Emily M. Ryan

Carbon Capture Simulation Initiative: A Case Study in Multiscale Modeling and New Challenges

Advanced multiscale modeling and simulation have the potential to dramatically reduce the time and cost to develop new carbon capture technologies. The Carbon Capture Simulation Initiative is a partnership among national laboratories, industry, and universities that is developing, demonstrating, and deploying a suite of such tools, including basic data submodels, steady-state and dynamic process models, process optimization and uncertainty quantification tools, an advanced dynamic process control framework, high-resolution filtered computational-fluid-dynamics (CFD) submodels, validated high-fidelity device-scale CFD models with quantified uncertainty, and a risk-analysis framework. These tools and models enable basic data submodels, including thermodynamics and kinetics, to be used within detailed process models to synthesize and optimize a process. The resulting process informs the development of process control systems and more detailed simulations of potential equipment to improve the design and reduce scale-up risk. Quantification and propagation of uncertainty across scales is an essential part of these tools and models.

A novel method for modeling Neumann and Robin boundary conditions in smoothed particle hydrodynamics

We present a novel smoothed particle hydrodynamics (SPH) method for diffusion equations subject to Neumann and Robin boundary conditions. The Neumann and Robin boundary conditions are common to many physical problems (such as heat/mass transfer), and can prove challenging to implement in numerical methods when the boundary geometry is complex. The new method presented here is based on the approximation of the sharp boundary with a diffuse interface and allows an efficient implementation of the Neumann and Robin boundary conditions in the SPH method. The paper discusses the details of the method and the criteria for the width of the diffuse interface. The method is used to simulate diffusion and reactions in a domain bounded by two concentric circles and reactive flow between two parallel plates and its accuracy is demonstrated through comparison with analytical and finite difference solutions. To further illustrate the capabilities of the model, a reactive flow in a porous medium was simulated and good convergence properties of the model are demonstrated.

Calibration of Computational Models With Categorical Parameters and Correlated Outputs via Bayesian Smoothing Spline ANOVA

It has become commonplace to use complex computer models to predict outcomes in regions where data do not exist. Typically these models need to be calibrated and validated using some experimental data, which often consists of multiple correlated outcomes. In addition, some of the model parameters may be categorical in nature, such as a pointer variable to alternate models (or submodels) for some of the physics of the system. Here, we present a general approach for calibration in such situations where an emulator of the computationally demanding models and a discrepancy term from the model to reality are represented within a Bayesian smoothing spline (BSS) ANOVA framework. The BSS-ANOVA framework has several advantages over the traditional Gaussian process, including ease of handling categorical inputs and correlated outputs, and improved computational efficiency. Finally, this framework is then applied to the problem that motivated its design; a calibration of a computational fluid dynamics (CFD) model of a bubbling fluidized which is used as an absorber in a CO2 capture system. Supplementary materials for this article are available online.

Pore-scale modeling of competitive adsorption in porous media.

In this paper we present a smoothed particle hydrodynamics (SPH) pore-scale multicomponent reactive transport model with competitive adsorption. SPH is a Lagrangian, particle based modeling method which uses the particles as interpolation points to discretize and solve flow and transport equations. The theory and details of the SPH pore-scale model are presented along with a novel method for handling surface reactions, the continuum surface reaction (CSR) model. The numerical accuracy of the CSR model is validated with analytical and finite difference solutions, and the effects of spatial and temporal resolution on the accuracy of the model are also discussed. The pore-scale model is used to study competitive adsorption for different Damköhler and Peclet numbers in a binary system where a plume of species B is introduced into a system which initially contains species A. The pore-scale model results are compared with a Darcy-scale model to investigate the accuracy of a Darcy-scale reactive transport model for a wide range of Damköhler and Peclet numbers. The comparison shows that the Darcy model over estimates the mass fraction of aqueous and adsorbed species B and underestimates the mass fractions of species A. The Darcy-scale model also predicts faster transport of species A and B through the system than the pore-scale model. The overestimation of the advective velocity and the extent of reactions by the Darcy-scale model are due to incomplete pore-scale mixing. As the degree of the solute mixing decreases with increasing Peclet and Damköhler numbers, so does the accuracy of the Darcy-scale model.

A hybrid micro-scale model for transport in connected macro-pores in porous media

This paper presents a hybrid model for transport in connected macro-pores in porous media. A pore-scale model is used to parameterize the hybrid model. The hybrid model explicitly models the advection and diffusion of species in the connected macro-pores and treats the porous media around the connected macro-pores as a continuum with effective transport properties. The pore-scale model is used to calculate the effective transport properties of the porous continuum. This approach negates the need to calibrate the hybrid model against experimental data, which is common for continuum-scale models of porous media, and allows an arbitrary microstructure to be considered. The paper presents the multi-scale modeling approach along with the details of the hybrid and pore-scale models. Validation of the model is also presented along with several case studies investigating the applicability of the multi-scale modeling approach to different geometries and transport conditions. The case studies show that the multi-scale modeling approach is accurate for various connected macro-pore geometries given that the porosity of the porous medium around the connected macro-pores is sufficiently small. The accuracy of the hybrid model decreases with increasing porosity of the matrix.

Suppressing Dendritic Lithium Formation Using Porous Media in Lithium Metal-Based Batteries

Because of its ultrahigh specific capacity, lithium metal holds great promise for revolutionizing current rechargeable battery technologies. Nevertheless, the unavoidable formation of dendritic Li, as well as the resulting safety hazards and poor cycling stability, have significantly hindered its practical applications. A mainstream strategy to solve this problem is introducing porous media, such as solid electrolytes, modified separators, or artificial protection layers, to block Li dendrite penetration. However, the scientific foundation of this strategy has not yet been elucidated. Herein, using experiments and simulation we analyze the role of the porous media in suppressing dendritic Li growth and probe the underlying fundamental mechanisms. It is found that the tortuous pores of the porous media, which drastically reduce the local flux of Li+ moving toward the anode and effectively extend the physical path of dendrite growth, are the key to achieving the nondendritic Li growth. On the basis of the theoretical exploration, we synthesize a novel porous silicon nitride submicron-wire membrane and incorporate it in both half-cell and full-cell configurations. The operation time of the battery cells is significantly extended without a short circuit. The findings lay the foundation to use a porous medium for achieving nondendritic Li growth in Li metal-based batteries.

Numerical Modeling of the Distributed Electrochemistry and Performance of Solid Oxide Fuels Cells

A cell-level distributed electrochemistry (DEC) modeling tool has been developed to enable prediction of solid oxide fuel cell performance by considering the coupled and spatially varying multi-physics that occur within the tri-layer. The approach calculates the distributed electrochemistry within the electrodes, which includes the charge transfer and electric potential fields, ion transport throughout the tri-layer, and gas distributions within the composite and porous electrodes. The thickness of the electrochemically active regions within the electrodes is calculated along with the distributions of charge transfer. The DEC modeling tool can examine the overall SOFC performance based on electrode microstructural parameters, such as particle size, pore size, porosity factor, electrolyte and electrode phase volume fractions, and triple-phase-boundary length. Recent developments in electrode fabrication methods have lead to increased interest in using graded and nano-structured electrodes to improve the electrochemical performance of SOFCs. This paper demonstrates how the DEC modeling tool can be used to help design novel electrode microstructures by optimizing a graded anode for high electrochemical performance.

Modeling and Validation of a Large Scale, Multiphase Carbon Capture System

As the effects of climate change continue to rise with increasing carbon dioxide emission rates, it is imperative that we develop an efficient method for carbon capture. This paper outlines the framework used to break down a large, complex carbon capture system into smaller unit problems for model validation, and uncertainty quantification. We use this framework to investigate the uncertainty and sensitivity of the hydrodynamics of a bubbling fluidized bed. Using the open-source computational fluid dynamics code MFIX we simulate a bubbling fluidized bed with an immersed horizontal tube bank. Mesh resolution and statistical steady state studies are conducted to identify the optimal operating conditions. The preliminary results show good agreement with experimental data from literature. Employing statistical sampling and analysis techniques we designed a set of simulations to quantify the sensitivity of the model to model parameters that are difficult to measure, including: coefficients of restitution, friction angles, packed bed void fraction, and drag models. Initial sensitivity analysis results indicate that no parameters may be omitted. Further uncertainty quantification analysis is underway to investigate and quantify the effects of model parameters on the simulations results.Copyright

Modeling the Electrochemistry of an SOFC through the Electrodes and Electrolyte

This paper describes a distributed electrochemistry model of the solid oxide fuel cell (SOFC) electrodes and electrolyte. The distributed electrochemistry (DEC) model solves the transport, reactions, and electric potential through the thickness of the SOFC electrodes. The DEC model allows the local conditions within the electrodes to be studied and allows for a better understanding of how electrochemical and microstructural parameters affect the electrodes. In this paper the governing equations and implementation of the DEC model are presented along with several case studies which are used to investigate the sensitivity of the cathode to the microstructural and electrochemical parameters of the model and to explore methods of improving the electrochemical performance of the SOFC cathode.

Void fraction inference in cavitating fuel injector flows

It has been shown that hydrodynamic cavitation within fuel injectors plays a significant role in their performance, with the desirable effect of broadening the resultant fuel spray. Experiments are challenging owing to the relatively small geometries, high pressure, and high Reynold’s number (Re) associated with such flows. Previous studies have observed cavitation in optically transparent nozzles at slower flows. By utilizing acoustic and vibration measurement techniques cavitation activity may be measured in a steel fuel injector at more practical Re flows used in applications. We report here experimental measurements taken using a laser vibrometer and a commercial fuel injector. Previous studies have demonstrated a resonant frequency shift as a function of injection pressure. Among competing hypotheses, our working hypothesis is that this shift is the result of mass unloading of cantilever mode oscillations of the fuel injector. The dynamic void fraction caused by cavitation activity within the fuel injector can then be inferred from the measured frequency shift. We report measurements of mode shapes and frequencies for static and flowing fuel injectors as functions of the flow rate.It has been shown that hydrodynamic cavitation within fuel injectors plays a significant role in their performance, with the desirable effect of broadening the resultant fuel spray. Experiments are challenging owing to the relatively small geometries, high pressure, and high Reynold’s number (Re) associated with such flows. Previous studies have observed cavitation in optically transparent nozzles at slower flows. By utilizing acoustic and vibration measurement techniques cavitation activity may be measured in a steel fuel injector at more practical Re flows used in applications. We report here experimental measurements taken using a laser vibrometer and a commercial fuel injector. Previous studies have demonstrated a resonant frequency shift as a function of injection pressure. Among competing hypotheses, our working hypothesis is that this shift is the result of mass unloading of cantilever mode oscillations of the fuel injector. The dynamic void fraction caused by cavitation activity within the fuel in...