A systematic comparison between FEBio and PolyFEM for biomechanical systems

A mitral valve reconstruction (MVR) is a complex operation in which the functionality of incompetent mitral valves is re-established by applying surgical techniques. This work deals with predictive biomechanical simulations of operation scenarios for an MVR, and the simulation's integration into a knowledge-based surgery assistance system. We present a framework for the definition of the corresponding surgical workflow, which combines semantically enriched surgical expert knowledge with a biomechanical simulation. Using an ontology, 'surgical rules' which describe decision and assessment criteria for surgical decision-making are represented in a knowledge base. Through reasoning these 'rules' can then be applied on patient-specific data in order to be converted into boundary conditions for the biomechanical soft tissue simulation, which is based on the Finite Elements Method (FEM). The simulation, which is implemented in the open-source C++ FEM software HiFlow3, is controlled via the Medical Simulation Markup Language (MSML), and makes use of High Performance Computing (HPC) methods to cope with real-time requirements in surgery. The simulation results are presented to surgeons to assess the quality of the virtual reconstruction and the consequential remedial effects on the mitral valve and its functionality. The whole setup has the potential to support the intraoperative decision-making process during MVR where the surgeon usually has to make fundamental decision under time pressure.

The coupled thermo-mechanical field analysis of TSV interposer is a typical multiscale simulation problem, it faces great difficulty of numerous TSVs and complex micro structures. To get balance between accuracy and efficiency, global/local finite element (GLFE) strategy often be used in the multiscale coupled field analysis. In steps of the GLFE strategy, global coarse mesh evaluation plays the key role and the mesh model of this step determines the calculation effect. Currently, finite element modeling for TSV interposer is mostly finished manually with the help of comprehensive finite element software. To improve the laboriously and time-consuming manual modeling procedures, a finite element modeling method specifically oriented for TSV interposer is proposed. The modeling method is an imitation of fabrication procedures, it consists of layer based geometry modeling, parametric meshing, automatic contact detection, automatic boundary condition building and automatic loading processes. TSV discretization methods affected the quality of the mesh model directly, 4 kinds of TSV discretization methods are proposed in this paper, namely: Fine Mesh Method, Single Point Method, Single Mesh Method and Equivalent Model Method, they reach different equilibrium points on model size and accuracy, feeding need of different simulation scenarios. As the implementation of the modeling method a SAAS cloud system is built, the system run in B/S mode and it can make the modeling procedures easier. Finally, with the help of the modeling method and the SAAS cloud system, a thermo-mechanical analysis of TSV interposer based 2.5D RF module is done. The comparison of the time consumption and results with comprehensive finite element software ANSYS Workbench indicates that the cloud system can get great efficiency with enough accuracy.

The objective of this study was to evaluate static and dynamic results on the foot pressure measurement and computer simulation for diabetes mellitus patients. The finite element analysis was used to compare with pressure foot measurement. The foot and ankle model consisted of 28 bony segments is created from DICOM CT slice from specific patient with diabetes mellitus diagnosis. All material properties are considered as homogeneous, isotropic and linearly elastic. Foot pressure measurement for both static and dynamic condition gave topographic distribution of high pressure points which is in correlation with clinical tests results. The result for maximum pressure measurement of the left foot 124.74 kPa is in good comparison with finite element results for 121 kPa. It looks that numerical simulation in combination with foot pressure measurement device can be efficient and inexpensive screening tool, which could go in direction for prevention of the diabetic foot complications, associated with high mortality and morbidity that has significant economic impact on healthcare system.

Presented is a detailed case study on structural Finite Element (FE) modeling and Modal Pushover Analysis (MPA) of a 14-story office building instrumented for seismic response investigation. The system identification tool was used to identify the structural dynamic properties, including the natural periods of vibration of the structure and level of critical damping based on seismic data recorded during small seismic ground motions. A series of FE models were created to improve the modeling technique. The final corrected FE model was refined and calibrated to match the identified structural natural periods. It was found that a FE model can be calibrated to give a good prediction of earthquake response. Using the calibrated FE model, the structural seismic behavior has been examined using the MPA procedure. In the MPA procedure, an improved analysis based on structural dynamic theory with invariant force distributions was used to generate the push loads. Four recorded ground acceleration time histories were used as input data for the MPA procedure. Five sets of push forces, corresponding to the effective earthquake forces from the first five modal expansions, were applied to the FE model. The final MPA results were combined from these five push-over cases using the Square-Root-of-Sum-of-Squares (SRSS) rule and the Complete Quadratic Combination (CQC) rule to get the total response. The MPA results were also compared with the Incremental Dynamic Analysis (IDA). It is found that the MPA and IDA results are reasonably matched. The MPA procedure is an improved tool for estimating seismic demands on buildings. Using the MPA procedure, the structural behavior can be examined during seismic loading and future performance of the building during damaging earthquakes can be predicted.

In shelf regions with steep bathymetry in the presence of density gradients, the computation of the baroclinic pressure gradient term in 3D shallow water models may either become unstable or physically unrealistic. This manuscript examines four algorithms to compute the baroclinic pressure gradient term in finite element models. Two common systems for discretizing the vertical are sigma or zlevel coordinates. In turn, permutations of these two coordinate systems serve as the basis for the four different algorithms examined herein. All are implemented in the context of the finite element hydrodynamic model, ADCIRC. Several density gradients that vary horizontally and vertically, with the pycnocline occurring at different depths, are used to evaluate the methods in a three-dimensional box grid with variable bathymetry. Initial testing, the subject of this work, focuses on model behavior for simplified problem with known analytic solutions. Long term goals for this study (the subject of subsequent papers) are three-fold: 1) to determine the vertical node placement algorithm that produces the most stable and physically realistic results; 2) to determine the interplay of vertical and horizontal resolution (and bathymetry and density profile), while considering simulation time; and 3) to produce accurate 3D flow fields and baroclinic pressure gradients. Outcomes from the study will be used to direct on-going modeling research in the Mississippi Sound. Introduction Background An accurate prediction of tides and circulation patterns using hydrodynamic models is useful in a wide variety of civilian and military applications that range 1. School of Civil Engineering and Environmental Science, 202 W. Boyd, Room 334, University of Oklahoma, Norman, OK, 73019, USA, dresback@ou.edu, kolar@ou.edu 2. Oceanography Division, Code 7322, Naval Research Laboratory, Stennis Space Center, MS, 39529, USA, blain@nrlssc.navy.mil 2 Dresback, Blain and Kolar from forecasting storm surges from extreme events, such as tsunamis and hurricanes, in order to plan development in coastal areas to predicting circulation patterns in order to guide fleet operations. Moreover, the accuracy of water quality models depends heavily on an accurate, robust hydrodynamic model. One class of models that finds frequent use for these and other applications are the so-called shallow water models. Shallow water equations in 2D are obtained by vertically averaging the mass and momentum balances over the depth of the fluid. For our applications, we solve the equations using algorithms amenable to irregular triangular meshes (e.g., finite element, finite volume). Such a meshing technique allows grids to be easily refined in shallow coastal areas or in areas with changing topography where high resolution is needed to accurately resolve tidal constituents and circulation patterns. Also irregular coastal boundaries are more accurately described with triangular elements, and flux-type boundary conditions enter the problem naturally. Models in this class include ADCIRC [16], QUODDY [22], and UTBEST [5]. Finite difference based models, such as SIMSYS2D[15], CH3D [4], and POM [30] that use a staggered grid on an orthogonal curvilinear mesh, are stable and mass conservative, but their grids are not as inherently flexible as those based on irregular triangular meshes [15, 29]. Early finite element solutions of the shallow water equations were often plagued by spurious oscillation modes. Various methods were introduced to eliminate the oscillations, but most include some type of artificial or numerical damping [27, 31]. Lynch and Gray [21] present the wave continuity equation as a means to eliminate spurious oscillations without resorting to artificial damping. It is currently the base algorithm in ADCIRC (ADvanced 3D CIRCulation model [16]), the model that is the subject of this research. Since the inception of the wave continuity formulation in 1979, the original algorithm has been modified in a number of substantial ways: Kinnmark introduced a numerical parameter to provide a general means of weighting the continuity equation [11]; viscous dissipation terms were incorporated [12, 20]; and 3D barotropic simulations were realized by resolving the velocity profile in the vertical [16, 25]. Most recently, the model has incorporated the following features: a wetting/drying algorithm for near-shore elements [17]; spherical coordinates for large domains via a map projection technique [13]; a parallel domain decomposition algorithm for the 2D portion of the code [26]; a fully implicit time marching algorithm [6]; options for hydraulic structures (e.g., levees, breakwaters); and a diagnostic baroclinic algorithm [18]. These advances are all present in the current version of the ADCIRC model, a model that represents over 20 years of research and development by scientists and engineers at six different institutions. ADCIRC has been extensively tested using analytical solutions and field data, and it is being used by a diverse group of researchers and practitioners to model the hydrodynamic behavior of many coastal and oceanic regions [2, 7, 8, 10, 23, 34].

Multichip Mechatronic Power Packages have been developed in Motorola for automotive applications. Copper heat sink-based metal substrates were used to improve thermal and electrical performance. In the early stage of development, mold delamination and die cracking have been observed after assembly. With some mold compound, die backside has large delaminated areas, while with other mold compound, delamination stops early but die cracks. Finite element analysis, incorporated with interface fracture mechanics method, was conducted to understand these phenomena. Impact of mold material properties and package geometry on post-assembly delamination was evaluated. Excellent agreements have been obtained between experimental data and the simulation results. The phenomenon of crack branching into the die was also studied. Finite element simulation can be used to predict whether and when the crack at the interface will turn and crack the die. With a thorough understanding of the failure mechanism, both mold delamination and die cracks have been eliminated completely in the final package development.

In the definition of Noll, a body is uniform if all points are made of the same material. As shown by Noll himself and by Epstein and Maugin, uniformity makes the Helmholtz free energy depend on the material point exclusively through a tensor field, called uniformity tensor or implant tensor or material isomorphism. Uniformity is therefore a particular case of inhomogeneity. In turn, uniformity includes homogeneity as a particular case: indeed, homogeneity is attained when the uniformity tensor happens to be integrable. This work focuses on the non-linear large-deformation behaviour of uniform dielectric elastomers. Building on the foundational works of Toupin, Eringen and others, this work integrates continuum mechanics with electrostatics to develop a finite element framework for analysing uniform dielectric elastomers. This framework allows for considering the inherent inhomogeneity in materials exhibiting non-linear electromechanical coupling such as electro-active polymers. The inhomogeneity is assumed to be self-driven, i.e., not implied by the second law of thermodynamics: rather, it depends on the torsion of the connection (covariant derivative) induced by the uniformity tensor. A MATLAB®-based finite element solver is developed and applied to the simulation of an electromechanical beam-type actuator. The solver is robust and capable of addressing various simulation scenarios. Numerical simulations demonstrate the significant impact of material uniformity on actuator performance. This research provides a tool for future applications in dielectric elastomers, particularly in sensors, actuators and bio-inspired robotics.

The knee is a biomechanically complex joint supported by multiple anatomical structures, making it vulnerable to multiple injuries. Finite element analysis is a valuable tool for studying joint biomechanics, particularly in pre-operative planning and injury evaluation. However, most models are based on computed tomography, which limits soft tissue visualization. Thus, a magnetic resonance imaging-based finite element model of the knee, incorporating bones, ligaments, tendons, cartilage, and menisci, was developed to improve realism and clinical relevance in biomechanical simulations. Magnetic resonance imaging data were obtained from a healthy adult male using a 1.5T scanner and processed using RETOMO and Rhinoceros software for 3D reconstruction and modeling. Meshes were cleaned, optimized, and anatomically validated. All major knee structures were modeled, including the femur, tibia, fibula, patella, cruciate and collateral ligaments, patellofemoral ligaments, quadriceps and patellar tendons, menisci, and articular cartilage. The resulting model reconstructed both hard and soft tissues of the knee joint with high anatomical fidelity, based on direct MRI segmentation and literature-supported anatomical definitions. The use of magnetic resonance imaging enabled high-resolution identification of soft tissues, while advanced mesh refinement preserved anatomical detail with optimized file management. The inclusion of structures like the anterolateral ligament and patellofemoral ligaments expands the model's clinical relevance in addressing a wider range of knee pathologies. This magnetic resonance imaging-based finite element analysis model provides a detailed and comprehensive, representation of the healthy human knee, including bones, cartilage, menisci, and tendons. While some ligament attachment points were derived from literature rather than MRI data, the model provides a foundation for future biomechanical studies, surgical planning and personalized treatment simulations.

On-field monitoring of head impacts, combined with finite element (FE) biomechanical simulation, allow for predictions of regional strain associated with a diagnosed concussion. However, attempts to correlate these predictions with in vivo measures of brain injury have not been published. This article reports an approach to and preliminary results from the correlation of subject-specific FE model-predicted regions of high strain associated with diagnosed concussion and diffusion tensor imaging to assess changes in white matter integrity in the corpus callosum (CC). Ten football and ice hockey players who wore instrumented helmets to record head impacts sustained during play completed high field magnetic resonance imaging preseason and within 10 days of a diagnosed concussion. The Dartmouth Subject-Specific FE Head model was used to generate regional predictions of strain and strain rate following each impact associated with concussion. Maps of change in fractional anisotropy (FA) and median diffusivity (MD) were generated for the CC of each athlete to correlate strain with change in FA and MD. Mean and maximum strain rate correlated with change in FA (Spearman ρ = 0.77, p = 0.01; 0.70, p = 0.031), and there was a similar trend for mean and maximum strain (0.56, p = 0.10; 0.6, p = 0.07), as well as for maximum strain with change in MD (-0.63, p = 0.07). Change in MD correlated with injury-to-imaging interval (ρ = -0.80, p = 0.006) but change in FA did not (ρ = 0.18, p = 0.62). These results provide preliminary confirmation that model-predicted strain and strain rate in the CC correlate with changes in indices of white matter integrity.

A statistical atlas based approach to automated subject-specific FE modeling

Background: Finite element (FE) analysis has shown promise for the evaluation of elastomeric foam personal protection devices. Although appropriate representation of foam materials is necessary in order to obtain realistic simulation results, material definitions used in the literature vary widely and often fail to account for the multi-mode loading experienced by these devices. This study aims to provide a library of elastomeric foam material parameters that can be used in FE simulations of complex loading scenarios. Method of Approach: Twelve foam materials used in footwear were tested in uni-axial compression, simple shear and volumetric compression. For each material, parameters for a common compressible hyperelastic material model used in FE analysis were determined using: (a) compression; (b) compression and shear data; and (c) data from all three tests. Results: Material parameters and Drucker stability limits for the best fits are provided with their associated errors. The material model was able to reproduce deformation modes for which data was provided during parameter determination but was unable to predict behavior in other deformation modes. Conclusions: Simulation results were found to be highly dependent on the extent of the test data used to determine the parameters in the material definition. This finding calls into question the many published results of simulations of complex loading that use foam material parameters obtained from a single mode of testing. The library of foam parameters developed here presents associated errors in three deformation modes that should provide for a more informed selection of material parameters.

A new spatial reasoning algorithm that can be used in multi‐body contact detection is presented. The algorithm achieves the partitioning of N bodies of arbitrary shape and size into N lists in order O(N) operations, where each list consists of bodies spatially near to the target object. The algorithm has been tested for objects of arbitrary shape and size, in two and three dimensions. However, we believe that it can be extended to dimensions of four and higher. The algorithm (CGRID) is a binning algorithm that extends traditional binning algorithms so that the arbitrary sizes and shapes can be handled efficiently. The algorithm has applications in discrete element, finite element, molecular dynamics, meshless methods, and lattice‐Boltzmann codes and also in domains such as path planning, target acquisition and general clustering problems.

ABSTRACT: The goal of this paper is to present recent developments aimed at improving computational efficiency and extending the range of material applicability of a 2D/3D FDEM geomechanical simulation software. Firstly, a hybrid FEM-FDEM logic was devised to allow for user-defined regions of the domain to be modeled as a continuum, while the remainder is captured by the FDEM formulation with an intrinsic cohesive zone model explicitly capturing fracturing. Benchmarking results indicate simulation speed-ups of up to 48x when using the new logic versus the traditional full FDEM approach. Secondly, the finite element formulation was enhanced with elasto-plastic constitutive models based on Drucker-Prager and Mohr-Coulomb failure criteria, effectively broadening the range of applicability to materials that exhibit irreversible damage processes under load without breaking. These developments were initially verified by comparing simulated stress distributions against analytical solutions for select boundary value problems. Practical validation of the novel FDEM formulation was achieved by capturing the variation of critical failure mechanism observed in a slope as a function of the type of rock mass jointing. The factors of safety computed with the strength reduction method compared very well with those reported in the literature for commercially available programs based on DEM and FEM. Finally, a direct comparison between FEM-based, elasto-plastic and FDEM-based, brittle-fracture models is presented for the case of a homogeneous rock slope. 1. INTRODUCTION The finite-discrete element method (FDEM) is a numerical method originally introduced by Munjiza et al. (1995) as a means of combining principles of continuum mechanics, such as the theory of elasticity and non-linear fracture mechanics, with discrete element algorithms to model fracture, fragmentation, and failure of cementitious materials and rocks. Building upon Munjiza's pioneering work, FDEM has been further developed by a multitude of research groups and organizations worldwide, and applied to a variety of rock mechanics and rock engineering problems where consideration of brittle fracturing processes is critical. Over the years, developments of FDEM have focused on several major areas of interest including (i) improvement of the core algorithms for deformation, fracture, interaction, and contact detection (e.g., Lei et al., 2016, Fukuda et al., 2021, Cai et al., 2023), (ii) incorporation of multi-physics capabilities to account for hydraulic and thermal effects (e.g., Yan and Jiao, 2018, Yan et al., 2019, Munjiza et al., 2020), and (iii) reduction of simulation run times by parallel computing (e.g., Lei et al., 2014; Lisjak et al., 2018; Fukuda et al, 2019). In the classic implementation of FDEM (Munjiza, 2004), the numerical representation of fractures is achieved by an intrinsic cohesive zone model (ICZM). With this approach, zero-thickness cohesive crack elements are inserted (at the beginning of the simulation) across pairs of adjacent solid finite elements throughout the entire modelling domain. All irreversible ("plastic") deformations are concentrated in the form of yielding and breakage of the interfaces between the solid finite elements, which remain elastic.

This article, written by Technology Editor Dennis Denney, contains highlights of paper SPE 94357, "Treating Uncertainties in Reservoir-Performance Prediction With Neural Networks," by J.P. Lechner, SPE, OMV A.G., and G. Zangl, SPE, Schlumberger Information Solutions, prepared for the 2005 SPE Europec/EAGE Annual Conference, Madrid, Spain, 13–16 June. In development projects, reservoir parameters are known only within certain ranges, which results in various realizations of the subsurface. Because of the computational time involved, simulation models to obtain a probability distribution of possible outcomes cannot cover all possible parameter combinations. Creating a response surface based on a reduced number of simulation runs becomes necessary. Such a response surface can be used to approximate results for several variations of input parameters. An approach in which reservoir response is captured by an artificial neural network (ANN) has been investigated. The trained ANN model was used in Monte Carlo simulations to generate the probability distribution of possible outcomes. Introduction Often, simulation models are built to design field-development plans. Because of the low level of information during the early development stage, a range of uncertainty in the prediction scenarios must be considered. Such uncertainties can be handled with ANNs. Numerical models (simulation models) are detailed and powerful predictive tools that can answer many questions regarding subsurface engineering. However, especially in the early development phase, uncertainties are large, and prediction results will span a broad range. To take into account the whole range of possible outcomes of reservoir simulation, optimization routines would have to run the numerical models perhaps thousands of times. Although the most likely solution that respects subsurface uncertainties is of interest, the most profitable solution for reservoir management must be found. Because of the computational time involved, these methodologies often are not used. Building a response surface that can predict many possible outcomes of a numerical simulation by processing a large variety of input parameters could provide a solution to this problem. The response surface must cover the non-linear dependencies between input and output parameters. Experimental design and response-surface modeling has been used to delineate subsurface uncertainty. Common applications include determining the probability distribution of original oil in place from geological models, quantifying uncertainty in predevelopment or preredevelopment projects, predicting production performance from different realizations of a geological model, and optimizing the location of new wells to maximize net profit. Methodology Fig. 1 shows the proposed workflow. As a first step, a limited number of simulation runs is carried out to define the most sensitive input parameters. In these runs, parameters are altered one at a time, either to the minimum or to the maximum. After selecting the most influential input parameters, three values (minimum, best-estimate, and maximum) are defined, and an experimental design is set up. The experimental design aims at obtaining the maximum information with a minimum number of simulation runs. However, practice showed that a minimum number of training data sets are required by the ANN to be able to make sufficiently accurate predictions. With these data sets containing varying input parameters and the corresponding output, an ANN is trained and tested with several additional simulation runs. After defining the probability distribution of the input parameters, the trained ANN is used as a proxy function for a Monte Carlo simulation. Thereby, a probability distribution of the desired output parameter (e.g., cumulative production after a certain number of years) is gained. The quality of the ANN is measured by the root-mean-square error of the deviation between the predicted and the actual output.

Human mothers wean their children from breast milk at an earlier developmental stage than do ape mothers, resulting in human children chewing solid and semi-solid foods using the deciduous dentition. Mechanical forces generated by chewing solid foods during the post-weaning period travel through not only the deciduous teeth, but also the enamel caps of the developing permanent teeth within the maxilla and mandible, which are not present in the adult face. The effects of mechanical stress propagating through these very stiff structures have yet to be examined. Based on a heuristic model, we predicted that the enamel of the embedded developing teeth would act to reduce stresses in the surrounding bony elements of the juvenile face. We tested this hypothesis by simulating occlusal loading in a finite element (FE) model of a child's cranium with a complete set of deciduous teeth and the first permanent molars embedded in the bony crypt in the maxilla. We modeled bone and enamel with appropriate material properties and assessed the effect of embedding high-stiffness enamel structures on stress distribution in the juvenile face. Against expectation, the presence of unerupted enamel caps does not affect the magnitude or location of stresses in the juvenile face. Our results do not support the hypothesis that the unerupted secondary teeth act to moderate stresses in the juvenile face.