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Measuring friction at an interface using ultrasonic response.

ABSTRACT: Friction between sliding surfaces is a fundamental phenomenon prevalent in many aspects of engineering. There are many sliding contact tribometers that measure friction force in a laboratory environment. However, the transfer of laboratory data to real machine elements is unreliable. Results depend on the specimen configuration, surface condition and environment. In this work, a method has been developed that uses the nonlinear response of a high-power ultrasonic wave to deduce friction coefficient in situ at an interface. When the high-power shear wave strikes a frictional interface, relative slip can occur. It imposes a nonlinear response and causes generation of higher-order odd frequency components in received ultrasonic signals. The amplitude of the harmonics depends on contact stress and local friction coefficient. This nonlinear ultrasonic response has been investigated both numerically and experimentally. A simple one-dimensional model has been used to predict nonlinearity generation. This model has been compared with experiments conducted on aluminium rough surfaces pressed together under increasing loads. Two strategies have been used to estimate the friction coefficient by correlating experimental and numerical third-order nonlinearity. It has proved possible to determine the friction coefficient in situ at the interface; values in the range of 0.22 to 0.61 were measured for different surface configurations.

SUBMITTER: Li X

PROVIDER: S-EPMC7544357 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Brain-computer interfaces (BCIs) are an emerging novel technology for stroke rehabilitation. Little is known about how dose-response relationships for BCI therapies affect brain and behavior changes. We report preliminary results on stroke patients (n = 16, 11 M) with persistent upper extremity motor impairment who received therapy using a BCI system with functional electrical stimulation of the hand and tongue stimulation. We collected MRI scans and behavioral data using the Action Research Arm Test (ARAT), 9-Hole Peg Test (9-HPT), and Stroke Impact Scale (SIS) before, during, and after the therapy period. Using anatomical and functional MRI, we computed Laterality Index (LI) for brain activity in the motor network during impaired hand finger tapping. Changes from baseline LI and behavioral scores were assessed for relationships with dose, intensity, and frequency of BCI therapy. We found that gains in SIS Strength were directly responsive to BCI therapy: therapy dose and intensity correlated positively with increased SIS Strength (p ? 0.05), although no direct relationships were identified with ARAT or 9-HPT scores. We found behavioral measures that were not directly sensitive to differences in BCI therapy administration but were associated with concurrent brain changes correlated with BCI therapy administration parameters: therapy dose and intensity showed significant (p ? 0.05) or trending (0.05 < p < 0.1) negative correlations with LI changes, while therapy frequency did not affect LI. Reductions in LI were then correlated (p ? 0.05) with increased SIS Activities of Daily Living scores and improved 9-HPT performance. Therefore, some behavioral changes may be reflected by brain changes sensitive to differences in BCI therapy administration, while others such as SIS Strength may be directly responsive to BCI therapy administration. Data preliminarily suggest that when using BCI in stroke rehabilitation, therapy frequency may be less important than dose and intensity.

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Measuring friction at an interface using ultrasonic response.

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