Search results

The purpose of this study is to mitigate the dimensional inaccuracy due to vertical curling/bending deformation of three-dimensional (3D) printed parts produced by selective laser sintering (SLS) using PA12 based on dimensional compensation of the computer-aided design (CAD) model.

To carry out this study, specially designed features are initially produced as references, and the dimensional deviations from the vertical bending deformation of the SLS process are analyzed. Next, the deformation patterns are formulated using a polynomial regression model in the global Cartesian coordinates of the building platform. Then, the compensation algorithm is implemented and the original 3D CAD file is preprocessed with an inverse transformation of the features to compensate the deformation errors.

It was found that the 3D printed parts from the SLS process have the dimensional inaccuracy due to the vertical bending pattern of the quadratic form. By implementing the compensation algorithm, it was statistically shown to effectively reduce bending deformations of various sample parts, including the automotive components, in SLS.

The position of samples in a batch has a direct impact on not only bending deformation but also on horizontal shape geometry error. However, the application of this algorithm is focused on the vertical bending deformation, which is estimated as a major part of dimensional inaccuracy.

This paper provides a practical case study with a real vehicle part. The algorithm was shown to provide a more realistic solution to the dimensional deformation of printed products, which is not manageable by simply using the constant scale factors provided by SLS 3D printer manufacturers.

This paper suggests that the vertical bending deformation from SLS’s 3D printed complex parts can be improved through the proposed compensation algorithm. The compensation algorithm was constructed by using the predictive regression model created from the bending deformation patterns of reference samples. The proposed compensation algorithm can be further used and applied for other complex samples without making additional reference parts.

The gas tungsten arc welding (GTAW) process is a widely used process that produces quality weldments. But the high heat generation from the GTAW arc can cause extreme temperatures as high as 20,000°C. The residual stresses and deformations are high accordingly. One of the methods for decreasing residual stresses and deformations is to change the welding pattern. In the literature, there are not so many examples of modeling dealing with welding patterns. This paper aims to investigate the influence of welding patterns on the deformations.

In this work, back-stepping patterns and partitioning of the weld line were investigated and the distortions and residual stresses were calculated. By doing this, temperature-dependent thermophysical and thermo-mechanical material properties were used. The temperature distribution and deformation from experiments with the same welding conditions were used for validation purposes.

Seven different welding patterns were analyzed. There is only one pattern with a single partition. There are three patterns investigated for both two and three partitioned weldings. The minimum deformation and the optimum residual stress combination is obtained for the last pattern, which is a three partitioned and diverging pattern.

The most important aspect of this paper is that it deals with welding patterns, which is not much studied beforehand. The other important thing is that the structural part and the thermal part of the simulation were coupled mutually and validated according to experiments.

The purpose of this paper is to provide a comprehensive review of a non-contact full-field optical measurement technique known as digital image correlation (DIC).

The approach of this review paper is to introduce the research pertaining to DIC. It comprehensively covers crucial facets including its principles, historical development, core challenges, current research status and practical applications. Additionally, it delves into unresolved issues and outlines future research objectives.

The findings of this review encompass essential aspects of DIC, including core issues like the subpixel registration algorithm, camera calibration, measurement of surface deformation in 3D complex structures and applications in ultra-high-temperature settings. Additionally, the review presents the prevailing strategies for addressing these challenges, the most recent advancements in DIC applications across quasi-static, dynamic, ultra-high-temperature, large-scale and micro-scale engineering domains, along with key directions for future research endeavors.

This review holds a substantial value as it furnishes a comprehensive and in-depth introduction to DIC, while also spotlighting its prospective applications.

Riveting deformation is inevitable because of local relatively large material flows and typical compliant parts assembly, which affect the final product dimensional quality and fatigue durability. However, traditional approaches are concentrated on elastic assembly variation simulation and do not consider the impact of local plastic deformation. This paper aims to present a successive calculation model to study the riveting deformation where local deformation is taken into consideration.

Based on the material constitutive model and friction coefficient obtained by experiments, an accurate three-dimensional finite element model was built primarily using ABAQUS and was verified by experiments. A successive calculation model of predicting riveting deformation was implemented by the Python and Matlab and was solved by the ABAQUS. Finally, three configuration experiments were conducted to evaluate the effectiveness of the model.

The model predicting results, obtained from two simple coupons and a wing panel, showed that it was a good compliant with the experimental results, and the riveting sequences had a significant effect on the distribution and magnitude of deformation.

The proposed model of predicting the deformation from riveting process was available in the early design stages, and some efficient suggestions for controlling deformation could be obtained.

A new predicting model of thin-walled sheet metal parts riveting deformation was presented to help the engineers to predict and control the assembly deformation more exactly.

Double-jacquard technique is referred as the most advanced technology for forming patterns on both layers of a 3D fabric knitted on a double-needle bar warp-knitting machine. In order to realize the computer-aided design and simulation of jacquard patterns, the purpose of this paper is to propose a mathematic model for representation of jacquard structures and an improved mass-spring model to improve the simulation of structural deformation behavior.

Primarily, it analyzes the jacquard patterning method and displacing principle to design jacquard structures on each layer and linking structures of two layers. Based on that, a loop geometry defined by six key points and segmental lines is built to transfer the jacquard bitmap and lapping movements into a fabric of loops and therefore realizing patterns visualization. Afterwards, an improved mass-spring model is built to simulate structural deformation, in which the fabric is simplified as a mesh of uniformly distributed mass particles. Each loop is treated as a massless particle while underlaps are referred as structural springs connecting loops particles. Elastic forces of these springs on each loop particle is calculated according to the Hook’s law and Newton’s second law, and then based on the explicit Euler’s equations, motion state of each particle is solved including the velocity and the shift.

Based on the above method, a simulator for double-layer jacquard fabrics is developed via Visual C++ language to visualize the patterned fabrics with pitting effects. With a jacquard shoe fabric as an example, this simulation model is proved to be practical and efficient by comparing the simulation result and real fabric.

Because of limited researches, 3D simulation modeling of this double-layer jacquard fabric will be studied in the further research.

The implement of this simulation method will offer the industries a time-saving and cost-saving approach for new fabrics development.

This approach can be used as a reference for simulating other knitted fabrics with jacquard patterns, such as jacquard garment fabrics and home textile fabrics.

Additive manufacturing (AM) promises to reduce the weight of the component, it is required to be shown that the mechanical performance of AM parts meets stringent industrial design criteria. Very few studies are made on finite element analysis (FEA) of the component produced by AM for real-life workload conditions. This study is supposed to do FEA of the wheel hub, manufactured using metal three-dimensional (3D) printing, under static multi-load conditions and effect of infill pattern on maximum stress, deformation and factor of safety.

This study conducted FEA on wheel-hub using Ansys. The approach of Orthotropic properties is used to do static analysis of wheel-hub and compared results of different metal 3D printing material (Ti-6Al-4V and Al-Si10-Mg) with hexagonal and triangular infill patterns.

Ti-6Al-4V with Honeycomb patterns shows better results in all cases and can be replaced with standard conventional material.

Because of the chosen research approach, the research results may lack generalisability. Therefore, it is required to do an experimental study.

Metal components with applications across the automobile industry can be manufactured using AM technology. With the help of AM, components with high strength to weight ratio can be manufactured.

This paper fulfils the identified need of FEA of the component produced by AM for real-life workload conditions. This study is supposed to do FEA of the wheel hub, manufactured using metal 3D printing, under static multi-load conditions and Effect of infill pattern on maximum stress, deformation and factor of safety.

Integrity of surface mount technology (SMT) components depends on their response to temperature changes caused by operating conditions. Temperature induced differential thermal expansions lead to strains in the interconnection structures of active devices. To evaluate these strains, temperature profiles of the interconnected components must be known. In this paper, a methodology for developing thermal models of SMT components is presented using thermal analysis system (TAS) and its application is demonstrated by simulating thermal fields of a representative package. Then, thermomechanical deformations of the package are measured quantitatively using state‐of‐the‐art laser‐based optoelectronic holography (OEH) methodology.

The purpose of this study is to numerically assess the misalignment-induced deformation and its implications, in the through-silicon via (TSV), silicon chip, solder micro-bump, and bonding layer.

The 3D finite element model features a TSV/micro-bump bonding structure connecting two adjacent silicon (Si) chips, with and without an underfill layer between. A case that the entire solder layer has transformed into an intermetallic layer is also considered.

The existence of an underfill layer enhances the overall resistance to shear deformation, although with a higher buildup of local stresses. High shear and tensile stresses can develop in the intermetallic and nearby regions of copper and Si if the solder alloy is replaced by an intermetallic layer. The carrier mobility change in Si may be extensively affected by the mechanical action, even in regions far away from the TSV.

This work parametrically explores the trend of stress and deformation fields due to mechanical shear and its influences on the electrical performance of devices. Potential for damage initiation in the TSV/micro-bump is also examined.

The purpose of this paper is to explore the basic loading state in local loading forming process of large-sized complicated rib-web component, which is important for understanding process characteristic, controlling metal flow and designing preformed geometry of the local loading forming process. Moreover the analytical models for different loading states are established to quickly predict the metal flow.

Through analysis of geometric characteristic of large-sized complicated rib-web component and the deformation characteristic on planes of metal flow by local loading method, a representative cross-section is put forward and designed, which could reflect the local loading forming characteristics of large-sized complicated rib-web component. Finite element method (FEM) is used to analyze the stress and metal flow, and the analytical models of metal flow are established by using slab method (SM).

Three local loading states and one whole loading state are found in the local loading forming process of representative cross-section. Further, four loading states also exist in local loading forming process of large-sized complicated rib-web components. With the metal distribution in the process, some local loading states may turn into whole loading state. For the representative cross-section, the relative error of metal distribution between SM and FEM results is less than 15 per cent, and the relative error of metal in the rib cavity between SM and FEM results is less than 10 per cent.

Metal flow can be controlled by adjusting the loading states in the process. According to the metal flow laws in different loading states, a simple unequal-thickness billet can be designed to achieve initial metal distribution, and then, the secondary metal distribution can be achieved in the process.

This study aims to automate the process of converting grading patterns into parametric patterns using artificial intelligence and to objectively evaluate the fitness of the converted patterns.

The developed system consists of a user interface that defines input data by importing multi-size grading patterns, an artificial neural network that learns the relationship between human body size and pattern geometry, and a module that converts training results into parametric patterns. In order to evaluate the fitness of the generated pattern, an objective fitting evaluation method using drape simulation was developed.

The body sizes of the wearer were input to the converted parametric pattern to generate a customized pattern. Resulting pattern showed a better fit than the grading pattern on the off-average body model.

In this study, a method has been developed that enables the users with minimal pattern drafting knowledge to convert grading patterns into parametric patterns using artificial intelligence and drape simulation. The human body's symmetry and the physical properties of fabric were not considered.

The system developed in this study requires less data compared to existing methods that attempt to design clothing patterns with machine learning. In addition, it was possible to evaluate pattern fitness on various body models through drape simulation based fit evaluation process for the first time.