Digital Image Correlation Approach Research Articles

Diagnosis of Forme Fruste Keratoconus Using Corvis ST Sequences with Digital Image Correlation and Machine Learning.

This study aimed to employ the incremental digital image correlation (DIC) method to obtain displacement and strain field data of the cornea from Corvis ST (CVS) sequences and access the performance of embedding these biomechanical data with machine learning models to distinguish forme fruste keratoconus (FFKC) from normal corneas. 100 subjects were categorized into normal (N = 50) and FFKC (N = 50) groups. Image sequences depicting the horizontal cross-section of the human cornea under air puff were captured using the Corvis ST tonometer. The high-speed evolution of full-field corneal displacement, strain, velocity, and strain rate was reconstructed utilizing the incremental DIC approach. Maximum (max-) and average (ave-) values of full-field displacement V, shear strain γxy, velocity VR, and shear strain rate γxyR were determined over time, generating eight evolution curves denoting max-V, max-γxy, max-VR, max-γxyR, ave-V, ave-γxy, ave-VR, and ave-γxyR, respectively. These evolution data were inputted into two machine learning (ML) models, specifically Naïve Bayes (NB) and Random Forest (RF) models, which were subsequently employed to construct a voting classifier. The performance of the models in diagnosing FFKC from normal corneas was compared to existing CVS parameters. The Normal group and the FFKC group each included 50 eyes. The FFKC group did not differ from healthy controls for age (p = 0.26) and gender (p = 0.36) at baseline, but they had significantly lower bIOP (p < 0.001) and thinner central cornea thickness (CCT) (p < 0.001). The results demonstrated that the proposed voting ensemble model yielded the highest performance with an AUC of 1.00, followed by the RF model with an AUC of 0.99. Radius and A2 Time emerged as the best-performing CVS parameters with AUC values of 0.948 and 0.938, respectively. Nonetheless, no existing Corvis ST parameters outperformed the ML models. A progressive enhancement in performance of the ML models was observed with incremental time points during the corneal deformation. This study represents the first instance where displacement and strain data following incremental DIC analysis of Corvis ST images were integrated with machine learning models to effectively differentiate FFKC corneas from normal ones, achieving superior accuracy compared to existing CVS parameters. Considering biomechanical responses of the inner cornea and their temporal pattern changes may significantly improve the early detection of keratoconus.

Improving surface plasmon resonance sensors with speckle image processing

This paper investigates digital image correlation approaches for assessing speckle patterns produced by surface plasmon resonance (SPR) imaging. An SPR sensor based on the Kretschmann setup comprising a gold-coated prism in a fixed angular position performs refractive index assessments in ethanol solutions. Subsequently, the acquisition system collects the reflected light and processes the speckle field images to evaluate the sensor's sensitivity, noise, and limit of detection. Based on three repetitions under similar conditions, the maximum resolution for the average intensity, zero-mean normalized cross-correlation, and the relative sum of square differences metrics are 4.90×10−4, 2.31×10−5, and 7.45×10−6 RIU, respectively, leading to an improved limit of detection without modifying the optical setup.

Unsupervised CNN-based DIC method for 2D displacement measurement

Digital image correlation (DIC) is a widely used technique for non-contact measurement of deformation. However, traditional DIC methods face challenges in balancing calculation efficiency and the quantity of seed points. Deep learning approaches, particularly supervised learning methods, have shown promise in improving DIC efficiency. However, these methods require high-quality training data, which can be time-consuming to generate ground truth annotations. To address these challenges, we propose an unsupervised convolutional neural network (CNN) based DIC method for 2D displacement measurement. Our approach leverages an encoder-decoder architecture with multi-level feature extraction, a dual-path correlation block, and an attention block to extract informative features from speckle images with varying characteristics. We utilize a speckle image warp model to transform the deformed speckle image to the predicted reference speckle image based on the predicted 2D displacement map. The unsupervised training is achieved by comparing the predicted and original reference speckle images. To optimize the network's parameters, we employ a composite loss function that takes into account both the Mean Squared Error (MSE) and Pearson correlation coefficient. By using unsupervised convolutional neural network (CNN) based DIC method, we eliminate the need for extensive training data annotation, which is a time-consuming process in supervised learning DIC methods. We have conducted several experiments to demonstrate the validity and robustness of our proposed method. The results show a significant reduction in Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) compared to a method proposed by Zhao et al. This indicates that our unsupervised CNN-based DIC approach can achieve accuracy comparable to supervised CNN-based DIC methods. For implementation and evaluation, we provide PyTorch code and datasets, which will be released at the following URL :https://github.com/fead1/DICNet-corr-unsupervised-learning-.

Functionally graded IWP reinforced cementitious composites: Design, fabrication, and the enhanced ductility

The Schoen I-graph-wrapped package (IWP) structures have many promising applications for their high specific mechanical properties. In this work, functionally graded IWP (FG-IWP) architectures were developed and constructed to enhance the ductility of the produced cementitious composites. The FG-IWP architectures were designed using two grading strategies: relative-density-based and cell-size-based. The flexural test was used to investigate the mechanical behavior of the proposed composites, including flexural strength and deflections. The failure patterns and strain distributions of the specimens were measured using the Digital image correlation (DIC) approach. The results reveal that the designed IWP architectures noticeably improve the flexural strength and ductility of the composites. Comparing the FG-IWP to the uniformly configured IWP architectures, the grading strategies exhibit an increased ductility. Furthermore, the two grading strategies have different effects on ductility improvement. Cell size gradient strategy yields greater enhancement in flexural strength, whereas relative density strategy leads to better enhancement in ductility. The variations of cell size and relative density parameter ranges also result in distinct improvement on mechanical properties. Overall, the outcomes of this study present an FG-IWP-based novel approach for improving the ductility of cementitious materials.

Measuring J‐R curve under dynamic loading conditions using digital image correlation

AbstractThis article describes a convenient method to quantify the dynamic J‐R curve through digital image correlation (DIC). The DIC approach, verified through numerical and experimental results for single edge notched bend (SE(B)) specimens, quantifies the dynamic J‐R curve during the drop‐weight tearing test (DWTT). The proposed method enables consistent measurement of the J‐integral and the amount of crack extension solely from the DIC measured displacement on the specimen surface, which facilitates direct comparison of fracture toughness under different strain rates. The results demonstrate enhanced Mode‐I fracture resistance of metallic materials under increased strain rates.

Enhanced Flexural Performance of Diamond Latticed Triply Periodic Minimal Surface Sandwich Panels

The additively manufactured bio‐inspired lattice structures have various superior properties in comparison to their solid counterparts as they are lightweight and suitable for fabricating various parts in aerospace sectors. This study limits the investigation of triply periodic minimal surface (TPMS)‐based diamond sheet and solid cellular structures with varying densities (25%, 35%, 45%, and graded) under flexural loading conditions. The sandwich panel structures are made using acrylonitrile butadiene styrene material utilizing the fused filament fabrication (FFF) process. In‐plane flexural performances of the FFF fabricated bio‐inspired TPMS diamond sandwich panels are investigated for the first time. The panels are created to investigate how density and unit cell geometry affect stiffness, strength, and energy absorption. The digital image correlation approach is used to visualize the deflection of the panels subjected to three‐point bending. Also, a theoretical analysis is done to find out the deflection of the sandwich panel structures. An Ashby chart shows the comparison of the specific energy absorption of the TPMS diamond sandwich panels used in this study with several other cellular core sandwich panels available in the literature. This study provides a valuable contribution to the improved energy absorption performance of additively manufactured cellular materials.

Numerical investigation on circular and elliptical bulge tests for inverse soft tissue characterization.

The acquisition of insights concerning the mechanobiology of aneurysmatic aortic tissues is an important field of investigation. The complete characterization of aneurysm mechanical behaviour can be carried out by biaxial experimental tests on ex vivo specimens. In literature, several works proposed bulge inflation tests as a valid method to analyse aneurysmatic tissue. Bulge test data processing requires the adoption of digital image correlation and inverse analysis approaches to estimate strain and stress distributions, respectively. In this context, however, the accuracy of inverse analysis method has not been evaluated yet. This aspect appears particularly interesting given the anisotropic behaviour of the soft tissue and the possibility to adopt different die geometries. The goal of this study is to provide an accuracy characterization of the inverse analysis applied to the bulge test technique using a numerical approach. In particular, different cases of bulge inflation were simulated in a finite element environment as a reference. To investigate the effect of tissue anisotropic degree and bulge die geometries (circular and elliptical), different input parameters were considered to obtain multiple test cases. The specimen deformed shapes, resulting from the reference finite element simulations, were then analysed through an inverse analysis approach to produce an estimation of stress distributions. The estimated stresses were, at last, compared with the values from the reference finite element simulations. The results demonstrated that the circular die geometry produces a satisfactory estimation accuracy only under certain conditions of material quasi-isotropy. On the other hand, the choice of an elliptical bulge die was proven to be more suitable for the analysis of anisotropic tissues.

The Shear Capacity Estimation of Reinforced Concrete Short Beams with Steel Fiber by Digital Image Correlation Approach

This research aimed to estimate the shear capacity of reinforced concrete short beams with steel fiber (RSF short beams) using DIC (digital image correlation). Four-point bending tests of RSF short beams with shear span ratio (a/d) of 1.0, 1.5, and 2.0 were conducted. 0.5% or 1.0% volume fraction of steel fiber was used. The distribution of minimum principal strain (Ɛ2) was obtained from DIC then the width of compressive strut was evaluated. The effects of volume fraction of steel fiber and shear span ratio were investigated. Finally, the shear capacity of RSF short beams was estimated with the help of DIC.

Effect of nanoscale interface modification on residual stress evolution during composite processing

The interface characteristics of the matrix and fibers significantly influence the evolution of residual stress in composite materials. In this study, we provide a methodology for reducing the residual stress in laminated composites by modifying the thermomechanical properties at the fiber–matrix interface. A hydrothermal chemical growth method was used to grow Zinc Oxide nanowires on the carbon fibers. We then utilized a novel digital image correlation approach to evaluate strains and residual stresses, in situ, throughout the autoclave curing of composites. We find that interface modification results in the reduction of residual stress and an increase in laminate strength and stiffness. Upon growing ZnO NWs on the carbon fibers, the maximum in situ in-plane strain components were reduced by approximately 55% and 31%, respectively, while the corresponding maximum residual stresses were decreased by 50.8% and 49.33% for the cross-play laminate [0°/90°] layup in the x and y directions, respectively. For the [45°/-45°] angle ply layup in the x-direction, the strain was decreased by 27.3%, and the maximum residual stress was reduced by 41.5%, whereas in the y-direction, the strain was decreased by 166.3%, and the maximum residual stress was reduced by 17.8%. Furthermore, mechanical testing revealed that the tensile strength for the [45°/-45°] and [0°/90°] laminates increased by 130% and 20%, respectively, with the interface modification.

Monitoring structural scale composite specimens in a post‐buckling regime: The integrated finite element stereo digital image correlation approach with geometrically non‐linear regularization

AbstractEven though the simulations used to describe the failure of laminates are becoming more and more predictive, complex testing under multiaxial loadings is still required to validate the design of structural parts in a wide range of industrial domains. It is thus essential to assess the actual boundary conditions to allow for an objective comparison between testing and calculations, in particular since the structural tests are complex and often leads to buckling. Therefore, accurate estimation of force and moment fluxes applied to the specimen is critical. In this context, stereo digital image correlation (SDIC) has proven to be an important measurement tool and provides very well‐resolved surface displacement fields, but the exploitation of such measurements to calculate fluxes remains problematic when testing composites. The first objective of this study is both to reduce the uncertainty associated with fluxes determination on a complex test and to simplify the extraction process with respect to existing procedures. The second objective is to make this methodology robust to geometrically non‐linear deformations. In this paper, we propose a new methodology that extracts minimal boundary conditions in the form of 3D mechanically admissible displacements fields. The approach developed uses a finite element SDIC (FE‐SDIC) method regularized by means of mechanical behaviour admissibility equations. Results show that the new methodology outputs much more accurate fluxes than classical data generated from multiple differentiations of the displacement fields. Excellent noise robustness is obtained and quantified. Numerical predictions have been satisfactorily compared with experimental data from one structural‐scale composite specimen under complex testing.

High-resolution monitoring of landslides with UAS photogrammetry and digital image correlation

ABSTRACT Periodically monitoring landslides is a key factor for supporting the realisation of hazard warning systems and risk reduction in the corresponding neighbourhood areas. Although satellite remote sensing solutions can be considered for low spatial resolution monitoring, this approach is still inappropriate for high spatial resolution investigations. Ground-based Radar Interferometry is also a widely used technique that allows for working at a proper spatial resolution, but it can often be an overbudget solution for most applications. Instead, photogrammetric surveys based on Unmanned Aerial System (UAS) imagery appear as a very interesting approach in terms of both spatial resolution and flexibility in temporally repeating the survey. Motivated by this observation, this work investigates the use of multi-temporal UAS surveys for landslide monitoring. To be more precise, Digital Image Correlation (DIC) has been applied to orthomosaics generated from different UAS photogrammetry surveys to compute the area’s deformation map. Compared with a reference GNSS survey, the results obtained using NHAZCA IRIS software and an in-house DIC approach show a deformation estimation accuracy of approximately 0.1 m, a reasonable accuracy for landslides moving at moderate velocity.

In-situ imaging approach for investigating residual stress formation in rolling process

In-depth experimental observations of the evolution of residual stress in response to a physical field during the manufacturing process are few. Hence, an in-situ imaging setup is designed to record the workpiece material deformation history during a mechanically dominant rolling process. A novel mechanics-enriched digital image correlation approach that enables the reconstruction of mechanical fields during the rolling process is proposed herein. Accordingly, a correlation between the mechanical effect and resulting residual stress is formulated. The residual stress evolution can be reproduced via inclusion theory based on in-process mechanical messages. This process is categorised into three phases based on their governing effects, i.e. the build-up phase (induced by the squeezing effect of the roller), loading phase (due to contact), and recovery phase (after unloading), to facilitate understanding regarding the residual stress formation mechanism. The methodology used in this study is validated via artificial tests and comparisons between predicted and measured residual stresses after the rolling process.

Preparation and fracture behavior of annularly aligned steel fiber reinforced cementitious composite: Experiment and simulation

Annularly cement-based structures are widely used in the harsh environments, such as municipal drainage and subway tunnels. The cracks in the structures will provide the penetrate channel of aggressive media, which induces the further deterioration. To prevent cracking and improve durability, an external circular magnetic field is applied in this work to prepare the annularly aligned steel fiber reinforced cementitious composites (ASFRC). The fracture behavior of annularly ASFRC is investigated by three-point bending fracture test. Moreover, the fracture propagation progress is elucidated based on the digital image correlation (DIC) approach. The results reveal that the initial fracture toughness (Kini) and fracture energy (GF) of annularly ASFRC arch notched beams are improved by more than 35% and 100%, respectively, when compared to the steel fiber reinforced cementitious composite (SFRC) with randomly distributed fibers. The development of the strain field produced by the DIC method also demonstrates that aligning steel fibers improves the crack resistance of arch notched beams greatly. Moreover, the effects of steel fiber volume fraction and initial notch ratio on fracture behavior of arch notched beams are further verified and measured based on numerical simulation method. This study can provide guidance for the application and promotion of annularly ASFRC.

In-vivo high-speed biomechanical imaging of the cornea using Corvis ST and digital image correlation

In-vivo corneal biomechanical characterization has gained significant clinical relevance in ophthalmology, especially in the early diagnosis of eye disorders and diseases (e.g. keratoconus). In clinical medicine, the air-puff-based tonometers such as Ocular Response Analyzer (ORA) and Corvis ST have been used in the in-vivo biomechanical testing. In the test, the high-speed dynamic deformation of the cornea under air-puff excitation is analyzed to identify the abnormities in the morphological and biomechanical properties of the cornea. While most existing measurements reflect the overall corneal biomechanical properties, in-vivo high-speed strain and strain rate fields at the tissue level have not been assessed. In this study, 20 subjects were classified into two different groups: the normal (NORM, N = 10) group and the keratoconus (KC, N = 10) group. Image sequences of the horizontal cross-section of the human cornea under air puff were captured by the Corvis ST tonometer. The macroscale mechanical response of the cornea was determined through image analysis. The high-speed evolution of full-field corneal displacement, strain, velocity, and strain rate was reconstructed using the incremental digital image correlation (DIC) approach. Differences in the parameters between the NORM and KC groups were statistically analyzed and compared. Statistical results indicated that compared with the NORM group, the KC corneas absorbed more energy (KC: 8.98 ± 2.76 mN mm; NORM: 4.79 ± 0.62 mN mm; p-value <0.001) with smaller tangent stiffness (KC: 22.49 ± 2.62 mN/mm; NORM: 24.52 ± 3.20 mN/mm; p-value = 0.15) and larger maximum deflection (KC: 0.99 ± 0.07 mN/mm; NORM: 0.92 ± 0.06 mN/mm; p-value <0.05) on the macro scale. Further, we also observed that The maximum displacement (KC: 1.17 ± 0.06 mm; NORM: 1.06 ± 0.07 mm; p-value <0.005), velocity (KC: 236 ± 29 mm/s; NORM: 203 ± 17 mm/s; p-value <0.01), shear strain (KC: 24.43 ± 2.59%; NORM: 20.26 ± 1.54%; p-value <0.001), and shear strain rate (KC: 69.74 ± 11.99 s−1; NORM: 54.84 ± 3.03 s−1; p-value <0.005) in the KC group significantly increased at the tissue level. This is the first time that the incremental DIC method was applied to the in-vivo high-speed corneal deformation measurement in combination with the Corvis ST tonometer. Through the image registration using incremental DIC analysis, spatiotemporal dynamic strain/strain rate maps of the cornea can be estimated at the tissue level. This is constructive for the clinical recognition and diagnosis of keratoconus at a more underlying level.

Experimental stress determination of blunt notches under combinations of modes I and II loading

An appropriate evaluation of the stress field for designing new or optimizing existing engineering structures is required. The primary goal of this paper is to use the digital image correlation (DIC) approach to ascertain the stress field around the root of various blunt notches. At first, extensive tests were performed using the Brazilian Disc (BD) specimen containing three distinct notches (U, VO, and Keyhole) under diverse loading conditions, including pure mode I, pure mode II, and mixed-mode I/II. The displacement fields output from the DIC experiments were employed as the input data for a computer program, and the coefficients of the stress and displacement fields were then determined utilizing the over-deterministic technique. Afterward, the computed coefficients were used to calculate the analytical stress field around the notch root by considering singular and higher-order terms for each notch type. Subsequently, the finite element (FE) method was employed to verify the accuracy of the stress field obtained from the DIC experiments. In addition, the influence of some major parameters such as notch opening angle, notch tip radius, and geometry on the stress distribution was investigated. This study validated the efficiency of the DIC approach in determining the unknown stress coefficients of rounded notches, especially the first non-singular term of the stress expansion, which is revealed to have a considerable impact on appraising the exact stress field around the notch curvature.

Mechanical characteristics of laser-deposited sandwich structures and quasi-homogeneous alloys of Fe-Cu system

The laser metal deposition approach implements a unique opportunity for controlling the fabrication of functionally graded and sandwich structures from different metal powders for artificial physical properties management. In this study, the quasi-homogeneous alloys were fabricated by the simultaneous feed of bronze and steel powders from different feeders of the LMD installation and the gradient structures by alternating deposition of the materials. The resulting alloys consisted of 50 wt% − 50 wt% and 25 wt% − 75 wt% non-gradient bronze-steel parts and sandwich structures of alternating 250-μm-height steel and bronze layers. The alloy based on aluminum bronze demonstrated the highest ultimate tensile strength (838.6 MPa). Its yield stress amounted to 665 MPa, strain-to-fracture – 0.035, Poisson’s ratio – 0.23, and modulus of resilience – 1.03 MJ/m3. A digital image correlation approach was applied to study the character of major strain distribution in the fabricated specimens and localizations of strain concentrators and compare them with all specimens’ failure areas. Fractography analysis showed a predominantly brittle character of failure. Investigated materials are expected to be applied as interface regions of Fe-Cu system functionally graded structures.

A Pre-Process Enhanced Digital Image Correlation Approach for Smart Structure Monitoring

This research provides a practical guideline for Digital Image Correlation (DIC) data variations minimization in structural engineering through simple image processing techniques. The main objective of this research is to investigate the Pixel Averaging (P.A.) effect on the differential strain Diff(εx) variations. Three concrete arches were tested with three-point bending using the DIC technique for strain measurements. The measured strains are obtained through two virtual horizontal extensometers in the middle of each arch. The Diff(εx) was selected to avoid other 2D-DIC issues, such as the sample-camera out-of-plane movement. Three image cases, namely, one, ten, and twenty averaged images, were used for DIC analysis of each arch. The conditions of each image case are assessed by computing the Diff(εx) variance and the linear least square criterion (R2) between the two extensometers. The second objective is to examine the speckles’ dilation effects on the speckle pattern density and surface component quality utilizing the Image Erode (I.E.) technique. The (P.A.) technique provided consistent differential strain Diff(εx) values with a variance reduction of up to (90%) when averaged images were used. The (R2) has considerably increased (from 0.46, 0.66, 0.91 to 0.90, 0.96, 0.99), respectively, for the three samples. Moreover, the (I.E.) technique provided qualitatively denser speckles with a highly consistent DIC surface component.

A plantar surface shear strain methodology utilising Digital Image Correlation

The increase in the global diabetic population is leading to an increase in associated complications such as diabetic foot ulceration (DFU), associated amputations, morbidity, which substantial treatment costs. Early identification of DFU risk is therefore of great benefit. International guidelines recommend off-loading is the most important intervention for healing and prevention of DFU, with current research focused on pressure measurement techniques. The contribution of strain to DFU formation is not well understood due to challenges in measurement. The limited data available in the literature suggest that plantar strain is involved in ulcer formation. As a consequence, there is a need for plantar strain measurement systems to advance understanding and inform clinical treatment. A method was developed to determine plantar strain based on a Digital Image Correlation (DIC) approach. A speckle pattern is applied to the plantar aspect of the foot using a low ink transference method. A raised walkway with transparent panels is combined with a calibrated camera to capture images of the plantar aspect throughout a single stance phase. Plantar strain is then determined using 2D DIC and custom analysis summarises these data into clinically relevant metrics. A feasibility study involving six healthy participants was used to assess the efficacy of this new technique. The feasibility study successfully captured plantar surface strain characteristics continuously throughout the stance phase for all participants. Peak mean and averaged mean strains varied in location between participants when mapped into anatomical regions of plantar interest, ranging from the calcaneus to the metatarsal heads and hallux. This method provides the ability to measure plantar skin strain for use in both research and clinical environments. It has the potential to inform improved understanding of the role of strain in DFU formation. Further studies using this technique can support these ambitions and help differentiate between healthy and abnormal plantar strain regimes.

Correction of full-field rigid body rotation and strain using a hybrid peridynamics and digital image correlation approach

Rigid body rotation is difficult to be removed independently while using digital image correlation (DIC) technique for monitoring the displacement and deformation of an object. Furthermore, strain measurement can also become inaccurate due to the presence of displacement caused by rigid body rotation. Common solutions to this problem, such as tracking a single-point's rotation, require additional reference information and only obtain one rigid body rotation angle of the object. In this study, a hybrid computational and experimental mechanics method based on peridynamics (PD) and DIC technique is proposed to measure the full-field rigid body rotation and strain. A DIC-based PD model can be established based on the full-field position data obtained by DIC. The calculation formulas for rigid body rotation and strain are derived in the framework of PD and the calculations of rotation and strain are mutually insensitive and independent. Therefore, without any additional reference information, the rigid body rotation and strain information can be obtained in the presence of simultaneous rigid body rotation and deformation. Different rigid body rotations in various regions of an object, whether large or small rotations, can be calculated by this method. Correspondingly, this method is effective for calculating the local rigid body rotations of objects undergoing local fracture. Numerical simulations and experimental tests were performed to verify the effectiveness of the proposed method. The calculation results show that the proposed method owns the ability to accurately calculate the rotation and strain in the above scenarios.

Deformation measurement in Al thin films at elevated temperatures by digital image correlation with speckles prepared by femtosecond laser

Deformation measurement in thin films at elevated temperatures is critical for assessing the reliability and performance of microelectronic devices. Digital image correlation (DIC) is a full-field, noncontact deformation measurement technique. However, the traditional DIC approach requires spraying paints for speckles, which is not suitable for high-temperature applications. The aim of this work is to propose a fully customizable speckle preparation method by pulsed laser that can deliver ideal speckle pattern, good contrast and consistency and controllable damage to sample for deformation measurement at elevated temperatures by DIC. Al thin films deposited on Si substrates were used for speckle preparation by FLs at different powers (10 mW, 8 mW, 6 mW and 4 mW). Serial images of speckles were captured as the temperature increased from room temperature to 325 °C, followed by data analysis. A finite element model was built to evaluate the deviation of measured strains in Al thin film from ideal values. To evaluate the damage of laser to sample surface during speckle preparation, a two-temperature model (TTM) was used to evaluate the ideal ablation depth at different laser fluences. Scanning electron microscopy and white light interferometry were also used to examine the surface damage and depth of holes. Based on our findings, speckles prepared by laser irradiation at 8 mW have the best speckle quality and measurement accuracy. The depth of speckles increased linearly with increasing laser power, ranging from 11.8 to 32.9 nm. The ideal depth calculated by the TTM was slightly lower than the experimental results, which can be attributed to the parameters of the model deviating from the actual sample (such as the reflectance of Al). DIC with speckles prepared by an FL can provide good measurement accuracy at elevated temperatures while causing minimal damage to the sample.