Non-invasive fractional flow reserve estimation in coronary arteries using angiographic images.

Coronary artery disease is the leading global cause of mortality and Fractional Flow Reserve (FFR) is widely regarded as the gold standard for assessing coronary artery stenosis severity. However, due to the limitations of invasive FFR measurements, there is a pressing need for a highly accurate virtual FFR calculation framework. Additionally, it's essential to consider local haemodynamic factors such as time-averaged wall shear stress (TAWSS), which play a critical role in advancement of atherosclerosis. This study introduces an innovative FFR computation method that involves creating five patient-specific geometries from two-dimensional coronary angiography images and conducting numerical simulations using computational fluid dynamics with a three-element Windkessel model boundary condition at the outlet to predict haemodynamic distribution. Furthermore, four distinct boundary condition methodologies are applied to each geometry for comprehensive analysis. Several haemodynamic features, including velocity, pressure, TAWSS, and oscillatory shear index are investigated and compared for each case. Results show that models with average boundary conditions can predict FFR values accurately and observed errors between invasive FFR and virtual FFR are found to be less than 5%.

A Review of Pressure Drop and Mixing Characteristics in Passive Mixers Involving Miscible Liquids.

The present review focuses on the recent studies carried out in passive micromixers for understanding the hydrodynamics and transport phenomena of miscible liquid-liquid (LL) systems in terms of pressure drop and mixing indices. First, the passive micromixers have been categorized based on the type of complexity in shape, size, and configuration. It is observed that the use of different aspect ratios of the microchannel width, presence of obstructions, flow and operating conditions, and fluid properties majorly affect the mixing characteristics and pressure drop in passive micromixers. A regime map for the micromixer selection based on optimization of mixing index (MI) and pressure drop has been identified based on the literature data for the Reynolds number (Re) range (1 ≤ Re ≤ 100). The map comprehensively summarizes the favorable, moderately favorable, or non-operable regimes of a micromixer. Further, regions for special applications of complex micromixer shapes and micromixers operating at low Re have been identified. Similarly, the operable limits for a micromixer based on pressure drop for Re range 0.1 < Re < 100,000 have been identified. A comparison of measured pressure drop with fundamentally derived analytical expressions show that Category 3 and 4 micromixers mostly have higher pressure drops, except for a few efficient ones. An MI regime map comprising diffusion, chaotic advection, and mixed advection-dominated zones has also been devised. An empirical correlation for pressure drop as a function of Reynolds number has been developed and a corresponding friction factor has been obtained. Predictions on heat and mass transfer based on analogies in micromixers have also been proposed.

Computational analysis of nasal airflow and its alteration by a nasal dilator.

Nasal airflow obstruction correlates with several ailments, such as higher patency, increased friction at the mucosal wall or the so-called Little's area, improper air conditioning, and snoring. Nasal dilators are frequently employed, mainly due to their ease of access and use, combined with their non-permanent and non-surgical nature. Their overall efficacy, however, has not been clearly demonstrated so far, with some studies reporting conflicting outcomes, mainly because being based on subjective evaluations. This study employs Computational Fluid Dynamics simulations to analyze the flow inside a real nose, performs an objective assessment of a nasal dilator's effect in terms of airflow and air conditioning, reporting flow paths, friction levels, heat and water fluxes and detailed temperature and humidity distributions. Coincidentally, the studied nose presents a septal deviation, with one nostril being wider than the other. The tubes of the dilator used in both nostrils are identical, as with any standard commercial dilator. Consequently, the dilator widens one nostril, as intended, but results in an obstruction in the other. This allows simultaneously addressing two situations, the nominal function of the dilator, as well as an off-design case. Results indicate a 24 % increase in nasal patency in the design situation. The effect, however, is limited, as quantified by appropriate measures, such as the flow-generated friction at the nose surfaces and the temperature fluxes. Hence, the effect of such a dilator in nominal conditions is perhaps not as large as might be hoped. In the off-design situation, nasal resistance increases by 62 %, an undesirable effect, illustrating the consequences of using an inappropriate dilator.

Computational fluid dynamics modeling of coronary artery blood flow using OpenFOAM: Validation with the food and drug administration benchmark nozzle model.

Cardiovascular disease (CVD), a global health concern, particularly coronary artery disease (CAD), poses a significant threat to well-being. Seeking safer and cost-effective diagnostic alternatives to invasive coronary angiography, noninvasive coronary computed tomography angiography (CCTA) gains prominence. This study employed OpenFOAM, an open-source Computational Fluid Dynamics (CFD) software, to analyze hemodynamic parameters in coronary arteries with serial stenoses. Patient-specific three-dimensional (3D) models from CCTA images offer insights into hemodynamic changes. OpenFOAM breaks away from traditional commercial software, validated against the FDA benchmark nozzle model for reliability. Applying this refined methodology to seventeen coronary arteries across nine patients, the study evaluates parameters like fractional flow reserve computed tomography simulation (FFRCTS), fluid velocity, and wall shear stress (WSS) over time. Findings include FFRCTS values exceeding 0.8 for grade 0 stenosis and falling below 0.5 for grade 5 stenosis. Central velocity remains nearly constant for grade 1 stenosis but increases 3.4-fold for grade 5 stenosis. This research innovates by utilizing OpenFOAM, departing from previous reliance on commercial software. Combining qualitative stenosis grading with quantitative FFRCTS and velocity measurements offers a more comprehensive assessment of coronary artery conditions. The study introduces 3D renderings of wall shear stress distribution across stenosis grades, providing an intuitive visualization of hemodynamic changes for valuable insights into coronary stenosis diagnosis.

A quasi-realistic computational model development and flow field study of the human upper and central airways.

The impact of drug delivery and particulate matter exposure on the human respiratory tract is influenced by various anatomical and physiological factors, particularly the structure of the respiratory tract and its fluid dynamics. This study employs computational fluid dynamics (CFD) to investigate airflow in two 3D models of the human air conducting zone. The first model uses a combination of CT-scan images and geometrical data from human cadaver to extract the upper and central airways down to the ninth generation, while the second model develops the lung airways from the first Carina to the end of the ninth generation using Kitaoka's deterministic algorithm. The study examines the differences in geometrical characteristics, airflow rates, velocity, Reynolds number, and pressure drops of both models in the inhalation and exhalation phases for different lobes and generations of the airways. From trachea to the ninth generation, the average air flowrates and Reynolds numbers exponentially decay in both models during inhalation and exhalation. The steady drop is the case for the average air velocity in Kitaoka's model, while that experiences a maximum in the 3rd or 4th generation in the quasi-realistic model. Besides, it is shown that the flow field remains laminar in the upper and central airways up to the total flow rate of 15 l/min. The results of this work can contribute to the understanding of flow behavior in upper respiratory tract.

Impact Exploration of Spatiotemporal Feature Derivation and Selection on Machine Learning-Based Predictive Models for Post-Embolization Cerebral Aneurysm Recanalization.

PURPOSE: To enhance the performance of machine learning (ML) models for the post-embolization recanalization of cerebral aneurysms, we evaluated the impact of hemodynamic feature derivation and selection method on six ML algorithms. METHODS: We utilized computational fluid dynamics (CFD) to simulate hemodynamics in 66 cerebral aneurysms from 65 patients, including 57 stable and nine recanalized aneurysms. We derived a total of 107 features for each aneurysm, encompassing four clinical features, 12 morphological features, and 91 hemodynamic features. To investigate the influence of feature derivation and selection methods on the ML models, we employed two derivation methods, simplified and fully derived, in combination with four selection methods: all features, statistically significant analysis, stepwise multivariate logistic regression analysis (stepwise-LR), and recursive feature elimination (RFE). Model performance was assessed using the area under the receiver operating characteristic curve (AUROC) and precision-recall curve (AUPRC) on both the training and testing datasets. RESULTS: The AUROC values on the testing dataset exhibited a wide-ranging spectrum, spanning from 0.373 to 0.863. Fully derived features and the RFE selection method demonstrated superior performance in intra-model comparisons. The multi-layer perceptron (MLP) model, trained with RFE-selected fully derived features, achieved the best performance on the testing dataset, with an AUROC value of 0.863 (95% CI: 0.684- 1.000). CONCLUSION: Our study demonstrated the importance of feature derivation and selection in determining the performance of ML models. This enabled the development of accurate decision-making models without the need to invade the patient.

Impact of Tissue Damage and Hemodynamics on Restenosis Following Percutaneous Transluminal Angioplasty: A Patient-Specific Multiscale Model.

Multiscale agent-based modeling frameworks have recently emerged as promising mechanobiological models to capture the interplay between biomechanical forces, cellular behavior, and molecular pathways underlying restenosis following percutaneous transluminal angioplasty (PTA). However, their applications are mainly limited to idealized scenarios. Herein, a multiscale agent-based modeling framework for investigating restenosis following PTA in a patient-specific superficial femoral artery (SFA) is proposed. The framework replicates the 2-month arterial wall remodeling in response to the PTA-induced injury and altered hemodynamics, by combining three modules: (i) the PTA module, consisting in a finite element structural mechanics simulation of PTA, featuring anisotropic hyperelastic material models coupled with a damage formulation for fibrous soft tissue and the element deletion strategy, providing the arterial wall damage and post-intervention configuration, (ii) the hemodynamics module, quantifying the post-intervention hemodynamics through computational fluid dynamics simulations, and (iii) the tissue remodeling module, based on an agent-based model of cellular dynamics. Two scenarios were explored, considering balloon expansion diameters of 5.2 and 6.2 mm. The framework captured PTA-induced arterial tissue lacerations and the post-PTA arterial wall remodeling. This remodeling process involved rapid cellular migration to the PTA-damaged regions, exacerbated cell proliferation and extracellular matrix production, resulting in lumen area reduction up to 1-month follow-up. After this initial reduction, the growth stabilized, due to the resolution of the inflammatory state and changes in hemodynamics. The similarity of the obtained results to clinical observations in treated SFAs suggests the potential of the framework for capturing patient-specific mechanobiological events occurring after PTA intervention.

An in-silico analysis of hydrodynamics and gas mass transfer characteristics in scale-down models for mammalian cell cultures.

Bioprocess scale-up and technology transfer can be challenging due to multiple variables that need to be optimized during process development from laboratory scale to commercial manufacturing. Cell cultures are highly sensitive to key factors during process transfer across scales, including geometric variability in bioreactors, shear stress from impeller and sparging activity, and nutrient gradients that occur due to increasing blend times. To improve the scale-up and scale-down of these processes, it is important to fully characterize bioreactors to better understand the differences that will occur within the culture environment, especially the hydrodynamic profiles that will vary in vessel designs across scales. In this study, a comprehensive hydrodynamic characterization of the Ambr® 250 mammalian single-use bioreactor was performed using time-accurate computational fluid dynamics simulations conducted with M-Star computational fluid dynamics software, which employs lattice-Boltzmann techniques to solve the Navier-Stokes transport equations at a mesoscopic scale. The single-phase and two-phase fluid properties within this small-scale vessel were analyzed in the context of agitation hydrodynamics and mass transfer (both within the bulk fluid and the free surface) to effectively characterize and understand the differences that scale-down models possess when compared to their large-scale counterparts. The model results validate the use of computational fluid dynamics as an in-silico tool to characterize bioreactor hydrodynamics and additionally identify important free-surface transfer mechanics that need to be considered during the qualification of a scale-down model in the development of mammalian bioprocesses.

Carding Behavior and Bearing Capacity of a Newly Developed Cylinder Card-Clothing Compatible with Cotton and Terylene Fibers by Nb Alloying of AISI 1090 Steel.

Changing the metallic card clothing on a carding machine is costly when the spinning mills want to card different fibers from cotton to terylene or vice versa. This article proposes a newly developed cylinder card clothing compatible with cotton and terylene fibers by Nb alloying of AISI 1090 steel so that the spinning mills can change the type of fiber without changing the card clothing. Based on an idea developed from classical carding balance theory to study the adaptability of the cylinder card clothing for cotton and terylene fibers, the wall shear stress was used as the basis for compatibility analysis of carding behavior and bearing capacity with cotton and terylene fibers and as the focus of this study. Nb alloying of AISI 1090 steel showed good wear resistance in carding areas after heat treatment with high hardness above 840 Hv0.2 and extremely fine grain grade of 13.5 class, which increased about 25% compared to conventional 80 WV. The testing results in the spinning mills, including one cotton and two terylene fibers, showed good performance with this newly developed card clothing. In conclusion, the card clothing made of Nb alloying of AISI 1090 steel can handle different fibers with acceptable carding performance.

Treatment for middle cerebral artery bifurcation aneurysms: in silico comparison of the novel Contour device and conventional flow-diverters.

Endovascular treatment has become the standard therapy for cerebral aneurysms, while the effective treatment for middle cerebral artery (MCA) bifurcation aneurysms remains a challenge. Current flow-diverting techniques with endovascular coils cover the aneurysm orifice as well as adjacent vessel branches, which may lead to branch occlusion. Novel endovascular flow disruptors, such as the Contour device (Cerus Endovascular), are of great potential to eliminate the risk of branch occlusion. However, there is a lack of valid comparison between novel flow disruptors and conventional (intraluminal) flow-diverters. In this study, two in silico MCA bifurcation aneurysm models were treated by specific Contour devices and flow-diverters using fast-deployment algorithms. Computational fluid dynamic simulations were used to examine the performance and efficiency of deployed devices. Hemodynamic parameters, including aneurysm inflow and wall shear stress, were compared among each Contour device, conventional flow-diverter, and untreated condition. Our results show that the placement of devices can effectively reduce the risk of aneurysm rupture, while the deployment of a Contour device causes more flow reduction than using flow-diverters (e.g. Silk Vista Baby). Besides, the Contour device presents the flow diversion capability of targeting the aneurysm neck without occluding the daughter vessel. In summary, the in silico aneurysm models presented in this study can serve as a powerful pre-planning tool for testing new treatment techniques, optimising device deployment, and predicting the performance in patient-specific aneurysm cases. Contour device is proved to be an effective treatment of MCA bifurcation aneurysms with less daughter vessel occlusion.

A new computational fluid dynamics based noninvasive assessment of portacaval pressure gradient.

Accurate assessment of portacaval pressure gradient (PCG) in patients with portal hypertension (PH) is of great significance both for diagnosis and treatment. This study aims to develop a noninvasive method for assessing PCG in PH patients and evaluate its accuracy and effectiveness. This study recruited 37 PH patients treated with transjugular intrahepatic portosystemic shunt (TIPS). computed tomography angiography was used to create three dimension (3D) models of each patient before and after TIPS. Doppler ultrasound examinations were conducted to obtain the patient's portal vein flow (or splenic vein and superior mesenteric vein). Using computational fluid dynamics (CFD) simulation, the patient's pre-TIPS and post-TIPS PCG was determined by the 3D models and ultrasound measurements. The accuracy of these noninvasive results was then compared to clinical invasive measurements. The results showed a strong linear correlation between the PCG simulated by CFD and the clinical invasive measurements both before and after TIPS (R2 = 0.998, P < 0.001 and R2 = 0.959, P < 0.001). The evaluation accuracy of this noninvasive method reached 94 %, and the influence of ultrasound result errors on the numerical accuracy was found to be marginal if the error was less than 20 %. Furthermore, the information about the hemodynamic environment in the portal system was obtained by this numerical method. Spiral flow patterns were observed in the portal vein of some patients. In a conclusion, this study proposes a noninvasive numerical method for assessing PCG in PH patients before and after TIPS. This method can assist doctors in accurately diagnosing patients and selecting appropriate treatment plans. Additionally, it can be used to further investigate potential biomechanical causes of complications related to TIPS in the future.

Computational Fluid Dynamics Analysis and Empirical Evaluation of Carboxymethylcellulose/Alginate 3D Bioprinting Inks for Screw-Based Microextrusion.

Three-dimensional microextrusion bioprinting technology uses pneumatics, pistons, or screws to transfer and extrude bioinks containing biomaterials and cells to print biological tissues and organs. Computational fluid dynamics (CFD) analysis can simulate the flow characteristics of bioinks in a control volume, and the effect on cell viability can be predicted by calculating the physical quantities. In this study, we developed an analysis system to predict the effect of a screw-based dispenser system (SDS) on cell viability in bioinks through rheological and CFD analyses. Furthermore, carboxymethylcellulose/alginate-based bioinks were used for the empirical evaluation of high-viscous bioinks. The viscosity of bioinks was determined by rheological measurement, and the viscosity coefficient for the CFD analysis was derived from a correlation equation by non-linear regression analysis. The mass flow rate derived from the analysis was successfully validated by comparison with that from the empirical evaluation. Finally, the cell viability was confirmed after bioprinting with bioinks containing C2C12 cells, suggesting that the developed SDS may be suitable for application in the field of bioengineering. Consequently, the developed bioink analysis system is applicable to a wide range of systems and materials, contributing to time and cost savings in the bioengineering industry.

Reducing variability in nasal surgery outcomes through computational fluid dynamics and advanced 3D virtual surgery techniques.

Objectives: This study aims to delineate the specific impact of using computational fluid dynamics (CFD) and 3D virtual surgery techniques in otolaryngology surgery, focusing on their roles in enhancing the precision of nasal surgery and optimizing future patient outcomes. The central objective was to assess whether these advanced technologies could reduce variability in surgical approaches and decision-making among specialists, thereby improving the consistency and efficacy of patient care in cases of nasal obstruction. Methods and results: Our methodology involved a detailed analysis of pre- and post-operative scenarios using CFD feedback. Six otolaryngologists participated, employing virtual surgery techniques on two patients with diagnosed nasal obstruction. The CFD analysis focused on quantifying key airflow parameters: right nasal flow rate (QR), left nasal flow rate (QL), flow symmetry (Ф), and bilateral nasal resistance (R). These parameters were meticulously compared before and after the application of CFD feedback to evaluate changes in surgical planning and outcomes. Quantitative analysis revealed a notable decrease in the standard deviation of the measured parameters among the specialists post-CFD feedback, indicating reduced variability in surgical approaches. Specifically, for Patient #1 the standard deviation for QR values dropped from 0.694 L/min to 0.602 L/min, and for QL values from 0.676 L/min to 0.584 L/min, and for Patient #2, the standard deviation for QR values decreased from 2.204 L/min to 0.958 L/min, and for QL values from 2.295 L/min to 1.014 L/min. Moreover, the variability range, represented by the differences between the maximum and minimum values for Ф and R, diminished significantly. Post-operative average values for all parameters showed a convergence towards ideal basal levels, suggesting a more uniform and effective surgical strategy across different surgeons. Conclusions: Both integration of CFD and 3D virtual surgery techniques in otolaryngology can substantially reduce variability in surgical planning and decision-making, ultimately leading to improved patient outcomes. These advanced tools have the potential to standardize the diagnosis and treatment of nasal pathologies, contributing to more effective and consistent care. Future research in this area should focus on larger patient cohorts and further exploration of the potential benefits and applications of CFD and virtual surgery in otolaryngology.

The impact of contrast retention on thrombus formation risks in patients with atrial fibrillation: A numerical study.

Background: Contrast retention (CR) is an important predictor of left atrial appendage thrombus (LAAT) and stroke in patients with non-valvular atrial fibrillation (AF). We sought to explore the underlying mechanisms of CR using computational fluid dynamic (CFD) simulations. Methods: A total of 12 patients with AF who underwent both cardiac computed tomography angiography (CTA) and transesophageal echocardiography (TEE) before left atrial appendage occlusion (LAAO) were included in the study. The patients were allocated into the CR group or non-CR group based on left atrial appendage (LAA) angiography. Patient-specific models were reconstructed to evaluate time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), relative residence time (RRT), and endothelial cell activation potential (ECAP). Additionally, the incidence of thrombosis was predicted using residence time (RT) at different time-points. Results: TAWSS was lower [median (Interquartile Range) 0.27 (0.19-0.47) vs 1.35 (0.92-1.79), p < 0.001] in LAA compared to left atrium. In contrast, RRT [1438 (409.70-13869) vs 2.23 (1.81-3.14), p < 0.001] and ECAP [122.70 (30.01-625.70) vs 0.19 (0.16-0.27), p < 0.001)] was higher in the LAA. The patients in the CR group had significantly higher RRT [(mean ± SD) 16274 ± 11797 vs 639.70 ± 595.20, p = 0.009] and ECAP [610.80 ± 365.30 vs 54.26 ± 54.38, p = 0.004] in the LAA compared to the non-CR group. Additionally, patients with CR had a wider range of thrombus-prone regions [0.44(0.27-0.66)% vs 0.05(0.03-0.27)%, p = 0.009] at the end of the 15th cardiac cycle. Conclusions: These findings suggest that CR might be an indicator of high-risk thrombus formation in the LAA. And CT-based CFD simulation may be a feasible substitute for the evaluation of LAA thrombotic risk in patients with AF, especially in patients with CR.

Mathematical modelling of a semi-dry SO2 scrubber based on a Lagrangian-Eulerian approach.

Semi-dry desulfurization is an efficient means of SO2 removal from the effluent gases from electrolysis cells in aluminum smelters. These gases are at low temperature and contain low concentrations of SO2, as opposed to thermal power plants. The removal is carried out by injecting powdered alkaline sorbent, hydrated lime (solid particles), into the SO2-containing gas (gas phase) in the presence of humidity. The reaction is controlled by the adsorption of SO2 onto the surface of lime. This study involves the mathematical modelling of a lab-scale scrubber using a Lagrangian-Eulerian approach in order to analyze the desulfurization efficiency. The model was validated based on experimental data. A parametric study was carried out to investigate the effects of particle size, sorbent amount, and relative humidity (RH) on the desulfurization efficiency. The results show that the particle size is the most important parameter; as the particle size decreases, the desulfurization efficiency increases. However, using finer particles may increase the process cost. The loss in SO2 capture efficiency due to the use of coarser particle size could be compensated by increasing the relative humidity (RH) of the gas, another key parameter of the process.

The Effects of Ambient Temperature and Atmospheric Humidity on the Diffusion Dynamics of Hydrogen Fluoride Gas Leakage Based on the Computational Fluid Dynamics Method.

In order to investigate the impact of environmental temperature and atmospheric humidity on the leakage and diffusion of hydrogen fluoride (HF) gas, this study focused on the real scenario of an HF chemical industrial park. Based on the actual dispersion scenario of HF gas, a proportionally scaled-down experimental platform for HF gas leakage was established to validate the accuracy and feasibility of numerical simulations under complex conditions. Using the validated model, the study calculated the complex scenarios of HF leakage and diffusion within the temperature range of 293 K to 313 K and the humidity range of 0% to 100%. The simulation results indicated that different environmental temperatures had a relatively small impact on the hazardous areas (the lethal area, severe injury area, light injury area, and maximum allowable concentration (MAC) area) formed by HF gas leakage. At 600 s of dispersion, the fluctuation range of hazardous area sizes under different temperature conditions was between 3.11% and 13.07%. In contrast to environmental temperature, atmospheric relative humidity had a more significant impact on the dispersion trend of HF leakage. Different relative humidity levels mainly affected the areas of the lethal zone, light injury zone, and MAC zone. When HF continued to leak and disperse for 600 s, compared to 0% relative humidity, 100% relative humidity reduced the lethal area by 35.7%, while increasing the light injury area and MAC area by 27.26% and 111.6%, respectively. The impact on the severe injury area was relatively small, decreasing by 1.68%. The results of this study are crucial for understanding the dispersion patterns of HF gas under different temperature and humidity conditions.

Computational Rhinology: Unraveling Discrepancies between In Silico and In Vivo Nasal Airflow Assessments for Enhanced Clinical Decision Support.

Computational rhinology is a specialized branch of biomechanics leveraging engineering techniques for mathematical modelling and simulation to complement the medical field of rhinology. Computational rhinology has already contributed significantly to advancing our understanding of the nasal function, including airflow patterns, mucosal cooling, particle deposition, and drug delivery, and is foreseen as a crucial element in, e.g., the development of virtual surgery as a clinical, patient-specific decision support tool. The current paper delves into the field of computational rhinology from a nasal airflow perspective, highlighting the use of computational fluid dynamics to enhance diagnostics and treatment of breathing disorders. This paper consists of three distinct parts-an introduction to and review of the field of computational rhinology, a review of the published literature on in vitro and in silico studies of nasal airflow, and the presentation and analysis of previously unpublished high-fidelity CFD simulation data of in silico rhinomanometry. While the two first parts of this paper summarize the current status and challenges in the application of computational tools in rhinology, the last part addresses the gross disagreement commonly observed when comparing in silico and in vivo rhinomanometry results. It is concluded that this discrepancy cannot readily be explained by CFD model deficiencies caused by poor choice of turbulence model, insufficient spatial or temporal resolution, or neglecting transient effects. Hence, alternative explanations such as nasal cavity compliance or drag effects due to nasal hair should be investigated.

Impact of single and combined local air pollution mitigation measures in an urban environment.

Urban air pollution is one of the most important environmental problems for human health and several strategies have been developed for its mitigation. The objective of this study is to assess the impact of single and combined mitigation measures on concentrations of air pollutants emitted by traffic at pedestrian level in the same urban environment. The effectiveness of different scenarios of green infrastructure (GI), the implementation of photocatalytic materials and traffic low emission zones (LEZ) are investigated, as well as several combinations of LEZ and GI. A wide set of scenarios is simulated through Computational Fluid Dynamics (CFD) modelling for two different wind directions (perpendicular (0°) and 45° wind directions). Wind flow for the BASE scenario without any measure implemented was previously evaluated using wind-tunnel measurements. Air pollutant concentrations for this scenario are compared with the results obtained from the different mitigation scenarios. Reduction of traffic emissions through LEZ is found to be the most effective single measure to improve local air quality. However, GI enhances the effects of LEZ, which makes the combination of LEZ + GI a very effective measure. The effectiveness of this combination depends on the GI layout, the intensity of emission reduction in the LEZ and the traffic diversion in streets surrounding the LEZ. These findings, in line with previous literature, suggest that the implementation of GI may increase air pollutant concentrations at pedestrian level for some cases. However, this study highlights that this negative effect on air quality can turn into positive when used in combination with reductions of local traffic emissions.

In silico parametric analysis of femoro-jugular venovenous ECMO and return cannula dynamics: In silico analysis of femoro-jugular VV ECMO.

BACKGROUND: Increasingly, computational fluid dynamics (CFD) is helping explore the impact of variables like: cannula design/size/position/flow rate and patient physiology on venovenous (VV) extracorporeal membrane oxygenation (ECMO). Here we use a CFD model to determine what role cardiac output (CO) plays and to analyse return cannula dynamics. METHODS: Using a patient-averaged model of the right atrium and venae cava, we virtually inserted a 19Fr return cannula and a 25Fr drainage cannula. Running large eddy simulations, we assessed cardiac output at: 3.5-6.5 L/min and ECMO flow rate at: 2-6 L/min. We analysed recirculation fraction (Rf), time-averaged wall shear stress (TAWSS), pressure, velocity, and turbulent kinetic energy (TKE) and extracorporeal flow fraction (EFF = ECMO flow rate/CO). RESULTS: Increased ECMO flow rate and decreased CO (high EFF) led to increased Rf (R = 0.98, log fit). Negative pressures developed in the venae cavae at low CO and high ECMO flow (high CR). Mean return cannula TAWSS was >10 Pa for all ECMO flow rates, with majority of the flow exiting the tip (94.0-95.8 %). CONCLUSIONS: Our results underpin the strong impact of CO on VV ECMO. A simple metric like EFF, once supported by clinical data, might help predict Rf for a patient at a given ECMO flow rate. The return cannula imparts high shear stresses on the blood, largely a result of the internal diameter.

Computational approaches for mechanobiology in cardiovascular development and diseases.

The cardiovascular development in vertebrates evolves in response to genetic and mechanical cues. The dynamic interplay among mechanics, cell biology, and anatomy continually shapes the hydraulic networks, characterized by complex, non-linear changes in anatomical structure and blood flow dynamics. To better understand this interplay, a diverse set of molecular and computational tools has been used to comprehensively study cardiovascular mechanobiology. With the continual advancement of computational capacity and numerical techniques, cardiovascular simulation is increasingly vital in both basic science research for understanding developmental mechanisms and disease etiologies, as well as in clinical studies aimed at enhancing treatment outcomes. This review provides an overview of computational cardiovascular modeling. Beginning with the fundamental concepts of computational cardiovascular modeling, it navigates through the applications of computational modeling in investigating mechanobiology during cardiac development. Second, the article illustrates the utility of computational hemodynamic modeling in the context of treatment planning for congenital heart diseases. It then delves into the predictive potential of computational models for elucidating tissue growth and remodeling processes. In closing, we outline prevailing challenges and future prospects, underscoring the transformative impact of computational cardiovascular modeling in reshaping cardiovascular science and clinical practice.