Fuzzy optimal control of multilayer coverage based on radon exhalation dynamics in uranium tailings

Area of Science:

• Environmental Science
• Nuclear Safety
• Radiation Protection

Background:

• Radon exhalation from uranium tailings poses significant environmental and health risks.
• Controlling radon requires understanding complex parameters like diffusion, porosity, and percolation.
• Multilayered cover systems are more effective than single layers for radon reduction.

Purpose of the Study:

• To develop a dynamic model for radon exhalation control using multilayered coverage.
• To address the challenge of radon control under uncertain environmental conditions.
• To provide a framework for optimal decision-making in radon mitigation strategies.

Main Methods:

• Constructed a dynamic radon exhalation model using percolation-diffusion migration equations.
• Incorporated uncertain parameters using triangular membership functions.
• Employed an immunogenetic algorithm to determine objective function extreme value intervals.
• Developed fuzzy objective and constraint models for radon exhalation control.
• Utilized swarm intelligence algorithms for optimal decision-making under varying conditions.

Main Results:

• Validated the effectiveness of the proposed radon exhalation model with a practical example.
• Demonstrated that fuzzy optimization provides a database of decision-making schemes.
• Showcased guidance for optimal control and flexible construction management of multilayered covers.
• Achieved optimal radon control decisions under different possibility levels and importance conditions.

Conclusions:

• The dynamic fuzzy optimization model effectively addresses radon exhalation from uranium tailings.
• Multilayered coverage, optimized through fuzzy logic, offers a robust solution for radon mitigation.
• The approach provides valuable decision support for nuclear safety and radiation environment management.