Previous Talks

Speaker: Dr. Ryo Araki (Assistant Professor, Tokyo University of Science)

Abstract: The small-scale universality of developed turbulence is often described as the small scales "forgetting" the macroscopic flow characteristics during the scale-local energy cascade. However, turbulence is inherently causal; for example, temporal fluctuations of small-scale quantities (such as the energy dissipation rate) exhibit a time-delayed correlation with large-scale quantities (such as the energy input rate). To reconcile this apparent paradox, we analysed high-Reynolds-number homogeneous and isotropic turbulence using information flux, a measure of how knowledge of a variable's current state reduces uncertainty about the future state of another variable in a dynamical system. Our analysis revealed a scale-local forward information transfer within the inertial range, accompanying the energy cascade. Furthermore, we examined the roles of different cascade mechanisms - vortex stretching (VS) and strain self-amplification (SSA) - in both energy and information transfer. Our findings indicate that these two transfers are governed by different mechanisms: the dominant energy cascade mechanism is not necessarily the most causal one, and vice versa.

Speaker: Mr. Jungjae Woo (Ph.D. student, Korea University)

Abstract: The integration of microbubble technology into fluid systems has opened new avenues for efficient and eco-friendly cleaning applications. This talk will present recent advancements in utilizing microbubble jets to enhance oil removal and energy efficiency in various cleaning applications. Microbubbles, characterized by their unique hydrodynamic properties and prolonged stability, have been shown to improve the removal of oil contaminants through enhanced jet instability, surface interactions, and turbulence intensification. To better understand the underlying mechanisms, the hydrodynamic characteristics of microbubble jets were analyzed, focusing on their influence on jet instability, velocity fields, and breakup dynamics. By incorporating microbubbles into conventional water jets, cleaning efficiency can be increased while reducing the reliance on chemical detergents and excessive water usage. These findings highlight the role of microbubble-driven jet instabilities in modifying flow behavior and their potential in developing next-generation eco-friendly cleaning technologies with maximized performance and minimized energy consumption.

Speaker: Dr. Mario Rüttgers (Researcher, Walter Benjamin Fellow, Inha University) [GS]

Abstract: With rising concerns regarding global warming and energy security, there is an increasing demand for renewable energy sources. Recently, meteorology-dependent renewable urban energy resources, i.e., urban wind turbines or solar energy devices, play a more and more important role in helping cities in shifting to an energy self-sufficient or energy positive status. This talk presents a tool that is developed for optimizing the utilization of urban wind turbines. The tool is realized with an optimization algorithm that combines and locates horizontal and vertical turbines in urban planning scenarios, while receiving feedback from urban flow predictions combined with the turbines’ power curves. The flow predictions are done by a graph convolutional neural network (GCNN) that is trained with data from computational fluid dynamics (CFD) simulations of randomly defined urban flows. The GCNN is fed with two types of inputs, i.e., information about the topology of the urban area, and wind conditions at the boundaries. The network is tested with cutouts of real cities and boundary conditions from publicly available meteorological data. The tool assists city planners in finding the perfect number and locations for urban wind turbines.

Speaker: Mr. Jiyeon Kim (Ph.D. student, Yonsei University) [GS]

Abstract: Recent advances in deep learning (DL) have highlighted the potential of generative models, which learn unknown data distributions to generate new samples from noise. By incorporating conditional inputs, these models enable various applications, including dynamics prediction, where past fields are used to predict future states. While generative adversarial network (GAN)-based models have dominated the field, challenges such as scalability and training instability persist. Recently, diffusion probabilistic models (DMs) have emerged, offering the robustness of likelihood-based approaches and achieving performance comparable to or surpassing GANs. However, their computational cost is significantly higher, often orders of magnitude greater than GANs with similar performance. This talk presents the application of DM to 2D turbulence prediction, along with a comprehensive performance evaluation against various DL models, including a conditional GAN. Our findings show that DMs outperform others at lead times shorter than the Eulerian integral time scale but experience significant performance degradation at longer lead times. Ongoing efforts to extend DMs to 3D turbulence prediction will also be discussed.

Speaker: Dr. Taeseok Kim (Assistant Professor, Jeju National University) [GS]

Abstract: The trend toward downsizing nuclear reactors is gaining significant traction due to enhanced safety and operational flexibility. The thermal components of reactors must also be reduced in size to meet compact design requirements. Among these components, the steam generator plays a critical role in nuclear reactor systems. Current small modular reactor (SMR) designs predominantly employ once-through helical steam generators; however, this approach faces limitations when adapting SMRs for maritime applications or low-power systems. The printed circuit heat exchanger (PCHE) has emerged as a promising alternative for steam generator applications due to its compact and efficient design. However, the characteristics of two-phase flow and boiling heat transfer in mini-channels, a key feature of PCHEs, remains insufficiently understood for direct application. In mini-channels, pressure drop and heat transfer coefficients significantly differ from those observed in conventional steam generator pipes. Two-phase flow parameters such as void fraction, flow regimes, and channel geometry can strongly influence these parameters. We are conducting research on the effects of PCHE design on two-phase flow pressure drops, heat transfer, and superheated steam generation.

Speaker: Mr. Yuta Iwatani (Ph.D. student, Tohoku University) [GS]

Abstract: Wall temperature can affect the dynamics of compressible flows through the dynamic viscosity and the nonlinear coupling of kinetic and internal energy, and the laminar-to-turbulent transition of the boundary layer (BL) is no exception. In this study, we investigate the effects of wall heat fluxes on the subharmonic transition of the boundary layer at Mach number 0.8 using direct numerical simulation (DNS), ultimately aiming to achieve drag reduction by controlling the BL in aircraft and other fluid machinery with wall temperature. The DNS results show that wall heating promotes the transition while cooling delays it. Notably, wall cooling impedes the growth of the two-dimensional linearly unstable mode (Mack’s first mode), while the subharmonic secondary instability of the first mode emerges, leading to flow behavior similar to oblique transition, distinct from the H-type transition observed in the heated and adiabatic cases. This shift in the predominant scenario, or the dominant modes, alters the nonlinear mode interactions in the transitional BL. We examine these nonlinear interactions of modes in the transitional BL using bispectral mode decomposition (BMD) and discuss the connection of the nonlinear mode interactions to the skin friction coefficient with the aid of the angular momentum integral analysis.

Speaker: Dr. Chungil Lee (Postdoctoral Research Associate, Tohoku University) [GS]

Abstract: Supersonic jets generated from the engine of the rocket and supersonic aircraft emit very strong noise. Screech tones are dominant noise source of jets and can cause structural fatigue in rockets and supersonic aircraft. Therefore, a precise understanding of screech dynamics is essential for both predicting and reducing screech tones. While many studies have been conducted to understand screech dynamics, the 3D unsteady dynamics of screech tones have not been experimentally reported due to the low temporal resolution of high-speed cameras. In the present work, we develop a 3D spatiotemporal super-resolution measurement technique to reconstruct time-resolved (TR) 3D flow fields from sensor data*. This approach simultaneously conducted the non-time-resolved 3D background oriented schlieren (3D-BOS) and TR microphone measurements. A linear regression model between 3D-BOS and microphone data is constructed to estimate TR 3D flow fields associated with screech tones from the microphone data. Using the proposed method, the intermittent events and azimuthal switching of flow structures associated with screech tones can be analyzed. (*Reference: Lee et al., Phys. Fluids, 2023)

Speaker: Dr. Shuji Otomo (Assistant Professor, Tokyo University of Agriculture and Technology) [GS]

Abstract: Accurate, non-intrusive force measurement remains challenging in many scenarios, particularly those involving animals or vehicles. Estimating forces from flowfields obtained via particle image velocimetry (PIV) has shown promise but remains highly complex. This talk presents the vortex force map (VFM) method as a solution for computing unsteady forces from PIV data. Beyond force computation, the VFM method also visualises the contribution of individual vortical structures to the overall force. The VFM method is applied to three kinematic cases: surging flat plates and pitching NACA 0018 aerofoils, at Reynolds numbers on the order of 10,000. These flows are characterised by massive separation, with coherent leading-edge and trailing-edge vortex shedding. In all cases, the VFM method demonstrates strong agreement with direct force measurements. Additionally, it proves robust to noise, a critical consideration in experimental fluid mechanics*. (* Reference: Otomo et al., Exp. Fluids, 2025, accepted)