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DOE OSTI2021

Investigation of the isoscalar response of 24 Mg to 6 Li scattering

24 Mg is a strongly deformed nucleus in the ground state. Deformation effects can be observed in the structure of the isoscalar giant monopole and quadrupole resonances. 24 Mg is also a nucleus that is well known to present different types of cluster-oscillation modes. Both giant resonances and cluster states are strongly populated by isoscalar transitions. To extract the E0, E1, and E2 transition strengths via 6 Li scattering. The 6 Li probe is a powerful tool for investigating the isoscalar nuclear response with a very favorable ratio of resonance-to-continuum background. Double-differential cross sections of 6 Li inelastic scattering, at the beam energy of 100 MeV/u, were measured in the excitation-energy range 10 – 40 MeV and scattering angles 0 - 3°. A multipole-decomposition analysis was performed for extracting the isoscalar E0 , E1, and E2 strength distributions. Results: The extracted multipole strengths were compared with predictions from consistent quasiparticle random phase approximation calculations. The theoretical predictions are in fair agreement with the experimental data. The E0 strength was also compared with results from antisymmetrized molecular dynamics calculations found in the literature. A few peaks in the experimental data might be associated with clustering in 24 Mg. Ground-state deformation effects were observed in the isoscalar giant monopole resonance (ISGMR) and isoscalar giant quadrupole resonance (ISGQR) distributions. The ISGMR strength is split in two peaks around 19 and 28 MeV. The ISGQR exhibits a pronounced peak at 20 MeV with a broadening at the low-energy region, similar to predictions from microscopic calculations. Signatures of excitation of cluster states were observed in the E0 response. Further studies including particle-decay measurements will be required to confirm the nature of the observed peaks.

20 ≤ A ≤ 38↗

DOE OSTI2021

Isospin mixing and the cubic isobaric multiplet mass equation in the lowest T=2, A=32 quintet

The isobaric multiplet mass equation (IMME) is known to break down in the first T=2,A=32 isospin quintet. In this work we combine high-resolution experimental data with state-of-the-art shell-model calculations to investigate isospin mixing as a possible cause for this violation. The experimental data are used to validate isospin-mixing matrix elements calculated with newly developed shell-model Hamiltonians. Our analysis shows that isospin mixing with nonanalog T=1 states contributes to the IMME breakdown, making the requirement of an anomalous cubic term inevitable for the multiplet.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2026

Compressor is A Sensor (Final Report)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

A mechanism-based quantitative multi-scale framework for investigating irradiation hardening of tungsten at low temperature

We present the development and validation of a mechanism-based multi-scale modeling framework to quantitatively link the irradiation defect evolution kinetics at the microscopic scale to the macroscopic yield strength and flow stress evolution of tungsten irradiated at low temperature (0.08 < T/T m < 0.18, where T m is the melting point and is equal to 3673 K). The mechanism-based strength model, proposed as the superposition of thermal softening and modified dispersed barrier hardening, is developed to understand the underlying strengthening mechanisms. The thermal softening exponent as defined in the Johnson-Cook model is obtained by fitting unirradiated yield strength at different temperatures. A set of irradiation-induced defect kinetics equations with the thermodynamics parameters derived from the atomic calculations reported in the literature is used to determine the densities and sizes of defect clusters at the meso-scale, and the predicted irradiation damage characteristics are in reasonable quantitative agreement with experimental data from literature. The effects of irradiation condition (temperature and irradiation dose) and test temperature on yield strength are quantitatively predicted and compared with experimental measurements from the literature. Here, the predicted irradiation hardening and strain hardening are compared with experimental data as model validation.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Analysis of historic fires to determine most frequent challenging events

The fire probabilistic risk assessment framework for nuclear power plants relies on experimental data to determine expected fire behavior or to validate models to predict fire conditions in the plant. To support reducing the uncertainty in this experimental data, a research effort was conducted to identify the most frequent and challenging fire scenarios using historic fire data from nuclear power plants in the United States. To support this effort, an electronic version of the publicly available Updated Fire Event Database developed by Electric Power Research Institute was produced resulting in data on 2111 fire events, 540 events were labelled as being challenging fires with 74.2% of these challenging fire events being due to eleven selected fire types. In conclusion, of these fire types, electrical and electronic equipment, transient combustibles, and liquid fires were the most frequent of the challenging fires. The fire scenario specifics were characterized for each of the eleven selected types and then related to existing fire experiments.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2022

Catalyst and reactor design considerations for selective production of acids by oxidative cleavage of alkenes and unsaturated fatty acids with H 2 O 2

Oxidative cleavage of alkenes and unsaturated fatty acids with hydrogen peroxide gives an efficient and sustainable process to obtain mono- and di-acids for polymers and lubricants with fewer safety risks and less environmental impact than processes that utilize ozone or other inorganic oxidizers (e.g., permanganate, dichromate, etc.). Guided by insight into the mechanisms for competing reaction pathways (i.e., epoxidation of alkene on W–(η 2 -O 2 ) complexes vs. H 2 O 2 decomposition) and the apparent kinetics derived from kinetic experiments, here, we postulate that W-based heterogeneous catalysts can provide high performance and stable operations at low H 2 O 2 concentrations. Semi-batch reactors with continuous introduction of H 2 O 2 solutions offer the means to maintain low H 2 O 2 concentrations while providing sufficient quantities of H 2 O 2 to satisfy the reaction stoichiometry. We derived simple kinetic model equations for the epoxidation, ring-opening, oxidative cleavage, and oxidation steps and fit theses equations to batch experimental data to obtain kinetic parameters. Furthermore, this kinetic model describes the concentration profiles of reactant, oxidant, and products well as shown by agreement with experimental data. Further predictions of the optimal H 2 O 2 feed rate for semi-batch operation utilized by the proposed rate expressions and the reactor design equations suggest that low H 2 O 2 feed rate increases selectivity towards oxidative cleavage products and selective use of H 2 O 2 for oxidative cleavage pathway. Comparisons of oxidative cleavage of 4-octene in batch and semi-batch reactors show that semibatch reactors with optimized molar feed rates of H 2 O 2 increased oxidative cleavage product selectivities (76% to 99%; with an increase in butyric acid selectivity from 1% to 55%) and H 2 O 2 selectivity (3% to 30%). In addition, semibatch reaction conditions used avoid H 2 O 2 -mediated dissolution of W-atoms from the catalyst. Analysis of these findings suggest that solid oxide catalysts will be effective for continuous oxidative cleavage reactions if deployed within fixed-bed reactors that allow for distributed introduction of reactants and therefore low in situ concentrations of H 2 O 2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Calculation of ion–ion mutual neutralization rate constants using Landau–Zener theory coupled with trajectory simulations for Ar + –Cl − , Br − , I −

In this computational study, we self-consistently calculate the rate constants of mutual neutralization reactions by incorporating the electron transfer probability, using Landau–Zener state transition theory with inputs derived from ab initio quantum chemistry calculations, into classical trajectory simulations. Electronic structure calculations are done using correlation consistent basis sets with multi-reference configuration interaction to map all the molecular electronic states below the ion-dissociation limit as a function of the distance between the reacting species. Our electronic structure calculations have been significantly improved from our previous work through improved selection of molecular electronic configurations maintaining a fine grid of 1a 0 over a wide range of bond lengths and accurate treatment of spin–orbit couplings. Non-adiabatic coupling matrix elements are calculated with the three-point central difference method near each avoided crossing to estimate the exact crossing point R x and coupling parameter H if , which are inputs to the multi-channel Landau–Zener theory to calculate the electron transition probability. Our approach is applied to estimate the mutual neutralization rate constants for the following ion pairs: Ar + –Cl − , Ar + –Br − , Ar + –I − at ∼133 Pa. Furthermore, our predictions are compared against the experimental data reported. It is seen that the improvement in the electronic structure calculation results in excellent agreement between the simulation results and the available experimental data to within a factor of ∼2 or ∼±50%.

Complete-active space self-consistent field↗

DOE OSTI2024

Localized basis set for plutonium

The implementation of optimal strictly localized atomic orbitals basis for plutonium (Pu) using norm-conserving pseudopotential density-functional theory (DFT) is presented. The basis set was applied to the α, β, γ, δ, δ', and ε phases of Pu, δ-Pu surface, and δ-PuGa alloys. The computed properties of the Pu phases and δ-Pu surface were in good agreement with both available experimental data and prior DFT calculations based on plane-wave methodologies. Results for the δ-PuGa alloys were also in good agreement with experimental data. Finally, the reliability of the basis set was further demonstrated by using ab initio molecular dynamics to model the diffusion coefficient and activation barrier for atomic diffusion in a δ-PuGa alloy.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2020

Connecting Nuclear Structure to Stellar Astrophysics: Neutron Skin in Tin Isotopes

The first observation of a neutron star merger by the LIGO-Virgo collaboration in 2017 highlights the need to improve our fundamental understanding of the equation of state of dense, neutron rich matter. The origin of heavy elements in the r-process and the structure of neutron stars are governed by the properties of neutron rich matter, for which experimental data is limited. Further analysis of this historic event and all future neutron star mergers relies on constraining the nuclear equation of state with experimental observables. We propose a novel method for systematically studying the evolution of the neutron skin in stable tin isotopes, by measuring the low-energy nuclear dipole strength over the broadest possible range of neutron-to-proton ratios in a single element. Nuclear resonance fluorescence with 100% linearly polarized photons from the High Intensity Gamma-ray Source (HIGS) facility was used to selectively measure the E1 photoabsorption strength of 112 Sn and 124 Sn at excitation energies from 3.5 MeV up to neutron separation, where the Pygmy Dipole Resonance dominates. The dipole polarizabilities of 112 Sn and 124 Sn were measured to be 9.03 ± 0.23 fm 3 and 9.11 ± 0.24 fm 3 , respectively. These uniquely systematically consistent measurements provide highly accurate experimental data for improving microscopic nuclear models as well as calculations of astrophysical nucleosynthesis and neutron star structure.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Photon induced $K\Lambda $ production on the proton at $E_{\gamma} < 3$ GeV

The associated photoproduction of $K\Lambda$ from the proton for $E_{\gamma} < 3$ GeV is studied using an isobar model in which the non-resonant contributions corresponding to $s$, $t$, $u$ channel diagrams are obtained from a non-linear sigma model with chiral SU(3) symmetry. The model also predicts a contact term and its coupling strength in a natural way to preserve gauge symmetry. The parameters used are the pion decay constant $f_{\pi}$, vector and axial vector current couplings of the baryon octet in terms of the symmetric and antisymmetric couplings $D$ and $F$. In the non-resonant sector, the model is almost parameter free except a common cut-off parameter $\Lambda_{B}$, to describe the hadronic form factors at the strong kaon-nucleon-hyperon($KN\Lambda$) vertices. In the resonance sector, contribution from the various nucleon resonances($R$) in the $s$ channel, hyperon resonances($Y^{*}$) in the $u$ channel, and the kaon resonances($K^{*}$ and $K_{1}$) in the $t$ channel, which are present in the PDG having spin $\le \frac{3}{2}$ and mass $<2$ GeV with significant branching ratio in $K\Lambda$ decay mode have been considered. In the case of the nucleon resonances($R$), the couplings $\gamma NR$ at the electromagnetic vertices are determined in terms of the helicity amplitudes and the $RK\Lambda$ couplings at the strong vertices are determined by the partial decay width of the resonances($R$) decaying to $K\Lambda$. The strong and the electromagnetic couplings of $u$ and $t$ channel resonances are fitted to reproduce the experimental data of CLAS and SAPHIR. The numerical results are presented for the total and differential scattering cross sections and are compared with the available experimental data from CLAS and SAPHIR as well as with some of the recent theoretical models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

A Universal Refrigerant Charge Fault Detection and Diagnostics Method Based on Pump Down Operation

The performance of the heat pump system varies greatly depending on the refrigerant charge amount. Improving the refrigerant charge fault detection and diagnostics (FDD) method of vapor compression systems have the potential for increasing energy efficiency and reducing service cost. Previous studies to predict refrigerant charge amount are mostly empirical methods which require significant amount of experimental data for high accuracy. The primary goal of this research is to develop a universal charge fault detection method which requires only a few experimental data with high prediction accuracy.Currently, pump down operations are typical practices by HVAC technicians when they need to open the refrigerant circuit to make a repairment. In addition, compressors have a built-in low-pressure cut-off protection function, and the compressor performance maps are commonly available from manufacturers. The proposed method innovatively utilizes the typical pump down operation, the compressor low-pressure cut-off protection, and the compressor performance map. It does not require any geometry information of heat exchangers, refrigerant lines, or charge buffers.The new charge prediction method is firstly formulated through theoretical analysis, then verified and calibrated by a quasi-steady-state simulation of the pump down process for a residential heat pump system. The quasi steady-state simulation uses an HVAC system simulation framework driven by DOE/ORNL Heat Pump Design Model (HPDM). Preliminary experiment validations with heat pump refrigerant leakage tests demonstrate the deviation of the proposed charge prediction method compared with measurement is within 8%. This technology makes refrigerant charge amount available at the technician’s fingertips and leads to shorter maintenance time and fewer site visits.

Li, Zhenning↗

DOE OSTI2022

Recent progress toward catalyst properties, performance, and prediction with data-driven methods

Herein, data-driven approaches are currently renovating the field of heterogenous catalysis and open a door to advance catalyst design. Their success depends heavily on the synergy among machine learning (ML), experimental data, and quantum mechanical (QM) calculations. In this brief survey of recent progress, we examine catalysis informatics in the context of (1) ML-aided catalyst characterizations, (2) knowledge extractions from experimental data, (3) predictions of catalytic properties and constructions of reaction networks, and (4) ML-enabled large-scale QM simulations. An outlook on the current challenges of this rapidly evolving field is also provided.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

304L Can Crush Validation Studies

Accurate prediction of ductile behavior of structural alloys up to and including failure is essential in component or system failure assessment, which is necessary for nuclear weapons alteration and life extensions programs of Sandia National Laboratories. Modeling such behavior requires computational capabilities to robustly capture strong nonlinearities (geometric and material), rate- dependent and temperature-dependent properties, and ductile failure mechanisms. This study's objective is to validate numerical simulations of a high-deformation crush of a stainless steel can. The process consists of identifying a suitable can geometry and loading conditions, conducting the laboratory testing, developing a high-quality Sierra/SM simulation, and then drawing comparisons between model and measurement to assess the fitness of the simulation in regards to material model (plasticity), finite element model construction, and failure model. Following previous material model calibration, a J 2 plasticity model with a microstructural BCJ failure model is employed to model the test specimen made of 304L stainless steel. Simulated results are verified and validated through mesh and mass-scaling convergence studies, parameter sensitivity studies, and a comparison to experimental data. The converged mesh and degree of mass-scaling are the mesh discretization with 140,372 elements, and a mass scaling with a target time increment of 1.0e-6 seconds and time step scale factor of 0.5, respectively. Results from the coupled thermal-mechanical explicit dynamic analysis are comparable to the experimental data. Simulated global force vs displacement (F/D) response predicts key points such as yield, ultimate, and kinks of the experimental F/D response. Furthermore, the final deformed shape of the can and field data predicted from the analysis are similar to that of the deformed can, as measured by 3D optical CMM scans and DIC data from the experiment.

36 MATERIALS SCIENCE↗

DOE OSTI2026

A physically based mechanical model for Mullins effect in thermoplastic polyurethanes

Despite decades of research, connecting the chemical and physical structure of thermoplastic polyurethanes to their mechanical properties remains highly challenging. Of particular note are their large-deformation and rate-dependent behaviors, which vary greatly with molecular chemistry, including the type and relative content of soft and hard segments. In this work, we develop a physically motivated mechanical theory for predicting the behavior of thermoplastic polyurethanes. The theory incorporates a representation of microstructural evolution during mechanical deformation, which captures the signatures of stress softening over cyclic loading (commonly referred to as the Mullins effect). There are only eight physically motivated fitting parameters, including a direct dependence on the hard segment fraction. The model predicts that increasing the hard segment fraction leads to higher stiffness and greater energy dissipation, in quantitative agreement with published experimental data. Furthermore, we provide a comprehensive analysis of the model and validate its predictions across several independent datasets focused on mechanical characterization. Direct comparisons to experimental data demonstrate its predictive capability on the effect of loading rate, cyclic deformations, and applied tension or compression. Altogether, this work establishes a predictive framework that connects polymer chemistry and microstructure to emergent mechanical behaviors.

36 MATERIALS SCIENCE↗

DOE OSTI2025

A buffering heat exchanger/thermal energy storage system for desalination applications

A buffering heat exchanger/thermal energy storage (BHXTES) system was designed using a fast-response phase-change material/graphite foam (PCM/GF) medium for desalination and potentially other industrial applications. Unlike a store-now-and-use-later TES system, this study focused on developing a dynamically balanced, continuously used, system that optimized three functions. A lab-scale prototype was designed and fabricated with a PureTemp 151/GF storage medium. The experimental data showed excellent thermal performance repeatability indicating minimal effects of PCM expansion and contraction on the GF as well as negligible PCM redistribution effects. The experimental data also served as a validation of the numerical model of the BHXTES system, after which optimization of the BHXTES system was conducted through numerical simulations for both PureTemp 151/GF and solar salt/GF as the storage medium. The results show that, with a Therminol 55 heat transfer fluid, continuous operation of the system can be realized with a solar energy source through cycles of 8-h changing for desalination and energy storage with the supplied heat followed by 16-h discharging for desalination with the stored energy. As a result, the working fluid outlet temperatures are generally in the ranges of approximately 128–160 °C for a PureTemp 151/GF medium and 198–220 °C for a solar salt/GF medium.

Buffering↗

DOE OSTI2021

The NUBASE2020 evaluation of nuclear physics properties *

The NUBASE2020 evaluation contains the recommended values of the main nuclear physics properties for all nuclei in their ground and excited, isomeric (T-1/2 >= 100 ns) states. It encompasses all experimental data published in primary (journal articles) and secondary (mainly laboratory reports and conference proceedings) references, together with the corresponding bibliographical information. In cases where no experimental data were available for a particular nuclide, trends in the behavior of specific properties in neighboring nuclei were examined and estimated values are proposed. Evaluation procedures and policies that were used during the development of this evaluated nuclear data library are presented, together with a detailed table of recommended values and their uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

$J/\psi $-p scattering length from the total and differential photoproduction cross sections

The J/ψ-p scattering length, αJ/ψp, can be extracted from the J/ψ photoproduction cross section near threshold using the Vector Meson Dominance (VMD) model to relate the reaction γp→J/ψp to J/ψp→J/ψp. Such estimates based on experimental data result in values for |αJ/ψp|, which are much lower than most of the theoretical predictions. In this work, we study the relations between the different results, depending on the use of the total or the differential cross sections, and the method of extrapolating the data to threshold in the case of a low-statistics data sample, such as the near threshold J/ψ photoproduction dataset. We estimate a range for |αJ/ψp| of 0.003–0.025 fm as extracted from experimental data within the VMD model and discuss possible reasons for such lower values compared to the theoretical results.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Transfer learning driven design optimization for inertial confinement fusion

Transfer learning is a promising approach to create predictive models that incorporate simulation and experimental data into a common framework. In this technique, a neural network is first trained on a large database of simulations and then partially retrained on sparse sets of experimental data to adjust predictions to be more consistent with reality. Previously, this technique has been used to create predictive models of Omega [Humbird et al., IEEE Trans. Plasma Sci. 48, 61–70 (2019)] and NIF [Humbird et al., Phys. Plasmas 28, 042709 (2021); Kustowski et al., Mach. Learn. 3, 015035 (2022)] inertial confinement fusion (ICF) experiments that are more accurate than simulations alone. Here, in this work, we conduct a transfer learning driven hypothetical ICF campaign in which the goal is to maximize experimental neutron yield via Bayesian optimization. The transfer learning model achieves yields within 5% of the maximum achievable yield in a modest-sized design space in fewer than 20 experiments. Furthermore, we demonstrate that this method is more efficient at optimizing designs than traditional model calibration techniques commonly employed in ICF design. Such an approach to ICF design could enable robust optimization of experimental performance under uncertainty.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗