Search Results (11,171)

The design of the high-speed on/off valve is challenging due to the interrelated structural parameters of its driving actuator. Hence, this study proposes a multi-objective optimization approach that integrates a backpropagation neural network and artificial fish swarm algorithm optimization techniques to accurately model the electromagnetic solenoid structure. The backpropagation neural network is fitted and trained using simulation data to obtain a reduced-order model of the system, enabling the precise prediction of the system’s output based on the input structural parameters. By employing the artificial fish swarm algorithms, with optimization objectives focusing on the valve’s opening and closing times, a Pareto optimal solution set comprising 30 solutions is generated. Utilizing the optimized structural parameters, a prototype is manufactured and an experimental setup is constructed to verify the dynamic characteristics and flow pressure drop. The high-speed on/off valve achieves an approximate opening and closing time of 3 ms. Notably, the system output predicted using the backpropagation neural network (BPNN) exhibits consistency with the experimental findings, providing a reliable alternative to mathematical modeling. Full article

To achieve high-fidelity large eddy simulation (LES) predictions of complex flows while keeping computational costs manageable, this study integrates a high-order WENO-ZQ scheme into the LES framework. The WENO-ZQ scheme has been extensively studied for its accuracy, robustness, and computational cost in inviscid flow applications. This study extended the WENO-ZQ scheme to viscous flows by integrating it into a three-dimensional structured grid LES CFD solver. High-fidelity simulations of turbulent boundary layer flow and supersonic compression ramp flows were conducted, with the scheme being applied for the first time to study laminar boundary layer transition and separation flows in the high-load, low-pressure turbine PakB cascade. Classic numerical case validations for viscous conditions demonstrate that the WENO-ZQ scheme, compared to the same-order WENO-JS scheme, exhibits lower dispersion and dissipation errors, faster convergence, and better high-frequency wave resolution. It maintains high-resolution accuracy with fewer grid points. In application cases, the WENO-ZQ scheme accurately captures the three-dimensional flow characteristics of shockwave–boundary layer interactions in supersonic compression ramps and shows high accuracy and resolution in predicting separation and separation-induced transition in low-pressure turbines. Full article

In the field of ocean engineering, the variation of flow field during ship−to−ship (STS) interaction has been a hot topic. Noteworthy, the effect of vortex distribution on flow field characteristic variations during STS interaction remains insufficiently researched. This study modifies the RNG k-ε model using the OpenFOAM platform and verifies its reliability by comparing it with literature data. Subsequently, extended research is conducted to investigate the flow field characteristics of two different ship hull sections under different Reynolds numbers (Re=68,000 and Re=6800), analyzing velocity components, vortex distribution, and trends in pressure and turbulent kinetic energy fields relative to the vortex field. The research reveals that Re primarily governs changes in upstream and downstream flow fields, while in the gap field, the variation in flow field characteristics is more constrained by geometry and boundary conditions. This research provides a valuable reference for assessing flow field characteristics in STS interactions. Full article

The solidification structure characteristics are decisive for the production of extra-thick slabs. This study developed a solidification heat transfer model and a cellular automaton–finite element coupled model to investigate the solidification behavior and structure characteristics of a 475 mm extra-thick slab. The models were applied under various continuous casting process parameters and different alloy element content. The simulation results reveal that casting speed has the most significant effect on the solidification behavior of extra-thick slabs, surpassing the impact of specific water flow and superheat. The solidification structure characteristics of the 475 mm extra-thick slabs were investigated under various conditions. The findings indicate that at higher casting speeds and superheats, the average grain size increases and the grain number decreases. The average grain size initially decreases and then increases with the rise in specific water flow, reaching its minimum at approximately 0.17 L·kg⁻¹. Additionally, the average grain radius first decreases and then slightly increases with an increase in carbon content, achieving the minimum value of about 0.17% carbon. Compared with carbon and manganese, silicon has a greater impact on the solidification structure of ultra-thick slabs, and a moderate increase in silicon content can effectively refine the grain size. This study provides a theoretical foundation for understanding the changes in solidification structure characteristics and optimizing continuous casting process parameters for 475 mm extra-thick slabs. Full article

The performance of the porous gas bearing depends on the geometric characteristics, material, fluid properties, and the properties of the porous media, which is a restrictor that controls the gas flow. Its application in industrial environments must support higher loads, higher supply pressure, and, consequently, higher pressure in the lubricant fluid film. Because porous media has a relatively low elastic modulus, it is necessary to consider its deformation when designing porous gas bearings. The design of porous gas bearings is a multi-objective problem in engineering because the optimization objectives commonly are to maximize the load capacity or static stiffness coefficient and minimize the airflow; these objectives conflict. This work presents a multi-objective optimization algorithm based on the nature-inspired Flower Pollination Algorithm enhanced with Non-Dominated Sorting Genetic Algorithm II. The algorithm is applied to optimize the design of a porous gas bearing, maximizing the resultant force and the static stiffness coefficient and minimizing the airflow. The results indicate a better performance of the Multi-Objective Flower Pollination Algorithm than the Multi-Objective Cuckoo Search. The results show a relatively short running time of 6 min for iterations and a low number of iterations of 50. Full article

Deep-sea hydraulic collection is a key technology for seabed mineral resource extraction, offering higher efficiency and environmental protection compared to other collection methods. However, due to their complex characteristics, the suction properties and influencing factors of polyhedral particles in hydraulic suction collection remain elusive. This study utilized dimensionless methods and conducted experiments to analyze the flow characteristics in cone-shaped collection hoods and the distribution of suction force on polyhedral particles, and researched the effect of various parameters, such as Φ, H/R, R/S, and H/d_p (referring to the nomenclature given in the last part of this paper), on the suction force coefficients of polyhedral particles based on the suction force coefficients of spheres by acquiring the suction coefficient ratio (k_c). The results indicate the following: (1) the presence of suction and coherent vortices in the horizontal positions of 0.1R to 0.2R within the central region, which move with changes in pump suction or cove height, benefiting particle collection; (2) the particle suction force (F_d) decreases with increasing sphericity (Φ), with a more pronounced decline in high-speed flow fields, exhibiting two peaks and one trough in the F_d curve within the hood’s flow field; (3) the k_c generally increases with decreasing Φ at the same collection position, showing increasingly stable fluctuations, and k_c is sensitive to surrounding flow velocities with a rapid growth trend at higher speed, revealing that the suction coefficient (C_d) of polyhedral particles is significantly larger than that of spherical particles with increasing flow speed in high-speed flow fields; (4) F_d decreases with increasing H/d_p, with a noticeable slowdown when H/d_p exceeds 3.5. This study reveals the force characteristics and influencing factors of non-spherical coarse particles in hydraulic suction collection flow fields, providing insights for the development of collection technologies and equipment for deep-sea solid mineral resources, particularly irregular coarse particles. Full article

The development of new turbomachinery designs requires numerous time-consuming and computationally intensive computational fluid dynamics (CFD) calculations. However, most of the generated high spatial resolution data remain unused at later development steps. That is also the case with automated optimization processes that use only a few integral values to determine objectives and constraints. To make further use of this vast amount of CFD data a data-driven AI model based on the Transformer architecture is developed and trained using the available CFD data. The presented method subsequently provides a fast approximation of the 3D flow for new designs. In this paper, the structure of the developed AI model is presented and the approximation quality is analyzed using a complex, state-of-the-art compressor test case. It is shown that the AI model can reproduce many characteristics of the 3D flow of new designs, and performance measures such as efficiency can be derived from these flow predictions. In addition, the complex test case revealed that greater design variation reduces the AI approximation quality which can lead to undesirable exploratory behavior in an optimization setup. Overall, the test case has shown promising results and has provided hints for further improvements to the AI model. Full article

A novel decomposition method that adheres to both local time translation symmetry and spatial rotational symmetry is proposed in this study, thereby extending the limitations of existing methods, which are typically restricted to quasi-two-dimensional configurations. Grounded in the FIK and RD identities, this method provides a clear physical and reliable interpretation suitable for arbitrary-curvature profiles. Utilizing this method, an analysis of the aerothermodynamic characteristics of the bistable states of curved compression ramp flows was conducted. The results reveal that the generation of undisturbed and peak Cf is dominated by viscous dissipation. Specifically, flow separation happens when all of the energy input from the work exerted by the adverse pressure gradient (APG) is insufficient to be entirely converted into local viscous dissipation and kinetic energy. Furthermore, the propensity for flow separation at higher wall temperatures is firstly elucidated quantitatively from the perspective of the work by the APG. The peak heat flux is predominantly triggered by the work of viscous stress, with the secondary contribution from energy transport playing a more significant role in the generation of the peak heat flux of the separation state than that of the attachment state. Full article

Precise control of furnace temperature (FT) is crucial for the stable, efficient operation and pollution control of the municipal solid waste incineration (MSWI) process. To address the inherent nonlinearity and uncertainty of the incineration process, a FT control strategy is proposed. Firstly, by analyzing the process characteristics of the MSWI process in terms of FT control, the secondary air flow is selected as the manipulated variable to control the FT. Secondly, an FT prediction model based on the Interval Type-2 Fuzzy Broad Learning System (IT2FBLS) is developed, incorporating online parameter learning and structural learning algorithms to enhance prediction accuracy. Next, particle swarm rolling optimization (PSRO) is used to solve the optimal control law sequence to ensure optimization efficiency. Finally, the stability of the proposed method is validated using Lyapunov theory, confirming the controller’s reliability in practical applications. Experiments based on actual operational data confirm the method’s effectiveness. Full article

Grey cast iron releases energy in the form of stress waves when damaged. To analyse the evolution of the physical and mechanical properties and acoustic emission characteristics of grey cast iron under uniaxial compression, acoustic emission signals were collected at different rates (0.5, 1, and 2 mm/s). Combined with load-time curves, damage modes were identified and classified using the parametric RA-AF correlation analysis method. The results indicate the loading rate effects on the strength, deformation, acoustic emission (AE), and energy evolution of grey cast iron specimens. The acoustic emission counts align with the engineering stress–strain response. To better illustrate the entire failure process of grey cast iron, from its internal microstructure to its macroscopic appearance, X-ray diffraction (XRD) and optical microscopy (OM) were employed for qualitative and quantitative analyses of the material’s internal microstructural characteristics. The equivalent crystal model of grey cast iron was constructed using a Particle Flow Software PFC2D 6.00.30 grain-based model (GBM) to simulate uniaxial compression acoustic emission tests. The calibration of fine parameters with indoor test results ensured good agreement with numerical simulation results. Acoustic emission dynamically monitors the compression process, while discrete element particle flow software further analyses the entire damage process from the inside to the outside. It provides a new research method and idea for the study of crack extension in some metal materials such as grey cast iron. Full article

The prediction of the wave load on a hovercraft is essential for the design of the hull structure and safety. However, theoretical methods for the prediction of wave loads are still not mature enough due to the unique and complex nature of the air cushion structure, and numerical modeling and simulation are challenging due to the complexity of the gas-solid-liquid three-phase coupling, so the study of wave loads on hovercrafts still relies on experimentation. In this study, we aim to analyze the wave load response characteristics of a four-chamber hovercraft by conducting a wave load model test under medium/low sea states. The load components and amplitude-frequency response characteristics were thoroughly analyzed based on the acquired data of the cushion pressure, acceleration, and bending moment. The main characteristics of the wave-induced response of the hovercraft were described in detail, and an analytical relationship between the cushion pressure and hull acceleration was derived. The reliability of the experimental results was confirmed through a comparison with the derived results. The relationship between the cushion pressure and cushion volume was investigated in terms of the observed geometric volume of the air chamber, and the relationship between the cushion pressure and flow rate was analyzed to validate the derivation of the theory of wave loads on hovercrafts. Full article

Machine learning has gained significant recognition as a powerful approach for medical diagnosis using medical images. Among various medical imaging modalities, contrast-enhanced CT (CECT) is utilized to obtain additional diagnostic information that improves visualization and evaluation of certain abnormalities in the human body, as well as to observe temporal changes in lesions and tumors across different time phases. However, developing such medical diagnostic systems presents two significant challenges: high technical complexity and substantial development effort. This paper presents a software platform that effectively addresses these challenges. Specifically, we propose a unified software process that fully automates contrast-enhanced CT (CECT)-specific disease diagnosis, with key tasks performed by leveraging task-specific machine learning models to enhance accuracy. The platform incorporates a suite of specialized machine learning models into the diagnostic process, enabling precise diagnosis of lesions, malignancies, tumors, tumor characteristics, and temporal changes over phases. Moreover, the platform has been designed according to the Open–Closed Principle, allowing it to be applicable to a wide range of CECT-based diagnostic systems. The platform has been implemented in Python using the Scikit-learn and TensorFlow libraries. To validate its applicability and reusability, a hepatocellular carcinoma (HCC) diagnosis system has been implemented. Full article

Ore collection is very important in deep-sea mining for seafloor massive sulfide (SMS). In view of the characteristics of SMS ores produced by mechanical crushing, which contain coarse particles and a wide particle size distribution, in-depth research on the collection process with a device combining a rotary crushing head and a flat suction mouth was conducted. In this paper, solid–liquid two-phase flow in the hydraulic collection process with a drum rotation is carried out using the computational fluid dynamics-discrete element method (CFD-DEM), and the flow field characteristics and particle motion characteristics are analyzed. The results indicate that particles with a maximum diameter of 20 mm can be effectively collected when the suction velocity is 3 m/s. The collection process of SMS mainly goes through three stages: particle disturbance start-up, partial particle influx, and stable collection. In addition, the appropriate drum speed facilitates the collection of SMS ore. Finally, the correctness of the numerical method was assessed using similarity experiments. This work can be used to guide the design of underwater mining equipment. Full article

In this paper, we study how cyclonic and anticyclonic vortices adapt their shape and orientation to a background shear flow in an effort to understand geophysical vortices. Here we use a balanced model that incorporates the effects of rotation and density stratification to model the case of an isolated vortex of uniform potential vorticity subjected to a background shear flow that mimics the effect of surrounding vortices. We find equilibrium states and analyze their linear stability to determine the vortex characteristics at the margin of stability. Differences are found between the cyclonic and anticyclonic equilibria depending on the background flow parameters. When there is only horizontal strain, the vertical aspect ratio of the vortex does not change, whereas increasing the imposed background strain rate causes a change in the horizontal cross section, with cyclones being more deformed than anticyclones for a given value of strain. Vertical shear not only causes changes in the vertical axis but also causes the vortex to tilt away from it upright position. Overall, anticyclonic equilibria tend to have a more circular horizontal cross section, a longer vertical axis, and a larger tilt angle with respect to cyclonic equilibria. The strongest asymmetry between the horizontal cross section of cyclonic and anticyclonic vortices occurs for low values of vertical shear, while the strongest asymmetry in the vertical axes and tilt angle occurs for large vertical shear. Finally, by expanding the vortex shape and orientation in terms of the strain rate, we derive simple formulas that provide insights into how the vortex equilibria depend on the background flow. Full article

This study validates the attributes of the mineral carbonation process employing circulating fluidized bed combustion (CFBC) ash, which is generated from thermal power plants, as a medium for carbon storage. Furthermore, an examination was conducted on the properties of construction materials produced through the recycling of carbonated circulating fluidized bed combustion (CFBC) ash. The carbonation characteristics of circulating fluidized bed combustion (CFBC) ash were investigated by analyzing the impact of CO₂ flow rate and solid content. Experiments were conducted to investigate the use of it as a concrete admixture by replacing cement at varying percentages ranging from 0% to 20% by weight. The stability and setting time were subsequently measured. To produce foam concrete, specimens were fabricated by substituting 0 to 30 wt% of the cement. Characteristics of the unhardened slurry, such as density, flow, and settlement depth, were measured, while characteristics after hardening, including density, compressive strength, and thermal conductivity, were also assessed. The findings of our research study validated that the carbonation rate of CFBC ash in the slurry exhibited distinct characteristics compared to the reaction in the solid–gas system. Manufactured carbonated circulating fluidized bed combustion (CFBC) ash, when used as a recycled concrete mixture, improved the initial strength of cement mortar by 5 to 12% based on the 7-day strength. In addition, it replaced 25 wt% of cement in the production of foam concrete, showing a density of 0.58 g/cm³, and the 28-day strength was 2.1 MPa, meeting the density standard of 0.6 grade foam concrete. Full article