Conceptual and physically based environmental simulation models as products of research environments efforts became complex software over time in order to allow describing the behaviour of natural phenomena more accurately. Results from these models are considered accurate but often require to operate an entire system of modeling resources with dedicated knowledge, an extensive set up, and sometimes significant computational time. Model complexity limits wide model adaptation among consultants because of lower available technical resources and capabilities. However, models should be ubiquitous to use in both research and consulting environments. This dissertation aims to address and alleviate two aspects of research model complexity: 1) for researchers, the model design complexity with respect to its internal software structure and 2) for consultants, the model application complexity with respect to data and parameter setup, runtime requirements, and proper model infrastructure setup. The first contribution provides modeling design and implementation support by managing interacting modeling solutions as “Directed Acyclic Graph”, while the second one helps to create surrogate models of complex physical models as a streamlined process. Both contributions are implemented within the OMS/CSIP modeling framework and infrastructure and were applied in various studies. First, a machine learning (ML)-based surrogate model approach is presented to respond to field application requirements to get quick but “accurate enough” model results with limited input and limited a-priori knowledge of the internal physical processes involved. The surrogate model aims to capture the behaviour of a physical model as an ensemble system of artificial neural networks (ANN). Here, the NeuroEvolution of Augmenting Topology (NEAT) technique has been leveraged because of its integration of a genetic approach to build and evolve its ANNs during supervised training. Throughout this phase, the thorough design of the services facilitate seamless monitoring of structural mutations of the artificial neural network and its performances with respect to behavioural emulation of the original model response. This results in a streamlined surrogate model generation. Furthermore, the stochasticity inherent to the evolutionary genetic algorithm combined with a specially designed cross-validation approach allows for straightforward use of the ensemble application. Several, slightly different artificial neural networks are concurrently trained. The ensemble system is built upon the selection of the utmost performant surrogate models and is used collectively to provide uncertainty quantified results when applied against new data. Secondly, a Directed Acyclic Graph (DAG) modeling structure NET3 was developed. NET3 provides appropriate data structures to represent modeling states interactions as relationships based on network topologies. The inherent structure of the DAG commands the execution of modeling tasks. NET3 implicitly manages the parallel computation depending on the network topology. A node of a NET3 modeling structure encapsulates any sort of modeling solution such as a system of ordinary differential equations, a set of statistical rules, or a system of partial differential equations. Each link connects these modeling solutions by handling their data flow. As a result, NET3 simplifies 1) the translation of physical mathematical concepts into model components, and 2) the management of complex interactions of modeling solutions. NET3 also pushes forward the idea of separating concerns between software architecture and scientific model codebase. It manages aspects that relate to the architectural design of the graph modeling structure and lets research scientist focus on their model’s domain. NET3 improves encapsulation and reusability of scientific/mathematical concepts. It avoids code duplication by allowing the same modeling solution to be adopted in different nodes and finely adapted to specific requirements. In summary, NET3 enables a new level of modeling flexibility by allowing to quickly change model representations to explore new modeling solutions. The two presented contributions were integrated into the Object Modeling System/Cloud Services Integrated Platform (OMS/CSIP) environmental modeling framework (EMF). EMFs are standard practice in environmental modeling because they represent a software solution of separating the burden of software architectural design management from scientific research. Here, OMS/CSIP has been identified “advanced” in terms of EMFs design. It offers high flexibility, low language invasiveness, fine and thorough architectural design, and innovative cloud computing deployment infrastructure. These aspects make OMS/CSIP infrastructure the suitable platform to host NEAT based surrogate modeling and NET3 extensions. Framework-enabled NEAT based Surrogate modeling (FeNS) results from the full integration of NEAT based surrogate modeling approach with OMS/CSIP platform. Here, the surrogate model approach was developed as CSIP services to help transitioning from research models to “field models” by enabling the modeling framework to interact with CSIP services, ML libraries, and a NoSQL database to emerge model surrogates for a(ny) modelling solution. OMS/CSIP was extended to harvest data from each model run and automatically derive the surrogate model at the modeling framework level. NET3 extends OMS modeling simulations to run as a graph network of interconnected modeling solutions. Furthermore, it enhances available OMS calibration algorithms to become multi-site calibration procedures. OMS already provided implicit parallel computation of independent components in a modeling solution. NET3 now adds a further layer of implicit parallelism by concurrently running independent modeling solutions. Two studies were carried out to develop and test FeSN while three applications supported the development and testing of NET3. Surrogate models of the Revised Universal Soil Loss Equation, Version 2 (R2) were generated to scale up from simple test cases with a constrained input space to more generic applications including a larger variety of input parameters. The main goal of the surrogate model was to streamline and simplify access to the R2 model behaviour. We performed sensitivity analysis of R2 to limit the input space to only relevant parameters (e.g. soil properties, climate parameter, field geometries, crop rotation description). The main study area was the State of Iowa starting from a single county (Clay county) ending up to four counties (Buena Vista, Cherokee, Clay, and Wright). Clustering methodologies were applied to improve surrogate model accuracy and to accelerate the training process by reducing the dataset size. The overall “goodness-of-fit” against the testing dataset estimated on the median of the uncertainty quantified result of the surrogate models ensemble was always above 0.95 Nash-Sutcliffe (NS), root mean squared error (RMSE) between 0.13 and 0.36, and bias between -0.07 and 0.02. In many cases, accuracy of the surrogate model with respect to testing dataset was above 0.98 NS. Surrogate models of the AgroEcoSystem (AgES) were generated to apply and test FeNS methodology to a semi-distributed hydrologic model. The main goal of the surrogate model was to streamline and simplify access to the AgES model behaviour. Only relevant lumped parameters on watershed centroid were used to train the surrogate models and limit the input space to only relevant parameters (e.g. precipitation, groundwater level, LAI, and potential evapotranspiration). The main study area was the South Fork Iowa River (SFIR) watershed in the State of Iowa across Wright, Franklin, Hamilton, and Hardin counties. The overall “goodness-of-fit” against the testing dataset estimated on the median of the uncertainty quantified result of the surrogate models ensemble was above 0.97 Nash-Sutcliffe (NS), root mean squared error (RMSE) of 2.24, and bias of -0.0794. With respect to NET3, the first application is the real-time modeling of flood forecasting through GEOframe system for the Civil Protection of Regione Basilicata implemented by PhD Bancheri. To scale the computation and finely tune calibration parameters, the Basilicata river basins were split into subcatchments where each was represented by a different NET3 node. The second application was part of Mr. Dalla Torre’s master thesis where the computational core of the rainfall-runoff model of Storm Water Management Model (SWMM by EPA) was componentized. NET3 now allows for reimplementing a concise and lightweight SWMM modeling core and highly parallel model runs. Software architectural design of rainfall-runoff, routing and sewer pipe design components targeted separation of concerns, single responsibility, and encapsulation principles. It resulted in clean and minimized code base. NET3 manages component connections and scalable computation by hosting rainfall-runoff modeling solution into separated nodes from routing and sewer pipe design modeling solution. It also enables each node of the modeling structure to 1) access a shared data structure to fetch input data from and push results to (SWMMobject), and 2) internally analyze the upstream subtree in order to adjust sewer pipe design parameters. The third test case is the application of a “system of systems” of urban models where each node of the graph modeling structure encapsulates a single responsibility system of models. Because of the stochasticity involved in each system of models, the entire graph modeling solution was required to run several times and generate independent realizations. Hence, NET3 was enabled to run a “graph of graphs” modeling structure.

The present thesis summarizes the research activity in the field of elastic structures subject to tangential follower forces performed in the Instability Lab of the University of Trento. Elastic structures loaded by nonconservative positional forces are interesting from different perspectives. First, they are subject to flutter instability, a dynamical instability which remains undetected using static approaches. Second, in these structures dissipation plays a fundamental and destabilizing role. Third, a critical load calculated in the limit of vanishing dissipation is found to be smaller than the critical load calculated in the same structure where the dissipation is assumed absent 'from the beginning'. This behaviour is so peculiar that is usually referred to as 'the Ziegler paradox' and was never experimentally substantiated before. Flutter instability in elastic structures subject to follower load, the most important cases being the famous Beck's and PflÃ1⁄4ger's columns (two elastic rods in a cantilever configuration, with an additional concentrated mass at the end of the rod in the latter case), have attracted, and still attract, a thorough research interest. In the present thesis, the effects of internal and external damping, crucial in the interpretation of experiments, have been investigated. Contrary to a common belief, it has been shown that the effect of external damping is qualitatively the same as the effect of internal damping, both yielding a pronounced destabilization paradox. This result corrects previous claims relative to destabilization by external damping of the Ziegler's and PflÃ1⁄4ger's elastic structures. The major challenge in the research area of follower forces is the practical realization of these forces, which was previously obtained only for the case of the Ziegler double pendulum (a two-degrees-of-freedom elastic system subject to a tangential force). Therefore, an experimental setup to introduce follower tangential forces at the end of an elastic rod was designed, realized, validated, and tested, in which the follower action is produced by exploiting Coulomb friction on an element (a freely-rotating wheel) in sliding contact against a plate (realized by a conveyor belt). It is therefore shown that follower forces can be realized in practice and the first experimental evidence is given of the flutter and divergence instability of the PflÃ1⁄4ger's column. Load thresholds for both the two instabilities are measured for the first time. Moreover, the detrimental effect of dissipation on the critical load for flutter is experimentally demonstrated. The introduced approach to follower forces discloses new horizons for testing self-oscillating structures and for exploring and documenting dynamic instabilities possible when nonconservative loads are applied.

“Smart Landscape”, starting from energy devices for the management and distribution of electricity resources, tends to define a possible vision of landscape. The main structure and process are based on the architecture of a “micro smart grid”, which is generally associated with urban energy grids and districts, but may become a figurative reference for new forms of landscape, such as “Smart Landscape”. The output of the research would be to show how the main strategies of “Smart Landscape” and its development could be applied in different context. The outcomes deriving from the theoretical framework and case study prototypes are: strategy (Interoperability and Accountability), structure (smart grid), and process (main case study). The prototype is the island of Venice Lido, to which the concept and structure of the “micro smart grid” would be applied, trying to follow analyses and pilot projects aimed at creating a research project called “L.I.D.O. – Venice: Learning Island Design Opportunities – Venezia. Sustainable scenarios for Venice Lido”. Smart Landscape is a reflection on development of an urban and landscape design typology linked to the changes brought by the continuous evolution of technologies and the increasingly pressing need for resilience of anthropized contexts, and not only.

In hydrological studies, it is very important to properly analyze the relationship among the different components of the water cycle, due to the complex feedback mechanisms typical of this system. The analysis of available time series is hence a fundamental step, which has to be performed before any modeling activity. Moreover, time series analysis can shed light over the spatial and temporal dynamics of correlated hydrological and climatological processes. In this work, we focus on three tools applied for time series analysis: homogeneity tests, wavelet analysis and copula analysis. Homogeneity tests allow to identify a first important kind of variability in the time series, which is not due to climate nor seasonal variability. Testing for inhomogeneities is therefore an important step that should be always performed on a time series before using it for any application. The homogenization of snow depth data, in particular, is a challenging task. Up to now, it has been performed analyzing available metadata, which often present contradictions and are rarely complete. In this work, we present a procedure to test the homogeneity of snow depth time series based on the Standard Normal Homogeneity Test (SNHT). The performance of the SNHT for the detection of inhomogeneities in snow depth data is further investigated with a comparison experiment, in which a dataset of snow depth time series relative to Austrian stations has been analyzed with both the SNHT and the HOMOP algorithm. The intercomparison study indicates that the two algorithms show comparable performance. The wavelet transform analysis allows to obtain a different kind of information about the variability of a time series. In fact, it determines the different frequency content of a signal in different time intervals. Moreover, the wavelet coherence analysis allows to identify periods where two time series are correlated and their phase shift. We apply the wavelet transform to a dataset of snow depth time series of stations distributed in the Adige catchment and on a dataset of 16 discharge time series located in the Adige and in the Inn catchments. The same datasets are used to perform a wavelet coherence analysis considering the Mediterranean Oscillation Index (MOI) and the North Atlantic Oscillation Index (NAOI). This analysis highlights a difference in the behavior of the snow time series collected below and above 1650 m a.s.l.. We also observe a difference between low and high elevation sites in the amount of mean seasonal snow depth and snow cover duration. More interestingly, snow time series collected at different elevations respond differently to temperature and more in general to climate changes. The wavelet analysis allows us also to distinguish between gauging stations belonging to different catchments, while the wavelet coherence analysis revealed non-stationary correlations with the MOI and NAOI, indicating a very complex relation between the measured quantities and climatic indexes. Finally the application of copulas allows modeling the marginal of each variable and their dependence structure independently. We apply this technique to two relevant cases. First we study snow related variables in relation with temperature, the NAOI and the MOI, which we already investigated with the wavelet coherence analysis. Then we model flood events registered at two stations of the Inn river: Wasserburg and Passau. This last analysis is performed with the goal of predicting future flood events and derive construction parameters for retention basins. We test three different combinations of variables (direct peak discharge-direct volume, direct peak discharge-direct volume-rising time-base flow, direct peak discharge-direct volume-rising time-moving threshold) describing the flood events and compare the results. The consistency in the results indicates that the proposed methodology is robust and reliable. This study shows the importance of approaching the analysis to hydrological time series from several points of view: quality of the data, variability of the time series and relation between different variables. Moreover, it shows that integrating the use of various time series analysis methods can greatly improve our understanding of the system behavior.

A new trend in the mechanical design of devices for advanced technologies, such as soft robotics and micro/nano mechanics, is the exploitation of structures undergoing large deflections, in an attempt of achieving superior performances. Within this framework, non-linear modelling becomes a fundamental tool for the design of compliant structures and deformable mechanism. Two structural systems are investigated, both based on the planar elastica and subject to movable and configurational constraints. These two structures disclose unforeseen behaviours when the values of the parameters defining the models are varied. The first structural system is an elastic rod constrained by a slowly rotating clamp, while the other end is loaded with a lumped mass weight. When this weight is lower than that corresponding to buckling, the edge of the rod describes a closed curve, behaving as an elastica compass. Differently, when the load is higher than that of buckling, a release of elastic energy is observed, leading to a snapback of the structure, so that the rod realizes an elastica catapult. The clamp in the above described structure is replaced by a frictionless and fixed sliding sleeve in the second system considered in this thesis. The rod is subject to a sudden release from the underformed configuration, providing dynamic effects on the system. By means of the variational approach, the presence of a configurational force at the exit of the sliding sleeve is proven within the dynamical setting, extending previous results restricted to the quasi-static assumption. The configurational force is found to strongly affect the dynamics of the structure. In particular, two different behaviours are observed, in which the rod may either completely penetrate in ("injection") or be expelled from ("ejection") the sliding sleeve. In both the above problems, the theoretical predictions are corroborated through the experimental validation on physical models, which have been ad hoc invented and designed. A new insight is obtained in the design of flexible devices, paving the way to applications in soft robotics.

Ecosystem Services (ESs) are the goods and services supplied by ecosystems. In order to fully understand their contribution to human wellbeing, there is a need to identify them, assess their supply, recognise areas where they appear together repeatedly and analyse the interactions that may exist among them. Most of these tasks are also specifically required by the European Biodiversity Strategy for 2020, which asks Member States, by 2014, to identify key ESs and to spatially assess their supply and demand (European Commission, 2011). Nevertheless, these are difficult tasks and to date they have been only partly performed: existing studies in fact have typically focused on a small sub-set of ESs and made use of information that poorly reflects the actual variability of the ESs distribution across a region. The present research aims to fill these gaps, by developing methods involving a wide set of ESs and providing a detailed ESs assessment, based on spatial and statistical analyses. The methods have been tested on an Alpine region of Italy, Trentino. The Alps present a heterogeneous landscape, resulting from the combination of natural and urbanized environments, that allows the supply of a wide range of ESs. The research has four specific objectives. The first objective focuses on the selection and the representation over specific spatial units of the real supply of multiple ESs. Operatively, 51 experts from the local administrative offices and research institutes have been involved in the selection of the most important ESs and spatial indicators for the case study. The experts identified 25 ESs and 57 representative spatial indicators (1 to 5 indicators for each service), and provided data for indicators mapping. To consider the heterogeneity of the ESs supply across the region, indicators were mapped over 20 different spatial units, including: land cover classes, cadastral parcels, fishing zones and catchments.The second objective is to develop and test a statistical method for identifying key indicators that are spatially-explicit and able to measure the biophysical, socio-cultural and economic values of ESs (both in terms of stock and flow). Spearman pairwise correlation analysis was performed among the indicators of the same service in order to identify the highly correlated ones, hence deemed to provide redundant information. Key indicators were selected among the lowly correlated ones. 35 indicators were selected for the case study (out of the 57 initial indicators). The analysis showed that there is a minimum number of key indicators for each ES. Accordingly, three general rules were identified for the selection: (i) if the supply of an ES is regulated, both its biophysical-stock and biophysical-flow indicators must be selected, (ii) if multiple stock (flow) biophysical indicators for a single ES are mapped over different spatial units, all stock (flow) indicators must be maintained, (iii) socio-cultural or economic indicators are always selected as key indicators. The third objective is to develop and test a statistical method for defining bundles of ESs, as sets of spatially correlated services. Principal Component Analysis was used to summarize the information of the 35 indicators, while hierarchical clustering was applied to identify 11 ESs clusters. Clusters were turned into bundles by analyzing the spatial variability of the services due to biophysical (e.g. morphological conditions) and human (e.g. land use) factors. The results of the analysis show that in Trentino multiple ESs can be grouped in a few number of bundles with a complex shape. In particular, areas with poor ESs supply are grouped in one single bundle and the largest bundle follows the spatial distribution of a single land cover class: i.e. forest.The fourth objective is to develop a method to study interactions among ESs, by combining statistical and spatial analyses. In fact, the supply of a given ES is correlated with the supply of other ESs and it is affected by multiple external factors. Correlations may be positive when an increase in the supply of one service corresponds to higher supplies of other services (i.e. synergies), or negative when an increase in the supply of one service corresponds to lower supplies of other services (i.e. tradeoffs). The degree of interactions among 35 key indicators is determined by performing a Spearman pairwise correlation analysis. The latter enabled to identify six patterns of ESs interactions, one pattern of tradeoffs and five of synergies. The analysis showed that the local land use management has not compromised the capacity of ecosystems to provide regulating services while supplying the provisioning ones. The external factors causing the variability of the services across the region were identified and explained by means of spatial and Spearman correlation analyses among the ESs principal components. Principal components were turned into drivers of change by analyzing the spatial variability of the ESs due to biophysical (e.g. forest density) and human (e.g. land use) factors. Land use management was found as the external factor that causes the greatest variability of the ESs distribution across the region. Within forest areas, forest management activities that involve loss of vegetation were found as the main drivers of ESs change. This research aimed to consider a wide set of ESs and information able to reflect the actual variability of the services distribution across a region. It proposed a scientifically sound methodology to deal with the main issues of the ESs spatial assessment, that may reveal efficiently applicable in other geographical areas where ESs are heterogeneously supplied.

Industrial process plants and power plants are crucial components of modern infrastructures, playing a pivotal role in sustaining communities through the provision of essential goods and services. These facilities contain critical equipment and structures vulnerable to damage or failure when exposed to seismic excitations without protection measures. Robust seismic protection ensures the preservation of structural integrity and functionality, guaranteeing the uninterrupted delivery of vital services like electricity generation, water treatment, and manufacturing. Consequently, seismic protection measures for these plants enhance overall community resilience and safety, mitigating potential disruptions and harm in the face of earthquakes. Based on these insights, a novel seismic protection system, known as metafoundation (MF), is revisited and enhanced. Geared towards offering cost-effective, modular, and multidirectional protection to critical infrastructure components, the investigation delves into the exploration and implementation of novel nonlinearities and mechanisms to finite locally resonant MFs in order to obtain further improvements. The thesis commences by elucidating the principles of periodic lattices and lattice-based acoustic metamaterials, the foundational concept of finite locally resonant MFs, using both analytical and numerical met-hodologies, followed by some experimental validation. Theoretical exploration encompasses one-dimensional linear and nonlinear metamaterials featuring local resonance properties, via resonators. By incorporating nonlinear mechanisms, such as the Bouc-Wen and Duffing oscillators, the study delves into unique nonlinear wave dynamics and evolving dispersion characteristics. Notably, the focus intensifies on bistable Duffing oscillators as the primary cell spring, and the reliability of numerical simulations is confirmed through experimental validation. Transitioning from theoretical frameworks to practical applications, the finite lattices has been analysed. The effectiveness of MFs under seismic loading relies significantly on the seismic input. Consequently, both natural and synthetic three-directional accelerograms — where the former were generated through a physics-based ground motion model — were utilized for performance assessment and, crucially, for optimization purposes. The inherent locally resonant property of MFs necessitates careful tuning of resonator parameters, as mistuning can lead to notable performance degradation. Optimization strategies encompassed frequency domain and time domain approaches for linear and nonlinear MFs, respectively. In the frequency domain, the Power Spectrum Density (PSD) functions of ground motions were considered alongside the transfer function of MF-superstructure coupled systems to quantify responses. The optimization was achieved through solving the multi-variable, multiobjective optimization problem, facilitated by a specialized algorithm based on sensitivity analysis. In the time domain, conversely, optimization focused on energy dissipation through time history analyses. To streamline computational efficiency, experimental design methods and Kriging models were employed. The pursuit of enhanced performance and novelty, required intricate nonlinear mechanisms in conjunction with MFs to be considered. The columns of MF were substituted with bistable ones. In another application instead, to enhance vertical seismic protection, unit cells featuring vertical quasi-zero-stiffness mechanisms were interconnected in series with locally resonant unit cells. Moreover, to improve performance and minimize MFs’ voluminous size —needed for low-frequency attenuation — the incorporation of novel inerters to resonators was considered. The implemented strategies based on 3D modelled MFs, were applied to a storage tank of a process plant and two in-design stage Small Modular Reactor (SMR) buildings. Detailed time history analyses revealed that MFs can effectively meet targeted performance objectives of the coupled systems. This includes achieving performance levels comparable to conventional isolation solutions for horizontal seismic excitation, while also safeguarding the superstructure against vertical actions and resultant rocking motions. Finally, it was shown that MFs offer a viable solution aligned with the primary development objective of SMRs, facilitating modular standardization for deployment in beyond-design earthquake locations without additional resistance of the superstructure.

This thesis work aims to successively analyze and develop "ex novo" problems concerning the use of finite elements for the analysis of issues characterized by high plasticity, geometrical and material nonlinearity, large displacements and rotations; all combined with the effect of temperature on the material mechanical properties. The ultimate objective of the work is the analysis and development of nonlinear Finite Elements devoted to the modelling of steel structures at ambient and elevated temperature. Three different experiences will be analyzed in this elaborate; each of them characterised by specific issues that may be involved in the analysis via finite element method of steel structures at ambient and elevated temperature. At the same time innovative aspects that are related, for example, to the particular typology of the analyzed case study (first case) or in the methodology used in the treatment of the problem (second and third case) are investigated. The thesis structure chronologically retraces this path and the results and the experience gained from each of them were exploited to ultimately implement a thermomechanical finite element that is expression of all the tackled problems. The thesis consists of a collection of three papers that have been published or submitted on each of the investigated topics. In detail: - In the first paper, a commercial finite-element code, of the type "multipurpose", such as ANSYS has been used for the analysis of innovative cold-formed, laterallyrestrained steel rectangular hollow flange beams subjected to monotonic bending test. The numerical analysis has been carried out by means of the direct comparison with experimental tests on real scale specimens; that has allowed the detection of some phenomenological problems that have been included in the model calibration. From a numerical point of view, this work has at first allowed to deeply investigate the plastic problem by means, for example, the appropriate identification of the constitutive laws for the material, the correct choice of hardening law and yield surface, and their impact on the model. The local buckling problem typical of these profiles has been evaluated, through the use of shell elements. Furthermore, the effect of the global and local imperfections, which have been introduced in the model with different amplitudes, has been deeply investigated by evaluating their effect on the ultimate load. The calibration of the model finally allowed to perform a series of parametric analyses in order to extend the results to an extended range of profiles, characterized by different slenderness. - In the second paper, the thermal problem has been introduced with the support of a finite element software, designed specifically for thermomechanical analysis (SAFIR). The case study is, in this case, based on a multi-storey steel-concrete composite open car park subjected to localized fire of vehicles. With this study, not only the plastic problem has been analyzed but also phenomena such as the effect of high geometrical nonlinearity and large displacements on the structure in addition to the temperature effect on materials mechanical properties. The case study has been used to evaluate the assumptions and the issues that arise when developing an innovative integrated modelling methodology between a computational fluid dynamics (CFD) software applied to compartment fires and a finite element (FE) software applied to structural systems. Particular emphasis has been given to the weak coupling approach developed between the CFD code fire dynamics simulator (FDS) and the FE software SAFIR. - In the third and last paper all the experiences obtained from the previous works have been focused on the implementation, inside the MATLAB environment, of a thermomechanical beam finite element based on the co-rotational beam theory for the analysis of two-dimensional frames heated under high temperature and subjected to plastic deformation and to the effect of geometrical nonlinearity. The finite element is mainly aimed at the study of steel structures, with double-symmetrical profiles such as IPE or HE cross sections, and could then be used as a modelling tool for typical frames subjected to thermal actions. The element implements both Euler-Bernoulli and Timoshenko beam theories and can analyse slender to moderately stocky structures. A co-rotational formulation was used for describing the beam kinematic. The degradation of the steel mechanical properties at high temperature according to the Eurocode 1993-1-2 was considered by integrating the material constitutive law based on a predetermined temperature field in the cross section. An improved displacement predictor for estimating the displacement field at the beginning of each time step was successfully implemented and allowed to significantly decrease the computational time. Furthermore, advanced path-following methods that detect secondary equilibrium paths owing to instability occurrence were implemented in order to analyse the elasticplastic post-buckling behaviour of compressed steel elements at high temperature without the need of introducing geometrical imperfections. In order to show the potential of the developed finite element by highlighting the practical implications, a parametric analysis was performed to show whether the element could reproduce the EN1993-1-2 buckling curve. Validation against experimental and numerical data obtained with commercial software like ABAQUS and SAFIR is thoroughly shown in the paper.

The average age of strategic constructions in the Western world is becoming higher and higher. Many of these structures need inspection, maintenance or replacement, resulting in significant costs. The accurate estimate of structural condition can make operators optimize the allocation of resources. Nowadays, the progress of technology and machine learning has made structural health monitoring appealing to the agencies that manage important structures. This has encouraged the research community in the study of new structural health monitoring methods. In spite of this, the use of monitoring data is often disregarded by practitioners, who still prefer to gather more information and then act based on experience. Similarly, unlike the design of civil structures, the design of structural health monitoring systems is carried out based on heuristics rather than on rigorous evaluations of the expected monitoring system effectiveness. In this doctoral thesis, I apply expected utility theory for the development of decision support systems to be used in structural health monitoring and I develop a procedure for the design of structural health monitoring systems that follows the scheme of semi-probabilistic structural design. The use of monitoring data in a decision support system that implements expected utility theory financially optimizes the management of civil structures. The proposed monitoring system design method enables practitioners to design monitoring systems using their experience and guarantees that the installation of a monitoring solution is financially convenient. I present the mathematical formulation for monitoring-based decision support systems and monitoring system design. Then, I propose the numerical algorithms for the development of monitoring-based decision support systems and solutions for monitoring data analysis. Finally, the proposed methods are applied to three case studies, which enabled me to discuss the application in real life and the hypotheses. The applications show also the feasibility of the proposed approaches and test the numerical algorithms.

Dielectric elastomer (DE) actuators are electromechanical transducers that essentially consist of one layer of an insulating soft elastomer coated on both sides with com- pliant electrodes. When a voltage is applied between the electrodes, an electrostatic pressure deforms the elastomer triggering the motion of the actuator. In this the- sis, this principle is exploited for the development of three different actuators: an electroactive compression bandage, a hydrostatically coupled actuator for use in the field of soft manipulators and a dielectric elastomer based inchworm-like robot able to perform locomotion. By doing so, several challenges related to the design, to the modeling and to the manufacturing of this kind of devices are raised and tackled. During the development of the electroactive compression bandage, the issue of electrical insulation and prevention of electrical discharge in wearable devices was addressed by using coating layers as an interface between the DE actuator and the human body. Both experimental investigations and a finite electro-elasticity analyti- cal model showed that the passive layers play a key role for an effective transmission of the actuation from the active layers to the load. Indeed, the model showed that by increasing the number of electroactive layers, the pressure variation can be increased, although with a saturation trend, providing a useful indication for future designs of such bandages. The second piece of work here reported consists in a design upgrade of the Hy- drostatically Coupled Dielectric Elastomer Actuator (HC-DEA), already known in the literature, that enable its use in the field of soft manipulators. The new design fea- tures segmented electrodes, which stand as four independent elements on the active membrane of the actuator, enabling it for generating both out of plane and in plane motions. This novel design makes the actuator suitable for delicate transportation of a flat object. This capability was proven via an experimental investigation in which a flat Petri dish was roto-translated on a platform composed of two actuators. The electromechanical transduction performance of the actuator was characterized and its contact mechanics was modeled. Finally, a smart robot structure that exploits anisotropic friction to achieve stick- slip locomotion is presented. The robot, which is made out just of a plastic beam, a planar dielectric elastomer actuator and four bristle pads with asymmetric rigid metallic bristles, exploits the resonance condition to reach the maximum locomotion speed. The fundamental frequency of the structure, which was estimated both ana- lytically and numerically, was identified within the range of frequencies in which the top locomotion speed was observed during the experiments to be identified.