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Fuel and Energy: Unlocking the Potential of Combustion Research Techniques

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "I2: Energy and Combustion Science".

Deadline for manuscript submissions: 10 April 2025 | Viewed by 294

Special Issue Editor

State Key Laboratory of Multiphase Flow in Power Engineering, Xi’an Jiaotong University, Xi’an 710049, China
Interests: new experimental method development and system design; green propellants and alternative fuels; spray and droplet kinetics; combustion chemical reaction model and theory; combustion mechanism simplification and numerical simulation

Special Issue Information

Dear Colleagues,

Combustion is a fundamental process that underlies many energy conversion systems. Despite its widespread use, combustion remains a complex and not fully understood phenomenon, with many opportunities for improvement in efficiency, emissions, and reliability. Recent advances in experimental and computational techniques have opened up new avenues for understanding the intricate physical and chemical processes involved in combustion.

We are pleased to invite you to contribute to this Special Issue on “Fuel and Energy: Unlocking the Potential of Combustion Research Techniques” in the journal Energies.

This Special Issue aims to showcase cutting-edge research in the development of new experimental and theoretical methods to gain insights into fundamental combustion phenomena, including autoignition, flame propagation, detonation, spark ignition, and flame extinction. The focus will be on the application of advanced diagnostic techniques and novel experimental designs to investigate combustion dynamics, as well as the chemical kinetic models for alternative fuels, including biofuels (e.g., ethanol, biodiesel) and e-fuels (e.g., methanol, dimethyl ether). By exploring these topics, this Special Issue aims to provide a comprehensive overview of the state of the art in combustion research and its potential to address the challenges in fundamental combustion studies.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Experimental and theoretical studies of fundamental combustion phenomena, such as autoignition, flame propagation, and extinction.
  • Development and application of advanced diagnostic techniques, including imaging and spectroscopy, to investigate combustion dynamics.
  • Chemical kinetic modeling of alternative fuels, including biofuels and e-fuels.
  • Uncertainty analysis of new experimental and theoretical methods in combustion research.
  • Novel concepts and applications of combustion technology, including advanced power generation systems and propulsion systems.

Dr. Yingtao Wu
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. Energies 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 2600 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 technology
  • alternative fuels, including biofuels (e.g., ethanol, biodiesel)
  • e-fuels (e.g., methanol, dimethyl ether)
  • chemical kinetics
  • experimental methods
  • theoretical modeling
  • uncertainty analysis
  • sustainable energy

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Published Papers (1 paper)

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Research

14 pages, 1721 KiB  
Article
Standardizing the Ignition Delay Time Measurements of Rapid Compression Machine: An Inverse Application of the Livengood–Wu Integral Method
by Zhonghao Zhao and Yingtao Wu
Energies 2025, 18(1), 165; https://doi.org/10.3390/en18010165 - 3 Jan 2025
Viewed by 222
Abstract
The rapid compression machine measures ignition delay time at high pressures and low to intermediate temperatures. However, unavoidable facility effects, such as compression and heat loss, shift the measurements away from ideal (adiabatic and constant volume) values to varying extents. Consequently, the ignition [...] Read more.
The rapid compression machine measures ignition delay time at high pressures and low to intermediate temperatures. However, unavoidable facility effects, such as compression and heat loss, shift the measurements away from ideal (adiabatic and constant volume) values to varying extents. Consequently, the ignition delay times measured by different facilities can be in large deviations, especially for fuel mixtures without negative temperature coefficient behavior. To address this issue, this work proposes a standardization algorithm that correlates the measurements to the ideal ignition delay times. The algorithm applies the Livengood–Wu integral method inversely and adopts a Bayesian approach to optimize the correlation parameters. The ignition delay times of an ethanol mixture under distinct facility effects were further used to test the performance of this algorithm. The results show that the dispersed ignition delay times can be effectively standardized within 20%, facilitating the direct comparison of measurements from different facilities. By setting a proper residual target of the algorithm, reasonable standardization accuracy can be achieved. This method enables a significantly easier interpretation of the rapid compression machine experimental data and can be broadly applied to any fuel mixtures exhibiting single-stage ignition characteristics. Full article
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: Standardizing the Ignition Delay Time Measurements of Rapid Compression Machine: An Inverse application of the Livengood-Wu Integral Method
Authors: Zhonghao Zhao; Yingtao Wu
Affiliation: Xi'an Jiaotong University
Abstract: The rapid compression machine measures ignition delay time at high pressures and low to intermediate temperatures. However, unavoidable facility effects, such as compression and heat loss, shift the measurements away from ideal (adiabatic and constant volume) values to varying extents. Consequently, the ignition delay times measured by different facilities are in large deviations especially for fuel mixtures without negative temperature coefficient behavior. To address this issue, this work proposes a standardization algorithm that correlates the measurements to the ideal ignition delay times. The algorithm applies the Livengood-Wu integral method inversely, and adopts a Bayesian approach to optimize the correlation parameters. The ignition delay times of an ethanol mixture under distinct facility effects were further used to test the performance of this algorithm. Results show that the dispersed ignition delay times can be effectively standardized within 20%, facilitating the direct comparison of measurements from different facilities. By setting a proper residual target of the algorithm, reasonable standardization accuracy can be achieved.

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