https://www.scipedia.com/sj/collection-engineering Thu, 09 Feb 2017 15:52:58 +0100 https://www.scipedia.com/sj/collection-engineering This collection gathers research and technical articles in the field of Engineering categories.

]]> Scipedia content https://www.scipedia.com/sj/engineering Thu, 06 Apr 2017 12:59:42 +0200 https://www.scipedia.com/sj/engineering The collection is a repository of open access articles where academic achievements of great importance in engineering science and technology can be disseminated and shared. The collection includes new focus, and updates on central issues; heuristic comments and reviews on major issues, articles, and events; research results, in the form of research articles, reviews, perspectives, short communications regarding critical issues, and so on.

]]> Scipedia content https://www.scipedia.com/sj/jestech Mon, 10 Apr 2017 16:12:08 +0200 https://www.scipedia.com/sj/jestech The collection is a repository of open access articles, both theoretical and experimental high quality papers of permanent interest, in the field of engineering and applied science which aims to promote the theory and practice of technology and engineering.

]]> Scipedia content https://www.scipedia.com/sj/view/356526 Sun, 15 Sep 2024 12:00:04 +0200 https://www.scipedia.com/sj/view/356526 La Colección de Memorias del Congreso Internacional de Ingeniería Mecánica y Mecatrónica Aplicada (CIIMMA, es un conjunto de resúmenes presentados en los congresos CIIMMA celebrados del 2022 a la fecha. En dichos resúmenes se pretende mostrar los avances científicos y tecnológicos asociados con el desarrollo de la ingeniería mecánica, mecatrónica y aplicada con un enfoque multidisciplinario.

 

]]> Miguel Villagómez Galindo https://www.scipedia.com/sj/specialissuerimni98 Wed, 18 Mar 2026 07:47:28 +0100 https://www.scipedia.com/sj/specialissuerimni98 Deadline Date: 31 December 2026

 

The growing complexity of modern metallurgical processes, encompassing everything from pyrometallurgical and hydrometallurgical extraction to advanced alloy design and thermomechanical processing, demands a paradigm shift beyond traditional empirical and numerical methods. Challenges persist in handling multiphase flow, multi-physics coupling, non-equilibrium phenomena, microstructural evolution across scales, and plant-wide real-time optimization—areas where artificial intelligence (AI) offer transformative potential.

This Special Issue seeks to compile pioneering research at simulation and modelling, and also the intersection of AI, simulation, and metallurgical engineering, addressing critical gaps between algorithmic advancements and their practical application in the metals industry. We highlight computational strategies where AI augments, accelerates, or replaces conventional methods to achieve:

Key Focus Areas:

1. Modelling and Optimization of Metallurgical Process

2. Hybrid Numerical-AI Frameworks

3. Industrial Applications and Digital Twins

4. Fundamental Advances and Data-Driven Discovery

This issue aims to establish best practices for integrating AI into the metallurgical engineering workflow while critically examining its limitations (e.g., data quality and scarcity, model interpretability, overfitting risks, and industrial scalability). Contributions should demonstrate rigorous validation against experimental results or high-fidelity numerical benchmarks, showcasing tangible advancements in the field of simulation and modeling for metallurgical engineering.

]]> Jason Jiang