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result(s) for
"Joints (Engineering) Mathematical models."
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An energy-based analytical model for adhesively bonded stepped and simple-lap joined CFRP laminates
An energy-based analytical model is proposed here to investigate the mechanical behavior of adhesively bonded simple-lap and stepped-lap joints (SLJ) with carbon fiber-reinforced polymer (CFRP) adherends subjected to tensile loading. In this study, the CFRP uni-directional (UD) adherends of
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are considered to be joined. The governing differential equations (GDEs) of equilibrium are derived for the adhesively bonded adherends in stepped lap joint configuration following an energy-based approach. Additionally, this model is reduced for GDEs of the simple-lap joint configuration. The finite difference scheme is employed to obtain the numerical solution of the proposed analytical model. The field distributions of strain and displacement over the specimen surfaces are captured in the experimental investigation using the full field technique of 2D digital image correlation (DIC). The analytical model generates the load–displacement curve, validated against experimental and finite element (FE) predictions. Additionally, a sensitivity analysis is conducted to assess the influence of the design parameters of the adhesive joint, including the thickness of the adhesive layer, length of overlap region, and elastic modulus. Finally, the analytical model prediction of the peak load for damage in adhesively bonded joints under shear loading is compared with experimental results. The developed analytical model provides an understanding of the mechanical behavior, including possible failure/critical locations of the adhesive joints from the design perspective.
Journal Article
OpenCap: Human movement dynamics from smartphone videos
Measures of human movement dynamics can predict outcomes like injury risk or musculoskeletal disease progression. However, these measures are rarely quantified in large-scale research studies or clinical practice due to the prohibitive cost, time, and expertise required. Here we present and validate OpenCap, an open-source platform for computing both the kinematics (i.e., motion) and dynamics (i.e., forces) of human movement using videos captured from two or more smartphones. OpenCap leverages pose estimation algorithms to identify body landmarks from videos; deep learning and biomechanical models to estimate three-dimensional kinematics; and physics-based simulations to estimate muscle activations and musculoskeletal dynamics. OpenCap’s web application enables users to collect synchronous videos and visualize movement data that is automatically processed in the cloud, thereby eliminating the need for specialized hardware, software, and expertise. We show that OpenCap accurately predicts dynamic measures, like muscle activations, joint loads, and joint moments, which can be used to screen for disease risk, evaluate intervention efficacy, assess between-group movement differences, and inform rehabilitation decisions. Additionally, we demonstrate OpenCap’s practical utility through a 100-subject field study, where a clinician using OpenCap estimated musculoskeletal dynamics 25 times faster than a laboratory-based approach at less than 1% of the cost. By democratizing access to human movement analysis, OpenCap can accelerate the incorporation of biomechanical metrics into large-scale research studies, clinical trials, and clinical practice.
Journal Article
Why are Antagonist Muscles Co-activated in My Simulation? A Musculoskeletal Model for Analysing Human Locomotor Tasks
Existing “off-the-shelf” musculoskeletal models are problematic when simulating movements that involve substantial hip and knee flexion, such as the upstroke of pedalling, because they tend to generate excessive passive fibre force. The goal of this study was to develop a refined musculoskeletal model capable of simulating pedalling and fast running, in addition to walking, which predicts the activation patterns of muscles better than existing models. Specifically, we tested whether the anomalous co-activation of antagonist muscles, commonly observed in simulations, could be resolved if the passive forces generated by the underlying model were diminished. We refined the
OpenSim™
model published by Rajagopal
et al
. (IEEE Trans Biomed Eng 63:1–1,
2016
) by increasing the model’s range of knee flexion, updating the paths of the knee muscles, and modifying the force-generating properties of eleven muscles. Simulations of pedalling, running and walking based on this model reproduced measured EMG activity better than simulations based on the existing model—even when both models tracked the same subject-specific kinematics. Improvements in the predicted activations were associated with decreases in the net passive moments; for example, the net passive knee moment during the upstroke of pedalling decreased from 36.9 N m (existing model) to 6.3 N m (refined model), resulting in a dramatic decrease in the co-activation of knee flexors. The refined model is available from SimTK.org and is suitable for analysing movements with up to 120° of hip flexion and 140° of knee flexion.
Journal Article
Comparison of eight published static finite element models of the intact lumbar spine: Predictive power of models improves when combined together
Finite element (FE) model studies have made important contributions to our understanding of functional biomechanics of the lumbar spine. However, if a model is used to answer clinical and biomechanical questions over a certain population, their inherently large inter-subject variability has to be considered. Current FE model studies, however, generally account only for a single distinct spinal geometry with one set of material properties. This raises questions concerning their predictive power, their range of results and on their agreement with in vitro and in vivo values.
Eight well-established FE models of the lumbar spine (L1-5) of different research centers around the globe were subjected to pure and combined loading modes and compared to in vitro and in vivo measurements for intervertebral rotations, disc pressures and facet joint forces.
Under pure moment loading, the predicted L1-5 rotations of almost all models fell within the reported in vitro ranges, and their median values differed on average by only 2° for flexion-extension, 1° for lateral bending and 5° for axial rotation. Predicted median facet joint forces and disc pressures were also in good agreement with published median in vitro values. However, the ranges of predictions were larger and exceeded those reported in vitro, especially for the facet joint forces. For all combined loading modes, except for flexion, predicted median segmental intervertebral rotations and disc pressures were in good agreement with measured in vivo values.
In light of high inter-subject variability, the generalization of results of a single model to a population remains a concern. This study demonstrated that the pooled median of individual model results, similar to a probabilistic approach, can be used as an improved predictive tool in order to estimate the response of the lumbar spine.
Journal Article
Statistical Shape Modeling to Determine Poromechanics of the Human Knee Joint
Subject-specific knee joint models are widely used to predict joint contact mechanics for individuals but may not capture the variance in knee joint geometry across a population. Statistical shape modeling uses the dataset of a cohort to encapsulate population-wide variability. The present study aimed to develop a shape modeling procedure for poromechanical finite element models of knee joint to account for population diversity in the creep response of knees. Shape models of right knee joints were created from MRI of 31 healthy male subjects using principal component analysis. Creep analysis was performed for 13 shape models in total, i.e., the average model, plus six models for both the first and second principal modes. For a given loading, the contact and fluid pressures varied substantially within these mathematically produced models but compared reasonably well to that of three subject-specific models that were constructed from individual knees, representing approximately the smallest, median and largest knees of the 31 right knees. While the joint size variation, generally represented by the first principal component, predominantly influenced the magnitudes of contact and fluid pressures, the joint shape variation characterized by the second principal component further affected the pressure distribution, and load sharing between the lateral and medial compartments. The present study evaluated a workflow for the statistical shape modeling of poromechanical behavior of knee joints with sample results based on a small population. However, the workflow can be readily used for a large population to address the challenge of interpatient variability in joint contact mechanics, particularly in contact and fluid pressures in articular cartilage, and variable creep behaviors of the joint associated with individual anatomical variations.
Journal Article
Infrared in-line monitoring of flaws in steel welded joints: a preliminary approach with SMAW and GMAW processes
The non-destructive full-field non-contact thermographic technique is applied for non-destructive flaw detection of the welded joints, in real-time and offline configuration. In this paper, a thermographic procedure for real-time flaw detection in manual arc welding process is presented. Surface temperature acquisitions by means of an IR camera were performed during arc welding process of 8 specimen both for calibration and validation of the numerical model. The investigated variables are the technique (manual stick arc (SMAW) and gas arc (GMAW) welding) and the joint shape (butt and T joint) for steel joints, in sound conditions and with artificial flaws. Numerical simulation of welding thermal transients was run to obtain the expected surface temperature fields and thermal behavior for different welding parameter configurations. Hardness measurement and micro-graphic analysis were performed to validate numerical simulation results. The real-time thermographic study of the weld pool gives direct indications of anomalies; local studies of the thermal transient and thermal profiles can detect some kind of flaws; microstructural analysis of Heat-Affected Zone (HAZ) and surrounding areas higlights the presence of austenite and martensite distribution which justifies the thermal transients and thermal profiles for different welding configurations. Comparing real-time IR acquisition of the welding process with simulated thermal contours of sound processes provides information of presence of some kind of flaws. Since most of the flaws are generated in the weld pool, it is possible to recognize anomalies directly from the thermal acquisitions or with post-processing the acquired data.
Journal Article
Comparing on-line continuous movement decoding with joints unconstrained and constrained based on a generic musculoskeletal model
Human–machine interface (HMI) has been extensively developed and applied in rehabilitation. However, the performance of amputees on continuous movement decoding was significantly decreased compared with that of able-bodied individuals. To explore the impact of the absence of joint movements on the performance of HMI in rehabilitation, a generic musculoskeletal model (MM) was employed in this study to evaluate and compare the performance of subjects completing a series of on-line tasks with the wrist and metacarpophalangeal (MCP) joints unconstrained and constrained. The performance of the generic MM has been demonstrated in previous studies. The electromyography (EMG) signals of four muscles were employed as inputs of the generic MM to realize the continuous movement decoding of wrist and MCP joints. Ten able-bodied subjects were recruited to perform the on-line tasks. The completion time, the number of overshoots, and the path efficiency of the tasks were taken as the indexes to quantify the subjects’ performance. The muscle activation associated with the movement was analyzed. Across all tasks and subjects, the average values of the three indexes with the joints unconstrained were 7.7 s, 0.59, and 0.38, respectively, while those with the joints constrained were 17.86 s, 1.47, and 0.22, respectively. The results demonstrated that the subjects performed better with the wrist and MCP joints unconstrained than with those joints constrained in the on-line tasks, suggesting that the absence of joint movements can be a reason of the decreased performance of continuous movement decoding with HMIs. Meanwhile, it is revealed that the different performance on motion behaviors is caused by the absence of joint movements.
Graphical abstract
Journal Article
Open Knee(s): A Free and Open Source Library of Specimen-Specific Models and Related Digital Assets for Finite Element Analysis of the Knee Joint
There is a growing interest in the use of virtual representations of the knee for musculoskeletal research and clinical decision making, and to generate digital evidence for design and regulation of implants. Accessibility to previously developed models and related digital assets can dramatically reduce barriers to entry to conduct simulation-based studies of the knee joint and therefore help accelerate scientific discovery and clinical innovations. Development of models for finite element analysis is a demanding process that is both time consuming and resource intensive. It necessitates expertise to transform raw data to reliable virtual representations. Modeling and simulation workflow has many processes such as image segmentation, surface geometry generation, mesh generation and finally, creation of a finite element representation with relevant loading and boundary conditions. The outcome of the workflow is not only the end-point knee model but also many other digital by-products. When all of these data, derivate assets, and tools are freely and openly accessible, researchers can bypass some or all the steps required to build models and focus on using them to address their research goals. With provenance to specimen-specific anatomical and mechanical data and traceability of digital assets throughout the whole lifecycle of the model, reproducibility and credibility of the modeling practice can be established. The objective of this study is to disseminate Open Knee(s), a cohort of eight knee models (and relevant digital assets) for finite element analysis, that are based on comprehensive specimen-specific imaging data. In addition, the models and by-products of modeling workflows are described along with model development strategies and tools. Passive flexion served as a test simulation case, demonstrating an end-user application. Potential roadmaps for reuse of Open Knee(s) are also discussed.
Journal Article
Are Subject-Specific Musculoskeletal Models Robust to the Uncertainties in Parameter Identification?
Subject-specific musculoskeletal modeling can be applied to study musculoskeletal disorders, allowing inclusion of personalized anatomy and properties. Independent of the tools used for model creation, there are unavoidable uncertainties associated with parameter identification, whose effect on model predictions is still not fully understood. The aim of the present study was to analyze the sensitivity of subject-specific model predictions (i.e., joint angles, joint moments, muscle and joint contact forces) during walking to the uncertainties in the identification of body landmark positions, maximum muscle tension and musculotendon geometry. To this aim, we created an MRI-based musculoskeletal model of the lower limbs, defined as a 7-segment, 10-degree-of-freedom articulated linkage, actuated by 84 musculotendon units. We then performed a Monte-Carlo probabilistic analysis perturbing model parameters according to their uncertainty, and solving a typical inverse dynamics and static optimization problem using 500 models that included the different sets of perturbed variable values. Model creation and gait simulations were performed by using freely available software that we developed to standardize the process of model creation, integrate with OpenSim and create probabilistic simulations of movement. The uncertainties in input variables had a moderate effect on model predictions, as muscle and joint contact forces showed maximum standard deviation of 0.3 times body-weight and maximum range of 2.1 times body-weight. In addition, the output variables significantly correlated with few input variables (up to 7 out of 312) across the gait cycle, including the geometry definition of larger muscles and the maximum muscle tension in limited gait portions. Although we found subject-specific models not markedly sensitive to parameter identification, researchers should be aware of the model precision in relation to the intended application. In fact, force predictions could be affected by an uncertainty in the same order of magnitude of its value, although this condition has low probability to occur.
Journal Article