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Particle scattering simulations are an useful tool to plan experiments, design detectors, estimate doses in irradiated materials and medical treatment planning.
Geant4 is a Monte-Carlo toolkit for the simulation of of particles scattering in matter. Photons, electrons, ions etc can be simulated with energies in the eV to GeV range. Their interactions with matter in arbitrary scattering geometries be studied. Scattering models, cross sections and material parameters can be set to cover interactions in gas, liquid and solid state. The import of geometries from computer aided design files or the protein data base is possible.
It is currently being applied in high energy and nuclear physics, accelerator and detector design, space application, dosimetry and medical sciences.
In this first part of the talk a brief overview over the structure, functionality and possible applications of Geant4 will be given. In the second part an example application will be presented: The determination of the microscopic dose-damage relations in aqueous environment for electron irradiated plasmid DNA will be explained. Therefore, we combine electron scattering simulations in water with calculations concerning the movement of biomolecules to obtain the energy deposit in the biologically relevant nanoscopic volume. We present, how to combine these simulational results and experimental data via a generalized damage model to determine the microscopic dose-damage relation at a molecular level.
Determination of Distribution Function used in MCS on Safety Analysis of Hydrogen Pressure Vessel
(2019)
The test data of static burst strength and load cycle strength of composite pressure vessels are often described by GAUSSian normal or WEIBULL distribution function to perform safety analyses. The goodness of assumed distribution function plays a significant role in the inferential statistics to predict the population properties by using limited test data. Often, GAUSSian and WEIBULL probability nets are empirical methods used to validate the distribution function; Anderson-Darling and KolmogorovSmirnov tests are the mostly favorable approaches for Goodness of Fit. However, the different approaches used to determine the parameters of distribution function lead mostly to different conclusions for safety assessments. In this study, six different methods are investigated to show the variations on the rates for accepting the composite pressure vessels according to GTR No. 13 life test procedure. The six methods are: a) NormLog based method, b) Least squares regression, c) Weighted least squares regression, d) A linear approach based on good linear unbiased estimators, e) Maximum likelihood estimation and f) The method of moments estimation. In addition, various approaches of ranking function are considered. In the study, Monte Carlo simulations are conducted to generate basic populations based on the distribution functions which are determined using different methods. Then the samples are extracted randomly from a population and evaluated to obtain acceptance rate. Here, the “populations” and “samples” are corresponding to the burst strength or load cycle strength of the pressure vessels made from composite material and a plastic liner (type 4) for the storage of hydrogen. To the end, the results are discussed, and the best reliable methods are proposed.
Composite pressure vessels (CPVs) are becoming the state of the art for storage for compressed hydrogen (CH2) in automotive applications. There is a strong interest of car manufacturers to use lightweight and less-costly gas storage units. In order to reduce the necessary amount of expensive carbon fibre, the nominal safety margins are becoming gradually smaller, pushing the limits of the regulations for type approval. At the same time, the total volume of these vessels increases to extend the range of the vehicles, increasing the consequences for worst-case scenarios like the rupture of the CPVs in service.
This presentation presents insights gained in the project “TAnk HYdrogen Automotive” (TAHYA). Its aim is to improve the safety of current regulations for type approval of pressure vessels for the use in hydrogen fueled vehicles, namely GTR No. 13 and ECE R 134.
For the assessment of safety, the probabilistic approach developed by division 3.5 of BAM is used. Monte-Carlo-Simulations were conducted leading to the identification of several weak spots, mainly found in the burst test and the batch test.
By changing the requirements for burst tests and the approach for batch tests, the identified weak spots can be strongly reduced.