[go: up one dir, main page]

Millman et al., 2006 - Google Patents

Uncertainty quantification with a B-spline stochastic projection

Millman et al., 2006

Document ID
11211490755346036772
Author
Millman D
King P
Maple R
Beran P
Chilton L
Publication year
Publication venue
AIAA journal

External Links

Snippet

FLUID-STRUCTURE interaction can result in the loss of dynamic stability to a time periodic instability that grows unbounded [1]. When nonlinear aerodynamics (eg, transient shocks or boundary layer separation) or nonlinear structural responses are present to counter the …
Continue reading at arc.aiaa.org (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50—Computer-aided design
    • G06F17/5009—Computer-aided design using simulation
    • G06F17/5018—Computer-aided design using simulation using finite difference methods or finite element methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50—Computer-aided design
    • G06F17/5009—Computer-aided design using simulation
    • G06F17/504—Formal methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/11—Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F2217/00—Indexing scheme relating to computer aided design [CAD]
    • G06F2217/16—Numerical modeling
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F2217/00—Indexing scheme relating to computer aided design [CAD]
    • G06F2217/46—Fuselage

Similar Documents

Publication Publication Date Title
Jameson et al. Continuous adjoint method for unstructured grids
Dwivedi et al. Input-output analysis of shock boundary layer interaction
Mateescu et al. A biased flux method for solving the Euler equations in subsonic, transonic and supersonic flows
Ren et al. Design sensitivity analysis with polynomial chaos for robust optimization
Millman et al. Uncertainty quantification with a B-spline stochastic projection
Demiroglu et al. Multi-fidelity sonic boom minimization of a supersonic aircraft by parametric wing shape design
Rule et al. Design of an aeroelastic delta wing model for active flutter control
Lee et al. Multipoint nose shape optimization of space launcher using response surface method
Munteanu et al. Reduced-order-model approach for aeroelastic analysis involving aerodynamic and structural nonlinearities
Pan et al. Wing flutter prediction by a small-disturbance euler method on body-fitted curvilinear grids
Millman et al. Predicting uncertainty propagation in a highly nonlinear system with a stochastic projection method
Millman et al. A Stochastic Approach for Predicting Bifurcation of a Pitch-Plunge Airfoil
Jalali Khouzani et al. Airfoil inverse design based on laminar compressible adjoint lattice B oltzmann method
Winter et al. Nonlinear reduced-order modeling of unsteady aerodynamic loads based on dynamic local linear neuro-fuzzy models
Poirion On some stochastic methods applied to aeroservoelasticity
Florea et al. Eigenmode analysis of unsteady flows about airfoils
Williams et al. Reduced order modelling of aircraft gust response for use in early design stages
Won et al. Non-linear impulse methods for aeroelastic simulations
Hong et al. Simulations of a twin-engine transport flutter model in the transonic dynamics tunnel
Vuruskan et al. Impact of turbulence models and objective function on three-dimensional robust aerodynamic optimization
Vuruskan et al. Investigation of the impact of turbulence models on robust aerodynamic shape optimization
Millman et al. Estimating the probability of failure of a nonlinear aeroelastic system
Brüderlin et al. Reduced-order model for robust aeroelastic control
Dias et al. A high-order parallel Newton-Krylov flow solver for the Euler equations
Munteanu et al. An Efficient Approach for Solving Nonlinear Aeroelastic Phenomenona Using Reduced-Order Modeling