Ratcheting response of biological tissues over asymmetric loading cycles

The purpose of this study is to examine the ratcheting phenomenon in a variety of biological tissues including the trabecular bone, meniscus, articular cartilage and skin, and propose a parametric model to predict the ratcheting strain of these tissues. Furthermore, utilizing experimental data, and the influence of different mechanical and biological parameters on the ratcheting strain are discussed. The dependency of ratcheting on frequency, stress rate, stress variation, physiological environment, and tissue sites is demonstrated. Besides, stiffness of the toe and linear regions in each cycle, and the modulus of the failure region of the stress-strain curve are computed. The energy dissipation in different cycles at two frequencies of 1 Hz and 10 Hz is discussed. A parametric model was employed to predict ratcheting behavior of the said biological tissues. The model predictions of the strain accumulation in tissues are found in agreement with the experimental data.

Ratcheting response of biological tissues over asymmetric loading cycles

The purpose of this study is to examine the ratcheting phenomenon in a variety of biological tissues including the trabecular bone, meniscus, articular cartilage and skin, and propose a parametric model to predict the ratcheting strain of these tissues. Furthermore, utilizing experimental data, and the influence of different mechanical and biological parameters on the ratcheting strain are discussed. The dependency of ratcheting on frequency, stress rate, stress variation, physiological environment, and tissue sites is demonstrated. Besides, stiffness of the toe and linear regions in each cycle, and the modulus of the failure region of the stress-strain curve are computed. The energy dissipation in different cycles at two frequencies of 1 Hz and 10 Hz is discussed. A parametric model was employed to predict ratcheting behavior of the said biological tissues. The model predictions of the strain accumulation in tissues are found in agreement with the experimental data.

A Radial-Based Centralized Kriging Method for System Reliability Assessment

System reliability assessment is a challenging task when using computationally intensive models. In this work, a radial-based centralized Kriging method (RCKM) is proposed for achieving high efficiency and accuracy. The method contains two components: Kriging-based system most probable point (MPP) search and radial-based centralized sampling. The former searches for the system MPP by progressively updating Kriging models regardless of the nonlinearity of the performance functions. The latter refines the Kriging models with the training points (TPs) collected from pregenerated samples. It concentrates the sampling in the important high-probability density region. Both components utilize a composite criterion to identify the critical Kriging models for system failure. The final Kriging models are sufficiently accurate only at those sections of the limit states that bound the system failure region. Its efficiency and accuracy are demonstrated via application to three examples.