Methodology for managing the effect of uncertainty in simulation-based design

Abstract

Simulation-based design has become an inherent part of multidisciplinary design as simulation tools provide designers with a exible and computationally ef cient means to explore the interrelationships among various dis-ciplines. Complicationsarise when the simulationprogramsmay havedeviationsassociated with inputparameters (external uncertainties), as well as internal uncertainties due to the inaccuracies of the simulation tools or system models. These uncertainties will have a great in uence on design negotiationsbetween variousdisciplines andmay force designers to make conservative decisions. An integrated methodology for propagating and mitigating the effect of uncertainties is proposed. Two approaches, namely, the extreme condition approach and the statistical approach, are developed to propagate the effect of uncertainties across a design system comprising interrelated subsystem analyses. Using the extreme condition approach, an interval of the output from a chain of simulations is obtained, whereas the statistical approach provides statistical estimates of the output. An uncertainty mitigation strategy based on the principles of robust design is proposed. The methodology is presented using an illustrative simulation chain and is veri ed using the case study of a six-link function-generator linkage design. Nomenclature a = vector of system objective F = vector of simulation function f = response surface model (function) g = vector of system constraint S = displacement of slider w = weighting factor x = vector of design variable x ̄ = vector of nominal value of x y = vector of linking variable z = vector of system output a = maximum pressure angle D x = vector of range of x " = vector of error model µ = vector of mean value = vector of standard deviation} = crank angle w = rocker angle I