Inverse Finite Element Modeling Research Articles

Characterisation of human penile tissue properties using experimental testing combined with multi-target inverse finite element modelling

This paper presents an inverse finite element (FE) approach aimed at estimating multi-layered human penile tissues. The inverse FE approach integrates experimental force–displacement and boundary deformation data of penile tissues with a developed FE model and uses new experimental data on human penile tissue. The experimental study encompasses whole organ plate-compression tests and individual layer tensile and compression tests, providing comprehensive insights into the tissue's mechanical behaviour. The biomechanical characterisation of penile tissue is of crucial significance for understanding its mechanical behaviour under various physiological and pathological conditions. The FE model is constructed using the realistic geometry of the penile segment and appropriate constitutive models for each tissue layer to leverage the accuracy and consistency of the model. Through systematic variation of tissue parameters in the inverse FE algorithm, simulations achieve the best match with both force–displacement and deformed boundary results obtained from the whole organ plate-compression tests. Test results from individual tissue layers are also utilised to assess the estimated parameters. The proposed inverse FE approach allows for the estimation of penile tissue parameters with high precision and reliability, shedding light on the mechanical properties of this complex biological organ. This work has applications not only in urology but also for researchers in various disciplines of biomechanics. As a result, our study contributes to advancing the understanding of human penile tissue mechanics whilst the methodology could also be applied to a range of other soft biological tissues. Statement of significanceThis research uses a multi-target inverse finite element (FE) approach for estimating the material parameters of human penile tissues. By integrating experimental data and a realistic FE model, this study achieves high-precision constitutive model parameter estimation, offering key insights into penile tissue mechanics under various loading conditions. The significance of this work lies in the use of this inverse FE approach for fresh-frozen human penile tissues, to identify the mechanical properties and constitutive models for both segregated tunica albuginea and corpus cavernosum as well as intact penile tissue segments. The study's scientific impact lies in its advancement of the understanding of human urological tissue mechanics, impacting researchers and clinicians alike.

Quantification of Cartilage Poroelastic Material Properties Via Analysis of Loading-Induced Cell Death.

Articular cartilage (AC) is a load-bearing tissue that covers long bones in synovial joints. The biphasic/poroelastic mechanical properties of AC help it to protect joints by distributing loads, absorbing impact forces, and reducing friction. Unfortunately, alterations in these mechanical properties adversely impact cartilage function and precede joint degeneration in the form of osteoarthritis (OA). Thus, understanding what factors regulate the poroelastic mechanical properties of cartilage is of great scientific and clinical interest. Transgenic mouse models provide a valuable platform to delineate how specific genes contribute to cartilage mechanical properties. However, the poroelastic mechanical properties of murine articular cartilage are challenging to measure due to its small size (thickness ∼ 50 microns). In the current study, our objective was to test whether the poroelastic mechanical properties of murine articular cartilage can be determined based solely on time-dependent cell death measurements under constant loading conditions. We hypothesized that in murine articular cartilage subjected to constant, sub-impact loading from an incongruent surface, cell death area and tissue strain are closely correlated. We further hypothesized that the relationship between cell death area and tissue strain can be used-in combination with inverse finite element modeling-to compute poroelastic mechanical properties. To test these hypotheses, murine cartilage-on-bone explants from different anatomical locations were subjected to constant loading conditions by an incongruent surface in a custom device. Cell death area increased over time and scaled linearly with strain, which rose in magnitude over time due to poroelastic creep. Thus, we were able to infer tissue strain from cell death area measurements. Moreover, using tissue strain values inferred from cell death area measurements, we applied an inverse finite element modeling procedure to compute poroelastic material properties and acquired data consistent with previous studies. Collectively, our findings demonstrate in the key role poroelastic creep plays in mediating cell survival in mechanically loaded cartilage and verify that cell death area can be used as a surrogate measure of tissue strain that enables determination of murine cartilage mechanical properties.

Poster Session: Estimation of scleral biomechanical properties from air-puff-coupled optical coherence tomography.

Progression of myopia is usually accompanied by axial overgrowth of the eyeball, which affects scleral biomechanics (BM). To study scleral biomechanics, we propose the use of air-puff deformation swept-source OCT imaging. Air-puff deformation imaging was performed at different sites of ex vivo porcine (n=5) and rabbit (n=3) eyes, (<24hr postmortem): Nasal/temporal equatorial and posterior sclera (NE, NP, TE, TP), superior (S) and inferior (I) sclera, and cornea (C). Intraocular pressure was kept at 15mmHg. Deformation data were used as input to inverse finite element model (FEM) algorithms to reconstruct BM properties. Experimental deformation amplitudes showed dependence on the animal model, with porcine scleras exhibiting greater inter-site variation (displacement of S, I was up to four times greater than that of N, T), while rabbit scleras exhibited at most 40% of displacement differences between all sites. Both models showed significant (p<.001) differences in the temporal deformation profile between sclera and (C), but similarities in all scleral locations, suggesting that the scleral temporal profile is independent of scleral thickness variations. The FEM estimated an elastic modulus of 1.84 ± 0.30 MPa (I) to 6.04 ± 2.11 MPa (TE) for the porcine sclera. The use of scleral air-puff imaging is promising for noninvasive investigation of structural changes in the sclera associated with myopia and for monitoring possible modulation of scleral stiffness with myopia treatment.

In vivo biomechanical assessment of iridial deformations and muscle contractions in human eyes.

The iris is a muscular organ whose deformations can cause primary angle-closure glaucoma (PACG), a leading cause of blindness. PACG risk assessment does not consider iridial biomechanical factors, despite their expected influence on iris deformations. Here, we exploited an existing biometric dataset consisting of near-infrared movies acquired during the pupillary light reflex (PLR) as a unique resource to study iris biomechanics. The PLR caused significant (greater than 100%) and essentially spatially uniform radial strains in the iris in vivo, consistent with previous findings. Inverse finite-element modelling showed that sphincter muscle tractions were ca fivefold greater than iridial stroma stiffness (range 4- to 13-fold, depending on sphincter muscle size). This muscle traction is greater than has been previously estimated, which may be due to methodological differences and/or to different patient populations in our study (European descent) versus previous studies (Asian); the latter possibility is of particular interest due to differential incidence rates of PACG in these populations. Our methodology is fast and inexpensive and may be a useful tool in understanding biomechanical factors contributing to PACG.

Nonlinear Viscoelastic Properties of 3D-Printed Tissue Mimicking Materials and Metrics to Determine the Best Printed Material Match to Tissue Mechanical Behavior

3D-printed biomaterials have become ubiquitous for clinical applications including tissue-mimicking surgical/procedure planning models and implantable tissue engineering scaffolds. In each case, a fundamental hypothesis is that printed material mechanical properties should match those of the tissue being replaced or modeled as closely as possible. Evaluating these hypotheses requires 1) consistent nonlinear elastic/viscoelastic constitutive model fits of 3D-printed biomaterials and tissues and 2) metrics to determine how well 3D-printed biomaterial mechanical properties match a corresponding tissue. Here we utilize inverse finite element modeling to fit nonlinear viscoelastic models with Neo-Hookean kernels to 29 Polyjet 3D-printed tissue-mimicking materials. We demonstrate that the viscoelastic models fit well with R2 &amp;gt; 0.95. We also introduce three metrics ( least-squares difference, Kolmogorov–Smirnov statistics, and the area under stress/strain or load/displacement curve) to compare printed material properties to tissue properties. All metrics showed lower values for better matches between 3D-printed materials and tissues. These results provide a template for comparing 3D-printed material mechanical properties to tissue mechanical properties, and therefore, a basis for testing the fundamental hypotheses of 3D-printed tissue-mimicking materials.

Quantification of the heterogeneous effect of static and dynamic perivascular structures on patient-specific local aortic wall mechanics using inverse finite element modeling and DENSE MRI

Recent studies have highlighted the relevance of perivascular interactions on aortic wall mechanics. Most of the approaches assume static perivascular structures; however, the beating heart dynamically displaces the neighboring aorta. We develop a model to account for the effect of periaortic interactions due to static and dynamic structures by prescribing a moving elastic foundation boundary condition (EFBC) embedded into an inverse finite element algorithm using in vivo displacements from 2D displacement encoding with stimulated echoes (DENSE) MRI as target data. We applied this method at three different locations of interest, the distal aortic arch (DAA), descending thoracic aorta (DTA), and infrarenal abdominal aorta (IAA) for a total of 27 cases in healthy humans. The model reproduces the target diastole-to-systole deformation and bulk displacement of the aortic wall with median displacement errors below 0.5mm. The EFBC showed good agreement with the location of anatomical features and was consistent among individuals of similar characteristics. Results show that an energy source acting on the adventitia is required to reproduce the displacements measured at the vicinity of the heart, but not at the abdomen. The average adventitial load as a percentage of the luminal pulse-pressure was found to increase with age and to decrease along the descending aorta, from 61% at the DAA to 37% at the DTA, and 30% at the IAA. This approach offers a patient-specific method to estimate in vivo adventitial loads and aortic wall stiffness, which can bring a better understanding of normal and pathological in vivo aortic function.

Determining adhesion of critical interfaces in microelectronics – A reverse Finite Element Modelling approach based on nanoindentation

State-of-the-art microelectronic devices, especially power semiconductors, are usually exposed to harsh environmental conditions on the one hand, for example large temperature hubs, and to challenging application conditions on the other hand, such as pulsed current applications. Mechanical robustness and reliability have become more and more challenging in recent years. Along with a continuous shrinkage of dimensions, thin film materials are stacked and micro-structured for optimized performance of such devices. Major risks for device reliability can result from loss of adhesion at interfaces of these stacked thin films. Therefore, it is crucial for such devices to feature perfect initial adhesion of the said thin film layers, even after exposure to thermal treatment or in presence of intrinsic stress. In order to validate device robustness, the quality of interface adhesion between isolating and metallization layers should be carefully assessed. A particular focus is set on interfaces between the following, widely employed materials: Cu, Al, WTi, BPSG, SiN etc. Robustness by design at critical interfaces has relied more and more on advanced Finite Element Modelling (FEM) methods in recent years. This includes explicit modelling of adhesion and delamination. Accurate parameters that describe interfacial adhesion – critical adhesion energies in tensile and shear mode – need to be extracted by means of suitable experiments on tailored test vehicles. FEM is able in turn to verify the existing theoretical framework about extracting adhesion energies from experiments, given that the analytical models are often phenomenological and based on simplified assumptions. Experimentally, Nanoindentation on designed multi-layer thin film stacks has proven to be a suitable method to investigate inter-layer adhesion strength on test vehicle basis. We focused on layered stacks of tungsten‑titanium (WTi) and Boron-Phosphorous-Silicate Glass (BPSG) on Silicon substrates. The WTi layer exhibits compressive stress tailored by means of deposition. When an axis-symmetric conical or spherical indenter penetrates the WTi film, buckles around the indenter imprint arise upon loading and may propagate during unloading. Buckle geometry is measured by means of focused ion beam and Scanning Electron Microscopy. Afterwards the critical adhesion energies can be determined by existing analytical models. Combining experimental and simulation methods one may follow a Physics-of-Failure approach and assess the failure mechanisms related to thin film delamination and interface fracture. With experimental results on hand, we implemented an FE model of the same multi-layer system. Initiation and propagation of delamination was modeled by means of a Cohesive Zone Model (CZM) based on a cohesive surface contact approach. The model incorporates elastic-plastic deformation as well as intrinsic stresses of all layers, including the substrate. Following an inverse FEM approach, we reproduced the size of the delaminated area and load-displacement curves of the indenter by recursively readjusting Cohesive Zone parameters. The so-obtained adhesion parameters and modelling can be used elsewhere in delamination risk assessments of industrial semiconductor applications. This approach also gives insight into the accuracy of the formulae used for calculating the total energy release rate and extracting the further relevant parameters without the need to rely on phenomenological assumptions.

The effect of radiolytic oxidation on the elastic properties of nuclear graphite measured by electronic speckle pattern interferometry

• Three-point bend measurement data characterised by ESPI and inverse modelling. • Static Young's modulus , Poisson's ratio and strength determined. • Measurements performed on 218 irradiated graphite beams taken from UK AGR stations. • Graphite samples (6 × 6 × 19 mm) cover dose range to 21.1 DPA and weight loss to 46%. • Modulus and strength correlate well with radiolytic weight loss. The Young's modulus, Poisson's ratio and flexural strength of 218 beams of radiolytically oxidised nuclear graphite have been determined by combining electronic speckle pattern interferometry, ESPI, and inverse finite element modelling techniques. The graphite was extracted from three operational advanced gas cooled reactor stations where it had been subjected to fast neutron irradiation and radiolytic oxidation resulting in mass loss. The 6 × 6 × 19 mm beam samples had densities ranging from 1063 – 1840 kg.m −3 , equivalent to weight losses up to 46%, with cumulative neutron doses of up to 161 × 10 20 n.cm −2 equivalent Dido nickel dose, or 21.1 displacements per atom, significantly extending the datasets available in the open literature to higher levels of both dose and oxidation. In situ ESPI measurements were collected during three-point bend tests, creating full field displacement maps of the evolving deformation to which simulations were matched by chi-squared minimisation of the elastic properties. Potential loading abnormalities were accounted for in the fitting process to ensure the simulations were representative, with total uncertainties in the determined Young's modulus and Poisson's ratio values of ± 4.5% and ± 0.08, respectively. Consistent trends were observed in the behaviour of the material from the different stations, with strong positive dependences on density for both the flexural strength and Young's modulus. The strength and Young's modulus remained well correlated even to high levels of oxidation mass loss. Conversely, the Poisson's ratio was practically invariant with oxidation with mean values of 0.21 ± 0.03, 0.24 ± 0.05 and 0.25 ± 0.05 for the three stations. The combined ESPI-finite element measurement approach is demonstrated as robust for irradiated small specimens, making it suitable for monitoring graphite in future reactors. The collected data support the safety assessments of the current reactors, enabling predictions of the responses to progressively higher mean core mass loss.

Multicomponent material property characterization of atherosclerotic human carotid arteries through a Bayesian Optimization based inverse finite element approach

ObjectivePlaque rupture in atherosclerotic carotid arteries is a main cause of ischemic stroke and it is correlated with high plaque stresses. Hence, analyzing stress patterns is essential for plaque specific rupture risk assessment. However, the critical information of the multicomponent material properties of atherosclerotic carotid arteries is still lacking greatly. This work aims to characterize component-wise material properties of atherosclerotic human carotid arteries under (almost) physiological loading conditions. MethodsAn inverse finite element modeling (iFEM) framework was developed to characterize fibrous intima and vessel wall material properties of 13 cross sections from five carotids. The novel pipeline comprised ex-vivo inflation testing, pre-clinical high frequency ultrasound for deriving plaque deformations, pre-clinical high-magnetic field magnetic resonance imaging, finite element modeling, and a sample efficient machine learning based Bayesian Optimization. ResultsThe nonlinear Yeoh constants for the fibrous intima and wall layers were successfully obtained. The optimization scheme of the iFEM reached the global minimum with a mean error of 3.8% in 133 iterations on average. The uniqueness of the results were confirmed with the inverted Gaussian Process (GP) model trained during the iFEM protocol. ConclusionThe developed iFEM approach combined with the inverted GP model successfully predicted component-wise material properties of intact atherosclerotic human carotids ex-vivo under physiological-like loading conditions. SignificanceWe developed a novel iFEM framework for the nonlinear, component-wise material characterization of atherosclerotic arteries and utilized it to obtain human atherosclerotic carotid material properties. The developed iFEM framework has great potential to be advanced for patient-specific in-vivo application.

Multicomponent Mechanical Characterization of Atherosclerotic Human Coronary Arteries: An Experimental and Computational Hybrid Approach.

Atherosclerotic plaque rupture in coronary arteries, an important trigger of myocardial infarction, is shown to correlate with high levels of pressure-induced mechanical stresses in plaques. Finite element (FE) analyses are commonly used for plaque stress assessment. However, the required information of heterogenous material properties of atherosclerotic coronaries remains to be scarce. In this work, we characterized the component-wise mechanical properties of atherosclerotic human coronary arteries. To achieve this, we performed ex vivo inflation tests on post-mortem human coronary arteries and developed an inverse FE modeling (iFEM) pipeline, which combined high-frequency ultrasound deformation measurements, a high-field magnetic resonance-based artery composition characterization, and a machine learning-based Bayesian optimization (BO) with uniqueness assessment. By using the developed pipeline, 10 cross-sections from five atherosclerotic human coronary arteries were analyzed, and the Yeoh material model constants of the fibrous intima and arterial wall components were determined. This work outlines the developed pipeline and provides the knowledge of non-linear, multicomponent mechanical properties of atherosclerotic human coronary arteries.

An enhanced inverse beam element for shape estimation of beam-like structures

The inverse finite element method (iFEM) is a mechanics-based algorithm for deformed-shape estimation of structures. In this paper, an enhanced inverse beam element named iEBT2 is developed based on classical beam theory. The element formulation is derived by minimizing a weighted-errors functional that consists of experimental and numerical section strains. The improved coefficient matrix KR is always non-singular, assuring that the solution of iFEM formulation exists. Location-independent feature of matrix KR simplifies the inverse finite element modeling, especially for complicated structures. Weighting constants are utilized to define error functional, aiming to penalize the contributions from “measure-less” stations. Numerical and experimental cases have been performed and demonstrated excellent predictive capability when iEBT2 model has complete strain measures. In the case of missing strain components, iEBT2 enables deformation estimation and its accuracy is acceptable in general. The enhanced inverse element extends the practical usefulness of iFEM in shape-sensing analysis of civil infrastructures.

Inverse modeling framework for characterizing patient-specific microstructural changes in the pulmonary arteries

Microstructural changes in the pulmonary arteries associated with pulmonary arterial hypertension (PAH) is not well understood and characterized in humans. To address this issue, we developed and applied a patient-specific inverse finite element (FE) modeling framework to characterize mechanical and structural changes of the micro-constituents in the proximal pulmonary arteries using in-vivo pressure measurements and magnetic resonance images. The framework was applied using data acquired from a pediatric PAH patient and a heart transplant patient with normal pulmonary arterial pressure, which serves as control. Parameters of a constrained mixture model that are associated with the structure and mechanical properties of elastin, collagen fibers and smooth muscle cells were optimized to fit the patient-specific pressure-diameter responses of the main pulmonary artery. Based on the optimized parameters, individual stress and linearized stiffness resultants of the three tissue constituents, as well as their aggregated values, were estimated in the pulmonary artery. Aggregated stress resultant and stiffness are, respectively, 4.6 and 3.4 times higher in the PAH patient than the control subject. Stress and stiffness resultants of each tissue constituent are also higher in the PAH patient. Specifically, the mean stress resultant is highest in elastin (PAH: 69.96, control: 14.42 kPa-mm), followed by those in smooth muscle cell (PAH: 13.95, control: 4.016 kPa-mm) and collagen fibers (PAH: 13.19, control: 2.908 kPa-mm) in both the PAH patient and the control subject. This result implies that elastin may be the key load-bearing constituent in the pulmonary arteries of the PAH patient and the control subject.

Prediction of spot weld fatigue life using finite element approach

Resistant spot welding is predominantly used in automotive industry for joining sheet metal. Mostly automobile fatigue failure occurs in and around spot welding (80%). So, accurate prediction of the deformation, stresses and fatigue life of spot weld is necessary. In this work finite element model of spot weld and experimental study of coach peel test of spot welded low carbon steel sheets are presented. The property change in various zones of spot weld is found by nano-indentation test followed by inverse finite element modelling. Spot weld failure happens at the interface between nugget and heat affected zone due to the geometric stress concentration and property change that occurs during the welding process. Solid elements are successful in capturing the geometric stress concentration, but they increase the simulation cost and hence a model with combined shell and solid elements is used. For nugget solid elements are used and tore present all other parts of spot weld shell elements are used. Tensile and fatigue tests on coach peel specimen are done as per ASTM standardD903-98. The simulation results are found to be in close agreement with experimental results.

In vivo estimation of murine iris stiffness using finite element modeling

The iris plays an important role in certain types of glaucoma, including primary angle-closure glaucoma and pigmentary glaucoma. Iris mechanics are also important in influencing trabecular meshwork deformation in response to intraocular pressure changes in some animal species. Although mice are widely used to study ocular disease, including glaucoma, the in vivo biomechanical properties of the murine iris are unknown. Thus, the primary objective of this study was to estimate murine iris biomechanical stiffness. We used optical coherence tomography (OCT) images of the anterior segment of living mice (n = 13, age = 7.3 ± 3.2 [mean ± SD] months) at sequentially increasing IOP levels, observing IOP-dependent iris deformations. We then used an inverse finite element model to predict iris deformations under the same conditions, estimating iris stiffness by maximizing agreement between OCT data and numerical simulations. Our results show an in vivo murine iris stiffness of 96.1 ± 54.7 kPa (mean ± SD), which did not correlate with age but was dependent on gender. Our results further showed strong evidence of reverse pupillary block, with mean posterior chamber pressure remaining at approximately 12 mmHg even as anterior chamber pressure was set to much higher levels. Our approach to monitoring iris stiffness in vivo is applicable to study potential changes of iris stiffness in various pathophysiological conditions and thus has significant potential for clinical care of ocular disease involving iris biomechanics.

Calibration of the modified Mohr-Coulomb fracture model by use of localization analyses for three tempers of an AA6016 aluminium alloy

This paper presents a novel calibration procedure of the modified Mohr-Coulomb (MMC) fracture model by use of localization analyses and applies it for three tempers of an AA6016 aluminium alloy. The localization analyses employ the imperfection band approach, where metal plasticity is assigned outside the band and porous plasticity is assigned inside the band. Ductile failure is thus assumed to occur when the deformation localizes into a narrow band. The metal plasticity model is calibrated from notch tension tests using inverse finite element modelling. The porous plasticity model is calibrated by use of localization analyses where the deformation histories from finite element simulations of notch and plane-strain tension tests are prescribed as boundary conditions. Subsequently, localization analyses are used to establish the failure locus in stress space for proportional loading conditions and thus to determine the parameters of the MMC fracture model. Finite element simulations of notch tension and in-plane simple shear tests as well as two load cases of the modified Arcan test are used to validate the calibrated fracture model. The predictions by the simulations are in good agreement with the experiments, even though some deviations are seen for each temper. The results demonstrate that localization analyses are a cost-effective and reliable tool for predicting ductile failure, reducing the number of mechanical tests required to calibrate the MMC fracture model compared to the hybrid experimental-numerical approach usually applied.

In vivo estimation of normal left ventricular stiffness and contractility based on routine cine MR acquisition

Post-myocardial infarction remodeling process is known to alter the mechanical properties of the heart. Biomechanical parameters, such as tissue stiffness and contractility, would be useful for clinicians to better assess the severity of the diseased heart. However, these parameters are difficult to obtain in the current clinical practice. In this paper, we estimated subject-specific in vivo myocardial stiffness and contractility from 21 healthy volunteers, based on left ventricle models constructed from data acquired from routine cardiac MR acquisition only. The subject-specific biomechanical parameters were quantified using an inverse finite-element modelling approach. The personalized models were evaluated against relevant clinical metrics extracted from the MR data, such as circumferential strain, wall thickness and fractional thickening. We obtained the ranges of healthy biomechanical indices of 1.60 ± 0.22 kPa for left ventricular stiffness and 95.13 ± 14.56 kPa for left ventricular contractility. These reference normal values can be used for future model-based investigation on the stiffness and contractility of ischemic myocardium.

4D-CT Hyper-Elastography Using a Biomechanical Model.

Low dose computed tomography (LDCT) is the current gold-standard for lung cancer diagnosis. However, accuracy of diagnosis is limited by the radiologist's ability to discern cancerous from non-cancerous nodules. To assist with diagnoses, a 4D-CT lung elastography method is proposed to distinguish nodules based on tissue stiffness properties. The technique relies on a patient-specific inverse finite element (FE) model of the lung solved using an optimization algorithm. The FE model incorporates hyperelastic material properties for tumor and healthy regions and was deformed according to respiration physiology. The tumor hyperelastic parameters and trans-pulmonary pressure were estimated using an optimization algorithm that maximizes similarity between the actual and simulated tumor and lung image data. The proposed technique was evaluated using an in-silico study where the lung tumor elastic properties were assumed. Following that evaluation, the technique was applied to clinical 4D-CT data of two lung cancer patients. Results from the evaluation study show that the elastography technique recovered known tumor parameters with only 6% error. Tumor hyperelastic properties from the clinical data are also reported. Results from this proof of concept study demonstrate the ability to perform lung elastography with 4D-CT data alone. Advancements in the technique could lead to improved diagnoses and timely treatment of lung cancer.

Biomechanical properties of the rat sclera obtained with inverse finite element modeling.

It is widely accepted that biomechanics plays an important role in glaucoma pathophysiology, but the mechanisms involved are largely unknown. Rats are a common animal model of glaucoma, and finite element models are being developed to provide much-needed insight into the biomechanical environment of the posterior rat eye. However, material properties of rat ocular tissues, including the sclera, are currently unknown. Since the sclera plays a major role in posterior ocular biomechanics, our goal was to use inverse finite element modeling to extract rat scleral material properties. We first used digital image correlation to measure scleral surface displacement during whole-globe inflation testing. We modeled the sclera as a nonlinear material with embedded collagen fibers and then fit modeled displacements to experimental data using a differential evolution algorithm. Subject-specific models were constructed in which 3 parameters described the stiffness of the ground substance and collagen fibers in the posterior eye, and 16 parameters defined the primary orientation and alignment of fibers within eight scleral sub-regions. We successfully extracted scleral material properties for eight rat eyes. Model displacements recreated general patterns of the experimental displacements but did not always match local patterns. The fiber directions and fiber concentration parameters were highly variable, but on average, fibers were aligned circumferentially and were more aligned in the peripapillary sclera than in the peripheral sclera. The material properties determined here will be used to inform future finite element models of the rat posterior eye with the goal of elucidating the role of biomechanics in glaucoma pathophysiology.

Damage quantification in foam core sandwich composites via finite element model updating and artificial neural networks

The main idea of this paper is to propose a nondestructive evaluation (NDE) system for two types of damages, core cracking and skin/core debonding, in fiberglass/foam core sandwich structures based on the inverse eigensensitivity-based finite element model updating using the modal test results, and the artificial neural networks. First, the modal testing was conducted on the fabricated fiberglass/foam core sandwich specimens, in the intact and damaged states, and the natural frequencies were extracted. Finite element modeling and inverse eigensensitivity-based model updating of the intact and damaged sandwich structures were conducted and the parameters of the models were identified. Afterward, the updated finite element models were employed to generate a large dataset of the first five harmonic frequencies of the damaged sandwich structures with different damage sizes and locations. This dataset was adopted to train the machine learning models for detection, localization, and size estimation of the core cracking and skin/core debonding damages. A multilayer perceptron neural network classification model was used for detection of types of damages and also a multilayer perceptron neural network regression model was fitted to the dataset for automatically estimation of the locations and dimensions of damages. This intelligent system of damage quantification was also used to make predictions on real damaged specimens not seen by the system. The results indicated that the extracted natural frequencies from the accurate finite element model, in coordination with the experimental data, and using the artificial neural networks can provide an effective system for nondestructive evaluation of foam core sandwich structures.

Combining Freehand Ultrasound-Based Indentation and Inverse Finite Element Modeling for the Identification of Hyperelastic Material Properties of Thigh Soft Tissues.

Finite element analysis (FEA) is a numerical modeling tool vastly employed in research facilities to analyze and predict load transmission between the human body and a medical device, such as a prosthesis or an exoskeleton. Yet, the use of finite element modeling (FEM) in a framework compatible with clinical constraints is hindered by, among others, heavy and time-consuming assessments of material properties. Ultrasound (U.S.) imaging opens new and unique opportunities for the assessment of in vivo material properties of soft tissues. Confident of these advances, a method combining a freehand U.S. probe and a force sensor was developed in order to compute the hyperelastic constitutive parameters of the soft tissues of the thigh in both relaxed (R) and contracted (C) muscles' configurations. Seven asymptomatic subjects were included for the experiment. Two operators in each configuration performed the acquisitions. Inverse FEM allowed for the optimization of an Ogden's hyperelastic constitutive model of soft tissues of the thigh in large displacement. The mean shear modulus identified for configurations R and C was, respectively, 3.2 ± 1.3 kPa and 13.7 ± 6.5 kPa. The mean alpha parameter identified for configurations R and C was, respectively, 10 ± 1 and 9 ± 4. An analysis of variance showed that the configuration had an effect on constitutive parameters but not on the operator.