Pore Network Simulation of Gas-Liquid Distribution in Porous Transport Layers

Pore network models are powerful tools to simulate invasion and transport processes in porous media. They are widely applied in the field of geology and the drying of porous media, and have recently also received attention in fuel cell applications. Here we want to describe and discuss how pore network models can be used as a prescriptive tool for future water electrolysis technologies. In detail, we suggest in a first approach a pore network model of drainage for the prediction of the oxygen and water invasion process inside the anodic porous transport layer at high current densities. We neglect wetting liquid films and show that, in this situation, numerous isolated liquid clusters develop when oxygen invades the pore network. In the simulation with narrow pore size distribution, the volumetric ratio of the liquid transporting clusters connected between the catalyst layer and the water supply channel is only around 3% of the total liquid volume contained inside the pore network at the moment when the water supply route through the pore network is interrupted; whereas around 40% of the volume is occupied by the continuous gas phase. The majority of liquid clusters are disconnected from the water supply routes through the pore network if liquid films along the walls of the porous transport layer are disregarded. Moreover, these clusters hinder the countercurrent oxygen transport. A higher ratio of liquid transporting clusters was obtained for greater pore size distribution. Based on the results of pore network drainage simulations, we sketch a new route for the extraction of transport parameters from Monte Carlo simulations, incorporating pore scale flow computations and Darcy flow

Pore network model of primary freeze drying

[EN] he pore scale progression of the sublimation front during primary freeze drying depends on the local vapor transport and the local heat transfer as well. If the pore space is size distributed, vapor and heat transfer may spatially vary. Beyond that, the pore size distribution can substantially affect the physics of the transport mechanisms if they occur in a transitional regime. Exemplarily, if the critical mean free path is locally exceeded, the vapor transport regime passes from viscous flow to Knudsen diffusion. At the same time, the heat transfer is affected by the local ratio of pore space to the solid skeleton. The impact of the pore size distribution on the transitional vapor and heat transfer can be studied by pore scale models such as the pore network model. As a first approach, we present a pore network model with vapor transport in the transitional regime between Knudsen diffusion and viscous flow at constant temperature in the dry region. We demonstrate the impact of pore size distribution, temperature and pressure on the vapor transport regimes. Then we study on the example of a 2D square lattice, how the presence of micro and macro pores affects the macroscopic progression of the sublimation front.Vorhauer, N.; Först, P.; Schuchmann, H.; Tsotsas, E. (2018). Pore network model of primary freeze drying. En IDS 2018. 21st International Drying Symposium Proceedings. Editorial Universitat Politècnica de València. 221-228. https://doi.org/10.4995/IDS2018.2018.7284OCS22122

Experimental investigation on pore size distribution and drying kinetics during lyophilization of sugar solutions

[EN] The pore structure is a decisive factor for the process efficiency and product quality of freeze dried products. In this work the two-dimensional ice crystal structure was investigated for maltodextrin solutions with different concentrations by a freeze drying microscope. The resulting drying kinetics was investigated for different pore structures. Additionally the three-dimensional pore structure of the freeze dried samples was measured by µ-computed tomography and the pore size distribution was quantified by image analysis techniques. The two- and three-dimensional pore size distributions were compared and linked to the drying kinetics.Foerst, P.; Lechner, M.; Vorhauer, N.; Schuchmann, H.; Tsotsas, E. (2018). Experimental investigation on pore size distribution and drying kinetics during lyophilization of sugar solutions. En IDS 2018. 21st International Drying Symposium Proceedings. Editorial Universitat Politècnica de València. 1415-1422. https://doi.org/10.4995/IDS2018.2018.7310OCS1415142

Deep learning-assisted radiomics facilitates multimodal prognostication for personalized treatment strategies in low-grade glioma

Determining the optimal course of treatment for low grade glioma (LGG) patients is challenging and frequently reliant on subjective judgment and limited scientific evidence. Our objective was to develop a comprehensive deep learning assisted radiomics model for assessing not only overall survival in LGG, but also the likelihood of future malignancy and glioma growth velocity. Thus, we retrospectively included 349 LGG patients to develop a prediction model using clinical, anatomical, and preoperative MRI data. Before performing radiomics analysis, a U2-model for glioma segmentation was utilized to prevent bias, yielding a mean whole tumor Dice score of 0.837. Overall survival and time to malignancy were estimated using Cox proportional hazard models. In a postoperative model, we derived a C-index of 0.82 (CI 0.79-0.86) for the training cohort over 10 years and 0.74 (Cl 0.64-0.84) for the test cohort. Preoperative models showed a C-index of 0.77 (Cl 0.73-0.82) for training and 0.67 (Cl 0.57-0.80) test sets. Our findings suggest that we can reliably predict the survival of a heterogeneous population of glioma patients in both preoperative and postoperative scenarios. Further, we demonstrate the utility of radiomics in predicting biological tumor activity, such as the time to malignancy and the LGG growth rate

Steady-State Water Drainage by Oxygen in Anodic Porous Transport Layer of Electrolyzers: A 2D Pore Network Study

Recently, pore network modelling has been attracting attention in the investigation of electrolysis. This study focuses on a 2D pore network model with the purpose to study the drainage of water by oxygen in anodic porous transport layers (PTL). The oxygen gas produced at the anode catalyst layer by the oxidation of water flows counter currently to the educt through the PTL. When it invades the water-filled pores of the PTL, the liquid is drained from the porous medium. For the pore network model presented here, we assume that this process occurs in distinct steps and applies classical rules of invasion percolation with quasi-static drainage. As the invasion occurs in the capillary-dominated regime, it is dictated by the pore structure and the pore size distribution. Viscous and liquid film flows are neglected and gravity forces are disregarded. The curvature of the two-phase interface within the pores, which essentially dictates the invasion process, is computed from the Young Laplace equation. We show and discuss results from Monte Carlo pore network simulations and compare them qualitatively to microfluidic experiments from literature. The invasion patterns of different types of PTLs, i.e., felt, foam, sintered, are compared with pore network simulations. In addition to this, we study the impact of pore size distribution on the phase patterns of oxygen and water inside the pore network. Based on these results, it can be recommended that pore network modeling is a valuable tool to study the correlation between kinetic losses of water electrolysis processes and current density