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This paper aims to describe the outcomes of the Main10ance project, which focused on developing an integrated HBIM-GIS platform to support the maintenance and conservation plans for the historic built heritage. The pilot case is the UNESCO complex of the Sacri Monti, located in northern Italy and Switzerland, which consists of groups of chapels and architectural artifacts holding significant historical and cultural value. Given their importance, specific maintenance plans involving multiple stakeholders and specialists are required. This study focuses on creating a unified system that semantically and spatially describes the architectural elements of the case study and the surrounding context and indoor assets. After a 3D integrated metric survey and the related data processing, parametric 3D models were created in a BIM environment, and a spatial database was developed to incorporate both geometric and alphanumeric entities. The database enables interoperability among different actors and domains, gathering heritage-related information crucial for restoration and conservation purposes. Additionally, the custom 4MAIN10ANCE web platform was developed with different levels of details (LODs), enabling the retrieval of both 2D and 3D data and establishing connections between the BIM models of the chapels and associated information.

The use of composite materials in several sectors, such as aeronautics and automotive, has been gaining distinction in recent years. However, due to their high costs, as well as unique characteristics, consequences of their heterogeneity, they present challenging gaps to be studied. As a result, the finite element method has been used as a way to analyze composite materials subjected to the most distinctive situations. Therefore, this work aims to approach the modeling of composite materials, focusing on material properties, failure criteria, types of elements and main application sectors. From the modeling point of view, different levels of modeling—micro, meso and macro, are presented. Regarding properties, different mechanical characteristics, theories and constitutive relationships involved to model these materials are presented. The text also discusses the types of elements most commonly used to simulate composites, which are solids, peel, plate and cohesive, as well as the various failure criteria developed and used for the simulation of these materials. In addition, the present article lists the main industrial sectors in which composite material simulation is used, and their gains from it, including aeronautics, aerospace, automotive, naval, energy, civil, sports, manufacturing and even electronics.

A great proportion of the existing architectural heritage, including historical and monumental constructions, is made of brick/block masonry. This material shows a strong anisotropic behaviour resulting from the specific arrangement of units and mortar joints, which renders the accurate simulation of the masonry response a complex task. In general, mesoscale modelling approaches provide realistic predictions due to the explicit representation of the masonry bond characteristics. However, these detailed models are very computationally demanding and mostly unsuitable for practical assessment of large structures. Macroscale models are more efficient, but they require complex calibration procedures to evaluate model material parameters. This paper presents an advanced continuum macroscale model based on a two-scale nonlinear description for masonry material which requires only simple calibration at structural scale. A continuum strain field is considered at the macroscale level, while a 3D distribution of embedded internal layers allows for the anisotropic mesoscale features at the local level. A damage-plasticity constitutive model is employed to mechanically characterise each internal layer using different material properties along the two main directions on the plane of the masonry panel and along its thickness. The accuracy of the proposed macroscale model is assessed considering the response of structural walls previously tested under in-plane and out-of-plane loading and modelled using the more refined mesoscale strategy. The results achieved confirm the significant potential and the ability of the proposed macroscale description for brick/block masonry to provide accurate and efficient response predictions under different monotonic and cyclic loading conditions.

The issue of urban regeneration has taken a strong centrality in recent European and national debates, particularly applied in the transformation of suburban settlements. Urban regeneration practices represent a potential tool to steer transformations toward criteria of environmental sustainability and resilience, resulting in reduced land consumption from decreased demand for new urbanization, and increased urban quality and collective well-being. The redevelopment of public housing requires a comprehensive rethinking of its use pattern and integrated and social cohesion tools to act with targeted measures in situations of marginality and physical, social and economic degradation. Working on these pieces of the city becomes fertile ground and a catalyst for opportunities in terms of regeneration of the urban fabric, with benefits and positive impacts, from the local level to a broader scale, driving ambitious measures to combat climate change. The research, articulated on closely related layers − public space and private space, outdoor space and indoor space − from the urban to the architectural scale aims to formulate meta-project guidelines applied to the case study of San Basilio, a suburban settlement of public housing within the city of Rome.

This paper analyses the complexity of electroencephalogram (EEG) signals in different temporal scales for the analysis and classification of focal and non-focal EEG signals. Futures from an original multiscale permutation Lempel–Ziv complexity measure (MPLZC) were obtained. MPLZC measure combines a multiscale structure, ordinal analysis, and permutation Lempel–Ziv complexity for quantifying the dynamic changes of an electroencephalogram (EEG). We also show the dependency of MPLZC on several straight-forward signal processing concepts, which appear in biomedical EEG activity via a set of synthetic signals. The main material of the study consists of EEG signals, which were obtained from the Bern-Barcelona EEG database. The signals were divided into two groups: focal EEG signals (n = 100) and non-focal EEG signals (n = 100); statistical analysis was performed by means of non-parametric Mann–Whitney test. The mean value of MPLZC results in the non-focal group are significantly higher than those in the focal group for scales above 1 (p < 0.05). The result indicates that the non-focal EEG signals are more complex. MPLZC feature sets are used for the least squares support vector machine (LS-SVM) classifier to classify into the focal and non-focal EEG signals. Our experimental results confirmed the usefulness of the MPLZC method for distinguishing focal and non-focal EEG signals with a classification accuracy of 86%.

Prediction of the acoustic performance of 3D printed materials is investigated at normal and grazing incidence. A direct numerical (microscopic) simulation that solves the full set of Navier–Stokes equations is used as a reference. It is compared with a macroscopic approach in which the material is represented by an equivalent fluid. The materials have a periodic microstructure, consisting either of a single network of spherical or cubic cavities connected by cylindrical channels or of a double-nested network. The samples are printed using the stereolithography technique and are tested using an impedance tube and a duct test bench. For single network geometries, the results of sound absorption at normal and grazing incidence predicted using the equivalent fluid approach are in good agreement with those obtained by the microscopic approach. Comparisons with impedance tube measurements confirm that both approaches can accurately predict the absorption coefficient of the samples. For the in-duct liner configuration, the transmission loss measurements and predictions show similar evolution with frequency change, despite the discrepancy in amplitude. For the double network geometry, the equivalent fluid approach cannot exactly reproduce the results obtained with the direct numerical simulation. Finally, while the predictions with the microscopic approach provide a good match with the impedance tube measurements, only a poor agreement is obtained using the duct testing bench.

Collapse of granular material is usually accompanied by long run-out granular flows in natural hazards, e.g. rock/debris flow and snow avalanches. This paper presents a novel multi-scale approach for modelling granular column collapse with large deformation. This approach employs the smoothed particle hydrodynamics (SPH) method to solve large deformation boundary value problems, while using a micromechanical model to derive the nonlinear material response required by the SPH method. After examining the effect of initial cell size, the proposed approach is subsequently applied to simulate the flow of granular column in a rectangular channel at a low water content by varying the initial aspect ratio. The numerical results show good agreement with various experimental observations on both collapse process and final deposit morphology. Furthermore, the meso-scale behaviour is also captured owing to the advantages of the micromechanical model. Finally, it was demonstrated that the novel multi-scale approach is helpful in improving the understanding of granular collapse and should be an effective computational tool for the analysis of real-scale granular flow.

The development of robust mathematical models could provide the necessary tools for a more rapid, efficient, and reliable spouted bed technology development. Computer simulations can be very useful to aid this design and scale-up process: firstly, they can contribute to obtain a fundamental insight into their complex dynamic behavior by understanding the elementary physical principles such as drag, friction, dissipation etc.; secondly, the simulations can be used as a design tool where the ultimate goal is to have a numerical model with predictive capabilities for gas-particle flows at engineering scale. Clearly, one single simulation method will not be able to achieve this goal, but a hierarchy of methods modelling phenomena on different length and time scales can achieve this. The most fruitful approach will be when they are simultaneously followed, so that they can mutually benefit from each other. In this sense, this paper presents a review of the current state of the art of modelling on spouted and spout-fluid beds through an analysis of recent literature following a multiscale approach (molecular and particle, lab, plant and industrial scale). The main features of the different scales together with their current limits are discussed and specific topics are highlighted as paths that still need to be explored. In summary, the paper aims to define the theoretical setline and the basis of improvement that would lead to a robust multiscale model with solid links between micro and macroscopic phenomena. If done with the correct balance between accuracy and computational costs it will gear SB towards their reliable and successful implementation.

In neuroscience, functional connectivity is a concept that can be mathematically formulated as a graph of interactions between oscillatory brain rhythms and individual neuronal activity. Typically, each graph corresponds to a cognitive state and provides insight into higher cognitive processes, such as learning. However, a model or method to assess directed interactions within and across brain oscillations and individual neuronal activity is lacking. In this article, we propose a new model called HM-MVAR (Heterogeneous Multiscale Multivariate Autoregressive) that represents linear combinations of neural interaction patterns. These patterns include phase-locking, where the amplitude of one signal is modulated by the phase of another, and power-triggered phenomena, where the amplitude of one signal is modulated by the amplitude of another. Due to the multiscale structure, we use a block version of stationarity to exhibit conditions under which the process obeying the HM-MVAR model exists and is stationary. We also propose a data-driven weighted LASSO estimator based on martingale exponential deviation inequalities, which may have intrinsic interest in probability theory. We prove that our estimator satisfies an oracle inequality and present its strong performance in realistic simulations. Finally, applying our model and method on a publicly available multiscale electrophysiological data set, we recover interactions described in the literature but also uncover new phenomena of potential interest.

Aluminium plate-fin heat exchangers are widely used in automotive, aerospace, and other industrial applications. Extensive research has been conducted on these coolers, yet accurate predictive tools for their thermo-hydraulic performance are still lacking, due to the wide variety of geometric parameters and working fluids involved. This work proposes an original approach based purely on physical principles and established models, combining detailed numerical models for the extended surfaces and manifolds, with global models aimed at accurately evaluating overall head losses and heat transfer rates in plate-fin heat exchangers. Extended surfaces are studied by means of computational models of unitary fin modules under fully developed flow conditions. Entrance effects are analysed through dedicated numerical models. Numerical results on extended surfaces are extended to whole heat exchangers by global models for heat transfer and head losses, based on the ε−NTU method and the Darcy–Weisbach equation, respectively. The proposed approach is presented and validated through the analysis of a case study comprising several heat exchangers featuring different geometries and working fluids. Numerically derived heat transfer rates and head losses are compared with experimental data showing maximum deviations of ±20% for most of the tested configurations, highlighting the strength of the proposed modelling methodology.