This introduction paper is based on the paper “Casting Microstructure Inspection Using Computer Vision: Dendrite Spacing in Aluminum Alloys” published by “Metals”. 1. Overview: 2. Abstract: This paper investigates the determination of secondary dendrite arm spacing (SDAS) using convolutional neural networks (CNNs). The aim was to build a Deep Learning (DL) model for SDAS prediction
This article introduces the paper “Evaluation of the Microstructure and Properties of As-Cast Magnesium Alloys with 9% Al and 9% Zn Additions” presented in Materials, MDPI. 1. Overview: Title: Evaluation of the Microstructure and Properties of As-Cast Magnesium Alloys with 9% Al and 9% Zn AdditionsAuthors: Lechosław Tuz, Vít Novák, and František TatíčekPublication Year: 2025Publishing
This introductory paper is the research content of the paper [“Predicting Die Cracking in Die-Cast Products Using a Surrogate Model Based on Geometrical Features”] published by [Computer-Aided Design & Applications] 1. Overview: 2. Abstracts or Introduction This paper explores the development and application of a surrogate model for predicting die cracks in die-cast products, focusing
This article introduces the paper “Multi-Objective Optimization of Plate-Fin Heat Exchangers via Non-Dominated Sequencing”. 1. Overview: 2. Research Background: Plate-fin heat exchangers are widely used for heat dissipation in automotive engines due to their compact and lightweight structure, excellent heat transfer performance, and low production cost. Serrated staggered fins are commonly employed to enhance the
by Dirk Lehmhus Fraunhofer Institute for Manufacturing Technology and Advanced Materials IFAM, Wiener Straße 12, 28359 Bremen, GermanyMetals 2024, 14(3), 334; https://doi.org/10.3390/met14030334Submission received: 25 February 2024 / Accepted: 8 March 2024 / Published: 14 March 2024(This article belongs to the Special Issue Advances in Metal Casting Technology) 1. Introduction It is a platitude that science and technology do not necessarily evolve along straight paths.
