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Modelling and Simulation in Engineering - Hindawi | 2025 Impact Factor:1.1 | Cite Score:2.8 | SCOPUS Q3

Modelling and Simulation in Engineering Journal With Cite Score

Cite Score and Journal Rank of Modelling and Simulation in Engineering

  • About: Modelling and Simulation in Engineering is a peer-reviewed journal that focuses on the development and application of modelling and simulation techniques in engineering. The journal covers a broad spectrum of topics including mathematical and computational models, simulation methodologies, and applications across various engineering disciplines such as mechanical, civil, electrical, and aerospace engineering. Modelling and Simulation in Engineering aims to provide a platform for disseminating research that advances the field of engineering through improved modelling and simulation practices.
  • Objective:
    The primary objective of Modelling and Simulation in Engineering is to advance the science and practice of modelling and simulation in engineering by publishing high-quality research and innovations. The journal seeks to offer a comprehensive resource for researchers, engineers, and practitioners to share their work on new models, simulation techniques, and applications. Modelling and Simulation in Engineering aims to support the development and application of advanced modelling and simulation methods that enhance engineering design, analysis, and decision-making.
  • Interdisciplinary Approach:
    Modelling and Simulation in Engineering embraces an interdisciplinary approach, encouraging contributions from diverse fields such as applied mathematics, computer science, systems engineering, and various engineering disciplines. This approach ensures a broad exploration of modelling and simulation topics, integrating different perspectives and methodologies. By promoting interdisciplinary research, the journal addresses complex challenges in engineering and fosters the development of integrated solutions that advance the state of modelling and simulation practices.
  • Impact:
    The journal has a significant impact on both academic research and practical applications in engineering modelling and simulation. It is widely cited by researchers, engineers, and industry professionals interested in the latest developments and techniques in these fields. The research published in Modelling and Simulation in Engineering contributes to the advancement of new models, simulation methods, and applications that improve engineering design, analysis, and decision-making processes. The journal serves as a valuable resource for professionals involved in the development and application of modelling and simulation technologies.
  • Significance:
    Modelling and Simulation in Engineering plays a crucial role in advancing the study and practice of engineering modelling and simulation by providing a platform for high-quality research and practical insights. Its contributions support the development of innovative modelling and simulation methods and technologies that address current and future challenges in engineering. The journals commitment to excellence and interdisciplinary focus make it an essential resource for anyone involved in research, development, and application in engineering modelling and simulation. Through its rigorous scholarship and broad coverage, Modelling and Simulation in Engineering helps shape the future of engineering practice and innovation.

  • Editor-in-Chief:  Angelos Markopoulos

  • Scope: The Modelling and Simulation in Engineering (MSE) journal focuses on the development and application of modeling and simulation techniques in engineering. Its scope includes, but is not limited to:
  • Modeling Techniques: Research on various modeling techniques used in engineering, including mathematical, computational, and physical models. This includes approaches like finite element modeling, computational fluid dynamics, and system dynamics.
  • Simulation Methods: Studies on simulation methods and tools for analyzing and predicting the behavior of engineering systems. This includes discrete event simulation, Monte Carlo simulations, and agent-based modeling.
  • Engineering Applications: Application of modeling and simulation in various engineering disciplines, such as mechanical, civil, aerospace, electrical, and chemical engineering. Research may cover practical applications, case studies, and real-world problem-solving.
  • Validation and Verification: Research on techniques for validating and verifying models and simulations to ensure their accuracy and reliability. This includes comparisons with experimental data, sensitivity analysis, and uncertainty quantification.
  • Simulation Software and Tools: Development and evaluation of software and tools for modeling and simulation. This includes advancements in simulation platforms, user interfaces, and integration with other engineering tools.
  • Optimization: Application of optimization techniques in conjunction with modeling and simulation to improve engineering designs and processes. This includes methods for parameter tuning, design optimization, and multi-objective optimization.
  • Multiscale Modeling: Research on multiscale modeling approaches that integrate different scales of analysis, from microscopic to macroscopic levels. This includes hierarchical modeling and bridging the gap between different scales.
  • Real-Time Simulation: Development and application of real-time simulation techniques for applications that require immediate feedback and decision-making. This includes control systems, real-time monitoring, and interactive simulations.
  • Data-Driven Modeling: Exploration of data-driven approaches to modeling, including machine learning and artificial intelligence techniques. This includes predictive modeling, pattern recognition, and data assimilation.
  • Stochastic Modeling: Research on stochastic and probabilistic methods in modeling and simulation, including random processes, uncertainty modeling, and risk analysis.
  • System Dynamics: Application of system dynamics modeling to analyze and understand complex engineering systems and their interactions over time.
  • Simulation-Based Design: Use of simulation techniques in the design process to evaluate and refine engineering solutions. This includes virtual prototyping, design space exploration, and iterative design.
  • Educational Applications: Research on the use of modeling and simulation in engineering education, including instructional tools, teaching methodologies, and educational simulations.
  • Emerging Trends: Exploration of emerging trends and technologies in modeling and simulation, including advancements in computational power, new algorithms, and interdisciplinary applications.
  • Latest Research Topics for PhD in Computer Science
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  • Print ISSN:  1687-5591

    Electronic ISSN:  1687-5605

  • Abstracting and Indexing:  Scopus

  • Imapct Factor 1.1:  2025

  • Subject Area and Category:   Computer Science, Computer Science Applications, Engineering, Engineering (miscellaneous), Mathematics, Modeling and Simulation

  • Publication Frequency:  

  • H Index:  33

  • Best Quartile:

    Q1:  

    Q2:  

    Q3:  Computer Science Applications

    Q4:  

  • Cite Score:  2.8

  • SNIP:  0.672

  • Journal Rank(SJR):  0.259