High-resolution Finite Element Models Research Articles

Mercury cycling in contaminated coastal environments: modeling the benthic-pelagic coupling and microbial resistance in the Venice Lagoon

Anthropogenic activities have been releasing mercury for centuries, and despite global efforts to control emissions, concentrations in environmental media remain high. Coastal sediments can be a long-term repository for mercury, but also a secondary source, and competing processes in marine ecosystems can lead to the conversion of mercury into the toxic and bioaccumulative species methylmercury, which threatens ecosystem and human health. We investigate the fate and transport of three mercury species in a coastal lagoon affected by historical pollution using a novel high-resolution finite element model that integrates mercury biogeochemistry, sediment dynamics and hydrodynamics. The model resolves mercury dynamics in the seawater and the seabed taking into account partitioning, transport driven by water and sediment, and photochemical and microbial transformations. We simulated three years (early 2000s, 2019, and 2020) to assess the spatio-temporal distribution of mercury species concentrations and performed a sensitivity analysis to account for uncertainties. The modeled mercury species concentrations show high temporal and spatial variability, with water concentrations in some areas of the lagoon exceeding those of the open Mediterranean Sea by two orders of magnitude, consistent with available observations from the early 2000s. The results support conclusions about the importance of different processes in shaping the environmental gradients of mercury species. Due to the past accumulation of mercury in the lagoon sediments, inorganic mercury in the water is closely related to the resuspension of contaminated sediments, which is significantly reduced by the presence of benthic vegetation. The gradients of methylmercury depend on the combination of several factors, of which sediment resuspension and mercury methylation are the most relevant. The results add insights into mercury dynamics at coastal sites characterized by a combination of past pollution (i.e. sediment enrichment) and erosive processes, and suggest possible nature-based mitigation strategies such as the preservation of the integrity of benthic vegetation and morphology.

A corrugated steel fender for bridge pier protection against truck collision

This study proposes a novel corrugated steel fender system to protect bridge piers against truck collisions. In particular, the impact energy is mainly absorbed through the deformation of corrugated steel webs in the fender. Pendulum impact tests are conducted to demonstrate the benefits of installing the corrugated steel web to increase the fender stiffness, engage more lateral displacement, and dissipate considerable impact energy. Advanced finite element (FE) models are established using the software LS-DYNA and verified against experimental results of the pendulum impact test. Modeling considerations are implemented into developing a high-resolution FE model to simulate full-scale truck–fender–bridge collisions, which discloses the fender’s effectiveness in protecting the bridge pier. The proposed fender system can mitigate the post-impact damage to the bridge pier by reducing its peak impact force, lateral displacement, and bending moment at the base. Moreover, parametric analyses are performed to investigate the effects of different fender design variables on the peak impact force and absorbed impact energy. Among various design parameters, the thicknesses of the corrugated steel web and surface steel plate are the predominant ones. Finally, an optimal fender design criteria is proposed to simultaneously minimize the impact damage to the bridge pier and the truck.

Solitary wave-based site-specific bone quality assessment: A numerical study of the proximal femur

We examine numerically the feasibility of using a relatively new solitary wave-based non-destructive test (NDT) method for site-specific bone quality assessment. Towards this end, we present numerical predictions of the effective elastic modulus of trabecular bone in the proximal femur using highly nonlinear solitary waves (HNSWs) propagating in a one-dimensional chain of spherical steel particles. A computational bone reconstruction technique, enabled through topology optimization, is developed to generate high-resolution finite-element models representing the complex architecture of the trabecular network in the femoral neck region of the proximal femur. The reconstructed bone microstructure models are then used as the inspection medium in a virtual NDT setup in the form of a hybrid discrete-element/finite-element (DE/FE) model, capable of simulating the propagation of HNSWs in the granular chain and their interaction with the bone microstructures. By inserting a face sheet between the granular chain and the porous trabecular bone model, our calculations evince that dynamic loading by the incident solitary wave results in nearly uniaxial deformation of the bone microstructure (rather than localized contact indentations), and this is shown to enhance the accuracy and reliability of the solitary wave-based prediction of the bone’s effective elastic modulus. Using the delay of the primary reflected solitary wave in the estimation of the elastic modulus of bone, we are able to estimate the effective elastic moduli of the porous bone models with adequate accuracy. Based on these numerical findings, we believe that solitary wave-based non-destructive evaluation of computationally reconstructed artificial bone models could form the baseline for advanced bone quality assessment tools.

Probabilistic impact fragility analysis of bridges under Barge collision and local scour

Vessel collision is a common cause of structural failure to bridges crossing navigable waterways. Although numerous efforts focus on the safety evaluation of bridge structures under vessel impact, very few jointly consider a more threatening situation that involves a scoured bridge colliding with a vessel (e.g., a barge). In this work, an impact fragility analysis (IFA) process is proposed to understand a bridge's failure probability under the combined hazards. To achieve high-fidelity modeling of material behavior during the collision process, scaled pier-foundation models subjected to pendulum impacts are experimentally studied. Nonlinear material models and an explicit dynamic simulation procedure are verified, which are further adopted to develop a high-resolution finite-element model for a full-scale three-span bridge. The resulting impact-fragility models conditional upon impact velocities at different scour depths reveal essential insights into the failure modes of the bridge. The findings include that: (1) scour has a minor effect on the probability of slight and moderate damage at various impact velocities; (2) at a high impact velocity (when higher than an impact fragility velocity threshold), scour can significantly increase the probability of major damage and collapse; (3) barge-tonnage has a significant influence on the threshold value reflecting the significant scour effects.

Targeting bladder function with network-specific epidural stimulation after chronic spinal cord injury

Profound dysfunctional reorganization of spinal networks and extensive loss of functional continuity after spinal cord injury (SCI) has not precluded individuals from achieving coordinated voluntary activity and gaining multi-systemic autonomic control. Bladder function is enhanced by approaches, such as spinal cord epidural stimulation (scES) that modulates and strengthens spared circuitry, even in cases of clinically complete SCI. It is unknown whether scES parameters specifically configured for modulating the activity of the lower urinary tract (LUT) could improve both bladder storage and emptying. Functional bladder mapping studies, conducted during filling cystometry, identified specific scES parameters that improved bladder compliance, while maintaining stable blood pressure, and enabled the initiation of voiding in seven individuals with motor complete SCI. Using high-resolution magnetic resonance imaging and finite element modeling, specific neuroanatomical structures responsible for modulating bladder function were identified and plotted as heat maps. Data from this pilot clinical trial indicate that scES neuromodulation that targets bladder compliance reduces incidences of urinary incontinence and provides a means for mitigating autonomic dysreflexia associated with bladder distention. The ability to initiate voiding with targeted scES is a key step towards regaining volitional control of LUT function, advancing the application and adaptability of scES for autonomic function.

Order-Reduced Modeling-Based Multi-Level Damage Identification Using Piezoelectric Impedance Measurement

Identifying small-sized damage in early state is an important subject in structural health monitoring (SHM) field. Despite the success of inverse model updating analysis for damage identification practice, the critical challenge remains. The capture of small-sized damage requires high-resolution finite element (FE) model, resulting in a high-dimensional model updating problem without the prior knowledge. This is computationally intractable. In this research, we develop a multi-level scheme to conduct damage identification, which circumvents the curse of dimensionality. To facilitate the damage identification, the piezoelectric impedance that is sensitive to the small-sized damage is utilized and a large-scale electromechanical FE model is constructed accordingly to predict the impedance response. Based upon the full-scale FE model, an order-reduced modeling approach is developed and integrated into the model updating framework to expedite the analysis. Multi-objective simulated annealing (MOSA) optimization algorithm is employed to direct the model updating through minimizing the discrepancy between the impedance prediction and measurement. The case studies are carried out to illustrate the effectiveness of proposed methodology.

Performance assessment of deteriorating reinforced concrete drainage culverts: A case study

Rectangular reinforced concrete (RC) culverts are widely used in drainage systems of many megacities, which may experience significant deterioration due to the corrosive sewage environment. How to assess the performance of existing RC culverts is crucial to the public safety. Currently, very few studies have been reported on the assessment of the performance of deteriorating RC culverts which are in service. This paper reports the research work on the performance assessment of a drainage culvert in Shanghai, China, which is one of the most populous megacities in the world. Field investigations are first conducted to examine the deterioration of drainage culverts in the real world. The deterioration of the culvert is modeled through a stochastic model, which is calibrated based on field investigation data. The performance of the culvert is then examined through the local design code, which seems to be overconservative for ultimate bearing capacity assessment. To avoid the conservative assumptions in the design code method, a high-resolution finite element model is built to assess the performance of the culvert. During the assessment process, the uncertainty associated with the deterioration is also considered. Based on the findings from the research, recommendations are made regarding the maintenance of the drainage culverts. The research reported in this paper may also provide useful reference for assessing the performance of deteriorating culverts in other regions of the world.

Sodium channels and the intercalated disk - it is all about location, location, location.

Sodium channels and the intercalated disk - it is all about location, location, location.

Predictions of the elastic modulus of trabecular bone in the femoral head and the intertrochanter: a solitary wave-based approach.

This paper deals with the numerical prediction of the elastic modulus of trabecular bone in the femoral head (FH) and the intertrochanteric (IT) region via site-specific bone quality assessment using solitary waves in a one-dimensional granular chain. For accurate evaluation of bone quality, high-resolution finite element models of bone microstructures in both FH and IT are generated using a topology optimization-based bone microstructure reconstruction scheme. A hybrid discrete element/finite element (DE/FE) model is then developed to study the interaction of highly nonlinear solitary waves in a granular chain with the generated bone microstructures. For more robust and reliable prediction of the bone's mechanical properties, a face sheet is placed at the interface between the last chain particle and thebone microstructure, allowing more bone volume to be engaged in the dynamic deformation during interaction with the solitary wave. The hybrid DE/FE model was used to predict the elastic modulus of the IT and FH by analysing the characteristic features of the two primary reflected solitary waves. It was found that the solitary wave interaction is highly sensitive to the elastic modulus of the bone microstructure and can be used to identify differences in bone density. Moreover, it was found that the use of a relatively stiff face sheet significantly reduces the sensitivity of the wave interaction to local stiffness variations across the test surface of the bone, thereby enhancing the robustness and reliability of the proposed method. We also studied the effect of the face sheet thickness on the characteristics of the reflected solitary waves and found that the optimal thickness that minimizes the error in the modulus predictions is 4mm for the FH and 2mm for the IT, if the primary reflected solitary wave is considered in the evaluation process. We envisage that the proposed diagnostic scheme, in conjunction with 3D-printed high-resolution bone models of an actual patient, could provide a viable solution to current limitations in site-specific bone quality assessment.

Combined Machine-Learning and Finite-Element Approach for Multiscale 3D Stress Modeling

SummaryIn this paper, we propose a methodology that combines finite-element modeling with neural networks in the numerical modeling of systems with behavior that involves a wide span of spatial scales.The method starts by constructing a high-resolution model of the subsurface, including its elastic mechanical properties and pore pressures. A second model is also constructed by scaling up mechanical properties and pressures into a coarse spatial resolution. Inexpensive finite-element solutions for stress are then obtained in the coarse model. These stress solutions aim at capturing regional trends and large-scale stress correlations. Finite-element solutions for stress are also obtained in high resolution, but only in a small subvolume of the 3D model. These stress solutions aim at estimating fine-grained details of the stress field introduced by the heterogeneity of rock properties at the fine scale.A neural network is then trained to infer the transformation rules that map stress solutions between different scales. The inputs to the training are pressure and mechanical properties in high and low resolutions. The output is the fine-scale stress computed in the subvolume of the high-resolution model.Once trained, the neural network can be used to approximate a high-resolution stress field in the entire 3D volume using the coarse-scale solution and only providing high-resolution material properties and pressures.The results obtained indicate that when the coarse finite-element solutions are combined with the neural-network estimates, the results are within a 2 to 4% error of the results that would be computed with high-resolution finite-element models, but at a fraction of the cost in time and computational resources. This paper discusses the benefits and drawbacks of the method and illustrates its applicability by means of a worked example.

Inter-episodes earthquake migration in the Bohai-Zhangjiakou Fault Zone, North China: Insights from numerical modeling.

In this paper, we focus on why intraplate seismic initiation and migration occurs, which has widely been considered to be caused by static stress triggering caused by earthquakes, as well as post-seismic slips. To illustrate the mechanism underlying large earthquakes, in particular the migration caused by two key episodes that occurred after 1500 in the Bohai-Zhangjiakou Fault Zone (BZFZ) of North China, we developed a high-resolution three-dimensional viscoelastic finite element model that includes the active faults with vertical segmentation, their periodical locking, and the lithosphere heterogeneity. We used the birth and death of element groups to simulate stress intensity changes during the two episodes (named Episode I and II), with our results showing that the Tangshan earthquake was primarily triggered by the Sanhe-Pinggu M8.0 earthquake in 1679, whereas the Zhangbei M6.2 earthquake in 1998 was not triggered by earthquakes in Episode I. According to our work, the calculated stress changes in the different segments of the fault zone correspond to the magnitude of the triggered earthquakes. Further, the largest stress decrease was near the Sanhe-Pinggu fault and occurred the largest earthquake in Episode I, whereas the largest stress increase was near the Tangshan fault and occurred during the largest earthquake in Episode II. Given the above, we propose a model for seismic migration to describe the dynamic mechanisms of earthquake migration within the BZFZ and North China, in which the factors affecting both the seismic migration path and intensity primarily include the distance between the triggered active fault and the original fault, the coupling of the active faults, the location and scale of the low-velocity anomaly, its distance from the active fault, and the location and scale of the crustal thinning.

The Role of Vertebral Porosity and Implant Loading Mode on Bone-Tissue Stress in the Human Vertebral Body Following Lumbar Total Disc Arthroplasty.

Micro-computed tomography- (micro-CT-) based finite element analysis of cadaveric human lumbar vertebrae virtually implanted with total disc arthroplasty (TDA) implants. (1) Assess the relationship between vertebral porosity and maximum levels of bone-tissue stress following TDA; (2) determine whether the implant's loading mode (axial compression vs. sagittal bending) alters the relationship between vertebral porosity and bone-tissue stress. Implant subsidence may be related to the bone biomechanics in the underlying vertebral body, which are poorly understood. For example, it remains unclear how the stresses that develop in the supporting bone tissue depend on the implant's loading mode or on typical inter-individual variations in vertebral morphology. Data from micro-CT scans from 12 human lumbar vertebrae (8 males, 4 females; 51-89 years of age; bone volume fraction [BV/TV] = 0.060-0.145) were used to construct high-resolution finite element models (37 μm element edge length) comprising disc-vertebra-implant motion segments. Implants were loaded to 800 N of force in axial compression, flexion-, and extension-induced impingement. For comparison, the same net loads were applied via an intact disc without an implant. Linear regression was used to assess the relationship between BV/TV, loading mode, and the specimen-specific change in stress caused by implantation. The increase in maximum bone-tissue stress caused by implantation depended on loading mode (P < 0.001), increasing more in bending-induced impingement than axial compression (for the same applied force). The change in maximum stress was significantly associated with BV/TV (P = 0.002): higher porosity vertebrae experienced a disproportionate increase in stress compared with lower porosity vertebrae. There was a significant interaction between loading mode and BV/TV (P = 0.002), indicating that loading mode altered the relationship between BV/TV and the change in maximum bone-tissue stress. Typically-sized TDA implants disproportionately increase the bone-tissue stress in more porous vertebrae; this affect is accentuated when the implant impinges in sagittal bending.Level of Evidence: N/A.

Statistical analysis of the crack sensitivity of fiber networks

Fracturing two-dimensional random fiber networks of different densities (porosities) were statistically analyzed using both high-resolution finite element models and image analysis algorithms. Under small strains, the finite element fracture models revealed that networks with high relative densities were able to localize evolving fractures to small cracks while surprisingly larger cracks were required to localize fractures in networks of lower density. Further, it is indicated that the pore size distribution in fiber networks is rather diverse and can be captured using two mixed Gamma distributions; one part describing the background size distribution containing the vast majority of pores, and a second part describing the size distribution of larger pores and open regions. The second part covers less than 5% of the total network area but seems to be of paramount importance for the network’s global fracture behavior. It seems as a fiber network’s crack sensitivity is related to the average pore size in the second part of the mixed Gamma distribution. The analysis is remarkably consistent with reported experiments.

Parametric Investigation of the Effects of Localization and Slenderness on the Stress–Strain Response and Confinement Efficiency in FRP-Wrapped Concrete Cylinders

In order to improve the efficiency of fiber reinforced plastics (FRP) confinement as a method to repair and strengthen concrete structures, a parametric analysis was carried out to investigate the effects of cylinder slenderness and the stiffness of the confinement on the localization pattern, the stress–strain response and the effectiveness of the confinement. FRP-wrapped concrete cylinders under axial compression were modeled in a high-resolution finite element model. Concrete was modeled as a Mohr–Coulomb material. The bi-linear stress–strain structural responses concur with published experimental data. Localization along discrete shear planes results in a failure mechanism that causes non-uniform hoop stresses in the FRP wrap due to the movement of solid wedges in the mechanism. A characteristic length for localization was identified and found in agreement with published experimental observations. The confinement efficiency shows a clear dependence on the confinement level and a weak dependence on slenderness above the characteristic length. A simple mechanistic model is proposed for the second branch of the bi-linear stress–strain response curve. The results of this study can be used to estimate the confinement efficiency factor and refine the design recommendations of Equation 12.1 of ACI 440.2R17.

Numerical predictions of the interaction between highly nonlinear solitary waves and the microstructure of trabecular bone in the femoral head

The unique properties of highly nonlinear solitary waves in granular chains have prompted extensive research in the area of non-destructive testing and led to the development of new diagnostic schemes with potential applications in the healthcare industry. Here, we study numerically the interaction between highly nonlinear solitary waves in a granular chain and the microstructure of trabecular bone in the femoral head. High-resolution finite element models of bone microstructures with varying bone volume fraction are generated using a topology optimization-based bone microstructure reconstruction scheme. The obtained FE models of the trabecular bone were then used to develop a hybrid discrete/finite element model able to simulate the propagation of highly nonlinear solitary waves in a vertical array of steel particles, and their interaction with the adjacent bone microstructure model was studied. Two test modes were considered, one where the granular chain was placed in direct contact with the bone microstructure model, while in the second test mode, a face sheet was included between the chain and the bone model. For both test modes, we found that the characteristic features of the reflected solitary waves are sensitive to the effective compressive modulus of the bone microstructure models and follow similar trends than those obtained for a homogeneous, non-porous solid. It was also found that the use of the face sheet substantially reduces the sensitivity of the predictions to small changes in the bone topology, making it a robust and reliable method for non-destructive evaluation of the effective elastic modulus of cellular materials with small structural dimensions, as it is required for the site-specific evaluation of the mechanical properties of trabecular bone.

Simulating fracture in a wood microstructure using a high-resolution dynamic phase field model

As a simplified model, wood can be considered as consisting of hollow cells held together by a weaker middle lamella. We use a high-resolution finite element model, endowed with a phase field model for brittle fracture to model such a structure. The micro-structured discretised materials, with and without middle lamella, differ significantly from a homogenous continuum reference in terms of damage patterns. There is also significant difference between the models with and without middle lamella, since damage localises in the weaker middle lamella, which underlines the importance to include the middle lamella in mechanical analyses. At increased loading velocity, the damage becomes scattered over a larger region ahead of the crack tip, indicating that dynamic effects affect the crack behaviour and that dynamics need to be taken into consideration when loading rates are high or when crack propagation is unstable.

High-resolution 3D weld toe stress analysis and ACPD method for weld toe fatigue crack initiation

Weld toe fatigue crack initiation is highly dependent on the local weld toe stress-concentrating geometry including any inherent flaws. These flaws are responsible for premature fatigue crack initiation (FCI) and must be minimised to maximise the fatigue life of a welded joint. In this work, a data-rich methodology has been developed to capture the true weld toe geometry and resulting local weld toe stress-field and relate this to the FCI life of a steel arc-welded joint. To obtain FCI lives, interrupted fatigue test was performed on the welded joint monitored by a novel multi-probe array of alternating current potential drop (ACPD) probes across the weld toe. This setup enabled the FCI sites to be located and the FCI life to be determined and gave an indication of early fatigue crack propagation rates. To understand fully the local weld toe stress-field, high-resolution (5 μm) 3D linear-elastic finite element (FE) models were generated from X-ray micro-computed tomography (μ-CT) of each weld toe after fatigue testing. From these models, approximately 202 stress concentration factors (SCFs) were computed for every 1 mm of weld toe. These two novel methodologies successfully link to provide an assessment of the weld quality and this is correlated with the fatigue performance.

Unsupervised machine learning based on non-negative tensor factorization for analyzing reactive-mixing

Analysis of reactive-diffusion simulations representing complex mixing processes requires a large number of independent model runs. For each high-fidelity model simulation, the model inputs are varied and the predicted mixing behavior is represented by temporal and spatial changes in species concentration. It is then required to discern how the model inputs (such as diffusivity, dispersion, anisotropy, and velocity field properties) impact the mixing process. This task is challenging and typically involves interpretation of large model outputs representing temporal and spatial changes of species concentration within the model domain. However, the task can be automated and substantially simplified by applying Machine Learning (ML) methods. In this paper, we present an application of an unsupervised ML method (called NTFk) using Non-negative Tensor Factorization (NTF) coupled with a custom clustering procedure based on k-means to reveal the temporal and spatial features in product concentrations. An attractive and unique aspect of the proposed ML method is that it ensures the extracted features are non-negative, which is important to obtain a meaningful deconstruction of the mixing processes. The ML methodology is applied to a large set of high-resolution finite-element model simulations representing anisotropic reaction-diffusion processes in perturbed vortex-based velocity fields. The applied finite-element method ensures that spatial and temporal species concentration are always non-negative, even in the case of high anisotropic contrasts. The simulated reaction is a fast irreversible bimolecular reaction A+B→C, where species A and B react to form species C. The reactive-diffusion model input parameters that control mixing include properties of the velocity field (such as vortex structures), anisotropic dispersion, and molecular diffusion. We demonstrate the applicability of the ML feature extraction method to produce a meaningful deconstruction of model outputs to discriminate between different physical processes impacting the reactants, their mixing, and the spatial distribution of the product C. The presented ML analysis allowed us to identify additive temporal and spatial features that characterize mixing behavior. The application of the proposed NTFk approach is not limited to reactive-mixing. NTFk can be readily applied to any observed or simulated datasets that can be represented as tensors (multi-dimensional arrays) and have separable latent signatures or features.

Construction and validation of a high resolution finite element model of the Japanese koto

The Japanese koto is recognized for its complex resonances, but few studies have been conducted to understand its acoustic properties. This paper presents a COMSOL Multiphysics finite element model of a hand-crafted, professional-grade Japanese koto. To do this, the complex internal and external geometry was captured on 2400 CAT scan cross-sections and imported into Comsol. The model was validated by reference to literature data, Chladni patterns, frequency response experiments, acoustic camera and laser scanning vibrometer studies. These results were then compared to the sound as played on the actual instrument. Challenges in the model’s development arising from the materials and construction of the instrument are discussed, most notably the anisotropic nature of the paulownia wood including multiple grain orientations used in its construction and the added complexity of modeling the organic shape of the real, hand-crafted 1.83 m long instrument with its major internal variations. These developments were guided by parallel studies in less intractable geometry such as simpler box models or models with idealized geometrical shapes lofted along a spline. The CAT scan derived model is used as a quasi-experimental tool to investigate the effect of internal components of the koto on its resonances and results presented.The Japanese koto is recognized for its complex resonances, but few studies have been conducted to understand its acoustic properties. This paper presents a COMSOL Multiphysics finite element model of a hand-crafted, professional-grade Japanese koto. To do this, the complex internal and external geometry was captured on 2400 CAT scan cross-sections and imported into Comsol. The model was validated by reference to literature data, Chladni patterns, frequency response experiments, acoustic camera and laser scanning vibrometer studies. These results were then compared to the sound as played on the actual instrument. Challenges in the model’s development arising from the materials and construction of the instrument are discussed, most notably the anisotropic nature of the paulownia wood including multiple grain orientations used in its construction and the added complexity of modeling the organic shape of the real, hand-crafted 1.83 m long instrument with its major internal variations. These developments were...

High-resolution finite element modeling for bond in high-strength concrete beam

This study presents a physics-based rib-scale finite element (FE) model to study bond-zone behavior for spliced longitudinal bars in reinforced concrete beams subjected to monotonically increasing loading. In this model, a high-resolution mesh is used in the vicinity of the bar-concrete interface to capture the geometry of the ribs on the reinforcing steel. At the concrete-bar interface, a contact formulation that properly represents normal and frictional force transfer is used; adhesion between concrete and steel is ignored. The FE model is calibrated using data from beam splice tests performed by Ramirez and Russell [1]. It is observed that concrete tensile strength and tangential friction at the concrete-steel interface determine simulated response; these quantities are calibrated to provide accurate simulation of experimental results. The calibrated model provides results in good agreement with test data. Load-displacement response as well as concrete crack patterns are accurately simulated, and the proposed model can distinguish between the behavior of uncoated and epoxy-coated deformed bars as well as simulate the impact on bond strength of confinement provided by transverse steel.