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Advanced Casting of Materials

A special issue of Materials (ISSN 1996-1944). This special issue belongs to the section "Manufacturing Processes and Systems".

Deadline for manuscript submissions: 10 October 2024 | Viewed by 7250

Special Issue Editor

Key Laboratory for Advanced Materials Processing Technology, School of Materials Science and Engineering, Tsinghua University, Beijing 100084, China
Interests: solidification; casting; additive manufacturing; modelling and simulation

Special Issue Information

Dear Colleagues,

Casting technology has a long history, irreplaceable not only in the past, but also in the future, playing very important roles in critical equipment and products such as aeroengines, nuclear power plants, rockets, vehicles, etc. Casting technology is driven by strong requirements from various areas, for example, hypersonic aircraft, heavy duty rockets, electric vehicles and high speed trains; on the other hand, it is being reshaped by new technologies such as information technology, additive manufacturing, virtual technology, artificial intelligence, etc. The aims of castings and their production are a higher quality, faster production, stronger mechanical properties and being more environmentally friendly.

This Special Issue aims to provide a platform for the latest advances in casting technologies. This issue will include the following topics:

  • Advanced casting alloys;
  • Solidification and microstructure control;
  • Residual stress and deformation control;
  • Advanced casting technologies;
  • Additive manufacturing vs. casting;
  • Modelling and simulation;
  • Casting materials aimed at environmental protection.

Dr. Jinwu Kang
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Materials is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • solidification
  • casting
  • microstructure
  • additive manufacturing
  • modelling and simulation
  • mechanical properties
  • cast alloys
  • defect prediction and control

Published Papers (6 papers)

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Research

18 pages, 19273 KiB  
Article
Data–Physics Fusion-Driven Defect Predictions for Titanium Alloy Casing Using Neural Network
by Peng Yu, Xiaoyuan Ji, Tao Sun, Wenhao Zhou, Wen Li, Qian Xu, Xiwang Qie, Yajun Yin, Xu Shen and Jianxin Zhou
Materials 2024, 17(10), 2226; https://doi.org/10.3390/ma17102226 - 9 May 2024
Viewed by 396
Abstract
The quality of Ti alloy casing is crucial for the safe and stable operation of aero engines. However, the fluctuation of key process parameters during the investment casting process of titanium alloy casings has a significant influence on the volume and number of [...] Read more.
The quality of Ti alloy casing is crucial for the safe and stable operation of aero engines. However, the fluctuation of key process parameters during the investment casting process of titanium alloy casings has a significant influence on the volume and number of porosity defects, and this influence cannot be effectively suppressed at present. Therefore, this paper proposes a strategy to control the influence of process parameters on shrinkage volume and number. This study constructed multiple regression prediction models and neural network prediction models of porosity volume and number for a ZTC4 casing by simulating the gravity investment casting process. The results show that the multiple regression prediction model and neural network prediction model of shrinkage cavity total volume have an accuracy of over 99%. The accuracy of the neural network prediction model is higher than that of the multiple regression model, and the neural network model realizes the accurate prediction of shrinkage defect volume and defect number through pouring temperature, pouring time, and mold shell temperature. The sensitivity degree of casing defects to key process parameters, from high to low, is as follows: pouring temperature, pouring time, and mold temperature. Further optimizing the key process parameter window reduces the influence of process parameter fluctuation on the volume and number of porosity defects in casing castings. This study provides a reference for actual production control process parameters to reduce shrinkage cavity and loose defects. Full article
(This article belongs to the Special Issue Advanced Casting of Materials)
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17 pages, 3918 KiB  
Article
Thermo-Mechanical Optimization of Die Casting Molds Using Topology Optimization and Numerical Simulations
by Serouj Djabraian, Fabian Teichmann and Sebastian Müller
Materials 2024, 17(9), 2114; https://doi.org/10.3390/ma17092114 - 30 Apr 2024
Viewed by 444
Abstract
Conventional cooling channels used in die casting molds exhibit significant drawbacks, resulting in extended cooling times for cast parts. Issues such as the formation of dirt, limescale, and corrosion substantially diminish the thermal efficiency of these channels, leading to challenges in achieving uniform [...] Read more.
Conventional cooling channels used in die casting molds exhibit significant drawbacks, resulting in extended cooling times for cast parts. Issues such as the formation of dirt, limescale, and corrosion substantially diminish the thermal efficiency of these channels, leading to challenges in achieving uniform cooling and potential quality issues. In response to these challenges, this study proposes Topology Optimization as a novel approach. It involves designing cooling structures through Topology Optimization to replace traditional cooling channels, incorporating both Discrete and Gaussian boundary conditions to optimize thermal efficiency. Additionally, Structural Topology Optimization is employed to ensure structural integrity, preventing deformation or yielding under high loads during the die casting process. Numerical analysis revealed superior thermal performance compared to conventional channels, particularly when subjected to Discrete and Gaussian boundary conditions. Furthermore, the application of the latter establishes conformal cooling and minimizes temperature gradients in the casting, reducing casting defects such as shrinkage porosity. These findings highlight the efficacy of Topology Optimization in addressing the challenges of traditional cooling methods, with wide-ranging implications for manufacturing processes utilizing permanent molds for shaping materials. Full article
(This article belongs to the Special Issue Advanced Casting of Materials)
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18 pages, 5516 KiB  
Article
Research on Solid Shell Growth during Continuous Steel Casting
by Marek Velička, René Pyszko, Mario Machů, Jiří Burda, Tomáš Kubín, Hana Ovčačíková and David Rigo
Materials 2023, 16(15), 5302; https://doi.org/10.3390/ma16155302 - 28 Jul 2023
Viewed by 1038
Abstract
The continuous steel casting process must simultaneously meet the requirements for production performance, quality and safety against breakouts. Knowing the thickness of the solidified shell, particularly at the exit of the mould, is useful for the casting process control and breakout prevention. Shell [...] Read more.
The continuous steel casting process must simultaneously meet the requirements for production performance, quality and safety against breakouts. Knowing the thickness of the solidified shell, particularly at the exit of the mould, is useful for the casting process control and breakout prevention. Shell thickness is difficult to measure during casting; in practice, it is predicted by indirect methods and models. But after undesired rupture of the shell and leakage of the liquid steel, it is possible to measure the shell thickness directly. This article is focused on the problem of the growth and measurement of the solid shell obtained after the breakout of a round block with a diameter of 410 mm. An original methodology was developed in which a surface mesh of points was created from the individual scanned parts of the block using a 3D laser scanner. Research has shown differences of up to 6 mm between the maximum and minimum shell thickness at the mould exit. A regression function of the average shell thickness on time was found. The results of the real shell growth were further used for the verification of the original numerical model of cooling and solidification of the round block. Full article
(This article belongs to the Special Issue Advanced Casting of Materials)
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14 pages, 7313 KiB  
Article
The Effect of Boron (B) and Copper (Cu) on the Microstructure and Graphite Morphology of Spheroidal Graphite Cast Iron
by Jin-Su Ha, Ji-Woo Hong, Ji-Wook Kim, Soo-Bin Han, Chang-Young Choi, Hye-Jin Song, Jin-Seok Jang, Dong-Yul Kim, Dae-Cheol Ko, Seong-Hoon Yi and Yong-Jae Cho
Materials 2023, 16(12), 4225; https://doi.org/10.3390/ma16124225 - 7 Jun 2023
Cited by 1 | Viewed by 1266
Abstract
This study examines the impacts of copper and boron in parts per million (ppm) on the microstructure and mechanical properties of spheroidal graphite cast iron (SCI). Boron’s inclusion increases the ferrite content whereas copper augments the stability of pearlite. The interaction between the [...] Read more.
This study examines the impacts of copper and boron in parts per million (ppm) on the microstructure and mechanical properties of spheroidal graphite cast iron (SCI). Boron’s inclusion increases the ferrite content whereas copper augments the stability of pearlite. The interaction between the two significantly influences the ferrite content. Differential scanning calorimetry (DSC) analysis indicates that boron alters the enthalpy change of the α + Fe3C → γ conversion and the α → γ conversion. Scanning electron microscope (SEM) analysis confirms the locations of copper and boron. Mechanical property assessments using a universal testing machine show that the inclusion of boron and copper decreases the tensile strength and yield strength of SCI, but simultaneously enhances elongation. Additionally, in SCI production, the utilization of copper-bearing scrap and trace amounts of boron-containing scrap metal, especially in the casting of ferritic nodular cast iron, offers potential for resource recycling. This highlights the importance of resource conservation and recycling in advancing sustainable manufacturing practices. These findings provide critical insights into the effects of boron and copper on SCI’s behavior, contributing to the design and development of high-performance SCI materials. Full article
(This article belongs to the Special Issue Advanced Casting of Materials)
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15 pages, 8959 KiB  
Article
Study on the Gas Release of 3D-Printed Furan Resin Sand Core during the Casting Process
by Xiaolong Wang, Qihua Wu, Yuhang Huang, Na Li, Xiongzhi Wu, Xiuming Chen, Jiwu Wang, Tao Jing, Tianyou Huang and Jinwu Kang
Materials 2023, 16(11), 4152; https://doi.org/10.3390/ma16114152 - 2 Jun 2023
Cited by 4 | Viewed by 1590
Abstract
In sand casting, gas porosity is a common defect that can result in decreased strength, leakage, rough surfaces, or other problems. Although the forming mechanism is very complicated, gas release from sand cores is often a significant contributor to the formation of gas [...] Read more.
In sand casting, gas porosity is a common defect that can result in decreased strength, leakage, rough surfaces, or other problems. Although the forming mechanism is very complicated, gas release from sand cores is often a significant contributor to the formation of gas porosity defects. Therefore, studying the gas release behavior of sand cores is crucial to solving this problem. Current research on the gas release behavior of sand cores mainly focuses on parameters such as gas permeability and gas generation properties, through experimental measurement and numerical simulation methods. However, accurately reflecting the gas generation situation in the actual casting process is difficult, and there are certain limitations. To achieve the actual casting condition, a sand core was designed and enclosed inside a casting. The core print was extended to the sand mold surface, with two types of core prints: hollow and dense. Pressure and airflow speed sensors were installed on the exposed surface of the core print to investigate the burn-off of the binder of the 3D-printed furan resin quartz sand cores. The experimental results showed that the gas generation rate was high in the initial stage of the burn-off process. The gas pressure quickly reached its peak in the initial stage and then decreased rapidly. The exhaust speed of the dense type of core print was 1 m/s, lasting for 500 s. The pressure peak of the hollow-type sand core was 1.09 kPa, and the exhaust speed peak was 1.89 m/s. The binder can be sufficiently burned off for the location surrounding the casting and the crack-affected area, so the burnt sand appears white, while the burnt core appears black due to insufficient burning of the binder because of isolation from the air. The gas generated by the burnt resin sand in contact with air was 30.7% less than that generated by the burnt resin sand insulated from the air. Full article
(This article belongs to the Special Issue Advanced Casting of Materials)
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15 pages, 1647 KiB  
Article
A Decision Support System (DSS) for the Prediction and Selection of Optimum Operational Parameters in Pressure Die-Casting Processes
by Juan Martínez-Pastor, Juan José Hernández-Ortega and Rosendo Zamora
Materials 2022, 15(15), 5309; https://doi.org/10.3390/ma15155309 - 2 Aug 2022
Cited by 3 | Viewed by 1534
Abstract
A large number of material and process parameters affect both the part quality and the process performance in pressure die-casting (PDC) processes. The complex relations between most of these variables make PDC process optimisation a difficult issue which has been widely studied for [...] Read more.
A large number of material and process parameters affect both the part quality and the process performance in pressure die-casting (PDC) processes. The complex relations between most of these variables make PDC process optimisation a difficult issue which has been widely studied for many years. Although there are several analytical and numerical models to optimise certain process parameters, it is difficult to establish a specific operational configuration for PDC machines that ensures the joint optimisation of these variables. Therefore, in this study, some of these optimisation models have been implemented in a Decision Support System (DSS) that allows us to define an operational region that establishes a setup of machine parameters that ensures the manufacture of quality parts. By using this DSS, the user can set the values of the input variables related to the casting material, the die, or the casting machine. Then the corresponding calculations are made by the system and the results are expressed in terms of certain output variables such as the maximum filling time, maximum filling fraction, or the plunger velocity profile among others. The DSS allows the user to estimate the influence between input and output variables and find proper values for the input variables to achieve an optimum operational range. Consequently, improved process performance can be achieved taking into account productivity, part quality, and economic aspects. Full article
(This article belongs to the Special Issue Advanced Casting of Materials)
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