Deformable Part Research Articles

Laser‐Based Closed‐Loop Controlled Heat Treatment for Residual Stress Relief of Additively Manufactured AlSi10Mg Components

In laser powder bed fusion of metals small melt pools with extremely short solidification times and steep temperature gradients to the surrounding material exist due to the layer‐wise and selective melting process with small areas of energy input compared to the cooler, solid ambient material. This causes high thermally induced residual stresses (RS), which can lead to the immediate rejection of the component due to critical part deformation and inhomogeneous mechanical properties under load. To prevent this, furnace‐based stress relief heat treatments are commonly applied before cutting‐off the part from the built platform. In this study a novel closed‐loop controlled laser‐based heat treatment using temperature feedback through inline pyrometer measurement is investigated, enabling a fast and highly efficient postprocess stress relief. Therefore, a laser beam is guided by a scanner optics in a meandering pattern over the top surface of AlSi10Mg cantilever specimens. It enables a decrease of near‐surface RS from 158 to 5 N mm−2, resulting in a reduction of displacement by over 90% at material affecting depths up to 3 mm and area rates of 8 to 163 mm2 s−1.

Applications of Denoising Diffusion Probability Model in Image Processing

Abstract. In 2020, Jonathan Ho et al. from the University of Berkeley proposed the Denoising Diffusion Probabilistic Models (DDPM), which improved on the shortcomings of the previous-generation Deformable Part Models (DPM). At the same time, they also surpassed previous generative models in image synthesis effects by using noise prediction, such as Generative Adversarial Networks (GAN), Variational Auto-Encoders (VAE), flow-based models and energy-based models, etc. After that, the denoising diffusion probabilistic models gradually received more discussions and research. In 2022, OpenAI launched the DALL-E 2, realizing Text-to-Image generation combined with the denoising diffusion probabilistic model. Two years later, with the release of Sora, the first Text-to-Video large models based on DALL-E, the denoising diffusion probabilistic models have received unprecedented attention in the multi-modal field. This article first provides the background and development process of the denoising diffusion probabilistic models. Secondly, it introduces the algorithmic principles of the diffusion models. Following that, it lists the applications of the models in the area of images. In the last section, it expounds on the advantages, disadvantages and future trends of the denoising diffusion probabilistic models.

Finite element simulation of hybrid manufacturing of Ti–6Al–4 V by arc-directed energy deposition and friction stir processing

ABSTRACT FSP is a novel technology that can improve the microstructure and mechanical properties of ADED. In this study, an FSP-ADED hybrid manufacturing finite element model was constructed for stress and strain simulating the Ti–6Al–4 V alloy. The results show that continuous shrinkage of the deposition wall was broken after inter-layer FSP. The minimum tensile RS was obtained near the wall top. The tensile RS was increased after the deposition of the second layer; however, the overall stress level was lower than that of ADED alone. After two layers of FSP, the average value of longitudinal stress in the stirred zone was reduced by 54%. The warping deformation of hybrid manufactured components was reduced by 30.9%. It was proved that FSP-ADED hybrid manufacturing is an effective method to reduce RS and deformation of titanium alloy large-scale structural parts in the aerospace field.

Simulated inter-filament fusion in embedded 3D printing

In embedded 3D printing (EMB3D), a nozzle extrudes continuous filaments inside of a viscoelastic support bath. Compared to other extrusion processes, EMB3D enables softer structures and print paths that conform better to the shape of the part, allowing for complex structures such as tissues and organs. However, strategies for high-quality dimensional accuracy and mechanical properties remain undocumented in EMB3D. This work uses computational fluid dynamics simulations in OpenFOAM to probe the underlying physics behind two processes: deformation of the printed part due to nearby nozzle motion and fusion between neighboring filaments during printing. Through simulations, we disentangle yielding from viscous dissipation, and we isolate interfacial tension effects from rheology effects, which are difficult to separate in experiments. Critically, these simulations find that disturbance and fusion are controlled by the flow of support fluid around the nozzle. To avoid part deformation, the nozzle must remain far from existing parts during non-printing moves, moreso when traveling next to the part than above the part and especially when the interfacial tension between the ink and support is non-zero. Additionally, because support can become trapped between filaments at zero interfacial tension, the spacing between filaments must be tight enough to produce over-printing, or printing too much material for the designed space. In non-Newtonian fluids, spacings for vertical walls must be even tighter than spacings for horizontal planes. At these spacings, printing a new filament sometimes creates and sometimes mitigates shape defects in the old filament. While non-zero ink-support interfacial tensions produce better inter-filament fusion than zero interfacial tension, interfacial tension also produces shape defects. Slicing algorithms that consider these unique EMB3D defects are needed to improve mechanical properties and dimensional accuracy of bioprinted constructs.

Effect of wall thickness on the precipitation behavior, microstructure, electrical conductivity and mechanical properties of copper alloy prepared by electron beam powder bed fusion

Electron beam powder bed fusion (EB-PBF) is one of the most promising technologies for preparing thin-walled copper alloy, because copper alloy have a high energy absorption rate for electron beam, and high preheating temperature can reduce the solidification temperature gradient and reduce the deformation of thin-walled parts. At present, there are few reports on the systematic research work on the EB-PBF of thin-walled CuCrZr alloy parts, and it's impossible to effectively supervise the production of complex thin-walled CuCrZr alloy parts. This work aims to investigate the effect of thickness on the microstructure and mechanical properties of CuCrZr alloy produced by EB-PBF. As the wall thickness decreases from 5.0 mm to 0.3 mm, the grain sizes of the XY and YZ planes decreased from 20.4 μm and 43.1 μm to 14.5 μm and 21.5 μm respectively, and the texture intensity decreased from 16.04 and 23.57 to 7.62 and 10.99. The analysis showed that Cr2O3 nanoprecipitates were precipitated in situ in the sample, and their average size decreased from 65.8 nm to 21.6 nm. Due to the reduction in grain and nanoprecipitate size, the performance of thin-walled samples is significantly enhanced, with yield strength (YS) increasing from 112 MPa to 165 MPa and conductivity increasing from 71.7 %IACS to 86.1 %IACS. Finally, the main contributions to the YS of specimens with different wall thicknesses was discussed. Precipitation strengthening and dislocation strengthening are the main strengthening mechanisms in thin-walled samples, and the gradual refinement of nano-precipitates is the main reason for the improvement of mechanical properties as the wall thickness decreases.

A novel approach to control thermal induced buckling during laser welding of battery housing through a unilateral N-2-1 fixturing principle

Battery housing (BH) in modern electric vehicles must meet demanding functional requirements. The design and geometry of the BH become intricate to prevent damage during collisions and to ensure absolute impermeability to gases and water during operation. Moreover, in the pursuit of a lightweight BH, manufacturers rely on high-strength 6xxx aluminium alloys, posing significant challenges for the welding processes. It is estimated that up to 30 m of weld length is required during the construction of battery housings including joining the lid and under-shield to the main structural frame and joining the ribs to the frame for standard vehicles. Due to the increasing use of thin sheets for lightweighting the structure, thermal-induced buckling may occur and generate critical dimensional unconformities going beyond design tolerances. This underpins the need to optimise fixturing design to control thermal-induced buckling.This paper goes beyond the state-of-the-art “N-2-1” approaches for fixturing thin and deformable parts and proposes the new principle of “unilateral N-2-1 fixturing”. The driving idea is adding unilateral restraints to the direction of thermal contraction, which ultimately causes buckling; and, keeping the direction where the thermal expansion occurs in a free state. The methodology is based on three main steps: (1) physics-based modelling of parts and fixtures using a thermo-mechanical FEA simulation; (2) calibration of the weld heat source using metallographic data; (3) validation using optical scanning technology. The methodology was demonstrated during the laser beam welding of a high-strength aluminium 6xxx thin deformable lid to a rigid high-strength 6xxx aluminium extrusion frame. Results indicated that the thermal induced buckling deformation was reduced from 15 mm, when using the state-of-the-art fixturing approach, to approximately 2 mm with the proposed methodology.

Research on online deformation monitoring of thin-walled parts driven by digital twin

Thin-walled parts are widely used in aerospace. Because thin-walled parts have thin walls, weak stiffness, and are easy to deform and other characteristics, it is easy to produce deformation in the processing, affecting the quality and accuracy of the workpiece processing. Therefore, accurate and efficient online real-time monitoring of the deformation of thin-walled parts has become a vital issue in process control. The visualization, real-time monitoring, and iterative optimization of digital twin technology can effectively solve the problem of online monitoring of thin-walled parts processing. Therefore, this paper proposes a digital twin driven deformation monitoring method for thin-walled parts, which realizes the effective monitoring of deformation during the processing of thin-walled parts. Firstly, the digital twin architecture for online deformation monitoring of thin-walled parts is established, and the critical technologies of the digital twin for online deformation monitoring of thin-walled parts are proposed. Secondly, the Support Vector Regression (SVR) finite element surrogate model is established to realize the rapid simulation of thin-walled parts cutting. At the same time, a One-Dimensional Convolutional Neural Network (1DCNN) combined with the Self-Attention Mechanism (SAM) deformation prediction model was established based on sensor data. The real-time monitoring and accurate prediction of the deformation of thin-walled components are realized through the parallel guidance of the deep learning and surrogate model. Finally, an experimental analysis was carried out by machining thin-walled plates of aluminum alloy 7075, and the fit of the monitoring models was above 95%, thus verifying the validity of the proposed method.

Superflexible Carbon Nanofibers for Multidimensional Complex Deformation Sensing in Soft Robots.

Soft robots can make complex motions or deformations due to their infinite freedom, which poses great challenges for monitoring their motion and position. While previous investigations of flexible sensing either focused on stretchable or compression deformations in one or two directions, the complex multidimensional deformations that occur on the surfaces of soft robots have been frequently overlooked. In this work, inspired by spider silk, superflexible carbon nanofibers with a bundled structure were biomimetically designed and fabricated using electrospinning technology and carbonization treatment. The fabricated fibers can be microscopically folded at 180° and can sustain multidimensional shrinkage deformation without microstructural damage during 200,000 times of repeated folding. In addition, the fibers process ultrasmall bending resistance that is two orders of magnitude lower than that of A4 paper and commercial conductive fibers, demonstrating excellent flexibility that is ideal for fabricating sensors in soft robots. Combining the study of origami techniques and mechanical simulations, the bending resistance of the fibers was found to have a step change in response to different deformation angles and radii. As a demonstration, a sensor based on this flexible carbon nanofiber successfully monitors the irregular shrinkage deformation of soft parts, showing great potential in applications of grasping, recognition, and perception. This work sheds light on the design of ultraflexible conductive carbon materials and provides an avenue for the extreme shape-morphing monitoring of soft robots.

Improvements in Injection Moulds Cooling and Manufacturing Efficiency Achieved by Wire Arc Additive Manufacturing Using Conformal Cooling Concept.

The plastic injection moulding industry is a constantly developing industrial field. This industrial process requires the manufacturing of metal moulds using complex heating and cooling systems. The purpose of this research is to optimize both the plastic injection moulding process and the mould manufacturing process itself by combining practices in this industry with current additive manufacturing technologies, specifically Wire Arc Additive Manufacturing (WAAM) technology. A mould punch was manufactured by using both WAAM technology, whose internal cooling system has been designed under the concept of Conformal Cooling, and conventional cooling channel designs and manufacturing techniques in order to carry out a comparative analysis. Theoretical results obtained by CAE methods showed an improvement in heat extraction in the WAAM mould. In addition, the WAAM mould was able to achieve better temperature homogeneity in the final part, minimizing deformations in the final part after extraction. Finally, the WAAM manufacturing process was proven to be more efficient in terms of material consumption than the conventional mould, reducing the buy-to-fly ratio of the part by 5.11.

Investigation of the influence of initial residual stress and toolpaths on milling deformation of titanium alloy

Titanium alloy structural components are widely used in the aerospace industry due to their excellent physical properties. However, their susceptibility to machining deformation during milling, attributed to the presence of initial residual stress, poses a significant challenge. Therefore, this paper proposes a finite element model for predicting milling deformation in Ti6Al4V titanium alloy structural parts, considering initial residual stress. The methodology involves establishing the initial residual stress field of titanium alloy components based on a mathematical model of annealing heat transfer and a theoretical study of thermal elasto-plastic constitutive relation, with experimental confirmation of model accuracy. Based on the initial residual stress, a finite element model was developed to predict the maximum deformation under different toolpaths. Finally, a comparative analysis with milling experiments validated the proposed models. The experimental results demonstrated a remarkable alignment with the finite element model, showcasing the correctness of the developed models. The maximum deviation in deformation observed was within the range of 0.003 mm–0.011 mm. This study is the first to comprehensively consider the effects of initial residual stress and toolpaths on titanium alloy milling deformation, and to experimentally verify the proposed model’s accuracy and practicality. It provides a new theoretical basis and technical guidelines for titanium alloy milling deformation.

On influence of microstructural anisotropy of additive manufactured structures upon machining dynamics: An example of milling of Ti6Al4V thin-walled parts

Thin-walled structures, as common component specification for aerospace components, easily experience deformation and chatter issues during machining (e.g. milling) operations. With Additively Manufactured (AM) materials being increasingly applied in these areas, it is found that their microstructural anisotropy can lead to varied mechanical properties and machinability in different directions. However, former research on thin-walled parts mainly focused on bulk materials, while the machining performance of these thin-wall structures produced from AM processes remains unclear. In this view, this research aims to reveal the effect of microstructural anisotropy resulting from AM process on the machining (deformation and stability) of thin-walled parts by taking Ti6Al4V as an example. Three kinds of AM Ti6Al4V thin-walled parts were fabricated with different laser scanning strategies, in which the prior columnar β grains were found to grow along the building direction and led to a variation in mechanical properties. Owing to this, the deformation and machining stability varied in the AM thin-walled parts with different β phase crystallization orientations on the same milling directions, which could be attributed to the changes of cutting force and dynamic parameters (e.g., frequency, stiffness (determined by elastic modulus), damping ratio) in different orientations. This investigation could provide a reference for the selection of printing strategies and follow-up machining process of AM thin-walled parts when considering their microstructural anisotropy.

A measurement method for the axial bending deformation of parts with circumferential cycling element based on laser profile sensor

Abstract The cross-section of the CPP (circumferential periodic parts) is composed of fixed shaped elements regularly arranged in the circumferential direction, examples include cylinders, positive prisms, lead screws, gear shafts, and spline shafts, it has applications in many fields. Existing research has not yet proposed a universal method for measuring the axial bending of CPP. This paper presents a non-contact measurement method using a laser profile sensor that is capable of measuring axial bending of CPP. The axis of a shaft part is determined by connecting the geometric center of each cross-section. This method is suitable for measuring the bending deformation of most CPS (circumferential periodic shaft parts). To verify the validity of this method, numerical simulation calculations are conducted on cylinders, hexagonal prisms, and lead screws. Additionally, comparative experiments are performed on lead screws using self-built experimental platform and a measuring projector to investigate the effectiveness and repeatability.

Developing the use of domestic photoelastic coating materials to determine the deformation of parts of complex geometric shapes

The paper presents the results of using some domestic materials in the manufacture of photoelastic coatings to study the stress-strain state in the process of strength testing of parts and assemblies of complex geometric shapes. Based on the analysis of the market for domestic materials for the production of photoelastic coatings, several materials were tested, their mechanical and optical characteristics were determined, and the technology for the production of photoelastic coatings was developed. This paper presents comparative results of a study of the stress-strain state (SSS) of a number of samples and products of aviation and space technology of different levels of complexity, prepared with domestic and foreign photoelastic coatings.

Numerical simulation and experimental analysis of thermal conduction and stress in laser cladding repair of thin-walled parts

To minimize the deformation of thin-walled parts during the laser cladding process and enhance the quality of the repaired parts, the Finite Element Abaqus software was used to develop a thermal conduction and 3D stress model, the heat source used in the experiments was a double ellipsoid heat source model. This model simulates the thermal process and the deformation resulting from residual stresses in the laser cladding process on a titanium alloy substrate with a thickness of 2 mm. Through the simulation, the temperature field of the substrate at the end of each pass was obtained, and the cladding sequence with the smallest temperature gradient during the multi-pass laser melting process was determined. By combining simulation and practice, the multilayer stacking pattern was optimized to achieve deformation control. Analog simulation experiments indicate that the optimized single-layer multi-pass laser cladding method results in less heat accumulation and thermal stress compared to the unidirectional sequential scanning method. The flatness test results show that the specimens have less deformation with the optimized multilayer stacking method. In addition, the metallographic organisation of the two cladding specimens is analysed in this paper, and the results show that the optimised specimens exhibit excellent microstructures and properties.

Integrated framework of multi−physics mechanism models for gas−powder flow, molten pool evolution and part deformation in high alloy steel additive manufacturing process

Multi−physics numerical models for metal additive manufacturing (MAM) could replace the expensive trial−and−error experiments, reveal the mechanisms of printing process, and provide an effective means of optimizing process parameters and mitigating part defects. However, the existing simulations of MAM process seldom consider the coupling effects between multiple recursive processes. There is an urgent need to overcome the dilemma of limiting MAM process simulation to a localized single sub−process. For directed energy deposition (DED) additive manufacturing process, the integrated simulation framework proposed in this study consists of a gas−powder flow model, a heat and fluid flow model, and a sequentially coupled thermal–mechanical model, which can be used to predict the feedstock feeding process, the evolution of molten pool, and the residual deformations of metal part, respectively. The accurate results of the three recursive sub−processes can be obtained by delivering the validated parameters between models. Corresponding experiments are conducted to verify the accuracy of the integrated framework based on 12CrNi2 alloy powders. The deviation of the predicted focal distance of powder streams is 5.14 %, and the deviations of the predicted molten pool height and width are all less than 8.5 %. The integrated framework could rapidly and accurately predict the residual deformation tendency and the position where the maximum deformation occurs. For single−track and eight−layer line deposition, the deviations of the predicted maximum deformation are all within 0.1 mm. The integrated framework could efficiently provide accurate and comprehensive solutions for optimizing DED process.

SmartFixture: Physics-guided reinforcement learning for automatic fixture layout design in manufacturing systems

Fixture layout design critically impacts the shape deformation of large-scale sheet parts and the quality of the final product in the assembly process. The existing works focus on developing Mathematical-Optimization (MO)-based methods to generate the optimal fixture layout via interacting with Finite Element Analysis (FEA)-based simulations or its surrogate models. Their limitations can be summarized as memorylessness and lack of scalability. Memorylessness indicates that the experience in designing the fixture layout for one part is usually not transferable to others. Scalability becomes an issue for MO-based methods when the design space of fixtures is large. Furthermore, the surrogate models might have limited representation capacity when modeling high-fidelity simulations. To address these limitations, we propose a learning-based framework, SmartFixture, to design the fixture layout by training a Reinforcement learning agent through direct interaction with the FEA-based simulations. The advantages of the proposed framework include: (i) it is generalizable to design fixture layouts for unseen scenarios after offline training; (ii) it is capable of finding the optimal fixture layout over a massive search space. Experiments demonstrate that the proposed framework consistently generates the best fixture layouts that receive the smallest shape deformations on the sheet parts with different initial shape variations.

Numerical simulation of a laser beam welding process: From a thermomechanical model to the experimental inspection and validation

In laser beam welding (LBW) complex physical phenomena occur during laser-material interaction, which prolong the parameterisation of the process due to the extended trial and error tests. Therefore, predicting the process behaviour leads to a more productive and cost-reduced process experimental tuning. Besides, as LBW is a thermal process, part distortion plays a relevant role in the final result, and hence, thermal and mechanical analysis are both required. In view of this, in the present research, a novel multiscale numerical model, capable of predicting the thermomechanical behaviour of the LBW process has been developed. The significance of the model is its capability of forecasting the part distortion and thermal field employing two fully coupled modules, where the laser heat source automatically adapts to the welding regime without the need to consider the melt pool dynamics and at a low computational cost. The local model determines the melt pool dimensions and thermal field. Besides, the second module, the global model, figures out the part distortion based on the thermal results. Finally, the presented numerical simulations are experimentally validated with the corresponding temperature monitoring during the welding process, the posterior metallography inspection, and the part deformation measurement. The results present a high accuracy, with a maximum error below 10 % at the temperature measurements, an average dimensional deviation of 0.14 mm and 0.18 mm respectively for the weld bead depth and width, and a vertical deformation average error of 0.15 mm.

Experimental and numerical analysis of new thermoplastic composite mandrels

In the field of aerospace, the application of carbon fiber composite parts is increasing year by year. As an important factor in the manufacturing of composite parts, tools play a crucial role in the manufacturing accuracy of composite parts, and composite tools have higher accuracy to better meet the manufacturing requirements. In this study, the properties of the novel thermoplastic composite mandrel of the new polymethyl methacrylate matrix are further investigated and a model is proposed to simulate the curing and spring back process of the composite part with the proposed composite mandrel. In detail, the glass transition temperature test and dynamic frequency test were carried out for the thermoplastic composite mandrel. The material constitutive equation of the thermoplastic composite mandrel was constructed based on the experimental data, and the accuracy of the constitutive equation of thermoplastic matrix material was verified by tensile experiments of matrix materials under constant strain conditions. Finally, the simulation result is compared with the fabricated part, and the effectiveness of the proposed method has been verified. This proved that the developed constitutive model of thermoplastic composite mandrel can effectively predict the curing deformation of composite parts with complex structures.

Design for assembly principles applied to deformable parts, a natural frequency based methodology for interfaces design

Design for assembly principles applied to deformable parts, a natural frequency based methodology for interfaces design

Analytical modelling for residual stress prediction in multi-step side milling of GH4169 thin-wall parts based on deformation

GH4169 thin-walled parts are widely used in aerospace due to their high-temperature, corrosion resistance, and fatigue strength. However, they often deform from machining-induced residual stress, which is a significant unresolved manufacturing challenge. Additionally, initial residual stress from previous steps critically impacts subsequent processes. This study found that the residual stress of side milling of thin-walled parts under smaller cutting parameters is mainly caused by mechanical effects, and the influence of milling heat can be ignored. In this study, an analytical prediction model for residual stress of multi-step side milling thin-walled parts based on the deformation of thin-walled parts is proposed for the first time, which is suitable for smaller cutting parameters. Then, the proposed model is examined the mechanisms through which residual stresses develop during side milling and defined the applicability of model based on specific assumptions. To validate these assumptions, an experimental setup was devloped to simulate the movement of the heat source during milling. Subsequent two-step side milling experiments on GH4169 confirmed the accuracy of the analytical prediction model in predicting the residual stresses of multi-step side milling in thin-walled parts. It was observed that higher equivalent bending stiffness in thin-walled parts correlates with reduced machining deformation. The analytical model also provides a strategic approach to control machining deformation by managing the equivalent bending stiffness of the parts.