This study investigates and deconstructs a foundational premise in the literature: that the performance parameters of clean fibrous air filters for inertia-dominated particles—namely, particle capture efficiency, pressure drop, and quality factor—are primarily governed by two key non-dimensional numbers, the Stokes number (St) and the fibre-based Reynolds number (Ref). For this purpose, different combinations of particle diameter and face velocity were considered at varying air densities, such that St and Ref remained constant; however, another non-dimensional number, the particle-based Reynolds number (Rep), exhibited a uniform variation. A three-dimensional numerical model was developed to simulate particle-laden airflow across an initially clean fibre-segment and subsequent particle capture, using a coupled lattice Boltzmann method (LBM) and discrete element method (DEM). It was found that, while keeping St and Ref constant, increasing particle diameter threefold and decreasing face velocity ninefold causes particle deposition morphology to shift toward multilayered patterns, particle capture efficiency to show a mixed trend, and pressure drop to decrease by up to a factor of 4.3. Consequently, the overall filtration performance, as represented by the quality factor, increases by a factor of up to 5.08. Furthermore, the results show that for a given St and Ref, large particles injected at a low face velocity yield better overall filtration performance compared to small particles injected at a high face velocity. For the quality factor, the particle-based Reynolds number at the inlet emerges as the key governing parameter, increasing monotonically by a factor of three with the above parametric variations.

This study investigates the application of wetting boundary conditions for modelling flows in complex curved geometries, such as rough fractures. It implements and analyses two common variants of the wetting boundary condition within the three-dimensional (3D) phase field lattice Boltzmann method. It provides a straightforward and novel extension of the geometrical approach to curved three-dimensional surfaces. It additionally implements surface-energy approach. A novel interpolation-based mitigation of the staircase approximation for curved boundaries is then developed and consistently applied to both wetting boundary conditions. The objectives of simplicity and parallel compute efficiency in implementation are emphasised. Through detailed validation on a series of 3D benchmark cases involving curved surfaces, such as droplet spread on a sphere, capillary intrusion, and droplet impact on a sphere, the behaviour of the wetting boundary conditions are validated and the differences between methods are highlighted. To demonstrate the applicability of the proposed approach in complex geometries with varying surface curvatures, two-phase flow through a synthetic rough fracture is presented. The suitability of the methods for complex simulations is also verified by comparing the computational performance between all investigated methods using this fracture flow test case. The present work thus contributes to the field of multiphase flow modelling with the lattice Boltzmann method in realistic applications where addressing the impact of complex geometries is essential.

Solar energy, particularly solar thermal technology, has gained popularity as a possible long-term replacement to fossil fuels. The application of concentrated photovoltaic-solar thermal (CPV/T) collectors, which are improved by spectral filter fluids (SFF) and nanotechnology, has the potential to provide both higher thermal power for heating and cooling as well as improved electrical power generation. This work contributes new insight by quantifying the influence of nanoparticle agglomeration on collector performance and highlighting the challenges associated with the heterogeneous distribution of nanoparticles in CPV/T systems. The study employed coupled Eulerian multiphase modeling and discrete ordinate (DO) radiation modeling to examine slip velocity, nanoparticle diameter (including agglomeration), and suspension concentration. Population balance modeling (PBM) was utilized to determine the nanoparticle size distribution, and the obtained results were validated through comparison with experimental and numerical studies. When neglecting the effect of agglomeration and breakage of the non-solar participating media, the maximum error for this configuration was found to be 3.58% when compared to experimental work. From the solar participating study, in terms of electrical energy production, the best performance obtained was 16.64% with a volume fraction of 0.005% when considering agglomeration and breakage. It was also found that the Sauter diameter increases with volume fraction as the tendency for nanoparticle agglomeration increases. This study provides a broader view of the application of multiphase modeling in solar participating and non-solar participating media and, additionally, provides insight on the effect of various boundary conditions on the key system performance indicators. To extend this work, the flow Reynolds number can be increased in addition to varying the type of working fluid.

The behaviour of non-Newtonian fluids, and their interaction with other fluid phases and components, is of interest in a diverse range of scientific and engineering problems. In the context of the lattice Boltzmann method (LBM), both non-Newtonian rheology and multiphase flows have received significant attention in the literature. This study builds on that work by presenting the development and validation of a phase-field LBM which combines these features in three-dimensional flows. Specifically, the model presented herein combines the simulation of Herschel-Bulkley fluids, which exhibit both a yield stress and power-law dependence on shear rate, interacting with a Newtonian fluid. The developed model is verified and validated using a diverse set of rheological properties and flow conditions, which in their totality represent an additional contribution of this work. Comparison with steady-state layered Poiseuille flow, where one fluid is Newtonian and the other is non-Newtonian, showed excellent correlation with the corresponding analytic solution. Validation against analytic solutions for the rise of a power-law fluid in a capillary tube also showed good correlation, but highlighted some sensitivity to initial conditions and high velocities occurring early in the simulation. A demonstration of the model in a microfluidic junction highlighted how non-Newtonian rheology can alter behaviour from cases where only Newtonian fluids are present. It also showed that significant changes in behaviour can occur when making small and smooth changes in non-Newtonian parameters. To summarise, this work broadens the range of physical phenomena that can be captured in computational analysis of complex fluid flows using the LBM.

This study numerically investigates counter-current slug flow by considering the motion of a Taylor bubble in annular conduits with downward-flowing liquids using the Volume-of-Fluid method implemented in the commercial computational fluid dynamics software ANSYS Fluent (Release 19.2). The translational velocity of a counter-current ascending or co-current descending Taylor bubble in vertical concentric annuli and the corresponding distribution parameter (C-0) are analyzed. The latter is correlated in terms of Eotvos number (Eo) and inverse viscosity number (Nf) within the range of Eo between 40 and 400 and Nf between 40 and 320. The proposed correlation provides an accurate fit to the numerical data with an average error of 2.64%, and is successfully compared with published numerical findings. In general, the smooth and stable shape of the bubble is disrupted as the counter-current flow velocity (Fr-l) increases above a critical value, leading to the formation of surface waves and the displacement of the bubble tip away from the annular gap center and towards the outer pipe. C-0 increases with Eo and Nf, plateauing at high values of Eo. The effects of annulus inclination (theta) and eccentricity (epsilon) on bubble rise velocity are examined within the common range of theta and epsilon encountered during the drilling of oil, gas, or geothermal wells, i.e. 0 degrees <= theta <= 60 degrees and 0 <= epsilon <= 0.7, and their impact on the C-0. The increasing Fr-l and theta lead to a streamlined bubble with pointed nose and thus a reduction in the wrap angle (theta(wrap)), ultimately leading to reduced drag compared to the vertical annulus case and a decrease in C-0. As the epsilon increases, which is accompanied by an increase in the degree of bubble eccentricity, the corresponding C-0 decreases. For a constant Eo = 100 and Nf = 160 with inclination angle of theta = 40 degrees and eccentricity of epsilon = 0.5, the C-0 < 1 is observed.

Methane pyrolysis using a molten media bubble column reactor is a promising technique for hydrogen production with low carbon dioxide emissions at a feasible price. Understanding the bubble dynamics in molten media is essential to elucidate the reaction mechanisms and establish design requirements for efficient reactors. Computational fluid dynamics provides an effective means to understand the hydrodynamics in opaque molten media. This research used the volume of fluid method to study the effects of gas injection rate as well as variations in gas and molten media (iron, aluminum, and a salt mixture of sodium bromide and potassium bromide in a 48.7:51.3 molar ratio) properties on bubble dynamics. The computational model was first validated using existing experimental and empirical observations. This study makes fundamental contributions to the understanding of bubble dynamics in molten media. First, it was confirmed that gas properties had a small effect on bubble dynamics. The difference in bubble diameters between argon at ambient temperature and 1600 degrees C was less than 10%. Second, it was found that the volumetric gas injection rate and molten media properties significantly impacted the bubble dynamics, including the bubble diameter and flow regime. Future work will build on these findings to recommend appropriate operating conditions and molten media for specific pyrolysis reactor designs. (C) 2024 Author(s).

Recent clinical studies have reported that heart failure with preserved ejection fraction (HFpEF) can be divided into two phenotypes based on the range of ejection fraction (EF), namely HFpEF with higher EF and HFpEF with lower EF. These phenotypes exhibit distinct left ventricle (LV) remodelling patterns and dynamics. However, the influence of LV remodelling on various LV functional indices and the underlying mechanics for these two phenotypes are not well understood. To address these issues, this study employs a coupled finite element analysis (FEA) framework to analyse the impact of various ventricular remodelling patterns, specifically concentric remodelling (CR), concentric hypertrophy (CH), and eccentric hypertrophy (EH), with and without LV wall thickening on LV functional indices. Further, the geometries with a moderate level of remodelling from each pattern are subjected to fibre stiffening and contractile impairment to examine their effect in replicating the different features of HFpEF. The results show that with severe CR, LV could exhibit the characteristics of HFpEF with higher EF, as observed in recent clinical studies. Controlled fibre stiffening can simultaneously increase the end-diastolic pressure (EDP) and reduce the peak longitudinal strain (ell) without significant reduction in EF, facilitating the moderate CR geometries to fit into this phenotype. Similarly, fibre stiffening can assist the CH and ‘EH with wall thickening’ cases to replicate HFpEF with lower EF. These findings suggest that potential treatment for these two phenotypes should target the bio-origins of their distinct ventricular remodelling patterns and the extent of myocardial stiffening.

This study develops a computationally efficient phase-field lattice Boltzmann (LB) model with the capability to simulate thermocapillary flows. The model was implemented into the open-source simulation framework, WALBERLA, and extended to conduct the collision stage using central moments. The multiphase model was coupled with both a passive-scalar thermal LB and a RungeKutta (RK) solution to the energy equation in order to resolve temperature-dependent surface tension phenomena. Various lattice stencils (D3Q7, D3Q15, D3Q19, D3Q27) were tested for the passive-scalar LB, and both the second- and fourth-order RK methods were investigated. There was no significant difference observed in the accuracy of the LB or RK schemes. The passive scalar D3Q7 LB discretisation tended to provide computational benefits, while the second order RK scheme is superior in memory usage. This paper makes contributions relating to the modelling of thermocapillary flows and to understanding the behaviour of droplet capture with thermal sources analogous to thermal tweezers. Four primary contributions to the literature are identified. First, a new 3D thermocapillary, central-moment phase-field LB model is presented and implemented in the open-source software, WALBERLA. Second, the accuracy and computational performance of various techniques to resolve the energy equation for multiphase, incompressible fluids are investigated. Third, the dynamic droplet transport behaviour in the presence of thermal sources is studied, and insight is provided into the potential ability to manipulate droplets based on local domain heating. Finally, a concise analysis of the computational performance and near-perfect scaling results on NVIDIA and AMD GPU-clusters is shown. This research enables the detailed study of droplet manipulation and control in thermocapillary devices by providing a highly-efficient computational modelling methodology.

Fibrous air filters have emerged extensively as a remedial indoor solution to address severe air pollution. To understand the complexities involved in variation of their performance with respect to their fiber anisotropy, a fundamental numerical study is undertaken to investigate the capture of inertia-dominated airborne particles by a fiber-segment at different through-plane orientations with respect to airflow direction. An in-house MATLAB code has been developed using the lattice Boltzmann method to model the airflow across fiber-segment, coupled with the Lagrangian approach to model the motion of particles as well as their interactions with the fiber-segment. The filtration performance parameters, viz., capture efficiency, pressure drop, and quality factor, have been evaluated at different through-plane orientations of the fiber-segment for its various segmental aspect ratios and different Stokes numbers. It is found that as the fiber-segment is turned from a parallel to orthogonal orientation with respect to airflow direction, the capture efficiency and pressure drop exhibit either a monotonic rise or broadly an increasing–decreasing kind of trend with an intermediate maximum, depending on the segmental aspect ratio of fiber and the Stokes number. Also, both these parameters are observed to decrease as the segmental aspect ratio of fiber is increased. Furthermore, an optimum through-plane orientation as well as an optimum segmental aspect ratio of the fiber-segment are found to exist for which the overall filtration performance is highest. The indicative optimum through-plane orientation of the fiber-segment is found to be a function of its segmental aspect ratio but not the Stokes number.

The permeability of rocks is important in a range of geoscientific applications, including CO_2 sequestration, geothermal energy extraction, and in situ mineral recovery. This work presents an investigation of the change in permeability in porphyry rock samples due to blast-induced fracturing. Two samples were analysed before and after exposure to stress waves induced by the detonation of an explosive charge. Micro-computed tomography was used to image the interior of the samples at a pixel resolution of 10.3 μ m . The images were segmented into void, matrix, and grain to help quantify the differences in the rock samples. Following this, they were binarised as void or solid and the cumulant lattice Boltzmann method (LBM) was applied to simulate the flow of fluid through the connected void space. A correction required with the use of inlet and outlet reservoirs in computational permeability assessment was also proposed. Interrogation of the steady-state flow field allowed the pre- and post-loading permeability to be extracted. Conclusions were then drawn as to the effectiveness of blasting for enhancing fluid accessibility via the generation of microfractures in the rock matrix within the vicinity of a detonated charge. This paper makes contributions in three fundamental areas relating to the numerical assessment of permeability and the enhancement of fluid accessibility in low-porosity rocks. Firstly, a correction factor was proposed to account for the reservoirs commonly imposed on digitised rock samples when investigating sample permeability through numerical methods. Secondly, it validates the benefits of the LBM in handling complex geometries that would be intractable with conventional computational fluid dynamics methods that require body-fitted meshing. This is done with a novel implementation of the cumulant LBM in the open-source TCLB code. Finally, the improvement in fluid accessibility in low-permeability rock samples was shown through the assessment of multiple regions within two blasted samples. It was found that the blast-induced loading can generate extended microfractures that results in multiple orders of magnitude of permeability enhancement if the target rock possesses existing weaknesses and/or mineralisation.

This study compares the free-surface lattice Boltzmann method (FSLBM) with the conservative Allen–Cahn phase-field lattice Boltzmann method (PFLBM) in their ability to model two-phase flows in which the behavior of the system is dominated by the heavy phase. Both models are introduced and their individual properties, strengths and weaknesses are thoroughly discussed. Six numerical benchmark cases were simulated with both models, including (i) a standing gravity and (ii) capillary wave, (iii) an unconfined rising gas bubble in liquid, (iv) a Taylor bubble in a cylindrical tube, and (v) the vertical and (vi) oblique impact of a drop into a pool of liquid. Comparing the simulation results with either analytical models or experimental data from the literature, four major observations were made. Firstly, the PFLBM selected was able to simulate flows purely governed by surface tension with reasonable accuracy. Secondly, the FSLBM, a sharp interface model, generally requires a lower resolution than the PFLBM, a diffuse interface model. However, in the limit case of a standing wave, this was not observed. Thirdly, in simulations of a bubble moving in a liquid, the FSLBM accurately predicted the bubble's shape and rise velocity with low computational resolution. Finally, the PFLBM's accuracy is found to be sensitive to the choice of the model's mobility parameter and interface width.

Solution flow can significantly influence metal recovery and kinetics in leaching, especially in heap/dump/Insitu leaching, however, the vast majority of the work in this area has focused on the inter-particle fluid flow, and only a few studies have investigated the capillary rise behaviour within rock samples. This deserves more attention because it plays a fundamental role in the recovery process and the diffusion pathways for lixiviants and reacted products. This short communication presents a simple methodology for the estimation of capillary action by testing different rock types by Time Lapse Digital Imaging. The method was sensitive to pixel variation which can be intercepted as the response in wettability variation. It can certainly be coupled with other technologies for ore characterization, such as X-ray micro-tomography, to further understand how the pore size distribution influences capillary response, and the fluid rise through pore spaces to interact with ore grains.

X-ray computed tomography (XCT) is routinely used in geosciences for the purpose of rock characterisation. High-quality micro-CT images are successfully used for fracture characterisation, as well as analysis of grains and pores. In contrast, the use of XCT for mineral identification is uncommon and often ineffective. Implementation of micro-CT imaging techniques for mineral identification is affected by the accuracy and precision of the image segmentation results. Conventional segmentation methods such as thresholding, watershed, and active contouring are user-biased and do not provide the robust distinction between various heavy accessory minerals in granite rocks. Heavy ore minerals such as pyrite, chalcopyrite, molybdenite, and ilmenite are readily recognised in grey-scale micro-CT images because of their high attenuation coefficient, but further differentiation between these minerals using only traditional segmentation methods is challenging. Conversely, deep convolutional neural networks (CNNs) are fully self-trained, and they have demonstrated accurate semantic segmentation results for rock images. However, the application of CNN semantic segmentation for igneous rocks is not well documented. In this research, the U-Net 2.5D CNN was deployed to train the neural network on a combination of high-resolution micro-CT and mineral liberation analysis (MLA) images to identify different accessory mineral regions of interest (ROIs). The image segmentation results were assessed using MLA and SEM data, and the accuracy of segmentation was found to be greater than 97%. The methodology developed in this study can be extended to map the mineralogy of granite samples unseen by the CNN to further validate the robustness of the approach.

X-ray micro-computed tomography (micro-CT) is widely used for three-dimensional analysis of many rock types. However, the practical implementation of this method for micro-porous samples requires a compromise between the resolution of the images and the obtainable field of view (FOV). Generally, resolution enhancement results in a reduction of the FOV. The generation of high-quality micro-CT images is an expensive and time consuming task due to the competing requirements of a large FOV and fine resolution. To alleviate this, super-resolution processing, based on deep learning, is proposed to improve the quality of low-resolution images that can obtain a large FOV. In this research, a super-resolution technique employing the three-dimensional U-Net convolutional neural network (CNN) architecture was applied to enhance the resolution of granodiorite rock sample images. This was undertaken using two sets of micro-CT image triplexes, where the first triplex contained 3-, 6-, and 12-micron resolution sets, and the second triplex contained 1-, 2-, and 4-micron resolution sets. For each triplex, 80% of the images were used for training the neural network with the remaining 20% used for validation. Further validation was performed by comparing the processed results to images obtained from scanning electron microscopy (SEM). It was observed that super-resolution processing can significantly improve the low-resolution micro-CT image quality without physically reducing the sample size typically required for high-resolution scanning. It is expected that this technique could assist practitioners reveal features absent in small samples (e.g. large fractures and or rock textures). Furthermore, images restored through super-resolution processing maintain the FOV of the lower resolution scan, a task that would be comparatively expensive and time consuming to acquire in a high-resolution scan. The workflow proposed in this study has a significant impact on a range of fields including the numerical prediction of rock permeability, and segmentation for advanced mineral analysis.

This study implements and analyses two common variants of the wetting boundary condition within the three-dimensional phase field lattice Boltzmann method. It provides a simple, novel extension of the geometrical approach, used extensively in 2D, to curved 3D boundaries. Additionally, a novel technique to account for the effects of the staircase approximation of curved boundaries is presented and applied to both methods. Through detailed validation on a series of 3D benchmark cases involving curved surfaces, such as droplet spread on a sphere, capillary intrusion, and droplet impact on a sphere, the behaviour of the wetting boundary conditions are validated and the differences between methods are illustrated. To demonstrate the applicability of the proposed methods to complex geometries with varying surface curvatures, two-phase flow through a synthetic rough fracture is presented. The suitability of the methods for complex simulations is also verified by comparing the computational performance between all investigated methods using the fracture flow test case. The present work thus contributes to the field of multiphase flow modelling with the lattice Boltzmann method in application to realistic complex geometries.

Wellbore instability is an important consideration during both drilling and production of hydrocarbon reservoirs. The optimal well trajectory must be determined during the design phase to avoid wellbore shear failures. This study makes two fundamental contributions towards improving contemporary wellbore shear models. For the first time, the analytical wellbore shear models are formulated implicitly to significantly improve the computational efficiency and obtainable accuracy. The stability problem is resolved with the bisection method and an optimisation algorithm, where Powell's method and the Nelder-Mead method have been implemented here. The second contribution is to account for the depletion of various formations, especially coal, in the stability models. Three stress models, namely those of Gray, Shi and Durucan, and Cui and Bustin, were used to develop stress paths for a depleted coal reservoir. The results were quantified via the maximum allowable pressure (MAP), which indicates the wellbore pressure required to avoid wellbore failure and thus guide corresponding operational decisions. The results of this work show that implicit methods significantly improve computational efficiency over the conventional iterative method used in the literature and industry. In particular, it was found that Powell's method saves greater than 95% of the computation time for sandstone and coal case studies, respectively. In terms of stability during depletion, a higher depletion pressure resulted in an increased MAP. For a drilling application, this means that a greater overbalance pressure is required. While in a production application, a lower maximum drawdown pressure would be expected. The Gray model indicates the largest impact on stability prediction for depleted coals, and the Cui and Bustin model is the most conservative among the three stress models. The proposed numerical framework provides an efficient tool to determine the optimal well trajectory for different formations (e.g. coal, clastic rock) experiencing depletion before or after drilling.

This study analyzes the fracture patterns generated from the high-energy release caused by commercially available explosives and the current capability of numerical methods to replicate this. The mechanics of rock fracture and fragmentation are first studied using the Hybrid Stress Blasting Model (HSBM) at the lab-scale through comparison with experimental results available in the literature. Following this, an in-house experimental blast campaign was undertaken with a detailed examination of an unconfined, 605 mm diameter cylindrical sample and a pressurised (confined), 700 mm diameter cylindrical sample. The post-blast samples were dissected and fractures were visually mapped before comparing the fracture intensity results to the output of the HSBM, which captures stress-wave-induced damage but not gas loading, for these test cases. This paper makes contributions to the literature in three fundamental areas. Firstly, the capability of numerical methods to capture the phenomenology of blasting on rock fracture and fragmentation was validated and the limitations were discussed when looking to use this as a design tool for practical blasting operations. Secondly, the experimental campaign provides detailed insights into the response of cementitious grout materials to internal, blast-induced loading that can be applied in various fields such as mining and construction. Finally, the impact of confining pressure on blast damage was investigated and details were provided for how this can be captured in numerical predictions. It was found that certain aspects of the material response can be well predicted through numerical analysis, namely, the damage radius and the number of dominant fractures. However, it also indicated a shortcoming in the explicit comparison of fracture intensity measures such as P21, with the use of damage metrics appearing more appropriate. The grout-based testing methodology discussed in this work provides an efficient means for gathering data on the impacts of individually controlled aspects of a blast in both unconfined, and confined environments.