Search Results (236)

Event cameras provide microsecond temporal resolution, high dynamic range, and low latency by asynchronously capturing per-pixel luminance changes, thereby introducing a novel sensing paradigm. These advantages render them well-suited for high-speed applications such as autonomous vehicles and dynamic environments. Nevertheless, the sparsity of event data and the absence of dense annotations are significant obstacles to supervised learning for motion segmentation from event streams. Domain adaptation is also challenging due to the considerable domain shift in intensity images. To address these challenges, we propose a two-phase cross-modality adaptation framework that translates motion segmentation knowledge from labeled RGB-flow data to unlabeled event streams. A dual-branch encoder extracts modality-specific motion and appearance features from RGB and optical flow in the source domain. Using reconstruction networks, event voxel grids are converted into pseudo-image and pseudo-flow modalities in the target domain. These modalities are subsequently re-encoded using frozen RGB-trained encoders. Multi-level consistency losses are implemented on features, predictions, and outputs to enforce domain alignment. Our design enables the model to acquire domain-invariant, semantically rich features through the use of shallow architectures, thereby reducing training costs and facilitating real-time inference with a lightweight prediction path. The proposed architecture, alongside the utilized hybrid loss function, effectively bridges the domain and modality gap. We evaluate our method on two challenging benchmarks: EVIMO2, which incorporates real-world dynamics, high-speed motion, illumination variation, and multiple independently moving objects; and MOD++, which features complex object dynamics, collisions, and dense 1kHz supervision in synthetic scenes. The proposed UDA framework achieves 83.1% and 79.4% accuracy on EVIMO2 and MOD++, respectively, outperforming existing state-of-the-art approaches, such as EV-Transfer and SHOT, by up to 3.6%. Additionally, it is lighter and faster and also delivers enhanced mIoU and F1 Score. Full article

To further investigate the collision process and tectonic regime transition between the North China (NCB) and South China Block (SCB), two magnetotelluric profiles were arranged across the Dabie Orogeny Belt (DOB) and eastern SCB. We then obtain the lithospheric resistivity models. The prominent feature revealed by our new model is an extensive conductive arc from the lower crust to the upper mantle, across the Jiangnan orogenic belt (JNOB) and the eastern Cathaysia Block (CAB). In addition, a huge resistor beneath the conductive arc is revealed, which is separated by a conductive wedge. Combining the heat flow and seismic tomographic imaging results, the conductors are to contain a large amount of hot material that present as the detachment layers (belts) controlled by the two subduction slabs. Considering multi-phase magmatism in the study area, new models suggest an intracontinental tectonic event in eastern CAB. Therefore, we propose a reliable tectonic process that occurred in the study area, including five stages: (1) an eastward intracontinental subduction and orogen carried out in CAB before the collision between SCB and NCB; (2) an extensional structural developed in CAB, following the subduction slab wrecking/sinking; (3) after the collision with NCB, the SCB crust/lithosphere thickened following the westward subduction of the Paleo-Pacific plate; (4) following the westward Yangtze slab sinking, the regional extension developed with the asthenosphere upwelling beneath SCB; (5) afterwards, the SCB was welded into one continent in a setting of westward compression. Full article

This study experimentally investigates the dynamic behavior and energy conversion characteristics of a single contaminated bubble (d_eq = 2.49–3.54 mm, Re_b = 470–830) rising near a vertical wall (S* = 1.41–2.02) in a linear shear flow (the conditions of average flow rate 0.1 m/s and shear rate 0.5 s⁻¹) using a vertical water tunnel and varying sodium dodecyl sulfate (SDS) concentrations (0–50 ppm) and bubble sizes (via needle nozzles). High-speed imaging with orthogonal shadowgraphy captures bubble trajectories, rotation, deformation, and oscillation modes (2, 0) and (2, 2), revealing that an increasing SDS concentration suppresses deformation and the inclination amplitude while enhancing the oscillation frequency, particularly for smaller bubbles. Velocity analysis shows that vertical components remain steady, whereas wall-normal and spanwise fluctuations diminish with surfactant concentration, indicating stabilized trajectories. Additional mass force coefficients are larger for bigger bubbles and decrease with contamination level. Energy analysis demonstrates that surface energy dominates the total energy budget, with vertical kinetic energy comprising over 70% of the total kinetic energy under high SDS concentrations. The results highlight strong scale dependence and Marangoni effects in controlling near-wall bubble motion and energy transfer, providing insights for optimizing gas–liquid two-phase flow processes in chemical and environmental engineering applications. Full article

This study addresses the characterization of two-phase flow phenomena in a microchannel heat sink designed to cool high-concentration photovoltaic cells. Two-phase flows can introduce instabilities that affect heat exchange efficiency, a challenge intensified by the small dimensions of microchannels. A single polydimethylsiloxane (PDMS) microchannel was fixed on a stainless steel sheet, heated by the Joule effect, which was cooled by the working fluid HFE 7100 as it undergoes phase change. Experiments were performed using two microchannel widths with a fixed height and length, testing two heat fluxes and three values of the Reynolds number, within the laminar flow regime. Temperature and pressure drop data were collected alongside high-speed and time- and space-resolved thermal images, enabling the observation of flow boiling patterns and the identification of instabilities. Enhanced surfaces with microcavities depict a positive effect of a regular pattern of microcavities on the surface, increasing the heat transfer coefficient by 34–279% and promoting a more stable flow with decreased pressure losses. Full article

In gas–liquid two-phase flows, diverging channels such as diffusers often develop low-pressure separation zones where gas can accumulate, hindering pressure recovery and reducing system performance. This issue is particularly critical in centrifugal pumps, where it leads to efficiency losses. Unlike pumps, diffusers without rotating components allow for more precise experimental studies. This research investigates a passive control method using upstream cross-flow steps to reduce gas accumulation in a horizontal diverging channel. Thin metallic sheets with toothed geometries of 2 mm, 5 mm, and 8 mm heights were installed upstream to interact with the flow. These features aim to enhance turbulence, break up larger gas pockets, and promote vertical bubble dispersion, all while minimizing additional flow separation. The diffuser was intentionally designed with an expanding angle to encourage flow separation and gas accumulation. The experiments covered various two-phase flow conditions (liquid Reynolds number 59,530–78,330; gas Reynolds number 3–9.25), and high-speed imaging captured detailed phase interactions. The results show that the steps significantly reduce gas accumulation, especially at higher water flow rates. These findings support the development of more accurate computational models and offer insights for optimizing centrifugal pump designs by minimizing gas buildup in separated flow regions. Full article

An in-depth analysis of the two-phase flow in a hydraulic braking pipeline can reveal its evolution process pertinent for designing and maintaining the hydraulic system. In this study, a high-speed camera examined the two-phase flow pattern and bubble characteristics in a hydraulic braking pipeline. Bubble flow pattern recognition, bubble segmentation, and bubble tracking were performed to analyze the bubble movement, including its behavior, distribution, velocity, and acceleration. The results indicate that the gas–liquid two-phase flow patterns in the hydraulic braking pipeline include bubbly, slug, plug, annular, and transient flows. Experiments reveal that bubbly flow is the most frequent, followed by slug, plug, and transient flows. However, plug and transient flows are unstable, while annular flow occurs at a wheel speed of 200 r/min. Bubbles predominantly appear in the upper section of the pipeline. Furthermore, large bubbles travel faster than small bubbles, whereas slug flow bubbles exhibit higher velocities than those in plug or transient flows. Full article

Gas–water two-phase flow in horizontal and inclined wells is significantly influenced by gravitational forces and spatial asymmetry around the wellbore, resulting in complex and variable flow patterns. Accurate measurement of water holdup is essential for analyzing phase distribution and understanding multiphase flow behavior. Water holdup imaging provides a valuable means for visualizing the spatial distribution and proportion of gas and water phases within the wellbore. In this study, air and tap water were used to simulate downhole gas and formation water, respectively. An array capacitance arraay tool (CAT) was employed to measure water holdup under varying total flow rates and water cuts in a horizontal well experimental setup. A total of 228 datasets were collected, and the measurements were processed in MATLAB (2020 version) using three interpolation algorithms: simple linear interpolation, inverse distance interpolation, and Lagrangian nonlinear interpolation. Water holdup across the wellbore cross-section was also calculated using arithmetic averaging and integration methods. The results obtained from the three imaging algorithms were compared with these reference values to evaluate accuracy and visualize imaging performance. The CAT demonstrated reliable measurement capabilities under low- to medium-flow conditions, accurately capturing fluid distribution. For stratified flow regimes, the linear interpolation algorithm provided the clearest depiction of the gas–water interface. Under low- to medium-flow rates with high water content, both inverse distance and Lagrangian methods produced more refined images of phase distribution. In dispersed flow conditions, the Lagrangian nonlinear interpolation algorithm delivered the highest accuracy, effectively capturing subtle variations within the complex flow field. Full article

This study employs Particle Image Velocimetry (PIV) technology to investigate the statistical properties and flow structures of the turbulent boundary layer over smooth walls and riblet walls with yaw angles of 0, ±30° in both clear water and liquid–solid two-phase flow fields. The results indicate that, compared to the smooth wall, streamwise riblet walls and 30° divergent riblet walls can reduce the boundary layer thickness, wall friction force, comprehensive turbulence intensity, and Reynolds stress, with the divergent riblet wall being more effective. In contrast, convergent riblet walls have the opposite effect. The addition of particles leads to an increase in boundary layer thickness and a reduction in wall friction resistance, primarily by reducing turbulence fluctuations and Reynolds stress in the logarithmic region of the turbulent boundary layer. Moreover, the two types of drag-reduction riblet walls can decrease the energy content ratio of near-wall streak structures and suppress their motion in the spanwise direction. Their impact on burst events is mainly characterized by a reduction in the number of ejection events and their contribution to Reynolds shear stress. In comparison, convergent riblet walls have the complete opposite effect and also enhance the intensity of burst events. The addition of particles can fragment streak structures and suppress the intensity and number of burst events, acting similarly on drag-reduction riblet walls and further strengthening their drag reduction characteristics. Full article

Gas–liquid two-phase flow is very common in fluid machinery and has complex multiphase flow characteristics. Under the gas-containing conditions, common issues in fluid machinery include the transport of liquid, bubble variations, and pressure drop characteristics; these can be analyzed using a simplified venturi tube. In order to investigate the influence of incoming gas on the gas–liquid flow, a venturi tube with the range of inlet gas volume fraction (IGVF) from 0 to 16% was used in this experiment. The development of a two-phase flow was recorded by using high-speed photography. Under different initial liquid flow rates and gas content conditions, the evolution of the two-phase flow was similar, with the main difference being the rate of evolution. The incoming gas mainly underwent a process from column shape to expansion and then to fragmentation passing through the venturi tube. In the experimental images, the projected area of the main bubble increased linearly with the increase in IGVF. Meanwhile, the transporting ability of the venturi tube was weakened due to the blockage caused by high gas content, especially when the IGVF exceeded 10%. The pressure drop characteristics indicated an increase in losses with the increase in gas content. Full article

This study presents a comprehensive numerical framework for Background-Oriented Schlieren (BOS) to systematically evaluate its performance and reconstructive capabilities under complex flow conditions. This framework integrates two stages: forward modeling, using ray tracing to simulate image degradation, and inverse processing, using optical flow and a conjugate gradient algorithm to extract displacements and reconstruct phase information. This method is first validated using turbulent flow fields in the Johns Hopkins Turbulence Database, where the reconstructed phase screens closely match the original data, with relative errors below 4% and structural similarity indices above 0.75 in all cases, providing a possible restoration method for degraded flow field images. It is then applied to shock wave fields with varying Mach numbers; this method achieves meaningful reconstruction at short ranges but fails under long-range imaging due to severe wavefront distortions. However, even in degraded conditions, the extracted optical flow fields preserve structural features correlated with the underlying shock patterns, indicating potential for BOS-based target recognition. These findings highlight both the capabilities and limitations of BOS and suggest new pathways for extending its use beyond traditional flow visualization. Full article

Hydraulic fracturing significantly impacts water production. This makes it crucial to determine whether its effects on formation water production are beneficial or detrimental in complex reservoir stimulations. This paper gives the influence that acts on pore structure variations and irreducible water transformation by hydraulic fracturing; by using NMR and Micro-CT, pore-throat reconfiguration in core samples induced fracturing. Two main pore variation types were identified from CT images. To analyze the gas–water flow mechanisms in pre-fracturing and post-fracturing reservoir conditions, we tested quantifying changes in irreducible water transforms into movable water saturation by using a triaxial in situ flow system, thereby elucidating the impact of the hydraulic fracture on irreducible water saturation. The experiments demonstrate that pore structures are significantly modified in terms of connectivity and diameter through hydraulic fracturing. During damage zone formation, 12.4–19.2% of small pores coalesce into larger pores through integration of isolated spaces. This variation enhances fluid mobility, transforms 1.38–11.61% of irreducible water, and decreases starting pressure gradients by 1 MPa/100 m to 0.1 MPa/100 m. Modified pore structure leads to the iso-permeability point shifting toward higher water saturation. The gas-phase relative permeability at irreducible water saturation is two times as high as that of the matrix sample. Fractured zones show a 20–23% conversion efficiency of irreducible to movable water. In addition, based on the results of experimental data, hydraulic fracturing increased water production by 3607 to 9163 m³. However, this effect is only maintained during the first 3 to 6 months post-fracture. These results quantify the transformation of irreducible water into movable water in hydraulic fracturing. This study provides key performance indicators for gas reservoir applications. Full article

This paper presents a control framework for the image tracking of two-wheeled self-balancing carts, with the objective of achieving precise tracking control. Exploiting the remarkable memory capacity of the Long Short-Term Memory (LSTM) neural network for sequence signals, the framework conducts image memory judgment and memorization, aiming to enhance control accuracy. After the training phase, comprehensive simulations and real-world experiments are carried out based on the established model to verify the effectiveness and practicality of the proposed control strategy. The system utilizes the TSL1401 linear array CCD lens to detect black tapes on the ground and identify and memorize surrounding images. Through the establishment of a continuous set of training sample points, the LSTM network is trained using Python and TensorFlow. This training process optimizes the network’s weights and generates weight files, which can be readily converted into machine code for physical implementation. Initially, the effectiveness of the control law is verified through simulating the symmetrical steering control of the two-wheeled cart. The simulation results demonstrate the validity of the proposed design method and its superior performance. Finally, a physical two-wheeled self-balancing cart is developed to further validate the feasibility of the framework. Experimental results confirm that this method is highly effective, demonstrating robust image tracking capabilities and optimal tracking performance. Full article

Oil–water relative permeability is essential for reservoir development and enhanced oil recovery (EOR). Traditional core displacement experiments assume static wettability, whereas in real reservoirs, wettability evolves over time due to waterflooding and rock–fluid interactions, significantly altering flow behavior. Existing numerical methods, including conventional lattice Boltzmann models (LBM), fail to account for these changes and lead to inaccurate predictions. This study integrates laboratory-measured contact angles into a time-dependent wettability-adjusted LBM framework, ensuring real-time wettability updates during simulation. Micro-CT imaging captures oil–water displacement and contact angle evolution at different flooding stages, which are incorporated into the Shan–Chen LBM model. Results show that neglecting the time-dependent wettability overestimates the residual oil saturation and underestimates the water-phase permeability. In contrast, our method reduces the residual oil saturation by up to 35% and expands the two-phase flow region by 15%, aligning closely with experimental observations. This approach enhances the accuracy of relative permeability modeling, providing a more reliable tool for optimizing waterflooding strategies and improving oil recovery efficiency. Full article

To address the temporal jitter with low segmentation accuracy and the lack of high-precision transformations for specific object classes in video generation, we propose the fish body pattern sync-style network for ornamental fish videos. This network innovatively integrates dynamic texture transfer with instance segmentation, adopting a two-stage processing architecture. First, high-precision video frame segmentation is performed using Mask2Former to eliminate background elements that do not participate in the style transfer process. Then, we introduce the wavelet-gated styling network, which reconstructs a multi-scale feature space via discrete wavelet transform, enhancing the granularity of multi-scale style features during the image generation phase. Additionally, we embed a convolutional block attention module within the residual modules, not only improving the realism of the generated images but also effectively reducing boundary artifacts in foreground objects. Furthermore, to mitigate the frame-to-frame jitter commonly observed in generated videos, we incorporate a contrastive coherence preserving loss into the training process of the style transfer network. This enhances the perceptual loss function, thereby preventing video flickering and ensuring improved temporal consistency. In real-world aquarium scenes, compared to state-of-the-art methods, FSSNet effectively preserves localized texture details in generated videos and achieves competitive SSIM and PSNR scores. Moreover, temporal consistency is significantly improved. The flow warping error index decreases to 1.412. We chose FNST (fast neural style transfer) as our baseline model and demonstrate improvements in both model parameter count and runtime efficiency. According to user preferences, 43.75% of participants preferred the dynamic effects generated by this method. Full article

Objective: Cerebral vascularization is made of the symmetrical arterial system, with muscular walls, and the venous system, more variable and dominated by sinuses and jugular veins. Factors like age and posture influence this network, complicating its study. Phase-contrast MRI is the gold standard for quantifying cerebral circulation. This study aimed to quantify the dynamics of the cerebral blood system using PC-MRI. Materials and Methods: Thirty-six healthy adults participated. Imaging was performed on a 3T MRI (Philips Achieva) in a supine position. Two slices were acquired: intracranial and extracranial. In-house software analyzed flow curves over a cardiac cycle. Each vessel’s contribution was evaluated. Results: Extracranial venous drainage was categorized as jugular-dominant, equivalent, or peripheral-dominant. A similar classification applied intracranially. Intracranial flows showed low variability (5–9%), while extracranial venous flows, especially in the internal jugular veins, had higher variability (17–21%). Some extracranial veins were absent. Conclusions: There is significant venous heterogeneity in the extracranial region. PC-MRI enables the quantification of cerebral dynamics. Full article