Qian Xue

Asymmetric activation of intrinsic laryngeal muscles is common in human phonation, yet its effects on vocal fold (VF) vibration and acoustic output remain unclear. In this study, we used a high-fidelity, anatomically resolved 3D computational framework to examine how asymmetric thyroarytenoid (TA) and cricothyroid (CT) activation regulates VF strain, vibratory dynamics, and flow-related acoustics. The results show that TA activation is the primary source of left–right mechanical imbalance. In contrast, CT asymmetry produces limited vibratory asymmetry due to the bilateral anatomical constraints of the thyroid cartilage. Under TA asymmetry, increasing CT activation primarily regulates longitudinal strain and strengthens bilateral coupling. With low–moderate TA asymmetry, the VFs remained frequency-locked, with fundamental frequency jointly modulated by both sides. As asymmetry increased beyond a critical threshold, frequency dominance shifted toward the mechanically softer fold and synchronization broke down, producing biphonation. Increasing CT activation stabilized the system by increasing longitudinal tension, redistributing mechanical asymmetry, and suppressing frequency divergence across a wide range of asymmetric TA conditions. Flow and acoustic measures followed these coupling-driven trends, with unstable coupling associated with reduced acoustic efficiency and breathier phonation. Together, these findings clarify how neuromuscular control and mechanical coupling jointly shape asymmetric phonation.

Two-dimensional fluid–structure interaction (FSI) simulations were conducted to study the influence of the supraglottal tract on intraglottal pressure during vocal fold closing in human phonation. The FSI framework couples a three-mass vocal fold model, an incompressible Navier–Stokes flow solver, and a linear perturbed compressible acoustic solver. Four configurations were simulated under varying subglottal pressures, combining divergent and nearly straight vocal fold closing patterns with and without a supraglottal tract. Comparison of straight closing configurations with and without a supraglottal tract revealed the isolated effect of supraglottal inertance, while the analysis of divergent closing configurations showed the combined effects of supraglottal inertance and intraglottal flow separation. Parameters, including the glottal opening, glottal angle, medial surface wall pressure, which directly reflects how intraglottal pressure is converted to the driving force of the vocal fold motion, and intraglottal flow dynamics, were analyzed. The results show that the supraglottal tract influences intraglottal pressure, as well as the medial surface wall pressure, through two primary mechanisms. First, it reduces medial surface wall pressure through inertance effects during flow deceleration. Second, in the divergent closing configurations, it further decreases medial surface wall pressure by intensifying the flow separation effect. This enhanced flow separation effect is because the supraglottal tract increases peak jet velocity during glottis closing, which strengthens the shear layer and enhances flow circulation after flow separation. Consequently, it leads to more negative glottal pressure, particularly under high subglottal pressures.

Harbor seals use uniquely shaped whiskers to detect, locate, and follow prey. This remarkable capability offers promising insights for advancing underwater sensing technologies. Previous studies have shown that these whiskers generate hairpin vortices, which help suppress self-induced vibrations and enhance sensitivity to subtle flow disturbances. However, in nature, seal whiskers are not always perfectly straight, and the impact of curvature on their sensing function has not been fully understood. In this study, we use direct numerical simulations to examine the flow over whiskers with varying degrees of curvature. Our findings reveal that bending in the whisker disrupts the formation of hairpin vortices and induces von Kármán vortex streets in the bent region instead. As a result, the lift oscillation, considered as the self-induced noise, is increased, which is not favorable for flow sensing. The findings provide new insights into how whisker morphology influences the sensory performance of seal whiskers and inform the design of whisker-inspired underwater sensors.

Pinnipeds, with highly sensitive whiskers, can detect instantaneous spatial hydrodynamic disturbances, crucial for tracking wakes and their sources. However, no existing engineering solution replicates this for intelligent passive flow perception. To bridge this gap, we propose a low-cost, whisker-inspired sensor designed for use in arrays for underwater sensing and tracking. The sensor integrates metal foil strain gages within a polydimethylsiloxane soft base, coupled with a 3D-printed biomimetic seal whisker model. It exhibits low self-noise in undisturbed flow and high sensitivity in wake detection, identifying flow speeds as low as 0.5 mm s⁻¹—comparable to biological whiskers (∼0.25 mm s⁻¹). The dual strain gage design, placed on adjacent perpendicular sides, allows precise measurement of whisker bending amplitude and direction. The sensor shows excellent linearity, repeatability, fatigue life, short response time and superior dynamic performance in the low-frequency range (⩽35 Hz). Despite its high performance, it is cost-effective and easy to fabricate, requiring no specialized facilities or extensive training, making it ideal for large-scale array deployment. To demonstrate its potential, we tested a nine-sensor array capable of predicting dipole source locations using an artificial neural network model. This work demonstrates the feasibility of whisker-inspired sensing for robust spatial flow perception in underwater environments.

This study investigates the impact of subglottic stenosis (SGS) on voice production using a subject-specific laryngeal and airway model. Direct numerical simulations of fluid–structure–acoustic interaction were employed to analyze glottal flow dynamics, vocal fold vibration, and acoustics under realistic conditions. The model accurately captured key physiological parameters, including the glottal flow rate, vocal fold vibration patterns, and the first four formant frequencies. Simulations of varying SGS severity revealed that up to 75% stenosis, vocal function remains largely unaffected. However, at 90% severity, significant changes in glottal flow and acoustics were observed, with vocal fold vibration remaining stable. At 96%, severe reductions in glottal flow and acoustics, along with marked changes in vocal fold dynamics, were detected. Flow resistance, the ratio of glottal to stenosis area, and pressure drop across the vocal folds were identified as critical factors influencing these changes. The use of anatomically realistic airway and vocal fold geometries revealed that while anatomical variations minimally affect voice production at lower stenosis grades, they become critical at severe stenosis levels (>90%), particularly in capturing distinct anterior–posterior opening patterns and focused jet effects that alter glottal dynamics. These findings suggest that while simplified models suffice for analyzing mild to moderate stenosis, patient-specific geometric details are essential for accurate prediction of vocal fold dynamics in severe cases.

Fish fin rays constitute a sophisticated control system for ray-finned fish, facilitating versatile locomotion within complex fluid environments. Despite extensive research on the kinematics and hydrodynamics of fish locomotion, the intricate control strategies in fin-ray actuation remain largely unexplored. While deep reinforcement learning (DRL) has demonstrated potential in managing complex nonlinear dynamics; its trial-and-error nature limits its application to problems involving computationally demanding environmental interactions. This study introduces a cutting-edge off-policy DRL algorithm, interacting with a fluid–structure interaction (FSI) environment to acquire intricate fin-ray control strategies tailored for various propulsive performance objectives. To enhance training efficiency and enable scalable parallelism, an innovative asynchronous parallel training (APT) strategy is proposed, which fully decouples FSI environment interactions and policy/value network optimization. The results demonstrated the success of the proposed method in discovering optimal complex policies for fin-ray actuation control, resulting in a superior propulsive performance compared to the optimal sinusoidal actuation function identified through a parametric grid search. The merit and effectiveness of the APT approach are also showcased through comprehensive comparison with conventional DRL training strategies in numerical experiments of controlling nonlinear dynamics.

The cross-flow vortex-induced vibration (VIV) response of an elastically mounted idealized undulatory seal whisker (USW) shape is investigated in a wide range of reduced velocity at angles of attack (AOAs) from 0° to 90° and a low Reynolds number of 300. The mass ratio is set to 1.0 to represent the real seal whisker. Dynamic mode decomposition is used to investigate the vortex shedding mode in various cases. In agreement with past studies, the VIV response of the USW is highly AOA-dependent because of the change in the underlying vortex dynamics. At zero AOA, the undulatory shape leads to a hairpin vortex mode that results in extremely low lift force oscillation with a lowered frequency. The frequency remains unaffected by VIV throughout the tested range of reduced velocity. As the AOA deviates from zero, alternating shedding of spanwise vortices becomes dominant. A mixed vortex shedding mode is observed at AOA = 15° in the transition. As the AOA deviated from zero, the VIV amplitude increases rapidly by two orders, reaching the maximum of about 3 times diameter at 90°. An infinite lock-in branch is present for AOA from 60° to 90°, where the VIV amplitude remains high regardless of the increase in reduced velocity.

A human laryngeal model, incorporating all the cartilages and the intrinsic muscles, was reconstructed based on MRI data. The vocal fold was represented as a multilayer structure with detailed inner components. The activation levels of the thyroarytenoid (TA) and cricothyroid (CT) muscles were systematically varied from zero to full activation allowing for the analysis of their interaction and influence on vocal fold dynamics and glottal flow. The finite element method was employed to calculate the vocal fold dynamics, while the one-dimensional Bernoulli equation was utilized to calculate the glottal flow. The analysis was focused on the muscle influence on the fundamental frequency (f_o). We found that while CT and TA activation increased the f_o in most of the conditions, TA activation resulted in a frequency drop when it was moderately activated. We show that this frequency drop was associated with the sudden increase of the vertical motion when the vibration transited from involving the whole tissue to mainly in the cover layer. The transition of the vibration pattern was caused by the increased body-cover stiffness ratio that resulted from TA activation.

Baleen whales (mysticetes) use vocalizations to mediate their complex social and reproductive behaviours in vast, opaque marine environments¹. Adapting to an obligate aquatic lifestyle demanded fundamental physiological changes to efficiently produce sound, including laryngeal specializations^2,3,4. Whereas toothed whales (odontocetes) evolved a nasal vocal organ⁵, mysticetes have been thought to use the larynx for sound production^1,6,7,8. However, there has been no direct demonstration that the mysticete larynx can phonate, or if it does, how it produces the great diversity of mysticete sounds⁹. Here we combine experiments on the excised larynx of three mysticete species with detailed anatomy and computational models to show that mysticetes evolved unique laryngeal structures for sound production. These structures allow some of the largest animals that ever lived to efficiently produce frequency-modulated, low-frequency calls. Furthermore, we show that this phonation mechanism is likely to be ancestral to all mysticetes and shares its fundamental physical basis with most terrestrial mammals, including humans¹⁰, birds¹¹, and their closest relatives, odontocetes⁵. However, these laryngeal structures set insurmountable physiological limits to the frequency range and depth of their vocalizations, preventing them from escaping anthropogenic vessel noise^12,13 and communicating at great depths¹⁴, thereby greatly reducing their active communication range.