Evaluation of Effectiveness Factors for Multicomponent Diffusion Models Inside 3D Catalyst Shapes

被引:14
|
作者
Donaubauer, Philipp J. [1 ,2 ]
Hinrichsen, Olaf [1 ,2 ]
机构
[1] Tech Univ Munich, Dept Chem, D-85748 Garching, Germany
[2] Tech Univ Munich, Catalysis Res Ctr, D-85748 Garching, Germany
关键词
FIXED-BED; REACTION-RATES; FLOW; PARTICLES; TRANSPORT; PELLETS; METHANATION; PREDICTION; BEHAVIOR; CFD;
D O I
10.1021/acs.iecr.8b04922
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
On an industrial scale, the efficiency of heterogeneous catalysis is commonly subject to diffusive transport limitations. The binary friction model (BFM) combines Maxwell-Stefan-type diffusion, pore effects and viscous contributions for multicomponent reaction mixtures. A variety of catalyst shapes have been developed over the years to overcome transport problems. However, rigorous modeling of multicomponent diffusion-reaction problems in 3D geometries remains an ongoing challenge. We successfully applied the BFM to nine shapes, all varying in size and catalyst loading. The volume-to-surface ratio and the curvature of the bodies were found to be the characteristic features of the pellets, describing the reaction-diffusion interplay. With this, the 3D shape can be adequately approximated with straightforward 1D strategies. Finally, a comparison to Fickian diffusion models highlights the similarities and discrepancies to the Maxwell-Stefan concept of the BFM. These findings can contribute to an integral description of 3D reaction-diffusion problems in homogeneously distributed, mesoporous catalysts.
引用
收藏
页码:110 / 119
页数:10
相关论文
共 50 条
  • [1] Effectiveness of inside/outside determination in relation to 3D non-convex shapes using CUDA
    Kodama, Satoshi
    IMAGING SCIENCE JOURNAL, 2018, 66 (07): : 409 - 418
  • [2] Reconstructing Recognizable 3D Face Shapes based on 3D Morphable Models
    Jiang, Diqiong
    Jin, Yiwei
    Zhang, Fang-Lue
    Lai, Yu-Kun
    Deng, Risheng
    Tong, Ruofeng
    Tang, Min
    COMPUTER GRAPHICS FORUM, 2022, 41 (06) : 348 - 364
  • [3] Diffusion models for 3D generation: A survey
    Wang, Chen
    Peng, Hao-Yang
    Liu, Ying-Tian
    Gu, Jiatao
    Hu, Shi-Min
    COMPUTATIONAL VISUAL MEDIA, 2025, 11 (01): : 1 - 28
  • [4] NPMs: Neural Parametric Models for 3D Deformable Shapes
    Palafox, Pablo
    Bozic, Aljaz
    Thies, Justus
    Niessner, Matthias
    Dai, Angela
    2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2021), 2021, : 12675 - 12685
  • [5] POLYGONAL SHAPES DETECTION IN 3D MODELS OF COMPLEX ARCHITECTURES
    Benciolini, G. B.
    Vitti, A.
    3D-ARCH 2015 - 3D VIRTUAL RECONSTRUCTION AND VISUALIZATION OF COMPLEX ARCHITECTURES, 2015, 40-5 (W4): : 387 - 392
  • [6] An interactive analysis of harmonic and diffusion equations on discrete 3D shapes
    Patane, Giuseppe
    Spagnuolo, Michela
    COMPUTERS & GRAPHICS-UK, 2013, 37 (05): : 526 - 538
  • [7] IMPORTANCE OF ALIGNING TRAINING STRATEGY WITH EVALUATION FOR DIFFUSION MODELS IN 3D MULTICLASS SEGMENTATION
    Fu, Yunguan
    Li, Yiwen
    Saeed, Shaheer U.
    Clarkson, Matthew J.
    Hu, Yipeng
    arXiv, 2023,
  • [8] Importance of Aligning Training Strategy with Evaluation for Diffusion Models in 3D Multiclass Segmentation
    Fu, Yunguan
    Li, Yiwen
    Saeed, Shaheer U.
    Clarkson, Matthew J.
    Hu, Yipeng
    DEEP GENERATIVE MODELS, DGM4MICCAI 2023, 2024, 14533 : 86 - 95
  • [9] The Interestingness of 3D Shapes
    Lau, Manfred
    Power, Luther
    ACM SYMPOSIUM ON APPLIED PERCEPTION (SAP 2020), 2020,
  • [10] 3D Electromagnetic Diffusion Models for Reverberant Environments
    Flintoft, I. D.
    Dawson, J. F.
    2017 INTERNATIONAL CONFERENCE ON ELECTROMAGNETICS IN ADVANCED APPLICATIONS (ICEAA), 2017, : 511 - 514