Hot tearing is one of the most severe and irreversible casting defects for many metallic materials. In 2004, Eskin et al. published a review paper in which the development of hot tearing of aluminium ...alloys was evaluated (Eskin and Suyitno, 2004). Sixteen years have passed and this domain has undergone considerable development. Nevertheless, an updated systematic description of this field has not been presented. Therefore, this article presents the latest research status of the hot tearing during the casting of aluminium alloys. The first part explains the hot tearing phenomenon and its occurrence mechanism. The second part presents a detailed description and analysis of the characterisation methods of the mushy zone mechanical properties and hot tearing susceptibility. The third part presents considerable data pertaining to the mushy zone behaviour, including those of the linear contraction and load behaviour during solidification, semi-solid strength and ductility, and characteristic points related to hot tearing. The fourth part examines the effect of the composition and casting process parameters on the hot tearing susceptibility of aluminium alloys. The fifth part describes the hot tearing simulations and the associated criteria and mechanisms. Finally, recommendations for the further development of hot tearing research are presented.
Today, steel castings have become an integral part of modern foundry production. In the process of obtaining castings, any defects inevitably appear. In this paper, we consider the production reasons ...for the formation of defects in the manufacture of castings made of 35XGSL steel when casting on investment models. The features of heat removal from the casting during primary and secondary crystallization are also considered. The classification of casting zones by the orientation of crystals in castings is given. The regularity of the influence of the cooling intensity on the shrinkage character is revealed.
In order to relieve the problem of a false and missed detection of casting defects in X-ray detection, a robust detection method based on vision attention mechanism and deep learning of feature map ...is proposed. The ray images are used as input sequence, the false detection is eliminated by the intra-frame attention strategy, and the missed detection is excluded by the inter-frame deep convolution neural network (DCNN) strategy. In the intra-frame detection stage, the center-peripheral difference method is proposed to simulate the difference operation of biological vision; the suspicious defect area is directly detected according to the gradient threshold in this stage. In the inter-frame learning stage, the convolution neural network is established based on deep learning strategy to extract defect feature from a suspicious defect area; a deep learning feature vector is obtained in this stage. The similarity degree of the suspicious defect area is computed by a feature vector; a casting defect is tracked by the similarity matching of the suspicious defect in continuous frames; then, the false defects (such as noise) is excluded after defect tracking. The experimental results show that the false rate and missed rate for detection of casting defects are less than 4%, and the accuracy of the defect detection is more than 96%, which proves the robustness of the proposed method.
A casting image classification method based on multi-agent reinforcement learning is proposed in this paper to solve the problem of casting defects detection. To reduce the detection time, each agent ...observes only a small part of the image and can move freely on the image to judge the result together. In the proposed method, the convolutional neural network is used to extract the local observation features, and the hidden state of the gated recurrent unit is used for message transmission between different agents. Each agent acts in a decentralized manner based on its own observations. All agents work together to determine the image type and update the parameters of the models by the stochastic gradient descent method. The new method maintains high accuracy. Meanwhile, the computational time can be significantly reduced to only one fifth of that of the GhostNet.
•Hot deformation behavior and constitutive description of flow stress for HEAs are summarized.•Effects of deformation conditions, phases, and dynamic precipitation are discussed.•Necklace DRX and the ...effects of processing parameters on the DRX grain size are discussed.•Constitutive modeling techniques for the prediction of flow stress of HEAs are critically discussed.•Future prospects in the field of hot deformation and constitutive modeling of HEAs are listed.
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This review article summarizes the hot deformation behavior of high entropy alloys (HEAs) and the corresponding constitutive description of flow stress. The potential of hot working for grain refinement via dynamic recrystallization (DRX), reduction of casting defects, and enhancement of mechanical properties of HEAs is explained. The necklace formation, work hardening analysis for identification of the occurrence and initiation of DRX, and the effects of processing parameters on dynamically recrystallized grain size are discussed. The effects of deformation conditions (represented by the Zener-Hollomon parameter), alloying elements, dynamic precipitation, and the presence of phases on the hot deformation behavior and restoration processes of DRX and dynamic recovery (DRV) are overviewed. The application of processing maps for the characterization of the onset of flow instability, cracking, flow softening, and DRX during hot forming of HEAs is presented. Regarding the constitutive modeling of flow stress for characterization of material flow (at different deformation temperatures, strain rates, and strain), the utilization of the threshold stress (due to the presence of phases or their precipitation during high-temperature deformation), and temperature-dependent Young’s modulus, as well as correlating the obtained values of deformation activation energy and stress exponent with the expected ones from the creep theories are taken into account. Afterward, the available methods and equations for modeling and prediction of flow curves during thermomechanical processing are assessed, where the strain-compensated Arrhenius model, artificial neural network (ANN) model, Zerilli-Armstrong model, Johnson-Cook model, Hensel-Spittel model, and dislocation density-based multiscale constitutive model are presented. Finally, some suggestions for future research works are proposed.
In this research work the classification of defects of castings obtained by electric arc smelting is considered. Of particular interest to researchers is the rock-like and naphthalene fractures. A ...stone-like fracture is characterized by a clearly defined uniform surface over which the fracture occurs. Grain boundaries are partially soluble in the austenite phase, consisting of fine individual particles or films formed from molten eutectics. It is also worth noting that most often the stone-like fracture is observed at the grain boundaries.
The intense competition, in the world, for all components has compelled. All manufacturers try to manufacture parts with low cost, good quality, and on-time delivery. Nowadays, minimizing defects in ...casting is a significant issue in a foundry. Casting simulation has evolved into a useful tool for visualizing mold filling, solidification, and cooling and forecasting the location of internal flaws, including shrinkage porosity, sand inclusions, and cold closes. Controlling shrinkage porosity, inclusions, and cold run flaws have all improved dramatically. In this case, using a computer to replicate mold filling and solidification is beneficial to the foundry sector. It also increases the confidence in the quality of its castings and lowers the cost of rejection. It has also helped reduce the cost of methoding; simulation of casting processes is gaining acceptance in the foundry sector worldwide. It is being used to rectify existing castings, make new ones, and enable the emergence of new castings with no need for shop-floor trials. Because of its increased productivity, less energy and resources are required for melting and recycling. As energy is reduced, productivity improves, and as productivity rises, profit begins to rise as well. Metal casting technologies productivity and reliability are often under growing capable to improve high-quality components. In this paper, a contextual investigation on a center plate casting for replacing the current experimentation technique by using Auto-castX1 simulation software so that it can diminish the rejection rate from 8.5 to 3.5%. Simulation of the casting process has proved to be an effective tool in developing cost-effective and high-performance cast components.
The combination of light metals (aluminum, magnesium and titanium) and innovative casting processes provides cost-effective technologies to produce lightweight components and systems for many ...industrial applications. This article provides a comprehensive and yet critical review of light alloy development for cast components used in lightweight and high-performance structural and propulsion applications. It also summarized some latest process innovations in gravity casting, high pressure die casting, and low pressure casting, to overcome some fundamental issues related to defect formation in casting processes. Emerging casting processes developed in the last twenty years, such as semisolid processing, squeeze casting, ablation casting, bimetallic overcasting, and diffusion solidification processing, are discussed for further development. Recent advances in casting simulation and the concept of Integrated Computational Materials Engineering (ICME) are summarized for casting applications. Finally, future perspectives in light alloy development (including green alloys, high entropy alloys and metal matric composites), process innovations (such as high integrity casting, multi-material manufacturing and additive manufacturing), and ICME development are presented to stimulate further research and sustainable development in this important field of metals processing technology.
•Artificial defects effectively characterized fatigue strength of Ni-Resist.•Maximum-sized defect in a specimen determines fatigue limit.•Extreme-value statistics efficiently predicts lower-bound of ...fatigue limit.•Competition between propagation of multiple cracks controls fatigue life.
Ductile Ni-resist cast iron with an austenitic matrix structure contains significant casting defects that reduce the fatigue strength. Using specimens with artificial defects of various shapes and sizes, rotating bending and tension–compression fatigue tests were carried out. The maximum-sized defect in a specimen determined the fatigue limit. Therefore, the lower bound of the scatter in the fatigue limit was estimated using the area parameter model in combination with the statistics of extreme values applied to the maximum defect sizes. In contrast, the competition between propagation of multiple cracks from small material defects controlled the fatigue life.
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