Universität Stuttgart
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Item Open Access Comprehensive study of failure mechanisms of field-aged automotive lead batteries(2023) Conradt, Rafael; Schröer, Philipp; Dazer, Martin; Wirth, Jonathan; Jöris, Florian; Schulte, Dominik; Birke, Kai PeterModern vehicles have increasing safety requirements and a need for reliable low-voltage power supply in their on-board power supply systems. Understanding the causes and probabilities of failures in a 12 V power supply is crucial. Field analyses of aged and failed 12 V lead batteries can provide valuable insights regarding this topic. In a previous study, non-invasive electrical testing was used to objectively determine the reasons for failure and the lifetime of individual batteries. By identifying all of the potential failure mechanisms, the Latin hypercube sampling method was found to effectively reduce the required sample size. To ensure sufficient confidence in validating diagnostic algorithms and calculating time-dependent failure rates, all identified aging phenomena must be considered. This study presents a probability distribution of the failure mechanisms that occur in the field, as well as provides insights into potential opportunities, but it also challenges diagnostic approaches for current and future vehicles.Item Open Access Classifying physical exercises and counting repetitions using three-dimensional pose estimation(2023) Wallmann, JonasResistance training is known to increase physical and mental health but requires a lot of knowledge and experience to be done effectively and safely. Personal trainers and physiotherapists provide their knowledge to athletes but their profession requires a lot of learning and experience, thus making their services often not affordable to the general public. Automating certain aspects of their work will make their services more available to the general population and therefore lead to more safe and more effective athletes. The first steps of automating personal training lie in observing a subject train and understanding their performed workout. This provides the basics for future work of automating providing feedback on exercise execution and improving their training regimes. In order to do so, we developed a proof-of-concept program, that uses a two-dimensional camera video as an input to classify what exercise a user performs and automatically counts the number of performed repetitions, in real-time. It should work without imposing requirements in the camera perspective or needing to know what exercise will be performed in advance. This is achieved by using a three-dimensional pose estimation model and defining a rule-based algorithm, that considers the position and angle of joints that characterize the performed exercises We evaluate our proof-of-concept program using videos of subjects performing squats and push-ups in order to understand the accuracy in a real-world scenario. Our program achieved an overall accuracy of 95.57% for the squats and 93.69% for the push-up evaluation.Item Open Access Fractional calculus for distributions(2024) Hilfer, Rudolf; Kleiner, TillmannFractional derivatives and integrals for measures and distributions are reviewed. The focus is on domains and co-domains for translation invariant fractional operators. Fractional derivatives and integrals interpreted as -convolution operators with power law kernels are found to have the largest domains of definition. As a result, extending domains from functions to distributions via convolution operators contributes to far reaching unifications of many previously existing definitions of fractional integrals and derivatives. Weyl fractional operators are thereby extended to distributions using the method of adjoints. In addition, discretized fractional calculus and fractional calculus of periodic distributions can both be formulated and understood in terms of -convolution.Item Open Access Physics-informed transformers for electronic quantum states(2025) Sobral, João Augusto; Perle, Michael; Scheurer, Mathias S.Neural-network-based variational quantum states, particularly autoregressive models, are powerful tools for describing complex many-body wave functions. However, their performance depends on the computational basis chosen and they often lack physical interpretability. We propose a modified variational Monte-Carlo framework which leverages prior physical information to construct a complete computational many-body basis containing a reference state that serves as a rough approximation to the true ground state. A Transformer is used to parametrize and autoregressively sample corrections to this reference state, giving rise to a more interpretable and computationally efficient representation of the ground state. We demonstrate this approach in a fermionic model featuring a metal-insulator transition by employing Hartree-Fock and a strong-coupling limit to define physics-informed bases. We also show that the Transformer’s hidden representation captures the natural energetic order of the different basis states. This work paves the way for more efficient and interpretable neural quantum-state representations.Item Open Access Designing actuation concepts for adaptive slabs with integrated fluidic actuators using influence matrices(2022) Nitzlader, Markus; Steffen, Simon; Bosch, Matthias J.; Binz, Hansgeorg; Kreimeyer, Matthias; Blandini, LucioPrevious work has shown that floor slabs make up most of the material mass of building structures and are typically made of reinforced concrete. Considering the associated resource consumption and greenhouse gas emissions, new approaches are needed in order to reduce the built environment’s impact on the ongoing climate crisis. Various studies have demonstrated that adaptive building structures offer a potential solution for reducing material resource consumption and associated emissions. Adaptive structures have the ability to improve load-bearing performance by specifically reacting to external loads. This work applies the concept of adaptive structures to reinforced concrete slabs through the integration of fluidic actuators into the cross-section. The optimal integration of actuators in reinforced concrete slabs is a challenging interdisciplinary design problem that involves many parameters. In this work, actuation influence matrices are extended to slabs and used as an analysis and evaluation tool for deriving actuation concepts for adaptive slabs with integrated fluidic actuators. To define requirements for the actuator concept, a new procedure for the selection of actuation modes, actuator placement and the computation of actuation forces is developed. This method can also be employed to compute the required number of active elements for a given load case. The new method is highlighted in a case study of a 2 m × 2 m floor.Item Open Access A timed off-switch for dynamic control of gene expression in Corynebacterium glutamicum(2021) Siebert, Daniel; Altenbuchner, Josef; Blombach, BastianDynamic control of gene expression mainly relies on inducible systems, which require supplementation of (costly) inducer molecules. In contrast, synthetic regulatory circuits, which allow the timed shutdown of gene expression, are rarely available and therefore represent highly attractive tools for metabolic engineering. To achieve this, we utilized the VanR/PvanABK* regulatory system of Corynebacterium glutamicum, which consists of the transcriptional repressor VanR and a modified promoter of the vanABK operon (PvanABK*). VanR activity is modulated by one of the phenolic compounds ferulic acid, vanillin or vanillic acid, which are co-metabolized with d-glucose. Thus, gene expression in the presence of d-glucose is turned off if one of the effector molecules is depleted from the medium. To dynamically control the expression of the aceE gene, encoding the E1 subunit of the pyruvate dehydrogenase complex that is essential for growth on d-glucose, we replaced the native promoter by vanR/PvanABK* yielding C. glutamicum ΔPaceE::vanR-PvanABK*. The biomass yield of this strain increased linearly with the supplemented amount of effector. After consumption of the phenolic compounds growth ceased, however, C. glutamicumΔPaceE::vanR-PvanABK* continued to utilize the residual d-glucose to produce significant amounts of pyruvate, l-alanine, and l-valine. Interestingly, equimolar concentrations of the three phenolic compounds resulted in different biomass yields; and with increasing effector concentration, the product spectrum shifted from pyruvate over l-alanine to l-valine. To further test the suitability of the VanR/PvanABK* system, we overexpressed the l-valine biosynthesis genes ilvBNCE in C. glutamicum ΔPaceE::vanR-PvanABK*, which resulted in efficient l-valine production with a yield of about 0.36 mol l-valine per mol d-glucose. These results demonstrate that the VanR/PvanABK* system is a valuable tool to control gene expression in C. glutamicum in a timed manner by the cheap and abundant phenolic compounds ferulic acid, vanillin, and vanillic acid.Item Open Access Development of an Euler-Lagrangian framework for point-particle tracking to enable efficient multiscale simulations of complex flows(2023) Kschidock, HelenaIn this work, we implement, test, and validate an Euler-Lagrangian point-particle tracking framework for the commercial aerodynamics and aeroacoustics simulation tool ultraFluidX, which is based on the Lattice Boltzmann Method and optimized for GPUs. Our framework successfully simulates one-way and two-way coupled particle-laden flows based on drag forces and gravitation. Trilinear interpolation is used for determining the fluid's macroscopic properties at the particle position. Object and domain boundary conditions are implemented using a planar surface approximation. The whole particle framework is run within three dedicated GPU kernels, and data is only copied back to the CPU upon output. We show validation for the velocity interpolation, gravitational acceleration, back-coupling forces and boundary conditions, and test runtimes and memory requirements. We also propose the next steps required to make the particle framework ready for use in engineering applications.Item Open Access Water level monitoring at SAPOS stations through GNSS-IR : a case study at the station Iffezheim(2023) Wagner, Sven B.The German SAPOS-Network comprises approximately 270 permanent GNSS receivers, capturing signals from Global Navigation Satellite Systems such as GPS, GLONASS, Galileo, and BeiDou. Primarily employed for generating kinematic, mathematical, and physical models within their respective regions, these receivers hold untapped potential for alternative applications. GNSS receivers capture multipath errors, typically considered unwanted interferences resulting from signal reflections off surfaces beneath the antenna. Despite their potential to adversely affect data precision, these interferences contain valuable information about the reflecting surface. As satellites pass through the receivers’ field of view at specific elevation angles, the interference between the direct and reflected signals leads to constructive and destructive patterns. This phenomenon occurs due to variations in signal phase between the direct and reflected signal, enhancing or dampening the signal strength. These variations in signal strength are captured in the satellites Signal-to-Noise Ratio (SNR) data. Spectral analysis of the SNR data can be used to determine the frequency of the interference pattern. Combining this frequency with the corresponding signal wavelength and satellite elevation angles allows the calculation of the vertical distance between the antenna phase centre and the reflecting surface on Earth. This method, known as GNSS Interferometric Reflectometry (GNSS-IR), provides a valuable means of monitoring surface information, including soil moisture, snow depth, and water levels. At SAPOS stations near rivers and water bodies, GNSS-IR offers a cost-effective, accessible, and innovative opportunity to gather water level information using the already existing infrastructure. This research explores the potential of GNSSIR for water level monitoring at SAPOS stations focusing on the Iffezheim station along the Rhine River near the City of Karlsruhe in southern Germany.Item Open Access Charge regulation and swelling of weak polyelectrolyte nanogels in divalent salt solutions(2026) Beyer, David; Holm, ChristianWe use computer simulations to investigate the behavior of a weak polyelectrolyte nanogel in a solution containing divalent salt. In our simulations, we systematically vary the bulk pH value and the bulk concentration of divalent salt, allowing us to study the influence of charge regulation and divalent ions on the ionization behavior, ion partitioning, and nanogel swelling. With regard to the ionization behavior, we observe that, with an increasing concentration of divalent salt, the suppression of ionization becomes weaker. Moreover, we find that the strongly non‐uniform ionization profile observed in the absence of divalent counterions becomes increasingly uniform as the concentration of divalent salt is increased. We also study the partitioning of monovalent and divalent counterions between the nanogel and the bulk solution; our analysis shows that the uptake of divalent ions may be enhanced by up to tenfold as compared to the mean‐field prediction. Finally, we consider the influence of divalent ions on the pH‐dependent swelling behavior of the nanogel. Here, we observe a two‐stage swelling driven by charge regulation and ion partitioning. Overall, our results highlight the complex interplay of ionization equilibria, valency effects, and ion partitioning in weak polyelectrolyte systems.Item Open Access Feasibility analysis of using Model Predictive Control in Demand-Side Management of residential building(2020) Ramachandran Selvaraj, Sri VishnuThe energy systems are becoming smart recently with an increase in communication capabilities between producer, distributor and consumer. Also, many distributed renewable energy producers both in large and domestic scale are adding to the system day by day. Executing Smart Demand-Side Management (DSM) programs can help in providing financial benefits and stability of the energy system without compromising the comfort of end-users. Model Predictive Control (MPC) is an advanced method of process control that is used to control a process while satisfying a set of constraints. Due to its ability to predict future events and generate optimal control, it is widely used in process industries since the 1980s and in recent years it is introduced in power systems. This motivates to study the economic feasibility of using MPC in executing DSM for Residential building, to optimize the power consumption costs and stability of the energy system in the presence of local renewable energy sources (E.g., PV system). The main contribution of this thesis work is to measure the economic benefit of using MPC on DSM of household electricity consumption. A detailed study of modeling the demand side, i.e the appliances of a smart home, along with the domestic energy generators is done in the initial part. Apart from the physical properties of the renewable energy generators, the influence of external factors like weather, dynamic-pricing of electricity and changing user preference is also considered in the model. This formulated model is used to perform simulation of the residential building to generate an optimized energy consumption schedule and calculate the resulting economic benefits. The periodic changes in weather forecast and dynamic-prices are fed into the simulation to improve the prediction accuracy of the system. Lastly, the model is evaluated on a physical implementation to analyze its performance. There are multiple findings as part of the result of this thesis, like the economic benefit of using such a system will encourage many users to participate in Demand response programs, this in turn will help in the reduction of pollution originating from non-renewable energy generators.