Multiscale Numerical Model Research Articles

An energy-environment coupled simulation framework for multi-scale and multi-facet evaluation of data center

This paper focuses on analyzing the thermal environment and optimizing energy consumption in data centers, which has largely omitted from previous studies. The thermal environmental of data centers is simulated and analyzed by utilizing the established “server-rack-room” multi-scale heat transfer numerical model. Based on this, the coupling simulation model of thermal environment and energy consumption in data centers is proposed to explore the relationship between them, and the corresponding optimization strategy is put forward. The energy consumption simulated by energy-environment coupled model and non-coupled model can reach a discrepancy of over 30 %, which indicates that the thermal environment impacts the power consumption of the data center significantly. Besides, the effect of several operational parameters of air conditioning system on the thermal environment and energy consumption of data center is analyzed. Through the particle swarm optimization algorithm, the optimal system parameters, which meet the requirements of thermal environment and lead to the lowest energy consumption, are found for typical cities in different climatic regions. The recommended settings include the supply air temperature of about 24 ∼ 26 ℃, the air supply volume of 8 m3/s, and the temperature difference of about 3.5 ℃ between the supply air temperature and the supply chilled water temperature. Under the optimized parameter setting, the highest temperature of server decreases to below 71 ℃, and the energy saving rate is more than 6 %.

Evaluating the effectiveness of the modified multi-scale multi-physics coupled model for solid oxide fuel cells: A comparative analysis

A multi-scale multi-physics coupling numerical model serves as an effective tool to study the performance and improve the efficiency of solid oxide fuel cells (SOFCs) and provides the theory and data support for optimizing SOFC structure and operational strategy. To improve the accuracy and reliability of the model, this work established a modified simulation model that considers the effect of operational, structural, and physical parameters of SOFCs. First, the electrochemical kinetics equation, multi-component diffusion lattice Boltzmann (LB) model, and heat transfer LB model are modified by incorporating the reaction gas molar fraction, gas mixture concentration, temperature, and other parameters. Second, a regional hierarchical modeling strategy is proposed, and the multi-scale coupling model is modified by coupling mass and heat transfer. Third, considering the effect of carbon monoxide molar fraction, temperature difference, concentration change and porosity on electrochemical, mass, and heat transfer processes, the effectiveness of modification model is analyzed and validated. Results demonstrate that the modified model considerably improves the numerical simulation to handle the complex operational conditions of SOFCs. The modified model's predictions show better accuracy compared with experimental data, while maintaining consistency with the trends predicted by the original numerical models.

A review of multiscale numerical modeling of rock mechanics and rock engineering

AbstractRock is geometrically and mechanically multiscale in nature, and the traditional phenomenological laws at the macroscale cannot render a quantitative relationship between microscopic damage of rocks and overall rock structural degradation. This may lead to problems in the evaluation of rock structure stability and safe life. Multiscale numerical modeling is regarded as an effective way to gain insight into factors affecting rock properties from a cross‐scale view. This study compiles the history of theoretical developments and numerical techniques related to rock multiscale issues according to different modeling architectures, that is, the homogenization theory, the hierarchical approach, and the concurrent approach. For these approaches, their benefits, drawbacks, and application scope are underlined. Despite the considerable attempts that have been made, some key issues still result in multiple challenges. Therefore, this study points out the perspectives of rock multiscale issues so as to provide a research direction for the future. The review results show that, in addition to numerical techniques, for example, high‐performance computing, more attention should be paid to the development of an advanced constitutive model with consideration of fine geometrical descriptions of rock to facilitate solutions to multiscale problems in rock mechanics and rock engineering.

Stochastic Multiscale Modeling of Electrical Conductivity of Carbon Nanotube Polymer Nanocomposites: An Interpretable Machine Learning Approach

This study introduces an interpretable machine learning (ML) framework for efficiently predicting the electrical conductivity of carbon nanotube (CNT)/polymer nanocomposites. A stochastic multiscale numerical model based on representative volume element (RVE) is employed to generate a representative dataset. This dataset is used to train three ML models, including random forest, XGBoost, and artificial neural networks (ANN). The dataset includes six input features: CNT length, aspect ratio, intrinsic CNT conductivity, number of CNT conduction channels, energy barrier height, and volume fraction, with the electrical conductivity of the nanocomposites as the output feature. The findings highlight the exceptional accuracy of the ANN model in predicting electrical conductivity at significantly lower computational costs. Furthermore, the use of Shapley additive explanations (SHAP) enhances the interpretability of these ML models, identifying the volume fraction, energy barrier height, and intrinsic CNT conductivity as the most influential factors affecting conductivity. This approach sets the stage for rapid and efficient modeling of CNT/polymer nanocomposites facilitating the design of materials with tailored electrical properties for diverse applications.

Experimental and numerical investigation of flexural behavior of precast tunnel segments with hybrid reinforcement

Precast concrete segments reinforced with a combination of steel fibers and conventional rebar (RC-SFRC) have gained prominence in the mechanized construction of tunnels in recent years due to the advantages offered by this hybrid reinforcement solution in enhancing the mechanical behavior of these structural members. This research aims to understand better the flexural behavior of RC-SFRC tunnel segments proposed to replace conventional reinforcement in São Paulo Metro Line 5. An experimental program and numerical analyses using a multiscale model were conducted to predict the post-cracking parameters of SFRC through three-point bending tests according to EN14651 and assess the flexural behavior of full-scale tunnel segments. In both scenarios, 2D multiscale numerical models with discrete and explicit representations of the reinforcements were applied. The comparison of numerical and experimental results in terms of crack width, mean crack spacing, deflection, and the ultimate and service loads derived from design predictions demonstrate that the proposed RC-SFRC reinforcement represents an advantageous alternative, significantly enhancing the performance of the segments for both serviceability and ultimate limit states. Furthermore, the responses show that the adopted numerical strategy is promising and can be consolidated as a tool for optimizing the design process.

Numerical simulation of a laser beam welding process: From a thermomechanical model to the experimental inspection and validation

In laser beam welding (LBW) complex physical phenomena occur during laser-material interaction, which prolong the parameterisation of the process due to the extended trial and error tests. Therefore, predicting the process behaviour leads to a more productive and cost-reduced process experimental tuning. Besides, as LBW is a thermal process, part distortion plays a relevant role in the final result, and hence, thermal and mechanical analysis are both required. In view of this, in the present research, a novel multiscale numerical model, capable of predicting the thermomechanical behaviour of the LBW process has been developed. The significance of the model is its capability of forecasting the part distortion and thermal field employing two fully coupled modules, where the laser heat source automatically adapts to the welding regime without the need to consider the melt pool dynamics and at a low computational cost. The local model determines the melt pool dimensions and thermal field. Besides, the second module, the global model, figures out the part distortion based on the thermal results. Finally, the presented numerical simulations are experimentally validated with the corresponding temperature monitoring during the welding process, the posterior metallography inspection, and the part deformation measurement. The results present a high accuracy, with a maximum error below 10 % at the temperature measurements, an average dimensional deviation of 0.14 mm and 0.18 mm respectively for the weld bead depth and width, and a vertical deformation average error of 0.15 mm.

Evaluation of the influence of climatic changes on the degradation of the historic buildings

While climatic change has been a widely studied topic, its impact on cultural heritage degradation remains a gap to overcome. The environment can contribute to the degradation of historic buildings and materials decay, especially temperature and humidity. So, characterizing the micro-climates of a landmark zone and understanding the influence of the recovery layers, building disposition, and street characteristics on environmental parameters are the first steps to investigating resilience strategies for heritage conservation and micro-climates. Thus, this paper presents a new approach to assess the influence of climatic warming on historic building degradation, combining multiscale experimental data and numerical modeling. The environmental parameters of the historic center of Aracati downtown, such as concentration of CO2, relative humidity, temperature, and air condition, were characterized and used together with urban volumetry to discuss the influence of on the urban microclimate and relate the data to the physical degradation of cultural heritage. An uncrewed aerial vehicle was used to register the volumetry of the historic center, and the data was used to simulate the wind conditions. Following this, numerical analysis was used to investigate the rising damp and thermal tension distributions under temperature variation over the years (from 2023 to 2100). The methodology’s applicability was demonstrated in recurrence with the Nosso Senhor do Bonfim Church, one of the most representative heritage constructions from Aracati downtown. Finally, the new methodology contributed to understanding how urban volumetry contributes to the climatic conditions of a historic area and demonstrates that the increase of the temperature can significantly affect the rising damps and the development of stress tension.

Multi-field and multi-scale dynamic numerical modeling of supercritical CO2 and fly ash mineralization

Fly ash-CO2 mineralization technology can effectively control gas–solid waste emissions and improve the climate environment. However, rationally describing the evolution mechanism of the fly ash-supercritical CO2 mineralization reaction and accurately predicting the efficiency of the mineralization reaction are of great significance for improving and evaluating the supercritical CO2 mineralization sequestration capacity. Fly ash micro- and nanopore multi-scale effects are the key to influencing the supercritical CO2 seepage-mineralization reaction mechanism. None of the current theoretical models consider the pore multi-scale effects, thus the validity and accuracy of predicting and describing the evolutionary mechanism of supercritical CO2 mineralization rates and efficiencies are questionable. To address this scientific issue, a multi-scale continuous pore structure theoretical model was established based on the structural characteristics of fly ash micro- and nanopores. Additionally, a new model of supercritical CO2 multi-field and multi-scale dynamic mineralization theory was developed by considering parameters such as temperature, pressure, and humidity. The accuracy of the model was verified through the mineralization experiments. The new model effectively describes the dynamic evolution mechanism of supercritical CO2 mineralized fly ash. The effects of parameters such as temperature, pressure, water vapor diffusion coefficient, supercritical CO2 permeability, and pore multi-scale effect on the efficiency and mineralization rate were investigated through numerical simulation. The results showed the following: The mineralization efficiency exhibited a parabolic increase with temperature, with 72℃ being the turning point for the growth rate of mineralization efficiency, and 82℃ being the optimal effective temperature to promote the mineralization efficiency of supercritical CO2. A 3.5-fold increase in supercritical CO2 pressure changes the mineralization efficiency by a maximum of only 0.0493 %. Increasing the water vapor diffusion coefficient by 5 orders of magnitude changes the mineralization efficiency by only 8.3 %. The pore attenuation coefficient increases by 3 orders of magnitude, and the supercritical CO2 mineralization efficiency changes by a factor of 2.27. A model that does not account for pore multi-scale effects overestimates the fly ash- supercritical CO2 mineralization efficiency by a factor of 2.47 at a permeability of 3 × 10-10 m2. Therefore, neglecting the pore continuum multi-scale effect can lead to a serious overestimation of the mineralization efficiency of supercritical CO2.

Multi-scale modeling of fog harvesting using thin-fiber grids – Towards new design rubrics

Fog collectors with fibers thinner than 1 mm harvest fog droplets more effectively at a low airflow velocity around 1 m s-1 than thicker fibers. However, existing models and design rubrics are restricted to thick fibers at higher velocity. This paper reports a multi-scale numerical model for fog harvesting at airflow velocity of 1 m s-1 using thin-fiber grids with different fiber spacing and diameter. The numerical model can simulate fog harvesting at two extreme length scales that are comparable to collector scale at the large end and fiber scale at the small end. The results confirm two new and important effects of fiber grid geometries on water collection efficiency, which are not included in existing theories and design rubrics. First, dense thin-fiber grids negatively influence the collection efficiency because of wall effect caused by viscous boundary layers. Second, the sparse thin-fiber grids can benefit from isolated clogging waterdrops and maintain relatively high efficiency when clogging blocks multiple grid openings. The two identified effects are then included to develop a new performance map for fog collectors, thereby shaping new design rubrics for fog harvesting. This work extends the existing theories of fog harvesting and sheds light on the design of novel fog collectors.

Multiscale numerical modeling of clay brick masonry under compressive loading

Multiscale numerical modeling of clay brick masonry under compressive loading

Multi-scale investigation of heat and momentum transfer in packed-bed TES systems up to 800 K

With the rising cost of energy and the advancement of corporate social responsibility, there is a growing interest in addressing the challenge of recovering and storing high-temperature waste heat. Sensible heat storage in packed beds stands out as a cost-effective and seemingly straightforward solution for high-temperature Thermal Energy Storage (TES). Engineering models developed to design low-temperature TES systems were tentatively used to design this new generation of high-temperature systems. Delving into the physics of coupled heat and mass transfer reveals a lack of validation of this approach. This study seeks to establish a comprehensive bottom-up methodology - from the particle scale up to the system level - to provide informed and validated engineering models for the design of high-temperature TES systems. To achieve this goal, we developed a multi-scale numerical model to explore the physics of heat and momentum transfer in packed-bed TES systems. At the microscopic scale (pore/particle), we consider the flow of a compressible high-temperature gas between the particles, coupled to transient heat conduction within the particles, with particular attention given to incorporating accurate temperature-dependent viscosity for the gas phase and thermal conductivity and density for both solid and gas phases. At the macroscopic scale (engineering), we propose a high-temperature extension of state-of-the-art two-equation TES models. The governing equations considered are the volume-average conservation laws for gas-mass, gas-momentum and energy of both phases. The multi-scale strategy is applied to a randomly packed bed of spherical particles generated with the discrete element method (DEM) software LIGGGHTS. Numerical models for both scales were implemented in the Porous material Analysis Toolbox based on OpenFoam (PATO), which is made available in Open Source by NASA. Microscopic scale simulations were used to infer the effective parameters needed to inform the macroscopic model, namely, permeability, Forchheimer coefficient, effective thermal conductivities, and the heat transfer coefficient. The informed macroscopic model reproduces with excellent accuracy the average temperature fields of the physics-based microscopic model. Pore-scale analysis shows highly three-dimensional flow characterized by reverse flow and strong cross-flow in the packed bed system. Moreover, it indicates the coupling between temperature and velocity fields, where a nonuniform velocity field results in uneven temperature distributions across the fluid and the solid spheres within the packed bed, subsequently affecting the macroscopic heat transfer coefficient. The overall strategy is validated by comparison to available experimental data. This bottom-up methodology contributes to the understanding and opens new perspectives for a more precise design and monitoring of high-temperature TES systems.

A multiscale fracture model using peridynamic enrichment of finite elements within an adaptive partition of unity: Experimental validation

Partition of unity methods (PUM) are of domain decomposition type and provide the opportunity for multiscale and multiphysics numerical modeling. Here, we apply Peridynamic (PD) enrichment to propagate cracks in the PUM global–local enrichment scheme. We apply linear elasticity globally and PD over local zones where fractures occur. The elastic fields provide appropriate boundary data for local PD simulations on a subdomain containing the crack tip to grow the crack. Once the updated crack path is found the elastic field in the body and surrounding the crack is updated using the PUM basis with an elastic field enrichment near the crack. The subdomain for the PD simulation is chosen to include the current crack tip as well as features that influence crack growth. This paper is part II of this series and validates the combined PD/PUM simulator against the experimental results. The results of numerical simulation show that we attain good agreement between experiment and simulation with a local PD subdomain that is moving with the crack tip and adaptively chosen size.

Cross-scale modeling of microencapsulated self-healing composite with multiphase medium and their damage competition behavior

Constructing a high-fidelity cross-scale numerical model is the primary challenge in the multiscale analysis of multiphase medium composites.The Discrete Element Method is used in this study to build a three-medium multiscale numerical model. Further, the dynamic damage problem of microcapsules and the damage competition issues are investigated. The results indicate that (1) The damage evolution process, the location of maximum damage, and the final damage pattern of microcapsule embedded in the matrix and exposed to the ideal environment differed considerably. (2) The effect of microcapsule volume fraction on the mechanical strength of the matrix in self-healing composites is not linearly negatively correlated, but instead, there is a non-linear relationship, which is highly dependent on the strength ratio of the microcapsule to the matrix. (3) In self-healing composites, damage competition between the microcapsules and the matrix has a decisive influence on triggering the self-healing mechanism. (4) To obtain a better self-healing effect, the microcapsule volume fraction should not exceed 1.5 %, and the mechanical strength pre-maintenance should not be more than 95 % of the failure strength. The multiphase medium & multiscale analysis method proposed in this study also provides a new approach for visualizing the progressive dynamic damage problem in self-healing composites.

Thermomechanical performance analysis of MicroPCM-enhanced energy pile concrete: A multiscale numerical study and formulation design implications

Energy pile is a form of pile foundation that combines load-bearing and heat exchange, marking a pivotal avenue for harnessing geothermal energy. Recent strides in research have highlighted the incorporation of microencapsulated phase change materials (MicroPCM) into energy piles due to their potential to amplify heat transfer efficiency. The thermomechanical behavior of phase change energy piles, however, becomes intricate owing to the dual impact of thermal and mechanical loads. Thus, a holistic multiscale analysis remains indispensable to grasp the repercussions of varied MicroPCM concentrations on the thermomechanical attributes of phase change concrete and the dominant mechanisms driving their thermo-mechanical performance. In the study, we propose an innovative multiscale numerical model to investigate the thermomechanical performance of MicroPCM-enhanced energy pile concrete, taking into account the randomly distributed MicroPCM particles and aggregate. The sensitivity analysis pinpointing the intrinsic determinants of phase change concrete was conducted to discern the pivotal contributors to its thermomechanical response. Core insights revealed that while MicroPCM addition might compromise the mechanical strength of concrete owing to its inherently weaker properties, it unquestionably bolsters the thermal characteristics of phase change concrete. The thermal conductivity of phase change concrete stands in inverse relation to its porosity and direct correspondence with its saturation level. Correlation evaluations ascertained that the thermal prowess of phase change concrete is predominantly swayed by saturation, followed by porosity, and lastly, MicroPCM content. This inquiry endeavors to elevate the heat transfer efficacy of energy piles by finetuning the formulation design of phase change concrete materials, shedding light on underlying mechanisms, and laying a robust foundation for the forthcoming adoption of MicroPCM energy piles.

Towards an efficient multi-scale numerical model of the impact behavior of woven materials with global/local approach

This paper presents the global/local approach in the multi-scale modeling of woven material impact behavior. This approach optimally considers important microscopic mechanisms to accurately predict outcomes and reduce computational time. The inspiration for this approach stems from the specific behavior exhibited by woven materials under ballistic impact:(1) Zone 1 (Local) is a small square around the impact position, requiring comprehensive microscopic modeling to describe complex physical phenomena accurately.(2) Zone 2 (Global) represents the remaining fabric outside of Zone 1, exhibiting more global behavior and modeled with a mesoscopic model.Building upon a previous work's joining technique, an interface between these two zones is implemented and validated through numerical tensile testing. The proposed approach is then compared to the complete mesoscopic model already validated in the case of a 2D Kevlar KM2 woven fabric submitted to ballistic impact. The global/local approach demonstrates slightly greater flexibility due to the presence of microscopic yarns. It successfully predicts all microscopic phenomena while significantly reducing the degrees of freedom compared to full microscopic modeling along the entire yarn length.

Multiscale numerical modeling of large-format additive manufacturing processes using carbon fiber reinforced polymer for digital twin applications

Large Format Additive Manufacturing (LFAM) has gained prominence in the aerospace and automotive industries, where topology optimization has become crucial. LFAM facilitates the layer-by-layer production of sizeable industrial components in carbon fiber (CF) reinforced polymers, however 3D printing at large scales results in warpage generation. Printed components are deformed as residual stresses generated due to thermal gradients between adjacent layers. This paper tackles the problem at two different scales: the micro and macroscale. Initially, the microstructure characterization of the thermoplastic ABS matrix composite material enriched with 20% short CF is used in the development of numerical models to understand the mechanical behavior of the studied material. Numerical modeling is performed simultaneously by means of Mean-Field (MF) homogenization methods and Finite Element Analysis (FEA). Outcomes validated with corrected experimental mechanical testing results show a discrepancy in the elastic modulus of 7.8% with respect to FE multi-layer analysis. Micro-level results are coupled with the a macroscopic approach to reproduce the LFAM process, demonstrating the feasibility of the tool in the development of a Digital Twin (DT).

Numerical simulation analysis of forming of continuous fiber reinforced polypropylene composites: Relaxation, creep, and hot stamping

In this study, the viscoelastic constitutive equation of continuous glass fiber reinforced polypropylene composites based on the generalized Maxwell model and SCFM model was constructed by combining genetic algorithm. Based on this, a multi-scale numerical model for describing material relaxation and creep is proposed, and the accuracy of different scale models was compared through experiments. The forming state of the workpiece under various stamping speeds and preheating temperatures was also examined using a hot stamping numerical model. The independent design of the hot stamping hemispherical mold was used to confirm the hot stamping model's accuracy. The study's findings demonstrate that the macroscopic model can accurately simulate the relaxation and creep of composite materials. The hot stamping simulation results are match up well with experimental results. Composite molding defects appeared at the waist of the part, and defects were accompanied by resin loss.

Multiscale computational fluid dynamics modelling of spatial ALD on porous li-ion battery electrodes

The self-limiting surface reaction characteristic of atomic layer deposition (ALD) makes it ideal for the surface modification of electrode materials for lithium-ion batteries (LIBs). Spatial ALD shows promise as a scalable method for the coating on pre-fabricated electrode sheets. As a strong-coupled multiscale process, various process conditions and microstructure parameters have great influences on the macroscale fluid dynamics and the pore-scale diffusion–reaction process, thus affecting the coating efficiency. This study presents a multiscale numerical model that combines computational fluid dynamics (CFD) with multilevel pore-scale diffusion–reaction kinetics to explore the spatial ALD process on porous LIB electrodes. The dynamic mesh method is utilized to simulate electrode movement. The considerable active surface-to-volume ratio of the porous structure limits the precursor infiltration depth due to the low diffusion rate and inadequate precursor supply. As the electrode velocity increases, an asymmetric distribution of precursor concentration under the injector is observed with a rapid decrease. Elevating both the precursor concentration and inlet gas velocity augments the coating depth by enhancing the supply of the precursor. The experimental data aligns well with our numerical results, verifying the accuracy of the multiscale CFD model. Our observations reveal that a relatively lower operating pressure, around 0.1 atm, compared to 0.01 atm and 1 atm, optimizes the deposition rate along the electrode depth during the half-ALD cycle, especially when the pore size is larger. Electrode porosity of about 0.4 notably improves coating uniformity by elevating the precursor diffusion rate. Predictions show that with a substrate velocity of 0.2 m/s, the coating depth on an electrode having higher porosity at the top compared to the bottom via atmospheric spatial ALD could reach a depth of 38 μm with a precursor utilization of 78 %.

Assessing turbulence and mixing parameterizations in the gray-zone of multiscale simulations over mountainous terrain during the METEX21 field experiment

Multiscale numerical weather prediction models transition from mesoscale, where turbulence is fully parameterized, to microscale, where the majority of highly energetic scales of turbulence are resolved. The turbulence gray-zone is situated between these two regimes and multiscale models must downscale through these resolutions. Here, we compare three multiscale simulations which vary by the parameterization used for turbulence and mixing within the gray-zone. The three parameterizations analyzed are the Mellor-Yamada Nakanishi and Niino (MYNN) Level 2.5 planetary boundary layer scheme, the TKE-1.5 large eddy simulation (LES) closure scheme, and a recently developed three-dimensional planetary boundary layer scheme based on the Mellor-Yamada model. The simulation domain includes complex (i.e., mountainous) terrain in Nevada that was instrumented with meteorological towers, profiling and scanning lidars, a tethered balloon, and a surface flux tower. Simulations are compared to each other and to observations, with assessment of model skill at predicting wind speed, wind direction and TKE, and qualitative evaluations of transport and dispersion of smoke from controlled releases. This analysis demonstrates that microscale predictions of transport and dispersion can be significantly influenced by the choice of turbulence and mixing parameterization in the terra incognita, particularly over regions of complex terrain and with strong local forcing. This influence may not be apparent in the analysis of model skill, and motivates future field campaigns involving controlled tracer releases and corresponding modeling studies of the turbulence gray-zone.

Multiscale numerical modeling of a complete spray evolution including breakup of liquid jet injection in gaseous cross flow

A direct coupling of the Volume of Fluid method (VOF) and the Lagrangian Particle Tracking (LPT) technique within a Large Eddy Simulation (LES) framework is revisited and assessed by numerically investigating a liquid jet injection into a cross-flowing air (JICF). To close the subgrid scale (SGS) terms appropriate SGS models are considered. In particular, an interfacial SGS term is included into the VOF scalar transport equation in order to achieve a suitable LES and to describe properly the liquid column and the break-up processes (primary and secondary). The dilute spray region including the droplets resulting from the secondary breakup is solved using the LPT approach. Since the latter allows the cell size to be multiple times larger than the droplet diameter, this reduces the computational expenses significantly making it possible to handle the simulation of the whole spray evolution including the complete liquid atomization without complex tunable atomization models. For this purpose, two operating conditions of a JICF existing in the literature are considered. The achieved results are first presented in terms of mesh sensitivity, required computational costs and impact of the interfacial SGS term. Next, comparisons between pure VOF/LES and VOF/LPT/LES for both qualitative features and quantitative properties are provided and discussed. In overall, a good agreement with experiments for the quantitative properties is reported. It is especially found that both the Rosin–Rammler and Gaussian distributions offer nearly a more accurate fit to the particle size distribution except for the range from 0 to 10 μm. Together with the detailed characteristics of vortices evolving and an extended breakup regime map, the spray characteristics including the spray structure are well captured. Finally, even though the interfacial SGS term has an evident influence on the jet and atomization dynamics, its impact on quantitative properties is not so prominent under these operating conditions.