7(32) and 105.0(98) mb, respectively. The results are within uncertainty of calculated fission spectrum averaged cross sections based on recently re-evaluated chlorine nuclear data, which confirm recent impact studies performed for the Molten Chloride Reactor Experiment. Meanwhile, there currently exists only one published criticality benchmark experiment that is sufficiently sensitive to chlorine nuclear data. Discrepancies are found with this set of criticality safety benchmarks, which are more sensitive to thermal and epithermal neutron energies than the energies, above 100 keV, tested in this current work. Hence, there is still a need to re-evaluate the chlorine nuclear data at lower energies to assess these discrepancies. Interpretation of the data from future “faster” criticality benchmarks, which are needed for next-gen fast reactor designs, benefit from the improved constraints on the chlorine nuclear data validated in this work.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Experiments for validation of TSL evaluations [Slides]

There is a recent revival of thermal scattering evaluation capabilities and there are many new evaluations available in ENDF-8.0 and elsewhere. This creates a need for experimental validation other than criticality benchmarks. Thermal scattering libraries (TSL) provide information to describe the double differential thermal scattering at different moderator temperatures. For moderators, the biggest effect of TSL is the thermal scattering cross section.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗