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Modeling dry friction is a challenging task. Accurate models must incorporate hysteretic rise of force across displacement and non-linearity from the Stribeck effect. Though sufficiently accurate models have been proposed for simple friction systems where these two effects dominate, certain rotational friction systems introduce self-energizing and accompanying backlash effects. These systems are termed self-energizing systems. In these systems, the friction force is amplified by a mechanical advantage which is charged through motion and released during reversing the direction of travel. This produces energized and backlash regimes within which the friction device follows different dynamic behaviors. This paper examines self-energizing rotational friction, and proposes a combined physics and machine learning approach to produce a unified model for energized and backlash regimes. In this multi-process information fusion methodology, a classical LuGre friction model is augmented to allow state-dependent parameterization provided by a machine learning model. The method for training the model from experimental data is given, and demonstrated with a 20 kN banded rotary friction device used for structural control. Source code replicating the methodology is provided. Results demonstrate that the combined model is capable of reproducing the backlash effect and reduces error compared to the standard LuGre model by a cumulative 32.8%; in terms modeling the tested banded rotary friction device. In these experimental tests, realistic pre-defined displacements inputs are used to validate the damper. The output of the machine learning model is analyzed and found to align with the physical understanding of the banded rotary friction device. 

The central difference is a popular algorithm used to integrate the equations of motion, yet suffers from two drawbacks: (1) it is only conditionally stable and requires a small-time step to maintain numerical stability; (2) it is nondissipative, and high-frequency spurious oscillations may appear and compromise the accuracy of the solution. These drawbacks are detrimental to applying the algorithm to the real-time hybrid simulation of large, complex nonlinear structural systems. In this paper, the conventional central difference algorithm is modified to overcome these drawbacks, and the modified algorithm is applied to the real-time hybrid simulation of complex structural systems. 

Abstract Near‐fault pulse‐type ground motions have characteristics that are substantially different from ordinary far‐field ground motions. It is essential to understand the unique effects of pulse‐type ground motions on structures and include the effects in seismic design. This paper investigates the effects of near‐fault pulse‐type ground motions on the structural response of a 3‐story steel structure with nonlinear viscous dampers using the real‐time hybrid simulation (RTHS) testing method. The structure is designed for 75% of the code‐specified design base shear strength. In the RTHS, the loop of action and reaction between the experimental and numerical partitions are executed in real time, accurately capturing the velocity pulse effects of pulse‐type ground motions. A set of 10 unscaled pulse‐type ground motions at the design basis earthquake (DBE) level is used for the RTHS. The test results validated that RTHS is a viable method for experimentally investigating the complicated structural behavior of structures with rate‐dependent damping devices, and showed that the dampers are essentially effective in earthquake hazard mitigation effects involving pulse‐type ground motions. The average peak story drift ratio under the set of pulse‐type ground motions is 1.08% radians with a COV value less than 0.3, which indicated that structural system would achieve the ASCE 7–10 seismic performance objective for Occupancy Category III structures under the DBE level pulse‐type ground motions. Additionally, a nonlinear Maxwell model for the nonlinear viscous dampers is validated for future structural reliability numerical studies involving pulse‐type ground motions. 

Abstract Damage caused by earthquakes to buildings and their contents (e.g., sensitive equipment) can impact life safety and disrupt business operations following an event. Floor isolation systems (FISs) are a promising retrofit strategy for protecting vital building contents. In this study, real‐time hybrid simulation (RTHS) is utilized to experimentally incorporate multi‐scale (building–FIS–equipment) interactions. For this, an experimental setup representing one bearing of a rolling pendulum (RP) based FIS is studied—first through characterization tests and then through RTHS. A series of tests was conducted at the Natural Hazards Engineering Research Infrastructure (NHERI) Experimental Facility at Lehigh University. Multiple excitations were used to study the experimental setup under uni‐axial loading. Details of the experimental testbed and test protocols for the characterization and RTHS tests are presented, along with results from these tests, which focused on the effect of different rolling surface treatments for supplemental damping, the FIS–equipment and building–FIS interactions, and rigorous evaluation of different RP isolation bearing designs through RTHS.