A Planar Model of an Ankle Joint with Optimized Material Parameters and Hertzian Contact Pairs

Borucka, Aleksandra; Ciszkiewicz, Adam

doi:10.3390/ma12162621

Cited by 7 publications

(23 citation statements)

References 41 publications

(64 reference statements)

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“…The second aim of the study was to analyze the uncertainty of a planar model of the ankle proposed in [26]. This analysis was carried out with the bounds on geometrical and material parameters set to 0.50 mm and 5.00% respectively.…”

Section: Aim Of the Studymentioning

confidence: 99%

“…The planar ankle model employed in this study was based on [26]-see Figure 1. It contained two rigid bodies-one moving and one stationary.…”

Section: Ankle Model Assumed To Verify the Proceduresmentioning

confidence: 99%

“…Furthermore, the bodies also interacted through Hertzian contact pairs of a spheresphere type, which represented the cartilage. The details concerning the mathematical equations for computing the forces of the elements and the equilibrium of such systems can be found in the following publications [26][27][28][29][30][31]. Internally, within the procedure, the models were solved for static equilibrium under the following external moment loads: Mext = −5.00: 5.00 Nm in 11 steps.…”

Section: Ankle Model Assumed To Verify the Proceduresmentioning

confidence: 99%

“…The convergence settings for the solver were set to the default ones. However, an additional condition was imposed on the solver-the sum of the absolute values of the residual loads had to be less than 1.0 × 10 −10 (see [26] for further details).…”

Section: Objective Functionmentioning

confidence: 99%

“…The initial population of the algorithm was generated randomly with the bounds based on the prior ankle model [26]. The lower and the upper bound for the geometrical parameters were obtained by adding and subtracting 0.50 mm respectively from the parameters based on [26]. The bounds for the material parameters were relative and set to ±5.00%, again based on [26].…”

Section: Generating the Initial Population For The Algorithmmentioning

confidence: 99%

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Analyzing Uncertainty of an Ankle Joint Model with Genetic Algorithm

Ciszkiewicz

2020

Materials

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Recent studies in biomechanical modeling suggest a paradigm shift, in which the parameters of biomechanical models would no longer treated as fixed values but as random variables with, often unknown, distributions. In turn, novel and efficient numerical methods will be required to handle such complicated modeling problems. The main aim of this study was to introduce and verify genetic algorithm for analyzing uncertainty in biomechanical modeling. The idea of the method was to encode two adversarial models within one decision variable vector. These structures would then be concurrently optimized with the objective being the maximization of the difference between their outputs. The approach, albeit expensive numerically, offered a general formulation of the uncertainty analysis, which did not constrain the search space. The second aim of the study was to apply the proposed procedure to analyze the uncertainty of an ankle joint model with 43 parameters and flexible links. The bounds on geometrical and material parameters of the model were set to 0.50 mm and 5.00% respectively. The results obtained from the analysis were unexpected. The two obtained adversarial structures were almost visually indistinguishable and differed up to 38.52% in their angular displacements.

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Section: Aim Of the Studymentioning

confidence: 99%

“…The planar ankle model employed in this study was based on [26]-see Figure 1. It contained two rigid bodies-one moving and one stationary.…”

Section: Ankle Model Assumed To Verify the Proceduresmentioning

confidence: 99%