Aerodynamics of thrust vectoring by Navier-Stokes solutions

Induced aerodynamics from thrust vectoring are investigated by a computational fluid dynamic method. A thin-layer Reynolds-averaged Navier-Stokes code with multiblock capability is used. Jet properties are specified on the nozzle exit plane to simulate the jet momentum. Results for a rectangular jet in a cross flow are compared with data to verify the code. Further verification of the calculation is made by comparing the numerical results with transonic data for a wing-body combination. Additional calculations were performed to elucidate the following thrust vectoring effects: the thrust vectoring effect on shock and expansion waves, induced effects on nearby surfaces, and the thrust vectoring effect on the leading edge vortex

Magnetic groundstate and Fermi surface of bcc Eu

Using spin-spiral technique within the full potential linearized augmented-plane-waves (LAPW) electronic structure method we investigate the magnon spectrum and N\'eel temperature of bcc Eu. Ground state corresponding to an incommensurate spin-spiral is obtained in agreement with experiment and previous calculations. We demonstrate that the magnetic coupling is primarily through the intra-atomic $f-s$ and $f-d$ exchange and Ruderman-Kittel-Kasuya-Yosida mechanism. We show that the existence of this spin-spiral is closely connected to a nesting feature of the Fermi surface which was not noticed before.Comment: 6 pages 8 figure

Comparative model accuracy of a data-fitted generalized Aw-Rascle-Zhang model

The Aw-Rascle-Zhang (ARZ) model can be interpreted as a generalization of the Lighthill-Whitham-Richards (LWR) model, possessing a family of fundamental diagram curves, each of which represents a class of drivers with a different empty road velocity. A weakness of this approach is that different drivers possess vastly different densities at which traffic flow stagnates. This drawback can be overcome by modifying the pressure relation in the ARZ model, leading to the generalized Aw-Rascle-Zhang (GARZ) model. We present an approach to determine the parameter functions of the GARZ model from fundamental diagram measurement data. The predictive accuracy of the resulting data-fitted GARZ model is compared to other traffic models by means of a three-detector test setup, employing two types of data: vehicle trajectory data, and sensor data. This work also considers the extension of the ARZ and the GARZ models to models with a relaxation term, and conducts an investigation of the optimal relaxation time.Comment: 30 pages, 10 figures, 3 table