Computational study demonstrates a multi-objective optimization framework for decorative materials in environmental design, indicating improved aesthetic fidelity and reduced functional redundancy.
New decorative materials are increasingly required to satisfy both functional performance and style-expression demands in environmental design. To address the lack of quantitative relationships between material properties and style characteristics, this study proposes a collaborative optimization framework integrating material-property characterization, style-feature modeling, and application optimization. A twelve-dimensional parameter system covering mechanical, thermal, optical, and surface-response characteristics is established, and a quantitative mapping mechanism between material parameters and style features is constructed through multi-objective optimization. Particular attention is given to optical response behaviors, including diffuse reflectance, spectral characteristics, and surface scattering properties, which are modeled using BRDF-based analysis and multi-physics simulation. The framework further incorporates thermal-response evaluation and life-cycle assessment to achieve coordinated optimization of functional effectiveness and sustainability. Based on 245 groups of experimental and simulation data, the proposed method achieves a style restoration index of 0.92, reduces style adaptation error to 4.3%, and compresses functional redundancy to 7.8% while maintaining carbon-emission intensity within the prescribed threshold. The results demonstrate that the integration of material-response characterization, optical-response modeling, and data-driven optimization provides an effective engineering approach for the application of advanced decorative materials and functional composites in environmental design.
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Lv et al. (2026) studied this question.
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