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At least 235 records · Page 13

Modelling and simulation of brinicle formation

Below the Arctic sea ice, under the right conditions, a flux of icy brine flows down into the sea. The icy brine has a much lower fusion point and is denser than normal seawater. As a result, it sinks while freezing everything around it, forming an ice channel called a brinicle (also known as ice stalactite). In this paper, we develop a mathematical model for this phenomenon, assuming cylindrical symmetry. The fluid is considered to be viscous and quasi-stationary. The heat and salt transport are weakly coupled to the fluid motion and are modelled with the corresponding conservation equations, accounting for diffusive and convective effects. Finite-element discretization is employed to solve the coupled system of partial differential equations. We find that the model can capture the general behaviour of the physical system and generate brinicle-like structures while also recovering dendrite composition, which is a physically expected feature aligned with previous experimental results. This represents, to our knowledge, the first complete model proposed that captures the global structure of the physical phenomenon even though it has some discrepancies, such as brine accumulation.

97 MATHEMATICS AND COMPUTING↗

Learning unknown physics of non-Newtonian fluids

Here, we use physics-informed neural networks (PINNs) to learn viscosity models of two non-Newtonian systems (polymer melts and suspensions of particles) using only velocity measurements. For synthetic velocity data generated with the power-law viscosity model, the PINN-inferred viscosity model agrees with the analytical model for shear rates with large absolute values but deviates for shear rates near zero where the analytical model has an unphysical singularity. Once the viscosity model is learned the PINN method can solve the momentum conservation equation using only the boundary conditions.

42 ENGINEERING↗

Verification, Validation, and Uncertainty Quantification in Thermal Hydraulics, Freeman Scholar Lecture (2019)

Engineering problems are generally solved by analytical models or computer codes. These models, in addition to conservation equations, also include many empirical relationships and approximate numerical methods. Each of these components contributes to the uncertainty in the prediction. A systematic approach to judge the applicability of the code to the intended application is needed. It starts from verification of implementation of formulation in the code, identification of important phenomena, finding relevant tests with quantified uncertainty for these phenomena, and validation of the code by comparing predictions with the relevant test data. The relevant tests must address phenomena as expected in the intended application. In case of small size or limited condition tests, the scaling analyses are needed to assess the relevancy of the tests. Finally, a statement of uncertainty in the prediction is needed. Systematic approaches are described to aggregate uncertainties from different components of the code for intended application. Here, verification, validation, and uncertainty quantifications (VVUQs) are briefly described.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Drying of a Fully Saturated Porous Medium With Excess Water Layers: A Numerical Study

Abstract Drying of moist porous media can be very energy inefficient. For example, in the pulp and paper industry, paper drying consumes more than two-thirds of the total energy used in paper machines. Novel drying technologies can decrease the energy used for drying and lessen the manufacturing processes' carbon footprint. Developing next-generation drying technologies to dry moist porous media may require an understanding of removing moisture from a fully saturated porous material with excess water. This paper provides a fundamental understanding of heat and mass transfer in a fully saturated porous medium with excess water. This is relevant, for example, in drying tissue as well as pulp or paper for the purpose of thermal insulation where pressing is preferred to be avoided to overcome the reduction in the sheet thickness. For this purpose, a theoretical drying model is developed where the porous medium corresponds to paper and is assumed to be sandwiched between two excess-water layers (bottom and top). The conjugate model consists of energy and mass conservation equations for each layer. The model is validated with corresponding experimental data. In the model, the thickness of each water layer is calculated as a function of drying time based on local temperature and total moisture content. The numerical model is transient and one-dimensional in space (i.e., in the thickness direction). This paper demonstrates the governing equations, boundary conditions, and results when the saturated porous medium with water layers is heated from one side. Moisture and temperature profiles are estimated in the thickness direction of the porous medium as it dries.

Engineering↗

The research into the propagation law of the shock wave of a gas explosion inside a building

Based on the dissipation rate conservation equations of turbulent kinetic energy in the k‐ ε turbulence model, a complicated three‐dimensional finite element model of a kitchen filled with gas mixture is developed by using the open source field operation and manipulation (OpenFOAM). Two representative kitchens were used to investigate the propagation law of the shock wave of a gas explosion inside a building by considering the key characteristics of the blast shock wave. The influence of some crucial parameters, such as initial conditions and kitchen parameters, on the properties of the blast shock wave is investigated. The basic steps to predict the peak pressure of the blast shock wave are given in consideration of the initial condition and the kitchen whilst the injury effect of the blast shock wave on the humans and animals is evaluated. The research results indicate that the pressure time history and the peak pressure space distribution are greatly influenced by the kitchen design layout. The coupled interaction between the initial temperature and gas volume concentration, especially at the upper and lower explosion limits of the gas, significantly affects the peak pressure. The peak pressure varies significantly with the opening and the buffer; however, it has little relation with the width, length, and height of the kitchen. The proposed method can accurately and effectively predict the peak pressure of the blast shock wave inside buildings. In terms of the peak pressure space distribution of the explosion shock wave, the peak pressure is much higher than the threshold of the killing pressure, which is unsafe for the humans and animals in the building.

Lin, Shu-Chao↗

DualSPHysics-INL

Funded by the DOE's Bioenergy Technology Office through the Feedstock-Conversion Interface Consortium, INL researchers developed this code to model biomass freestock flow in various handling equipment, such as hoppers and augers. Built on top of an existing open-source code DualSPHysics (https://dual.sphysics.org/) , the enrichment includes modification of the mass conservation equation that switching tracking density to void ratio, adding a hypoplastic constitutive law to better capture the flow physics of this type of material and implementing a novel boundary condition that can handle the dynamic contact between material and equipment. All implementation were realized via Nvidia CUDA, so GPU accelaration can be leveraged to signifiantly speed up the computational process.

Jin, Wencheng [Idaho National Laboratory (INL), Id↗

Isotherm Modeling and Techno-Economic Analysis of Contactor Technologies for New Tetraamine-Appended MOF for NGCC Applications

Recently, a family of tetraamine-functionalized metal-organic frameworks (MOF) has been reported as promising sorbent materials for capturing CO2 from flue gas conditions relevant to natural gas combined cycle (NGCC) applications. The main advantages of these materials are their two-step cooperative CO2 adsorption, which gives rise to unusual two step-shaped CO2 adsorption profiles and their high thermal stability. This work presents the modelling of the two-transition isotherm of the tetraamine-appended MOF, N,N'-bis(3-aminopropyl)-1,4-diaminobutane (3-4-3)-appended Mg2(dobpdc), and the techno-economic analysis (TEA) of carbon capture processes utilizing this sorbent. Due to the unusual isotherm shapes of the experimental CO2 adsorption data for tetraamine-appended Mg2(dobpdc) and the strong nonlinearity of CO2 loading with respect to temperature and pressure, we tested two different models which use logistic functions for representing the different isotherm behaviors in the different pressure ranges. The first model uses the quadratic isotherm model in the low-pressure region, the Langmuir isotherm model in the middle pressure range, and the dual site Langmuir isotherm model in the high-pressure range. To model the transition between regions we used the arctangent functions independent of temperature and the thermal effect was accounted by using the Clausius-Clapeyron relation]. The second model is an extension of the weighted dual-site Langmuir isotherm model presented by Hughes et al.. In this extended model, the dual-site Langmuir isotherm is employed in the three transition regions, using temperature-dependent logistic functions to activate or deactivate the isotherm model in the low, middle, and high-pressure ranges. Both models fit the experimental data quite well with root mean squared errors (RMSE’s) of 0.41 and 0.17 for model 1 and model 2, respectively. Since model 2 resulted in a lower RMSE, it was leveraged for the development of the gas/solid contactor models used by the TEA. Specifically, two different contactor models, an axial-flow fixed bed and moving bed contactor, were developed as part of this work. These models are dynamic, pressure-driven, and consist of mass, energy, and momentum conservation equations. A kinetic model was also developed by performing parameter estimation using experimental fixed bed breakthrough data. These models are then used to simulate CO2 capture processes from the flue gas generated from a ~600 gross MW NGCC power plant. A cost model was developed which considers the capital cost of the reactors and the significant operating costs such as steam and electricity. Using NETL’s Framework for the Optimization and Quantification of Uncertainty of Uncertainty and Surrogates tool (FOQUS), which has the capability of linking models built using numerous modelling platforms with derivative-free optimization solvers, a techno-economic optimization of the carbon capture processes was performed which minimizes the cost of capture.

Caballero, Daison↗

Vidyut3d: A Gpu Accelerated Fluid Solver for Non-Equilibrium Plasmas on Adaptive Grids

We present the numerical methods, programming methodology, verification, and performance assessment of a non-equilibrium plasma fluid solver that can effectively utilize current and upcoming central processing and graphics processing unit (CPU+GPU) architectures, in this work. Our plasma fluid model solves the coupled conservation equations for species transport, electrostatic Poisson and electron temperature on adaptive Cartesian grids. Our solver is written using performance portable adaptive-grid/particle management library, AMReX, and is portable over widely available vendor specific GPU architectures. We present verification of our solver using method of manufactured solutions that indicate formal second order accuracy with central diffusion and fifth-order weighted-essentially-non-oscillatory (WENO) advection scheme. We also verify our solver with published literature on capacitive discharges and atmospheric pressure streamer propagation. We demonstrate the use of our solver on two 3D simulation cases: an atmospheric streamer propagation in Ar-H2 mixtures and a low pressure twin electrode radio frequency reactor. Our performance studies on three different CPU+GPU architectures indicate approximately 150-400X speed-up using AMD and NVIDIA GPUs per time step compared to a single CPU core for a 4 million cell simulation with 15 species.

Sitaraman, Hariswaran↗

CTF Validation and Verification (V.4.2)

Coolant-Boiling in Rod Arrays- Two Fluids (COBRA-TF) is a thermal/hydraulic (T/H) simulation code designed for Light Water Reactor (LWR) analysis. It uses a two-fluid, three-field (i.e. fluid film, fluid drops, and vapor) modeling approach. Both sub-channel and 3D Cartesian forms of nine conservation equations are available for LWR modeling. The code was originally developed by Pacific Northwest Laboratory in 1980 and has been used and modified by several institutions over the last several decades. COBRA-TF is also used at the Pennsylvania State University (PSU) by the Reactor Dynamics and Fuel Modeling Group (RDFMG) and has been improved, updated, and subsequently became the PSU RDFMG version of COBRA-TF (CTF). One part of the improvement process includes validating the methods in CTF. This document seeks to provide a certain level of certainty and confidence in the predictive capabilities of the code for the scenarios it was designed to model-rod bundle geometries with operating conditions that are representative of prototypical Pressurized Water Reactor (PWR)s and Boiling Water Reactor (BWR)s in both normal and accident conditions. This is done by modeling a variety of experiments that simulate these scenarios and then presenting a qualitative and quantitative analysis of the results that demonstrates the accuracy to which CTF is capable of capturing specific quantities of interest.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Improvements to CTF Code Verification and Unit Testing (FY2020)

In 2010, the U.S. Department of Energy created its first Energy Innovation Hub, which focuses on improving Light Water Reactors (LWRs) through Modeling and Simulation. This hub, named the Consortium for the Advanced Simulation of LWRs (CASL), attempts to characterize and understand LWR behavior under normal operating conditions and use any gained insights to improve their efficiency. In collaboration with North Carolina State University (NCSU), CASL has worked extensively on the thermal-hydraulic subchannel code Coolant Boiling in Rod Arrays—Three Field (COBRA-TF). The NCSU/CASL version of COBRA-TF has been rebranded as CTF. This document focuses on code verification test problems that ensure CTF converges to the correct answer for the intended application. The suite of code verification tests are mapped to the underlying conservation equations of CTF, and significant gaps are addressed. Convergence behavior and numerical errors are quantified for each of the tests. Tests that converge at the correct rate to the corresponding analytic solution are incorporated into the CTF automated regression suite. A new verification utility is created for this purpose, which enables code verification by generalizing the process. For problems that do not behave correctly, the results are reported but the problem is not included in the regression suite. In addition to verification studies, this document also quantifies the existing tests of constitutive models. A few existing gaps are addressed by adding new unit tests.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

(U) A Theoretical Study of Asay Foil Trajectories (V.02)

We consider the trajectory of a generic Asay foil ejecta momentum diagnostic sensor, for scenarios where ejecta are produced at a planar surface and fly ballistically through a perfect vacuum to the sensor. To do so, we build upon a previously established mathematical formalism derived for the analytic study of stationary sensors (i.e., piezopins). First, we derive the momentum conservation equation for the problem, in a form amenable to accelerating sensors, in terms of a generic ejecta source areal mass function (“source model”). This defines an integro-differential equation (IDE) for the foil trajectory. When ejecta production is instantaneous - as is generally assumed in momentum diagnostic data analyses - the IDE leads to an implicit and easily calculable closed-form solution for the foil trajectory in a perfect system, as long as the ejecta particle velocity distribution is twice-integrable. General properties of the instant-production trajectory solution indicate the existence of a boundary condition the particle velocity distribution must satisfy in order for the analytically predicted foil trajectories to be compatible with certain features commonly observed in foil data. This boundary condition is identical to one derived previously from a consideration of piezopin data. Armed with the analytic solution for instant production, we also consider various techniques used to extract time-dependent cumulative ejecta masses from foil trajectories, and derive an expression for the error imposed by using an approximated equation of motion. This analytic trajectory solution furthermore makes it possible to examine the common practice of presenting inferred cumulative ejecta masses as a function of a normalized implied velocity; we derive conditions under which this methodology is and is not meaningful. We also propose a strategy for extending the instant-production trajectory solution to time-dependent source functions.

42 ENGINEERING↗

Explicit Modeling of Pebble Temperature in the Porous-medium Framework for Pebble-bed Reactors Applications

In this study, an explicit model for pebble temperature calculations in the framework of a porous-medium approach has been developed and implemented in the SAM code. The solid-phase energy conservation equation, including the explicit modeling of pebble temperature, is a multi-scale model, which can predict the macroscopic (pebble-bed) and microscopic (pebble) temperature distributions under both steady-state and transient conditions. Extensive and successful code verifications and demonstrations have been performed for this newly developed model. By explicitly modeling pebble temperatures, this new model addresses a major deficiency of the previously implemented model, which assumed a local solid-phase thermal equilibrium that is not appropriate for pebble-bed reactor design and safety analysis applications.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

CTF Theory Manual (V.4.2)

Coolant-Boiling in Rod Arrays—Two Fluids (COBRA-TF) is a thermal/hydraulic (T/H) simulation code designed for light water reactor (LWR) vessel analysis. It uses a two-fluid, three-field (i.e. fluid film, fluid drops, and vapor) modeling approach. Both sub-channel and 3D Cartesian forms of 9 conservation equations are available for LWR modeling. The code was originally developed by Pacific Northwest Laboratory in 1980 and had been used and modified by several institutions over the last few decades. COBRA-TF also found use at the Pennsylvania State University (PSU) by the Reactor Dynamics and Fuel Modeling Group (RDFMG) and has been improved, updated, and subsequently re-branded as CTF. As part of the improvement process, it was necessary to generate sufficient documentation for the open-source code which had lacked such material upon being adopted by RDFMG. This document serves mainly as a theory manual for CTF, detailing the many two-phase heat transfer, drag, and important accident scenario models contained in the code as well as the numerical solution process utilized. Coding of the models is also discussed, all with consideration for updates that have been made when transitioning from COBRA-TF to CTF. Further documentation outside of this manual is also available at RDFMG which focus on code input deck generation and source code global variable and module listings

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Performance Results for Sensor Assignment Problem as Solved on a Multi-Node Cluster

An earlier report described a procedure for optimal sensor set selection and its implementation on a computational cluster. This new and innovative capability was developed to facilitate a reduction in operations staffing levels to improve plant economics. By automating surveillance and maintenance tasks through early detection of degrading sensors and equipment, staff can be more efficiently deployed. The method uses automated reasoning and domain knowledge in the form of the conservation equations to infer from plant measurements the state of equipment health. Inclusion of domain knowledge addresses the problem that exists with pure data-driven methods that there are no rigorous guidelines for determining what constitutes an adequate sensor set. Formalizing the procedure for sensor set selection as we have done results in a more reliable and explainable diagnosis of plant equipment health. Importantly, from the standpoint of the plant owner, personnel are provided with an early and explicit diagnosis of an equipment problem. That in principle automates the process and eliminates having to send personnel into the plant to find the cause as typically occurs when a data-driven method detects an anomaly. In this report we describe first results obtained using a computational cluster to solve the sensor set selection problem as framed above. The case described addresses the problem of equipment health monitoring in the high-pressure (HP) feedwater system of a pressurized light water reactor as seen through the eyes of our collaborating utility partner. Maintenance of this system can amount to millions of dollars per year if equipment health issues go undiagnosed and lead to loss of function. On examining the potential that is inherent in the installed sensor set for diagnosing equipment health degradation, it was found that greater fault resolution capability can be achieved using a sensor set that is 20 percent fewer in number. The take-away is that compared to the installed sensor set there exists a more strategic assignment of sensors that will furnish better health monitoring capability and with fewer sensors. Where the problem defies solution by manual inspection, as is the case here, one can be found by an algorithm. The solution was obtained in four hours using 30 computational cores. The HP feedwater problem as posed above illustrates the added value of approaching the sensor selection problem as one amenable to algorithmic solution. This problem is of interest to advanced reactor designers and to utilities that are setting up remote monitoring and diagnostic centers.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Machine Learning Assisted Safety Modeling and Analysis of Advanced Reactors

With the advances in computational power and numerical methods, analysts can now rely on first-principle simulations to predict ultra-fine details in a variety of applications. Advances in machine learning (ML) have produced algorithms that can now learn high-level abstractions via hierarchical models. This project aims to leverage advances in ML techniques and the available high-resolution simulation data to develop a novel modeling and simulation (M\&S) methodology for reactor safety analysis. While application-agnostic ML techniques are available, complex physics constraints need to be incorporated into ML techniques to build ML-based closures for computationally efficient predictive simulations. This project intends to develop a physics-guided data-driven multi-scale methodology for M\&S of advanced reactors. The project focuses on thermal fluid (T/F) phenomena, which play major roles in advanced reactor safety. Specifically, we propose a data-driven coarse-mesh turbulence model based on local flow features for the transient analysis of thermal mixing and stratification in a sodium-cooled fast reactor (SFR). The model has a coarse-mesh setup to ensure computational efficiency, while it is trained by fine-mesh computational fluid dynamics (CFD) data with Reynolds-averaged Navier-Stokes (RANS) turbulence model to ensure accuracy. Three different neural networks are developed and tested for loss-of-flow transients in the hot pool of SFR, i.e. the densely connected convolutional neural network (DCNN), long-short-term-memory network based on proper orthogonal decomposition (POD-LSTM), and the DCNN informed by LSTM (DCNN-LSTM). The performances of these three neural networks are evaluated based on baseline models. The DCNN-LSTM model has been chosen for further hyperparameter optimization. Furthermore, based on a simplified two-dimensional case, uncertainty quantification (UQ) of the developed ML-based closure are investigated with three methods, i.e. Monte Carlo dropout, deep ensemble, and Bayesian neural network. The developed ML-based turbulent viscosity closure relation based on deep ensemble is then integrated into the system analysis module SAM and serves as a term in the conservation equations. Such a SAM-ML based procedure guarantees that the obtained results are consistent with the physical constraints of the thermal-fluid system. The SAM-ML simulation on the same loss-of-flow transient showed comparable accuracy with the CFD simulation but with a much coarser mesh setup. Last but not least, the ML-based closure improvement with the support of higher-fidelity data from large eddy simulation (LES) is discussed. As a first step towards this direction, a baseline LES simulation is performed to obtain comparable data with RANS results. Based on the early results, future investigation on further improving the ML-based closure is discussed. We believe the developed approach that combines scientific machine learning with nuclear system analysis code can benefit the advanced reactor community as more accurate safety analyses will better characterize reactor safety margins and reduce licensing efforts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Computational Physics Overview [Slides]

Computational physics is an important part of the overall investment in National Security Science at LANL. Computational physics is the study and implementation of numerical analysis to solve problems in physics for which a quantitative theory already exists. Historically, computational physics was the first application of modern computers in science. There are three key elements to computational physics: mathematical models of physical phenomena and conservation equations, computer codes that implement these models, and computer platforms that execute the code instructions and manipulate the data.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Computational fluid dynamic modeling to determine the indoor environment of an electron-ion collider service building

The design for the Electron-Ion Collider (EIC) calls for several service buildings that house various power supplies and control electronics for the collider ring itself. In order to operate within specified conditions, the ambient air entering the power supplies needs to be within a certain temperature range while dissipating the heat from losses. Proper cooling is therefore a necessity in the service buildings to ensure that every aspect of the EIC works as intended. Since the EIC is in the design stage, we are evaluating the indoor environment of the service building using the current design specifications. We have researched multiple forms of literature and performed the necessary calculations to compile a list of boundary conditions that accurately represent the situation at hand. We are using computational fluid dynamics modeling to solve the conservation equations for mass, momentum, and energy (Navier-Stokes). This allows us to perform a finite element analysis which will give us the flow distribution in the room as well as temperature profiles throughout the building. We have obtained a simulation result giving us the temperature profiles for the building and it shows that the placement of the racks and supply vents are essential to obtaining an even temperature distribution. This model will provide a basis for design decisions which will affect the overall cooling of the service building without extending the schedule and avoiding a costly reworking of the cooling system.

43 PARTICLE ACCELERATORS↗

CTF Validation and Verification: Version 4.3

Coolant-Boiling in Rod Arrays- Two Fluids (COBRA-TF) is a thermal/hydraulic (T/H) simulation code designed for light water reactor (LWR) analysis. It uses a two-fluid, three-field (i.e., fluid film, fluid drops, and vapor) modeling approach. Both subchannel and 3D Cartesian forms of nine conservation equations are available for LWR modeling. The code was originally developed by Pacific Northwest Laboratory in 1980 and has been used and modified by several institutions over the last several decades. COBRA-TF is also used at the Pennsylvania State University (PSU) by the Reactor Dynamics and Fuel Modeling Group (RDFMG) and has been improved, updated, and subsequently became the CTF. One part of the improvement process includes validating the methods in CTF. This document seeks to provide a certain level of certainty and confidence in the predictive capabilities of the code for the scenarios it was designed to model—rod bundle geometries with operating conditions that are representative of prototypical pressurized water reactor (PWR)s and boiling water reactor (BWR)s in both normal and accident conditions. This is done by modeling a variety of experiments that simulate these scenarios and then presenting a qualitative and quantitative analysis of the results that demonstrates the accuracy to which CTF is capable of capturing specific quantities of interest.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗