High-fidelity analysis is engaged in earnest when a request is made from the Damage Assessment Team, which operates primarily at the Mission Control Center at Johnson Space Center in Houston, TX. A geometric description is provided to the analysis team that can be discretized into a computational grid. The analysis team has developed a number of rapid-turnaround, grid generation schemes based on both algebraic and partial-differential-equation techniques. In particular, Gridgen scripts have been created to model common types of damage scenarios (such as a cavity formed by debris impact or protruding gap filler). These technologies allow for high-quality, block-structured grids to be generated automatically in less than an hour.
The primary goal of these simulations is to determine the aerothermal environment induced by a given damage in relation to a reference, undamaged state. Accordingly, a number of simulations of the entire Orbiter have been pre-computed at relevant reentry conditions 7 8. These results are archived on a 7TB disk array at NAS and are mirrored across the agency for redundancy. These global solutions provide both a reference for undamaged configuration and a convenient starting point for local analysis. Due to the predominantly hyperbolic nature of the governing equations, many areas on the vehicle are amenable to a local analysis approach, which considers only the damage site in isolation with upstream boundary conditions imposed using solutions from the reference dataset. Consequently, the resulting grid (hence the computing time) is significantly smaller than a global simulation of the entire vehicle with the damage site. This approach has proved invaluable in reducing the turnaround time of obtaining high fidelity CFD solutions (see reference 2 for more details). These improvements have enabled the mission support teams to either compute more cases or use less computing resources.
In recent Shuttle missions, ground-based arc-jet experiments have been performed, for evaluating material performance. However, any ground test can at best approximate the real aerothermal environment because no facility can duplicate the extreme flight conditions during reentry. Increasingly, this high-fidelity analysis capability has been used to help characterize ground-based testing and provides an invaluable tool for comparing and contrasting the test and flight environments.
Finally, rigorous quality control procedures have been implemented that fit into the aggressive timeline. This is a critical component of any computational simulation that is used in engineering design, but its importance is elevated for situations that are critical for risk analysis. Specifically, in this context an erroneous solution can be worse than just a waste of resources – it can actually be dangerous because simulation data are often used to judge the relative risk of two scenarios. Erroneous data could possibly lead decision-makers to actually choose the riskier of the two options. For the case of aerothermal analysis, a number of quantitative quality-control steps have been instituted to avoid this scenario. For example, simulations performed at the same conditions using both LAURA and DPLR are used as a quality control check. Additionally, metrics for quantifying the iterative solver for grid convergence are computed as part of the solution process. Finally, a team member who was not involved in producing the result subjects each simulation to a predefined quality control process.