Finite deformation elastography of articular cartilage and biomaterials based on imaging and topology optimization

Tissues and engineered biomaterials exhibit exquisite local variation in stiffness that defines their function. Conventional elastography quantifies stiffness in soft (e.g. brain, liver) tissue, but robust quantification in stiff (e.g. musculoskeletal) tissues is challenging due to dissipation of high frequency shear waves. We describe new development of finite deformation elastography that utilizes magnetic resonance imaging of low frequency, physiological-level (large magnitude) displacements, coupled to an iterative topology optimization routine to investigate stiffness heterogeneity, including spatial gradients and inclusions. We reconstruct 2D and 3D stiffness distributions in bilayer agarose hydrogels and silicon materials that exhibit heterogeneous displacement/strain responses. We map stiffness in porcine and sheep articular cartilage deep within the bony articular joint space in situ for the first time. Elevated cartilage stiffness localized to the superficial zone is further related to collagen fiber compaction and loss of water content during cyclic loading, as assessed by independent T2 measurements. We additionally describe technical challenges needed to achieve in vivo elastography measurements. Our results introduce new functional imaging biomarkers, which can be assessed nondestructively, with clinical potential to diagnose and track progression of disease in early stages, including osteoarthritis or tissue degeneration. </div

Reconstruction and Simulation of Cellular Traction Forces

Biological cells are able to sense the stiffness, geometry and topography of their environment and sensitively respond to it. For this purpose, they actively apply contractile forces to the extracellular space, which can be determined by traction force microscopy. Thereby cells are cultured on elastically deformable substrates and cellular traction patterns are quanti- tatively reconstructed from measured substrate deformations, by solving the inverse elastic problem. In this thesis we investigate the influence of environmental topography to cellular force generation and the distribution of intracellular tension. For this purpose, we reconstruct traction forces on wavy elastic substrates, using a novel technique based on finite element methods. In order to relate forces to single cell-matrix contacts and different structures of the cytoskeleton, we then introduce another novel variant of traction force microscopy, which introduces cell contraction modeling into the process of cellular traction reconstruction. This approach is robust against experimental noise and does not need regularisation. We apply this method to experimental data to demonstrate that different types of actin fibers in the cell statistically show different contractilities. We complete our investigation by simulation studies considering cell colonies and single cells as thermoelastically contracting continuum coupled to an elastic substrate. In particular we examined the effect of geometry on cellular behavior in collective cell migration and tissue invasion during tumor metastasis

Microstructures to control elasticity in 3D printing

We propose a method for fabricating deformable objects with spatially varying elasticity using 3D printing. Using a single, relatively stiff printer material, our method designs an assembly of small-scale microstructures that have the effect of a softer material at the object scale, with properties depending on the microstructure used in each part of the object. We build on work in the area of metamaterials, using numerical optimization to design tiled microstructures with desired properties, but with the key difference that our method designs families of related structures that can be interpolated to smoothly vary the material properties over a wide range. To create an object with spatially varying elastic properties, we tile the object's interior with microstructures drawn from these families, generating a different microstructure for each cell using an efficient algorithm to select compatible structures for neighboring cells. We show results computed for both 2D and 3D objects, validating several 2D and 3D printed structures using standard material tests as well as demonstrating various example applications

Stratégies efficaces en caractérisation des matériaux et calibration de modèles mécaniques pour la conception virtuelle des tôles métalliques

The mechanical design of sheet metal forming parts tends to be more virtual, reducing delays and manufacturing costs. Reliable numerical simulations can also lead to optimized metallic parts using accurately calibrated advanced constitutive models. Thus, the aim of this thesis is to improve the representation of the mechanical behavior of the material in the numerical model, by developing efficient and accurate methodologies to calibrate advanced constitutive models. A recent trend in material characterization is the use of a limited number of heterogeneous mechanical tests, which provide more valuable data than classical quasi-homogeneous tests. Yet, the design of the most suitable tests is still an open question. To that extent, an overview of heterogeneous mechanical tests for metallic sheets is provided. However, no standards exist for such tests, so specific metrics to analyze the achieved mechanical states are suggested and applied to four tests. Results show that the use of various metrics provides a good basis to qualitatively and quantitatively evaluate heterogeneous mechanical tests. Due to the development of full-field measurement techniques, it is possible to use heterogeneous mechanical tests to characterize the behavior of materials. However, no analytical solution exists between the measured fields and the material parameters. Inverse methodologies are required to calibrate constitutive models using an optimization algorithm to find the best material parameters. Most applications tend to use a gradient-based algorithm without exploring other possibilities. The performance of gradient-based and -free algorithms in the calibration of a thermoelastoviscoplastic model is discussed in terms of efficiency and robustness of the optimization process. Often, plane stress conditions are assumed in the calibration of constitutive models. Nevertheless, it is still unclear whether these are acceptable when dealing with large deformations. To further understand these limitations, the calibration of constitutive models is compared using the virtual fields method implemented in 2D and 3D frameworks. However, the 3D framework requires volumetric information of the kinematic fields, which is experimentally difficult to obtain. To address this constraint, an already existing volume reconstruction method, named internal mesh generation, is further improved to take into account strain gradients in the thickness. The uncertainty of the method is quantified through virtual experiments and synthetic images. Overall, the impact of this thesis is related to (i) the importance of establishing standard metrics in the selection and design of heterogeneous mechanical tests, and (ii) enhancing the calibration of advanced constitutive models from a 2D to a 3D framework.O projeto mecânico de peças por conformação de chapas metálicas tende a ser mais virtual, reduzindo atrasos e custos de produção. Simulações numéricas confiáveis também podem levar a peças optimizadas usando modelos constitutivos avançados calibrados com precisão. Assim, o objetivo desta tese é melhorar a representação do comportamento mecânico do material no modelo numérico, através do desenvolvimento de metodologias eficientes e precisas para a calibração de modelos constitutivos avançados. Uma tendência recente na caracterização de materiais é o uso de um número limitado de ensaios mecânicos heterogéneos, que fornecem dados mais valiosos do que os ensaios clássicos quase-homogéneos. No entanto, a concepção de ensaios mais adequados ainda é uma questão em aberto. Este trabalho detalha os ensaios mecânicos heterogêneos para chapas metálicas. No entanto, não existem ainda normas para estes ensaios, pelo que métricas específicas para analisar os estados mecânicos são sugeridas e aplicadas a quatro ensaios. Os resultados mostram que o uso de várias métricas disponibiliza uma boa base para avaliar ensaios mecânicos heterogéneos. Devido ao desenvolvimento de técnicas de medição de campo total, é possível utilizar ensaios mecânicos heterogéneos para caracterizar o comportamento dos materiais. No entanto, não existe uma solução analítica entre os campos medidos e os parâmetros do material. Metodologias inversas são necessárias para calibrar os modelos constitutivos usando um algoritmo de otimização para encontrar os melhores parâmetros do material. A maioria das aplicações tende a usar um algoritmo baseado em gradiente sem explorar outras possibilidades. O desempenho de vários algoritmos na calibração de um modelo termoelastoviscoplástico é discutido em termos de eficiência e robustez do processo de otimização. Frequentemente, são utilizadas condições de estado plano de tensão na calibração de modelos constitutivos, hipótese que é questionada quando se trata de grandes deformações. A calibração de modelos constitutivos é comparada usando o método de campos virtuais implementado em 2D e 3D. No entanto, a implementação 3D requer informações volumétricas dos campos cinemáticos, o que é experimentalmente difícil de obter. Um método de reconstrução volúmica já existente é melhorado para considerar os gradientes de deformação ao longo da espessura. A incerteza do método é quantificada através de ensaios virtuais e imagens sintéticas. No geral, o impacto desta tese está relacionado com (i) a importância de estabelecer métricas na seleção e concepção de ensaios mecânicos heterogéneos, e (ii) promover desenvolvimentos na calibração de modelos constitutivos avançados de 2D para 3D.La conception mécanique des pièces métalliques tend à être plus virtuelle, réduisant les délais et les coûts de fabrication. Des simulations numériques fiables peuvent conduire à des pièces optimisées en utilisant des modèles mécaniques avancés calibrés avec précision. Ainsi, l’objectif de cette thèse est d’améliorer la représentation du comportement mécanique du matériau dans le modèle numérique, en développant des méthodologies efficaces et précises pour calibrer des modèles de comportement avancés. Une tendance récente dans la caractérisation des matériaux est l’utilisation d’un nombre limité d’essais mécaniques hétérogènes, qui fournissent des données plus riches que les essais classiques quasi-homogènes. Pourtant, la conception des tests les plus adaptés reste une question ouverte. Ce tra- vail détaille les essais mécaniques hétérogènes pour les tôles métalliques. Cependant, aucune norme n’existe pour de tels tests, ainsi des métriques spécifiques pour analyser les états mécaniques sont suggérées et appliquées à quatre tests. Les résultats montrent que l’utilisation de diverses métriques fournit une bonne base pour évaluer des essais mécaniques hétérogènes. L’utilisation des essais mécaniques hétérogènes pour caractériser le com- portement des matériaux est rendue possible par des mesures de champ. Cependant, aucune solution analytique n’existe entre les champs mesurés et les paramètres du matériau. Des méthodologies inverses sont nécessaires pour calibrer les modèles de comportement à l’aide d’un algorithme d’optimi- sation afin de déterminer les meilleurs paramètres de matériau. Un algorithme basé sur le gradient est très fréquemment utilisé, sans explorer d’autres pos- sibilités. La performance de plusieurs algorithmes dans la calibration d’un modèle thermoélastoviscoplastique est discutée en termes d’efficacité et de robustesse du processus d’optimisation. Souvent, des conditions de contraintes planes sont supposées dans la cal- ibration des modèles, hypothèse qui est remise en cause dans le cas de forte localisation des déformations. La calibration de modèles de comporte- ment est comparée à l’aide de la méthode des champs virtuels développée dans les cadres 2D et 3D. Cependant, le cadre 3D nécessite des informations volumétriques des champs cinématiques, ce qui est expérimentalement dif- ficile à obtenir. Une méthode de reconstruction volumique déjà existante est encore améliorée pour prendre en compte les gradients de déformation dans l’épaisseur. L’incertitude de la méthode est quantifiée par des expériences virtuelles, à l’aide d’images de synthèse. Dans l’ensemble, l’impact de cette thèse est lié à (i) l’importance d’établir des métriques dans la sélection et la conception d’essais mécaniques hétérogènes, et (ii) à faire progresser la calibration de modèles de comportement avancés d’un cadre 2D à un cadre 3D.Programa Doutoral em Engenharia Mecânic

Pressure and saturation estimation from PRM time-lapse seismic data for a compacting reservoir

Observed 4D effects are influenced by a combination of changes in both pressure and saturation in the reservoir. Decomposition of pressure and saturation changes is crucial to explain the different physical variables that have contributed to the 4D seismic responses. This thesis addresses the challenges of pressure and saturation decomposition from such time-lapse seismic data in a compacting chalk reservoir. The technique employed integrates reservoir engineering concepts and geophysical knowledge. The innovation in this methodology is the ability to capture the complicated water weakening behaviour of the chalk as a non-linear proxy model controlled by only three constants. Thus, changes in pressure and saturation are estimated via a Bayesian inversion by employing compaction curves derived from the laboratory, constraints from the simulation model predictions, time strain information and the observed fractional change in and . The approach is tested on both synthetic and field data from the Ekofisk field in the North Sea. The results are in good agreement with well production data, and help explain strong localized anomalies in both the Ekofisk and Tor formations. These results also suggest updates to the reservoir simulation model. The second part of the thesis focuses on the geomechanics of the overburden, and the opportunity to use time-lapse time-shifts to estimate pore pressure changes in the reservoir. To achieve this, a semi-analytical approach by Geertsma is used, which numerically integrates the displacements from a nucleus of strain. This model relates the overburden time-lapse time-shifts to reservoir pressure. The existing method by Hodgson (2009) is modified to estimate reservoir pressure change and also the average dilation factor or R-factor for both the reservoir and overburden. The R-factors can be quantified when prior constraints are available from a well history matched simulation model, and their uncertainty defined. The results indicate that the magnitude of R is a function of strain change polarity, and that this asymmetry is required to match the observed timeshifts. The recovered average R-factor is 16, using the permanent reservoir monitoring (PRM) data. The streamer data has recovered average R-factors in the range of 7.2 to 18.4. Despite the limiting assumptions of a homogeneous medium, the method is beneficial, as it treats arbitrary subsurface geometries, and, in contrast to the complex numerical approaches, it is simple to parameterise and computationally fast. Finally, the aim and objective of this research have been met predominantly by the use of PRM data. These applications could not have been achieved without such highly repeatable and short repeat period acquisitions. This points to the value in using these data in reservoir characterisation, inversion and history matching

Enhancement of the Feature Extraction Capability in Global Damage Detection Using Wavelet Theory

The main objective of this study is to assess the specific capabilities of the defect energy parameter technique for global damage detection developed by Saleeb and coworkers. The feature extraction is the most important capability in any damage-detection technique. Features are any parameters extracted from the processed measurement data in order to enhance damage detection. The damage feature extraction capability was studied extensively by analyzing various simulation results. The practical significance in structural health monitoring is that the detection at early stages of small-size defects is always desirable. The amount of changes in the structure's response due to these small defects was determined to show the needed level of accuracy in the experimental methods. The arrangement of fine/extensive sensor network to measure required data for the detection is an "unlimited" ability, but there is a difficulty to place extensive number of sensors on a structure. Therefore, an investigation was conducted using the measurements of coarse sensor network. The white and the pink noises, which cover most of the frequency ranges that are typically encountered in the many measuring devices used (e.g., accelerometers, strain gauges, etc.) are added to the displacements to investigate the effect of noisy measurements in the detection technique. The noisy displacements and the noisy damage parameter values are used to study the signal feature reconstruction using wavelets. The enhancement of the feature extraction capability was successfully achieved by the wavelet theory