Mathematical Models and Artificial Intelligence Methods for Digital Twins in Science, Engineering and Medicine
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 20 September 2025 | Viewed by 559
Special Issue Editor
Interests: applied mathematics; mathematical modeling in physics and engineering; optimal control; optimization; inverse problems; mathematical finance; numerical methods
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The use of mathematical models in science, engineering and medicine is common. Usually, a model contains unknown parameters that must be determined using data generated from the observation of the phenomenon under investigation. The process of determining the model parameters using the data is called model calibration. The calibrated model can be used for prediction purposes.
In recent years, huge developments in the areas of sensors, telecommunications and computing power have made the emergence of 'digital twin technology' possible. A digital twin can be regarded as an 'enhanced' version of a mathematical model. The main features that characterize a digital twin are as follows:
- The dynamical interaction between the physical twin and its digital counterpart. Data taken from the physical twin are fitted and used in the digital twin during the evolution of the phenomenon studied.
- The data fitted in the digital twin are relative to the unique physical twin studied. For example, in the medicine, the data are relative to the individual patient under treatment.
- The digital twin and, in particular, its prediction capabilities are used in the decision-making process to optimize the outcome of the experiment or of the medical treatment.
The roots of digital twin technology are in aerospace engineering and in robotics. However, today, this technology is a widely applicable set of ideas that can be used in many different situations. Let us mention some of specific contexts where digital twin could be useful:
- Science: in the study of climate change.
- Engineering: in the governance of complex systems in logistics or in manufacturing. For example, in the manufacturing predictive maintenance of individual physical assets.
- Medicine: in precision medicine, where treatment and drugs are designed for the individual patient.
The Special Issue aims to collect contributions that involve mathematical models and/or artificial intelligence methods in the development and use of digital twins. Papers concerned with specific applications are welcome.
Prof. Dr. Francesco Zirilli
Guest Editor
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Keywords
- mathematical model
- artificial intelligence
- digital twin
- sensor
- numerical method
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