Search Results (360)

Since 2011, massive strandings of pelagic Sargassum have become a recurrent environmental hazard across the tropical Atlantic and Caribbean archipelago, creating an urgent need for reliable short-term drift forecasts to support coastal risk management. This study evaluates key sources of uncertainty in operational Sargassum drift forecasting by analyzing the sensitivity of Lagrangian simulations to the representation of floating material and to environmental forcing fields. The analysis uses two complementary observational datasets: trajectories of four GPS-tracked Sargassum mats deployed near Puerto Rico and thirteen 24 h displacement vectors derived from sequential Sentinel-3 satellite detections across the tropical North Atlantic. Drift simulations were performed with the MOTHY model under multiple configurations, testing two material parameterizations, different atmospheric forcings, and several ocean circulation products and vertical current integration strategies. The results indicate that the best agreement with observed trajectories is obtained for partially immersed structures, highlighting the importance of balancing wind exposure and hydrodynamic drag. Sensitivity experiments further show that ocean circulation forcing dominates trajectory skill, while higher-resolution atmospheric forcing provides limited improvement under offshore conditions. Overall, the study confirms the importance of accurately representing upper-ocean transport processes and provides observational support for several operational choices implemented in the Météo-France Sargassum forecasting system. Full article

Background: Some widely used wildland fire behavior models, like the Fire Area Simulator (FARSITE), propagate fire fronts by computing the front-normal velocity (spread rate) as a function of local inputs and the front-normal direction. Such models are sometimes observed to cause the collapse of crown fires into sharp wedge shapes that eliminate heading fire behavior. Aims: We set out to document this phenomenon and, more generally, understand the relationships between fire shapes and spread rate functions. Methods: The phenomenon is studied both mathematically and through simulation experiments. Non-smooth fire fronts are theorized mathematically by an Eikonal partial differential equation ($H(x,\tau ,D\tau )=1$), where the unknown $\tau \left(x\right)$ is the time-of-arrival function and the Hamiltonian $H(x,t,p)$ is positively homogeneous and possibly non-convex in p; convex analysis is used to study viscosity solutions in constant conditions. Results: We show that a fire spread model preserves the smoothness of fire fronts if and only if it is equivalent to using the Huygens principle. Nontrivially, this is equivalent to a convexity criterion on the inverse spread rate profile, which is then the polar dual of the Huygens wavelet; this corresponds to Hamiltonian–Lagrangian duality. The relevance of smoothness-destroying models to crown fire is debated. Exact analytical formulas are derived for fire growth in constant conditions. Conclusions: Our understanding of fire spread models is improved by solving the spread equations in more general ways than previously known. In particular, the collapse of heading crown fires into sharp shapes is now explained. Smoothness-destroying spread models cannot be simulated by algorithms based on travel time like cellular automata; their general well-definedness remains an open question. Fire modelers can use these findings to guide their search for improved crown fire models, and more generally to verify the accuracy of numerical implementations. Full article

The minimal geometric deformation method is applied on Einstein–Maxwell field equations in this study to obtain two novel exact anisotropic solutions for polytropic configurations. A static spherically symmetric seed structure penetrated by the anisotropic fluid distribution is taken into consideration in order to accomplish this goal. The gravitational interaction of the new Lagrangian density is then coupled with the initial fluid configuration, representing an additional matter source. We obtain the field equations that correspond to the associated charged fluid sources. Two separate decoupled systems are developed when the field equations are subjected to a radial transformation. By applying the distinct constraints, each system’s solution is determined individually. The entire fluid configuration is then generated by combining these solutions via a certain linear combination. The constraints needed to determine the integration constants in the internal solutions are provided by junction conditions at the interface between the interior and exterior geometry. The suggested models are then verified by comparing them graphically under the observational data from the $CenX-3$ candidate star. In conclusion, for certain values of the decoupling parameter, our derived relativistic solutions satisfy established physical acceptability requirements. Full article

We propose a novel method for testing gravity models using seismic waves’ velocities. By imposing observational constraints on Earth’s moment of inertia and mass, we rigorously limit the gravitational models’ parameters within a $2\sigma$ accuracy. Our method, taking the PREM model as our reference and assuming its viability, constrains the parameters governing additional terms to the General Relativity Lagrangian to the following ranges: $-2\times {10}^9\lesssim \beta \lesssim {10}^9{\mathrm{m}}^2$ for Palatini $f\left(R\right)$ gravity, $-8\times {10}^9\lesssim ϵ\lesssim 4\times {10}^9{\mathrm{m}}^2$ for Eddington-inspired Born–Infeld gravity, and $-{10}^{-3}\lesssim \mathrm{{\rm Y}}\lesssim {10}^{-3}$ for Degenerate Higher-Order Scalar–Tensor theories. We also discuss potential avenues to enhance the proposed method, aiming to impose even tighter constraints on gravity models. Full article

Flood discharge observations in Japan are shifting from the conventional float-based methods to unmanned techniques such as radio-wave current meters. These approaches differ fundamentally in their measurement principles: the former is based on a Lagrangian framework, whereas the latter relies on a Eulerian framework. In this study, surface velocity fields obtained using particle image velocimetry (PIV) were used to track virtual tracers and derive Lagrangian surface velocities, providing a basis for examining the characteristics of Lagrangian and Eulerian measurements in an actual river under flood conditions. The uncertainties associated with the two frameworks were quantitatively compared, and the principal sources of uncertainty in Lagrangian measurements were identified. To achieve accurate discharge observation based on Eulerian measurements, the influences of measurement duration, subsection configuration, and vertical velocity distribution were investigated. The results suggest that measuring many points over a short duration is more effective than measuring a few points over a long duration. In a fixed-point measurement of subsurface velocity, a velocity dip was observed. Furthermore, the results quantitatively demonstrate the effects of bridge-pier wakes on the required averaging time and subsection configuration, highlighting the practical advantage of conducting observations on the upstream side of bridges. Full article

Public health suffers from noxious gas emitted by massive beached Sargassum algae. Net-barrages deployed in near-shore seas can contain Sargassum, provided they efficiently resist the additional hydrodynamic pressure induced by the catch. Nowadays, the design and installation of net-barrages are empiric. Structural breaks and anchor and mooring chain drifts can arise. We provide a mechanical model to evaluate stresses and loads on a structure made of fishing nets and buoy moorings. Hydrodynamic uncertainties occur through catches, fouling and sea current amplitudes appearing in lagoons or sheltered bays. This study presents a non-linear four-node finite-element model for continuous elastic membranes undergoing large displacements and small strains. The model relies on the Lagrangian linearly elastic membrane theory, employing the non-linear Green strain tensor and a non-updated hydrodynamic loading. We study forcings fixed a priori on a netting section of barrage that is 50 m long and 1 m high with double layer, e.g., two net-faces. We consider low and moderate current velocities, 0.05 and 0.35 m∙s⁻¹, while assuming specific vertical and horizontal catch pressures. A barrage installed in the reef lagoon at Le François on Martinique Island that is observable by satellite imagery could benefit of the computed net and mooring tensions. Full article

Tropical cyclones (TCs) and the Madden–Julian Oscillation (MJO) are two of the most impactful weather systems in the tropics. For example, it is not uncommon for a strong TC to kill hundreds of people and cause tens of billions of dollars in damage. The MJO modulates not only TCs but also monsoons around the world, which contribute essential rainfall for agriculture that supports billions of people, but which also can cause deadly floods. Because of the close coupling between the MJO and TCs, as well as the several week predictability of the MJO, models that can accurately simulate both kinds of weather systems have the potential to be useful for both mid-range weather forecasting and studies of impacts of climate change. This paper describes the further development of one such model, the Lagrangian Atmospheric Model (LAM), which simulates atmospheric motions by predicting motions of individual air parcels, and which has been shown to accurately simulate the MJO in previous studies. In this study, a new parameterization of cloud albedo is included in the LAM, and the model is tuned to improve simulations of TC distributions while still maintaining a robust and realistic MJO. Objective metrics of the model basic state, MJO quality, and TC distributions are used to optimize parameter selections for the cloud albedo parameterization and convective mixing. After tuning the LAM using dozens of 3-year simulations, we conduct two longer simulations forced with observed sea surface temperatures to verify that the new version of LAM has a substantially improved representation of TCs while still maintaining a realistic MJO. Full article

This study presents an optimized numerical and empirical modeling framework for ionic wind-driven electrostatic precipitators designed for atmospheric particulate matter (PM) removal. While traditional particle tracing models in long ducts often suffer from transient evaluation errors (the “flight time paradox”), this work introduces a Fate-based Steady-state Evaluation (FSE) method. By coupling Electrostatics, Laminar Flow, and Particle Tracing in a high-fidelity 2D axisymmetric model, we achieved a baseline validation with a Mean Absolute Error (MAE) of 5.3% compared to experimental data (20 kV, 0.5 m/s). Furthermore, a non-linear regression engine based on a physical-exponential decay function was developed to provide real-time performance predictions. The resulting hybrid model demonstrates a high scientific reliability (R² = 0.98), establishing it as a robust tool for the design and optimization of air purification systems targeting fine atmospheric aerosols (0.1–3.0 μm). In addition, the proposed Fate-based Steady-state Evaluation (FSE) method eliminates transient bias commonly observed in long-duct Lagrangian particle simulations. This methodological improvement enables statistically consistent efficiency estimation for electrohydrodynamic filtration systems and can be applied to a broad class of Computational Fluid Dynamics (CFD)-based particulate capture studies. The developed framework enables rapid design optimization of compact electrohydrodynamic filtration systems and provides a practical alternative to computationally expensive full-scale Computational Fluid Dynamics (CFD) simulations. Full article

Hydrogen-enriched fuel injection in staged gas-turbine combustors is commonly achieved through jet-in-crossflow (JICF) configurations, where flame stabilization is governed by a local balance between flow-induced strain/mixing and chemical reaction rates. This work investigates turbulent reacting JICF relevant to staged combustion conditions using high-fidelity simulations with adaptive mesh refinement (AMR) and differential-diffusion effects together with Lagrangian particle statistics. Chemistry model uncertainties are incorporated by using a projection method that maps uncertainty estimates from detailed mechanisms into the model used in this work. Results show that the macroscopic flame topology remains in a stable two-branch regime (lee-stabilized and lifted) and is primarily controlled by the jet momentum–flux ratio J. Visualization of the normalized scalar dissipation rate reveals that the flame front resides on the low-dissipation side of intense mixing layers, occupying an intermediate region between over-strained and under-mixed regions. While hydrogen content does not significantly change the global stabilization mode for the cases studied, uncertainty analysis reveals composition-dependent differences that are not apparent in the mean behavior alone. In particular, visualization in Eulerian (χ, T) state-space analysis and particle statistics conditioned on the stoichiometric surface demonstrate that higher-hydrogen cases observe a lower scalar dissipation rate and exhibit substantially reduced variability in OH production under kinetic-parameter perturbations, whereas lower-hydrogen blends experience higher dissipation and amplified chemical sensitivity. These findings highlight that, even in globally similar JICF regimes, the hydrogen content can modify the local response of the flame to kinetic-parameter uncertainty, motivating uncertainty-aware interpretation and design for hydrogen-fueled staging systems. Full article

Bioaerosols released during wildland and prescribed fires may influence ecosystems, air quality, and microbial dispersal, yet their transport and deposition remain poorly understood. This study combined infrared uncrewed aircraft system (UAS) observations of a prescribed burn with the coupled fire–atmosphere model WRF-SFIRE and a Lagrangian particle model in order to evaluate how uncertainties in simulated fire behavior affect predicted bioaerosol (bacterial cell) transport and deposition. A reconstruction of the observed spatiotemporal evolution of the fire was derived from thermal UAS measurements acquired during the burn and incorporated into a WRF-SFIRE simulation, in which the modeled fire spread was constrained to follow this reconstructed progression. This benchmark run was compared with two unconstrained, fully coupled simulations that used a low and a high estimate of fuel moisture content (FMC) to represent typical uncertainty in fire rate of spread (ROS) prediction. Despite substantial differences in fire intensity and plume dynamics among the simulations, the resulting bioaerosol transport pathways and deposition patterns were broadly consistent across cases. The horizontal transport of the bioaerosols was dominated by the ambient Easterly wind and the bioaerosols were lofted by fire-affected updrafts—some exceeding 10 m/s—within the buoyant plume structure resolved in WRF-SFIRE. Deposition hot-spots appeared in consistent locations in the three simulations, especially regions where topography forced up-slope transport. Although the most intense fire produced slightly greater local deposition—likely due to a combination of stronger fire-induced downdrafts and overturning from penetration into strong vertical wind shear above the boundary layer—differences were small relative to the overall deposition footprint. These results suggested that, for burns of this scale, bioaerosol transport and deposition predictions are relatively robust to realistic uncertainties in fire-behavior modeling. This finding indicates that coupled fire–atmosphere and particle-transport modeling frameworks could be employed to quantitatively forecast microbial transport and deposition during future controlled burn experiments. Full article

Ammonia (NH₃) has emerged as a promising carbon-free fuel for next-generation green energy systems due to its high hydrogen density, ease of storage and transport, and compatibility with existing infrastructure. These attributes contrast with hydrogen, which presents major challenges related to storage, safety, and high-pressure handling. Thus, ammonia offers a more practical alternative for combustion-based applications. However, its low reactivity and complex vaporization behavior, particularly under flash-boiling conditions, pose challenges for accurate modeling. This study presents a comprehensive numerical investigation of liquid-ammonia spray behavior under a range of ambient pressures, encompassing both flash-boiling and non-flashing conditions. Simulations were conducted using the Lagrangian particle tracking method, coupled with various turbulence models (the renormalization group (RNG) family, k-ω family, $\varsigma -f$, V2F models) to evaluate their predictive performance. Validation against experimental data for liquid and vapor penetration demonstrated that the V2F model achieved the best overall balance between accuracy and computational efficiency. Under strong flash-boiling conditions (2 bar), rapid droplet breakup and notable cooling were observed, with droplet temperatures decreasing to approximately 235 K within a few millimeters of the nozzle. In contrast, the cooling effect was more moderate under non-flashing conditions at higher ambient pressures (10–15 bar). Although the current findings were based on numerical simulations, experimental studies are ongoing to validate and refine the modeling framework further. This work provided valuable insights into the coupled effects of turbulence, phase change, and thermal transport in superheated ammonia sprays. Future research will build upon these results by extending the model to NH₃/H₂ dual-fuel systems, refining turbulence-phase interaction models, and exploring the potential application of ammonia-based flash-boiling cooling systems for electric vehicle (EV) battery thermal management. Full article

Urban air quality is influenced by the removal of particulate matter through dry deposition, yet this process is often simplified in models, potentially underestimating the role of vertical building surfaces. This study investigates the impact of aerosol deposition on building walls on PM_2.5 concentrations and the deposition budget within the urban canopy. We utilized a Large Eddy Simulation model coupled with a Lagrangian Particle Transport module to simulate aerosol dispersion in randomized urban configurations corresponding to Local Climate Zones (LCZs) 4, 5, and 6. The results indicate that under the considered conditions, vertical walls can act as a primary sink for PM_2.5, capturing over 70% of deposited particles downwind from sources in high-rise environments. We observed a non-linear sensitivity of airborne concentrations to wall deposition efficiency; a relatively low capture probability (10%) reduced near-surface concentrations by 25–30%. Furthermore, for fine and coarse particles (up to ~20 µm), the uncertainty in wall deposition parameterization appeared to outweigh the influence of particle physical properties on dispersion patterns. These findings suggest that neglecting wall deposition may lead to overestimation of urban pollution levels, highlighting the importance of refining particle–wall interaction parameterizations in air quality models. Full article

Accumulation of plastic litter in the marine environment is a pressing global concern. To study this issue, we use the Blue2 Modelling Framework (Blue2MF), an integrated modelling tool developed by the Joint Research Centre (JRC) of the European Commission. Our study uses the Lagrangian model LTRANS-Zlev (LTRANS) in the Blue2MF to simulate the trajectories, distribution, and accumulation of macroplastics in five European marine basins: the Baltic Sea, Black Sea, Mediterranean Sea, Atlantic Northwest European Shelf, and Atlantic Southwest European Shelf. By incorporating model-estimated macroplastic inputs from land and estimations of maritime (fishing) sources, we simulate distribution patterns of marine macroplastics between 2016 and 2018. Our study addresses the challenges involved in modelling the spatial distribution and abundances of macroplastics with the LTRANS model and the factors that may condition the estimation of the model accuracy when model results are compared/validated with marine litter observations available. We compare our model results with available observations, achieving a good agreement between predicted and observed macroplastic distributions and abundances and estimating the model accuracy for both beached and floating macroplastics. Our study provides a basis for future forecast runs to evaluate the impact of policy/management options on marine macroplastic pollution in European Seas. Full article

Slow lateral wandering and trochoidal-like motion are commonly observed in intense atmospheric vortices, yet most reduced-order vortex models assume a fixed axis or represent centre motion as purely advective. In this work, we propose a minimal reduced-order framework in which slow gyroscopic precession is introduced as an explicit degree of freedom superimposed on a rapidly rotating vortex core. The vortex is represented by a Burgers–Rott-type velocity field with time-dependent stretching rate and circulation, while the vortex centre undergoes a slow precessional motion governed by a time-dependent rate ${\Omega }_p\left(t\right)$. The evolution of the vortex parameters is coupled to environmental variability through simple relaxation laws driven by standard large-scale diagnostics, including convective available potential energy, vertical shear, and background vorticity. A tracker-only analysis of tropical cyclone best-track data is used to constrain the appropriate dynamical regime at the track scale, indicating that observed centre wandering typically occurs in a slow-precession limit P = ${\Omega }_p/{\omega }_c\ll 1$. Numerical demonstrations in cyclone-like configurations show that, despite the smallness of the precession number, cumulative lateral displacement and enhanced Lagrangian dispersion can develop over the vortex lifetime. The proposed framework is intended as a proof-of-concept reduced-order model that isolates the role of weak, environmentally forced precession in modulating vortex wandering and transport, and complements more detailed numerical and observational studies. Full article

Wind-driven shear and vertical mixing in the upper meter of the ocean strongly regulate near-surface circulation and buoyant tracer transport, yet direct field observations immediately beneath the air–sea interface remain scarce. We present Lagrangian observations, equipped with an upward-looking Acoustic Doppler Current Profiler (ADCP), collected during 5–7 April 2022 in the Jeju Strait under wind stresses of 0.0006–0.19 Pa. Near-surface shear and turbulence metrics were resolved within the top surface layer (TSL), and a response-time analysis showed that upper-layer shear responded most promptly to wind variability, whereas deeper-layer shear and sea-state metrics adjusted more slowly. Wave-period variability exhibited the weakest coupling, indicating additional nonlocal influences. Reynolds-stress estimates showed that the along-wind momentum flux was predominantly negative, indicating net downward transfer of downwind momentum, while cross-direction fluxes were smaller on average and frequently reversed sign, consistent with intermittent lateral transfers associated with evolving wave–current interactions. Using an eddy-viscosity framework, we derived stress-based exponential-saturation parameterizations for depth-averaged shear and vertical diffusivity, with the diffusivity magnitude treated as sensitive to the assumed turbulent Prandtl number. The relationships are intended for event-scale conditions within the observed forcing range and provide field-constrained, implementation-ready formulations for near-surface transport and mixing models. Full article