cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.28965204
title: Numerical study of Leidenfrost effect suppression on structured thermal pillars using a lattice Boltzmann method

description: A three-dimensional pseudopotential central moments lattice Boltzmann method, coupled with a fourth-order Runge–Kutta scheme for the temperature field, is employed to study the impact of Leidenfrost droplets on overheated structured thermal pillar surfaces. The numerical method is validated through simulations of liquid–vapour phase-change processes and dynamic impingement of Leidenfrost droplet on overheated walls. A parametric study varying surface temperature, droplet inertia, and pillar dimensions provides insights into droplet dynamics and Leidenfrost point (LFP). Results demonstrate that structured thermal pillars significantly elevate the LFP compared to flat surfaces by enhancing vapour flow beneath the droplet. Detailed analyses reveal that increasing surface temperature promotes the Leidenfrost phenomenon, while droplet inertia affects the rebound height but not LFP, resulting in a lower average vaporisation rate when Leidenfrost effect happens. Furthermore, the influence of pillar dimensions on the LFP is explored by establishing phase diagrams of the Jacob number (<i>Ja</i>) against pillar width, height, and spatial distribution. The results indicate that narrower and taller pillars are more advantageous in suppressing the Leidenfrost effect. When the pillar height exceeds 40% of the droplet radius, the suppression effect diminishes. Moreover, increasing the number of pillars, resulting in smaller tunnel and pillar widths, tends to enhance the Leidenfrost effect.
DOI: 10.6084/m9.figshare.28965204.v1
title: Numerical study of Leidenfrost effect suppression on structured thermal pillars using a lattice Boltzmann method

description: A three-dimensional pseudopotential central moments lattice Boltzmann method, coupled with a fourth-order Runge–Kutta scheme for the temperature field, is employed to study the impact of Leidenfrost droplets on overheated structured thermal pillar surfaces. The numerical method is validated through simulations of liquid–vapour phase-change processes and dynamic impingement of Leidenfrost droplet on overheated walls. A parametric study varying surface temperature, droplet inertia, and pillar dimensions provides insights into droplet dynamics and Leidenfrost point (LFP). Results demonstrate that structured thermal pillars significantly elevate the LFP compared to flat surfaces by enhancing vapour flow beneath the droplet. Detailed analyses reveal that increasing surface temperature promotes the Leidenfrost phenomenon, while droplet inertia affects the rebound height but not LFP, resulting in a lower average vaporisation rate when Leidenfrost effect happens. Furthermore, the influence of pillar dimensions on the LFP is explored by establishing phase diagrams of the Jacob number (<i>Ja</i>) against pillar width, height, and spatial distribution. The results indicate that narrower and taller pillars are more advantageous in suppressing the Leidenfrost effect. When the pillar height exceeds 40% of the droplet radius, the suppression effect diminishes. Moreover, increasing the number of pillars, resulting in smaller tunnel and pillar widths, tends to enhance the Leidenfrost effect.
DOI: 10.6084/m9.figshare.29513543
title: Frequent estuarine engineering exacerbates flood risk in the Greater Bay Area

description: Global mega-bay systems are experiencing intensive estuarine engineering (e.g. dredging and reclamation), yet the compound effects and underlying mechanisms driving flood risk amplification remain insufficiently quantified. This study investigates flood risk changes in the Bay-Inlet-Channel system of China’s Greater Bay Area (ranked as the world's fourth largest mega-bay) through extreme value analysis of 1965–2017 water level records using generalized extreme value (GEV) theory and max-stable process modelling. Our results demonstrate spatially heterogeneity in flood risk trends, with differential extreme water level rise changes: 0.22 cm/yr at the bay mouth, 0.65 cm/yr in the inner bay, and 0.56 cm/yr in the upper tidal reach (Shiziyang), coinciding with a risk escalation from Category II (strong) to Category I (extreme). Hydrodynamic analysis reveals that deposition-induced tidal range attenuation at the bay mouth partially moderates flood risk acceleration, whereas synergistic effects of erosional dredging and convergent reclamation amplify both tidal and surge dynamics, consequently exacerbating flood risk in the inner bay, with the tidal reach exhibiting intermediate trends due to energy dissipation through Humen Inlet. Numerical simulations quantify maximum impacts on extreme high water levels, with 9.61% rising associated with slower-propagating waves from reclamation and 3.33% decreased with faster-propagating waves induced by dredging. Projections under SSP5-8.5 sea-level rise scenarios indicate that extreme high water levels will surpass optimized 300-yr return levels defense standards by 2080 (outer bay), 2090 (inner bay), and 2100 (tidal reach). These findings provide critical insights into global flood risk management in engineered mega-bay systems and advance methodological frameworks for extreme water level assessment.
DOI: 10.6084/m9.figshare.29513543.v1
title: Frequent estuarine engineering exacerbates flood risk in the Greater Bay Area

description: Global mega-bay systems are experiencing intensive estuarine engineering (e.g. dredging and reclamation), yet the compound effects and underlying mechanisms driving flood risk amplification remain insufficiently quantified. This study investigates flood risk changes in the Bay-Inlet-Channel system of China’s Greater Bay Area (ranked as the world's fourth largest mega-bay) through extreme value analysis of 1965–2017 water level records using generalized extreme value (GEV) theory and max-stable process modelling. Our results demonstrate spatially heterogeneity in flood risk trends, with differential extreme water level rise changes: 0.22 cm/yr at the bay mouth, 0.65 cm/yr in the inner bay, and 0.56 cm/yr in the upper tidal reach (Shiziyang), coinciding with a risk escalation from Category II (strong) to Category I (extreme). Hydrodynamic analysis reveals that deposition-induced tidal range attenuation at the bay mouth partially moderates flood risk acceleration, whereas synergistic effects of erosional dredging and convergent reclamation amplify both tidal and surge dynamics, consequently exacerbating flood risk in the inner bay, with the tidal reach exhibiting intermediate trends due to energy dissipation through Humen Inlet. Numerical simulations quantify maximum impacts on extreme high water levels, with 9.61% rising associated with slower-propagating waves from reclamation and 3.33% decreased with faster-propagating waves induced by dredging. Projections under SSP5-8.5 sea-level rise scenarios indicate that extreme high water levels will surpass optimized 300-yr return levels defense standards by 2080 (outer bay), 2090 (inner bay), and 2100 (tidal reach). These findings provide critical insights into global flood risk management in engineered mega-bay systems and advance methodological frameworks for extreme water level assessment.
DOI: 10.6084/m9.figshare.30092152
title: Coupled dynamic characteristics of the hull and cushioning structure of high-speed water entry vehicle

description: To mitigate the extreme mechanical challenges posed by peak and intense instantaneous impacts during high-speed water entry, this paper proposes a rigid polyurethane foam (RPUF) filled cushioning structure to absorb impact energy and minimize hull deformation. The mechanical properties and constitutive parameters of RPUF are characterised by dynamic and static compression tests. The coupled Euler–Lagrange method was used to perform numerical simulations of the water entry process for vehicles equipped with cushioning structure. The load mitigation efficiency of the cushioning structure, as well as its deformation and failure modes, were comprehensively examined. Additionally, based on the response surface methodology, an analysis was conducted to evaluate the influencing factors contributing to the deformation of the vehicle's hull structure. The research results show that the load reduction efficiency can reach a minimum of 50% under various conditions, with a maximum load reduction efficiency of 80.1% and a maximum structural deformation reduction of up to 57.1% being achieved under certain conditions. It is also observed that the density of the RPUF material has a significant effect on the load reduction efficiency, while the strain rate effect has a relatively small effect. As the Froude number increases, the load reduction efficiency of the cushioning structure decreases and the deformation of the vehicle hull increases.
DOI: 10.6084/m9.figshare.30092152.v1
title: Coupled dynamic characteristics of the hull and cushioning structure of high-speed water entry vehicle

description: To mitigate the extreme mechanical challenges posed by peak and intense instantaneous impacts during high-speed water entry, this paper proposes a rigid polyurethane foam (RPUF) filled cushioning structure to absorb impact energy and minimize hull deformation. The mechanical properties and constitutive parameters of RPUF are characterised by dynamic and static compression tests. The coupled Euler–Lagrange method was used to perform numerical simulations of the water entry process for vehicles equipped with cushioning structure. The load mitigation efficiency of the cushioning structure, as well as its deformation and failure modes, were comprehensively examined. Additionally, based on the response surface methodology, an analysis was conducted to evaluate the influencing factors contributing to the deformation of the vehicle's hull structure. The research results show that the load reduction efficiency can reach a minimum of 50% under various conditions, with a maximum load reduction efficiency of 80.1% and a maximum structural deformation reduction of up to 57.1% being achieved under certain conditions. It is also observed that the density of the RPUF material has a significant effect on the load reduction efficiency, while the strain rate effect has a relatively small effect. As the Froude number increases, the load reduction efficiency of the cushioning structure decreases and the deformation of the vehicle hull increases.
DOI: 10.6084/m9.figshare.30580471
title: The role of narrow fringing reefs in tsunami mitigation: a numerical modelling study along the Sanya coastline

description: This study assesses the tsunami mitigation capacity of narrow fringing reefs (50–200 m width) under varying ecological health states using a high-resolution implementation of the COMCOT model. Satellite-derived reef bathymetry (20 m resolution) and non-uniform bottom friction coefficients were incorporated to simulate tsunami propagation from four ∼Mw 9 earthquake scenarios along the Manila Subduction zone. The results indicate that healthy reefs can reduce the maximum on-platform current velocities by nearly 80% and delay wave arrival by 5–10 min – providing a critical window for early evacuation. While these narrow coral reefs exert limited influence on initial tsunami wave crests, they significantly attenuate subsequent waves, with up to 50% reduction in wave heights when the peak arrives after the first crest. These findings highlight the disproportionate protective value of healthy narrow fringing reefs, framing them as essential natural infrastructure for tsunami risk reduction. This study offers quantitative thresholds for targeted reef conservation and supports the integration of ecological parameters into computational tsunami hazard modelling frameworks.
DOI: 10.6084/m9.figshare.30580471.v1
title: The role of narrow fringing reefs in tsunami mitigation: a numerical modelling study along the Sanya coastline

description: This study assesses the tsunami mitigation capacity of narrow fringing reefs (50–200 m width) under varying ecological health states using a high-resolution implementation of the COMCOT model. Satellite-derived reef bathymetry (20 m resolution) and non-uniform bottom friction coefficients were incorporated to simulate tsunami propagation from four ∼Mw 9 earthquake scenarios along the Manila Subduction zone. The results indicate that healthy reefs can reduce the maximum on-platform current velocities by nearly 80% and delay wave arrival by 5–10 min – providing a critical window for early evacuation. While these narrow coral reefs exert limited influence on initial tsunami wave crests, they significantly attenuate subsequent waves, with up to 50% reduction in wave heights when the peak arrives after the first crest. These findings highlight the disproportionate protective value of healthy narrow fringing reefs, framing them as essential natural infrastructure for tsunami risk reduction. This study offers quantitative thresholds for targeted reef conservation and supports the integration of ecological parameters into computational tsunami hazard modelling frameworks.
DOI: 10.6084/m9.figshare.30692040
title: Hydraulic optimization of a stormwater pumping station by physical and computational fluid dynamics modeling

description: Hydraulic optimization can enhance the reliability, efficiency, and sustainability of stormwater pumping stations. This study was intended to thoroughly assess the hydraulic performance of a specific stormwater pumping station and to propose improved options for regularizing the flow and minimizing sediment deposition. A 1:5 scale physical model was built and three-dimensional computational fluid dynamics (CFD) models were developed and validated. Response surface methodology (RSM) was employed and integrated with CFD for optimizing the parameters of design modifications, including deflector plates and diversion piers. For the existing configuration, the collecting chamber exhibits a large recirculation zone driven by the oblique approach flow and is prone to sedimentation because bottom shear is insufficient. A properly designed deflector plate can reduce the potential area for sediment deposition by nearly 90%. Flow patterns in the pump sump are primarily governed by the operating scheme and the modeling results demonstrate that significant recirculation and vortices are present. The strategic installation of an additional deflector plate alongside two diversion piers significantly mitigates recirculation and sedimentation risk, with their optimized dimensions and spatial configuration determined through parametric analysis. The CFD framework was coupled with a discrete phase model (DPM) to simulate sediment transport and quantify the self-cleaning benefits of the modifications. Simulations confirm that the optimized configuration increases particle export efficiency across all scenarios, particularly for coarser or denser particles under low-flow conditions, which are traditionally the most problematic for sediment accumulation.
DOI: 10.6084/m9.figshare.30692040.v1
title: Hydraulic optimization of a stormwater pumping station by physical and computational fluid dynamics modeling

description: Hydraulic optimization can enhance the reliability, efficiency, and sustainability of stormwater pumping stations. This study was intended to thoroughly assess the hydraulic performance of a specific stormwater pumping station and to propose improved options for regularizing the flow and minimizing sediment deposition. A 1:5 scale physical model was built and three-dimensional computational fluid dynamics (CFD) models were developed and validated. Response surface methodology (RSM) was employed and integrated with CFD for optimizing the parameters of design modifications, including deflector plates and diversion piers. For the existing configuration, the collecting chamber exhibits a large recirculation zone driven by the oblique approach flow and is prone to sedimentation because bottom shear is insufficient. A properly designed deflector plate can reduce the potential area for sediment deposition by nearly 90%. Flow patterns in the pump sump are primarily governed by the operating scheme and the modeling results demonstrate that significant recirculation and vortices are present. The strategic installation of an additional deflector plate alongside two diversion piers significantly mitigates recirculation and sedimentation risk, with their optimized dimensions and spatial configuration determined through parametric analysis. The CFD framework was coupled with a discrete phase model (DPM) to simulate sediment transport and quantify the self-cleaning benefits of the modifications. Simulations confirm that the optimized configuration increases particle export efficiency across all scenarios, particularly for coarser or denser particles under low-flow conditions, which are traditionally the most problematic for sediment accumulation.
DOI: 10.6084/m9.figshare.30580372
title: Embedded LES modelling of atmospheric boundary layer in urban region using accelerated turbulence generation

description: A novel development of Embedded Large Eddy Simulation (ELES) model was proposed for urban wind field simulations, incorporating the synthetic volume force method integrated with the Graphic Processing Unit (GPU) parallel computing. By combining the advantages of RANS and LES, the proposed model enhances both computational efficiency and accuracy in comparison to conventional LES models. A validation simulation for the atmospheric boundary layer wind field was conducted to assess the accuracy of the proposed method. Subsequently, an ideal urban block was used to evaluate the influence of LES region sizes and the positioning of the RANS (Reynolds-Averaged Navier-Stokes)/LES interface on the simulation results. It was found that the positioning of the RANS/LES interface in the ELES model appears to have little effects on the mean wind field, while it does affect the fluctuating wind speed results. Comparative analysis with wind tunnel experiments and conventional large eddy simulation confirmed the efficacy of the proposed ELES with accelerated turbulence generation.
DOI: 10.6084/m9.figshare.30580372.v1
title: Embedded LES modelling of atmospheric boundary layer in urban region using accelerated turbulence generation

description: A novel development of Embedded Large Eddy Simulation (ELES) model was proposed for urban wind field simulations, incorporating the synthetic volume force method integrated with the Graphic Processing Unit (GPU) parallel computing. By combining the advantages of RANS and LES, the proposed model enhances both computational efficiency and accuracy in comparison to conventional LES models. A validation simulation for the atmospheric boundary layer wind field was conducted to assess the accuracy of the proposed method. Subsequently, an ideal urban block was used to evaluate the influence of LES region sizes and the positioning of the RANS (Reynolds-Averaged Navier-Stokes)/LES interface on the simulation results. It was found that the positioning of the RANS/LES interface in the ELES model appears to have little effects on the mean wind field, while it does affect the fluctuating wind speed results. Comparative analysis with wind tunnel experiments and conventional large eddy simulation confirmed the efficacy of the proposed ELES with accelerated turbulence generation.
DOI: 10.6084/m9.figshare.28093648
title: Thermal runaway and flame propagation in battery packs: numerical simulation and deep learning prediction

description: The widespread application of lithium-ion battery technology faces a significant challenge from the inherent risk of thermal runaway and consequent fire spread. This paper proposes an intelligent framework for predicting the temperature distribution and thermal runaway propagation in a battery pack across diverse conditions, including various battery types, ambient temperatures, and fire heat release rates. First, we generate an extensive numerical database, comprising 36 simulations of battery jet flame and thermal runaway processes that are validated by experimental data. Subsequently, a dual-agent artificial intelligence (AI) model is employed to forecast the cell-to-cell thermal runaway propagation and evolution of temperature field in the battery pack. The results demonstrate the accuracy and reliability of the deep-learning approach in capturing battery thermal runaway dynamics. Quantitatively, the AI-based methodology achieves a relative error below 10% for thermal runaway time predictions in database-contained scenarios and below 30% for extrapolated cases. The model also shows excellent performance in predicting temperature field distributions, with an R² value exceeding 0.99 and a maximal MSE of 1.52 s². This study underscores the potential of AI method in improving the battery safety management, thereby facilitating timely interventions, preventive maintenance and fire safety of battery energy storage system.
DOI: 10.6084/m9.figshare.28093648.v1
title: Thermal runaway and flame propagation in battery packs: numerical simulation and deep learning prediction

description: The widespread application of lithium-ion battery technology faces a significant challenge from the inherent risk of thermal runaway and consequent fire spread. This paper proposes an intelligent framework for predicting the temperature distribution and thermal runaway propagation in a battery pack across diverse conditions, including various battery types, ambient temperatures, and fire heat release rates. First, we generate an extensive numerical database, comprising 36 simulations of battery jet flame and thermal runaway processes that are validated by experimental data. Subsequently, a dual-agent artificial intelligence (AI) model is employed to forecast the cell-to-cell thermal runaway propagation and evolution of temperature field in the battery pack. The results demonstrate the accuracy and reliability of the deep-learning approach in capturing battery thermal runaway dynamics. Quantitatively, the AI-based methodology achieves a relative error below 10% for thermal runaway time predictions in database-contained scenarios and below 30% for extrapolated cases. The model also shows excellent performance in predicting temperature field distributions, with an R² value exceeding 0.99 and a maximal MSE of 1.52 s². This study underscores the potential of AI method in improving the battery safety management, thereby facilitating timely interventions, preventive maintenance and fire safety of battery energy storage system.