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International Journal for Multiscale Computational Engineering - Begell House | 2024 Impact Factor: 1.4 | Cite Score:3.8 | Q2

International Journal for Multiscale Computational Engineering With Cite Score

Cite Score and Journal Rank of International Journal for Multiscale Computational Engineering

  • About: The International Journal for Multiscale Computational Engineering (JMCSE) is a peer-reviewed journal that focuses on the development and application of computational methods for addressing problems across multiple scales in engineering. It covers a wide range of topics related to multiscale modeling, simulation, and analysis in engineering disciplines. The journal aims to provide a platform for researchers and practitioners to share advancements in computational techniques that tackle complex, multiscale problems in engineering.
  • Objective:
    The primary objective of JMCSE is to advance the field of multiscale computational engineering by offering a comprehensive resource for researchers, engineers, and computational scientists. The journal seeks to explore new methodologies, technologies, and applications in multiscale modeling and simulation. JMCSE aims to support the development of effective computational approaches that address complex problems involving interactions across different scales, from the microscopic to the macroscopic.
  • Interdisciplinary Approach:
    JMCSE adopts an interdisciplinary approach by integrating insights from various fields such as computational mechanics, materials science, physics, mathematics, and engineering. This approach ensures a broad exploration of multiscale computational techniques, incorporating diverse perspectives and methodologies. By promoting interdisciplinary research, the journal addresses complex challenges and fosters the development of comprehensive solutions for multiscale problems in engineering.
  • Impact:
    The journal has a significant impact on both academic research and practical applications in the field of multiscale computational engineering. It is widely cited by researchers and professionals interested in the latest advancements and innovations in multiscale modeling and simulation. The research published in JMCSE contributes to the advancement of new computational methods and tools that improve the accuracy and efficiency of multiscale analyses in engineering. The journal serves as a valuable resource for those involved in the development and application of multiscale computational techniques.
  • Significance:
    The International Journal for Multiscale Computational Engineering plays a crucial role in advancing the study and application of multiscale computational methods by providing a platform for high-quality research and practical insights. Its contributions support the development of innovative computational approaches that address current and emerging challenges in engineering. The journals commitment to excellence and its interdisciplinary focus make it an essential resource for researchers, engineers, and computational scientists involved in the field of multiscale engineering. Through its rigorous scholarship and broad coverage, JMCSE helps shape the future of multiscale computational engineering and its applications.

  • Editor-in-Chief:  Jacob Fish

  • Scope: The International Journal for Multiscale Computational Engineering focuses on research and developments in multiscale computational methods and their applications. Its scope includes, but is not limited to:
  • Multiscale Modeling: Research on multiscale modeling techniques that bridge different scales of analysis, from atomic to macroscopic levels, to understand and predict complex systems.
  • Computational Methods and Algorithms: Exploration of computational methods and algorithms designed for multiscale problems, including hierarchical modeling, adaptive algorithms, and coupling techniques.
  • Applications in Materials Science: Studies on the application of multiscale computational methods to materials science, including the design and analysis of materials with specific properties.
  • Structural Mechanics: Research on the use of multiscale methods to model and analyze structures and mechanical systems, including damage assessment, deformation, and failure analysis.
  • Fluid Dynamics: Exploration of multiscale approaches in fluid dynamics, including turbulence modeling, flow analysis, and simulations of complex fluid systems.
  • Biological Systems: Studies on the application of multiscale computational techniques to biological systems, including cellular and tissue modeling, and the simulation of biological processes.
  • Engineering Design: Research on integrating multiscale computational methods into engineering design processes, including optimization, performance prediction, and system design.
  • Computational Chemistry and Physics: Exploration of multiscale methods in computational chemistry and physics, including electronic structure calculations and molecular dynamics simulations.
  • Data Analysis and Visualization: Research on techniques for analyzing and visualizing multiscale data, including data reduction, representation, and interpretation.
  • Software and Tools: Studies on the development and implementation of software and tools for multiscale computations, including computational frameworks, simulation platforms, and user interfaces.
  • Numerical Methods: Exploration of numerical methods and techniques specifically designed for multiscale problems, including discretization methods, solvers, and error analysis.
  • Multiscale Optimization: Research on optimization techniques that incorporate multiscale considerations, including multi-objective optimization and hierarchical optimization strategies.
  • Latest Research Topics for PhD in Computer Science
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  • Print ISSN:  15431649

    Electronic ISSN:  

  • Abstracting and Indexing:  SCOPUS

  • Imapct Factor 2024:  1.4

  • Subject Area and Category:   Computer Science, Computer Networks and Communications, Engineering, Computational Mechanics, Control and Systems Engineering

  • Publication Frequency:  

  • H Index:  35

  • Best Quartile:

    Q1:  

    Q2:  Computational Mechanics

    Q3:  

    Q4:  

  • Cite Score:  3.8

  • SNIP:  0.729

  • Journal Rank(SJR):  0.361