Search Results (89)

Synchronous grouting slurry is widely used in shield tunnel construction to fill the gaps between stratum and shield tail segments. However, as grout is nearly liquid in the initial stages, the tunnel lining segments recently separated from the shield tail are easily affected by the upward buoyancy generated by grout, causing issues such as longitudinal misalignment and opening of ring joints. Therefore, studying the upward buoyancy characteristics of synchronous grout is crucial. In this study, floating characterisation parameters of grout were investigated using buoyancy model tests, orthogonal tests, and comprehensive tests. The floating characterisation parameters are affected by distribution ratio and types of each grout component. The relationship between the floating characterisation parameters of grout and buoyancy was established. The results show that density, flow index, and shear strength can be used as the floating characterisation parameters. Binder–sand and water–binder ratios have the largest impact on the density. The bentonite–water ratio exerts a primary influence on the flow index, while the water–binder ratio contributes a secondary effect. In addition, bentonite–water and binder–sand ratios have the greatest effect on the shear strength. Furthermore, the particle size of sand and type of bentonite considerably influence the flow index and shear strength. A high-shear grout using well-graded fine sand and a high mesh of sodium bentonite was considered in this study. When the content of bentonite exceeds 7% (P2.2), Archimedes’ law is not applicable for calculating the upward buoyancy of grout. Buoyancy supply rate exhibits gradual enhancement with flow index elevation, yet with diminishing growth rates. Full article

In freeform surface grid structures, quadrilateral meshes offer high visual transparency and simple joint connections, but their structural stability is relatively limited. To enhance stability, designers often introduce additional structural elements along the diagonals of the quadrilateral mesh, forming double-layer quadrilateral grid systems such as cable-braced gridshells. However, current design methodologies do not support the simultaneous optimization of both layers. As a result, the two layers are often designed independently in practical applications, leading to complex joint detailing that compromises construction efficiency, architectural aesthetics, and overall structural performance. To address these challenges, this study presents a weighted multi-objective geometry optimization framework based on a Guided-Projection algorithm. The proposed method integrates half-edge data structure and multiple geometric and structural constraints, enabling the simultaneous optimization of quadrilateral mesh planarity (i.e., panels lying on flat planes) and the orthogonality (i.e., angles approaching 90°) of diagonal cable layouts. Through multiple case studies, the method demonstrates significant improvements in panel planarity and cable orthogonality. The results also highlight the algorithm’s rapid convergence and high computational efficiency. Finite element analysis further validates the structural benefits of the optimized configurations, including reduced peak axial forces in cables, more uniform cable force distribution, and enhanced overall stiffness and buckling resistance. In conclusion, the method improves structural stability, constructability, and design efficiency, offering a practical tool for optimizing freeform cable-braced gridshells. Full article

To address the issues of large errors, low accuracy, and time-consuming simulations in finite element (FE) models of tapping processes, which hinder the identification of optimal structural parameters, this study integrates FE simulation with experimental testing to optimize the structural parameters of spiral taps specifically designed for stainless steel. Initially, single-factor experiments were conducted to analyze the influence of mesh parameters on experimental outcomes, leading to the identification of optimal mesh coefficients. Subsequently, the accuracy of the FE tapping simulation model was validated by comparing trends in axial force, torque, and chip morphology between simulations and actual tapping experiments. Orthogonal experimental design combined with entropy weight analysis and range analysis was then employed to conduct FE simulations. The results indicated that the optimal structural parameter combination is a helix angle of 43°, cone angle of 19°, and cutting edge relief amount of 0.18 mm. Finally, based on this combination, optimized spiral taps were manufactured and subjected to comparative performance testing. The results demonstrated significant improvements: the average maximum axial force decreased by 33.22%, average maximum torque decreased by 13.41%, average axial force decreased by 38.22%, and average torque decreased by 24.87%. Error analysis comparing corrected simulation results with actual tapping tests revealed axial force and torque error rates of 5.04% and 0.24%, respectively. Full article

Structural cracks can critically undermine infrastructure integrity, driving the need for precise, scalable inspection methods beyond conventional visual or 2D image-based approaches. This study presents an automated system integrating photogrammetric 3D reconstruction with deep learning to quantify crack dimensions in a spatial context. Multiple images are processed via Agisoft Metashape to generate high-fidelity 3D meshes. Then, a subset of images are automatically selected based on camera orientation and distance, and a deep learning algorithm is applied to detect cracks in 2D images. The detected crack edges are projected onto a 3D mesh, enabling width measurements grounded in the structure’s true geometry rather than perspective-distorted 2D approximations. This methodology addresses the key limitations of traditional methods (parallax, occlusion, and surface curvature errors) and shows how these limitations can be mitigated by spatially anchoring measurements to the 3D model. Laboratory validation confirms the system’s robustness, with controlled tests highlighting the importance of near-orthogonal camera angles and ground sample distance (GSD) thresholds to ensure crack detectability. By synthesizing photogrammetry and a convolutional neural network (CNN), the framework eliminates subjectivity in inspections, enhances safety by reducing manual intervention, and provides engineers with dimensionally accurate data for maintenance decisions. Full article

After nearly two decades of development, transient electromagnetic (TEM) 3D forward modeling technology has significantly improved both numerical precision and computational efficiency, primarily through advancements in mesh generation and the optimization of linear equation solvers. However, the dominant approach still relies on direct solvers, which require substantial memory and complicate the modeling of electromagnetic responses in large-scale models. This paper proposes a new method for solving large-scale TEM responses, building on previous studies. The TEM response is expressed as a matrix exponential function with an analytic initial field for a step-off source, which can be efficiently solved using the Shift-and-Invert Krylov (SAI-Krylov) subspace method. The Arnoldi algorithm is used to construct the orthogonal basis for the Krylov subspace, and the preconditioned conjugate gradient (PCG) method is applied to solve large-scale linear equations. The paper further explores how dividing the off-time and optimizing parameters for each time interval can enhance computational efficiency. The numerical results show that this parameter optimization strategy reduces the iteration count of the PCG method, improving efficiency by a factor of 5 compared to conventional iterative methods. Additionally, the proposed method outperforms direct solvers for large-scale model calculations. Conventional approaches require numerous matrix factorizations and thousands of back-substitutions, whereas the proposed method only solves about 300 linear equations. The accuracy of the approach is validated using 1D and 3D models, and the propagation characteristics of the TEM field are studied in large-scale models. Full article

In the current energy landscape, efficiency is a critical topic. Therefore, even in the case of geared transmissions, it is essential to predict and calculate power losses as accurately as possible from the design phase. There are mainly three categories of losses in a gear unit: friction—the power losses due to the contact between teeth in rotation on the one hand and the seals with the spindles on the other hand; churning—the power losses generated by the air–lubricant mixture compression around teeth roots during rotation; and windage—the power losses due to the teeth aerodynamic trail in the air–lubricant mixture. While the first two categories of losses are intensively studied in the literature, the papers focusing on windage power losses are less representative. An estimation of windage power losses can be performed by numerical simulation, and the accuracy of the results depends on the mesh density and the available computing power. The present study discusses the influence of meshing on the windage torque of an orthogonal face gear immersed in air and compares numerical results generated by SolidWorks 2025 Flow Simulation software with experimental data measured on a test rig. Full article

This article discusses the problem of numerically solving the Navier–Stokes equations, the heat conduction equation, and the transport equation in the orthogonal coordinates of a free curve. Since the numerical solution domain is complex, the curvilinear mesh method was used. To do so, first, a boundary value problem was posed for the elliptic equation to automate the creation of orthogonal curved meshes. By numerically solving this problem, the program code for the curvilinear mesh generator was created. The motion of a liquid or gas through a porous medium was described by numerically solving the Navier–Stokes equations in freely curvilinear orthogonal coordinates. The transformation of the Navier–Stokes equation system, written in the stream function, vorticity variables, and cylindrical coordinates, into arbitrary curvilinear coordinates, was considered in detail by introducing metric coefficients. To solve these equations, the coefficients of which vary rapidly, a three-layer differential scheme was developed. The approximation, stability, and compactness of the differential scheme were previously studied. The considered problem was considered to be the mathematical model of a car catalytic converter, and computational experiments were conducted. Calculations were performed with the developed program code in different geometries of the computational domain and different values of grid size. The Reynolds number was changed from 100 to 10,000, and its effect on the size of the backflow in front of the porous medium was discussed. The software code, which is based on the differential equation of the Navier–Stokes equations written in the orthogonal coordinates of a curved line, and its calculation algorithm can be used for the mathematical and computer modeling of automobile catalytic converters and chemical reactors. Full article

This paper proposes a dual-mode thermal analysis framework for the composite cage rotor bearingless induction motor (CCR-BIM), which combines lumped parameter thermal network (LPTN) and finite element thermal model (FETM) methods with experimental verification. The CCR-BIM, an advanced motor design combining torque and suspension windings within a single stator core, offers significant advantages in high-speed and high-precision applications. However, accurate thermal management remains a critical challenge due to its complex structure and increased losses. An LPTN model tailored to the unique thermal characteristics of the CCR-BIM is proposed, and detailed FETM simulations and experimental tests are validated. The LPTN model employs a meshing method to discretize the motor into orthogonal thermal nodes, enabling the rapid and accurate calculation of steady-state temperatures. The FETM further verifies the LPTN results by simulating the transient and steady-state temperature fields. Experimental validation using a 2 kW CCR-BIM test platform confirms the effectiveness of both models, with temperature predictions closely matching measured values. This study provides a reliable thermal analysis method for CCR-BIM. Full article

Machining of No. 45 steel (AISI 1045) becomes more vital due to its widespread use. In this study, machining performances of abrasive water jet machining (AWJM) of No. 45 steel, including material removal rate, notch depth, and nozzle wear rate, were obtained by experimental and computational results. The Taguchi L16 orthogonal array design was used to study the influence of process parameters on machining performance. The optimal material removal rate and notch depth were achieved when abrasive particle size, operating pressure, and abrasive feed rate were 80 #, 400 MPa, and 840 g/min, respectively. The optimal nozzle wear rate was achieved when abrasive particle size, operating pressure, and abrasive feed rate were 80 #, 400 MPa, and 260 g/min, respectively. When the abrasive particle size is 80 # (namely the mesh number is 80), the particle diameter is usually between 0.18 and 0.25 mm according to the corresponding relationship between the international standard mesh number and particle diameter. Analysis of Variance was conducted to evaluate the statistical significance of the experimental results. Using regression analysis, an empirical model was developed to predict the response values of the AWJM process. Multi-response optimization was then carried out using the Decision Engineering Analysis and Resolution method. The optimal parameter solution for a higher material removal rate, a bigger notch depth, and a smaller nozzle wear rate was achieved when abrasive particle size, operating pressure, and abrasive feed rate were 120 #, 400 MPa, and 870 g/min, respectively. Full article

The double-bearing vortex pump is a new type of high-efficiency vortex pump. Compared with the traditional vortex pump, its volume and mass are significantly reduced, and its reliability is greatly improved. As the core component of the pump, the impeller has a decisive impact on the overall performance of the pump. Therefore, in order to deeply understand the internal flow mechanism of the vortex pump and improve its hydraulic performance. The mesh model of the double-bearing vortex pump is established by using UG 12.0 and ANSYS Fluent 2022 R1 software, and the influence of different rotational speeds on the flow field characteristics, such as fluid velocity and pressure in the internal vortex pump, is analyzed. The accuracy of the numerical simulation results is verified through experiments. On this basis, the impeller structure of the vortex pump is optimized by introducing the orthogonal design method and taking the impeller diameter, blade groove radius, blade number, and impeller width as optimization parameters. The results indicate that the number of blades is the most critical factor affecting the performance of vortex pumps, and the optimized impeller design increases the head and efficiency of the vortex pump by 18.9% and 11.6%, respectively. This provides important reference for improving the structural design of vortex pump impellers and enhancing their hydraulic performance. Full article

This study addresses the issue of biofouling on marine aquaculture cages, where organisms like algae and purple mussels negatively impact both the safety of the aquaculture environment and the integrity of the cages. To solve this problem, the paper introduces a cage cleaning device based on the cavitation jet principle. Using finite volume simulation software, the cavitation process of the device’s nozzle was modeled, with the gas-phase volume fraction used as the evaluation metric. Key experimental factors, such as the second section throat contraction angle, second section throat radius, and end diffusion angle, were analyzed through single-factor and quadratic regression orthogonal experiments to assess their effect on the cavitation performance. The optimal combination of nozzle parameters was determined to be a second section throat contraction angle of 41.047°, a second section throat radius of 0.834 mm, and an end diffusion angle of 35.495°. Under these conditions, the gas-phase volume fraction reached 0.941, indicating optimal cavitation performance. To validate these findings and further optimize the nozzle’s operational parameters, a nozzle cavitation test bench was constructed. Test results demonstrated that when the target distance was set at 15 mm and the angle at 20°, the surface roughness and maximum surface depth of the target were 6.215 μm and 22.030 μm, respectively, with the nozzle exhibiting the best cavitation effect at these settings. This nozzle design meets the requirements for efficient mesh cleaning, and the research provides valuable insights for future development and optimization of cleaning devices for aquaculture net cages. Full article

Aiming at the saline soil in Binhai New Area, which is solid and sclerotic, and addressing the problem of poor quality and low efficiency of traditional rotary tillage, this research designed a high-speed rotary tiller that can realize the high-speed rotation of knife rollers to cut. The average operating speed is higher than that of the ordinary rotary tiller. We analyzed the rotary tiller operating conditions and rotary tiller knife cutting process and conducted a movement trajectory theoretical analysis to determine the rotary tiller’s high-speed operating speed relationship. The working process of a high-speed rotary tiller was simulated using EDEM software. The experimental indicators included the soil-crushing rate and surface smoothness after tilling. The experimental factors included the forward speed of the machine, the rotational speed of the blade roller, and the tilling depth. An orthogonal experiment was performed to establish regression equations for the soil-crushing rate and surface smoothness. Using Design-Expert analysis software, we obtained the following optimal combination of parameters: a knife roller speed at 310 r/min, tillage depth of 13.2 cm, and machine forward speed of 4.8 km/h. At this time, the simulation values of the soil fragmentation rate and surface flatness were 90.6% and 18.2 mm, respectively. When determining the optimal knife roller speed of 310 r/min, a transient structural simulation under the mesh bevel gear transient was conducted. The simulation analysis showed that the maximum equivalent stress value was 584.57 MPa, which was smaller than the permissible stress of 695.8 MPa, meeting the bevel gear meshing strength requirements. Under the optimal combination determined by a field comparison test, the results show that the values of the high-speed rotary tiller operation after the soil-breaking rate, tillage depth, the tillage depth stability coefficient, and vegetation cover were 89.3%, 14.2 cm, 92.8%, and 90.3%. The land surface flatness was 16.4 mm, which is superior to the ordinary rotary tiller operation effects, meeting the agronomic requirements for pre-sowing land preparation for peanuts in the saline land of Binhai New Area. Full article

Aircraft cabins have high occupant densities and may introduce the risk of COVID-19 contamination. In this study, a segment of a Boeing 767 aircraft cabin with a mixing type of air distribution system was investigated for COVID-19 deposition. A section of a Boeing 737-300 cabin, featuring four rows with 28 box-shaped mannequins, was used for simulation. Conditioned air entered through ceiling inlets and exited near the floor, simulating a mixed air distribution system. Cough droplets were modeled using the Discrete Phase Model from two locations: the centre seat in the second row and the window seat in the fourth row. These droplets had a mean diameter of 90 µm, an exhalation velocity of 11.5 m/s and a flow rate of 8.5 L/s. A high-quality polyhedral mesh of about 7.5 million elements was created, with a skewness of 0.65 and an orthogonality of 0.3. The SIMPLE algorithm and a second-order upwind finite volume method were used to model airflow and droplet dynamics. It was found that the ceiling accounted for the maximum concentration followed by the seats. The concentration of deposits was almost 50% more when the source was at window as compared to the centre seat. The Covid particles resided for longer duration when the source was at the centre of the cabin than when it was located near the widow. Full article

The transient plane source (TPS) method heat transfer model was established. A body-fitted coordinate system is proposed to transform the unstructured grid structure to improve the speed of solving the heat transfer direct problem of the winding probe. A parallel Bayesian optimization algorithm based on a multi-objective hybrid strategy (MHS) is proposed based on an inverse problem. The efficiency of the thermophysical properties inversion was improved. The results show that the meshing method of 30° is the best. The transformation of body-fitted mesh is related to the orthogonality and density of the mesh. Compared with parameter inversion the computational fluid dynamics (CFD) software, the absolute values of the relative deviations of different materials are less than 0.03%. The calculation speeds of the body-fitted grid program are more than 36% and 91% higher than those of the CFD and self-developed unstructured mesh programs, respectively. The application of body-fitted coordinate system effectively improves the calculation speed of the TPS method. The MHS is more competitive than other algorithms in parallel mode, both in terms of accuracy and speed. The accuracy of the inversion is less affected by the number of initial samples, time range, and parallel points. The number of parallel points increased from 2 to 6, reducing the computation time by 66.6%. Adding parallel points effectively accelerates the convergence of algorithms. Full article

Workpiece surface quality is a critical metric for assessing machining quality. However, due to the complex coupling characteristics of cutting factors, accurately predicting surface roughness remains challenging. Typically, roughness is measured post-machining using specialized instruments, which delays feedback and hampers timely problem detection, ultimately resulting in cutting resource wastage. To address this issue, this paper introduces a predictive model for workpiece surface roughness based on the finite element (FE) method and advanced image processing techniques. Initially, an orthogonal turning experiment was designed, and an FE cutting model was constructed to assess the distribution of cutting forces and temperatures under varying cutting parameters. Image processing methods (including mesh calibration, edge extraction, and contour fitting) were then applied to extract surface characteristics from the FE simulation outputs, yielding preliminary estimates of surface roughness. By employing range and regression analyses methods, this study quantitatively evaluates the interdependencies among cutting parameters, forces, temperatures, and roughness, subsequently formulating a multivariate regression model to predict surface roughness. Finally, a turning experiment under actual working conditions was conducted, confirming the model’s capacity to predict the $R_a$ trend with an accuracy of 85.07%. Thus, the proposed model provides a precise predictive tool for surface roughness, offering valuable guidance for optimizing machining parameters and supporting proactive control in the turning process, ultimately enhancing machining efficiency and quality. Full article