electromagnetic metal casting computation designs Fig1

The European Physical Journal Plus volume 136, Article number: 704 (2021) Cite this article

Abstract

Electromagnetic metal casting (EMC) is a casting technique that uses electromagnetic energy to heat metal powders. It is a faster, cleaner, and less time-consuming operation. Solid metals create issues in electromagnetics since they reflect the electromagnetic radiation rather than consume it—electromagnetic energy processing results in sounded pieces with higher-ranking material properties and a more excellent microstructure solution. For the physical production of the electromagnetic casting process, knowledge of electromagnetic material interaction is critical. Even where the heated material is an excellent electromagnetic absorber, the total heating quality is sometimes insufficient. Numerical modelling works on finding the proper coupled effects between properties to bring out the most effective operation. The main parameters influencing the quality of output of the EMC process are: power dissipated per unit volume into the material, penetration depth of electromagnetics, complex magnetic permeability and complex dielectric permittivity. The contact mechanism and interference pattern also, in turn, determines the quality of the process. Only a few parameters, such as the environment’s temperature, the interference pattern, and the rate of metal solidification, can be controlled by AI models. Neural networks are used to achieve exact outcomes by stimulating the neurons in the human brain. Additive manufacturing (AM) is used to design mold and cores for metal casting. The models outperformed the traditional DFA optimization approach, which is susceptible to local minima. The system works only offline, so real-time analysis and corrections are not yet possible.

Korea Abstract

전자기 금속 주조 (EMC)는 전자기 에너지를 사용하여 금속 분말을 가열하는 주조 기술입니다. 더 빠르고 깨끗하며 시간이 덜 소요되는 작업입니다.

고체 금속은 전자기 복사를 소비하는 대신 반사하기 때문에 전자기학에서 문제를 일으킵니다. 전자기 에너지 처리는 더 높은 등급의 재료 특성과 더 우수한 미세 구조 솔루션을 가진 사운드 조각을 만듭니다.

전자기 주조 공정의 물리적 생산을 위해서는 전자기 물질 상호 작용에 대한 지식이 중요합니다. 가열된 물질이 우수한 전자기 흡수재인 경우에도 전체 가열 품질이 때때로 불충분합니다. 수치 모델링은 가장 효과적인 작업을 이끌어 내기 위해 속성 간의 적절한 결합 효과를 찾는데 사용됩니다.

EMC 공정의 출력 품질에 영향을 미치는 주요 매개 변수는 단위 부피당 재료로 분산되는 전력, 전자기의 침투 깊이, 복합 자기 투과성 및 복합 유전율입니다. 접촉 메커니즘과 간섭 패턴 또한 공정의 품질을 결정합니다. 환경 온도, 간섭 패턴 및 금속 응고 속도와 같은 몇 가지 매개 변수 만 AI 모델로 제어 할 수 있습니다.

신경망은 인간 뇌의 뉴런을 자극하여 정확한 결과를 얻기 위해 사용됩니다. 적층 제조 (AM)는 금속 주조용 몰드 및 코어를 설계하는 데 사용됩니다. 모델은 로컬 최소값에 영향을 받기 쉬운 기존 DFA 최적화 접근 방식을 능가했습니다. 이 시스템은 오프라인에서만 작동하므로 실시간 분석 및 수정은 아직 불가능합니다.

electromagnetic metal casting computation designs Fig1
electromagnetic metal casting computation designs Fig1
electromagnetic metal casting computation designs Fig2
electromagnetic metal casting computation designs Fig2
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electromagnetic metal casting computation designs Fig3
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electromagnetic metal casting computation designs Fig4
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electromagnetic metal casting computation designs Fig6
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electromagnetic metal casting computation designs Fig7
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electromagnetic metal casting computation designs Fig8
electromagnetic metal casting computation designs Fig9
electromagnetic metal casting computation designs Fig9

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