Artificial Intelligence in the Design of Solid Propellants for Aerospace Applications
A special issue of Aerospace (ISSN 2226-4310). This special issue belongs to the section "Astronautics & Space Science".
Deadline for manuscript submissions: 31 December 2025 | Viewed by 29
Special Issue Editor
Interests: advanced composite materials; structural integrity and safety; computational modeling; energetic materials; solid propellants; safety simulations; machine learning for solid propellants applications in aerospace
Special Issue Information
Dear Colleagues,
Solid propellants are critical power sources for solid rocket engines used in missiles and space vehicles, playing an essential role in aerospace propulsion. With increasing demands for high burning rates, enhanced safety, and cost-effective formulations, there is a pressing need for more efficient design and optimization strategies. Traditional trial-and-error methods are often costly, time-consuming, and potentially hazardous. In this context, artificial intelligence (AI) and data-driven approaches are rapidly emerging as transformative tools for predicting and optimizing the key performance metrics of solid propellants, such as safety, burning rate, mechanical performance, and specific impulse.
The aim of this Special Issue is to contribute to the development of solid propellant technologies by exploring the integration of artificial intelligence (AI) and data-driven approaches, with a particular emphasis on aerospace applications. This Special Issue invites original research articles, reviews, and communications focusing on AI-assisted formulation design, the predictive modeling of key performance indicators (such as burning rate, specific impulse, and sensitivity), and experimental validation guided by machine learning. Contributions addressing hybrid modeling strategies that combine physics-based simulations with data-driven techniques are particularly welcome. Additional areas of interest include the physical and chemical properties of solid propellant components, interpretable and trustworthy AI models for material design, and intelligent design frameworks tailored for aerospace propulsion systems.
All submitted papers will undergo a rigorous peer review process to ensure they make a novel and meaningful contribution. A high academic standard will be upheld throughout the editorial process. The Editors are committed to conducting an efficient review and publication process to ensure the timely dissemination of high-impact research in this rapidly evolving field.
Dr. Tianshuai Wang
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. Aerospace is an international peer-reviewed open access monthly 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
- artificial intelligence
- aerospace applications
- solid propellant
- modeling
- energetic materials
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