Estimation Of Elastic Modulus Research Articles

Determinants of Human Corneal Mechanical Wave Dispersion for In Vivo Optical Coherence Elastography.

To characterize frequency-dependent wave speed dispersion in the human cornea using microliter air-pulse optical coherence elastography (OCE), and to evaluate the applicability of Lamb wave theory for determining corneal elastic modulus using high-frequency symmetric (S0) and anti-symmetric (A0) guided waves in cornea. Wave speed dispersion analysis for transient (0.5 ms) microliter air-pulse stimulation was performed in four rabbit eyes ex vivo and compared to air-coupled ultrasound excitation. The effects of stimulation angle and sample geometry on the dispersion were evaluated in corneal phantoms. Corneal wave speed dispersion was measured in 36 healthy human eyes in vivo. Air-pulse-induced dispersion was comparable to ultrasound-induced dispersion between 0.7 and 5 kHz (mean-difference ± 1.96 × SD: 0.006 ± 0.5m/s) in ex vivo rabbit corneas. Stimulation 0° relative to the surface normal generated A0 Lamb waves in corneal tissue phantoms, while oblique stimulation (35° and 65°) generated S0 waves. Stimulating normal to the human corneal apex in vivo (0°) induced A0 waves, plateauing at 10.87 to 13.63m/s at 4 kHz, and when obliquely stimulated at the periphery (65°), produced S0 waves, plateauing at 13.10 to 15.98m/s at 4 kHz. Air-pulse OCE can be used to measure human corneal Lamb wave dispersion of A0 and S0 propagation modes in vivo. These modes are selectively excited by changing the stimulation angle. Accounting for wave speed dispersion enables reliable estimation of corneal elastic modulus in vivo. This work demonstrates the feasibility of air-pulse stimulation for robust OCE measurements of corneal stiffness in vivo for disease detection and therapy evaluation.

Estimation of uniaxial compressive strength and elastic modulus of carbonate rocks by various methods

Estimation of uniaxial compressive strength and elastic modulus of carbonate rocks by various methods

Local Stress in Cylindrically Curved Lipid Membrane: Insights into Local Versus Global Lateral Fluidity Models.

Lipid membranes, which are fundamental to cellular function, undergo various mechanical deformations. Accurate modeling of these processes necessitates a thorough understanding of membrane elasticity. The lateral shear modulus, a critical parameter describing membrane resistance to lateral stresses, remains elusive due to the membrane's fluid nature. Two contrasting hypotheses, local fluidity and global fluidity, have been proposed. While the former suggests a zero local lateral shear modulus anywhere within lipid monolayers, the latter posits that only the integral of this modulus over the monolayer thickness vanishes. These differing models lead to distinct estimations of other elastic moduli and affect the modeling of biological processes, such as membrane fusion/fission and membrane-mediated interactions. Notably, they predict distinct local stress distributions in cylindrically curved membranes. The local fluidity model proposes isotropic local lateral stress, whereas the global fluidity model predicts anisotropy due to anisotropic local lateral stretching of lipid monolayers. Using molecular dynamics simulations, this study directly investigates these models by analyzing local stress in a cylindrically curved membrane. The results conclusively demonstrate the existence of static local lateral shear stress and anisotropy in local lateral stress within the monolayers of the cylindrical membrane, strongly supporting the global fluidity model. These findings have significant implications for the calculation of surface elastic moduli and offer novel insights into the fundamental principles governing lipid membrane elasticity.

Estimation of cement paste stiffness and UHPC elastic modulus through measured phase-property upscaling

The elastic stiffness of bulk concrete materials results from the complex interaction of aggregates, voids, and hydrated cement (which can have multiple hardened phases at multiple length scales). Given the complexities associated with understanding the arrangement of these particles within bulk concrete volumes, estimations for elastic modulus often rely on empirical correlations with unit weight and compressive strength. Such estimations are inherently scale-dependent and fail to capture variability in mix designs, particularly the variability found in specialty concrete mixes. To develop a scale-independent method for estimating elastic modulus from mix-design volume fraction information, this study explores a novel bottom-up approach using cement paste phase stiffness values determined through micro-mechanical experimentation and randomized Monte-Carlo spring arrangement simulations. Statistical representations of cement paste phase stiffness distributions and bulk volume fraction data are combined to provide estimations for elastic stiffness in both the composite cement paste and bulk concrete containing fine aggregate and fibers. Resulting a priori estimations of UHPC cement paste stiffness from the micro-mechanical upscaling simulations were within 4% of measured values (based on mix-design and void volume fraction information alone) for a selected sample of mix proportions. When applied to the two UHPC mixes containing fibers and fine aggregate, upscaling simulations consistently overpredicted the measured elastic modulus, likely due to the aggregate-cement interfacial transition zone (ITZ) properties that were not captured in the micro-mechanical testing.

Computational comparison study of virtual compression and shear test for estimation of apparent elastic moduli under various boundary conditions.

Virtual compression tests based on finite element analysis are representative noninvasive methods to evaluate bone strength. However, owing to the characteristic porous structure of bones, the material obtained from micro-computed tomography images in the finite-element model is not uniformly distributed. These characteristics cause differences in the apparent elastic moduli depending on the boundary conditions and affect the accuracy of bone-strength evaluation. Therefore, this study aimed to evaluate and compare the apparent elastic moduli under various, virtual-compression and shear-test boundary conditions. Four, nonuniform models were constructed with increasing model complexity. For representative boundary conditions, two, different, testing directions, and constrained surfaces were applied. As a result, the apparent elastic moduli of the nonuniform model varied up to 55.2% based on where the constrained surface was located in the single-end-cemented condition. Additionally, when connectivity in the test direction was lost, the accuracy of the apparent elastic moduli was low. A graphical comparison showed that the equivalent-stress distribution was more advantageous for analyzing load transferability and physical behavior than the strain-energy distribution. These results clearly show that the prediction accuracy of the apparent elastic moduli can be guaranteed if the boundary condition on the constraint and loading surfaces of the nonuniform model are applied symmetrically and the connectivity of the elements in the testing direction is well maintained. This study will aid in precision improvement of bone-strength-indicator determination for osteoporosis prevention.

Demonstrating a Quartz Crystal Microbalance with Dissipation (QCMD) to Enhance the Monitoring and Mechanistic Understanding of Iron Carbonate Crystalline Films.

This paper reports the real time monitoring of siderite deposition, on both Au- and Fe-coated surfaces, using the changes in frequency and dissipation of quartz crystal microbalance with dissipation (QCMD). In an iron chloride solution saturated with carbon dioxide, buffered with sodium bicarbonate to pH 6.8, roughly spherical particles of siderite formed within 15 min, which subsequently deposited on the QCMD crystal surface. Imaging of the surface showed a layer formed from particles ca. < 0.5 μm in diameter. Larger particles are clearly deposited on top of the lower layer; these larger particles are >1 μm in diameter. Monitoring of the frequency clearly differentiates the formation of the lower layer from the larger crystals deposited on top at later times. The elastic moduli calculated from QCMD data showed a progressive dissipation increase; the modeling of the solid-liquid interface using a flat approximation resulted in a poor estimation of elastic and storage moduli. Rather, the impedance modeled as a viscoelastic layer in contact with a semi-infinite liquid, where a random bumpy surface with a Gaussian correlator is used, is much more accurate in determining the elastic and storage moduli as losses from the uneven interface are considered. A further step considers that the film is in fact a composite consisting of hard spherical particles of siderite with water in the vacant spaces. This is treated by considering the individual contributions of the phases to the losses measured, thereby further improving the accuracy of the description of the film and the QCMD data. Collectively, this work presents a new framework for the use of QCMD, paired with traditional approaches, to enhance the understanding of crystal deposition and film formation as well as quantify the often evolving mechanical properties.

Improved estimation of uniaxial compressive strength and elastic modulus for carbonate rocks using back propagation neural network and buckingham pi theorem

Improved estimation of uniaxial compressive strength and elastic modulus for carbonate rocks using back propagation neural network and buckingham pi theorem

Constrained amorphous interphase in plasticized poly(lactic acid): Composition and tensile elastic modulus estimation

The study investigates the distribution of the plasticizers acetyl triethyl citrate (ATEC) and acetyl tributyl citrate (ATBC) in the mobile amorphous (MAF) and rigid amorphous (RAF) fractions of semi-crystalline plasticized poly (lactic acid) (PLA) containing 5 wt% of plasticizer. During crystallization, the ATEC and ATBC concentration in the MAF increases from 5 to about 8 wt%. At the end of crystallization, the plasticizers concentration in the RAF is lower than that in the MAF. The progressive decrease of the ATEC and ATBC concentration in the RAF region could be linked to the growth of subsidiary lamellae in more restricted amorphous areas. The study also introduces an estimation of the tensile elastic modulus of the RAF (ERAF) in semi-crystalline pure and plasticized PLA containing α-crystals. The mechanical model with crystalline lamellae perpendicular to the stress direction turned out to be the most appropriate arrangement to represent the morphological organization in PLA samples prepared by injection-moulding processing at high pressure. The mathematical procedure led to a crystal elastic modulus (EC) of the α-phase in excellent agreement with the theoretical value reported in the literature (EC = 14 GPa), and to an ERAF value around 5.5 GPa, for both pure and plasticized PLA, thus suggesting that both ATEC and ATBC do not exert plasticizing action on the RAF.

From a distance: Shuttleworth revisited.

The Shuttleworth equation: a linear stress-strain relation ubiquitously used in modeling the behavior of soft surfaces. Its validity in the realm of materials subject to large deformation is a topic of current debate. Here, we allow for large deformation by deriving the constitutive behavior of the surface from the general framework of finite kinematics. We distinguish cases of finite and infinitesimal surface relaxation preceding an infinitesimal applied deformation. The Shuttleworth equation identifies as the Cauchy stress measure in the fully linearized setting. We show that both in finite and linearized cases, measured elastic constants depend on the utilized stress measure. In addition, we discuss the physical implications of our results and analyze the impact of surface relaxation on the estimation of surface elastic moduli in the light of two different test cases.

Estimation of elastic modulus of recycle aggregate concrete based on hybrid and ensemble‐hybrid approaches

AbstractThe utilization of recycled aggregate concrete (RAC) within the construction sector has the potential to prevent irreversible harm to the environment and reduce the depletion of natural resources. Nonetheless, it is essential to scrutinize the quality of RAC before utilizing it in practical applications. RAC's most significant design parameter is its elastic modulus, typically determined through time‐consuming and costly experiments. Machine learning (ML) techniques can be a feasible solution to reduce the number of experiments required and obtain accurate estimates. This article employs two robust ML techniques, namely Xtreme Gradient Boosting (XGB) and Adaptive Boosting regression, in three distinct modes, namely individual, hybrid, and ensemble‐hybrid methods. Furthermore, phasor particle swarm optimization (PPSO) and chaos game optimization (CGO) have been utilized in hybrid and ensemble‐hybrid modes to optimize final results, minimize errors, and obtain highly precise outcomes. As mentioned earlier, several evaluators were employed to identify the most appropriate model to compare the modes. The findings suggest that the relevant optimizers significantly contributed to achieving superior metric values. Specifically, the results indicated that PPSO exhibited greater efficacy than CGO in optimizing outputs and enhancing accuracy. The hybrid models, particularly XGB in conjunction with PPSO, yielded the most favorable correlation coefficient and root mean square error values equal to 0.996 and 0.336 and can serve as an effective ML method to determine elastic modulus of recycle aggregate concrete for time and energy storage.

A novel relationship between elastic modulus and void ratio associated with principal stress for coral calcareous sand

Elastic moduli, e.g. shear modulus G and bulk modulus K, are important parameters of geotechnical materials, which are not only the indices for the evaluation of the deformation ability of soils but also the important basic parameters for the development of the constitutive models of geotechnical materials. In this study, a series of triaxial loading-unloading-reloading shear tests and isotropic loading-unloading-reloading tests are conducted to study several typical mechanical properties of coral calcareous sand (CCS), and the void ratio evolution during loading, unloading and reloading. The test results show that the stress-strain curves during multiple unloading processes are almost parallel, and their slopes are much greater than the deformation modulus at the initial stage of loading. The relationship between the confining pressure and the volumetric strain can be defined approximately by a hyperbolic equation under the condition of monotonic loading of confining pressure. Under the condition of confining pressure unloading, the evolution of void ratio is linear in the e-lnp′ plane, and these lines are a series of almost parallel lines if there are multiple processes of unloading. Based on the experimental results, it is found that the modified Hardin formulae for the elastic modulus estimation have a significant deviation from the tested values for CCS. Based on the experimental results, it is proposed that the elastic modulus of soils should be determined by the intersection line of two spatial surfaces in the G/K-e-p'/pa space (pa: atmosphere pressure). “Ye formulation” is further proposed for the estimation of the elastic modulus of CCS. This new estimation formulation for soil elastic modulus would provide a new method to accurately describe the mechanical behavior of granular soils.

On the variants of SVM method for the estimation of soil elastic modulus from TSD model: Numerical parametric study

The accurate estimation of the subgrade resilient modulus MR is a crucial element in designing durable and resilient pavements as it quantifies the soil’s bearing capacity to withstand traffic loads without excessive deformation or failure. Conventional methods and devices that are used to estimate MR, such as the Falling Weight Deflectometer (FWD) have several limitations due to operational and security constraints when measuring at the network level. To overcome these limitations, Traffic Speed Deflectometer (TSD) has been developed, which can continuously assess the pavement bearing capacity without requiring traffic control. However, processing the massive amounts of data generated by TSD requires specialized processing techniques such as Machine Learning (ML). Therefore, the primary objective of this paper is to develop an efficient and effective model that can accurately estimate MR by combining two techniques: (TSD + ML). The study uses numerical simulations of deflection velocity slope SV under TSD as the forward model. The research employs Support Vector Machine (SVM) algorithm for ML to classify and estimate MR modulus values from a synthetic and controlled dataset. SVM model exhibits robust performance in both classification and regression analysis, whereas, 95% of the discrepancies between estimated and tested values did not exceed ±15MPa. Advanced numerical validation, sensitivity analysis and parameter estimation methods were also conducted to optimize the model’s performance. Overall, the approach proposed in this paper has the potential to make a significant impact in the field of subgrade evaluation and can facilitate the development of better road infrastructure.

Estimation of yield strength and elastic modulus of aerospace-grade aluminum 7075 composite reinforced with silicon carbide and graphite

This study aims to find a suitable theoretical model to estimate yield strength and elastic modulus of the AA7075 base cast and hybrid composite reinforced with silicon carbide and graphite (micron-sized) to attain high quality, high performance, and low-cost metal matrix composite. Compared to AA7075 base cast CM1 (AA7075 base cast) ultimate tensile strength, yield strength, and flexural strength of hybrid composite CM4 (AA7075 + 15 wt% SiC + 5 wt% Graphite), CM3 (AA7075 + 10 wt% SiC + 5 wt% Graphite), and CM2 (AA7075 + 5 wt% SiC + 5 wt% Graphite) increased (29%, 24%, and 19%), (36%, 35%, and 27%), and (19%, 13%, and 6%) respectively. Micro-mechanics contributed higher, followed by other strengthening mechanisms like load transfer, grain refinement, and thermal mismatch with respect to the volume fraction of the reinforcement particle in the aluminum metal matrix. In the yield strength model, Ramakrishnan-Modified Shear Lag-Mirza and Chen model, Li model, sum of contribution model, and proposed model estimated closer values. They agreed with experimental data at all values up to 7.34% of reinforcement volume fraction. In the elastic modulus model, Hashin-Shtrikman – average, upper, and lower bound and the proposed model estimated well and agreed with experimental data at lower and higher volume fractions of reinforcement.

Estimation of elastic modulus, fracture toughness and strength of 47.5B-derived bioactive glass-ceramics for bone scaffold applications: a nanoindentation study

The knowledge of the mechanical properties of glass–ceramic materials used in bone scaffolds is the key to the optimal design of tissue engineering devices. In this paper, the elastic properties and fracture toughness of silicate bioactive glass-ceramics based on the 47.5B parent composition were quantified for the first time through nanoindentation. Specifically, the effect of sintering temperature was investigated by testing samples sintered at six different temperatures. The samples sintered at higher temperatures exhibited elastic modulus and fracture toughness higher than those of the lower temperature samples. Both properties are comparable with those shown by similar bioactive glasses available in literature, supporting the mechanical suitability of the materials for bone applications. An estimation of tensile strength as a function of flaw size is also provided by means of fracture mechanics approaches.

Tissue Viscoelasticity Quantification Using Smartphone Tactile Imaging Probe With an Indenter and Viscoelastic Pitting Recovery Model

Viscoelasticity of human tissue often carries important physiological information linking to many fatal diseases, such as heart failure, renal impairment, and liver failure. Fluid retention due to these diseases cause swelling of body parts (edema) and changes the viscoelastic characteristic of the tissue. We hypothesize that the viscoelastic behavior change of the tissue can be estimated by creating and quantifying the pit on the swelled body parts. Here, we present a smartphone tactile imaging probe with an indenter (STIP-I) system that measures the pitting parameters and characterizes the viscoelastic behavior. This system consists of tactile imaging sensing that utilizes a light diffusion in a polydimethylsiloxane (PDMS)-based optical waveguide and a Viscoelastic Pitting Recovery (VPR) computation model. The prototype STIP-I system is tested using edematous tissue phantoms, which show a moderate measurement error of 29.5% for the pitting parameters and excellent performance of 7.60% error in elastic modulus estimation. The STIP-I system is expected to bring a new approach to understanding viscoelasticity changes due to various diseases.

Evaluation of local changes in radio-frequency signal waveform and brightness caused by vessel dilatation for ascertaining reliability of elasticity estimation inside heterogeneous plaque: a preliminary study.

To diagnose plaque characteristics, we previously developed an ultrasonic method to estimate the local elastic modulus from the ratio of the pulse pressure to the strain of the arterial wall due to dilatation in systole by transcutaneously measuring the minute thinning in thickness during one cardiac cycle. For plaques, however, some target regions became thicker as the vessel dilates, resulting in false elasticity. Therefore, a method to identify a reliable target for the elastic modulus estimation is indispensable. As a candidate for an identification index of plaques that become thicker during one cardiac cycle, the correlation of the radio-frequency (RF) signals remains high and it is not sufficient to obtain the elasticity. In this study, we thoroughly observed the target with a high correlation but positive strain in the plaque and characterized it by the property of the surrounding area. For the plaque formed in the right carotid sinus of a patient with hyperlipidemia and the wall of the right common carotid artery of a young healthy male, (1) the correlation value as the similarity between the RF signals, (2) change in brightness obtained from the log-compressed envelope signals, and (3) strain obtained between the time of the R-wave and that of the maximum vessel dilatation were observed to characterize the region in the plaque. In the plaque, it was found that the region with high correlation and positive strain and its surrounding area could be classified into one of the three typical patterns. As a preliminary study, this study provides a clue to assert the reliability of elasticity estimates for a region with high correlation and positive strain in the plaque based on measurable properties.

Accurate measurement of elasticity of the radial artery wall considering changes in cross-sectional shape of artery caused by pushing pressure applied by ultrasound probe

For the early diagnosis of atherosclerosis, our group developed an ultrasound probe that can simultaneously measure blood pressure and vessel diameter at the same position. However, because the developed probe requires the blood vessel to be deformed by pushing to measure the blood pressure, it affects the estimation of the vessel’s elastic modulus. In the present study, we derived a series of equations to estimate the elastic modulus of a blood vessel considering the pushing pressure applied by the ultrasound probe and the resultant deformation of the blood vessel. The validity of the proposed method was verified by numerical calculations, and then the method was applied to in vivo measurements. The proposed method resulted in fewer variations in the elastic modulus estimates with different pushing pressures compared with the conventional method.

Estimation and Comparison of Effective Elastic Modulus of Different Scaffolds Using Curve Fitting Method for Additive Manufacturing Field

Estimation and Comparison of Effective Elastic Modulus of Different Scaffolds Using Curve Fitting Method for Additive Manufacturing Field

Discussion on the paper entitled “Estimating elasticity modulus and uniaxial compressive strength of sandstone using indentation test” by E. Mousavi, A. Cheshomi and M. Ashtari [Journal of Petroleum Science and Engineering 169 (2018) 157–166

A discussion on the paper by Mousavi et al. (2018) is presented. The paper is focused on the estimation of elastic modulus (E) and uniaxial compressive strength (UCS) of sandstone using indentation test. The authors concluded that the thickness effect of samples on the indentation indices (critical transition force (CTF) and indentation modulus (IM)) was negligible. They proposed a dimensionless surface parameter (S) to eliminate the size effect on the E and UCS. On the basis of the test results and analysis method presented in the paper by Mousavi et al. (2018), three aspects of indentation test need to be clarified: the methods to prevent the movement of rock specimens, the results obtained from indentation test and the effect of specimen sizes on the CTF and IM. Meanwhile, the present discussion paper proposed some references for the methods to prevent the movement of rock specimens and the methods to eliminate the size effect in indentation test.

Understanding the Geodetic Signature of Large Aquifer Systems: Example of the Ozark Plateaus in Central United States

AbstractThe continuous redistribution of water involved in the hydrologic cycle leads to deformation of the solid Earth. On a global scale, this deformation is well explained by the loading imposed by hydrological mass variations and can be quantified to first order with space‐based gravimetric and geodetic measurements. At the regional scale, however, aquifer systems also undergo poroelastic deformation in response to groundwater fluctuations. Disentangling these related but distinct 3D deformation fields from geodetic time series is essential to accurately invert for changes in continental water mass, to understand the mechanical response of aquifers to internal pressure changes as well as to correct time series for these known effects. Here, we demonstrate a methodology to accomplish this task by considering the example of the well‐instrumented Ozark Plateaus Aquifer System (OPAS) in the central United States. We begin by characterizing the most important sources of groundwater level variations in the spatially heterogeneous piezometer dataset using an Independent Component Analysis. Then, to estimate the associated poroelastic displacements, we project geodetic time series corrected for hydrological loading effects onto the dominant groundwater temporal functions. We interpret the extracted displacements in light of analytical solutions and a 2D model relating groundwater level variations to surface displacements. In particular, the relatively low estimates of elastic moduli inferred from the poroelastic displacements and groundwater fluctuations may be indicative of aquifer layers with a high fracture density. Our findings suggest that OPAS undergoes significant poroelastic deformation, including highly heterogeneous horizontal poroelastic displacements.