ABSTRACT
In this study, a Computational Fluid Dynamics (CFD) model was developed to predict all relevant phenomena occurring during a moist heat sterilization process at a high level of temporal and spatial resolution. The developed CFD model was used to simulate the distribution of, e.g., pressure, temperature and residual air within a large-scale industrial steam autoclave (multiphase flow models) which was not published until now. Moreover, the thermodynamic behavior and distribution of fluids and temperatures inside the sterilization load was simulated which were verified with measurements. Based on the obtained sterilization temperature profiles in connection with the sterilization environment (e.g., NCGs, natural convection), the bacterial inactivation could be simulated. A complete moist heat sterilization process was simulated, including all relevant phenomena inside an autoclave chamber and a Peritoneal Dialysis Bag System (PDBS), which represents a complex sterilization item. To verify the simulation results, simulated pressures and temperatures were compared with measurement data for both the autoclave chamber and the PDBS. The results show that the simulated and measured values were in excellent accordance. By using the novel CFD model, the distribution of steam and residual air inside the autoclave chamber, as well as the natural convection inside the sterilization load, could be precisely predicted. To predict the inactivation of Geobacillus stearothermophilus inside different moist heat environments, the CFD model was extended with bacterial inactivation kinetics based on measurement data. The simulation results clearly indicate that our developed CFD model can be used to predict the inactivation kinetics of bacteria, depending on the sterilization temperature profile of the sterilization process as well as the moist heat sterilization environment, and to resolve the kinetics in time and space. Therefore, the developed CFD model represents a powerful tool that might be used in the future to predict, e.g., â³worst caseâ³ locations for any given autoclave and sterilization load or any other relevant process parameter, enabling the operator to develop an effective sterilization process.
ABSTRACT
In recent years, thermoplastic composites have found their place in large business sectors and are in direct rivalry to thermoset matrix composites. In order to ensure efficient and lean processes, process modeling gains ever-growing attention. This work shows the computational fluid dynamics (CFD)-modeling of a typical heating step in a thermoforming process of a thermoplastic composite sheet. When heating thermoplastic composites, the heat conduction proceeds anisotropic, and the sheets are subject to thermal deconsolidation when heated above the melting temperature of the polymer matrix adding to the anisotropic effect. These effects are neglected in known process models and this study shows the first successful attempt at introducing them into CFD-modeling of the heating of thermoplastic composite sheets. Thus, the simulation requires temperature dependent values for the anisotropic thermal conductivity and the coefficient of linear thermal expansion, which are calculated with novel physical models which were developed solely for this cause. This alters the behavior of an isotropic CFD-model and allows the successful validation via laboratory experiments using glass fiber reinforced polypropylene (PP/GF) sheets with embedded thermocouples to check the internal temperature distribution when the sheet is heated to the designated forming temperature in a composite thermoforming press. The incorporation of this newly developed process model reduces the error in the core temperature prediction from close to 70 °C to 3 °C at the forming temperature.
