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The design of metamaterials relies on numerical simulations to both obtain the basic distribution of displacements, stresses and strains throughout the domain, and to find structures that handle the loads optimally. Linear elasticity theory is often employed for these simulations; however, this formulation fails to capture large displacements, and the results obtained in highly deformed structures may not be as efficient as possible. In this present work, the goal is to solve hyperelastic problems using Neo-hookean materials, using a formulation geared towards the field of topology optimization for further later implementations. Hyperelasticity is posed as a minimization problem, which is discretized using the finite element method, and solved using a Newton-Raphson algorithm implemented in a MATLAB-based topology optimization toolbox. After showing that the formulation is consistent with the small displacements theory, four tests are carried out to validate the implementation. The results obtained are promising from a physical meaning perspective, but a lack of quadratic convergence in the Newton-Raphson algorithm suggests the presence of an error in the calculation of the tangent operator.

Aquest treball implementa una metodologia per analitzar l'expressió dels morfògens, que són molècules o factors que actuen com a senyals químiques fonamentals en el desenvolupament d'un organisme i són essencials per a la formació de patrons en la biologia. Aquests morfògens estan presents en imatges de LFSM (microscòpia de làmina de fluorescència per llum) obtingudes durant el procés de regeneració de l'articulació sinovial de l'Axolotl, capturades mitjançant la tècnica de HCR FISH (Cadena de Reacció d'Hibridació Fluorescent in situ, per les seves sigles en anglès), amb la finalitat de quantificar i mesurar els principals patrons de concentració. Per aconseguir-ho, s'utilitzen les eines proporcionades per les aplicacions d'anàlisi d'imatges en l'entorn MATLAB, en conjunció amb la teoria relacionada amb l'anàlisi d'imatges de fluorescència i els fonaments de les imatges biològiques. L'objectiu principal és establir un marc de referència per als models proposats en la predicció de patrons de Turing en la regeneració cel·lular., Este trabajo implementa una metodología para analizar la expresión de los morfogenes, que son moléculas o factores que actúan como señales químicas fundamentales en el desarrollo de un organismo, y son esenciales para la formación de patrones en la biología. Estos morfogenes están presentes en imágenes de LFSM (microscopía de lámina de fluorescencia por luz) obtenidas durante el proceso de regeneración de la articulación sinovial del Axolotl, capturadas mediante la técnica de HCR FISH (Cadena de Reacción de Hibridación Fluorescente in situ, por sus siglas en inglés), con el fin de cuantificar y medir los principales patrones de concentración. Para lograrlo, se utilizan las herramientas proporcionadas por las aplicaciones de análisis de imágenes en el entorno MATLAB, en conjunción con la teoría relacionada con el análisis de imágenes de fluorescencia y los fundamentos de las imágenes biológicas. El objetivo principal es establecer un marco de referencia para los modelos propuestos en la predicción de patrones de Turing en la regeneración celular., This work implements a fundamental methodology to analyze the expression of morphogens, which are molecules or factors that act as fundamental chemical signals in the development of an organism and are essential for the formation of patterns in biology. These morphogens are present in images obtained through LFSM (Light Sheet Fluorescence Microscopy) during the regeneration process of the synovial joint in Axolotls, captured using the HCR FISH technique (Fluorescent In Situ Hybridization Chain Reaction), with the aim of quantifying and measuring the main concentration patterns. To achieve this, the tools provided by image analysis applications in the MATLAB environment are used in conjunction with the theory related to fluorescence image analysis and the fundamentals of biological images. The main objective is to establish a reference framework for the proposed models in the prediction of Turing patterns in cellular regeneration.

En un món on la digitalització de processos és una tendència, sorgeix sovint la necessitat de desenvolupar eines tecnològiques que ens ajudin a realitzar certes tasques. D’aquesta manera, la feina que realitzem les persones adquireix un valor afegit, deixant en mans de la tecnologia i els ordinadors aquells processos més rutinaris i que es poden automatitzar. Aquest projecte n’és una mostra. L’elaboració del pla de vol per part del pilot d’una aeronau és una activitat imprescindible per a poder assegurar el correcte desenvolupament d’un vol. Sota el marc normatiu corresponent i les indicacions del manual de vol, el pilot ha d’efectuar una sèrie de verificacions complexes, però que sovint acaben resultant repetitives. Davant d’aquesta situació ha sorgit la idea de poder automatitzar l’elaboració d’un pla de vol per mitjà d’un programa que assisteixi al pilot. Tenint en compte la facilitat amb la que hom pot disposar d’un terminal mòbil amb capacitats similars a les d’un ordinador, s’obre la via de poder treballar amb una aplicació mòbil. D’aquesta manera, el present projecte s’ha centrat en estudiar la viabilitat de desenvolupar una eina com l’esmentada i centrada en un helicòpter biturbina Bell 412. Per a aquest estudi s’ha programat una aplicació prototipus que reprodueixi el procés que realitza el pilot. Aquesta, però, realitza els càlculs i les verificacions de manera automàtica, permetent a l’usuari centrar-se en les dades d’entrada que facilita i en els resultats que s’obtenen. En aquest sentit, comença la verificació tenint en comte aspectes previs al vol com poden ser l’anàlisi de pesos i centratge. A partir d’aquí passa per les comprovacions corresponents respecte a les actuacions que comprenen totes les fases del vol des de l’enlairament fins a l’aterratge. Els resultats obtinguts en aquest estudi demostren que una aplicació que realitzi aquestes tasques és viable. Si bé el programa que s’ha desenvolupat presenta limitacions implícites i ofereix resultats q

Understanding and characterizing the mechanical and structural properties of brain tissue is essential for developing and calibrating reliable material models. Based on the Theory of Porous Media, a novel nonlinear poro-viscoelastic computational model was recently proposed to describe the mechanical response of the tissue under different loading conditions. The model contains parameters related to the time-dependent behavior arising from both the viscoelastic relaxation of the solid matrix and its interaction with the fluid phase. This study focuses on the characterization of these parameters through indentation experiments on a tailor-made polyvinyl alcohol-based hydrogel mimicking brain tissue. The material behavior is adjusted to ex vivo porcine brain tissue. An inverse parameter identification scheme using a trust region reflective algorithm is introduced and applied to match experimental data obtained from the indentation with the proposed computational model. By minimizing the error between experimental values and finite element simulation results, the optimal constitutive model parameters of the brain tissue-mimicking hydrogel are extracted. Finally, the model is validated using the derived material parameters in a finite element simulation., We gratefully acknowledge the financial support by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) through grants BU 3728/3-1 and STE 544/70-1 and financial support by the Austrian Science Fund (FWF, Project-Nr. I 4828-N)., Peer Reviewed, Postprint (published version)

A substantial fraction of the time that computational modellers dedicate to developing their models is actually spent trouble-shooting and debugging their code. However, how this process unfolds is seldom spoken about, maybe because it is hard to articulate as it relies mostly on the mental catalogues we have built with the experience of past failures. To help newcomers to the field of material modelling, here we attempt to fill this gap and provide a perspective on how to identify and fix mistakes in computational solid mechanics models. To this aim, we describe the components that make up such a model and then identify possible sources of errors. In practice, finding mistakes is often better done by considering the symptoms of what is going wrong. As a consequence, we provide strategies to narrow down where in the model the problem may be, based on observation and a catalogue of frequent causes of observed errors. In a final section, we also discuss how one-time bug-free models can be kept bug-free in view of the fact that computational models are typically under continual development. We hope that this collection of approaches and suggestions serves as a “road map” to find and fix mistakes in computational models, and more importantly, keep the problems solved so that modellers can enjoy the beauty of material modelling and simulation., EC and JPP wish to thank their former supervisor Paul Steinmann for the inspiration to write this paper, which can be traced back to the talk we prepared for the ECCM-ECFD conference held in Glasgow in 2018. EC’s work was partially supported by the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 841047. WB’s work was partially supported by the National Science Foundation under award OAC-1835673; by award DMS-1821210; by award EAR-1925595; and by the Computational Infrastructure in Geodynamics initiative (CIG), through the National Science Foundation under Award EAR-1550901 and The University of California – Davis ., Peer Reviewed, Postprint (published version)

The competence to apply ethics in the development of new technologies is currently not addressed in university programs for aerospace engineering at the national level. Therefore, the purpose of this project is to guide future aerospace engineers in making ethical decisions. This project is divided into three different parts. In the first one, different teaching methodologies are studied. Active learning, which includes case studies, is concluded to be the most effective for students. In the second part, using these methodologies, the syllabus for an elective on ethics for the aerospace engineering curriculum has been developed. This syllabus covers important moral concepts in the design, development, testing, and certification processes, as well as the concept of responsibility. Finally, in the third part, a teaching guide has been developed, divided into each session, to carry out the instruction of this course. After all, this project has successfully fulfilled all its initial requirements and developed a course that is ready to be taught.

As the era of frequent human space travel nears, it becomes imperative to understand the brain’s reaction to microgravity conditions. This research delves into the intricate mechanics of brain tissue, focusing specifically on its poro-viscoelastic characteristics. Employing a novel finite element computational model, which is built on the open-source deal.II library, the study analyses experimental data from ex vivo mice brain tissue tests. The detailed investigation into the porous and viscous response separation aids in refining the model’s accuracy. Initially, post-processing of the experimental data is executed, drawing from foundational principles of poroelasticity and viscoelasticity. Subsequently, a sensitivity analysis is undertaken to identify key parameters in the computational model, enhancing the comprehension of the model’s intricacies. Importantly, the emphasis of the study remains on the brain’s biophysical behavior, avoiding any digression into algorithmic or material model modifications. With the insights obtained, the experimental setup is replicated, identifying the inherent limitations of the experiments and providing valuable pointers on potential improvements. Bridging the computational model with the experimental data, this work represents a step towards the long-term objective of comprehending brain mechanics, as well as its response to microgravity.

En aquest treball de fi de grau es presenta una proposta detallada per canviar la metodologia docent de l’assignatura de Disseny d’Avions, impartida en el grau d’Enginyeria en Vehicles Aeroespacials de l’ESEIAAT, UPC. L’objectiu principal, doncs, és afavorir la participació activa dels alumnes durant el procés d’aprenentatge a través d’una metodologia d’aprenentatge basat en projectes (Project-Based Learning, PBL). En primer lloc, s’ha dut a terme una recerca exhaustiva sobre les característiques de l’aprenentatge basat en projectes, el qual s’ha definit com un mètode d’ensenyament en què els estudiants aprenen participant activament en projectes del món real i personalment significatius. A través d’aquesta recerca, s’ha pogut constatar que el PBL millora el rendiment acadèmic dels alumnes, ja que augmenta la seva motivació i implicació en les sessions lectives. També, és un mètode que potencia diverses habilitats socials com el treball en equip o la cooperació entre grups de treball, molt lligat amb el concepte d’aprenentatge cooperatiu (cooperative learning). Finalment, s’han analitzat algunes experiències PBL dutes a terme en assignatures de l’àmbit aeroespacial en diferents graus universitaris, en què els resultats obtinguts són generalment satisfactoris. Tenint tot això en compte, s’ha optat per implementar una nova metodologia docent per a l’assignatura Disseny d’Avions que incorpori algunes característiques de l’aprenentatge basat en projectes. Així doncs, s’han planificat les sessions lectives corresponents a la primera meitat de l’assignatura i s’ha generat el material docent necessari per tal que els estudiants puguin assolir els objectius de la matèria. D’aquesta manera, s’han elaborat qüestionaris previs a les sessions i s’ha redactat un treball de referència que servirà com a model a l’hora de fer el disseny conceptual de l’avió. Per últim, es conclou que la proposta elaborada permetrà replantejar l’assignatura de Disseny d’Avions a través d’una metodol

Movement-induced forces are critical to correct joint formation, but it is unclear how cells sense and respond to these mechanical cues. To study the role of mechanical stimuli in the shaping of the joint, we combined experiments on regenerating axolotl (Ambystoma mexicanum) forelimbs with a poroelastic model of bone rudiment growth. Animals either regrew forelimbs normally (control) or were injected with a transient receptor potential vanilloid 4 (TRPV4) agonist during joint morphogenesis. We quantified growth and shape in regrown humeri from whole-mount light sheet fluorescence images of the regenerated limbs. Results revealed significant differences in morphology and cell proliferation between groups, indicating that TRPV4 desensitization has an effect on joint shape. To link TRPV4 desensitization with impaired mechanosensitivity, we developed a finite element model of a regenerating humerus. Local tissue growth was the sum of a biological contribution proportional to chondrocyte density, which was constant, and a mechanical contribution proportional to fluid pressure. Computational predictions of growth agreed with experimental outcomes of joint shape, suggesting that interstitial pressure driven from cyclic mechanical stimuli promotes local tissue growth. Predictive computational models informed by experimental findings allow us to explore potential physical mechanisms involved in tissue growth to advance our understanding of the mechanobiology of joint morphogenesis., This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 841047 and the National Science Foundation under grant no. 1727518. J.J.M. has been also funded by the Spanish Ministry of Science and Innovation under grant no. DPI2016-74929-R, and by the local government Generalitat de Catalunya under grant no. 2017 SGR 1278. K.L. was supported by a Northeastern University Undergraduate Research and Fellowships PEAK Experiences Award., Peer Reviewed, Postprint (published version)

Segmentation of 3D images to identify cells and their molecular outputs can be difficult and tedious. Machine learning algorithms provide a promising alternative to manual analysis as emerging 3D image processing technology can save considerable time. For those unfamiliar with machine learning or 3D image analysis, the rapid advancement of the field can make navigating the newest software options confusing. In this paper, two open-source machine learning algorithms, Cellpose and Stardist, are compared in their application on a 3D light sheet dataset counting fluorescently stained proliferative cell nuclei. The effects of image tiling and background subtraction are shown through image analysis pipelines for both algorithms. Based on our analysis, the relative ease of use of Cellpose and the absence of need to train a model leaves it a strong option for 3D cell segmentation despite relatively longer processing times. When Cellpose's pretrained model yields results that are not of sufficient quality, or the analysis of a large dataset is required, Stardist may be more appropriate. Despite the time it takes to train the model, Stardist can create a model specialized to the users' dataset that can be iteratively improved until predictions are satisfactory with far lower processing time relative to other methods., This project has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 841047 and NSF CMMI #1727518., Peer Reviewed, Postprint (author's final draft)

The development of the vertebrate joint is punctuated by a series of coordinated events regulated by molecular markers called morphogens. Some morphogens can activate or inhibit proliferation and/or the cell differentiation process, which results in tissue growth. The way morphogens diffuse and interact is still not well understood. The reaction-diffusion equations have been used to model the patterning of morphogens in limb development. This work aims at studying how pattern may develop and influence the formation of a limb joint during embryo morphogenesis using the Schnakenberg reaction system. Our study focuses on identifying the conditions for the appearance of Turing patterns by studying the reaction-diffusion equations analytically and using finite element analysis. We show that the model parameters, the initial conditions, the boundary conditions and growth of the domain impact the evolution of pattern. Because non-linearities play a strong role in the pattern production, final patterns are difficult to predict especially in the growth process, Incoming

Aquest treball s’inicia amb la finalitat de desenvolupar l’estudi per l’automatització del càlcul de les actuacions de vol de l’helicòpter biturbina Eurocopter AS355 amb la intenció de facilitar i agilitzar la preparació del pla de vol. Per a assolir aquest objectiu, s’ha de comprovar la normativa aplicable a aquest tipus d’operacions, consistent en dos documents: la normativa general europea d’actuacions classe 1 Air Operations (EASA EAR Regulation No 965/2012) i el manual de vol específic de l’Eurocopter AS355 (Eurocopter Flight Manual AS 355 N). Per dur a terme aquesta automatització, es fa servir el programa Engauge Digitizer per a la digitalització de les corbes, i GNU Octave per al tractament de les dades i obtenció de resultats. El resultat d’aquest treball és un codi que, a partir de dades obtingudes directament de l’usuari i de la lectura digital de gràfiques del manual de vol, calcula els paràmetres necessaris per a omplir el pla de vol i compara els resultats amb la normativa per a comprovar que siguin vàlids. També mostra les gràfiques digitalitzades per a una millor visualització dels resultats. Finalment, es fa un procés de validació i verificació dels mètodes emprats pel codi i dels resultats per tal de garantir que els resultats proporcionats són de confiança. Aquest procés es basa a comparar les corbes digitals i analògiques per analitzar l’error comès en les regressions, i comparar resultats per a comprovar si l’error és destacable o no. Es conclou que els resultats són molt fiables per als rangs d’actuació locals (Catalunya).

Endochondral ossification, the process by which long bones grow in length, is regulated by mechanical forces. Computational models, specifically finite element models, have been used for decades to understand the role of mechanical loading on endochondral ossification. This perspective outlines the stages of model development in which models are used to: 1) explore phenomena, 2) explain pathologies, 3) predict clinical outcomes, and 4) design therapies. As the models progress through the stages, they increase in specificity and biofidelity. We give specific examples of models of endochondral ossification and expect models of other mechanobiological systems to follow similar development stages., Peer Reviewed, Postprint (published version)

Brain tissue is one of the softest tissues in the human body and the quantification of its mechanical properties has challenged scientists over the past decades. Associated experimental results in the literature have been contradictory as characterizing the mechanical response of brain tissue not only requires well-designed experimental setups that can record the ultrasoft response, but also appropriate approaches to analyze the corresponding data. Due to the extreme complexity of brain tissue behavior, nonlinear continuum mechanics has proven an expedient tool to analyze testing data and predict the mechanical response using a combination of hyper-, visco-, or poro-elastic models. Such models can not only allow for personalized predictions through finite element simulations, but also help to comprehensively understand the physical mechanisms underlying the tissue response. Here, we use a nonlinear poro-viscoelastic computational model to evaluate the effect of different intrinsic material properties (permeability, shear moduli, nonlinearity, viscosity) on the tissue response during different quasi-static biomechanical measurements, i.e., large-strain compression and tension as well as indentation experiments. We show that not only the permeability but also the properties of the viscoelastic solid largely control the fluid flow within and out of the sample. This reveals the close coupling between viscous and porous effects in brain tissue behavior. Strikingly, our simulations can explain why indentation experiments yield that white matter tissue in the human brain is stiffer than gray matter, while large-strain compression experiments show the opposite trend. These observations can be attributed to different experimental loading and boundary conditions as well as assumptions made during data analysis. The present study provides an important step to better understand experimental data previously published in the literature and can help to improve experimental setups, Peer Reviewed, Postprint (published version)

Measuring nascent macromolecular synthesis in vivo is key to understanding how cells and tissues progress through development and respond to external cues. Here we perform in vivo injection of alkyne- or azide-modified analogs of thymidine, uridine, methionine, and glucosamine to label nascent synthesis of DNA, RNA, protein, and glycosylation. Three-dimensional volumetric imaging of nascent macromolecule synthesis was performed in axolotl salamander tissue using whole-mount click chemistry-based fluorescent staining followed by light sheet fluorescent microscopy. We also developed an image processing pipeline for segmentation and classification of morphological regions of interest and individual cells, and we apply this pipeline to the regenerating humerus. We demonstrate our approach is sensitive to biological perturbations by measuring changes in DNA synthesis after limb denervation. This method provides a powerful means to quantitatively interrogate macromolecule synthesis in heterogenous tissues at the organ, cellular, and molecular levels of organization, Peer Reviewed, Postprint (published version)

The biomechanical characterization of human brain tissue and the development of appropriate mechanical models is crucial to provide realistic computational predictions that can assist personalized treatment of neurological disorders with a strong biomechanical component. Here, we present a novel material model that combines finite viscoelasticity with a nonlinear biphasic poroelastic formulation, developed within the context of the Theory of Porous Media. Embedded in a finite element framework, our model is capable of predicting the brain tissue response under multiple loading conditions. We show that our model can capture both experimentally observed fluid flow and conditioning aspects of brain tissue behavior in addition to its well-established nonlinear and compression–tension asymmetric characteristics. Our results support the notion that porous and viscous effects are highly interrelated and that additional experimental data are required to reliably identify the model parameters. The modular and object-oriented design with automatic differentiation makes our open-source code easily amendable to future extensions. We provide a solid foundation towards the development of a reliable and comprehensive biomechanical model for brain tissue, which will be a versatile and useful tool in elucidating the rheology of brain tissue behavior to help the biomedical and clinical communities in the future study, prevention and treatment of brain injury and disease, Peer Reviewed, Postprint (author's final draft)

Endoluminal vacuum-assisted closure (E-VAC) is a promising therapy to treat anastomotic leakages of the oesophagus and bowel which are associated with high morbidity and mortality rates. An open-pore polyurethane foam is introduced into the leakage cavity and connected to a device that applies a suction pressure to accelerate the closure of the defect. Computational analysis of this healing process can advance our understanding of the biomechanical mechanisms at play. To this aim, we use a dual-stage finite-element analysis in which (i) the structural problem addresses the cavity reduction caused by the suction and (ii) a new constitutive formulation models tissue healing via permanent deformations coupled to a stiffness increase. The numerical implementation in an in-house code is described and a qualitative example illustrates the basic characteristics of the model. The computational model successfully reproduces the generic closure of an anastomotic leakage cavity, supporting the hypothesis that suction pressure promotes healing by means of the aforementioned mechanisms. However, the current framework needs to be enriched with empirical data to help advance device designs and treatment guidelines. Nonetheless, this conceptual study confirms that computational analysis can reproduce E-VAC of anastomotic leakages and establishes the bases for better understanding the mechanobiology of anastomotic defect healing., Peer Reviewed, Postprint (published version)

Remodelling of soft biological tissue is characterized by interacting biochemical and biomechanical events, which change the tissue's microstructure, and, consequently, its macroscopic mechanical properties. Remodelling is a well-defined stage of the healing process, and aims at recovering or repairing the injured extracellular matrix. Like other physiological processes, remodelling is thought to be driven by homeostasis, i.e. it tends to re-establish the properties of the uninjured tissue. However, homeostasis may never be reached, such that remodelling may also appear as a continuous pathological transformation of diseased tissues during aneurysm expansion, for example. A simple constitutive model for soft biological tissues that regards remodelling as homeostatic-driven turnover is developed. Specifically, the recoverable effective tissue damage, whose rate is the sum of a mechanical damage rate and a healing rate, serves as a scalar internal thermodynamic variable. In order to integrate the biochemical and biomechanical aspects of remodelling, the healing rate is, on the one hand, driven by mechanical stimuli, but, on the other hand, subjected to simple metabolic constraints. The proposed model is formulated in accordance with continuum damage mechanics within an open-system thermodynamics framework. The numerical implementation in an in-house finite-element code is described, particularized for Ogden hyperelasticity. Numerical examples illustrate the basic constitutive characteristics of the model and demonstrate its potential in representing aspects of remodelling of soft tissues. Simulation results are verified for their plausibility, but also validated against reported experimental data., Peer Reviewed, Postprint (author's final draft)

Versió amb diverses seccions encriptades, per drets d'editor, Premi extraordinari doctorat UPC curs 2015-2016, àmbit d’Enginyeria Civil, Living biological tissues are complex structures that have the capacity of evolving in response to external loads and environmental stimuli. The adequate modelling of soft biological tissue behaviour is a key issue in successfully reproducing biomechanical problems through computational analysis. This study presents a general constitutive formulation capable of representing the behaviour of these tissues through finite element simulation. It is based on phenomenological models that, used in combination with the generalized mixing theory, can numerically reproduce a wide range of material behaviours. First, the passive behaviour of tissues is characterized by means of hyperelastic and finite-strain damage models. A new generalized damage model is proposed, providing a flexible and versatile formulation that can reproduce a wide range of tissue behaviour. It can be particularized to any hyperelastic model and requires identifying only two material parameters. Then, the use of these constitutive models with generalized mixing theory in a finite-strain framework is described and tools to account for the anisotropic behaviour of tissues are put forth. The active behaviour of tissues is characterized through constitutive models capable of reproducing the growth and remodelling phenomena. These are built on the hyperelastic and damage formulations described above and, thus, represent the active extension of the passive tissue behaviour. A growth model considering biological availability is used and extended to include directional growth. In addition, a novel constitutive model for homeostatic-driven turnover remodelling is presented and discussed. This model captures the stiffness recovery that occurs in healing tissues, understood as a recovery or reversal of damage in the tissue, which is driven by both mechanical and biochemical stimuli. Finally, the issue of correctly identifying the material parameters for computational modelling is addressed. An inverse method using, Els teixits biològics vius són estructures complexes que tenen la capacitat d'evolucionar en resposta a càrregues externes i estímuls ambientals. El modelat adequat del comportament del teixit biològic tou és un tema clau per poder reproduir amb èxit problemes biomecànics mitjançant anàlisi computacional. Aquest estudi presenta una formulació constitutiva general capaç de representar el comportament d'aquests teixits mitjançant la simulació amb elements finits. Es basa en models fenomenològics que, usats en combinació amb la teoria de mescles generalitzada, permeten reproduir numèricament un ampli ventall de comportaments materials. Primer, el comportament passiu dels teixits es caracteritza amb models hiperelàstics i de dany en grans deformacions. Es proposa un model generalitzat de dany que proporciona una formulació versàtil i flexible per poder reproduir una extensa gamma de conductes de teixits. Pot ser particularitzat amb qualsevol model hiperelàstic i requereix identificar tan sols dos paràmetres materials. Llavors, es descriu l'ús d'aquests models constitutius en conjunt amb la teoria generalitzada de mescles, desenvolupada en el marc de grans deformacions, i es presenten eines que permeten incorporar les propietats anisòtropes dels teixits. El comportament actiu dels teixits es caracteritza mitjançant models constitutius capaços de reproduir els fenòmens de creixement i remodelació. Aquests es construeixen sobre les formulacions d'hiperelasticitat i dany descrites anteriorment i, per tant, suposen l'extensió activa del comportament passiu del teixit. Es fa servir un model de creixement que té en compte la disponibilitat biològica de l'organisme, que després s'amplia per incloure dany direccional en el model. També es presenta i analitza un nou model constitutiu per al remodelat per renovació tendint a l’homeòstasi (homeostatic-driven turnover remodelling). Aquest model captura la recuperació de rigidesa que s'observa en teixits que es guareixen. Aquí, el re, Award-winning, Postprint (published version)

This is the accepted version of the following article: [Comellas, E., Bellomo, F. J., and Oller, S. (2015) A generalized finite-strain damage model for quasi-incompressible hyperelasticity using hybrid formulation. Int. J. Numer. Meth. Engng, doi: 10.1002/nme.5118.], which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/nme.5118/abstract, A new generalized damage model for quasi-incompressible hyperelasticity in a total Lagrangian finite-strain framework is presented. A Kachanov-like reduction factor (1 - D) is applied on the deviatoric part of the hyperelastic constitutive model. Linear and exponential softening are defined as damage evolution laws, both describable in terms of only two material parameters. The model is formulated following continuum damage mechanics theory such that it can be particularized for any hyperelastic model based on the volumetric–isochoric split of the Helmholtz free energy. However, in the present work, it has been implemented in an in-house finite element code for neo-Hooke and Ogden hyperelasticity. The details of the hybrid formulation used are also described. A couple of three-dimensional examples are presented to illustrate the main characteristics of the damage model. The results obtained reproduce a wide range of softening behaviors, highlighting the versatility of the formulation proposed. The damage formulation has been developed to be used in conjunction with mixing theory in order to model the behavior of fibered biological tissues. As an example, the markedly different behaviors of the fundamental components of the rectus sheath were reproduced using the damage model, obtaining excellent correlation with the experimental results from literature., Peer Reviewed, Postprint (author’s final draft)

An optimization method to identify the material parameters of composite structures using an inverse method is proposed. This methodology compares experimental results with their numerical reproduction using the finite element method in order to obtain an estimation of the error between the results. This error estimation is then used by an evolutionary optimizer to determine, in an iterative process, the value of the material parameters which result in the best numerical fit. The novelty of the method is in the coupling between the simple genetic algorithm and the mixing theory used to numerically reproduce the composite behavior. The methodology proposed has been validated through a simple example which illustrates the exploitability of the method in relation to the modeling of damaged composite structures., Peer Reviewed, Postprint (author’s final draft)

Cervical spine discectomy is a relatively common medical procedure which entails the surgical removal of a herniated intervertebral disc which is then replaced with an adequate prosthesis. Surgeons rely on their expertise to minimize the damage induced on the adjacent vertebrae and discs during this invasive procedure in order to reduce the patient's postsurgical distress. A typical cervical spine discectomy has been modelled and tested using the Finite Element Method (FEM) with the intention of contributing to better elucidate its immediate physical consequences on the vertebrae and intervertebral discs. Internal stresses, strains and damage levels can be obtained through the use of FE models, which can prove useful in improving surgical procedures or tailoring them to the need of particular patients. To this aim, a model of four cervical vertebrae with their corresponding discs has been built. Spinal ligaments, zygapophyseal joints and uncovertebral joints have also been included. The vertebrae have been modelled using a damage model whilst the intervertebral discs and ligaments have been treated as separate hyperelastic materials. Also, the nucleus and the annulus of the discs have been di erentiated. The problem has been solved following non-linear large deformation theory and considering prestress in the ligaments. The model's accuracy has been assessed through comparison of previously published results for di erent spinal movements (N. Kallemeyn et al., Med Eng Phys, 32(5):482-489 (2010)). Then, the model has been numerically tested for a load case representative of the discectomy procedure., Peer Reviewed, Postprint (published version)

El TFC consisteix en la realització de la justificació estructural del calaix de torsió de l'estabilitzador horitzontal d'una aeronau. Les principals activitats a realitzar en el TFC són: 1.- definició/recopilació dels admissibles del materials 2.- selecció dels casos crítics de càrrega 3.- anàlisi detallat dels elements estructurals (spars, skins, stringers, stiffeners, etc.) 4.- compilació dels resultats. Els principals anàlisis estructurals que seràn duts a terme són: 1.- pandeig i resistència dels panells amb i sense forat 2.- interaccions entre pandeig i concentració d'esforços en panells amb forats 3.- pandeig, resistència i crippling dels rigiditzadors 4.- estudi del rematxat i pegat i dels angulars entre d'altres.