Universität Stuttgart
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Item Open Access Comparison study of phase-field and level-set method for three-phase systems including two minerals(2022) Kelm, Mathis; Gärttner, Stephan; Bringedal, Carina; Flemisch, Bernd; Knabner, Peter; Ray, NadjaWe investigate reactive flow and transport in evolving porous media. Solute species that are transported within the fluid phase are taking part in mineral precipitation and dissolution reactions for two competing mineral phases. The evolution of the three phases is not known a-priori but depends on the concentration of the dissolved solute species. To model the coupled behavior, phase-field and level-set models are formulated. These formulations are compared in three increasingly challenging setups including significant mineral overgrowth. Simulation outcomes are examined with respect to mineral volumes and surface areas as well as derived effective quantities such as diffusion and permeability tensors. In doing so, we extend the results of current benchmarks for mineral dissolution/precipitation at the pore-scale to the multiphasic solid case. Both approaches are found to be able to simulate the evolution of the three-phase system, but the phase-field model is influenced by curvature-driven motion.Item Open Access Identification of linear time-invariant systems with dynamic mode decomposition(2022) Heiland, Jan; Unger, BenjaminDynamic mode decomposition (DMD) is a popular data-driven framework to extract linear dynamics from complex high-dimensional systems. In this work, we study the system identification properties of DMD. We first show that DMD is invariant under linear transformations in the image of the data matrix. If, in addition, the data are constructed from a linear time-invariant system, then we prove that DMD can recover the original dynamics under mild conditions. If the linear dynamics are discretized with the Runge–Kutta method, then we further classify the error of the DMD approximation and detail that for one-stage Runge–Kutta methods; even the continuous dynamics can be recovered with DMD. A numerical example illustrates the theoretical findings.Item Open Access A microstructurally-based, multi-scale, continuum-mechanical model of skeletal muscle tissue(2019) Bleiler, Christian; Ponte Castañeda, Pedro; Röhrle, OliverItem Open Access Cross-bridge mechanics estimated from skeletal muscles’ work-loop responses to impacts in legged locomotion(2021) Christensen, Kasper B.; Günther, Michael; Schmitt, Syn; Siebert, TobiasLegged locomotion has evolved as the most common form of terrestrial locomotion. When the leg makes contact with a solid surface, muscles absorb some of the shock-wave accelerations (impacts) that propagate through the body. We built a custom-made frame to which we fixated a rat (Rattus norvegicus, Wistar) muscle (m. gastrocnemius medialis and lateralis: GAS) for emulating an impact. We found that the fibre material of the muscle dissipates between 3.5 and 23μJ ranging from fresh, fully active to passive muscle material, respectively. Accordingly, the corresponding dissipated energy in a half-sarcomere ranges between 10.4 and 68zJ, respectively. At maximum activity, a single cross-bridge would, thus, dissipate 0.6% of the mechanical work available per ATP split per impact, and up to 16% energy in common, submaximal, activities. We also found the cross-bridge stiffness as low as 2.2pNnm-1, which can be explained by the Coulomb-actuating cross-bridge part dominating the sarcomere stiffness. Results of the study provide a deeper understanding of contractile dynamics during early ground contact in bouncy gait.Item Open Access Pressure management via brine extraction in geological CO2 storage : adaptive optimization strategies under poorly characterized reservoir conditions(2019) González-Nicolás, Ana; Cihan, Abdullah; Petrusak, Robin; Zhou, Quanlin; Trautz, Robert; Godec, Michael; Birkholzer, Jens T.Industrial-scale injection of CO2 into the subsurface increases the fluid pressure in the reservoir, which if not properly controlled can potentially lead to geomechanical damage (i.e., fracturing of the caprock or reactivation of faults) and subsequent CO2 leakage. Brine extraction is one approach for managing formation pressure, effective stress, and plume movement in response to CO2 injection. The management of the extracted brine can be expensive (i.e., due to transportation, treatment, disposal, or re-injection), with added cost to the carbon capture and sequestration (CCS); thus, minimizing the volume of extraction brine is of great importance to ensure that the economics of CCS are favorable. The main objective of this study is to demonstrate the use of adaptive optimization methods in the planning of brine extraction and to investigate how the quality of initial site characterization data and the use of newly acquired monitoring data (e.g. pressure at observation wells) impact the optimization performance. We apply an adaptive management approach that integrates monitoring, calibration, and optimization of brine extraction rates to achieve pre-defined pressure constraints. Our results show that reservoir pressure management can be extremely benefited by early and high frequency pressure monitoring during early injection times, especially for poor initial reservoir characterization. Low frequencies of model calibration and optimization with monitoring data may lead to optimization problems, because either pressure buildup constraints are violated or excessively high extraction rates are proposed. The adaptive pressure management approach may constitute an effective tool to manage pressure buildup under uncertain reservoir conditions by minimizing the volumes of extracted brine while controlling pressure buildup.Item Open Access A physiology-guided classification of active-stress and active-strain approaches for continuum-mechanical modeling of skeletal muscle tissue(2021) Klotz, Thomas; Bleiler, Christian; Röhrle, OliverThe well-established sliding filament and cross-bridge theory explain the major biophysical mechanism responsible for a skeletal muscle's active behavior on a cellular level. However, the biomechanical function of skeletal muscles on the tissue scale, which is caused by the complex interplay of muscle fibers and extracellular connective tissue, is much less understood. Mathematical models provide one possibility to investigate physiological hypotheses. Continuum-mechanical models have hereby proven themselves to be very suitable to study the biomechanical behavior of whole muscles or entire limbs. Existing continuum-mechanical skeletal muscle models use either an active-stress or an active-strain approach to phenomenologically describe the mechanical behavior of active contractions. While any macroscopic constitutive model can be judged by it's ability to accurately replicate experimental data, the evaluation of muscle-specific material descriptions is difficult as suitable data is, unfortunately, currently not available. Thus, the discussions become more philosophical rather than following rigid methodological criteria. Within this work, we provide a extensive discussion on the underlying modeling assumptions of both the active-stress and the active-strain approach in the context of existing hypotheses of skeletal muscle physiology. We conclude that the active-stress approach resolves an idealized tissue transmitting active stresses through an independent pathway. In contrast, the active-strain approach reflects an idealized tissue employing an indirect, coupled pathway for active stress transmission. Finally the physiological hypothesis that skeletal muscles exhibit redundant pathways of intramuscular stress transmission represents the basis for considering a mixed-active-stress-active-strain constitutive framework.Item Open Access Editorial - somatosensory integration in human movement : perspectives for neuromechanics, modelling and rehabilitation(2021) Gizzi, Leonardo; Vujaklija, Ivan; Sartori, Massimo; Röhrle, Oliver; Severini, GiacomoItem Open Access A deep learning approach for large-scale groundwater heat pump temperature prediction(2022) Scheurer, StefaniaHeating and cooling buildings is one of the most energy-intensive aspects of modern life. To minimize the impact on global warming and decelerate climate change, more efficient and carbon emission-mitigating technologies such as openloop groundwater heat pumps (GWHP) for heating and cooling buildings are being used and quickly adopted. Nowadays, in order to guarantee their optimal use and prevent negative interactions, city planners need to optimize their placement in the urban landscape. This optimization process requires fast models that simulate the effect of a GWHP on the groundwater temperature. Considering a large domain with multiple GWHPs, this work introduces a framework for the groundwater temperature prediction. While using a learned local surrogate model, a convolutional neural network, to predict the local temperature field around every single GWHP, a physics-informed neural network (PINN) is employed afterwards to correct the global initial solution of stitched together local predictions. As the violations of the physical laws described by the underlying partial differential equation(s) are spatially unevenly distributed, two different methods for drawing sampling points, on the basis of which the training of the PINN to correct the global initial solution takes place, are investigated and compared. This work shows that it is possible for a PINN to correct the global initial solution of stitched together local predictions in a domain with multiple GWHPs. However, there are still opportunities to improve the quality and decrease the computational time of the presented framework. The best method for drawing sampling points depends on the scenario and the placement of the GWHPs. Thus, no general statement can be made, which of the two methods is more suitable. This work provides a good basis for further investigation of the presented framework.Item Open Access Temperate regenerative agriculture practices increase soil carbon but not crop yield : a meta-analysis(2022) Jordon, Matthew W.; Willis, Kathy J.; Bürkner, Paul-Christian; Haddaway, Neal R.; Smith, Pete; Petrokofsky, GillianRegenerative Agriculture (RA) claims to build soil organic carbon (SOC) and increase crop yields through simultaneous adoption of a suite of management practices which restore soil health. However, this claim is largely unevidenced as few studies of fully integrated regenerative systems are currently available. As a first step to addressing this knowledge gap, we here examine three practices now being promoted as part of RA: reducing tillage intensity, cover cropping and including a grass-based phase in arable rotations (ley-arable rotations). Our Bayesian meta-analysis of 195 paired SOC and crop yield observations from a systematic review of published studies finds statistically significant increases in SOC concentration for reduced tillage intensity (0.06 g C · 100 g-1) and ley-arable rotations (0.05 g C · 100-1 g yr-1 of ley) compared to conventional practice over an average study duration of 15 years, but no effect of cover crops. None of these practices reduce yield during cropping years, although we find no evidence of a win-win between increasing SOC and enhanced agricultural productivity following adoption. Future work should also evaluate the net greenhouse gas emission implications of each practice and potential for synergistic effects if RA practices are adopted in combination. Nevertheless, our results suggest that the RA practices investigated here can be promoted by land managers and policy makers without crop yield losses.Item Open Access Strategies for simplifying reactive transport models : a Bayesian model comparison(2020) Schäfer Rodrigues Silva, Aline; Guthke, Anneli; Höge, Marvin; Cirpka, Olaf A.; Nowak, WolfgangFor simulating reactive transport on aquifer scale, various modeling approaches have been proposed. They vary considerably in their computational demands and in the amount of data needed for their calibration. Typically, the more complex a model is, the more data are required to sufficiently constrain its parameters. In this study, we assess a set of five models that simulate aerobic respiration and denitrification in a heterogeneous aquifer at quasi steady state. In a probabilistic framework, we test whether simplified approaches can be used as alternatives to the most detailed model. The simplifications are achieved by neglecting processes such as dispersion or biomass dynamics, or by replacing spatial discretization with travel‐time‐based coordinates. We use the model justifiability analysis proposed by Schöniger, Illman, et al. (2015, https://doi.org/10.1016/j.jhydrol.2015.07.047) to determine how similar the simplified models are to the reference model. This analysis rests on the principles of Bayesian model selection and performs a tradeoff between goodness‐of‐fit to reference data and model complexity, which is important for the reliability of predictions. Results show that, in principle, the simplified models are able to reproduce the predictions of the reference model in the considered scenario. Yet, it became evident that it can be challenging to define appropriate ranges for effective parameters of simplified models. This issue can lead to overly wide predictive distributions, which counteract the apparent simplicity of the models. We found that performing the justifiability analysis on the case of model simplification is an objective and comprehensive approach to assess the suitability of candidate models with different levels of detail.