Search Results (364)

As the core equipment for efficient wastewater treatment, the internal structure of microporous aeration bioreactors directly determines the mass transfer efficiency and treatment performance. Based on Computational Fluid Dynamics (CFD) technology, this study explores the optimization mechanism of a Spherical Grid-Structured on the internal flow field of the reactor through a 3D numerical simulation system, aiming to improve the aeration efficiency and resource utilization. This study used a combination of experimental and numerical simulations to compare and analyze different configurations of the Spherical Grid-Structure. The simulation results show that the optimal equilibrium of the flow field inside the reactor is achieved when the diameter of the grid sphere is 2980 mm: the average flow velocity is increased by 22%, the uniformity of the pressure distribution is improved by 25%, and the peak turbulent kinetic energy is increased by 30%. Based on the Kalman vortex street theory, the periodic vortex induced by the grid structure refines the bubble size to 50–80 microns, improves the oxygen transfer efficiency by 20%, increases the spatial distribution uniformity of bubbles by 35%, and significantly reduces the dead zone volume from 28% to 16.8%, which is a decrease of 40%. This study reveals the quantitative relationship between the structural parameters of the grid and the flow field characteristics through a pure numerical simulation, which provides a theoretical basis and quantifiable optimization scheme for the structural design of the microporous aeration bioreactor, which is of great significance in promoting the development of low-energy and high-efficiency wastewater treatment technology. Full article

An Analog-to-Digital Converter (ADC) is an indispensable part of image sensor systems. This paper presents a silicon-based 13-bit 100 kS/s two-step single-slope analog-to-digital converter (TS-SS ADC) for infrared image sensors with a frame rate of 100 Hz. For the charge leakage and offset voltage issues inherent in conventional TS-SS ADC, a four-terminal comparator was employed to resolve the fine ramp voltage offset caused by charge redistribution in storage and parasitic capacitors. In addition, a current-steering digital-to-analog converter (DAC) was adopted to calibrate the voltage reference of the dynamic comparator and mitigate differential nonlinearity (DNL)/integral nonlinearity (INL). To eliminate quantization dead zones, a 1-bit redundancy was incorporated into the fine quantization circuit. Finally, the quantization scheme consisted of 7-bit coarse quantization followed by 7-bit fine quantization. The ADC was implemented using an SMIC 55 nm processSemiconductor Manufacturing International Corporation, Shanghai, China. The post-simulation results show that when the power supply is 3.3 V, the ADC achieves a quantization range of 1.3 V–3 V. Operating at a 100 kS/s sampling rate, the proposed ADC exhibits an effective number of bits (ENOBs) of 11.86, a spurious-free dynamic range (SFDR) of 97.45 dB, and a signal-to-noise-and-distortion ratio (SNDR) of 73.13 dB. The power consumption of the ADC was 22.18 mW. Full article

The Threshold Pressure Gradient (TPG) phenomenon exerts a profound influence on fluid flow dynamics in heavy oil reservoirs. However, the discrepancies between the True Threshold Pressure Gradient (TTPG) and Pseudo-Threshold Pressure Gradient (PTPG) significantly impede accurate residual oil evaluation and rational field development planning. This study proposes a dual-exponential conversion model that effectively bridges the discrepancy between TTPG and PTPG, achieving an average deviation of 12.77–17.89% between calculated and measured TTPG values. Nonlinear seepage simulations demonstrate that TTPG induces distinct flow barrier effects, driving residual oil accumulation within low-permeability interlayers and the formation of well-defined “dead oil zones.” In contrast, the linear approximation inherent in PTPG overestimates flow initiation resistance, resulting in a 47% reduction in recovery efficiency and widespread residual oil enrichment. By developing a TTPG–PTPG conversion model and incorporating genuine nonlinear seepage characteristics into simulations, this study effectively mitigates the systematic errors arising from the linear PTPG assumption, thereby providing a scientific basis for accurately predicting residual oil distribution and enhancing oil recovery efficiency. Full article

Lithium metal is a promising anode material for next-generation batteries due to its high specific capacity and low density. However, conventional mechanical processing methods are unsuitable due to lithium’s high reactivity and adhesion. Laser cutting offers a non-contact alternative, but photothermal effects can negatively impact the cutting quality and electrochemical performance. This study investigates the influence of pulse duration on the cutting-edge characteristics and electrochemical behavior of laser-cut 20 µm lithium metal on 10 µm copper foils using nanosecond and picosecond laser systems. It was demonstrated that shorter pulse durations significantly reduce the heat-affected zone (HAZ), resulting in improved cutting quality. Electrochemical tests in symmetric Li|Li cells revealed that laser-cut electrodes exhibit enhanced cycling stability compared with mechanically separated anodes, despite the presence of localized dead lithium “reservoirs”. While the overall pulse duration did not show a direct impact on ionic resistance, the characteristics of the cutting edge, particularly the extent of the HAZ, were found to influence the electrochemical performance. Full article

The role of on-site wastewater treatment (OSWT) is increasingly important for water reuse and local sustainability, but treatment efficiency is highly dependent on hydraulic behavior and mixing. This study used validated CFD simulations and tracer experiments to analyze flow patterns and mixing performance in a six-zone OSWT unit under different operational scenarios, including inflow, aeration, recirculation, combined mechanisms, and closed-loop operation without inflow. The results show that influent flow is essential for maintaining convective transport and system-wide momentum, while aeration and recirculation enhance local mixing, but cannot fully overcome geometric dead zones. The combined use of inflow, aeration, and recirculation achieved the highest mixing efficiency and minimized the dead volume, whereas scenarios lacking inflow exhibited severe stagnation and expanded dead zones. These findings highlight the need to integrate hydraulic interventions with thoughtful reactor design to ensure effective and resilient small-scale wastewater treatment systems. Full article

The continuous monitoring of forest vegetation conditions is of the utmost importance. The commonly used tools for assessing vegetation conditions are the normalized difference vegetation index (NDVI) and its successor—the enhanced vegetation index (EVI). In this study, the NDVI and EVI were coupled with the data on the number of dead trees removed during sanitation felling in an area of 13,780 km² during the period 2015–2022. In order to determine which satellite-borne index best represents the actual condition of vegetation in forests of the European temperate zone, the classes of the trend in changes in the NDVI and EVI were compared with the respective trends in the volume of dead trees, following the assumption that a positive trend in the spectral index values should be reflected by a negative trend in the volume of dead trees, and vice versa. The analyses were carried out for pixels within the all-species mask in the study area and for pixels representing individual tree species. NDVI is a good predictor of forest vegetation in the European temperate zone and is substantially better than EVI. Spatially, NDVI yields more pixels showing a negative slope for the trend in changes in the spectral index values, while EVI seems to overestimate the number of positive slopes. A larger number of negative slopes in the trend in changes in NDVI seems to agree with the increasing volume of dead trees in the analysed period. Comparing the detected trend class masks for spectral indices and the multi-annual course of dead trees, in 12 out of 16 cases, the slopes of the trend in changes in NDVI agree with the slopes of the trend in the volume of dead trees, while for EVI, this number is reduced to 9. In addition, NDVI reflects the condition of coniferous tree species, Scots pine and Norway spruce, substantially better. Full article

This paper presents a distributed adaptive formation control strategy for a multiple near-space vehicles (NSVs) system operating under unknown input constraints and external disturbances. In challenging near-space environments, the control system must address not only model uncertainties and parameter variations but also accommodate the input limitations of actuators. To address these challenges, we design an adaptive distributed formation control strategy for vehicle formation that relies exclusively on relative attitude information. This approach is grounded in the principles of angle rigidity formation theory, which has not previously been applied in the near-space vehicle domain. The aim of the adaptive formation control strategy is to maintain the desired formation shape for the near-space vehicles (NSVs) system with external disturbances, actuator dead zones, and saturation. In addition, neural networks are employed to approximate the inherent nonlinear uncertainties within the NSV models. An adaptive estimation technique is concurrently included to address parameter variations and to alleviate the impact of external disturbances, actuator dead zones, and saturation effects. Finally, a Lyapunov-based analysis is used to rigorously demonstrate the stability of the NSV formation system. The simulation results validate the effectiveness and robustness of the proposed control strategy in uncertain environments. Full article

The 6 February 2023 M_W 7.8 and M_W 7.6 earthquakes in southeastern Türkiye ruptured more than 400 km of the East Anatolian Fault Zone (EAFZ), producing one of the most destructive seismic sequences in recent history. Here, we integrate InSAR data, a new GNSS velocity field, and small-magnitude earthquakes to investigate the coseismic deformation, rupture geometry, and interseismic strain accumulation along the EAFZ. Using elastic dislocation modeling with a variable-strike, multi-segment fault geometry, we constrain the slip distribution of the mainshocks, showing improved fits to the surface displacement compared to the planar fault model. The M_W 7.8 event ruptured a number of fault segments over ~300 km, while the M_W 7.6 event activated a more localized fault system with a peak slip exceeding 15 m. We also model two moderate events (M_W 5.6 in 2020 and M_W 5.3 in 2022) along the southwestern part of the Pütürge segment—an area not ruptured during the 2020 or 2023 sequences. GNSS-derived strain-rate and locking depth estimates reveal strong interseismic coupling and significant strain accumulation in this region, suggesting the potential for a future large earthquake (M_W 6.6–7.1). Similarly, the Hatay region, at the southwestern termination of the 2023 rupture, shows a persistent strain accumulation and complex fault interactions involving the Dead Sea Fault and the Cyprus Arc. Our results demonstrate the importance of combining remote sensing and geodetic data to constrain fault kinematics, evaluate rupture segmentation, and assess the seismic hazard in tectonically active regions. Targeted monitoring at rupture terminations—such as the Pütürge and Hatay sectors—may be crucial for anticipating future large-magnitude earthquakes. Full article

Flexible manipulators are widely applied in many fields. Here, the control design for a simplified flexible manipulator model with nonlinear inputs and state constraints is studied. The impact of two inputs and disturbances on the system was considered. One torque input comes from the joint motor, and the other input force comes from the linkage actuator tip. The input constraints of a dead zone are applied to both inputs to the manipulator. To offset the effect of the nonlinear input, we first linearize the dead zone and convert it into a linear-input characteristic and a finite error value. Then, the adaptive rate is designed to compensate for the effects of the nonlinear input. For the state constraints, an adaptive controller is proposed based on a symmetric tangent-type barrier Lyapunov function which can operate under closer constraint conditions, and parameter tunability offers flexibility in balancing the constraints’ tightness and performance. The stability proof ensures that all states are within the given constraint range. The provided simulation results indicate that the system is not sensitive to the initial values, and when the initial values are taken to be between open intervals (−0.4, 0.34), this ensures the stability of the system and does not violate the constraint bounds. Full article

In this paper, a fixed-time control strategy based on neural networks is proposed for a space robot with an input dead zone. First, a model-based control method is proposed based on the fixed-time convergence framework. Due to internal errors and external environmental disturbances, the inertial parameters of dynamic models generally exhibit uncertainties, and model-based control methods may exhibit deviations in trajectory tracking. In order to counteract the adverse effects of uncertain inertial parameters on the system and ensure the stability of the control system, an adaptive learning control method based on neural networks is further proposed. To enhance the learning rate of neural networks and achieve the convergence of neural weights within a fixed time, a neural network update rate combined with virtual control rate is proposed. In addition, considering the issue of the joint input dead zone affecting the precision and stability of the space robot, a novel adaptive law is proposed in conjunction with system error signal feedback to mitigate adverse effects. According to the Lyapunov stability theory, the stability of the closed-loop system is proven, with the trajectory tracking error converging to a small neighborhood around zero. Finally, numerical simulation results demonstrate the effectiveness of the control algorithm. Full article

The electrolyte flow field plays a pivotal role in determining the electrochemical performance of aqueous AgO-Al batteries. However, traditional flow field structures often suffer from the formation of dead zones, leading to uneven mass transport and side reactions. In this study, a flow field optimization strategy incorporating dead-zone compensation is proposed, which identifies localized dead zones and implements structural corrections to enhance electrolyte distribution. Numerical simulations reveal improved flow uniformity and reduced concentration polarization, while experimental validation confirms enhanced battery performance under the optimized configuration. This work provides a generalizable approach for electrolyte flow field design that improves mass transfer and electrochemical efficiency, offering practical insights for the development of high-performance aqueous batteries. Full article

Digital transformation (DT) has become a crucial driver of competitiveness in the shipping industry. However, many small- and medium-sized enterprises (SMEs) encounter barriers that result in digital transformation dead zones (DTDZs), where digital initiatives stagnate or fail to achieve the expected outcomes. This study investigates the key factors contributing to digital stagnation specifically within Vietnamese shipping SMEs, adopting the lens of the dynamic capabilities theory (DCT)—a framework that emphasizes firms’ abilities to sense opportunities, seize them, and reconfigure resources to maintain competitiveness in rapidly evolving environments. The DCT provides a dynamic and process-oriented perspective on how organizations adapt to technological change by building flexible and integrative capabilities. Based on quantitative data collected from 588 respondents across the Vietnamese shipping sector, the study employed structural equation modeling (SEM) to empirically assess the relationships among critical digital transformation variables. The findings reveal that inadequate sensing capabilities and a lack of data analytics are the most significant barriers, limiting firms’ ability to identify and act on digital opportunities. Additionally, limited ecosystem collaboration and supply chain fragmentation further exacerbate digital inertia. While poor reconfiguration capabilities and weak seizing capabilities also contribute to digital stagnation, their effects are comparatively weaker. The study offers theoretical contributions by extending the DCT, the resource-based view (RBV), and the ecosystem theory to the maritime sector, emphasizing the interplay between organizational, technological, and external barriers. Practical implications highlight the need for strategic investments in data analytics, ecosystem collaboration, and adaptive leadership to overcome digital stagnation. Full article

In order to meet the demand for high-voltage architectures of 400 V and 800 V in electric vehicle systems, high-power DC-DC converters have become a key focus of research. The Four-Switch Buck–Boost converter has gained widespread application due to its wide voltage conversion range, consistent input and output polarity, and the capability of bidirectional power transfer. This paper focuses on the energy conversion requirements in high-voltage scenarios for electric vehicles, analyzing the working principle of this converter and typical control strategies. It summarizes the issues encountered under different control strategies and presents improvements. Hard-switching multi-mode control strategies aim to improve control algorithms and logic to mitigate large duty cycle variations and voltage gain discontinuities caused by dead zones. For control strategies based on controlling the inductor current to achieve soft-switching, the discussion mainly focuses on optimizing the implementation of soft-switching, reducing overall system losses, and improving the computation speed. Finally, the paper summarizes FSBB control strategies and outlines future directions, providing theoretical support for high-voltage fast charging and onboard power supplies in electric vehicles. Full article

In subtropical regions of China, the expansion of Moso bamboo has become increasingly prominent, resulting in massive mortality of original trees in adjacent forest stands. Significant changes have also occurred in the population characteristics and spatial distribution patterns of these native tree species. This study aims to examine the impacts of Moso bamboo (Phyllostachys edulis) expansion on the successional dynamics of coniferous and broad-leaved mixed forests. Three sample plots were successively set up in the transition zone from bamboo to conifer and broad-leaved forest, including conifer and broad-leaved mixed forest (CF), transition forest (TF), and Moso bamboo forest (MF); a total of 72 10 m × 10 m quadrats (24 per forest type) were included. The species composition, diameter class structure and distribution pattern of living stems and snags (dead standing stems) were studied. The results showed that during the late expansion phase of bamboo, the density of living stems and snags separately increased by 2234 stems·ha⁻¹ and 433 stems·ha⁻¹, basal area increments of 23.45 m²·ha⁻¹ and 7.81 m²·ha⁻¹. The individuals with large diameter in living stems and snags gradually decreased, and the distribution range of the diameter steps mainly narrowed to 10–15 cm. On the scale of 0–10 m, the spatial pattern of standing stems changed from random and weak aggregation distribution to strong aggregation distribution and then to weak aggregation and random distribution in the three stands, while the overall distribution of snags in the three stands was random. The spatial correlation between living stems and snags evolved from uncorrelated in CF, to significant positive correlation in TF, and then to positive correlation and uncorrelation in MF. These results indicated that the bamboo expansion accelerated the mortality rate of the original tree species, leading to the diversity of tree species decreased, the composition of diameter classes was simplified, the degree of stem aggregation increased, and intra- and inter-species competition became the main reasons for tree death. Full article

Tungsten Inert Gas (TIG) welding is a widespread welding process used in the industry for high-quality joints. However, this welding process suffers from lower productivity. Activated Tungsten Inert Gas (ATIG) is a variant of the TIG that aims to increase the depth penetration capability of conventional TIG welding. This is achieved by applying a thin coating of activating flux material onto the workpiece surface before welding. This work investigates the effect of the thermophysical properties of individual metallic oxide fluxes on 316L stainless steel weld morphology. Four levels of current intensity (120, 150, 180, 200 A) are considered. The weld speed up to 15 cm/min and arc length of 2 mm are maintained constant. Thirteen oxides were tested under various levels of current intensity in addition to multiple thermophysical properties combinations, and the depth penetration (D) and the aspect ratio (R) were recorded. This process has provided 52 combinations (13 oxides * 4 currents). Based on the numerical observations, linear and nonlinear models for describing the effect of the thermophysical parameters on the weld characteristics were tuned using a particle swarm optimization algorithm. While the linear model provided good prediction accuracy, the nonlinear exponential model outperformed the linear one for the depth yielding a mean absolute percentage error of 17%, a coefficient of determination of 0.8266, and a root mean square error of 0.9665 mm. The inverse optimization process, where the depth penetration ranged from 1.5 mm to 12 mm, thus covering a large spectrum of industries, the automotive, power plants, and construction industries, was solved to determine the envelopes’ lower and upper limits of optimal oxide thermophysical properties. The results that allowed the design of the fluxes to be used in advance were promising since they provided the oxide designer with the numerical ranges of the oxide components to achieve the targeted depths. Future directions of this work can be built around investigating additional nonlinear models, including saturation and dead-zone, to efficiently estimate the effect of the thermophysical properties on the welding process of other materials. Full article