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Abstract The geometry and motility of the stomach play a critical role in the digestion of ingested liquid meals. Sleeve gastrectomy, a common type of bariatric surgery used to reduce the size of the stomach, significantly alters the stomach's anatomy and motility, which impacts gastric emptying and digestion. In this study, we use an imaging data-based computational model, StomachSim, to investigate the consequences of sleeve gastrectomy. The pre-operative stomach anatomy was derived from imaging data, and the postsleeve gastrectomy shapes were generated for different resection volumes. We investigate the effect of sleeve sizes and motility patterns on gastric mixing and emptying. Simulations were conducted using an immersed-boundary flow solver, modeling a liquid meal to analyze changes in gastric mixing and emptying rates. The results reveal that different degrees of volume reduction and impaired gastric motility have complex effects on stomach's mixing and emptying functions, which are important factors in gastric health of the patient. Specifically, the total gastric liquid emptying rates increased by 21% with a 30% volume reduction and by 51% with reductions exceeding 50%, due to altered intragastric pressure. Additionally, impaired motility functions resulted in slower mixing, leading to delayed food emptying. These findings provide insights into the biomechanical effects of sleeve gastrectomy on gastric digestion and emptying functions, highlighting the potential of computational models to inform surgical planning and postoperative management. 

We employ a novel computational modelling framework to perform high-fidelity direct numerical simulations of aero-structural interactions in bat-inspired membrane wings. The wing of a bat consists of an elastic membrane supported by a highly articulated skeleton, enabling localised control over wing movement and deformation during flight. By modelling these complex deformations, along with realistic wing movements and interactions with the surrounding airflow, we expect to gain new insights into the performance of these unique wings. Our model achieves a high degree of realism by incorporating experimental measurements of the skeleton’s joint movements to guide the fluid–structure interaction simulations. The simulations reveal that different segments of the wing undergo distinct aeroelastic deformations, impacting the flow dynamics and aerodynamic loads. Specifically, the simulations show significant variations in the effectiveness of the wing in generating lift, drag and thrust forces across different segments and regions of the wing. We employ a force partitioning method to analyse the causality of pressure loads over the wing, demonstrating that vortex-induced pressure forces are dominant while added-mass contributions to aerodynamic loads are minimal. This approach also elucidates the role of various flow structures in shaping pressure distributions. Finally, we compare the fully articulated, flexible bat wing with equivalent stiff wings derived from the same kinematics, demonstrating the critical impact of wing articulation and deformation on aerodynamic efficiency. 

An in silico model of the stomach is presented to study the phenomenon of duodenogastric reflux. We use the model to investigate the role of pyloric incompetence, food properties, and gastroparesis on reflux. This first-ever in silico study of duodenogastric reflux provides new insights into the mechanisms and factors implicated in this reflux and the sequelae of conditions that result from the exposure of the stomach lumen to bile. 

Abstract Immersed boundary methods (IBMs) have evolved over the past 50 years from a specialized technique in biofluid dynamics and applied mathematics to a cornerstone of computational fluid dynamics. Many recent advancements in immersed boundary methods have centered on sharp-interface immersed boundary methods, which offer enhanced accuracy and fidelity for flow simulations. This paper outlines the key principles that have driven our own efforts in the development of sharp-interface immersed boundary methods over the past 25 years. We also highlight the power and versatility of these methods by showcasing a range of applications, spanning biolocomotion (i.e., swimming and flying), physiological flows, compressible aerodynamics, fluid–structure interaction (FSI), and flow-induced noise. 

Pyloric interventions are surgical procedures employed to increase the gastric emptying rate in gastroparesis patients. In this study, we use anin silicomodel to investigate the consequences of pyloric intervention on gastric flow and emptying for two phenotypes of gastroparesis: antral hypomotility and decreased gastric tone. The transpyloric pressure gradient predicted by thein silicomodel, based on viscous fluid flow equations, is compared againstin vivomeasurements. Both phenotypes exhibit a similar pre-procedural emptying rate reduction, but after pyloric surgery, antral hypomotility case with preserved gastric tone shows significant improvements in emptying rates, up to 131%, accompanied by bile reflux from the duodenum into the stomach. Conversely, severely reduced gastric tone cases exhibited a post-procedural reduction in the net emptying rate due to the relatively larger bile reflux. In cases with a combination of antral hypomotility and reduced gastric tone, post-procedural improvements were observed only when both conditions were mild. Our findings highlight the pivotal role of the relative increase in pyloric orifice diameter in determining post-operative emptying rates. The study suggests a possible explanation for the selective response of patients toward these procedures and underscores the potential ofin silicomodelling to generate valuable insights to inform gastric surgery. 

This article presents the evolutionary history of immersed boundary methods (IBMs), tracing their origins to the very beginning of computational fluid dynamics in the late 1950s all the way to the present day. The article highlights the advancements in this simulation methodology over the last 50 years and explores the interplay between IBMs and body-conformal grid methods during this time. Drawing upon the authors’ combined experience of more than 40 years in this arena, the perspective offered is personal and subjective. By employing a critical and comparative approach through the chronological lens, we hope that this article empowers the reader to understand both the capabilities and limitations of these methods, and to pursue advancements that fill the key gaps and break new ground. 

A reduced-order model of face mask aerodynamics and aerosol filtration is introduced. This model incorporates existing empirical data on filtration efficiency for different types of face masks, as well as the size distribution of exhaled aerosol particles. By considering realistic peripheral gap profiles, our model estimates both the extent of peripheral leakage and the fitted filtration efficiency of face masks in terms of outward protection. Simulations employing realistic peripheral gap profiles reveal that, for surgical masks, 80% or more of the total exhaled airflow could leak through the mask periphery, even when the average peripheral gap measures only 0.65 mm. However, the majority of exhaled aerosol particles do not follow the flow path through the peripheral gaps but, instead, impact directly on the mask fabric. As a result, these face masks can filter out approximately 70% of the exhaled particles despite the significant peripheral leakage. To validate our model, we compare its predictions with experimental data, and we find a reasonable agreement in estimating the outward protection provided by surgical masks. This validation underscores the reliability of our model in assessing the efficacy of surgical masks. Moreover, leveraging the insights gained from our model, we explore the impact of mask usage on the transmission of respiratory viruses within communities. By considering various scenarios, we can assess the potential reduction in viral spread achieved through widespread mask adoption. 

Although face masks have been used for over a century to provide protection against airborne pathogens and pollutants, close scrutiny of their effectiveness has peaked in the past two years in response to the COVID-19 pandemic. The simplicity of face masks belies the complexity of the physical phenomena that determine their effectiveness as a defense against airborne infections. This complexity is rooted in the fact that the effectiveness of face masks depends on the combined effects of respiratory aerodynamics, filtration flow physics, droplet dynamics and their interactions with porous materials, structural dynamics, physiology, and even human behavior. At its core, however, the face mask is a flow-handling device, and in the current review, we take a flow physics–centric view of face masks and the key phenomena that underlie their function. We summarize the state of the art in experimental measurements, as well as the growing body of computational studies that have contributed to our understanding of the factors that determine the effectiveness of face masks. The review also lays out some of the important open questions and technical challenges associated with the effectiveness of face masks. 

Although face masks have been used for over a century to provide protection against airborne pathogens and pollutants, close scrutiny of their effectiveness has peaked in the past two years in response to the COVID-19 pandemic. The simplicity of face masks belies the complexity of the physical phenomena that determine their effectiveness as a defense against airborne infections. This complexity is rooted in the fact that the effectiveness of face masks depends on the combined effects of respiratory aerodynamics, filtration flow physics, droplet dynamics and their interactions with porous materials, structural dynamics, physiology, and even human behavior. At its core, however, the face mask is a flow-handling device, and in the current review, we take a flow physics–centric view of face masks and the key phenomena that underlie their function. We summarize the state of the art in experimental measurements, as well as the growing body of computational studies that have contributed to our understanding of the factors that determine the effectiveness of face masks. The review also lays out some of the important open questions and technical challenges associated with the effectiveness of face masks. 

The peristaltic motion of stomach walls combines with the secretion of digestive enzymes to initiate the process that breaks down food. In this study, the mixing, breakdown, and emptying of a liquid meal containing protein is simulated in a model of a human stomach. In this model, pepsin, the gastric enzyme responsible for protein hydrolysis, is secreted from the proximal region of the stomach walls and allowed to react with the contents of the stomach. The velocities of the retropulsive jet induced by the peristaltic motion, the emptying rate, and the extent of hydrolysis are quantified for a control case as well as for three other cases with reduced motility of the stomach, which may result from conditions such as diabetes mellitus. This study quantifies the effect of stomach motility on the rate of food breakdown and its emptying into the duodenum and we correlate these observations with the mixing in the stomach induced by the wall motion.