Search Results (107)

If a CO₂ reservoir or transmission pipeline were to leak, both the surrounding ecology and maritime traffic safety could be put at risk. To better understand and prepare for this risk, multiphase Computational Fluid Dynamics (CFD) models were built in ANSYS Fluent to capture the behavior of a leak once it enters the water. A 3D Eulerian–Eulerian model was used for validation, while a simplified 2D model was applied to simulate conditions at a 50-m depth. The models integrate bubble dynamics, gas holdup, CO₂ dissolution, dissolved species transport, and seawater acidification into a unified CFD framework. Mass transfer was calculated using the Hughmark correlation, and local seawater temperature and salinity were factored in to determine dissociation behavior and the relevant Henry’s Law constant. To confirm the 3D model’s accuracy, results were checked against two experimental datasets: the QICS field study and the Hauser Tank experiments. The team also modeled a hypothetical release scenario at the High Island 10L site and compared the results with earlier published work. The results show that at a depth of 50 m, the surrounding water column can completely absorb a CO₂ release at a rate of 35 kg/s, since the gas dissolves into the seawater as it rises toward the surface. Beyond confirming this mitigation capacity, the simulations shed light on how a leak would actually unfold in the environment, including the shape and movement of the rising bubble plume, how much CO₂ dissolves along the way, and the resulting shifts in seawater pH and pCO₂. Together, this provides a practical framework for assessing how CO₂ leaks could affect marine environments in the Gulf of Mexico. Full article

Coastal power plants draw seawater from the open ocean through their cooling-water circulation systems. The cooling water falls over an overflow weir inside the siphon well, entraining large quantities of air, and generates a foam pollution plume upon discharge to the sea. By combining physical model experiments with numerical simulation, this study investigates the key factors governing foam stability and the aeration behavior of the water downstream of the siphon-well overflow weir. The principal conclusions are as follows: among the three single-factor variables tested in controlled laboratory conditions—temperature, salinity, and shellfish-flesh suspension concentration—the biological substance proxy showed the strongest effect on foam stability; when the shellfish-flesh suspension concentration reaches 20% (mass/volume basis, independently prepared), the foam volume and half-life increase by factors of 1.4 and 3.36, respectively, relative to the 4% baseline condition. When the dimensionless aeration depth z/z₉₀ < 0.75, the air-concentration profile rises relatively slowly with depth, whereas it increases more rapidly as the free surface is approached. Within the investigated viscosity range of 1.0–8.3 mPa·s (1.0 mPa·s for the pure-water control and 1.5–8.3 mPa·s for the measured viscosities of the 4–20% shellfish-flesh suspensions), the cross-sectional mean air concentration shows an overall decreasing trend as the liquid-phase viscosity increases, and the total bubble number density decreases correspondingly. The findings provide a laboratory-based indication of the mechanisms that must be addressed in the development of physical foam-suppression technologies; confirmation against field discharge water is required. Full article

Underground deep vertical spaces are a new form of architectural structure for the efficient use of land resources. However, their slender geometry can intensify smoke transport and thermal hazards during fires. Sealing is a potential emergency strategy, but its influence on smoke dynamics and flame extinction in deep shafts remains insufficiently quantified. This study investigates smoke transportation characteristics and flame self-extinction in a sealed deep vertical space using 1:26 reduced-scale experiments combined with CFD simulations. Across the tested conditions, sealing consistently increased the characteristic upper-shaft centerline temperature rise, with enhancements ranging from 43.2% to 374.9%. The vertical centerline temperature above the fire exhibits a segmented decay behavior: in the plume-rise region it follows a power-law trend, while the decay coefficient deviates from the ideal-plume expectation, consistent with the thermal shielding effect associated with the confined upper hot-gas layer. Under sealed conditions, a distinct “ghosting” flame behavior and eventual self-extinction were observed. The combined flame, thermal, and simulated flow-field evidence is consistent with an oxygen-limited interpretation, although this mechanism was not directly verified by gas-species measurements. Based on the reduced-scale dataset, the self-extinction time was normalized by the characteristic oxygen-consumption timescale $t_{o_2}$, yielding ${\displaystyle \frac{t_{\mathrm{ext}}}{t_{O_2}}}=2.074{\left({\displaystyle \frac{h}{1 \mathrm{m}}}\right)}^{-0.394}{\left({\displaystyle \frac{Q}{1 \mathrm{kW}}}\right)}^{-0.071}$, which provides a quantitative description of flame self-extinction under the tested sealed conditions. Full article

Rising atmospheric CO₂ levels pose a critical challenge to achieving global sustainability targets. Geological carbon sequestration (GCS) offers a long-term solution for reducing greenhouse gas emissions, but its large-scale deployment faces limitations in cost, uncertainty, and operational risk. Recent advances in machine learning (ML) present transformative opportunities to enhance every stage of the carbon capture and storage (CCS) lifecycle, from pre-injection evaluation to post-injection monitoring. This review systematically examines ML integration in CCS applications, emphasizing roles in geological characterization, injection optimization, plume prediction, and leakage detection. It provides a structured overview of ML methodologies including Random Forest, Support Vector Regression, and XGBoost, along with emerging deep learning models used for anomaly detection and uncertainty quantification. Experimental insights, monitoring techniques, and real-time data applications are summarized to illustrate ML’s capability in accelerating simulations, reducing costs, and increasing safety assurance. Furthermore, real-world case studies such as Sleipner (Norway), Illinois Basin–Decatur (USA), Boundary Dam (Canada), Gorgon (Australia), and Quest (Canada) demonstrate how ML has enhanced performance, predictive accuracy, and storage reliability in field-scale CCS projects. The review concludes by identifying existing challenges, data scarcity, interpretability, and regulatory integration, and proposes a unified ML framework for scalable, autonomous, and secure CO₂ storage. Overall, this study provides a comprehensive roadmap for leveraging artificial intelligence to achieve reliable, cost-effective, and sustainable carbon management solutions aligned with global net-zero objectives. Full article

The South Atlantic is a classic region of hotspot volcanism, with numerous intraplate magmatic structures, such as the Walvis Ridge, Rio Grande Rise, Fernando de Noronha Ridge, and Victoria-Trinda Ridge. These structures record mantle plume activity and plate tectonics since the breakup of the South America–Africa continent, but the spatiotemporal correlations of mantle end-members among different hotspot systems remain unclear. This paper uses the Unified Manifold Approximation and Projection Algorithm (UMAP) and Hierarchical Agglomeration Clustering Algorithm (HAC) to perform dimensionality reduction and cluster analysis on 288 basalt Sr-Nd-Pb isotope data from 12 major hotspot-derived seamount chains/rises in the South Atlantic, identifying three types of mantle end-members: EM-type, HIMU-type, and PREMA/FOZO-type. The results show that HIMU-type end-members are mainly distributed in St. Helena Island and its associated Guinea seamount chain; EMI-type end-members dominate the Walvis Ridge basement, Rio Grande Rise, and discovered seamount chain; and PREMA/FOZO-type end-members are mainly distributed in the Brazilian continental margin seamount chain. In terms of time series, EM-type magmatic activity began in the Early Cretaceous (~132 Ma), while HIMU-type hotspot activity appeared later (~82 Ma), and both were vertically superimposed on the Walvis Ridge basement. Based on the spatiotemporal distribution characteristics of mantle end-members in hotspots in the South Atlantic and Indian Oceans, this paper proposes a two-stage magmatism model for hotspots at the African margin: in the early stage, EM-type material, associated with continental delamination and ancient lithosphere recycling, preferentially melted, forming large-scale submarine plateaus or seamount chains; in the later stage, HIMU-type material, associated with the reactivation of subducted oceanic crust or Archean carbonated subcontinental lithospheric mantle (SCLM), melted and rose in weak areas of mature oceanic crust, forming smaller seamounts. This study provides a new perspective on the unified genetic mechanism of multiple hotspots in the South Atlantic and offers a reference for understanding the generation, evolution, and magmatic activity of hotspots during the breakup of Gondwana. Full article

Methane source-rate inversion from remote-sensing plume imagery is essential for emissions monitoring, but its accuracy is often limited by uncertainty in ancillary wind information. This study examines how physical knowledge can be integrated into a deep-learning inversion model when the available wind input is imperfect. Using a controlled large-eddy-simulation (LES) benchmark designed for EnMAP/PRISMA-style imaging-spectrometer methane quantification, we compare six models that span image-only regression, flexible wind conditioning, simplified hard integrated-mass-enhancement (IME) coupling, and soft physics-guided learning under clean inputs, deterministic wind bias, stochastic Gaussian wind noise, and source-rate-stratified tests. Under clean benchmark conditions, flexible wind conditioning provides the best scalar accuracy, with FiLM reaching a mean absolute percentage error (MAPE) of 6.19% and a root mean squared error (RMSE) of 1323.36, followed closely by Concat (MAPE 6.37%, RMSE 1325.69). The simplified hard-coupling model is sensitive to wind perturbations: DIN-hard rises from MAPE 8.44% under clean inputs to 31.39% and 26.89% under deterministic wind-bias multipliers α = 0.7 and α = 1.3, respectively, and becomes unstable under stronger Gaussian wind noise in the tested protocol. By contrast, DIN-soft-v2 remains competitive under clean conditions (MAPE 6.39%, RMSE 1360.94), follows smoother degradation under biased or noisy wind, and improves plume spatial diagnostics relative to DIN-soft (center-of-mass shift 3.92 versus 4.07 pixels; plume alignment degree 2.60 versus 2.72 degrees). The calibrated IME-style physical baseline reaches a clean MAPE 24.45%, indicating that the learning-based models substantially outperform this benchmark physical proxy. Within this LES-based benchmark and the tested wind-perturbation protocols, the results suggest that IME-inspired physical knowledge is more robustly incorporated as a calibratable soft prior than as the simplified hard log-additive forward coupling considered here; however, transfer to real satellite scenes still requires validation. Full article

To investigate the influence of fire-resistant overhanging eave geometry (width and installation height) on vertical fire spread along building facades, a nine-story building model was developed using PyroSim (version 2023.2.0816), and simulations were conducted using Fire Dynamics Simulator. The results show that window-ejected flames form a buoyant spill plume that adheres to the facade due to the Coandă effect and air entrainment, resulting in a rapid temperature rise above window openings. Increasing both eave width (W) and installation height exhibited measurable but limited effectiveness in suppressing vertical fire spread. Specifically, increasing eave width significantly enhances flame deflection and reduces facade-attached plume intensity, whereas increasing installation height primarily alters plume impingement location with comparatively weaker suppression effects. A critical transition is observed at an eave width of approximately 0.4 m, beyond which lateral spill flames are induced due to flow obstruction. The relationship between eave geometry and flame behavior is further interpreted through dimensionless analysis based on characteristic fire diameter (D*), revealing that effective suppression occurs when W/D* exceeds a threshold value. These findings provide simulation-based insights into facade fire protection design, although further investigation is required to incorporate wind effects, complex facade geometries, and combustible materials. Full article

The Rio Grande Rise (RGR) is the largest oceanic plateau in the South Atlantic and represents a key natural laboratory for understanding oceanic plateau formation, deep-sea circulation, ecosystem functioning, and ferromanganese crust development. This study presents a critical synthesis of current scientific knowledge on the RGR, integrating geological, geophysical, oceanographic, biological, and geochemical evidence published over the last two decades. Geophysical data reveal a complex tectono-magmatic evolution involving Late Cretaceous plume-related volcanism, crustal thickening, rifting, and subsequent subsidence. The structural framework of the plateau is dominated by the Cruzeiro do Sul Rift, which plays a central role in controlling sedimentation, magmatism, and seawater circulation. Oceanographic studies demonstrate that the interaction between the southern branch of the South Equatorial Current and the complex topography of the RGR generates intense internal tides and bottom currents, strongly influencing sediment transport and benthic habitats. Biological investigations indicate that the RGR hosts diverse deep-sea communities, including sponge grounds, cold-water corals, and associated fauna, whose distribution is tightly linked to geomorphology and hydrodynamics. Ferromanganese crusts occurring on the plateau preserve valuable geochemical records of oceanographic and redox conditions, although their spatial distribution, thickness, and metal budgets remain incompletely constrained. Despite major advances, significant knowledge gaps persist regarding crustal structure, sedimentary evolution, ecosystem functioning, and mineral formation processes. This review highlights these uncertainties and outlines research priorities necessary to improve understanding of oceanic plateaus and deep-sea systems in the South Atlantic. Full article

This study experimentally investigates the dynamics of air bubble plumes in water under varying thermal and hydrodynamic conditions using a two-dimensional Particle Image Velocimetry (PIV) system. The experimental setup consists of a transparent acrylic tank equipped with a bubble generator, a controlled heating system, and a synchronized PIV arrangement to capture both bubble motion and the induced liquid flow field. Experiments were conducted over a range of water temperatures (21–60 °C), air flow rates, and water depths (200–600 mm) to systematically quantify their coupled influence on bubble plume behavior. The results demonstrate that bubble rising velocity (defined here as the mean vertical, buoyancy-driven component of bubble motion measured in the fully developed plume region) increases with water temperature, gas flow rate, and water depth. For a fixed gas flow rate and water depth, increasing the water temperature from 40 °C to 60 °C resulted in an approximately twofold increase in bubble rising velocity, primarily due to reduced liquid viscosity and enhanced buoyancy forces. Bubble velocity also increased with gas flow rate and water depth, reflecting stronger momentum input and extended acceleration distances within taller water columns. PIV-resolved velocity fields further reveal that the surrounding fluid velocity increases proportionally with bubble rising velocity and temperature, confirming a strong coupling between bubble motion and plume-induced circulation. The surrounding liquid velocity reached approximately 30–60% of the corresponding bubble rising velocity, depending on operating conditions. These findings provide quantitative experimental insight into the coupled effects of thermal conditions, gas injection rate, and liquid depth on bubble–liquid interactions. The results contribute valuable validation data for multiphase flow modeling and offer practical relevance for thermal–hydraulic, chemical, and environmental engineering applications involving bubble-driven transport processes. Full article

The first application of theory of the rise of line thermals was to understand the rise of turbulent smoke plumes emitted from smoke stacks into a cross-wind. Initial solutions required numerical calculations. In this article analytical solutions are found, and these are used here to explore solutions for the rise of buoyant line wakes from submarine vehicles. Solutions cater for wakes in both neutral and stable environments, and for sources which have either negative or positive initial buoyancy. Account is also taken of sources with differing size and initial momentum. Practical examples of submarine thermal wake flows are given using neutral and typical stably stratified upper ocean conditions and a range of source conditions. A key result is that small-diameter submarine wakes with high temperatures produced in weakly stratified ocean waters will have a large height of rise, and may easily reach the surface. By contrast, large-source-diameter wakes, with temperatures close to ambient and emitted into strongly stratified oceans, will have very small heights of rise. Full article

Gravity currents constrained by bottom walls are prevalent in engineering applications such as industrial discharges and deep-sea mining, and will pose significant environmental risks. In this study, the influence of jet source parameters on the dynamics and diffusion characteristics of particle-driven bottom currents was investigated through physical experiments using Digital Image Processing (DIP). This non-invasive technology is cost-effective and exhibits broad applicability. The results demonstrated that the downstream plume front $d_{\mathrm{L}\mathrm{m}\mathrm{a}\mathrm{x}}$, the maximum lift height $h_{\mathrm{L}\mathrm{m}\mathrm{a}\mathrm{x}}$ and the average lift height $h_{\mathrm{a}\mathrm{v}\mathrm{e}}$ all exhibit a decreasing trend with increasing Richardson number (Ri) after impingement, and show a linear increase with rising Reynolds number (Re). The plume diffusion scale S follows a two-stage evolution: during the inertia-dominated stage, S evolves exponentially over time t as $S=a{e}^{bt}$, while in the equilibrium stage of negative buoyancy and turbulent dissipation, S follows a power-law relationship $S=a{t}^b$ (b < 1). The rate of change of S increases with smaller jet angles α, and the variations with dimensionless bottom clearance H/D remain within 10%. The dimensionless average longitudinal expansion rate ${\displaystyle \frac{\overline{E}}{\sqrt{g\prime /D}}}$ reaches minimum values at α = 75°, peaks at H/D = 10, and exhibits a linear decreasing trend with Ri. As Re increases, ${\displaystyle \frac{\overline{E}}{\sqrt{g\prime /D}}}$ displays a three-stage fluctuating behavior. This study provides valuable experimental data that improve the understanding of gravity current behavior under wall confinement and support the predictive modelling of gravity current. Full article

High-speed jet-in-crossflow (JICF) configurations are central to several aerospace applications, including turbine-blade film cooling, thrust vectoring, and fuel or hydrogen injection in combusting or reacting flows. This study employs high-fidelity direct numerical simulations (DNS) to investigate the dynamics of a supersonic jet (Mach 3.73) interacting with a subsonic crossflow (Mach 0.8) at low Reynolds numbers. Three momentum-flux ratios (J = 2.8, 5.6, and 10.2) are considered, capturing a broad range of jet–crossflow interaction regimes. Turbulent inflow conditions are generated using the Dynamic Multiscale Approach (DMA), ensuring physically consistent boundary-layer turbulence and accurate representation of jet–crossflow interactions. Modal decomposition via proper orthogonal decomposition (POD) and spectral POD (SPOD) is used to identify the dominant spatial and spectral features of the flow. Across the three configurations, near-wall mean shear enhances small-scale turbulence, while increasing J intensifies jet penetration and vortex dynamics, producing broadband spectral gains. Downstream of the jet injection, the spectra broadly preserve the expected standard pressure and velocity scaling across the frequency range, except at high frequencies. POD reveals coherent vortical structures associated with shear-layer roll-up, jet flapping, and counter-rotating vortex pair (CVP) formation, with increasing spatial organization at higher momentum ratios. Further, POD reveals a shift in dominant structures: shear-layer roll-up governs the leading mode at high J, whereas CVP and jet–wall interactions dominate at lower J. Spectral POD identifies global plume oscillations whose Strouhal number rises with J, reflecting a transition from slow, wall-controlled flapping to faster, jet-dominated dynamics. Overall, the results demonstrate that the momentum-flux ratio (J) regulates not only jet penetration and mixing but also the hierarchy and characteristic frequencies of coherent vortical, thermal, and pressure and acoustic structures. The predominance of shear-layer roll-up over counter-rotating vortex pair (CVP) dynamics at high J, the systematic upward shift of plume-oscillation frequencies, and the strong analogy with low-frequency shock–boundary-layer interaction (SBLI) dynamics collectively provide new mechanistic insight into the unsteady behavior of supersonic jet-in-crossflow flows. Full article

Landfills serve as a primary disposal method for municipal solid waste in China, with over 20,000 operational sites nationwide; however, long-term operations risk leachate leakage and groundwater contamination. Amid intensifying climate change and human activities, understanding contaminant evolution mechanisms in landfills has become critically urgent. Focusing on a representative plain-based landfill in North China, this study integrated field investigations and groundwater monitoring to establish a monthly coupled groundwater flow–solute transport model (using MODFLOW and MT3DMS codes) based on site-specific hydrogeological boundaries and multi-year monitoring data, analyzing spatiotemporal plume evolution under the coupled impacts of precipitation variability (climate change) and intensive groundwater extraction (human activities), spanning the historical period (2021–2024) and future projections (2025–2040). Historical simulations demonstrated robust model performance with satisfactory calibration against observed water levels and chloride concentrations, revealing that the current contamination plume exhibits a distinct distribution beneath the site. Future projections indicate nonlinear concentration increases: in the plume core zone, concentrations rise with precipitation, whereas at the advancing front, concentrations escalate with extraction intensity. Spatially, high-risk zones (>200 mg/L) emerge earlier under wetter conditions—under the baseline scenario (S0), such zones form by 2033 and exceed site boundaries by 2037. Plume expansion scales positively with extraction intensity, reaching its maximum advancement and coverage under the high-extraction scenario. These findings demonstrate dual drivers—precipitation accelerates contaminant accumulation through enhanced leaching, while groundwater extraction promotes plume expansion via heightened hydraulic gradients. This work elucidates coupled climate–human activity impacts on landfill contamination mechanisms, proposing a transferable numerical modeling framework that provides a quantitative scientific basis for post-closure supervision, risk assessment, and regional groundwater protection strategies, thereby aligning with China’s Standard for Pollution Control on the Landfill Site of Municipal Solid Waste and the Zero-Waste City initiative. Full article

This study investigates the dispersion and condensation behavior of tritiated water vapor released into the atmosphere using moist air as a carrier, with an emphasis on safety optimization for nuclear power plant effluent discharge. A coupled heat and mass transfer model was developed and implemented in CFD simulations to analyze the evolution of temperature and relative humidity during the mixing of exhaust moist air with ambient air. The effects of key atmospheric and operational parameters—including the ambient wind speed, turbulence intensity, ambient temperature, relative humidity, and exhaust velocity—were systematically examined. The results indicate that the temperature difference between the exhaust gas and ambient air is the primary factor governing condensation risk. Low wind speeds and weak turbulence favor near-field humidity accumulation, while higher wind speeds and turbulence intensities enhance mixing and dilution, thereby reducing local humidity peaks but extending the downwind impact range. Increasing exhaust velocity strengthens plume rise and long-range transport due to enhanced momentum and latent heat release, mitigating accumulation near the chimney outlet. Furthermore, high ambient temperatures significantly increase the air’s moisture-holding capacity, allowing higher exhaust humidity without inducing condensation. Full article

A quantitative understanding of methane leakage has become essential for safety design as eco-friendly fuel systems expand in modern ship applications. To address this need, controlled methane-release experiments were conducted in a large indoor chamber (30 × 16 × 20 m) to evaluate how sensor-network resolution (1 m vs. 0.5 m spacing) influences dispersion measurement and 5% Lower Explosive Limit (LEL)-based risk assessment. Initial tests with a 1 m grid showed that most sensors detected only low concentrations except for near the release nozzle, demonstrating that coarse spatial resolution cannot capture the primary dispersion pathway or transient peaks. This limitation motivated the use of a 0.5 m high-density sensor network, which enabled clear identification of the dispersion centerline, concentration-gradient development, early detection behavior, and the evolution of diluted regions, particularly under buoyancy-driven plume rise. Experimental results were compared with CFD simulations using the RNG k–ε and k–ω GEKO turbulence models. Strong agreement was obtained in peak concentration, concentration-rise rates during the accumulation phase, and LEL-based dispersion distances. These findings confirm the suitability of the selected turbulence models for predicting methane behavior in large enclosed spaces and highlight the sensitivity of model–experiment agreement to measurement resolution. The results provide an experimentally grounded reference for sensor layout design and verification of gas-detection strategies in ship compartments, fuel-gas preparation rooms, and modular supply units. Overall, the study establishes a methodological framework that integrates high-resolution experiments with CFD modeling to support safer design and operation of methane-fueled vessels. Full article