Search Results (640)

Culverts are widely used to provide crossings over small rivers and can strongly influence flood hydraulics by controlling upstream water levels. During high flows, insufficient conveyance may cause pressurization and overtopping, with important implications for flood hazard assessment. Although computational fluid dynamics (CFD) is increasingly applied to investigate these complex hydraulic processes, systematic evaluations of its performance remain limited. This study addresses this gap by validating a three-dimensional CFD model against previously published laboratory experiments for culvert-only, weir-only and combined culvert–weir configurations under both steady (rising and receding discharge sequences) and unsteady flow conditions. Beyond benchmark validation, diagnostic analyses examined inlet region mesh resolution, inflow ramp history and turbulence closure, together with the associated outlet ventilation and attachment mechanisms. The model reproduced upstream water levels with mean absolute relative error (MARE) values ranging from 0.90% to 5.42% and captured the main stage–discharge relationships across the tested configurations. However, the experimentally observed transition from partially full to pressurized flow in the combined culvert–weir configuration was not reproduced consistently. The diagnostic analyses showed that inlet resolution influences entrance losses and post-submergence headwater, inflow history alters outlet attachment and ventilation and turbulence closure affects barrel filling and air-pocket morphology. The results indicate that CFD can reproduce water level and overtopping responses well when carefully configured, while regime transition prediction remains more uncertain because of its sensitivity to ventilation and discharge history effects. Full article

Compared with single-swirl configurations, linearly arranged multi-swirl burners introduce complex inter-jet interactions that significantly alter flame dynamics; however, the underlying mechanisms remain poorly understood. In this study, direct numerical simulation (DNS) is employed to investigate a lean-hydrogen multi-swirl flame, aiming to elucidate its flame structure and dynamic evolution. The flame development region is divided into upstream (Region 1) and downstream (Region 2) regions, based on the critical location where the flame stretch transitions from positive to negative. The flow field, flame morphology, thickness, stretch, curvature, and their joint statistical relationships are systematically compared between the two regions. The results show that in Region 1, the flame stretch is dominated by positive strain rate, and the flame maintains a continuous structure and a small thickness. In Region 2, the curvature stretch becomes dominant, leading to severe flame wrinkling, local extinction and breakup, with the mean flame thickness increasing to about 1.5 times that of the laminar flame. Joint PDF analyses reveal that negative flame stretch is correlated with a large negative curvature in Region 2, whereas in Region 1, it is not affected by the curvature sign. The downstream flame also exhibits higher displacement speeds, indicating intensified turbulence–flame interaction. This study reveals the streamwise transition mechanism of the multi-swirl flame from strain-dominated to curvature-dominated dynamics, clarifies the distinct coupling modes of upstream stabilization and downstream fragmentation, and provides new theoretical guidance for stable combustion and wide-operability design of lean-hydrogen swirl combustors. Full article

Boundary-layer atmospheric stability, wind-shear variability, and thermodynamic forcing are all important factors for the initiation, intensification, and transport of dust storms. But there is limited knowledge of the quantitative evaluation of bulk-layer atmospheric stability and the relation between wind-driven dust dynamics and atmospheric stability in arid and semi-arid regions. In this research, a hybrid AI–meteorology framework, HyMet-Fusion, is presented that combines visual information derived from satellite observations with physics-based indicators of atmospheric stability to evaluate atmospheric stability during dust storm events over Iraq. The proposed framework is based on the use of deep features extracted from the satellite imagery through a frozen EfficientNetB0 backbone, combined with indicators derived from the ERA5 pressure level data for the atmosphere, such as the Bulk Richardson Number (Bulk Ri), the Wind Shear (WS) and the Dry Air Index (DAI). The two branches were merged using a late fusion (0.75 physics/0.25 image) and each hour was classified into three atmospheric stability conditions: Relatively Stable, Moderately Unstable and Unstable. The overall hourly accuracy using a Leave-One-Event-Out (LOEO) cross-validation scheme, where each dust event was used for independent testing and no dust event was used for training, was 72.4%, with 81.2% accuracy for the dominant stability state and 92.2% correct assessment of the unstable condition time for the severe dust events. Inaccuracies were mainly (66%) in the conservative direction (more instability). Unstable atmospheric conditions were also found to be associated with all severe dust storms and coincided with higher wind shear, lower Bulk Ri values and higher thermodynamic variability. Moderate and light dust events were primarily associated with transitional and relatively stable atmospheric conditions, and differed between the various regions, primarily in Kirkuk and Nasiriyah. Correlation analysis showed that wind shear had the highest correlation with atmospheric instability (r = 0.92), followed by DAI (r = 0.90) and Bulk Ri (r = −0.75). In addition, the wind shear also increased significantly from light to severe dust events at all stations investigated, showing that wind shear is a critical factor for turbulent mixing, vertical momentum exchange and dust uplift processes. The results suggest wind shear is the leading dynamics mechanism for bulk-layer instability in Iraqi dust storms. The findings highlight the complementary benefit of using physics-based atmospheric indicators embedded with deep learning satellite image analysis. The HyMet-Fusion system can be used as a transferable method for observing wind-driven instability of the atmosphere and related dust hazards, which could be employed in boundary-layer meteorology, air-quality forecasting, aviation safety and environmental risk assessment in arid and semi-arid areas. Full article

Wind power ramp events (abrupt swings in output driven by frontal passages, sea-breeze transitions, and turbulence) are among the hardest problems for operators integrating renewables. Forecasting models are usually judged by aggregate error metrics (MAE, RMSE, overall directional accuracy) that average stable and ramp periods together, masking how a model behaves during the ramps that actually stress the grid. We address this on two fronts. First, we propose a regime-stratified evaluation that reports ramp event directional accuracy (ramp-DA) separately from stable-period accuracy and argue that ramp-DA should be a primary metric for grid-integration forecasting. Second, we build an ensemble of five regime-specialised sub-models trained with a direction-focused loss that penalises sign errors in the forecast power change, using only on-site SCADA wind speed and power. On 33,411 held-out samples from three onshore Greek farms, the ensemble reaches 76.5% ramp-DA, against 70.1% for a two-layer LSTM (+6.4 pp) and 74.3% and 74.1% for the PatchTST and iTransformer baselines. A strict leave-one-farm-out test retains 77.4% ramp-DA on a fully unseen farm. Overall directional accuracy rises 3.4 points, evidence that aggregate metrics understate the ramp-focused gain, while mean absolute error falls 19% compared to the LSTM (Diebold–Mariano p < 0.001). Full article

This study investigated the influence of a novel flow–through electro-Fenton (EF) reactor configuration on hydrodynamics and dye removal efficiency using Pt and boron-doped diamond (BDD) anodes coupled with a carbon–PTFE gas diffusion cathode. In this work, an innovative pre–pilot-scale reactor operating in recirculation mode was used to treat 100 mg L⁻¹ Calcon dye solutions in 0.05 mol L⁻¹ Na₂SO₄ at pH 3.0 under electrochemical oxidation (EO) with electrogenerated H₂O₂ (EO-H₂O₂), EF, and Photoelectro-Fenton (PEF) conditions. The effects of applied current density (30–90 mA cm⁻²) and Fe²⁺ concentration (0.25–0.75 mmol L⁻¹) were evaluated through color removal, TOC decay, and identification of oxidation intermediates. The hydrodynamic characterization results revealed flow conditions in a transitional region between laminar and turbulent flow (Re = 3.6 × 10³; Sh = 246). Comparing EF and EO-H₂O₂ processes, when Fe²⁺ was added to the solution, it significantly accelerated discoloration and, consequently, dye degradation in the former, while the absence of Fe²⁺ resulted in slower discoloration kinetics, reaching only 85.8% color removal after 180 min in the latter. The best performance was obtained with 0.50 mmol L⁻¹ Fe²⁺ in EF, achieving >98% discoloration. Among the investigated processes, PEF exhibited the highest mineralization efficiency. TOC removals using BDD as the anode efficiently reached high mineralization levels of 83.88%, 86.99%, and 93.38% for EO-H₂O₂, EF, and PEF, respectively, while Pt as the anode achieved 81.80%, 85.14%, and 91.63%. Overall, the BDD/PEF system showed the best degradation and mineralization performance. The proposed reactor was designed at the pre-pilot scale and incorporates vertical recirculation flow with hydrodynamic optimization, enabling efficient mass transfer and improved oxidant generation. The study provides practical insights into the reactor engineering aspects required for the future scale-up of EF technologies. Full article

Small multirotor UAVs frequently operate in crosswind conditions, yet the aerodynamic interaction between windward and leeward propeller pairs remains incompletely understood. This study investigates the performance of a quadcopter propeller system under lateral crosswind using steady-state RANS simulations with the Transition SST turbulence model, validated against wind tunnel measurements (thrust and torque deviations within $5.4\%$). A parametric matrix of five rotational speeds (8000–12,000 RPM) and six freestream velocities (0–10 m/s) is systematically examined. While thrust and power coefficients of all propellers increase monotonically with freestream velocity, the figure of merit ($FM$) of leeward propellers exhibits a previously unreported non-monotonic response: it decreases from hover, reaches a minimum near $6 \mathrm{m}/\mathrm{s}$, and partially recovers at higher velocities. Windward propellers show no such degradation. Our velocity contour and streamline analyses reveal that this behavior originates from windward wake ingestion into the leeward inflow region, which peaks at intermediate freestream velocities and is progressively alleviated as the stronger crosswind convects the wake downstream. The non-monotonic $FM$ response is therefore a direct consequence of the competition between wake-induced inflow degradation and freestream-driven aerodynamic augmentation. Our findings provide a systematic aerodynamic dataset essential for crosswind attitude control and propulsion system design in multirotor UAVs. Full article

Accurate prediction of NO emissions is important for the development of low-emission gas turbine combustors. This study evaluates several NO formation models for a 78 MW F-class gas turbine using a decoupled post-processing framework. Steady RANS simulations were performed with a partially premixed flamelet/PDF combustion model. Thermal NO, prompt NO, the N₂O intermediate pathway, and turbulence–chemistry interaction were assessed at 50% and 100% load. Thermal NO was the dominant pathway and showed strong load dependence. Using partial equilibrium for O radicals increased outlet NO by 16.46% at 50% load and 43.69% at 100% load. Including partial-equilibrium OH further increased NO by 8.67% at 50% load but had little effect at full load. Prompt NO remained on the order of 10⁻³ ppm. The N₂O pathway and turbulence–chemistry interaction also affected the prediction, especially at full load. The selected model was further compared with field measurements during load ramping and pilot-ratio variation. Most load-ramping predictions agreed with measurements within 18%. The results demonstrate the applicability of the proposed framework for engineering NO emission prediction while also identifying limitations under transitional operating conditions. Full article

Just energy transitions in the Global South unfold under conditions of institutional fragmentation, fiscal constraints, and high socio-ecological turbulence, making governance capacity a critical bottleneck for effective decarbonization and climate justice. This study proposes the Cybernetic Environmental Hub (CEH) framework, which extends the Viable System Model (VSM) to sustainability governance by integrating AIoT-enabled environmental monitoring, Early Warning Systems, decentralized data governance, and justice-centered institutional design. Methodologically, the article is primarily a conceptual framework paper accompanied by an illustrative single-site qualitative case study designed to probe the plausibility and diagnostic utility of the proposed architecture rather than to generate statistical generalization. The research combines theoretical development with participatory territorial diagnostics in the Caribbean Mining Corridor, where socio-ecological challenges were collected through participatory innovation workshops, thematically coded, and mapped onto the five VSM subsystems to identify systemic “variety gaps.” The analysis indicates that fragmented operational initiatives coexist with weak meta-systemic coordination, limiting adaptive capacity in energy transition processes. The CEH architecture is proposed to address these deficiencies by embedding AIoT sensing, federated learning, blockchain-based coordination, and Early Warning Systems within recursive governance structures and is grounded in a real cyber-physical deployment of around 90 monitoring stations across Albania, La Jagua de Ibirico and Algarrobo. The study also introduces a Territorial Governance Maturity Model (H1–H3) to diagnose systemic learning capacities and transition readiness across technological, institutional, data governance, and justice dimensions. The findings suggest that cybernetic environmental hubs may function as socio-technical infrastructures supporting coordinated, adaptive, and justice-centered energy transitions in the Global South, while comparative empirical evidence remains an agenda for future work. Full article

Inorganic scale deposition in crude oil–water transport trunklines is a formidable flow assurance challenge, uniquely exacerbated in extensive gathering networks where multiple production flowlines commingle multiphase fluids. As some fields experience progressively higher water cuts, the mixing of incompatible waters, characterized by diverse thermodynamic profiles and varying concentrations of scaling ions (Ca²⁺, Ba²⁺, Sr²⁺, ${\mathrm{SO}}_4^{2-}$, ${\mathrm{CO}}_3^{2-}$, etc.) triggers severe precipitation. This comprehensive literature review synthesizes seminal and contemporary studies to critically evaluate the state-of-the-art methodologies for assessing scaling risks in these intricate systems. Progressing chronologically and thematically, the analysis details the transition from static, bulk-fluid thermodynamic equilibrium calculations to dynamic, high-fidelity deterministic and probabilistic approaches. These advanced frameworks include Reactive Transport Modeling (RTM), Computational Fluid Dynamics (CFD), and Machine Learning (ML) architectures. Special emphasis is placed on the mathematical governing equations that dictate trunkline-specific phenomena: multi-stream commingling, non-isothermal gradients, probabilistic kinetic induction, and the profound impact of turbulent transport (turbophoresis) on crystal attachment and wall shear detachment. Finally, an integrated, multi-tier flow assurance workflow is proposed to guide future field-scale risk management and digital twin deployment. Full article

Pressure relief valves (PRVs) are key safety components in power transformers, and their discharge performance directly influences pressure mitigation during internal fault events. This study presents a density-based topology optimization approach to improve the internal flow passage of a transformer PRV. Optimization is carried out within a predefined design domain while preserving the original external geometry and functional constraints of the valve. Pressure drop is defined as the objective function, and the Brinkman penalization method is used to model the fluid–solid transition during the optimization process. Based on the optimized topology, a reconstructed valve configuration is developed and evaluated using transient computational fluid dynamics (CFD) simulations. The transient inlet pressure boundary condition is obtained from a 6 MJ transformer arcing experiment to ensure realistic operating conditions. The hydraulic performance of the baseline and optimized designs is compared in terms of cumulative discharged volume, pressure field evolution, velocity distribution, and turbulent kinetic energy. The results indicate that the optimized flow passage reduces internal flow resistance and improves flow organization within the valve chamber under transient conditions. Over a 19 ms discharge period, the cumulative discharged volume increases from 13.219 L to 13.601 L, corresponding to an improvement of approximately 3%. These findings demonstrate that topology optimization can effectively enhance the transient discharge performance of transformer PRVs and provide a basis for improving internal flow design in similar hydraulic safety devices. Full article

Ammonia is increasingly regarded as a carbon-free energy carrier for hard-to-electrify power sectors, including marine propulsion, heavy-duty transport, and distributed generation. Its direct use in internal combustion engines, however, is constrained by high ignition energy, low laminar flame speed, narrow flammability limits, slow low-temperature chemistry, and strong trade-offs among efficiency, nitrogen-containing emissions, and unburned ammonia slip. Hydrogen enrichment is one of the most effective routes for improving ammonia combustion reactivity, but it also introduces a multivariable control problem: hydrogen fraction, ammonia injection timing, injection mode, air-path dilution, ignition strategy, and aftertreatment operation are tightly coupled and strongly condition-dependent. This review synthesizes recent progress in ammonia–hydrogen and ammonia-based dual-fuel engine control from a control-oriented perspective. The discussion first summarizes application scenarios, nonlinear combustion-mode transitions, emission-formation pathways, and control-relevant metrics. It then compares actuator-level strategies, including ammonia injection timing and staging, port and direct injection, hydrogen energy-fraction scheduling, excess-air-ratio and EGR control, high-energy ignition, and turbulent jet ignition. Advanced optimization methods are further reviewed, with emphasis on model predictive control, control-oriented combustion and emission models, artificial-intelligence-based virtual sensors, and reinforcement-learning control. The analysis shows that the central challenge is no longer whether ammonia can burn in an engine, but how a controller can keep the system inside a narrow moving window bounded by misfire, knock, NO_x, N₂O, and NH₃ slip. Finally, future research priorities are proposed, including engine–aftertreatment co-optimization, physics-informed virtual sensing, digital-twin-assisted calibration, lightweight deployment on electronic control units, and robust control under fuel and aging uncertainty. Full article

Background: Diabetes mellitus is highly prevalent in Saudi Arabia and shapes individuals’ lived experiences within culturally and religiously embedded contexts. Although existing research has extensively examined biomedical, behavioral, and psychosocial dimensions of diabetes using quantitative and conventional qualitative approaches, there remains limited understanding of how individuals interpret, construct meaning, and reconstruct identity in relation to the illness over time. In particular, phenomenological inquiry is needed to access the lived, embodied, and existential dimensions of type 2 diabetes that are often not captured in existing outcome- or theme-focused qualitative studies. This study aimed to explore how Saudi adults with type 2 diabetes experience identity transitions, construct meaning, and undergo personal transformation. Methods: A hermeneutic phenomenological design informed by van Manen was employed. Twenty-seven Saudi adults with type 2 diabetes of at least one year’s duration were purposively recruited from a tertiary diabetes center in Riyadh. The sample size was guided by the principles of hermeneutic phenomenology, which prioritize depth, richness, and interpretive adequacy rather than numerical saturation. Recruitment and data collection continued until interpretive sufficiency was achieved, defined as the point at which no new experiential meanings or conceptual insights emerged across iterative analysis. Data were generated through in-depth, face-to-face interviews conducted in Arabic. Analysis followed an iterative interpretive process guided by the hermeneutic circle. Reflexivity, member checking, and peer review were used to enhance rigor. Results: Diabetes was experienced as a profound multidimensional disruption affecting embodiment, social roles, emotional well-being, and existential orientation. Participants described persistent fatigue and bodily limitation, shifting family roles and reduced social participation, emotional turbulence moving from shock to acceptance, and ongoing processes of meaning-making grounded in faith, gratitude, and strengthened family relationships. Conclusions: Living with diabetes involves an ongoing process of meaning-making and identity reconstruction that extends beyond clinical disease management to include emotional, social, and existential dimensions. These findings highlight the importance of culturally sensitive, person-centered care that addresses the lived experience of chronic illness within its sociocultural and spiritual context. Full article

Reducing aerodynamic drag on medium-duty freight trucks is essential for improving fuel efficiency; however, the relationship between local flow modification, aerodynamic loads, and propulsion-power demand has not yet been sufficiently quantified. This study evaluates the aerodynamic influence of a front deflector on a Chevrolet NQR 1015 box truck using steady RANS CFD with the k–ω SST turbulence model under zero-yaw conditions from 50 to 120 km/h. The numerical setup included near-wall inflation layers and mesh characterization, as well as grid-independence assessments based on C_D, and the Grid Convergence Index. The deflector produced consistent aerodynamic improvements, reducing average drag coefficient by 14.1%, while the average lift coefficient decreased by 73.5%. These aerodynamic changes reduced the average required propulsion power from 53.86 kW to 50.39 kW, corresponding to a 6.4% reduction, with a maximum saving of 8.1% at 120 km/h. Pressure, velocity, and pressure-coefficient C_P distributions indicate that the deflector promotes smoother flow redirection at the cab–box transition, attenuates suction peaks, and suggests lower pressure losses associated with the separated-flow and wake regions. Full article

To investigate the dynamic transmission of unsteady hydraulic excitation within pumped-storage units, this study presents a numerical investigation on the three-dimensional shafting vibrations of a pump-turbine based on a one-way transient fluid-structure interaction approach. To resolve the flow field, we adopt the shear stress transport (SST) k-ω turbulence model in conjunction with the Zwart-Gerber-Belamri (ZGB) cavitation model, and the combined numerical approach is first calibrated against experimental measurements. The results indicate that under the 70% partial load, an eccentric helical vortex rope develops inside the draft tube, generating intense low-frequency pressure pulsations that induce chaotic shaft orbits and distinct orbital drift at the turbine guide bearing. Conversely, near the optimal efficiency point (90% load), the vortex rope transitions into a slender, straight conical core, yielding minimum vibration magnitude and exceptional operational stability. At the 100% rated load, the vortex rope expands into a robust straight conical structure extending continuously into the elbow section. Stress analysis reveals that while equivalent stress concentrations consistently occur at the blade root regions, a reduction in the cavitation number at both 90% and 100% loads leads to a counterintuitive decline in blade surface peak stress values. Additionally, stiffness sensitivity analysis demonstrates that the relative change rates of the shaft runout are highly sensitive to the stiffness variations of the turbine guide bearing, where a stiffness reduction triggers a substantial runout growth of approximately 100% along the X- and Y-directions, whereas the variations in the upper and lower guide bearings exert extremely weak impacts. Full article

The weir–flume combination facility is a type of river flow-measurement structure consisting of a flow weir and a Crump weir, designed to integrate flow measurement and upstream backwater regulation, while incorporating a central flume intended to provide a potential passage for aquatic organisms. This study proposes a novel combined weir–flume structure and systematically validates its hydraulic performance through integrated physical experimentation and high-fidelity numerical simulation. Laboratory tests across a flow range of 5–79 L/s revealed longitudinal water surface profiles and Froude number (Fr) distributions. The study findings show that: (1) As the flow increases, the flow regime of the combination facility transitions from flume flow to weir flow, with the critical transition point at a relative water depth of 0.885. (2) The RNG k-ε turbulence model in Flow-3D software (v11.2, Flow Science, Inc., Santa Fe, NM, USA) effectively simulates the flow movement in the weir–flume combination facility, with water depth simulation results closely matching the measured values, and the maximum relative error not exceeding 5%. (3) The Fr and flow velocity in the weir–flume combination facility first increase and then decrease along the length, forming a large, thin water layer area downstream of the facility, where both Fr and flow velocity reach their maximum values. (4) Flow measurement formulas for flume flow and weir flow are obtained through data fitting, with relative errors between the calculated values and measured flow rates being less than 3%. The present study focuses on the hydraulic performance and flow measurement capability of the proposed facility. Although the structural configuration is intended to facilitate ecological passage, its ecological effectiveness was not evaluated and requires further investigation in future studies. Full article