Using dual response surfaces to reduce variability in launch vehicle design: A case study

Space transportation system conceptual design is a multidisciplinary process containing considerable element of risk. Uncertainties from one engineering discipline may propagate to another through linking parameters and the final system output may have an accumulation of risk. This may lead to significant deviations from expected performance. An estimate of variability or design risk therefore becomes essential for a robust design. This study utilizes the dual response surface approach to quantify variability in critical performance characteristics during conceptual design phase of a launch vehicle. Using design of experiments methods and disciplinary design analysis codes, dual response surfaces are constructed for the mean and standard deviation to quantify variability in vehicle weight and sizing analysis. Next, an optimum solution is sought to minimize variability subject to a constraint on mean weight. In this application, the dual response surface approach lead to quantifying and minimizing variability without much increase in design effort.