NMR, Metabonomics and Molecular Profiles: Applications to the Quality Assessment of Foodstuffs

Nuclear Magnetic Resonance (NMR) is a branch of spectroscopy that is based on the fact that many atomic nuclei may be oriented by a strong magnetic field and will absorb radiofrequency radiation at characteristic frequencies. The parameters that can be measured on the resulting spectral lines (line positions, intensities, line widths, multiplicities and transients in time-dependent experi-ments) can be interpreted in terms of molecular structure, conformation, molecular motion and other rate processes. In this way, high resolution (HR) NMR allows performing qualitative and quantitative analysis of samples in solution, in order to determine the structure of molecules in solution and not only. In the past, high-field NMR spectroscopy has mainly concerned with the elucidation of chemical structure in solution, but today is emerging as a powerful exploratory tool for probing biochemical and physical processes. It represents a versatile tool for the analysis of foods. In literature many NMR studies have been reported on different type of food such as wine, olive oil, coffee, fruit juices, milk, meat, egg, starch granules, flour, etc using different NMR techniques. Traditionally, univariate analytical methods have been used to ex-plore spectroscopic data. This method is useful to measure or to se-lect a single descriptive variable from the whole spectrum and , at the end, only this variable is analyzed. This univariate methods ap-proach, applied to HR-NMR data, lead to different problems due especially to the complexity of an NMR spectrum. In fact, the lat-ter is composed of different signals belonging to different mole-cules, but it is also true that the same molecules can be represented by different signals, generally strongly correlated. The univariate methods, in this case, takes in account only one or a few variables, causing a loss of information. Thus, when dealing with complex samples like foodstuff, univariate analysis of spectra data results not enough powerful. Spectra need to be considered in their wholeness and, for analysing them, it must be taken in consideration the whole data matrix: chemometric methods are designed to treat such multivariate data. Multivariate data analysis is used for a number of distinct, differ-ent purposes and the aims can be divided into three main groups: • data description (explorative data structure modelling of any ge-neric n-dimensional data matrix, PCA for example); • regression and prediction (PLS); • classification and prediction of class belongings for new samples (LDA and PLS-DA and ECVA). The aim of this PhD thesis was to verify the possibility of identify-ing and classifying plants or foodstuffs, in different classes, based on the concerted variation in metabolite levels, detected by NMR spectra and using the multivariate data analysis as a tool to inter-pret NMR information. It is important to underline that the results obtained are useful to point out the metabolic consequences of a specific modification on foodstuffs, avoiding the use of a targeted analysis for the different metabolites. The data analysis is performed by applying chemomet-ric multivariate techniques to the NMR dataset of spectra acquired. The research work presented in this thesis is the result of a three years PhD study. This thesis reports the main results obtained from these two main activities: A1) Evaluation of a data pre-processing system in order to mini-mize unwanted sources of variations, due to different instrumental set up, manual spectra processing and to sample preparations arte-facts; A2) Application of multivariate chemiometric models in data analy-sis.

Interpreting Judgements using Knowledge Representation Methods and Computational Models of Argument

The goal of the present research is to define a Semantic Web framework for precedent modelling, by using knowledge extracted from text, metadata, and rules, while maintaining a strong text-to-knowledge morphism between legal text and legal concepts, in order to fill the gap between legal document and its semantics. The framework is composed of four different models that make use of standard languages from the Semantic Web stack of technologies: a document metadata structure, modelling the main parts of a judgement, and creating a bridge between a text and its semantic annotations of legal concepts; a legal core ontology, modelling abstract legal concepts and institutions contained in a rule of law; a legal domain ontology, modelling the main legal concepts in a specific domain concerned by case-law; an argumentation system, modelling the structure of argumentation. The input to the framework includes metadata associated with judicial concepts, and an ontology library representing the structure of case-law. The research relies on the previous efforts of the community in the field of legal knowledge representation and rule interchange for applications in the legal domain, in order to apply the theory to a set of real legal documents, stressing the OWL axioms definitions as much as possible in order to enable them to provide a semantically powerful representation of the legal document and a solid ground for an argumentation system using a defeasible subset of predicate logics. It appears that some new features of OWL2 unlock useful reasoning features for legal knowledge, especially if combined with defeasible rules and argumentation schemes. The main task is thus to formalize legal concepts and argumentation patterns contained in a judgement, with the following requirement: to check, validate and reuse the discourse of a judge - and the argumentation he produces - as expressed by the judicial text.

Soil-structure interaction during tunnelling in urban area: observations and 3D numerical modelling

This work illustrates a soil-tunnel-structure interaction study performed by an integrated,geotechnical and structural,approach based on 3D finite element analyses and validated against experimental observations.The study aims at analysing the response of reinforced concrete framed buildings on discrete foundations in interaction with metro lines.It refers to the case of the twin tunnels of the Milan (Italy) metro line 5,recently built in coarse grained materials using EPB machines,for which subsidence measurements collected along ground and building sections during tunnelling were available.Settlements measured under freefield conditions are firstly back interpreted using Gaussian empirical predictions. Then,the in situ measurements’ analysis is extended to include the evolving response of a 9 storey reinforced concrete building while being undercrossed by the metro line.In the finite element study,the soil mechanical behaviour is described using an advanced constitutive model. This latter,when combined with a proper simulation of the excavation process, proves to realistically reproduce the subsidence profiles under free field conditions and to capture the interaction phenomena occurring between the twin tunnels during the excavation. Furthermore, when the numerical model is extended to include the building, schematised in a detailed manner, the results are in good agreement with the monitoring data for different stages of the twin tunnelling. Thus, they indirectly confirm the satisfactory performance of the adopted numerical approach which also allows a direct evaluation of the structural response as an outcome of the analysis. Further analyses are also carried out modelling the building with different levels of detail. The results highlight that, in this case, the simplified approach based on the equivalent plate schematisation is inadequate to capture the real tunnelling induced displacement field. The overall behaviour of the system proves to be mainly influenced by the buried portion of the building which plays an essential role in the interaction mechanism, due to its high stiffness.

Neural network modelling of the wave-structure interaction processes

This thesis presents a new Artificial Neural Network (ANN) able to predict at once the main parameters representative of the wave-structure interaction processes, i.e. the wave overtopping discharge, the wave transmission coefficient and the wave reflection coefficient. The new ANN has been specifically developed in order to provide managers and scientists with a tool that can be efficiently used for design purposes. The development of this ANN started with the preparation of a new extended and homogeneous database that collects all the available tests reporting at least one of the three parameters, for a total amount of 16’165 data. The variety of structure types and wave attack conditions in the database includes smooth, rock and armour unit slopes, berm breakwaters, vertical walls, low crested structures, oblique wave attacks. Some of the existing ANNs were compared and improved, leading to the selection of a final ANN, whose architecture was optimized through an in-depth sensitivity analysis to the training parameters of the ANN. Each of the selected 15 input parameters represents a physical aspect of the wave-structure interaction process, describing the wave attack (wave steepness and obliquity, breaking and shoaling factors), the structure geometry (submergence, straight or non-straight slope, with or without berm or toe, presence or not of a crown wall), or the structure type (smooth or covered by an armour layer, with permeable or impermeable core). The advanced ANN here proposed provides accurate predictions for all the three parameters, and demonstrates to overcome the limits imposed by the traditional formulae and approach adopted so far by some of the existing ANNs. The possibility to adopt just one model to obtain a handy and accurate evaluation of the overall performance of a coastal or harbor structure represents the most important and exportable result of the work.

Modelling UV response of biomolecules: from electronic structure to ab-initio dynamics.

The interaction of organic chromophores with light initiates ultrafast processes in the timescale of femtoseconds. An atomistic understanding of the mechanism driving such photoinduced reactions opens up the door to exploit them for our benefit. This thesis studies the interactions of ultraviolet light with the DNA/RNA molecules and the amino-acid tryptophan. Using some of the most accurate electronic structure methods and sophisticated environmental modelling, the works documented herein enable quantitative comparisons with cutting-edge experimental data. The relaxation pathways undertaken by the excited molecule are revealed through static and dynamical investigations of the excited-state potential energy surface. The profound role played by the dynamic response of the environment to guide the excitation in these timescales is addressed thoroughly.

Reduced-order modelling, circuit-level design and SOI fabrication of microelectromechanical resonators

This thesis deals with two important research aspects concerning radio frequency (RF) microresonators and switches. First, a new approach for compact modeling and simulation of these devices is presented. Then, a combined process flow for their simultaneous fabrication on a SOI substrate is proposed. Compact models for microresonators and switches are extracted by applying mathematical model order reduction (MOR) to the devices finite element (FE) description in ANSYS c° . The behaviour of these devices includes forms of nonlinearities. However, an approximation in the creation of the FE model is introduced, which enables the use of linear model order reduction. Microresonators are modeled with the introduction of transducer elements, which allow for direct coupling of the electrical and mechanical domain. The coupled system element matrices are linearized around an operating point and reduced. The resulting macromodel is valid for small signal analysis around the bias point, such as harmonic pre-stressed analysis. This is extremely useful for characterizing the frequency response of resonators. Compact modelling of switches preserves the nonlinearity of the device behaviour. Nonlinear reduced order models are obtained by reducing the number of nonlinearities in the system and handling them as input to the system. In this way, the system can be reduced using linear MOR techniques and nonlinearities are introduced directly in the reduced order model. The reduction of the number of system nonlinearities implies the approximation of all distributed forces in the model with lumped forces. Both for microresonators and switches, a procedure for matrices extraction has been developed so that reduced order models include the effects of electrical and mechanical pre-stress. The extraction process is fast and can be done automatically from ANSYS binary files. The method has been applied for the simulation of several devices both at devices and circuit level. Simulation results have been compared with full model simulations, and, when available, experimental data. Reduced order models have proven to conserve the accuracy of finite element method and to give a good description of the overall device behaviour, despite the introduced approximations. In addition, simulation is very fast, both at device and circuit level. A combined process-flow for the integrated fabrication of microresonators and switches has been defined. For this purpose, two processes that are optimized for the independent fabrication of these devices are merged. The major advantage of this process is the possibility to create on-chip circuit blocks that include both microresonators and switches. An application is, for example, aswitched filter bank for wireless transceiver. The process for microresonators fabrication is characterized by the use of silicon on insulator (SOI) wafers and on a deep reactive ion etching (DRIE) step for the creation of the vibrating structures in single-crystal silicon and the use of a sacrificial oxide layer for the definition of resonator to electrode distance. The fabrication of switches is characterized by the use of two different conductive layers for the definition of the actuation electrodes and by the use of a photoresist as a sacrificial layer for the creation of the suspended structure. Both processes have a gold electroplating step, for the creation of the resonators electrodes, transmission lines and suspended structures. The combined process flow is designed such that it conserves the basic properties of the original processes. Neither the performance of the resonators nor the performance of the switches results affected by the simultaneous fabrication. Moreover, common fabrication steps are shared, which allows for cheaper and faster fabrication.

Biomechanical modelling of human knee during living activities

The knee joint is a key structure of the human locomotor system. The knowledge of how each single anatomical structure of the knee contributes to determine the physiological function of the knee, is of fundamental importance for the development of new prostheses and novel clinical, surgical, and rehabilitative procedures. In this context, a modelling approach is necessary to estimate the biomechanic function of each anatomical structure during daily living activities. The main aim of this study was to obtain a subject-specific model of the knee joint of a selected healthy subject. In particular, 3D models of the cruciate ligaments and of the tibio-femoral articular contact were proposed and developed using accurate bony geometries and kinematics reliably recorded by means of nuclear magnetic resonance and 3D video-fluoroscopy from the selected subject. Regarding the model of the cruciate ligaments, each ligament was modelled with 25 linear-elastic elements paying particular attention to the anatomical twisting of the fibres. The devised model was as subject-specific as possible. The geometrical parameters were directly estimated from the experimental measurements, whereas the only mechanical parameter of the model, the elastic modulus, had to be considered from the literature because of the invasiveness of the needed measurements. Thus, the developed model was employed for simulations of stability tests and during living activities. Physiologically meaningful results were always obtained. Nevertheless, the lack of subject-specific mechanical characterization induced to design and partially develop a novel experimental method to characterize the mechanics of the human cruciate ligaments in living healthy subjects. Moreover, using the same subject-specific data, the tibio-femoral articular interaction was modelled investigating the location of the contact point during the execution of daily motor tasks and the contact area at the full extension with and without the whole body weight of the subject. Two different approaches were implemented and their efficiency was evaluated. Thus, pros and cons of each approach were discussed in order to suggest future improvements of this methodologies. The final results of this study will contribute to produce useful methodologies for the investigation of the in-vivo function and pathology of the knee joint during the execution of daily living activities. Thus, the developed methodologies will be useful tools for the development of new prostheses, tools and procedures both in research field and in diagnostic, surgical and rehabilitative fields.

A new approach for the dynamic modelling of the human knee

Mathematical models of the knee joint are important tools which have both theoretical and practical applications. They are used by researchers to fully understand the stabilizing role of the components of the joint, by engineers as an aid for prosthetic design, by surgeons during the planning of an operation or during the operation itself, and by orthopedists for diagnosis and rehabilitation purposes. The principal aims of knee models are to reproduce the restraining function of each structure of the joint and to replicate the relative motion of the bones which constitute the joint itself. It is clear that the first point is functional to the second one. However, the standard procedures for the dynamic modelling of the knee tend to be more focused on the second aspect: the motion of the joint is correctly replicated, but the stabilizing role of the articular components is somehow lost. A first contribution of this dissertation is the definition of a novel approach — called sequential approach — for the dynamic modelling of the knee. The procedure makes it possible to develop more and more sophisticated models of the joint by a succession of steps, starting from a first simple model of its passive motion. The fundamental characteristic of the proposed procedure is that the results obtained at each step do not worsen those already obtained at previous steps, thus preserving the restraining function of the knee structures. The models which stem from the first two steps of the sequential approach are then presented. The result of the first step is a model of the passive motion of the knee, comprehensive of the patello-femoral joint. Kinematical and anatomical considerations lead to define a one degree of freedom rigid link mechanism, whose members represent determinate components of the joint. The result of the second step is a stiffness model of the knee. This model is obtained from the first one, by following the rules of the proposed procedure. Both models have been identified from experimental data by means of an optimization procedure. The simulated motions of the models then have been compared to the experimental ones. Both models accurately reproduce the motion of the joint under the corresponding loading conditions. Moreover, the sequential approach makes sure the results obtained at the first step are not worsened at the second step: the stiffness model can also reproduce the passive motion of the knee with the same accuracy than the previous simpler model. The procedure proved to be successful and thus promising for the definition of more complex models which could also involve the effect of muscular forces.

Modelling coupled physical-biogeochemical processes in ice-covered oceans

The last decades have seen a large effort of the scientific community to study and understand the physics of sea ice. We currently have a wide - even though still not exhaustive - knowledge of the sea ice dynamics and thermodynamics and of their temporal and spatial variability. Sea ice biogeochemistry is instead largely unknown. Sea ice algae production may account for up to 25% of overall primary production in ice-covered waters of the Southern Ocean. However, the influence of physical factors, such as the location of ice formation, the role of snow cover and light availability on sea ice primary production is poorly understood. There are only sparse localized observations and little knowledge of the functioning of sea ice biogeochemistry at larger scales. Modelling becomes then an auxiliary tool to help qualifying and quantifying the role of sea ice biogeochemistry in the ocean dynamics. In this thesis, a novel approach is used for the modelling and coupling of sea ice biogeochemistry - and in particular its primary production - to sea ice physics. Previous attempts were based on the coupling of rather complex sea ice physical models to empirical or relatively simple biological or biogeochemical models. The focus is moved here to a more biologically-oriented point of view. A simple, however comprehensive, physical model of the sea ice thermodynamics (ESIM) was developed and coupled to a novel sea ice implementation (BFM-SI) of the Biogeochemical Flux Model (BFM). The BFM is a comprehensive model, largely used and validated in the open ocean environment and in regional seas. The physical model has been developed having in mind the biogeochemical properties of sea ice and the physical inputs required to model sea ice biogeochemistry. The central concept of the coupling is the modelling of the Biologically-Active-Layer (BAL), which is the time-varying fraction of sea ice that is continuously connected to the ocean via brines pockets and channels and it acts as rich habitat for many microorganisms. The physical model provides the key physical properties of the BAL (e.g., brines volume, temperature and salinity), and the BFM-SI simulates the physiological and ecological response of the biological community to the physical enviroment. The new biogeochemical model is also coupled to the pelagic BFM through the exchange of organic and inorganic matter at the boundaries between the two systems . This is done by computing the entrapment of matter and gases when sea ice grows and release to the ocean when sea ice melts to ensure mass conservation. The model was tested in different ice-covered regions of the world ocean to test the generality of the parameterizations. The focus was particularly on the regions of landfast ice, where primary production is generally large. The implementation of the BFM in sea ice and the coupling structure in General Circulation Models will add a new component to the latters (and in general to Earth System Models), which will be able to provide adequate estimate of the role and importance of sea ice biogeochemistry in the global carbon cycle.

New mechanisms for modelling the motion of the human ankle complex

The relevance of human joint models was shown in the literature. In particular, the great importance of models for the joint passive motion simulation (i.e. motion under virtually unloaded conditions) was outlined. They clarify the role played by the principal anatomical structures of the articulation, enhancing the comprehension of surgical treatments, and in particular the design of total ankle replacement and ligament reconstruction. Equivalent rigid link mechanisms proved to be an efficient tool for an accurate simulation of the joint passive motion. This thesis focuses on the ankle complex (i.e. the anatomical structure composed of the tibiotalar and the subtalar joints), which has a considerable role in human locomotion. The lack of interpreting models of this articulation and the poor results of total ankle replacement arthroplasty have strongly suggested devising new mathematical models capable of reproducing the restraining function of each structure of the joint and of replicating the relative motion of the bones which constitute the joint itself. In this contest, novel equivalent mechanisms are proposed for modelling the ankle passive motion. Their geometry is based on the joint’s anatomical structures. In particular, the role of the main ligaments of the articulation is investigated under passive conditions by means of nine 5-5 fully parallel mechanisms. Based on this investigation, a one-DOF spatial mechanism is developed for modelling the passive motion of the lower leg. The model considers many passive structures constituting the articulation, overcoming the limitations of previous models which took into account few anatomical elements of the ankle complex. All the models have been identified from experimental data by means of optimization procedure. Then, the simulated motions have been compared to the experimental one, in order to show the efficiency of the approach and thus to deduce the role of each anatomical structure in the ankle kinematic behavior.

Machine-learning methods for structure prediction of β-barrel membrane proteins

Different types of proteins exist with diverse functions that are essential for living organisms. An important class of proteins is represented by transmembrane proteins which are specifically designed to be inserted into biological membranes and devised to perform very important functions in the cell such as cell communication and active transport across the membrane. Transmembrane β-barrels (TMBBs) are a sub-class of membrane proteins largely under-represented in structure databases because of the extreme difficulty in experimental structure determination. For this reason, computational tools that are able to predict the structure of TMBBs are needed. In this thesis, two computational problems related to TMBBs were addressed: the detection of TMBBs in large datasets of proteins and the prediction of the topology of TMBB proteins. Firstly, a method for TMBB detection was presented based on a novel neural network framework for variable-length sequence classification. The proposed approach was validated on a non-redundant dataset of proteins. Furthermore, we carried-out genome-wide detection using the entire Escherichia coli proteome. In both experiments, the method significantly outperformed other existing state-of-the-art approaches, reaching very high PPV (92%) and MCC (0.82). Secondly, a method was also introduced for TMBB topology prediction. The proposed approach is based on grammatical modelling and probabilistic discriminative models for sequence data labeling. The method was evaluated using a newly generated dataset of 38 TMBB proteins obtained from high-resolution data in the PDB. Results have shown that the model is able to correctly predict topologies of 25 out of 38 protein chains in the dataset. When tested on previously released datasets, the performances of the proposed approach were measured as comparable or superior to the current state-of-the-art of TMBB topology prediction.

Nonlinear Characterization and Modelling of GaN HEMTs for Microwave Power Amplifier Applications

Semiconductors technologies are rapidly evolving driven by the need for higher performance demanded by applications. Thanks to the numerous advantages that it offers, gallium nitride (GaN) is quickly becoming the technology of reference in the field of power amplification at high frequency. The RF power density of AlGaN/GaN HEMTs (High Electron Mobility Transistor) is an order of magnitude higher than the one of gallium arsenide (GaAs) transistors. The first demonstration of GaN devices dates back only to 1993. Although over the past few years some commercial products have started to be available, the development of a new technology is a long process. The technology of AlGaN/GaN HEMT is not yet fully mature, some issues related to dispersive phenomena and also to reliability are still present. Dispersive phenomena, also referred as long-term memory effects, have a detrimental impact on RF performances and are due both to the presence of traps in the device structure and to self-heating effects. A better understanding of these problems is needed to further improve the obtainable performances. Moreover, new models of devices that take into consideration these effects are necessary for accurate circuit designs. New characterization techniques are thus needed both to gain insight into these problems and improve the technology and to develop more accurate device models. This thesis presents the research conducted on the development of new charac- terization and modelling methodologies for GaN-based devices and on the use of this technology for high frequency power amplifier applications.

Modelling and analysis of networked control strategies in smart power distribution grids: development of co-simulation tools

This thesis is focused on Smart Grid applications in medium voltage distribution networks. For the development of new applications it appears useful the availability of simulation tools able to model dynamic behavior of both the power system and the communication network. Such a co-simulation environment would allow the assessment of the feasibility of using a given network technology to support communication-based Smart Grid control schemes on an existing segment of the electrical grid and to determine the range of control schemes that different communications technologies can support. For this reason, is presented a co-simulation platform that has been built by linking the Electromagnetic Transients Program Simulator (EMTP v3.0) with a Telecommunication Network Simulator (OPNET-Riverbed v18.0). The simulator is used to design and analyze a coordinate use of Distributed Energy Resources (DERs) for the voltage/var control (VVC) in distribution network. This thesis is focused control structure based on the use of phase measurement units (PMUs). In order to limit the required reinforcements of the communication infrastructures currently adopted by Distribution Network Operators (DNOs), the study is focused on leader-less MAS schemes that do not assign special coordinating rules to specific agents. Leader-less MAS are expected to produce more uniform communication traffic than centralized approaches that include a moderator agent. Moreover, leader-less MAS are expected to be less affected by limitations and constraint of some communication links. The developed co-simulator has allowed the definition of specific countermeasures against the limitations of the communication network, with particular reference to the latency and loss and information, for both the case of wired and wireless communication networks. Moreover, the co-simulation platform has bee also coupled with a mobility simulator in order to study specific countermeasures against the negative effects on the medium voltage/current distribution network caused by the concurrent connection of electric vehicles.

Modelling biogeochemical cycles in forest ecosystems: a Bayesian approach

Forest models are tools for explaining and predicting the dynamics of forest ecosystems. They simulate forest behavior by integrating information on the underlying processes in trees, soil and atmosphere. Bayesian calibration is the application of probability theory to parameter estimation. It is a method, applicable to all models, that quantifies output uncertainty and identifies key parameters and variables. This study aims at testing the Bayesian procedure for calibration to different types of forest models, to evaluate their performances and the uncertainties associated with them. In particular,we aimed at 1) applying a Bayesian framework to calibrate forest models and test their performances in different biomes and different environmental conditions, 2) identifying and solve structure-related issues in simple models, and 3) identifying the advantages of additional information made available when calibrating forest models with a Bayesian approach. We applied the Bayesian framework to calibrate the Prelued model on eight Italian eddy-covariance sites in Chapter 2. The ability of Prelued to reproduce the estimated Gross Primary Productivity (GPP) was tested over contrasting natural vegetation types that represented a wide range of climatic and environmental conditions. The issues related to Prelued's multiplicative structure were the main topic of Chapter 3: several different MCMC-based procedures were applied within a Bayesian framework to calibrate the model, and their performances were compared. A more complex model was applied in Chapter 4, focusing on the application of the physiology-based model HYDRALL to the forest ecosystem of Lavarone (IT) to evaluate the importance of additional information in the calibration procedure and their impact on model performances, model uncertainties, and parameter estimation. Overall, the Bayesian technique proved to be an excellent and versatile tool to successfully calibrate forest models of different structure and complexity, on different kind and number of variables and with a different number of parameters involved.

Numerical modelling and structural optimization of multifunctional maritime structures aimed to protect harbours and produce energy

The main objective of this PhD thesis is to optimize a specific multifunctional maritime structure for harbour protection and energy production, named Overtopping Breakwater for Energy Conversion (OBREC), developed by the team of the University of Campania. This device is provided with a sloping plate followed by a unique reservoir, which is linked with the machine room (where the energy conversion occurs) by means of a pipe passing through the crown wall, provided with a parapet on top of it. Therefore, the potential energy of the overtopping waves, collected inside the reservoir located above the still water level, is then converted by means of low – head turbines. In order to improve the understanding of the wave – structure interactions with OBREC, several methodologies have been used and combined together: i. analysis of recent experimental campaigns on wave overtopping discharges and pressures at the crown wall on small – scale OBREC cross sections, carried out in other laboratories by the team of the University of Campania; ii. new experiments on cross sections similar to the OBREC device, planned and carried out in the hydraulic lab at the University of Bologna in the framework of this PhD work; iii. numerical modelling with a 1 – phase incompressible fluid model IH – 2VOF, developed by the University of Cantabria, and with a 2 – phase incompressible fluid model OpenFOAM, both available from the literature; iv. numerical modelling with a new 2 – phase compressible fluid model developed in the OpenFOAM environment within this PhD work; v. analysis of the data gained from the monitoring of the OBREC prototype installation.