Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Charles M. Denegri"'
Publikováno v:
Journal of Aircraft. 58:236-243
Earlier work did not find any static stiffness nonlinearities in the F-16 wing structure, but suggested that dynamic nonlinearities may be present. Computational studies have demonstrated that smal...
Publikováno v:
AIAA Scitech 2019 Forum.
Publikováno v:
AIAA Scitech 2019 Forum.
Publikováno v:
Journal of Aircraft. 53:243-250
A well-known F-16 external store configuration was studied using a time-domain computational aeroelasticity code. The code used a medium-fidelity Euler flow solver coupled with a linear modal representation of the structure. A key feature of the code
Publikováno v:
Journal of Aircraft. 50:1637-1645
F-16 testing revealed differences in limit-cycle oscillation response characteristics associated with subtle aerodynamic variations of the underwing missiles. Physical length differences between long and short missiles led to the accidental discovery
Publikováno v:
Journal of Aircraft. 51:693-695
Publikováno v:
Journal of Aircraft. 46:1667-1672
A computational investigation of the flutter onset and limit cycle oscillation behavior of various F-16 fighter weapons and stores configurations is presented. A nonlinear harmonic balance compressible Reynolds-averaged Navier–Stokescomputational f
Publikováno v:
Journal of Aircraft. 42:500-508
Oscillatory wing response data were measured on an F-16C aircraft during limit-cycle-oscillation (LCO) testing of an external store configuration. The configuration tested exhibited typical LCO response in the transonic flight regime. Deformation cha
Autor:
Michael R. Johnson, Charles M. Denegri
Publikováno v:
Journal of Aircraft. 40:194-203
A dynamic artificial neural network in the form of a multilayer perceptron with a delayed recurrent feedback connection is investigated to determine its ability to predict linear and nonlinear flutter response characteristics. Flight-test results sho
Autor:
Michael R. Johnson, Charles M. Denegri
Publikováno v:
Journal of Guidance, Control, and Dynamics. 24:887-895
A static arti cial neural network in the form of a multilayer perceptron is investigated to determine its ability to predict linear and nonlinear utter response characteristics. The network is developed and trained using linear utter analysis