Data-driven nonlinear model reduction to spectral submanifolds in mechanical systems.

While data-driven model reduction techniques are well-established for linearizable mechanical systems, general approaches to reducing nonlinearizable systems with multiple coexisting steady states have been unavailable. In this paper, we review such a data-driven nonlinear model reduction methodology based on spectral submanifolds. As input, this approach takes observations of unforced nonlinear oscillations to construct normal forms of the dynamics reduced to very low-dimensional invariant manifolds. These normal forms capture amplitude-dependent properties and are accurate enough to provide predictions for nonlinearizable system response under the additions of external forcing. We illustrate these results on examples from structural vibrations, featuring both synthetic and experimental data. This article is part of the theme issue 'Data-driven prediction in dynamical systems'.

Brain-mimicking phantom for biomechanical validation of motion sensitive MR imaging techniques.

Motion sensitive MR imaging techniques allow for the non-invasive evaluation of biological tissues by using different excitation schemes, including physiological/intrinsic motions caused by cardiac pulsation or respiration, and vibrations caused by an external actuator. The mechanical biomarkers extracted through these imaging techniques have been shown to hold diagnostic value for various neurological disorders and conditions. Amplified MRI (aMRI), a cardiac gated imaging technique, can help track and quantify low frequency intrinsic motion of the brain. As for high frequency actuation, the mechanical response of brain tissue can be measured by applying external high frequency actuation in combination with a motion sensitive MR imaging sequence called Magnetic Resonance Elastography (MRE). Due to the frequency-dependent behavior of brain mechanics, there is a need to develop brain phantom models that can mimic the broadband mechanical response of the brain in order to validate motion-sensitive MR imaging techniques. Here, we have designed a novel phantom test setup that enables both the low and high frequency responses of a brain-mimicking phantom to be captured, allowing for both aMRI and MRE imaging techniques to be applied on the same phantom model. This setup combines two different vibration sources: a pneumatic actuator, for low frequency/intrinsic motion (1 Hz) for use in aMRI, and a piezoelectric actuator for high frequency actuation (30-60 Hz) for use in MRE. Our results show that in MRE experiments performed from 30 Hz through 60 Hz, propagating shear waves attenuate faster at higher driving frequencies, consistent with results in the literature. Furthermore, actuator coupling has a substantial effect on wave amplitude, with weaker coupling causing lower amplitude wave field images, specifically shown in the top-surface shear loading configuration. For intrinsic actuation, our results indicate that aMRI linearly amplifies motion up to at least an amplification factor of 9 for instances of both visible and sub-voxel motion, validated by varying power levels of pneumatic actuation (40%-80% power) under MR, and through video analysis outside the MRI scanner room. While this investigation used a homogeneous brain-mimicking phantom, our setup can be used to study the mechanics of non-homogeneous phantom configurations with bio-interfaces in the future.

Relaxation capacity of cartilage is a critical factor in rate- and integrity-dependent fracture.

Articular cartilage heals poorly but experiences mechanically induced damage across a broad range of loading rates and matrix integrity. Because loading rates and matrix integrity affect cartilage mechanical responses due to poroviscoelastic relaxation mechanisms, their effects on cartilage failure are important for assessing and preventing failure. This paper investigated rate- and integrity-dependent crack nucleation in cartilage from pre- to post-relaxation timescales. Rate-dependent crack nucleation and relaxation responses were obtained as a function of matrix integrity through microindentation. Total work for crack nucleation increased with decreased matrix integrity, and with decreased loading rates. Critical energy release rate of intact cartilage was estimated as 2.39 ± 1.39 to 2.48 ± 1.26 kJ m-2 in a pre-relaxation timescale. These findings showed that crack nucleation is delayed when cartilage can accommodate localized loading through poroviscoelastic relaxation mechanisms before fracture at a given loading rate and integrity state.