Ministry of Housing and Urban-Rural Development

The development of high-efficiency energy dissipation devices is crucial for mitigating the significant threat posed by seismic loads to modern buildings. Therefore, the purpose of this work is to design a novel fluid viscous inerter damper (FVID) and systematically investigate its mechanical performance through theoretical derivations, experiments, and finite element simulations. Furthermore, the impact of FVIDs on the seismic performance of structures is comprehensively evaluated. The advantage of FVID is that under external excitation, the fluid can flow through multiple channels, thereby generating inertial and damping forces to dissipate energy. The theoretical model of FVID’s output force is determined based on FVID’s construction and fluid flow characteristics. The hysteresis performance of the FVID is evaluated through cyclic loading tests, and the influence of the cross-sectional radius and number of turns of the helical tube on its output force is analyzed. By performing finite element simulations of the internal flow field of FVID, the distributions of fluid pressure and velocity at different positions within FVID are analyzed. Based on Simulink, the focus is on investigating the control effect of FVID on structural responses under non-pulse near-field ground motions, pulse-type near-field ground motions, and far-field ground motions. The results indicate that the FVID has a strong energy-dissipation capacity and can effectively reduce structural responses under different types of earthquakes. The cross-sectional radius of the helical tube is a key design parameter that determines the damper’s output force. For highly destructive pulse-type near-field ground motions, FVIDs still exhibit excellent comprehensive performance in the structure.

Spatial density plays a pivotal role in influencing land-use patterns and land consumption. To meet evolving industrial needs and maximize limited land resources, incorporating floor area ratio (FAR) optimization into urban planning is essential. Existing studies on floor area ratio largely focus on residential land, overlooking how industrial FAR varies across regions and sectors and what drives these differences. This study addresses this gap by analyzing newly supplied industrial land data from 90 counties in Zhejiang Province, China (2019-2023), using panel regression analysis. The findings reveal a steady FAR increase of 6.8% annually, with the highest levels in the northern coastal cities Hangzhou and Ningbo, a mid-range peak around Jinhua, and relatively lower but rising values toward the southern areas including Wenzhou. FAR is positively associated with land prices and government land supply, but negatively with per capita arable land. Significant regional and industrial disparities are observed, shaped by geography, land price and industry structure. These findings underscore the need for adaptive FAR policies that balance land efficiency and industrial compatibility. The study recommends stabilizing industrial land prices, supporting clustered small and micro enterprises with higher-density development, and selectively implementing the Industry's Going Upstairs (IGU) strategy based on structural load, production characteristics, and suitability for mixed-use.

This study addresses the technical challenges of using construction residue sand (CRS) with high mud content in 3D printing by developing a novel sustainable mortar system. The key novelty lies in optimizing the mix design with calcium sulfoaluminate cement (CSA) and defining a quantitative printability window. Results show that at a CSA dosage of 10–15% and a sand–binder ratio of 1.4–1.5, the mortar achieves excellent printability, with a fluidity of 165–195 mm and a slump of 10–40 mm. Mechanistically, CSA promotes AFt formation, refining pore structure, and enhancing mechanical strength. This work provides a high-value pathway for recycling construction waste and advancing green intelligent construction.

The sustainable recycling of construction waste is a critical challenge in civil engineering. Recycled powder (RP) shows great potential as a supplementary cementitious material, but the deterioration in frost resistance it causes limits the application of recycled powder concrete (RPC) in cold regions. This study screened the polycarboxylate superplasticizer (PC) with optimal compatibility with RP through adsorption tests and systematically compared the improvement effects of antifreeze water-reducer (AR), air-entraining agent (AE), and antifreeze agent (AF) on frost resistance. Macroscopic properties were evaluated via freeze-thaw cycle tests, and microscopic mechanisms were analyzed using scanning electron microscopy (SEM), super depth of field (SDF) imaging, and mercury intrusion porosimetry (MIP). Results indicated that after 200 freeze-thaw cycles, the frost resistance improvement ranked as 1% AF > AR > 5% AE. Quantitative analysis revealed that AF optimized the pore structure, reducing the proportion of harmful pores > 200nm by 8.73%, significantly increasing hydration products, and effectively inhibiting frost heave damage. The study confirms that AF effectively enhances the durability of RPC, providing technical support for the resource utilization of construction waste in concrete engineering in cold regions.

Accurate cooling load prediction is essential for energy-efficient HVAC system operation. However, the stochastic and nonlinear nature of load data challenges conventional neural networks, causing prediction delays and errors. To address this, a novel hybrid model is developed. The approach first applies a two-stage decomposition (CEEMDAN with K-means and VMD) to process complex cooling load data. Then, a CNN-BiLSTM network optimized by the Crested Porcupine Optimizer and integrated with an attention mechanism is constructed for prediction. Experimental results demonstrate the model’s high performance, achieving a 96.75% prediction accuracy with a MAPE of 3.25% and an R2 of 0.9929. The proposed model shows strong robustness and generalization, providing a reliable reference for intelligent building energy management.

Currently, there remains a lack of systematic quantitative analysis of the acoustic impact mechanism of ancestral temple theatres in relation to their core function of opera performance. This paper takes the Zhaomutang—a typical ancestral temple theatre in northeast Jiangxi—as an example, and comprehensively uses on-site mapping, impulse response testing, and ODEON three-dimensional sound field simulation to conduct acoustic sensitivity analysis on five key spatial elements of the theatre. The results show that the theatre has a hierarchical sound field pattern along its depth, characterized by “high in the front, low in the rear, stronger on the sides and weaker in the middle”. The front patio and the Xiangtang support the clarity of Gan opera dialogue and the fullness of singing through early lateral reflections and moderate reverberation (EDT of 0.8–1.1 s, C80 of 3.2–6.1 dB). However, the rear patio and the Qintang show apparent loudness deficiency (G of −1.5–3.2 dB) and lack of spatial immersion (LF80 below 0.23). The most effective optimization comes from the reconstruction of the geometric relationship between performers and audience: moving the performers forward and appropriately raising the stage and audience area floor can significantly shorten the rear area EDT and increase C80 and G; in contrast, the improvement in sound quality brought about by adding a patio cover and raising the gables is minimal, and the changes in various parameters are generally less than 1 JND. Based on this, the “schedule priority—reversible intervention” acoustic maintenance strategy for living heritage is proposed, and it is suggested that reversible reflective components be set in the side corridor to specifically enhance the sense of immersion in the rear area sound field. The study constructs a quantitative correlation framework of space, materials, and sound field, providing methodological support and parameter basis for the acoustic assessment and protective utilization of ancestral temple theatres.

The recent rise in anti-globalization sentiment has renewed interest in how tariffs influence the location decisions of multinational enterprises (MNEs). However, these decisions have also been reshaped by ongoing geopolitical tensions-a factor that remains underexplored in the existing literature. In this study, we construct a panel dataset comprising 283,272 country-country-industry observations spanning the years 2009 to 2021. The data are drawn from the WITS, BvD, World Bank, and GDELT databases. Using fixed-effects regression, fixed-effects logit, and fixed-effects negative binomial models, we examine how MNEs respond to tariffs under varying levels of geopolitical risk. Our analysis yields three key insights. First, in contexts of low or no geopolitical risk, higher tariffs increase the likelihood of international investment by MNEs, consistent with the “tariff jumping” hypothesis. However, under high geopolitical risk, this effect disappears-regardless of tariff levels, MNEs are not more likely to invest abroad. Second, tariff increases can escalate low levels of geopolitical tension between home and host countries, further discouraging international investment. In contrast, high levels of geopolitical risk are not significantly correlated with tariff changes. Third, when low-level geopolitical tensions arise, MNEs may redirect investment to neighboring countries or major trading partners of the host country as a way to access its market indirectly.