Experimental Mechanics最新文献

Background

3D Stereo Digital Image Correlation (stereo-DIC) is a powerful experimental tool for measuring full-field, three-dimensional surface deformations, especially for non-planar surfaces and out-of-plane displacements. By capturing and comparing digital images of speckle-patterned samples before and after deformation, stereo-DIC can resolve full-field displacement and strain fields.

Objective

However, current post-processing methods in stereo-DIC are less robust compared to 2D-DIC, particularly when dealing with heterogeneous deformation fields in complex geometries or with discontinuities. To address these challenges, we recently developed a novel hybrid local subset and global-DIC post-processing algorithm, called the Augmented Lagrangian Digital Image Correlation (ALDIC) method, which ensures global kinematic compatibility while maintaining computational efficiency and applicability to adaptive meshes.

Methods

ALDIC has already demonstrated strong robustness and precision in 2D applications. Building on this progress, here we extend this framework to 3D, presenting the 3D Stereo Augmented Lagrangian Digital Image Correlation (stereo-ALDIC). To further enhance performance, we implemented cumulative and incremental tracking modes to resolve both small and large deformations. Additionally, the integration of an adaptive quadtree mesh allows the method to handle complex geometries with ease.

Results

Through various case studies, we demonstrate that stereo-ALDIC outperforms conventional local subset-based stereo-DIC methods in both accuracy and robustness, offering significant advancements for 3D measurement. An open-source MATLAB implementation for stereo-ALDIC is freely available.

Background

The ability to predict structural failures in civil engineering remains limited, particularly in assessing imminent failure conditions through real-time monitoring. This study addresses significant gaps in the identification of failure precursors in prestressed concrete structures.

Objective

The primary objective of this research is to enhance the prediction of impending failures in bridge girders through advanced analysis of Acoustic Emission (AE) signals.

Methods

Two innovative approaches are employed: Natural Time (NT) analysis and the Method of Critical Fluctuations-Based (MCF-B) approach. These methodologies are applied to AE data collected from girders subjected to three- and four-point bending tests, specifically those from a decommissioned 50-year-old prestressed concrete bridge in Turin, Italy.

Results

The analysis reveals that critical regions identified through the convergence of Natural Time (NT) parameters correlate significantly with spikes in acoustic emission activity, indicating impending structural failure. The Method of Critical Fluctuations-Based (MCF-B) approach successfully identifies critical states, yielding consistent results across varying threshold levels, which reinforces its reliability.

Conclusions

The findings underscore the effectiveness of both Natural Time (NT) and the Method of Critical Fluctuations-Based (MCF-B) approaches in predicting imminent structural failures, providing valuable insights for future structural health monitoring practices and enhancing the safety of aging infrastructure.

Background

Measuring the mode-I toughness of two-dimensional (2D) lattice materials and other thin-sheet materials poses a significant challenge with existing testing techniques. For example, material compression ahead of the crack or unstable crack growth frequently arise during testing of these materials and can complicate toughness measurements.

Objective

This study investigates a new experimental method, the hinged rigid beam (HRB), to evaluate the mode-I toughness of elastic-brittle 2D lattice and thin-sheet materials.

Methods

The HRB uses stiff beams and a hinged boundary to create a monotonically decreasing tensile stress along the length of the test material in the direction of the crack path. An analytical model, corrected using finite element studies, allows the critical strain energy release rate to be extracted from experimental data collected in HRB testing. Tests on homogeneous poly(methyl methacrylate) (PMMA) are performed to validate the technique and model. Then, 2D triangular and hexagonal lattices with varying relative densities are characterized using the HRB.

Results

Compliance measurements from experiments on homogeneous PMMA closely match the corrected model, and toughness measurements are consistent with previously reported values. Stable crack growth was observed in the tested lattice specimens, and toughness values were readily calculated. Toughnesses are compared to models for lattice fracture that use simple scaling laws. Good agreement is observed between experiments and model, especially at lower relative densities. As the relative density of the triangular lattices increased, the failure mode transitioned from strut-based to node-based, and the measured toughness values diverge from the models.

Conclusions

The HRB method allows for stable crack growth and prevents alternative modes of failure, like buckling, in thin-sheet materials and 2D lattices. This new experimental approach can be used for the fracture testing of a wide range of thin or highly compliant materials.

Background

Shape memory alloys (SMAs) have revolutionized structural retrofitting by leveraging their intrinsic shape memory effect (SME) to generate pre-stress through non-destructive thermal activation. While offering superior advantages over passive repair methods, the long-term effectiveness of SMA-based retrofitting critically hinges on the retention of recovery stress under cyclic fatigue loading. However, the degradation mechanisms governing recovery stress under combined phase transformation and fatigue remain poorly quantified, impeding the optimization of SMA applications in engineering practice.

Objective

This study systematically investigates the fatigue-induced degradation of recovery stress in Nickel-Titanium (NiTi) SMAs under high-stress cyclic loading, aiming to unravel the interplay between macroscopic mechanical behavior and microstructural evolution.

Method

A multi-scale experimental framework integrates macroscopic mechanical testing (high-stress cyclic loading at five stress levels) with microscopic fracture analysis (scanning electron microscopy). Empirical relationships between stress amplitude and fatigue life (N_i) / recovery stress loss rate (RSLR) are established, while crack propagation modes are quantitatively correlated to stress amplitudes.

Results

Fatigue life and deformation increments exhibit inverse proportionality to applied stress amplitude. Concurrently, experimental findings identify a critical yield stress threshold (385 MPa) that governs recovery stress degradation. Below this threshold, RSLR remains negligible (2.13 × 10^–5 MPa/cycle), preserving > 96% of initial recovery stress after 742,229 cycles. Above this threshold, transverse crack propagation leads to an accelerated degradation of the recovery stress.

Conclusion

The identified yield stress threshold and empirical models provide a mechanistic foundation for designing fatigue resistant SMA retrofitting systems. By linking macro-mechanical degradation to microstructural crack evolution, this work advances the predictive capability for recovery stress retention, enabling optimized SMA deployment in critical infrastructure under high-stress service conditions.

Background

Understanding the stochastic nature of elastic constants is crucial for the probabilistic analysis of structural response. Although significant progress has been made in experimentally characterizing deformation fields, few studies have addressed the spatial variability of material properties.

Objective

This study aims to develop a robust numerical-experimental method for characterizing the statistics of the elastic constants of heterogeneous materials.

Methods

The proposed method integrates digital image correlation (DIC) with finite element (FE) analysis. Through an iterative matching process between DIC-measured strain fields and FE simulations, the random spatial distributions of elastic constants are identified. This information is then used to determine the probability distributions, spatial autocorrelation functions, and cross-correlation functions of the elastic constants.

Results

The method is applied to microcrystalline cellulose tablets subjected to diametral compression. The experimental results highlight the influence of compaction pressure on the statistical characteristics of the elastic constants. The analysis also uncovers key methodological considerations, including the DIC measurement noise, applied load level, matching region selection, and DIC resolution.

Conclusions

The study demonstrates that the spatial distribution of elastic constants of heterogenous materials can be determined by optimal fitting of DIC-measured strain fields with those from elastic FE analysis. The resulting probability distribution and spatial correlation can be directly employed to generate the random fields of elastic properties for stochastic FE simulations.

Background

XPHD (ex-Poro Hydrodynamic) lubrication has emerged as an innovative and eco-friendly solution to current lubricating systems. It uses a high porosity and highly compressible material impregnated with fluid to enhance the pressure generation mechanism of hydrodynamic bearings.

Objective

The objective of our work is to study the mechanical behavior of water-imbibed polymeric foams which can replace oil in hydrodynamic bearings. The behavior depends on the interactions happening between the fluid flow and the solid phase as the latter undergoes important compressive and shear loads.

Methods

In this study, a dedicated testing device was developed to reproduce loading conditions like in hydrodynamic bearings and Digital Image Correlation has been adapted to measure local strains at the scale of cells and observe the deformation mechanisms.

Results

As a first candidate, open-cell polyurethane foams imbibed with water were selected and tested in a range of compression ratios, speeds and geometries of the loading element.

Conclusions

The evolution of strain fields under these loading scenarios and the contribution of the pore pressure in the local deformations of cells and pores are discussed and highlighted to provide a better understanding of the coupled phenomena.

Background

Deviatoric stress, as a pivotal factor influencing both the mechanical properties and durability of propellant, stands as a critical metric for assessing the quality of produced solid rocket motors (SRMs) and evaluating the processing parameters. The inherent characteristics of SRMs significantly restrict the application of existing methods in cure-induced stress measurements, thereby hindering the calibration of finite element models and optimization of the manufacturing processes.

Objective

This study is to develop a method for in-situ monitoring of cure-induced deviatoric stress.

Methods

Prefabricated structures with strain sensors are embedded for monitoring cure-induced deviatoric stress, and full-scale experiments were conducted to compare the influence of different cure technologies. Coupled thermo-chemo-mechanical simulations are performed to verify the feasibility of the proposed method.

Results

The Pearson correlation coefficient of the strain in the prefabricated structure and the cure-induced deviatoric stress is up to -1.000, which proves the feasibility of the proposed method. A 55.87% reduction in signal with pressure cure technology could be observed, which may help to prove the mitigation of pressure cure technology in cure-induced deviatoric stress.

Conclusion

The proposed method is capable of in-situ monitoring of cure-induced deviatoric stress in propellant charges during the curing and cooling phases. Pressure cure technology can help to lower the residual deviatoric stress during the curing phases, while during the cooling and pressure-releasing process, the rate of variation in deviatoric stress is more prominent.

Background

Stereo-digital image correlation (DIC) has found widespread application in experimental mechanics due to its full-field, non-contact deformation measurement capabilities. However, in liquid nitrogen environments, challenges arise from the difficulties associated with observation under cryogenic and within liquid media, as well as the resulting calibration issues. As a result, existing methods have yet to be effectively applied in such conditions.

Objective

To enable in-situ stereo-DIC in liquid nitrogen environments, and to address the challenges of visualization and calibration in extreme conditions.

Methods

A specially designed bi-prism was developed to solve the challenges posed by boiling bubbles, window frosting, and spatial constraints in liquid nitrogen immersion. To address the calibration issues in stereo-DIC systems in cryogenic, an accurate theoretical model based on a bi-prism-based pseudo-stereo refraction optical path was developed, and a two-step calibration method based on the epipolar constraint was established. In this method, the bi-prism does not need to be precisely positioned. Instead, by pre-calibrating the internal parameters of a single camera, the spatial position parameters of the bi-prism can be determined through the speckle features and the epipolar geometric relationship, fully determining the optical system.

Results

At room temperature, the diameter measurement error of the ping-pong ball was 0.57%, and the displacement error was less than 0.03 mm. In liquid nitrogen immersion, displacement detection of an aluminum alloy sample and accurate measurement of the bending deformation of a polycarbonate rod were successfully performed.

Conclusions

This study presents a novel bi-prism-based single-camera stereo-DIC method, achieving in-situ measurements in a liquid nitrogen environment. The reliability and practicality of the proposed method were validated under various experimental conditions, demonstrating its significant potential in extreme environments.