The prediction of supersonic wave drag is a crucial aspect of the design and optimization of aerodynamic bodies, particularly in high-speed flight applications such as supersonic aircraft and spacecraft. Accurate wave drag prediction is essential for assessing the performance, fuel efficiency, and overall aerodynamic characteristics of vehicles that travel at speeds greater than the speed of sound. Among various approaches used to predict wave drag, multifidelity methods have emerged as an effective way to balance accuracy with computational efficiency. These methods combine models of varying fidelity to provide a more comprehensive and reliable assessment of wave drag, while minimizing computational cost. The application of multifidelity methods to the prediction of supersonic wave drag for axisymmetric bodies provides an interesting case study in balancing the trade-offs between model accuracy and computational resources. Supersonic wave drag, also known as shock drag, arises due to the formation of shock waves around an object moving through a compressible fluid, such as air at supersonic speeds. As a supersonic body moves through the air, it generates shock waves that cause a discontinuous change in pressure, temperature, and velocity.
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