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Recent efforts to improve the statistical rigor of both developmental and operational testing include recommendations to consider second-order screening designs. In this paper, we provide a broad review of screening designs and second-order screening designs. We then consider a real-world wind tunnel experiment case study from the recent published literature and use subject matter expertise to consider the viability of second-order screening design, a recently developed design called the DSD+, to sufficiently screen important factors in complex, nonlinear systems of interest using just a single experimental design.

Two recent and powerful screening designs are compared. The comparisons focus on how robust each design is with respect to assumptions of model heredity and sparsity. Four truth models having varied aspects of heredity and sparsity are used; each examined at four levels of random noise. Each screening method is analyzed against the random data using the method's proposed analysis approach and compared in terms of correctly identified model components, incorrectly identified model components (type I error), and missed model components (type II error). Copyright © 2013 John Wiley & Sons, Ltd.

Recent military operations have showcased the abilities of unmanned aerial vehicles (UAVs), particularly in their ability to effectively perform those tasks too dangerous for manned aircraft. We examine non-autonomous operations of an UAV in those instances where the vehicle is used for laser target designation in support of precision guided munitions with non-line-of-sight command and control of the UAV. Non-line of sight UAV control requires a satellite communications link which involves a level of signal delay, or signal latency. This latency may impact the accuracy of the laser designation and thus the accuracy of the guided weapon. A simulation model is defined, built, and used to address the signal latency impacts of our defined UAV targeting scenario.

Run efficient second order designs suitable for both factor screening and the fitting of a second-order response model are of interest in complex system characterisation efforts particularly when those efforts encounter budgetary constraints limiting their test programme. Leading designs are the smaller sized definitive screening design and the larger sized design, fractional Box-Behken design. When specific domain knowledge of system factor interactions is available, either a priori or a posteriori , that domain knowledge can be exploited to generate the definitive screening design plus. This paper describes how to generate the single DSD+, how to augment a DSD to arrive at the DSD+ and compares the performance of the two designs under a variety of effect sparsity, effect heredity and model noise conditions. The DSD+, with its extra k – 1 runs for k factors is shown to greatly improve the screen and model fitting capabilities of the DSD.