Development of resource-saving composition of sand-clay mixtures for steel castings with improved physical and chemical characteristics

The paper examines the problems of traditional sand-clay mixtures (SСM) used in steel castings and proposes solutions. Standard compositions including quartz sand, water and bentonite often exhibit limited gas permeability and insufficient strength. To address this, starch and soda ash were introduced as environmentally friendly additives. The scientific novelty of this research lies in the use of starch and soda ash to enhance the binding structure of sand-clay mixtures, thereby simultaneously improving strength and gas permeability without increasing production costs. Experimental analysis confirmed improvements in compressive strength and gas permeability, making the proposed mixture promising for industrial applications

Study on vortex-induced vibration response of large-scale two-lay steel trusses bridge under large wind angle of attack

With the advancement of urbanization, two-lay trusses bridges are widely used because of their good traffic capacity and structural performance. However, the aerodynamic behavior of this beam type is still in the exploratory stage. The local microclimate characteristics at the bridge site in mountainous cities are obvious, and it is easy to form a large wind angle of attack, which has a significant impact on the vortex-induced vibration (VIV) performance of the bridge. Therefore, this study takes a long-span two-lay steel trusses bridge in a mountainous city as the engineering background, and uses wind tunnel test and numerical calculation methods to study the changes of the static three-component force coefficient and VIV response of the main beam in the construction and completion state under the action of high wind angle of attack. The results show that the three-component force coefficient curves under different wind speeds are close to each other, and the Reynolds number effect is not obvious. The vibration test shows that the vertical bending VIV first occurs at +3° and +5°, and then two torsional VIV with different amplitudes occur. Both vertical bending and torsional VIV are simple harmonic vibrations with a single frequency, and the vertical bending VIV frequency is locked at 2.227 Hz, and the torsional VIV frequency is locked at 4.289 Hz, which are close to the natural frequency of the test model. Compared with +3°, the maximum amplitude of vertical bending VIV under +5° increases by 30.0 %, while the maximum amplitude of torsional VIV under high and low wind speed increases by 16.6 % and 12.7 % respectively, and the locking range is longer. It can be seen that the wind angle of attack has a significant effect on the VIV response of the main beam in the completion state. Especially, the trusses beam at a large angle is more sensitive to VIV, and it is more prone to large-scale and large-amplitude VIV. The research results can provide a theoretical basis for the aerodynamic shape optimization and provide a reference for the design of related bridges

Enhanced photocatalytic CO2 reduction performance of Cu-Doped ZnO: synthesis, characterization, and mechanistic insights

In this study, we utilized in situ infrared spectroscopy to comprehensively analyze the behavior of copper-doped zinc oxide (Cu-ZnO) in photocatalytic CO2 reduction reactions. By pyrolyzing copper-doped ZIF-8 precursors, we achieved a uniform distribution of copper within the zinc oxide matrix. Experiments conducted under simulated sunlight conditions demonstrated that Cu-ZnO exhibits enhanced activity and selectivity in the conversion of CO2 to CO compared to undoped ZnO. The findings from in situ infrared spectroscopy indicate that copper doping significantly improves the material's ability to adsorb and activate CO2, thereby enhancing its photocatalytic performance. This study has developed the application of in situ infrared spectroscopy in surface catalysis and provided a new direction for exploring the catalytic mechanism of photocatalytic CO2 reduction

Equations of motion for the rigid and elastic double pendulum using Lagrange’s equations

The double pendulum is a well-known system exhibiting nonlinear dynamics and chaotic behavior. This study extends the conventional rigid double pendulum by introducing elastic extensions in the links, leading to a system known as the elastic double pendulum. The mathematical model incorporates both rotational and translational motion, accounting for elastic deformations using Hooke’s Law. The governing equations are derived using Lagrangian mechanics, considering both gravitational and spring potential energy contributions. Numerical simulations are performed to compare the motion of the elastic and rigid double pendulums, highlighting differences in phase-space trajectories, energy transfer, and stability characteristics. Results demonstrate that elasticity introduces additional oscillatory components, increases system nonlinearity, and affects the overall predictability of motion. These findings provide insights into elastic multi-body dynamics and have potential applications in flexible robotic arms, soft mechanisms, and bio-inspired locomotion

Bispectrum analysis based on dual channel homologous information fusion and its application in fault diagnosis

High order spectrum is a powerful tool for processing the nonlinear and non-Gaussian signals of rotating machinery. As one typical representative of high order spectrum, the bispectrum analysis method has been used widely due to its advantages of low order and effective algorithm. However, traditional bispectrum analysis method based on single channel information often results in inconsistent fault feature extraction results while analyzing the phase coupling of complex vibration signals collected from two different measurement directions at the same measurement point, which will have great negative impact on subsequent rotor dynamic balancing experiment requiring phase information or fault diagnosis. The full vector spectrum analysis method based on dual channel homologous information fusion is an improved method of original two classical homologous information fusion methods (holographic spectrum and full spectrum), which could extract the dual channel fusion features while preserving the original information effectively. To overcome the shortcomings of traditional bispectrum and take advantages of full vector spectrum, a novel bispectrum analysis method based on full vector spectrum analysis is proposed. The proposed method could integrate the dual channel signal information effectively to display the secondary phase coupling comprehensively and accurately, fully reflect the nonlinear feature information contained in the signal, and provide accurate and reliable basis for feature extraction and fault diagnosis in the next step, whose effectiveness and advantage are verified through simulation and experiment

Advanced design strategies and applications for enhanced higher-order multisegment denatured pascal curve gears

The existing Pascal curve gears suffer from limited flexibility in pitch curves and restricted changes in transmission ratios. This has impeded the application in a range of mechanical systems that require more adaptable gear solutions. For this, a design procedure for higher-order multisegment denatured Pascal curve gear is proposed. This innovative design offers greater flexibility in pitch curves and allows for a broader range of transmission ratios. The analysis of the transmission ratio confirms the theoretical predictions and highlights the effectiveness of the proposed gear design in achieving variable transmission ratios. The transmission mechanism of the higher-order multisegment denatured Pascal curve gear is analyzed and the unified mathematical expression of the families of Pascal curve gear is derived. The non-circular gears with free-form pitch curves can be obtained from higher-order multi-segment denatured Pascal curves by adjusting design parameters to unify different types of pitch curves. This approach provides significant flexibility in achieving specific transmission characteristics. Then the transmission characteristics are discussed. To further validate the design, the visual analysis and design software of the higher-order multisegment denatured Pascal curve gear is compiled based on Visual Basic, and is verified with the example. The novelty Pascal curve gears is applied to drive the differential velocity vane pump. The displacement, instantaneous flow rate, and pulsation rate of the differential velocity vane pump are calculated. The novelty drive mechanism could meet the requirements and have good performance. The application shows that the higher-order multisegment denatured Pascal curve gear is feasible in practice

Almaty ankle exoskeleton: comparative analysis and structural improvements of versions V.1 and V.2

This paper presents a comparative analysis of the V.1 and V.2 versions of the Almaty Ankle Exoskeleton. The main objective of the study is to identify the structural and functional shortcomings observed in the first version (V.1) and to develop an improved prototype in the second version (V.2) by addressing these issues. The paper compares the kinematic schemes, CAD models, and physical prototypes of both versions, highlighting their structural differences and technical advancements. In addition, the results of a static structural analysis performed on the V.2 prototype using the Finite Element Analysis (FEA) method are presented. This analysis allowed for the evaluation of stress, strain, and displacement distribution within the structure. The results demonstrated that the exoskeleton can effectively handle applied loads, although additional reinforcement is required in certain critical regions. Overall, the findings provide a foundation for engineering solutions aimed at enhancing the functional performance of the ankle exoskeleton and its application in rehabilitation processes

Visual large language models for welding assessment

This paper evaluates the effectiveness of visual large language models (LLMs) for weld defect identification, focusing on their potential utility for novice welders. Using the Gemma-3B, Gemma-27B and Qwen2.5-VL-32B models, we benchmark performance against a standardized weld defect dataset and compare against a most modern version of the more traditional YOLO architecture, YOLOv12. Results show the 27B model achieves 66.36 % recall and a lower precision of 46.10 %, while the 3B model demonstrates poor reliability at 35.05 % recall, comparable to the results of the YOLOv12. Meanwhile, Qwen2.5-VL-32B does not produce sufficiently reliable results to gauge them automatically. We conclude that large LLMs can achieve quantitatively superior results on difficult datasets by leveraging innate understanding of welding stemming from their massive pre-training data, allowing improved functionality compared to current state of the art object detectors, and would appear to be beneficial when used in aid of novice welders in training

Resistance to penetration of a bulldozer blade when the machine is stationary

The study of the resistance of the bulldozer blade burial at a stationary machine is aimed at studying the force factors acting on the working tool during its penetration into the ground. When the machine is not moving, the blade deepening causes an increase in passive resistance from the ground, which acts on the front and rear edges of the blade. This resistance increases with the depth of burial, which requires an increase in force for further advancement of the working body into the ground. An important feature is that in the initial stages of blade insertion, the resistance at the front face increases significantly, increasing the forces. At the rear edge, the re-sistance also increases as the blade deepens. Cutting angles have a significant effect on resistance changes: at higher cutting angles, the resistance decreases, reducing the load on the working mechanisms. The results of the study emphasize that for efficient knife deepening with the machine stationary, higher cutting angles should be used, which reduces passive resistance, improving productivity and reducing energy costs

AI-driven VIN verification and RFID integration for error-proofing in automotive manufacturing

This paper presents an automated solution that combines deep learning-based computer vision with radio-frequency identification (RFID) technology to verify Vehicle Identification Numbers (VINs) during automotive production. The approach utilizes a YOLO-based object detection model for VIN localization and optical character recognition (OCR) for text extraction. An RFID tag linked to each component provides a reference VIN from the production system. A programmable logic controller (PLC) compares the AI-detected VIN with the RFID data in real time, halting the process if inconsistencies are detected. Otherwise, validated information is used to retrieve precise build instructions. This system enhances traceability, prevents assembly errors, and reduces rework, contributing to Industry 4.0 initiatives. Experimental validation confirmed the effectiveness of this integrated solution