Geometrical Defects Research Articles

Formulating a GIS-based geometric design quality assessment model for Mountain highways

Highways play an important role in China’s economic development, especially in mountainous regions. In reality, design of mountainous highways can be a challenging task due to complex geological and topographic conditions. From the safety perspective, it is also important that road geometric design defects and potential accident blind spots can be reasonably identified from the design. To this end, this study formulated an innovative Geographic Information System (GIS)-based geometric design quality assessment model for mountain highways. First, a fault tree analysis (FTA) was conducted to identify a series of highway design risk factors. Second, a decision-making trial and evaluation laboratory (DEMATEL) technique was employed to derive the factors’ weight and sensitivity. Third, road driving suitability, traffic safety sensitivity, design risk factors, and effective distance were taken into account to formulate a design quality assessment model. Forth, two case studies based on a mountainous highway located in southwest China were conducted to validate this model. The case studies established that improving geometric design quality can significantly improve the road traffic safety of mountainous highways. It is also revealed that the existence of steep slopes, tunnels, and rapid horizontal and vertical alignment change can considerably compromise the geometric design quality (GDQ), therefore, configuring these parameters is worth of further investigation. Last but not least, this study provides essential knowledge to the regime of accident prevention, high-risk road section location and mapping, traffic safety management, and design of smart transport systems.

Numerical approach to study the effect of shape defect in multi-fastened joints during the assembly process

When designing joined structures, deterministic approaches are commonly considered insufficient to ensure a good compromise between mechanical performances and manufacturing tolerances due to the many sources of variability. Reliability-based design approaches are promising, but they require structural models that take into account the different sources of variability and the complex physical phenomena that govern their effects on mechanical behaviour.This paper proposes a method to analyse the fastening process of parts that include geometric form defects. The structural behaviour of the joint is simulated using a finite element model combining connectors and rigid surfaces to represent fasteners. With this approach, the calculation time can be drastically reduced while frictional contact is maintained between fasteners and parts. Shape defects are generated by translating parts mesh nodes. The method is applied to a case study and its efficiency is evaluated by analysing the evolution of axial bolt preloads and transverse bolt forces during the assembly process. Results demonstrate the ability of the method to simulate different clamping sequences and to capture the interaction between shape defects, bolt-hole clearance and target axial preload.

A new study for healing pitting defects of 316L stainless steel based on microarc technology

A new method for healing corrosion defects was proposed based on the microarc thermal effect, which is enhanced at local geometric defects according to the local additional potential model (LAPM). Finite element analysis (FEA), corrosion tests and surface characterization were used to simulate the principles and evaluate the healing efficiency. The results showed under the microarc effect, the local additional current can be used to detect and heal corrosion defects. This method has an effective healing ability for the initial corrosion defects, and the healed microstructure was composed of recrystallized grains. After being healed, corrosion performance varies slightly.

Geometrical defect detection for additive manufacturing with machine learning models

This study proposed a scheme based on Machine Learning (ML) models to detect geometric defects of additively manufactured objects. The ML models are trained with synthetic 3D point clouds with defects and then applied to detect defects in actual production. Using synthetic 3D point clouds rather than experimental data could save a huge amount of training time and costs associated with many prints for each design. Besides distance differences of individual points between source and target point clouds, this scheme uses a new concept called “patch” to capture macro-level information about nearby points for ML training and implementation. Numerical comparisons of prediction results on experimental data with different shapes showed that the proposed scheme outperformed the existing Z-difference method in the literature. Five ML methods (Bagging of Trees, Gradient Boosting, Random Forest, K-nearest Neighbors and Linear Supported Vector Machine) were compared under various conditions, such as different point cloud densities and defect sizes. Bagging and Random Forest were found the two best models regarding predictability; and the right patch size was found to be at 20. The proposed ML-based scheme is applicable to in-situ defect detection during additive manufacturing with the aid of a proper 3D data acquisition system.

Investigating Effect of Strain and Geometric Defects on Single Polarization Vortex in PbTiO3 Nanowires

The single polarization vortex structure in nanowire can be used to store binary data in Non-Volatile Ferroelectric Random Access Memories (NVFRAM or FRAM). However, at the nanoscale, mechanical strains or geometry defects (cracks) can affect the polarization vortex and they are one of the reasons to reduce the service life as well as the reliability of the device. In this study, the atomic simulation method using the interactive potential function based on the core-shell model is selected to investigate the effects of strain, cracks and domain wall deviations (DW) on the single polarization vortex in PbTiO3 (PTO) nanowires. The results obtained showed that the polarization vortex can appear or disappear depending on the position and size of the crack. Deviations in the DW position make the polarization vortex change the size and shape. Besides, the magnitude of the vortex investigated increases under tension strain and decreases under compression strain. Especially, in large compression strain (10%), the vortex can be disappeared.

Influence of Laser Beam Power and Scanning Speed on the Macrostructural Characteristics of AISI 316L and AISI 431 Stainless Steel Depositions Produced by Laser Cladding Process

In the laser cladding process, control of the process parameters and knowledge of the characteristics of the materials used are essential for obtaining depositions with excellent metallurgical union, satisfactory dilution values, absence of defects, and acceptable geometric characteristics. Without such precautions, depositions can exhibit low or excess dilution, low wettability, and the presence of pores, consequently reducing the performance of the materials. The aim of the present work was to evaluate the effects of the laser beam power, with maximum power of 4000 W and continuous wave mode, and scanning speed in laser cladding processes employing the AISI 316L austenitic stainless steel and the AISI 431 martensitic stainless steel, considering the geometric characteristics, dilution, and structural defects of the depositions. It was found that the laser power had a greater effect on the width and dilution of the depositions, while the scanning speed influenced the deposition height. The depositions of AISI 431 steel presented dilution values between 9 and 25%, using power settings between 1400 and 1600 W. The depositions of AISI 316L steel required higher power values between 1900 and 2600 W to achieve dilution values between 15 and 41%. The existence of pores and satisfactory hardness values were observed for both materials, with the average of microhardness of 522 HV0.5/15 and 356 HV0.5/15 on the AISI 431 and AISI 316L depositions. It was also found that the different characteristics of the addition metals, considering their morphology, particle size distribution, and flow rate, led to significant changes in the geometric features of the depositions.

Stress-deformed state of the container with the presence of an displacement of the butt edges in the ring welded joint of the body

Capacitive equipment of oil refineries is widely used in the operation of technological units and plays one of the dominant roles, both in terms of metal consumption and the degree of use. Depending on the purpose, the required capacity of the stored product and constructive features, containers reach rather large overall dimensions, which creates certain difficulties in diagnosing the entire surface of the vessel. In the process of manufacturing and repairing the bodies of technological tanks, it is possible to form such a geometric defect as “displacement of the edges of the abutting elements” when welding cylindrical shells to each other by circular welded seams. In the presence of geometric defects of this type, additional stress concentrators are created in the areas of the presence of these defects, which may be a prerequisite for the transition of an object to the limiting state in a fairly short period of time from the action of increased pressures and temperatures. Also, the presence of displacement of the edges on the body of the capacitive apparatuses can have a negative effect on the stress-deformed state of the considered capacity as a whole and to the formation of dislocation zones of increased stresses. Therefore, the actual work is the study of the stress-deformed state of the container with the presence of a zone of displacement of the edges in the circumferential welded seam of the body from the viewpoint of the formation of zones of increased stress. This work evaluates the stress-deformed state of the capacitive apparatus under the influence of operating parameters with a different location of the edge displacement zone in the circumferential weld on the apparatus body.

Comparison and optimisation of fast array-based ultrasound testing

Phased array ultrasonic testing (PAUT) is now a widely used technique in industry for non-destructive testing. Arrays offer an intuitive view of the interior of a component from which geometric features and defects can be observed. Arrays also offer detailed information about the nature and extent of any defects. In recent years, full matrix capture (FMC) and the total focusing method (TFM) have attracted significant interest due to the high resolution of the images possible throughout an inspection volume. Due to the requirement of transmitting on each element separately, full matrix capture-based imaging techniques limit the maximum frame rate and scan speed achievable. Recently, to increase the speed of data acquisition, new techniques such as plane wave imaging (PWI) and virtual source aperture (VSA) have been introduced. They allow a significant reduction in the number of firings to be achieved without contributing to any major loss of image quality. In this paper, an in-depth comparison of these techniques using a hybrid linear system model and the analysis of experimental data is performed to assess the image quality of these emerging imaging algorithms and hence identify the optimal parameters for faster imaging.

In-situ synchrotron X-ray tomography investigation of the imperfect smooth-shell cylinder structure

Lattice materials at micro scale with extraordinary stiffness and strength have demonstrated promising industrial application potentials in aerospace, transport, automotive, biomedical and other sections. However, the complex fabrication process at micro scale will inevitably induce stochastic geometric defects within as-fabricated lattice materials, thus quantitatively evaluation of the mechanical integrity of 3D-printed micro lattice structures becomes a critical important issue. In this paper, mechanical behavior of the micro Schwarz Primitive triply periodic minimal surfaces (P-TPMS) cylinder shell structures fabricated with projection micro-stereolithography (PμSL) 3D printing technique were investigated. Meanwhile, synchrotron X-Ray micro-tomography (SR-μCT) 3D imaging and interrupted in-situ compression experiment were employed for quantifying the effect of defects on the compression mechanical performances. It is found that the thickness along vertical direction was larger than along horizontal direction. Afterwards, three different types of finite element models were developed for understanding the effects of fabrication defects on the mechanical behavior characteristic. Simulation results demonstrated that the statistical model was more accurate and efficient when compared with the ideal model and real geometry reconstructed model. Finally, parametric study was also presented to gain insight into the role of thickness imperfections on the mechanical performance of the shell.

An analytical approach to symmetry breaking in multipole RF-traps

Radio-frequency (RF) linear multipole traps have been shown to be very sensitive to mis-positioning of their electrodes, which results in a symmetry breaking and leads to extra local minima in the trapping potential as shown in Pedregosa-Gutierrez et al (2018 J. Mod. Opt. 65 529) disturbing the operation of the trap. In this work, we analytically describe the RF-potential of a realistic octupole trap by including lower order terms to the well-established equation for a perfectly symmetric octupole trap. We describe the geometry by a combination of identified defects, characterized by simple analytical expressions. A complete equation is proposed for a trap with any electrode deviation relying on a combination of the simple cases where the defects are taken individually. Our approach is validated by comparison between analytical and numerical results for defect sizes up to 4% of the trap radius. As described in Pedregosa-Gutierrez et al (2018 Rev. Sci. Instrum. 89 123101), an independent fine-tuning of the amplitude of the RF voltage applied on each electrode can be used to mitigate the geometrical defects of a realistic trap. In a different way than in Pedregosa-Gutierrez et al (2018 Rev. Sci. Instrum. 89 123101), the knowledge of an analytical equation for the potential allows to design the set of RF-voltages required for this compensation, based on the experimental measurement of the ion positions in the trap, without information concerning the exact position of each electrode, and with a small number of iterations. The requirements, performances and limitations of this protocol are discussed via comparison of numerical simulations and analytical results.

Additively manufactured Ti–6Al–4V thin struts via laser powder bed fusion: Effect of building orientation on geometrical accuracy and mechanical properties

Porous metal lattice structures have a very high potential in biomedical applications, setting as innovative new generation prosthetic devices. Laser powder bed fusion (L-PBF) is one of the most widely used additive manufacturing (AM) techniques involved in the production of Ti6Al4V lattice structures. The mechanical and failure behavior of lattice structures is strongly affected by geometrical imperfections and defects occurring during L-PBF process. Due to the influence of multiple process parameters and to their combined effect, the mechanical properties of these structures are not yet properly understood. Despite the major commitment to characterize and better comprehend lattice structures, little attention has been paid to the impact that single struts have on the overall lattice properties.In this work, the authors have investigated the tensile strength and fatigue behavior of thin L-PBF Ti6Al4V lattice struts at different building orientations (0°, 15°, 45°, and 90°). This investigation has been focused on the effect that microstructural defects (particularly porosity) and actual surface geometry (including surface texture and geometrical errors such as varying cross-section shape and size) have on the mechanical performances of the struts in relation to their building direction. The results have shown that there is a tendency, particularly for low printing angles, of fatigue life to decrease with decreasing of the building angle. This is mainly due to the surge in surface texture and loss in cross-sectional regularity. On the other hand, the monotonic tensile test results have shown a low sensitivity to these factors. The strut failure behavior has been examined employing dynamic digital image correlation (DIC) of tensile tests and scanning electron imaging (SEM) of the fracture surfaces.

Geometrical defect identification of a SCARA robot from a vector modeling of kinematic joints invariants

This article introduces a new geometric vector modeling method of serial kinematic robot consistent with the identification process. This method is based on the definition of position and orientation of the robot joint invariants. For example, the invariant of the rotational joint is a straight-line (rotational joint axis). Thus, only independent geometrical parameters are introduced to model the joint axis position and orientation in space. Note that, the orientation is not constrained as in the Denavit–Hartenberg (DH) formalism. This article presents the methodology to define these geometrical parameters and the geometrical model. In this context, the identification method relies on "Circle Point Analysis". The points are measured with a laser tracker. Indeed, with a relevant processing of the measured points, we directly identify the invariants of joints. This method is applied to a SCARA robot geometric modeling. After an identification process, this methodology allows improving inverse kinematic error compared to the classical DH geometrical model with first and second-order defects. Moreover, the obtained residual error mean value is close to the accuracy of the measurement process.

Mode I critical energy release rate of additively manufactured polyamide samples

One accepted cause that generates low mechanical strength and/or fracture properties is the presence of defects in the structure of the material. Additive Manufacturing does not except this rule, especially the powder bed fusion technologies that relays on powder spreading through a mechanical blade or roller followed by laser sintering or melting. The paper presents experimental investigations on fracture properties of polyamide PA2200 samples obtained by selective laser sintering. The mode I critical energy release rate and mode I fracture toughness were determined in accordance to ASTM D 5528 – 01 for four sets of samples: one set without induced geometrical defects, and three other sets having interlayer and intralayer defects. The results consist of geometrical evaluation of the samples and error computing on one-hand and fracture properties on the other hand. In addition, a study on absorbed energy in the defect section of samples was conducted, leading to a direct correlation between the defect percentages (0.0%, 0.1%, 0.3% and 0.5%) and the absorbed energy.

Image-based numerical characterization and experimental validation of tensile behavior of octet-truss lattice structures

Abstract The production of lightweight metal lattice structures has received much attention due to the recent developments in additive manufacturing (AM). The design flexibility comes, however, with the complexity of the underlying physics. In fact, metal additive manufacturing introduces process-induced geometrical defects that mainly result in deviations of the effective geometry from the nominal one. This change in the final printed shape is the primary cause of the gap between the as-designed and as-manufactured mechanical behavior of AM products. Thus, the possibility to incorporate the precise manufactured geometries into the computational analysis is crucial for the quality and performance assessment of the final parts. Computed tomography (CT) is an accurate method for the acquisition of the manufactured shape. However, it is often not feasible to integrate the CT-based geometrical information into the traditional computational analysis due to the complexity of the meshing procedure for such high-resolution geometrical models and the prohibitive numerical costs. In this work, an embedded numerical framework is applied to efficiently simulate and compare the mechanical behavior of as-designed to as-manufactured octet-truss lattice structures. The parts are produced using laser powder bed fusion (LPBF). Employing an immersed boundary method, namely the Finite Cell Method (FCM), we perform direct numerical simulations (DNS) and first-order numerical homogenization analysis of a tensile test for a 3D printed octet-truss structure. Numerical results based on CT scan (as-manufactured geometry) show an excellent agreement with experimental measurements, whereas both DNS and first-order numerical homogenization performed directly on the 3D virtual model (as-designed geometry) of the structure show a significant deviation from experimental data.

Generation mechanism and suppression method of landing error of two successively deposited metal droplets caused by coalescence and solidification

Accurate deposition of metal droplets is crucial to limit geometrical defects in metal droplet-based 3D printing. However, unpredictable movements of the droplets displaced from the original landing location due to surface tension-driven flow before it is hindered by solidification, named landing error, lead to broken traces, irregular waved surfaces, or collapsed structures. In the present work, the effect of solidification at the early-time coalescence of two deposited metal droplets on the landing error was revealed. High-speed images were presented to observe coalescence dynamics. A volume of fluid (VOF) based numerical model was developed to analyze the generation mechanism of the landing error. An interesting phenomenon is observed that the second droplet absorbs more mass from the first droplet to form a bigger spherical crown with the increase of substrate temperature, resulting in the distinct final shapes. Inspired by this, a mass conservation model was proposed to predict the dependence of the landing error on substrate temperature. Metal droplets overlapping experiments were further conducted to verify the model and establish the relationship between the landing error and the substrate temperature. Predictions agreed well with experimental results. Finally, a strategy of increasing the thermal conductivity of the substrate to suppress the landing error at high substrate temperatures was proposed, which significantly expanded the processing window of the accurate deposition. This work can provide useful theoretical and experimental guidance for accurate printing of high-quality lines or patterns by utilizing metal droplets.

Prediction of the deformed geometry of vat photo-polymerized components using a multi-physical modeling framework

In photopolymerization-based additive manufacturing a complex interplay exists between the vat photopolymerization process characteristics and the (photo-active) resin’s material properties, which governs the trajectory from the input target geometry to the resulting true geometry of a printed component. Particularly for fine featured geometries, there might be a clear mismatch between the latter two. Determining whether the entire component is printable can only be properly assessed through a test-print. The current work proposes an alternative modeling-driven route, which, after system and material characterization, facilitates predicting the geometrical defects of the resulting solidified component (including deformation). This is enabled through a coupled multi-physical modeling of irradiation, photopolymerization, solidification and chemical shrinkage.

Analyzing part accuracy and sources of variability for additively manufactured lattice parts made on multiple printers

Scalable production using additive manufacturing (AM) requires quality systems that monitor and control manufacturing variability across many machines in a factory environment. AM process variability can result in geometric inaccuracies in parts that can affect their mechanical behavior; however, most research focuses on a single machine and hardware set, while part inaccuracy and AM variability across multiple printers remains poorly understood. This study establishes a framework to study the accuracy of polymer parts made on three identical printers and evaluates the role of manufacturing process parameters and their impact on part variability. We fabricate 90 polymer hexagonal lattice parts over nine builds on three identical Carbon M2 machines with interchangeable hardware tools. Each part is measured using automated metrology that extracts the size and shape of the part features and automatically measures defects. Each hexagonal part consists of 237 individual walls that were measured for 90 parts, resulting in 21,330 individual geometric measurements. Using statistical methods to analyze geometric defects as a function of machine, hardware set, and location in the build, we find that the observed variability can be correlated with process parameters. Geometric defects in the wall thickness depend upon machine and location within the build but do not depend on the hardware tool, while geometric defects in the wall length and height of the part depend upon machine and tool but not location. The uniformity within the parts, measured by standard deviations of the individual features within a part, mostly depends upon unmeasured parameters. We use a generalized linear model (GLM) to model the variability and to predict defects. The framework introduced here can be extended to analyze additional machines and process parameters and provides a practical tool to account for manufacturing variability in an AM production environment.

Shear strength reduction of trapezoidal corrugated steel plates with artificial corrosion pits

To investigate the ultimate shear strength reduction of trapezoidal corrugated steel plates (TCSPs) under corrosive condition, TCSPs with artificial corrosion pits (ACP) were taken as the research objects, and nonlinear shear buckling analysis was conducted by numerical simulation and experimental verification based on finite element method (FEM). The formula of the ultimate shear strength reduction coefficient η is proposed using the typical parameters influencing ACP, including ACP range Rr, ACP depth Rd, and equivalent corrosion rate γ. Fifteen specimens were designed with different ACP parameters, including Rr, Rd, and ACP diameter dp, and the shear buckling load test of TCSPs was performed. Results show that the distribution pattern of ACP has no effect on the shear strength of TCSPs, and the error between random distribution and array distribution is less than 1.5%. The ultimate shear strength reduction of TCSPs is related to Rr, Rd, and γ. The influence of ACP parameters on the shear strength of TCSPs is similar in different initial geometric defect modes. The proposed formula for calculating the strength reduction of TCSPs is in good agreement with the FEM and experiment results.

Optimizing temperature-dependent molar volume fraction of biodiesel fuel in a pseudo-binary mixture through Bragg fiber waveguide sensor having defect layer

In the present communication, the temperature-dependent molar volume fraction of various kinds of renewable biodiesel fuel resources in a pseudo-binary mixture is theoretically optimized through the Bragg fiber waveguide (BFW) sensor with a geometrical defect in periodic cylindrical Bragg reflectors. BFW structure is modelled using a transfer matrix method (TMM) and Henkel formalism in a cylindrical coordinate system. The temperature dependence molar volume fraction is linked to the change in the refractive index of the pseudo-binary mixture, which is further predicted using the capacity of various models; Lorentz-Lorenz, Dale-Gladstone, Eykman, Newton, and Kay. In the presence of a geometric defect layer, a sharp transmission peak of 0.1nmfull width at half maxima (FWHM) is obtained in the considered photonic band gap (PBG), which is sensitive to the change in core refractive index. The temperature-dependent (due to different weather conditions) maximum sensitivity of the proposed sensor is found to be 1280 nm/RIU, which is further compared with the phoxonic crystal-based static temperature sensor having sensitivity 142 nm/RIU only. Along with improved sensitivity in the proposed sensor, other sensing performance parameters detection accuracy and quality parameter (which are inversely proportional to the FWHM) are also improved due to least FWHM of resonant transmission peak about 0.1 nm comparatively.

Multi-scale evolution mechanism and knowledge construction of a digital twin mimic model

• This paper has the following improvements over previous studies. • The digital twin product quality knowledge model is constructed to express the product quality factors and to cover all the factors that cause the product quality problems. • This paper studies the multi-scale evolution mechanism of digital twin mimic model and explains the evolution mechanism from data to knowledge. • An adaptive data transmission interface is constructed. The product quality data can be transferred to the visualization and product decision module adaptively. Metal products are susceptible to factors such as cutting force, clamping force and heat in the machining process, resulting in product quality problems, such as geometric deformation and surface defects . The real-time observation and control of product quality are integral to optimizing machining process. Digital twin technologies can be used to monitor and control the quality of products via multi-scale based quality analysis. However, previous research on digital twin lacks a fine-grained expression and generation method for product multi-scale quality, making it impossible to carry out an in-depth analysis of product quality. Aiming at addressing this challenge, we study the multi-scale evolution mechanism of the digital twin model and explore the knowledge generation method of the digital twin data. The proposed method constructed the digital twin quality knowledge model from the macro, meso, and micro levels by utilizing the data of the digital twin mimic model. These multi-scale quality knowledge models can express product quality in a fine-grained way and provide data support for digital twin-based decision-making. Finally, we tested the method in monitoring and controlling the machining quality of an air rudder to verify the feasibility of the proposed method.