Eldorado - Repositorium der TU Dortmund

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Bei diesem Service handelt es sich um das Institutionelle Repositorium der Technischen Universität Dortmund. Hier werden Ressourcen aus und für Lehre, Studium und Forschung gespeichert, erschlossen und der Öffentlichkeit zugänglich gemacht.

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Aktuellste Veröffentlichungen

Modeling and analysis of discrete particle detection in wide-field surface plasmon resonance microscopy
(Elsevier BV, 2024-03-08) Al-Bataineh, Qais M.; Telfah, Ahmad D.; Tavares, Carlos J.; Hergenröder, Roland
Wide-field surface plasmon resonance microscopy (WF-SPRM), based on Kretschmann’s configuration, is a powerful technique for detecting nano-objects in solution. In this study, key parameters for building a highly sensitive WF-SPRM are optimized, including laser wavelength, prism refractive index, numerical aperture of the objective, and gold layer thickness. A medium model describes the surface plasmon resonance (SPR) sensor principle, treating molecules bound on the sensor surface as an effective medium with an effective refractive index and thickness. On the other hand, the SPR discrete particle model is introduced to describe the detection principle for discrete particles. Theoretical, numerical, and experimental analyses are conducted, and the calculated intensity profiles of single and double nanoparticles from the discrete particle model describe the experimental profiles well. Furthermore, the influence of coating the gold layer with a dielectric layer on the SPR sensitivity is investigated for varying refractive indices.
Deformation-induced damage in finitely-strained metal sheets: Large-area damage quantification and mechanical property assessment
(2026) Gerlach, Jan; Reclik, Tom; Wollenweber, Maximilian Aeneas; Gitschel, Robin; Hahn, Marlon; Al-Samman, Talal; Korte-Kerzel, Sandra; Kerzel, Ulrich; Korkolis, Yannis P.
Reliable identification of damage-induced property changes in formed metal sheets remains challenging because plas-tic deformation alters the mechanical response through several coupled mechanisms. Moreover, pronounced ductile damage evolution occurs predominantly under inhomogeneous states of deformation, e.g., strain localization, which compromises the characterization of potential effects of damage on macroscopic mechanical properties, e.g., elastic stiffness. In this study, damage in dual-phase steel DP800 sheets is isolated from other concurrent mechanisms using a novel “sheet extrusion” process. The flat, finitely-strained sheets exhibit large regions with homogeneous properties, enabling subsequent characterization of damage-induced property changes. Damage in the form of microscopic voids is then characterized by large-area scanning electron microscopy (SEM) measurements, and damage-induced property changes are determined by subsequent characterization tests on specimens extracted from the extruded sheets. It is found that deformation-induced damage does not measurably affect the apparent elastic stiffness or the pre-necking tensile response. In contrast, differences in fracture-related performance quantities, i.e., the remaining ductility and the tensile impact energy, indicate that higher deformation-induced damage promotes earlier macroscopic failure by increasing the likelihood of local void coalescence during subsequent loading.
High Speed Forming 2025
(2025-08) Korkolis, Yannis P.; Daehn, Glenn S.
Modeling and contribution of flexible heating systems for transmission grid congestion management
(Elsevier BV, 2024-06-26) Kröger, David; Teodosic, Milijana; Rehtanz, Christian
The large-scale integration of flexible heating systems in the European electricity market leads to a substantial increase of transportation requirements and consecutively grid congestions in the continental transmission grid. Novel model formulations for the grid-aware operation of both individual small-scale heat pumps and large-scale power-to-heat (PtH) units located in district heating networks are presented. The functionality of the models and the contribution of flexible heating systems for transmission grid congestion management is evaluated by running simulations for the target year 2035 for the German transmission grid. The findings show a decrease in annual conventional redispatch volumes and renewable energy sources (RES) curtailment resulting in cost savings of approximately 5% through the integration of flexible heating systems in the grid congestion management scheme. The analysis suggests that especially large-scale PtH units in combination with thermal energy storages can contribute significantly to the alleviation of grid congestion and foster RES integration.
Mixed bioconvection of nanofluid of oxytactic bacteria through a porous cavity with inlet and outlet under periodic magnetic field using artificial intelligence based on LightGBM algorithm
(Elsevier BV, 2024-04-24) Hussain, Shafqat; Öztop, Hakan F.; Alsharif, Abdullah Madhi; Ertam, Fatih
The comprehension of microorganisms’ responses to magnetic field and fluid motion offers potential for the advancement of targeted drug delivery systems or medical interventions reliant on biological fluids. In this paper, the mixed bioconvection flow of nanofluid of oxytactic bacteria has been investigated through a porous cavity with inlet and outlet ports under the impact of periodic magnetic field. All the walls of the cavity are fixed at the constant high temperature. The proposed problem has been modeled first and then simulated using the finite element method. The computed computational fluid dynamics results have been analyzed for the several important controlling parameters. It is observed that there is at least 65% increment on heat transfer between the lowest and highest Peclet numbers. Further, regression analysis was conducted using the LightGBM algorithm. Careful parameter tuning was performed to avoid overfitting, ensuring that the model did not memorize the training data. According to the ℝ² values used for regression analysis, in the 18 datasets used for the performance metric comparison of the artificial intelligence model, a total of 18 targets were tried to be predicted for different Richardson number (0.1, 1, and 10) and Lewis Number (0.1, 1, and 10) values for each motile microorganisms, temperature and oxygen concentration values specified in the datasets, and a minimum accuracy of 95% and a maximum accuracy of 98% were obtained. These findings demonstrate the capability of the LightGBM algorithm to accurately predict the target variable within a high range of accuracy for the given datasets.