Simulation study on PEM fuel cell gas diffusion layers using x-ray tomography based Lattice Boltzmann method

The Polymer Electrolyte Membrane (PEM) fuel cell has a great potential in leading the future energy generation due to its advantages of zero emissions, higher power density and efficiency. For a PEM fuel cell, the Membrane-Electrode Assembly (MEA) is the key component which consists of a membrane, two catalyst layers and two gas diffusion layers (GDL). The success of optimum PEM fuel cell power output relies on the mass transport to the electrode especially on the cathode side. The carbon based GDL is one of the most important components in the fuel cell since it has one of the basic roles of providing path ways for reactant gases transport to the catalyst layer as well as excess water removal. A detailed understanding and visualization of the GDL from micro-scale level is limited by traditional numerical tool such as CFD and experimental methods due to the complex geometry of the porous GDL structural. In order to take the actual geometry information of the porous GDL into consideration, the x-ray tomography technique is employed which is able to reconstructed the actual structure of the carbon paper or carbon cloth GDLs to three-dimensional digital binary image which can be read directly by the LB model to carry out the simulation. This research work contributes to develop the combined methodology of x-ray tomography based the three-dimensional single phase Lattice Boltzmann (LB) simulation. This newly developed methodology demonstrates its capacity of simulating the flow characteristics and transport phenomena in the porous media by dealing with collision of the particles at pore-scale. The results reveal the heterogeneous nature of the GDL structures which influence the transportation of the reactants in terms of physical parameters of the GDLs such as porosity, permeability and tortuosity. The compression effects on the carbon cloth GDLs have been investigated. The results show that the c applied compression pressure on the GDLs will have negative effects on average pore size, porosity as well as through-plane permeability. A compression pressure range is suggested by the results which gives optimum in-plane permeability to through-plane permeability. The compression effects on one-dimensional water and oxygen partial pressures in the main flow direction have been studied at low, medium and high current densities. It s been observed that the water and oxygen pressure drop across the GDL increase with increasing the compression pressure. Key Words: PEM fuel cell, GDL, LB simulation, SPSC, SPMC, x-ray tomography, carbon paper, carbon cloth, porosity, permeability, degree of anisotropy, tortuosity, flow transport

Quantitative analysis of numerical estimates for the permeability of porous media from lattice-Boltzmann simulations

During the last decade, lattice-Boltzmann (LB) simulations have been improved to become an efficient tool for determining the permeability of porous media samples. However, well known improvements of the original algorithm are often not implemented. These include for example multirelaxation time schemes or improved boundary conditions, as well as different possibilities to impose a pressure gradient. This paper shows that a significant difference of the calculated permeabilities can be found unless one uses a carefully selected setup. We present a detailed discussion of possible simulation setups and quantitative studies of the influence of simulation parameters. We illustrate our results by applying the algorithm to a Fontainebleau sandstone and by comparing our benchmark studies to other numerical permeability measurements in the literature.Comment: 14 pages, 11 figure

A simplified mesoscale 3D model for characterizing fibrinolysis under flow conditions

One of the routine clinical treatments to eliminate ischemic stroke thrombi is injecting a biochemical product into the patient’s bloodstream, which breaks down the thrombi’s fibrin fibers: intravenous or intravascular thrombolysis. However, this procedure is not without risk for the patient; the worst circumstances can cause a brain hemorrhage or embolism that can be fatal. Improvement in patient management drastically reduced these risks, and patients who benefited from thrombolysis soon after the onset of the stroke have a significantly better 3-month prognosis, but treatment success is highly variable. The causes of this variability remain unclear, and it is likely that some fundamental aspects still require thorough investigations. For that reason, we conducted in vitro flow-driven fibrinolysis experiments to study pure fibrin thrombi breakdown in controlled conditions and observed that the lysis front evolved non-linearly in time. To understand these results, we developed an analytical 1D lysis model in which the thrombus is considered a porous medium. The lytic cascade is reduced to a second-order reaction involving fibrin and a surrogate pro-fibrinolytic agent. The model was able to reproduce the observed lysis evolution under the assumptions of constant fluid velocity and lysis occurring only at the front. For adding complexity, such as clot heterogeneity or complex flow conditions, we propose a 3-dimensional mesoscopic numerical model of blood flow and fibrinolysis, which validates the analytical model’s results. Such a numerical model could help us better understand the spatial evolution of the thrombi breakdown, extract the most relevant physiological parameters to lysis efficiency, and possibly explain the failure of the clinical treatment. These findings suggest that even though real-world fibrinolysis is a complex biological process, a simplified model can recover the main features of lysis evolution.</p

Constriction Percolation Model for Coupled Diffusion-Reaction Corrosion of Zirconium in PWR

We develop a new constriction-based percolation paradigm, using cellular automata to predict the transport of oxygen through a stochastically-cracked Zr oxide layer within a real-time coupled diffusion-reaction framework We simulate such branching trees by generating a series of porosity-controlled media. Furthermore, we develop an analytical criterion based on compressive yielding for bridging the transition state in corrosion regime, where the percolation threshold has been achieved. Consequently, our model predicts the arrival rate of oxygen ions at the oxide interface during the so-called post-transition regime, where the bulk diffusion is no longer the rate-limiting factor

Model-Informed Drug Development: In Silico Assessment of Drug Bioperformance following Oral and Percutaneous Administration

The pharmaceutical industry has faced significant changes in recent years, primarily influenced by regulatory standards, market competition, and the need to accelerate drug development. Model-informed drug development (MIDD) leverages quantitative computational models to facilitate decision-making processes. This approach sheds light on the complex interplay between the influence of a drug’s performance and the resulting clinical outcomes. This comprehensive review aims to explain the mechanisms that control the dissolution and/or release of drugs and their subsequent permeation through biological membranes. Furthermore, the importance of simulating these processes through a variety of in silico models is emphasized. Advanced compartmental absorption models provide an analytical framework to understand the kinetics of transit, dissolution, and absorption associated with orally administered drugs. In contrast, for topical and transdermal drug delivery systems, the prediction of drug permeation is predominantly based on quantitative structure–permeation relationships and molecular dynamics simulations. This review describes a variety of modeling strategies, ranging from mechanistic to empirical equations, and highlights the growing importance of state-of-the-art tools such as artificial intelligence, as well as advanced imaging and spectroscopic techniques

Cellular-automata models of natural processes, implementation on supercomputers

Представлены результаты анализа моделирующих способностей и вычислительных свойств методов клеточно-автоматного (КА) моделирования нелинейных пространственно распределенных процессов. Работа преследует две цели: 1) показать соответствие свойств КА-моделей современным тенденциям развития параллельных многопроцессорных архитектур (дискретность представления данных, локальность взаимодействий) и 2) раскрыть возможности КА-методов для компьютерного моделирования естественных существенно нелинейных, диссипативных процессов, не поддающихся традиционным методам математического моделирования. Обобщается опыт КА-моделирования, полученный в ИВМиМГ СО РАН. Работа содержит формальное представление КА-моделей, методы их построения, а также результаты реализации ряда тестовых и реальных задач на суперкомпьютерах

Tortuosity of porous media: Image analysis and physical simulation

Tortuosity is widely used as a critical parameter to predict transport properties of porous media, such as rocks and soils. But unlike other standard microstructural properties, the concept of tortuosity is vague with multiple definitions and various evaluation methods introduced in different contexts. Hydraulic, electrical, diffusional, and thermal tortuosities are defined to describe different transport processes in porous media, while geometrical tortuosity is introduced to characterize the morphological property of porous microstructures. In particular, the rapid development of microscopy imaging techniques has made digital microstructures of porous media increasingly accessible, from which geometrical and physical tortuosities can be evaluated using various image analysis and numerical simulation methods. These tortuosities are defined differently and can differ greatly in value, but in many works of literature, they are used interchangeably. To address this situation, we systematically examine geometrical, hydraulic, electrical, diffusional, and thermal tortuosities from the viewpoints of the definition and evaluation method. For the same porous medium, visible discrepancies are found in the evaluated geometrical and physical tortuosities, depending on the specific definition and the evaluation method adopted. This observation makes it questionable to directly use the geometrical tortuosity as a substitute for physical tortuosities, a common practice in the literature. Thus, the correlations between geometrical and physical tortuosities are further analyzed, which also takes into account the influence of both image size and resolution. From the correlation analysis, phenomenological relations between geometrical and physical tortuosities are established, so that the latter can be accurately predicted by using the former which is much cheaper to evaluate from digital microstructures

Mathematical and computational models for bone tissue engineering in bioreactor systems

Research into cellular engineered bone grafts offers a promising solution to problems associated with the currently used auto- and allografts. Bioreactor systems can facilitate the development of functional cellular bone grafts by augmenting mass transport through media convection and shear flow-induced mechanical stimulation. Developing successful and reproducible protocols for growing bone tissue in vitro is dependent on tuning the bioreactor operating conditions to the specific cell type and graft design. This process, largely reliant on a trial-and-error approach, is challenging, time-consuming and expensive. Modelling can streamline the process by providing further insight into the effect of the bioreactor environment on the cell culture, and by identifying a beneficial range of operational settings to stimulate tissue production. Models can explore the impact of changing flow speeds, scaffold properties, and nutrient and growth factor concentrations. Aiming to act as an introductory reference for bone tissue engineers looking to direct their experimental work, this article presents a comprehensive framework of mathematical models on various aspects of bioreactor bone cultures and overviews modelling case studies from literature