ABSTRACT
Background: Computational fluid dynamics (CFD) simulations, in-vitro setups, and experimental ex-vivo approaches have been applied to numerous alveolar geometries over the past years. They aimed to study and examine airflow patterns, particle transport, particle propagation depth, particle residence times, and particle-alveolar wall deposition fractions. These studies are imperative to both pharmaceutical and toxicological studies, especially nowadays with the escalation of the menacing COVID-19 virus. However, most of these studies ignored the surfactant layer that covers the alveoli and the effect of the air-surfactant surface tension on flow dynamics and air-alveolar surface mechanics. Methods: The present study employs a realistic human breathing profile of 4.75s for one complete breathing cycle to emphasize the importance of the surfactant layer by numerically comparing airflow phenomena between a surfactant-enriched and surfactant-deficient model. The acinar model exhibits physiologically accurate alveolar and duct dimensions extending from lung generations 18 to 23. Airflow patterns in the surfactant-enriched model support previous findings that the recirculation of the flow is affected by its propagation depth. Proximal lung generations experience dominant recirculating flow while farther generations in the distal alveolar region exhibit dominant radial flows. In the surfactant-enriched model, surface tension values alternate during inhalation and exhalation, with values increasing to 25 mN/m at the inhalation and decreasing to 1 mN/m at the end of the exhalation. In the surfactant-deficient model, only water coats the alveolar walls with a high surface tension value of 70 mN/m. Results: Results showed that surfactant deficiency in the alveoli adversely alters airflow behavior and generates unsteady chaotic breathing through the production of vorticities, accompanied by higher vorticity magnitudes (100% increase at the end of exhalation) and higher velocity magnitudes (8.69% increase during inhalation and 11.9% increase during exhalation). In addition, high air-water surface tension in the surfactant-deficient case was found to induce higher shear stress values (by around a factor of 10) on the alveolar walls than that of the surfactant-enriched case. Conclusion: Overall, it was concluded that the presence of the surfactant improves respiratory mechanics and allows for smooth breathing and normal respiration.
ABSTRACT
The respiratory system has been mainly analyzed using experimental procedures. With technological development, new opportunities have been created to analyze the respiratory system using noninvasive procedures, such as numerical methods. Numerical methods have allowed researchers to obtain important information about minimally invasive procedure. It also allows to analyze diseases such as asthma, chronic obstructive pulmonary disease, lung cancer, pulmonary fibrosis, COVID-19, etc. The results obtained by these methods can be used to correlate with experimental data and to further improve treatments of patients. © 2022 Elsevier Inc. All rights reserved.
ABSTRACT
With the increase in inevitable large-scale crowd aggregation, disastrous pedestrian stampedes occurred with increasing frequency over the past decade. To prevent these tragedies, it is significant to assess crowd accident-risk (CAR) and identify high-risk areas to control crowd flow dynamically. The cost function of a conventional fluid dynamics model is improved with new items of Gaussian white noise and protection factor, considering both the abnormal pedestrian movements and social distance control due to epidemic, thereby to establish an improved crowd flow model comprehensively. Different from conventional density-based pedestrian aggregation-risk models, this study proposes a hybrid crowd accident-risk assessment (HCRA) model based on internal energy and information entropy. Using the HCRA model, we can consider not only crowd density but also the modulus and direction of a crowd velocity vector simultaneously. Then this study designs a framework to realize crowd accident risk assessment based on the improved crowd-flow model and HCRA model. To validate the proposed models, case studies of CAR assessment in the large-scale waiting hall of the Shanghai Hongqiao railway station are conducted. The pedestrian social control distance-range of 1.0 m-2.0 m under the COVID-19 epidemic situation is verified numerically. Moreover, a valuable result is that this social control distance-range can be shortened to 1.0 m-1.9 m without increase of crow accident-risk. Subsequently, the down-limit of accommodation-capacity of this large waiting hall can be enhanced to 10.54%under this epidemic. IEEE
ABSTRACT
The global pandemic declared by the WHO in March 2020 made urgent the need for an affordable adult ventilator for the Philippine market. An existing low-cost infant ventilator developed by Dr. Enrique Ostrea Jr was redesigned and upgraded into one suitable for adult use. A team of Doctors, Engineers, and Technicians was gathered to work on the project. The team was tasked to develop a low-cost, pressure- and volume-controlled ventilator suitable for adult and infant use in the shortest possible time. A model of the ventilator was created using the simulation software Scilab. The model was used to predict its behavior and guide the design of the ventilator. Experiments were conducted to validate the results from the model. It was found that the model satisfactorily predicted the dynamics of the flow inside the ventilator. The modeling and validation activities helped us build the new low-cost ventialtor in less than four months. © 2021 IEEE.
ABSTRACT
During the COVID-19 pandemic, a shortage of mechanical ventilators was reported and ventilator sharing between patients was proposed as an ultimate solution. Two lung simulators were ventilated by one anesthesia machine connected through two respiratory circuits and T-pieces. Five different combinations of compliances (30-50 mL × cmH2O-1) and resistances (5-20 cmH2O × L-1 × s-1) were tested. The ventilation setting was: pressure-controlled ventilation, positive end-expiratory pressure 15 cmH2O, inspiratory pressure 10 cmH2O, respiratory rate 20 bpm. Pressures and flows from all the circuit sections have been recorded and analyzed. Simulated patients with equal compliance and resistance received similar ventilation. Compliance reduction from 50 to 30 mL × cmH2O-1 decreased the tidal volume (VT) by 32% (418 ± 49 vs. 285 ± 17 mL). The resistance increase from 5 to 20 cmH2O × L-1 × s-1 decreased VT by 22% (425 ± 69 vs. 331 ± 51 mL). The maximal alveolar pressure was lower at higher compliance and resistance values and decreased linearly with the time constant (r² = 0.80, p < 0.001). The minimum alveolar pressure ranged from 15.5 ± 0.04 to 16.57 ± 0.04 cmH2O. Cross-flows between the simulated patients have been recorded in all the tested combinations, during both the inspiratory and expiratory phases. The simultaneous ventilation of two patients with one ventilator may be unable to match individual patient's needs and has a high risk of cross-interference.
ABSTRACT
The 15th Society of Cardiovascular Computed Tomography (SCCT) annual scientific meeting (ASM) welcomed 770 digital attendees from 44 countries, over 2 days, with a program that included 30 sessions across three simultaneously streaming channels, 10 exhibitors and a diverse range of scientific abstracts. In addition, #SCCT2020 generated >5900 tweets from nearly 700 engaged social media participants resulting in an estimated 38 million digital impressions and becoming #1 trending medical meeting in social media in the world during the meeting time period. This article summarizes the many themes and topics of presentation and discussion in this meeting, and the many technical advances that are likely to impact future clinical practice in cardiovascular computed tomography.