Investigation on Surface Finishing of Components Ground with Lapping Kinematics: Lapgrinding Process

Over the last three decades, researchers have responded to the demands of industry to manufacture mechanical components with geometrical tolerance, dimensional tolerance, and surface finishing in nanometer levels. The new lapgrinding process developed in Brazil utilizes lapping kinematics and a flat grinding wheel dressed with a single-point diamond dresser in agreement with overlap factor (U(d)) theory. In the present work, the influences of different U(d) values on dressing (U(d) = 1, 3 e 5) and grain size of the grinding wheel made of silicon carbide (SiC = 800, 600 e 300 mesh) are analyzed on surface finishing of stainless steel AISI 420 flat workpieces submitted to the lapgrinding process. The best results, obtained after 10 minutes of machining, were: average surface roughness (Ra) 1.92 nm; 1.19 mu m flatness deviation of 25.4 mm diameter workpieces and mirrored surface finishing. Given the surface quality achieved, the lapgrinding process can be included among the ultra-precision finishing processes and, depending on the application, the steps of lapping followed by polishing can be replaced by the proposed abrasive process.

Modelling and optimization of the cephalosporin C production bioprocess in a fed-batch bioreactor with invert sugar as substrate

Cephalosporin C production process optimization was studied based on four experiments carried out in an agitated and aerated tank fermenter operated as a fed-batch reactor. The microorganism Cephalosporium acremonium ATCC 48272 (C-10) was cultivated in a synthetic medium containing glucose as major carbon and energy source. The additional medium contained a hydrolyzed sucrose solution as the main carbon and energy source and it was added after the glucose depletion. By manipulating the supplementary feed rate, it was possible to increase antibiotic production. A mathematical model to represent the fed-batch production process was developed. It was observed that the model was applicable under different operation conditions, showing that optimization studies can be made based on this model. (C) 1999 Elsevier B.V. Ltd. All rights reserved.

Genetic Algorithms (Binary and Real Codes) for the Optimisation of a Fermentation Process for Butanol Production

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Towards an intelligent graphical interface for linear programming modelling

The increase of computing power of the microcomputers has stimulated the building of direct manipulation interfaces that allow graphical representation of Linear Programming (LP) models. This work discusses the components of such a graphical interface as the basis for a system to assist users in the process of formulating LP problems. In essence, this work proposes a methodology which considers the modelling task as divided into three stages which are specification of the Data Model, the Conceptual Model and the LP Model. The necessity for using Artificial Intelligence techniques in the problem conceptualisation and to help the model formulation task is illustrated.

Mobile Robot navigation modelling, control and applications

This work presents and discusses the main topics involved on the design of a mobile robot system and focus on the control and navigation systems for autonomous mobile robots. Introduces the main aspects of the Robot design, which is a holistic vision about all the steps of the development process of an autonomous mobile robot; discusses the problems addressed to the conceptualization of the mobile robot physical structure and its relation to the world. Presents the dynamic and control analysis for navigation robots with kinematic and dynamic model and, for final, presents applications for a robotic platform of Automation, Simulation, Control and Supervision of Mobile Robots Navigation, with studies of dynamic and kinematic modelling, control algorithms, mechanisms for mapping and localization, trajectory planning and the platform simulator. © 2012 Praise Worthy Prize S.r.l. - All rights reserved.

Use of uniform designs in combination with neural networks for viral infection process development

This work aimed to compare the predictive capacity of empirical models, based on the uniform design utilization combined to artificial neural networks with respect to classical factorial designs in bioprocess, using as example the rabies virus replication in BHK-21 cells. The viral infection process parameters under study were temperature (34°C, 37°C), multiplicity of infection (0.04, 0.07, 0.1), times of infection, and harvest (24, 48, 72 hours) and the monitored output parameter was viral production. A multilevel factorial experimental design was performed for the study of this system. Fractions of this experimental approach (18, 24, 30, 36 and 42 runs), defined according uniform designs, were used as alternative for modelling through artificial neural network and thereafter an output variable optimization was carried out by means of genetic algorithm methodology. Model prediction capacities for all uniform design approaches under study were better than that found for classical factorial design approach. It was demonstrated that uniform design in combination with artificial neural network could be an efficient experimental approach for modelling complex bioprocess like viral production. For the present study case, 67% of experimental resources were saved when compared to a classical factorial design approach. In the near future, this strategy could replace the established factorial designs used in the bioprocess development activities performed within biopharmaceutical organizations because of the improvements gained in the economics of experimentation that do not sacrifice the quality of decisions.

Evolution of extrafloral nectaries: adaptive process and selective regime changes from forest to savanna

Much effort has been devoted to understanding the function of extrafloral nectaries (EFNs) for antplantherbivore interactions. However, the pattern of evolution of such structures throughout the history of plant lineages remains unexplored. In this study, we used empirical knowledge on plant defences mediated by ants as a theoretical framework to test specific hypotheses about the adaptive role of EFNs during plant evolution. Emphasis was given to different processes (neutral or adaptive) and factors (habitat change and trade-offs with new trichomes) that may have affected the evolution of antplant associations. We measured seven EFN quantitative traits in all 105 species included in a well-supported phylogeny of the tribe Bignonieae (Bignoniaceae) and collected field data on antEFN interactions in 32 species. We identified a positive association between ant visitation (a surrogate of ant guarding) and the abundance of EFNs in vegetative plant parts and rejected the hypothesis of phylogenetic conservatism of EFNs, with most traits presenting K-values < 1. Modelling the evolution of EFN traits using maximum likelihood approaches further suggested adaptive evolution, with static-optimum models showing a better fit than purely drift models. In addition, the abundance of EFNs was associated with habitat shifts (with a decrease in the abundance of EFNs from forest to savannas), and a potential trade-off was detected between the abundance of EFNs and estipitate glandular trichomes (i.e. trichomes with sticky secretion). These evolutionary associations suggest divergent selection between species as well as explains K-values < 1. Experimental studies with multiple lineages of forest and savanna taxa may improve our understanding of the role of nectaries in plants. Overall, our results suggest that the evolution of EFNs was likely associated with the adaptive process which probably played an important role in the diversification of this plant group.

Phenol biodegradation by a microbial consortium: application of artificial neural network (ANN) modelling

In this study, an effective microbial consortium for the biodegradation of phenol was grown under different operational conditions, and the effects of phosphate concentration (1.4 g L-1, 2.8 g L-1, 4.2 g L-1), temperature (25 degrees C, 30 degrees C, 35 degrees C), agitation (150 rpm, 200 rpm, 250 rpm) and pH (6, 7, 8) on phenol degradation were investigated, whereupon an artificial neural network (ANN) model was developed in order to predict degradation. The learning, recall and generalization characteristics of neural networks were studied using data from the phenol degradation system. The efficiency of the model generated by the ANN was then tested and compared with the experimental results obtained. In both cases, the results corroborate the idea that aeration and temperature are crucial to increasing the efficiency of biodegradation.

Modelling shared attention through relational reinforcement learning

Shared attention is a type of communication very important among human beings. It is sometimes reserved for the more complex form of communication being constituted by a sequence of four steps: mutual gaze, gaze following, imperative pointing and declarative pointing. Some approaches have been proposed in Human-Robot Interaction area to solve part of shared attention process, that is, the most of works proposed try to solve the first two steps. Models based on temporal difference, neural networks, probabilistic and reinforcement learning are methods used in several works. In this article, we are presenting a robotic architecture that provides a robot or agent, the capacity of learning mutual gaze, gaze following and declarative pointing using a robotic head interacting with a caregiver. Three learning methods have been incorporated to this architecture and a comparison of their performance has been done to find the most adequate to be used in real experiment. The learning capabilities of this architecture have been analyzed by observing the robot interacting with the human in a controlled environment. The experimental results show that the robotic head is able to produce appropriate behavior and to learn from sociable interaction.

Probabilistic failure modelling of reinforced concrete structures subjected to chloride penetration

Structural durability is an important criterion that must be evaluated for every type of structure. Concerning reinforced concrete members, chloride diffusion process is widely used to evaluate durability, especially when these structures are constructed in aggressive atmospheres. The chloride ingress triggers the corrosion of reinforcements; therefore, by modelling this phenomenon, the corrosion process can be better evaluated as well as the structural durability. The corrosion begins when a threshold level of chloride concentration is reached at the steel bars of reinforcements. Despite the robustness of several models proposed in literature, deterministic approaches fail to predict accurately the corrosion time initiation due the inherent randomness observed in this process. In this regard, structural durability can be more realistically represented using probabilistic approaches. This paper addresses the analyses of probabilistic corrosion time initiation in reinforced concrete structures exposed to chloride penetration. The chloride penetration is modelled using the Fick's diffusion law. This law simulates the chloride diffusion process considering time-dependent effects. The probability of failure is calculated using Monte Carlo simulation and the first order reliability method, with a direct coupling approach. Some examples are considered in order to study these phenomena. Moreover, a simplified method is proposed to determine optimal values for concrete cover.

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.

Tactile perception - Perception of tactile distance changes with body site: a neural network modelling study.

La distorsione della percezione della distanza tra due stimoli puntuali applicati sulla superfice della pelle di diverse regioni corporee è conosciuta come Illusione di Weber. Questa illusione è stata osservata, e verificata, in molti esperimenti in cui ai soggetti era chiesto di giudicare la distanza tra due stimoli applicati sulla superficie della pelle di differenti parti corporee. Da tali esperimenti si è dedotto che una stessa distanza tra gli stimoli è giudicata differentemente per diverse regioni corporee. Il concetto secondo cui la distanza sulla pelle è spesso percepita in maniera alterata è ampiamente condiviso, ma i meccanismi neurali che manovrano questa illusione sono, allo stesso tempo, ancora ampiamente sconosciuti. In particolare, non è ancora chiaro come sia interpretata la distanza tra due stimoli puntuali simultanei, e quali aree celebrali siano coinvolte in questa elaborazione. L’illusione di Weber può essere spiegata, in parte, considerando la differenza in termini di densità meccano-recettoriale delle differenti regioni corporee, e l’immagine distorta del nostro corpo che risiede nella Corteccia Primaria Somato-Sensoriale (homunculus). Tuttavia, questi meccanismi sembrano non sufficienti a spiegare il fenomeno osservato: infatti, secondo i risultati derivanti da 100 anni di sperimentazioni, le distorsioni effettive nel giudizio delle distanze sono molto più piccole rispetto alle distorsioni che la Corteccia Primaria suggerisce. In altre parole, l’illusione osservata negli esperimenti tattili è molto più piccola rispetto all’effetto prodotto dalla differente densità recettoriale che affligge le diverse parti del corpo, o dall’estensione corticale. Ciò, ha portato a ipotizzare che la percezione della distanza tattile richieda la presenza di un’ulteriore area celebrale, e di ulteriori meccanismi che operino allo scopo di ridimensionare – almeno parzialmente – le informazioni derivanti dalla corteccia primaria, in modo da mantenere una certa costanza nella percezione della distanza tattile lungo la superfice corporea. E’ stata così proposta la presenza di una sorta di “processo di ridimensionamento”, chiamato “Rescaling Process” che opera per ridurre questa illusione verso una percezione più verosimile. Il verificarsi di questo processo è sostenuto da molti ricercatori in ambito neuro scientifico; in particolare, dal Dr. Matthew Longo, neuro scienziato del Department of Psychological Sciences (Birkbeck University of London), le cui ricerche sulla percezione della distanza tattile e sulla rappresentazione corporea sembrano confermare questa ipotesi. Tuttavia, i meccanismi neurali, e i circuiti che stanno alla base di questo potenziale “Rescaling Process” sono ancora ampiamente sconosciuti. Lo scopo di questa tesi è stato quello di chiarire la possibile organizzazione della rete, e i meccanismi neurali che scatenano l’illusione di Weber e il “Rescaling Process”, usando un modello di rete neurale. La maggior parte del lavoro è stata svolta nel Dipartimento di Scienze Psicologiche della Birkbeck University of London, sotto la supervisione del Dott. M. Longo, il quale ha contribuito principalmente all’interpretazione dei risultati del modello, dando suggerimenti sull’elaborazione dei risultati in modo da ottenere un’informazione più chiara; inoltre egli ha fornito utili direttive per la validazione dei risultati durante l’implementazione di test statistici. Per replicare l’illusione di Weber ed il “Rescaling Proess”, la rete neurale è stata organizzata con due strati principali di neuroni corrispondenti a due differenti aree funzionali corticali: • Primo strato di neuroni (il quale dà il via ad una prima elaborazione degli stimoli esterni): questo strato può essere pensato come parte della Corteccia Primaria Somato-Sensoriale affetta da Magnificazione Corticale (homunculus). • Secondo strato di neuroni (successiva elaborazione delle informazioni provenienti dal primo strato): questo strato può rappresentare un’Area Corticale più elevata coinvolta nell’implementazione del “Rescaling Process”. Le reti neurali sono state costruite includendo connessioni sinaptiche all’interno di ogni strato (Sinapsi Laterali), e connessioni sinaptiche tra i due strati neurali (Sinapsi Feed-Forward), assumendo inoltre che l’attività di ogni neurone dipenda dal suo input attraverso una relazione sigmoidale statica, cosi come da una dinamica del primo ordine. In particolare, usando la struttura appena descritta, sono state implementate due differenti reti neurali, per due differenti regioni corporee (per esempio, Mano e Braccio), caratterizzate da differente risoluzione tattile e differente Magnificazione Corticale, in modo da replicare l’Illusione di Weber ed il “Rescaling Process”. Questi modelli possono aiutare a comprendere il meccanismo dell’illusione di Weber e dare così una possibile spiegazione al “Rescaling Process”. Inoltre, le reti neurali implementate forniscono un valido contributo per la comprensione della strategia adottata dal cervello nell’interpretazione della distanza sulla superficie della pelle. Oltre allo scopo di comprensione, tali modelli potrebbero essere impiegati altresì per formulare predizioni che potranno poi essere verificate in seguito, in vivo, su soggetti reali attraverso esperimenti di percezione tattile. E’ importante sottolineare che i modelli implementati sono da considerarsi prettamente come modelli funzionali e non intendono replicare dettagli fisiologici ed anatomici. I principali risultati ottenuti tramite questi modelli sono la riproduzione del fenomeno della “Weber’s Illusion” per due differenti regioni corporee, Mano e Braccio, come riportato nei tanti articoli riguardanti le illusioni tattili (per esempio “The perception of distance and location for dual tactile pressures” di Barry G. Green). L’illusione di Weber è stata registrata attraverso l’output delle reti neurali, e poi rappresentata graficamente, cercando di spiegare le ragioni di tali risultati.

Tactile Perception - Perception of tactile distance on a single skin surface changes with stimulus orientation: a neuronal network modelling study

L’interazione che abbiamo con l’ambiente che ci circonda dipende sia da diverse tipologie di stimoli esterni che percepiamo (tattili, visivi, acustici, ecc.) sia dalla loro elaborazione per opera del nostro sistema nervoso. A volte però, l’integrazione e l’elaborazione di tali input possono causare effetti d’illusione. Ciò si presenta, ad esempio, nella percezione tattile. Infatti, la percezione di distanze tattili varia al variare della regione corporea considerata. Il concetto che distanze sulla cute siano frequentemente erroneamente percepite, è stato scoperto circa un secolo fa da Weber. In particolare, una determinata distanza fisica, è percepita maggiore su parti del corpo che presentano una più alta densità di meccanocettori rispetto a distanze applicate su parti del corpo con inferiore densità. Oltre a questa illusione, un importante fenomeno osservato in vivo è rappresentato dal fatto che la percezione della distanza tattile dipende dall’orientazione degli stimoli applicati sulla cute. In sostanza, la distanza percepita su una regione cutanea varia al variare dell’orientazione degli stimoli applicati. Recentemente, Longo e Haggard (Longo & Haggard, J.Exp.Psychol. Hum Percept Perform 37: 720-726, 2011), allo scopo di investigare come sia rappresentato il nostro corpo all’interno del nostro cervello, hanno messo a confronto distanze tattili a diverse orientazioni sulla mano deducendo che la distanza fra due stimoli puntuali è percepita maggiore se applicata trasversalmente sulla mano anziché longitudinalmente. Tale illusione è nota con il nome di Illusione Tattile Orientazione-Dipendente e diversi risultati riportati in letteratura dimostrano che tale illusione dipende dalla distanza che intercorre fra i due stimoli puntuali sulla cute. Infatti, Green riporta in un suo articolo (Green, Percpept Pshycophys 31, 315-323, 1982) il fatto che maggiore sia la distanza applicata e maggiore risulterà l’effetto illusivo che si presenta. L’illusione di Weber e l’illusione tattile orientazione-dipendente sono spiegate in letteratura considerando differenze riguardanti la densità di recettori, gli effetti di magnificazione corticale a livello della corteccia primaria somatosensoriale (regioni della corteccia somatosensoriale, di dimensioni differenti, sono adibite a diverse regioni corporee) e differenze nella dimensione e forma dei campi recettivi. Tuttavia tali effetti di illusione risultano molto meno rilevanti rispetto a quelli che ci si aspetta semplicemente considerando i meccanismi fisiologici, elencati in precedenza, che li causano. Ciò suggerisce che l’informazione tattile elaborata a livello della corteccia primaria somatosensoriale, riceva successivi step di elaborazione in aree corticali di più alto livello. Esse agiscono allo scopo di ridurre il divario fra distanza percepita trasversalmente e distanza percepita longitudinalmente, rendendole più simili tra loro. Tale processo assume il nome di “Rescaling Process”. I meccanismi neurali che operano nel cervello allo scopo di garantire Rescaling Process restano ancora largamente sconosciuti. Perciò, lo scopo del mio progetto di tesi è stato quello di realizzare un modello di rete neurale che simulasse gli aspetti riguardanti la percezione tattile, l’illusione orientazione-dipendente e il processo di rescaling avanzando possibili ipotesi circa i meccanismi neurali che concorrono alla loro realizzazione. Il modello computazionale si compone di due diversi layers neurali che processano l’informazione tattile. Uno di questi rappresenta un’area corticale di più basso livello (chiamata Area1) nella quale una prima e distorta rappresentazione tattile è realizzata. Per questo, tale layer potrebbe rappresentare un’area della corteccia primaria somatosensoriale, dove la rappresentazione della distanza tattile è significativamente distorta a causa dell’anisotropia dei campi recettivi e della magnificazione corticale. Il secondo layer (chiamato Area2) rappresenta un’area di più alto livello che riceve le informazioni tattili dal primo e ne riduce la loro distorsione mediante Rescaling Process. Questo layer potrebbe rappresentare aree corticali superiori (ad esempio la corteccia parietale o quella temporale) adibite anch’esse alla percezione di distanze tattili ed implicate nel Rescaling Process. Nel modello, i neuroni in Area1 ricevono informazioni dagli stimoli esterni (applicati sulla cute) inviando quindi informazioni ai neuroni in Area2 mediante sinapsi Feed-forward eccitatorie. Di fatto, neuroni appartenenti ad uno stesso layer comunicano fra loro attraverso sinapsi laterali aventi una forma a cappello Messicano. E’ importante affermare che la rete neurale implementata è principalmente un modello concettuale che non si preme di fornire un’accurata riproduzione delle strutture fisiologiche ed anatomiche. Per questo occorre considerare un livello astratto di implementazione senza specificare un’esatta corrispondenza tra layers nel modello e regioni anatomiche presenti nel cervello. Tuttavia, i meccanismi inclusi nel modello sono biologicamente plausibili. Dunque la rete neurale può essere utile per una migliore comprensione dei molteplici meccanismi agenti nel nostro cervello, allo scopo di elaborare diversi input tattili. Infatti, il modello è in grado di riprodurre diversi risultati riportati negli articoli di Green e Longo & Haggard.

Fluid dynamic analysis and modelling of industrial chemical equipment

The research is aimed at contributing to the identification of reliable fully predictive Computational Fluid Dynamics (CFD) methods for the numerical simulation of equipment typically adopted in the chemical and process industries. The apparatuses selected for the investigation, specifically membrane modules, stirred vessels and fluidized beds, were characterized by a different and often complex fluid dynamic behaviour and in some cases the momentum transfer phenomena were coupled with mass transfer or multiphase interactions. Firs of all, a novel modelling approach based on CFD for the prediction of the gas separation process in membrane modules for hydrogen purification is developed. The reliability of the gas velocity field calculated numerically is assessed by comparison of the predictions with experimental velocity data collected by Particle Image Velocimetry, while the applicability of the model to properly predict the separation process under a wide range of operating conditions is assessed through a strict comparison with permeation experimental data. Then, the effect of numerical issues on the RANS-based predictions of single phase stirred tanks is analysed. The homogenisation process of a scalar tracer is also investigated and simulation results are compared to original passive tracer homogenisation curves determined with Planar Laser Induced Fluorescence. The capability of a CFD approach based on the solution of RANS equations is also investigated for describing the fluid dynamic characteristics of the dispersion of organics in water. Finally, an Eulerian-Eulerian fluid-dynamic model is used to simulate mono-disperse suspensions of Geldart A Group particles fluidized by a Newtonian incompressible fluid as well as binary segregating fluidized beds of particles differing in size and density. The results obtained under a number of different operating conditions are compared with literature experimental data and the effect of numerical uncertainties on axial segregation is also discussed.

Modelling and analysis of internally BFRP reinforced beams at elevated temperatures

The aim of the work is to conduct a finite element model analysis on a small – size concrete beam and on a full size concrete beam internally reinforced with BFRP exposed at elevated temperatures. Experimental tests performed at Kingston University have been used to compare the results from the numerical analysis for the small – size concrete beam. Once the behavior of the small – size beam at room temperature is investigated and switching to the heating phase reinforced beams are tested at 100°C, 200°C and 300°C in loaded condition. The aim of the finite element analysis is to reflect the three – point bending test adopted into the oven during the exposure of the beam at room temperature and at elevated temperatures. Performance and deformability of reinforced beams are straightly correlated to the material properties and a wide analysis on elastic modulus and coefficient of thermal expansion is given in this work. Develop a good correlation between the numerical model and the experimental test is the main objective of the analysis on the small – size concrete beam, for both modelling the aim is also to estimate which is the deterioration of the material properties due to the heating process and the influence of different parameters on the final result. The focus of the full – size modelling which involved the last part of this work is to evaluate the effect of elevated temperatures, the material deterioration and the deflection trend on a reinforced beam characterized by a different size. A comparison between the results from different modelling has been developed.