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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).
Liquid metal embrittlement (LME) cracking is a phenomenon observed during resistance spot welding (RSW) of zinccoated advanced highstrength steels (AHSS) in automotive manufacturing. In this study, severe cracks are observed at the edge of the sheet under reduced flange widths. These cracks, traversing the AHSS sheet, culminate at the edge with a width of approximately 1.2 mm.
Through combined numerical and experimental investigations, and material testing, these cracks are identified and validated as a new type of LME crack. The mechanism behind this crack formation is attributed to unique geometric conditions that, when compared to center welding, amplify radial material flow by ninefold to 0.87 mm. The resultant tangential tensile stresses approximate 760 MPa, which exceed the yield strength of the examined advanced highstrength steel (AHSS) under heightened temperature conditions, and when combined with liquid zinc, promote the formation of this new type of LME crack.
The present work is part of the AIFRI project (Artificial Intelligence For Rail Inspection), where we and our project partners train a neural network for defect detection and classification. Our goal at BAM is to generate artificial ultrasound and eddy current training data for the A.I. This paper has an exploratory nature, where we focus on the simulation of eddy current signals for head check cracks, one of the most important rail surface defects. The goal of this paper is twofold. On the one hand, we present our general simulation setup. This includes geometric models for head check cracks with features like branching and direction change, a model for the HC10 rail testing probe, and the configuration of the Faraday simulation software.
On the other hand, we use the Faraday software to simulate eddy current testing signals with a strong focus on the influence of the damage depth on the signal, while differentiating between different crack geometries. Here, we observe an early saturation effect of the test signal at a damage depth of 2 mm (at a crack angle of 25◦ to the surface). That is about 2 mm earlier than we would expect from measurements at a crack angle of 90◦. This behavior will be investigated further in a future paper. Finally, we interpolate the simulated signals in a two-step curve fitting process. With these interpolations we may generate eddy current test signals for any damage depth within the simulated range.
The interest in using computer simulations of dimensional x-ray computed tomography (dXCT) for various metrological purposes—such as measurement planning, performance prediction, performance optimisation and, finally, measurement uncertainty estimation—is increasing along with the ever-growing demand for more reliable measurements with dXCT. However, before a piece of simulation software can be used for tasks related to coordinate metrology, it has to be ensured that it is able to simulate physical laws, characteristic effects and basic CT system functionalities correctly and with sufficient accuracy. In short, the software must be qualified for dimensional metrology tasks. As one part of such a qualification process, a method is presented here for determining conformity intervals of 2D tests (projection-based tests) based on 3D tests (testing based on dimensional evaluations in a reconstructed volume) for the assessment of dXCT simulation software. The method consists of varying relevant parameter values in order to verify their influence on 3D measurement results. The results of the 3D tests with varied parameter values are then transferred to the quantities tested in the 2D tests and used as the basis for determining conformity intervals. Two approaches are applied for determining whether or not a variation of a parameter value is significant: (a) statistical and (b) heuristic. Two examples are presented, each based on simulated images, which show the application of the two different approaches for determining conformity intervals for the results of the 2D tests.
Accessing radiation damage to biomolecules on the nanoscale by particle-scattering simulations
(2023)
Radiation damage to DNA plays a central role in radiation therapy to cure cancer. The physico-chemical and biological processes involved encompass huge time and spatial scales. To obtain a comprehensive understanding on the nano and the macro scale is a very challenging tasks for experimental techniques alone. Therefore particle-scattering simulations are often applied to complement measurements and aide their interpretation, to help in the planning of experiments, to predict their outcome and to test damage models. In the last years, powerful multipurpose particle-scattering framework based on the Monte-Carlo simulation (MCS) method, such as Geant4 and Geant4-DNA, were extended by user friendly interfaces such as TOPAS and TOPAS-nBio. This shifts their applicability from the realm of dedicated specialists to a broader range of scientists. In the present review we aim to give an overview over MCS based approaches to understand radiation interaction on a broad scale, ranging from cancerous tissue, cells and their organelles including the nucleus, mitochondria and membranes, over radiosensitizer such as metallic nanoparticles, and water with additional radical scavenger, down to isolated biomolecules in the form of DNA, RNA, proteins and DNA-protein complexes. Hereby the degradation of biomolecules by direct damage from inelastic scattering processes during the physical stage, and the indirect damage caused by radicals during the chemical stage as well as some parts of the early biological response is covered. Due to their high abundance the action of hydroxyl radicals (•OH) and secondary low energy electrons (LEE) as well as prehydrated electrons are covered in additional detail. Applications in the prediction of DNA damage, DNA repair processes, cell survival and apoptosis, influence of radiosensitizer on the dose distribution within cells and their organelles, the study of linear energy transfer (LET), the relative biological effectiveness (RBE), ion beam cancer therapy, microbeam radiation therapy (MRT), the FLASH effect, and the radiation induced bystander effect are reviewed.
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.
A versatile software package in the form of a Python extension, named CDEF (computing Debye’s scattering formula for extraordinary form factors), is proposed to calculate approximate scattering profiles of arbitrarily shaped nanoparticles for small-angle X-ray scattering (SAXS). CDEF generates a quasi-randomly distributed point cloud in the desired particle shape and then applies the open-source software DEBYER for efficient evaluation of Debye’s scattering formula to calculate the SAXS pattern (https://github.com/j-from-b/CDEF). If self-correlation of the scattering signal is not omitted, the quasi-random distribution provides faster convergence compared with a true-random distribution of the scatterers, especially at higher momentum transfer. The usage of the software is demonstrated for the evaluation of scattering data of Au nanocubes with rounded edges, which were measured at the four-crystal monochromator beamline of PTB at the synchrotron radiation facility BESSY II in Berlin. The implementation is fast enough to run on a single desktop computer and perform model fits within minutes. The accuracy of the method was analyzed by comparison with analytically known form factors and verified with another implementation, the SPONGE, based on a similar principle with fewer approximations. Additionally, the SPONGE coupled to McSAS3 allows one to retrieve information on the uncertainty of the size distribution using a Monte Carlo uncertainty estimation algorithm.
Despite considerable advances in synthesizing high-quality core/shell upconversion (UC) nanocrystals (NC; UCNC) and UCNC photophysics, the application of near-infrared (NIR)-excitable lanthanide-doped UCNC in the life and material sciences is still hampered by the relatively low upconversion luminescence (UCL) of UCNC of small size or thin protecting shell. To obtain deeper insights into energy transfer and surface quenching processes involving Yb3+ and Er3+ ions, we examined energy loss processes in differently sized solid core NaYF4 nanocrystals doped with either Yb3+ (YbNC; 20% Yb3+) or Er3+ (ErNC; 2% Er3+) and co-doped with Yb3+ and Er3+ (YbErNC; 20% Yb3+ and 2% Er3+) without a surface protection shell and coated with a thin and a thick NaYF4 shell in comparison to single and co-doped bulk materials. Luminescence studies at 375 nm excitation demonstrate backenergy transfer (BET) from the 4G11/2 state of Er3+ to the 2F5/2 state of Yb3+, through which the red Er3+ 4F9/2 state is efficiently populated. Excitation power density (P)-dependent steady state and time-resolved photoluminescence measurements at different excitation and emission wavelengths enable to separate surface-related and volume-related effects for two-photonic and threephotonic processes involved in UCL and indicate a different influence of surface passivation on the green and red Er3+ emission.
The intensity and lifetime of the latter respond particularly to an increase in volume of the active UCNC core. We provide a threedimensional random walk model to describe these effects that can be used in the future to predict the UCL behavior of UCNC.
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. 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.
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 future experimental work which aims to obtain a mechanistic understanding of cell death induced by radioactive 198Au.
Different approaches have been attempted so far to reduce fuel consumption and linked pollutants, including vehicle equipment and design, with rational driving style being recognized as a potential source of fuel savings. However, no specific methodology had been suggested so far to assess fuel economy of driving other than the fuel consumed itself. In this paper, the Standard deviation of driving acceleration has been found to be directly associated to fuel consumption, so that the less dispersion of the driving acceleration, produces the lower fuel consumptions and emissions. Such metric could be thus used to assess driving style.