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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.
This paper deals with life prediction by observation and simulation of short fatigue cracks in cyclically loaded smooth and notched specimens made of 0.15 wt-% carbon steel SAE1017. The measured crack behaviour was simulated in a microstructural environment. Reference tests under constant amplitude loading allowed to determine model parameters and hence a reasonable life prediction by simulation resulted even for service loading. Short crack behaviour was a measurable property for damage also to compare smooth and notched specimens.
For decades, the low-strain impact integrity testing using a hammer blow is well established as a method of quality assurance for various pile types. However, this method has its limitations. Our research and development focuses on improving the excitation signal using a shaker system in contrast to the standard hammer method. Another approach is to increase the amount of sensors used during testing. The purpose is to identify the direction of wave propagation which gives advantages under difficult conditions, such as piles below structures.
Pile integrity testing (PIT) using a shaker system was performed on two 11 m long piles of 90 cm in diameter. While one pile was intact, the other one showed a flaw at approx. 3.5 m below pile top, which was confirmed by standard PIT in 2012. A logarithmic sweep between 500 Hz and 1 KHz of 0.1 s was used as the input signal, being vertically injected into the pile. Prior to that, simulations on similar pile geometries showed that the depth of the pile toe as well as flaws within the pile can be extracted by applying regularized deconvolution. The result is the impulse response in the time domain.
The application of deconvolution on the measured signals shows that it is possible to identify the pile length but it is more difficult to clearly extract the flaw’s position in the pile. Additional digital signal processing techniques and the improvement of the regularized deconvolution method as well as the experimental setup need to be investigated.
Another way to improve the PIT method is to use a multichannel sensor arrangement. By arranging several accelerometers vertically along the accessible part of the pile shaft, it is possible to distinguish between downward and upward traveling waves. Furthermore, it is possible to estimate the unknown wave speed, which gives the possibility of more accurate pile length calculations. The method was evaluated successfully during a measurement campaign of a slab foundation with subjacent piles. In 20 of 28 cases the pile length could be detected accurately.
Non-destructive testing of rail tracks is carried out by using rail inspection cars equipped with ultrasonic and eddy current measurement. The evaluation of test data is mainly done manually, supported by a software tool which pre-selects relevant indications shown to the evaluators. The resulting indications have to be checked on-site using hand-held testing equipment. Maintenance interventions are then derived on the basis of these on-site findings.
Overall aim of the AIFRI (Artificial Intelligence For Rail Inspection) project - funded by the German Federal Ministry of Digital and Transport (BMDV) as part of the mFUND programme under funding code 19FS2014 – is to increase the degree of automation of the inspection process from the evaluation of the data to the planning of maintenance interventions. The accuracy of defect detection shall be increased by applying AI methods in order to enable an automated classification of detected indications into risk classes. For this purpose, data from both eddy current inspections and ultrasonic inspections will be used in combination.
Within the framework of this data-driven project, relevant defect patterns and artefacts present in the rail are analysed and implemented into a configurable digital twin. With the help of this digital twin virtual defects can be generated and used to train AI algorithms for detection and classification. With the help of reliability assessment trained AI algorithms will be evaluated with regard to the resulting quality in defect detection and characterisation.
A particular aspect of the development of AI methods is the data fusion of different NDT data sources: Thereby, synergies are used that arise from linking eddy current and ultrasonic inspection data in a combined model.
In the course of the project a demonstrator consisting of the developed IT-tool and an asset management system will be implemented and tested in the field using real-world data.
The cause and type of solid particle erosion varies across different industries and locations in plants, for instance the particles could be volcanic ash in aero-engines, fly ash in boilers, exfoliated scale in steam turbines or mineral matter in oil excavation. In all cases the durability of materials can be improved through better surface engineering and coatings, but the development of these is restricted also due to lack of generic models. In this respect, the simulation of a single impact with finite element methods using 100.000 knots would take about 15 minutes. In order to simulate an entire particle erosion experiment, up to one billion of such impacts would have to be considered. In order to simulate an entire particle erosion experiment, the current work presents an alternative approach capable of calculating about half a billion impacts on a substrate in less than six hours on a standard PC. The predictions of the simulation will be compared to a steel sample at 600°C eroded by aluminum oxide particles with a velocity around 210 m/s.
The cause and type of solid particle erosion varies across different industries and locations in plants, for instance the particles could be volcanic ash in aero-engines, fly ash in boilers, exfoliated scale in steam turbines or mineral matter in oil excavation. In all cases the durability of materials can be improved through better surface engineering and coatings, but the development of these is restricted also due to lack of generic models. In this respect, the simulation of a single impact with finite element methods using 100.000 knots would take about 15 minutes. In order to simulate an entire particle erosion experiment, up to one billion of such impacts would have to be considered. In order to simulate an entire particle erosion experiment, the current work presents an alternative approach capable of calculating about half a billion impacts on a substrate in less than six hours on a standard PC. The predictions of the simulation will be compared to a steel sample at 600°C eroded by aluminum oxide particles with a velocity around 210 m/s.
Wear mechanisms, as adhesion, abrasion, fatigue and tribochemical wear, are complex in their physical and chemical nature. A theoretical description and prediction of wear are in most cases still far from reality. It is, therefore, important to use test rigs before a practical application of a given material combination under tribological loading.
On the other hand, model equations can be helpful for wear description, if a single wear mechanism is dominant.
Under oscillating and continuous sliding contact conditions, equations for wear calculation are presented to describe running-in and stationary wear behaviour of metals and ceramics. By using shear energy density, real area of contact, flash temperature, activation energy and numerical simulations with the method of movable cellular automata (MCA), wear data were calculated and compared to experimental laboratory results.
Industrial radiography or Radiographic Testing (RT) is a method of non-destructive testing where many types of manufactured components can be examined to verify the internal structure and integrity of the specimen. The computer program aRTist can generate synthetic radiographs from a virtual RT test set-up. In the field of industrial radiology simulation is used, e.g. to optimize techniques for complex applications, to support the preparation of written procedures, and for education purposes.
The simulator aRTist combines analytical and Monte Carlo methods to efficiently model the radiation transport. The program comes with a graphical user interface written in Tcl/Tk. In combination of Tcl/Tk and the 3D capabilities of the visualization toolkit (VTK) a practical and convenient simulator has been realized. This will be illustrated by discussing application scenarios of classical radiography, X-ray computer tomography, and X-ray backscatter imaging. Additionally, some insight to the software implementation of the simulator will be given.
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.
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.
Liquid metal embrittlement (LME) cracking can occur during resistance spot welding (RSW) in zinc-coated advanced high-strength steels (AHSS) for automotive production. In this study, a methodological variation of hold time is performed to investigate the process-related crack influence factors. A combination of numerical and experimental investigations confirms, that the extent of heat dissipation and re-heating of the sheet surface can be influenced and thus the degree of crack formation can be controlled in a targeted manner by the parameterisation of the hold time. The temperature and stress history of crack-free and crack-afflicted spot welds are analysed and a conclusion on the borders defining the LME active region is derived.
MaUS is an acronym for ”Material und Umweltsimulationen“. Plastics are in the focus of environmental politics due to their long term behaviour and therefore to their persistence. Not only that they appear as visible contaminants in the sea and on the beach, but their unknown behaviour concerning their additives as well as the related transformation products are anxious. Therefore, we wish to establish a certified reference method to provide a method for testing plastics.
Aim of this project is the development of fast motion standard reference methods for testing plastics regarding to their environmental compatibility. To establish these testing methods, we use polystyrene (PS) and polypropylene (PP) with environmental relevant brominated flame retardants, known for their persistent bioaccumulative and toxic (PBT) properties. In case of PS the material contains 1 wt% of 1,2,5,6,9,10-hexabromocyclododecan (HBCD) and in case of PP 0.1 wt% bromodiphenylether (BDE-209), which is known as a substance of very high concern (SVHC). Furthermore, we use polycarbonate (PC), which is still used as material in baby flasks and releases Bisphenol A (BPA), an estrogenic active substance.
As an additional material PTFE is used for its importance as a source for two ubiquitous environmental substances (PFOS and PFOA), whose toxicological effects are still incompletely known.
The focus in this current work is set on the transfer of potential pollutants out of applied materials mentioned above into environmental compartments like water or soil. Here an accelerated aging concept should be developed to shortened time consuming natural processes. For these resulting simulations we use a programmable weathering chamber with dry and wet periods and with high and low temperatures. These programmes run for several weeks and according to a defined sampling schedule we take water samples, run a clean-up procedure by SPE (Molecular imprinted polymers (MiPs) resp. polymer based cartridges (Waters Oasis HLB)) and analyse them by HPLC-UV resp. LC-MS/MS. Of most interest in case of flame retardants are photocatalytic transformation products. Therefore, we conduct a non-target-screening resp. a suspected target-screening by LC-MS/MS and HRMS.
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. In this work, two newly developed continuous and discrete-geometric models for simulations of AuNP in cells are presented. 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.
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.
The aim of this research is to characterize a surface that has experienced low wear on asperities. The procedure used is similar to an Abbott-Firestone approach and based on functional bearing of projected area, surface area and material volume. Surface features extracted from surface height maps provide more comprehensive information about topography changes due to wear. Thus, they were used to detect low wear volumes on the top of asperities.
The aim of this research is to characterize a surface that has experienced low wear on asperities. The procedure used is similar to an Abbott-Firestone approach and based on functional bearing of projected area, surface area and material volume. Surface features extracted from surface height maps provide more comprehensive information about topography changes due to wear. Thus, they were used to detect low wear volumes on the top of asperities.
Implementation of soilcrete columns via jet grouting or deep soil mixing to stabilize problematic subsurface soils is common in underground construction. However, industry is faced with limited options to characterize column geometry and quality of the resulting soilcrete without excavation or destructive testing. Laboratory-scale experiments were conducted on simulated soilcrete columns using crosshole ultrasonic testing to evaluate the feasibility of acoustic tomography to characterize soilcrete geometry and quality. Data were acquired on multiple columns immediately after placement up to a curing time of 120 hours. Jet grout compressional wave velocity (VP) was estimated using a first arrival time approach and inverted to construct acoustic tomograms. Acoustic tomograms indicate that crosshole ultrasonic testing is able to characterize the changes in acoustic properties that result from jet-grout curing, locate contrasts between weaker/stronger regions in the jet grout, and estimate geometry of the column.
Structural Health Monitoring (SHM) mittels geführter Ultraschallwellen ermöglicht eine kontinuierliche Überwachung komplexer Bauteile und liefert umfangreiche Informationen über deren strukturelle Integrität. Die aufgezeichneten Signale sind jedoch komplex und werden daher zunehmend mittels KI verarbeitet, um Anomalien in der Systemintegrität automatisch zu erkennen. Eine Herausforderung dabei ist jedoch das Trainieren solcher KI-Modelle, da dafür große Mengen an Trainingsdaten inklusive diverser Schadensfälle benötigt werden, um eine hohe Genauigkeit und Zuverlässigkeit zu gewährleisten. Experimentelle Generierung dieser Daten ist wegen des enormen Zeit- und Kostenaufwands nicht möglich.
Eine Alternative hierfür bieten die numerischen Simulationen, da dadurch Trainingsdaten für beliebige Anzahl an Schadenskonfigurationen erzeugt werden können. Das Hauptproblem dabei ist jedoch die Abweichung zwischen den experimentellen und simulierten Daten (durch z.B. Abweichungen bei der Geometrie, Randbedingungen oder Materialparameter). Um diese Abweichungen zu reduzieren bzw. zu eliminieren, wird ein KI-Modell mit einer Autoencoder-Decoder Architektur vorgestellt, die mittels eines Experiments kalibriert werden kann und anschließend in der Lage ist, die Genauigkeit der Simulationsergebnisse nachträglich zu erhöhen.