Systems Modelling, Simulation and Experimentation for Condition Monitoring
A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Machines Testing and Maintenance".
Deadline for manuscript submissions: 30 November 2025 | Viewed by 48
Special Issue Editor
Interests: thermal management; aircraft fuels; environmental control systems
Special Issue Information
Dear Colleagues,
This Special Issue explores the evolving landscape of systems modelling, simulation, and experimental validation techniques within the field of condition monitoring (CM). With increasing demands for reliability, safety, and efficiency across engineering systems—particularly in aerospace, automotive, energy, and manufacturing sectors—condition monitoring has emerged as a critical enabler of predictive maintenance and intelligent asset management.
This Issue brings together cutting-edge research that highlights the integration of physics-based models, data-driven approaches, and hybrid methodologies to diagnose, predict, and manage system health. It features contributions that employ digital twins, multi-domain simulation frameworks, machine learning algorithms, and real-time sensor fusion to monitor complex systems under operational conditions.
A key emphasis is placed on the synergy between modelling and physical experimentation, showcasing methods that validate simulations through controlled testing or in situ measurements. These contributions provide insights into scalable frameworks that reduce maintenance costs, optimise lifecycle performance, and support decision-making in real-world applications. This Issue is aimed at researchers, engineers, and practitioners who are advancing the frontiers of intelligent condition monitoring through innovative approaches that combine computational rigour with experimental depth.
Dr. Fakhre Ali
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. Machines 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
- condition monitoring
- reliability
- predictive maintenance
- data-driven
- digital twins
- machine learning
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