Abstract

Marine fog is defined as a turbulent air layer contiguous the ocean surface, laden with ~ 1-30 microns sized water droplets, characterized by the Meteorological Optical Range (i.e., visibility) less than 1 km. Fog disrupts transportation, poses security threats, disorients human perception and impacts communications and ecosystems. Net deposition of water vapor on hygroscopic aerosols in near-saturated marine environments leads to marine fog through collusion of dynamic, thermodynamic and physicochemical processes. On larger scales, temperature inhomogeneities of synoptic [low-pressure, colder] weather systems break down to the dissipation (Obukhov-Corrsin) scales, providing an entrée for marine-fog genesis. Evolving fog droplets and their aerosol nuclei are embedded in the smallest (Kolmogorov) eddies of atmospheric turbulence, and a host of two-phase microphysical process involving deposition/evaporation on/from the droplets, droplet surface tension, and eddy straining motions affect the growth, maturation and dissipation (i.e., lifecycle) of fog. This presentation will describe some major findings of a five-year (2021-26) multidisciplinary, multi-investigator, integrative project dubbed Fatima (Fog and turbulence interactions in the marine atmosphere) on marine fog. Ship and land/platform-based field observations in Grand Banks, Sable Island (an islet in the region where warm Gulf Stream and cold Labrador waters mix) and Hibernia Oil Platform in 2022 as well as multi-ship and aircraft observations in the Yellow Sea (off-coast of the Republic of Korea) in 2023, all accompanied by high-resolution and numerical weather prediction (NWP) model simulations, elicited new meteorological and [bio]physicochemical processes associated with fog lifecycle. The results elicited new physical processes, and indicated some commonly used concepts on fog dynamics need revisiting. This work was funded by the Grant N00014-21-1-2296 of the US Office of Naval Research, administered by the Marine Meteorology and Space Weather Program.

Abstract

Large-eddy simulation (LES) has been increasingly used to predict turbulent flows in navy hydrodynamics, such as flow-structure interaction and hydro-acoustics. These tasks require that LES should be time-accurate: it can correctly predict wavenumber-frequency spectra of velocity and pressure fields and their equivalent space-time correlations. The conventional turbulence models based on one single flow process suffers from their capability of representing the competitive balances of multiple flow processes, such as energy dissipation and random backscatter, attached and separated flows, and the numerical issues, such as stochastic and realization differentials. The machine learning method is potential to become the workhorse for turbulence modelling and numerical issues. In this talk, we present our recent work. (1) Data-driven turbulence models with random forcing: this class of models can be used to correctly predict wavenumber and frequency energy spectra and thus turbulence-generated noise; (2) Knowledge integrated additive (KIA) wall model: this model overcome the issue of “catastrophic forgetting” in machines learning and can be used to numerically simulate attached and separated flows. (3) LES-based shape optimization: the regularized ensemble Kalman method is introduced to overcome the blow-up of model gradients due to the chaotic nature of turbulence and the LES used for reduction of turbulence-generated noise. The application of LES to the noise radiated from turbulent flows around underwater vehicles is also presented.

Abstract

Fish exhibit exceptional hydrodynamic performance, combining energy-efficient propulsion, agile manoeuvring, and adaptive environmental sensing. This keynote presents a multidisciplinary research effort, with a primary focus on marine hydrodynamics, aimed at exploring and characterizing biological swimming mechanisms to inform the design of next￾generation underwater vehicles and robots. Application areas include marine aquaculture, underwater monitoring, and autonomous exploration. The work integrates experimental, theoretical, and numerical approaches. Controlled experiments on live fish were conducted in swim tunnels using species representative of two different swimming modes. Configurations such as solitary and schooling arrangements were tested to analyse behavioural and hydrodynamic influences on swimming efficiency. These experiments also addressed boundary effects, body size, and critical swimming speed, factors relevant for both biological insight and aquaculture system optimisation. Complementing the experimental work, advanced numerical simulations were carried out using two-dimensional, self-propelled fish-like foils. These investigated the effects of body shape, motion strategies (e.g., prescribed undulation, rigid flapping, morphing bodies), and flow regimes on propulsive performance. Parametric analyses examined thrust generation, input power, recoil effects, and flow confinement, offering insights into how different features can influence locomotion and energy efficiency in engineered systems. Two pillars of ongoing research are also discussed. The first involves theoretical and numerical investigations using simplified hydrodynamic and structural models to advance the understanding of stability and manoeuvrability as functions of body morphology, fin positioning, and material flexibility. These studies support design strategies for robotic platforms capable of tuning stiffness or adapting morphology to improve directional control and passive stability. The second pillar concerns bio-inspired flow sensing, modelled after the lateral-line system. A digital twin and signal-processing framework is introduced to investigate how distributed passive sensors mounted on a vehicle can interpret wake dynamics and detect upstream obstacles. Both simulations and experimental validations support the feasibility of such sensing strategies to enhance environmental awareness and obstacle avoidance in cluttered or low-visibility environments. This keynote will also present relevant findings from the state-of-the-art in the field, such as the role of added-mass in fish-like manoeuvring, and will outline potential future research directions. While significant progress has been made, further work is required to fully uncover the key hydrodynamic principles of biological swimming and effectively translate them into adaptable, efficient, and sustainable technologies for underwater applications.

Abstract

Waves have distinctive properties that enable intriguing applications, such as cloaking, super-resolution imaging, defect detection, and noise and vibration control. In this lecture, the speaker will focus on two key properties: time reversibility and subwavelength control. He will use experimental and numerical examples to demonstrate and explain these properties across various types of waves. Following this, he will present findings from the application of these techniques in over 15 real-world projects related to water supply and drainage systems. Additionally, the speaker will discuss recent research on subwavelength control of coastal gravity waves using Helmholtz resonators and highlight their significant potential for coastal engineering applications.