Universität Stuttgart
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Item Open Access Exploring tailored fiber placement in biocomposite modular structures(2025) Petrš, Jan; Spyridonos, Evgenia; Grabowska, Paulina; Grisin, Benjamin; Carosella, Stefan; Middendorf, Peter; Dahy, HanaaItem Open Access Manipulating wetting and pore filling by wall transparency(2025) Kondrat, Svyatoslav; Schimmele, Lothar; Giacomello, Alberto; Tasinkevych, Mykola; Dietrich, S.Atomically thin walls become increasingly prevalent in modern technologies. Exhibiting a unique property-transparency to interparticle interactions-such walls influence processes as diverse as capacitive energy storage, electron transfer, and wetting. However, the impact of wall transparency on wetting and capillary phenomena remains poorly understood. Herein, we employ classical density functional theory to explore how van der Waals interactions across thin solid walls affect capillarity and substrate wetting. Our findings demonstrate that a fluid-filled, sidewise-open channel beneath a thin wall can drastically enhance the lyophobicity of the wall (hydrophobicity if fluid is water), up to the point of effectively transforming lyophilic surfaces into lyophobic ones. Conversely, a fluid covering a thin wall can convert capillary condensation to drying and induce unusual capillary phases within the channel. These findings highlight the potential of wall transparency as a tool for manipulating channel filling and wetting behaviors, emphasizing its significance for interfacial phenomena and fluid adsorption in porous materials.Item Open Access Introducing tree-based-regression models for prediction of hard rock TBM performance with consideration of rock type(2022) Salimi, Alireza; Rostami, Jamal; Moormann, Christian; Hassanpour, JafarPrediction of machine performance is a fundamental step for planning, cost estimation/control and selection of the machine type when using a tunnel boring machine (TBM). Penetration rate (PR) and machine utilization (U) are the two principal measures of TBM performance for evaluating the feasibility of using a machine in a given ground condition. However, despite the widespread use of TBMs and established track records, accurate estimation of machine performance could still be a challenge, particularly in complex geological conditions. Since different types of rocks have varied texture (cementation and grain size), and respond differently to cutting forces in the TBM tunnelling, incorporating the effects of rock type in performance prediction models can improve the accuracy of the estimates. The aim of this study was to develop models for predicting penetration rate of hard rock TBMs in different types of rock based on field penetration index (FPI), using multivariable regression analysis and machine learning algorithm, including classification and regression tree (CART). The proposed models offer estimated FPIs in different rock types, rock strength, and rock mass properties in the form of graphs (diagrams), which can be used to estimate TBM penetration rate. The proposed models have been developed based on the analysis of a comprehensive database of TBM performance in various rock types and offers more accurate estimates of machine performance by incorporating many of the key parameters available in typical geotechnical reports and contract documents. The models also exhibit sensitivity to rock mass parameters for predicting the penetration rate.Item Open Access Low-field chip-based Overhauser dynamic nuclear polarization platforms(2026) Yang, Qing; Anders, Jens (Prof. Dr.)Item Open Access Multiphoton quantum interference at ultracompact inverse-designed multiport beam splitter(2025) Huang, Shiang-Yu; Kumar, Shreya; Huster, Jeldrik; Augenstein, Yannick; Rockstuhl, Carsten; Barz, StefanieItem Open Access GeSn‐on‐Si avalanche photodiodes with high responsivity and low dark current(2025) Wanitzek, Maurice; Ramachandra, Harishnarayan; Spieth, Christian; Daus, Alwin; Schulze, Jörg; Oehme, MichaelGeSn‐on‐Si avalanche photodiodes (APDs) are emerging as a promising solution for low‐light detection in the short‐wave infrared (SWIR) spectral range, including applications in imaging and telecommunications. In this work, key challenges such as high dark current and limited responsivity are addressed by demonstrating devices, which combine low noise with high signal amplification, while remaining compatible with silicon‐based technology. GeSn‐on‐Si APDs with various Sn concentrations up to 1.9% are fabricated and characterized. The GeSn layers are grown pseudomorphically on Ge virtual substrates on Si wafers using molecular beam epitaxy. The devices comprise a double‐mesa structure and exhibit a dark current dominated by a perimeter leakage path, independent of the Sn content. A dark current below 1 µA is maintained up to the onset of avalanche breakdown, marking a significant improvement compared to prior work. A record‐high responsivity of 14.7 A W -1 is achieved at 1550 nm for the APD with 1.9% Sn. Through impulse response measurements, the 3‐dB bandwidth is determined to 1.2 GHz on devices with an 80 µm diameter, resulting in a responsivity‐bandwidth‐product of 17.6 A W -1 GHz -1 . These results highlight the potential of GeSn‐on‐Si APDs for high‐performance, low‐light applications in the SWIR range.Item Open Access Analysis of target data-dependent greedy kernel algorithms : convergence rates for f-, f· P- and f/P-greedy(2022) Wenzel, Tizian; Santin, Gabriele; Haasdonk, BernardData-dependent greedy algorithms in kernel spaces are known to provide fast converging interpolants, while being extremely easy to implement and efficient to run. Despite this experimental evidence, no detailed theory has yet been presented. This situation is unsatisfactory, especially when compared to the case of the data-independent P-greedy algorithm, for which optimal convergence rates are available, despite its performances being usually inferior to the ones of target data-dependent algorithms. In this work, we fill this gap by first defining a new scale of greedy algorithms for interpolation that comprises all the existing ones in a unique analysis, where the degree of dependency of the selection criterion on the functional data is quantified by a real parameter. We then prove new convergence rates where this degree is taken into account, and we show that, possibly up to a logarithmic factor, target data-dependent selection strategies provide faster convergence. In particular, for the first time we obtain convergence rates for target data adaptive interpolation that are faster than the ones given by uniform points, without the need of any special assumption on the target function. These results are made possible by refining an earlier analysis of greedy algorithms in general Hilbert spaces. The rates are confirmed by a number of numerical examples.Item Open Access Application of self‐diagnosis and self‐repair on a truss prototype that adapts to loading through shape morphing(2025) Reksowardojo, Arka P.; Senatore, Gennaro; Blandini, Lucio; Smith, Ian F. C.This paper presents experimental testing of self‐diagnosis and self‐repair strategies on an adaptive truss prototype that counteracts the effect of loading through shape morphing. The prototype is a simply supported spatial truss with a span of 6 m and is equipped with 12 linear actuators. The structure is designed to adapt to external loads through shape morphing-that is, by undergoing large shape changes to achieve configurations that are optimal for load‐bearing. A damage event is replicated via the removal of a truss element, which simulates a loss of stiffness caused by buckling or fracture. A damage detection and localization algorithm is implemented based on the similarity evaluation of numerical and empirical redundancy matrices. Testing results demonstrate the efficacy of this method, with up to 81% and 79% accuracy for detection and localization, respectively, obtained considering all scenarios including false alarms (false positives) in the nondamaged state. For damaged states, the detection accuracy is 100% (no false negative). A self‐repair strategy based on shape morphing is proposed. The structure is controlled into a shape that is optimal to carry the external load, achieving a significant stress redistribution to mitigate the effect of damage. Experimental results demonstrate that when an element of the structure is removed to simulate damage, the stress increases by up to 22% compared to the undamaged condition. This increase is fully recovered through shape adaptation. Actuator faults were also analyzed. With all actuators in operation, shape adaptation reduces stress by up to 22% under peak load (in the absence of damage). When two actuators are simulated as faulty, a stress reduction of up to 11% is still achieved, demonstrating the effectiveness of the proposed shape morphing–based control strategy.Item Open Access Investigation of a large‐scale adaptive concrete beam with integrated fluidic actuators(2022) Burghardt, Timon; Kelleter, Christian; Bosch, Matthias; Nitzlader, Markus; Bachmann, Matthias; Binz, Hansgeorg; Blandini, Lucio; Sobek, WernerAs the world population keeps growing, so does the demand for new construction. Considering material resources are limited, it will be unfeasible to meet such demand employing conventional construction methods. A new resource‐saving approach is provided by adaptive structures. Using sensors, actuators and control units, structures are enabled to adapt to loads, for example, to compensate for deformations. Since deformations are dominant in the design of bending‐stressed load‐bearing structures, adaptivity enables such structures to be realized using less material and achieving the same load‐bearing capacity in comparison to conventional designs. This article presents a concrete beam of typical building dimensions that compensates deflections by means of integrated fluidic actuators. These actuators offer the possibility of reacting optimally to general loading. The investigation is carried out on an approximately 4‐m‐long beam with integrated hydraulic actuators. To ensure the overall functionality, accurate dimensioning of the beam as well as the hydraulic system is mandatory. Analytical design of the beam and actuation system are carried out for predimensioning. Experimental testing validates the function and demonstrates that the adaptive beam works as predicted. A fully compensation in deflection is possible. Therefore, a significant increase in load‐bearing capacity is possible with the same material input compared to conventional beams.Item Open Access Bedload transport estimation in mountainous intermittent rivers and streams(Stuttgart : Eigenverlag des Instituts für Wasser- und Umweltsystemmodellierung der Universität Stuttgart, 2023) Sadid, Najibullah; Wieprecht, Silke (Prof. Dr.-Ing.)Rivers and streams with the flow, sediment, and habitat seasonality are termed as intermittent rivers and streams (IRS). IRS are the main water bodies in arid and semi-arid regions of the world but are also found in the temperate and humid environment, where they are particularly draining headwater streams. Thus, a large part of headwater streams in the mountainous regions behave as intermittent water bodies, where the steep channel slope and a wide variety of sediment sizes add to their hydrosedimentological complexity. Bedload transport as an important sedimentological characteristic of mountainous IRS and essential for planning sediment management strategies, is far from being well understood. Often the knowledge of lowland perennial rivers is adapted to steep IRS, which may lead to an overestimation of bedload transport mainly due to the overestimation of near-bed flow characteristics. Despite the development of numerous methods for modifying near-bed flow parameters for steep IRS such as Double-averaging of Navier-Stokes equation and flow resistance methods modifications for steep IRS, their application is limited to small domains and laboratory conditions. In this research, the flow resistance, main determinant of near-bed flow characteristic is estimated using a regime channel approach. In this approach, the flow resistance is estimated on reach-scale based on the channel’s regime dimension, slope and bankfull discharge assuming an IRS is in regime state (equilibrium condition). A channel’s regime state represents a long-term average characteristic of a river and does not significantly change over time. A channel reach of a constant slope develops a certain flow resistance during its regime state development to resist the change imposed by bankfull discharge and maintain a specific regime geometry, slope, and sediment grain size. 2D- hydromorphological computer simulations are employed to simulate the development of channel regime state for several cases of initial geometries, slopes, and grain sizes by steering the flow resistance. This modifies the riverbed shear stress by the ratio of total flow resistance to grain resistance also known as relative flow resistance µ in order to account for flow energy dissipation on resistance sources such as macro-roughness elements (MRE), and bedforms. Alternatively, two cases of MRE as a main flow resistance inducer is built as non-erodible trapezoidal shapes (i) randomly distributed over the channel bed, and (ii) arranged in cascade bedforms are used in regime channel simulations. MRE protects the channel by reducing the exposed riverbed to erosion and changing the flow characteristics in their vicinity. Regime channel simulations are performed on artificial channels of initial slopes between 0.0% to 10% and initial dimensions of 5.5 m x 200 m and 16.5 m x 200 m resembling a fixed (laboratory) and an extended-width (natural wide channel) condition. Three channel slope combination cases representing a natural channel reach which can be composed of one or more constant slope stretch are also studied beside single slope channels. Steady state simulations are performed for six sediment grain size (GSD) sets, which cover a wide spectrum of naturally occurring sediment sizes. The simulation results show a power-law relationship between µ and regime channel slopes for all channel dimensions, reach combinations, GSD, initial slopes and with (R1) and without sediment feeding (R). The increase in relative flow resistance (µ) with regime channel slope is well reproduced in form of bedforms. Regime channels developed step-pool to cascade bedforms for steep slopes and plane- to riffle bed for gentle slopes channels. The relationship between µ and regime slope derived using regime channel simulation approach exhibits good agreement with some field measurement of flow resistance for mountainous rivers and streams. The approach is applied on two IRS case studies with observed data in Kabul River basin, Afghanistan to estimate bedload transport. The relative flow resistance resulted from models calibration showed good agreement with those derived from test channels regime development simulation. The outcome of channel regime simulation with presence of MRE as geometrical shapes produced a logarithmic-law with a horizontal asymptote relationship between MRE concentrations and channel regime slopes. Similar results are also reported from flume experiments that the ratio of drag to total shear stress increases rapidly when the MRE are sufficiently distant. Regime channels develop micro-channels around MRE, where the bulk of bedload transport occur. For MRE arrangements as cascades, the results show a power-law relationship between channel regime slope and step-pool dimensions λ = LD/DB. The results obtained are in good agreement with field measurement of naturally occurring and artificially built λ relationship with SR. Future studies can further enrich the validation of this approach by applying it to other study sites. Present modelling tools have their limitations when dealing with strong geometries which is often the case for mountain rivers, therefore, improvement in modelling techniques is required to flexibly deal with abrupt changes in riverbed geometry for instance when implementing MRE as main flow resistance inducer.