02 Fakultät Bau- und Umweltingenieurwissenschaften
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/3
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Item Open Access Smooth or with a snap! Biomechanics of trap reopening in the Venus flytrap (Dionaea muscipula)(2022) Durak, Grażyna M.; Thierer, Rebecca; Sachse, Renate; Bischoff, Manfred; Speck, Thomas; Poppinga, SimonFast snapping in the carnivorous Venus flytrap (Dionaea muscipula) involves trap lobe bending and abrupt curvature inversion (snap‐buckling), but how do these traps reopen? Here, the trap reopening mechanics in two different D. muscipula clones, producing normal‐sized (N traps, max. ≈3 cm in length) and large traps (L traps, max. ≈4.5 cm in length) are investigated. Time‐lapse experiments reveal that both N and L traps can reopen by smooth and continuous outward lobe bending, but only L traps can undergo smooth bending followed by a much faster snap‐through of the lobes. Additionally, L traps can reopen asynchronously, with one of the lobes moving before the other. This study challenges the current consensus on trap reopening, which describes it as a slow, smooth process driven by hydraulics and cell growth and/or expansion. Based on the results gained via three‐dimensional digital image correlation (3D‐DIC), morphological and mechanical investigations, the differences in trap reopening are proposed to stem from a combination of size and slenderness of individual traps. This study elucidates trap reopening processes in the (in)famous Dionaea snap traps - unique shape‐shifting structures of great interest for plant biomechanics, functional morphology, and applications in biomimetics, i.e., soft robotics.Item Open Access Automated parametric Rietveld refinement and its application to two dimensional X-ray powder diffraction experiments(2011) Rajiv, Paneerselvam; Joswig, Manfred (Prof. Dr.)Parametric Rietveld refinement has opened new possibilities to simultaneously refine multiple powder diffraction patterns collected in in situ 2D experiments; in that way the models of crystallographic variables that changes with external variables can be introduced into the refinement. The substitution of a variable with its model during the refinement has several advantages, including the improved precision of variables, direct extraction/refinement of some parameters from powder data which is otherwise impractical (e.g., activation energy), etc. The basic requirement for the realization of sequential/parametric refinements (or Whole Powder Pattern Fit-WPPF) in 2D X-ray powder diffraction (XRPD) is a robust software that handles the data and performs fast WPPF. This concern has been primarily addressed in this thesis with the help of a software, in combination with the existing total pattern analysis software (Topas). The developed software could considerably speedup and automate the sequential/parametric quantitative analysis of large number of 2D powder data, which is in general a monotonous and time consuming task. The software also provides routines that automatically determines the reconstructive phase transitions of samples from the 2D powder data and facilitates the independent refinements (or WPPFs) of the determined phases. Two practical scientific applications of parametric Rietveld refinement method have been demonstrated with the assistance of the developed program. The first application concerns the kinetic analysis of several polymorphs and polymorphs-additives mixtures of copper phthalocyanine (CuPC). The reaction rate constant and the order of reactions involving the phase transitions of various forms of CuPC were directly extracted from the isothermal experimental data by introducing the Johnson-Mehl-Avrami-Kolmogorov relation as a model of the phase fraction during the multi phase parametric Rietveld refinement. Parametric refinements could be successfully performed for most of the CuPC data collected in the experiment, however the convergence of some of the refinements showed a strong dependence on the reaction rate. In many cases, the precision of the refined parameters could be improved considerably when the data collected between the optimal time steps alone were used in the refinement. The second application demonstrates the feasibility of the parameterization of crystallite size with respect to the annealing time/temperature. Some of the data samples used in the kinetic analysis (CuPC) and the temperature dependent nanocrystalline TiO2 data were used in this demonstration. The success of the parameterization of crystallite size depended strongly on the quality of the data used, on the uniformity of the variation of the crystallite size with time/temperature and also on the correctness of the model that describes the crystallite size variation with time/temperature. This application in its present form is general; as such it can be used for stabilizing other variables during parametric refinement.Item 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 Magnetic putty as a reconfigurable, recyclable, and accessible soft robotic material(2023) Li, Meng; Pal, Aniket; Byun, Junghwan; Gardi, Gaurav; Sitti, MetinMagnetically hard materials are widely used to build soft magnetic robots, providing large magnetic force/torque and macrodomain programmability. However, their high magnetic coercivity often presents practical challenges when attempting to reconfigure magnetization patterns, requiring a large magnetic field or heating. In this study, magnetic putty is introduced as a magnetically hard and soft material with large remanence and low coercivity. It is shown that the magnetization of magnetic putty can be easily reoriented with maximum magnitude using an external field that is only one‐tenth of its coercivity. Additionally, magnetic putty is a malleable, autonomous self‐healing material that can be recycled and repurposed. The authors anticipate magnetic putty could provide a versatile and accessible tool for various magnetic robotics applications for fast prototyping and explorations for research and educational purposes.Item Open Access Entwicklung von Leuchtdichteverteilungs- und Steuerungskonzepten für den Bildschirmarbeitsplatz(2014) Hubschneider, Carolin; Sedlbauer, Klaus Peter (Prof. Dr.-Ing.)Die Lichtumgebung beeinflusst Leistung, Ermüdung und Empfinden am Büroarbeitsplatz. Durch die Integration des Monitors in die Arbeitswelt hat sich einerseits die Blickrichtung im Vergleich zur reinen Schreibtischarbeit geändert, andererseits stellt der Monitor, als selbstleuchtende Fläche, ein weiteres Element der Leuchtdichteumgebung der Nutzer dar. Ziel der vorliegenden Arbeit ist es zu klären, welche Komponenten des Gesichtsfelds Einfluss auf die Nutzer nehmen und zu einer gesteigerten Leistungsfähigkeit führen. Diese Komponenten sind: - die Leuchtdichten des Monitors - die Leuchtdichten der Arbeitsfläche - die Leuchtdichten des Wandabschnitts hinter dem Monitor - die Leuchtdichteverhältnisse dieser Flächen Außerdem wird die Möglichkeit der Erstellung eines Steuerungsalgorithmus auf Basis der gewonnen Daten überprüft. Innerhalb der Arbeit werden drei aufeinander aufbauende Studien durchgeführt. In Studie 1 werden im Testraum sechs verschiedene Lichtbedingungen hergestellt, welche sich in Leuchtdichteniveau und Verteilung unterschieden. Innerhalb der Lichtbedingungen werden drei verschiedene Monitorleuchtdichten verwendet. Die sich daraus ergebenden 18 Leuchtdichteumgebungen werden mittels verschiedener Fragebögen und Leistungstests bezüglich ihrer Wirkung auf die Nutzer überprüft. Es wird nachgewiesen, dass neben der singulären Betrachtung der Leuchtdichten der Einzelflächen auch die Verhältnisse im Gesichtsfeld und das Miteinbeziehen der Komponente Monitor von großer Wichtigkeit sind. Studie 2 zielt auf eine möglichst umfassende Untersuchung der Verhältnisse im Gesichtsfeld ab, dazu werden die relevanten Flächen systematisch gegeneinander variiert und 54 resultierende Leuchtdichteumgebungen getestet. Die Wandabschnittsleuchtdichte und das Leuchtdichteverhältnis zwischen Monitor und Wandabschnitt werden als maßgebliche Größen identifiziert. Anhand der optimalen Leuchtdichteverhältnisse zwischen Monitor und Wandabschnitt werden zwei Varianten eines Steuerungsalgorithmus erstellt, welche die Monitorleuchtdichte anhand der Wandabschnittsleuchtdichte regulieren: die Leistungsatmosphäre-Steuerung und die Energie-Steuerung. Die konzipierten Steuerungsvarianten werden in Studie 3 unter realen Tageslichtbedingungen getestet. Es zeigen sich erste Hinweise, dass eine Anpassung der Monitorleuchtdichte an die Wandabschnittsleuchtdichte positiven Einfluss auf die Nutzer nehmen kann. Insgesamt kann die Variation der Leuchtdichten im Gesichtsfeld auch im moderaten Leuchtdichtebereich des Bürokontextes die Nutzer hinsichtlich verschiedener Maße der Leistung, der Ermüdung und des Empfindens beeinflussen. Besonders die visuelle Leistungsatmosphäre zeigt sich sensitiv gegenüber der Variation der Leuchtdichteumgebung. Betrachtet man die Innenflächen des Raumes so übt die Leuchtdichte des Wandabschnitts hinter dem Monitor einen größeren Einfluss auf die Nutzer aus als die der Arbeitsfläche. Es kann eine für die visuelle Leistungsatmosphäre optimale Wandabschnittsleuchtdichte von 336 cd/m2 unter Berücksichtigung eines Unsicherheitsbereichs zwischen 121 cd/m2 und 550 cd/m2 ermittelt werden. Bezüglich der Leuchtdichteverhältnisse der einzelnen Flächen der Leuchtdichteumgebung kann gezeigt werden, dass besonders das Leuchtdichteverhältnis zwischen Monitor und Wandabschnitt die Nutzer beeinflusst. Liegt dieses Verhältnis bei 1,24/1 so wird unter Berücksichtigung eines Unsicherheitsbereichs zwischen 0,40/1 bis 2,93/1 eine optimale visuelle Leistungsatmosphäre erreicht. Der Vergleich der beiden generierten Steuerungsalgorithmen mit einer konstanten Monitorleuchtdichte ergibt lediglich bei Betrachtung der Testpersonen ab 25 Jahren aussagekräftige Ergebnisse. Testpersonen in höherem Alter scheinen sensibler gegenüber Änderungen der Leuchtdichteumgebung zu sein. Die Leistungsatmosphäre-Steuerung führt zur höchsten visuellen Leistungsatmosphäre, außerdem waren die Testpersonen zur höchsten Leistung bei Bearbeitung des Konzentrations-Leistungs-Tests fähig. Vom Einsatz der Energie-Steuerung ist abzuraten, da dieser zu erhöhter visueller Ermüdung nach der Aufgabenbearbeitung und einer verminderten visuellen Leistungsatmosphäre führt.Item Open Access Investigations into the opening of fractures during hydraulic testing using a hybrid-dimensional flow formulation(2021) Schmidt, Patrick; Steeb, Holger; Renner, JörgWe applied a hybrid-dimensional flow model to pressure transients recorded during pumping experiments conducted at the Reiche Zeche underground research laboratory to study the opening behavior of fractures due to fluid injection. Two distinct types of pressure responses to flow-rate steps were identified that represent radial-symmetric and plane-axisymmetric flow regimes from a conventional pressure-diffusion perspective. We numerically modeled both using a radial-symmetric flow formulation for a fracture that comprises a non-linear constitutive relation for the contact mechanics governing reversible fracture surface interaction. The two types of pressure response can be modeled equally well. A sensitivity study revealed a positive correlation between fracture length and normal fracture stiffness that yield a match between field observations and numerical results. Decomposition of the acting normal stresses into stresses associated with the deformation state of the global fracture geometry and with the local contacts indicates that geometrically induced stresses contribute the more the lower the total effective normal stress and the shorter the fracture. Separating the contributions of the local contact mechanics and the overall fracture geometry to fracture normal stiffness indicates that the geometrical stiffness constitutes a lower bound for total stiffness; its relevance increases with decreasing fracture length. Our study demonstrates that non-linear hydro-mechanical coupling can lead to vastly different hydraulic responses and thus provides an alternative to conventional pressure-diffusion analysis that requires changes in flow regime to cover the full range of observations.Item Open Access Experimental multi-scale characterization using micro X-ray computed tomography(Stuttgart : Institute of Applied Mechanics, 2023) Ruf, Matthias; Steeb, Holger (Prof. Dr.-Ing.)The effective mechanical and hydro-mechanical behavior of porous media, granular solids, and related materials with complex morphologies is intimately linked to their internal microstructure on the pore/grain scale. For microstructural characterization, transmission micro X-Ray Computed Tomography (µXRCT) has emerged as a crucial three-dimensional (3D) imaging technique that can provide structural information from the micrometer to centimeter scale. Due to its non-destructive nature, it can be excellently combined with time-dependent investigations, either ex situ or in situ. In particular, the possibility of coupling mechanical or hydro-mechanical characterization with µXRCT-based 3D imaging in situ allows many physical phenomena to be studied in more detail and consequently understood more comprehensively. For example, the microstructure evolution can be observed under various controlled boundary conditions and linked to measured effective quantities. New insights and improved understanding can ultimately positively influence modeling approaches. In order to be able to perform such multi-scale studies, a modular, open, and versatile lab-based µXRCT system was developed within the scope of this work. It provides a spatial resolution of down to less than 10 µm. The developed system has an integrated universal testing machine that enables in situ compressive, tensile, and torsional studies as well as their combinations, parallel or sequential. Furthermore, hydro-mechanical coupled phenomena can be investigated using appropriate equipment, such as triaxial flow cells. Thanks to the open and modular concept, the developed system can be used in the future for a wide variety of multiphysics research questions and can be considered as an open experimental platform. Employing the established system, various multi-scale phenomena from different material classes are motivated and partly investigated in more detail within this work. For this purpose, classical experimental characterization methods are combined with µXRCT-based 3D imaging ex situ as well as in situ. Among others, 3D imaging is combined with ultrasound wave propagation measurements to investigate the influence of artificially generated crack networks in Carrara marble by different thermal treatment protocols. Load-sequence effects are demonstrated on an open-cell foam sample. An in situ workflow is shown to investigate the not-well-understood effective stiffness behavior of biphasic monodisperse granular packings of stiff and soft particles of different volume fractions at different stress states. The fracturing of a rock sample in a triaxial flow cell shows possibilities of application in the context of fracture mechanics. All resulting data sets, including metadata, are available via the Data Repository of the University of Stuttgart (DaRUS).Item Open Access Earthquake location by distinct constraints for sparse and doubtful data(2018) Eisermann, Andreas Samuel; Joswig, Manfred (Prof. Dr. rer. nat.)Earthquakes affected mankind since the days of old, claiming more human casualties than any other nature catastrophe. The determination of the hypocenter location displays one of the key subjects of seismology. Today’s standard approaches provide for trustable location estimates - given a large amount of stations with high quality data and proper assumptions about the sub-surface velocity structure. The same approaches fail, however, when this amount of stations and quality of data is not given, e.g. in the mapping of seismically active zones using low magnitude events: Here, only few stations detect the signals that sometimes barely exceed the noise level. Seismic phases appear hence unclear, rendering the information of arrival times doubtful. Another example are real-time location schemes (e.g. in Earthquake Early Warning Systems): Here, events need to be evaluated and located within fractions of seconds without knowledge of the complete waveform, and data available only from the first few stations that already detected. The objective of this thesis lies in a methodological development that provides for more accurate single event locations in the context of sparse and doubtful data. The less data is available the more the location estimate is determined and affected by the individual datum, its uncertainties and errors. The method of choice must therefore be outlier-resistant (e.g. ignore false picks) and incorporate all parameter uncertainties. When data is few, solutions may further be ambiguous (not due to errors in the input parameters, being exact solutions to a set of even ideal arrival times), meaningly: Multiple, significantly separated location candidates may exist. Also, models are usually only rough and simplified representations of the subsurface structure and will often not explain the observed data well enough. Today's standard approaches often disregard the corresponding uncertainties and, hence, often displace the hypocenter significantly to the true location - outside of the assumed error margins. Mislocations in earthquake early warning or forensic seismology may have far-reaching implications for society and on the political level. This thesis provides therefore a novel location methodology that incorporates the important uncertainties, naturally disregards outliers and thereby leads to robust hypocenter estimates. The work presented builds on the concept of (graphical) jackknifing, which contrary to most of today's standard approaches doesn't attempt to minimize the error in the over-determined system directly, but decomposes the system first into exactly- or even under-determined subsystems. This results in distinct location constraints that are based on arrival time differences between two- or three phases, only. Each constraint identifies a subset of space as possible hypocenter region. The combination of multiple constraints consecutively constrains the final hypocenter region. Since a single constraint relies on a minimum amount of phase onsets, only, solution discrepancies can be traced back to the individual phase data, which allows the data base (e.g. outliers) to be re-evaluated. The global solution is finally recomposed based on the sub-solutions deemed trustworthy, which provides robust and outlier resistant solutions. This concept is built on, supporting for three dimensional station layouts, complex velocity models and a volumetric computation, which render this approach suitable for a wide class of modern applications. A real-time methodology that regards uncertainties in phase picks, phase types and model parameters provides for robust and accurate locations when data is uncertain and sparse. New constraints are introduced, which allow to resolve ambiguities and provide for faster hypocenter and magnitude estimates in Earthquake Early Warning. A new direct search scheme is developed that integrates constraint probabilities over grid cells, which ensures the identification of sharp hypocenter regions independent of the grid's resolution, satisfying the demand for a complete search. The improvement in location quality is demonstrated using several examples ranging from gas-field low-magnitude event monitoring, forensic seismology to examples of real-time locations in Earthquake Early Warning.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 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.