Ab Initio-Based Kinetic Modeling for the Design of Molecular Catalysts: The Case of H 2 Production Electrocatalysts
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37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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Rapid Prediction of Low (<1%) trans Fat Content in Edible Oils and Fast Food Lipid Extracts by Infrared Spectroscopy and Partial Least Squares Regression
Abstract The United States Food and Drug Administration (FDA) ruled that partially hydrogenated oils (PHO), the major dietary source of industrially produced trans fat (TF), were no longer “generally recognized as safe (GRAS)” for any use in human food. Consequently, the objective of this study was to develop a rapid screening procedure using attenuated total reflection Fourier‐transform infrared (ATR‐FTIR) spectroscopy in conjunction with partial least squares regression (PLSR) for the quantitative and accurate prediction of low concentrations of trans fatty acid (TFAs) (<1% of total fatty acids (FAs)). Broad‐based calibration models were developed for a combined set of samples consisting of edible oils and fast food lipid extracts. Predicted concentrations of TFAs in the two matrices showed good correlation with the primary reference data generated by gas chromatography (GC) ( R 2 > 0.99) and high accuracy as evidenced by low root‐mean‐square error of cross‐validation (RMSECV) values. The lowest TFA concentration, determined by GC to be 0.13% of total FAs, was accurately predicted by ATR‐FTIR/PLSR as 0.18% of total FAs. This simple, rapid ATR‐FTIR/PLSR methodology has the potential for use as a screening alternative to conventional gas chromatographic methods for predicting the TFA content of edible oils and food lipid extracts for regulatory purposes and quality control of raw material and processed food. Practical Applications F DA ruled that partially hydrogenated oils were no longer “generally recognized as safe (GRAS)” for any use in human food. Consequently, we have proposed a rapid screening procedure, based on infrared spectroscopy and chemometrics, to rapidly and accurately predict low concentrations of trans fatty acids (<1% of total fatty acids) in edible oils and food lipid extracts.
Karunathilaka, Sanjeewa R.↗
Experimental and simulation study of target biasing effects on plasma transport in linear plasma device MPS-LD
Linear plasma devices (LPDs) are important experimental platforms for investigating plasma–material interactions (PMI). In PMI experiments, it has been found that applying a target bias not only effectively modifies the incident ion energy, but also induces significant changes in the electron density and electron temperature, whereby the evolution of these plasma parameters is primarily governed by plasma transport processes. However, at present, the physical process and mechanism underlying such bias-induced variations remain unclear. In this work, biasing experiments under argon plasma discharge conditions were first carried out on the MPS-LD device. For the corresponding experiments, an electric potential model was newly developed based on the BOUT++ LPD module, enabling self-consistent simulations of plasma transport under biased conditions. Numerical simulations were then performed to reproduce the experimental results and to validate the accuracy of the proposed model. Finally, by combining experimental measurements with numerical simulations, a bias-voltage scan was performed to investigate how the electron density and electron temperature vary with the bias voltage (U bias ). The results show that applying negative bias decreases the target electron density (n e,T ) while increasing the target electron temperature (T e,T ). In contrast, positive bias increases both n e,T and T e,T ; however, at high positive bias, n e,T first reaches a maximum and subsequently decreases with further increases in U bias . The underlying physical mechanisms are analyzed using particle flux, momentum, and energy conservation. It indicates that the applied bias regulates the parallel electric field, thereby changing ion and electron velocities, and consequently affecting the electron density. At high positive bias, the ion velocity is further influenced by ion viscosity, leading to the reversal in n e,T . Meanwhile, the enhanced parallel electric field drives stronger currents, significantly increasing ion–electron frictional work and converting the input bias power into electron energy, which raises the electron temperature. In conclusion, these results contribute to a deeper understanding of the effects and mechanisms of biasing on plasma transport in the MPS-LD device.
BOUT++ simulation↗
Coupling methods between finite element-based Boussinesq-type wave and particle-based free-surface flow models [Coupling methods between finite element-based Boussinesq-typewave and particle-based free-surface flow models]
We develop one-way coupling methods between a Boussinesq-type wave model based on the discontinuous Galerkin finite element method and a free-surface flow model based on a mesh-free particle method to strike a balance between accuracy and computational cost. In our proposed model, computation of the wave model in the global domain is conducted first, and the nonconstant velocity profiles in the vertical direction are reproduced by using its results. Computation of the free-surface flow is performed in a local domain included within the global domain with interface boundaries that move along the reproduced velocity field in a Lagrangian fashion. To represent the moving interfaces, we used a polygon wall boundary model for mesh-free particle methods. Verification and validation tests of our proposed model are performed, and results obtained by the model are compared with theoretical values and experimental results to show its accuracy and applicability.
97 MATHEMATICS AND COMPUTING↗
A scalable, open-source implementation of a large-scale mechanistic model for single cell proliferation and death signaling
Mechanistic models of how single cells respond to different perturbations can help integrate disparate big data sets or predict response to varied drug combinations. However, the construction and simulation of such models have proved challenging. Here, we developed a python-based model creation and simulation pipeline that converts a few structured text files into an SBML standard and is high-performance- and cloud-computing ready. We applied this pipeline to our large-scale, mechanistic pan-cancer signaling model (named SPARCED) and demonstrate it by adding an IFNγ pathway submodel. We then investigated whether a putative crosstalk mechanism could be consistent with experimental observations from the LINCS MCF10A Data Cube that IFNγ acts as an anti-proliferative factor. The analyses suggested this observation can be explained by IFNγ-induced SOCS1 sequestering activated EGF receptors. This work forms a foundational recipe for increased mechanistic model-based data integration on a single-cell level, an important building block for clinically-predictive mechanistic models.
60 APPLIED LIFE SCIENCES↗
Microstructural-Level Fuel Performance Modeling of U-Mo Monolithic Fuel
As the physics that governs the microstructural evolution of nuclear fuel span various time and spatial scales, to fully understand the fuel behavior inevitably involves atomic to mesoscale resolution that can be difficult to determine experimentally. Microstructural-level modeling and simulations can be used to develop physics-based materials models that can provide physical understanding to inform fabrication process control, as well as a valuable feedback mechanism between post-irradiation examination (PIE) results and fabrication parameters. In accordance with the program schedule, the primary goals of the microstructure modeling effort are to: 1. Address critical microstructural questions and provide practical guidance to the fabricator via the fuel product specification; 2. Provide mechanistic inputs for the existing fuel performance code to improve its descriptive and predictive capability at the macroscopic scale. In fiscal year (FY)-21, the work scope consisted of six main facets: (1) the effect of carbides on fuel performance; (2) gas diffusivity in different phases; (3) integration of microstructural fuel performance modeling; (4) property degradation; (5) irradiation creep; and (6) historical analysis of microstructure data. Brief summaries of each are included below.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Developing the Oxidation Kinetic Model for Magnetite Pellet
Oxidation is a vital phenomenon for magnetite pellets in their excursion through the furnace during induration. One of the pre-requisites for magnetite pellets to achieve homogeneously structured good quality pellets is to have complete oxidation before sintering begins. Partially oxidized magnetite pellets, upon sintering, might result in inhomogeneous structured pellets which could be detrimental to pellet quality. It is necessary to understand the mechanisms responsible for magnetite oxidation, and hence, it is intended in this study to investigate experimentally as well as develop a mathematical model based on oxidation kinetics. Oxidation of pellets is largely influenced by the oxidation kinetics of particles and hence should be studied at particle as well as at pellet scale. The principles of the Grain Model have been adopted to develop the Oxidation Model at pellet scale, whereas the particles’ oxidation follows the Avrami Kinetic Model. Isothermal oxidation experiments performed Thermogravimetric Analyzer showed that oxidation rate of magnetite at pellet scale contained two peaks. They were complemented well by oxidation rates predicted from the model. Further, the pellet was investigated microstructurally at pellet and particle scale to substantiate the findings from the experiments and the model. The oxidation model developed is used to predict the progression of oxidation in the magnetite pellet with respect to the reaction time at three different temperatures (873 K, 973 K, and 1073 K (600 °C, 700 °C, and 800 °C)) and at four levels of oxygen (0.21, 0.30, 0.60, and 1.00 atm) in the oxidizing gas.
36 MATERIALS SCIENCE↗
Use Cases and Model Development of Thermal Storage Coupling for Advanced Nuclear Reactors
This report discusses the different options for coupling thermal energy storage (TES) systems to advanced nuclear power plants (A-NPPs) in order to enable flexible and hybrid plant operation. An advanced light-water reactor (ALWR) and a high-temperature gas-cooled reactor (HTGR) were selected as the initial use cases for demonstrating a thermally balanced energy storage coupling design for thermal power extraction. Cost functions for the A-LWR were derived from the fully balanced models that were developed based on three different coupling options with three different thermal energy bypass ratios. For the next steps, cost functions for the HTGR will also be derived, and additional nuclear reactors (e.g., a liquid-cooled fast reactor [LFR] or molten-salt reactor [MSR]) will be evaluated for coupling with TES in similar fashion, including the evaluation of their steady-state condition models and cost functions. The models presented herein showcase several design considerations, focusing on optimal deployment methodologies for achieving steady-state operation with minimum disruption to the nuclear power generation cycle. This report presents the results of steady state models developed using Aspen HYSYS®, wherein the thermal energy bypass for an NPP-TES coupling was varied up to 50%. The various components were sized using Aspen Process Economic Analyzer (APEA) and Aspen Exchanger Design and Rating (EDR), when applicable. Cost functions from these models were developed using the latest publicly available data obtained from APEA V11. The current steady-state models and cost functions provide a baseline for additional work focusing on dynamic operation and process optimization by using Idaho National Laboratory (INL)’s Framework for Optimization of Resources and Economics (FORCE) tools to evaluate the technoeconomic viability and transient operations of TES-coupled A-NPPs.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Modeling the influence of bubble pressure on grain boundary separation and fission gas release
Grain boundary (GB) separation as a mechanism for fission gas release (FGR), complementary to gas bubble interlinkage, has been experimentally observed in irradiated light water reactor fuel. However there has been limited effort to develop physics-based models incorporating this mechanism for the analysis of FGR. In this work, a computational study is carried out to investigate GB separation in UO2 fuel under the effect of gas bubble pressure and hydrostatic stress. A non-dimensional stress intensity factor formula is obtained through 2D axisymmetric analyses considering lenticular bubbles and Mode-I crack growth. The obtained functional form can be used in higher length-scale models to estimate the contribution of GB separation to FGR.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Prediction of residual stresses in a multipass pipe weld by a novel 3D finite element approach
Due to enormous computation cost, current residual stress simulation of multipass girth welds are mostly performed using two-dimensional (2D) axisymmetric models. The 2D model can only provide limited estimation on the residual stresses by assuming its axisymmetric distribution. In this study, a highly efficient thermal-mechanical finite element code for three-dimensional (3D) model has been developed based on high performance Graphics Processing Unit (GPU) computers. Our code is further accelerated by considering the unique physics associated with welding processes that are characterized by steep temperature gradient and a moving arc heat source. It is capable of modeling large-scale welding problems that cannot be easily handled by the existing commercial simulation tools. To demonstrate the accuracy and efficiency, our code was compared with a commercial software by simulating a 3D multi-pass girth weld model with over 1 million elements. Our code achieved comparable solution accuracy with respect to the commercial one but with over 100 times saving on computational cost. Moreover, the three-dimensional analysis demonstrated more realistic stress distribution that is not axisymmetric in hoop direction.
Huang, Hui↗
SOLAR OPACITY CALCULATIONS USING THE SUPER-TRANSITION-ARRAY METHOD
A new opacity model has been developed based on the Super-Transition-Array (STA) method for the calculation of monochromatic opacities of plasmas in local thermodynamic equilibrium. The atomic code, named STAR (STA-Revised), is described and used to calculate spectral opacities for a solar model implementing the recent AGSS09 composition. Calculations are carried out throughout the solar radiative zone. The relative contributions of different chemical elements and atomic processes to the total Rosseland mean opacity are analyzed in detail. Monochromatic opacities and charge-state distributions are compared with the widely used Opacity Project (OP) code, for several elements near the radiation–convection interface. STAR Rosseland opacities for the solar mixture show a very good agreement with OP and the OPAL opacity code throughout the radiation zone. Finally, an explicit STA calculation was performed of the full AGSS09 photospheric mixture, including all heavy metals. It was shown that, due to their extremely low abundance, and despite being very good photon absorbers, the heavy elements do not affect the Rosseland opacity.
79 ASTRONOMY AND ASTROPHYSICS↗
Atomistic Simulations in Support of UO{sub 2} Fuel Performance Modeling
Large fission gas atoms such as Xe have very low solubility in the UO{sub 2} fuel matrix, which drives precipitation and growth of intra-granular fission gas bubbles, segregation of gas atoms to grain boundaries and evolution of intergranular bubbles. The inter-granular bubbles develop percolation networks leading to release of the fission gas. Fission gas bubbles induce fuel swelling and the fuel thermal conductivity is reduced by both fission gas bubbles and dispersed gas atoms. When fission gas is released from the fuel to the plenum, the pressure on the clad walls increases and the gap thermal conductivity decreases. All of these detrimentally affect fuel performance. The thermal conductivity of UO{sub 2} is low across a wide temperature range compared to iso-structural materials such as ThO{sub 2}, which is caused by the coupling between phonons carrying heat and uranium spins or magnetism providing a scattering mechanism with very low mean free path. For in-pile conditions the thermal conductivity is further reduced due to, for example, radiation damage, generation of fission products and fission gases and fuel microstructure evolution. This results in a complex burn-up dependent thermal conductivity. Thermal conductivity and fission gas evolution are two of the most important properties determining UO{sub 2} nuclear fuel performance. Both properties have significant uncertainty. In order to reduce this uncertainty, new models are being developed based on multi-scale simulations that attempt to improve the description of material properties and also couple them to the microstructure state of the material. In this paper we highlight atomistic calculations and simulations used to develop meso-scale models of the evolution of fission gases and thermal conductivity in UO{sub 2}. Literature examples of the application of these results and the corresponding models to fuel performance simulations will also be given. (author)
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Developing Cheap but Useful Machine Learning-Based Models for Investigating High-Entropy Alloy Catalysts
Not Available
36 MATERIALS SCIENCE↗
On the pressure effect in energetic deposition of Cu thin films by modulated pulsed power magnetron sputtering: A global plasma model and experiments
The modulated pulsed power magnetron sputtering (MPPMS) discharge processes are numerically modeled and experimentally investigated, in order to explore the effect of the pressure on MPPMS discharges as well as on the microstructure of the deposited thin films. A global plasma model has been developed based on a volume-averaged global description of the ionization region, considering the loss of electrons by cross-B diffusion. The temporal variations of internal plasma parameters at different pressures from 0.1 to 0.7 Pa are obtained by fitting the model to duplicate the experimental discharge data, and Cu thin films are deposited by MPPMS at the corresponding pressures. The surface morphology, grain size and orientation, and microstructure of the deposited thin films are investigated by scanning electron microscopy, transmission electron microscopy, and x-ray diffraction. By increasing the pressure from 0.1 to 0.7 Pa, both the ion bombardment energy and substrate temperature which are estimated by the modeled plasma parameters decrease, corresponding to the observed transition of the deposited thin films from a void free structure with a wide distribution of grain size (zone T) into an underdense structure with a fine fiber texture (zone 1) in the extended structure zone diagram (SZD). The microstructure and texture transition of Cu thin films are well-explained by the extended SZD, suggesting that the primary plasma processes are properly incorporated in the model. The results contribute to the understanding of the characteristics of MPPMS discharges, as well as its correlation with the microstructure and texture of deposited Cu thin films.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Development of a MOOSE-based crystal plasticity model with irradiation defect evolution for irradiation creep in 316
Irradiation creep and irradiation swelling are two of the lifetime limiting factors for structural materials in nuclear reactors. These mechanical effects are driven by irradiation defect evolution and the interaction of those defects with dislocations in the microstructure. We present here a coupled cluster dynamics – crystal plasticity approach to model irradiation swelling and creep behavior in 316 SS. The time-dependent evolution of irradiation defects is calculated with a cluster dynamics approach and passed to the crystal plasticity model to compute the dislocation evolution. We show the impact of the irradiation defect evolution on the stress state in the material, which drives inelastic deformation through dislocation motion. The inelastic deformation in the 316 SS is dependent on the dose rate, where the inelastic deformation driven by the early-stage irradiation defect evolution determines the mechanical behavior of the 316 SS.
316 Stainless Steels↗
Developing a generalized ML-based NLTE spectral model for HED applications
Explore the source record for details and available documents.
Schaeuble, Marc-Andre↗
Modeling of Inverter Based AC Microgrids for Control Development.
Abstract not provided.
Wilson, David G.↗