Modelling and Simulation in Engineering

Scope & Guideline

Transforming Ideas into Engineering Realities

Introduction

Delve into the academic richness of Modelling and Simulation in Engineering with our guidelines, detailing its aims and scope. Our resource identifies emerging and trending topics paving the way for new academic progress. We also provide insights into declining or waning topics, helping you stay informed about changing research landscapes. Evaluate highly cited topics and recent publications within these guidelines to align your work with influential scholarly trends.
LanguageEnglish
ISSN1687-5591
PublisherHINDAWI LTD
Support Open AccessYes
CountryUnited States
TypeJournal
Convergefrom 2007 to 2024
AbbreviationMOD SIMUL ENG / Mod. Simul. Eng.
Frequency1 issue/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressADAM HOUSE, 3RD FLR, 1 FITZROY SQ, LONDON W1T 5HF, ENGLAND

Aims and Scopes

The journal 'Modelling and Simulation in Engineering' focuses on advancing the field of engineering through innovative modeling and simulation techniques. It encompasses a wide range of applications across various engineering disciplines, emphasizing both theoretical and practical approaches.
  1. Computational Modeling Techniques:
    The journal extensively publishes research on computational modeling methodologies, including finite element analysis (FEA), computational fluid dynamics (CFD), and machine learning-enhanced models, addressing complex engineering problems.
  2. Interdisciplinary Applications:
    Research often spans multiple engineering disciplines, showcasing applications in civil, mechanical, electrical, and environmental engineering, thereby promoting interdisciplinary collaboration.
  3. Real-World Case Studies:
    Many papers present real-world case studies, demonstrating the practical application of modeling and simulation methods in industrial and environmental contexts, which aids in bridging the gap between theory and practice.
  4. Innovative Simulation Approaches:
    The journal encourages the development and application of novel simulation techniques, including agent-based modeling and hybrid simulation approaches, to tackle emerging engineering challenges.
  5. Sustainability and Environmental Impact:
    A consistent focus on modeling approaches that assess environmental impacts and sustainability, particularly in the context of energy systems, resource management, and urban planning.
The journal has observed several emerging themes and trends that reflect the evolving landscape of engineering modeling and simulation. These areas are gaining prominence in recent publications and indicate the journal's responsiveness to contemporary challenges.
  1. Machine Learning and AI Integration:
    There is a growing trend towards integrating machine learning and artificial intelligence into modeling and simulation, enhancing predictive capabilities and automating complex processes across various engineering fields.
  2. Sustainability and Green Engineering Models:
    Research focused on sustainability, energy efficiency, and environmental impacts is on the rise, with an emphasis on developing models that optimize resource usage and minimize ecological footprints.
  3. Smart Systems and IoT Applications:
    The emergence of smart systems and the Internet of Things (IoT) is increasingly reflected in the journal's publications, showcasing models that facilitate smarter infrastructure and real-time data analysis.
  4. Advanced Materials and Structural Analysis:
    There is a notable increase in studies related to advanced materials and their applications in structural analysis, particularly in the context of structural integrity and performance under various conditions.
  5. Dynamic Simulation of Human Behavior:
    Research that involves the dynamic simulation of human behavior in emergency situations, transportation systems, and urban planning is gaining traction, highlighting the importance of human factors in engineering models.

Declining or Waning

While the journal has maintained a robust focus on several core themes, some areas have seen a decline in publication frequency or relevance. The following points highlight these waning scopes.
  1. Traditional Mechanical Systems Analysis:
    Papers focusing solely on conventional mechanical systems without integrating advanced computational methods or interdisciplinary approaches have decreased, as the field shifts towards more complex and integrated modeling techniques.
  2. Basic Statistical Modeling:
    There is a noted decline in the publication of basic statistical modeling studies, as the journal increasingly favors advanced modeling techniques that incorporate machine learning and AI methodologies.
  3. Single-Domain Studies:
    Research that isolates itself within a single engineering domain without cross-disciplinary implications appears to be waning, reflecting a broader trend towards interdisciplinary research that addresses complex real-world problems.

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