Planning cities for extreme heat: a methodological framework for urban resilience in residential building blocks

Engineering notes

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Chinese explanation / 中文解读

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Original abstract

The escalating frequency and intensity of extreme heatwaves (HWs) pose a critical challenge for densifying residential building blocks, creating a conflict between minimizing building energy demand and maintaining outdoor thermal safety. While optimizing morphology for resilience is a priority, current research predominantly relies on static analyses that assume a fixed climatic baseline. This overlooks the non-linear evolution of performance trade-offs, leaving designers trapped in a “stationarity trap.” This study addresses this gap by developing and validating a computational framework for the longitudinal, multi-objective optimization of residential building blocks under non-stationary climatic pressures. The methodology is demonstrated through an empirical application to a representative district in Stuttgart, Germany. The workflow integrates high-resolution climate projections (RCP8.5) with parametric modeling of distinct building block archetypes. A stacked ensemble of machine learning surrogate models is trained on physics-based simulation data and validated, achieving high predictive fidelity ( R 2 > 0.93). This predictive core drives a multi-objective optimization engine to balance Energy Use Intensity (EUI), Photovoltaic Potential (PVEG), and the Universal Thermal Climate Index (UTCI). Finally, SHAP-based interpretability is employed to quantify the shifting hierarchies of morphological influence across Historical, Mid-Future, and Far-Future horizons. Application of the workflow identifies three critical paradigm shifts in the performance logic of residential blocks. First, a quantifiable “Climate Penalty” emerges, with optimized designs exhibiting a systemic 60%–74% increase in baseline energy demand. Second, a non-linear “Adaptation Inversion” indicates that optimal strategies must pivot from “ventilative openness” in the mid-century to “defensive densification” (mutual shading) under late-century extremes. Third, a “Typological Grammar” of resilience reveals that adaptive levers are strictly governed by the intrinsic geometry of each block type rather than universal design rules. These findings demonstrate that static, universally optimal forms are fundamentally untenable. Ultimately, this research provides a robust methodological foundation for transitioning from static master planning toward adaptive, typology-specific resilience strategies for future residential districts.

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