Mechanical signals influence the morphology, function, differentiation, proliferation, and growth of cells. Due to the small size of cells, it is essential to analyze their mechanobiological responses with an in vitro mechanical loading device. Cells are cultured on an elastic silicone membrane substrate, and mechanical signals are transmitted to the cells by the substrate applying mechanical loads. However, large areas of non-uniform strain fields are generated on the elastic membrane, affecting the experiment\'s accuracy. In the study, finite-element analysis served as the basis of optimization, with uniform strain as the objective. The thickness of the basement membrane and loading constraints were parametrically adjusted. Through finite-element cycle iteration, the \"M\" profile basement membrane structure of the culture chamber was obtained to enhance the uniform strain field of the membrane. The optimized strain field of culture chamber was confirmed by three-dimensional digital image correlation (3D-DIC) technology. The results showed that the optimized chamber improved the strain uniformity factor. The uniform strain area proportion of the new chamber reached 90%, compared to approximately 70% of the current chambers. The new chamber further improved the uniformity and accuracy of the strain, demonstrating promising application prospects.

Rock is the main construction material of rock engineering, such as the engineering of mines and tunnels; in addition, its mechanical properties and failure laws are of great significance to the stability evaluation of rock engineering, especially under the conditions of coupled static-static stresses. In this study, granite specimens were manufactured with artificial flaws. Coupled static and dynamic loads tests were carried out with a modified split Hopkinson pressure bar (SHPB) apparatus; and six typical levels of axial pre-stresses and three crack inclination angles were designed. Three-dimensional digital image correlation (3D-DIC) was also applied to record and analyze the fracturing process and damage evolution of the specimens. The test results show that there was no compaction stage in the stress-strain curve under combined dynamic and static loading. The dynamic strength of the specimens increased first and then decreased with the increase in the static pressure; moreover, the specimens reached the maximum dynamic strength when the static pressure was 10% UCS. The dynamic strength decreased first and then increased with the increase in the crack inclination angle; and the lowest strength appeared when the inclination angle was 45°. The change in axial compression had a significant influence on the failure mode, and the failure mode gradually transformed from shear-tensile failure to shear failure with the increase in the pre-stress. The tensile strain was usually generated at the end of the fractures or near the rock bridge. When the axial pressure was small, the tensile strain zone parallel to the loading direction was easily generated; and when the axial pressure was large, a shear strain zone developed, extending along the diagonal direction. The research results can provide a theoretical reference for the correct understanding of the failure mechanisms of granite and its engineering stability under actual conditions.

Creep-associated changes in disc bulging and axial strains are essential for the research and development of mechano-bionic biomaterials and have been assessed in various ways in ex vivo creep studies. Nonetheless, the reported methods for measurement were limited by location inaccuracy, a lack of synchronousness, and destructiveness. To this end, this study focuses on the accurate, synchronous, and noninvasive assessment of bugling and strains using the 3D digital image correlation (3D-DIC) system and the impact of creep on them. After a preload of 30 min, the porcine cervical discs were loaded with different loads for 4 h of creep. Axial strains and lateral bulging of three locations on the discs were synchronously measured. The three-parameter solid model and the newly proposed horizontal asymptote model were used to fit the acquired data. The results showed that the load application reduced disc strains by 6.39% under 300 N, 11.28% under 400 N, and 12.59% under 500 N. Meanwhile, the largest protrusion occurred in the middle of discs with a bugling of 1.50 mm, 1.67 mm, and 1.87 mm. Comparison of the peer results showed that the 3D-DIC system could be used in ex vivo biomechanical studies with reliability and had potential in the assessment of the mechanical behavior of novel biomaterials. The phenomenon of the largest middle protrusion enlightened further the strength of spinal implants in this area. The mathematical characterizations of bulging and strains under different loads yielded various model parameters, which are prerequisites for developing implanted biomaterials.

This paper follows up on a reference paper that inspired MDPI\'s Topic \"Stochastic Geomechanics: From Experimentation to Forward Modeling\", where global and local deformation effects on sand specimens are fully described from high resolution boundary displacement fields, and supported by its experimental database, which is open to the scientific community for further study. This paper introduces the use of spatio-temporal statistics from a subset of such an experimental database to characterize the specimens\' spatio-temporal displacement fields, populated by repeating a set of triaxial compression tests on drained, dry, vacuum-consolidated sand specimens, tested under similar experimentally controlled conditions. A three-dimensional digital image correlation (3D-DIC) technique was used to measure the specimens\' boundary displacement fields throughout the course of shearing under axial compression. Spatio-temporal first- and second-order statistics were computed for different data dimensionality conditions (0D, 0D-T, 1D-T, 3D-T) to identify and characterize the dominant failure mechanisms across different testing specimens. This allowed us to quantify localization phenomena\'s spatio-temporal uncertainty. Results show that the uncertainty captured along the deformation process across different dimensionality conditions can be directly associated with different failure mechanisms, including localization patterns, such as the onset and evolution of shear, compression, and expansion bands. These spatio-temporal observations show the dependencies between locally distinctive displacement regions over a specimen\'s surface, and across different times during a specimen\'s shearing process. Results of this work provide boundary spatio-temporal statistics of experimental evidence in sands, which sets the basis for the development of research on the numerical simulation of sand\'s constitutive behavior. Moreover, it allows to add a new understanding on the effect of uncertainty on the mechanistic interpretation of sands\' kinematic phenomena.

A comprehensive experimental database containing results of a series of dry vacuum-consolidated triaxial compression tests was populated. The tests were performed on sand specimens and conducted under similar experimental conditions, in which specimens\' boundary deformation was captured using a three-dimensional digital image correlation analysis (3D-DIC). The use of a standard triaxial device along with the 3D-DIC technology allowed the specimens\' global and local boundary displacement fields to be computed from start to end of the compression phase. By repeating each test under the same experimental conditions and building the specimens using the same type of sand, the boundary deformation patterns could be identified, and the statistics associated with both global and local displacement fields could be assessed. Making this experimental database available to others should serve to calibrate as well as develop new forward models to account for effects associated with the specimens\' local displacements and material heterogeneity and include statistics to represent a specimen\'s random response. Moreover, this work will serve as a basis for the statistical characterization of spatio-temporal boundary localization effects used to develop stochastic models and machine-learning models, and simulate virtual triaxial tests.