Topic Editors

Faculty of Civil Engineering, Architecture and Environmental Engineering, Lodz University of Technology, 6 Politechniki Street, 90-924 Lodz, Poland
1. Coimbra Institute of Engineering, Polytechnic University of Coimbra, Rua Pedro Nunes-Quinta da Nora, 3030-199 Coimbra, Portugal
2. RCM2+ Research Centre for Asset Management and Systems Engineering, Polytechnic University of Coimbra, Rua Pedro Nunes, 3030-199 Coimbra, Portugal

Numerical Methods and Computer Simulations in Energy Analysis, 3rd Edition

Abstract submission deadline
31 May 2026
Manuscript submission deadline
31 August 2026
Viewed by
234

Topic Information

Dear Colleagues,

This Topic is a continuation of the previous successful Topic “Numerical Methods and Computer Simulations in Energy Analysis”.

The main aim of this Topic is the dissemination of research regarding the current state of numerical methods, models, optimization algorithms, and computer simulation techniques in relation to energy analysis. Energy analysis comprises the processes of harvesting, consumption, storage, accumulation, transformation, and also its direct usage for the various energy-based numerical technique formulations and implementations. Modern numerical techniques include the finite element method, finite volume method, boundary element method, and the finite difference method. Likewise, this Topic covers approaches based on optimization algorithms, machine learning methods, and computer simulation techniques. Studies on a variety of meshless or semi-analytical approaches are welcome, together with those that address artificial intelligence or cellular automata models.

The interaction between these two fields includes the reliability engineering of (solar, geothermal, or wind) energy systems, the computer analysis of various coupled phenomena in engineering, numerical solutions of various fluid and heat flow problems, and simulations of thermal, mechanical, and electromagnetic energy exchanges in modern engineering systems and structures. Numerical studies of the energetic efficiency, optimization, and durability of new technical solutions are especially welcome, including hybrid energy harvesting.

All contributions related to numerical sensitivity analysis, as well as analyses of statistical scattering or stochastic phenomena in different forms of energy exchanges, are also invited. Semi-analytical approaches in energy numerical analysis are understood in the form of computer programs that are written in conjunction with computer algebra systems and their applications to deliver energy and its exchange determination for some specific applications. The most important aspect could be an engagement of the AI tools to discover the interconnections between the energy-related state parameters in different systems and their design parameters; studies describing new implementations of such algorithms are highly encouraged.

Manuscripts from academia, research and development laboratories, industry, and also from small companies are invited to this Topic collection.

Prof. Dr. Marcin Kamiński
Dr. Mateus Mendes
Topic Editors

Keywords

  • energy analysis
  • numerical techniques
  • optimization algorithms
  • computer simulation
  • finite element
  • optimization algorithms
  • machine learning
  • computer simulation
  • artificial intelligence

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Applied Sciences
applsci
2.5 5.3 2011 18.4 Days CHF 2400 Submit
Computers
computers
2.6 5.4 2012 15.5 Days CHF 1800 Submit
Energies
energies
3.0 6.2 2008 16.8 Days CHF 2600 Submit
Entropy
entropy
2.1 4.9 1999 22.3 Days CHF 2600 Submit
Mathematics
mathematics
2.3 4.0 2013 18.3 Days CHF 2600 Submit

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Published Papers (1 paper)

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30 pages, 6658 KiB  
Article
Dynamic Modeling of a Compressed Natural Gas Refueling Station and Multi-Objective Optimization via Gray Relational Analysis Method
by Fatih Özcan and Muhsin Kılıç
Appl. Sci. 2025, 15(9), 4908; https://doi.org/10.3390/app15094908 - 28 Apr 2025
Viewed by 121
Abstract
Compressed natural gas (CNG) refueling stations operate under highly dynamic thermodynamic conditions, requiring accurate modeling and optimization to ensure efficient performance. In this study, a dynamic simulation model of a CNG station was developed using MATLAB-SIMULINK, including detailed subsystems for multi-stage compression, cascade [...] Read more.
Compressed natural gas (CNG) refueling stations operate under highly dynamic thermodynamic conditions, requiring accurate modeling and optimization to ensure efficient performance. In this study, a dynamic simulation model of a CNG station was developed using MATLAB-SIMULINK, including detailed subsystems for multi-stage compression, cascade storage, and vehicle tank filling. Real gas effects were incorporated to improve prediction accuracy of the pressure, temperature, and mass flow rate variations during fast filling. The model was validated against experimental data, showing good agreement in both pressure rise and flow rate evolution. A two-stage multi-objective optimization approach was applied using Taguchi experimental design and gray relational analysis (GRA). In the first stage, storage pressures were optimized to maximize the number of vehicles filled and gas mass delivered, while minimizing compressor-specific work. The second stage focused on optimizing the volume distribution among the low, medium, and high-pressure tanks. The combined optimization led to a 12.33% reduction in compressor-specific energy consumption with minimal change in refueling throughput. These results highlight the critical influence of pressure levels and volume ratios in cascade storage systems on station performance. The presented methodology provides a systematic framework for the analysis and optimization of transient operating conditions in CNG infrastructure. Full article
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