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This study aims to analyse the non-linear losses of a porous media (stack) composed by parallel plates and inserted in a resonator tube in oscillatory flows by proposing numerical correlations between pressure gradient and velocity.

The numerical correlations origin from computational fluid dynamics simulations, conducted at the microscopic scale, in which three fluid channels representing the porous media are taken into account. More specifically, for a specific frequency and stack porosity, the oscillating pressure input is varied, and the velocity and the pressure-drop are post-processed in the frequency domain (Fast Fourier Transform analysis).

It emerges that the viscous component of pressure drop follows a quadratic trend with respect to velocity inside the stack, while the inertial component is linear also at high-velocity regimes. Furthermore, the non-linear coefficient b of the correlation ax + bx² (related to the Forchheimer coefficient) is discovered to be dependent on frequency. The largest value of the b is found at low frequencies as the fluid particle displacement is comparable to the stack length. Furthermore, the lower the porosity the higher the Forchheimer term because the velocity gradients at the stack geometrical discontinuities are more pronounced.

The main novelty of this work is that, for the first time, non-linear losses of a parallel plate stack are investigated from a macroscopic point of view and summarised into a non-linear correlation, similar to the steady-state and well-known Darcy–Forchheimer law. The main difference is that it considers the frequency dependence of both Darcy and Forchheimer terms. The results can be used to enhance the analysis and design of thermoacoustic devices, which use the kind of stacks studied in the present work.

This study aims to develop an assessment strategy for fire damaged infrastructures based on the implementation of quick diagnostic techniques and consistent interpretation procedures, so to determine the residual safety margin and any need for repair works.

In this perspective, several tailored non-destructive test (NDT) methods have been developed in the past two decades, providing immediate results, with no need for time-consuming laboratory analyses. Moreover, matching their indications with the calculated effects of a tentative fire scenario allows harmonizing distinct pieces of evidence in the coherent physical framework of fire dynamics and heat transfer.

This approach was followed in the investigations on a concrete overpass in Verona (Italy) after a coach violently impacted one supporting pillar and caught fire in 2017. Technical specifications of the vehicle made it possible to bound the acceptable ranges for fire load and maximum rate of heat release, while surveillance video footage indicated the duration of the burning stage. Some established NDT methods (evaluation of discolouration, de-hydroxylation and rebar hardness) were implemented, together with advanced ultrasonic tests based on pulse refraction and pulse-echo tomography.

The results clearly showed the extension of the most damaged area at the intrados of the box girders and validated the maximum heating depth, as predicted by numerical analysis of the heat transient ensuing from the localized fire model.

This article introduces the Special Issue on Sustainable Management of Heritage Buildings in long-term perspective.

It starts by reviewing the gaps in knowledge and practice which led to the creation and implementation of the research project SyMBoL—Sustainable Management of Heritage Buildings in long-term perspective funded by the Norwegian Research Council over the 2018–2022 period. The SyMBoL project is the motivation at the base of this special issue.

The editorial paper briefly presents the main outcomes of SyMBoL. It then reviews the contributions to the Special Issue, focussing on the connection or differentiation with SyMBoL and on multidisciplinary findings that address some of the initial referred gaps.

The article shortly summarizes topics related to sustainable preservation of heritage buildings in time of reduced resources, energy crisis and impacts of natural hazards and global warming. Finally, it highlights future research directions targeted to overcome, or partially mitigate, the above-mentioned challenges, for example, taking advantage of no sestructive techniques interoperability, heritage building information modelling and digital twin models, and machine learning and risk assessment algorithms.

This study aims to carry out an investigation of design approaches that should be used for the design of unconventional, innovative transmission system for construction yards to privilege a smooth behaviour efficiency, and the use of innovative production techniques. Results are quite surprising, as with a proper method it is possible to demonstrate that a cycloidal drive with Wolfrom topology should be an interesting solution for the proposed application.

With a functional approach, also considering materials and specifications related to the investigated application, it is possible to demonstrate that possible optimal solutions should be quite different respect to the ones that can be suggested with a conventional approach. In particular for proposed applications constraints related to encumbrances, the choice of new material has led to the innovative unconventional choice of a Wolfrom cycloidal speed reducer.

Provided solution is innovative respect current state of the art for machine currently used in construction yards: in terms of adopted transmission layout; in terms of chosen materials, resulting in an innovative solution.

Current research has strong implications on the adoption of polimeric materials for the construction of reliable transmission for harsh industrial environment as the proposed case study (concrete mixer for construction yard).

Proposed transmission system is absolutely original and innovative respect current state of art also considering proposed materials and consequently production methods. This is an example of transmission designed to be built with polymeric materials by optimizing chosen topology respect to chosen material.

This paper aims to discuss the classification of targets based on their radar cross-section (RCS). The wavelength, the dimensions of the targets and the distance from the antenna are in the order of 1 mm, 1 m and 10 m, respectively.

The near-field RCS is considered, and the physical optics approximation is used for its numerical calculation. To model real scenarios, the authors assume that the incident angle is a random variable within a narrow interval, and repeated observations of the RCS are made for its random realizations. Then, the histogram of the RCS is calculated from the samples. The authors use a nearest neighbor rule to classify conducting plates with different shapes based on their RCS histogram.

This setup is considered as a simple model of traffic road sign classification by millimeter-wavelength radar. The performance and limitations of the algorithm are demonstrated through a set of representative numerical examples.

The proposed method extends the existing tools by using near-field RCS histograms as target features to achieve a classification algorithm.

In the wine industry, maintaining superior quality standards is crucial to meet the expectations of both producers and consumers. Traditional approaches to assessing wine quality involve labor-intensive processes and rely on the expertise of connoisseurs proficient in identifying taste profiles and key quality factors. In this research, we introduce an innovative and efficient approach centered on the analysis of volatile organic compounds (VOCs) signals using an electronic nose, thereby empowering nonexperts to accurately assess wine quality.

To devise an optimal algorithm for this purpose, we conducted four computational experiments, culminating in the development of a specialized deep learning network. This network seamlessly integrates 1D-convolutional and long-short-term memory layers, tailor-made for the intricate task at hand. Rigorous validation ensued, employing a leave-one-out cross-validation methodology to scrutinize the efficacy of our design.

The outcomes of these e-demonstrates were subjected to meticulous evaluation and analysis, which unequivocally demonstrate that our proposed architecture consistently attains promising recognition accuracies, ranging impressively from 87.8% to an astonishing 99.41%. All this is achieved within a remarkably brief timeframe of a mere 4 seconds. These compelling findings have far-reaching implications, promising to revolutionize the assessment and tracking of wine quality, ultimately affording substantial benefits to the wine industry and all its stakeholders, with a particular focus on the critical aspect of VOCs signal analysis.

This research has not been published anywhere else.