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Infrastructure sensors installed at elevated positions offer a broader perception range and encounter fewer occlusions. Integrating both infrastructure and ego-vehicle data through V2X communication, known as vehicle-infrastructure cooperation, has shown considerable advantages in enhancing perception capabilities and addressing corner cases encountered in single-vehicle autonomous driving. However, cooperative perception still faces numerous challenges, including limited communication bandwidth and practical communication interruptions. In this paper, we propose CTCE, a novel framework for cooperative 3D object detection. This framework transmits queries with temporal contexts enhancement, effectively balancing transmission efficiency and performance to accommodate real-world communication conditions. Additionally, we propose a temporal-guided fusion module to further improve performance. The roadside temporal enhancement and vehicle-side spatial-temporal fusion together constitute a multi-level temporal contexts integration mechanism, fully leveraging temporal information to enhance performance. Furthermore, a motion-aware reconstruction module is introduced to recover lost roadside queries due to communication interruptions. Experimental results on V2X-Seq and V2X-Sim datasets demonstrate that CTCE outperforms the baseline QUEST, achieving improvements of 3.8% and 1.3% in mAP, respectively. Experiments under communication interruption conditions validate CTCE's robustness to communication interruptions., Comment: Accepted by IEEE ITSC 2024

Solidification of droplets is of great importance to various technological applications, drawing considerable attention from scientists aiming to unravel the fundamental physical mechanisms. In the case of multicomponent droplets undergoing solidification, the emergence of concentration gradients may trigger significant interfacial flows that dominate the freezing dynamics. Here, we experimentally investigate the fascinating snow-globe freezing dynamics of supercooled ethanol-water droplets. We reveal that these unique freezing dynamics are driven by solidification-induced solutal Marangoni flow within the droplets. We quantitatively characterize the concentration-dependent migration and growth dynamics of ice particles, tightly connecting them to the solutal Marangoni effect and the associated convective heat transfer. Moreover, we show that the final wrapping state of droplets can be modulated by the concentration of ethanol. Our findings may pave the way for novel insights into the physicochemical hydrodynamics of multicomponent liquids undergoing phase transitions., Comment: 5 pages, 4 figures

We investigate the coupling effects of the two-phase interface, viscosity ratio, and density ratio of the dispersed phase to the continuous phase on the flow statistics in two-phase Taylor-Couette turbulence at a system Reynolds number of 6000 and a system Weber number of 10 using interface-resolved three-dimensional direct numerical simulations with the volume-of-fluid method. Our study focuses on four different scenarios: neutral droplets, low-viscosity droplets, light droplets, and low-viscosity light droplets. We find that neutral droplets and low-viscosity droplets primarily contribute to drag enhancement through the two-phase interface, while light droplets reduce the system's drag by explicitly reducing Reynolds stress due to the density dependence of Reynolds stress. Additionally, low-viscosity light droplets contribute to greater drag reduction by further reducing momentum transport near the inner cylinder and implicitly reducing Reynolds stress. While interfacial tension enhances turbulent kinetic energy (TKE) transport, drag enhancement is not strongly correlated with TKE transport for both neutral droplets and low-viscosity droplets. Light droplets primarily reduce the production term by diminishing Reynolds stress, whereas the density contrast between the phases boosts TKE transport near the inner wall. Therefore, the reduction in the dissipation rate is predominantly attributed to decreased turbulence production, causing drag reduction. For low-viscosity light droplets, the production term diminishes further, primarily due to their greater reduction in Reynolds stress, while reduced viscosity weakens the density difference's contribution to TKE transport near the inner cylinder, resulting in a more pronounced reduction in the dissipation rate and consequently stronger drag reduction. Our findings provide new insights into the turbulence modulation in two-phase flow.

The radar signal processing algorithm is one of the core components in through-wall radar human detection technology. Traditional algorithms (e.g., DFT and matched filtering) struggle to adaptively handle low signal-to-noise ratio echo signals in challenging and dynamic real-world through-wall application environments, which becomes a major bottleneck in the system. In this paper, we introduce an end-to-end through-wall radar human detection network (TWP-CNN), which takes raw radar Analog-to-Digital Converter (ADC) signals without any preprocessing as input. We replace the conventional radar signal processing flow with the proposed DFT-based adaptive feature extraction (DAFE) module. This module employs learnable parameterized 3D complex convolution layers to extract superior feature representations from ADC signals, which is beyond the limitation of traditional preprocessing methods. Additionally, by embedding phase information from radar data within the network and employing multi-task learning, a more accurate detection is achieved. Finally, due to the absence of through-wall radar datasets containing raw ADC data, we gathered a realistic through-wall (RTW) dataset using our in-house developed through-wall radar system. We trained and validated our proposed method on this dataset to confirm its effectiveness and superiority in real through-wall detection scenarios., Comment: 11pages,13figures

Understanding the solidification dynamics of impacted water droplets is fundamental and crucial for applications, especially with the presence of frost and salt. Here, we experimentally investigate the spreading and freezing dynamics of saline droplets upon impact on a cold, frosty surface. Our findings demonstrate that the frost and salt can lead to an extended spreading of impacted droplets under specific conditions. In addition to the well-known 1/2 inertial spreading scaling law for droplets impact on a cold substrate, we observe a distinct transition to a 1/10 scaling law dominated by the capillary-viscous relation at low impacting velocities. We formulate the onset criterion for this extended spreading regime and derive a scaling dependence that captures the droplet's arrested diameter over various supercooling temperatures, by incorporating the effect of impact inertia, partial-wetting behavior and salinity. Based on the analysis, a unified model is proposed for predicting the droplet arrested diameter over a wide range of impact velocity and salinity., Comment: 10 pages, 10 figures

The fields of therapeutic application and drug research and development (R&D) both face substantial challenges, i.e., the therapeutic domain calls for more treatment alternatives, while numerous promising pre-clinical drugs have failed in clinical trials. One of the reasons is the inadequacy of Cross-drug Response Evaluation (CRE) during the late stages of drug R&D. Although in-silico CRE models bring a promising solution, existing methodologies are restricted to early stages of drug R&D, such as target and cell-line levels, offering limited improvement to clinical success rates. Herein, we introduce DeepCRE, a pioneering AI model designed to predict CRE effectively in the late stages of drug R&D. DeepCRE outperforms the existing best models by achieving an average performance improvement of 17.7% in patient-level CRE, and a 5-fold increase in indication-level CRE, facilitating more accurate personalized treatment predictions and better pharmaceutical value assessment for indications, respectively. Furthermore, DeepCRE has identified a set of six drug candidates that show significantly greater effectiveness than a comparator set of two approved drugs in 5/8 colorectal cancer organoids. This demonstrates the capability of DeepCRE to systematically uncover a spectrum of drug candidates with enhanced therapeutic effects, highlighting its potential to transform drug R&D.

Evaporation of multicomponent droplets is important in a wide range of applications, albeit complex, and requires a careful investigation. We experimentally and numerically investigate the evaporation characteristics of spherical, ethanol-water droplets with different initial concentration ratios in the acoustic levitation field. Imaging techniques and infrared thermometry are used for acquiring volume and surface temperature variations of droplets, reflecting their mass and heat transfer characteristics. Numerical simulations are conducted using modified parameters based on a theoretical model to consider the effect of the acoustic field. The calculation results show good agreement with the experimental data. The concentration and temperature distribution within the droplet is further investigated based on the numerical results., Comment: 14 pages, 6 figures

We perform the linear stability analysis and direct numerical simulations to study the effect of radius ratio on the instability and flow characteristics of the sheared annular centrifugal Rayleigh-B\'enard convection (ACRBC), where the cold inner cylinder and the hot outer cylinder rotate with a small angular velocity difference. With the shear enhancement, the thermal convection is suppressed and finally gets stable for different radius ratios $\eta\in[0.2, 0.95]$. Considering the inhomogeneous distribution of shear stresses in the base flow, a new global Richardson number $Ri_g$ is defined and the marginal-state curves for different radius ratios are successfully unified in the parameter domain of $Ri_g$ and the Rayleigh number $Ra$. The results are consistent with the marginal-state curve of the wall-sheared classical RBC in the streamwise direction, demonstrating that the basic stabilization mechanisms are identical. Moreover, systems with small radius ratios exhibit greater geometric asymmetry. On the one hand, this results in a smaller equivalent aspect ratio for the system, accommodating fewer convection roll pairs. Fewer roll pairs are more likely to cause a transition in the flow structure during shear enhancement. On the other hand, the shear distribution is more inhomogeneous, allowing for an outward shift of the convection region and the elevation of bulk temperature under strong shear.

Photonic integrated circuits based on erbium doped thin film lithium niobate on insulator has attracted broad interests with insofar various waveguide amplifiers and microlasers demonstrated. Wideband operation facilitated by the broadband absorption and emission of erbium ions necessitates the functional integration of wavelength filter and multiplexer on the same chip. Here a low-loss wavelength division multiplexer at the resonant pumping and emission wavelengths (~1480 nm and 1530~1560 nm) of erbium ions based on angled multimode interferometer, is realized in the erbium doped thin film lithium niobate on insulator fabricated by the photolithography assisted chemomechanical etching technique. The minimum on-chip insertion losses of the fabricated device are <0.7 dB for both wavelength ranges, and a 3-dB bandwidth of >20 nm is measured at the telecom C-band. Besides, direct visualization of the multimode interference pattern by the visible upconversion fluorescence of erbium ions compares well with the simulated light propagation in the multimode interferometer. Spectral tuning of the wavelength division multiplexer by structural design is also demonstrated and discussed., Comment: 11 pages, 5 figures

This work presents the first fabricated electrophysiology-optogenetic closed-loop bidirectional brain-machine interface (CL-BBMI) system-on-chip (SoC) with electrical neural signal recording, on-chip sleep staging and optogenetic stimulation. The first multiplexer with static assignment based table lookup solution (MUXnet) for multiplier-free NN processor was proposed. A state-of-the-art average accuracy of 82.4% was achieved with an energy consumption of only 0.2$\mu$J/class in sleep staging task., Comment: 2 pages, 6 figures. Accepted by IEEE Custom Integrated Circuits Conference (CICC) 2024. The codes for the MUXnet (constructing neural networks using multiplexers instead of multipliers) will be open-sourced after the Journal version of this work is accepted

This paper studies the distributed optimization problem under the influence of heavy-tailed gradient noises. Here, a heavy-tailed noise means that the noise does not necessarily satisfy the bounded variance assumption. Instead, it satisfies a more general assumption. The commonly-used bounded variance assumption is a special case of the considered noise assumption. A typical example of this kind of noise is a Pareto distribution noise with tail index within (1,2], which has infinite variance. Despite that there has been several distributed optimization algorithms proposed for the heavy-tailed noise scenario, these algorithms need a centralized server in the network which collects the information of all clients. Different from these algorithms, this paper considers that there is no centralized server and the agents can only exchange information with neighbors in a communication graph. A distributed method combining gradient clipping and distributed stochastic subgradient projection is proposed. It is proven that when the gradient descent step-size and the gradient clipping step-size meet certain conditions, the state of each agent converges to the optimal solution of the distributed optimization problem with probability 1. The simulation results validate the algorithm.

Superconducting materials exhibit unique physical properties and hold great scientific value and vast industrial application prospects. However, due to limitations such as critical temperature (TC) and critical current density (JC), the large-scale application of superconducting materials remains challenging. Chemical doping has been a commonly used method to enhance the superconductivity of B(P)SCCO. However, satisfactory enhancement results have been difficult to achieve. In this study, we introduced green light GaN p-n junction particles as inhomogeneous phases into B(P)SCCO polycrystalline particles to form a smart meta-superconductors (SMSCs) structure. Based on the electroluminescence properties of the p-n junction, the Cooper pairs were stimulated and strengthened to enhance the superconductivity of B(P)SCCO. Experimental results demonstrate that the introduction of inhomogeneous phases can indeed enhance the critical temperature TC, critical current density JC, and complete diamagnetism (Meissner effect) of B(P)SCCO superconductors. Moreover, When the particle size of raw material of B(P)SCCO is reduced from 30{\mu}m to 5{\mu}m, the grain size of the sintered samples also decreases, and the optimal doping concentration of the inhomogeneous phases increases from 0.15 wt.% to 0.2 wt.%, further improving the enhancement of superconductivity., Comment: 17 pages,7 figures

Understanding the dynamics of material objects advected by turbulent flows is a long standing question in fluid dynamics. In this perspective article we focus on the characterization of the statistical properties of non-interacting finite-sized massive spherical particles advected by a vigorous turbulent flow. We study the fluctuations and temporal correlations of particle accelerations and explore their behaviours with respect to the particle size and the particle mass density by means of fully-resolved numerical simulations. We observe that the measured trends can not be interpreted as the simple multiplicative combination of the two dominant effects: the spatial filtering of fluid accelerations and the added-mass-adjusted fluid-to-particle density ratio. We argue that other hydrodynamical forces or effects, e.g. preferential flow sampling, have still a significant role even at the largest particle sizes, which rich here the integral scale of turbulence., Comment: 7 pages, 4 figures

Direct numerical simulations are performed to explore the effects of rotating direction of the vertical asymmetric rough wall on the transport properties of Taylor-Couette (TC) flow up to a Taylor number of $\textit{Ta} = 2.39 \times 10^7$. It is shown that compared to the smooth wall, the rough wall with vertical asymmetric strips can enhance the dimensionless torque \textit{Nu}$_\omega$, and more importantly, at high \textit{Ta} clockwise rotation of the inner rough wall (the fluid is sheared by the steeper slope side of the strips) results in a significantly bigger torque enhancement as compared to the counter-clockwise rotation (the fluid is sheared by the smaller slope side of the strips) due to the larger convective contribution to the angular velocity flux, although the rotating direction has a negligible effect on the torque at low \textit{Ta}. The larger torque enhancement caused by the clockwise rotation of vertical asymmetric rough wall at high \textit{Ta} is then explained by the stronger coupling between the rough wall and the bulk due to the larger biased azimuthal velocity towards the rough wall at the mid-gap of TC system, the increased intensity of turbulence manifesting by larger Reynolds stress and thinner boundary layer, and the more significant contribution of the pressure force on the surface of rough wall to the torque., Comment: 17 pages,11 figures

The presence of a dispersed phase can significantly modulate the drag in turbulent systems. We derived a conserved quantity that characterizes the radial transport of azimuthal momentum in the fluid-fluid two-phase Taylor-Couette turbulence. This quantity consists of contributions from advection, diffusion, and two-phase interface, which are closely related to density, viscosity, and interfacial tension, respectively. We found that the presence of the two-phase interface consistently produces a positive contribution to the momentum transport and leads to drag enhancement, while decreasing the density and viscosity ratios of the dispersed phase to the continuous phase reduces the contribution of local advection and diffusion terms to the momentum transport, respectively, resulting in drag reduction. Therefore, we concluded that the decreased density ratio and the decreased viscosity ratio work together to compete with the presence of two-phase interface for achieving drag modulation in fluid-fluid two-phase turbulence.

Catastrophic phase inversion, the sudden breakdown of a dense emulsion, occurs when the dispersed majority phase irreversibly exchanges role with the continuous minority phase. This common process has been extensively studied over the past decades and yet its fundamental physical mechanism has remained largely unexplored. Here we experimentally and numerically study the dynamics of catastrophic phase inversion as it occurs when the volume fraction of the dispersed phase exceeds a critical volume fraction (typically around 92% in experiments). Our data accurately quantify the abrupt change of both the global torque and average droplet size at approaching and across the phase inversion point, exhibiting strong hysteresis. Most importantly, we reveal that the fluctuations in the global torque diverge as a power-law while approaching the critical volume-fraction and we connect their growth to the formation of highly heterogeneous spatial droplet structures. The present finding, unveiling the tight connection between fluctuations in dynamic heterogeneity and the critical divergence of torque fluctuation, paves the way to a quantitative description of catastrophic phase inversion as an out-of-equilibrium critical-like phenomena.

Wind-wave interactions impose wind forcing on wave surface and wave effects on turbulent wind structures, which essentially influences the wind-wave loading on structures. Existing research treats the wind and wave loading separately and ignores their interactions. The present study aims to characterize the turbulent airflow over wave surfaces and analyze the coupled wind-wave loading on offshore wind turbines. A high-fidelity two-phase model is developed to simulate highly turbulent wind-wave fields based on the open-source program OpenFOAM. A numerical case study is conducted to simulate extreme wind-wave conditions, where coupled wind-wave fields are applied. The intensity of wave induced turbulences and the height of wave influenced regions are affected by the wind velocity and wave heights. Higher wind velocities induce greater turbulence, which can be increased by over 100%. Then the combined wind-wave loading on offshore wind turbines is simulated under operational and extreme conditions. Under operational conditions, the wind-wave coupling effect on the combined loading is minimal. However, under extreme conditions, the coupled wind-wave fields lead to an increase in the average aerodynamic loading and a significant amplification of the fluctuation in the aerodynamic loading. Specifically, the maximum bending moment Fy at both the tower bottom and the monopile bottom experiences an increase of around 6%. The standard deviation of the shear force at the tower bottom increases by up to 45%. Also, the standard deviation of the bending moment at the tower bottom increases by approximately 27%. This study reveals the importance of considering the wind-wave coupling effect under extreme conditions, which provides valuable insights into the planning and design of offshore wind turbines., Comment: arXiv admin note: substantial text overlap with arXiv:2206.02085

Recent extreme tropical cyclones caused extensive damages to critical civil infrastructure globally. To better capture the unique hurricane wind characteristics, a large eddy simulation (LES) Hurricane Boundary Layer (HBL) model is developed by considering the variation of meso-scale kinematic and thermodynamic conditions. An asymmetric model is adopted to obtain the gradient wind velocity using the National Hurricane Center data. The meso-scale thermal conditions are obtained by extracting the hourly air temperature and relative humidity profiles from generated proxy soundings. Measurements recorded at the Aransas County airport during Hurricane Harvey and that at the City of Naples during Irma are used to validate the developed LES model. Research results show that the simulated 10-minute average wind speed and direction are consistent with the observations. The developed model can well predict the high wind turbulences, which are around 20% in Hurricane Harvey and 26% in Hurricane Irma. The 3-s gust wind speeds reach 62.4 m/s at 10-m elevation during Hurricane Harvey and 53.5 m/s at 15-m elevation during Hurricane Irma, close to the field observed data of 61.3 m/s and 54.2 m/s, respectively. The simulated 3-s gust factors are close to the observation except at some moments with significant variations because of the poorly understood physical phenomena. The simulated wind spectrum in longitudinal and lateral directions agrees well with the observed results. In summary, the developed LES-based HBL model can capture the main characteristics of hurricane structure and turbulence characteristics and is applicable for modeling civil infrastructure exposed to hurricanes.

Improving the critical temperature (TC), critical magnetic field (HC), and critical current (JC) of superconducting materials has always been one of the most significant challenges in the field of superconductivity, but progress has been slow over the years. Based on the concept of injecting energy to enhance electron pairing states, in this study, we have employed a solid-state sintering method to fabricate a series of smart meta-superconductors (SMSCs) consisting of p-n junction nanostructures with a wavelength of 550 nm, doped within an MgB2 matrix. Experimental results demonstrate that compared to pure MgB2 samples, the critical transition temperature (TC) has increased by 1.2 K, the critical current (JC) has increased by 52.8%, and the Meissner effect (HC) shows significant improvement in its diamagnetic properties. This phenomenon of enhanced superconducting performance can be explained by the coupling between superconducting electrons and evanescent waves.

Hypothesis: Surfactant-free microemulsion (SFME), an emerging phenomenology that occurs in the monophasic zone of a broad category of ternary mixtures 'hydrophobe/hydrotrope/water', has attracted extensive interests due to their unique physicochemical properties. The potential of this kind of ternary fluid for solubilization and drug delivery make them promising candidates in many industrial scenarios. Experiments: Here the thermodynamic behavior of these multiscale nanodomains formed in the ternary trans-anethol/ethanol/water system over a wide range of temperatures is explored. The macroscopic physical properties of the ternary solutions are characterized, with revealing the temperature dependence of refractive index and dynamic viscosity. Findings: With increasing temperature, the ternary system shows extended areas in the monophasic zone. We demonstrate that the phase behavior and the multiscale nanodomains formed in the monophasic zone can be precisely and reversibly tuned by altering the temperature. Increasing temperature can destroy the stability of the multiscale nanodomains in equilibrium, with an exponential decay in the scattering light intensity. Nevertheless, molecular-scale aggregates and mesoscopic droplets exhibit significantly different response behaviors to temperature stimuli. The temperature-sensitive nature of the ternary SFME system provides a crucial step forward exploring and industrializing its stability.

In this Letter, we systematically investigate the Leidenfrost temperature for hot solid substrates with various thermal diffusivities and surface roughnesses. Based on the experimental results, we build a phenomenological model that considers the thermal diffusivity of a solid substrate and derive a relationship between the surface roughness and the resulting vapor film thickness. The generality of this model is supported by experimental data for different liquids and solid substrates. Our model thus allows for a theoretical prediction of the Leidenfrost temperature and develops a comprehensive understanding of the Leidenfrost effect., Comment: 6 pages, 5 figures

Hypothesis: Multi-component droplet evaporation has received significant attention in recent years due to the broad range of applications such as material science, environmental monitoring, and pharmaceuticals. The selective evaporation induced by the different physicochemical properties of components is expected to influence the concentration distributions and the separation of mixtures, thereby leading to rich interfacial phenomena and phase interactions. Experiments: A ternary mixture system containing hexadecane, ethanol, and diethyl ether is investigated in this study. The diethyl ether exhibits both surfactant-like and co-solvent properties. Systematic experiments were performed using acoustic levitation technique to achieve a contact-less evaporation condition. The evaporation dynamics and temperature information are acquired in the experiments, using high-speed photography and infrared thermography technologies. Findings: Three distinct stages, namely, "Ouzo state", "Janus state", and "Encapsulating state", are identified for the evaporating ternary droplet in acoustic levitation. A self-sustaining periodic freezing & melting evaporation mode is reported. A theoretical model is developed to characterize the multi-stage evaporating behaviors. We demonstrate the capability to tune the evaporating behaviors by varying the initial droplet composition. This work provides a deeper understanding of the interfacial dynamics and phase transitions involved in multi-component droplets and proposes novel strategies for the design and control of droplet-based systems

Turbulent plane-Couette flow suspended with finite-size spheroidal particles is studied using fully particle-resolved direct numerical simulations. The effects of particle aspect ratio on turbulent arguments and particle statistics are explored, leading to the same conclusions as the previous experimental findings \citep{wang2022finite}. By performing stress analysis, we find that the presence of particles introduces extra stresses to the system and accounts for the global drag increases. The particle-laden flow cases exhibit spectra that are consistent with the scaling of $k^{-5/3}$ and $k^{-3}$ in the large and small scales, respectively. While the $k^{-3}$ scaling observed in the particle-laden flow is reminiscent of bubbly flow, an examination of the particle Reynolds number suggests that the mechanism responsible may not be attributable to the pseudo-turbulence induced by particles as in the case of bubbles. In the view of particle statistics, we observe that spherical and non-spherical particles preferentially cluster in the near-wall and the bulk region, respectively, and that the orientations of non-spherical particles are affected by their aspect ratios, especially in the near-wall region. The present numerical results, combined with previous experimental findings in \cite{wang2022finite}, provide in-depth information on both the fluid and the particle phase, contributing to a better understanding of particle suspension in shear flows., Comment: 22 pages, 15 figures

We perform a two-dimensional numerical study on the thermal effect of porous media on global heat transport and flow structure in Rayleigh-B\'enard (RB) convection, focusing on the role of thermal conductivity $\lambda$ of porous media, which ranges from $0.1$ to $50$ relative to the fluid. The simulation is carried out in a square RB cell with the Rayleigh number $Ra$ ranging from $10^7$ to $10^9$ and the Prandtl number $Pr$ fixed at $4.3$. The porosity of the system is fixed at $\phi=0.812$, with the porous media modeled by a set of randomly displayed circular obstacles. For a fixed $Ra$, the increase of conductivity shows a small effect on the total heat transfer, slightly depressing the Nusselt number. The limited influence comes from the small number of obstacles contacting with thermal plumes in the system as well as the counteraction of the increased plume area and the depressed plume strength. The study shows that the global heat transfer is insensitive to the conduction effect of separated porous media in the bulk region, which may have implications for industrial designs.

We investigate experimentally and theoretically the interactions between a cavitation bubble and a hemispherical pendant oil droplet immersed in water. In experiments, the cavitation bubble is generated by a focused laser pulse right below the pendant droplet with well-controlled bubble-wall distances and bubble-droplet size ratios. By high-speed imaging, four typical interactions are observed, namely, oil droplet rupture, water droplet entrapment, oil droplet large deformation, and oil droplet mild deformation. The bubble jetting at the end of collapse and the migration of the bubble centroid are particularly different in each bubble-droplet interaction. We propose theoretical models based on the method of images for calculating the Kelvin impulse and the anisotropy parameter which quantitatively reflects the migration of the bubble centroid at the end of the collapse. Finally, we explain that a combination of the Weber number and the anisotropy parameter determines the regimes of the bubble-droplet interactions., Comment: 26 pages, 14 figures

Sea ice is crucial in many natural processes and human activities. Understanding the dynamical couplings between the inception, growth and equilibrium of sea ice and the rich fluid mechanical processes occurring at its interface and interior is of relevance in many domains ranging from geophysics to marine engineering. Here we experimentally investigate the complete freezing process of water with dissolved salt in a standard natural convection system, i.e., the prototypical Rayleigh-B\'enard cell. Due to the presence of a mushy phase, the studied system is considerably more complex than the freezing of freshwater in the same conditions (Wang et al. 2021c). We measure the ice thickness and porosity at the dynamical equilibrium state for different initial salinities of the solution and temperature gaps across the cell. These observables are non-trivially related to the controlling parameters of the system as they depend on the heat transport mode across the cell. We identify in the experiments 5 out of the 6 possible modes of heat transport. We highlight the occurrence of brine convection through the mushy ice and of penetrative convection in stably stratified liquid underlying the ice. A one-dimensional multi-layer heat flux model built on the known scaling relations of global heat transport in natural convection systems in liquids and porous media is proposed. It allows, given the measured porosity of the ice, to predict the corresponding ice thickness, in a unified framework., Comment: 20 pages, 6 figures