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A new finite volume (FV) method is proposed for the solution of convection‐diffusion equations defined on 2D convex domains of general shape. The domain is approximated by a polygonal region; a structured non‐uniform mesh is defined; the domain is partitioned in control volumes. The conservative form of the problem is solved by imposing the law to be verified on each control volume. The dependent variable is approximated to the second order by means of a quadratic profile. When, for the hyperbolic equation, discontinuities are present, or when the gradient of the solution is very high, a cubic profile is defined in such a way that it enjoys unidirectional monotonicity. Numerical results are given.

In this paper new cubic v‐splines monotonic one‐dimensional profiles are presented, for the finite volume solution of convection‐diffusion problems. By studying the profile in normalized variables, some weight functions have been determined for the profile. Being free of the requirement that the volumes be equal, the volume size can be reduced where needed. Numerical properties of the proposed method were formally analysed and are confirmed by numerical examples included here.

This study aims to develop a realistic 3D printing-based simulator for the training and planning of the left atrial appendage occlusion (LAAO) to be used in the cath lab.

Starting from a pre-operative computed tomography dataset of a patient already treated with LAAO, the model was obtained, consisting in the right and left heart, opportunely assembled to replicate the position and orientation of the patient's anatomy while lying on the cath lab table. Different 3D printing techniques and materials were used to mimic the interaction between the cardiac tissue and the clinical instrumentation. The simulator was tested in the cath lab under proper image guidance by three LAAO expert operators. The clinicians were required to assign a score in terms of realism to each material used to fabricate the fossa ovalis and the LAA.

The simulated interventions were successfully performed by the operators, who were able to navigate in the system and release the occluder device as during a real procedure. The intraoperative images acquired during the simulations were highly comparable with data from a real intervention, with a mean percentage difference below 10%.

This study demonstrated the feasibility of the proposed simulator to faithfully replicate the LAAO procedure and its potentiality to be used for multiple purposes, including the training of the young clinicians, the evaluation of the most complicated cases and the design of novel occluder devices, in a fully realistic setting.

The development of new advanced materials, such as photopolymerizable resins for use in stereolithography (SLA) and Ti6Al4V manufacture via selective laser melting (SLM) processes, have gained significant attention in recent years. Their accuracy, multi-material capability and application in novel fields, such as implantology, biomedical, aviation and energy industries, underscore the growing importance of these materials. The purpose of this study is oriented toward the application of new advanced materials in stent manufacturing realized by 3D printing technologies.

The methodology for designing personalized medical devices, implies computed tomography (CT) or magnetic resonance (MR) techniques. By realizing segmentation, reverse engineering and deriving a 3D model of a blood vessel, a subsequent stent design is achieved. The tessellation process and 3D printing methods can then be used to produce these parts. In this context, the SLA technology, in close correlation with the new types of developed resins, has brought significant evolution, as demonstrated through the analyses that are realized in the research presented in this study. This study undertakes a comprehensive approach, establishing experimentally the characteristics of two new types of photopolymerizable resins (both undoped and doped with micro-ceramic powders), remarking their great accuracy for 3D modeling in die-casting techniques, especially in the production process of customized stents.

A series of analyses were conducted, including scanning electron microscopy, energy-dispersive X-ray spectroscopy, mapping and roughness tests. Additionally, the structural integrity and molecular bonding of these resins were assessed by Fourier-transform infrared spectroscopy–attenuated total reflectance analysis. The research also explored the possibilities of using metallic alloys for producing the stents, comparing the direct manufacturing methods of stents’ struts by SLM technology using Ti6Al4V with stent models made from photopolymerizable resins using SLA. Furthermore, computer-aided engineering (CAE) simulations for two different stent struts were carried out, providing insights into the potential of using these materials and methods for realizing the production of stents.

This study covers advancements in materials and additive manufacturing methods but also approaches the use of CAE analysis, introducing in this way novel elements to the domain of customized stent manufacturing. The emerging applications of these resins, along with metallic alloys and 3D printing technologies, have brought significant contributions to the biomedical domain, as emphasized in this study. This study concludes by highlighting the current challenges and future research directions in the use of photopolymerizable resins and biocompatible metallic alloys, while also emphasizing the integration of artificial intelligence in the design process of customized stents by taking into consideration the 3D printing technologies that are used for producing these stents.

The performance of three frequently used level set-based segmentation methods is examined for the purpose of defining features and boundary conditions for image-based Eulerian fluid and solid mechanics models. The focus of the evaluation is to identify an approach that produces the best geometric representation from a computational fluid/solid modeling point of view. In particular, extraction of geometries from a wide variety of imaging modalities and noise intensities, to supply to an immersed boundary approach, is targeted.

Two- and three-dimensional images, acquired from optical, X-ray CT, and ultrasound imaging modalities, are segmented with active contours, k-means, and adaptive clustering methods. Segmentation contours are converted to level sets and smoothed as necessary for use in fluid/solid simulations. Results produced by the three approaches are compared visually and with contrast ratio, signal-to-noise ratio, and contrast-to-noise ratio measures.

While the active contours method possesses built-in smoothing and regularization and produces continuous contours, the clustering methods (k-means and adaptive clustering) produce discrete (pixelated) contours that require smoothing using speckle-reducing anisotropic diffusion (SRAD). Thus, for images with high contrast and low to moderate noise, active contours are generally preferable. However, adaptive clustering is found to be far superior to the other two methods for images possessing high levels of noise and global intensity variations, due to its more sophisticated use of local pixel/voxel intensity statistics.

It is often difficult to know a priori which segmentation will perform best for a given image type, particularly when geometric modeling is the ultimate goal. This work offers insight to the algorithm selection process, as well as outlining a practical framework for generating useful geometric surfaces in an Eulerian setting.

Over the past decade, in Europe the attention of scholars, as well as the focus of the political debate on the ‘urban social cohesion’, has become increasingly oriented to the issue of immigrants’ spatial segregation. This concern has gradually led to the promotion of urban policies oriented to fight against the residential segregation on ethnic basis, although the effects of residential concentration per se and social inclusion are not clearly identified, and minor attention has been devoted to understand and fight against the casual factors leading immigrants to occupy the most residual part of the social and physical urban space. By proposing a comparative analysis of two urban contexts – Copenhagen, Milan – that are different in terms of immigrants’ presence and legal status, as well as labour market integration and general welfare regime, the study explores some mechanisms promoting the social and spatial marginalization of immigrants in Europe. It also analyses the most important urban policies dealing with residential segregation, evaluating their capacity of facing the phenomenon or promoting (unexpected) negative consequences.

The purpose of this paper is to numerically study blood flow through a subject‐specific carotid artery with a moderately severe stenosis, also to thoroughly analyse the wall shear stress (WSS), oscillatory shear index (OSI) and WSS angular deviation (WSSAD). One of the important aspects of this study is the investigation on the influence of the extensions attached to the domain outlets.

The segmentation of the carotid artery is carried out using a deformable model based on a level set method. A geometric potential force (GPF) is employed to deform the level set to obtain the carotid artery geometry. The initial surface meshing is generated using an advanced marching cubes (MC) method, before improving the quality of the surface mesh via a number of mesh cosmetic steps. The volume mesh generation has two parts. In the first part, a quasi‐structured, boundary layer mesh is generated in the vicinity of the geometry walls. The second part of the meshing involves unstructured tetrahedral meshing of the inner part of the geometry. After the meshing stage, the flow boundary conditions are generated by numerically solving the Helmholtz equation in both space and time. Finally, the explicit characteristic‐based split (CBS) method is employed in a parallel environment to produce a detailed analysis of wall quantities.

In general, WSS is very high in the vicinity of the carotid artery apex and in the proximity of the stenosis. From the results obtained, it is clear that the influence of outlet domain extension is marginal. While the peak instantaneous WSS differs by a maximum of 5.7 per cent, the time‐averaged WSS difference due to extended domain is only 1.3 per cent. Two other derived parameters are also examined in the paper, the oscillating shear index and the WSSAD. Both these quantities also display minor or negligible differences due to domain extension.

It has been perceived that domain extension is essential to avoid wrong application of boundary conditions. The results obtained, however, conclusively show that the outlet domain extension has only a moderate influence on WSS. Thus, outlet extension to the domains may not be essential for arterial blood flows. It is also observed that the dramatic values of peak WSS obtained near the stenosis is the result of high resolution mesh along with boundary layers used in this study. Both the outcomes represent the originality of this paper.

Emergency departments (ED) are faced with the challenge of capacity planning that caused by the high demand for patients and limited resources. Consequently, inadequate resources lead to increased delays, impacts on the quality of care and increase the health-care costs. Such circumstances necessitate utilizing operational research modules, such as the Markov decision process (MDP) to enable better decision-making. The purpose of this paper is to demonstrate the applicability and usage of MDP on ED.

The adoption of MDP provides invaluable insights into system operations based on the different system states (e.g. very busy to unoccupied) to ensure optimal assigning of resources and reduced costs. In this paper, a descriptive health system model based on the MDP is presented, and a numerical example is illustrated to elaborate its appropriateness in optimal policy decision determination.

Faced with numerous decisions, hospital managers have to ensure that the appropriate technique is used to minimize any undesired outcomes. MDP has been shown to be a robust approach which provides support to the critical decision-making processes. Additionally, MDP also provides insights on the associated costs which enable the hospital managers to efficiently allocate resources ensuring quality health care and increased throughput while minimizing costs.

Applying MDP in the ED is a unique and good starting. MDP is powerful tool helps in making a decision in the critical situations, and the ED needs such tool.

This paper aims at showing that the finite element method is the most important numerical tool to analyse bio‐solids or bio‐fluids because of the constitutive complexity and unusual clinical input data and requirements involved. These features are absolutely mandatory and modify the mentality of an expert of FEM when he wants to contribute really to the progress of medical practice in their several forms, from biological basis to the surgical assistance. In this context, a clear view of the hierarchic importance of the phenomena involved is necessary to reply correctly to medical operators and to choose the right level of scale. While a scholarly culture of FEM and relative developments have to appeal the attention of biomedical engineers, at the same time their attention mainly is focused on the problem to solve, which must be validated clinically and experimentally. So while convergence remain a typical goal of the analyst, accuracy must be compared with the medical sensitivity. To do this, some physical conditions, less important in other application fields, as the boundary conditions, must be modelled in order to avoid that any model refinement gives unappreciable precision while tends to disregard what a clinician or a surgeon is able to understand and to use in the context of his professional practice. Setting up correct boundary conditions is an emblematic topic because it concerns a typical approach of computational methods applied to biomedical engineering which must consider two separate scale into analysis or a design approach. When a district of the body is to be analysed, the main goal should be to define correctly the subdomain that the district represents with respect to the whole and then to analyse other subdomains inside, at a level more and more micro, as into a system of Chinese boxes. When a medical device is to be designed a systemic view must be acquired. In this paper, we will start from this underlying feature concerning just FEM applications of a knee design carried out by the research staff of the Laboratory of Biological Structure Mechanics. Then other uses of FEM will be described as analysis fragments through problems studied by the authors and referenced in bibliography.

This study aims at enhancing the performance of a 16-stage axial compressor and improving the operating stability. The adopted approaches for upgrading the compressor are artificial neural network, optimization algorithms and computational fluid dynamics.

The process starts with developing several data sets for certain 2D sections by means of training several artificial neural networks (ANNs) as surrogate models. Afterward, the trained ANNs are applied to the 3D shape optimization along with parametrization of the blade stacking line. Specifying the significant design parameters, a wide range of geometrical variations are considered by implementation of appropriate number of design variables. The optimized shapes are analyzed by applying computational fluid dynamic to obtain the best geometry.

3D optimal results show improvements, especially in the case of decreasing or elimination of near walls corner separations. In addition, in comparison with the base geometry, numerical optimization shows an increase of 1.15 per cent in total isentropic efficiency in the first four stages, which results in 0.6 per cent improvement for the whole compressor, even while keeping the rest of the stages unchanged. To evaluate the numerical results, experimental data are compared with obtained data from simulation. Based on the results, the highest absolute relative deviation between experimental and numerical static pressure is approximately 7.5 per cent.

The blades geometry of an axial compressor used in a heavy-duty gas turbine is optimized by applying artificial neural network, and the results are compared with the base geometry numerically and experimentally.