Lam Vu

Nathanaël Machicoane

Danyu Li

Timothy B Morgan

Theodore J Heindel

Alberto Aliseda

Olivier Desjardins

A Computational Study of a Two-fluid Atomizing Coaxial Jet: Validation against Experimental Back-lit Imaging and Radiography and the Influence of Gas Velocity and Contact Line Model

Keywords: Air-blast Atomization, Contact Line Modeling, Liquid-Gas Flows, Validation

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Introduction

Two-fluid coaxial atomizers utilize a high-speed gas stream to destabilize a coflowing low-speed liquid jet. These devices are widely used in engineering systems such as spray dryers and fuel injectors. Accurate modeling of the liquid jet's initial destabilization and break up is of the upmost importance as it serves as an initial condition for the spray dispersion process. Because of the inherent difficulties associated with modeling primary atomization computationally [START_REF] Gorokhovski | Modeling primary atomization[END_REF], studies have mostly been limited to highly simplified and academic cases. Moreover, few studies have explored in detail the modeling of the nozzle exit. In particular, the impact of different modeling strategies for the high-speed gas, low-speed liquid, and the splitter plate separating the two streams, warrants careful investigation.

Liquid atomization has been studied extensively both through experiments and simulations but have had limitations based on the methods used. A non-exhaustive list of such methods are described below along with some of their limitations. Experimentally, the flow inside the nozzle cannot be easily quantified using standard particle image velocimetry (PIV) and hot-wire measurements. Back-lit imaging is an effective technique for visualizing the spray and can be used to accurately extract quantitative measurements of the liquid presence in a region where the liquid stays mostly intact [START_REF] Machicoane | Influence of steady and oscillating swirl on the near-field spray characteristics in a two-fluid coaxial atomizer[END_REF]. However, such measurements struggle in areas where the liquid is broken up and multiple liquid structures intersect a line of sight. In contrast, X-ray radiography penetrates the liquid, enabling the study of additional physics, such as bubble entrainment and contact line dynamics in extreme atomization conditions [START_REF] Machicoane | 19 Synchrotron radiography characterization of the liquid core dynamics in a canonical two-fluid coaxial atomizer[END_REF].

Recently, it has been used to extract quantitative measurements such as the integrated liquid depth along a line of sight [START_REF] Bothell | Comparison of X-ray and optical measurements in the near-field of an optically dense coaxial air-assisted atomizer[END_REF]. Simulations have had their own challenges such as robust numerical methods capable of handling topology change, discontinuous fluid properties across the interface and singular forces at the interface, and computational demand owing to the wide range of length and time scales [START_REF] Gorokhovski | Modeling primary atomization[END_REF]. Front tracking methods [START_REF] Tryggvason | A front-tracking method for the computations of multiphase flow[END_REF], which transport a surface mesh, are viable techniques but have difficulty with topology change as heuristics are needed for the deletion and re-population of surface elements. Diffuse interface methods [START_REF] Anderson | Diffuse-interface methods in fluid mechanics[END_REF] are also viable techniques, but diminish the sharpness of the discontinuities since the interface is smeared over a few computational cells. Level-set methods, which transport a signed distance function away from the interface, have been used extensively [START_REF] Sethian | Level set methods for fluid interfaces[END_REF] but suffer from mass conservation issues. These issues have been addressed by improvements such as the conservative level-set method [START_REF] Chiodi | A reformulation of the conservative level set reinitialization equation for accurate and robust simulation of complex multiphase flows[END_REF] and the refined grid level-set method [START_REF] Hermann | A balanced force refined level set grid method for two-phase flows on unstructured flow solver grids[END_REF]. Volume-of-Fluid (VOF) methods, using complex geometric transport operations [START_REF] Owkes | A computational framework for conservative, three-dimensional, unsplit, geometric transport with application to the volume-of-fluid (VOF) method[END_REF], have had success in handling topology change, ensuring discrete mass conservation and maintaining the sharp discontinuities.

Validating simulations against experiments is a crucial step in computational studies of sprays and the majority of past validation exercises of two-fluid atomizers have compared indirect quantities or reduced the modeling complexity because of the computational and experimental challenges described above. Demoulin et al. [START_REF] Demoulin | A new model for turbulent flows with large density fluctuations: Application to liquid atomization[END_REF] simulated primary break up by solving equations for a single fluid representing a liquid-gas mixture under the assumptions of high Reynolds and Weber numbers and compared centerline liquid volume fraction profiles against experiments.

Gorokhovski et al. [START_REF] Gorokhovski | Modeling primary atomization[END_REF] modeled the primary atomization by solving for the gas phase using a large-eddy simulation (LES) and the liquid phase using a stochastic liquid depletion modeling. This study yielded satisfactory agreement of liquid volume fraction distributions against experiments but most comparisons were qualitative. Fuster et al. [START_REF] Fuster | Simulation of primary atomization with an octree adaptive mesh refinement and VOF method[END_REF] presented simulations in a planar configuration at a lower viscosity and density ratio and compared droplet size distributions, as a function of mesh size, against experimental data. Fuster et al. [START_REF] Fuster | Instability regimes in the primary breakup region of planar coflowing sheets[END_REF] studied the influence of the splitter plate thickness on the peak frequency and made comparisons against linear stability analysis at low density ratios. For a single case, the frequency was compared against experiments and linear stability analysis at air-water conditions.

The study showed that at low gas-to-liquid dynamic pressure ratios, a convective instability is observed whereas at high dynamic pressure ratios, the instability is absolute. Xiao et al. [START_REF] Xiao | LES of turbulent liquid jet primary breakup in turbulent coaxial air flow[END_REF] simulated primary atomization at air-water conditions and showed great agreement in the average liquid core length, where the liquid core is defined to be the large coherent liquid structure attached to the nozzle, but generated the gas inflow using synthetic turbulence. This study showed the turbulent eddies in the liquid phase play a leading role on the interfacial instabilities. Muller et al.

[28] simulated primary break up of a high-viscosity fluid and showed excellent agreement in liquid core length and dominant frequency against experiments using the same geometry. Agbaglah et al. [START_REF] Agbaglah | Numerical simulation of the initial destabilization of an air-blasted liquid layer[END_REF] presented 3D simulations in a planar geometry at experimental air-water conditions and compared well the liquid cone length and the most unstable frequency. This study showed that inclining the gas inflow enhanced the formation of interfacial waves. Ling et al. [START_REF] Ling | Spray formation in a quasi-planar gas-liquid mixing layer at moderate density ratios: A numerical closeup[END_REF] performed massively resolved simulations at a lower density and viscosity ratio and reported on droplet size distributions, as a function of mesh size, and compared them against log-normal and Gamma distribution fits. The simulations qualitatively discussed the expansion of punctured holes in liquid sheets and the ligaments generated at the edge of their rims. Carmona et al. [START_REF] Carmona | A comparative study of direct numerical simulation and experimental results on a prefilming airblast atomization configuration[END_REF] performed simulations of a pre-filmed air-blast atomizer and made qualitative comparisons and drop size comparisons as a function of VOF iso-surface value. Even with current studies, more detailed and direct comparisons under realistic configurations are needed to validate computational capabilities.

In this work, we perform simulations of primary atomization in a coaxial two-fluid atomizer using the Volumeof-Fluid method and validate them against experiments. A novelty of our validation exercise is that we make direct comparisons of quantities obtained from experimental back-lit imaging and X-ray radiography under identical operating conditions, using the same geometry. Furthermore, the validation is comprehensive, including comparisons of liquid mass distribution and temporal dynamics of the liquid jet. Following the validation, we study the effect of using different gas inflow models which range from using an analytical velocity profile to a nozzle simulation. The liquid is laminar and modeled as a Poiseuille flow and a cylindrical splitter plate separates the liquid and gas streams. We discuss the influence of the contact line model which ranges from pinning the interface to a specified location on the splitter plate (fixed triple point) to a free moving contact line. For free moving contact lines, we employ a sub-grid scale (SGS) contact line model that assumes a static contact angle [START_REF] Wang | 3D numerical study of large-scale two-phase flows with contact lines and application to drop detachment from a horizontal fiber[END_REF]. We vary the static contact angle to understand the effect of nozzle tip wettability. These inflow modeling strategies are easily implementable and do not require large amounts of mesh resolution, making them particularly desirable from a practical engineering standpoint.

The paper is organized as follows: Section 2 discusses the experimental and numerical methods used, Section 3 validates our computational model against experiment, Section 4 discusses the influence of the gas velocity model, Section 5 discusses the influence of the contact line model, and conclusions are drawn in Section 6.

Methods

A Canonical Atomizer and Flow Conditions

Figure 1 shows the two-fluid coaxial atomizer [START_REF] Machicoane | 19 Synchrotron radiography characterization of the liquid core dynamics in a canonical two-fluid coaxial atomizer[END_REF] used in both simulations and experiment. Air enters the nozzle through four upstream ports perpendicular to the wall and flows through an annular passage at a total flow rate Q g . Liquid water flows through a straight circular pipe at a flow rate Q l . The outer wall of the liquid nozzle separates the two streams and its annular section at the exit plane, with inner and outer nominal diameter d l = 2 mm and D l = 3 mm, will be referred to as the splitter plate. The liquid and gas bulk exit velocities are defined as

U l = Q l /A l and U g = Q g /A g , where A l = πd 2 l /4 and A g = π(d 2 g -D 2
l )/4 are the liquid and gas nozzle exit flowthrough areas and d g = 10 mm is the gas nozzle inner diameter. The fluid properties used are kinematic viscosities of ν g = 1.45 × 10 -5 m 2 s -1 and ν l = 1.137 × 10 -6 m 2 s -1 , densities of ρ g = 1.226 kg m -3 and ρ l = 1000 kg m -3 , and a surface tension coefficient σ = 72 mN m -1 where subscripts g and l denote gas and liquid properties respectively. Water is injected through a round pipe while gas is injected through four gas ports into a converging nozzle. Note that the inset indicating the exit diameters in a) has been scaled up by a factor of two for visibility.

Table 1: Simulation's non-dimensional parameters: gas Reynolds number (Re g ), liquid Reynolds number (Re l ), gas-to-liquid dynamic pressure ratio (M), Weber number based on the liquid jet diameter but gas density and slip velocity between the two phases (We), density ratio (ρ * ) and viscosity ratio (µ * ). High-speed back-lit imaging is used to produce 2D projections of the liquid presence in the near-field. The images are post-processed using a sequence of operations that binarize the liquid core, defined to be the portion of the liquid jet that is still fully connected to the nozzle, such that a liquid pixel value is 1 and a gas pixel value is 0. The temporal and spatial resolutions for this study are 0.1 ms and 27 µm respectively. Details of this method are discussed further in [START_REF] Machicoane | Influence of steady and oscillating swirl on the near-field spray characteristics in a two-fluid coaxial atomizer[END_REF].

Re g ≡ 4Q g √ 4πA g ν g Re l ≡ ρ l U l d l µ l M ≡ ρ g U 2 g ρ l U 2 l We ≡ ρ g (U g -U l ) 2 d l σ ρ * ≡ ρ l ρ g µ * ≡
Synchrotron X-ray radiography of the resulting spray was performed at the Advance Photon Source (APS) at Argonne National Laboratory, 7-BM beamline [START_REF] Kastengren | The 7BM beamline at the aps: a facility for time-resolved fluid dynamics measurements[END_REF]. As opposed to binarized liquid data obtained from back-lit imaging, focused-beam radiography enables the point-wise measurement of the integrated liquid depth along a line of sight, referred to as the equivalent path length (EPL). The measurement technique relies on a monochromatic X-ray beam that is sent through the liquid and measured by a receiving pin-diode at 270 kHz. Based on the attenuation of the signal caused by the liquid, the EPL is deduced from Beer-Lambert's Law: EPL = (1/µ a ) ln(I 0 /I) where I 0 is the incident beam intensity, I is the beam intensity after passing through the spray, and µ a is the X-ray attenuation coefficient of water at the X-ray wavelength. These point measurements can be raster-scanned across the spray to gather longitudinal or transverse profiles of the liquid depth. Details of this technique are further described in [START_REF] Bothell | Comparison of X-ray and optical measurements in the near-field of an optically dense coaxial air-assisted atomizer[END_REF][START_REF] Heindel | X-ray imaging techniques to quantify spray characteristics in the near-field[END_REF],

and the experimental configurations and liquid phase visualization are detailed in [START_REF] Machicoane | 19 Synchrotron radiography characterization of the liquid core dynamics in a canonical two-fluid coaxial atomizer[END_REF].

2.3.

We consider an LES approach to the two-phase, incompressible Navier-Stokes equations

∇ • ũ = 0, (1)
∂ρ ũ ∂t + ∇ • (ρ ũ ũ) = -∇ p + ρg + ∇ • µ ∇ ũ + ∇ ũT + ∇ • τ S GS + F S T , (2)
where ( •) denotes a spatially filtered (resolved) quantity on the mesh, u is the velocity, p is the pressure, ρ is the density, µ is the dynamic viscosity, g is the gravitational acceleration, τ S GS is the sub-grid scale (SGS) stress, F S T is the surface tension force and t is time. We also consider the volume fraction transport equation

∂ α ∂t + ũ • ∇ α = 0, ( 3
)
where α is the ratio of liquid volume to cell volume in a computational cell and sub-grid scale effects have been neglected. The fluid properties are weighted based on the liquid volume fraction

ρ = (1 -α)ρ g + αρ l , (4)
µ -1 = (1 -α)µ -1 g + αµ -1 l , (5)
where subscripts 'g' and 'l' refer to gas and liquid quantities respectively.

The two-phase Navier-Stokes equations are solved using an in-house, conservative, finite-volume flow solver for low Mach number flows [START_REF] Desjardins | High order conservative finite difference scheme for variable density low Mach number turbulent flows[END_REF]. The solver employs second-order accurate methods in time and space. Away from the interface, the flow solver is discretely kinetic energy conserving. At the interface, local discontinuities degrade the methods and although mass is still discretely conserved and momentum is approximately conserved, kinetic energy conservation is lost. The volume fraction equation is solved with a geometric, semi-Lagrangian Volume-of-Fluid method [START_REF] Owkes | A computational framework for conservative, three-dimensional, unsplit, geometric transport with application to the volume-of-fluid (VOF) method[END_REF]. Inside each computational cell, the interface is represented locally as a plane using the piece-wise linear interface construction (PLIC) [START_REF] Rider | Reconstructing volume tracking[END_REF], with the plane normal calculated using LVIRA [START_REF] Pilliod | Second-order accurate volume-of-fluid algorithms for tracking material interfaces[END_REF]. A dynamic Smagorinsky turbulence model [START_REF] Meneveau | A Lagrangian dynamic subgrid-scale model of turbulence[END_REF] is used to close τ S GS . The surface tension force is calculated through

F S T = σ(κ + κ S GS )∇ α ( 6
)
where σ is the surface tension coefficient, κ is the resolved curvature and κ S GS is a sub-grid scale curvature. The surface tension force is embedded as a source term in the pressure Poisson equation using a continuous surface force approach [START_REF] Popinet | A front-tracking algorithm for accurate representation of surface tension[END_REF]. The resolved curvature of the interface is calculated using parabolic surface fits [START_REF] Scardovelli | Interface reconstruction with least-square fit and split Eulerian-Lagrangian advection[END_REF]. κ S GS is used to model surface wettability effects that exist at scales far below the mesh size and is controlled through a static contact angle θ s (see [START_REF] Wang | 3D numerical study of large-scale two-phase flows with contact lines and application to drop detachment from a horizontal fiber[END_REF]). Figure 2 shows a schematic of a grid cell that contains the triple point. In that cell, the mismatch between the interface angle resolved by the mesh (θ d ) and the angle at the wall (θ s ) is used to compute a SGS curvature

κ S GS = cos θ s -cos θ d ∆ , ( 7
)
where ∆ is the mesh spacing. If a cell does not have a triple point, then κ S GS is set to 0. For some of the atomization simulations presented herein, an auxiliary nozzle simulation of the internal gas flow of the nozzle is used to generate realistic inflow conditions. The domain size of this nozzle simulation is 10d g × 10d g × 10d g and the mesh is Cartesian with a uniform spacing ∆ n /d g = 0.05. The gas nozzle simulation is indicated in terms of the gas diameter d g since it is the relevant quantity here, and we remind that D l /d g = 0.3. The nozzle plenum is the furthest point upstream in the domain and the furthest point downstream is at a distance d g past the nozzle exit. The liquid injection is masked out as a solid and a single-phase solver is used, significantly reducing the computational cost. The converging nozzle walls are created by stair-stepping full cells that are treated as solid boundaries and the gas inflow is injected through the four normal ports upstream to match the gas flow rate Q g . This approach matches the nozzle 3D geometry used in the experiment and available at http://depts.washington.

Range of Gas Velocity and Contact Line Models

The gas velocity models used in this study were an analytical velocity profile and an additional nozzle simulation of the internal gas flow. The analytical profile [START_REF] Matas | Shear instability of an axisymmetric air-water coaxial jet[END_REF] and takes the form

u(r) = U g erf (r -R l )/δ w 1 + erf (r -R l )/δ w /2 R l ≤ r ≤ r g v(r) = w(r) = 0 (8)
where R l = D l /2 and r g = d g /2 are the lower and upper bounds containing the gas stream, r is the radial location, δ w is the prescribed gas vorticity thickness and U g is chosen such that the gas volumetric flow rate integrates to Q g .

Figure 3a shows an atomization simulation run with an analytical gas velocity profile while Fig. 3b shows a simulation where the nozzle and atomization simulations are coupled as described in Section 2.4.1.

The contact line models used in this study were pinning the contact line to the inner wall (r = r l = d l /2) pinning to the outer wall (r = R l ) and allowing for an unpinned/free moving contact line. The implementation of each is as follows: when pinning to r l , the splitter plate is modeled as a fully unwet wall while when pinning to R l , it is modeled as a fully wet wall. In both cases, the splitter plate cells are treated as a solid boundary for the velocity solver, but either taken to be a full liquid or gas cells when included in the LVIRA interface reconstruction. However, in the case where the contact line is free moving, the splitter plate cells are excluded from the LVIRA interface reconstruction but still treated as a solid boundary for velocity. For freely moving contact lines, the SGS contact line model described in Section 2.3 is employed. It should be noted that although the splitter plate is resolved by 2-3 cells in this study, results presented in the following section show that excellent agreement with experiment is still obtained. More detailed analysis of the contact line in a more highly resolved setting is left for future work.

Validation Against Experiments

The combination of using an additional nozzle simulation to model the gas profile and allowing for a free contact line with a static contact angle of 85 • yields the best agreement against experiments; qualitative comparisons are made in Fig. 4 and quantitative comparisons are made against metrics gathered from X-ray measurements in Fig. 5 and from back-lit imaging in Fig. 6. The atomization simulation presented in this section uses a refined mesh of size ∆/2.

Figure 4 shows snapshots of the flow comparing the simulations and experiments; emphasis is placed on the liquid core. At this low gas-to-liquid dynamic pressure ratio, the main instabilities observed are Kelvin-Helmholtz instabilities that develop just past the nozzle exit and a large-scale flapping instability. At large-scales, both exhibit similar liquid core lengths, interface topology, and flapping motion. The three snapshots illustrate the small-scale event of bag break up. The process begins with the development of a thick sheet, the high-speed gas subsequently inflates this sheet which forms a bag, and finally, when the sheet becomes sufficiently thin, the bag bursts. These thin sheets in the experiment can reach scales as small as O(1 µm) which computations cannot afford to resolve. In our simulations, the mesh sizes are O(100µm) and as such, bags prematurely break and leave behind large rims resembling a prong. Running at these mesh sizes allow simulations to be relatively affordable, costing around 100,000 core hours. T stat = 113d l /U l = 450 ms, i.e., 113 characteristic liquid time scales, while experimental measurements are gathered for 10 seconds, corresponding to 45 and 1000 flapping events respectively. Figure 5a shows a 2D map of EPL averaged in time. Figure 5b shows the comparison of mean EPL sampled along x, at the centerline (y = 0). The mean centerline EPL is a proxy for the liquid diameter at distances close to the nozzle exit and decreases in value downstream either because the flapping instability displaces the liquid core transversely away from the line of sight or the liquid core has deformed or fragmented. EPL measurements presented herein are normalized by D l since we will later pin the contact line to the outer wall of the liquid pipe, leading to a value of approximately 1 at the nozzle exit, x/D l = 0 (Note: it will not be exactly 1 because of the inexact nature associated with approximating a cylindrical geometry using a Cartesian mesh). Simulations are in excellent agreement with experiments as they are able to match well the centerline decay of mean EPL. Figure 5c shows that the simulations also match well the experimental standard Figure 6a shows a time instance of a binarized image of the liquid core and mimics an experimental back-lit image.

The quantities illustrated on the figure are the liquid core length L B , defined to be the instantaneous longitudinal extent of the liquid core, and the y liquid presence barycenter (y bary ) at a downstream location. Figure 6b shows that the simulations agree well with experimental results for the normalized probability density functions (PDF) of 6c shows a spectrum of a Fourier transform taken of a time signal of y bary (see [START_REF] Kaczmarek | Spatial characterization of the flapping instability of a laminar liquid jet fragmented by a swirled gas co-flow[END_REF] for more details). A flapping Strouhal number is calculated through S t = f dom d l /U g where f dom is the dominant frequency taken to be the frequency at which the spectrum peaks. y bary x/D l = 3, x/D l [START_REF] Delon | Flapping instability of a liquid jet[END_REF]. Note that this normalization does not claim any physical scaling but is done for non-dimensionalization purposes. Table 2 summarizes the comparison of the mean and standard deviation of L B and the flapping Strouhal number between the simulations and the experiments. Normalized Difference 12% 22% 13%

L B . Figure
We now look at the effect of mesh resolution on the statistics presented above. Two additional simulations using larger mesh resolutions ∆ and 2∆ are presented. Figure 7 shows the mean and standard deviation centerline EPL statistics and the PDF of liquid core length at these different mesh sizes. Mean and standard deviation centerline EPL statistics indicate that a simulation with a mesh resolution ∆ is relatively well converged because differences between ∆ and ∆/2 are small compared to differences between 2∆ and ∆. Furthermore, Fig. 7c shows that the liquid core length is not strongly affected by the mesh size. Although discrepancies are still present in statistics between mesh sizes ∆ and ∆/2, we conclude that a mesh size ∆ is sufficient to draw inferences from. As such, to reduce computational resources, future simulations presented will maintain a mesh size of ∆.

Impact of Gas Velocity Model

Gas Velocity Profiles

Figure 8 shows velocity profiles at the nozzle exit plane for the experiment, the auxiliary nozzle simulation and the analytical velocity profiles according to Eq. ( 8) at different vorticity thicknesses. For the analytical profiles, the vorticity thicknesses used are 2δ w , δ w and δ w /2 where δ w = 5.6h/ √ Re h is the vorticity thickness obtained from the correlation proposed by [START_REF] Marmottant | On spray formation[END_REF], h = (D ld g )/2 and Re h = U g h/ν g . No turbulent fluctuations are added to the inflow velocity profile. The experimental gas velocity profiles were measured a small distance downstream of the nozzle using hot-wires without any liquid present while the statistics in the simulation were sampled in the atomization domain. Various mesh sizes of the auxiliary nozzle simulation were tested and minimal changes in the stream-wise velocity statistics were observed. Figure 8a shows that the mean stream-wise velocity profile of the nozzle simulation and the analytical velocity profile with δ w /2 match the experimental vorticity thickness at the inner wall while the velocity profiles with vorticity thicknesses of δ w and 2δ w are a worse match. Figure 8b shows that the stream-wise standard deviation velocity predicted from the nozzle simulation match the experiment well at the inner wall, which can be expected to be most relevant for atomization, but are under-predicted within the outer gas shear layer.

Influence of Vorticity Thickness

Figures 9a and9b show the mean and standard deviation centerline EPL and Fig. 9c shows the liquid core length PDF of simulations using an analytical velocity profile at three different gas vorticity thicknesses (i.e., 2δ w , δ w and δ w /2). The contact line model used in these simulations was a free contact line with a static contact angle 85 • . The simulation presented in Section 3 using a mesh size ∆/2 will serve as a benchmark. Considering the simulation using a gas vorticity thickness δ w , the mean centerline EPL profile and liquid core length PDF have larger values compared to the benchmark case, suggesting that the jet breaks further downstream than in that case. Reducing the vorticity thickness by a factor of 2 more closely matches the vorticity thickness produced from the nozzle simulation used in the benchmark case and therefore, we observe better agreement in the mean centerline EPL profile. However, discrepancies still remain as the standard deviation centerline EPL for x/D l > 3 and the liquid core length PDF exhibits larger values. This can likely be attributed to the turbulence coming from the nozzle which is known to have a destabilizing effect [START_REF] Jiang | Impact of inlet gas turbulence on the formation, development and breakup of interfacial waves in a two-phase mixing layer[END_REF] and absent in the analytical inflow velocity profiles. Mean centerline EPL statistics and liquid core length for 2δ w have much larger values than all cases, confirming that increasing vorticity thickness increases the liquid core length. Table 3 summarizes the mean and standard deviation liquid core length and the flapping Strouhal number. Results show that decreasing the vorticity thickness decreases the mean liquid core length while increasing the dominant frequency. The latter is a trend consistent with past studies [START_REF] Fuster | Instability regimes in the primary breakup region of planar coflowing sheets[END_REF][START_REF] Matas | Shear instability of an axisymmetric air-water coaxial jet[END_REF] and related to studying the influence of gas velocity deficits on temporal dynamics [START_REF] Matas | Shear instability of an axisymmetric air-water coaxial jet[END_REF][START_REF] Matas | Experimental and analytical study of the shear instability of a gas-liquid mixing layer[END_REF]. However, using an analytical profile seems to under-predict the flapping Strouhal number by approximately 30% under the range of vorticity thicknesses presented here. This is further evidence that turbulent fluctuations play a key role on the break up processes and in particular, on the dominant frequencies [START_REF] Jiang | Impact of inlet gas turbulence on the formation, development and breakup of interfacial waves in a two-phase mixing layer[END_REF][START_REF] Matas | Influence of gas turbulence on the instability of an air-water mixing layer[END_REF].

Impact of Contact Line Model

Effect of Contact Line Location

The contact line model was varied by pinning the contact line to the splitter plate inner wall, outer wall and allowing for a free moving contact line with a static contact angle of 85 • . The gas flow model was maintained as an analytical velocity profile according to Eq. ( 8) with a vorticity thickness δ w .

Pinning the interface to the inner wall models the splitter plate as a fully unwet wall. This contact line model creates a gas re-circulation and low pressure region just downstream of the splitter plate. This gives rise to aspiration of the interface in the radial direction towards the gas. The consequence of this is observed in Fig. 10a where the initial mean EPL increases as the downstream distance is increased. It is only after x/D l ≈ 0.25, that the interface reaches the bulk of the high-speed gas stream and subsequently exhibits a monotonic decrease in mean EPL.

Pinning the interface to the outer wall models the splitter plate as a fully wet wall. Experimental high-resolution visible light imaging and X-ray imaging have shown that at this operating condition, the contact line lies mostly near the outer wall [START_REF] Heindel | X-ray imaging techniques to quantify spray characteristics in the near-field[END_REF][START_REF] Ricard | Role of convective acceleration in the interfacial instability of liquid-gas coaxial jets[END_REF]. Moreover, when adding swirl to the gas, it is observed that the contact line can even wick up into the gas flow region as shown in Fig. 11a. Therefore, pinning to the outer wall more closely matches the local experimental flow configuration. This pinning model results in a mean centerline EPL that decreases monotonically which is experimentally observed (see Fig. 5b). One can see in Fig. 10a that using a free contact line with an SGS contact line force with θ s = 85 • leads to similar mean EPL profiles to pinning to the outer wall. Figure 11b shows the PDF of the normalized radial location for the contact line such that a value of 0 indicates the interface is located at the inner wall while a value of 1 indicates it is at the outer wall. For θ s = 85 • , the contact line radius peaks near the outer wall, serving as an explanation of why pinning to the outer wall and this free contact line have similar mean EPL profiles. It can be observed in Fig. 10b that a free contact line model leads to more interfacial dynamics than pinning the outer wall since its standard deviation EPL profile is uniformly larger.

Figure 10c shows the PDF of the liquid core length and Table 4 summarizes the mean and standard deviation centerline EPL and Strouhal numbers for all three cases. Pinning to the inner wall leads to a liquid that is too stable as quantified by the large mean liquid core length and at times, the liquid core length is observed to exceed the downstream domain boundary. Pinning to the outer wall and having a free contact line have similar PDFs, with the free contact line exhibiting a slightly smaller mean liquid core length. Studies have shown that the vorticity thickness has a strong impact on the dominant frequency [START_REF] Fuster | Instability regimes in the primary breakup region of planar coflowing sheets[END_REF][START_REF] Matas | Shear instability of an axisymmetric air-water coaxial jet[END_REF]. Results show that the flapping Strouhal numbers are all within 2% of each other, suggesting that the dominant frequency is mostly independent of the contact line model for a fixed vorticity thickness. The static contact angle depends on many factors such as surface roughness, temperature, nozzle material and treatment. For aluminum, water and air, a reasonable static contact angle is between 70 • -90 • [START_REF] Majid | Static contact angle and large water droplet thickness measurements with the change of water temperature[END_REF][START_REF] Zhu | Influence of bond number on behaviors of liquid drops deposited onto solid substrates[END_REF]. In the present study, we consider the static contact angles 70 • , 85 • , and 110 • which model a moderately hydrophylic, less hydrophylic, and moderately hydrophobic surface respectively. In these simulations, an auxiliary nozzle simulation was used to provide the gas inflow velocity. Figure 11b shows the contact line radius PDFs measured at a fixed arc location. The PDFs show that the contact lines sit very close to the outer wall for θ s = 70 • , further away from the outer wall for θ s = 85 • and near the inner wall for θ s = 110 • . Figure 12a shows the mean and standard deviation centerline EPL profiles for simulations using these static contact angles. Because a simulation using θ s = 110 • results in a contact line close to the inner wall, its EPL profile follows a similar behavior to pinning to the inner wall, with an initial increase in EPL and subsequent monotonic decrease. Similarly, a simulation using θ s = 70 • results in a contact line close to the outer wall and as such, exhibits a behavior similar to pinning to the outer wall in that a monotonic decrease in EPL is observed. Figure 12b shows that increasing θ s shifts the standard deviation centerline EPL to the right. Figure 12c shows the PDFs of the liquid core length for simulations using θ s = 70 • and 85 • are similar while 110 • results in a profile shifted to the right. Table 5 summarizes the mean and standard deviation centerline EPL and flapping Strouhal number showing that as θ s is increased, the liquid core length and dominant frequency also increase.

This highlights the significant impact that the contact angle model can have on the downstream liquid distribution.

Conclusion

In this study, we have performed simulations of air-blast atomization in a coaxial two-fluid atomizer using a geometric Volume-of-Fluid method. Simulations were validated against experiments under identical air/water conditions and geometries. Excellent agreement of quantities such as the mean equivalent path length of the liquid (EPL), liquid core length, and dominant frequency was observed. A mesh refinement study was also conducted showing that these quantities were reasonably well mesh converged. The liquid was modeled using a Poiseuille flow while the gas inflow and contact line models were studied.

The gas inflow models considered were analytical velocity profiles at different vorticity thicknesses with no turbulent fluctuations added and an auxiliary nozzle simulation. Simulations using analytical velocity profiles were benchmarked against a simulation using the nozzle simulation. Results showed that decreasing the vorticity thickness decreased the mean liquid core length, the mean centerline EPL, and increased the dominant frequency of the liquid jet motions. While one analytical profile had a vorticity thickness that was close in value to the experiment and nozzle simulation, quantities such as the mean liquid core length remained larger. Furthermore, although decreasing the vorticity thickness increased the dominant frequency, a trend reported in other studies [START_REF] Fuster | Instability regimes in the primary breakup region of planar coflowing sheets[END_REF][START_REF] Matas | Shear instability of an axisymmetric air-water coaxial jet[END_REF], the dominant frequencies for the presented vorticity thicknesses yielded systematically lower values than the experiment. These results confirmed that turbulent fluctuations in the gas play an important role.

The contact line models considered were pinning to the inner wall of the splitter plate, the outer wall of the splitter plate, and allowing for a free contact line with a (SGS) contact line model using a static contact angle of 85 • . This study showed that the contact line model has a key influence on the liquid jet development and on the liquid distribution downstream. In particular, pinning to the outer wall or using a free moving contact line yielded better experimental agreement of quantities such as mean and standard deviation centerline EPL and mean liquid core length than pinning to the inner wall. Pinning to the inner wall resulted in an initial increase in mean centerline EPL downstream of the nozzle because of a re-circulation region created by the gas. In contrast, pinning to the outer wall or having a free moving contact line resulted in the monotonic decrease in EPL observed in the experiment. Results also indicated that when using an analytical gas velocity profile with a fixed vorticity thickness, the contact line model does not have a significant impact on the dominant frequency. The static contact angle was varied between θ s = 70 • , θ s = 85 • , and θ s = 110 • . Results showed in the θ s = 70 • case, i.e., modeling a hydrophylic surface, the mean centerline EPL exhibited similar trends to pinning to the outer wall while in the θ s = 110 • case, i.e., modeling a hydrophobic surface, trends were similar to pinning to the inner wall.

As the near-field region has been validated in this study and a better understanding of the impact of the gas velocity and contact line models have been gained, several research questions remain open. Since computational tools now result in strong agreement of liquid distribution compared against experiment, our research efforts will now shift to modeling the conversion of broken liquid structures in atomization simulations to Lagrangian particles in spray dispersion simulations. Promising research efforts have been made in this direction (e.g., [START_REF] Kim | Subgrid-scale capillary breakup model for liquid jet atomization[END_REF][START_REF] Tomar | Multiscale simulations of primary atomization[END_REF]) ( [START_REF] Chiodi | General, robust, and efficient polyhedron intersection in the interface reconstruction library[END_REF]). The inflow modeling of the gas has been studied in various forms which include modeling the velocity profile just downstream of the nozzle exit using a velocity deficit (e.g., [START_REF] Matas | Shear instability of an axisymmetric air-water coaxial jet[END_REF][START_REF] Matas | Experimental and analytical study of the shear instability of a gas-liquid mixing layer[END_REF]). However, current literature has not considered in detail the influence of the contact line which this study has shown to have an impact. Thus, a more detailed study of the contact line physics and different modeling strategies for the contact line would be useful.

Figure 1 :

 1 Figure 1: (Color online) Nozzle schematic cut longitudinally (left) and transversely (right). Water is injected through a round pipe while gas is

Figure 2 :

 2 Figure 2: (Color online) Schematic of sub-grid scale contact line. The model adds a sub-grid scale curvature based on an assumed static contact angle θ s to the resolved curvature based on θ d .

  edu/fluidlab/nozzle.shtml. All other boundaries are treated as Neumann outflow conditions. The gas velocity field at x = -1.16D l is then used as a Dirichlet inflow condition for the atomization simulation.

  (a) Atomization Domain Only (b) Atomization and Nozzle Domains Coupled

Figure 3 :

 3 Figure 3: (Color online) Illustration of the computational set up. Contour of α = 0.5 representing the interface is plotted in blue, pseudo-color of velocity magnitude are plotted on the cut planes with different normalization inside and outside the nozzle. a) Domain excludes the nozzle and utilizes an analytical profile to model the gas velocity and b) a separate nozzle simulation is coupled to the atomization domain.

Figure 4 :

 4 Figure 4: (Color online) Qualitative comparisons between the simulation (left) and experiment (right). Frames are separated by 1 ms.

5 Figure 5 :

 55 Figure 5: (Color online) Simulations compared against experiments. a) 2D mean EPL map with sampling locations marked, b-k) Transverse profiles of the mean (middle row) and standard deviation (bottom row) EPL, comparing the simulation ( ) and the experimental measurements ( ).

Figure 6 :

 6 Figure 6: (Color online) a) Simulation binarized image of the liquid core with relevant quantities, b) PDF of liquid core length comparing the simulation ( ) and the experiment ( ), and c) y x/D l = 3, f dom .

Figure 7 :

 7 Figure 7: (Color online) Mesh convergence of a-b) EPL statistics and c) liquid core length PDFs for simulations with mesh sizes 2∆ ( , ), ∆ ( , ), ∆/2 ( , ) compared against experiment ( ).

Figure 8 :

 8 Figure 8: (Color online) Comparisons of velocity statistics between analytical profiles with vorticity thicknesses 2δ w ( ), δ w ( ), δ w /2 ( ), additional nozzle simulation ( ) and experiment ( ). Note that D l /d g = 0.3.

Figure 9 :

 9 Figure 9: (Color online) Influence of velocity model on a-b) EPL statistics and c) 2δ w ( , ), δ w ( , ) and δ w /2 ( , ) compared against the benchmark ( , ).

  Figure 10: (Color online) Influence of contact line model on a-b) EPL statistics and c) liquid core length PDFs for pinned to inner wall ( , ), outer wall ( , ) and a free contact line ( , ).

  Figure 11: (Color online) a) Experimental image showing an instance where the contact line wicked up the outer wall into the gas flow region in the presence of gas swirl and b) θ s = 70 • ( ), θ s = 85 • ( ), θ s = 110 • ( ).

Figure 12 :

 12 Figure 12: (Color online) Influence of static contact angle on a-b) EPL statistics and c) liquid core length PDFs for θ s = 70 • ( , ), 85 • ( , ), and 110 • ( , ).

Table 1

 1 summarizes the non-dimensional parameters used in this case.

Table 2 :

 2 Comparisons between the simulation and the experiment of mean and standard deviation of L B and flapping Strouhal number obtained from binarized images.

	Simulation	5.24	1.15	7.52 × 10 -3
	Experiment	4.67	0.937	6.63 × 10 -3

⟨L B ⟩/D l L B,std /D l S t

Table 3 :

 3 Summary of mean and standard deviation of L B and flapping Strouhal number obtained from binarized images for gas velocity profiles at different vorticity thicknesses.

		⟨L B ⟩/D l L B,std /D l S t
	2δ w	8.59	0.539	4.66 × 10 -3
	δ w	6.92	1.18	4.93 × 10 -3
	δ w /2	6.24	1.16	5.57 × 10 -3
	Benchmark 5.24	1.15	7.52 × 10 -3

Table 4 :

 4 Summary of mean and standard deviation of L B and flapping Strouhal number for different contact line models.

	Pin to inner wall 8.50	0.583	4.92 × 10 -3
	Pin to outer wall 7.16	0.950	5.06 × 10 -3
	Free contact line 6.92	1.18	4.92 × 10 -3
	5.2. Effect of Static Contact Angle θ s

⟨L B ⟩/D l L B,std /D l S t

Table 5 :

 5 Summary of mean and standard deviation of L B and flapping Strouhal number for different static contact angles.

	θ s	⟨L B ⟩/D l L B,std /D l S t
	70 •	4.52	0.810	7.01 × 10 -3
	85 •	4.65	0.751	6.63 × 10 -3
	110 • 5.38	0.866	8.56 × 10 -3

Acknowledgements

This work was sponsored by the Office of Naval Research (ONR) as part of the Multidisciplinary University Research Initiatives (MURI) Program, under grant number N00014-16-1-2617. The views and conclusions contained herein are those of the authors only and should not be interpreted as representing those of ONR, the U.S. Navy or the U.S. Government. The X-ray imaging work was performed at the 7-BM beamline of the Advanced Photon Source, a U.S. Department of Energy (DOE) Office of Science User Facility operated for the DOE Office of Science by Argonne National Laboratory under Contract No. DE-AC02-06CH11357.


Akash Panigrahi

Sagar Verma

Matthieu Terris

Maria Vakalopoulou
email: maria.vakalopoulou@centralesupelec.fr

HAVE FOUNDATIONAL MODELS SEEN SATELLITE IMAGES?

This paper presents an investigation into the zero-shot performance of pre-trained foundation models on remote sensing tasks. Recent advances in self-supervised learning suggest that these models, when trained on vast amounts of unsupervised data, could potentially improve generalization across a number of downstream tasks. Our study offers an empirical evaluation of these models on standard remote-sensing benchmarks such as EuroSAT and BigEarthNet-S2, with the intent to confirm whether these models have encountered satellite imagery during their training phase. Moreover, we examine the impact of adding a geospatial domain-specific textual description of classes, contrasting it with the standard class-based prompts. Our findings indicate that the fine-tuned BLIP models exhibit superior zeroshot performance on these benchmarks compared to their standard counterparts, signifying that fine-tuning on standard benchmarks enhances performance. Furthermore, the addition of geospatial context variably influences performance depending on the specific model and dataset. This work provides crucial insights into the applicability of foundation models in remote sensing tasks and lays the groundwork for further research.

INTRODUCTION

Recent progress in self-supervision shows that pretraining large neural networks on vast amounts of unsupervised data can increase generalization for downstream tasks [START_REF] Radford | Learning transferable visual models from natural language supervision[END_REF][START_REF] Li | BLIP: Bootstrapping language-image pre-training for unified vision-language understanding and generation[END_REF]. Such models, recently coined as foundation models, have been transformational to computer vision and natural language processing. In this work, we analyze the zero-shot performance of these models on standard remote sensing image classification datasets as shown in Figure 1. This work aims to establish empirical evidence of whether these foundational models have seen satellite imagery during their training. We believe this can enable the remote sensing community to effectively utilize these models in different downstream tasks like classification, segmentation, object detection, and change detection.

RELATED WORKS

Radford et al. [START_REF] Radford | Learning transferable visual models from natural language supervision[END_REF] jointly trained image and text encoders (CLIP), using contrastive losses to maximize cosine similarity between image and text representations. Jia et al. [START_REF] Jia | Scaling up visual and vision-language representation learning with noisy text supervision[END_REF] curated an exascale, noisy dataset to train a simple dual-encoder architecture to align image and text embeddings using a contrastive loss. Li et al. [START_REF] Li | BLIP: Bootstrapping language-image pre-training for unified vision-language understanding and generation[END_REF] observe that noise in data leads to sub-optimal model training and attempt to alleviate the same through Cap-Filt, a bootstrapping mechanism that employs a captioner to synthesize captions, and a filter to remove noisy ones. Yuan et al. [START_REF] Yuan | Florence: A new foundation model for computer vision[END_REF] try to unify image-text learning by pre-training a combination of hierarchical vision transformer (image encoder) and modified CLIP (language encoder) on web-scale image-label-description triplets. The resultant model demonstrates the outstanding performance of a number of transfer types, including fewshot and zero-shot transfers. Lacost et al. [START_REF] Lacoste | Toward foundation models for earth monitoring: Proposal for a climate change benchmark[END_REF] proposed to use foundational models like CLIP to leverage satellite images for climate change problems. However, they focus on fine-tuning instead of zero-shot to overcome problems like the availability of small datasets, license issues, and distributional shifts. They do not show empirical evidence on why foundational models are better suited. To the best of our knowledge, our work is the first to show empirically how good foundational models are in the case of remote sensing problems.

EXPERIMENTS

We obtain zero-shot performance of two pretrained foundation models: CLIP and BLIP, and their imageencoder based variants on remote sensing datasets: Eu-roSAT [START_REF] Helber | EuroSAT: A novel dataset and deep learning benchmark for land use and land cover classification[END_REF] and BigEarthNet-S2 [START_REF] Sumbul | BigEarthNet: A large-scale benchmark archive for remote sensing image understanding[END_REF]. EuroSAT is a toy LULC classification dataset consisting of 27000 geo-referenced Sentinel-2 patches categorized into ten classes. BigEarthNet is a large-scale multi-label dataset with 590,326 Sentinel-2 patches. We observe the performance of these architectures in a standard setting and compare the same with a context-based setting wherein we provide a geospatial domain-specific textual description of classes in contrast to standard class-based prompts in the standard setting. These datasets and experiments performed here are available in the Geo-Engine platform [START_REF] Shin | Europa: Increasing accessibility of geospatial datasets[END_REF][START_REF] Verma | GeoEngine: A platform for production-ready geospatial research[END_REF].

For CLIP, pretrained ResNet and Transformer variants are available in the public domain. We generated inferences on EuroSAT and BigEarthNet-S2 for all these pretrained CLIP versions. For BLIP, standard base and large ViT weights, along with their variants fine-tuned on the large web-scale dataset bootstrapped through CapFilt, and other standard benchmarks like MS-COCO and Flickr30k, are available in the public domain. BLIP employs cross-attention between textual and visual representations instead of standard metrics like cosine similarity for image-text alignment. Such metrics for similarity computation will lead to an inaccurate measurement of its zero-shot performance on Eu-roSAT and BigEarthNet-S2 datasets. Instead, we repurposed the image-text retrieval mode of BLIP variants for image classification on the remote-sensing benchmarks.

RESULTS

We report our findings on the zero-shot performance of variants of foundation models like CLIP and BLIP on EuroSAT and BigEarthNet benchmarks in standardand context-based settings in Table 1. We observe that CLIP has a near-random performance on BigEarthNet-S2 owing to large image-encoder activations for (almost) all classes that lead to many false positives. We notice that fine-tuned BLIP models have a better zero-shot performance on EuroSAT and BigEarthNet benchmarks than standard variants and can safely conclude that finetuning on standard benchmarks improves performance. We observe that zero-shot performance on EuroSAT

CONCLUSION

In summary, our study presents an empirical examination of the zero-shot performance of pre-trained foundation models on standard remote-sensing datasets like EuroSAT and BigEarthNet-S2. Our findings reveal that fine-tuned BLIP variants outperform the standard version on these benchmarks, and incorporation of geospatial context during the inference stage can lead to mixed outcomes depending on model and dataset selected.

In the future, we intend to expand the scope of our investigation by involving more task types and datasets. We will be incorporating more foundational models, such as ALBEF [START_REF] Li | Align before fuse: Vision and language representation learning with momentum distillation[END_REF], ViLD [START_REF] Gu | Openvocabulary object detection via vision and language knowledge distillation[END_REF], and ZSI [START_REF] Zheng | Zero-shot instance segmentation[END_REF]. These models have been trained on different large private datasets, which may or may not have satellite and aerial images. Our larger experiment set will consist of BigEarthNet-S1, SynthWakeSAR [START_REF] Rizaev | SynthWakeSAR: A synthetic sar dataset for deep learning classification of ships at sea[END_REF] in case of classification. SeeDroneSeaV2 [START_REF] Kiefer | 1st workshop on maritime computer vision (macvi) 2023: Challenge results[END_REF], xView [START_REF] Lam | xView: Objects in context in overhead imagery[END_REF] and DOTA [START_REF] Xia | DOTA: A largescale dataset for object detection in aerial images[END_REF] in case of object detection. Houston UAV [START_REF] Goswami | FloodNet-to-FloodGAN : Generating Flood Scenes in Aerial Images[END_REF][START_REF] Verma | Aligning Geospatial AI for Disaster Relief with The Sphere Handbook[END_REF] in case of semantic segmentation. We also plan to utilize these models in a very naive way for change detection problems on OSCD BiDate [START_REF] Daudt | Urban change detection for multispectral earth observation using convolutional neural networks[END_REF], OSCD MultiDate [START_REF] Papadomanolaki | Detecting urban changes with recurrent neural networks from multitemporal sentinel-2 data[END_REF], and QFabric [START_REF] Verma | QFabric: Multi-task change detection dataset[END_REF] datasets.

Fig. 1 :

 1 Fig. 1: Captions show ground truth and top-5 predicted labels by CLIP (ViT-B/32) from BigEarthNet-S2 Dataset.

Table 1 :

 1 Zero-Shot Performance of CLIP and BLIP on EuroSAT and BigEarthNet-S2. Supervised training from scratch gives best results for ResNet-101 (93.72%) and ViT-B/16 (77.21%) for EuroSAT and BigEarthNet-S2 respectively.

	improves with the addition of remote-sensing context
	for smaller CLIP variants like ResNet50, ResNet101,
	and ViT-B/32, and degrades for larger architectures
	like ViT-L/14 and EfficientNet-based scaled versions of
	ResNet50. No such visible patterns could be observed in
	CLIP's performance on context-addition for BigEarth-
	Net labels. Adding geospatial priors leads to a marked
	improvement in zero-shot performance for most of the
	BLIP variants on EuroSAT. On BigEarthNet-S2, the ad-
	dition of context leads to a degradation in performance
	for most of the BLIP variants.


Matthieu Terris
email: matthieu.terris@gmail.comsagar@granular.ai

Sagar Verma

INVESTIGATING MODEL ROBUSTNESS AGAINST SENSOR VARIATION

Large datasets of geospatial satellite images are available online, exhibiting significant variations in both image quality and content. These variations in image quality stem from the image processing pipeline and image acquisition settings, resulting in subtle differences within datasets of images acquired with the same satellites. Recent progress in the field of image processing have considerably enhanced capabilities in noise and artifacts removal, as well as image super-resolution. Consequently, this opens up possibilities for homogenizing geospatial image datasets by reducing the intra-dataset variations in image quality. In this work, we show that conventional image detection and segmentation neural networks trained on geospatial data are robust neither to noise and artefact removal preprocessing, nor to mild resolution variations.

INTRODUCTION

Satellite data and geospatial machine learning offer an unparalleled source for objective global-scale data. The past decade has seen a nearly eight-fold increase in the number of earth observation satellites deployed to orbit. This increase represents a paradigm shift in the availability of satellite data and, thus, its potential in downstream applications. With imagery now available for nearly every place on earth daily, researchers can now rely on satellites for time-series data on natural and manmade changes. The ability to model earth's land use and land cover (LULC) and how it is changing due to human activities and natural phenomena will have manifold implications on the study of climate change, economic development, and anthropology. Further, it would serve as a valuable tool to improve decision-making in human-itarian aid and disaster relief efforts [START_REF] Verma | Aligning Geospatial AI for Disaster Relief with The Sphere Handbook[END_REF]. It would also provide critical insights into various topics such as sustainable development and urban sprawl, water and air contamination levels, and illegal construction.

The currently available geospatial imaging dataset shows great extrinsic and intrinsic diversity. As for extrinsic differences, BigEarthNet [START_REF] Sumbul | BigEarthNet: A large-scale benchmark archive for remote sensing image understanding[END_REF] images are created from Sentinel2 data, with a resolution of approximately 10m/pixel, while xView [START_REF] Lam | xView: Objects in context in overhead imagery[END_REF] has a 30cm/pixel resolution. Regarding intrinsic diversity, image data can show a strong signature given the satellite's orientation, camera sensitivity, altitude of the satellite, and image processing pipeline. Consequently, training models on satellite image data are prone to generalization issues on data acquired in a slightly different context [START_REF] Razzak | Multi-spectral multi-image super-resolution of sentinel-2 with radiometric consistency losses and its effect on building delineation[END_REF].

Image processing techniques thus seem necessary for homogenizing the dataset, but the influence of the processing pipeline on the final segmentation or detection quality is unpredictable. For instance, it has already been observed that super-resolving geospatial images strongly hurt the quality of detection models [START_REF] Van Etten | You only look twice: Rapid multi-scale object detection in satellite imagery[END_REF][START_REF] Shermeyer | The effects of super-resolution on object detection performance in satellite imagery[END_REF][START_REF] Wang | Remote sensing image super-resolution and object detection: Benchmark and state of the art[END_REF]. Similarly, the variability of the image quality within a given dataset is acknowledged, and some works have been using restoration models to improve their quality [START_REF] Rasti | Image restoration for remote sensing: Overview and toolbox[END_REF]. However, little is known about the influence on the resulting segmentation/detection performance. In this paper, we propose to investigate state-of-the-art models for image restoration and image super-resolution [START_REF] Liang | Swinir: Image restoration using swin transformer[END_REF][START_REF] Zhang | Practical blind denoising via swin-conv-unet and data synthesis[END_REF] and their influence on cornerstone tasks of geospatial imaging analysis, namely image detection and image segmentation.

PROPOSED APPROACH

Geospatial image datasets can contain both variations in noise and image processing artefacts [START_REF] Saunier | Technical note on quality assessment for blacksky[END_REF] as well as mild variations in resolution. Given networks trained for image detection and segmentaion on traditional geospatial image datasets, we propose to investigate the impact of two preprocessing pipelines: artifacts (and noise) removal and super-resolution. The former allows generating images with the same high quality fixed for each image, while the latter allows fixing the per-pixel resolution of each image during training. We next briefly detail these two pipelines.

Recent works in blind image restoration (i.e. when no assumption is made on the type of image degradation, such as the nature of the noise or of the compression artefacts) have shown impressive results for natural images. Such setup applies to geospatial image datasets, where the image acquisition pipeline is often only partially known. We use the SCUNet neural network [START_REF] Zhang | Practical blind denoising via swin-conv-unet and data synthesis[END_REF] as our artifacts removal pipeline, an architecture that has proven to be efficient for real image restoration tasks.

A longstanding limitation of super-resolution with deep neural networks was the restriction to integer upsampling factors. Recent works and new architectures have overcome this bottleneck [START_REF] Chen | Learning continuous image representation with local implicit image function[END_REF][START_REF] Lee | Local texture estimator for implicit representation function[END_REF], allowing the proposal of meaningful super-resolution factors adapted to each image. In this work, we use the LTE super resolution network [START_REF] Lee | Local texture estimator for implicit representation function[END_REF].

We use the YOLOv5 network [START_REF] Jocher | ultralytics/yolov5: v3.1 -Bug Fixes and Performance Improvements[END_REF] for both image detection and image segmentation; this network is trained on non-preprocessed versions of the datasets of interest.

EXPERIMENTAL RESULTS

Image segmentation after restoration

We show the influence of the noise and artifacts preprocessing with SCUNet neural network for image segmentation task in Figure 1. We notice that overall, the preprocessing tends to degrade the performance of the network. The roof class is less well detected (notice however that false positives also disappear), while the masks of cars are better recovered after the preprocessing step. This experiment suggests that the segmentation results strongly rely on statistical features, such as noise and artifacts that may not be visible to the naked eye. We however underline that preprocessing pipelines may be prone to errors, and in the particular example of Figure 1, the image restoration network over-smooths the image to the point of removing some visible tiles from the roof and replacing it with a uniform surface.

Image super resolution pipelines

We next propose to briefly investigate the performance of super-resolution methods for geospatial images on the BigEarthNet [START_REF] Sumbul | BigEarthNet: A large-scale benchmark archive for remote sensing image understanding[END_REF], DOTA [START_REF] Xia | DOTA: A largescale dataset for object detection in aerial images[END_REF] and xView [START_REF] Lam | xView: Objects in context in overhead imagery[END_REF] datasets. Since no groundtruth is available, we generate downsampled images with bicubic interpolation that will serve as our observations, with factors 1.5, 2 and 3. We next apply different super-resolution pipelines (namely bicubic interpolation, and LTE with SwinIR and RDN backbones) for these downsampled images and compute the PSNR between the recovered image and the original (groundtruth) image. Because geospatial images may suffer from strong artefacts, we also propose to add an additional artifacts removal step before performing super resolution. Metrics are given in Table 1. Overall, LTE with the RDN backbone performs best, with noticeable gains when an artifacts removal step is added prior to the SR network for DOTAv2.0 and BigEarthNet-S2. We notice that non-preprocessed LTE tend to perform poorly on the low quality image dataset BigEarthNet-S2, where bicubic interpolation works best.

Image detection after preprocessing

We next investigate the impact of variations in the resolution of the geospatial images on the image detection pipeline. Visual results on the xView dataset are presented in Figure 2, and metrics on the full dataset are shown in Table 2. As a first observation, one notices that the building detections in the case of non-preprocessed and preprocessed images are fairly similar. On the opposite, a clear loss in performance for the building class is visible when processing a super-resolved image.

Metrics on the xView dataset are shown in Table 2. We notice a clear loss in performance when performing either preprocessing or super resolution with factor 1.6. Notice that the decrease in performance varies among classes; for instance, the "Car" and "Aircraft" classes are rather robust to preprocessing. Similarly, the resolution variation does not impact equally the performance among classes.

Further experiments have been performed on following datasets DOTA [START_REF] Xia | DOTA: A largescale dataset for object detection in aerial images[END_REF], Houston UAV [START_REF] Goswami | FloodNet-to-FloodGAN : Generating Flood Scenes in Aerial Images[END_REF], OSCD BiDate [START_REF] Daudt | Urban change detection for multispectral earth observation using convolutional neural networks[END_REF], OSCD MultiDate [START_REF] Papadomanolaki | Detecting urban changes with recurrent neural networks from multitemporal sentinel-2 data[END_REF], SeeDroneSeaV2 [START_REF] Kiefer | 1st workshop on maritime computer vision (macvi) 2023: Challenge results[END_REF] and QFabric [START_REF] Verma | QFabric: Multi-task change detection dataset[END_REF]. These datasets and experiments' outputs are available in the GeoEngine platform [START_REF] Shin | Europa: Increasing accessibility of geospatial datasets[END_REF][START_REF] Verma | GeoEngine: A platform for production-ready geospatial research[END_REF].

CONCLUSION

In this paper, we have shown that applying state-ofthe-art restoration models for artifact removal and image super-resolution within the imaging pipeline can strongly perturb the predictions despite a very mild influence on the naked eye. While image restoration may improve some of the segmentation masks for some spe-cific classes, it leads to a drop in performance overall.

Preprocessing geospatial image datasets with image enhancement networks may reduce the dependency of neural networks for downstream tasks to spurious noise and artifacts.

Fig. 1 :

 1 Fig. 1: Influence of noise and artifacts removal on the segmentation results. (a) shows segmentation masks when no preprocessing is performed on the input image; (a) shows segmentation masks when noise and artifacts removal is performed on the input image.

Fig. 2 :

 2 Fig. 2: Experimental evidence of the influence of image restoration tools on the quality of Yolov5 object detection on the xView dataset. (a) shows results of image detection for a non-preprocessed image. (b) shows the result of Yolov5 on the same image, but that was preprocessed with SCUnet [10]. (c) Shows the results of Yolov5 on the same image, but super-resolved with a factor 1.6 with LTE [13]. Notice the different bounding boxes detected in the three cases. Method BigEarthNet-S2 DOTAv2.0 xView ×1.5 ×2 ×3 ×1.5 ×2 ×3 ×1.5 ×2 ×3 Bicubic 25.3 23.3 20.4 28.7 26.0 25.4 35.5 33.4 29.5 LTE-SWINIR 26.4 20.2 17.4 28.4 28.2 26.1 36.3 38.0 32.1 LTE-RDN 26.4 22.8 17.5 29.3 28.3 25.9 37.5 38.1 34.4 SCUNet + Bicubic 25.0 23.3 20.5 28.0 25.7 25.4 33.7 32.4 29.2 SCUNet + LTE-SWINIR 26.3 20.9 19.8 28.2 28.2 26.4 34.4 35.1 31.9 SCUNet + LTE-RDN 26.3 23.5 19.8 29.1 28.1 26.7 35.1 35.1 34.0

Table 1 :

 1 Comparison of pure SR (top) and preprocessed SR (bottom). Best results are indicated in red, second best in blue.

	5

Table 2 :

 2 Metrics on the xView validation set in the three cases. Notice the substantial decrease of the mean AP metric as one progressively moves from no preprocessing (first and fourth column) to noise and artefact removal (second and fifth) to super-resolved (third and sixth). We report top-level hierarchy by grouping semantically similar objects to avoid clutter.


Florence Amardeilh

Cédric Bousquet

Sylvie Guillemin-Lanne

Mathilde Wiss-Thebault

Laetitia Guillot

Denis Delamarre

Agnès Lillo-Le Louet

Anita Burgun

A Knowledge Management Platform for Documentation of Case Reports in Pharmacovigilance

Keywords: systems integration, information storage and retrieval, databases, drug adverse effects, text mining, semantic annotation, knowledge bases

Most countries have developed information systems to report drug adverse effects. However, as in other domains where systematic reviews are needed, there is little guidance on how systematic documentation of drug adverse effects should be performed. The objective of the VigiTermes project is to develop a platform to improve documentation of pharmacovigilance case reports for the pharmaceutical industry and regulatory authorities. In order to improve systematic reviews of adverse drug reactions, we developed a prototype that first reproduces and standardizes search strategies, then extracts information from the Medline abstracts which were retrieved and annotates them. The platform aims at providing transparent access and analysis tools to pharmacovigilance experts investigating relevance of safety signals related to drugs. The platform's architecture consists in the integration of two vendor tools ITM® and Luxid® and one academic web service for knowledge extraction from medical literature. Whereas a manual search performed by a pharmacovigilance expert retrieved 578 publications, the system proposed a list of 229 publications thus decreasing time required for review by 60%. Recall was 70% and additional developments are required in order to improve exhaustivity.

Introduction

The information about drug safety is based mainly on spontaneous reporting systems by health care professionals to a central agency and/or to the pharmaceutical companies [START_REF] Bright | Automated support for pharmacovigilance: A proposed system[END_REF]. Other sources of information are of interest to improve our knowledge of adverse drug reaction. The medical literature is one of them, and its analysis is mandatory for the pharmaceutical companies, as noted in the recent Guidelines on Pharmacovigilance for medicinal products for human use. "The Marketing Authorisation Holder is therefore expected to maintain awareness of possible publications by accessing a widely used systematic literature review and reference database (e.g., Medline, Excerpta Medica or Embase) no less frequently than once a week" [START_REF] Hopewell | Reporting of adverse events in systematic reviews can be improved: Survey results[END_REF].

Currently, with widespread use of internet, information retrieval, extraction and analysis of individual cases reports, or of other information (clinical studies, epidemiological studies, press releases, …), is a challenge for pharmacovigilants [START_REF] Cobert | The internet and drug safety[END_REF]. Several studies showed that researchers reported difficulties when searching electronic resources for information on adverse effects [START_REF] Loke | Cochrane adverse effects methods group. Systematic reviews of adverse effects: Framework for a structured approach[END_REF][START_REF] Golder | Poor reporting and inadequate searches were apparent in systematic reviews of adverse effects[END_REF][START_REF] Uren | Semantic annotation for knowledge management: Requirements and a survey of the state of the art[END_REF]. Among others, these difficulties are due to poor indexing, to the wide variety of articles that may be potentially useful, to variation in their qualities, as well as the lack of tools to perform systematic search. Moreover, the field of pharmacovigilance is extensive as all drugs and all adverse events must be under surveillance. The question and/or the answer about safety may be broad or narrow in scope. For example, a review with a broad scope might be "which adverse effects are associated with antidepressant therapy" and a narrow one being "the risk of suicide or suicidal behavior in teens taking a serotonin reuptake inhibitor". Adverse Drug Reaction (ADR) reviews may be appropriate targets for clustering techniques and require complex literature search strategies, as well as information extraction driven by domain knowledge. Therefore, it is desirable to develop a literature search strategy based on key elements of the pharmacovigilance field, to automate data mining in electronic databases, to have a better information retrieval and to assist the pharmacovigilance specialist visualizing and mining the results. Automation is one of the very important requirements, as it is needed to ease the knowledge acquisition bottleneck, particularly for annotating large collections of legacy documents [START_REF] Garcelon | Evidence in pharmacovigilance: extracting adverse drug reactions articles from MEDLINE to link them to case databases[END_REF].

In this article, we present for the first time the design of a new platform that automatically performs searches and identifies information on adverse drug reactions from the medical literature, as part of the VigiTermes project (http://vigitermes.univ-rennes1.fr).

Material and Methods

The architecture of the system is based on an integrated platform composed of both existing and specifically developed web services. When a new case is reported, the workflow consists of three main steps (i) to build and refine a normalised query to retrieve pertinent abstracts from Medline, (ii) to perform domain-oriented annotation on Medline abstracts and (iii) to enrich the knowledge base and the documentation of the case report. The steps are encapsulated in a UIMA [START_REF] Amardeilh | A semantic web portal with HLT capabilities[END_REF] (Unstructured Information Management Architecture) infrastructure, providing a rich text mining standardized environment for manipulating documents and annotations, and easing external components integration, being the ones presented in this article or others. Also, the UIMA infrastructure has been enriched to comply with the Semantic Web standards, so that the outputs can be easily accessed, shared and exploited by other applications.

Pubmed Querying Web Service

We reused and adapted the algorithm developed by Garcelon et al. for querying Medline [8]. The main entry is a pair of Adverse Effect (AE) -Active Ingredient (AI).

Additional parameters may be added for filtering purposes, such as gender, age class, publication type and period. The web service relies on a UMLS web service to normalize the entries [9] and the MEDLINE web service to retrieve the corresponding abstracts [10].

Luxid® Annotation Factory

Luxid® Annotation Factory (LAF) is a software component dedicated to information extraction: It takes as input original documents and enriches them with semantic annotations (categories, entities and relationships). All analysis steps are packaged in linguistics components that build a so-called Skill Cartridge™, which is plugged to the extraction server. It can be imagined as a cascade of extraction modules that condense the textual data into meaning. The analysis is based on finite state technology. A specific Skill Cartridge™ dedicated to pharmacovigilance has been defined, extracting medical entities (Diseases, Treatments, Diagnostic Methods, Symptoms, Patients, Clinical trials) as well as relationships (Diagnosis, Therapy, Drug use such as doses, route, frequency and duration).

Intelligent Topic Manager

The Intelligent Topic Manager® (ITM) [START_REF] Amardeilh | A semantic web portal with HLT capabilities[END_REF] is an ontology-based solution for Taxonomy, Thesaurus, Controlled vocabulary and Knowledge base Management based on the Semantic Web standards (RDF, OWL, SKOS). It allows access to distributed knowledge, management of large terminologies and collaborative and customized access for end users to legacy content through semantic portals. ITM uses MedDRA or the WHO-ART terminologies to consolidate and enrich the annotations and exploit them to automatically create new instances in the knowledge base such as the detected relations between adverse effects and drugs. This is operated by the ITM's Content Augmentation Manager (CA Manager), an open-source tool that is used to bridge the gap between information extraction tools and semantic repositories and that extends the UIMA framework with the Semantic Web standards.

Result

The VigiTermes solution for the semantic annotation of pharmacovigilance-related articles is a semantic portal that performs: 1) automated extraction and annotation of Medline abstracts with regard to a pharmacovigilance ontology and standard medical terminologies, and 2) case reports documentation thanks to the knowledge instances detected from the produced annotations. The semantic portal provides a user interface from which the pharmacovigilance expert submits a query with at least one AE and one AI as reported in the case. The platform then calls the web service that translates and enriches the user query in order to obtain a list of relevant PMIDs from Pubmed. This list of PMIDs is then sent to the CA Manager (see Figure 1) that transmits the abstract content of each PMID to Luxid® which extracts the relevant information and annotates it. This enriched content is then controlled by the CA Manager with respect to the medical terminologies and the knowledge base instances already stored in ITM. It consolidates each annotation and new knowledge instance thanks to a set of heuristic rules detailed in [START_REF] Amardeilh | Semantic annotation & ontology population[END_REF] before sending back the results to the semantic portal. The visualization step takes advantage of the produced annotations by highlighting the relevant concepts and instances identified in the abstracts. As of today, the pharmacovigilance regional centre of the European Georges Pompidou hospital experiments the VigiTermes semantic portal for functional validation. Use case is the documentation process for new ADR-AI case reports. Preliminary results have been obtained for the Pubmed Query web service. The gold standard was a Medline search performed by a pharmacovigilant expert who recorded his queries and identified the relevant publications based on 15 reported ADR cases. These relevant references represented 69 publications selected from the 578 retrieved with the Medline search (12%). The Pubmed Query component was then applied to the same set of 15 cases and the number of identified publications was 229. Within this set, 48 publications were belonging to the 69 relevant publications selected by the pharmacovigilance expert. Recall was 70% and precision 21%. Eleven cases of 15 have a recall of 100%.

Discussion and Conclusion

The medical literature is still a major source of information to evaluate drug safety: It has a valuable role in providing early warning alerts and can strengthen a signal detected by other means. Whereas pharmaceutical companies must organise a systematic survey only for the drugs they commercialize, regulatory authorities have to screen all the drugs available on the market. In any case, the amount of published literature on ADRs is overwhelming, so a standardized and automated tool would ensure that a minimum surveillance could be performed for each drug. The national French VigiTermes research project was funded to implement new methods for signal detection and analysis in pharmacovigilance. We presented the integration platform built to support the pharmacovigilance teams from industry and regulatory authorities by standardizing literature search on ADRs. The system works as a filter and it is able to reduce the number of abstracts to be reviewed by 60%. Additional developments are required in order to improve recall. The technical choices are based on Semantic Web technologies, including ontology development and Web services, and the new standards recently developed in Natural Language Processing (UIMA).

Knowledge-based approaches have already been developed for screening drugs and predicting drug safety at the pre-clinical stage whereas this knowledge management platform is dedicated to the documentation of spontaneous case reports after market authorization. The development perspectives of our project will aim at adding other pharmacovigilance-related data sources (such as Martindale, Meyler's Side effects of Drugs, other databases like Micromedex) in order to complete data obtained from Pubmed. The presented platform can also be improved by developing tailored user interfaces for the pharmacovigilance end user. Moreover, to tackle some actual limitations of the platform, ontologies like SNOMED CT, by offering the ability to relate concepts together, will be most valuable in order to build clusters of MedDRA terms that express similar medical conditions. The PharmARTS tool developed by another partner of the VigiTermes project implements mappings between SNOMED CT and MedDRA/WHO-ART and a web-based graphical interface in order to select adverse reaction terms corresponding to a formal definition expressed thanks to SNOMED CT concepts [START_REF] Alecu | PharmARTS: Terminology web services for drug safety data coding and retrieval[END_REF]. This would help to complement the current search strategy by adding subsumption mechanisms in the algorithm. Finally the platform should accommodate cross-platform integration with proprietary spontaneous reporting system or other signal detection tools.

Figure 1 .

 1 Figure 1. Case report documentation workflow

Corresponding Author: Florence Amardeilh, Mondeca, 3 cité Nollez, 75018 Paris, France; E-mail: florence.amardeilh@mondeca.com.

Acknowledgment. The VigiTermes project is funded by the French Agence Nationale pour la Recherche (ANR) ANR-07-TECSAN-026.