Investigation of prescribed movement in fluid–structure interaction simulation for the human phonation process

Zörner, Stefan; Döllinger, Michael

doi:10.1016/j.compfluid.2013.06.031

Cited by 35 publications

(27 citation statements)

References 25 publications

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“…The frequencies agree in given accuracy with frequencies obtained by the modal analysis summarized in Table 1 on previous page. This also corresponds well with the results of [12], where also primarily the first two eigenmodes were excited during FSI. …”

Section: Fsi Testsupporting

confidence: 73%

See 1 more Smart Citation

On Influence of Vocal Fold Size to Frequencies of Induced Vibrations

Valášek¹,

Horáček²,

Sváček³

2016

Topical Problems of Fluid Mechanics 2016

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The paper deals with modelling of fluid-structure interaction (FSI). Particularly it is concerned with the example of human vocal folds and their vibration under excitation by the fluid flow. The vocal folds are described as an elastic body with the assumption of small displacements and therefore the linear elasticity theory is used. The viscous incompressible fluid flow is considered. For the purpose of the numerical solution the arbitrary Lagrangian-Eulerian method is used. The whole problem is solved by the finite element method based solver. The numerical results of the influence of vocal folds dimensions are presented.

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Section: Fsi Testsupporting

confidence: 73%

“…The M5 model was used. The proportions of the fluid domain were [12], where the first two eigenmodes also correspond to the horizontal and vertical motions.…”

Section: Numerical Simulationsmentioning

confidence: 99%

On Influence of Vocal Fold Size to Frequencies of Induced Vibrations

Valášek¹,

Horáček²,

Sváček³

2016

Topical Problems of Fluid Mechanics 2016

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“…The most commonly used numerical model in these endeavors is the two-mass model by Ishizaka and Flanagan [28]. Higher fidelity models based, e.g., on a Lattice Boltzmann approach [29] or Navier-Stokes airflow model [30]–[32] are available, but usually computationally too expensive to employ in an inverse problem. Detailed reviews of available models are given by Erath et al [33] and Alipour et al [23].…”

Section: Related Workmentioning

confidence: 99%

Laryngeal Pressure Estimation With a Recurrent Neural Network

Gómez

Schützenberger

Semmler

et al. 2019

IEEE J. Transl. Eng. Health Med.

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Quantifying the physical parameters of voice production is essential for understanding the process of phonation and can aid in voice research and diagnosis. As an alternative to invasive measurements, they can be estimated by formulating an inverse problem using a numerical forward model. However, high-fidelity numerical models are often computationally too expensive for this. This paper presents a novel approach to train a long short-term memory network to estimate the subglottal pressure in the larynx at massively reduced computational cost using solely synthetic training data. We train the network on synthetic data from a numerical two-mass model and validate it on experimental data from 288 high-speed ex vivo video recordings of porcine vocal folds from a previous study. The training requires significantly fewer model evaluations compared with the previous optimization approach. On the test set, we maintain a comparable performance of 21.2% versus previous 17.7% mean absolute percentage error in estimating the subglottal pressure. The evaluation of one sample requires a vanishingly small amount of computation time. The presented approach is able to maintain estimation accuracy of the subglottal pressure at significantly reduced computational cost. The methodology is likely transferable to estimate other parameters and training with other numerical models. This improvement should allow the adoption of more sophisticated, high-fidelity numerical models of the larynx. The vast speedup is a critical step to enable a future clinical application and knowledge of parameters such as the subglottal pressure will aid in diagnosis and treatment selection.

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“…As an alternative and complementary method, computational models have been developed in recent decades. With the development of advanced numerical methods and improvement of computational power, more aspects of the phonation process, from glottal flow analysis [21][22][23][24][25] to mechanical analysis of oscillations of the vocal folds [26][27][28] and acoustic analysis of voice sources [29][30][31][32], have been investigated numerically in detail. These computational models have the advantage of simulating the entire process with enormously high spatial and temporal resolution in the flow region and the structural domain of the vocal fold tissue.…”

Section: Introductionmentioning

confidence: 99%

Towards a Clinically Applicable Computational Larynx Model

et al. 2019

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The enormous computational power and time required for simulating the complex phonation process preclude the effective clinical use of computational larynx models. The aim of this study was to evaluate the potential of a numerical larynx model, considering the computational time and resources required. Using Large Eddy Simulations (LES) in a 3D numerical larynx model with prescribed motion of vocal folds, the complicated fluid-structure interaction problem in phonation was reduced to a pure flow simulation with moving boundaries. The simulated laryngeal flow field is in good agreement with the experimental results obtained from authors’ synthetic larynx model. By systematically decreasing the spatial and temporal resolutions of the numerical model and optimizing the computational resources of the simulations, the elapsed simulation time was reduced by 90% to less than 70 h for 10 oscillation cycles of the vocal folds. The proposed computational larynx model with reduced mesh resolution is still able to capture the essential laryngeal flow characteristics and produce results with sufficiently good accuracy in a significant shorter time-to-solution. The reduction in computational time achieved is a promising step towards the clinical application of these computational larynx models in the near future.

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Investigation of prescribed movement in fluid–structure interaction simulation for the human phonation process

Cited by 35 publications

References 25 publications

On Influence of Vocal Fold Size to Frequencies of Induced Vibrations

On Influence of Vocal Fold Size to Frequencies of Induced Vibrations

Laryngeal Pressure Estimation With a Recurrent Neural Network

Towards a Clinically Applicable Computational Larynx Model

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