Digital Twin Technologies for Optimization and Innovation in Thermal Energy Systems

Thermal systems play a critical role in energy production, manufacturing, and building technologies. However, traditional approaches to thermal system design and maintenance are limited by a lack of real-time insights and predictive capability. Digital Twin technology, combining high-fidelity simulation, sensor data, and control algorithms, offers a powerful solution for overcoming these challenges. While DTs have been successfully deployed in aerospace and manufacturing, their use in thermal engineering is still emerging. This collection aims to showcase innovative research that brings DT concepts to the forefront of thermal science.

The goal of this Research Topic is to address the current gap in the application of Digital Twin technology within the field of thermal energy systems. By compiling contributions from academia and industry, this collection will explore how DTs can enhance system performance, reduce downtime, improve diagnostics, and facilitate real-time optimization. It also aims to open discussion on the standardization of DT approaches for thermal applications and define future research directions for this evolving domain.

This Research Topic welcomes manuscripts that address the development, application, and validation of Digital Twin systems in thermal energy domains. Areas of interest include (but are not limited to): modeling and simulation techniques, integration with IoT and sensor networks, control strategies, optimization algorithms, and real-world implementation.

Authors may submit original research articles, case studies, methods papers, brief research reports, and comprehensive review articles. Interdisciplinary and applied contributions are highly encouraged, especially those that link theory with industrial or real-world applications.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Data Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Data Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review
• Systematic Review
• Technology and Code

Keywords: Digital Twin, Thermal Systems, Energy Optimization, Modeling, System Diagnostics, Predictive Maintenance

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.