ABSTRACT In this work, a review of the theoretical aspects and an assessment to validate a Computational Fluid Dynamics (CFD) open-source code for applications in aerospace problems are discussed. The code uses a finite volume method, with cell-centered implementation, and it is suitable for simulations of inviscid, laminar, and turbulent flows. The code considers two-dimensional cases with unstructured meshes and employs the turbulence model known as Spalart-Allmaras. The implementation is detailed presenting the spatial discretization, including the upwind scheme, the linear reconstruction algorithm, and the calculation applying the method of gradients. The temporal discretization considers the application of a multistage explicit algorithm using a 5 stages Runge-Kutta method. The validation was done considering three cases of study: the inviscid shock tube, the laminar flat plate, and the flow over a rocket fairing. These cases are simulated using the software developed and the results are compared with analytical and experimental results. The rocket fairing case is related to the analysis of the Brazilian VLS launch during its transonic flight and it exemplifies the effect of the shock wave/boundary-layer interaction in its pressure distribution. The simulation results present a good agreement with the experimental results.

ABSTRACT In a beyond visual range (BVR) air combat, one of the challenges is identifying the best time to launch a missile, which is a decision that must be made quickly. The decision involves combining knowledge about altitude, speed, distance, onboard sensor systems information, aircraft type, and type of missile on the aircraft, as well as intelligence on the opponent’s behavior. This paper discusses an approach to evaluate the probability of shoot-down of an unmanned combat air vehicle (UCAV) in a BVR air combat, based on a decision support system model that makes use of parameters available from the onboard sensors of the shooter UCAV. The strategic options development and analysis (SODA) method is applied to select the main features available in the on-board sensor systems of the shooter aircraft required to launch a missile successfully. Such features help us to develop an artificial neural network (ANN) for shoot-down prediction. The ANN was trained with a data set with 1093 registered shoots in military exercises, and it shows 78.0% accuracy with the cross-validation procedure.

Abstract: The C2* radical is used as a system probe tool to the reactive flow diagnostic, and it was chosen due to its large occurrence in plasma and combustion in aeronautics and aerospace applications. The rotational temperatures of C2* species were determined by the comparison between experimental and theoretical data. The simulation code was developed by the authors, using C++ language and the object oriented paradigm, and it includes a set of new tools that increase the efficacy of the C2* probe to determine the rotational temperature of the system. A brute force approach for the determination of spectral parameters was adopted in this version of the computer code. The statistical parameter c2 was used as an objective criterion to determine the better match of experimental and synthesized spectra. The results showed that the program works even with low-quality experimental data, typically collected from in situ airborne compact apparatus. The technique was applied to flames of a Bunsen burner, and the rotational temperature of ca. 2100 K was calculated.