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Physics-informed neural networks (PINNs) have become a new tendency in flow simulation, because of their self-advantage of integrating both physical and monitored information of fields in solving the Navier–Stokes equation and its variants. In view of the strengths of PINN, this study aims to investigate the impact of spatially embedded data distribution on the flow field results around the train in the crosswind environment reconstructed by PINN.

PINN can integrate data residuals with physical residuals into the loss function to train its parameters, allowing it to approximate the solution of the governing equations. In addition, with the aid of labelled training data, PINN can also incorporate the real site information of the flow field in model training. In light of this, the PINN model is adopted to reconstruct a two-dimensional time-averaged flow field around a train under crosswinds in the spatial domain with the aid of sparse flow field data, and the prediction results are compared with the reference results obtained from numerical modelling.

The prediction results from PINN results demonstrated a low discrepancy with those obtained from numerical simulations. The results of this study indicate that a threshold of the spatial embedded data density exists, in both the near wall and far wall areas on the train’s leeward side, as well as the near train surface area. In other words, a negative effect on the PINN reconstruction accuracy will emerge if the spatial embedded data density exceeds or slips below the threshold. Also, the optimum arrangement of the spatial embedded data in reconstructing the flow field of the train in crosswinds is obtained in this work.

In this work, a strategy of reconstructing the time-averaged flow field of the train under crosswind conditions is proposed based on the physics-informed data-driven method, which enhances the scope of neural network applications. In addition, for the flow field reconstruction, the effect of spatial embedded data arrangement in PINN is compared to improve its accuracy.

Under the repeated action of the construction load, opening deformation and disturbed deformation occurred at the precast box culvert joints of the shield tunnel. The objective of this paper is to investigate the effect of construction vehicle loading on the mechanical deformation characteristics of the internal structure of a large-diameter shield tunnel during the entire construction period.

The structural response of the prefabricated internal structure under heavy construction vehicle loads at four different construction stages (prefabricated box culvert installation, curved lining cast-in-place, lane slab installation and pavement structure casting) was analyzed through field tests and ABAQUS (finite element analysis software) numerical simulation.

Heavy construction vehicles can cause significant mechanical impacts on the internal structure, as the construction phase progresses, the integrity of the internal structure with the tunnel section increases. The vertical and horizontal deformation of the internal structure is significantly reduced, and the overall stress level of the internal structure is reduced. The bolts connecting the precast box culvert have the maximum stress at the initial stage of construction, as the construction proceeds the stress distribution among the bolts gradually becomes uniform.

This study can provide a reference for the design model, theoretical analysis and construction technology of the internal structure during the construction of large-diameter tunnel projects.

The purpose of this review is to comprehensively consider the material properties and processing of additive titanium alloy and provide a new perspective for the robotic grinding and polishing of additive titanium alloy blades to ensure the surface integrity and machining accuracy of the blades.

At present, robot grinding and polishing are mainstream processing methods in blade automatic processing. This review systematically summarizes the processing characteristics and processing methods of additive manufacturing (AM) titanium alloy blades. On the one hand, the unique manufacturing process and thermal effect of AM have created the unique processing characteristics of additive titanium alloy blades. On the other hand, the robot grinding and polishing process needs to incorporate the material removal model into the traditional processing flow according to the processing characteristics of the additive titanium alloy.

Robot belt grinding can solve the processing problem of additive titanium alloy blades. The complex surface of the blade generates a robot grinding trajectory through trajectory planning. The trajectory planning of the robot profoundly affects the machining accuracy and surface quality of the blade. Subsequent research is needed to solve the problems of high machining accuracy of blade profiles, complex surface material removal models and uneven distribution of blade machining allowance. In the process parameters of the robot, the grinding parameters, trajectory planning and error compensation affect the surface quality of the blade through the material removal method, grinding force and grinding temperature. The machining accuracy of the blade surface is affected by robot vibration and stiffness.

This review systematically summarizes the processing characteristics and processing methods of aviation titanium alloy blades manufactured by AM. Combined with the material properties of additive titanium alloy, it provides a new idea for robot grinding and polishing of aviation titanium alloy blades manufactured by AM.

This paper is devoted to prepare micro-cone structure with variable cross-section size by Stereo Lithography Appearance (SLA)-based 3D additive manufacturing technology. It is mainly focused on analyzing the forming mechanism of equipment and factors affecting the forming quality and accuracy, investigating the influence of forming process parameters on the printing quality and optimization of the printing quality. This study is expected to provide a µ-SLA surface preparation technology and process parameters selection with low cost, high precision and short preparation period for microstructure forming.

The µ-SLA process is optimized based on the variable cross-section micro-cone structure printing. Multi-index analysis method was used to analyze the influence of process parameters. The process parameter influencing order is determined and validated with flawless micro array structure.

After the optimization analysis of the top diameter size, the bottom diameter size and the overall height, the influence order of the printing process parameters on the quality of the micro-cone forming is: exposure time (B), print layer thickness (A) and number of vibrations (C). The optimal scheme is A1B3C1, that is, the layer thickness of 5 µm, the exposure time of 3000 ms and the vibration of 64x. At this time, the cone structure with the bottom diameter of 50 µm and the cone angle of 5° could obtain a better surface structure.

This study is expected to provide a µ-SLA surface preparation technology and process parameters selection with low cost, high precision and short preparation period for microstructure forming.

Adoption of integrated MOS based pseudo-resistor (PR) structures instead of using off-chip passive poly resistors for analog circuits in complementary metal oxide semiconductor technology (CMOS) is an area-efficient way for realizing larger time constants. However, issue of common-mode voltage shifting and excess dependency on the process and temperature variations introduce nonlinearity in such structures. So there is dire need to not only closely look for the origin of the problem with the help of a thorough mathematical analysis but also suggest the most suitable PR structure for the purpose catering broadly to biomedical analog circuit applications.

In this work, incremental resistance (IR) expressions and IR range for balanced PR (BPR) structures operating in the subthreshold region have been closely analyzed for broader range of process-voltage-temperature variations. All the post-layout simulations have been obtained using BSIM3V3 device models in 0.18 µm standard CMOS process.

The obtained results show that the pertinent problem of common-mode voltage shifting in such PR structures is completely resolved in scaled gate linearization and bulk-driven quasi-floating gate (BDQFG) BPR structures. Among all BPR structures, BDQFG BPR remarkably shows constant IR value of 1 TΩ over −1 V to 1 V voltage swing for wider process and temperature variations.

Various balanced PR design techniques reported in this work will help the research community in implementing larger time constants for analog-mixed signal circuits.

The PR design techniques presented in the present piece of work is expected to be used in developing tunable and accurate biomedical prosthetics.

The BPR structures thoroughly analyzed and reported in this work may be useful in the design of analog circuits specifically for applications such as neural signal recording, cardiac electrical impedance tomography and other low-frequency biomedical applications.

While performance demands in the natural world are varied, graded lattice structures reveal distinctive mechanical properties with tremendous engineering application potential. For biomechanical functions where mechanical qualities are required from supporting under external loading and permeability is crucial which affects bone tissue engineering, the geometric design in lattice structure for bone scaffolds in loading-bearing applications is necessary. However, when tweaking structural traits, these two factors frequently clash. For graded lattice structures, this study aims to develop a design-optimization strategy to attain improved attributes across different domains.

To handle diverse stress states, parametric modeling is used to produce strut-based lattice structures with spatially varied densities. The tailored initial gradients in lattice structure are subject to automatic property evaluation procedure that hinges on finite element method and computational fluid dynamics simulations. The geometric parameters of lattice structures with numerous objectives are then optimized using an iterative optimization process based on a non-dominated genetic algorithm.

The initial stress-based design of graded lattice structure with spatially variable densities is generated based on the stress conditions. The results from subsequent dual-objective optimization show a series of topologies with gradually improved trade-offs between mechanical properties and permeability.

In this study, a novel structural design-optimization methodology is proposed for mathematically optimizing strut-based graded lattice structures to achieve enhanced performance in multiple domains.

The main aim of this study is to examine the behavior of reinforced concrete short columns strengthened using longitudinal near surface mounted (NSM)-carbon fiber reinforced polymer (CFRP) strips.

A full 3D-finite element (FE) model was developed using ABAQUS in order to conduct the analysis. The model is first validated based on experimental data available in the literature, and then the effect of concrete compressive strength, number of CFRP strips that are used and the spacing between them were taken in consideration for both concentric and eccentric loading cases. The parametric study specimens were divided into three groups. The first group consisted of unstrengthened columns and served as control specimens. The second group consisted of columns strengthened by longitudinal CFRP strips at two opposite column faces.

The results of this study are used to develop interaction diagrams for CFRP-strengthened short columns and to develop best-fit equations to estimate the nominal axial load and moment capacities for these strengthened columns. The results showed that the specimens that were strengthened using more longitudinal CFRP strips showed a significant increase in axial load capacity and a significant improvement in the interaction diagram, especially at large load eccentricity values. This result can be justified by the fact that longitudinal strips effectively resist the bending moment that is generated due to eccentric loading. Generally, the process of strengthening using longitudinal strips only has a reasonable effect and it can be typically considered an excellent choice considering the economic aspect when the budget of strengthening is limited.

This research aims at studying the performance of strengthened rectangular reinforced concrete short columns with CFRP strips using FE method, developing interaction diagrams of strengthened columns in order to investigate the effect of different parameters such as compressive strength (20, 30 and 40 MPa), number of CFRP strips (1, 2, 3 and 4) and the spacing between CFRP strips in terms of the ratio of CFRP center point distance to column outside dimension ratio (0.60, 0.70 and 0.80) on the behavior of strengthened RC columns and improving empirical formulas to predict the nominal axial load and moment capacities of strengthened RC columns. These parameters that directly affect short column load carrying capacity are presented in ACI-318 (2014).

This study aims to evaluate the failure behavior of glass fiber-reinforced epoxy (GFRE) laminate subjected to cyclic loading conditions. It involves experimental investigation and statistical analysis using Weibull distribution to characterize the failure behavior of the GFRE composite laminate.

Fatigue tests were conducted using a tension–tension loading scheme at a frequency of 2 Hz and a loading ratio (R) of 0.1. The tests were performed at five different stress levels, corresponding to 50%–90% of the ultimate tensile strength (UTS). Failure behavior was assessed through cyclic stress-strain hysteresis plots, dynamic modulus behavior and scanning electron microscopy (SEM) analysis of fracture surfaces.

The study identified common modes of failure, including fiber pullouts, fiber breakage and matrix cracking. At low stress levels, fiber breakage, matrix cracking and fiber pullouts occurred due to high shear stresses at the fiber–matrix interface. Conversely, at high stress levels, fiber breakage and matrix cracking predominated. Higher stress levels led to larger stress-strain hysteresis loops, indicating increased energy dissipation during cyclic loading. High stress levels were associated with a more significant decrease in stiffness over time, implying a shorter fatigue life, while lower stress levels resulted in a gradual decline in stiffness, leading to extended fatigue life.

This study makes a valuable contribution to understanding fatigue behavior under tension–tension loading conditions, coupled with an in-depth analysis of the failure mechanism in GFRE composite laminate at different stress levels. The fatigue behavior is scrutinized through stress-strain hysteresis plots and dynamic modulus versus normalized cycles plots. Furthermore, the characterization of the failure mechanism is enhanced by using SEM imaging of fractured specimens. The Weibull distribution approach is used to obtain a reliable estimate of fatigue life.

Construction material management is an important process in supporting construction operations that affect project performance. Previous studies attempt to identify factors influencing material management in different stages such as procurement, transportation and utilization. However, they lack a model to explain the relationship between influential factors and the effectiveness of material management. Therefore, this study aims to validate the variables and key factors influencing the effectiveness of material management processes.

A total of 42 variables were reviewed from literature in different stages of material management process. Survey questionnaires were used to collect data about participants' perceptions on these variables. The respondents were 200 project engineers and project managers from construction sites and offices in Vietnam. Then factor analysis techniques were undertaken to validate the structure of factor groups. Two methods of exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were, respectively, performed to evaluate and verify the model's fit.

Factors influencing the effectiveness of material management were grouped into nine main factors, which are procurement issues, site conditions, planning and handling on site, industrial environments, contractual issues, quality control, suppliers and manufacturers' issues, transportation in and out site and security on site.

The paper has several implications for theory and methodology related to material management. It features influential factors in association with the material management effectiveness. Therefore, senior managers can more fully understand the errors in their works and propose timely solutions to limit the unwanted risks.

This research contributes on theoretical development on factors influencing effectiveness of material management processes. The key findings on influential factors can be applied to measure the effectiveness of material management processes.

Lattice structures are widely used for achieving optimal topology in additive manufacturing. However, the use of different lattices in a single design can result in stress concentrations at the transition points. This study aims to investigate the influence of Bezier curves on mechanical properties during the transformation from one lattice structure to another. It specifically focuses on the transition from a hexagonal to diamond lattice, using Bezier curves of various orders.

The curves were designed by passing them through the same control points for different orders, such as third, fifth and seventh. The samples were sliced for 3D printing, and a tensile test was conducted. Young’s modulus and energy absorption abilities were measured to compare the mechanical properties of the models created with Bezier curves for the transformation between hexagonal and diamond models.

The analysis revealed a gradual change in mechanical properties from the hexagonal to the diamond lattice. Moreover, different orders of Bezier curves exhibited varying mechanical properties during the transformation between the two lattices. As the order of the Bezier curve increased, the mechanical properties smoothly changed from the hexagonal to diamond lattice. This prevented stress concentrations or mechanical behavior mismatch caused by sudden deformations at the transitions between the curves used in the design.

The study’s innovative use of Bezier curves of different orders to smoothly transformation between hexagonal and diamond lattices in additive manufacturing offers a practical solution to prevent stress concentrations and mechanical inconsistencies during such design transitions.