Search Results (237)

To investigate the evolution of turbulent-structure scales in decelerating open-channel flow, this study uses a high-frequency particle image velocimetry system in combination with a 28 m high-precision variable-slope flume to conduct controlled flume experiments. The analysis includes cross-sectional specific energy, velocity profiles, turbulence intensity, Reynolds stress, cross-correlation, and power spectral density. The study examines the turbulent statistical characteristics of decelerating flow and the evolution of turbulent-structure scale distributions during streamwise development. The results show that the velocity profile within the decelerating-flow region generally follows a logarithmic distribution, whereas the outer-region velocity profile gradually deviates from the logarithmic law as water depth increases. Compared with uniform open-channel flow, decelerating flow exhibits significantly higher turbulence intensities and Reynolds-stress levels. During flow development, turbulent structures maintain stronger spatial coherence, with spatial correlation increasing as water depth increases. As the nonuniformity coefficient γ increases, the turbulent-structure scale distribution shifts from bimodal to unimodal. Across the measured sections, the dominant turbulent-structure scales range approximately from λ/H = 2.5 to 20, over the ranges Re_τ = 596–849 and γ = 1.2–2.8. During downstream development, turbulent kinetic energy increases progressively and is redistributed from large and small scales toward intermediate scales. These results provide new insight into turbulence-scale redistribution in decelerating open-channel flow. Full article

Accurate freeway Improvements in traffic state prediction accuracy and enhanced stability enable more proactive traffic control and demand management strategies, thereby reducing congestion spillover effects, unnecessary acceleration–deceleration cycles, and the resulting fuel consumption and emissions. Yet, this remains challenging due to the interplay between deterministic traffic flow mechanisms and stochastic disturbances. Purely data-driven models suffer from error accumulation under out-of-distribution conditions, while physics-based models lack flexibility in capturing nonlinear deviations. This paper proposes MDURP, a physics-constrained residual learning framework that reformulates prediction as a residual-space learning problem. A calibrated Cell Transmission Model generates a physically admissible baseline; deep learning models are then restricted to learning the residuals. Wavelet decomposition and GARCH volatility modeling address the multi-scale and heteroskedastic characteristics of these residuals. Experimental results demonstrate that MDURP consistently outperforms baseline models, reducing MAE by an average of 6.8%, RMSE by an average of 4%. The framework also suppresses long-term error accumulation, with MAPE escalation slowing from 0.79% to 0.58% per step. These gains confirm that anchoring deep learning within a physics-defined residual space enhances both accuracy and stability. Full article

The momentum transport and scale-dependent motion characteristics within vegetation canopies play a crucial role in shaping near-surface turbulent structures and exchange processes, yet the interactions among different turbulent scales and their statistical representations remain insufficiently understood. Based on a series of controlled wind tunnel experiments, this study identifies coherent turbulent structures using a phase-space algorithm constructed from streamwise velocity fluctuation u′, acceleration a, and jerk j, and compares transport efficiency (exuberance η). This study uses scale-wise (cut-off frequency) momentum flux contribution analysis, natural visibility graph (NVG), and large–small-scale amplitude modulation to examine transport and multiscale behaviors across different canopy densities, array layouts, and inflow conditions. Results show that canopy density (different C_d drag coefficient) is a primary factor governing transport efficiency. Under low-wind staggered configurations, increasing canopy density strengthens the contribution of low-frequency large-scale motions to total momentum flux. In contrast, high-wind aligned configurations intensify canopy-top shear, enhancing small-scale motions and thereby reducing the relative contribution of large-scale motions. NVG analysis further reveals that in high-density canopies, large-scale acceleration and deceleration events tend toward equilibrium, whereas deceleration events dominate consistently in low- and medium-density cases. Amplitude modulation results indicate that high-density cases exhibit highly consistent modulation behavior, followed by low-density cases, while medium-density cases display a pronounced height-dependent variation, characterized by a distinct modulation critical point. This study proposes a unified analytical framework integrating coherent structure detection, graph-theoretic analysis, multiscale transport characterization, and large–small-scale modulation, providing a comprehensive description of momentum transport and scale motions within canopy flows, and it offers new insight into the mechanisms governing complex vegetation canopy turbulence. Full article

This study develops an analytical description of the motion of dilute solid particles in the boundary layer of laminar horizontal flows subjected to weak transverse pulsations. The analysis is formulated for dilute spherical solid particles subjected to transverse velocity pulsations in a laminar boundary-layer flow. A coupled matrix representation of the governing equations is formulated, and closed-form solutions are obtained using Laplace transformation. The analytical expressions capture transient evolution, forced oscillations, resonance effects, and long-term behaviour for particles with different density ratios. Numerical evaluation shows that light particles migrate toward faster regions of the boundary layer and accelerate longitudinally, while heavy particles move toward slower layers and decelerate. Transverse pulsations generate oscillatory trajectories whose amplitude increases near resonance. Impulsive perturbations superimposed on the continuous motion lead to discontinuous transitions consistent with the linear matrix system. The results provide a unified physical interpretation of particle redistribution mechanisms in boundary layers and offer a compact analytical tool for dilute multiphase flow modelling. Full article

This study analyses the transition from traditional barrier-based toll collection to a free-flow tolling (FFT) system on a national motorway corridor. The aim is to quantify how FFT affects mobility, safety and environmental performance when physical toll plazas are replaced by overhead gantries. Operational data at toll barriers and booths are first characterised in terms of traffic volumes, queue events and accident frequency, and a set of Key Performance Indicators is defined to describe both mobility and environmental effects. Travel times are modelled for light and heavy vehicles, distinguishing between electronic toll collection and manual payment, while demand variations are estimated using elasticities with respect to travel time. Environmental impacts are assessed through an energy-based model of deceleration, queueing and acceleration combined with fuel-specific emission factors for CO₂-equivalent and PM₁₀. The results show that removing physical toll plazas reduces queues by about 79.5% and is expected to reduce accidents in toll areas by roughly 50%, with CO₂-equivalent emissions at toll locations decreasing by up to 80% for light vehicles and 85% for heavy vehicles, and corridor-wide emissions also being significantly reduced, even when induced demand is considered. A final application to a photovoltaic green island on a decommissioned toll plaza illustrates how FFT can be coupled with infrastructure reuse to support cost-effective decarbonisation. Full article

Lava flows represent complex thermofluid phenomena in which surface cooling leads to the formation of a solidified surface layer. Understanding the influence of such a surface layer on fluid flow is an important issue in lava flow modeling. It also shares essential characteristics with a wide range of engineering problems involving surface solidification. However, the role of plastic surface skin in controlling flow deceleration and stopping behavior has not been sufficiently clarified in existing models. In this study, two-dimensional smoothed particle hydrodynamics (SPH) simulations were conducted to investigate the influence of surface skin formation on lava flow dynamics. The temperature dependence of viscosity was introduced to reproduce a plastic surface skin. The skin was represented as a low-temperature, high-viscosity region. Comparisons with simulations without surface skin formation demonstrated that the surface skin exhibits a suppressive effect on the flow. This behavior was consistent with qualitative observations of flowing lava. It was also found that this surface skin caused the successive deceleration characteristic in Bingham fluids. As a result, both the flow velocity and the flowing distance are affected. These results suggest that accurate lava flow simulations require models that incorporate both surface skin effects and non-Newtonian behavior. Full article

To enhance the hydrothermal performance of micro pin fin heat sinks (MPFHSs), this paper proposes five MPFHSs with different streamwise pin fin height variation modes and experimentally and numerically compares their hydrothermal performance, including pressure drop, maximum and average temperatures, and comprehensive performance evaluation criteria. The results indicate that, taking the uniform PFs height (UH) design as a reference, the designs with linearly increasing streamwise PFs height (LIH) and increasing streamwise PFs height with decelerating growth rate (DIH) demonstrate lower heat sink temperatures. Conversely, the designs with linearly decreasing streamwise PFs height (LDH) and decreasing streamwise PFs height with accelerating reduction rate (ADH) result in higher heat sink temperature. In addition, the comprehensive performance of LDH and ADH outperforms that of UH at low inlet flow rates, while the DIH surpasses that of UH at higher flow rates. As the inlet flow rate increases from 0.02 L/min to 0.5 L/min, our numerical study shows that the comprehensive performance of LDH and ADH decreases by 14.9% and 6.2%, respectively, whereas that of LIH and DIH increases by 17.4% and 10.2%, respectively. This finding provides insights to improve the hydrothermal performance of MPFHS. Full article

The Lower North River (LNR) exhibits a distinctive anabranching pattern in the Pearl River Basin, China. However, research has predominantly focused on vertical channel adjustments relying on in situ measurements, while the large-scale spatiotemporal dynamics of the anabranching planform have received limited attention. To address this gap, this study quantified the evolution of the anabranching planform from 1990 to 2022 using remote sensing images, focusing on anabranching intensity and island morphology, and analyzed driving factors using hydrological observations. Results revealed three evolutionary phases driven by shifting dominance of human interventions. During the first phase (1990–2004), the LNR experienced a moderate decline in anabranching intensity and widespread shrinkage of river islands, primarily attributed to sediment starvation induced by upstream dams. In the second phase (2004–2013), the decline in anabranching intensity accelerated and the proportion of expanding islands increased, driven by unregulated sand mining and channel regulation. In the third phase (2013–2022), the rapid decline in anabranching intensity decelerated and the islands shifted from a shrinkage-dominated to a stable-dominated state following the implementation of strict mining management and the physical confinement imposed by engineering structures. These findings reveal distinct morphological responses of the LNR to flow–sediment regimes and anthropogenic physical interventions, offering insights into the sustainable management of large anabranching rivers worldwide in the Anthropocene. Full article

Accurately describing driver response mechanisms is fundamental to microscopic traffic modeling. Traditional car-following models typically assume a fixed reaction time, implying a temporal symmetry where drivers exhibit identical response characteristics during acceleration and deceleration. To address this limitation, this paper proposes a Delay Adaptive Car-following Model that incorporates an asymmetric dynamic delay function to capture the symmetry breaking in driving behavior. Calibrated using empirical trajectory data from the Next Generation Simulation program, the proposed model demonstrates superior accuracy over the conventional Full Velocity Difference Model by effectively reproducing the realistic phenomenon of sluggish acceleration and agile deceleration. Linear stability analysis and numerical simulations reveal that, unlike fixed symmetric delays which often induce instability, the asymmetric dynamic delay acts as a self-adaptive damper. This mechanism suppresses the amplification of disturbances and prevents the formation of stop-and-go waves. The results confirm that incorporating temporal symmetry breaking into delay mechanisms significantly enhances the robustness of traffic flow against oscillations. Full article

This paper introduces a biological surface that is resistant to erosion under liquid–solid two-phase flow. Numerical simulations are used to study the erosion of smooth and ribbed shells by particles. The results show that when the flow direction is perpendicular to the direction of the shell ribs, the total erosion rate of the ribbed shell is 29.08% lower than that of the smooth shell, and the impact velocity of particles with a diameter of 0.5 mm on the ribbed shell is 15.91% lower than that on the smooth shell. This phenomenon occurs because a low-velocity flow field is formed in the grooves of the ribbed shell, which causes the particles to decelerate for some time before impacting the shell. This ribbed structure may provide design ideas for equipment that is susceptible to erosion. Full article

Significant progress in autonomous vehicle (AV) development has been made over the years through advancements in artificial intelligence, sensor technology, and data processing; however, many challenges remain, particularly regarding road safety and the complexity of adapting these vehicles to certain traffic situations. As a result, many European countries are funding research projects and setting targets and strategic plans for autonomous mobility, while scientific research proposes establishing standards and design guidelines for adapting road infrastructure to new transportation trends. This review paper examines physical road infrastructure in the era of AVs and identifies potential modifications, considering the development of AVs during both the early and later stages of their introduction into mixed traffic flow. Accordingly, necessary road infrastructure adaptations and the main design parameters affecting road geometric design for AV operation are presented. The design parameters considered include stopping sight distance, vertical curve radii, straight sections, lanes, and others. Furthermore, potential changes in existing physical infrastructure are illustrated using the example of a deceleration lane. Whether it is new infrastructure or modifications to existing infrastructure, both are analyzed in terms of the proportion of AVs in the traffic flow. Full article

Reliable traffic simulations with high-quality results contribute to the understanding of the traffic system and effective planning. In this article, firstly, an existing cellular automata (CA) model is modified to perform a comprehensive analysis of the influence of key parameters on traffic flow and average velocity. The simulations are conducted with realistic parameter values under heterogeneous conditions. Based on a safety analysis, a novel adaptive acceleration capability is developed, allowing vehicles to accelerate or decelerate at the desired acceleration/deceleration rate depending on the current road conditions. Secondly, the reaction time parameter is introduced into the model to study its impact on traffic under homogeneous and heterogeneous conditions. Thirdly, the model can simulate traffic flow according to different maximum velocities. Additionally, the influence of the maximum acceleration rate on traffic is studied. The results show that the maximum traffic flow at a maximum velocity of 60 km/h and a reaction time of 1 s is 2198 vehicles/h at a density of 0.29 vehicle/cell in adaptive acceleration mode. Generally, the adaptive acceleration capability increases traffic flow by up to 30% at densities of less than 0.7 vehicle/cell and even more at higher densities. Similarly, a 0.2 s lower reaction time increases traffic flow by up to 40%. At a maximum velocity of 110 km/h, the maximum traffic flow is 23% higher than at 50 km/h. However, the maximum velocity has little effect on traffic flow at higher densities. The maximum acceleration rate has a limited impact on traffic flow. Full article

Understanding the transient flow phenomena accompanying projectile discharge is essential for improving the safety, efficiency, and predictability of small-scale ballistic systems. Despite extensive numerical studies on muzzle flows and shock formation, experimental visualization and quantitative data on the coupling between pressure waves, jet structures, and projectile motion remain limited. This work addresses this gap by employing high-speed schlieren imaging and schlieren image velocimetry (SIV) to investigate the near-field aerodynamics of an airsoft-type projectile propelled by a CO₂ jet. Three optical configurations were analyzed—a Toepler single-mirror system, a Z-type without knife edge, and a Z-type with knife edge—to assess their sensitivity and suitability for resolving acoustic and turbulent features. The measured velocity of concentric pressure waves (≈355 m/s) agrees with the theoretical local speed of sound, validating the optical calibration. Projectile tracking yielded a mean speed of 71 ± 1.6 m/s, with drag and kinetic energy analyses confirming significant near-muzzle deceleration due to jet–projectile interaction. The SIV analysis provided additional insight into the convection velocity of coherent jet structures (≈75 m/s), tangent velocity fluctuations (±0.8 m/s), and vorticity distribution along the jet boundary. The results demonstrate that even compact schlieren setups, when coupled with quantitative image analysis, can capture the essential dynamics of unsteady compressible flows, providing a foundation for future diagnostic development and modeling of projectile–jet interactions. Full article

To investigate the flow-field characteristics of a submerged pre-mixed abrasive water jet impinging on a wall, a physical model of the conical–cylindrical nozzle and computation domain of a submerged pre-mixed abrasive-water-jet flow field were established. Based on the software of FLUENT 2022R2, numerical simulation of the solid–liquid two-phase flow characteristics of the submerged pre-mixed abrasive water jet impinging on a wall was conducted using the DPM particle trajectory model and the realizable $k–\epsilon$ turbulence model. The simulation results indicate that a “water cushion layer” forms when the submerged pre-mixed abrasive water jet impinges on a wall. Tilting the nozzle appropriately facilitates the rapid dispersion of water and abrasive particles, which is beneficial for cutting. The axial-jet velocity increases rapidly in the convergent section of the nozzle, continues to accelerate over a certain distance after entering the cylindrical section, reaches its maximum value inside the nozzle, and then decelerates to a steady value before exiting the nozzle. In addition, the standoff distance has minimal impact on the flow-field characteristic inside the nozzle. When impinging on a wall surface, rapid decay of axial-jet velocity generates significant stagnation pressure. The stagnation pressure decreases with increasing standoff distance for different standoff-distance models. Considering the effects of standoff distance on jet velocity and abrasive particle dynamics, a standoff distance of 5 mm is determined to be optimal for submerged pre-mixed abrasive-water-jet pipe-cutting operations. When the submergence depth is less than 100 m, its effect on the flow-field characteristics of a submerged pre-mixed abrasive water jet impinging on a wall surface remains minimal. For underwater oil pipelines operating at depths not exceeding 100 m, the influence of submergence depth can be disregarded during cutting operations. Full article

It is of great significance to construct a networked energy-saving driving strategy method and application framework to solve the problems of traffic disorder, speed fluctuations, and high energy consumption caused by frequent acceleration, deceleration, and lane changing of vehicles in road sections with variable traffic flow. Considering the mixed traffic scenario where autonomous vehicles and manually driven vehicles interact and infiltrate, a hybrid traffic flow vehicle energy-saving driving model was established, and the Dueling Double Deep Q-Network (D3QN) was used to optimize and solve the energy-saving driving model; Selecting Qingdao urban intersections as application scenarios, energy-saving driving strategy application facilities were constructed in simulation experiments to carry out simulation verification of energy-saving driving strategies for mixed traffic flow in the context of vehicle networking. The simulation results show that in different scenarios with different proportions of CAVs, the energy-saving strategy based on D3QN deep reinforcement learning algorithm can achieve fuel savings of 8.41%~6.67% compared to conventional strategies. Compared with the ordinary reinforcement learning algorithm Q-learning, its fuel saving rate is increased by 1.94%~1.5%, and the energy-saving effect becomes more significant with the increase of traffic density; From the perspective of dynamic characteristics, the speed stability under the control of D3QN algorithm is superior to Q-learning algorithm, and significantly better than conventional strategies, further highlighting the comprehensive advantages of D3QN algorithm in optimizing traffic flow status and energy consumption control. The energy-saving driving strategy in the networked environment can reduce fuel consumption caused by speed fluctuations and traffic flow frequency disturbances, and optimize the stability of traffic flow operation. Full article