As it is known, the Womersley function models velocity as a function of radius and time. It has been widely used to simulate the pulsatile blood flow through circular ducts. In this context, the present study is focused on the introduction of a simple function as an approximation of the Womersley function in order to evaluate its accuracy. This approximation consists of a simple quadratic function, suitable to be implemented in most commercial and non-commercial computational fluid dynamics codes, without the aid of external mathematical libraries. The Womersley function and the new function have been implemented here as boundary conditions in OpenFOAM ESI software (v.1906). The discrepancy between the obtained results proved to be within 0.7%, which fully validates the calculation approach implemented here. This approach is valid when a simplified analysis of the system is pointed out, in which flow reversals are not contemplated.

A mono-dimensional code for the simulation of the effects of High Frequency Ignition systems (HFI) on the production of chemical radicals was developed and here presented. The simulations were carried out by considering the typical environmental thermodynamic conditions of a nowadays engine at full load. An electron transport model is linked with a Boltzmann solver coupled with a chemistry solver, affecting the Electron Energy Distribution Function (EEDF) in order to obtain the physical conditions leading to the production of radical components for a given fuel mixture. The transport equations for the electrons, the positive and the negative ions, and the Gauss’ law in a steady-state plasma region. Then the Boltzmann equation for the electrons, in a spatially homogeneous steady-state case, is solved in order to obtain the EEDF. Finally the chemical kinetics model is employed assuming a fuel-air mixture neglecting the fuel carbon atoms due to the assumption that electron-impact dissociation reactions, which initiate the combustion, exhibit a greater reaction rate compared to those based on hydrocarbon thermal dissociation and therefore can be neglected in this work. Results show the production of the hydrogen (H), nitrogen (N), and oxygen (O) radicals and the radius of the initial discharge under different simulated engine operating conditions characterizing the role of a plasma corona effect for the induced chemical ignition in gasoline-powered engines.

Reducing green-house gases emission from light-duty vehicles is compulsory in order to slow down the climate change. The application of High Frequency Ignition systems based on the Corona discharge effect has shown the potential to extend the dilution limit of engine operating conditions promoting lower temperatures and faster combustion events, thus, higher thermal and indicating efficiency. Furthermore, predicting the behavior of Corona ignition devices against new sustainable fuel blends, including renewable hydrogen and biogas, is crucial in order to deal with the short-intermediate term fleet electric transition. The numerical evaluation of Corona-induced discharge radius and radical species under those conditions can be helpful in order to capture local effects that could be reached only with complex and expensive optical investigations. Using an extended version of the Corona one-dimensional code previously published by the present authors, the simulation of pure methane and different methane–hydrogen blends, and biogas–hydrogen blends mixed with air was performed. Each mixture was simulated both for 10% recirculated exhaust gas dilution and for its corresponding dilute upper limit, which was estimated by means of chemical kinetics simulations integrated with a custom misfire detection criterion.

Nowadays, with the rocketing of computational power, advanced numerical tools, and parallel computing, multi-scale simulations are becoming applied more and more to complex multi-physics industrial processes. One of the several challenging processes to be numerically modelled is gas phase nanoparticle synthesis. In an applied industrial scenario, the possibility to correctly estimate the geometric properties of the mesoscopic entities population (e.g., their size distribution) and to more precisely control the results is a crucial step to improve the quality and efficiency of the production. The “NanoDOME” project (2015–2018) aims to be an efficient and functional computational service to be applied in such processes. NanoDOME has also been refactored and upscaled during the H2020 Project “SimDOME”. To prove its reliability, we present here an integrated study between experimental data and NanoDOME’s predictions. The main goal is to finely investigate the effect of a reactor’s thermodynamic conditions on the thermophysical history of mesoscopic entities along the computational domain. To achieve this goal, the production of silver nanoparticles has been assessed for five cases with different experimental operative conditions of the reactor. The time evolution and final size distribution of nanoparticles have been simulated with NanoDOME by exploiting the method of moments and population balance model. The validation is performed by comparing NanoDOME’s calculations with the experimental data.

Background: Accurate prognoses are challenging in high-risk vascular conditions, such as abdominal aortic aneurysms, and limited diagnostic standards, decision-making criteria, and data semantics often hinder clinical reliability and impede diagnostics’ digital transition. This study aims to evaluate the performance, robustness, and usability of an automatic, replicable pipeline for aortic lumen surface reconstruction for pathological vessels. The goal is to provide a solid tool for geometric reconstruction to a more complex enhanced diagnostic framework. Methods: A U-Net convolutional neural network is trained using preoperative CTA scans, with 101 for model training and 14 for model testing, covering a wide anatomical and aortoiliac pathology spectrum. Validation included segmentation metric, robustness, reliability, and usability assessments. Performances are investigated by means of the test set’s prediction metrics for several instances of the model’s input. Clinical reliability is evaluated based on manual measurements performed by a vascular surgeon on the obtained 3D aortic lumen surfaces. Results: The test set is selected to cover a wide portion of aortoiliac pathologies. The algorithm demonstrated robustness with an average F1-score of 0.850 ± 0.120 and an intersection over union score of 0.760 ± 0.150 in the test set. Clinical reliability is assessed using the mean absolute errors for diameter and length measurements, respectively, of 1.73 mm and 2.27 mm. The 3D surface reconstruction demonstrated reliability, low processing times, and clinically valid reconstructions. Conclusions: The proposed algorithm can correctly reconstruct pathological vessels. Secondary aortoiliac pathologies are detected properly for challenging anatomies. To conclude, the proposed 3D reconstruction application to a digital, patient-specific diagnostic tool is, therefore, possible. Automatic replicable pipelines ensured the usability of the model’s outputs.

Background/Objectives: The aberrant subclavian artery (ASA) represents the most common congenital anomaly of the aortic arch, and is frequently associated with a Kommerell diverticulum, an aneurysmal dilation at the anomalous vessel origin. This condition carries a significant risk of rupture and dissection, and growing evidence indicates that local hemodynamic alterations may contribute to its development and progression. Computational Fluid Dynamics (CFD) provides a valuable non-invasive modality to assess biomechanical stresses and elucidate the pathophysiological mechanisms underlying these vascular abnormalities. Methods: In this study, twelve thoracic CT angiography scans were analyzed: six from patients with ASA and six from individuals with normal aortic anatomy. CFD simulations were performed using OpenFOAM, with standardized boundary conditions applied across all cases to isolate the influence of anatomical differences in flow behavior. Four key hemodynamic metrics were evaluated—Wall Shear Stress (WSS), Oscillatory Shear Index (OSI), Drag Forces (DF), and Turbulent Viscosity Ratio (TVR). The aortic arch was subdivided into Ishimaru zones 0–3, with an adapted definition accounting for ASA anatomy. For each region, time- and space-averaged quantities were computed to characterize mean values and oscillatory behavior. Conclusions: The findings demonstrate that patients with ASA exhibit markedly altered hemodynamics in zones 1–3 compared to controls, with consistently elevated WSS, OSI, DF, and TVR. The most pronounced abnormalities occurred in zones 2–3 near the origin of the aberrant vessel, where disturbed flow patterns and off-axis mechanical forces were observed. These features may promote chronic wall stress, endothelial dysfunction, and localized aneurysmal degeneration. Notably, two patients (M1 and M6) displayed particularly elevated drag forces and TVR in the distal arch, correlating with the presence of a distal aneurysm and right-sided arch configuration, respectively. Overall, this work supports the hypothesis that aberrant hemodynamics contribute to Kommerell diverticulum formation and progression, and highlights the CFD’s feasibility for clarifying disease mechanisms, characterizing flow patterns, and informing endovascular planning by identifying hemodynamically favorable landing zones.