Effects of Polarization on Particle-Laden Flows.

Simulations of particle-laden flow with dielectric particles are carried out with varying levels of electrical charging and particle polarization. Simulation results reveal three distinct flow regions. For low particle charge and polarizability, flow is nearly symmetric and nonmeandering. For strong charging and polarization, particles form a continuous and tightly clustered sheet close to one of the walls. Between these extremes, particles form localized particle-rich regions, around which the gas executes a meandering flow. These results indicate that polarization can lead to qualitative changes in the characteristics of particle-laden flows subject to tribocharging.

Validated respiratory drug deposition predictions from 2D and 3D medical images with statistical shape models and convolutional neural networks.

For the one billion sufferers of respiratory disease, managing their disease with inhalers crucially influences their quality of life. Generic treatment plans could be improved with the aid of computational models that account for patient-specific features such as breathing pattern, lung pathology and morphology. Therefore, we aim to develop and validate an automated computational framework for patient-specific deposition modelling. To that end, an image processing approach is proposed that could produce 3D patient respiratory geometries from 2D chest X-rays and 3D CT images. We evaluated the airway and lung morphology produced by our image processing framework, and assessed deposition compared to in vivo data. The 2D-to-3D image processing reproduces airway diameter to 9% median error compared to ground truth segmentations, but is sensitive to outliers of up to 33% due to lung outline noise. Predicted regional deposition gave 5% median error compared to in vivo measurements. The proposed framework is capable of providing patient-specific deposition measurements for varying treatments, to determine which treatment would best satisfy the needs imposed by each patient (such as disease and lung/airway morphology). Integration of patient-specific modelling into clinical practice as an additional decision-making tool could optimise treatment plans and lower the burden of respiratory diseases.

Computational homogenization of histological microstructures in human prostate tissue: Heterogeneity, anisotropy and tension-compression asymmetry.

Human prostatic tissue exhibits complex mechanical behaviour due to its multiphasic, heterogeneous nature, with hierarchical microstructures involving epithelial compartments, acinar lumens and stromal tissue all interconnected in complex networks. This study aims to establish a computational homogenization framework for quantifying the mechanical behaviour of prostate tissue, considering its multiphasic heterogeneous microstructures and the mechanical characteristics of tissue constituents. Representative tissue microstructure models were reconstructed from high-resolution histology images. Parametric studies on the mechanical properties of the tissue constituents, particularly the fibre-reinforced hyper-elasticity of the stromal tissue, were carried out to investigate their effects on the apparent tissue properties. These were then benchmarked against the experimental data reported in literature. Results showed significant anisotropy, both structural and mechanical, and tension-compression asymmetry of the apparent behaviours of the prostatic tissue. Strong correlation with the key microstructural indices such as area fractions of tissue constituents and the tissue fabric tensor was also observed. The correlation between the stromal tissue orientation and the principal directions of the apparent properties suggested an essential role of stromal tissue in determining the directions of anisotropy and the compression-tension asymmetry characteristics in normal human prostatic tissue. This work presented a homogenization and histology-based computational approach to characterize the apparent mechanical behaviours of human prostatic or other similar glandular tissues, with the ultimate aim of assessing how pathological conditions (e.g., prostate cancer and benign prostatic hyperplasia) could affect the tissue mechanical properties in a future study.

Effect of patient inhalation profile and airway structure on drug deposition in image-based models with particle-particle interactions.

For many of the one billion sufferers of respiratory diseases worldwide, managing their disease with inhalers improves their ability to breathe. Poor disease management and rising pollution can trigger exacerbations that require urgent relief. Higher drug deposition in the throat instead of the lungs limits the impact on patient symptoms. To optimise delivery to the lung, patient-specific computational studies of aerosol inhalation can be used. However in many studies, inhalation modelling does not represent situations when the breathing is impaired, such as in recovery from an exacerbation, where the patient's inhalation is much faster and shorter. Here we compare differences in deposition of inhaler particles (10, 4 µm) in the airways of three patients. We aimed to evaluate deposition differences between healthy and impaired breathing with image-based healthy and diseased patient models. We found that the ratio of drug in the lower to upper lobes was 35% larger with a healthy inhalation. For smaller particles the upper airway deposition was similar in all patients, but local deposition hotspots differed in size, location and intensity. Our results identify that image-based airways must be used in respiratory modelling. Various inhalation profiles should be tested for optimal prediction of inhaler deposition.

Multiscale mechanical consequences of ocean acidification for cold-water corals.

Ocean acidification is a threat to deep-sea corals and could lead to dramatic and rapid loss of the reef framework habitat they build. Weakening of structurally critical parts of the coral reef framework can lead to physical habitat collapse on an ecosystem scale, reducing the potential for biodiversity support. The mechanism underpinning crumbling and collapse of corals can be described via a combination of laboratory-scale experiments and mathematical and computational models. We synthesise data from electron back-scatter diffraction, micro-computed tomography, and micromechanical experiments, supplemented by molecular dynamics and continuum micromechanics simulations to predict failure of coral structures under increasing porosity and dissolution. Results reveal remarkable mechanical properties of the building material of cold-water coral skeletons of 462 MPa compressive strength and 45-67 GPa stiffness. This is 10 times stronger than concrete, twice as strong as ultrahigh performance fibre reinforced concrete, or nacre. Contrary to what would be expected, CWCs retain the strength of their skeletal building material despite a loss of its stiffness even when synthesised under future oceanic conditions. As this is on the material length-scale, it is independent of increasing porosity from exposure to corrosive water or bioerosion. Our models then illustrate how small increases in porosity lead to significantly increased risk of crumbling coral habitat. This new understanding, combined with projections of how seawater chemistry will change over the coming decades, will help support future conservation and management efforts of these vulnerable marine ecosystems by identifying which ecosystems are at risk and when they will be at risk, allowing assessment of the impact upon associated biodiversity.

Particle-based coarse-grained approach for simulating dry powder inhaler.

Drug delivery via dry powder inhaler (DPI) is a complex process affected by multiple factors involving gas and particles. The performance of a carrier-based formulation depends on the release of active pharmaceutical ingredient (API) particles, typically characterized by fine particle fraction (FPF) and dispersion fraction (DF). Computational Fluid Dynamics coupled with Discrete Element Method (CFD-DEM) can capture relevant gas and particle interactions but is computationally expensive, especially when tracking all carrier and API particles. This study assessed the efficacy of two coarse-grained CFD-DEM approaches, the Discrete Parcel Method and the representative particle approach, through highly-resolved CFD-DEM simulations. The representative particle approach simulates all carrier particles and a subset of API particles, whereas the Discrete Parcel Method tracks parcels representing a specified number of carrier or API particles. Both approaches are viable for a small carrier-API size ratio which requires modest degrees of coarse-graining, but the Discrete Parcel Method showed limitations for a large carrier-API size ratio. The representative particle approach can approximate CFD-DEM results with reasonable accuracies when simulations include at least 10 representative API particles per carrier. Using the representative particle approach, we probed powder characteristics that could affect FPF and DF in a model problem and correlated these fractions with the maximum carrier-API cohesive force per unit mass of API particles.

Toward Constitutive Models for Momentum, Species, and Energy Transport in Gas-Particle Flows.

As multiscale structures are inherent in multiphase flows, constitutive models employed in conjunction with transport equations for momentum, species, and energy are scale dependent. We suggest that this scale dependency can be better quantified through deep learning techniques and formulation of transport equations for additional quantities such as drift velocity and analogies for species, energy, and momentum transfer. How one should incorporate interparticle forces, which arise through van der Waals interaction, dynamic liquid bridges between wet particles, and tribocharging, in multiscale models warrants further study. Development of multiscale models that account for all the known interactions would improve confidence in the use of simulations to explore design options, decrease the number of pilot-scale experiments, and accelerate commercialization of new technologies.