02 Fakultät Bau- und Umweltingenieurwissenschaften
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/3
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Item Open Access Reconstruction of μXRCT data sets using the ASTRA toolbox(2020) Voland, PaulItem Open Access The role of parvalbumin, sarcoplasmatic reticulum calcium pump rate, rates of cross-bridge dynamics, and ryanodine receptor calcium current on peripheral muscle fatigue: a simulation study(2016) Röhrle, Oliver; Neumann, Verena; Heidlauf, ThomasItem Open Access Multiscale modeling and stability analysis of soft active materials : from electro- and magneto-active elastomers to polymeric hydrogels(Stuttgart : Institute of Applied Mechanics, 2023) Polukhov, Elten; Keip, Marc-André (Prof. Dr.-Ing.)This work is dedicated to modeling and stability analysis of stimuli-responsive, soft active materials within a multiscale variational framework. In particular, composite electro- and magneto-active polymers and polymeric hydrogels are under consideration. When electro- and magneto-active polymers (EAP and MAP) are fabricated in the form of composites, they comprise at least two phases: a polymeric matrix and embedded electric or magnetic particles. As a result, the obtained composite is soft, highly stretchable, and fracture resistant like polymer and undergoes stimuli-induced deformation due to the interaction of particles. By designing the microstructure of EAP or MAP composites, a compressive or a tensile deformation can be induced under electric or magnetic fields, and also coupling response of the composite can be enhanced. Hence, these materials have found applications as sensors, actuators, energy harvesters, absorbers, and soft, programmable, smart devices in various areas of engineering. Similarly, polymeric hydrogels are also stimuli-responsive materials. They undergo large volumetric deformations due to the diffusion of a solvent into the polymer network of hydrogels. In this case, the obtained material shows the characteristic behavior of polymer and solvent. Therefore, these materials can also be considered in the form of composites to enhance the response further. Since hydrogels are biocompatible materials, they have found applications as contact lenses, wound dressings, drug encapsulators and carriers in bio-medicine, among other similar applications of electro- and magneto-active polymers. All above mentioned favorable features of these materials, as well as their application possibilities, make it necessary to develop mathematical models and numerical tools to simulate the response of them in order to design pertinent microstructures for particular applications as well as understand the observed complex patterns such as wrinkling, creasing, snapping, localization or pattern transformations, among others. These instabilities are often considered as failure points of materials. However, many recent works take advantage of instabilities for smart applications. Investigation of these instabilities and prediction of their onset and mode are some of the main goals of this work. In this sense, the thesis is organized into three main parts. The first part is devoted to the state of the art in the development, fabrication, and modeling of soft active materials as well as the continuum mechanical description of the magneto-electro-elasticity. The second part is dedicated to multiscale instabilities in electro- and magneto-active polymer composites within a minimization-type variational homogenization setting. This means that the highly heterogeneous problem is not resolved on one scale due to computational inefficiency but is replaced by an equivalent homogeneous problem. The effective response of the macroscopic homogeneous problem is determined by solving a microscopic representative volume element which includes all the geometrical and material non-linearities. To bridge these two scales, the Hill-Mandel macro-homogeneity condition is utilized. Within this framework, we investigate both macroscopic and microscopic instabilities. The former are important not only from a physical point of view but also from a computational point of view since the macroscopic stability (strong ellipticity) is necessary for the existence of minimizers at the macroscopic scale. Similarly, the investigation of the latter instabilities are also important to determine the pattern transformations at the microscale due to external action. Thereby the critical domain of homogenization is also determined for computation of accurate effective results. Both investigations are carried out for various composite microstructures and it is found that they play a crucial role in the response of the materials. Therefore, they must be considered for designing EAP and MAP composites as well as for providing reliable computations. The third part of the thesis is dedicated to polymeric hydrogels. Here, we develop a minimization-based homogenization framework to determine the response of transient periodic hydrogel systems. We demonstrate the prevailing size effect as a result of a transient microscopic problem, which has been investigated for various microstructures. Exploiting the elements of the proposed framework, we explore the material and structural instabilities in single and two-phase hydrogel systems. Here, we have observed complex experimentally observed and novel 2D pattern transformations such as diamond-plate patterns coupled with and without wrinkling of internal surfaces for perforated microstructures and 3D pattern transformations in thin reinforced hydrogel composites. The results indicate that the obtained patterns can be controlled by tuning the material and geometrical parameters of the composite.Item Open Access Capturing local details in fluid-flow simulations : options, challenges and applications using marker-and-cell schemes(Stuttgart : Eigenverlag des Instituts für Wasser- und Umweltsystemmodellierung der Universität Stuttgart, 2024) Lipp, Melanie Gloria; Helmig, Rainer (Prof. Dr.-Ing.)Complex local flow structures appear in a wide range of free-flow systems, e.g. vortices build after obstacles. For understanding and predicting numerous processes, it is important to capture local details in free fluid flow, which is the focus of this work. Particularly, we are interested in local flow structures in free flow coupled to porous-medium flow. A better resolution of local structures in free flow can be achieved by refining computational grids, which is studied in this thesis. Particularly, we focus on finite-volume/finite-difference methods for the two-dimensional Navier-Stokes equations with constant density and constant viscosity, using the marker-and-cell method (pressures in cell centers, velocities on cell faces) and rectangular control volumes. There exists a variety of methods, with a range of characteristics, which can be used to refine computational grids. The first objective of this work was to develop for many different available approaches one common way of description of a class of methods within our focus and to display their similarities and differences. The second objective was to gain insight and in-detail understanding of the local-refinement-methods' behavior by examining one chosen method before numerical solution, i.e. by examining local truncation errors. The third objective was to gain further understanding of the local-refinement-methods' behavior as well as display examples, in which the chosen method is beneficial when neglecting computational-efficiency issues, by examining our chosen method after numerical solution, i.e. by examining actual numerical solutions.Item Open Access An XFEM-based model for fluid flow in fractured porous media(2015) Schwenck, Nicolas; Flemisch, Bernd (PD Dr. rer. nat.)Many fields of applications for porous media flow include geometrically anisotropic inclusions and strongly discontinuous material coefficients which differ in orders of magnitude. If the extension of those heterogeneities is small in normal direction compared to the tangential directions, e.g., long and thin, those features are called fractures. Examples which include such fractured porous-media systems in earth sciences include reservoir engineering, groundwater-resource management, carbon capture and storage (CCS), radioactive-waste reposition, coal bed methane migration in mines, geothermal engineering and hydraulic fracturing. The analysis and prediction of flow in fractured porous-media systems is important for all the aforementioned applications. Experiments are usually too expensive and time consuming to satisfy the demand for fast but accurate decision making information. Many different conceptual and numerical models to treat fractured porous-media systems can be found in the literature. However, even in the time of large supercomputers with massive parallel computing power, the computational efficiency, and therefore the economic efficiency, plays a dominating role in the evaluation of simulation software. In this thesis an efficient method to simulate flow in fractured porous media systems is presented. Darcy flow in fractures and matrix is assumed. The presented method is suited best for flow regimes depending on both, the fractures and the surrounding rock matrix and is able to account for highly conductive but also almost impermeable fractures with respect to the surrounding matrix. The newly developed method is based on a co-dimension one conceptual model for the fracture network which is embedded in the surrounding matrix. The basis for this model reduction is given in Martin et al. (2005). Numerically the fracture network is resolved by its own grid and coupled to the independent matrix grid. The discretization on this matrix grid allows jumps in the solution across the geometrical position of the fractures within elements by discontinuous basis functions. This discretization method is known as eXtended Finite Element Method (XFEM). A similar approach was simultaneously developed in D’Angelo and Scotti (2012). The main novelty of this work is the extension of the aforementioned conceptual model, which only accounts for a single fracture ending on the boundary of the matrix domain, towards more complex fracture networks and suitable boundary conditions. This work can be structured into the development and implementation of three conceptual models (see 1–3 below) and their respective validation. It is followed by an evaluation of quality and efficiency with respect to established models (see 4 below). The implementation is carried out using DUNE, a toolbox for solving partial differential equations. 1. The first extension is the treatment of fractures, which end inside the domain. This includes the conceptual coupling at the fracture tips as well as the numerical treatment within the XFEM of the matrix elements, in which the fracture ends. The validation shows, that the proposed treatment is efficient and for most validation cases produces the desired accuracy. 2. In the second part, a conceptual model for intersecting fractures is developed and the implementation within the XFEM is presented. The validation shows that the proposed model and implementation can capture the complex physics of fracture crossings very accurately. 3. Of special interest are the boundary conditions for lower-dimensional fractures intersecting the matrix boundary. The established models very often use for simplicity constant values across lower-dimensional intersections. This is physically not always correct, because in reality lower-dimensional objects do not exist and if a gradient on the rock matrix boundary exists, there is also a gradient on the fracture boundary. Therefore, a sophisticated interpolation method is proposed. It is easy to apply because very often discrete measured data is given to the model as input anyway and the proposed interpolation of values at the boundary is separated from the flow problem inside the domain. The concepts and results of the crossing model (2) and the boundary-condition interpolation (3) are published in Schwenck et al. (2014). 4. To show the performance of the newly developed model including the three major aspects mentioned above, it is compared against several established models and implementations within the simulation framework DuMux. The results of this comparison are published in Schwenck et al. (2015). The model presented here combines the advantages of lower-dimensional models and non-matching grids while keeping the ability to represent the fracture geometry and its influence on the matrix flow field exactly. Therefore, it is an efficient alternative to established models.Item Open Access Technical note: Space-time statistical quality control of extreme precipitation observations(2022) El Hachem, Abbas; Seidel, Jochen; Imbery, Florian; Junghänel, Thomas; Bárdossy, AndrásInformation about precipitation extremes is of vital importance for many hydrological planning and design purposes. However, due to various sources of error, some of the observed extremes may be inaccurate or false. The purpose of this investigation is to present quality control of observed extremes using space–time statistical methods. To cope with the highly skewed rainfall distribution, a Box–Cox transformation with a suitable parameter was used. The value at the location of a potential outlier is estimated using the surrounding stations and the calculated spatial variogram and compared to the suspicious observation. If the difference exceeds the threshold of the test, the value is flagged as a possible outlier. The same procedure is repeated for different temporal aggregations in order to avoid singularities caused by convection. Detected outliers are subsequently compared to the corresponding radar and discharge observations, and finally, implausible extremes are removed. The procedure is demonstrated using observations of sub-daily and daily temporal resolution in Germany.Item Open Access The benefit of muscle-actuated systems : internal mechanics, optimization and learning(Stuttgart : Institut für Modellierung und Simulation Biomechanischer Systeme, Computational Biophysics and Biorobotics, 2023) Wochner, Isabell; Schmitt, Syn (Prof. Dr.)We are facing the challenge of an over-aging and overweight society. This leads to an increasing number of movement disorders and causes the loss of mobility and independence. To address this pressing issue, we need to develop new rehabilitation techniques and design innovative assistive devices. Achieving this goal requires a deeper understanding of the underlying mechanics that control muscle-actuated motion. However, despite extensive studies, the neural control of muscle-actuated motion remains poorly understood. While experiments are valuable and necessary tools to further our understanding, they are often limited by ethical and practical constraints. Therefore, simulating muscle-actuated motion has become increasingly important for testing hypotheses and bridge this knowledge gap. In silico, we can establish cause-effect relationships that are experimentally difficult or even impossible to measure. By changing morphological aspects of the underlying musculoskeletal structure or the neural control strategy itself, simulations are crucial in the quest for a deeper understanding of muscle-actuated motion. The insights gained from these simulations paves the way to develop new rehabilitation techniques, enhance pre-surgical planning, design better assistive devices and improve the performance of current robots. The primary objective of this dissertation is to study the intricate interplay between musculoskeletal dynamics, neural controller and the environment. To achieve this goal, a simulation framework has been developed as part of this thesis, enabling the modeling and control of muscle-actuated motion using both model-based and learning-based methods. By utilizing this framework, musculoskeletal models of the arm, head-neck complex and a simplified whole-body model are investigated in conjunction with various concepts of motor control. The main research questions of this thesis are therefore: 1. How does the neural control strategy select muscle activation patterns to generate the desired movement, and can we use this knowledge to design better assistive devices? 2. How does the musculoskeletal dynamics facilitate the neural control strategy in accomplishing this task of generating desired movements? To address these research questions, this thesis comprises a total of five journal and conference articles. More specifically, contributions I-III of this thesis focus on addressing the first research question which aims to understand how voluntary and reflexive movements can be predicted. First, we investigate various optimality principles using a musculoskeletal arm model to predict point-to-manifold reaching tasks. By using predictive simulations, we demonstrate how the arm would move towards a goal if, for example, our neural control strategy would minimize energy consumption. The main finding of this contribution shows that it is essential to include muscle dynamics and consider tasks with more openly defined targets to draw accurate conclusions about motor control. Through our analysis, we show that a combination of mechanical work, jerk and neuronal stimulation effort best predicts point-reaching when compared to human experiments. Second, we propose a novel method to optimize the design of exoskeleton power units taking into account the load cycle of predicted human movements. To achieve this goal, we employ a forward dynamic simulation of a generic musculoskeletal arm model, which is first scaled to represent different individuals. Next, we predict individual human motions and employ the predicted human torques to scale the electrical power units employing a novel scalability model. By considering the individual user needs and task demands, our approach achieves a lighter and more efficient design. In conclusion, our framework demonstrates the potential to improve the design of individual assistive devices. The third contribution focuses on predicting reflexive movements in response to sudden perturbations of the head-neck complex. To achieve this, we conducted experiments in which volunteers were placed on a table while supporting their heads with a trapdoor. This trapdoor was then suddenly released leading to a downward movement of the head until the reflexive reaction of the muscles stops the head from falling. We analyzed the results of these experiments, presenting characteristic parameters and highlighting differences between separate age and gender groups. Using this data, we also set up benchmark validations for a musculoskeletal head-neck model, including reflex control strategies. Our main findings are that there are large individual differences in reflexive responses between participants and that the perturbation direction significantly affects the reflexive response. Furthermore, we show that this data can be used as a benchmark test to validate musculoskeletal models and different muscle control strategies. While the first three contributions focus on the research question (1), contributions IV-V focus on (2) whether and how the musculoskeletal dynamics facilitate the learning and control task of various movements. We utilize a recently introduced information-theoretic approach called control effort to quantify the minimally required information to perform specific movements. By applying this concept, we can for example quantify how much biological muscles reduce the neuronal information load compared to technical DC-motors. We present a novel optimization algorithm to find this control effort and apply it to point-reaching and walking tasks. The main finding of this contribution is that the musculoskeletal dynamics reduce the control effort required for these movements compared to torque-driven systems. Finally, we hypothesize that the highly nonlinear muscle dynamics not only facilitate the control task but also provide inherent stability that is beneficial for learning from scratch. To test this, we employed various learning strategies for multiple anthropomorphic tasks, including point-reaching, ball-hitting, hopping, and squatting. The results of this investigation demonstrate that using muscle-like actuators improves the data-efficiency of the learning tasks. Additionally, including the muscle dynamics improves the robustness towards hyperparameters and allows for a better generalization towards unknown and unlearned perturbations. In summary, this thesis enhances existing methods to control and learn muscle-actuated motion, quantifies the control effort needed to perform certain movements and demonstrates that the inherent stability of the muscle dynamics facilitates the learning task. The models, control strategies, and experimental data presented in this work aid researchers in science and industry to improve their predictions in various fields such as neuroscience, ergonomics, rehabilitation, passive safety systems, and robotics. This allows us to reverse-engineer how we as humans control movement, uncovering the complex relationship between musculoskeletal dynamics and neural controller.Item Open Access Multiscale modeling and simulation of transport processes in porous media(2022) Bringedal, Carina; Helmig, Rainer (Prof. Dr.-Ing.)Item Open Access Optimality principles in human point-to-manifold reaching accounting for muscle dynamics(2020) Wochner, Isabell; Driess, Danny; Zimmermann, Heiko; Häufle, Daniel F. B.; Toussaint, Marc; Schmitt, SynHuman arm movements are highly stereotypical under a large variety of experimental conditions. This is striking due to the high redundancy of the human musculoskeletal system, which in principle allows many possible trajectories toward a goal. Many researchers hypothesize that through evolution, learning, and adaption, the human system has developed optimal control strategies to select between these possibilities. Various optimality principles were proposed in the literature that reproduce human-like trajectories in certain conditions. However, these studies often focus on a single cost function and use simple torque-driven models of motion generation, which are not consistent with human muscle-actuated motion. The underlying structure of our human system, with the use of muscle dynamics in interaction with the control principles, might have a significant influence on what optimality principles best model human motion. To investigate this hypothesis, we consider a point-to-manifold reaching task that leaves the target underdetermined. Given hypothesized motion objectives, the control input is generated using Bayesian optimization, which is a machine learning based method that trades-off exploitation and exploration. Using numerical simulations with Hill-type muscles, we show that a combination of optimality principles best predicts human point-to-manifold reaching when accounting for the muscle dynamics.Item Open Access Finite strain hyperelastic multiscale homogenization via projection, efficient sampling and concentric interpolation(Stuttgart : Institute of Applied Mechanics, 2021) Kunc, Oliver; Fritzen, Felix (Prof. Dr.-Ing. Dipl.-Math. techn.)