Filtern
Erscheinungsjahr
Dokumenttyp
- Beitrag zu einem Tagungsband (87)
- Zeitschriftenartikel (68)
- Vortrag (52)
- Posterpräsentation (25)
- Beitrag zu einem Sammelband (10)
- Dissertation (5)
- Forschungsbericht (5)
- Forschungsdatensatz (3)
- Video (1)
Sprache
- Englisch (196)
- Deutsch (59)
- Mehrsprachig (1)
Schlagworte
- Simulation (256) (entfernen)
Organisationseinheit der BAM
- 8 Zerstörungsfreie Prüfung (39)
- 6 Materialchemie (25)
- 8.4 Akustische und elektromagnetische Verfahren (20)
- 6.6 Physik und chemische Analytik der Polymere (18)
- 8.5 Röntgenbildgebung (14)
- 3 Gefahrgutumschließungen; Energiespeicher (7)
- 6.5 Synthese und Streuverfahren nanostrukturierter Materialien (7)
- 9 Komponentensicherheit (7)
- 5 Werkstofftechnik (5)
- 9.3 Schweißtechnische Fertigungsverfahren (5)
Eingeladener Vortrag
- nein (52)
Im Rahmen des Forschungsprojekts "Artificial Intelligence for Rail Inspection" (AIFRI) wird ein KI-Algorithmus entwickelt, um die Fehlererkennung und Bewertung bei der Auswertung von Schienenprüfungen mittels Ultraschall- und Wirbelstromprüfverfahren zu verbessern. Je nach Prüfverfahren werden relevante Schienenschädigungen (z. B. Head Checks) und Artefakte (z. B. Bohrungen) entsprechend analysiert und in einem parametrisierbaren digitalen Zwilling abgebildet, um anschließend die KI-Algorithmen trainieren zu können. Mit der Simulation können Prüffahrten virtuell durchgeführt und Schadensbilder für das KI-Training erzeugt werden, die das Verhalten komplexer Systeme reproduzieren, ohne dass das reale System benötigt wird. Die Modellannahmen sind dabei von erheblicher Bedeutung, denn unzureichende Modellannahmen führen leicht zu falschen Simulationsergebnissen. Um die Ergebnisse einer Simulation ordnungsgemäß darstellen zu können, ist das Simulationsmodell selbst zu überprüfen.
Die Vollständigkeit, Richtigkeit und Genauigkeit der Simulationsergebnisse werden anhand von realen Prüfungen verifiziert. Für die Verifikation der Ultraschallsimulation werden hier Stegbohrungen als Referenzreflektoren herangezogen. Als Testkörper stehen Schienensegmente mit unterschiedlichen Profiltypen sowie speziell angefertigte Testkörper mit schienenähnlicher Geometrie zur Verfügung. In den Testkörpern befinden sich künstliche und reale Schädigungen in Kopf-, Steg- und Fußbereich, sowie Bohrungen mit Nuten. Die Validierung der Wirbelstromsimulation erfolgt an Testkörpern, die aus Schienenköpfen gefertigt sind. Dabei werden die Signale für unterschiedliche Nuttiefen und Nutenpaare mit unterschiedlichen Abständen untersucht.
Für die Modellierung der Simulationsergebnisse verweisen wir auf das ebenfalls eingereichte Poster „Simulation von Ultraschall- und Wirbelstromprüfdaten für die Schienenprüfung“.
Das Projekt AIFRI wird im Rahmen der Innovationsinitiative mFUND unter dem Förderkennzeichen 19FS2014 durch das Bundesministerium für Digitales und Verkehr gefördert.
Im Rahmen des Forschungsprojekts "Artificial Intelligence for Rail Inspection" (AIFRI) wird ein KI-Algorithmus entwickelt, um die Fehlererkennung und Bewertung bei der Auswertung von Schienenprüfungen mittels Ultraschall- und Wirbelstromprüfverfahren zu verbessern. Die Bandbreite möglicher Defekte und die Menge an Einflussgrößen auf die Schienenprüfung ist sehr groß, aber die Prüfdaten aus dem Feld bilden diese Bandbreite nicht balanciert ab und sind unzureichend gelabelt. Durch Simulationen werden große Mengen detailliert gelabelter Daten für relevante Schienenschädigungen und Artefakte bereitgestellt. Aus diesen Daten werden wiederum virtuellen Prüffahrten erstellt, die für das Training und die Validierung der KI genutzt werden können.
In unserem Poster stellen wir die Simulation dieser Ultraschall- und Wirbelstromprüfdaten vor. Dabei gehen wir im Detail auf die Themen CAD-Modellierung, Modellparameter, Simulationssoftware und Signalverarbeitung ein. Wir stellen ausgewählt die Simulation von Head Checks für Wirbelstromprüfverfahren und Bohrungsanrissen für Ultraschallprüfverfahren dar, da das Erkennen dieser Schädigungstypen bei der Schienenprüfung hohe Priorität innehat.
Für die Verifikation der Simulationsergebnisse verweisen wir auf den ebenfalls eingereichten Vortrag „Verifikation von Ultraschall- und Wirbelstromsimulationen bei der Schienenprüfung“.
Das Projekt AIFRI wird im Rahmen der Innovationsinitiative mFUND unter dem Förderkennzeichen 19FS2014 durch das Bundesministerium für Digitales und Verkehr gefördert.
The dripping behaviour of polymers is often observed experimentally through the UL94 flammability standard test. In this work, polymeric dripping under fire is investigated numerically using particle finite element method. A parametric analysis was carried out to observe the influence of a single property on overall dripping behaviour via a UL94 vertical test model. Surrogates and property ranges were defined for variation of the following parameters: glass transition temperature (Tg), melting temperature (Tm), decomposition temperature (Td), density (ρ), specific heat capacity (Cp), apparent effective heat of combustion of the volatiles, char yield (μ), thermal conductivity (k), and viscosity (η). Polyamide, poly(ether ether ketone), poly(methyl methacrylate), and polysulfone were used as benchmarks. Simulated results showed that specific heat capacity, thermal conductivity, and char yield allied with viscosity were the properties that most influenced dripping behaviour (starting time and occurrence).
Additive manufacturing (AM) offers significantly greater freedom of design compared to conventional manufacturing processes since the final parts are built layer by layer. This enables metal AM, also known as metal 3D printing, to be utilized for improving efficiency and functionality, for the production of parts with very complex geometries, and rapid prototyping. However, despite many technological advancements made in recent years, several challenges hinder the mass adoption of metal AM. One of these challenges is mechanical anisotropy which describes the dependency of material properties on the material orientation. Therefore, in this work, stainless steel 316L parts produced by laser-based powder bed fusion are used to isolate and understand the root cause of anisotropy in AM parts. Furthermore, an efficient and accurate multiscale numerical framework is presented for predicting the deformation behavior of actual AM parts on the macroscale undergoing large plastic deformations. Finally, a novel constitutive model for the plastic spin is formulated to capture the influence of the microstructure evolution on the material behavior on the macroscale.
3D concrete printing is an innovative new construction technology offering the potential to enable an efficient production of individual structures with less consumption of resources. The technology will mainly shape the future construction philosophy, automate the build process and help reaching the climate goals in civil engineering. From the design of a structure to the printed component, many individual steps based on different software are required which must be repeated for each new or changed structure. First, the geometry of the structure is created in a CAD program. Second, the print path is defined in a slicer software creating the machine code for the printer (G-Code). Finally, the structure can be printed. Furthermore, a numerical model of the printed structure is necessary for process optimization and control. In that way the number of test prints can be reduced, costs can be saved, and the component behavior can be predicted. For those purposes, an automated workflow allowing to run all steps or individual steps without interacting with each individual software program is required. Furthermore, changes in parameters or the exchange of parts (using a different design or different printer) must be possible in a simple manner. In the presented work, such an automated workflow based on the example of a parametrized wall element for extrusion-based concrete printing is developed. The investigated wall structure is parametrized using the global geometry parameters: height, width, thickness, radius, kind of infill structure (honey-comb, zig-zag) and number of repeated infills. All above mentioned steps are implemented via python interfaces using pydoit as workflow tool. General interfaces with prescribed input and output files are defined allowing adaptations for different software and tools. The described workflow is tested by performing a test series investigating the influence of the in-fill structure on the mechanical properties of the test walls.
The change of DNA radiation damage upon hydration: In-situ observations by near-ambient-pressure XPS
(2023)
Ionizing radiation damage to DNA plays a fundamental role in cancer therapy. X-ray photoelectron-spectroscopy (XPS) allows simultaneous irradiation and damage monitoring. Although water radiolysis is essential for radiation damage, all previous XPS studies were performed in vacuum. Here we present near-ambient-pressure XPS experiments to directly measure DNA damage under water atmosphere. They permit in-situ monitoring of the effects of radicals on fully hydrated double-stranded DNA. The results allow us to distinguish direct damage, by photons and secondary low-energy electrons (LEE), from damage by hydroxyl radicals or hydration induced modifications of damage pathways. The exposure of dry DNA to x-rays leads to strand-breaks at the sugar-phosphate backbone, while deoxyribose and nucleobases are less affected. In contrast, a strong increase of DNA damage is observed in water, where OH-radicals are produced. In consequence, base damage and base release become predominant, even though the number of strand-breaks increases further.
State-of-the-art laser powder bed fusion (PBF-LB/M) machines allow pre-heating of the substrate plate to reduce stress and improve part quality. However, two major issues have been shown in the past: First, with increasing build height the apparent pre-heat temperature at the surface can deviate drastically from the nominal pre-heat temperature in the substrate plate. Second, even within a single layer the local surface pre-heat temperature can show large gradients due to thermal bottlenecks in the part geometry underneath the top surface. Both lead to unwanted changes in microstructure or defects in the final parts. In this study, a first attempt is taken to show the feasibility of pre-heating the top surface with the onboard laser beam to overcome the mentioned issues. A single layer of a group of three parts built from IN718 to a height of 33.5 mm is pre-heated in a commercially available PBF-LB/M machine to an average steady state surface temperature of 200 °C using the onboard laser beam. The parts are continuously heated, omitting powder deposition and melting step. Temperatures are measured by thermocouples underneath the surface. The experiments are supported by a thermal finite element (FE) model that predicts the temperature field in the parts. When heating the parts uniformly with the laser beam, differences in surface temperatures as large as 170 K are observed. To overcome this inhomogeneity, the heat flux supplied by the laser beam is modulated. An optimized, spatial heat flow distribution is provided by the thermal FE model and translated into a scan pattern that reproduces the optimized heat distribution on the PBF-LB/M machine by locally modulating hatch distance and scan velocity. This successfully reduces the differences in surface temperature to 20 K. Thermographic imaging shows that a homogeneous surface temperature can be achieved despite the localized heat input by the beam. The potential for industrial application of the optimized laser-heating technique is discussed.
Soft polymers such as the investigated polyurethane, characterized by low Young’s moduli and prone to high shear deflection, are frequently applied in pneumatic cylinders. Their performance and lifetime without external lubrication are highly determined by the friction between seal and shaft and the wear rate. FEM simulation has established itself as a tool in seal design processes but requires input values for friction and wear depending on material, load, and velocity. This paper presents a tribological test configuration for long stroke, reciprocating movement, allowing the generation of data which meet the requirements of input parameters for FEM simulations without the geometrical influences of specific seal profiles. A numerical parameter study, performed with an FEM model, revealed the most eligible sample geometry as a flat, disc-shaped sample of the polymer glued on a stiff sample holder. At the same time, the study illustrates that the sensitivity of the contact pressure distribution to Poisson’s ratio and CoF can be minimized by the developed and verified setup. It ensures robust, reliable, and repeatable experimental results with uniform contact pressures and constant contact areas to be used in databases and FEM simulations of seals, enabling upscaling from generically shaped samples to complex seal profiles.
Dose enhancement by gold nanoparticles (AuNP) increases the biological effectiveness of radiation damage in biomolecules and tissue. To apply them effectively during cancer therapy their influence on the locally delivered dose has to be determined.[1] Hereby, the AuNP locations strongly influence the energy deposit in the nucleus, mitochondria, membrane and the cytosol of the targeted cells. To estimate these effects, particle scattering simulations are applied. In general, different approaches for modeling the AuNP and their distribution within the cell are possible. In this work, two newly developed continuous and discrete-geometric models for simulations of AuNP in cells are presented. [2] These models are applicable to simulations of internal emitters and external radiation sources. Most of the current studies on AuNP focus on external beam therapy. In contrast, we apply the presented models in Monte-Carlo particle scattering simulations to characterize the energy deposit in cell organelles by radioactive 198AuNP. They emit beta and gamma rays and are therefore considered for applications with solid tumors. Differences in local dose enhancement between randomly distributed and nucleus targeted nanoparticles are compared. Hereby nucleus targeted nanoparticels showed a strong local dose enhancement in the radio sensitive nucleus. These results are the foundation for ongoing experimental work which aims to obtain a mechanistic understanding of cell death induced by radioactive 198Au.