Balaji, Nidish NarayanaaBrake, Mathew R.W.2019-08-122019-08-122019Balaji, Nidish Narayanaa and Brake, Mathew R.W.. "The surrogate system hypothesis for joint mechanics." <i>Mechanical Systems and Signal Processing,</i> 126, (2019) Elsevier: 42-64. https://doi.org/10.1016/j.ymssp.2019.02.013.https://hdl.handle.net/1911/106209The main challenges in the design and analysis of jointed structures deal with the prediction of dissipation across bolted interfaces. Since friction is thought to be one of the main mechanisms for this, the current study investigates the utility of frictional parameter identification applied across different structures. Based on recent discoveries, a Surrogate System Hypothesis has been formulated to systematize this: the hypothesis states in brief, that the physical properties of a joint are independent of its structural context. The current work seeks to obtain a better understanding of the underlying systems by evaluating a confidence metric for the hypothesis for a relatively simple set of systems—physically perturbed configurations of the Brake-Reuß Beam. Interfacial friction is modeled using whole jointed patches with distributed hysteretic (Iwan) elements and simulations are conducted using the Quasi-Static Modal Analysis (QSMA) approach to estimate the modal characteristics of the system response (amplitude dependence of natural frequency and dissipation). Posing the estimation as a Multi-Objective Optimization Problem (MOOP) is shown to reveal important features of both the employed constitutive model as well as the structure that is modeled. Consequently, the approach is used to evaluate the epistemic uncertainty inherent in three different friction models. The studies reveal that a confidence metric for the hypothesis can be formulated in such a way that it is nearly independent of the friction constitutive model that is employed.engThis is an author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by Elsevier.Journal articleJoint mechanicsFriction modelingMulti-Objective Optimizationhttps://doi.org/10.1016/j.ymssp.2019.02.013