Computer Methods in Applied Mechanics and Engineering
Generative Artificial Intelligence for Predictive Simulations and Decision-Making in Science and Engineering
摘要截稿:
全文截稿: 2024-08-01
影响因子: 5.763
期刊难度:
CCF分类: 无
中科院JCR分区:
• 大类 : 工程技术 - 1区
• 小类 : 工程:综合 - 1区
• 小类 : 数学跨学科应用 - 1区
• 小类 : 力学 - 1区
Overview
The advent of generative artificial intelligence (AI) marks a paradigm shift in AI that also fosters unprecedented advancements in predictive simulations and decision-making in the sciences and engineering. This special issue focuses on generative AI methodologies that meet the unique demands of science and engineering applications, such as limited data availability, complex physics that are governed by nonlinear, non-stationary, and multi-scale phenomena, dynamic environments with rapidly changing conditions, and domain knowledge provided in the form of physical laws and constraints. Furthermore, generative AI techniques for high-consequence decision-making in science and engineering require rigorous validation and verification, robustness, interpretability, and uncertainty quantification for maintaining the integrity of the overall process. This special issue aims to capture the current state and articulate the future directions of this rapidly evolving field, fostering a dialogue among researchers in mathematics, computational sciences, and engineering.
Guest editors:
Prof. Youssef MarzoukMassachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
Assoc. Prof. Benjamin PeherstorferNew York University, New York, New York, United States of America
Manuscript submission information:
Guest Editor Invitation Only
Open for Submission: from 22-Mar-2024 to 01-Aug-2024
Submission Site: Editorial Manager®
Article Type Name: "VSI: GenAI4Science" - please select this item when you submit invited-manuscripts online
All manuscripts will be peer-reviewed. Submissions will be evaluated based on originality, significance, technical quality, and clarity. Once accepted, articles will be posted online immediately and published in a journal regular issue within weeks. Articles will also be simultaneously collected in the online special issue.
Guide for Authors will be helpful for your future contributions, read more: Guide for authors - Computer Methods in Applied Mechanics and Engineering
For more information about our Journal, please visit our ScienceDirect Page: Computer Methods in Applied Mechanics and Engineering | Journal | ScienceDirect.com by Elsevier
Keywords:
generative artificial intelligence;
scientific machine learning;
flow- and diffusion-based modeling;
reduced and latent modeling;
probabilistic forecasting;
Monte Carlo sampling;
active learning