Weatherability Optimization for Ice-Shell Architecture Using Explainable Surrogate Models
Weatherability and Structural Reliability of Ice-Shell Architecture
The climatic vulnerability of ice-shell buildings is a major factor restricting their large-scale application, especially in cold regions such as northeastern China. Extreme temperature fluctuations, solar radiation, and wind loads contribute to elastic energy degradation and structural instability. This topic examines the mechanisms of weather-induced deterioration and their implications for safety, reliability, and long-term performance. Understanding these relationships establishes a scientific foundation for developing predictive tools and enhancing resilience in ice-shell construction.
Surrogate Modeling for Early-Stage Architectural Optimization
Early-stage design often struggles with limited data, making direct simulation-based optimization slow and resource-intensive. Surrogate models offer an efficient alternative by approximating complex physical behaviors using a reduced number of computational samples. This section discusses the construction, training, and deployment of surrogate models tailored for ice-shell architecture. It highlights how these models reduce computational cost, support rapid design exploration, and enable iterative adjustments without sacrificing prediction accuracy.
SHAP-Based Explainable AI for Feature Interpretation
Explainability is essential in architectural engineering, where design choices must be transparent, justifiable, and reproducible. This topic focuses on using Shapley Additive Explanations (SHAP) to interpret the influence of spatial and shape-related features on weatherability outcomes. By quantifying the contribution of each parameter, SHAP enhances model trustworthiness, identifies dominant design variables, and guides architects and engineers toward more informed and evidence-driven decisions.
Validation Through Engineering Case Studies
To ensure practical reliability, the proposed methodology is validated through two real engineering cases of airbag mold ice-shell buildings. This topic elaborates on the evaluation process, comparing predicted weatherability indices with actual performance outcomes. The findings demonstrate the method’s effectiveness in capturing climatic coupling relationships, such as orientation effects and geometric dependencies, confirming its generalizability across varied ice-shell scenarios.
Optimization Results and Design Parameter Sensitivity
The study reveals that key parameters—such as long-axis length, support length, and building orientation—play decisive roles in determining the weatherability index. Through targeted optimization, the approach successfully reduces the index by 30–40%, showcasing substantial improvements in durability and safety. This topic highlights the sensitivity of design variables, unveils optimal configurations, and emphasizes how automation-driven optimization can transform the design process for ice-shell architecture.
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