Biomimetic flow fields for proton exchange membrane fuel cells: A review of design trends

Bipolar Plate design is one of the most active research fields in Polymer Electrolyte Membrane Fuel Cells (PEMFCs) development. Bipolar Plates are key components for ensuring an appropriate water management within the cell, preventing flooding and enhancing the cell operation at high current densities. This work presents a literature review covering bipolar plate designs based on nature or biological structures such as fractals, leaves or lungs. Biological inspiration comes from the fact that fluid distribution systems found in plants and animals such as leaves, blood vessels, or lungs perform their functions (mostly the same functions that are required for bipolar plates) with a remarkable efficiency, after millions of years of natural evolution. Such biomimetic designs have been explored to date with success, but it is generally acknowledged that biomimetic designs have not yet achieved their full potential. Many biomimetic designs have been derived using computer simulation tools, in particular Computational Fluid Dynamics (CFD) so that the use of CFD is included in the review. A detailed review including performance benchmarking, time line evolution, challenges and proposals, as well as manufacturing issues is discussed.Ministerio de Ciencia, Innovación y Universidades ENE2017-91159-EXPMinisterio de Economía y Competitividad UNSE15-CE296

In situ visualization of large-scale turbulence simulations in Nek5000 with ParaView Catalyst

In situ visualization on high-performance computing systems allows us to analyze simulation results that would otherwise be impossible, given the size of the simulation data sets and offline post-processing execution time. We develop an in situ adaptor for Paraview Catalyst and Nek5000, a massively parallel Fortran and C code for computational fluid dynamics. We perform a strong scalability test up to 2048 cores on KTH’s Beskow Cray XC40 supercomputer and assess in situ visualization’s impact on the Nek5000 performance. In our study case, a high-fidelity simulation of turbulent flow, we observe that in situ operations significantly limit the strong scalability of the code, reducing the relative parallel efficiency to only ≈ 21 % on 2048 cores (the relative efficiency of Nek5000 without in situ operations is ≈ 99 %). Through profiling with Arm MAP, we identified a bottleneck in the image composition step (that uses the Radix-kr algorithm) where a majority of the time is spent on MPI communication. We also identified an imbalance of in situ processing time between rank 0 and all other ranks. In our case, better scaling and load-balancing in the parallel image composition would considerably improve the performance of Nek5000 with in situ capabilities. In general, the result of this study highlights the technical challenges posed by the integration of high-performance simulation codes and data-analysis libraries and their practical use in complex cases, even when efficient algorithms already exist for a certain application scenario

Challenges in imaging and predictive modeling of rhizosphere processes

Background Plant-soil interaction is central to human food production and ecosystem function. Thus, it is essential to not only understand, but also to develop predictive mathematical models which can be used to assess how climate and soil management practices will affect these interactions. Scope In this paper we review the current developments in structural and chemical imaging of rhizosphere processes within the context of multiscale mathematical image based modeling. We outline areas that need more research and areas which would benefit from more detailed understanding. Conclusions We conclude that the combination of structural and chemical imaging with modeling is an incredibly powerful tool which is fundamental for understanding how plant roots interact with soil. We emphasize the need for more researchers to be attracted to this area that is so fertile for future discoveries. Finally, model building must go hand in hand with experiments. In particular, there is a real need to integrate rhizosphere structural and chemical imaging with modeling for better understanding of the rhizosphere processes leading to models which explicitly account for pore scale processes

Two-phase flow and oxygen transport in the perforated gas diffusion layer of proton exchange membrane fuel cell

Liquid water transport in perforated gas diffusion layers (GDLs)is numerically investigated using a three-dimensional (3D)two-phase volume of fluid (VOF)model and a stochastic reconstruction model of GDL microstructures. Different perforation depths and diameters are investigated, in comparison with the GDL without perforation. It is found that perforation can considerably reduce the liquid water level inside a GDL. The perforation diameter (D = 100 μm)and the depth (H = 100 μm)show pronounced effect. In addition, two different perforation locations, i.e. the GDL center and the liquid water break-through point, are investigated. Results show that the latter perforation location works more efficiently. Moreover, the perforation perimeter wettability is studied, and it is found that a hydrophilic region around the perforation further reduces the water saturation. Finally, the oxygen transport in the partially-saturated GDL is studied using an oxygen diffusion model. Results indicate that perforation reduces the oxygen diffusion resistance in GDLs and improves the oxygen concentration at the GDL bottom up to 101% (D = 100 μm and H = 100 μm)

Review of the Synergies Between Computational Modeling and Experimental Characterization of Materials Across Length Scales

With the increasing interplay between experimental and computational approaches at multiple length scales, new research directions are emerging in materials science and computational mechanics. Such cooperative interactions find many applications in the development, characterization and design of complex material systems. This manuscript provides a broad and comprehensive overview of recent trends where predictive modeling capabilities are developed in conjunction with experiments and advanced characterization to gain a greater insight into structure-properties relationships and study various physical phenomena and mechanisms. The focus of this review is on the intersections of multiscale materials experiments and modeling relevant to the materials mechanics community. After a general discussion on the perspective from various communities, the article focuses on the latest experimental and theoretical opportunities. Emphasis is given to the role of experiments in multiscale models, including insights into how computations can be used as discovery tools for materials engineering, rather than to "simply" support experimental work. This is illustrated by examples from several application areas on structural materials. This manuscript ends with a discussion on some problems and open scientific questions that are being explored in order to advance this relatively new field of research.Comment: 25 pages, 11 figures, review article accepted for publication in J. Mater. Sc

Indoor mould growth prediction using coupled computational fluid dynamics and mould growth model

This study investigates, using in-situ and numerical simulation experiments, airflow and hygrothermal distribution in a mechanically ventilated academic research facility with known cases of microbial proliferations. Microclimate parameters were obtained from in-situ experiments and used as boundary conditions and validation of the numerical experiments with a commercial computational fluid dynamics (CFD) analysis tool using the standard k–ε model. Good agreements were obtained with less than 10% deviations between the measured and simulated results. Subsequent upon successful validation, the model was used to investigate hygrothermal and airflow profile within the shelves holding stored components in the facility. The predicted in-shelf hygrothermal profile was superimposed on mould growth limiting curve earlier documented in the literature. Results revealed the growth of xerophilic species in most parts of the shelves. The mould growth prediction was found in correlation with the microbial investigation in the case-studied room reported by the authors elsewhere. Satisfactory prediction of mould growth in the room successfully proved that the CFD simulation can be used to investigate the conditions that lead to microbial growth in the indoor environment