Engineering With Computer - Springer - Impact Factor

Engineering With Computers - Springer | 2024 Impact Factor:4.9 | Cite Score:18.6 | Q1

Impact Factor and Journal Rank of Engineering With Computers

About: Engineering with Computers is a reputable, peer-reviewed journal that serves as a platform for researchers, engineers, and practitioners to publish high-quality research articles and innovative applications in the field of computer-aided engineering (CAE). Published by Springer, the journal covers a broad spectrum of topics related to the integration of computational tools, techniques, and methodologies in various engineering disciplines.
Content Types: Research Articles: Original research presenting new theories, methodologies, algorithms, and empirical findings in the field of computer-aided engineering. Review Articles: Comprehensive reviews that summarize current advancements, highlight significant trends, and identify future research directions in computer-aided engineering. Technical Notes: Brief reports on innovative techniques, tools, and findings relevant to computer-aided engineering.
High Standards and Impact: Peer-Reviewed: The journal employs a rigorous peer-review process to ensure the publication of high-quality, accurate, and impactful research. Citation Impact: Articles published in Engineering with Computers are frequently cited, reflecting the journal significant influence and relevance in the field. Reputation: Known for its high standards and contributions to the field, the journal is widely respected and trusted by the scientific and engineering communities.
Global Reach: International Contributions: The journal attracts contributions from researchers and professionals worldwide, providing a diverse and global perspective on computer-aided engineering. Broad Accessibility: Ensures that research findings are accessible to a wide audience through various academic and research databases, libraries, and online platforms.
Significance: Engineering with Computers is a leading journal that significantly contributes to the advancement of research and practice in the field of computer-aided engineering. Its comprehensive scope, rigorous standards, and international reach make it an invaluable resource for researchers, practitioners, and academics dedicated to the study and development of computer-aided engineering techniques and methodologies.

Journal Home: Journal Homepage

Editor-in-Chief: Jessica Zhang

Scope: It publishes original research articles, reviews, and technical notes that advance the understanding and application of computational methods in engineering practice. The scope of the journal encompasses a wide range of topics related to the intersection of engineering and computer science.
Key areas covered by the journal include, but are not limited to:
Computer-Aided Engineering (CAE): Research on the development and application of computational methods, algorithms, and software tools to support engineering design, analysis, optimization, and decision-making processes.
Finite Element Analysis (FEA): Studies on the theory, implementation, and application of finite element methods for solving complex engineering problems in structural mechanics, fluid dynamics, heat transfer, and electromagnetics.
Multidisciplinary Design Optimization (MDO): Exploration of optimization techniques and methodologies for optimizing engineering systems that involve multiple disciplines, objectives, and constraints.
Computer-Aided Design (CAD): Research on computer-aided design tools and methodologies for creating, modifying, and analyzing geometric models of engineering components and systems.
Simulation and Modeling: Application of computational simulation and modeling techniques to predict and analyze the behavior of engineering systems under various operating conditions.
Virtual Prototyping and Simulation: Development and application of virtual prototyping and simulation technologies to simulate the performance and behavior of physical prototypes in a virtual environment.
High-Performance Computing (HPC): Studies on the use of high-performance computing techniques and parallel processing for accelerating computational simulations and analyses in engineering.
Artificial Intelligence and Machine Learning: Integration of artificial intelligence and machine learning techniques into engineering computational tools and methodologies to enhance automation, optimization, and decision-making capabilities.
Engineering Applications: Practical applications and case studies demonstrating the use of computer-aided engineering tools and techniques in various engineering domains, including aerospace, automotive, civil, mechanical, and electrical engineering.