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Comparison of two multi-objective optimization methods for composite radiation shielding materials.

Yao Cai1, Rui Hao2, Shaojie Yu2

  • 1China Ship Development and Design Center, Wuhan, 430064, China; School of Nuclear Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China.

Applied Radiation and Isotopes : Including Data, Instrumentation and Methods for Use in Agriculture, Industry and Medicine
|February 19, 2020
PubMed
Summary
This summary is machine-generated.

Two optimization methods were developed for radiation shielding composites, considering shielding, mass, volume, and mechanical/thermal properties. Both methods achieved synergistic optimization, with differences in solution sets provided.

Keywords:
Multi-objectiveNuclearOptimizationShielding material

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Area of Science:

  • Materials Science
  • Nuclear Engineering
  • Computational Science

Background:

  • Radiation shielding materials require optimization of multiple properties, including shielding effectiveness, mass, volume, mechanical strength, and thermal stability.
  • Resin matrix composites offer potential for tailored radiation shielding applications.

Purpose of the Study:

  • To establish and compare two multi-objective optimization methods for radiation shielding composites.
  • To achieve synergistic optimization of shielding, mass, volume, mechanical, and thermal properties.

Main Methods:

  • Utilized the Shuffled Complex Evolution (SCE) and Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) algorithms.
  • Employed the MCNP program for radiation shielding performance simulation.
  • Integrated widely used prediction models for mechanical and thermal property calculations.

Main Results:

  • Both the priori and posteriori optimization methods successfully achieved synergistic optimization of the targeted material properties.
  • The priori method yielded a single solution based on predefined weight values.
  • The posteriori method generated the complete Pareto-optimal set, offering a broader range of solutions.

Conclusions:

  • Both optimization methods are effective for radiation shielding materials, each with distinct advantages.
  • The choice between the priori and posteriori methods depends on specific application requirements and desired solution characteristics.