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At least 1,063 records · Page 59

Computation of conventional and alternative jet fuel sensitivity to lean blowout

Large Eddy Simulations (LES) are performed to compute the sensitivity of a conventional (A-2) and an alternate bio-jet (C-1) fuel to Lean Blowout (LBO). A realistic aviation gas turbine engine combustor configuration is considered. Reliable experimental LBO data and OH* chemiluminescence data for the conventional and alternate jet fuel in the combustor configuration have recently become available. The present work utilizes a highly automated, on-the-fly meshing strategy, along with adaptive mesh refinement, to demonstrate the feasibility of capturing the realistic combustion processes. A Lagrangian framework, with initial conditions specified using measurements of spray statistics, is used to model the fuel spray. Newly developed compact reaction mechanisms based on fuel surrogates are validated for the A-2 and the C-1 fuels. The compact reaction mechanisms are implemented using a detailed finite rate chemistry solver. Spray statistics computed by the present LES simulations compare well with available measurements at stable flame conditions near the lean blowout limit. The computed shape of the stable flame as represented by line integrated OH concentrations compares well with the experimental OH* chemiluminescence data. Lean blowout is reached by gradually decreasing the fuel flow rate in the computations, similar to that in the experiments. The results of the LES simulations effectively capture the fuel composition effects and estimate the sensitivity of the LBO limits to the fuel type. The computed trends in LBO limits agree within engineering accuracy with the experimental results for conventional and alternative aviation fuels. The methodology for predicting the fuel composition effects on the lean blowout limits in a fully resolved realistic, complex combustor is established for the first time.

Adaptive mesh refinement↗

Distributed approximate minimal Steiner trees with millions of seed vertices on billion-edge graphs

In this report, we present a parallel 2-approximation Steiner minimal tree algorithm and its MPI-based distributed implementation. In place of expensive distance computations between all pairs of seed vertices, the solution we employ exploits a cheaper Voronoi cell computation. Our design leverages asynchronous processing and message prioritization to accelerate convergence of distance computations, and harnesses vertex and edge centric processing to offer fast time-to-solution. We demonstrate scalability and performance using real-world graphs with up to 128 billion edges and 512 compute nodes, and show the ability to find Steiner trees with up to one million seed vertices. Using 12 data instances, we present comparison with the state-of-the-art exact solver, SCIP-Jack, and two sequential 2-approximate algorithms. We empirically show that, on average, the total distance of the Steiner tree identified by our solution is 1.1290 times greater than the Steiner minimal tree – well within the theoretical approximation bound of 2.

97 MATHEMATICS AND COMPUTING↗

Current interrupt method for calculating the electrochemical impedance in a solid oxide electrolysis stack

Here, in this work the time domain response of Solid Oxide Electrolysis Cells (SOEC) to a current interruption was transformed into the frequency domain using a carrier function Laplace transform, which is fit to the experimental data using a MATLAB Complex Nonlinear Least Squares (CNLS) solver. The hardware implementation, consisting principally of a high-speed switch and a fast-logging Analog to Digital Converter (ADC), was assembled and tested using a calibration module to assess the accuracy, repeatability, and speed of acquisition of the prototype device as compared against a calibrated commercial impedance spectrometer. Additionally, the current interrupt device and commercial FRA were used to acquire the impedance spectra of a four cell SOEC stack with a large, 300 cm 2 , active cell area.

SOEC↗

Multiscale model predictive control of battery systems for frequency regulation markets using physics-based models

In this work, we propose a multiscale model predictive control (MPC) framework for stationary battery systems that exploits high-fidelity models to trade-off short-term economic incentives provided by energy and frequency regulation (FR) markets and long-term degradation effects. We find that the MPC framework can drastically reduce long-term degradation while properly responding to FR and energy market signals (compared to MPC formulations that use low-fidelity models). Our results also provide evidence that sophisticated battery models can be embedded within closed-loop MPC simulations by using modern nonlinear programming solvers (we provide an efficient and easy-to-use implementation in Julia). We use insights obtained with our simulations to design a low-complexity MPC formulation that matches the behavior obtained with high-fidelity models. This is done by designing a suitable terminal penalty term that implicitly captures long-term degradation. The results suggest that complex degradation behavior can be accounted for in low-complexity MPC formulations by properly designing the cost function. We believe that our proof-of-concept results can be of industrial relevance, as battery vendors are seeking to participate in fast-changing electricity markets while maintaining asset integrity.

42 ENGINEERING↗

A fully ro-vibrationally resolved corona model for the molecular hydrogen Fulcher-𝛼 system

A ro-vibrationally resolved corona model for the molecular hydrogen Fulcher-𝛼 transition based on the Yacora solver is introduced. The model couples 1365 ro-vibrational levels of the 𝑋 1 ⁢𝛴$^+_𝑔$, 𝑑 3⁢ 𝛱 𝑢 and 𝑎 3 ⁢𝛴$^+_𝑔$ states via electron impact excitation from the ground state into the 𝑑 3⁢ 𝛱 𝑢 state and subsequent spontaneous emission into the 𝑎 3 ⁢𝛴$+_𝑔$ state. For the process of electron impact excitation a set of 45260 fully ro-vibrationally resolved cross sections calculated with the molecular convergent close-coupling (MCCC) method in the adiabatic-nuclei formulation is applied. The MCCC cross sections are compared with results of a scaling method used in other works, demonstrating the need for dedicated ro-vibrationally resolved cross sections. By post-processing the model output, entire Fulcher spectra can be simulated. These spectra are benchmarked with measurements from an inductively coupled plasma discharge at a pressure between 1.1–10 Pa and a RF power of 700 W. The model results agree very well with the experiment both in relative shape and in absolute value. A non-ro-vibrationally resolved, purely electronically resolved collisional radiative model for molecular hydrogen (including further states and reaction channels) is applied to investigate the validity of the corona approximation for the benchmark plasmas and the relevance of possible process extensions of the corona model. Furthermore, the influence of collisional quenching, autoionization and predissociation is discussed.

74 ATOMIC AND MOLECULAR PHYSICS↗

Posterior Regularized Bayesian Neural Network incorporating soft and hard knowledge constraints

Neural Networks (NNs) have been widely used in supervised learning due to their ability to model complex nonlinear patterns, often presented in high-dimensional data such as images and text. However, traditional NNs often lack the ability for uncertainty quantification. Bayesian NNs (BNNS) could help measure the uncertainty by considering the distributions of the NN model parameters. Besides, domain knowledge is commonly available and could improve the performance of BNNs if it can be appropriately incorporated. In this work, we propose a novel Posterior-Regularized Bayesian Neural Network (PR-BNN) model by incorporating different types of knowledge constraints, such as the soft and hard constraints, as a posterior regularization term. Furthermore, we propose to combine the augmented Lagrangian method and the existing BNN solvers for efficient inference. Furthermore, the experiments in simulation and two case studies about aviation landing prediction and solar energy output prediction have shown the knowledge constraints and the performance improvement of the proposed model over traditional BNNs without the constraints.

14 SOLAR ENERGY↗

Convergence study of wakefield simulations with GdfidL and ECHO3D

The interaction of charged particle beams with vacuum chamber components gives rise to electromagnetic wakefields, whose frequency-domain representation is known as beam coupling impedance. Geometric impedance arising from discontinuities and transitions in the vacuum chamber is the focus of this study. Minimizing this impedance is essential to mitigate adverse collective effects in modern storage rings operating with high-intensity particle beams. Accurate and reliable impedance simulations is a key factor of the vacuum chamber design. This paper presents the results of a convergence study of two widely used electromagnetic solvers, GdfidL and ECHO3D, applied to key vacuum-chamber components of the National Synchrotron Light Source II (NSLS-II) storage ring. Detailed comparisons are performed for several geometries, including flange absorbers, RF bellows, button-type beam position monitors, and an in-vacuum undulator (IVU). The results show notable differences in convergence and computational efficiency between the two codes. While GdfidL provides highly resolved results and serves as a common benchmark tool, ECHO3D yields consistent results with coarser meshes, significantly reducing simulation time and memory demands. Simulations with a full-geometry IVU model demonstrate that simplified taper-transition models can miss important impedance contributions. In conclusion, these findings provide practical guidelines for efficient and accurate impedance modeling to optimize design of vacuum chamber components for accelerators.

36 MATERIALS SCIENCE↗

Demonstrating the impact of ro-vibrationally excited H 2 on divertor detachment via population modelling

EDGE2D-EIRENE profiles characteristic for low recycling, high recycling and detached plasmas are postprocessed applying a vibrationally resolved collisional radiative (CR) model based on the Yacora solver to predict excited state densities and thus the molecular Lyman-, Werner- and Fulcher band emission intensities. These emission intensities are compared to predictions from the AMJUEL database standardly used in EIRENE. Lower Fulcher band and higher Lyman- and Werner band emission is predicted by the Yacora model in comparison to AMJUEL suggesting that inconsistent results from model based evaluation of measured spectra are expected depending on which model and molecular emission band is considered. The implications on detachment rate predictions are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

EVALUATION OF HOT CHANNEL FACTOR FOR SODIUM-COOLED FAST REACTORS WITH MULTI-PHYSICS TOOLKIT

The evaluation of hot channel factor (HCF) is of great significance to the quantification of safety margins for reactor designs. In this paper, HCFs for a sodium-cooled fast reactor (SFR) are evaluated with the Simulation-based High-efficiency Advanced Reactor Prototyping (SHARP) toolkit, which is developed under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) Campaign of DOE for multi-physics reactor performance and safety simulations. The high-fidelity neutronics and thermal hydraulics solvers PROTEUS and Nek5000 in the SHARP toolkit are coupled to perform the multi-physics simulations for HCF evaluation. The HCFs induced by cladding manufacturing tolerance, fissile content mal-distribution, wire orientation and uncertainties on the cladding, coolant, and fuel properties are evaluated for a reference core SFR design (AFR-100). The HCFs calculated with the SHARP toolkit are compared to legacy HCFs for similar reactor types. The comparison demonstrates the reduction or elimination of modeling uncertainties in the calculation of HCFs using high fidelity advanced modeling and simulation tools without the need of expensive experiments. Moreover, the reduction of the uncertainties on HCFs evaluation allows an increase in nominal parameters and safety margin, which in turn improves the economic competitiveness of the SFR.

Hot channel factor (HCF)↗

Validation of numerical models for seismic fluid-structure-interaction analysis of nuclear, safety-related equipment

Seismic design, qualification, and risk assessment of nuclear safety-related vessels filled with liquid will have to consider the interaction between the vessel (tank), the contained liquid, and submerged components, if any. Seismic fluid-structure-interaction (FSI) analysis of nuclear vessels will rely on numerical models, which are required to be verified and validated. This study validates previously-verified numerical models using test data generated from earthquake-simulator experiments involving a cylindrical tank. Two solvers in LS-DYNA for FSI simulations are used for the numerical analysis: Arbitrary-Lagrangian-Eulerian (ALE) and Incompressible Computational Fluid Dynamics (ICFD). Numerical and test results are compared for responses critical to seismic design of advanced reactor vessels: hydrodynamic pressures on the tank wall, reactions at the support, and wave heights of the contained liquid. Analysis is performed for one-, two-, and three-directional seismic inputs with a range of intensity, and rocking motions. The accuracy of the numerical results and different methods for outputting wave heights are discussed. Recommendations for validation of seismic FSI numerical models of advanced reactors are provided. As a result, the validation exercise presented in this study is broadly applicable to cylindrical tanks, regardless of industry sector.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Initial demonstration of automated fuel performance modeling with 1977 EBR-II metallic fuel pins using BISON code with FIPD and IMIS databases

Using the BISON fuel performance code, simulations were conducted using an automated process to read initial and operating conditions from the Fuels Irradiation and Physics Database (FIPD) and Integral Fast Reactor materials information system (IMIS) database, which contains metallic fuel data from the Experimental Breeder Reactor-II (EBR-II). This work demonstrates use of an integrated framework to access the vast majority of EBR-II experimental fuel pin data to support rapid development of fuel performance models for next-generation metallic fuel systems. With this capability, validation for fuel qualification can be performed rapidly. Between IMIS and FIPD, there is enough information to conduct 1977 unique EBR-II metallic fuel pin histories from 24 different experiments, at varying levels of detail between the two databases. Each of these histories includes a high-resolution power history, flux history, coolant channel flow rates, and coolant channel temperatures. Fission gas release (FGR), cumulative damage fraction (CDF), fuel axial swelling, cladding profilometry, and burnup were all simulated in BISON. The results were compared to post-irradiation examination (PIE) results for the initial demonstration of automated BISON modeling. BISON simulations conducted with IMIS and FIPD were in rough agreement with PIE measurements and calculations. Cladding profilometry, FGR, and fuel axial swelling were found to be in rough agreement with PIE measurements, depending on the physics used within the BISON input files. Here, the mechanical contact solver chosen was found to significantly impact axial fuel swelling and cladding strain predictions. CDF values were assessed to see whether pin failure may have been predicted (CDF ≥ 1). This work suggests that continued development of an automated tool for BISON should focus on inclusion of the Fast Flux Test Facility (FFTF) experimental data for a larger database for metallic fuel, improved physical models to better capture fuel performance, such as fuel-cladding interactions, and a more detailed comparison with available PIE data to further the BISON model development.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Numerical study of multi-component flow and mixing in a scaled fission product venting system

Numerical simulation of isothermal multi-component gas flow was conducted to study fluid flow and mixing in a scaled low-pressure, low-temperature test facility for the fission product venting system (FPVS) of a gas cooled fast reactor (GFR). The geometry of FPVS test facility was an open loop including gradual expansion coupling and two 90°pipe elbows. First, the validation of large eddy simulation (LES) wall-adapting local eddy-viscosity (WALE) turbulent model was performed for transitional flow in a circular pipe with gradual expansion. The reactingFOAM solver in OpenFOAM v8 was employed. By introducing appropriate turbulence disturbance at the flow inlet, such as turbulence intensity, the numerical results showed good agreement in (1) the velocity profile downstream of the pipe expansion measured by particle image velocimetry (PIV) in this study, and (2) the reattachment length reported in the literature. Using this validated model, the numerical simulation of flow and component mixing was performed for the FPVS with an inlet flowrate corresponding to a Reynolds number of 2,400 to investigate the flow behavior and component mixing. Standard deviation of the mass fraction of component, referred to as absolute mixing index (AMI), was calculated to quantify the mixing of components, showing that the component mixing length determined by AMI is related to the reattachment length downstream of the expansion. Additionally, this study was able to identify the best location in the FPVS test facility to measure the velocity and concentration profies where multicomponent flow is well mixed.

15 GEOTHERMAL ENERGY↗

Verification and validation of the Alternative Nonlinear Two-phase Subchannel (ANTS) code

The Alternative Nonlinear Two-phase Subchannel solver (ANTS) code was written to provide a fast-running, steady-state, pin-resolved modeling and simulation tool for analysis of common boiling water reactor (BWR) geometry and common operating conditions. ANTS has been integrated into the Virtual Environment for Reactor Application (VERA) core simulator software, where it can be used to provide a thermal/hydraulic (T/H) subchannel solution that is then used to provide neutronic feedback as well as perform the fuel depletion and temperature solution. Herein, this paper presents the rigorous analysis performed on the ANTS code, which includes both code and solution verification testing, benchmarking with the existing two-phase subchannel capability in VERA, CTF, and validation testing using popular two-phase experiments such as PWR Sub-channel and Bundle Tests (PSBT), BWR Full-size Fine-mesh Bundle Tests (BFBT), Risø, and FRIGG. This assessment was used to qualify ANTS for its intended applications before its use for core-scale, multiphysics BWR simulations. In general, it was found that agreement with experimental data was good; errors were within the range of experimental data uncertainty. Furthermore, code and solution verification confirmed that the governing equations and the most important closure terms were correctly implemented and behaving as expected.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

SAM-ML: Integrating data-driven closure with nuclear system code SAM for improved modeling capability

Advanced reactors often involve complicated thermal-fluid (T-F) phenomena. Modeling such phenomena with the traditional one-dimensional (1-D) system code is a challenging task. The System Analysis Module (SAM), a modern nuclear system code, has developed a coarse mesh multi-dimensional (multi-D) flow model to capture the spatial effect of T-F phenomena in advanced reactors. As a coarse mesh solver, constitutive relations are required for SAM's multi-D model for unresolved fine-scale physics, such as turbulence. Here this work presents a novel approach that integrates neural networks as data-driven closure for SAM's multi-D flow model. The data-driven closure is trained with fine-resolution data to ensure its accuracy while maintaining a coarse mesh setup to ensure its efficiency and consistency with SAM. We demonstrate the applicability of this SAM-ML capability in an open volume thermal stratification problem, where a neural network model serves as the eddy viscosity closure. A customized interface between the neural network and SAM is developed to ensure flexible and efficient data exchange. The SAM-ML results demonstrate superior performance compared to SAM's built-in zero-equation eddy viscosity closure. The case study shows that although the generalization capability of the data-driven closure still needs to be improved for different transient case or different geometric setup, SAM -ML demonstrates good potential for challenging simulation problems with improved accuracy and computational efficiency.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Thermomechanical analysis and modeling of involute-shaped fuel plates using the Cheverton–Kelley experiments for the High Flux Isotope Reactor

Three research reactors with involute-shaped fuel plates are pursuing conversion from highly enriched uranium to low-enriched uranium fuel. Various core design and safety evaluation studies are essential to assess the feasibility of the conversion. The use of 3D computational multiphysics codes is being explored in these analyses and therefore they must undergo a thorough evaluation and quality assurance process due to their potential impact on nuclear safety. Here, the Cheverton and Kelley physical tests performed in the late 1960s to investigate the deflections of HFIR’s outer plate under uniform pressure and temperature fields are simulated by employing commercially available computational codes, with the goals to (1) verify and validate the models and numerical solvers implemented in the codes for thermomechanical analysis of involute reactor plates and (2) to develop a benchmark computational test to evaluate future versions of existing software or newly developed computational codes. The results of the simulations showed good agreement with each other as well as against the Cheverton–Kelley experimental data. Some minor deviations were observed for a few multiphysics cases and their potential origins and impact on the analysis results is investigated in the paper. The validated models increase the confidence in using multiphysics codes to evaluate existing or new LEU designs.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

CFD simulations of Molten Salt Fast Reactor core cavity flows

Computational Fluid Dynamics (CFD) has become increasingly important in the research and development of advanced nuclear reactors. Here, in the current study, extensive CFD simulations were conducted for the coolant flow in Molten Salt Fast Reactor (MSFR) core models using the state-of-the-art spectral element flow solver Nek5000 and multiscale coarse-mesh thermal-hydraulic software Pronghorn. The underlying motivation is to seek an in-depth understanding of how the internal velocity distribution can be influenced by the MSFR core cavity shape, the Reynolds number, turbulence modeling options and the inlet boundary conditions. The CFD techniques involved in this investigation range from coarse-mesh CFD, RANS modeling, to the high-fidelity LES calculations. Specifically, a series of RANS simulations were performed for the 2-D axisymmetric core model and 3-D wedge domains to study the flow distribution inside the MSFR core. It is observed that a proper representation of the MSFR inlet channel duct is important for the prediction of internal flow distribution. It is also showcased here how researchers can leverage the Nek5000 CFD results to calibrate more efficient coarse-mesh CFD tools, like Pronghorn, for the actual MSFR design needs. Moreover, this paper highlights a 3-D LES model for an entire MSFR core using the spectral element method and demonstrates the feasibility of this modeling approach. The readiness and potential limitations of the RANS approach are examined with respect to the high-fidelity LES simulations. The present investigation lays a solid foundation as we are leveraging the high-fidelity CFD capabilities to inform MSFR design efforts.

97 MATHEMATICS AND COMPUTING↗

High fidelity multiphysics tightly coupled model for a lead cooled fast reactor concept and application to statistical calculation of hot channel factors

A tightly coupled multiphysics code system is established using the MOOSE framework for hot channel factor (HCF) evaluation on a Lead Fast Reactor (LFR) concept. The coupled system is driven by the Griffin multiphysics coupling capability under which the MOOSE Heat Transfer module and NekRS computational fluid dynamics solver are coupled for conjugate heat transfer using the Cardinal application. The coupled capability is demonstrated on an LFR assembly model based on materials and geometry of a prototypical lead-cooled fast reactor design by Westinghouse Electric Company, LLC. Moreover, the work integrates the Multiphysics Object Oriented Simulation Environment (MOOSE) Stochastic Tools Module (STM) to perform calculations for statistical analysis of HCF. Furthermore, the coupling strategy and workflow demonstrated in this paper is not only useful for predicting accurate hot channel factors for different kinds of advanced reactors but also for other engineering applications such as control rod worth assessment, generation of high-fidelity database for Artificial intelligence (AI)/machine learning (ML) training, design optimization and multi-resolution modeling.

Cardinal↗

Effects of grain size and porosity on cladding failure in high-burnup UO 2 : A sensitivity and uncertainty study

Isotopic taggants are being studied to aid in the provenance assessment of nuclear materials. However, these taggants must be selected such that they do not adversely affect fuel performance during normal operation or accident scenarios. Taggants are known to affect the fuel’s grain size and porosity. In the work described in this paper, the BISON fuel performance code was used to assess the potential effects of taggants (i.e., grain size and porosity) on fuel rod behavior and cladding failure during a high-burnup, large-break loss-of-coolant accident. Here, 281 individual fuel rods from the same reactor core were modeled for a sensitivity study, a parametric study, and uncertainty quantification. The cladding failure predictions often exhibited stochastic behavior. After additional study, it was found that the cladding failure model is highly sensitive to residual error inherent to numerical approximation solvers. Some strategies to mitigate this sensitivity are discussed. The study found no relationship between known taggant effects and cladding failure status. However, taggants were found to affect the time and location of failure in certain rods. In conclusion, future work to continue investigating and validating these findings is briefly discussed.

Doped UO 2↗