Strain Measurement Method Research Articles

Interpretation of intra-operative strain differences in ascending thoracic aortic repair patients

Local biaxial deformation plays a pivotal role in evaluating the tissue state of the ascending aorta and in driving intramural cell-mediated tissue remodeling. Unfortunately, the absence of anatomical markers on the ascending aorta presents challenges in capturing deformation. Utilizing our established intra-operative biaxial strain measurement method, we delineated local biaxial deformation characteristics in patients undergoing aortic valve replacement and coronary artery bypass graft surgery recipients (n = 20), and Aortic Repair surgery patients (n = 47). Expectedly, mean circumferential strains positively correlated with pulse pressure and negatively correlated with age and diameter. A new observation was that the mean axial strains exhibited the same trend as the mean circumferential strains when correlated with pulse pressure, age and diameter. Interestingly, on analyzing local biaxial strains, our findings revealed higher circumferential strains (by 1 %) proximal to the heart compared to distal regions across the cohorts and within each patient cohort. Furthermore, no discernible regional strain distinctions were noted between the medial and lateral sides of the ascending aorta for the entire patient population and individual cohorts. Patients undergoing Aortic Repair surgery indicated lower strains (ranging from 1 to 3 %) as compared to the other cohort. Our approach holds the potential to establish a foundational framework for the integrated examination of the mechanical and biological conditions and their role in ascending aortic aneurysm development.

Time-frequency reassignment of blade tip timing signal

The health condition of a rotor blade can be assessed by its dynamic frequency with respect the rotational speed, which can be derived from the time–frequency analysis of the blade vibration signal. Blade tip timing (BTT), as a non-contact measurement technique, provides an alternative to traditional contact strain measurement methods. However, the vibration signal measured by BTT is usually undersampled, which limits the application of conventional time–frequency analysis methods. BTT sparse time–frequency methods utilize the sparsity to reconstruct undersampled BTT signals. Nevertheless, BTT sparse time–frequency representation suffers from poor concentration and inaccurate estimation of the dynamic frequency, especially in the case of fast varying speed and limited BTT sensors. In this paper, a BTT time–frequency reassignment method is proposed to enhance the concentration of the BTT time–frequency spectrum and improve the accuracy of dynamic frequency estimation. Firstly, BTT time–frequency reassignment utilizes the blade natural frequency, obtained from the Campbell diagram, as prior information. The blade dynamic frequency with respect to the rotational speed is estimated by combining the prior frequency with the measured frequency in the Bayesian framework. Subsequently, weights are assigned to both the time–frequency coefficients and the posterior frequency. The time–frequency coefficients are relocated around the posterior frequency according to the weights. The advantages of BTT time–frequency reassignment are demonstrated through a simulation, a laboratory test and a full-scale aeroengine test. Both simulation and experimental results demonstrate that BTT time–frequency reassignment enhances the concentration of the BTT time–frequency spectrum and improves the accuracy of the estimated dynamic frequency when limited BTT sensors are available. The influence of the prior frequency is discussed to evaluate the robustness of BTT time–frequency reassignment. In the full-scale aeroengine test, the reliability of BTT time–frequency reassignment is verified under the fast varying speed.

A deep learning based method for left ventricular strain measurements: repeatability and accuracy compared to experienced echocardiographers

BackgroundSpeckle tracking echocardiography (STE) provides quantification of left ventricular (LV) deformation and is useful in the assessment of LV function. STE is increasingly being used clinically, and every effort to simplify and standardize STE is important. Manual outlining of regions of interest (ROIs) is labor intensive and may influence assessment of strain values.PurposeWe hypothesized that a deep learning (DL) model, trained on clinical echocardiographic exams, can be combined with a readily available echocardiographic analysis software, to automate strain calculation with comparable fidelity to trained cardiologists.MethodsData consisted of still frame echocardiographic images with cardiologist-defined ROIs from 672 clinical echocardiographic exams from a university hospital outpatient clinic. Exams included patients with ischemic heart disease, heart failure, valvular disease, and conduction abnormalities, and some healthy subjects. An EfficientNetB1-based architecture was employed, and different techniques and properties including data set size, data quality, augmentations, and transfer learning were evaluated. DL predicted ROIs were reintroduced into commercially available echocardiographic analysis software to automatically calculate strain values.ResultsDL-automated strain calculations had an average absolute difference of 0.75 (95% CI 0.58–0.92) for global longitudinal strain (GLS), and 1.16 (95% CI 1.03–1.29) for single-projection longitudinal strain (LS), compared to operators. A Bland–Altman plot revealed no obvious bias, though there were fewer outliers in the lower average LS ranges. Techniques and data properties yielded no significant increase/decrease in performance.ConclusionThe study demonstrates that DL-assisted, automated strain measurements are feasible, and provide results within interobserver variation. Employing DL in echocardiographic analyses could further facilitate adoption of STE parameters in clinical practice and research, and improve reproducibility.

Surface patterning for multi-scale strain analysis of in-situ SEM mechanical experiments

Scanning electron microscopy (SEM) enables microstructure characterization at multi-scale, having potential to quantify strain distribution across multiple fields of view (FOVs) and exploring coordinated relationships among the deformations of multi-scale microstructures. Optimizing distribution of multi-scale speckles is crucial for achieving high precision and efficiency in digital image correlation (DIC) computations. In this work, a multi-scale strain measurement method is proposed for in-situ SEM mechanical experiments, which relies on an uncomplicated multi-scale speckle preparation method. Multi-scale speckle preparation can be achieved by the combination of spin-coating and magnetron sputtering. By using micro- and macro-speckle, multi-scale strain calculations can be achieved during the in-situ SEM mechanical loading. The InSn macro-speckle is composed of controllable-sized InSn nanoscale speckles, ensuring that the accuracy of DIC measurements in the microscopic regions are not compromised by the coverage of macro-speckles in the testing region. In regions covered exclusively by SiO2 nano-speckles, in-situ SEM mechanical loading allows for the acquisition of high-resolution DIC (HR-DIC) and electron backscatter diffraction (EBSD) data from the same region and under the same deformation state. Experiments are conducted to illustrate the functionality and utility of the multi-scale speckles. Such experimental analyses offer an opportunity to further explore multi-scale strain heterogeneity in some advanced structural materials and provide reliable experimental verification for material mechanics simulations.

Surface Strain Measurement for Non-Intrusive Internal Pressure Evaluation of a Cannon

Abstract Recent cutting-edge designs for gun barrels, projectiles, and propellants require testing, such as measuring the internal pressure during firing. However, there are concerns with the current drilling method to mount pressure transducers near the breech and chamber of the gun barrel where pressure is highest. To address this challenge, the team hereby presents an alternative, nonintrusive strain measurement method. This method focuses on determining the feasibility and accuracy of relating tangential strain along the sidewall of a gun barrel to the drastic internal pressure rise created during combustion. A transient structural, numerical model of a 155 mm gun barrel was created using ansys. The pressure was derived using the outline in Interior Ballistics of High Velocity Guns, version 2, and the model was validated using published experimental tangential strain testing data from a gun of the same caliber. The model was then used to demonstrate the ideal location for strain measurement along the sidewall of the chamber. Furthermore, three different pressure ranges were simulated in the model. The behavior of the tangential strain in each case indicates a similar trend to the internal pressure rise and oscillation due to a dominant frequency of the barrel. A method to predict internal pressure from external tangential strain was developed. The internal pressure predicted is within 4% of the pressure applied in the model. In the sensitivity study, the thickness and elastic modulus of the gun barrel were found to be the primary factors affecting tangential strain. Overall, this work helps to understand tangential strain behavior on the sidewall of a large-caliber gun barrel and lays the ground for an accurate prediction of internal pressure from external tangential strain.

In-vivo left atrial surface motion and strain measurement using novel mesh regularized image block matching method with 4D-CTA

Atrial strain and motion play important roles in evaluation of stroke risks for patients with atrial fibrillation. While cardiac computed tomographic angiography (CTA) provides detailed left atrial morphology with unparallel image resolution, finding a suitable strain measurement method for CTA remains a considerable challenge. In this paper, for the first time, we introduced a mesh regularized image block matching method to estimate 3D left atrial (LA) surface strain with 4D CTA. A series of performance tests with ex-vivo phantom and in-vivo 4D-CTA data were deployed. In conclusion, our proposed method could provide reliable LA motion and strain data within limited time.

Multi-Directional Strain Measurement in Fiber-Reinforced Plastic Based on Birefringence of Embedded Fiber Bragg Grating.

Embedded fiber Bragg gratings are increasingly applied for in-situ strain measurement in fiber-reinforced plastics, integral to high-end aerospace equipment. Existing research primarily focuses on in-plane strain measurement, limited by the fact that fiber Bragg gratings are mainly sensitive to axial strain. However, out-of-plane strain measurement is equally important for comprehending structural deformation. The birefringence of fiber Bragg gratings shows promise for addressing this problem; yet, the strain transfer relationship between composites and optical fibers, along with the decoupling method for multi-directional strains, remains inadequately explored. This study introduces an innovative method for multi-directional strain measurement in fiber-reinforced plastics using the birefringence of a single-fiber Bragg grating. The strain transfer relationship between composites and embedded optical fibers was derived based on Kollar's analytical model, leading to the development of a multi-directional strain decoupling methodology. This method was experimentally validated on carbon fiber/polyetherimide laminates under thermo-mechanical loading. Its reliability was confirmed by comparing experimental results and finite element simulations. These findings significantly broaden the application scenarios of fiber Bragg gratings, advancing the in-situ measurement technology crucial for the next generation of high-end aerospace equipment.

Unraveling the Intrinsic Thermal Behavior of Freestanding Ionomer Films Depending on Thickness from Commercial Membrane to Nanofilm.

Proton exchange membrane fuel cells (PEMFCs) for automotive applications are required to achieve mechanical reliability at various temperatures ranging from subfreezing to 80 °C. The thermal behavior of the electrode should be considered at the initial design stage to design a robust automotive fuel cell electrode. Recently, a behavior different from that of the bulk state has been reported for ionomers with a few nanometers of thickness. Therefore, the intrinsic thermal behavior of ionomer films with thicknesses from micrometers to nanometers is quantitatively investigated in this study. By introducing the fabrication of a pseudo-freestanding Nafion thin film and in-plane thermal strain measurement method on the water surface, the thermal expansion of the freestanding Nafion thin film was successfully measured with minimizing substrate constraints. Thermal strain measurement and X-ray scattering studies revealed that the weakening of intermolecular interaction within the hydrophobic and hydrophilic domains in the Nafion thin film caused thermal expansion, and well-structured hydrophobic domains could suppress thermal expansion. The thermal expansion behavior with different heat treatments provides evidence of the thin-film-to-bulk transition of the fully hydrated Nafion film. Intrinsic thermal behavior without substrate interactions can facilitate an understanding of the thermal behavior of electrodes and provide insight into designing a robust PEMFC in temperature-varying environments.

A New Technology for Industrial Strain Mapping Using Single-Wall Carbon Nanotube Sensors

Measurements of mechanical strain are widely used in heavy industry to design and test new structures and to ensure the safety of installed infrastructure. However, the few practical methods for strain measurement all have serious limitations. To complement these methods, we have developed a new strain technology, called S4 for “strain-sensing smart skin,” which uses single-wall carbon nanotubes (SWCNTs) as microscopic sensors. Nanotubes dilutely embedded in a polymer are applied as a thin film to specimen surfaces of interest. Subsequent strains in the specimen are transmitted by load transfer through the film to the nanotubes, inducing axial compression or extension. Those small structural deformations of the SWCNTs alter the semiconducting band gaps in predictable ways, causing proportional shifts in the peak wavelengths of their near-infrared fluorescence emission. Shifts are quantified by optically exciting the specimen surface and spectrally analyzing the resulting fluorescence to deduce strain values at the probed locations. The S4 method has recently been implemented using hyperspectral imaging. We demonstrate measurements in less than one minute of strain maps containing hundreds of thousands of pixels with 50 microstrain noise levels and 0.2 mm spatial resolution. This technology has promising potential to become a large-scale commercialized application of carbon nanotechnology.

Influence of pipe rocking on the effectiveness of the load transfer along the drillstring during slide drilling: A comprehensive experimental study

The application of surface rocking-pipe-assisted drilling (SRPAD) technology is largely dependent on the ability driller to transfer an appropriate amount of weight to the bit. However, the impact of surface torque oscillations on the longitudinal drag and frictional torque is not thoroughly understood. For this purpose, in this study, a novel experimental apparatus was developed to study the load transfer characteristics along a drillstring during SRPAD. In the experiment, the forces and torques at both ends of the simulated drillstring were recorded, and the mechanical responses at various positions on the drillstring are monitored using a strain-measuring method. The experimental results suggest that properly rocking the drillstring back and forth can help operators regain most of the friction-reducing performance of conventional rotating drillstrings. Furtherore, we found that, if the pipe-rocking parameters, including the rocking velocity, rocking angle, surface hookload, and holding time, are properly controlled, the load transfer efficiency can be effectively improved. In particular, the rocking angle and surface hookload should be increased to reduce the stick-slip effect and buckling distortion. The experimental results provide important guidance for improving the performance of SRPAD system, though the flowing of drilling fluid and the influence of bent-housing motors are not taken into consideration.

Research on the OFDR strain measurement method based on similarity features of dual-segment RSS.

Optical frequency domain reflectometry (OFDR) is a research hotspot in fiber optic sensing technology. This technology can be used for strain, vibration and temperature sensing and has great application prospects in fields such as deformation analysis of aerospace components and bridge monitoring. This article analyzes the reasons for strain demodulation errors under large strains. In response to the problem of reduced similarity between the reference state signal and the measured state signal, a strain measurement method based on the similarity feature of a double-segment Rayleigh scattering spectrum is proposed. Local segments at both ends of the reference state signal are used as new fingerprint spectra, and the offset of the measured state signal similarity spectrum is synchronously searched after extension. At the same time, by revealing the mechanism of strain edge demodulation errors, a strain edge optimization method based on automatic adjustment of the sliding window center position is proposed. A comparison experiment was conducted with traditional methods to verify the effectiveness of the above method. Finally, a sensing unit length of 32.6 mm was achieved with a frequency modulation bandwidth of 5 nm, and the measurement range was from ± 2000 µɛ to ± 2500 µɛ. The measurable spectral offset was increased from 48% to 60%, with a maximum standard deviation of 1.9 µɛ.

Elastic strain mapping of plastically deformed materials by TEM

A method for mapping elastic strains by TEM in plastically deformed materials is presented. A characteristic feature of plastically deformed materials, which cannot be handled by standard strain measurement method, is the presence of orientation gradients. To circumvent this issue, we couple orientation and strain maps obtained from scanning precession electron diffraction datasets. More specifically, orientation gradients are taken into account by 1) identifying the diffraction spot positions in a reference pattern, 2) measuring the disorientation between the diffraction patterns in the map and the reference pattern, 3) rotating the coordinate system following the measured disorientation at each position in the map, 4) calculating strains in the rotated coordinate system. At present, only azimuthal rotations of the crystal are handled. The method is illustrated on a Cr2AlC monocrystal micropilar deformed in near simple flexion during a nanomechanical test. After plastic deformation, the sample contains dislocations arranged in pile-ups and walls. The strain-field around each dislocation is consistent with theory, and a clear difference is observed between the strain fields around pile-ups and walls. It is further remarked that strain maps allow for the orientation of the Burgers vector to be identified. Since the loading undergone by the sample is known, this also allows for the position of the dislocation sources to be estimated. Perspectives for the study of deformed materials are finally discussed.

MV-SSRP: Machine Vision Approach for Stress–Strain Measurement in Rice Plants

Rice plants’ ability to develop lodging resistance is essential for their proper growth and development, and understanding the stress–strain relationship is crucial for a comprehensive analysis of this resilience. Nevertheless, significant data variability, inefficiency, and substantial observational inaccuracies hinder current measurement and analysis techniques. Therefore, this study proposes a machine vision-based stress–strain measurement method for rice plants to address these limitations. The technique primarily involves the implementation of the proposed MV-SSRP rotating target detection network, which enhances the model’s ability to predict the strain of rice stalks accurately when subjected to bending forces through the integration of the spatial channel reorganization convolution (ScConv) and Squeeze-and-Excitation (SE) attention mechanism. A stress–strain dynamic relationship model was also developed by incorporating real-time stress data obtained from a mechanical testing device. The experimental findings demonstrated that MV-SSRP attained precision, recall, and mean average precision (mAP) rates of 93.4%, 92.6%, and 97.6%, respectively, in the context of target detection. These metrics represented improvements of 4.8%, 3.8%, and 5.1%, respectively, over the performance of the YOLOv8sOBB model. This investigation contributes a theoretical framework and technical underpinning for examining rice lodging resistance.

Definition of the Change Regulations in the Porosity of Semi-permeable Membranes After the Separation of Dairy Raw Materials

Topicality. The article provides a methodology for calculating structural and physical characteristics of semi-permeable membranes after their use in the technological process. During the operation of the membranes, the permeability decreases due to the clogging of their pores with colloidal substances. As a result, it is necessary to obtain data on the distribution of pores on the surface of the investigated ultrafiltration membrane. The aim of the article is to determine the change regularities in the porosity of the semi-permeable membrane, which is used in the technological process of separating dairy raw materials. This will make it possible to predict hydrodynamic properties of the ultrafiltration membrane. Research methods. A strain-measuring (statistical) method is offered, as well as structural and physical characteristics of semi-permeable membranes are determined in the process of membrane filtration of skimmed dairy raw materials. The possibility of constructing mathematical dependencies and methods for determining physical properties and structural analysis of the semi-permeable membrane is highlighted. This technique makes it possible to define not only the surface of the semi-permeable membrane, but also the surface of the polarisation layer of high molecular weight substances. Results. Based on the research results, the dependences of physical properties and structural components of the semi-permeable membrane after the processing of dairy raw materials are constructed. The results of the conducted study show that after ultrafiltration of skimmed dairy raw materials, the pore sizes undergo significant changes. Conclusions and discussion. An increase in the number of pores with a diameter of less than 10 nm is established. The spectrum of the radii of microcapillaries shifts towards decreasing, which occurs as a result of the deposition of particles of the dispersed phase in the microcapillaries. The implementation of research results can take place in industrial conditions, in order to determine the structural and physical characteristics of different types of membranes during the concentration of liquids of different origins for the development of new modifications of filter elements. The conditions for the industrial use of the obtained results are the resolution of issues relating to the laboratory studies of structural and physical characteristics with production results.

The Effect of Stiffness on Friction, Surface Strain and Contact Area of a Sliding Finger Pad Simulant

This study investigates the frictional and surface strain behaviour of silicone hemispherical finger pad simulants with different stiffness during tribological interactions with a smooth glass plate. A novel contact area and strain measurement method employing a digital image correlation technique was employed to give new understanding of the pad behaviour during sliding. The frictional behaviour of the sliding finger pad simulant is dominated by the adhesion mechanism, with a small overall contribution from deformation, as suggested by the high principal strains at the edge of the contact area. The strain behaviour is also influenced by the magnitude of the normal force and the stiffness of the samples.

Grating (Moiré) Microinterferometric Displacement/Strain Sensor with Polarization Phase Shift.

Grating (moiré) interferometry is one of the well-known methods for full-field in-plane displacement and strain measurement. There are many design solutions for grating interferometers, including systems with a microinterferometric waveguide head. This article proposes a modification to the conventional waveguide interferometer head, enabling the implementation of a polarization fringe phase shift for automatic fringe pattern analysis. This article presents both the theoretical considerations associated with the proposed solution and its experimental verification, along with the concept of in-plane displacement/strain sensing using the described head.

Nonlinear optimization DIC method inspired by unsupervised learning for high order displacement measurement

Digital Image Correlation (DIC) is the most widely used non-contact full-field strain measurement method, but due to the influence of subset calculations in principle, measuring complex deformation with high strain gradients within the subset remains a challenge. DIC based on neural networks performs well in complex deformation measurement scenarios, but its measurement accuracy and generalization ability depend on extensive training sets. This paper proposes a nonlinear optimization DIC method inspired by unsupervised learning that requires only a single pair of images. Unlike traditional unsupervised algorithms of optical flow estimation or Particle Image Velocimetry (PIV), the shape function in traditional DIC is incorporated into the loss function. This allows the use of only the reference image and the deformed image as input dataset, and the correct displacement field can be output after parameter optimization through training. This method does not require additional training sets to measure high-order strain fields like traditional neural networks-based DIC. The proposed method has demonstrated promising results in simulation experiments for high-order strain measurement and does not require additional datasets of the same type. In the measurement of the star-shaped displacement fields, its accuracy is better than the traditional DIC based on the subset, and it maintains convergence even when the strain is large, a situation where traditional DIC fails to converge. In addition, compared with the network obtained by supervised training as a pre-trained model, the method proposed in this paper can achieve superior results. The methods of the article can theoretically be applied to the result optimization of other networks beyond those discussed in this paper.

Microcrack monitoring and fracture evolution of coal and rock using integrated acoustic emission and digital image correlation techniques.

The mechanical properties of a coal-rock body were examined through uniaxial compression tests, and the rupture process of the coal-rock body was monitored in real time using a combined acoustic emission (AE) monitoring system and a digital image correlation (DIC) full-field strain measurement system. From a comparison of the mechanical properties of coal and sandstone, clear differences are apparent regarding the uniaxial compressive strength, deformation characteristics, and damage mode; the brittle failure characteristics of the coal samples are also more evident. The change in AE energy reflects the accumulation and release of elastic energy during the rupture process, and the evolution of AE localization points under different stress levels can effectively reflect rupture propagation. Further, the DIC full-field strain measurement method can quantitatively monitor the evolution of the displacement and strain fields at the marking point and surface simultaneously, thereby overcoming the limitations of traditional empirical and qualitative rupture processes. During monitoring, the AE focuses on the internal rupture of the specimen and the DIC focuses on the surface deformation. These complement each other and reflect the rupture process more comprehensively.

Bending creep behaviour of various polymer films analysed by surface strain measurement.

Understanding the temporal bending deformation of polymer films is key to designing mechanically durable flexible electronic devices. However, such creep behaviour under persistent bending remains unclear due to a lack of precise and accurate bending strain analysis methods. Herein, we quantitatively analysed the bending creep behaviour of various polymeric films using our developed strain measurement method that can precisely measure surface strain from optical diffraction. The surface strain measurement reveals that bending creep deformation differs depending on the polymer structure. The four-element Burgers model was employed to model the temporal strain increase on the bending surface successfully. By fitting the four-element model to the time course of the measured surface strain, we found that each polymer film has a different threshold surface strain for the appearance of bending creep deformation. Such disparity in the bending creep behaviour can be explained by the difference in strain energy density between the polymer films and their elastic model; polymer films with a small strain energy density difference show small bending creep deformation. The results obtained in this study contribute to the elucidation of the bending creep behaviour of polymer films and the development of flexible electronic devices operated under persistent bending.

Textile-based strain sensors for fiber-reinforced composites under tension, compression and bending

Abstract This research addresses the challenging task of monitoring the structural integrity of fiber-reinforced composite (FRC) components under complex loading conditions. Ensuring the safety and functionality of these components is critical but economically challenging. Therefore, this study presents an innovative approach using textile-based strain sensors that are cost-effective and structurally compatible with carbon fiber-reinforced plastic (CFRP) components. The investigation includes the systematic electromechanical characterization and comparison of four different sensor materials at the yarn and composite scale in various test scenarios. Cyclic tensile, compression, and bending tests of CFRP specimens are performed and show good reproducibility of sensor signals within the elastic range, with significant agreement observed with applied strain measurement methods, particularly in tensile tests. Although there are minor deviations in compression and bending evaluations, the signals are still meaningful for in-situ detection of complex loading patterns, crack initiation, and structural failure. The study demonstrates that the integration of textile-based sensor yarns allows for continuous structural health monitoring (SHM) of CFRP components under various loading scenarios, including tensile, bending, and especially compressive loads.