Large Geometry Research Articles

Three-Dimensional (3D) Flood Simulation Aids Informed Decision Making: A Case of a Two-Story Underground Parking Lot in Beijing

Flooding in underground spaces, such as subway stations, underground malls, and garages, has increased due to intensified rainfall, urbanization, and population growth. Traditional 2D simulations often overlook crucial vertical flow variations, especially in steep transitions like stairs and ramps. The current study aims to investigate the flood dynamics in large underground geometries by taking a parking lot in Beijing, China, as a study case. The model overcomes the limitations of previous simulations by adapting a full 3D mesh-based simulation with reasonable computational cost. Unlike earlier studies, this model employs a high temporal resolution transient inflow at the inlet to the underground space. Simulation scenarios consider different return periods (5, 20, and 100 years) and inlet water depths, providing an analysis of their impact on flood status in the underground structure. The model generates high spatial–temporal results, enabling precise detection of flood-prone locations, evacuation times, and suggested mitigation techniques. The results recommend evacuating from hazard areas before the 10th minute during extreme flood events. Additionally, the study estimates a 40% increase in flood hazards for scenarios with direct connections between levels. Overall, the study highlights the importance of 3D simulations for accurate risk assessment.

Investigation of smoothed particle hydrodynamics (SPH) method for modeling of two-phase flow through porous medium: application for drainage and imbibition processes

The drainage and imbibition processes are critical mechanisms in petroleum engineering. These processes in a porous medium are controlled by surface forces and pressure gradients. The study of these processes in the pore scale by common simulators always has limitations in multiphase flow modeling. Also, obtaining relative permeability curves through laboratory analysis requires expensive equipment. Additionally, these laboratory experiments are quite expensive and may introduce significant uncertainties. For this purpose, this study investigated the creation of relative permeability curves and their effect on oil production. Initially, single-phase fluid and two-phase droplet flow within a fracture with both soft and rough surfaces were utilized to validate the formulation of the Smoothed Particle Hydrodynamics (SPH) method. Then, by using three randomly constructed porous medium models, the imbibition and drainage processes have been studied. Finally, sensitivity study has been carried out on critical parameters related to fluid flow dynamics in the porous environment, including pressure changes, wettability, and heterogeneity in drainage and imbibition processes. The simulation results were consistent with current theories; therefore, it is reasonable to consider SPH to characterize the fluid flow dynamic during the drainage and imbibition processes. According to sensitivity studies, pressure gradient (residual saturation of displaced fluid is about 5.65% and 8.44%) and heterogeneity (the residual saturation of the displaced fluid was 4.04% and 2.98%) have the largest impact on flow modeling in both drainage and imbibition processes and wettability (the residual saturation became 36.62% and 5.12%) has significant effect on the drainage process through porous medium. In general, fluid flow dynamic studies can be performed using the SPH method to model fluid flow in simple and complex porous medium under various flow conditions. The SPH method can also be used as an applicable tool to investigate the hydrocarbon fluids flow within larger geometries in the future.

Emerging trends in large format additive manufacturing processes and hybrid techniques

AbstractLarge format additive manufacturing (LFAM) technologies are rapidly growing with significant potential for application in multiple technological sectors like aerospace, tooling, automotive, marine, construction, and energy. LFAM processes offer significant advantages including reduced lead time, cost, and material waste, which are further amplified due to the increased volume of the components. This review paper focuses on LFAM technologies with the highest technology readiness level, i.e., metal Directed Energy Deposition (DED), polymer extrusion, and solid-state deposition (i.e. cold spray additive manufacturing (CSAM)). Common system setups, the maximum deposition rate, and the range of processable materials, along with the achievable mechanical properties and geometrical characteristics, are outlined for each technology, both in individual and hybrid manufacturing formats. The main technological challenges are gathered and discussed to highlight the areas that require further development. Finally, the current industrial applications for LFAM technologies and the expected future developments are outlined. This review provides an overview of LFAM technologies’ current status and discusses their potential in improving the manufacturing of complex and large geometries, with a significant reduction in material and energy consumption, while ensuring high-quality and high-performance components.

A low-profile ultra-wideband magneto-electric dipole antenna for ground penetrating radar

ABSTRACT Ultra-wideband antennas that operate at low frequencies usually have a large geometry, which makes them very limited in practical engineering application environment where space is often constrained. In this paper, a novel low-frequency low-profile ultra-wideband magneto-electric (ME) dipole antenna is designed for the application in ground penetrating radar (GPR) to detect deeply buried targets. The antenna is designed at the operation frequency of 230 MHz, so that the objects that are buried as deep as 1.5 m can be detected. Compared to the traditional low-frequency _antennas, it has a profile as low as 740 mm × 140 mm × 150 mm ( 0.49 λ × 0.09 λ × 0.10 λ ). Based on the simulation analysis and validation measurements, the proposed ME dipole antenna has a wide impedance bandwidth for S 11 < − 10 dB from 135 MHz to 382 MHz even when environmental influence is considered. The antenna is further validated with a GPR experiment, where a pipeline with a diameter of about 200 mm at 1200 mm beneath the road surface is successfully detected by an impulse GPR system where the proposed antennas are integrated.

(Invited) Using a Chemo-Mechanical Model to Investigate Electrolyte Infiltration and Surface Reconstruction within Cracked Cathode Material

One of the main goals in modeling lithium-ion batteries is to improve/predict longevity and resilience of new chemistries. To that end, this talk investigates the formation of stress-induced fracture within polycrystalline cathode particles and the impact on capacity loss. The model captures anisotropic Li diffusion within a single polycrystalline particle comprised of hundreds to thousands of randomly oriented grains. Fracture is primarily due to non-ideal grain interactions with slight dependence on high-rate charge demands. Essentially, when neighboring grains are misaligned, they expand a different rates relative to one another leading to high stresses and ultimately the formation of intraparticle cracks. A previous study showed that small particle with large or single grain geometry tend to crack less and retain the most capacity.Cracks within the cathode particle that have access to the surface can potentially fill with electrolyte. When this happens, the cracks can be considered new active surface area where the lithium intercalation reaction can occur. Under sufficient conditions, this could lead to better performance because the grains of the cracked particle start to operate more like a network of single-grain particles. However, the newly open surface area is also subject to side reactions and surface reconstruction resulting in diminished transport properties and potentially trapped lithium. The goal of this talk is to investigate this balance between improved lithium transport pathways caused by lithium infiltration and the reduced diffusion due to surface reconstruction.

Enhancing Ionic Selectivity and Osmotic Energy by Using an Ultrathin Zr‐MOF‐Based Heterogeneous Membrane with Trilayered Continuous Porous Structure

AbstractDesigning a nanofluidic membrane with high selectivity and fast ion transport property is the key towards high‐performance osmotic energy conversion. However, most of reported membranes can produce power density less than commercial benchmark (5 W/m2), due to the imbalance between ion selectivity and permeability. Here, we report a novel nanoarchitectured design of a heterogeneous membrane with an ultrathin and dense zirconium‐based UiO‐66‐NH2 metal–organic framework (MOF) layer and a highly aligned and interconnected branched alumina nanochannel membrane. The design leads to a continuous trilayered pore structure of large geometry gradient in the sequence from angstrom‐scale to nano‐scale to sub‐microscale, which enables the enhanced directional ion transport, and the angstrom‐sized (~6.6–7 Å) UiO‐66‐NH2 windows render the membrane with high ion selectivity. Consequently, the novel heterogeneous membrane can achieve a high‐performance power of ~8 W/m2 by mixing synthetic seawater and river water. The power density can be largely upgraded to an ultrahigh ~17.1 W/m2 along with ~48.5 % conversion efficiency at a 50‐fold KCl gradient. This work not only presents a new membrane design approach but also showcases the great potential of employing the zirconium‐based MOF channels as ion‐channel‐mimetic membranes for highly efficient blue energy harvesting.

Enhancing Ionic Selectivity and Osmotic Energy by Using an Ultrathin Zr-MOF-Based Heterogeneous Membrane with Trilayered Continuous Porous Structure.

Designing a nanofluidic membrane with high selectivity and fast ion transport property is the key towards high-performance osmotic energy conversion. However, most of reported membranes can produce power density less than commercial benchmark (5 W/m2), due to the imbalance between ion selectivity and permeability. Here, we report a novel nanoarchitectured design of a heterogeneous membrane with an ultrathin and dense zirconium-based UiO-66-NH2 metal-organic framework (MOF) layer and a highly aligned and interconnected branched alumina nanochannel membrane. The design leads to a continuous trilayered pore structure of large geometry gradient in the sequence from angstrom-scale to nano-scale to sub-microscale, which enables the enhanced directional ion transport, and the angstrom-sized (~6.6-7 Å) UiO-66-NH2 windows render the membrane with high ion selectivity. Consequently, the novel heterogeneous membrane can achieve a high-performance power of ~8 W/m2 by mixing synthetic seawater and river water. The power density can be largely upgraded to an ultrahigh ~17.1 W/m2 along with ~48.5 % conversion efficiency at a 50-fold KCl gradient. This work not only presents a new membrane design approach but also showcases the great potential of employing the zirconium-based MOF channels as ion-channel-mimetic membranes for highly efficient blue energy harvesting.

Spatially confined synthesis of large-sized MoS2 nanosheets in molten KSCN toward efficient hydrogen evolution

Low-temperature KSCN molten salt is a promising technique to synthesize defect-rich MoS2 catalysts for hydrogen evolution reaction (HER). However, owing to the fast ion diffusion rate for rapid crystal growth, the resultant catalysts show a morphology of microsphere, which aggregates from MoS2 nanosheets, to suppress the catalytic performance. In this work, large-sized few-layer MoS2 nanosheets are synthesized via a spatial confinement strategy by adding inert NaCl into the KSCN molten salt. With the NaCl spacer to physically block the long-distance ion diffusion and isolate the chemical reaction, the MoS2 nucleation and subsequent crystal growth could be controlled, guiding the nanosheets to grow along the narrow gap between the NaCl crystals to avoid aggregation. As a result, ultrathin MoS2 nanosheets with a large geometry size are constructed. Profiting from the architecture to expose active sites and boost charge transfer kinetics, the large-sized few-layer MoS2 nanosheets exhibit an impressive HER performance, showing a small η 10 of 160 mV and a low Tafel slope of 53 mV dec−1 with excellent stability. This work provides not only an efficient HER catalyst but also a facile spatial confinement technique to design and synthesize a large spectrum of transition metal sulfides for broad uses.

Morita equivalence of two $\ell^p$ Roe-type algebras

Given a metric space with bounded geometry, one may associate with it the \ell^{p} uniform Roe algebra and the \ell^{p} uniform algebra, both containing information about the large scale geometry of the metric space. We show that these two Banach algebras are Morita equivalent in the sense of Lafforgue for 1\leq p&lt;\infty . As a consequence, these two Banach algebras have the same K -theory. We then define an \ell^{p} uniform coarse assembly map taking values in the K -theory of the \ell^{p} uniform Roe algebra and show that it is not always surjective.

Volumetric Additive Manufacturing of SiOC by Xolography.

Additive manufacturing (AM) of ceramics has significantly contributed to advancements in ceramic fabrication, solving some of the difficulties of conventional ceramic processing and providing additional possibilities for the structure and function of components. However, defects induced by the layer-by-layer approach on which traditional AM techniques are based still constitute a challenge to address. This study presents the volumetric AM of a SiOC ceramic from a preceramic polymer using xolography, a linear volumetric AM process that allows to avoid the staircase effect typical of other vat photopolymerization techniques. Besides optimizing the trade-off between preceramic polymer content and transmittance, a pore generator is introduced to create transient channels for gas release before decomposition of the organic constituents and moieties, resulting in crack-free solid ceramic structures even at low ceramic yield. Formulation optimization alleviated sinking of printed parts during printing and prevented shape distortion. Complexsolid and porous ceramic structures with a smooth surface and sharp features are fabricated under the optimized parameters. This work provides a new method for the AM of ceramics at µm/mm scale with high surface quality and large geometry variety in an efficient way, opening the possibility for applications in fields such as micromechanical systems and microelectronic components.

Development of new improved plastic collapse moment equations of pressurized different angled pipe bends under bending moments

In a piping system, pipe bends are more flexible than straight pipes because of their curved geometry, supplemented by higher stress and strain concentration, leading to one of the crucial components in piping industries. Therefore, safe design of pipe bends is essential for smooth running of the piping system, and plastic collapse moment is one of its criteria. This paper utilizes three-dimensional finite element analyses to model empirical solutions for the plastic collapse moment for different angled pipe bends subjected to combined pressure and in-plane closing, in-plane opening, and out-of-plane bending moments. Plastic collapse moments for 30∘ to 180∘ pipe bends are determined for elastic perfectly plastic and strain hardening materials, employing large geometry change option and internal pressure effect. It is observed from results that pressure effect is more prominent in thinner pipe bends of larger bend angle under all bending cases. For in-plane opening and out-of-plane bending moments, collapse moment increases and then decreases with increase in pressure intensity for all sizes of pipe bend. However, for in-plane opening bending moment, collapse moments keep on decreasing for thicker ([Formula: see text] = 11.33) pipe bends. Finally, the study presents new improved plastic collapse moment solutions for different angled pipe bends under bending moment and internal pressure, derived from the finite element results of elastic perfectly plastic and strain hardening material models.

GPU-accelerated CFD-DEM modeling of gas-solid flow with complex geometry and an application to raceway dynamics in industry-scale blast furnaces

The coupling of Computational Fluid Dynamics (CFD) and Discrete Element Model (DEM) is a powerful tool for simulating dense particulate systems, yet the conventional CFD-DEM has limits for systems with large particle numbers and complex geometry. This paper reports a novel GPU-based CFD-DEM model to simulate the gas–solid flow with large particle numbers and complex geometry. A novel coupling strategy between the CFD solver and DEM solver is developed, featuring high efficiency and stability. The developed model is validated against the experimental measurements, and its efficiency is compared to the previous CFD-DEM simulations. Then, for demonstration, the model is employed to simulate the dynamic behavior of gas–solid flow in the raceway in ironmaking blast furnaces by considering complex tuyere structure details and the huge particle numbers involved. This model allows to study the effect of the tuyere angle in terms of raceway formulation and tuyere erosion. The results show that the largest and most stable raceway volume can be reached at 5° downward tuyere, although the −5° tuyere nose experiences more wear than 10° downward tuyere. The model provides a cost-effective tool to overcome the longstanding challenge of simulating dense fluid-particle systems with huge particle numbers and complex geometry.

Characterisation of the neutron field for streaming analyses in TT operations at JET

Assessing radiation fields in the biological shield penetrations of fusion reactors is a challenging task. At the Joint European Torus (JET) the neutron field at larger distances from the torus has been calculated and measured. JET operated in 2021–22 with a tritium-tritium plasma and neutronics experiments were performed for validating in a real fusion environment the neutronics codes and nuclear data applied in ITER nuclear analyses. In particular, the fluence of neutrons passing through the penetrations of the JET vacuum vessel and the torus hall was measured and compared with calculations in order to assess the capability of state-of-the-art numerical tools to correctly predict the radiation streaming in large and complex geometries. The neutron fluence was monitored at several locations inside the torus hall at larger distances from the tokamak with activation foils and thermo-luminescent detectors. The calculations have been performed in a two-step process using the deterministic code ADVANTG to determine the variance reduction parameters and with MCNP for subsequent calculation of the neutron field with the Monte Carlo method. The paper presents results of calculations and the first comparison to experimentally obtained values.

A GPU-accelerated computational fluid dynamics solver for assessing shear-driven indoor airflow and virus transmission by scale-resolved simulations

We explore the applicability of MATLAB for 3D computational fluid dynamics (CFD) of shear-driven indoor airflows. A new scale-resolving, large-eddy simulation (LES) solver titled DNSLABIB is proposed for MATLAB utilizing graphics processing units (GPUs). In DNSLABIB, the finite difference method is applied for the convection and diffusion terms while a Poisson equation solver based on the fast Fourier transform (FFT) is employed for the pressure. The immersed boundary method (IBM) for Cartesian grids is proposed to model solid walls and objects, doorways, and air ducts by binary masking of the solid/fluid domains. The solver is validated in two canonical reference cases and against experimental data. Then, we demonstrate the validity of DNSLABIB in a room geometry by comparing the results against another CFD software (OpenFOAM). Next, we demonstrate the solver performance in several isothermal indoor ventilation configurations and the implications of the results are discussed in the context of airborne transmission of COVID-19. The novel numerical findings using the new CFD solver are as follows. First, a linear scaling of DNSLABIB is demonstrated and a speed-up by a factor of 3-4 is also noted in comparison to similar OpenFOAM simulations. Second, ventilation in three different indoor geometries are studied at both low (0.1 m/s) and high (1 m/s) airflow rates corresponding to Re=5000 and Re=50000. An analysis of the indoor CO2 concentration is carried out as the room is emptied from stale, high CO2 content air. We estimate the air changes per hour (ACH) values for three different room geometries and show that the numerical estimates from 3D CFD simulations differ by 80%–150% (Re=50000) and 75%–140% (Re=5000) from the theoretical ACH value based on the perfect mixing assumption. Third, the analysis of the CO2 probability distributions (PDFs) indicates a relatively non-uniform distribution of fresh air indoors. Fourth, utilizing a time-dependent Wells-Riley analysis, an example is provided on the growth of the cumulative infection risk which is shown to reduce rapidly after the ventilation is started. The average infection risk is shown to reduce by a factor of 2 for lower ventilation rates (ACH=3.4-6.3) and 10 for the higher ventilation rates (ACH=37-64). Finally, we utilize the new solver to comment on respiratory particle transport indoors. A key contribution of the paper is to provide an efficient, GPU compatible CFD solver environment enabling scale-resolved simulations (LES/DNS) of airflow in large indoor geometries on a single GPU designed for high-performance computing. The demonstrated efficacy of MATLAB for GPU computing indicates a high potential of DNSLABIB for various future developments on airflow prediction.

End-to-end path planning for homogeneous temperature fields in additive manufacturing

This study explores a novel approach to path planning in deposition-based additive manufacturing, integrating the frequently overlooked process-induced temperature fields. Currently, existing approaches either ignore temperature effects entirely or only consider them in small-scale problems due to the high computational cost involved in predicting them and the combinatorial nature of path planning optimization. To address these challenges, the present work proposes an optimization pipeline that involves deriving a reduced order model from a finite volume method model with balanced truncation, using an analytical function to model the heat input and, calculating the steady-state response of the system to an arbitrary path using the Laplace transformation. Then, the optimization is transformed into a sequential decision-making problem and approximated with Monte Carlo tree search. The pipeline is validated through computational and experimental results, demonstrating its efficiency in managing large and complex geometries, as well as its resilience in overcoming the challenges posed by the simulation to reality gap.

Straight fiber bundles with non-uniform porosity: Shell-side hydrodynamics and mass transfer in cross flow

This study explores fully developed shell-side hydrodynamics and mass transfer past straight fiber bundles with non-uniform porosity in cross-flow. Simplified geometries made up by checkerboard arrays of alternately high and low porosity regions are considered. Simulations are performed for two domain sizes: a small geometry (26 fibers) and a large geometry (104 fibers). In the small geometry, the Darcy friction coefficient (fT) exhibits hydraulic isotropy at low transverse flow Reynolds numbers (ReT) but becomes dependent on the flow attack angle (θ) at higher ReT. In the large geometry, this dependency is observed at lower ReT. A non-uniform porosity reduces fT at almost all ReT and θ in the small geometry, with the large geometry exhibiting a more complex behavior. Regarding mass transfer, up to ReT≈1-10 (depending on θ), a non-uniform porosity leads to lower Sherwood numbers compared to regular square arrays. However, at higher ReT, it enhances mass transfer.

Oxygen Isotope and Fluorine Impurity Signatures during the Conversion of Uranium Ore Concentrates to Nuclear Fuel.

Within the front end of the nuclear fuel cycle, many processes impart forensic signatures. Oxygen-stable isotopes (δ18O values) of uranium-bearing materials have been theorized to provide the processing and geolocational signatures of interdicted materials. However, this signature has been minimally utilized due to a limited understanding of how oxygen isotopes are influenced during uranium processing. This study explores oxygen isotope exchange and fractionation between magnesium diuranate (MDU), ammonium diuranate (ADU), and uranyl fluoride (UO2F2) with steam (water vapor) during their reduction to UOx. The MDU was precipitated from two water sources, one enriched and one depleted in 18O. The UO2F2 was precipitated from a single water source and either directly reduced or converted to ADU prior to reduction. All MDU, ADU, and UO2F2 were reduced to UOx in a 10% hydrogen/90% nitrogen atmosphere that was dry or included steam. Powder X-ray diffraction (p-XRD) was used to verify the composition of materials after reduction as mixtures of primarily U3O8, U4O9, and UO2 with trace magnesium and fluorine phases in UOx from MDU and UO2F2, respectively. The bulk oxygen isotope composition of UOx from MDU was analyzed using fluorination to remove the lattice-bound oxygen, and then O2 was subsequently analyzed with isotope ratio mass spectrometry (IRMS). The oxygen isotope compositions of the ADU, UO2F2, and the resulting UOx were analyzed by large geometry secondary ion mass spectrometry (LG-SIMS). When reduced with steam, the MDU, ADU, and UO2F2 experienced significant oxygen isotope exchange, and the resulting δ18O values of UOx approached the values of the steam. When reduced without steam, the δ18O values of converted ADU, U3O8, and UOx products remained similar to those of the UO2F2 starting material. LG-SIMS isotope mapping of F impurity abundances and distributions showed that direct steam-assisted reduction from UO2F2 significantly removed F impurities while dry reduction from UO2F2 led to the formation of UOx that was enhanced in F impurities. In addition, when UO2F2 was processed via precipitation to ADU and calcination to U3O8, F impurities were largely removed, and reductions to UOx with and without steam each had low F impurities. Overall, these findings show promise for combining multiple signatures to predict the process history during the conversion of uranium ore concentrates to nuclear fuel.

Engineered Heterogenous Subnanochannel Membranes with a Tri‐Continuous Pore Structure of Large Geometry Gradient for Massively Enhanced Osmotic Power Conversion from Organic Solutions (Adv. Funct. Mater. 7/2024)

Engineered Heterogenous Subnanochannel Membranes with a Tri‐Continuous Pore Structure of Large Geometry Gradient for Massively Enhanced Osmotic Power Conversion from Organic Solutions (Adv. Funct. Mater. 7/2024)

Secondary Ion Mass Spectral Imaging of Metals and Alloys.

Secondary Ion Mass Spectrometry (SIMS) is an outstanding technique for Mass Spectral Imaging (MSI) due to its notable advantages, including high sensitivity, selectivity, and high dynamic range. As a result, SIMS has been employed across many domains of science. In this review, we provide an in-depth overview of the fundamental principles underlying SIMS, followed by an account of the recent development of SIMS instruments. The review encompasses various applications of specific SIMS instruments, notably static SIMS with time-of-flight SIMS (ToF-SIMS) as a widely used platform and dynamic SIMS with Nano SIMS and large geometry SIMS as successful instruments. We particularly focus on SIMS utility in microanalysis and imaging of metals and alloys as materials of interest. Additionally, we discuss the challenges in big SIMS data analysis and give examples of machine leaning (ML) and Artificial Intelligence (AI) for effective MSI data analysis. Finally, we recommend the outlook of SIMS development. It is anticipated that in situ and operando SIMS has the potential to significantly enhance the investigation of metals and alloys by enabling real-time examinations of material surfaces and interfaces during dynamic transformations.

Assessing and Improving the Accuracy of Visible Infrared Imaging Radiometer Suite Ocean Color Products in Environments with High Solar Zenith Angles

Utilizing in situ measurement data to assess satellite-derived long-term ocean color products under different observational conditions is crucial for ensuring data quality and integrity. In this study, we conducted an extensive evaluation and analysis of Visible Infrared Imaging Radiometer Suite (VIIRS) remote sensing reflectance (Rrs) products using long-term OC-CCI in situ data from 2012 to 2021. Our research findings indicate that, well beyond its designed operational lifespan, the root mean square difference accuracy of VIIRS Rrs products across most spectral bands remains superior to 0.002 (sr−1). However, VIIRS Rrs products in shorter wavelength bands (e.g., at 412 nm) have exhibited significantly lower accuracy and a long-term bias in recent years. The annual precision of VIIRS Rrs products demonstrated a declining trend, particularly in coastal or eutrophic waters. This degradation in accuracy highlights the imperative for continuous monitoring of VIIRS performance and further advancements in the atmospheric correction algorithm, especially to address satellite records at high solar zenith angles (SZAs) and observation zenith angles (OZAs). Our analysis indicates that, in observation environments with high SZAs (greater than 70°), the accuracy of VIIRS Rrs products has declined by nearly 50% compared to typical solar zenith angle observation conditions. To address the challenge of declining accuracy under large observation geometries, we introduced the neural network atmospheric correction model (NN-V). Developed based on meticulously curated VIIRS products, the NN-V model exhibits outstanding performance in handling VIIRS data in conditions of extensive observation geometries. During the winter season in high-latitude marine regions, the NN-V model demonstrates a remarkable enhancement in ocean color product coverage, achieving an increase of nearly 20 times compared to traditional methods.