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Localized vortices can have significant influence on transport of inhaled particles through the upper respiratory tract. These vortices have complex three-dimensional structure with details dependent on the anatomical geometry. Using a highly simplified model, we demonstrate that changes in transport characteristics with geometric distortion can be estimated by accounting merely for the net strength and location of the vorticity in a two-dimensional projection. Test cases consider 30 L/min inhaled airflow containing suspended spherical water droplets from 1 micrometer to 30 micrometers in diameter through (1) a healthy upper respiratory tract and (2) a distorted variation mimicking a glottic tumor. The reduced-order model approximates the system by a two-dimensional potential flow with embedded point vortices having features derived from Large Eddy Simulations of inhaled airflow through anatomically realistic, tomography-based, three-dimensional tracts. The effects of vorticity and particle size on changes in particle transport are shown to be consistent between the reduced-order model and the full-scale simulations., Comment: 10 pages, 7 figures

Surgical masks have played a crucial role in healthcare facilities to protect against respiratory and infectious diseases, particularly during the COVID-19 pandemic. However, the synthetic fibers, mainly made of polypropylene, used in their production may adversely affect the environment and human health. Recent studies have confirmed the presence of microplastics and fibers in human lungs and have related these synthetic particles with the occurrence of pulmonary ground glass nodules. Using a piston system to simulate human breathing, this study investigates the role of surgical masks as a direct source of inhalation of microplastics. Results reveal the release of particles of sizes ranging from nanometers (300 nm) to millimeters (~2 mm) during normal breathing conditions, raising concerns about the potential health risks. Notably, large visible particles (> 1 mm) were observed to be ejected from masks with limited wear after only a few breathing cycles. Given the widespread use of masks by healthcare workers and the potential future need for mask usage by the general population during seasonal infectious diseases or new pandemics, developing face masks using safe materials for both users and the environment is imperative., Comment: 11 pages, 3 figures

We present a novel thermodynamic parameter estimation framework for energy-based surgery on live tissue, with direct applications to tissue characterization during electrosurgery. This framework addresses the problem of estimating tissue-specific thermodynamics in real-time, which would enable accurate prediction of thermal damage impact to the tissue and damage-conscious planning of electrosurgical procedures. Our approach provides basic thermodynamic information such as thermal diffusivity, and also allows for obtaining the thermal relaxation time and a model of the heat source, yielding in real-time a controlled hyperbolic thermodynamics model. The latter accounts for the finite thermal propagation time necessary for modeling of the electrosurgical action, in which the probe motion speed often surpasses the speed of thermal propagation in the tissue operated on. Our approach relies solely on thermographer feedback and a knowledge of the power level and position of the electrosurgical pencil, imposing only very minor adjustments to normal electrosurgery to obtain a high-fidelity model of the tissue-probe interaction. Our method is minimally invasive and can be performed in situ. We apply our method first to simulated data based on porcine muscle tissue to verify its accuracy and then to in vivo liver tissue, and compare the results with those from the literature. This comparison shows that parameterizing the Maxwell--Cattaneo model through the framework proposed yields a noticeably higher fidelity real-time adaptable representation of the thermodynamic tissue response to the electrosurgical impact than currently available. A discussion on the differences between the live and the dead tissue thermodynamics is also provided., Comment: Accepted for publication in the IEEE Transactions on Biomedical Engineering. Research reported in this publication was supported by the National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health under award number R01EB029766

We present a novel 3D adaptive observer framework for use in the determination of subsurface organic tissue temperatures in electrosurgery. The observer structure leverages pointwise 2D surface temperature readings obtained from a real-time infrared thermographer for both parameter estimation and temperature field observation. We introduce a novel approach to decoupled parameter adaptation and estimation, wherein the parameter estimation can run in real-time, while the observer loop runs on a slower time scale. To achieve this, we introduce a novel parameter estimation method known as attention-based noise-robust averaging, in which surface thermography time series are used to directly estimate the tissue's diffusivity. Our observer contains a real-time parameter adaptation component based on this diffusivity adaptation law, as well as a Luenberger-type corrector based on the sensed surface temperature. In this work, we also present a novel model structure adapted to the setting of robotic surgery, wherein we model the electrosurgical heat distribution as a compactly supported magnitude- and velocity-controlled heat source involving a new nonlinear input mapping. We demonstrate satisfactory performance of the adaptive observer in simulation, using real-life experimental ex vivo porcine tissue data., Comment: Paper accepted to the 2022 IEEE Conference on Decision and Control (CDC 2022)

Small - but finite - fluid inertia can be leveraged to generate steady flows out of liquid vibrations around an immersed interface. In engineering, external high-frequency drivers (10$^2$-10$^5$ Hz) allow this inertial rectification phenomenon, known as viscous streaming, to be employed in micron-scale devices for precise flow control, particle manipulation and spatially controlled chemistry. However, beyond artificial settings, streaming may also be accessed by larger-scale biological systems pertaining to lower frequencies. Then, millimeter-size bacteria or larvae that oscillate cilia and appendages in the 1-10Hz range may be able to endogenously rectify surrounding flows, for feeding or locomotion, removing the need for external actuators, tethers or tubings. In support of this hypothesis, here we demonstrate an in vitro living system able to produce streaming flows, endogenously, autonomously and unassisted. Computationally informed, our biological device generates oscillatory flows through the cyclic contractions of an engineered muscle tissue, shaped in the form of a ring and suspended in fluid within a Micro-Particle Image Velocimetry setup, for analysis. Flow patterns consistent with streaming simulations are observed for low-frequency muscle contractions (2-4Hz), either spontaneous or light-induced, illustrating system autonomy and controllability, respectively. Thus, this work provides experimental evidence of biologically powered streaming in untethered millimeter-scale living systems, showcasing the utility of bio-hybrid technology for fundamental and applied fluid mechanics.

Passive filtering is a common strategy used to reduce airborne disease transmission and particulate contaminants in buildings and individual covers. The engineering of high-performance filters with relatively low flow resistance but high virus- or particle-blocking efficiency is a nontrivial problem of paramount relevance, as evidenced in the variety of industrial filtration systems and the worldwide use of face masks. In this case, standard N95-level covers have high virus-blocking efficiency, but they can cause breathing discomfort. Next-generation industrial filters and masks should retain sufficiently small droplets and aerosols while having low resistance. We introduce a novel 3D printable particle filter inspired by animals' complex nasal anatomy. Unlike standard random-media-based filters, the proposed concept relies on equally spaced channels with tortuous airflow paths. These two strategies induce distinct effects: a reduced resistance and a high likelihood of particle trapping by altering their trajectories with tortuous paths and induced local flow instability. The structures are tested for pressure drop and particle filtering efficiency over a wide range of airflow rates. We have also cross-validated the observed efficiency through numerical simulations. The designed filters exhibit a lower pressure drop than the commercial mask and air filters (N95, surgical, and high-efficiency particulate air (HEPA)). The concept provides a new approach to developing scalable, flexible, high-efficiency air filters for various engineering applications.

The structure of the turbulence-driven power fluctuations in a wind farm is fundamentally described from basic concepts. A derived tuning-free model, supported with experiments, reveals the underlying spectral content of the power fluctuations of a wind farm. It contains two power-law trends and oscillations in the relatively low- and high-frequency ranges. The former is mostly due to the turbulent interaction between the flow and the turbine properties; whereas the latter is due to the advection between turbine pairs. The spectral wind-farm scale power fluctuations $\Phi_P$ exhibits a power-law decay proportional to $f^{-5/3-2}$ in the region corresponding to the turbulence inertial subrange and at relatively large scales, $\Phi_P\sim f^{-2}$. Due to the advection and turbulent diffusion of large-scale structures, a spectral oscillation exists with the product of a sinusoidal behavior and an exponential decay in the frequency domain., Comment: 7 pages, 7 figures, submitted to Physical Review E