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Cells within connective tissues routinely experience a wide range of non-uniform mechanical loads that regulate many cell behaviors. In this study, we developed an experimental system to produce complex strain patterns for the study of strain magnitude, anisotropy, and gradient effects on cells in culture. A standard equibiaxial cell stretching system was modified by affixing glass coverslips (5, 10, or 15 mm diameter) to the center of 35 mm diameter flexible-bottomed culture wells. Ring inserts were utilized to limit applied strain to different levels in each individual well at a given vacuum pressure thus enabling parallel experiments at different strain levels. Deformation fields were measured using high-density mapping for up to 6% applied strain. The addition of the rigid inclusion creates strong circumferential and radial strain gradients, with a continuous range of stretch anisotropy ranging from strip biaxial to equibiaxial strain and radial strains up to 24% near the inclusion. Dermal fibroblasts seeded within our 2D system (5 mm inclusions; 2% applied strain for 2 days at 0.2 Hz) demonstrated the characteristic orientation perpendicular to the direction of principal strain. Dermal fibroblasts seeded within fibrin gels (5 mm inclusions; 6% applied strain for 8 days at 0.2 Hz) oriented themselves similarly and compacted their surrounding matrix to an increasing extent with local strain magnitude. This study verifies how inhomogeneous strain fields can be produced in a tunable and simply constructed system and demonstrates the potential utility for studying gradients with a continuous spectrum of strain magnitudes and anisotropies.

The article presents a wavelet-based structural health monitoring technique for structures subjected to an earthquake excitation utilizing the instantaneous modal information. The instantaneous mode shape information is first extracted from the vibration response data collected during an earthquake event by using a wavelet packet sifting process. A confidence index (CI) is proposed to validate the results obtained. The identified normalized instantaneous mode shapes in conjunction with the corresponding CIs can be effectively used to monitor damage development in the structure. The effectiveness of the proposed approach is illustrated for two damage scenarios, sudden stiffness loss and progressive stiffness degradation, and different base excitations including three real earthquake signals and a random signal. Consistently good results were obtained in all cases. Issues related to robustness of the method in the presence of a measurement noise and sensitivity to damage severity are discussed.

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Sensitivity of regular wavelets to singularity has been used to detect a suddenly occurred structural damage and estimate its location in a large-scale structure. The usage of the approach is sometimes limited by a demand to the signal that the measurement data need to include the time period when the damage occurred. In this paper a concept of pseudo-wavelet is proposed based on shifting and scaling of conventional wavelets and a related pseudo-wavelet transform (PWT) is defined. A class of pseudo-wavelets is defined based on the frequency response function of the single degree of freedom mass-spring-dashpot system. A PWT-based system identification technique is developed to estimate the system parameters, mainly the natural frequencies and the damping ratios of the structure using vibration data. The approach can be applied for structural health monitoring. Change in system parameters using any two segments of response data may suggest occurrence of structural damages. The proposed approach is illustrated for single- and multiple-degree-of-freedom mass-spring-dashpot systems using simulated vibration response data. In all the case studies, the structural parameters are successfully estimated.

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The paper presents a comparative study of the effectiveness of three novel damage detection techniques namely Continuous Wavelet Transform (CWT), Empirical Mode Decomposition (EMD) and Wavelet Packet Sifting (WPS). The health condition of a mechanical or civil engineering structure can be assessed by monitoring a change in natural frequencies and mode shapes. CWT method can be used to identify the instantaneous values of these modal parameters by the wavelet ridges. Using the EMD method, intrinsic mode functions (IMF) can be sifted from a vibration signal, whereas a newly-developed WPS technique can decompose a signal into its dominant mono-frequency components. Instantaneous modal information can be extracted by incorporating the EMD and WPS with the Hilbert Transform. These techniques are illustrated for simulated vibration data from a three-degree-of-freedom system subjected to (i) sudden damage and (ii) progressive damage. The aspects related to the implementation algorithms, sensitivity to damage type and the robustness issues in case of noisy data are discussed. In case of progressive damage, all methods performed well. WPS technique performed better in case of sudden damage whereas CWT demonstrated robustness in case of noisy data.