Stochastic 3D modeling of non-woven materials with wet-proofing agent

Gaiselmann, Gerd; Froning, Dieter; Tötzke, Christian; Quick, Christian; Manke, Ingo; Lehnert, Werner; Schmidt, Volker

doi:10.1016/j.ijhydene.2013.04.144

Cited by 40 publications

(39 citation statements)

References 23 publications

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“…The second method, image-based reconstruction, employs experimental diagnostic imaging, such as SEM, TEM, or X-ray computed tomography (XCT), combined with a numerical processing step that converts the images to a virtual structure thus translating the original experimental images into a morphology that can be used for numerical analysis. [187][188][189][190] For the latter approach, this can be accomplished, for example, by extracting images from the center lines of single fiber from the resultant images of GDLs. These center lines are then used in conjunction with a stochastic algorithm to reconnect parts of the center lines in an attempt to preserve the curvature of the fibers.…”

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confidence: 99%

“…These center lines are then used in conjunction with a stochastic algorithm to reconnect parts of the center lines in an attempt to preserve the curvature of the fibers. 190 The limitation of the rendered pore space and features within the domain remain the limit of the spatial resolution of the imaging technique itself as well as the ability to determine the distinct phases (e.g., Teflon and carbon and sometimes water are not easy to distinguish with X-rays). 191 For stochastic reconstruction, the virtual generation of the microstructures relies on the use of a random number generator, statistical distribution of geometric information relating to the constituent materials that comprise the media, and a series of rule-sets.…”

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confidence: 99%

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A Critical Review of Modeling Transport Phenomena in Polymer-Electrolyte Fuel Cells

Weber

Borup

Darling³

et al. 2014

J. Electrochem. Soc.

509

394

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Polymer-electrolyte fuel cells are a promising energy-conversion technology. Over the last several decades significant progress has been made in increasing their performance and durability, of which continuum-level modeling of the transport processes has played an integral part. In this review, we examine the state-of-the-art modeling approaches, with a goal of elucidating the knowledge gaps and needs going forward in the field. In particular, the focus is on multiphase flow, especially in terms of understanding interactions at interfaces, and catalyst layers with a focus on the impacts of ionomer thin-films and multiscale phenomena. Overall, we highlight where there is consensus in terms of modeling approaches as well as opportunities for further improvement and clarification, including identification of several critical areas for future research. Fuel cells may become the energy-delivery devices of the 21 st century. Although there are many types of fuel cells, polymer-electrolyte fuel cells (PEFCs) are receiving the most attention for automotive and small stationary applications. In a PEFC, fuel and oxygen are combined electrochemically. If hydrogen is used as the fuel, it oxidizes at the anode releasing proton and electrons according toThe generated protons are transported across the membrane and the electrons across the external circuit. At the cathode catalyst layer, protons and electrons recombine with oxygen to generate waterAlthough the above electrode reactions are written in single step, multiple elementary reaction pathways are possible at each electrode. During the operation of a PEFC, many interrelated and complex phenomena occur. These processes include mass and heat transfer, electrochemical reactions, and ionic and electronic transport. * Electrochemical Society Active Member. z E-mail: azweber@lbl.govOver the last several decades significant progress has been made in increasing PEFC performance and durability. Such progress has been enabled by experiments and computation at multiple scales, with the bulk of the focus being on optimizing and discovering new materials for the membrane-electrode-assembly (MEA), composed of the proton-exchange membrane (PEM), catalyst layers, and diffusionmedia (DM) backing layers. In particular, continuum modeling has been invaluable in providing understanding and insight into processes and phenomena that cannot be resolved or uncoupled through experiments. While modeling of the transport and related phenomena has progressed greatly, there are still some critical areas that need attention. These areas include modeling the catalyst layer and multiphase phenomena in the PEFC porous media.While there have been various reviews over the years of PEFC modeling 1-7 and issues, [8][9][10][11][12][13][14] as well as numerous books and book chapters, there is a need to examine critically the field in terms of what has been done and what needs to be done. This review serves that purpose with a focus on transport modeling of PEFCs. This is not meant to be an exhaustive review...

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confidence: 99%

A Critical Review of Modeling Transport Phenomena in Polymer-Electrolyte Fuel Cells

Weber

Borup

Darling³

et al. 2014

J. Electrochem. Soc.

509

394

View full text Add to dashboard Cite

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“…The stem of a coral can be described as a polygonal track Recently, this novel approach to describe polygonal tracks by multivariate times series has successfully been applied to model the courses of carbon fibers used in so-called gas-diffusion layers of proton exchange membrane fuel cells, see [14,15].…”

Section: Single-stem Modelmentioning

confidence: 99%

“…[8,9]. For more information about random polygonal track models based on multivariate time series, the reader is referred to [14,15]. Parameter Estimation.…”

Section: Single-stem Modelmentioning

confidence: 99%

Competitive stochastic growth model for the 3D morphology of eutectic Si in Al–Si alloys

Gaiselmann

Stenzel

Kruglova

et al. 2013

Computational Materials Science

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A competitive stochastic growth model is developed for the simulation of the 3D morphology of eutectic silicon in Al-Si alloys, which represents the colonies of pairwise disconnected Si corals in an Al matrix. The model is based on ideas from stochastic geometry and multivariate time series analysis. The 3D model is validated by comparing morphological characteristics computed for experimental 3D FIB-SEM data, and for realizations drawn from the model. Good agreement between the simulation model and the experimental image data is shown confirming the efficiency of using the competitive stochastic growth model for the generation of virtual eutectic silicon morphologies.

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“…On the other hand, both the Monte Carlo simulations of the model as well as the computation of the empirical characteristics are often very time-consuming. In particular, this applies for stochastic geometric models of complex random structures such as fiber systems (Altendorf and Jeulin, 2011;Gaiselmann et al, 2013) or foam structures (Lautensack, 2008;Redenbach, 2009).…”

Section: Introductionmentioning

confidence: 99%

A Quasi-Likelihood Approach to Parameter Estimation for Simulatable Statistical Models

2014

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This paper introduces a parameter estimation method for a general class of statistical models. The method exclusively relies on the possibility to conduct simulations for the construction of interpolation-based metamodels of informative empirical characteristics and some subjectively chosen correlation structure of the underlying spatial random process. In the absence of likelihood functions for such statistical models, which is often the case in stochastic geometric modelling, the idea is to follow a quasi-likelihood (QL) approach to construct an optimal estimating function surrogate based on a set of interpolated summary statistics. Solving these estimating equations one can account for both the random errors due to simulations and the uncertainty about the meta-models. Thus, putting the QL approach to parameter estimation into a stochastic simulation setting the proposed method essentially consists of finding roots to a sequence of approximating quasiscore functions. As a simple demonstrating example, the proposed method is applied to a special parameter estimation problem of a planar Boolean model with discs. Here, the quasi-score function has a half-analytical, numerically tractable representation and allows for the comparison of the model parameter estimates found by the simulation-based method and obtained from solving the exact quasi-score equations.

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Stochastic 3D modeling of non-woven materials with wet-proofing agent

Cited by 40 publications

References 23 publications

A Critical Review of Modeling Transport Phenomena in Polymer-Electrolyte Fuel Cells

A Critical Review of Modeling Transport Phenomena in Polymer-Electrolyte Fuel Cells

Competitive stochastic growth model for the 3D morphology of eutectic Si in Al–Si alloys

A Quasi-Likelihood Approach to Parameter Estimation for Simulatable Statistical Models

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