Transport in Porous Media最新文献

The study presented in this paper is devoted to the laminar forced convection heat transfer in a porous microduct with a circular cross section. At small cross-section scales, the effects of roughness at the duct walls may be important for the evaluation of the heat transfer rate. The analysis aims to provide the Nusselt number as a quantity dependent on the boundary shape uncertainty by averaging over statistical samples of microducts having different roughness distributions generated randomly. Each statistical sample refers to a prescribed ratio between the maximum size of the wall roughness and the microduct nominal radius, and to a prescribed number of nodes employed to draw the boundary shape. Boundary conditions of either uniform wall temperature (T condition) or wall heating (H1 or H2 conditions) are considered. The results show that both the roughness and the number of nodes defining the microduct cross-sectional shape tend to inhibit the heat transfer: a sufficiently high value of the roughness amplitude may halve the Nusselt number relative to the smooth case. The Nusselt number obtained for the H2 condition decreases faster with the roughness amplitude compared with the Nusselt number obtained for the T and H1 conditions.

This study extends the classical Darcy–Bénard convection problem for isoflux thermal conditions in a horizontal porous layer with basic cellular flow and Hadley circulation to incorporate the Forchheimer effect taking care of inertial effects at medium/high flow rates. The traditional Darcy–Bénard problem can be considered a limiting case of this extension, omitting the circulation in an infinitely wide single cell. Three key parameters govern the basic circulation and temperature fields in this isoflux Darcy–Forchheimer–Bénard problem: the Forchheimer resistance number, the Rayleigh number, and the horizontal temperature gradient parameter. Although solutions are unique in the classical Darcy flow, dual Hadley solutions are detected in the Forchheimer extended Darcy flow valid for certain limited Forchheimer resistance number. Despite the fact that these solutions are asymmetric themselves, unlike the symmetric structure in the classical Hadley cell, dual solutions are formed as the symmetric part of each other with respect to a movable point. While the temperature gradient parameter enhances and readjusts the temperature distribution through the porous layer, the Forchheimer resistive force is shown to conversely reduce the magnitude of the cellular circulation and lower the overall temperature of the porous media in one instance, it increases in the other, exhibiting contrasting thermal behavior.

This study presents advanced numerical simulation of thermotaxis behavior in thermotactic microorganisms suspended within a fluid-saturated porous medium. Based on our previously established linear stability analysis framework, we extend the investigation to supercritical regimes, where thermotactic bioconvection patterns emerge due to the dynamic coupling between microorganism motility, thermal diffusion, and induced fluid flow. The mathematical formulation employs volume-averaged governing equations incorporating Darcy’s law and the Boussinesq approximation, with a focus on key dimensionless parameters including the Peclet number (Pe), Lewis number (Le), thermal Rayleigh number (Ra_T), and bioconvection Rayleigh number (Ra_N).The simulation explores various heating configurations—namely heated-from-below and heated-from-above—demonstrating how Pe modulates the onset of pattern formation, while Le exerts a stabilizing influence. This research provides the first numerical evidence of thermotactic bioconvection beyond critical thresholds in porous media. The findings elucidate fundamental mechanisms governing microorganism gradient-based motion and have potential applications in biosystems modeling, including thermally guided sperm migration, and explanations for Harmful Algal Bloom formation on water surfaces. The interplay between parameters offers a comprehensive insight into the regulation of bioconvection regimes, contributing to broader understanding in biological transport phenomena, microfluidics, and environmental modeling.

Enhanced geothermal system (EGS), typically designed as a doublet of injection and production wells, is a promising approach to exploit hot dry rock (HDR) resources. However, modeling fluid flow and heat transfer in fractured reservoirs remains challenging due to multi-scale fracture heterogeneities and coupled interactions. This study develops a three-dimensional discrete fracture network (DFN)-based thermal-hydraulic coupling model solved by the finite element method (FEM) to efficiently evaluate the heat extraction performance of fractured HDR reservoirs. The developed modeling scheme is validated against analytical and numerical benchmarks, and then applied to a large-scale fractured geothermal reservoir. Results show that the heterogeneity of the fracture network leads to a highly uneven temperature distribution, with the cold front advancing along the primary percolating fracture network pathways. Higher injection temperature and larger fracture aperture accelerate the geothermal reservoir cooling, while the increased well spacing extends EGS lifetime and reduce the electricity cost. This research provides deeper insights into the development of 3D EGS and supports the optimization of operational parameters and economic feasibility.

The usability of enzymatically induced calcium carbonate precipitation (EICP) as a method for altering porous media properties, soil stabilization, or biocementation depends on our ability to predict the spatial distribution of the precipitated calcium carbonate in porous media. While current REV-scale models can reproduce the main features of laboratory experiments, they neglect effects like the formation of preferential flow paths and the appearance of multiple polymorphs of calcium carbonate with differing properties. We show that extending an existing EICP model by the conceptual assumption of a mobile precipitate, amorphous calcium carbonate (ACC), allows for the formation of preferential flow paths when the initial porosity is heterogeneous. We apply sensitivity analysis to understand the influence of characteristic parameters of ACC that are uncertain or unknown, and compare two model variations based on different formulations of the ACC detachment term to analyze the plausibility of our hypothesis. An arbitrary polynomial chaos (aPC) surrogate model is trained based on the full model and used to reduce the computational cost of this study.

We present a probabilistic diffusion-based framework for reconstructing scientific microstructure images with missing or corrupted regions. Motivated by challenges in characterizing porous media, our method employs denoising diffusion probabilistic models to learn a conditional distribution over image completions given partial observations. Trained on grayscale images of porous structures, the model generalizes well across samples with varying morphology and entropy. We evaluate its performance on two distinct datasets using a range of masking strategies, including irregular occlusions, large missing regions, and structured patterns such as stripes and cutouts. The proposed model reconstructs high-fidelity completions that are both visually plausible and physically consistent. Quantitative evaluations based on pore size distribution, two-point correlation functions, and pixel-level error metrics show that the generated outputs preserve critical features and statistical descriptors of the original media. Additional analyses of pixel intensity profiles and latent activation patterns reveal that the model can infer fine-scale details while maintaining global structure. These results explain the potential of latent diffusion-based inpainting as a robust tool for digital reconstruction and scientific imaging in complex material systems.

In seasonally frozen regions, ice-water phase transitions during spring snowmelt critically reshape the thermo-hydraulic properties of porous media. However, the underlying pore-scale mechanisms remain poorly quantified, particularly the dynamic variations in thermo-hydraulic transport parameters during melting processes. In this study, a pore-scale numerical model for ice-water phase transitions was developed using the Lattice Boltzmann Method (LBM) with a double-distribution function approach, and its accuracy was rigorously validated. The model enables in-depth investigation of the complex microscopic mechanisms governing coupled heat and fluid flow in porous media under phase change conditions. The results demonstrate that the heterogeneity of porous media structures and thermal boundary conditions jointly govern ice melting dynamics, leading to spatially heterogeneous temperature and phase distributions. Quantitative and qualitative analysis shows that the decrease of porosity significantly speeds up the ice melting rate under the same conditions.

Donald Arthur Nield died peacefully at Golden View Care, Cromwell, New Zealand, surrounded by family, on May 25, 2024, aged 89. He was the dearly loved husband of Rachel, cherished father and father-in-law of Cherry and Robert, Alex and Michael, Peter and Janice, and treasured Grandpa of Elizabeth, John, Charlotte, Frank, Rachel, and Michael. This is a scientific memoir written by D. A. Nield himself. In late March 2017 Don sent a copy of the document, below unedited, to Craig Simmons. This was in response to a discussion that Simmons had with Nield at that time when Simmons was preparing a historical note on the Elder Problem with John W. Elder. We can do no better than to publish Nield’s autobiographical note posthumously as is—in his own words. Nield himself called it “A scientific memoir.”

Graphical abstract

This study investigates the use of X-ray microtomography (XMT) to reveal the structure of complex porous biological tissues and the fluid flow through them during wetting. It also evaluates fluid dynamical simulations based on XMT data to reproduce and analyse these flows, with a final aim of revealing fluid transport and void formation in such tissues. To fulfil the objectives, the wetting flow of a polymer liquid through an initially dry conditioned Norway spruce wood sample is visualised using XMT at the MAX IV synchrotron. The liquid flow front progression captured after 24 s and 48 s reveals uneven filling of longitudinal tracheids and flow between them via the tiny pits which connect tracheids. Most tracheids fill between 24 and 48 s, possibly due to removal of air inclusions. Large density gradients near cell walls suggest that the fluid followed and deposited along wall structures. Computational fluid dynamics simulations (CFD) of saturated flow through the tomography-based geometry indicate velocity profiles that resemble pipe flow in longitudinal tracheids and flow rate differences among them. The latter indicates that the geometry itself may cause the experimentally observed uneven flow. Streamlines show intra-tracheid flow development and clear flow direction change at the pits. Additionally, wetting simulations, using a constant contact angle, capture initial uneven filling between the tracheids on shorter time scales than could be capture by the experiments. These simulations furthermore show air entrapment during filling, consistent with experimental observations. Combining XMT with CFD enables detailed studies of flow in biological porous media. Faster X-ray scanning, incorporating dynamic contact angles and accounting for diffusion in simulations could further refine insights into fluid progression during capillary-driven flow into complex structures of porous biological tissues.