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A Polynomial Chaos-Based Kalman Filter Approach for Parameter Estimation of Mechanical Systems
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Mechanical systems operate under parametric and external excitation uncertainties. The polynomial chaos approach has been shown to be more efficient than Monte Carlo for quantifying the effects ...
Comparison of Linear, Nonlinear, Hysteretic, and Probabilistic Models for Magnetorheological Fluid Dampers
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Magnetorheological (MR) fluid dampers have a semicontrollable damping force output that is dependent on the current input to the damper, as well as the relative velocity. The mechanical construction, ...
Stochastic Analysis of the Wheel-Rail Contact Friction Using the Polynomial Chaos Theory
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: The coefficient of friction (CoF) is a very important factor for designing, operating, and maintaining the wheel-rail system. In the real world, accurate estimation of the CoF at the wheel-rail ...
Parametric Design Optimization of Uncertain Ordinary Differential Equation Systems
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: This work presents a novel optimal design framework that treats uncertain dynamical systems described by ordinary differential equations. Uncertainty in multibody dynamical systems comes from various ...