Complex Structural Components Research Articles

Numerical Simulations and Experimental Verification of T-Structure Welding Deformation Using the Step-by-Step Loading Inherent Strain Method

The existing inherent strain method is improved in this paper to address the shortcomings of the existing inherent strain method in the process of loading inherent strain. Unlike the traditional inherent strain method, which uses one-step loading inherent strain for each weld seam for one-time elastic calculation, the improved inherent strain method uses step-by-step loading inherent strain for each weld seam for multiple elastic calculations to predict welding deformation. The step-by-step loading inherent strain method (SBS-ISM) is more in line with the actual welding deformation generation process. Firstly, the local finite element model of the T-joint was used to analyze the welding deformation and extract the inherent strain by using the thermal elastic–plastic finite element method (TEP-FEM). Subsequently, the one-step loading inherent strain method (OS-ISM) and the step-by-step loading inherent strain method (SBS-ISM) were used to predict the welding deformation for the same local finite element model, respectively. The comparative results showed that the trend and magnitude of welding deformation calculated using SBS-ISM was much closer to those calculated using TEP-FEM. The OS-ISM and SBS-ISM were used to predict the welding deformation of the backward centrifugal fan impeller under different welding sequences, respectively. By comparing the welding deformation results calculated using the two inherent strain methods with the experimental results, it was demonstrated that the step-by-step loading inherent strain method (SBS-ISM) provides more accurate and reliable predictions of welding deformation for large and complex thin-walled T-shaped structural components compared to the one-step loading inherent strain method (OS-ISM).

Predicting characteristics of cracks in concrete structure using convolutional neural network and image processing

The degradation of infrastructures such as bridges, highways, buildings, and dams has been accelerated due to environmental and loading consequences. The most popular method for inspecting existing concrete structures has been visual inspection. Inspectors assess defects visually based on their engineering expertise, competence, and experience. This method, however, is subjective, tiresome, inefficient, and constrained by the requirement for access to multiple components of complex structures. The angle, width, and length of the crack allow us to figure out the cause of the propagation and extent of the damage, and rehabilitation can be suggested based on them. This research proposes an algorithm based on a pre-trained convolutional neural network (CNN) and image processing (IP) to obtain the crack angle, width, endpoint length, and actual path length in a concrete structure. The results show low relative errors of 2.19%, 14.88%, and 1.11%, respectively for the crack angle, width, and endpoint length from the CNN and IP methods developed in this research. The actual path length is found to be 14.69% greater than the crack endpoint length. When calculating the crack length, it is crucial to consider its irregular shape and the likelihood that its actual path length will be greater than the direct distance between the endpoints. This study suggests measurement methods that precisely consider the crack shape to estimate its actual path length.

Additive Manufacturing of Advanced Ceramics Using Preceramic Polymers

Ceramic materials are used in various industrial applications, as they possess exceptional physical, chemical, thermal, mechanical, electrical, magnetic, and optical properties. Ceramic structural components, especially those with highly complex structures and shapes, are difficult to fabricate with conventional methods, such as sintering and hot isostatic pressing (HIP). The use of preceramic polymers has many advantages, such as excellent processibility, easy shape change, and tailorable composition for fabricating high-performance ceramic components. Additive manufacturing (AM) is an evolving manufacturing technique that can be used to construct complex and intricate structural components. Integrating polymer-derived ceramics and AM techniques has drawn significant attention, as it overcomes the limitations and challenges of conventional fabrication approaches. This review discusses the current research that used AM technologies to fabricate ceramic articles from preceramic feedstock materials, and it demonstrates that AM processes are effective and versatile approaches for fabricating ceramic components. The future of producing ceramics using preceramic feedstock materials for AM processes is also discussed at the end.

Fused deposition modeling of carbon‐reinforced polymer matrix composites: A comprehensive review

AbstractCarbon‐reinforced polymer matrix composites (PMCs) have been thoroughly applied in different fields because of their benefits, such as low specific gravity, corrosion resistance, good electrical conductivity, and robust mechanical properties. Especially, with the emergence of fused deposition modeling (FDM) technology has further promoted the application of such materials in complex structural components. Recently, FDM printing carbon‐reinforced PMCs have become a hot topic in composites research, and many promising results have been achieved around related research. In order to help readers have a comprehensive and systematic understanding of the latest research progress of FDM printing carbon‐reinforced PMCs in terms of material modification, processing, material properties, and application levels, this paper reviews the properties and processes of FDM printed carbon‐reinforced PMCs and their potential applications in aerospace, flexible sensing, electrochemistry, and biomedical fields. The effects of commonly used carbon reinforcing materials on the performance of FDM printed PMCs were contrasted and analyzed. Moreover, the process optimization of printing carbon‐reinforced PMCs was introduced and highlighted. Finally, the current challenges and future research directions of FDM printing carbon‐reinforced PMCs were analyzed and prospected.

Visualizing heterogeneous dipole fields by terahertz light coupling in individual nano-junctions

The challenge underlying superconducting quantum computing is to remove materials bottleneck for highly coherent quantum devices. The nonuniformity and complex structural components in the underlying quantum circuits often lead to local electric field concentration, charge scattering, dissipation and ultimately decoherence. Here we visualize interface dipole heterogeneous distribution of individual Al/AlOx/Al junctions employed in transmon qubits by broadband terahertz scanning near-field microscopy that enables the non-destructive and contactless identification of defective boundaries in nano-junctions at an extremely precise nanoscale level. Our THz nano-imaging tool reveals an asymmetry across the junction in electromagnetic wave-junction coupling response that manifests as hot (high intensity) vs cold (low intensity) spots in the spatial electrical field structures and correlates with defected boundaries from the multi-angle deposition processes in Josephson junction fabrication inside qubit devices. The demonstrated local electromagnetic scattering method offers high sensitivity, allowing for reliable device defect detection in the pursuit of improved quantum circuit fabrication for ultimately optimizing coherence times.

Development of a Deep Learning Platform for Sheet Stamping Geometry Optimisation under Manufacturing Constraints

Sheet stamping is a widely adopted manufacturing technique for producing complex structural components with high stiffness-to-weight ratios. However, designing such components is a non-trivial task that requires careful consideration of manufacturing constraints to avoid introducing defects in the final product. To address this challenge, this research introduces a novel deep-learning-based platform that optimises 3D component designs by considering manufacturing capabilities. This platform was realised by developing a methodology to combine two neural networks that handle non-parametric geometry representations, namely a geometry generator based on Signed Distance Fields (SDFs) and an image-based manufacturability surrogate model. This combination enables the optimisation of complex geometries that can be represented using various parameterisation schemes. The optimisation approach implemented in the platform utilises gradient-based techniques to update the inputs to the geometry generator based on manufacturability information from the surrogate model. The platform is demonstrated using two geometry classes, Corners and Bulkheads, each having three geometry subclasses, with four diverse case studies conducted to optimise these geometries under post-stamped thinning constraints. The case studies demonstrate how the platform enables free morphing of complex geometries, while also guiding manufacturability-driven geometric changes in a direction that leads to significant improvements in component quality. For instance, one of the cases shows that optimising the complex component geometry can reduce the maximum thinning from 45% to satisfy the thinning constraint of 10%. By utilising the proposed platform, designers can identify optimal component geometries that ensure manufacturing feasibility for sheet stamping, reducing design development time and design costs.

The influence of keyhole dynamic behaviors on the asymmetry characteristics of weld during dissimilar materials laser keyhole welding by experimental and numerical simulation methods

The joining of dissimilar materials has been attracted more and more attention and widely used in the manufacturing of complex structural components. Due to the difference of thermophysical parameters of materials, the formed weld tends to show the asymmetry characteristics including geometric morphology and alloy compositions during the process of dissimilar materials laser welding. Therefore, a 3D multiphase flow model is proposed in this paper to investigate the asymmetry characteristics of weld formed in the dissimilar materials laser keyhole welding. The results obtained from the molten pool behaviors calculation under different welding conditions are compared and the effects of welding conditions on the molten pool behaviors induced by keyhole generation are discussed in detail. The weld geometries and alloy compositions distribution under different welding process conditions are obtained. Simultaneously, the effects of keyhole dynamic behaviors on the geometrical morphology of weld and asymmetry distribution of alloy compositions are analyzed. The good agreement between the calculated and experimental results is found, which approves that the developed model can be used to improve the weld geometric morphology and alloy compositions. Hence, the proposed method is efficient for welding process improvement to obtain the desired welded joints in practical dissimilar materials laser keyhole welding.

Surface characterization of SAE 304 after WED cutting: an experimental investigation and optimization

Stainless steel 304 is an iron-chromium-nickel-based alloy developed for structural applications. This alloy exhibits good mechanical strength along with excellent resistance to various atmospheric conditions. Due to the increasing demand for complex, precise, and high-quality structural components, the wire-electrical-discharge-cutting (WEDC) process is recommended as a powerful technique instead of conventional machine tools. The experimental layout is designed based on L27 Taguchi orthogonal array where pulse-on-time, pulse-off-time, servo voltage, and wire feed are selected as control variables. Post experimentation, roughness profile, topography, morphology, recast surface, and subsurface microhardness of the cut section of SAE 304 alloy were evaluated. Thereafter, the desirability function approach is used to find the optimum cutting conditions. The experimental investigation reveals lower profile roughness, smoother topography, no micro-cracks, least recast layer, and minimum hardness alteration under a trim-cut strategy which is found to be useful for safe, durable, and high–strength complex structural components.

A new multi-scale coupling simulation of natural circulation system based on self-adaption data interaction method

Multi-scale coupling simulation can obtain both system characteristics and three-dimensional flow field of complex structural components. Therefore, it is a significant method to investigate the safety on passive systems of nuclear reactor. Aiming at the problems in the existing data interaction strategy, this paper first built an adaptive threshold function based on historical interaction information, developed the updating strategy of natural circulation flow velocity, and proposed the optimization strategy for initial flow velocity. And then, it compared and analyzed the difference between fixed iteration number method and self-adaption data interaction method. The results showed that the convergence speed was increased by more than 78%. Both convergence speed and convergence ability were not affected by initial flow velocity. The study provides some constructive instructions to build multi-scale coupling simulation with high efficiency and strong robustness, and is helpful in jointly optimizing the design of system characteristics and nuclear reactor structure.

Material extrusion additive manufacturing of 17–4 PH stainless steel: effect of process parameters on mechanical properties

Purpose Regardless of the materials used, additive manufacturing (AM) is one of the most popular emerging fabrication processes used for creating complex and intricate structural components. This study aims to investigate the effects of process parameters – namely, nozzle diameter, layer thickness and infill density on microstructure as well as the mechanical properties of 17–4 PH stainless steel specimens fabricated via material extrusion AM. Design/methodology/approach The experimental approach investigates the effects of printing parameters, including nozzle diameter, layer thickness and infill density, on surface roughness, physical and mechanical properties of the printed specimens. The tests were triplicated to ensure reproducibility of the experimental results. Findings The highest ultimate tensile strength, 795.26 MPa, was obtained on specimen that was fabricated with a 0.4 mm nozzle diameter, 0.14 mm layer thickness and 30% infill density. Furthermore, a 0.4 mm nozzle diameter also provided slightly better ductility. This came at the expense of surface finishing, as a 0.25 mm nozzle diameter exhibited better surface finishing over a 0.4 mm nozzle diameter. Infill density was shown to slightly influence the tensile properties, whereas layer thickness showed a significant effect on surface roughness. By contrast, hardness and ductility were independent of nozzle diameter, layer thickness and infill density. Originality/value This paper presents a comprehensive analysis relating to various input printing parameters on microstructural, physical and mechanical properties of additively manufactured 17–4 PH stainless steel to improve the printability and processability via AM.

Build an Integrated Scene Teaching System for Additive Manufacturing Based on the Integration of Production and Education

Additive manufacturing, also known as 3D printing, is known as one of the subversive intelligent manufacturing technologies that can lead industrial transformation. It has significant advantages in personalized customization and preparation of complex structural components, and is having an important impact on traditional manufacturing process, factory production and processing mode and the entire manufacturing industry chain. At present, the talent gap of additive manufacturing and related specialties in China exceeds 10 million, of which the manufacturing industry has the largest demand for additive manufacturing application talents. It is estimated that the talent gap will be 8 million by 2025. The construction of scenario based teaching system of additive manufacturing integrated courses based on the integration of production and education. At present, it is urgent for universities and vocational education to fully integrate the “research” and “technology” of universities and vocational education institutions with the “production” of enterprises to build a scenario of production and education integration education that suits students. By creating real and vivid scenes for students, Help students get familiar with the background and business operation process of the integrated operation of additive manufacturing, strengthen students’ ability to integrate theoretical knowledge, and apply what they have learned in combination with practice.

A novel methodology for the prediction of the stress–strain response of laser powder bed fusion lattice structure based on a multi-scale approach

Additive manufacturing (AM), and in particular laser powder bed fusion (LPBF), is a technology that allows to easily produce geometrically complex structural components. Among others, an example is represented by lattice structures which allow to obtain lightweight components with enhanced mechanical properties. Despite a large number of papers available in the literature, mechanical behavior of lattice structures made by LPBF is still difficult to predict, due to microstructure modifications induced by their small features, scanning strategy and building direction. In this regard, a multi-scale approach to predict the effective σ−ϵ response within the lattice structure is proposed in this investigation. It mainly consists in local measurements by nano-indentation tests, carried out at different portion of the lattice structure and along different orientation to build the effective constitutive response of the component. In this way, possible modifications induced by the LPBF process within the microstructure can be captured. Relying on experimental investigations at both macro and nano-scale, a numerical model for stainless steel 316L octet-truss lattice specimen has been calibrated. To improve the accuracy of the simulations, the geometrical model was built starting from the real geometry of the component through μ-CT images. Obtained results revealed that using the as-built geometry and effective local properties is fundamental for an accurate prediction of the mechanical behavior of lattice structures made by LPBF manufacturing process.

Surface improvement of laser powder bed fusion processed Ti6Al4V for fatigue applications

• Effect of wet-chemical etching of LPBF Ti6Al4V using 5%HF+10%HNO 3 solution on surface quality and fatigue properties was studied. • Etching results in 5-fold reduction in average roughness (from 32.7 to 6.4 µm), leading to a 2-fold increase in fatigue endurance limit (from 150 MPa to 300 MPa). • The effect is highly consistent on complex geometrical surfaces, as demonstrated in case of AM lattice structure. Laser Powder Bed Fusion holds significant potential for the manufacturing of highly complex Ti6Al4V structural components, however the as-produced surface roughness severely limits the fatigue life of components. To reduce the effect of high surface roughness, post processing methods applicable to all geometries are desired. In this study wet-chemical etching methods were examined with regard to fatigue performance. Wet-chemical etching techniques with hydrofluoric acid-containing solutions were assessed for the change in surface condition, material loss, and resultant fatigue response across a range of chemical etchants, with reference to the as-built and machine finished states. Hydrofluoric and nitric acid containing solutions proved to be effective in reducing average surface roughness R a from 32.7 µm to 6.4 µm, and doubling the effective fatigue endurance limit from 150 MPa to 300 MPa.

CFD–DPM Simulation Study of the Effect of Powder Layer Thickness on the SLM Spatter Behavior

Selective Laser Melting (SLM) has significant advantages in manufacturing complex structural components and refining the alloy microstructure; however, spatter, as a phenomenon that accompanies the entire SLM forming process, is prone to problems such as inclusions, porosity, and low powder recovery quality. In this paper, a Computational Fluid Dynamics–Discrete Particle Method (CFD–DPM) simulation flow for predicting the SLM spatter behavior is established based on the open-source code OpenFOAM. Among them, the single-phase flow Navier–Stokes equation is used in the Eulerian framework to equivalently describe the effect of metal vapor and protective gas on the flow field of the forming cavity, and the DPM method is used in the Lagrangian framework to describe the metal particle motion, and the factors affecting the particle motion include particle–particle collision, particle–wall collision, fluid drag force, gravity, buoyancy force, and additional mass force. In addition, the equivalent volume force and fluid drag force are used to characterize the fluid–particle coupling interaction. For the spatter behavior and powder bed denudation phenomenon, the calculation results show that the spatter height and the drop location show a clear correlation, and the powder bed denudation phenomenon is caused by the high-speed gas flow, causing the surrounding gas to gather in the forming area, which in turn drives the motion of the powder bed particles. For the effect of powder layer thickness on spatter and powder bed denudation, the calculation results show that the effect of powder layer thickness on the number of spatters is large (when the thickness was increased from 50 μm to 100 μm, the number of spatters increased by 157%), but the effect on spatter height and drop location distribution is small. When the powder layer thickness is small, the width of the denudation zone is significantly larger, but when the powder layer reaches a certain thickness, the width of the denudation zone does not show significant changes. It should be noted that the presented model has not been directly validated by experiments so far due to the difficulty of tracking the large-scale motion of SLM spatter in real time by current experimental means.

A comparative study on precipitation behavior of a sand-cast Al–Li–Cu alloy with the different quenching rates

The performance of large-size structural components with varied wall thickness is mainly determined by the quench sensitivity, while there was a blank of the studies on the quench sensitivity of cast Al–Li alloys. In this study, the precipitation behavior of sand-cast Al–2Li–2Cu-0.5Mg-0.15Sc-0.15Zr-0.05Ti alloy subjected to different quenching conditions in room temperature water, boiling water and air was compared. The effect of the quenching rates on the formation mechanisms of δ΄ (Al3Li) and T1 (Al2CuLi) precipitates was discussed. It was found that a rapid quenching rate facilitated the precipitation of T1 phases and the refinement of δ′ phases, which contributes to the improvement of the mechanical properties. During the subsequent ageing, the strength and ductility were enhanced with the quenching rate increasing, but the strength did not vary by more than 15%, indicating that the sand-cast Al–Li–Cu alloy owns a lower quench sensitivity. This work is expected to enlighten the understanding of the evolution mechanisms of precipitates during quenching and provide a reference for the heat treatment of complex structural components for cast Al–Li alloys.

Study on microscopic fringe structured light measurement method for tiny and complex structural components

Study on microscopic fringe structured light measurement method for tiny and complex structural components

Fluorescence inner filters of Arthrospira platensis: Novel perspective for precise fluorescence-based sensors

Microalgae have been reputed as novel biological materials due to their unique structure, surface functionality and optical activity, making them worthwhile agents in biosensing and theranostic applications. However, further scrutiny is required for utilizing them in routine optical techniques due to their complex structure and diverse chemical components. Here, laser induced fluorescence (LIF) features of a bio-compatible microalgae i. e. Arthrospira platensis (Spirulina) have been assessed. Typical fluorescence properties as well as the inner filter effects (IFEs) were examined and revealed to be strongly dependent on concentration, excitation wavelength, and detection geometry as well. IFEs and resulting spectral shifts have been analyzed considering various SP chromophores, reabsorption processes, and resonance energy transfer (RET) mainly from “Carotenoids to Phycobilisomes” as well as “Phycobilisomes to Chlorophyll-a”. As a result, LIF spectral shift due to the re-absorption events (secondary-IFE) is introduced as a credible parameter for design of precise fluorescence-based sensors, due to being less dependent on ambient noises. We hope that the findings provide novel features regarding the LIF of Spirulina (SP) that could be utilized to design and develop optical sensors in the field of photonics, material diagnosis and biomedical theranostics.

Building height-related creep properties of Inconel 718 superalloy fabricated by laser powder bed fusion

The building height-dependent creep properties and microstructures of laser powder bed fusion-fabricated Inconel 718 superalloy were investigated. Creep specimens taken from the as-fabricated plate component at different building heights were tested along the building direction at 650 °C. The results show that under the same heat treatment condition, the recrystallization degree of the specimens taken from the bottom, middle and top of the Inconel 718 plate component differs widely due to the differences in the dislocation density and the texture intensity along the building direction. The bottom specimen exhibited a high recrystallization degree and thus had the longest creep life. Such excellent creep properties of the bottom specimen are mainly attributed to the lower dislocation density and the higher Taylor factor, which cause the lower creep rate, and the lower grain boundary volume fraction, thus reducing the void nucleation sites. The present findings reveal that the impact of the building height-dependent creep performance on the overall service reliability should be considered comprehensively in the subsequent geometrical design of the laser powder bed fusion-fabricated complex structural components.

Seismic Response Analysis of Anchor Joint in Shield–Driven Tunnel Considering Soil–Structure Interaction

The seismic behavior of the anchor joint in shield-driven tunnel is very difficult to determine with the conventional methods due to the extensive simplifications. This paper proposed an improved approach to investigate the seismic response of the anchor joint, considering both the soil-structure-interaction effect and the actual geometric features. Two three-dimensional numerical models were established, including the soil-tunnel system and the refined model of the anchor joint. A seismic analysis study was first conducted on the soil-tunnel model under different seismic input waves to obtain the responses of the joint opening and offset. Then, these results were imposed on the refined model of anchor joint to further examine its detailed performance under seismic excitations. The joint opening and offset under earthquake excitations from different directions were discussed. The distribution characteristics of the stress of the anchor joint were interpreted. Finally, safety evaluations on the anchor joint were executed based on the overall seismic responses. The results show that the maximum opening and offset of the anchor joint under the two-directional horizontal earthquake are greater than those under the unidirectional conditions, while different deformation trends are observed for the joints at distinct locations. The maximum opening of the anchor joint can reach 0.73 mm, whereas the peak offset is only 0.35 mm. The local plastic strain of the anchor joint increases under the seismic action, but all of the joints are still kept in the safe state under the most unfavorable conditions. The developed method in this paper can also be accessed by the seismic study on other types of joints with complex structural components in shield tunnels.

Three-dimensional shape and deformation measurement on complex structure parts

Stereo digital image correlation technique (stereo-DIC or 3D-DIC) has been widely used in three-dimensional (3D) shape and deformation measurement due to its high accuracy and flexibility. But it is a tough task for it to deal with complex structure components because of the severe perspective distortion in two views. This paper seeks to resolve this issue using a single-camera system based on DIC-assisted fringe projection profilometry (FPP). A pixel-wise and complete 3D geometry of complex structures can be reconstructed using the robust and efficient Gray-coded method based on a FPP system. And then, DIC is just used to perform the temporal matching and complete full-field pixel-to-pixel tracking. The in- and out-of-plane deformation are obtained at the same time by directly comparing the accurate and complete 3D data of each corresponding pixel. Speckle pattern design and fringe denoising methods are carefully compared and chosen to simultaneously guarantee the measuring accuracy of 3D shape and deformation. Experimental results demonstrate the proposed method is an effective means to achieve full-field 3D shape and deformation measurement on complex parts, such as honeycomb structure and braided composite tube, which are challenging and even impossible for the traditional stereo-DIC method.