Amid evolving public health challenges and increasing demands for carbon reduction, the optimization of hospital building performance has become a critical concern. This study focuses on nursing units in general hospital wards, with the aim of balancing natural ventilation, daylighting, and energy efficiency. A parametric generation and multi-objective optimization framework was developed on the Grasshopper platform, integrating spatial parameter modeling with performance simulations of natural ventilation (Butterfly), daylighting (Honeybee-Radiance), and energy consumption (Honeybee-Energy). Coupled with the Wallacei evolutionary algorithm, the framework enabled an automated workflow that facilitated coordinated optimization of multiple objectives. The results revealed pronounced trade-offs among the three indicators. Relative to the original scheme, the Average Optimal Solution improved ventilation from 0.37 to 0.51 m/s and daylighting from 58.72 % to 63.04 %, with only a slight increase in energy use intensity (about 0.7 %). The AWS-Optimal Solution achieved the highest ventilation (0.52 m/s), the AUDI-Optimal Solution delivered the best daylighting (64.29 %), and the EUIOptimal Solution minimized energy consumption (211.62 kWh/(m2 & sdot;a)) at the expense of other indicators. These findings confirm that single-objective optimization undermines overall performance, whereas multi-objective optimization ensures more balanced outcomes. The proposed approach contributes methodological and theoretical foundations for performance-driven, lowcarbon hospital design, thereby supporting the development of sustainable healthcare environments.

Rural building clusters have significant prospects for solar energy application. However, the unclear impact of building shading on solar radiation distribution impedes their effective utilization. To address this issue, we conducted case studies in three villages with diverse morphologies in Nanjing. Employing a 12.5 m resolution digital elevation model (DEM), 3D building models, and hourly radiation simulation, we investigated the annual accumulated solar irradiance of these villages with and without building shading. The results showed that the impact of mutual shading is more substantial on facades than on rooftops. Without the shading, the façade annual accumulated solar radiation is 29.8–55.5

Hot and arid regions require substantial energy to maintain indoor thermal comfort due to extreme climatic conditions. Selection and optimization of building materials offer substantial potential for enhancing energy efficiency and thermal comfort. This study investigates building envelope materials' impacts on energy efficiency and occupant comfort through multi-objective optimization, evaluating six materials (insulated adobe, adobe, fire bricks, concrete, stone masonry and sintered bricks). In addition to Energy Use Intensity (EUI), Predicted Mean Vote (PMV) and Percentage of People Dissatisfied (PPD), a novel comfort level index is proposed, integrating thermal comfort perception and energy efficiency. This index quantifies both occupant thermal comfort perception and energy effectiveness of achieving such comfort conditions. A case study of Sukkur, Pakistan, using EnergyPlus simulations revealed insulated adobe as the optimal solution. Its Pareto-optimal configuration reduced annual energy consumption by 37.6% compared to concrete while ensuring thermal comfort for occupants. The results highlight that insulated adobe has superior thermophysical properties for balancing energy savings and comfort in hot, arid climates. This framework provides architects and policymakers with a decision-making tool to achieve climate-responsive designs through material optimization, advancing sustainable construction practices. The methodology and index offer theoretical and practical contributions to building performance evaluation.

3D modeling is of great significance to building engineering, visualization and design, but it remains challenges of scalability, cost, and labor-intensive manual processes that are difficult to apply on a large scale in building heritage preservation and rural revitalization. To address these issues, this study proposes a novel deep learning-based approach, which for the first time combines instance segmentation, Mask2Former and Mask R-CNN, with shadow-derived height estimation from remote sensing images to achieve automated 3D reconstruction of Jiangnan traditional villages. Deep learning algorithms, Mask2Former and Mask R-CNN, were used to automatically train and predict the datasets of buildings and shadows. Morphological postprocessing was then applied to regularize the extracted binary mask contours of traditional villages, and building heights were estimated through calculated shadow lengths. Finally, validation was conducted through comparisons between deep learning-estimated and measured heights from unmanned aerial vehicle tilt photography across two villages. Results demonstrate that, Mask2Former shows better performance, with accuracy of 88.95 % and precision of 89.46 %. The mean absolute error, root mean square error, and mean absolute percentage error are of all buildings are 0.53 m, 0.92 m, 9.59 %, respectively, confirming the reliability of the proposed approach in estimating building heights. This study provides an automated, efficient, and lowcost technique for 3D modeling in rural buildings, addressing the critical need for scalable traditional villages heritage digitization.

Rural building retrofit plays a pivotal role in achieving national energy goals and enhancing residential wellbeing. However, due to the neglect of village morphology, its progress and effectiveness are impeded. To address this issue, this study examined 300 rural building groups, including traditional and non-traditional villages in Nanjing, China. Combining URBANopt SDK with a SHAP value-based machine learning model, we quantified the impact of rural morphology on building cluster energy use intensity (EUI) and retrofit performance for the first time. Furthermore, to account for rising energy demands in rural regions, a high-intensity energy use pattern was introduced to evaluate the long-term dynamics of morphological effects. The results show that average building footprint area (BFPA) is the most influential morphology. As BFPA increases from 50 to 100 m2, cluster EUI declines linearly. Roof insulation proved the most effective retrofit measure, yielding EUI savings exceeding 6 % and 10 % in current and future scenarios, respectively. With rising energy demand, morphological influences intensify: the EUI gap between clusters with minimum and maximum BFPAs widened to 14.6 %, while energy-saving rates for all measures nearly doubled. These findings highlight the necessity to incorporate rural morphology into building energy retrofit, particularly in a future of growing energy demand.

Rural areas have a large quantity of rooftops and facades appropriate for installing PV panels. However, the unclear impact of rural morphology on PV potential hinders their effective utilization. To address this challenge, this study examined 300 clusters of traditional and non-traditional rural buildings in Nanjing. 17 morphological indicators were identified, representing plot shape, built density, building form, and terrain variation. The annual PV power generation and Levelized cost of electricity (LCOE) were simulated. Using an explainable machine learning framework (XGBoost algorithm combined with SHAP values), we explored the relationship between rural building morphology and PV potential. The results revealed that mean building height (BH) and floor area ratio (FAR) are key factors for PV power generation, while only BH is crucial for LCOE. As BH and FAR increase, PV generation declines, while LCOE rises. Particularly, BH has a stronger influence on technical potential in traditional clusters, whereas FAR plays a comparable role in non-traditional ones. Using these indicators, rural clusters can be categorized into three typologies for technical potential: low BH-low FAR, high BHlow FAR, and high BH-high FAR, and two for economic potential: low BH and high BH, with mean values being 176.1, 134, 121.5 kWh/m2/y, and 0.5, 0.53 CHY/kWh, respectively. A demonstration conducted outside Nanjing showed that our findings can be applied to the broader Yangtze River Delta region with a maximum error of less than 15 %. This study provides insights to inform rural PV policy-making and system planning, which are essential for China's low-carbon energy transition.

The increasing density and height of residential buildings have heightened the concerns regarding inadequate sunshine exposure in outdoor areas. With multi-objective optimization experiments, existing evaluation measures, such as Sunshine Times (ST), are not able to sufficiently capture the spatial features required to find the best design for outdoor sunlight conditions quickly. Spatial Outdoor Sunshine Autonomy (sOSA) is proposed in this paper as a comprehensive indicator for the rapid assessment of cumulative sunlight exposure in various outdoor scenarios. The definition of the indicator is first presented through formula derivation. Subsequently, the rapid simulation method of the sOSA indicator in Rhino is demonstrated. Utilizing the Maigao Bridge Block in Nanjing as a prototype, the application of this indicator in multi-objective optimization experiments for new residential area planning and design is showcased. Finally, the results are evaluated, and the suggestion is made to combine sOSA with ST maps and wind speed cloud maps for enhanced practical guidance.

Limited comprehensive methods exist for studying spatial energy consumption distribution, integrating statistical and energy data. This paper introduces a novel approach for analyzing residential heating and cooling energy demand distribution. It employs clustering algorithms to study climate variables' impact on energy demand distribution and assesses building energy demand intensity regionally, taking China as a case study. Initially compiling a dataset comprising climate characteristics, socioeconomic factors, and energy demand through data collection and simulation, the study compares clustering algorithms, highlighting the effectiveness of K-means in clustering high-dimensional climate-energy datasets. K-means analysis reveals temperature-based daily methods significantly affect building energy intensity, alongside factors like radiation intensity and humidity impacting regional energy demand variably. Additionally, climate's influence on residential building energy consumption intensity varies regionally, with total energy demand influenced by population and economic factors. This paper offers insights for energy management and policy formulation.

This paper studies the sufficient, necessary, and optimal conditions of the phenomenal transparency of architectural space (PTAS) by the eigenvector and eigenvalue of the gradient function of Scalar Field Function (SFF). Then, the SFF's method is used to analyze the PTAS of significant contemporary or canonical architectural works. The conclusions are: the eigenvalue of the SFF and its integral can be used to describe PTAS; the sufficient and necessary conditions of PTAS are the eigenvalue cannot be zero, and the area integral of the eigenvalue should be greater than a certain value; the optimal condition of PTAS is that the eigenvalue is the largest; the corresponding design methods include spatial stratification, graphic overlay, and grid rotation.

Characterization of solar photovoltaic (PV) potential is crucial for promoting renewable energy in rural areas, where there are a large number of roofs and facades ideal for PV module installation. However, accurately estimating solar PV potential on three-dimensional (3D) rural surfaces has been challenging due to the lack of 3D building models. To address this issue, we proposed a novel approach, which for the first time constructs rural 3D building models from publicly available satellite images and vector maps. Based on these models, it precisely evaluates the solar PV potential of rural rooftops and facades. The approach was validated against two realistic 3D village models and on-site solar radiation measurements. Using the validated approach, case studies in a village and on a large-scale island were conducted, respectively. The results showed that rural rooftops facing south and north, and facades facing south and west, have the highest PV potential ranks. North-facing rooftops with a slope of 30° represent 32.7% of the total rooftop solar PV potential, therefore, they should not be neglected in future evaluations. The proposed approach is cost-effective and valid for accurately assessing micro- and macro-scale rural solar PV potential that can facilitate rural renewable energy penetration.

为了量化分析水体微气候冷却效应,指导村镇规划设计,采用实地测量和数值模拟等方法,研究了宜兴市周铁镇中水体气温冷却值的时空分布特点,并将村镇形态要素指标与水体冷却值进行相关性分析,得到不同半径范围形态要素指标对水体冷却值的影响效果,从而构建出基于村镇形态要素指标的水体冷却值回归模型.结果 表明,季节变化、日夜交替以及风向风速均会对水体的冷却范围与强度产生影响.除气象要素以外,水体自身及其外部空间与植被特征共同影响水体冷却效应;水体率与绿化率的增加、周边建筑密度的减小,会导致水体冷却效应增强.基于数值模拟结果提出的水体冷却值回归模型可依据村镇形态要素指标判断水体冷却值大小,进而为村镇水体空间的设计与改造提供微气候层面的技术指导.

To improve the poor thermal properties of traditional structural insulated panels (SIPs) for better energy saving effect in the building, composited structural insulated panels (CSIPs) with glass fiber reinforced plastic (GFRP) and cement (GFRC) materials were developed in this study. ANSYS is used to simulate the thermal properties of SIPs and CSIPs, and energy consumption of a house with these creative CSIPs were simulated by EnergyPlus. The results indicated that the zone method and modified zone method are acceptable to compute the R-value of the SIPs and the CSIPs. However, isothermal method and the parallel method are unsuitable to calculate their thermal resistance. A reduction in the stud web area and replacement of the steel web by less conductive materials are two effective ways to improve the thermal performance of SIPs. Furthermore, in terms of energy savings and thermal properties, GFRP SIPs are considerably better than steel SIPs. The conclusions are: the thermal properties of CSIPs with GFRP, GFRC or wood sheathings are nearly the same. However, a tube stud should be preferentially selected considering that its mechanical properties, easy design and construction are better than that of a folded plate. Moreover, GFRP and GFRC sheathings are given priority over wood. The novelty and new contribution of this paper is to design a thermal insulation, mechanical and durable CSIP with GFRP and GFRC, and use ANSYS to calculate its thermophysical properties and use EnergyPlus to simulate the energy consumption of a house with this CSIP.

Integrated transportation system planning is forward-looking and oriented to the future development of transportation. It is an important issue for special planning in terms of current land and spatial planning, and all community sectors recognize its importance. The continuous development of big data technology in recent years has brought a great deal of transformative power to urban traffic planning theory and technology. Using mobile phone signaling data (MPSD) to analyze and calculate traffic data information is a new technology in wide-area dynamic traffic detection. This paper uses MPSD to extract traffic contact characteristic data, commuter contact characteristic data, and thermal population data to analyze the traffic characteristics of Ma'anshan's metropolitan clusters, suburbs, and city areas. We identify its co-urban connection characteristics with neighboring cities and the strong southern river corridor of the metropolis, the characteristics of the connection, and the centripetal connection of the central city. According to the problems existing in Ma'anshan's facility configuration and traffic model, we propose corresponding countermeasures: building a multilevel integrated transportation system in the same city at the metropolitan cluster regional level; forming a centrally radiating multiple-transit network to support the development of the urban spatial pattern at the suburban level; and forming public transportation leadership and road support to optimize the urban transportation network at the city level.

建筑体形系数计算式包含的因子有建筑的长、宽和高,把长和宽两因素进行组合,即为建筑的底层平面形态.通过DesignBuilder软件模拟与分析发现:建筑平面面形系数与底层面积和建筑能耗息息相关,其中建筑能耗与面形系数呈正比关系,与底层面积呈反比关系,并由此推导出建筑平面能耗系数算式.为揭示斯宅传统民居平面能耗系数在宏观层面的分布特征,借助G.E.软件分析各子区域内的一字形平面民居、L形平面民居、凹字形平面民居和回字形平面民居的分布规律和频数统计特征,再应用所推导算式计算各个子区域内的民居平面能耗系数.在子区域统计数据基础上进行综合分析得出:天井院民居的节能效果最好,三合院民居次之,折角民居再次之,单体民居最差.

This paper proposes field function to mathematically describe the Raumplan, aiming at being helpful for the building design. Through space thought experiments, three basic principles are established: (1) the key to the sensation of space is whether there is a sense of being marked; (2) the boundary is necessary but not sufficient for the generation of spatial perception; (3) the spatial scale must be comparable to the scale of the observer to create spatial perception. In the Raumplan, the sense of being marked between spaces is determined by the connection between the spaces. Mathematically, the connectivity allows field functions to be represented in the same coordinate system and thus to be comparable. Since the sense of being marked is mutual, there is no special reference space. Each space can be used as a reference space to mark another space, which corresponds to the equal weighting between rooms.

A vacuum insulation panel (VIP) is an inorganic composite insulation panel with a thermal conductivity of almost 0.004 W/(m.K) and a Class A fire resistance rating (noncombustible) that can achieve both heat preservation and fire protection. However, the application of VIPs in the construction industry still has many problems that need to be studied experimentally. In this paper, the building environment cabin is used to simulate wall insulation systems with three different insulation materials or construction methods, including pasted VIP boards, dry-hung composite VIP boards, and extruded polystyrene (XPS) insulation boards, and studying them in different working conditions, such as winter, summer, dry and wet, and assess the insulation performance under adverse conditions such as punctures. The conclusions are as follows: (1) In the thermal resistance test, considering that the heat flow on the surface of the envelope structure is susceptible to external disturbances, the average value of the heat flow on the indoor and outdoor surfaces of the structure should be taken into account when calculating the heat resistance of the envelope structure; (2) the test error of the working conditions under summer changing temperature conditions is greater than the constant temperature working conditions in winter; (3) the thermal resistance of the dry-hung VIP wall is greater than that of the pasted VIP wall because the static air interlayer behind the dry-hung VIPs causes the insulation effect to greatly increase; (4) the measured thermal resistance with the 50 mm pasted XPS is 32% lower than that of the wall with the 12 mm pasted VIPs; (5) after the VIP is punctured, its thermal resistance will be greatly reduced. In a wet environment, the extent of the decline will further increase.

该文从被动节能设计流程以及绿色建筑评价体系中存在的若干不足为切入点,借助以Grasshopper为平台的Ladybug&Honeybee设计软件,以一个商业综合体的前期节能设计策划为案例.在遵循国内既有相关节能设计标准的前提下,制定一套包括"总图布局"、"单体设计"和"细部优化"的建筑可持续设计策略.从而使设计的各个环节都能真正做到"有据可循",实现以降低能耗为目标导向的建筑形体控制和优化设计方法.

The passive strategy for buildings in summer hot and winter cold zone are complicated, requiring a combination for various passive techniques. Previous studies on the passive strategies usually stray into the trade-off between single passive technique and energy saving. This work focuses on the completely passive cooling and heating, by using a River-Air Source Heat Pump (RASHP) and Greenhouse (GH) system, for the courtyard buildings located in Jiangnan region of China. The proposed heating and cooling systems can be run, using the solar energy purely. Due to the Jiangnan region with a high density of water network, the cooling space system can be achieved by using the evaporative cooling effect of water. In winter, the airflow circulation and space heating are achieved in the target rooms, whose construction is similar to that of Trombe wall. The proposed systems are also beneficial to maximize daylighting and energy saving of artificial lighting in the building interiors, via replacing the eaves of roofs over patio by a glazed device. Furthermore, the proposed systems can be easily created in the courtyard buildings, without complicated construction and special devices. The total annual energy consumption in the novel-designed scenario integrated with the proposed systems is 19528.88 kW.h, 5839.57 kW.h lower than the conventional one, with energy saving of 23%. The completely passive heating and cooling systems with daylighting function can provide a new body of building energy saving to fill the knowledge gap in this field.