Strain Estimation Research Articles

Improve myocardial strain estimation based on deformable groupwise registration with a locally low-rank dissimilarity metric

BackgroundCurrent mainstream cardiovascular magnetic resonance-feature tracking (CMR-FT) methods, including optical flow and pairwise registration, often suffer from the drift effect caused by accumulative tracking errors. Here, we developed a CMR-FT method based on deformable groupwise registration with a locally low-rank (LLR) dissimilarity metric to improve myocardial tracking and strain estimation accuracy.MethodsThe proposed method, Groupwise-LLR, performs feature tracking by iteratively updating the entire displacement field across all cardiac phases to minimize the sum of the patchwise signal ranks of the deformed movie. The method was compared with alternative CMR-FT methods including the Farneback optical flow, a sequentially pairwise registration method, and a global low rankness-based groupwise registration method via a simulated dataset (n = 20), a public cine data set (n = 100), and an in-house tagging-MRI patient dataset (n = 16). The proposed method was also compared with two general groupwise registration methods, nD + t B-Splines and pTVreg, in simulations and in vivo tracking.ResultsOn the simulated dataset, Groupwise-LLR achieved the lowest point tracking errors (p = 0.13 against pTVreg for the temporally averaged point tracking errors in the long-axis view, and p < 0.05 for all other cases), voxelwise strain errors (all p < 0.05), and global strain errors (p = 0.05 against pTVreg for the longitudinal global strain errors, and p < 0.05 for all other cases). On the public dataset, Groupwise-LLR achieved the lowest contour tracking errors (all p < 0.05), reduced the drift effect in late-diastole, and preserved similar inter-observer reproducibility as the alternative methods. On the patient dataset, Groupwise-LLR correlated better with tagging-MRI for radial strains than the other CMR-FT methods in multiple myocardial segments and levels.ConclusionsThe proposed Groupwise-LLR reduces the drift effect and provides more accurate myocardial tracking and strain estimation than the alternative methods. The method may thus facilitate a more accurate estimation of myocardial strains for clinical assessments of cardiac function.

Ultimate strain estimation of concrete wrapped by aramid fiber employing coati optimization-based systems

Ultimate strain estimation of concrete wrapped by aramid fiber employing coati optimization-based systems

Fatigue Assessment of Copper‐Brazed Stainless‐Steel Joints for Plate Heat Exchangers

ABSTRACTCyclic pressures can cause fatigue failure in the brazed joints and plates of the plate heat exchangers (PHEs). This study examines the fatigue behavior of PHEs made from 316L and 304L steels brazed with copper foils employing strain‐controlled fatigue tests to explore if 304L could replace 316L in the existing production line for cost reduction. Fatigue tests were conducted at four different load levels with a stress ratio of zero and a frequency of 5 Hz. Finite Element Analysis was used to assess strain distribution and estimate PHE lifespan based on generated strain versus number of cycles to failure curves. The microstructural analysis revealed that copper diffuses more easily into 316L than 304L, and using 50 μm thick foil causes more defects compared with 100 μm foil. It was shown that 316L joints have a significantly increased fatigue life compared with 304L. Both 316L and 304L met the 15‐year lifetime requirement set by manufacturers.

Stress–strain curve estimation from load–depth curve of spherical indentation test based on finite element analysis and optimization

A stress–strain curve is one of the most important indicators of material properties for characterizing constitutive behavior. It can be directly obtained from a conventional uniaxial tensile test or load–displacement curve using an instrumented indentation test (IIT). An IIT uses formulations of the effective indentation strain and stress or the iterative finite element analysis (FEA) of the indentation process using a constitutive model, such as a power-law constitutive model. In this study, an iterative FEA is used to obtain the engineering stress–strain curve. However, it focused on considering the realistic plastic flow of specific materials without idealizing the power-law constitutive model. A concept for stress–strain estimation using a master stress–strain curve for specific materials was proposed, and its usefulness was validated via FEA and optimization techniques. In the future, this methodology can be extended to deep learning technology to address the issue of time consumption in iterative optimization methods.

Allylic Epoxides Increase the Strain Energy of Cyclic Olefin Monomers for Ring-Opening Metathesis Polymerization.

Ring-opening metathesis polymerization (ROMP) is an effective method for synthesizing functional polymers, but since the technique typically relies on high ring strain cyclic olefins, the most common monomers are norbornene derivatives. The reliance on one class of monomer limits the obtainable properties of ROMP polymers. In this work, we investigate new bicyclic monomers synthesized via epoxidation of commercial dienes. DFT estimates of these monomers' ring strains suggests a significant increase in strain for cyclic olefins containing allylic epoxides. We found that the eight-membered (3,4-COO) and five-membered (CPO) cyclic olefins were particularly effective for ROMP. CPO was of especially intriguing due to its excellent polymerizability when compared to the limited reactivity of other five-membered rings. Unlike polynorbornenes, the resulting polymers of both monomers displayed glass transition temperatures well below room temperature. Interestingly, poly(3,4-COO) showed both high stereo- and regioregularity while poly(CPO) showed little regularity. Both polymers could be readily modified via post-polymerization ring-opening of the reactive allylic epoxides. With a high epoxide density in poly(CPO), CPO is an exciting new ROMP monomer that is easily synthesized, can be polymerized to high conversion at room temperature, and may be facilely modified to yield a wide range of functional materials.

Analytic modeling and validation of strain in textile-based OLEDs for advanced textile display technologies

In the IoT era, the demand for wearable displays is rapidly growing, catalyzing the advancement of research into textile-based organic light-emitting diodes (OLEDs). This growing interest stems particularly from the inherent flexibility of textile-based OLEDs1,2, allowing for seamless integration into the dynamic and interactive functionalities of cutting-edge wearable technology, alongside their superior electrical performance. The durability and mechanical robustness of these displays, especially under physical stress and deformation, are critical to their practical application and longevity. Thus, understanding and enhancing the mechanical properties of textile-based OLEDs is paramount for their successful integration into wearable technologies. However, many studies assessing the mechanical properties of OLEDs have predominantly relied on simplistic bending test outcomes determined by the radius, often neglecting or insufficiently analyzing the strain exerted on the OLEDs atop textile substrates in relation to curvature of these devices. Existing analyses typically presume pure bending, though such an assumption leads to considerable errors in strain estimations, making such approaches problematic if the goal is practical application in actual wearable display products. To address these limitations, an analytic model that includes a comprehensive energy equation is introduced, considering the stretching energy, bending energy, and shear energy of each layer composing the textile substrate. This holistic approach provides a novel formula specifically designed to calculate the top surface strain of textile substrates. Robust validation of this formula is conducted by comparing its results with strain measurements obtained from digital image correlation (DIC) and finite element analysis (FEA) outcomes from ANSYS across various bending radii (or equivalently, curvatures). The close alignment of the calculated strain values with those derived from DIC and FEA not only underscores the precision of this formula but also highlights its significant potential for enhancing the designs and functionalities of future wearable display technologies under real-world conditions.

Dynamic strain field estimation of fixed offshore support structures using limited acceleration measurements

The strain history affecting the fatigue life of fixed offshore support structures is one of the most important topics in structural monitoring. However, some critical fatigue locations are located below the seabed, and the installation of strain gauges at these locations entails significant maintenance costs. In contrast, acceleration which reflects the vibration characteristics of the structure is an easily accessible and more stable physical parameter. Therefore, this study presents a strain estimation scheme that uses limited acceleration measurements to estimate the dynamic strain field of the fixed offshore support structures. An adaptive displacement reconstruction method is used to obtain the displacements at the master degrees of freedom, then the global displacements are obtained by the evolutionary orthogonal response expansion method, and finally, these displacements are implemented into the numerical software by redefining the boundary conditions to obtain the dynamic strain field. The advantage of the proposed method over the traditional strain-solving forward problem is that it relies solely on measured acceleration and structural geometry information, without requiring displacement, strain, or modal information. The correctness of the proposed method is verified by a numerical jacket platform model with multi-harmonic and non-stationary random excitations. Furthermore, physical experiments under eccentric rotation and hammering excitations are performed to assess the applicability of the proposed method on a wind turbine model equipped with laser displacement and fibre bragg grating sensors as reference measurements. The results show that the proposed method can accurately predict the dynamic strains of jacket platform and wind turbine support structures, while the appropriate agreement between the estimated strains and the numerical results, and the optical measured response is observed, with maximum estimation errors of 1.80% and 4.63%, respectively. Summarily, the application of the approach enables a new type of strain monitoring applicable to fixed offshore support structures.

An ANI-2 enabled open-source protocol to estimate ligand strain after docking.

In protein-ligand docking, the score assigned to a protein-ligand complex is approximate. Especially, the internal energy of the ligand is difficult to compute precisely using a molecular mechanics based force-field, introducing significant noise in the rank-ordering of ligands. We propose an open-source protocol (https://github.com/UnixJunkie/MMO), using two quantum mechanics (QM) single point energy calculations, plus a Monte Carlo (Monte Carlo) based ligand minimization procedure in-between, to estimate ligand strain after docking. The MC simulation uses the ANI-2x (QM approximating) force field and is performed in the dihedral space. On some protein targets, using strain filtering after docking allows to significantly improve hit rates. We performed a structure-based virtual screening campaign on nine protein targets from the Laboratoire d'Innovation Thérapeutique-PubChem assays dataset using Cambridge crystallographic data centre genetic optimization for ligand docking. Then, docked ligands were submitted to the strain estimation protocol and the impact on hit rate was analyzed. As for docking, the method does not always work. However, if sufficient active and inactive molecules are known for a given protein target, its efficiency can be evaluated.

Two-dimensional thermal and dynamical strain in landfast sea ice from InSAR: results from a new analytical inverse method and field observations

Abstract Observing continuous strain in sea ice at geophysical scales of tens of meters to kilometers requires displacement measurements made with millimeter-scale precision. Satellite-based interferometric synthetic aperture radar (InSAR) provides such precise measurements of relative surface displacement over broad spatial areas at regular intervals and, unlike point displacement measurements, it allows confident delineation of continuously deforming regions. However, InSAR only captures the 1-D component of surface displacement parallel to a radar's lines-of-sight. Additional analysis is required to translate between these 1-D observations and the horizontal or vertical displacements they arose from. Previous studies utilize an iterative inverse model to constrain estimates of horizontal surface displacement from InSAR. Here we build upon that work outlining a new analytical inverse modeling method for quantifying displacement and strain over continuous regions of sea ice and provide comparison between model results and independent displacement observations. We demonstrate the inverse method over both landfast and drifting ice along the Alaskan coastline. These intercomparisons highlight environments in which displacements inverted from interferograms may be used as an independent estimator of surface strain, as well as the potential for the outlined inverse methods to be used in conjunction with other observing methods.

Insights into deformation-induced heating: Temperature-strain prediction in SCM440 steel under deformation scenarios

Recently, deformation-induced temperature was found to be predictable based on corresponding strain, enabling broader applications in temperature prediction and strain measurement. This prediction relies on the temperature-strain relationship during deformation. However, the influence of deformation rate has not been addressed, despite most materials exhibiting rate-dependent behavior that affects both material properties and deformation-induced temperature. This study aims to explore the rate-dependent behavior of the temperature-strain relationship and develop a prediction model. Thermal-strain analysis reveals a linear correlation between deformation-induced temperature and plastic strain, with rate-dependent behavior governed by the deformation rate. Relationships among change in temperature difference per unit strain, heat generation rate, and strain rate are utilized to establish the prediction model. The developed model is primarily applied under various deformation conditions in uniaxial tensile testing. Prediction results for temperature and strain closely match measured values, with an overall difference within 5 % in most cases, except at slow deformation rates where strain estimation is less effective due to dominant heat convection. The model was also applied to three-point bending tests with different artificial-defect specimens, revealing predictable temperature results with a maximum difference of 7 % and estimated strains agreeing with a 5 % error band in the initial 20 % of plastic strain development. Both findings underscore the crucial influence of heat transfer on prediction accuracy, suggesting its necessity in further improvements. This study provides insights into temperature-strain prediction driven by deformation-induced heating, offering guidance for temperature-strain prediction methods and paving the way for applications in thermal-based inspection and temperature-based strain measurement.

Measurement of Internal Residual Stress of Three-Directional Components and Estimation of Inherent Strain in Carburized Steel for Large Rolling Bearings by Combining the Contour Method and XRD Method

Measurement of Internal Residual Stress of Three-Directional Components and Estimation of Inherent Strain in Carburized Steel for Large Rolling Bearings by Combining the Contour Method and XRD Method

On the contribution of local anisotropic creep to macroscopic irradiation-induced growth in zirconium alloy polycrystals

ABSTRACT Zirconium alloys used in nuclear reactor exhibit, under fast neutron flux, a macroscopic deformation even without applied stress called irradiation induced growth. Because of the polycrystalline nature of the material, the local growth of individual grains results in strain incompatibilities yielding to intergranular stresses and thus to local creep. In order to study and understand the influence of the local anisotropic creep on the macroscopic growth behaviour, an analytical and a numerical study have been undertaken, using Voigt and self-consistent estimates and also fast Fourier transform simulations. It is shown that the anisotropic local creep has a strong influence on the effective macroscopic growth strain of the polycrystal. Especially, when the deformation is difficult along the 〈 c 〉 axis, a growth enhancement effect is observed. This phenomenon is well explained in the frame of the Voigt estimate using a reduced fibre texture. Computations conducted using a texture representative of the industrial material provide a quantitative confirmation of this enhancement effect. This work demonstrates the significant contribution of the local anisotropic creep to the macroscopic in-reactor growth strain of zirconium alloys. Highlights The local creep anisotropy has a strong influence on macroscopic irradiation growth of polycrystalline zirconium tubes. The macroscopic axial growth can be significantly enhanced by the interactions between grains when local creep deformation is prevented along the 〈 c 〉 axis. A simplified representation of grain interactions (reduced fibre texture and Voigt estimate) offers a qualitative understanding of this phenomenon. Refined estimates of the effective growth strain are provided for realistic crystallographic texture using polycrystalline unit-cell FFT computations.

CineVN: Variational network reconstruction for rapid functional cardiac cine MRI.

To develop a reconstruction method for highly accelerated cardiac cine MRI with high spatiotemporal resolution and low temporal blurring, and to demonstrate accurate estimation of ventricular volumes and myocardial strain in healthy subjects and in patients. The proposed method, called CineVN, employs a spatiotemporal Variational Network combined with conjugate gradient descent for optimized data consistency and improved image quality. The method is first evaluated on retrospectively undersampled cine MRI data in terms of image quality. Then, prospectively accelerated data are acquired in 18 healthy subjects both segmented over two heartbeats per slice as well as in real time with 1.6 mm isotropic resolution. Ventricular volumes and strain parameters are computed and compared to a compressed sensing reconstruction and to a conventional reference cine MRI acquisition. Lastly, the method is demonstrated in 46 patients and ventricular volumes and strain parameters are evaluated. CineVN outperformed compressed sensing in image quality metrics on retrospectively undersampled data. Functional parameters and myocardial strain were the most accurate for CineVN compared to two state-of-the-art compressed sensing methods. Deep learning-based reconstruction using our proposed method enables accurate evaluation of cardiac function in real-time cine MRI with high spatiotemporal resolution. This has the potential to improve cardiac imaging particularly for patients with arrhythmia or impaired breath-hold capability.

Fluid-Solid Interaction Analysis for Developing In-Situ Strain and Flow Sensors for Prosthetic Valve Monitoring.

Transcatheter aortic valve implantation (TAVI) was initially developed for adult patients, but there is a growing interest to expand this procedure to younger individuals with longer life expectancies. However, the gradual degradation of biological valve leaflets in transcatheter heart valves (THV) presents significant challenges for this extension. This study aimed to establish a multiphysics computational framework to analyze structural and flow measurements of TAVI and evaluate the integration of optical fiber and photoplethysmography (PPG) sensors for monitoring valve function. A two-way fluid-solid interaction (FSI) analysis was performed on an idealized aortic vessel before and after the virtual deployment of the SAPIEN 3 Ultra (S3) THV. Subsequently, an analytical analysis was conducted to estimate the PPG signal using computational flow predictions and to analyze the effect of different pressure gradients and distances between PPG sensors. Circumferential strain estimates from the embedded optical fiber in the FSI model were highest in the sinus of Valsalva; however, the optimal fiber positioning was found to be distal to the sino-tubular junction to minimize bending effects. The findings also demonstrated that positioning PPG sensors both upstream and downstream of the bioprosthesis can be used to effectively assess the pressure gradient across the valve. We concluded that computational modeling allows sensor design to quantify vessel wall strain and pressure gradients across valve leaflets, with the ultimate goal of developing low-cost monitoring systems for detecting valve deterioration.

3D regional evaluation of right ventricular myocardial work from cineCT.

Regional myocardial work (MW) is not measured in the right ventricle (RV) due to a lack of high spatial resolution regional strain (RS) estimates throughout the ventricle. We present a cineCT-based approach to evaluate regional RV performance and demonstrate its ability to phenotype three complex populations: end-stage LV failure (HF), chronic thromboembolic pulmonary hypertension (CTEPH), and repaired tetralogy of Fallot (rTOF). 49 patients (19 HF, 11 CTEPH, 19 rTOF) underwent cineCT and right heart catheterization (RHC). RS was estimated from full-cycle ECG-gated cineCT and combined with RHC pressure waveforms to create regional pressure-strain loops; endocardial MW was measured as the loop area. Detailed, 3D mapping of RS and MW enabled spatial visualization of strain and work strength, and phenotyping of patients. HF patients demonstrated more overall impaired strain and work compared to the CTEPH and rTOF cohorts. For example, the HF patients had more akinetic areas (median: 9%) than CTEPH (median: <1%, p=0.02) and rTOF (median: 1%, p<0.01) and performed more low work (median: 69%) than the rTOF cohort (median: 38%, p<0.01). The CTEPH cohort had more impairment in the septal wall; <1% of the free wall and 16% of the septal wall performed negative work. The rTOF cohort demonstrated a wide distribution of strain and work, ranging from hypokinetic to hyperkinetic strain and low to medium-high work. Impaired strain (-0.15≤RS) and negative work were strongly-to-very strongly correlated with RVEF (R=-0.89, p<0.01; R=-0.70, p<0.01 respectively), while impaired work (MW≤5 mmHg) was moderately correlated with RVEF (R=-0.53, p<0.01). Regional RV MW maps can be derived from clinical CT and RHC studies and can provide patient-specific phenotyping of RV function in complex heart disease patients. Evaluating regional variations in right ventricular (RV) performance can be challenging, particularly in patients with significant impairments due to the need for 3D spatial coverage with high spatial resolution. ECG-gated cineCT can fully visualize the RV and be used to quantify regional strain with high spatial resolution. However, strain is influenced by loading conditions. Myocardial work (MW) - measured clinically derived as the ventricular pressure-strain loop area - is considered a more comprehensive metric due to its independence of preload and afterload. In this study, we sought to develop regional RV myocardial work (MW) assessments in 3D with high spatial resolution by combining cineCT-derived regional strain with RV pressure waveforms from right heart catheterization (RHC). We developed our method using data from three clinical cohorts who routinely undergo cineCT and RHC: patients in heart failure, patients with chronic thromboembolic pulmonary hypertension, and adults with repaired tetralogy of Fallot.We demonstrate that regional strain and work provide different perspectives on RV performance. While strain can be used to evaluate apparent function, similar profiles of RV strain can lead to different MW estimates. Specifically, MW integrates apparent strain with measures of afterload, and timing information helps to account for dyssynchrony. As a result, CT-based assessment of RV MW appears to be a useful new metric for the care of patients with dysfunction.

Attention-Based Neural Network for Cardiac MRI Segmentation: Application to Strain and Volume Computation

ContextDeep learning algorithms have been widely used for cardiac image segmentation. However, most of these architectures rely on convolutions that hardly model long-range dependencies, limiting their ability to extract contextual information. Moreover, the traditional U-net architecture suffers from the difference of semantic information between feature maps of the encoder and decoder (also known as the semantic gap). Material and methodTo address this issue, a new network architecture relying on attention mechanism was introduced. Swin Filtering Blocks (SFB), that use Swin Transformer blocks in a cross-attention manner, were added between the encoder and the decoder to filter information coming from the encoder based on the feature map from the decoder. Attention was also employed at the lowest resolution in the form of a transformer layer to increase the receptive field of the network.We conducted experiments to assess both generalization capability and to evaluate how training on all frames of the cardiac cycle rather than only the end-diastole and end-systole impacts strain and segmentation performances. Results and conclusionVisual inspection of feature maps suggested that Swin Filtering Blocks contribute to the reduction of the semantic gap. Performing attention between all patches using a transformer layer brought higher performance than convolutions. Training the model with all phases of the cardiac cycle resulted in slightly more accurate segmentations while leading to a more noticeable improvement for strain estimation. A limited decrease in performance was observed when testing on out-of-distribution data, but the gap widens for the most apical slices.

Computationally efficient adaptive optimization of vector-method parameters for phase-sensitive strain estimation in optical coherence elastography

A new method for automatic adaptive optimization of strain estimation in phase-sensitive optical coherence tomography (OCT) is introduced. More specifically, this paper focuses on optimizing the estimation of strain using the vector method, in which OCT signals are treated as vectors in the complex plane. In phase-sensitive optical coherence elastography, the tissue strain is extracted from the interframe phase variation between the complex-valued scans acquired for the initial and deformed tissue. This phase variation is proportional to interframe displacements of scatterers and corresponds to the argument of the pixel-by-pixel product of the initial OCT scan and complex-conjugate deformed scan. Measurement noises and the so-called ‘speckle noise’ that are intrinsic to OCT scans cause degradation of the derived scan obtained by such multiplication. To mitigate the noise influence, complex-valued pixel amplitudes in the derived scan are usually averaged over a certain window. The interframe strain is found by estimating the gradient of the interframe phase difference. The noise influence on the strain estimation can also be reduced by increasing the scale over which the phase-variation gradient is estimated. However, choosing a too large window for preliminary averaging may significantly distort the reconstructed strain distribution. Similarly, a too large scale for gradient estimation may also cause errors in the estimated-strain magnitude and even its sign (because of possible phase wrapping). Therefore, appropriately performed adaptive choice of the strain-estimation parameters can greatly improve the quality of strain estimation. Here, we present a unified approach for adaptive choice of both the averaging-window size and gradient-estimation scale that were initially considered separately. The new method is computationally simplified but enables approximately the same strain-estimation quality, as demonstrated using both simulated and experimental OCT data.

Simultaneous Coherent and Displacement Compounding for 2-D Noninvasive Carotid Strain Imaging: A Proof of Principle Study.

Arteriosclerosis results from lipid buildup in artery walls, leading to plaque formation, and is a leading cause of death. Plaque rupture can cause blood clots that might lead to a stroke. Distinguishing plaque types is a challenge, but ultrasound (US) elastography can help by assessing plaque composition based on strain values. Since the artery has a circular structure, an accurate axial and lateral displacement strategy is needed to derive the radial and circumferential strains. A high-precision lateral displacement is challenging due to the lack of phase information in the lateral direction of the beamformed RF data. Previously, our group has developed a compounding technique in which the lateral displacement is estimated using triangulation of the axial displacement estimated from transmitting and beamforming US beams at ±20°. However, transmitting with a single plane wave will reduce signal-to-noise and contrast-to-noise ratio as well as lateral resolution. In this article, we combine our displacement compounding with coherent compounding. Instead of transmitting a single plane wave, multiple plane waves are transmitted at certain angles centered on the angle of the beamforming grids, and then, the backscattered wavefronts are beamformed and coherently compounded on the center of the transmit beams (-20°, +20°, and 0°). The numerical investigation using the GE9LD probe ( f0 = 5.32 MHz, pitch = 230 μ m, and width = 43.9 mm) led us to 19 plane waves spanning angles within -10° to 10° (with respect to center of the transmit beams), resulting in a total of 57 plane wave transmit (for three beamforming grids at 0° and ±20°). FIELD II simulations of a cylindrically shaped phantom (mimicking the carotid artery) at a signal-to-noise ratio (SNR) ≥ 20 dB show that the proposed method decreases the root-mean-square error (RMSE) of the lateral displacement and strain estimations by 40% and 45% compared to the previous method, respectively. The results of our experiments with a carotid artery phantom [made out of 10% polyvinyl alcohol (PVA)] show that the proposed method provides strain images with higher quality and more in agreement with the theory, with 26% lower standard deviation, especially at the peak systolic phase. The proposed method paves the path toward improved quality in vivo 2-D strain imaging using our displacement compounding technique and translating it to 3-D with a row-column array.

Experimental evaluation of geotextile in-filled sand cushioning system against rock fall impact using 2D digital image correlation technique

Rockfall on slopes always poses potential threat to the safety of people and infrastructures. Though, constructions of rockfall protection shelters were considered an appropriate solution, still there is a lack of understanding on rock mass-structure-sand cushion interaction which was mainly due to the impact and rebound characteristics of the detached falling rock mass. Considering rockfall induced impact response, geotextile in-filled sand bags have been developed in this study as a confined energy dissipation member against rock fall conditions. Using scaled down model structure, the performance of geotextile in-filled sand cushioning system against impact forces were evaluated and compared. Additionally, the study specially used 2D Digital Image Correlation technique for displacement, strain estimation and force calculation measurement on the structure and geotextile in-filled sandbags due to rock fall impact. The observations proved that, provision of geotextile in-filled sand bags over the structure showed 99% energy dissipation against impact load and can be an alternative to conventional sand cushioning layer with minimum additional load on the rock fall protection system. Also, 2D DIC monitoring found reliable in impact application studies for estimating force and displacement measurement.

Quantitative analysis of crustal deformation, seismic strain, and stress estimation in Iran via earthquake mechanisms

Quantitative analysis of crustal deformation, seismic strain, and stress estimation in Iran via earthquake mechanisms