Velocity Field Research Articles

Modified (n+1)D Laplacian for smooth pressure reconstruction based on time-resolved velocimetry (1): analysis and numerics

Abstract We analyze a smooth pressure solver based on the "modified Poisson equation": ∇2 p +ξ 2∂2 p/∂ t 2 = f(u(t)), where p is the pressure field, u (t) is the velocity field measured by time-resolved image velocimetry, and ξ 2 is a tunable parameter to control the solver's diffusive behavior in time. This modified Poisson equation aims at obtaining smooth pressure fields from potentially noisy image velocimetry measurements, and is a part of the current four-dimensional (4D) pressure solver (implemented in, for example, DaVis 10.2) by LaVision. This work focuses on investigating three aspects of the "modified Poisson equation": smoothing effect, error propagation, and drift in time. We first provide rigorous analysis and validate that this solver can sufficiently smooth the computed pressure field by setting a large enough ξ 2. However, a large value of ξ 2 may cause large errors in the reconstructed pressure fields. Then we introduce an upper bound on the error in the reconstructed pressure fields to quantify the error propagation dynamics. Finally, we discuss the potential drift due to the partitioning in time, which is an optional strategy used in LaVision's current 4D pressure solver to reduce computational costs. Our analysis and validation not only show that careful choice of the parameters (e.g., ξ 2) is needed for smooth and accurate pressure field reconstruction but provide theoretical guidelines for parameter tuning when similar pressure solvers are used for time-resolved image velocimetry data.

Conservation equations for open-channel flow: effects of bed roughness and secondary currents

AbstractTime-averaged velocity fields in uniform open-channel flows over rough beds may exhibit spatial heterogeneities due to the effects of bed roughness and secondary currents (SCs). The latter typically originate from the turbulence anisotropy and spatial heterogeneity introduced by the solid and mixed corners (i.e., between sidewalls and water surface), but may also appear due to roughness spanwise heterogeneities, e.g., associated with patchy vegetation distributions or streamwise sediment ridges on the channel bed. In this paper, we propose rigorous conservation equations for momentum, kinetic energy and fluid stresses accounting for the contributions of bed roughness and SCs, separately. Particular attention is given to the terms regulating the energy exchanges between roughness-induced and SC-related motions, which are expected to provide information on the physical mechanisms leading to the generation of roughness-induced SCs. The proposed approach is illustrated using a large-eddy simulation of a rough-bed open-channel flow.

Predictive Modeling of Future Full-Ocean Depth SSPs Utilizing Hierarchical Long Short-Term Memory Neural Networks

The spatial-temporal distribution of underwater sound speed plays a critical role in determining the propagation mode of underwater acoustic signals. Therefore, rapid estimation and prediction of sound speed distribution are imperative for facilitating underwater positioning, navigation, and timing (PNT) services. While sound speed profile (SSP) inversion methods offer quicker response times compared to direct measurement methods, these methods often focus on constructing spatial sound velocity fields and heavily rely on sonar observation data, thus imposing stringent requirements on data sources. To delve into the temporal distribution pattern of sound speed and achieve SSP prediction without relying on sonar observation data, we introduce the hierarchical long short-term memory (H-LSTM) neural network for SSP prediction. Our method enables the estimation of sound speed distribution without the need for on-site data measurement, significantly enhancing time efficiency. Compared to other state-of-the-art approaches, the H-LSTM model achieves a root mean square error (RMSE) of less than 1 m/s in predicting monthly average sound speed distribution. Its prediction accuracy has improved several-fold over alternative methods, which validates the robust capability of our proposed model in predicting SSP.

Numerical Study on Fluid Flow Behavior and Heat Transfer Performance of Porous Media Manufactured by a Space Holder Method.

The velocity field and temperature field are crucial for metal foams to be used as a heat exchanger, but they are difficult to obtain through physical experiments. In this work, the fluid flow behavior and heat transfer performance in open-cell metal foam were numerically studied. Porous 3D models with different porosities (55-75%) and pore sizes (250 μm, 550 μm, and 1000 μm) were created based on the porous structure manufactured by the Lost Carbonate Sintering method. A wide flow velocity range from 0.0001 m/s to 0.3 m/s, covering both laminar and turbulent flow regimes, is fully studied for the first time. Pressure drop, heat transfer coefficient, permeability, form drag coefficient, temperature and velocity distributions were calculated. The calculated results agree well with our previous experimental results, indicating that the model works well. The results showed that pressure drop increased with decreasing porosity and increasing pore size. Permeability increased and the form drag coefficient decreased with increasing porosity, and both increased with increasing pore size. The heat transfer coefficient increased with increasing velocity and porosity, whereas it slightly decreased with increasing pore size. The results also showed that at high velocity, only the metal foam close to the heat source contributes to heat dissipation.

Computational analysis of microgravity and viscous dissipation impact on periodical heat transfer of MHD fluid along porous radiative surface with thermal slip effects

The current thermal slip and Magnetohydrodynamic analysis plays prominent importance in heat insulation materials, polishing of artificial heart valves, heat exchangers, magnetic resonance imaging and nanoburning processes. The main objective of the existing article is to deliberate the impact of thermal slip, thermal radiation and viscous dissipation on magnetized cone embedded in a porous medium under reduced gravitational pressure. Convective heating characteristics are used to increase the rate of heating throughout the porous cone. For viscous flow along a heated and magnetized cone, the conclusions are drawn. The simulated nonlinear partial differential equations are transformed into a dimensionless state by means of suitable non-dimensional variables. The technique of finite differences is implemented to solve the given model with Gaussian elimination approach. The FORTRAN language is used to make uniform algorithm for asymptotic results according to the boundary conditions. The influence of controlling parameters, such as thermal radiation parameter Rd, Prandtl number Pr, porosity parameter Ω, viscous dissipation parameter Ec, δ thermal slip parameter, Rg reduced gravity parameter and mixed convection parameter λ is applied. Graphical representations were created to show the consequences of various parameters on velocity, temperature and magnetic field profiles along with fluctuating skin friction, fluctuating heat and oscillatory current density. It is found that velocity and temperature profile enhances as radiation parameter enhances. It is noted that the amplitude and oscillations in heat transfer and electromagnetic waves enhances as magnetic Prandtl factor increases.

3D simulations of a neon burning convective shell in a massive star

ABSTRACT The treatment of convection remains a major weakness in the modelling of stellar evolution with one-dimensional (1D) codes. The ever-increasing computing power makes now possible to simulate in three-dimensional (3D) part of a star for a fraction of its life, allowing us to study the full complexity of convective zones with hydrodynamics codes. Here, we performed state-of-the-art hydrodynamics simulations of turbulence in a neon-burning convective zone, during the late stage of the life of a massive star. We produced a set of simulations varying the resolution of the computing domain (from 1283 to 10243 cells) and the efficiency of the nuclear reactions (by boosting the energy generation rate from nominal to a factor of 1000). We analysed our results by the mean of Fourier transform of the velocity field, and mean-field decomposition of the various transport equations. Our results are in line with previous studies, showing that the behaviour of the bulk of the convective zone is already well captured at a relatively low resolution (2563), while the details of the convective boundaries require higher resolutions. The different boosting factors used show how various quantities (velocity, buoyancy, abundances, and abundance variances) depend on the energy generation rate. We found that for low boosting factors, convective zones are well mixed, validating the approach usually used in 1D stellar evolution codes. However, when nuclear burning and turbulent transport occur on the same time-scale, a more sophisticated treatment would be needed. This is typically the case when shell mergers occur.

Optimizing flow uniformity and velocity fields in aquaculture tanks by modifying water inlets and nozzles arrangement: A computational fluid dynamics study

Ensuring optimal conditions for fish, especially in terms of uniform velocity fields, is crucial for aquaculture systems to attain self-cleaning efficiency in rearing tanks and better fish behavior, which ultimately impacts their survival and growth. The current study presented a full-scale computational fluid dynamics (CFD) model of three types of circular, square and square arc angle tanks used in aquaculture farms to choose the most optimal tank based on the flow uniformity and velocity field. At the next step, the optimal arrangement of the inlet number, inlet location, inlet angle, as well as the number of nozzles on each inlet was reconfigured to create the most optimal tank. The simulations were done using the CFD software FLUENT distributed by the ANSYS Corporation. The software calculates velocities in the tanks by solving the Reynolds-averaged Navier-Stokes equations of continuity and momentum that govern the mean turbulent flow of water. The results illustrated circular and square arc angle tanks had significantly more uniform fluid velocity compared to the square tanks, which the square arc angle tank due to better flow velocity near the wall and space utilization was selected for further rearrangements. Additionally, the implementation of two entrance pipes near the corner of the two parallel walls with an entry angle of 0° in a square arc angle tank resulted in a more consistent water velocity. As the number of inlet nozzles increased to six, the water streamlines became more uniform, suggesting a more consistent water velocity throughout the tank. However, when the number of input nozzles increased to nine, the tension on the nozzle apertures were increased probably due to the decrease of distance between them. Findings of the present study concluded that two inlets in the corner with an entry angle of 0° and six nozzles on each inlet pipe could provide the optimum water velocity in the square arc angle tanks.

Diffusiophoresis of a Charged Soft Sphere in a Charged Spherical Cavity

The quasi-steady diffusiophoresis of a soft particle composed of an uncharged hard sphere core and a uniformly charged porous surface layer in a concentric charged spherical cavity full of a symmetric electrolyte solution with a concentration gradient is analyzed. By using a regular perturbation method with small fixed charge densities of the soft particle and cavity wall, the linearized electrokinetic equations relevant to the fluid velocity field, electric potential profile, and ionic concentration distributions are solved. A closed-form formula for the diffusiophoretic (electrophoretic and chemiphoretic) velocity of the soft particle is obtained as a function of the ratios of the core-to-particle radii, particle-to-cavity radii, particle radius to the Debye screening length, and particle radius to the permeation length in the porous layer. In typical cases, the confining charged cavity wall significantly influences the diffusiophoresis of the soft particle. The fluid flow caused by the diffusioosmosis (electroosmosis and chemiosmosis) along the cavity wall can considerably change the diffusiophoretic velocity of the particle and even reverse its direction. In general, the diffusiophoretic velocity decreases with increasing core-to-particle radius ratios, particle-to-cavity radius ratios, and the ratio of the particle radius to the permeation length in the porous layer, but increases with increasing ratios of the particle radius to the Debye length.

A simultaneous non-invasive diagnosis method for flame temperature and velocity fields based on radiation self-calibration and optical flow

The measurement of flame temperature and velocity is crucial to combustion research, hence it is of great significance to develop a non-invasive diagnosis technology for the measurement of flame temperature and velocity. In this study, a single-camera simultaneous non-invasive diagnosis technology for flame temperature and velocity field was developed, based on radiation self-calibration and optical flow method. The diagnosis method was applied to two case studies, propane diffusion flame and solid surface spread flame. The reconstructed flame temperature field was compared with measuring results by thermocouples. Results show that the reconstructed temperature field can accurately describe the symmetrical distribution characteristics and the clear high-temperature front. The combustion zone reconstruction temperature was 1250–1380 K for propane diffusion flame and the maximum reconstruction temperature was 1400 K for solid spread flame. The maximum relative error between the reconstructed temperature and the measured values by thermocouples is less than 15 %. Additionally, the flow velocity field at the flame edge was also measured, which could provide a good qualitative characterization of flame kinematic.

Microfluidic flow tuning via asymmetric flow of nematic liquid crystal under temperature gradient

In this work, efficient microfluidic flow rate tuning based on the asymmetric flow of nematic liquid crystal 5CB under a horizontal temperature gradient is studied. Rectangular microchannels with the width of 100 μm are fabricated through soft lithography and treated with homeotropic surface anchoring conditions. Polarized optical microscopy is applied to explore the unique optical anisotropic characteristics of the nematic liquid crystal. The asymmetric velocity profiles in the microchannel are obtained by particle tracking velocimetry. The effects of temperature, flow rate, and aspect ratio on the velocity profile and split ratio of the asymmetric flow are quantitatively studied for the first time, while the mechanism of the flow asymmetry of the nematic liquid crystal is discussed. The results show that the asymmetric flow of the nematic liquid crystal occurs after the horizontal temperature gradient is applied, with the velocity in the heated region markedly higher than its counterpart. The split ratio of the asymmetric flow increases with the increase in the temperature gradient and the decrease in the flow rate. The aspect ratio influences the asymmetric flow through approaches of average velocity and surface anchoring strength, while the former is more distinct. The impacts of temperature gradient, flow rate, and aspect ratio on the flow asymmetry of nematic liquid crystals are caused by the coupling between physical properties, velocity field, and director field. Microchannels based on the asymmetric flow characteristics of nematic liquid crystals can act as a novel kind of temperature-controlled microvalve to achieve efficient microfluidic flow tuning.

ST-LSTM-SA: A New Ocean Sound Velocity Field Prediction Model Based on Deep Learning

ST-LSTM-SA: A New Ocean Sound Velocity Field Prediction Model Based on Deep Learning

Are High-Σ1 Massive Blue Spiral Galaxies Rejuvenated Systems?

Quiescent galaxies generally possess denser cores than star-forming galaxies with similar mass. As a measurement of the core density, the central stellar mass surface density within a radius of 1 kpc (Σ1) was thus suggested to be closely related to galaxy quenching. Massive star-forming galaxies with high Σ1 do not fit into this picture. To understand the origin of such galaxies, we compare the spatially resolved stellar population and star formation properties of massive (>1010.5 M ⊙) blue spiral galaxies with high and low Σ1, divided by Σ1 = 109.4 M ⊙ kpc−2, based on the final release of MaNGA integral field unit data. We find that both high-Σ1 and low-Σ1 blue spirals show large diversities in stellar population and star formation properties. Despite the diversities, high-Σ1 blue spirals are statistically different from the low-Σ1 ones. Specifically, the radial profiles of the luminosity-weighted age and Mgb/〈Fe〉 show that high-Σ1 blue spirals consist of a larger fraction of galaxies with younger and less α-element-enhanced centers than their low-Σ1 counterparts, ∼55% versus ∼30%. The galaxies with younger centers mostly have higher central specific star formation rates, which still follow the spaxel-based star formation main-sequence relation. Examinations of the Hα velocity field and the optical structures suggest that galactic bars or galaxy interactions should be responsible for the rejuvenation of these galaxies. The remaining ∼45% of high-Σ1 blue spirals are consistent with the inside-out growth scenario.

A spectroscopic investigation of thermal instability for cylindrical equilibria with background flow

Context. Flows are omnipresent and govern the dynamics of plasma. Solar tornadoes are a class of apparently rotating prominences that might be formed by thermal instability. In spectroscopic studies on thermal instability, background flow is commonly neglected. Aims. We here determine the effect of background flow on thermal instability in cylindrical magnetic field configurations. How various parameters affect the distribution of eigenmodes in the magnetohydrodynamic (MHD) spectrum is also explored. We investigate whether discrete thermal modes exist. Methods. In an analytical study, we extended upon the literature by including a generic background flow in a cylindrical coordinate system. The non-adiabatic MHD equations are linearised, Fourier-analysed, and examined to understand how a background flow changes the continua. An approximate expression for discrete thermal modes is derived using a Wentzel-Kramers-Brillouin (WKB) analysis. The analytical results are then verified for a benchmark equilibrium using the eigenvalue code Legolas. The eigenfunctions of discrete thermal modes are visualised in 2D and 3D. Results. The thermal continuum is Doppler-shifted due to the background flow, just like the slow and Alfvén continua. Discrete modes are altered because the governing equations contain flow-related terms. An approximate expression to predict the appearance of discrete thermal modes based on the equilibrium parameters is derived. All analytical expressions match the numerical results. The distribution of the density perturbations of the discrete thermal modes is not a uniform or singular condensation, due to the shape of the eigenfunctions and the dependence of the assumed waveform on the coordinates and wavenumbers. A 3D visualisation of the total velocity field shows that the helical field is heavily influenced by the radial velocity perturbation. Conclusions. We derived analytic expressions for non-adiabatic MHD modes of a cylindrical equilibrium with background flow and verified them using a coronal equilibrium. However, the equations are valid for and can be applied in other astrophysical environments.

Modeling of periodical shearing flow in a fibrous space with applications in shear-induced brain injury

This paper presents a theoretical model examining the interaction between a fibrous network and viscous fluid flow driven by an oscillating boundary. The aim is to understand how oscillating impacts are transmitted from the skull, through the arachnoid trabeculae network filled with cerebrospinal fluid, as observed in shaken baby syndrome. The model uses an effective medium approach to determine the fluid velocity field while each fiber is treated as a soft string undergoing deformation. Results indicate that the frequency of oscillation, fiber stiffness, and porous structure resistance significantly influence the oscillating shearing flow, as indicated by the Womersley (Wo), Brinkman (α), and Bingham (Bm) numbers. Application of the model to shaken baby syndrome suggests that oscillations in the cerebrospinal fluid and arachnoid trabeculae can significantly surpass those on the skull, leading to intense shear stress penetration to the brain. This model is the first study to integrate the dynamic response of string-like fibrous networks in fluid flows with oscillating boundaries and offers a quantitative framework for predicting the transmission of shearing forces from the skull to the brain matter.

Super-resolution reconstruction of turbulent flows with a hybrid framework of attention

In a plethora of research endeavors concerning flow fields, acquiring high-resolution data is paramount. However, obtaining high-resolution turbulence data invariably requires substantial computational resources. Although super-resolution reconstruction of turbulent fields has emerged as a salient technique for detail extraction, conventional interpolation methods pose a significant challenge in reconstructing small-scale structures, often resulting in overly smooth outcomes. In this study, we propose a novel hybrid framework of spatially-adaptive feature attention (HSAFA) for the high-quality reconstruction of turbulent fields. This framework is characterized by the implementation of multidimensional feature fusion, which enhances the model's ability to capture details of turbulence. We rigorously applied the proposed model to datasets comprising laminar flow around a square cylinder and turbulent channel flows, with the reconstructed instantaneous velocity fields and statistics subjected to exhaustive and comparative analysis. Our findings demonstrate that HSAFA is capable of effectively reconstructing high-resolution turbulence fields from significantly low-resolution data, covering the range from laminar to turbulent flows.

Spatiotemporal characteristics of flow in the bend and return channel perturbed by rotor–stator interaction

The flows in turbomachinery systems are strongly perturbed by the rotor–stator interaction (RSI) between the rotating and stationary through-flow components, generating the fluctuating flows. This work presents a numerical investigation of a flow in a test centrifugal pump system consisting of an impeller, diffuser, bend, and return channel at the designed and low flow rates. Both vaneless and vaned diffuser models are considered to determine the perturbation of the diffuser vanes on the flow. The objective is to quantitatively assess the impacts of two influential factors, i.e., the diffuser type and the flow rate, on the spatiotemporal characteristics of the transient flow in the various through-flow components. Particular attention is paid to the generation of the reversed flow, circulating vortices, and temporal fluctuations of the velocity field. It is found from the numerical data that both the flow rate and the diffuser type affect the temporal fluctuations of the flow, primarily via the impact of the RSI-induced large-scale vortices generated in the passages of the impeller and the vaned diffuser. The flow in the bend experiences the streamline curvature on the solid walls; thus, the peak values of the fluctuating amplitude of the streamwise and transverse velocities and the reversed flow may shift between the two halves of the channel close to the inner and outer wall. The boundary layer flow patterns are mainly determined by the flow rate at the low flow rate and by the diffuser vanes at the designed flow rate. This work comprehensively reveals the transient behaviors and unsteadiness of the flow which was not provided in the experimental investigation for the test centrifugal pump system which was widely studied since the essential flow physics are included. The numerical data in the stationary bend and return channel are first provided, which are of engineering significance for this type of centrifugal turbomachinery.

Flow mixing and heat transfer deterioration investigation of supercritical carbon dioxide in wire-wrapped bundles

As one selection of the fourth-generation reactors, the gas cooled reactor has received enormous attention such as high power conversion efficiency and simple cycle layout. In this paper, the flow mixing and heat transfer characteristics of supercritical carbon dioxide within a seven-pin wire-wrapped bundle were investigated. Due to the lack of more experiments data of velocity field, two experiments were selected to validate the uncertainty of different turbulence models from the view of temperature field. The analysis of mass exchange between different subchannels revealed that coolant flows consistently in a certain direction in edge and corner subchannels, whereas in center subchannels, the cross flow changes direction periodically. The mixing coefficients at three types of subchannel interfaces were fitted by a sine function with the R2 values are all greater than 0.96. For different mass flux and pressures, the root mean square error between correlations and simulations was less than 1 × 10-3, except when Re equals 15000. Additionally, the heat transfer deterioration of SCO2 was observed. While wire spacers can mitigate the extent of heat transfer deterioration, they cannot completely eliminate it. The Performance Evaluation Criterion (PEC) was introduced to assess the effectiveness of wire spacers in enhancing heat transfer. The results indicate that the PEC exceed unity, meaning that the enhanced heat transfer capability outweighs the additional resistance loss caused by wire spacers. With increasing pressure, the PEC decreases but remains greater than unity. The mixing of coolant between different subchannel induced by wire spacers can reduce the wall temperature of rods at the edge of the bundle. However, the seven-pin wire-wrapped bundle was investigated in this work, and the results may not accurately reflect the flow and heat transfer inside a real reactor rod bundle. In the future, a larger scale rod bundle should be conducted to obtain more universally applicable and realistic flow and heat transfer phenomenon for reactor assembly design.

Investigation on algorithms for simulating large deformation and impact loads

It is a challenge to simulate the hydrodynamic problems covering the large deformation of the free surface arising in severe circumstances with intense flow. This paper investigates algorithms based on the moving particle semi-implicit method for simulating large deformation and impact loads. The algorithm discretizes the fluid domain into a series of particles, each representing a part of the fluid. The pressure field calculation is implicit, and the velocity field calculation is explicit. Three models, including the gradient model, source term, and free-surface detection, have been improved and compared to determine which improvement is the best to enhance the accuracy and stability. The enhanced pressure gradient guarantees that momentum conservation can be satisfied. Particle density and velocity divergence are incompressible conditions combined in the mixed source term approach. The arc approach is used in the free-surface judging process. The results show that the combination of three models is the most effective in exploring the problems of hydrodynamic pressure and dam break. The issue of liquid sloshing including roll and sway investigates the effect of the initial distance and time step. It is found that the simulation accuracy of impact pressure can be increased as the initial distance and the time step decrease. Finally, the free surface breaking and liquid splashing phenomena are easily observed, and the method can accurately simulate the massive deformation of the free surface. These findings are helpful for hazard assessments of the various fluid mechanics-related problems.

An efficient deep learning-based workflow for real-time CO2 plume visualization in saline aquifer using distributed pressure and temperature measurements

Underground carbon dioxide (CO2) sequestration is widely accepted as a proven and established technology to respond to global warming from greenhouse gas emissions. It is crucial to monitor the CO2 plume effectively throughout the life cycle of a geologic CO2 sequestration project to ensure safety and storage efficacy. We propose a fast and efficient deep learning workflow for near real-time data assimilation, forecasting and visualization of CO2 plume evolution in saline aquifer and demonstrate its application at a field site.Our proposed workflow integrates field measurements, including distributed pressure and temperature at wells to visualize spatial and temporal migration of the CO2 plume in the subsurface. The deep learning framework has two key concepts that enhance the efficiency of the training and robustness of the CO2 plume prediction: first, instead of using multiple saturation images as output of the deep-learning model, a single Time of Flight (TOF) image are used to represent CO2 plume propagation; second, we use variational autoencoder-decoder (VAE) for high dimensional image data compression considering uncertainties in the predicted images. Time-of-Flight (TOF) is the travel time of a neural particle from the injection point, which is calculated along streamline based on the velocity field by considering reservoir heterogeneity and driving forces. The latent variables of VAE are estimated through a deep neural network model with inputs of distributed pressure and temperature measurements. Subsequently, the decoder part of the VAE expands the estimated latent variables to the original dimension of the TOF images. We demonstrate the efficacy of the proposed method by comparison with the more traditional pareto-based multi-objective Genetic Algorithm (MOGA) for the assimilation of the field measurements and forecasting of the CO2 plume migration.The power and utility of our proposed workflow are demonstrated by application to the Illinois Basin-Decatur Project (IBDP). The IBDP is a large scale 3-year CO2 storage test and is part of the Midwest Regional Carbon Sequestration Partnership (MRCSP). The field measurements include bottom-hole pressure and distributed temperature sensing (DTS) data at the injection well, and the distributed pressure measurements at several locations along the monitoring well. The dynamic model is a compositional model with 1.7 million cells. First, we identify the influential parameters using sensitivity analysis based on the pressure and temperature responses. Next, the sensitive parameters are sampled from a pre-specified range and a comprehensive training dataset is generated, including the pressure and temperature measurements and TOF images based on flow simulation results from a variety of geological model realizations. The trained neural network model can identify geological model realizations that capture the spatial and temporal migration of pressure and CO2 saturation based on Euclidean distance within the VAE latent space. For comparison with traditional history matching workflow, the selected sensitive parameters are also tuned using MOGA with the pressure and temperature measurements. A reasonable agreement is obtained for the predicted CO2 plume migration between two workflows. The proposed deep learning workflow shows significant speed-up compared to the traditional multi-objective optimization-based history matching workflow (5 h for training and seconds for prediction; compared to several days/weeks for the MOGA).The novelty of this work is the application of an efficient deep learning-based workflow to a large-scale CO2 storage test site for assimilating field measurements and predicting CO2 plume propagation in a near real-time and comparison with traditional history matching approach.

Tectonic deformation in El Salvador from combined InSAR and GNSS data

The country of El Salvador, located at the convergent boundary of the Cocos and Caribbean plates, is subject to frequent seismic events and complex surface deformation. This paper presents the first Interferometric Synthetic Aperture Radar (InSAR)-based velocity field of El Salvador produced by combining InSAR and new GNSS data, which allows us to gain a deeper understanding of the intricate crustal deformation processes in the region. We use L-Band ALOS PALSAR images from five ascending and two descending tracks, as well as 171 continuous and episodic GNSS stations across El Salvador and the Caribbean. The inversion of GNSS and InSAR velocities along fault-perpendicular profiles enable us to assess the accommodation of tectonic deformation along the El Salvador Fault Zone (ESFZ), providing a better constraint on the behaviour of its main structures. Additionally, we are able to better understand how the deformation is transmitted at the western (Jalpatagua-Ipala) and eastern (Fonseca Gulf) terminations of the ESFZ.