Saili Simulator Launcher 35
A study of the use of an iterative forward and inverse modelling approach in a meteorological simulator was performed at a UK met office during 1992. The use of the Meteorolcogical Parameter Reprojection (MPHIP) system and the National Center for Environmental Prediction (NCEP) is investigated. For both the forward and the inverse models, fast data assimilation is used to provide an initial estimate for a specified time period. The approach is then iterated, using the inverse model in a forecasting mode, and allows time-variant estimates of various meteorological parameters. The method is found to be successful in predicting the evolution of the atmosphere, as well as the forecast error. It is an example of the rapid-response meteorological forecast system which has been demonstrated in the UK. The real-time capacity of the MPHIP system is evaluated. A programmatic evaluation of many of the modelling approaches used in the UK is required to assess the overall value and potential of systems like MPHIP.
In this paper, to the best of our knowledge, we have implemented the first simulator for the abdominal aortic aneurysm (AAA) repair. The architecture of the AAA simulator follows the SmartMESH architecture, which includes a multicellular unit, a task manager, and a mesh manager. We have also developed the key functions of the simulator, including the abdominal aorta geometry, tissue structure, tissue deformation, boundary condition, and an AAA task. The AAA task manager can perform AAA repair simulation using real patient CT images without modifying the CT image data. The AAA simulator is implemented in the Python programming language with a mesh-based approach. The AAA simulator is evaluated in the simulation of the case of the repair of a thoracic aortic aneurysm. The simulator can reproduce the AAA pathological cases in accordance with the described AAA repair process.