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China is in the transition period of urbanization, and the imbalance of land use generated during the original rapid development of megacities still exists, resulting in the preservation of a large number of urban villages in the peripheral areas of cities. Unlike formal housing, these villages are heavily influenced by the confrontation and interweaving between top-down policies of local governments and bottom-up spontaneous construction by local villagers, resulting in a diverse and complex status quo. At the same time, self-built housing in urban villages has become a gathering place for a large number of low-income migrants due to its relatively low rental prices. In terms of the research of urban villages on the current situation of housing, the real needs of users and housing performance are mostly subjective judgments and conclusions. Therefore, the entry point of this paper is the leased space and the leasers, taking Laojuntang Village in Chaoyang District of Beijing as the research object and analyzing its current problems and the real needs of users. This paper adopts an integrated approach of fuzzy Kano model evaluation and building performance simulation. After analyzing the data and discussing the influencing factors, this paper identifies the specific problems and user needs that exist in leased spaces in Laojuntang Village: (1) The architectural performance of leased space is a Must-be Quality, which is the bottom-line requirement and must be improved. (2) The quality of the basic facilities and equipment of the leased space is mostly a One-dimensional Quality, Attractive Quality, and the degree of importance is lower than that of the building performance. (3) The external activity facilities of the leased space are mostly undifferentiated needs, for which the local users are not particularly prominent. (4) The scale and plot ratio of local housing is relatively high, and users are dissatisfied and complaining, which falls under the category of Reverse Quality. [ABSTRACT FROM AUTHOR]

In order to fully implement systematic, continuous and effective supervision of financial institutions and promote the safe, steady, and efficient operation of China's financial system, this research needs to develop a fully intelligent financial supervision information system, so as to take measures to effectively prevent and resolve financial risks. In this paper, based on ML (machine learning), an LSTM (long short-term memory) model with good comprehensive performance is built. This model is different from the existing scorecard model which relies on statistical learning. It not only further reduces the dependence on financial experts, but also has the ability of rapid iteration. The post-loan risk early warning model based on RF (random forest) algorithm is designed. The model parameters are optimized, which makes the risk early warning model have higher accuracy. The results show that when the data amount is 10,000 to 50,000, the accuracy of the model is relatively high when it is input into the model. When the amount of data is low, the overall throughput of the model is still very high. It shows that the pre-warning model of post-lending risk constructed in this paper has a strong risk prediction ability. [ABSTRACT FROM AUTHOR]

The proper application of machine learning and genetic algorithms in the early stage of library design can obtain better all-around building performance. The all-around performance of the library, such as indoor temperature, solar radiation, indoor lighting, etc., must be fully considered in the initial design stage. Aiming at building performance optimization and based on the method of "generative design", this paper constructs the library's comprehensive performance evaluation workflow and rapid prediction combined with the LightGBM algorithm. A library in a cold region of China is taken as the research object to verify its application. In this study, 5000 scheme samples generated in the iterative genetic optimization process were taken as data sets. The LightGBM algorithm was used to classify and predict design schemes, with a precision of 0.78, recall rate of 0.93, and F1-Score of 0.851. This method can help architects to fully exploit the optimization potential of the building's all-around performance in the initial stage of library design and ensure the timely interaction and feedback between design decisions and performance evaluation. [ABSTRACT FROM AUTHOR]

In the circumstances of "Carbon Peak," it is imminent to implement green construction technology in the construction industry as it is a major source of CO2 emissions. Nevertheless, little study has been done on the impact of self‐face awareness (SA) on green building project performance (GP). On the basis of a large‐scale questionnaire survey in China and an in‐depth analysis of the four categories (cognition, behavior, satisfaction, and performance), this paper has added an SA dimension, and proposed a new impacting path. Then, based on the improved conceptual model for measuring the impact of green construction behavior on GP, this paper has conducted empirical tests by using a large sample of questionnaire data and partial least square‐structural equation modeling method. The results show that: (1) green construction behavior has a positive impact on GP, and the impact of perceived behavioral control of green construction technology is most significant for promoting green construction in the industry, and SA has a significant positive effect on green construction in the industry; (2) environmental perception and perceived behavioral control for green construction technology play a mediating role; and (3) significant differences indeed exist in the multigroup analysis, and the biggest difference is working experiences in the engineering field. Finally, this paper has proposed corresponding management implications based on the above findings. The main contribution of this study is that this study has developed a new dimension (SA) to the model considering Chinese national and cultural differences, in an attempt to reveal the impact of green construction technology on GP in the Chinese context. In addition, the promotion of green construction (PGC) in the construction industry was also added based on the sustainability perspective, which is the first attempt to explore the role of the PGC. [ABSTRACT FROM AUTHOR]

Selecting an appropriate ANN model is crucial for speeding up the process of building performance simulation during the design phase of residential building layouts, particularly when evaluating three or more green performance metrics simultaneously. In this study, daylight, visual, and outdoor thermal metrics were selected as main green performance. To find the suitable ANN model, sensitivity analysis was used to obtain a set of proper parameters applied to the ANN structure. To train the ANN model with a higher predicting accuracy, this paper tested four different scenarios of ANN parameter setups to find some general guidelines about how to set up an ANN model to predict DF, sunlight hours, QuVue and UTCI. The results showed that an ANN model with a combined output variable demonstrated better average prediction accuracy than ANN models with a separated output variable. Having two times the number of training samplings compared to the number of input variables can lead to a high accuracy of prediction. The ideal number of neurons in the hidden layer was approximately 1.5 times the number of input variables. These findings of how to improve the ANN model may provide guidance for modeling an ANN for building performance. [ABSTRACT FROM AUTHOR]

Current requirements for residential energy-efficient design solutions in China are relatively homogeneous, requiring only improvements in overall building energy performance, often ignoring the energy differences between different residential housing units. This paper proposes a multi-objective research framework based on an occupant behavior model of air conditioning and a Non-dominated Sorting Genetic Algorithm-II (NSGA-II) to study energy-efficient design solutions for residential envelopes. The optimal energy-saving design scheme has a 22.56% and 35.34% reduction in energy consumption difference between residential units and overall building energy consumption, respectively, both of which have been optimized substantially. Moreover, the overall energy performance of the building can be improved when the "energy performance difference between housing units" (EDH) is reduced, which verifies that EDH is an important criterion for improving the energy performance of residential housing units. [ABSTRACT FROM AUTHOR]

Research background: With the rapid development of civil engineering, the traditional low rise building model can no longer meet the needs of urbanization, and high-rise building structure has become the future development direction. In recent years, earthquake disasters occur frequently in China, which has caused huge losses to high-rise buildings. Therefore, we must strengthen the relevant research of high-rise building structures, which can make the high-rise building structural columns meet the requirements of safety performance. Therefore, the health detection and seismic performance evaluation of high-rise buildings will be of great significance. Research method: Through static elastic-plastic evaluation, we can calculate the dissipated strain energy of the structural column, which will further obtain the damage index of the structural column and obtain relevant data. Through this calculation method, we can complete the seismic performance evaluation of high-rise buildings, which is a calculation mode different from the traditional finite element software analysis. Through static elastic-plastic analysis, the seismic performance evaluation of high-rise buildings will have higher accuracy, which will build a damage index. Therefore, this paper uses a variety of research methods, mainly literature survey and empirical analysis. Through literature analysis, this paper can fully and correctly understand the methods of health detection and seismic performance evaluation of high-rise building structures at home and abroad, which will further clarify the current research level at home and abroad. Through empirical research, this paper analyzes specific examples, which can obtain more accurate results. Conclusion: In this paper, the seismic performance of high-rise buildings is comprehensively evaluated according to the damage index value of building structural columns. The simulation results show that more ideal seismic evaluation results can be obtained. [ABSTRACT FROM AUTHOR]

Prefabricated building construction has emerged as a transformative technology in construction engineering and the building industries. However, owing to its research characteristics, the relevant literature on prefabricated buildings is diverse and fragmented. This study offers a comparative review of relevant 21st century literature on prefabricated buildings using VOSviewer1.6.18 software. The research progress and future opportunities about prefabricated buildings were comprehensively analyzed, which provides recommendations for its subsequent development. Through keyword searches on the Web of Science, 3214 documents were identified, and an overall analysis of co-citations and co-authorship was conducted. Additionally, a comparative co-occurrence analysis highlighted the differences between China and other countries. Further elaboration of research hotspots is provided, and three future research directions are proposed: (1) energy conservation and reducing the environmental impact of prefabricated buildings, (2) improving the performance of prefabricated building components, and (3) deepening the understanding of the behavior of prefabricated structures under seismic and dynamic conditions. This study provides practitioners and scholars in the field of construction engineering with a comprehensive overview of the literature on prefabricated buildings and paves the way for future advancements in the industry. The findings of this study can be used to promote prefabricated buildings in the architecture, engineering, and construction industries. [ABSTRACT FROM AUTHOR]

This paper investigates the case building's cooling effect, energy saving, and carbon sequestration with green facade and green roof. The west and east GF is covered with wisteria, and the GR is planted with different kinds of vegetables. The cooling effect of the GF and GR is analyzed by field test. The cooling energy saving of the GF and GR is deeply discussed with EnergyPlus software simulation. Carbon sequestrations of the GF and GR are calculated considering both plant photosynthetic and energy saving with the field test and simulation. The results show that the average external surface temperature reduction of the west GF, east GF, and GR is 4.5°C, 4.2°C, and 9.7°C on sunny days, 1.3°C, 1.3°C, and 1.4°C respectively on cloudy days. The total cooling energy saving of the GF and GR is 4.75 kWh/m2. The cooling energy saving of the GR with seven kinds of vegetables varies from 529.6 to 2936.3 kWh, which is related to the LAI and height of vegetables. The daily cooling energy saving in hot sunny weather scenario is almost three times that in cool sunny. The carbon sequestration ability per planted GF area is 1.4 kg C/m2, and per planted GR area with seven different vegetables varies from 0.88 to 2.21 kg C/m2, in which the strongest is peanut, and the weakest is lettuce. At last, the cooling energy savings of GF in different orientations on hot, warm, and cool sunny days are discussed, which is shown that the cooling energy saving effect of the different oriented GF mainly depends on the received solar radiation amount in this orientation. The results of this research can provide some assistance in improving the design of the building GR and GF. [ABSTRACT FROM AUTHOR]

The excessive simplification of occupant behavior is considered as the most important factor that affects the uncertainty of building performance simulation, thus affects the reliability and generalizability of simulation-based design and forecast. In this paper, occupant behavior in air-conditioned office buildings of the Pearl River Delta (PRD) region was investigated and defined. Copies of 873 questionnaires about the occupant behavior in air-conditioned office buildings in the PRD region were collected to study the relationship between indoor environment quality and adaptive behaviors. Eight typical office occupant schedules were defined via K-means clustering method. A probability prediction model of cooling temperature set-point was established by using the Ordinal Logistic Regression method. According to the different control modes of air conditioning, window, blind and lighting equipment, four types of typical behavior patterns were proposed using the K-prototype clustering method, which could be developed into 20 typical occupant behavior styles of office buildings in the PRD region. [ABSTRACT FROM AUTHOR]

Purpose: A firm's inventions provide technical information for product planning and technical support for new product development (NPD). In the knowledge-based theory, inventing is regarded as a process of knowledge combination. This paper aims to classify the firm's inventive capabilities based on the combinatorial view and investigate the effects of inventive capabilities on NPD performance. Design/methodology/approach: Four types of inventive capabilities are identified concerned with the knowledge used to combine in the inventive activities. By utilizing a dataset of 572 firms from China's automotive manufacturing industry, the roles of different inventive activities in the generation of new inventions are compared. Then the effects of different inventive capabilities on NPD performance are empirically examined by using negative binomial regression analysis. Findings: The time series for the number of patented inventions derived from different types of combinations generally exhibits a steady upward trend, and the number of patents derived from recombination is much higher. The empirical results demonstrate that the inventive capabilities associated with reused recombination and creative recombination exhibit positive effects on NPD performance, and the inventive capabilities associated with novel combination and original combination exhibit non-linear effects on NPD performance. Originality/value: The findings contribute to NPD literature by investigating the effects of different inventive capabilities on NPD performance. This study also provides guidelines for manufacturing managers to improve NPD performance by building appropriate inventive capabilities. [ABSTRACT FROM AUTHOR]

With the acceleration of urbanization process in China, the usage of sustainable green buildings is getting a great attention and significance in order to reduce energy consumption. However, there are still challenges for evaluating the performance of green buildings in China due to the lack of unified codes/standards. This paper proposes a method based on cloud model to evaluate the performance of green buildings. This method overcomes the randomness and subjectivity of fuzzy concepts to the maximum extent; on this basis, the system's indexes including environmental–economic balance, regional social coordination, health, comfort, and green management can be established. The analytic hierarchy process and entropy weight methods are used to calculate the index weight; the cloud model is used to realize the transformation between qualitative and quantitative characteristics; and then, a mathematical evaluation model based on the cloud model is established. Finally, an empirical study is made based on a typical case in Shenzhen city, China. The findings of this research work reveal a performance index for green building created based on expert evaluations and a standard cloud yardstick created in the comprehensive cloud model. Based on the results of this manuscript, the industry can acquire benefits by suggesting effective measures that can be implemented in all stages of green buildings construction where the measurements execution and persuasive components make appraisal models for a green building. This study provides a consistent framework for researchers and other public to evaluate green buildings, and provides a solid foundation for further research and consideration basis on sustainable development and green building operation. [ABSTRACT FROM AUTHOR]

A reliable and effective qualitative near-infrared (NIR) spectroscopy discrimination method is critical for excellent model building, yet the performance of models built by these methods is highly dependent on valid feature extraction. The goal of feature selection is to associate the selected variables with the property of interest, which many have done successfully. However, many of selection methods focus only on strong association with the analytes or properties of interest, neglecting correlations between variables. A variable selection method based on a fast nondominated-ranking genetic algorithm (NSGA-II) was proposed in this paper for qualitative discrimination of NIR spectra. The method had two objective functions: (1) maximizing the sum of ratios of interclass variance to intraclass variance, (2) minimizing the sum of correlation coefficients between the selected variables. FT-NIR spectra of a total of 124 tobacco samples from different origins and parts in Guizhou Province, China, were used as the experimental objects, and the part-grade discrimination models of tobacco leaves were established by combining this method with partial least squares-based discriminant analysis (PLS-DA), and compared with PLS-DA model based on the full spectrum. The results showed that the performance of PLS-DA model with the NSGA-II was improved, with a comparable or better correct discrimination rate and reasonable discrimination rate, and could discriminate different parts of the tobacco leaves well. It indicates that the NSGA-II can select a few and effective feature variables to build a high-performance qualitative discrimination model and is proved to be a promising algorithm. In addition, the method is not designed exclusively for spectral data. It is a general strategy that could be used for variable selection for other types of data. [ABSTRACT FROM AUTHOR]

BACKGROUND: Innovation practice of the enterprise is a complicated dynamic process which shows different environmental characteristics and different degrees of uncertainty and externality in each stage of activity. Therefore, it is important to consider the government involvement in enterprise innovation initiatives and interventions in the different stages of innovation is a question to be explored. PURPOSE: This research study examines staged government interventions, situational characteristics impact in manufacturing innovative enterprises in china. DESIGN/METHODOLOGY/APPROACH: This quantitative study used the panel data including 443 manufacturing innovative enterprises in China from 2008 to 2011 to analyze the differential relationship between the government intervention and enterprises' innovation performance by building the framework of "government intervention – situational characteristics-innovation performance". FINDINGS: The empirical results show that single-stage government intervention produces an inhibitory effect on enterprises' innovation performance, but multi-stage government intervention has a significant role in promoting their performance, especially the combination of the initial stage of innovation and the stage of innovation marketization. The moderation of the situational characteristics on the relationship between the government intervention and enterprises' innovation performance has a larger difference. CONCLUSION: This paper supplements and extends previous research on institutions and innovations by the analysis of the relationship between government intervention, enterprise innovation, and regulatory mechanisms of enterprise R&D internationalization strategy, industry and regional characteristics. We deeply explore the transmission mechanism and internal process of government support in enterprise innovation, and effectively promote the development of the theory and practice of government support and enterprise innovation. [ABSTRACT FROM AUTHOR]

The number of studies considering building performance optimization (BPO) in the building design phase is steadily growing, but many of the existing studies do not consider the applicability of many-objective optimization algorithms when increasing the objective dimensions. This article first compares the NSGA-II, IDBEA, MSOPS-II, and NSGA-III algorithms. Then, the algorithm most suitable for many-objective optimization is combined with Artificial natural network(ANN) and TOPSIS-AHP to complete the optimization of four dimensions of building energy consumption (EC), useful daylight illuminance (UDI), comfort time ratio (CTR) and energy-saving envelope cost (ESEC) for village houses in cold regions of China. The results show that the NSGA-III algorithm performs well in terms of convergence speed, convergence, diversity, and uniformity when solving many-objective problems compared to the other three algorithms. Finally, four optimization strategies were selected using the TOPSIS-AHP method. [ABSTRACT FROM AUTHOR]

Featured Application: In cold climatic zones of China, an attached sunspace passive solar heating system was installed on a farmhouse to improve the indoor thermal environment in winter. The application of attached sunspace passive solar heating systems (ASPSHS) for farmhouses can improve building performance, reduce heating energy consumption and carbon dioxide emissions. In order to take better use of the attached sunspace to prevent heat transfer or promote natural ventilation, this paper presented a zero-state response control strategy for the opening and closing time of active interior window in the ASPSHS. In order to verify the application of this strategy, an attached sunspace was built in an actual farmhouse. A natural ventilation heat exchange model was built based on the farmhouse with attached sunspace. The proposed zero-state response control strategy was implemented in TRNSYS software. Field measurement in living lab was carried out to inspect the distribution of the thermal environment in the farmhouse with attached sunspace under a zero-state response control strategy in the cold region of northern China. The experimental results show that, even under −5.0–2.5 °C ambient temperature, the application of zero-state response control strategy effectively increases the internal temperature to an average of 25.45 °C higher than the outside, with 23% indoor discernible temperature differential in the sample daytime. The whole-season heating performance was evaluated by simulating the model for the heating season in 2020–2021. The simulation demonstrates that the ASPSHS under zero-state response control strategy can maintain a basic indoor temperature of 14 °C for 1094 h during the heating season, with a daytime heating guarantee rate of 73.33%, thus ensuring higher indoor heating comfort during the day. When compared to a farmhouse with an attached sunspace under the zero-state response control strategy, the energy savings rate can be enhanced by 20.88%, and carbon emissions can be reduced by 51.73%. Overall, the attached sunspace with the zero-state response control strategy can effectively increase the indoor temperature when the solar radiation is intensive and create a suitable thermal environment for the farmhouse in the cold region of northern China. [ABSTRACT FROM AUTHOR]

The regenerative design framework aims to ‘engage a broader range of possibilities by moving beyond the immediate building and site boundaries’. It implies that the environmental performance of buildings requires a revised definition so that it considers not only the building itself, but also its contribution beyond its own boundary, i.e. neighbourhoods. In high-density cities, outdoor spaces are culturally considered as the extension of one’s living spaces. The environmental performance of neighbourhoods is particularly important to the health and wellbeing of urban inhabitants. This paper aims to define the environmental performance of neighbourhoods in high-density urban context based on the experience acquired in previous studies in Hong Kong over the last 15 years. These studies cover a wide range of environmental issues including urban climate, outdoor thermal comfort, and daylighting design in high-density cities. Subsequent development of the assessment tools for environmental performance of neighbourhoods in Hong Kong is also presented. The framework of stakeholder engagement, as an integral part of the neighbourhood assessment tool, is discussed. This paper highlights the distinctive features of the environmental performance of neighbourhoods in high-density urban context and how it influences the professional practices in Hong Kong. [ABSTRACT FROM AUTHOR]

Data envelopment analysis (DEA) has proven to be a powerful technique for assessing the relative performance of a set of homogeneous decision-making units (DMUs). A critical feature of conventional DEA approaches is that only one or several sets of optimal virtual weights (or multipliers) are used to aggregate the ratio performance efficiencies, and thus, the efficiency scores might be too extreme or even unrealistic. Alternatively, this paper aims at developing a new performance dominance probability approach and applying it to analyze the banking operations in China. Towards that purpose, we first propose an extended eco-inefficiency model based on the DEA methodology to address banking activities and their possible relative performances. Since the eco-inefficiency will be obtained using a set of optimal weights, we further build a performance dominance structure by considering all sets of feasible weights from a data-driven perspective. Then, we develop two pairwise eco-inefficiency dominance concepts and propose the inefficiency dominance probability model. Finally, we illustrate the eco-inefficiency dominance probability approach with 32 Chinese listed banks from 2014 to 2018 to demonstrate the usefulness and efficacy of the proposed method. [ABSTRACT FROM AUTHOR]

The energy performance of buildings especially public buildings needs to be optimized together with environmental, social and cost performance, which can be achieved by the multiobjective optimization method. The traditional building performance simulation (BPS) based multiobjective optimization is time-consuming and inefficient. Practical projects of complex public building design usually involve many-objective optimization problems in which more than three objectives are considered. Using BPS based multiobjective optimization is not sufficient to solve this kind of design problem. This paper aims to propose an artificial neural network (ANN) based many-objective optimization design method, an architect-friendly integrated workflow has been implemented. The proposed method has been applied on a public library building in Changchun city of China to optimize its Energy Use Intensity (EUI), Spatial Daylight Autonomy (sDA), Useful Daylight Illuminance (UDI) and Building Envelope Cost (BEC). The optimization process has obtained 176 non-dominated solutions. By adopting the selected relative optimal solutions, 1.6×105–2.1×105 kWh energy can be saved per year; sDA value and UDI value can be increased by 8.1%–11.0% and 4.3%–4.7% respectively; BEC can be reduced by ¥1.2×105–2.1×105 ($1.7×104–3.0×104). The optimization time has been greatly shortened in this method and the whole process is highly efficient without manual data conversion between different platforms. [ABSTRACT FROM AUTHOR]

The seismic performance of a building hinges on the seismic capacity and damage features of the reinforced concrete (RC) frame with masonry infill walls. To reasonably evaluate the seismic performance and seismic economic loss of masonry infill walls, it is necessary to consider the in-plane (IP) and out-of-plane (OOP) interactions of these walls under seismic actions, and to model the vulnerability of the infill walls and the frame. Based on the test data on masonry infill walls, this paper designs a performance indicator for infill wall in the light of IP-OOP interactions, and determines the response threshold of each damage state. With the aid of OpenSees, the authors developed and verified a reasonable modeling method for RC frames with infill walls. As per the current code in China, a 5-storey RC frame with infill walls was designed, and two three-dimensional (3D) space models were established for the structure by the proposed modeling method. One of them considers IP-OOP interactions, and the other does not. Then, the structure was subjected to incremental dynamic analyses (IDA), and different damage indicators were determined to examine the damage of the infill walls and the overall structure, producing a set of vulnerability curves. The results show that the consideration of IP-OOP interactions significantly increases the probability of seismic damages on the infill walls and the overall structure. The most prominent increase was observed in the medium to serious damage stages. [ABSTRACT FROM AUTHOR]

In response to climate change, governments are developing policies to move toward ultra-low-energy or ‘zero-energy’ buildings (ZEBs). Policies, codes, and governance structures vary among regions, and there is no universally accepted definition of a ZEB. These variables make it difficult, for countries such as China that wish to set similar goals, to determine an optimum approach. This paper reviews ZEBs policies, programmes, and governance approaches in two jurisdictions that are leading ZEBs development: Denmark and the state of California in the United States. Different modes of governance (hierarchy: principal–agent relations, market: self organizing and network: independent actors) are examined specifically in relation to policy instruments (prescriptive, performance or outcome-based). The analysis highlights differences in institutional conditions and examines available data on energy performance resulting from a building policy framework. The purpose is to identify ZEBs governance and implementation deficits in China and analyse alternative governance approaches that could be employed in China, which is currently developing ZEBs targets and policies. Conclusions suggest that the ZEBs governance structure in China could benefit from widened participation by all societal actors involved in achieving ZEBs targets. China's ZEBs policies would benefit from employing a more balanced hybrid governance approach. [ABSTRACT FROM PUBLISHER]

Limited by the climate, economic level and energy-saving awareness of rural residents in the western China, rural houses are still in a stage of high energy consumption (EC) and low comfort. The passive design strategies should be given priority to provide an optimal design mode. The challenge is to find the best combination of design parameters. In this paper, rural single-storey detached houses are taken as the research objects. Three conflicted indicators are set as the objective function, namely building EC, thermal comfort and economy. The investigated design variables include building orientation, insulating layer thickness, window width & type, and indoor design temperature. A methodology of combining EnergyPlus and MOBO is used for multi-objective optimization, thus getting the Pareto solutions and using the weighted sum method to obtain the optimum parameter combinations. The proposed methodology for simulation-based multi-objective optimization is a useful tool to facilitate decision-making in building design. [ABSTRACT FROM AUTHOR]

Photovoltaic shading devices (PVSDs) have the dual function of providing shade and generating electricity, which can reduce building energy consumption and improve indoor daylighting levels. This study adopts a parametric performance design method and establishes a one-click simulation process by using the Grasshopper platform and Ladybugtools. The research focuses on the effect of dynamic PVSDs on daylighting and energy consumption in an office building in Qingdao. The optimal configuration of PVSDs for each month under three dynamic strategies (rotation, sliding, and hybrid) is determined here. Additionally, different control strategies and fixed PVSDs are compared to clarify the impact of various control strategies on daylighting and energy consumption. The findings reveal that, compared to no shading, dynamic PVSDs in the rotation strategy, sliding strategy, and hybrid strategy can achieve energy savings of 32.13%, 47.22%, and 50.38%, respectively. They can also increase the annual average UDI by 1.39%, 2.8%, and 3.1%, respectively. Dynamic PVSDs can significantly reduce the energy consumption of office buildings in Qingdao while improving indoor daylighting levels. A flexible control strategy that adapts to climate change can significantly improve building performance. This research can provide theoretical, methodological, and data support for the application of the PVSD in cold-climate regions in China. [ABSTRACT FROM AUTHOR]

Hong Kong buildings account for 90% of total electricity consumption and over 60% of greenhouse gas emissions. Therefore buildings present both a challenge and an opportunity for reduction in energy use and greenhouse gas emissions. Net Zero Energy Building (NZEB) and Net Zero Carbon Building (NZCB) are recognised as feasible strategies to reduce energy use and carbon emissions leading to a more sustainable built environment. While there is a growing number of NZEBs and NZCBs in relatively cool or temperate climates, there are relatively few examples in the subtropical climate, and in a densely populated city such as Hong Kong. This paper will examine the current progress towards a low carbon built environment in Hong Kong, zero energy/carbon design strategies and technologies applicable to building in a subtropical climate, and examines a case study of Hong Kong's first zero carbon building ZCB. ZCB's energy and carbon performance, experiences and lessons learned, and future directions are discussed. The paper will conclude with the challenges and opportunities for wider adoption of NZEBs and NZCBs in the Hong Kong construction industry. [ABSTRACT FROM AUTHOR]

The significant variation in building׳s energy intensity is partly due to the large number of distributed energy users characterized by heterogeneous lifestyles and nonuniform consumption behaviours. Understanding the degree of variation and its cause is critical to designing appropriate policies for energy efficiency improvement. This paper aims to provide a data-based benchmark of buildings energy performance in China and investigates the facts and causes of large variations in energy consumption across buildings based on updated and harmonised dataset. Specifically, the paper is the first in literature to decompose aggregate heating consumption in northern urban China and reallocate the disaggregate data to relevant residential and commercial building energy use, which makes it consistent to conduct international comparison of building performance in terms of primary energy intensity. It is found that buildings energy performance exhibits a sizeable heterogeneity varying with building typology and climate zones in China. Heating and cooling energy consumption for residential buildings located in HSCW climate zone may differ by a factor of 4–10 depending on the technology and energy supply mode, whereby nontechnical interventions may have significant impacts on total energy demand in the built environment. In particular, our analysis results point to the importance of making greater efforts in the commercial sector. Commercial buildings are found significantly more energy intensive than their residential counterpart, mainly due to the fact that BEE policy has been poorly implemented and architectural design has not been optimised in commercial sector. An estimate suggests that improving energy efficiency in the commercial sector may contribute to one-fifth of total energy savings potentials by 2020 in line with the IEA׳s 450 ppm scenario. It is necessary for Chinese building authorities to incorporate the heterogeneity characteristics across different climate zones and building typologies into BEE policy portfolio to effectively curb energy consumption related carbon emissions. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the effects of courtyard envelope design on the energy performance of office buildings in the hot summer–cold winter region of China. Two types of courtyard buildings were simulated with 200 energy models by changing the following variables: window–wall ratio (south, north, east, and west walls), window U-value, wall U-value, solar heat gain coefficient, and orientation. The treed Gaussian process (TGP) sensitivity analysis method was employed to quantify the contributions of parameters related to courtyard design that result in the changes of annual cooling, heating, lighting, and total energy consumption. The results show that the courtyard envelope design has a significant effect on the energy consumption in this case study. The most influential factor affecting annual cooling energy consumption and the annual total energy consumption is the orientation, which is responsible for 37% and 81%, respectively, in two layouts to annual cooling energy use. The corresponding proportion increased to 45% and 86% in terms of the total energy consumption. The most influential factor influencing annual heating energy use is the window U-value, which explained nearly 60% of the changes to the heating energy use. The effect of the solar heat gain coefficient in two kinds of layouts is as high as 82% and 79% for lighting energy use in this case study. Due to the different courtyard forms, the magnitude of the effect of the parameters on energy consumption and the main trend of the effect is slightly different. [ABSTRACT FROM AUTHOR]

• The effects of green roofs and practical green façades within courtyard area on public buildings investigated for "Hot Summer, cold Winter" region of China. • Internal surface temperatures for areas with and without external greening monitored and compared. • Heating and cooling energy consumption before and after greening compared from computer simulation as well as from smart meter readings. • Actual heating and cooling energy consumption before and after greening compared using statistical analyses. T -statistics and p -values show significant reductions were achieved. The "Hot Summer Cold Winter" climate region of China is one of the most challenging regions for providing occupant comfort in buildings, with high demands for heating as well as cooling, together with high humidity levels. Although the performance of buildings has improved with the implementation of the new Chinese National Building Standards for the Zhejiang Province, it is believed that adding passive strategies could help to alleviate the problem even further. This paper aims to investigate the effects of adding horizontal greening (green roof) and vertical greening in the courtyard area to existing public buildings in the "Hot Summer Cold Winter" climate region of China. Using computer simulation and measurements from a monitored case in the city of Ningbo, the effects of green retrofitting on human comfort and energy consumption are analysed. Simulation results suggest that with partial horizontal and vertical greening, the cooling load could be reduced by 8.8% and heating load by 1.85%. Comparisons between actual energy use before and after greening on the case building showed significant reductions in both winter and summer, confirming the positive effects of vertical and horizontal greening of public buildings in this region. [ABSTRACT FROM AUTHOR]

Solution regeneration of the heat-source tower is significant to guarantee the normal operation of the heat-source tower. Mechanical vapor recompression system is an efficient system for evaporation of solution. In this paper, mechanical vapor recompression system is applied to regenerate solution of heat-source tower. To clarify the merits of mechanical vapor recompression solution regeneration system, several typical solution regeneration systems are modelled. As a result, mechanical vapor recompression shows 35.7%, 73.5% and 91.2% energy saving compared to air-driven heat pump, three-effect evaporating system, and single effect evaporating system, respectively. Furthermore, a heat-source tower heat pump with solution generation system is installed in a typical building in Yangtze river region. The whole heating season performance is simulated to find the effects of different solution regeneration system on the whole heat pump system. As a conclusion, the seasonal coefficient of performance of heat pump is decreased 1.6% by mechanical vapor recompression regeneration system. Comparatively, the seasonal coefficient of performance of heat pump is decreased 2.6%, 4.2% and 10.0% by air-driven heat pump, three-effect evaporating system, and single effect evaporating system, respectively.Practical application: Solution regeneration systems for heat-source tower heat pump systems have been applied in building projects especially in hot summer and cold winter zone in China based on previous investigation. A heat-source tower heat pump system combined with heat pump solution regeneration system has been applied in an office building in Changsha, Hunan Province in China. And its practical operation energy consumption has been reduced obviously compared with traditional single effect evaporation system. Therefore, it is of vital importance to demonstrate the operating performance of different solution regeneration systems applied in heat-source tower heat pump systems in building. [ABSTRACT FROM AUTHOR]

• BIM-DB can effectively simulate building performance parameters. • The PSO-RF-NSGA-III hybrid method can be used to predict and optimize building performance. • NSGA can simultaneously optimize energy consumption, carbon emissions and thermal comfort. • The optimal building parameters are different in different regions. Near-zero-energy-consumption buildings (NZEBs) are of great significance for sustainable development, and their design and research have attracted increasing academic attention. To drive and realize the energy saving design and achieve carbon emission and thermal comfort optimization of NZEBs, in this paper, an intelligent optimization method integrating the BIM-DB and PSO-RF-NSGA-III method is established. Multiobjective optimization problems involving NZEBs in four typical climate regions in China are explored. With a typical office building as an example, first, simulation calculations regarding the energy consumption, carbon emissions and indoor thermal comfort in the four climatic regions are performed based on orthogonal tests and BIM-DB. Second, the nonlinear mapping relationships between building design parameters and prediction targets are constructed with the PSO-RF model, which is trained with sample data. The obtained nonlinear mapping relations are used to establish the objective function of NSGA-III, and the multiobjective Pareto-optimal solution set is obtained with the developed PSO-RF-NSGA-III algorithm. Finally, the only optimal solution is determined by using the ideal point method, and reference near-zero-energy-consumption office building parameters are calculated for different climate regions. The conclusions are as follows. (1) The PSO-RF algorithm can efficiently predict building energy consumption, carbon emissions and thermal comfort. In the four regions, the goodness of fit of the three targets is greater than 0.94. (2) Multiobjective optimization can be performed with the proposed RF-NSGA-III intelligent optimization method. After optimizing multiple groups of optimization schemes and adopting energy saving measures, the energy consumption levels in the four climate regions are reduced by 39.72 %, 32.22 %, 26.94 % and 35.37 %, and the other goals are optimized. (3) Index calculations indicate that the optimized building design parameters meet the specified standards for NZEBs, and the main influencing factors and corresponding measures vary from region to region. [ABSTRACT FROM AUTHOR]

Purpose-Rural residential buildings in China's cold areas still have large room for improvement in lighting, energy saving and other aspects due to their own development lag. Design/methodology/approach-Taking Zhaoyuan County residential buildings as an example, the spatial elements of residential buildings are quantified, and the variation intervals of each spatial element are determined based on this. Then the standard model of residential buildings is constructed, and the changing trend and related mechanism of heating energy consumption and natural lighting under the change of residential space elements are discussed. Findings-The results show that: in terms of heating energy saving, there is an obvious optimal solution between the window wall ratio of the south facade and the orientation of residential buildings; in indoor natural lighting, all spatial elements show positive and negative correlation without considering glare; building depth, eave height and plane girth area ratio are the key variables affecting heating energy consumption. Window to floor ratio, building eave height, building depth, and plane aspect ratio are the key variables that affect indoor lighting. The research results can provide reference for the energy-saving construction of residential buildings in cold areas. [ABSTRACT FROM AUTHOR]

Health climate is critical for achieving a better health performance in building construction projects. However, the topic is rarely investigated by extant literature. The aim of this study is to identify key determinants of health climate in building construction projects. To achieve this goal, a hypothesis was established between practitioners' perceptions of health climate and their health status, based on a comprehensive literature review and structured interviews conducted with experienced experts. Then, a questionnaire was developed and administered for data collection. Partial least-squares structural equation modeling was used for data processing and hypothesis test. Results showed that health climate in building construction projects is positively correlated with the health status of the practitioners, and that employment involvement was the most important determinant of health climate in building construction projects, followed by management commitment, and supportive environment. Moreover, significant factors under each determinant of health climate were also disclosed. As limited research has been conducted to examine health climate in building construction projects, this study bridges the knowledge gap and is a contributory work to the current body of knowledge of construction health. Additionally, the findings of this study can provide authorities and practitioners with a deeper understanding of construction health and thereby helping them bring forward more feasible measures to improve health in building construction projects. Thus, this study is useful to the practice as well. [ABSTRACT FROM AUTHOR]

The conventional typical meteorological year (TMY) based on continuous-year original meteorological records without considering abrupt climate changes (ACC) may not be able to represent a real "typical" climate properly. Consequently, building performance analyses and simulations based on TMY may be not accurate. Current research rarely tackles this issue in TMY development. This paper presents an innovative TMY development with the consideration of ACC in the original meteorological records. It is based on the Chinese standard weather database method (CSWD) with the meteorological records of six Chinese cities in different climate zones. It applies the Moving t-test method to identify and exclude ACC points and to refine the timescales for TMY development. It also depicts the development of individual typical meteorological months again with the ACC impact to improve the accuracy of TMY. The method has been verified in several building energy consumption and thermal comfort analyses. The results demonstrate that the analysis based on the new TMY climate datasets when considering ACC will end up with less energy consumption and better thermal performance compared to the analyses based on the conversion dataset without considering ACC. This experimental research will refine TMY development, and further improve building energy performance analysis and design. [ABSTRACT FROM AUTHOR]

In the early architectural design and energy saving reconstruction of building, it is essential need the typical meteorological year（TMY）for building performance analysis. The accuracy of the typical meteorological year data is directly impact the energy simulation results. In order to obtain accurate TMY data for construction engineering applications, the paper does the following work: (1) Reviewed the progress of the typical meteorological year; (2) Several TMY generation methods were compared using the same raw weather data, discusses the applicability of these methods for the cities of typical climate zones in China. Based on the most recent and comprehensive first-hand ground observation data, this paper adopts three methods to generate TMY for the typical city covering the climate zoning of China. Result shows different TMY generation method has applicability in different region, and through the simulation of building energy consumption, the comprehensive method has obvious advantages. It shows that in a region with diverse regional climate characteristics such as China, one certain method for selecting TMY is not enough, and comprehensive methods should be proposed to meet the needs of different building types and energy consumption simulation. • The development of typical meteorological year is reviewed. • Meteorological data covering China's climate zones are analyzed. • Several methods for generating typical meteorological year are compared. • Applicability of TMY method under different climate characteristics is obtained. [ABSTRACT FROM AUTHOR]

• SL, DL and DRL models were constructed for multi performance prediction of gymnasiums under different weather conditions. • Accuracy, time, interpretability, ease-of-use, hyperparameters, and robustness of the metamodels have been investigated. • Energy consumption, temperature and CO 2 time series vectors prediction were modeling with nine training sets. • Methodology for hyperparameters comparison using exhaustive grid search and sensitivity analysis. • RDPG is most accurate but time-consuming. LSTM is more efficient and also has relatively excellent accuracy. Building performance simulation (BPS) is essential for testing energy demand and indoor environment quality of different building designs. However, software for BPS is computationally intensive and impractical to run thousands even millions of simulations for performance analysis and optimization. Especially for the large space buildings, which usually have complex forms and high energy consumption. The computational problem could be overcome by the adoption of metamodels. Most correlational research focuses on single performance prediction of a particular building, which makes the model less robust when applied to multi vectors prediction for different buildings under multiple weather conditions. This paper leveraged six metamodels, which include recurrent deterministic policy gradient (RDPG), asynchronous advantage actor-critic (A3C), long short-term memory (LSTM), convolution neural network (CNN), artificial neural network (ANN) and support vector regression (SVR), to predict hourly-based multi performance vectors of gymnasiums under various design parameters and multiple weather conditions. Six metamodels are trained and tested on a large scale of datasets simulated by EnergyPlus over four gymnasium cases in different cities of China. The accuracy, efficiency, ease-of-use, robustness and interpretability of the models are investigated. To conduct a fair and detailed comparison, a methodological approach using grid searches for model settings selection assisted by sensitivity analysis is pursued. Principal component analysis (PCA) is also adopted to interpret the work process of the metamodels. The comparison showed that the RDPG model provides the most accurate prediction results with R2 converges at 0.993, 0.982 and 0.941 for energy, temperature and CO 2 , respectively. LSTM model is more efficient than RDPG, and suitable for users who need emphasis on both time and accuracy. ANN is suitable for users with limited time and require models of ease-of-use and robustness. SVR and ANN could be used for the automatically co-simulation with BPS software. In future research, the influence of occupant behavior also should be investigated. [ABSTRACT FROM AUTHOR]

• POE was carried out to compare the design target and operational effect after use. • A Large Irregular Green Commercial Building was chosen for in-depth analysis. • We recommend the building energy saving and carbon emission reduction strategy. Commercial buildings, especially large irregular commercial buildings with complex space and dense occupation, have high energy consumption and carbon emissions. Moreover, the actual operating performance differs significantly from its design, in terms of energy conservation and carbon emissions. This study selected an irregular large-scale green commercial building in Dalian, a coastal city in the cold zone of China. The running energy consumption and indoor physical environment were investigated and analyzed, and a satisfaction survey was conducted using the Post-occupancy evaluation (POE) methods. The promotion strategies of holistic design were proposed by comparing the operational building performance with the design target. The research shows that the energy consumption of the building was 68.02 kWh/m2, which failed to meet the standard requirements. The carbon emission was 74.76 kgCO 2 /m2. Less than 10 % of humidity in summer fell in the expected range, and the lowest value of PM 2.5 concentration in winter was 28.3 %. The score of indoor environmental quality and service satisfaction was low. This paper identifies the problems and analyzes the differences between the operation stage and design phase. It provides recommendations and guidelines for optimizing the carbon emission and indoor environment based on the performance improvement of building operational conditions. [ABSTRACT FROM AUTHOR]

• This method integrates uncertainty analysis and cluster analysis methods. • Proposed novel zoning indicators are statistically significant. • Moves from traditional weather-based approaches to a performance-based approach. • Robust tool to tackle complex relation between climate and building energy efficiency. • Provide evidence for the rationality of decision making in energy policy. Climatic zoning is an important tool in building energy policy and regulations, smaller and more homogeneous climate zones could help enhance the rationality of energy policymaking. In most countries, climate zoning is based on simplified climate models, and it is difficult to accurately represent the energy demand characteristics of buildings. Therefore, this paper proposes a novel climate subdivision method that tackles the complex relations between climate and building energy-efficient, which move from traditional weather-based approaches to a performance-based approach. Integrate the uncertainty analysis method and the building dynamic performance simulation to extract a novel statistically significant index as the basis for classification. The K -means clustering method and discriminant analysis method are used to obtain and verify the clustering results, respectively. Furthermore, the comparison with clustering results based on degree days confirms the superiority of the new method proposed in this paper in identifying building energy demand. The method is applied to the cold climate zone of China as a showcase. The results show significant differences in building energy demand and the order of key features affecting building performance between each region in the climatic zones. The zone can be further sub-divided into four groups considering the climate factor and building feature uncertainty, and clustering results have been verified by several evaluation indicators. [ABSTRACT FROM AUTHOR]

The rapid development of green buildings world widely has not delivered the anticipated energy related benefits because the real performance of green buildings is not as good as expected. This paper presents a building case study in China by applying a holistic approach which integrates system dynamics and energy performance simulation to evaluate the building performance gap and provide management strategies to minimize the performance gap. The case study in this paper is an office building located in Shanghai, which was awarded "Three Star" in Evaluation Standard for Green Buildings in China (GB/T 50378–2006). Several scenarios including six single management strategy scenarios and four multiple management strategy scenarios are carried out and in each scenario, building performance is analyzed qualitatively in terms of project quality (ranging from 0 to 1), and quantitatively in terms of energy use intensity (kWh/m2). The results of this case study are compared to another green office building located in the UK. The cross case mismatch between qualitative and quantitative results is due to four factors that performed better in reality that they were designed. It is demonstrated that multiple factors could help to increase building performance more than single factor especially when management cost was considered. The comparison of the two cases in China and the UK, shows that design factors should be treated in a more stringent way instead of referring values from local standard authorities only which could induce overdesign of the buildings. • This article integrates system dynamics with energy performance simulation. • This article tempts to quantify the effect of social factors on building performance gap. • This article documents well the developed framework and detailed application process to a case study in China. • This article provides a possible solution to help developers to improve actual building performance. [ABSTRACT FROM AUTHOR]

In recent years, the energy performance of public buildings has attracted substantial attention due to the significant energy-saving potential. As a semi-open high-space building, the high-speed railway station is obviously different from other public buildings and even traditional stations in terms of energy consumption and internal environment. This paper investigates the current energy consumption situation and environmental quality of 15 high-speed railway passenger stations in China. Results show that the energy consumption of the high-speed railway station is between 117–470 kWh/(m2·a). The energy consumption of the station is related to the area and the passenger flow. The energy use of the station using district heating is higher than that of the station without district heating in the same region. The higher glazing ratio induces good natural lighting in the station, but the uniformity of the lighting in the station is not good. The acceptable temperature range of passengers in winter is larger than that in summer. The average air change rate of the high-speed railway station is 3.2 h−1 in winter and 1.8 h−1 in summer, which is the main reason of high energy consumption of the HVAC (Heating Ventilation Air Conditioning) system in this kind of building. [ABSTRACT FROM AUTHOR]

Wind resistance is one of the most important safety targets for high-rise buildings, especially slab-shaped ones with relatively large length–width ratios. In this study, the characteristics of wind pressure on a reduced-scale model of a slab-shaped high-rise building were analyzed experimentally. The experiment was conducted using the DTC Initium electronic scanning pressure measurement system in the wind tunnel at the Xiamen University of Technology, China. The spatial distribution and time-frequency characteristics of the wind pressure signals were analyzed with various wind flow directions under uniform and boundary-layer inflow conditions. The results show that both of the inflow conditions and the wind directions have significant influences on the magnitude and distribution characteristics of the wind pressure on the building surfaces. The wavelet transform-based analysis shows that the wind pressure on the building surfaces presents obvious intermittent characteristics, with the instantaneous energies pulsating intensively in the time-frequency domain, illustrating the unsteady nature of the wind pressure loads on the building. The influence and risk of the unsteady pulsating pressure loads should be considered when evaluating the wind-resistant performances of this type of building. [ABSTRACT FROM AUTHOR]

Given the prediction of global warming, there is a growing concern about overheating in the severe cold and cold regions of China. In the past decades, indoor thermal comfort has been neglected in building practice, while efficiency-oriented improvements have been developed, such as increased insulation of building envelope. An extensive literature review shows contradictory conclusions about whether increased insulation can alleviate overheating. The aim of this research is to conduct simulations based on measured data to reveal the influence of insulation on overheating in dwellings in these regions of China. An unoccupied residential flat was monitored to determine the extent of overheating while eliminating the effects of other contributors, such as natural ventilation. Validated building performance simulations were carried out with altered insulation layer thickness in Integrated Environmental Solutions-Virtual Environment IESVE software to examine its influence on overheating during summertime in five representative cities. The results showed clear evidence of summer overheating in these regions. In Yichun, Harbin, Shenyang, Dalian and Beijing, walls with increased insulation were found to exacerbate overheating in the bedrooms without natural ventilation by 22.5%, 16.6%, 20.3%, 11.8% and 6.9%, respectively, compared to the uninsulated walls. This study provides useful information for building regulations on energy efficiency and thermal comfort. [ABSTRACT FROM AUTHOR]

Monitoring buildings' heat loss and quickly discovering high energy-consuming buildings in a certain area is of great significance for urban management departments to propose urban governance and management measures from the perspective of global optimization. Developing a 3D-infrared (3D-IR) model of a building or a complex created with infrared thermograph (IRT) obtained by unmanned aerial vehicle (UAV) technologies would greatly contribute to a comprehensive observation on the thermal performance of a study objective. In this paper, a procedure for high energy-consuming building screen based on the 3D infrared (IR) models of multiple buildings is proposed and demonstrated as an effective approach for regional evaluation comparing with measured heating energy data provided by the local municipal department. Firstly, the 3D-IR model of multiple buildings is established, where the single building models are built based on UAV-IRT technology respectively, and the modelling condition as well as the temperature-color mapping relationship of each building is unified. Secondly, the measuring schemes and the evaluation method of the building thermal performance based on the 3D-IR model is proposed. Thirdly, the energy-consuming performance of five buildings in Jining, a city in northern China, is measured and analyzed by using the above-mentioned methods. Finally, the proposed evaluation method of the building performance is applied to evaluate the tested buildings. By referencing to measured heat energy data, the proposed method can be taken as an efficient and reasonably accurate screen method. [ABSTRACT FROM AUTHOR]

Mechanical ventilation has a great impact on building simulation performance, such as indoor environment quality and building energy consumption. However, there is still a lack of accurate mechanical ventilation models established from long-term field data that can effectively predict building performance. In this study, one-year measurements on mechanical ventilation operation behavior were collected from 85 apartments, which were conducted with a mechanical ventilation system of the same brand in cold regions of North China. This permitted statistical analysis and clustering of the mechanical ventilation operation behavior by using the K-means method, leading to five behavior patterns. The results showed that 24% households operated mechanical ventilation system nearly all day, and there was a large difference in usage behaviors between the split system and the centralized system. Furthermore, two classes of models based on random forest and logistic regression were developed for predicting mechanical ventilation system operation (on/off) behavior. The models based on random forest showed high accuracy as it resulted in a 0.992 average in predictions. These models using field data can guide the selection of accurate input boundary conditions of mechanical ventilation and improve the accuracy of dwelling numerical simulations. [ABSTRACT FROM AUTHOR]

Background: Energy-efficient university campuses will play a vital role in the development of future sustainable cities, and will be important for achieving the Chinese carbon-neutrality goals. It is, therefore, necessary to develop new decision-making tools for evaluating the sustainability of campus buildings. Since university campuses typically comprise a broad variety of building types, standardized evaluation methods and tools, such as Green BIM, are needed. Green BIM (Building Information Modeling) emphasizes the importance and role of BIM technology in the design and construction of green buildings, providing a standardized framework for the decision-making process, and methods for improving the green performance of buildings. Methods: This study develops a method based on the Green BIM framework, using BIM architecture to analyse building performance, and the Assessment Standard for Green Building (GB/T 50378-2019) standard to establish benchmark values for evaluation, and project objectives. The method is evaluated on three examples of the most representative university buildings in northern China. The goal is to understand common denominators and differences between different types of campus buildings, in terms of green building indicators, that are important to consider in the early design stages of campus building complexes. Results: In this study, a library is used as a case study to demonstrate the tools for evaluating green performance. The study optimizes green performance from five aspects: surrounding environment, function layout, envelope performance and system transformation, and management measures improvement. The results show that this optimization scheme can achieve reductions of the annual loads of about 47.4%, in line with the national energy efficiency standards for public buildings. In particular, the heating load was reduced by 59.1%, and the cooling load reduced by 21.5%. Conclusion: A comprehensive approach, combining the aspects of planning, building design, system design, energy management, and energy conservation planning, is required to improve the green performance of university buildings to meet the goals. In the future, it will be further necessary to perform data mining of energy consumption patterns, and continue energy retrofitting of existing buildings and energy systems, to achieve the goal of green and low-carbon campuses. [ABSTRACT FROM AUTHOR]

The concept of net zero energy building (NZEB) has attracted worldwide attention and has the potential to achieve significant energy and emissions reductions. Various technical strategies have been demonstrated to be able to achieve the net-zero-energy target. However, this issue becomes more complex when the economic performances of these strategies are considered. Although studies on the economic performance of NZEBs can be found in the literature, gaps in the research still exist. This paper presents a systematic methodology that combines life cycle cost analysis, benefit-cost analysis, and dynamic building performance simulation to effectively evaluate the economic performance of individual NZEB technologies and holistic technical strategies and determine the most economically competitive options. To demonstrate the application and validity of the methodology, a case study of office buildings in the Yangtze River Delta region of China is presented. Although this case study is ad hoc, the proposed methodology is applicable to buildings of other types and in other regions as long as the climatic and economic conditions are known. • A methodology for developing economically efficient NZEB strategies is proposed. • The methodology combines building energy simulation, LCC and benefit-cost analysis. • A prototype of office buildings in the Yangtze River Delta region is established. • Economically competitive NZEB strategies for the prototype building are developed. • Without extra rooftop PV, designing the prototype as NZEB is economically inviable. [ABSTRACT FROM AUTHOR]

This paper used a simulation-based method to predict the life cycle energy performance of residential buildings in different climate zones of China. After comparison, GISS-E2-R was selected as the general climate model (GCM) for generating future weather data, and 15 locations in different climate zones of China were involved. To predict the life cycle building performance, we created a Python procedure to generate future weather data files for every year from 2020 to 2099 for each location and performed simulations on a parametric simulation tool. According to the simulation results, heating energy is expected to decrease, and cooling energy is expected to increase in the future under the influence of climate change. The more climate change there is, the greater the heating energy and cooling energy of the building change. There are three trends in residential building energy demand. For the locations where heating energy dominates, there will be a significant decrease in total energy demand. For the locations in central China, the increase in cooling energy will offset part of the decrease in heating energy; therefore, there will be a relatively small drop in the total energy demand. For the locations where cooling energy dominates, the total energy demand is expected to rise. Finally, a simple sensitivity analysis was conducted to explore the impact of the passive design of the window-to-wall ratio (WWR), solar heat gain coefficient (SHGC), wall construction and roof construction on the life cycle energy demand under representative concentration pathway (RCP) 8.5 and 4.5. • The applicability of multiple general climate models in China was evaluated. • Weather files from 2020 to 2099 were generated in batch for building simulation. • There are three trends in energy demand of residential building in China. • The life cycle energy demand in varying climate and locations was obtained. • The impact of passive design on life cycle energy demand was studied. [ABSTRACT FROM AUTHOR]

Human settlements grew up over time due to the action of many generations, taking shape according to the local geo-climatic characteristics and resources. This article discusses the co-evolutionary, largely unintentional and complex quality of the built environment, envisaged by studies on its morphogenesis since the mid-20th Century, in its relationship to the studies on the energetic performance of building fabrics, based on an urban morphological approach. The research-and-action proposal for the adaptive reuse of a historic residential neighbourhood in China, described here, endeavours to provide finetuned and ‘tailor-made’ improvements, making the most of the existing quality of the built environment while meeting present-day needs and expectations of the inhabitants. [ABSTRACT FROM AUTHOR]

Summary: There are two types of renewable energy widely used in China: air‐source heat pump and compact all glass solar vacuum pipe water heating systems. To compare the performance of these supply systems, test systems were installed on two adjacent apartment buildings with the same structure, shape, and material. Both sets of equipment were placed in the same environment for the same 31‐day period. The performances and performance parameters of the systems were systematically analyzed. The system energy consumption ratio of the compact all glass solar vacuum pipe water heating system was greater than that of the air‐source system on 81% of the days in the study period. However, extension theory analysis showed that the weight coefficients for the performance parameters of the two systems were equivalent over the study period. The grey relational degree between the system performance and the parameters were also calculated. The grey correlation degrees of the compact all glass solar vacuum pipe water heating system's properties with outlet temperature, inlet temperature, environment temperature, solar radiation, and sunshine time were 0.69, 0.71, 0.68, 0.70, and 0.68; and the grey correlation degrees of the air source heat pump water heating system's properties with outlet temperature, inlet temperature, environment temperature, solar radiation, and hours of sunshine were 0.71, 0.73, 0.71, 0.65, and 0.72. Furthermore, multivariate regression equations were used to study the changes of other parameters when one of the single variables changes. [ABSTRACT FROM AUTHOR]

• Traditional Chinese kang systems are reviewed and compared. • Improved kang systems are summarized and compared. • Possible directions for further study of Chinese kang are suggested. Chinese kang, which serves as the main space heating equipment in rural residences of cold regions of China, has received increasing attention due to people's increasing requirements of thermal comfort and concerns about indoor air environment in recent years. Most of the existing studies focused on one specific type of Chinese kang by using experimental or numerical methods to investigate the system's energy performance and its effect on the indoor environment. Therefore, there is a lack of comprehensive review of all the existing types of Chinese kangs. This paper firstly classifies the traditional Chinese kangs into three categories according to their culture and ethnic background. Secondly, the detailed construction, flue modality and thermal performance of the three kang systems are reviewed and compared. Thirdly, some recently proposed improved kang systems are introduced and analyzed. Finally, based on the review results, several possible research opportunities are suggested to guide future research on Chinese kangs. [ABSTRACT FROM AUTHOR]

• Thermochromic coatings with five different colors were prepared. • Spectral reflectivity and color-changing properties of the samples were measured. • A three-step control method is used to simulate energy performance for an office building model. • Thermochromic coatings are most favorable in areas with uniformly distributed cooling and heating demands. Thermochromic coatings are promising in lowering air conditioning energy consumption of buildings. In this paper, thermochromic coatings with five different colors are prepared and their optical properties are measured. A two-story office building model is established and simulation is conducted to evaluate the energy performance of thermochromic coatings by using a three-step control method based on their dynamic color-changing properties. A comparative analysis is carried out for thermochromic coatings, cool coating and common coating. It is observed that when the building is located in Shanghai, average daily surface temperature of thermochromic coatings is lower than the common coating during cooling period and higher than the cool coating during heating period. Annual energy consumption results indicate that thermochromic coatings can avoid the penalty of increasing heating load for cool coatings. In particular, the annual energy consumption of the office building using thermochromic coatings can be reduced by 4.28–5.02 kWh/m2 compared to the common coating, and 0.73–1.47 kWh/ m2 compared to the cool coating. Simulation of other cities in different climate zones in China reveals that thermochromic coatings have better energy saving effects especially for the areas with hot summers and cold winters, and relatively uniform distribution of cooling and heating demands. [ABSTRACT FROM AUTHOR]

In the context of residential energy consumption, the top-down approach and bottom-up approach have been developed to model and predict residential energy demand, and the bottom-up engineering model is a promising choice and an effective tool for urban planners and policymakers. However, unlike the existing building stock databases in some developed countries or regions, China's Pearl River Delta (PRD) region lacks such building databases. Thus, the study established a database of 120 residential districts in the PRD region, and developed typical models through the data of the collection, quantification and classification. In this paper, three typical residential district models have been defined, which was a supplement to previously develop seven typical residential building models. Moreover, four common family patterns in the PRD region were determined by literature research, the corresponding schedules and basic settings were developed subsequently for them. Finally, the simulations of the energy consumption of the three residential districts were conducted, whose energy consumption intensities were 28.43 kWh/m2a, 28.41 kWh/m2a and 28.24 kWh/m2a, respectively. The results of the simulation are similar to the results of the actual energy audit, which is considered that the typical residential buildings are representative yet simple-to-use energy model. [ABSTRACT FROM AUTHOR]