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This work delves into the significant advancements in epidemiological modeling and public health policy driven by detailed, quantitative analyses of COVID‐19 aerosol transmission utilizing the capabilities of the supercomputer Fugaku, the world's fastest supercomputer in 2020. By integrating novel computational fluid dynamics (CFD) techniques integrated in the multi‐physics solver CUBE, we achieved scalable, high‐resolution simulations essential for modeling micrometer‐sized virus‐containing aerosols, revolutionizing our understanding of transmission risks in various societal contexts. This innovation significantly reduced the time‐to‐solution for these intricate simulations and allowed for the quick creation of digital twins that captured a broad range of social scenarios with substantial transmission risks. These efforts required a significant amount of computational resources, which were provided for through Fugaku, during COVID‐19. The detailed transmission risk assessments that were produced through this work had a significant impact on public health policies and public behavior throughout Japan, exemplifying a pivotal shift in the digital transformation of epidemiology and the proactive management of pandemic‐related challenges. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

As evidenced by the worldwide pandemic, respiratory infectious diseases and their airborne transmission must be studied to safeguard public health. This study focuses on the emission and transport of speech-generated droplets, which can pose risk of infection depending on the loudness of the speech, its duration and the initial angle of exhalation. We have numerically investigated the transport of these droplets into the human respiratory tract by way of a natural breathing cycle in order to predict the infection probability of three strains of SARS-CoV-2 on a person who is listening at a one-meter distance. Numerical methods were used to set the boundary conditions of the speaking and breathing models and large eddy simulation (LES) was used for the unsteady simulation of approximately 10 breathing cycles. Four different mouth angles when speaking were contrasted to evaluate real conditions of human communication and the possibility of infection. Breathed virions were counted using two different approaches: the breathing zone of influence and direction deposition on the tissue. Our results show that infection probability drastically changes based on the mouth angle and the breathing zone of influence overpredicts the inhalation risk in all cases. We conclude that to portray real conditions, the probability of infection should be based on direct tissue deposition results to avoid overprediction and that several mouth angles must be considered in future analyses. Author summary: We have experienced the devastating nature of airborne transmitted diseases through the recent COVID-19 pandemic. To eradicate short and long-range cross-infection of viruses like SARS-CoV-2 and other such diseases, we need to unravel the fundamentals of droplet generation, transport and deposition due to human interactions. Here, we have computationally simulated viral droplet transport from one talking person to another and calculated the infection probability by predicting the exact number of virions attached to the respiratory tract tissue of the possible host. Our results emphasize the need of using real-like settings and conditions for virtual infection risk prediction to avoid under or overestimation. The ability to accurately predict infection probability of SARS-CoV-2 and other airborne transmitted diseases through computer simulations benefits society by enabling us to create new guidelines and preventive measures for present and future needs. [ABSTRACT FROM AUTHOR]

The fastest supercomputer in 2020, Fugaku, has not only achieved digital transformation of epidemiology in allowing end-to-end, detailed quantitative modeling of COVID-19 transmissions for the first time but also transformed the behavior of the entire Japanese public through its detailed analysis of transmission risks in multitudes of societal situations entailing heavy risks. A novel aerosol simulation methodology was synthesized out of a combination of a new CFD methods meeting industrial demands in the solver, CUBE (Jansson et al., 2019), which not only allowed the simulations to scale massively with high resolution required for micrometer virus-containing aerosol particles but also enabled extremely rapid time-to-solution due to its ability to generate the digital twins representing multitudes of societal situations in a matter of minutes, attaining true overall application high performance; such simulations have been running for the past 1.5°years on Fugaku, cumulatively consuming top supercomputer-class resources and the communicated by the media as well as becoming the basis for official public policies. [ABSTRACT FROM AUTHOR]

We propose a monolithic fluid–structure interaction (FSI) method that uses the cell‐centered finite volume formulation in the Eulerian description, Lagrangian marker particles allocated in the solid region, and the incompressible mixture formulation. In the proposed method, we compute all the basic equations and spatial derivatives, except the solid constitutive equations, on an Eulerian mesh to avoid neighboring particle search. Although full Eulerian methods that use a Cartesian mesh are attractive for FSI problems that require large‐scale computing and include complex geometries and the large deformation of the solid, they cannot avoid the numerical dissipation of the interfaces or internal variables of the solid caused by their advection. This computational problem has been a barrier to the industrial application of full Eulerian mesh methods. In the numerical examples, we confirmed that the proposed method retains sharp interfaces, such as the corners of a square solid, and yields more accurate numerical results for the deformation, energy, and incompressibility of a solid in fluid than our conventional Eulerian FSI method. [ABSTRACT FROM AUTHOR]

Writing high-performance solvers for engineering applications is a delicate task. These codes are often developed on an application to application basis, highly optimized to solve a certain problem. Here, we present our work on developing a general simulation framework for efficient computation of time-resolved approximations of complex industrial flow problems—Complex Unified Building cube method (CUBE). To address the challenges of emerging, modern supercomputers, suitable data structures and communication patterns are developed and incorporated into CUBE. We use a Cartesian grid together with various immersed boundary (IB) methods to accurately capture moving, complex geometries. The asymmetric workload of the IB is balanced by a predictive dynamic load balancer, and a multithreaded halo exchange algorithm is employed to efficiently overlap communication with computations. Our work also concerns efficient methods for handling the large amount of data produced by large-scale flow simulations, such as scalable parallel I/O, data compression, and in-situ processing. [ABSTRACT FROM AUTHOR]

Summary: We propose a full Eulerian incompressible solid‐fluid interaction scheme capable of achieving high parallel efficiency and easily generating meshes for complex solid geometries. While good scalability of a full Eulerian solid‐fluid interaction formulation has been reported by Sugiyama et al, their analysis was carried out using uniform Cartesian mesh and an artificial compressibility method. Typically, it is more challenging to achieve good scalability for hierarchical Cartesian meshes and a fully incompressible formulation. In addition, the conventional full Eulerian methods require a large computational cost to resolve complex solid geometries due to the usage of uniform Cartesian meshes. In an attempt to overcome the aforementioned issues, we employ the building‐cube method, where the computational domain is divided into cubic regions called cubes. Each cube is divided at equal intervals, the same number of cubes is assigned to each core, and the spatial loop processing is executed for each cube. The numerical method is verified by computing five numerical examples. In the weak scaling test, the parallel efficiency at 32768 cores with 32 cores as a reference is 93.6%. In the strong scaling test, the parallel efficiency at 32768 cores with 128 cores as a reference is 70.2%. [ABSTRACT FROM AUTHOR]

What wavelengths do undulatory swimmers use during propulsion? In this work we find that a wide range of body/caudal fin (BCF) swimmers, from larval zebrafish and herring to fully–grown eels, use specific wavelength (ratio of wavelength to tail amplitude of undulation) values that fall within a relatively narrow range. The possible emergence of this constraint is interrogated using numerical simulations of fluid–structure interaction. Based on these, it was found that there is an optimal specific wavelength (OSW) that maximizes the swimming speed and thrust generated by an undulatory swimmer. The observed values of specific wavelength for BCF animals are relatively close to this OSW. The mechanisms underlying the maximum propulsive thrust for BCF swimmers are quantified and are found to be consistent with the mechanisms hypothesized in prior work. The adherence to an optimal value of specific wavelength in most natural hydrodynamic propulsors gives rise to empirical design criteria for man–made propulsors. [ABSTRACT FROM AUTHOR]

Examples of animals evolving similar traits despite the absence of that trait in the last common ancestor, such as the wing and camera-type lens eye in vertebrates and invertebrates, are called cases of convergent evolution. Instances of convergent evolution of locomotory patterns that quantitatively agree with the mechanically optimal solution are very rare. Here, we show that, with respect to a very diverse group of aquatic animals, a mechanically optimal method of swimming with elongated fins has evolved independently at least eight times in both vertebrate and invertebrate swimmers across three different phyla. Specifically, if we take the length of an undulation along an animal’s fin during swimming and divide it by the mean amplitude of undulations along the fin length, the result is consistently around twenty. We call this value the optimal specific wavelength (OSW). We show that the OSW maximizes the force generated by the body, which also maximizes swimming speed. We hypothesize a mechanical basis for this optimality and suggest reasons for its repeated emergence through evolution. [ABSTRACT FROM AUTHOR]

Nearly eighty years ago, Gray reported that the drag power experienced by a dolphin was larger than the estimated muscle power - this is termed as Gray's paradox. We provide a fluid mechanical perspective of this paradox. The viewpoint that swimmers necessarily spend muscle energy to overcome drag in the direction of swimming needs revision. For example, in undulatory swimming most of the muscle energy is directly expended to generate lateral undulations of the body, and the drag power is balanced not by the muscle power but by the thrust power. Depending on drag model utilized, the drag power may be greater than muscle power without being paradoxical. [ABSTRACT FROM AUTHOR]

While wake structures of many forms of swimming and flying are well characterized, the wake generated by a freely swimming undulating fin has not yet been analyzed. These elongated fins allow fish to achieve enhanced agility exemplified by the forward, backward and vertical swimming capabilities of knifefish, and also have potential applications in the design of more maneuverable underwater vehicles. We present the flow structure of an undulating robotic fin model using particle image velocimetry to measure fluid velocity fields in the wake. We supplement the experimental robotic work with highfidelity computational fluid dynamics, simulating the hydrodynamics of both a virtual fish, whose fin kinematics and fin plus body morphology are measured from a freely swimming knifefish, and a virtual rendering of our robot. Our results indicate that a series of linked vortex tubes is shed off the long edge of the fin as the undulatory wave travels lengthwise along the fin. A jet at an oblique angle to the fin is associated with the successive vortex tubes, propelling the fish forward. The vortex structure bears similarity to the linked vortex ring structure trailing the oscillating caudal fin of a carangiform swimmer, though the vortex rings are distorted because of the undulatory kinematics of the elongated fin. [ABSTRACT FROM AUTHOR]

This study was designed to develop a computational fluid dynamics (CFD) method for unsteady analysis of a series of ski jump movements with attitude changes, and to analyse the aerodynamic characteristics of an expert jumper over the entire ski jump movement. Two ski jumpers participated in this study. A sensor-based motion capture suit was used to capture the jumper’s posture during the actual ski jump. A three-dimensional computer graphics animation was created by superimposing the joint angles obtained from the motion measurements of the 3D shape of the athlete. The unsteady aerodynamic forces acting on the ski jumper, from the takeoff to the landing, were then calculated using CFD. A time-varying spatially uniform flow was specified as the inflow boundary condition of the computational domain. The results indicated that both the lift and drag forces of the expert jumper increase rapidly during the initial flight when the jumper’s posture changes drastically. Thereafter, drag force decreased considerably, but the decrease in the lift force was less drastic. Later in the flight phase, the lift force acting on the expert jumper increased, and throughout the flight phase, the lift-drag ratio of the expert jumper remained higher than that of the unskilled jumper. [ABSTRACT FROM AUTHOR]

During an attempt to work on a stratified flow problem envisaged as a sequel of the paper by Sameen & Govindarajan (2007), it was found that the original paper contained errors in §§ 3.4 and 4.3 due to a factor of iα, which was inadvertently missed in two places in the code (i) in the buoyancy term due to the use of vertical velocity and streamfunction interchangeably, and (ii) in the apportionment between kinetic and potential energy in the Gmax calculation. Because of this, there were significant differences in the effect of Grashof number on stability. Figure 1 is the modified figure 9 of the original paper, for Pr =7 and ΔT = 25 K. The Poiseuille–Rayleigh–Bénard mode appears at Gr = 39.12 and is seen not to merge with the Poiseuille mode, unlike the conclusion made earlier. This modification applies at any Prandtl number from 10−2 to 102. The corrected versions of figures 17 and 21, showing Gmax contours for different Pr at Gr = 0 and different Gr for Pr = 1, are plotted in figures 2 and 3, respectively. The large growth reported at β = 0 was thus erroneous. The other main conclusions of the paper, that Prandtl number changes transient growth qualitatively, but not the least stable eigenmode, whereas viscosity stratification, which has a huge impact on exponential growth/decay, does not change transient growth much, remain the same. The secondary instabilities also remain unchanged. The stability equations (3.2) to (3.4) in the paper should read (for explanation, please refer to Sameen & Govindarajan 2007) (1)\begin{eqnarray} &&\hspace*{-6pt}\text{i}\alpha\left[(v^{\prime\prime}-(\alpha^2+\beta^2))(U-c)-U^{\prime\prime} v\right] =\frac{1}{Re}\bigg[\mu \left[v^{\text{i}v}-2(\alpha^2+\beta^2)v^{\prime\prime} +(\alpha^2+\beta^2)^2 v\right] \nonumber\\[2pt] &&+\,\frac{\text{d}\mu}{\text{d}T}T^{\prime}2 [v^{\prime\prime\prime}-(\alpha^2+\beta^2)v^{\prime}] +\frac{\text{d}\mu}{\text{d}T}T^{\prime\prime}[v^{\prime\prime}+(\alpha^2+\beta^2) v] +\frac{\text{d}^2\mu}{\text{d}T^2}\left(T^{\prime}\right)^2[v^{\prime\prime}+(\alpha^2+\beta^2) v] \nonumber \\[2pt] && -\,\frac{\text{d}\mu}{\text{d}T}\text{i}\alpha[U^{\prime}\hat{T}^{\prime\prime}+2U^{\prime\prime}\hat{T}^{\prime} +(\alpha^2U^{\prime}+U^{\prime\prime\prime})\hat{T}] -2\text{i}\alpha\frac{\text{d}^2\mu}{\text{d}T^2}U^{\prime}T^{\prime}\hat{T}^{\prime} -\text{i}\alpha\frac{\text{d}^2\mu}{\text{d}T^2}T^{\prime\prime}U^{\prime}\hat{T} \nonumber\\[2pt] && -\,2\text{i}\alpha\frac{\text{d}^2\mu}{\text{d}T^2}U^{\prime\prime}T^{\prime}\hat{T} -\text{i}\alpha\frac{\text{d}^3\mu}{\text{d}T^3}U^{\prime}(T^{\prime})^2\hat{T} {+\frac{Gr}{Re} (\alpha^2+\beta^2) \hat{T}}\bigg], \label{orr_eqn} \end{eqnarray}(2)\begin{flequation} \text{i}\alpha (U-c) \eta +\text{i}\beta U^{\prime}v=\frac{1}{Re}\bigg[\mu \big[\eta^{\prime\prime} -(\alpha^2+\beta^2)\eta\big] +\frac{\text{d}\mu}{\text{d}T}T^{\prime}\eta^{\prime}\nonumber \\ +\,\text{i}\beta\frac{\text{d}\mu}{\text{d}T}(U^{\prime\prime}\hat{T} +U^{\prime}\hat{T}^{\prime})+\text{i}\beta\frac{\text{d}^2\mu}{\text{d}T^2}T^{\prime}U^{\prime}\hat{T} \bigg], \label{sq_eqn} \end{flequation}(3)\begin{eqnarray} \text{i}\alpha (U-c)\hat T+{T}^{\prime}v =\frac{1}{RePr}[{\hat T}^{\prime\prime}-(\alpha^2 + \beta^2)\hat T]. \label{eneT_eqn} \end{eqnarray} [ABSTRACT FROM AUTHOR]

Natural convection is commonly used as a means of heat transfer in many practical products because it is highly cost-effective. The development of simulation tools for this type of application is generally accompanied by several critical issues, including high-temperature differences, rapid turnaround demand, and complex geometries. Under conditions of natural convection with high-temperature differences, the density of the medium is variable but the flow speed is low. Therefore, a compressible solver, i.e., Roe scheme developed by P.L. Roe in 1981, must be combined with a preconditioning method that can make the Roe scheme available at low speeds to allow the above situation to be addressed. The building cube method is adopted to make our method suitable for massive parallelization systems, which can reduce the calculation and turnaround times immensely. An immersed boundary method for compressible flows combined with a fast, easy to implement, and robust interpolation method is developed to handle flows with complex immersed geometries. The results show that the program described here is suitable for application to product design and analysis because of its wide applicability to natural convection with high-temperature differences, its capacity to handle complex geometries, and its feasibility for use in massive parallelization systems. [ABSTRACT FROM AUTHOR]

For nearly a century, researchers have tried to understand the swimming of aquatic animals in terms of a balance between the forward thrust from swimming movements and drag on the body. Prior approaches have failed to provide a separation of these two forces for undulatory swimmers such as lamprey and eels, where most parts of the body are simultaneously generating drag and thrust. We nonetheless show that this separation is possible, and delineate its fundamental basis in undulatory swimmers. Our approach unifies a vast diversity of undulatory aquatic animals (anguilliform, sub-carangiform, gymnotiform, bal-istiform, rajiform) and provides design principles for highly agile bioinspired underwater vehicles. This approach has practical utility within biology as well as engineering. It is a predictive tool for use in understanding the role of the mechanics of movement in the evolutionary emergence of morphological features relating to locomotion. For example, we demonstrate that the drag-thrust separation framework helps to predict the observed height of the ribbon fin of electric knifefish, a diverse group of neotropical fish which are an important model system in sensory neurobiology. We also show how drag-thrust separation leads to models that can predict the swimming velocity of an organism or a robotic vehicle.