Decision Science-Driven Selection of Advanced Thermal Protection Materials for Aerospace Applications

Advancements in aerospace technology have driven significant progress in developing materials for thermal protection. As aerospace systems evolve, they demand high-performance thermal protection solutions characterized by exceptional high-temperature resistance, lightweight properties, and efficient heat transmission. Addressing these challenges, Materials Informatics—often referred to as Materials 4.0—leverages extensive datasets on synthesis, processing, modeling, characterization, and material properties to enhance material discovery and selection for aerospace applications. A novel approach integrating multiple-attribute decision-making (MADM) methods, principal component analysis (PCA), and hierarchical cluster analysis (HCA) has been implemented for material evaluation. Property weights were determined using objective (Shannon’s entropy method) and subjective techniques to ensure a balanced assessment. Several MADM methods, including the Technique of Order Preference by Similarity to Ideal Solution (TOPSIS), Grey Relational Analysis (GRA), and Operational Competitive Ratio (OCRA), consistently similarly ranked materials. PCA and HCA further validated these rankings by clustering materials with similar characteristics. This study highlights correlations among various thermal protection materials, identifies viable substitutes for currently used materials, and suggests opportunities for performance enhancement. By consolidating material rankings and categorizing alloys based on shared attributes, the research provides valuable insights into selecting and developing sustainable thermal protection materials for aerospace applications.