Against the backdrop of rapid urbanization and climate change, energy burden inequity arises between existing and new residential buildings due to generational differences in building envelopes. This study develops a demand-side energy burden equity assessment framework based on energy simulations of typical existing and new apartments in representative cities across China’s five major climate zones. The framework integrates multi-climate conditions, long-term evolution under different Shared Socioeconomic Pathways, and adaptable retrofit implications. Results indicate that demand-side energy burden inequity is widespread but structurally heterogeneous across climate zones, with the largest disparity observed in heating-dominated regions (up to 95.69 kWh/m² in Harbin). Under future warming, three scaling pathways emerge: convergence in heating-dominated regions (up to −27%), divergence in cooling-dominated and mixed regions (up to +382%), and offsetting effects driven by heating–cooling structural shifts in cold regions (up to −5%). Retrofit analysis shows that combined envelope upgrades achieve substantial inequity reduction (88–152%), though with diminishing marginal returns, while single targeted measures already yield high benefits in cooling-dominated and mild regions (74% and 83%, respectively). The findings provide differentiated and forward-looking evidence to support equity-oriented interventions in urban residential retrofitting and policy design.

The sustainable renewal of existing university student dormitories requires effective identification of occupant-perceived improvement needs to support targeted interventions and efficient resource allocation. This study develops a renewal need prioritization framework by integrating explainable machine learning and impact-asymmetry analysis (IAA). Based on 1507 valid questionnaires from 10 campuses of seven universities in Guangdong Province, an XGBoost-SHAP model was used to identify key environmental attributes influencing overall satisfaction, followed by IAA to examine their asymmetric effects. The results show that: (1) 17 key attributes were identified from 42 indicators, of which 15 met the criteria for IAA classification and exhibited distinct asymmetric effects; (2) a five-level renewal need prioritization framework was established, with per capita usable area, bathroom type, storage space, study and discussion space, damp and mold prevention, and sound insulation identified as core renewal needs; and (3) improving residential unit comfort through spatial optimization, furniture configuration, and environmental enhancement is an important pathway for enhancing occupant well-being and the long-term adaptability of existing dormitory buildings. This study provides empirical evidence for prioritizing existing dormitory renewal and allocating limited resources more efficiently, contributing to the sustainability of existing university residential environments.

The rational determination of cable forces is critical for ensuring the desired mechanical behavior of long-span cable-stayed bridges during construction and service. However, conventional deterministic optimization methods often overlook uncertainties in construction processes, which may lead to deviations in the as-built state. This paper proposes a reliability-oriented multi-objective cable force optimization method. Taking a single-tower hybrid girder cable-stayed bridge as the case study, a finite element model is established in MIDAS Civil, and the influence matrix method is employed to construct the mapping between cable forces and structural responses. Sensitivity analysis is conducted on four parameters to identify the most influential factors. Cable tensioning error is treated as a random variable following a normal distribution, and Monte Carlo simulation is adopted to evaluate the reliability index β. A multi-objective particle swarm optimization (MOPSO) algorithm is then implemented to jointly minimize cable force deviations and maximize β. A Sobol global sensitivity analysis shows that the back cables S1~S3 dominate the variance in the cable-force deviation, and that cable-to-cable interactions contribute about 32% of the output variance. The deterministic scheme achieves an average deviation of 0.85% and reduces construction steps from 11 to 6. When the coefficient of variation is 0.5%, the failure-probability-based reliability index of the optimized scheme exceeds 3.72 (Pf < 10⁻⁴), meeting the target of 3.5. At 1.0%, the failure-probability-based index decreases to 2.27, while the second-moment index of the optimized scheme increases from 1.96 to 3.29. A benchmark against NSGA-II under the same evaluation budget shows that MOPSO covers a wider range of reliability–accuracy trade-offs, while NSGA-II produces a more uniform and better-converged Pareto front. The method embeds reliability in the optimization process, overcoming the limitation of post hoc verification. It is recommended that the tensioning variation be controlled within 0.5%.