To address the performance degradation of a double linear inverted pendulum under simultaneous parameter perturbations and external disturbances,an energy-optimization-based composite control strategy was proposed.The dynamic model was firstly established using the Lagrange method.Then,the LQR weight matrices were optimized by minimizing the state-energy sensitivity integral,and the minimum energy gain was corrected by combining the terminal state deviations caused by parameter perturbations.Finally,feedforward compensation was integrated with an extended state observer to construct a composite controller based on adjoint function energy optimization and feedforward compensation(AJFC).The results show that,under about 10%structural parameter perturbations,relatively large friction uncertainty and an external input disturbance of 1 m/s,the AJFF controller reduces the second-pendulum angle by about 87.6%and the cart steady-state displacement deviation by about 89.0%compared with the nominal LQR controller,while keeping the control input energy nearly unchanged;Compared with the sliding mode controller,it achieves better overall performance in cart displacement,pendulum-angle dynamic error and steady-state accuracy;Further±30%interval parameter perturbation analysis show that the system settling time is always maintained within the range of 3～5 s,and both the settling time and ITAE index are superior to those of the nominal LQR controller.The proposed method featuring a clear structure can effectively suppress external disturbances,and is easily engineering implementated,which provides some reference for the anti-disturbance control of similar underactuated systems.
To address the limitations of traditional polyacrylonitrile（PAN）-based photocatalysts, particularly their low specific surface area and the high recombination rate of photogenerated charge carriers that adversely affect photocatalytic activity, PAN was synthesized by combining a template method with bulk polymerization, followed by thermal treatment to obtain high-temperature cyclized polyacrylonitrile(HCPAN) with a porous structure. Fourier transform infrared spectroscopy(FTIR), Raman, X-ray photoelectron spectroscopy(XPS), scanning electron microscope(SEM), and BET were employed to characterize the chemical composition, structure, and morphology of the materials. The photoelectric properties were further analyzed by ultraviolet-visible diffuse reflectance spectra(UV-vis DRS), fluorescence spectrometer, and electrochemical impedance spectroscopy. The photocatalytic performance of HCPAN was evaluated through photocatalytic hydrogen evolution from water splitting, and the corresponding catalytic mechanism was investigated. The results show that the conjugation degree of HCPAN increases with increasing heat-treatment temperature. When the treatment temperature reaches 700 ℃, HCPAN-700 exhibits uniformly distributed pores and a high specific surface area of 1 032.33 m2/g, which facilitates the efficient exposure of catalytic active sites. Under irradiation, the hydrogen evolution rate reaches 102.8 μmol/（g ·h）.The porous conjugated framework enhances the migration efficiency of photogenerated charge carriers,which provides reference for the rational design of highly efficient PAN-based photocatalysts.
To address the insufficient stability of amorphous alloys during long-term oxygen evolution reaction(OER) processes, this study integrated the compositional design concept of high-entropy alloys into the material development of conventional amorphous alloys to enhance their catalytic durability. By leveraging the high-entropy effect of amorphous alloys, the electrocatalytic OER performance of Fe50Ni10Co10Mo10P10C5B5 high-entropy amorphous alloy wires was systematically evaluated. The surface structure was regulated through an electrochemical dealloying approach, which significantly improved the catalytic activity of the material. The results indicate that after electrochemical dealloying in 0.5 mol/L sulfuric acid(H2SO4) for 1 h, the high-entropy amorphous alloy wire exhibits an OER overpotential of only 241 mV and a Tafel slope of 48.1 mV/dec in 1 mol/L potassium hydroxide(KOH) solution at a current density of 10 mA/cm2. Moreover, after prolonged electrochemical operation(>242 h), the OER performance shows no significant degradation. The high-entropy amorphous alloy exhibits excellent catalytic activity and long-term stability in alkaline media, which is primarily attributed to the synergistic stabilization effect arising from the highly active surface of the amorphous structure and the configurational entropy associated with the multi-principal-element composition. This research can provide reference for the development of highly active and stable high-entropy amorphous alloy catalysts.
To improve the organic acid yield and substrate conversion efficiency in the fed-batch fermentation system of Bacillus megaterium, this study optimized the medium components and fermentation process control conditions using shake flasks and a 5 L bioreactor. An oxygen supply control strategy was guided by the quantitative oxygen uptake rate(OUR) and an optimal pH regulator composition was established for the fermentation process. The results show that the main factors affecting organic acid yield and substrate conversion efficiency are carbon source, MnSO4·H2O, pH value, oxygen supply level, and pH regulator composition. The optimal fermentation conditions are determined as follows:glucose as the carbon source, addition of 0.1 g/L MnSO4·H2O, pH controlled at 5.5 in a 5 L fermenter, moderate oxygen supply regulated by OUR feedback, and a mixture of NaOH and ammonia water at a ratio of 8∶2 as the pH regulator. Under these optimized conditions, the maximum organic acid yield reaches 165.61 g/L, and the glucose conversion rate reaches 50.41%. These results can effectively enhance the organic acid production efficiency and substrate conversion rate, providing reliable technical support for industrial scale-up production.
To address the surface icing problems of wind turbine blades and power transmission lines, a renewable flexible photothermal-electrothermal superhydrophobic coating was developed using spraying methods. Firstly, durable flexible sandpaper was employed as the micro-scale rough layer. Secondly, a silicone-based adhesive was used to fix the electrothermal layer between the micro-scale rough layer and a flexible silicone substrate. Finally, a photothermal superhydrophobic material was sprayed to complete the coating preparation. The results show that the coating had a contact angle of 152.78° and a sliding angle of 2.03°, with a light absorption rate as high as 96.6%. At a light intensity of 1 kW/m2, the coating surface temperature rises to 70.1 ℃ within 750 s, and a 3.0 mm thick ice layer is completely removed within 1 577 s. At an applied voltage of 6 V, the equilibrium temperature of the coating reaches 76.6 ℃, achieving complete removal of the 3.0 mm thick ice layer in 678 s. The coating demonstrates excellent stability, deformation resistance, and renewability. It can effectively inhibit surface icing and reduce ice accumulation, providing technical support for anti-icing and deicing applications in power systems.
To meet the requirements of real-time traffic cone detection and three-dimensional localization in construction and testing scenarios involving traffic cones, and to alleviate false positives and missed detections under complex illumination and occlusion conditions, this paper proposed a traffic cone recognition and localization method based on YOLOv5 and RGB-D fusion. First, 863 cone images featuring diverse lighting, viewing angles, and backgrounds were collected and annotated, and divided into training and validation sets in an 8∶2 ratio. Through data augmentation, hyperparameter tuning, and an early stopping strategy, the optimal model weights were obtained. Next, the trained model was deployed on an Intel RealSense D435 camera, achieving synchronized acquisition and spatial alignment of RGB and depth frames. Finally, depth information was extracted from the center region of the detection bounding box and combined with camera intrinsic parameters for back-projection to estimate 3D coordinates. Experimental results indicate that the proposed method has high detection accuracy (Precision≈99.8%, Recall≈99.6%, and mAP@0.5≈99.5%), with a processing speed of approximately 26 FPS (≈37 ms per frame), an average localization error of less than 5 cm. The method maintains stable performance under challenging conditions such as strong glare, shadows, and partial occlusion. This method integrates 2D detection and 3D localization of traffic cones, ensuring high detection accuracy while balancing real-time performance and localization precision. It can provide reference for traffic cone perception.
To address the industry pain points of insufficient research on flight allocation optimization for airport baggage sorting resources and low solving efficiency for large-scale problems, a bi-objective mixed-integer programming model was constructed to minimize resource occupation and total idle time. Firstly, it adopted a penalty function to transform the multi-objective problem into a single-objective one, and accurately depicted practical constraints including continuous resource occupation for transfer flights and task time conflicts. Next, given the NP-hard nature of the model, an improved multi-objective tabu search algorithm was designed, which used customized encoding, heuristic initial solution generation and random traversal neighborhood search strategy. Finally, parameter optimization was completed combing with orthogonal experiments. Verification on small-scale test cases shows that the model reduces the total idle time of resources by 24.2% and 17.1%， respectively. Accurate and efficient, the model and algorithm can directly guide the scheduling of airport baggage sorting resources, significantly improve resource utilization and reduce operating costs, and also provide a methodological reference for resource optimization in other operational links of airports.
To solve the problem of excessive ethanol emissions from the fermentation off-gas in fuel ethanol production, a spherical composite adsorbent MIL-100 (Fe) @PAA-TEPA was scaled up from the milligram to kilogram level by optimizing the preparation process under normal temperature and pressure, which was applied to the adsorption separation of ethanol from the fermentation off-gas. The results show that within the confined spaces of amine-functionalized polyacrylate porous microspheres(PAA-TEPA), the precursor of MIL-100(Fe) undergoes heterogeneous nucleation and in situ crystallization growth, and MIL-100(Fe) crystals are uniformly anchored inside PAA-TEPA microspheres, with a particle size reduced to about 55% of that of MIL-100(Fe) powder crystals; This structural refinement increases the number of active adsorption sites and shortens the diffusion distance, thereby enhancing both the thermodynamic and kinetic performance of ethanol adsorption. The double-tower adsorption separation process is achieved after 20 cycles of normal temperature adsorption and hot air desorption, ethanol adsorption capacity retention rate of composite adsorbent is 95% in simulated fuel ethanol fermentation off-gas, demonstrating its good cycle stability and suitable for large-scale production and application, which provides technical support for the standard-compliant emission of ethanol in fermentation off-gas.
In view of the problem that the current hydrogel materials need to rely on chemical crosslinking agents to make up for their insufficient mechanical properties in the biomedical field, silk fibroin(SF) and hyaluronic acid were modified to construct a material system that can form hydrogels without external crosslinking agents. Firstly, polyethyleneimine(PEI) was used for amino(—NH2) grafting modification of SF, and sodium periodate（NaIO4）was used to oxidize sodium hyaluronate(SH) to obtain aldehyde products.Then, the modified cationic silk fibroin(CSF) and oxidized sodium hyaluronate(OSH) were blended to form dynamic imine bond through Schiff base reaction, which made the hydrogel formed injectable. Finally,the influence of the volume ratio of CSF to OSH on the gelling time, morphology, chemical structure, mechanical properties and rheological properties of hydrogels was systematically studied. The results show that when the volume ratio of CSF to OSH is 1∶2, the hydrogel exhibits a short gelation time(148±9)s, the maximum storage modulus(354 Pa), a uniform pore structure, and favorable injectability.This system does not require chemical cross-linking agents and provides a theoretical reference for the application of SF injectable hydrogels in the biomedical field.
Chemical recycling provides a key route for the closed-loop circularity and high-value utilization of waste polyethylene terephthalate(PET), which presents inherent degradation challenges. Based on the analysis of the reaction mechanisms and process characteristics of major depolymerization pathways such as hydrolysis, alcoholysis, and aminolysis, the core bottlenecks of each technical route were compared, including catalyst cost and efficiency, feedstock adaptability, energy consumption, and product separation and purification. Furthermore, the mechanisms and application potential of emerging auxiliary technologies like ionic liquids, microwave assistance, biocatalysis, electrocatalysis and photocatalysis were summarized. A systematic assessment of different technological pathways was conducted by integrating techno-economic analysis(TEA) and life cycle assessment(LCA). The PET chemical recycling technology has evolved into a diversified framework. Alcoholysis has been relatively mature and achieved preliminary industrial implementation. However, large-scale development still faces multiple challenges. Future development should focus on the synergistic integration of technologies, rational design of catalytic systems, and tighter linkage with upstream polymerization processes, so as to promote efficient, green, and closed-loop recycling of waste polyester resources.
To investigate the coupled dynamic responses of the permeable asphalt pavement system under random vehicle loads,an analytical solution method based on the superposition principle was proposed.Firstly,a random vehicle load was obtained based on a 1/4 vehicle model under pavement roughness excitation,and a multi-layer permeable asphalt pavement model was established according to Biot's poroelasticity theory.Secondly,the governing equations were transformed into an orthogonal vector function coordinate system using the Fourier-Bessel series(FBS)method.Combined with the dual variable and position(DVP)method,the interlayer transfer relationships of the multi-layer permeable asphalt pavement were derived.Finally,the random vehicle load was equivalent to a circular random load input into the model,and analytical solutions for responses such as displacement,stress,and pore water pressure were obtained through superposition calculation.The results show that the proposed method exhibits favorable computational stability and low time consumption,with the analytical solutions showing high agreement with existing numerical examples.Pavement roughness,vehicle speed,and pavement structural permeability have significant impacts on the dynamic responses of the permeable asphalt pavement structure,which provides theoretical reference for asphalt pavement structural design,maintenance,and service life extension.
To evaluate the carbon emission issue during the production process of needle-punched geotextiles, S factory was taken as the research subject. A carbon footprint model for the production process of needle-punched geotextiles was constructed based on the life cycle assessment (LCA) method to calculate the carbon emissions in stages such as raw material usage, raw material transportation, production manufacturing, and auxiliary equipment operation. Through local sensitivity analysis and global sensitivity analysis, the key influencing factors of the carbon footprint were identified. Combined with the uncertainty assessment results of the Monte Carlo simulation, an optimized path for energy conservation and emission reduction was ultimately proposed. The research results show that for every ton of needle-punched geotextiles produced by S factory, the total carbon footprint of the production process is 4 374.61 kgCO2, with the highest proportion of raw material usage stage, which is the core focus of carbon reduction. The Monte Carlo simulation results also verify that the carbon footprint falls within the 95% confidence interval, confirming the reliability of the model results. The research findings can provide scientific basis for the carbon emission management of needle-punched geotextile production enterprises and facilitate the green and low-carbon transformation of the industry.
To address the decline in pedestrian detection accuracy caused by complex scenarios such as illumination variations, viewing angles, background interference and small pedestrian targets, which often lead to false positives and missed detections, a pedestrian detection model, YOLOv11-CREP, was proposed based on an improved YOLOv11n. Firstly, CSPDConv, which was formed by integrating standard convolution(Conv) with space-to-depth convolution(SPDConv), was introduced to reduce information loss and enhance critical feature extraction. Secondly, a new RepNCSPELAN4-GC module was proposed, which incorporates GhostConv to optimize the RepNCSPELAN4 module, reducing its parameter count. The improved RepNCSPELAN4-GC module was then used to partially replace the C3k2 modules in the Neck layer. Next, efficient multi-scale attention(EMAttention) and parallel network attention(ParNetAttention) were fused into a new EMPAttention module to enhance the detection ability of the model for small target pedestrians. Finally, considering the characteristics of small target pedestrains and occluded targets, a small-target detection head P2 was added to further improve the model’s recognition capability for small targets. The experiments show that compared with the original YOLOv11n model, YOLOv11-CREP improves the mean average precision(mAP) by 4.6 percentage points at an IoU threshold of 0.5, reaching 95.3%. When evaluated over the IoU range of 0.5 to 0.95, its mAP increases by 9.0 percentage points, reaching 70.2%. The proposed model achieves a balance between high detection performance and real-time requirements, effectively enhancing pedestrian detection performance in complex scenarios. It provides valuable references for modeling pedestrian detection tasks.
To address the limited 3D structural perception and insufficient feature discrimination in traditional welding joint classification and lack-of-fusion detection methods, this study proposed a 3D point cloud detection network that integrated geometric structure modeling with an attention mechanism, termed CA-PnPNet. First, the network was built upon the PointNet++ framework, in which a point neighborhood processing in 3D(PnP3D) was integrated into multiple feature extraction stages to strengthen the modeling of local spatial geometric relationships. In addition, a channel attention module (CAM) was incorporated to adaptively emphasize key features by capturing semantic dependencies across channels. Finally, the collaborative integration of these two modules at different feature layers enabled unified enhancement of both local point cloud geometric representation and semantic feature expression, resulting in more comprehensive 3D structural characterization. To validate the effectiveness of the method, multiple sets of comparative experiments were conducted. The results demonstrate that CA-PnPNet achieves an accuracy of 97.7% in the welding point cloud classification task, outperforming the baseline model by 1.9%, while improving the inference speed from 33.3 FPS to 36.1 FPS. These results validate the superior accuracy and real-time performance of the proposed method. Overall, CA-PnPNet provides an effective technical reference for intelligent detection and industrial quality monitoring of complex welded structures.
To address the limitations of the Chameleon algorithm in terms of parameter sensitivity, noise robustness, and computational efficiency, this study proposed a statistical-MST integrated hierarchical clustering algorithm(SHCA) based on the minimum spanning tree and statistical features. The minimum spanning tree was used to construct a sparse graph, eliminating manual parameter intervention, and the global optimality of the minimum spanning tree was used to avoid false cross cluster connections. The dynamic statistical merging strategy was designed to filter the noise combined with the local distance threshold, and the sub clusters were merged iteratively through the inter cluster connectivity test to ensure the intra cluster compactness and inter cluster separation. Experiment on 20 synthetic datasets and 10 real-world datasets was conducted. The result shows that the proposed SHCA algorithm outperforms existing methods in clustering performance; In cases where performance degradation is observed on certain datasets,the analysis reveals that manifold overlap is the primary contributing factor. Overall, SHCA significantly enhances clustering accuracy and result stability, providing some reference for subsequent research on clustering of large-scale and complex manifold data.
To suppress the formation of brittle magnesium-aluminum intermetallic compounds（IMCs）in the welding joints of magnesium-aluminum dissimilar metals and enhance the joint performance, a friction stir welding (FSW) technique was adopted and copper foil was used as an interlayer metal to weld 7075-T6 aluminum alloy and AZ31B magnesium alloy. A comprehensive suite of analytical techniques, including microstructural characterization, energy-dispersive spectrometer（EDS）, X-ray diffractometer（XRD）, hardness testing, and shear testing were employed to systematically investigate the microstructural evolution and mechanical properties of the magnesium/aluminum dissimilar metal joints with and without the copper interlayer. The experimental results reveal that the incorporation of a copper interlayer in the weld nugget zone establishes a ternary magnesium-aluminum-copper diffusion system. This system effectively suppresses interdiffusion behavior between magnesium and aluminum, which reduces the diffusion layer thickness in the weld nugget zone from 150 μm to 50 μm. Simultaneously, new diffusion layers are formed on both sides of the hook-shaped defects in copper-containing joints that effectively suppresses the formation of magnesium-aluminum IMCs, while promoting the formation of copper-magnesium and copper-aluminum IMCs. Meanwhile, the incorporation of the copper interlayer significantly reduces the area of hook-shaped defects at the joint interface and effectively mitigates stress concentration at the interface. Ultimately, compared to conventional joints, the fracture path of copper-containing joints is changed from the IMCs layer to the weld nugget zone. Average shear strength of the joints increases from 3 407 N to 4 615 N, representing a 35.5% improvement in shear performance. The study identifies the causes for the improvement of the mechanical properties of certain magnesium/aluminum dissimilar metals joints through FSW, providing reference for welding other dissimilar materials.
In order to enhance the response speed of the permanent magnet synchronous motor(PMSM) in cranes and the robustness of the system, an improved index law was proposed. The new sliding mode control(NSMC) in the speed loop was adopted based on field-oriented control（FOC）. A new function f(s) was introduced to enhance the response speed at which the system state variables approached the sliding mode surface. The sign function sign(s) was replaced by a continuous function h(s) to reduce the chattering caused by the discontinuity of the sign function. A new extended state observer(NESO) was designed to observe disturbances and further optimize the speed controller. The fal(s) function in traditional observer was replaced by a nonlinear smooth function K(s) to eliminate chattering and improve the observation accuracy of the observer. The results show that the motor speed is stable at approximately 0.05 s after starting, with a speed oscillation of about 10 r/min. It verifies the correctness of the controller algorithm. The designed algorithm can effectively improve the response speed of the system and provide reference for the control of PMSM in cranes.
Aiming to address the issue of increased production costs caused by the five-pass cold drawing forming for the sliding block in the rolling linear guide pair in a factory in Hebei Province, this study investigated the influence of parameters such as die cone angle and sizing belt length on billet deformation. The objective was to determine the optimal parameter combination to reduce the number of drawing passes and lower production costs. A finite element model for slider drawing and forming was established, and whether the stress at the minimum cross-section of the blank exceeded the tensile strength of the material during the drawing process was taken as the failure criterion for the orthogonal experiment. An orthogonal test analysis was conducted with four process parameters including die cone angle, sizing belt length, friction coefficient, and drawing speed, as influencing factors, to study the influence of process parameters on the stress at the minimum cross-sectional area of the billet during the forming process, as well as the primary and secondary relationships of interactions. The optimal parameter combination was obtained by combining range analysis (R-value method). Finally, the number of drawing passes was optimized through theoretical calculation, and the size structure of the die sizing belt was redesigned. The results indicate that the optimized drawing passes are reduced from five to three, and the influence degrees of various process parameters on the stress acting on the minimum cross-section of the billet are in the following order: die cone angle, sizing belt length, friction coefficient, and drawing speed. The optimal process parameters are as follows: the cone angle of the mold is 5 °, the sizing belt length is 10 mm, the friction coefficient is 0.06, and the drawing speed is 83 mm/s. The simulation results indicate that after optimization, the stress on the billet’s minimum cross-section remains below the tensile strength of the material (885 MPa) during all three-pass drawing passes, and the safety factor exceeds 1.25. Theoretical calculations show that the safety factors of the three-pass drawing all meet the requirements, which verifies the feasibility of the optimization scheme. The study reveals the primary and secondary relationships between key parameters of process and mold affecting drawing stress, providing theoretical reference for optimizing the multi-pass drawing process of rolling linear guide sliders.
To address the problem of rapid capacity decay of LiMn2O4 during the cycling process, Mn3O4 with different particle sizes and tap densities was prepared by manganese salt method, and used as a precursor to synthesize LiMn2O4 cathode material. The effects of Mn3O4 particle size and tap density on the electrochemical performance were investigated using X-ray diffraction, cyclic voltammetry, electrochemical impedance spectroscopy, and galvanostatic charge-discharge tests. The results indicate that increasing the particle size of the Mn3O4 precursor leads to a slight decrease in the initial discharge specific capacity, but significantly improves both cycling stability and rate performance. Compared with the material derived from 6 μm Mn3O4, the cathode material prepared from 10 μm Mn3O4 exhibits a 6.2% reduction in initial discharge capacity, while achieving an 8.0% increase in capacity retention after 300 cycles and a 25.2% improvement at 5 C. Moreover, when the tap density of Mn3O4 exceeds 2.5 g/cm3, the rate performance of the material deteriorates sharply. The LiMn2O4 sample prepared with a precursor particle size of 10 μm and tap density of 2.5 g/cm3 demonstrates the best overall electrochemical performance, delivering discharge specific capacities of 122.48, 111.9, and 78.42 mAh/g at 0.1, 1, and 5 C, respectively, along with a capacity retention of 90.3% after 300 cycles. This study clarifies the influence of precursor physical properties on the electrochemical properties of LiMn2O4, providing basis for the synthesis of high-performance LiMn2O4 materials.
Aiming at the problems of expansion and cracking that may occur in high-strength concrete(HSC) serving in long-term humid or water environments, the influence of further hydration on HSC property was studied by simulation test. Firstly, the influence of slag powder content on the physical and mechanical properties and permeability of HSC was discussed. Secondly, the influence mechanism of further hydration on the strength of concrete with or without slag powder was analyzed. Finally, the influence of loading degree on the strength of pre-damage concrete was expounded. The results show that the variation ranges of the compressive strength and ultrasonic sound velocity value for concretes with or without slag powder are both not obvious, while the decreased degree of the electric flux first decreases and then increases with an increase in the slag powder content. The decreased degree of compressive strength first increases and then decreases with an increase in loading degree and moreover, the increase in splitting tensile strength shows an increasing trend. The further hydration products continuously fill the initial cracks of pre-damage concrete. When the internal space of concrete is not sufficient to accommodate the products, the volume expansion of products leads to the formation of microcracks and a decrease in strength. However, during the late stage of further hydration, the new microcracks provide channels for the entry of extraneous water again, and the new products fill its internal pores and defects. This ultimately causes an increase in strength. The influence laws of slag powder and loading degree on the performance of HSC under further hydration effect are put forward, which provides some reference for the performance evaluation and design of HSC.
