Submit to Special Issue Submit Abstract to Special Issue Review for Applied Sciences Propose a Special Issue

Journal Menu

Journal Browser

Advances in Combustion Science and Engineering

Special Issue Editors
Special Issue Information
Keywords
Benefits of Publishing in a Special Issue
Published Papers

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Thermal Engineering".

Deadline for manuscript submissions: 20 June 2026 | Viewed by 4132

Share This Special Issue

Special Issue Editor

Dr. Ariyan Zare Ghadi

E-Mail Website
Guest Editor

School of Chemical Engineering, Chonnam National University, 77 Yongbong-ro, Buk-gu, Gwangju 61186, Republic of Korea
Interests: CFD; combustion; multiphase flows; heat and mass transfer

Special Issue Information

Dear Colleagues,

I am delighted to announce a new Special Issue of the prestigious international journal Applied Sciences, titled "Advances in Combustion Science and Engineering", for which I serve as the Guest Editor.

Combustion is essential for the production of energy, transportation, and industrial applications, forming the foundation of many technological and infrastructure advancements.

As global objectives veer toward sustainability, the development of cleaner, more efficient combustion technologies is critical for meeting energy demands while reducing environmental effects. This Special Issue focuses on the most recent research, developments, and applications in combustion science and engineering, including fundamental investigations, computational and experimental methodologies, and practical applications. Topics of interest include, but are not limited to, the following:

Combustion Modeling and Simulation
- Computational Fluid Dynamics (CFD) simulation for combustion;
- Kinetic studies of chemical reactions in combustion systems;
- Reduced-order modeling and machine learning in combustion research.
Combustion in Engines
- Advances in internal combustion engines, gas turbines, and propulsion systems;
- Strategies for improving engine efficiency and reducing emissions.
Alternative Fuels and Sustainability
- Combustion characteristics of hydrogen, ammonia, biofuels, and other renewable energy sources;
- Techno-economic analysis of alternative fuel systems.
Experimental Diagnostics
- Development of laser-based techniques, advanced imaging, and novel diagnostic tools for combustion analysis.
Pollutant Formation and Control
- Mechanisms of NO_x, CO, particulate formation, and promising emission reduction techniques.
Industrial Combustion Systems
- Innovations in burners, furnaces, and industrial-scale combustion technologies.
Deflagration and Detonation
- Studies on deflagration and detonation;
- Applications in propulsion systems, energy generation, and safety in industrial processes.
Energy Storage and Conversion
- Applications of combustion in hybrid systems, fuel cells, and energy recovery technologies.

We welcome submissions including theoretical, computational, experimental, and applied approaches to showcase the latest advancements and emerging trends in combustion science and engineering.

Dr. Ariyan Zare Ghadi
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

combustion
computational fluid dynamics
kinetic study
alternative fuels
combustion diagnostics
emission abatement

Benefits of Publishing in a Special Issue

Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (6 papers)

Download All Papers

Order results

Result details

Show export options Show export options

Select all

Export citation of selected articles as:

Research

Jump to: Review

17 pages, 28240 KB

Open AccessArticle

Ammonium Nitrate Coating with Nitrocellulose or the Inverse? A Study of the Coating Process and an Investigation of the Resulting Combustion Parameters

by Magdalena Fabin, Tomasz Jarosz, Kamil Barczak and Agnieszka Stolarczyk

Appl. Sci. 2025, 15(14), 7656; https://doi.org/10.3390/app15147656 - 8 Jul 2025

Viewed by 503

Abstract

This research focused on studying the issue of coating ammonium nitrate (AN) with nitrocellulose (NC) and its microcrystalline form (MNC), using two esterification methods: traditional (HNO₃/H₂SO₄) and in situ synthesis (KNO₃/H₂SO₄). This study employed Raman and IR spectroscopy, SEM, as well as thermokinetic and mechanical analyses. The results showed that the addition of NC-KNO₃ significantly increased the pseudo-energy of activation (E_A ≈ 268 kJ/mol for pure NC), improving thermal stability. MNC modifications, however, yielded inconclusive results. Despite the confirmed presence of NC on the AN surface (Raman band at 1128 cm⁻¹), SEM analysis did not show formation of a core–shell structure—a reversed-layer formation was observed, where AN deposited onto NC instead of the expected coating. The addition of diesel oil reduced the sensitivity of the mixtures (e.g., ANNC-D showed 35 J for impact and 288 N for friction) due to improved homogeneity. The esterification method affected the mechanical properties of the material: NC synthesised from HNO₃ was less sensitive than that obtained from KNO₃. This paper highlights the key role of nitrocellulose in modifying the properties of energetic materials, but further research is needed to control the coating process and optimise the synthesis conditions. Full article

(This article belongs to the Special Issue Advances in Combustion Science and Engineering)

► Show Figures

Figure 1

19 pages, 1361 KB

Open AccessArticle

Evaporation and Ignition of Isolated Fuel Drops in an Oxidizing Environment: Analytical Study Based on Varshavskii’s ‘Diffusion Theory’

by Laurencas Raslavičius

Appl. Sci. 2025, 15(13), 7488; https://doi.org/10.3390/app15137488 - 3 Jul 2025

Viewed by 476

Abstract

Varshavskii’s ‘Diffusion Theory’, less investigated due to its limited international visibility, can offer one of the simplest and, on the other hand, high-accuracy methods for evaluating the ignition delay of fossil fuel and biofuel droplets, including their blend. In this study, experimental pre-tests were conducted to determine pre-existing subject knowledge on stationary droplet combustion at ambient pressure and temperatures varying from 935 to 1010 K followed by simulation of droplet ignition times. The test fuels were mineral diesel (DF), RME and a 20% RME blend with DF. Simulations were performed for isobaric conditions. Using the detailed transport model and detailed chemical kinetics, the necessary rearrangements were made for the governing equations to meet the criteria for modern fuels (biodiesel, diesel, and blend). The influence of different physical parameters, such as droplet radius, or initial conditions, on the ignition delay time was investigated. The high sensitivity of the proposed methodology to experimental results was substantiated. Full article

(This article belongs to the Special Issue Advances in Combustion Science and Engineering)

► Show Figures

Figure 1

27 pages, 6139 KB

Open AccessArticle

Numerical Simulation of Natural Gas/Hydrogen Combustion in a Novel Laboratory Combustor

by Bruno M. Pinto, Gonçalo P. Pacheco, Miguel A. A. Mendes and Pedro J. Coelho

Appl. Sci. 2025, 15(13), 7123; https://doi.org/10.3390/app15137123 - 24 Jun 2025

Viewed by 666

Abstract

Hydrogen is a promising fuel in the current transition to zero-net CO₂ emissions. However, most practical combustion equipment is not yet ready to burn pure hydrogen without adaptation. In the meantime, blending hydrogen with natural gas is an interesting option. This work reports a computational study of the performance of swirl-stabilized natural gas/hydrogen flames in a novel combustion chamber design. The combustor employs an air-staging strategy, introducing secondary air through a top-mounted plenum in a direction opposite to the fuel jet. The thermal load is fixed at 5 kW, and the effects of fuel composition (hydrogen molar fraction ranging from zero to one), excess air coefficient (λ = 1.3, 1.5 or 1.7), and primary air fraction (α = 50–100%) on the velocity, temperature, and emissions are analysed. The results show that secondary air changes the flow pattern, reducing the central recirculation zone and lowering the temperature in the primary reaction zone while increasing it further downstream. Secondary air improves the performance of the combustor for pure hydrogen flames, reducing NO emissions to less than 50 ppm for λ = 1.3 and 50% primary air. For natural gas/hydrogen blends, a sufficiently high excess air level is required to keep CO emissions within acceptable limits. Full article

(This article belongs to the Special Issue Advances in Combustion Science and Engineering)

► Show Figures

Figure 1

26 pages, 4557 KB

Open AccessArticle

Quantitative Analysis of Explosion Characteristics Based on Ignition Location in an Ammonia Fuel Preparation Room Using CFD Simulation

by Jin-Woo Bae, Beom-Seok Noh, Ji-Woong Lee, Su-Jeong Choe, Kweon-Ha Park, Jeong-Do Kim and Jae-Hyuk Choi

Appl. Sci. 2025, 15(12), 6554; https://doi.org/10.3390/app15126554 - 11 Jun 2025

Cited by 2 | Viewed by 548

Abstract

Ammonia (NH₃) is a promising carbon-free marine fuel that is aligned with the International Maritime Organization’s (IMO) decarbonization targets. However, its high toxicity and flammability pose serious explosion hazards, particularly in confined fuel preparation spaces. This study investigates the influence of the ignition source location on the explosion characteristics of ammonia within an ammonia fuel preparation room using computational fluid dynamics (CFD) simulations via the FLACS platform. Nineteen ignition scenarios are established along the X-, Y-, and Z-axes. Key parameters, such as the maximum overpressure, pressure rise rate, reduction rate of flammable gas, ignition detection time, and spatial–temporal distributions of temperature and combustion products, are evaluated. The results show that the ignition location plays a critical role in the explosion dynamics. Ceiling-level ignition (Case 19) produced the highest overpressure (4.27 bar) and fastest pressure rise rate (2.20 bar/s), indicating the most hazardous condition. In contrast, the forward wall ignition (Case 13) resulted in the lowest overpressure (3.24 bar) and limited flame propagation. These findings provide essential insights into the risk assessment and safety design of ammonia-fueled marine systems. Full article

(This article belongs to the Special Issue Advances in Combustion Science and Engineering)

► Show Figures

Figure 1

21 pages, 11358 KB

Open AccessArticle

Hybrid Neural Network-Based Maritime Carbon Dioxide Emission Prediction: Incorporating Dynamics for Enhanced Accuracy

by Seunghun Lim and Jungmo Oh

Appl. Sci. 2025, 15(9), 4654; https://doi.org/10.3390/app15094654 - 23 Apr 2025

Viewed by 629

Abstract

The rapid expansion of international maritime transportation has led to rising greenhouse gas emissions, exacerbating climate change and environmental sustainability concerns. According to the International Maritime Organization, carbon dioxide (CO₂) emissions from vessels are projected to increase by over 17% by 2050. Traditional emission estimation methods are prone to inaccuracies due to uncertainties in emission factors, and inconsistencies in fuel consumption data. This study proposes deep learning-based CO₂ emission prediction models leveraging engine operation data. Unlike previous approaches that primarily relied on fuel consumption, this model incorporates multiple parameters capturing the relationship between combustion characteristics and emissions to enhance predictive accuracy. We developed and evaluated individual models—convolutional neural network (CNN), long short-term memory (LSTM), and temporal convolutional network (TCN)—as well as hybrid model (TCN–LSTM). The hybrid model achieved the highest predictive performance, with a coefficient of determination of 0.9726, outperforming other models across multiple quantitative metrics. These findings demonstrate the potential of deep learning for vessel emission assessment, providing a scientific basis for carbon management strategies and policy development in the international shipping industry. This study thus holds major academic and industrial value, advancing the field of deep learning-based emission prediction and extending its applicability to diverse operational scenarios. Full article

(This article belongs to the Special Issue Advances in Combustion Science and Engineering)

► Show Figures

Figure 1

Review

Jump to: Research

34 pages, 2400 KB

Open AccessReview

Data-Driven Computational Methods in Fuel Combustion: A Review of Applications

by Jacek Lukasz Wilk-Jakubowski, Lukasz Pawlik, Damian Frej and Grzegorz Wilk-Jakubowski

Appl. Sci. 2025, 15(13), 7204; https://doi.org/10.3390/app15137204 - 26 Jun 2025

Viewed by 806

Abstract

This review article provides a comprehensive analysis of the recent advancements in combustion science and engineering, focusing on the application of machine learning and genetic algorithms from 2015 to 2024. The study examines the integration of computational methods, including computational fluid dynamics, neural networks, and genetic algorithms, with various fuel types such as biodiesel, biomass, coal, gasoline, hydrogen, and natural gas. A systematic search in the Scopus database identified relevant articles, which were categorized based on fuel types and computational methodologies. The analysis covers key areas such as combustion modelling and simulation, engine applications, alternative fuels, pollutant control, and industrial combustion systems. This review highlights the growing role of machine learning and genetic algorithms in enhancing combustion efficiency, reducing emissions, and optimizing energy production, providing insights into the current state of the art and future trends in this critical field. The study further examines the geographical distribution of research, noting significant contributions from Canada, China, France, Germany, India, Iran, Japan, Malaysia, Pakistan, Saudi Arabia, the United Kingdom, and the United States, alongside other international contributions. A total of 165 peer-reviewed articles were analyzed, covering a range of combustion scenarios and fuel types. The most frequently applied methods include artificial neural networks (ANNs), support vector machines (SVMs), and random forests (RFs) for predictive modeling, as well as genetic algorithms (GAs) for system optimization. ANN-based models achieved high accuracy in predicting NO_x emissions and flame speed, with some studies reporting mean absolute errors below 5%. GA methods demonstrated effectiveness in fuel blend optimization and geometry design, achieving emission reductions of up to 30% in experimental setups. This review also highlights persistent challenges such as data availability, model generalization, and reproducibility, and proposes future directions toward more interpretable and standardized applications of ML/GA in combustion science. Full article

(This article belongs to the Special Issue Advances in Combustion Science and Engineering)

► Show Figures

Journal Menu

Journal Browser

Advances in Combustion Science and Engineering

Share This Special Issue

Special Issue Editor

Special Issue Information

Keywords

Benefits of Publishing in a Special Issue

Published Papers (6 papers)

Research

Review

Further Information

Guidelines

MDPI Initiatives

Follow MDPI