《1 Engineering research fronts》

1 Engineering research fronts

《1.1 Trends in Top 10 engineering research fronts》

1.1 Trends in Top 10 engineering research fronts

The Top 10 engineering research fronts in the field of civil, hydraulic, and architectural engineering are summarized in Table 1.1.1. These fronts cover a variety of disciplines, including geotechnical engineering, transportation engineering, architectural design and theory, surveying and mapping engineering, urban planning and landscaping, hydraulic engineering, structural engineering, municipal engineering, and engineering mechanics. Five of them were from experts’ nomination: “disaster mechanism and protection of vital transportation infrastructure”, “hybrid computing theory and methods in intelligent surveying and mapping”, “theory of urban renewal for high-density and complex space”, “theory and realization path of regional water balance under changing environments”, and “low-carbon resource utilization of urban sewage sludge”. The other five fronts were identified using the co-citation clustering method applied to the top 10% of highly citing papers, and they were confirmed in expert panel meetings. Table 1.1.2 presents annual statistics on the core papers published between 2016 and 2021 that are relevant to these Top 10 research fronts.

(1)   Disaster mitigation and risk control of underground engineering in extreme environments

The extreme environments of underground engineering refer to the extremely complex geological environments confronted during underground construction and the extreme natural hazards suffered during operation. Unlike typical unfavorable geological conditions, the extreme environments of underground engineering are of great uncertainty and complexity in evolutionary and cluster mechanisms. In recent years, in the construction of underground engineering represented by the Sichuan-Tibet Railway in China and the operation of underground engineering represented by the Heavy Rainstorm in Zhengzhou, China, the extreme environments have posed serious risks to underground engineering. It is of great significance to study the disaster mitigation and risk control of underground engineering in extreme environments. The current research focuses

《Table 1.1.1》

Table 1.1.1 Top 10 engineering research fronts in civil, hydraulic, and architectural engineering

No. Engineering research front Core papers Citations Citations per paper Mean year
1 Disaster mitigation and risk control of underground engineering in extreme environments 85 3722 43.79 2019.9
2 Disaster mechanism and protection of vital transportation infrastructure 37 1451 39.22 2018.8
3 Intelligent and responsive architecture for the elderly health 13 329 25.31 2018.8
4 Hybrid computing theory and methods in intelligent surveying and mapping 56 1671 29.84 2019.8
5 Theory of urban renewal for high-density and complex space 20 1245 62.25 2018.5
6 Theory and realization path of regional water balance under changing environments 30 1200 40 2018.3
7 Intelligent evaluation of engineering structures performance 29 1249 43.07 2018.8
8 Low-carbon resource utilization of urban sewage sludge 28 2584 92.29 2018.3
9 High-efficiency energy-absorbing composite structures for impact resistance 31 1233 39.77 2019
10 Intelligent monitoring and risk early-warning for dam safety 65 2110 32.46 2019.4

《Table 1.1.2》

Table 1.1.2 Annual number of core papers published for the Top 10 engineering research fronts in civil, hydraulic, and architectural engineering

No. Engineering research front 2016 2017 2018 2019 2020 2021
1 Disaster mitigation and risk control of underground engineering in extreme environments 3 2 5 13 31 31
2 Disaster mechanism and protection of vital transportation infrastructure 7 6 2 4 8 10
3 Intelligent and responsive architecture for the elderly health 2 1 2 2 4 2
4 Hybrid computing theory and methods in intelligent surveying and mapping 1 2 5 8 21 19
5 Theory of urban renewal for high-density and complex space 2 5 3 4 3 3
6 Theory and realization path of regional water balance under changing environments 8 3 5 6 3 5
7 Intelligent evaluation of engineering structures performance 3 5 2 9 4 6
8 Low-carbon resource utilization of urban sewage sludge 7 4 1 8 5 3
9 High-efficiency energy-absorbing composite structure for impact resistance 4 1 8 3 9 6
10 Intelligent monitoring and risk early-warning for dam safety 2 5 10 10 21 17

on: ① inversion analysis of high geo-stress fields in soft and hard rocks and risk prediction; ② characterization of the geothermal field of underground engineering, and optimization of supporting structures; ③ risk evaluation and control of tunnels in high-altitude cold areas; ④ seismic design and risk control of tunnels in areas of high seismic intensity; ⑤ risk assessment and control system of extraordinary waterlogging disasters in urban underground space. The development trend in the future is to identify geological conditions prone to disaster and clarify the catastrophic mechanisms in extreme environments. On this basis, multi-information is integrated for disaster prediction and mitigation. Meanwhile, attentions are also paid to accelerating the intelligentization of comprehensive management of underground space, strengthening the safety management of emergency response in underground space, and building a comprehensive management system for underground space. Between 2016 and 2021, 85 core papers relevant to this research front were published. These papers received 3 722 citations, with an average of 43.79 citations per paper.

(2)  Disaster mechanism and protection of vital transportation infrastructure

The research on this front is devoted to reveal performance deterioration and disaster-causing mechanism of vital transportation infrastructure (e.g., highway, railway, and airport) that undergoes extreme weathers, natural hazards (e.g., earthquakes and hurricanes), or emergencies due to engineering accidents or pipe leaking-induced collapse, and meanwhile to develop techniques for retaining or rapidly recovering functions of the affected transportation infrastructure. It is crucial to ensure long-term stable and safe operation of transportation, and reduce the impact of disaster on people’s travel. The main research directions include: ① disaster-causing mechanism of vital transportation infrastructure under extreme weathers, adverse geological conditions, and emergencies; ② assessment of function loss and traffic impact of vital transportation infrastructure during disasters; ③ key technologies for accurate inspection, monitoring, and early warning of service status of vital transportation infrastructure in complex environments; ④ key technologies for disaster mitigation and resilience maintenance of transportation infrastructure undergoing disasters. At present, this research front has been listed as a topic of urgent need that draws increasing attention and investigation over the next stage of transportation sector. In the future, progress of this front could be made in three aspects: ① the understanding on the mechanisms of infrastructure disaster may extend from single-factor leading mechanisms to multi-factor coupling mechanisms; ② the tools for infrastructure disaster assessment may evolve from numerical analyses and quantitative evaluation to fuzzy assessment and digital twin analyses of disaster evolution; ③ the methods for disaster prevention and control may advance from a single means focusing on monitoring and early warning to multiple means involving resilience design, intelligent operation and maintenance, and post-disaster recovery. Between 2016 and 2021, 37 core papers relevant to this research front were published. These papers received 1 451 citations, with an average of 39.22 citations per paper.

(3)   Intelligent and responsive architecture for the elderly health

Intelligent and responsive architecture for the elderly health is to intelligently regulate building environment and initiatively improve human health through comprehensive health monitoring and spatial response with the aid of environmental control technologies and intelligent response algorithms based on behavioral characteristics and health needs of the elderly. It is emerging as a key research direction for the development of healthy buildings. The relevant subjects include: ① integrated building health monitoring and spatial response mechanism via portable health monitoring and environmental sensing, which focuses on exploring the comprehensive perception and response mechanism of human health status and physical environment parameters; ② digital and intelligent environmental control based on Internet of Things (IoTs) for achieving a comprehensive control of the physical environment such as air, sound, light, heat, and color;  ③ intelligent response algorithms and smart control systems for health monitoring processing and decision-making mechanism. The future development of this front is to integrate multi-disciplinary knowledge (e.g., intelligent building and construction, computer and artificial intelligence, communication technology, and environmental science) for improving the health performance of buildings. Achievements in this direction would enable not only the adaptive transformation of existing buildings but also intelligent design and construction of new buildings. Between 2016 and 2021, 13 core papers relevant to this research front were published. These papers received 329 citations, with an average of 25.31 citations per paper.

(4)   Hybrid computing theory and methods in intelligent surveying and mapping

Hybrid computing theory and methods in intelligent surveying and mapping use knowledge engineering, deep learning, logical reasoning, swarm intelligence, and other new artificial intelligence technologies and means, to extract, describe and express the natural intelligence formed in human surveying and mapping activities. Combined with digital algorithms and models, the hybrid intelligent computing paradigm is built to realize the perception, cognition, expression and behavior computing in surveying and mapping. The subjects covered in this research front include: ① the analysis and modeling of natural intelligence in surveying and mapping; ② the knowledge system construction of the intelligent surveying and mapping; ③ the construction of the hybrid computing paradigm; ④ the implementation of the hybrid computing paradigm; ⑤ the mechanism and path of empowering production. In the future, this research could advance surveying and mapping data collection, processing, and service technologies from geometric information collection based on traditional measuring instruments to dynamic perception supported by ubiquitous smart sensors, from model and algorithm-led data processing to the knowledge- oriented and algorithm-based hybrid intelligent computing paradigm, and from the platform data information service to the online intelligent knowledge service. Between 2016 and 2021, 56 core papers relevant to this research front were published. These papers received 1 671 citations, with an average of 29.84 citations per paper.

(5)  Theory of urban renewal for high-density and complex space

Urban renewal is an important and effective approach to solve the problems associated with high-density and complex urban space. It helps clarify the space operation mechanism of high-density and complex space, reshape the image of the built environment, improve the urban environment quality, and revitalize the space value of the built environment. The theory of urban renewal for high-density and complex space is to improve the quality and efficiency in planning, design and construction of the high-density built environment in accordance with the law of urban development especially in areas or for subjects that cannot satisfy or meet the needs of social and economic development. The main research interests include: ① operation rule and principle of high- density and complex urban space; ② the new methodology and approach of urban renewal for high density and complex urban space; ③ multi-dimensional and refined analysis technological system of the built environment based on urban multi-source big data; ④ urban renewal planning and design method of high-density and complex space supported by digital technology; ⑤ intelligent platform based construction management and control approach of urban renewal. The future development trends of this research include: ① to establish a theoretical system and working path of urban renewal for high-density and complex space with healthy, green and sustainable development goals; ② to enable objective and quantitative analysis for high-density and complex space features recognition and sign diagnosis based on multi-source urban big data; ③ to promote applications of urban renewal planning, design and optimization of high-density and complex space based on virtual and real interactive digital technology; ④ to develop a periodic intelligent platform for urban renewal planning, construction and control of high-density and complex spaces; ⑤ through above ways to promote high-quality and sustainable development of high-density urban built environment. Between 2016 and 2021, 20 core papers relevant to this research front were published. These papers received 1 245 citations, with an average of 62.25 citations per paper.

(6)   Theory and realization path of regional water balance under changing environments

Regional water balance refers to the spatial storage, the exchange between revenue and expenditure, and the transformation characteristics of water in the regional water cycle system and its various circles under the coupled action of natural and human factors. The state of regional water balance not only affects the water resources carrying capacity, but also is an “indicator” and “barometer” that informs us the utilization of regional water resources exceeding the carrying capacity. Due to the complexity and uncertainty in the interaction and feedback among water resources- ecological environment-socioeconomic system, strengthening the rigid constraints of water resources and achieving a healthy regional water balance in changing environments becomes one of the basic prerequisites for promoting the ecological civilization from concept to practice, ensuring the overall national security, and facilitating green development.

The main subjects of this front include: ① regional water balance mechanism and its constitutive relationship; ② the relationship between the state and the carrying capacity of water resources; ③ dynamic evaluation and regulation of regional water balance under changing environments; ④ the path of building the healthy regional water balance. The future development trends mainly include: ① to strengthen dynamic monitoring and analysis of the basic elements of regional water balance and water resources carrying capacity; ② to improve the theory and the method of water balance evaluation and early warning; ③ to construct the collective strategy for increasing regional water resources carrying capacity and optimizing water balance status; and ④ to work out the strategic goals and development paths of land use and restoration under rigid constraints of water resources. Between 2016 and 2021, 30 core papers relevant to this research front were published. These papers received 1 200 citations, with an average of 40.00 citations per paper.

(7)    Intelligent evaluation of engineering structures performance

Traditional performance evaluation methods for engineering structures are limited in accuracy and efficiency due to limitation of theoretical development, structural complexity, limited data, and random deviation of structures. Emerging information technologies such as artificial intelligence, sensing technology and big data are profoundly changing design, construction and maintenance of engineering structures. The relevant research involves intelligent evaluation of mechanical performance at different levels, such as material, cross section, structural member, connection and structure. Intelligent evaluation of engineering structures improves efficiency of design, construction, operation and maintenance of structures, and increases accuracy of structural performance evaluation. The main research subjects include: ① intelligent evaluation algorithm and theory of engineering structural performance; ② multiscale mechanical performance evaluation of engineering structures under different hazards, such as earthquakes, fires, winds and geo-hazards; ③ damage state and bearing capacity evaluation of engineering structures under daily service conditions. The future development trends include such as: ① intelligent design of engineering structures and systems; ② physics-informed neural network for intelligent evaluation of engineering structures. Between 2016 and 2021, 29 core papers relevant to this research front were published. These papers received 1 249 citations, with an average of 43.07 citations per paper.

(8)  Low-carbon resource utilization of urban sewage sludge

Low-carbon resource utilization of urban sewage sludge refers to the full use of energy and resource such as organic matters and nutrient elements contained in the sludge to realize low- carbon treatment and disposal of sludge. Urban sewage sludge has the dual properties of pollutant and resource. Its improper treatment and disposal are prone to generate greenhouse gases such as methane with high warming potential. Meanwhile, sludge has good potential for resource utilization. Facing the challenges brought by global climate change, the low-carbon resource utilization of multiple substances of sludge has become an important approach and research hotspot to achieve energy self-sufficiency and carbon cycle of sewage treatment plants. The main research subjects include: ① mechanism and technology of deep development of sludge biomass energy based on efficient regulation of anaerobic flora, targeted strengthening of methanogenic metabolic pathways, and synergistic complementation of sludge and organic wastes, which improves biomass conversion rate of low organic matter sludge to above 40% stably; ② mechanism and technology of efficient and low- carbon sludge drying and incineration based on staged combustion for excavating sludge calorific value while reducing the emission of non-carbon dioxide greenhouse gases, multi- stage recovery and comprehensive utilization of heat from drying exhaust gas and incineration flue gas, and dynamic regulation and optimization of energy allocation; ③ land use technology of sludge treatment products or derivative products, and morphological transformation law, product- environment interaction mechanism and secondary pollution risk control technology of key substances with resource and environmental attributes; ④ high value extraction and recycling technology of carbon, nitrogen and phosphorus in sludge. The main development trend in the future is to integrate interdisciplinary development, and further carry out research on key technologies for improving the efficiency of sludge energy and resource recovery, safety risk assessment and control of resource utilization, which helps to realize the efficient recycling of sludge energy and resource, and improve the low-carbon level of sludge treatment and disposal. Between 2016 and 2021, 28 core papers relevant to this research front were published. These papers received 2 584 citations, with an average of 92.29 citations per paper.

(9)  High-efficiency energy-absorbing composite structure for impact resistance

With their capacity of irreversible deformations that absorb the kinetic energy, high-efficiency energy-absorbing composite structures provide a solution to possible accidents, explosions or impacts during life cycles of engineering structures. Compared with traditional metal-based energy- absorbing structures, they have higher specific strength and stiffness, and exhibit advantages such as environmental friendliness, vibration and noise suppression, presenting obvious superiority for the objective of carbon peaking and carbon neutrality. Typical structural types of high-efficiency energy-absorbing composite structures include fiber/matrix composite structures, metal and fiber-reinforced polymer composite structures, foam and architected core sandwich structures, etc. The evaluation of their impact resistance involves a variety of behaviors such as fiber fracture, matrix cracking, interface failure and their coupling effects, and is related to different loading rate conditions, namely the quasi- static, low-speed and high-speed impact. The main topics of this research includes: ① failure modes of high-efficiency energy-absorbing composite structures and influence of the design and manufacturing process; ② simulation of the impact process of high-efficiency energy-absorbing composite structures and evaluation methods of impact resistance; ③ health monitoring and maintenance of high-efficiency energy-absorbing composite structures considering sustainability. The future research trend is to carry out the impact resistance performance evaluation considering the life-cycle performance demand of engineering structures, and especially to solve the failure criterion under high- speed impact conditions. Meanwhile, the failure modes and the assessment for new materials (e.g., nanocomposites, functional gradient materials, negative Poisson’s ratio materials) and new manufacturing process (e.g., additive manufacturing) should be considered, and the multi-objective optimization design could be conducted. Between 2016 and 2021, 31 core papers relevant to this research front were published. These papers received 1 233 citations, with an average of 39.77 citations per paper.

(10)   Intelligent monitoring and risk early-warning for dam safety

The construction and safe operation of dams, as critical infrastructure, are crucial to flood mitigation as well as economic, ecological and public safety. Dam safety management is becoming more digitalized, network-based and intelligent. Dam safety intelligent monitoring system utilizes modern information technologies, such as IoTs, cloud computing and big data, being able to perceive multi- source information in an all-round way. Data fusion helps to build an intelligent monitoring system featuring deep perception, comprehensive interconnection, deep fusion, wide-scope sharing, smart application and ubiquitous service. The system provides functions of forecasting, early- warning, rehearsal and emergency plan, and supports high- quality development of dam safety management covering the whole-process and the full-chain of development. Based on physics-informed data-driven model, risk early-warning enables evaluation of the real-time dam risk, sends early- warning signals in time upon risk beyond design levels, and implements emergency plans as necessary. The main topics of this research include: ① multi-source information fusion and diagnosis of dam safety; ② dam structural performance evolution, prediction and early-warning; ③ intelligent diagnosis and decision-making on dam safety based on big data; ④ application of modern information technology in dam safety management; ⑤ formulation of risk early-warning indicators; ⑥ risk emergency response and decision-making mechanism. The future research may focus on breakthroughs in bottleneck technologies, such as numerical identification of dam damages, virtual scenario construction for rapid and accurate diagnosis of safety performance, and strengthened capabilities in deep perception, risk assessment and early- warning to effectively guarantee the safe operation of dams with scientific and technological supports. Between 2016 and 2021, 65 core papers relevant to this research front were published. These papers received 2 110 citations, with an average of 32.46 citations per paper.

《1.2 Interpretations for three key engineering research fronts》

1.2 Interpretations for three key engineering research fronts

1.2.1 Disaster mitigation and risk control of underground engineering in extreme environments

The worldwide development and utilization of underground space is in great demand and has broad prospects. With the increase in construction scales, the worldwide development of underground space is gradually extended to the regions with harsh geological conditions. Extreme environments characterized with high geo-stresses that stimulate large deformation in soft rock or rockburst in hard rock, and high ground temperature pose huge risks to underground engineering. Besides, extreme weathers affect the world at an increasing frequency, and add additional challenges to the operation and management of underground projects. The research of disaster mitigation and risk control of underground engineering under extreme environments is of great significance to ensure safety and shorten construction.

Currently, the major topics of this research front include:

1)  Inversion analysis of high geo-stress fields in soft and hard rocks and risk prediction. Geo-stresses are largely random and uncertain, and the local measurement of geo-stresses has great uncertainty. The following issues are of interest: ① reasonably selecting the measured indexes for geo- stress inversion in underground engineering with different lithologies; ② analyzing the inversion criteria of initial geo- stress fields in different lithologies; ③ obtaining geo-stress distribution; ④ predicting large deformation in surrounding rock and rockburst.

2)   Characterization of geothermal fields in underground engineering and optimization of supporting structures. Efforts are devoted to ① infer geothermal fields from field measurements, ② study the influence of high geothermal temperature on the thermal stresses and the mechanical properties (e.g., strength and durability) of concrete supporting structures, and ③ simultaneously improve the structures’ capacity in thermal insulation and stability in heated environments.

3)   Risk evaluation and control of tunnels in high-altitude cold areas. This topic is to ① depict the temperature change in linings and surrounding rock, ② explore the mechanism of freezing damage, ③ optimize the engineering measures for mitigating freezing damage during construction and operation, and ④ ensure safe operation of the tunnels by minimizing traffic interruption due to freezing.

4)  Seismic design and risk control of tunnels in areas of high seismic intensity. This topic is to ① develop reliable theories and methods for seismic analysis of tunnels in areas prone to strong motions, ② reveal seismic response of tunnels and the resulting disaster, and ③ improve mitigation measures.

5)   Risk assessment and control system of extraordinary waterlogging disasters in urban underground space. This topic is to ① identify main causes of disasters in urban underground space during extremely flood seasons, ② establish methods for risk assessment and disaster control, ③ integrate intelligent networks of underground engineering towards a waterlogging disaster prevention and control system, and ④ plan post-disaster recovery.

As shown in Table 1.1.1, 85 core papers concerning “disaster mitigation and risk control of underground engineering in extreme environments” were published between 2016 and 2021, with each paper being cited 43.79 times on average. The top five countries in terms of output of core papers on this topic are China, Iran, Malaysia, Vietnam, and the USA (Table 1.2.1). China is one of the most active countries, having published 69.41% of the core papers. The five countries with the highest average citations were Norway, Australia, Malaysia, Iran, and Vietnam. The papers published by Chinese authors were cited 43.81 times on average, which is slightly above the overall average. As illustrated by the international collaborative network depicted in Figure 1.2.1, close cooperation was observed among the ten most productive countries.

The five institutions that published the most core papers were Chang’an University, Xi’an University of Architecture and Technology, Amirkabir University of Technology, Universiti Teknologi Malaysia, and Chongqing University (Table 1.2.2). Chang’an University and Xi’an University of Architecture and Technology have focused on the structural response of underground engineering under adverse geological conditions dominated by loess areas and the design of new supporting structures for underground engineering. Amirkabir University of Technology has focused on application of new intelligent technologies such as neural networks in prediction, optimization and design of underground engineering. As illustrated in Figure 1.2.2, the ten most productive institutions have conducted collaborative studies in this regard.

As shown in Table 1.2.3, the five most active countries in terms of paper citations were China, Iran, the USA, Vietnam, and Australia. The top five institutions in terms of citations of core

《Table 1.2.1》

Table 1.2.1 Countries with the greatest output of core papers on “disaster mitigation and risk control of underground engineering in extreme environments”

No. Country Core papers Percentage of core papers/% Citations Citations per paper Mean year
1 China 59 69.41 2 585 43.81 2020
2 Iran 19 22.35 1 036 54.53 2019.8
3 Malaysia 16 18.82 1 049 65.56 2019.6
4 Vietnam 9 10.59 426 47.33 2020.2
5 USA 8 9.41 358 44.75 2019.5
6 Australia 6 7.06 418 69.67 2019.2
7 Norway 4 4.71 324 81 2020.5
8 India 4 4.71 177 44.25 2019.5
9 Canada 3 3.53 98 32.67 2019
10 Italy 3 3.53 75 25 2019.7

《Figure 1.2.1》

Figure 1.2.1 Collaboration network among major countries in the engineering research front of “disaster mitigation and risk control of underground engineering in extreme environments”

《Table 1.2.2》

Table 1.2.2 Institutions with the greatest output of core papers on “disaster mitigation and risk control of underground engineering in extreme environments”

No. Institution Core papers Percentage of core papers/% Citations Citations per paper Mean year
1 Chang’an University 20 23.53 455 22.75 2020.3
2 Xi’an University of Architecture and Technology 19 22.35 443 23.32 2020.3
3 Amirkabir University of Technology 17 20 1001 58.88 2019.7
4  Universiti Teknologi Malaysia 16 18.82 1049 65.56 2019.6
5 Chongqing University 11 12.94 885 80.45 2019.6
6 China University of Mining and Technology 8 9.41 427 53.38 2019.9
7 Duy Tan University 8 9.41 358 44.75 2020.2
8 China Railway First Survey & Design Institute Group Co., Ltd. 7 8.24 233 33.29 2020
9 Central South University 6 7.06 240 40 2020.5
10 Xi’an University of Architecture and Technology 5 5.88 130 26 2020.6

《Figure 1.2.2》

Figure 1.2.2 Collaboration network among major institutions in the engineering research front of “disaster mitigation and risk control of underground engineering in extreme environments”

《Table 1.2.3》

Table 1.2.3 Countries with the greatest output of citing papers on “disaster mitigation and risk control of underground engineering in extreme environments”

No. Country Citing papers Percentage of citing papers/% Mean year
1 China 1 178 48.48 2020.5
2 Iran 263 10.82 2020.3
3 USA 178 7.33 2020.4
4 Vietnam 171 7.04 2020.4
5 Australia 158 6.5 2020.4
6 Malaysia 114 4.69 2020.2
7 India 102 4.2 2020.5
8 Russia 78 3.21 2020.7
9 Italy 66 2.72 2020.7
10 UK 62 2.55 2020.6

papers were Duy Tan University, Central South University, China University of Mining and Technology, Chongqing University, and Chang’an University (Table 1.2.4). China ranked the first in the quantity of core papers produced and the number of citations of core papers, indicating that Chinese researchers pay close attention to this front.

Summarizing the above statistics, Chinese scholars have performed well and become the leader in the research of “disaster mitigation and risk control of underground engineering in extreme environments”.

In the next ten years, the key directions of this research front lie in identification of disastrous geological conditions and clarification of the catastrophic mechanism under extreme environments, establishment of urban underground space disaster assessment and control systems under extreme weathers, and promotion of the intelligent construction of underground engineering. Meanwhile, in terms of the development trend, the front will gradually develop towards refinement, systematization and intelligentization. The outcomes of this front are of great potential and will be widely used in underground projects, which are threatened by increasingly harsh environments during their construction and increasingly frequent extreme weathers during their operation (Figure 1.2.3).

《Table 1.2.4》

Table 1.2.4 Institutions with the greatest output of citing papers on “disaster mitigation and risk control of underground engineering in extreme environments”

No. Institution Citing papers Percentage of citing papers/% Mean year
1 Duy Tan University 125 13.87 2020.3
2 Central South University 119 13.21 2020.5
3 China University of Mining and Technology 106 11.76 2020.1
4 Chongqing University 101 11.21 2020.6
5 Chang’an University 94 10.43 2020.4
6 Xi’an University of Architecture and Technology 70 7.77 2020.5
7 Islamic Azad University 65 7.21 2020.3
8 Amirkabir University of Technology 65 7.21 2019.9
9 Universiti Teknologi Malaysia 64 7.1 2019.9
10 Ton Duc Thang University 51 5.66 2020.3

《Figure 1.2.3》

Figure 1.2.3 Roadmap of the engineering research front of “disaster mitigation and risk control of underground engineering in extreme environments”

1.2.2 Disaster mechanism and protection of vital trans- portation infrastructure

The transportation infrastructure including highway, railway, and airport frequently experiences complex environments and hazards, and the vital transportation infrastructure often suffers from serious damage and sudden reduction in service life due to insufficient resilience. This not only increases the life-cycle cost of vital transportation infrastructure, but also reduces the post-disaster service capacity of entire transportation system. Currently, systematic research on catastrophe mechanism and protection of vital transportation infrastructure is still in the preliminary stage. It is of great significance to clarify the service performance degradation and disaster-causing mechanism for vital transportation infrastructure under emergencies due to extreme weathers or natural hazards, and further develop methods for maintaining safety and rapid recovery during emergencies. At present, the relevant research has been expanded from the single-disaster resistance design to more systematic research involving disaster recognition, assessment, monitoring and early warning, prevention and control. The main topics include:

1)   Disaster-causing mechanism of vital transportation infrastructure under extreme weathers and adverse geological conditions. Various tools, such as small scale modelling, in- situ tests and numerical simulations, are deployed to reveal the damage mechanism of vital transportation infrastructure caused by earthquakes, typhoons, freeze-thaw, debris flows, engineering disturbance, torrents, foundation damage, and accidents, and formulate the evolving functionality or performance of vital transportation infrastructure.

2)   Assessment of function loss of vital transportation infrastructure and traffic impact. This topic is to ① identify proper assessment index driven by big data with physical support using advanced methods such as fuzzy evaluation and numerical analyses, ② improve the methods for accurately evaluating the function loss and the traffic delay due to natural hazards and sudden accidents, and ③ establish the twin theory and model for disaster occurrence and evolution of vital transportation infrastructure.

3)  Accurate monitoring and early warning for the service status of vital transportation infrastructure in complex environments. This topic aims to ① innovate the theory of non-destructive detection and real-time monitoring of the service status of vital transportation infrastructure under natural hazards and traffic loads, ② create a new generation of “space-sky-earth” integrated disaster intelligent monitoring theory and method with the help of Beidou system, and ③ build a digital system for time-dependent service performance prediction and real-time warning based on big data mining for vital transportation infrastructure.

4)   Disaster mitigation and resilience maintenance of vital transportation infrastructure. This topic aims to ① propose a universal mechanism for efficient repair and rapid reinforcement of damaged parts of vital transportation infrastructure in complex post-disaster scenarios, ② innovate the theory of temporary maintenance, rapid rescue, and function recovery of vital transportation infrastructure after disasters, and ③ clarify the principles of resilience design, recovery and improvement of vital transportation infrastructure in disaster affected environments.

As shown in Table 1.1.1, 37 core papers concerning “disaster mechanism and protection of vital transportation infrastructure” were published between 2016 and 2021, with each paper being cited an average of 39.22 times. The top five countries in terms of output of core papers on this topic are the USA, Italy, China, Singapore, and Greece (Table 1.2.5). China is very active, having published 5.41% of the core papers. The five countries with the highest average citations were Serbia, China, Saudi Arabia, Japan, and Malaysia. The papers published by Chinese authors were cited 76.50 times on average, which is above the overall average. As illustrated by the international collaborative network depicted in Figure 1.2.4, close cooperation was observed among the most productive top 10 countries.

The five institutions that published the most core papers were The University of Texas at Arlington, The University of Oklahoma, University of Illinois, Texas A&M University, and Florida International University (Table 1.2.6). The University of Texas at Arlington has focused on the disaster resilience analysis of infrastructure, the weight analysis of the key process of infrastructure post-disaster reconstruction, and the influencing factor of post-disaster environment on infrastructure reconstruction; The University of Oklahoma has focused on the resilience-based infrastructure disaster resilience and risk mitigation analysis; University of Illinois has focused on the assessment of disaster resilience and post- disaster impact of transportation infrastructure in city based on mathematical and empirical methods. Cooperation is rare

《Table 1.2.5》

Table 1.2.5 Countries with the greatest output of core papers on “disaster mechanism and protection of vital transportation infrastructure”

No. Country Core papers Percentage of core papers/% Citations Citations per paper Mean year
1 USA 27 72.97 1 041 38.56 2019.3
2 Italy 3 8.11 48 16 2019.3
3 China 2 5.41 153 76.5 2019
4 Singapore 2 5.41 58 29 2019.5
5 Greece 2 5.41 42 21 2018
6 Serbia 1 2.7 105 105 2017
7 Saudi Arabia 1 2.7 75 75 2019
8 Japan 1 2.7 45 45 2017
9 Malaysia 1 2.7 45 45 2019
10 Germany 1 2.7 41 41 2018

《Figure 1.2.4》

Figure 1.2.4 Collaboration network among major countries in the engineering research front of “disaster mechanism and protection of  vital transportation infrastructure”

《Table 1.2.6》

Table 1.2.6 Institutions with the greatest output of core papers on “disaster mechanism and protection of vital transportation infrastructure”

No. Institution Core papers Percentage of core papers/% Citations Citations per paper Mean year
1 The University of Texas at Arlington 6 16.22 42 7 2020.3
2 The University of Oklahoma 3 8.11 321 107 2017
3 University of Illinois 3 8.11 87 29 2019.7
4 Texas A&M University 2 5.41 24 12 2020.5
5 Florida International University 2 5.41 13 6.5 2018.5

among major institutions.

As shown in Table 1.2.7, the five most active countries in terms of paper citations were USA, China, UK, Iran, and Canada.

The top five institutions in terms of citations of core papers were Texas A&M University, Tsinghua University, The Hong Kong Polytechnic University, University of Illinois, and Tongji University (Table 1.2.8). According to the number of citations of core papers, there are differences between the top five countries in terms of output of core papers and the five most active countries in terms of paper citations, which indicates that this front has received common attention from scholars from different countries.

Based on the above statistics, the proportion of paper citations in China is far higher than the core papers, indicating that Chinese researchers paid close attention to this front.

In the next 5–10 years, the engineering research front of“disaster mechanism and protection of vital transportation infrastructures” will focus on the development direction of disaster-causing mechanisms, disaster evaluation system, monitoring and early warning platform, and disaster prevention and resilience recovery technology (Figure 1.2.5).

1.2.3 Intelligent and responsive architecture for the elderly health

Building for the elderly has become an important research direction in recent years aiming to improve the health

《Table 1.2.7》

Table 1.2.7 Countries with the greatest output of citing papers on “disaster mechanism and protection of vital transportation infrastructure”

No. Country Citing papers Percentage of citing papers/% Mean year
1 USA 438 30.8 2020
2 China 425 29.89 2020.1
3 UK 97 6.82 2020.1
4 Iran 93 6.54 2020
5 Canada 72 5.06 2020.2
6 India 60 4.22 2020.2
7 Australia 55 3.87 2019.9
8 Italy 54 3.8 2019.8
9 South Korea 53 3.73 2019.9
10 Germany 41 2.88 2020.1

《Table 1.2.8》

Table 1.2.8 Institutions with the greatest output of citing papers on “disaster mechanism and protection of vital transportation infrastructure”

No. Institution Citing papers Percentage of citing papers/% Mean year
1 Texas A&M University 37 14.92 2020.1
2 Tsinghua University 27 10.89 2020.3
3 The Hong Kong Polytechnic University 25 10.08 2020
4 University of Illinois 23 9.27 2020.4
5 Tongji University 22 8.87 2020.2
6 Chinese Academy of Sciences 22 8.87 2020
7 The University of Texas at Arlington 21 8.47 2021
8 University of Tehran 20 8.06 2019.9
9 Delft University of Technology 18 7.26 2020.4
10 The University of Oklahoma 17 6.85 2019.6

《Figure 1.2.5》

Figure 1.2.5 Roadmap of the engineering research front of “disaster mechanism and protection of vital transportation infrastructure”

performance of buildings and promote the well-being of the elderly. Intelligent and responsive architecture for the elderly health is to intelligently regulate building environment and initiatively improve human health through comprehensive health monitoring and spatial response using environmental control technology and intelligent response algorithms based on behavioral characteristics and health needs of the elderly. Relevant studies and insights provide effective support for the aging adaptation and intelligent empowerment of a large number of existing buildings with billions of square meters, as well as the intelligent design and construction of new buildings. Existing studies of buildings for the elderly mainly focus on behavioral characteristics, physical space and facilities adaption, which are difficult to dynamically adjust and respond to their health needs in real time. Nevertheless, with the technological innovation of wearable biosensors and IoTs, low-cost portable physical and mental health monitoring and environmental data acquisition become possible in daily lives. Accordingly, intelligent and responsive regulation of indoor environment to achieve active health intervention has become a hot direction for buildings for the elderly. The relevant topics are as follow:

1)   Integrating building health monitoring and spatial response mechanism. Portable health monitoring equipment and environmental sensors are utilized for achieving comprehensive perception of human health status and physical environmental parameters, with special attention to the personalized characteristics of different user groups such as the disabled, the demented, and the active elderly. In particular, a focus is placed on intelligent early warning and real-time response mechanisms for accidental risks such as falls and strokes.

2)   Digital and intelligent environmental control. Instant control of physical environment of buildings (e.g., air, sound, light, heat, color, and vegetation) are enabled based on the environmental health data obtained from real-time monitors. Furthermore, it becomes possible to achieve optimized and intelligent configuration of the built environment via multi-system comprehensive control instead of single-system control.

3)  Intelligent response algorithms and smart control systems. Building intelligent infrastructure is developed based on deep learning and reinforcement learning. In order to fully meet the need of environmental health monitoring, responsive facilities in buildings and health monitoring equipment are managed and controlled in a comprehensive manner. Besides, mechanisms are established for information transmission, processing and decision making mechanism for the ultimate goal targeting the integration of information system and physical system.

As shown in Table 1.1.1, 13 core papers concerning “intelligent and responsive architecture for the elderly health” were published between 2016 and 2021, with each paper being cited an average of 25.31 times. The top five countries in terms of output of core papers on this topic are USA, Italy, China, France, and India (Table 1.2.9). China is very active, having published 15.38% of the core papers. The five countries with the highest average citations were France, India, Greece, Italy, and Spain. The papers published by Chinese authors were cited 23.50 times on average, which is slightly lower than the overall average. As illustrated by the international collaborative network depicted in Figure 1.2.6, close

《Table 1.2.9》

Table 1.2.9 Countries with the greatest output of core papers on “intelligent and responsive architecture for the elderly health”

No. Country Core papers Percentage of core papers/% Citations Citations per paper Mean year
1 USA 3 23.08 31 10.33 2018.3
2 Italy 2 15.38 107 53.5 2020.5
3 China 2 15.38 47 23.5 2019.5
4 France 1 7.69 99 99 2020
5 India 1 7.69 99 99 2020
6 Greece 1 7.69 68 68 2016
7 Spain 1 7.69 50 50 2016
8 Singapore 1 7.69 27 27 2019
9 Tunisia 1 7.69 16 16 2020
10 Egypt 1 7.69 9 9 2017

《Figure 1.2.6》

Figure 1.2.6 Collaboration network among major countries in the engineering research front of “intelligent and responsive architecture for the elderly health”

cooperation was observed among the most productive Top 10 countries.

The five institutions that published the most core papers were Great Lakes Institute of Management, Paris School of Business, Link Campus University, University of Turin, and The Aristotle University of Thessaloniki (Table 1.2.10). As illustrated in Figure 1.2.7, the ten most productive institutions have conducted collaborative studies in this regard.

As shown in Table 1.2.11, the five most active countries in terms of paper citations were China, Spain, Italy, Greece, and the UK. The top five institutions in terms of citations of core papers were The Aristotle University of Thessaloniki, The University of Castilla-La Mancha, University of Waterloo, Nanyang Technological University, and Shanghai Jiao Tong University (Table 1.2.12). According to the number of citations of core papers, there are differences between the top five countries in terms of output of core papers and the five most active countries in terms of paper citations, which indicates that this front has received common attention from scholars from different countries.

《Table 1.2.10》

Table 1.2.10 Institutions with the greatest output of core papers on “intelligent and responsive architecture for the elderly health”

No. Institution Core papers Percentage of core papers/% Citations Citations per paper Mean year
1 Great Lakes Institute of Management 1 7.69 99 99 2020
2 Paris School of Business 1 7.69 99 99 2020
3 Link Campus University 1 7.69 99 99 2020
4 University of Turin 1 7.69 99 99 2020
5 The Aristotle University of Thessaloniki 1 7.69 68 68 2016
6 The Greek Association of Alzheimer’s Disease and Related Disorders 1 7.69 68 68 2016
7  Conservatorio Profesional de Música Maestro Gómez Villa 1 7.69 50 50 2016
8  University of Carlos III Madrid 1 7.69 50 50 2016
9 The University of Castilla-La Mancha 1 7.69 50 50 2016
10  Nanyang Technological University 1 7.69 27 27 2019

《Figure 1.2.7》

Figure 1.2.7 Collaboration network among major institutions in the engineering research front of “intelligent and responsive architecture for the elderly health”

《Table 1.2.11》

Table 1.2.11 Countries with the greatest output of citing papers on “intelligent and responsive architecture for the elderly health”

No. Country Citing papers Percentage of citing papers/% Mean year
1 China 58 18.12 2020.4
2 Spain 49 15.31 2019
3 Italy 32 10 2020
4 Greece 30 9.38 2017.7
5 UK 30 9.38 2019.7
6 India 30 9.38 2020.4
7 USA 22 6.88 2020.4
8 Germany 19 5.94 2019
9 France 18 5.62 2020.4
10 Canada 16 5 2020.1

《Table 1.2.12》

Table 1.2.12 Institutions with the greatest output of citing papers on “intelligent and responsive architecture for the elderly health”

No. Institution Citing papers Percentage of citing papers/% Mean year
1 The Aristotle University of Thessaloniki 26 28.26 2017.4
2 The University of Castilla-La Mancha 23 25 2018.4
3 University of Waterloo 6 6.52 2020.5
4 Nanyang Technological University 6 6.52 2020.3
5 Shanghai Jiao Tong University 6 6.52 2020.3
6 Biomedical Research Networking Center in Mental Health 5 5.43 2019.8
7 University of Seville 4 4.35 2017
8 Sapienza University of Rome 4 4.35 2019.2
9  King Saud University 4 4.35 2019.5
10 University of Valencia 4 4.35 2018.5

《Figure 1.2.8》

Figure 1.2.8 Roadmap of the engineering research front of “intelligent and responsive architecture for the elderly health”

《2 Engineering development fronts》

2 Engineering development fronts

《2.1 Trends in Top 10 engineering development fronts》

2.1 Trends in Top 10 engineering development fronts

The Top 10 engineering development fronts in the field of civil, hydraulic, and architectural engineering are summarized in Table 2.1.1. These fronts cover a variety of disciplines, including geotechnical and underground engineering, hydraulic engineering, architectural design and theory, surveying and mapping engineering, construction materials, transportation planning, urban planning and landscaping, municipal engineering, and bridge engineering. The following development fronts were from experts’ nomination: “intelligent monitoring and early warning technologies for hidden defects of transportation infrastructure” and “control of algal and odor pollution in urban water supply system”.

The remaining fronts were identified from patent maps and confirmed in expert panel meetings. Table 2.1.2 presents annual statistics on patents registered between 2016 and 2021 related to these Top 10 development fronts.

(1)   Active prevention and control of geohazards along the Sichuan-Tibet Railway

The active prevention and control of geohazards refers to the technologies that employ advanced measures to eliminate

《Table 2.1.1》

Table 2.1.1 Top 10 engineering development fronts in civil, hydraulic, and architectural engineering

No. Engineering development front Published patents Citations Citations per patent Mean year
1 Active prevention and control of geohazards along the SichuanTibet Railway 279 860 3.08 2019.4
2 Riverway ecological environment conservation and restoration 296 1273 4.3 2019.6
3  Modeling and optimization of urban building energy consumption and carbon emission 13 275 21.15 2018.4
4  Autonomous positioning and navigation of unmanned systems 37 376 10.16 2018.8
5  Intelligent perception and prediction of multi-source information on underground engineering status 87 164 1.89 2019.8
6  Healing materials and techniques for different service environments 65 207 3.18 2019
7  Intelligent monitoring and early warning for hidden defects of transportation infrastructure 18 85 4.72 2018.8
8  Dynamic measurement and performance enhancement of green infrastructure ecosystem services 62 110 1.77 2019.2
9  Control of algal and odor pollution in urban water supply system 41 26 0.63 2019
10  Reliability evaluation and maintenance for bridge structures 79 131 1.66 2018.76

《Table 2.1.2》

Table 2.1.2 Annual number of core patents published for the Top 10 engineering development fronts in civil, hydraulic, and architectural engineering

No. Engineering development front 2016 2017 2018 2019 2020 2021
1 Active prevention and control of geohazards along the SichuanTibet Railway 18 21 37 44 70 89
2 Riverway ecological environment conservation and restoration 12 26 32 41 87 98
3 Modeling and optimization of urban building energy consumption and carbon emission 3 1 1 4 4 0
4 Autonomous positioning and navigation of unmanned systems 4 8 3 8 6 8
5 Intelligent perception and prediction of multi-source information of underground engineering status 4 6 10 12 10 45
6 Healing materials and techniques for different service environments 6 4 11 18 18 8
7 Intelligent monitoring and early warning for hidden defects of transportation infrastructure 1 4 2 5 2 4
8 Dynamic measurement and performance enhancement of green infrastructure ecosystem services 6 7 8 10 7 24
9 Control of algal and odor pollution in urban water supply system 2 8 8 5 8 10
10 Reliability evaluation and maintenance for bridge structures 6 14 13 17 18 11

hidden risks before forming geological disasters. The principle of these technologies is to use digitalized, informatized, mechanized and intelligentized techniques to establish an information database of geohazard source characteristics. The goal of being active and predictive is achieved through deployment of standardized modeling, network interaction, visual cognition, high-performance computing, and intelligent decision-making among other technologies in various core tasks such as quantitative assessment, intelligent monitoring, risk analysis, disaster warning, prevention and control, and emergency response. Driven by the digital chain, it becomes possible to enable integration and coordination of detection, assessment, monitoring, early warning, prevention and control, and emergency rescue against geohazards, and ultimately raise the level of disaster prevention and control by avoiding, transferring, and minimizing geohazards risk. The Sichuan- Tibet Railway is threatened frequently by geohazards such as landslides, debris flows, rockfalls, earthquakes, high geo- stress rockbursts and excessive deformations, high geothermal damages, active fault dislocations, and inrush of water and mud. The applications of the active prevention and control technologies against the geohazards involve: ① quantitative assessment of geohazards risk under coupling dynamic interaction of intensive internal and external forces; ② three-dimensional comprehensive intelligent monitoring and early warning of geohazards; ③ active prevention and control in advance and intelligent construction for complex bridges, tunnels, and high-steep slopes; ④ rapid and intelligent emergency rescue for geological disaster chain in mountainous areas. The key of these technologies is to deeply and extensively utilize modern technologies, such as the IoTs, big data, artificial intelligence, and building information modelling (BIM), to innovate upon new materials, new structures, and new techniques applicable in the key components (e.g., bridges, tunnels and high-steep slope) of the Sichuan-Tibet Railway and adaptive to harsh environment, and thus to achieve life-cycle early detection, warning and precise control of geohazards. Between 2016 and 2021, 279 patents relevant to this research front were registered. These patents received 860 citations, with an average of 3.08 citations per patent.

(2)   Riverway ecological environment conservation and restoration

Riverway ecological environment conservation and restoration is critical for maintaining the ecological security boundary of territorial space, maintaining or assisting the restoration of river ecosystem to the natural or near-natural state, so as to maintain and improve its ecological integrity and sustainability. It is also a scientific and technological frontier of international common concern, and its main technical directions include: ① the intelligent integration technology of riverway monitoring, evaluation and smart collaborative watershed management system; ② riverway green low- carbon and naturalization restoration technology; ③ riverway ecosystem function and biodiversity of conservation and restoration technology. New technologies, such as artificial intelligence, support of river ecological environment conservation and restoration technology, and accelerate the river ecological management of precision, fine, systematic transformation, which provides effectively technical support to guarantee the sustainability of river ecosystem and land ecological security, and achieves the ecological civilization goal of harmonious coexistence of man and nature. Between 2016 and 2021, 296 patents relevant to this research front were registered. These patents received 1 273 citations, with an average of 4.30 citations per patent.

(3)   Modeling and optimization of urban building energy consumption and carbon emission

Modeling and optimization of urban building energy consumption and carbon emission is to establish physics- based models of energy consumption of buildings, and optimize design and operation of buildings through quantitative analyses of the impact of different factors on energy consumption and carbon emission of buildings. It is a key technical means to achieve energy saving and emission reduction in field of building engineering. The main topics of this front include: ① buildings’ big data acquisition and digital city construction, which facilitates digital collection of building information and establishment of digital cities; ② automatic modeling of energy consumption of buildings at regional scale, which enables rapid modeling and automatic model calibration based on operational data; ③ regional energy system design and operation optimization, which supports intelligent response of energy consumption and power supply in buildings; ④ carbon emission prediction and optimization of urban building clusters, and analysis of the emission reduction potential brought by different energy-saving technologies. The future development trend is to upgrade the physical models of regional building energy consumption, improve regional building energy efficiency by integrating multi-disciplinary knowledge from energy-saving buildings, geographic information science, computer technology, and artificial intelligence, and help promote the carbon peaking and carbon neutrality goals. Between 2016 and 2021, 13 patents relevant to this research front were registered. These patents received 275 citations, with an average of 21.15 citations per patent.

(4)   Autonomous positioning and navigation of unmanned systems

Autonomous positioning and navigation of unmanned systems is the general term of real-time positioning, autonomous map construction and path planning method. It is one of the key technologies of autonomous mobile unmanned systems and one of the development fronts in the field of surveying and mapping engineering. There exist a wide range of application needs in autonomous mobile systems such as unmanned aerial vehicles, unmanned ships and unmanned submarines. Development trends in this front include: ① high-precision autonomous positioning technology, which determines the position and attitude of unmanned systems in the workspace by using global navigation satellite systems (GNSS), simultaneous localization and mapping (SLAM), dead reckoning, space beacon positioning and other technologies independently or in combination; ② map building technology in a dynamic environment, which is oriented to dynamic scenes, senses the surrounding spatial information through various sensors and models the environment map; ③ efficient local path planning algorithm, with which the unmanned system uses dynamic path algorithm to plan the optimal moving route according to the perceived environmental information. Between 2016 and 2021, 37 patents relevant to this research front were registered. These patents received 376 citations, with an average of 10.16 citations per patent.

(5)   Intelligent perception and prediction of multi-source information on underground engineering status

Intelligent perception and prediction of multi-source information on underground engineering status refers to sensing the characteristic indicators of the multi-factor status through various smart sensors and fusing multi-source heterogeneous data to clean and correlate the status data for a consistent interpretation of underground engineering status. Through machine learning and big data algorithms, one can comprehensively evaluate underground engineering status, quickly diagnose and accurately identify faults, and thereby realize intelligent prediction of underground engineering status. In practice, complex and dynamically changing responses of underground structures arise from highly variable geological conditions and surrounding engineering disturbances. Intelligent perception and prediction of multi- source information enables comprehensive evaluation of underground engineering operating status and supports decision making for underground engineering management.

The main subjects involved in this front include: ① the holographic perception method and technological system of sensing underground engineering status based on wireless sensing, optical fiber, electromagnetic wave, sound wave, camera, laser, etc.; ② the technologies (such as the Internet of Things, edge computing, and deep learning) in characterization, fusion, and dynamic update of multi-source heterogeneous sensing data across time, space, scale, and media to achieve consistent interpretation of underground engineering status; ③ the physics-informed machine learning algorithms (such as Bayesian and Convolutional neural networks) to establish an evolution model of underground engineering status considering the influence of time and space in an uncertain environment, and realize fast evaluation, prediction and early warning of engineering status; ④ underground digital platforms and underground engineering digital bases via BIM, city-scale urban information model (CIM), and digital twin models to realize 3D visualization feedback and update of underground engineering status. The technologies for perception and prediction of underground engineering status developed rapidly in recent years. The real-time intelligent perception and efficient prediction technology integrating multi-smart sensors has gradually become an effective means to reduce risks and avoid accidents in underground engineering. It is in the mainstream future trend of intelligent management and control of underground engineering safety. Between 2016 and 2021, 87 patents relevant to this research front were registered. These patents received 164 citations, with an average of 1.89 citations per patent.

(6) Healing materials and techniques for different service environments

Concrete deteriorates in service safety and durability due to accelerated damage and structural failure, as it is exposed to largely fluctuating temperature, strong radiation or/and severely corrosive environments in high plateau, ocean, desert or deep ground. It is vital to repair degraded parts in time to achieve long-term safety of concrete structures. At present, the development for concrete healing materials and techniques mainly involves: ① design of healing materials, such as polymer-cement based composite healing material, grouting healing material, fiber reinforced composite healing material; ② analysis of healing behavior, such as the characterization of crack healing behavior and the anti- corrosion behavior; ③ performance evaluation, such as mechanical properties, impermeability, corrosion resistance properties; and ④ simulation for predicting long-term repair of concrete. The existing healing materials and techniques suffer from the lack of intelligent healing methods, vagueness in healing behavior, destructive technique for performance evaluation, and the insufficiency of data platform and high- throughput simulation methods. Thus, the development trend of this field will revolve around intelligent repair design, in-situ nondestructive assessment, data platform construction and high-throughput operation. Between 2016 and 2021, 65 patents relevant to this research front were registered. These patents received 207 citations, with an average of 3.18 citations per patent.

(7) Intelligent monitoring and early warning for hidden defects of transportation infrastructure

Under the coupling effect of traffic loads and environmental variation, the base layer and soil foundation of transportation infrastructure are prone to internal diseases, such as cracking, void and settlement. These diseases are often unobservable directly from the surface, and they are often defined as hidden defects which are difficult to be monitored and positioned. Supported with big data and artificial intelligence, the intelligent monitoring and early warning of such hidden defects aims at accurate monitoring, rapid diagnosis, and real-time early warning of hidden defects based on the work flow of sensor monitoring, three-dimensional positioning, inversion diagnosis, health assessment, and decision making for early warning. The main topics of this front involve: ① equipment for accurate detection, three-dimensional positioning and digital sensing of hidden defects; ② analytical inversion theory and high-precision diagnosis algorithms; ③ database of typical hidden defects and cloud computing aided prediction systems; ④ platforms for health assessment and decision making for early warning. In the future, the relevant equipment may be no more multi-segment, large-scale and wired, and become intensive, light-weight and wireless. The passive detection means that heavily relies on man power could be replaced by intelligent, sensing and active means for prediction and early warning. Besides, the platforms may be transformed from the ones mechanized and processed for data collection into intelligent and automatic ones that support monitoring and early warning. Between 2016 and 2021, 18 patents relevant to this research front were registered. These patents received 85 citations, with an average of 4.72 citations per patent.

(8)  Dynamic measurement and performance enhancement of green infrastructure ecosystem services

In the context of climate change and the demanding need for improving global ecosystems, green infrastructure (GI) is considered to be one of the most important strategies to actively respond to climate change, increase carbon sinks, ensure national ecological security, and achieve sustainable development. The focus of GI development is to achieve more accurate quantification and more efficient provision of ecosystem services. GI highlights the “life supporting” functions of natural environment, forms an interconnected blue-green space network with comprehensive ecological functions, and integrates with regional landscape structures and other land uses in urban environment. GI provides provisioning ecosystem services (such as water supply), regulating ecosystem services (such as stormwater regulation, water quality regulation, air purification, soil contamination mitigation, soil and water conservation, carbon sink), supporting ecosystem services (such as supporting biodiversity) and cultural ecosystem services (such as promoting livability and providing recreational activities). In order to improve the efficiency of global ecosystem services provision, the most challenging issue is to reveal the mechanism of multi- scale coupling and multi-functional synergy of the ecosystem services provided by GI based on high-precision, all-factor, and whole-process dynamic quantification. The main topics of this front involve: ① quantitative analysis and dynamic metrics of GI ecosystem services supply; ② “space-air-ground” measurement equipment and intelligent perception system for GI ecosystem services; ③ spatiotemporal evolution and simultaneously global comparison of GI ecosystem services efficiency; ④ highly-efficient integrated technical system for GI construction. In response to climate change, increasing attention is paid to the performance and efficiency of key ecosystem services of GI, such as carbon emission reduction and carbon sink increase, stormwater regulation and storage, and water purification. Between 2016 and 2021, 62 patents relevant to this research front were registered. These patents received 110 citations, with an average of 1.77 citations per patent.

(9)  Control of algal and odor pollution in urban water supply system

Algal and odor pollution in urban water supply system refers to a series of drinking water quality problems caused by algal and odor substances in source water and water supply system, which undermine stable operation of drinking water treatment plants. Algal and odor pollution is aggravated by declining dissolved oxygen and intensified eutrophication in source water as a result of global temperature rising and accelerated urbanization. Effective control of algae and odor pollution in urban water supply system is key for health and safety of drinking water. The main topics of this front include: ① systematic ecological management and water source protection at the scale of city clusters; ② upgrading conventional treatment processes to strengthen the treatment of algae and odor pollution; ③ chemical treatment technologies based on active substances with strong oxidizing capacity (e.g., ozone catalytic oxidation, permanganate oxidation, ferrate oxidation, and photocatalysis) to achieve effective degradation of algae toxins and odor substances; ④ development of novel membranes and adsorbents based on the principles of physical separation and adsorption, such as ceramic membranes, activated carbon and bio-char; ⑤ low- cost biological treatment technologies with outstanding environmental adaptability; ⑥ intelligent monitoring- treatment system for algae and odor pollution by integrating advanced sensors, artificial intelligence, and automatic control technology. The focus of future development in this field aims at targeted source control with the support of accurate analysis and traceability of algae and odor substances, and highly automated, intelligent, low-cost, efficient, and easy- to-maintain technologies by conducting inter-disciplinary research among water treatment engineering, microbiology, chemistry, physics, and artificial intelligence. Between 2016 and 2021, 41 patents relevant to this research front were registered. These patents received 26 citations, with an average of 0.63 citations per patent.

(10)    Reliability evaluation and maintenance for bridge structures

The reliability of a bridge structure refers to the ability of the bridge structure to complete its predetermined function in face of many uncertain events and factors in planning, design, construction, management and maintenance during its life cycle. Structural reliability assessment is the process of modeling and analyzing the influence of these uncertain events and factors on structural behavior, and evaluating the life-cycle performance of structural engineering. The main technical directions include: ① uncertainty simulation of bridge construction process and behavior control of green construction process; ② uncertainty simulation of bridge completion and operation load process and maintenance of structural limit and fatigue reliability; ③ uncertainty simulation of deflagration process of bridge structure and guarantee of stability of components and structures; ④ risk scenario analysis of wind-induced catastrophic load process of cable bridge and the guarantee of structural aeroelastic stability;  ⑤ the uncertain simulation of bridge earthquake and ship impact damage process and the maintenance of structural toughness and reliability. In recent years, the development trend has paid more attention to the branch evolution analysis of the behavior mode of green bridge structure under the consideration of uncertainty factors, the evaluation of the inducement failure and reliability maintenance of the continuous failure behavior of soft bridge structure under the disaster risk events, the reliability evolution analysis and damage control of the bridge structure system. Between 2016 and 2021, 79 patents relevant to this research front were registered. These patents received 131 citations, with an average of 1.66 citations per patent.

《2.2 Interpretations for three key engineering development fronts》

2.2 Interpretations for three key engineering development fronts

2.2.1 Active prevention and control of geohazards along the Sichuan-Tibet Railway

Traditional technologies for geohazard prevention and control cannot meet the need of construction safety and efficiency in the Sichuan-Tibet Railway due to unsatisfactory results, difficult implementation during construction, low-level intelligence, and passivity. Alternatively, it has become a priority to develop active approaches to prevent and control geohazards along the Sichuan-Tibet Railway. Currently, the new generation of the information technologies represented by IoTs, big data, artificial intelligence and BIM is accelerating the advancement in civil engineering technologies characterized by new materials, new structures, and new techniques. The fusion across multiple disciplines is profoundly changing the theory and the technology for disaster prevention and mitigation. Accordingly, the way for preventing and controlling geohazards along the Sichuan- Tibet Railway changes from passive to active with an aim at comprehensive disaster prevention at full scales rather than for individual critical parts.

The core of active prevention and control of geohazards along the Sichuan-Tibet Railway is “being active”. The relevant subjects involved in this front are as follows:

1)  Quantitative risk assessment, which includes: ① data- and model-driven identification of geohazards, such as landslides, debris flows, rockfalls, earthquakes, high geo-stress rockbursts and excessive deformations, high geothermal damage, active fault dislocations, and water and mud inrush; ② quantitative and rapid assessment of geohazard risk under coupling dynamic interaction of intensive internal and external forces.

2)   Intelligent monitoring and early warning, including variable-frequency intelligent monitoring and early warning technology for geohazards, “space-sky-surface-interior” three-dimensional comprehensive intelligent monitoring and early warning technology for geohazards, artificial intelligence and decision-making technology, intelligent perception and data mining technology, and technology integration and information modelling.

3)  Advanced prevention and control, which includes: ① anti- slide piles and retaining walls, and active rockfall netting protection technology; ② debris flow blocking and drainage technology; ③ damping flexible lining, and light-weight concrete; ④ ventilation and mechanized cooling technology of high geothermal tunnels; ⑤ pressure relief blasting technology, stress release and relief technology; ⑥ layered support and active pressure yielding support technology for large-deformation tunnels; ⑦ flexible protection technology for rockbursts, and kinetic energy release technology for active fractures; ⑧ advanced pre-grouting technology for water and mud inrush, curtain grouting, and high-pressure split grouting technology.

4)  Intelligent construction, including intelligent construction technology, robot system and automation technology, modular and refined construction technology, precise control and decision-making technology.

5)  Intelligent emergency rescue, including comprehensive intelligent command system for emergency rescue, rapid recovery technology for infrastructure and grid power system, emergency escape and refuge technology, and intelligent removal technology for hidden dangers.

As listed in Table 2.1.1, 279 patents related to this topic were registered between 2016 and 2021, with each patent being cited 3.08 times on average. The three countries that registered the most patents were China, South Korea, and the USA (Table 2.2.1). Among these countries, China was at the forefront of development, contributing 91.40% of the patents. The average citation frequency of Chinese patents was 2.64. Cooperation is rare among major countries.

The five organizations that produced the most patents were Gansu Province Academy of Sciences Institute of Geological and Natural Disasters Prevention, China Institute of Geoenvironment Monitoring, Chongqing Geological Bureau of Geology and Minerals Exploration, Shandong Geological Environment Monitoring Station, and Kunming University of Science and Technology (Table 2.2.2). From the above ranking of core patent output institutions, Gansu Province Academy of Sciences Institute of Geological and Natural Disasters Prevention has focused on debris flow disaster prevention, landslide hazard assessment and stability monitoring and early warning in the Loess area; China Institute of Geoenvironment Monitoring has focused on protection measures for high level landslide debris flow disasters, monitoring and warning of regional geological disasters and cave-ins and rockfalls; Chongqing Geological Bureau of Geology and Minerals Exploration has focused on monitoring and warning of underground water, landslides, collapses, ground fractures and other disasters in mines and karst areas. Cooperation among these organizations is rare (Figure 2.2.1).

As shown in Figure 2.2.2, the future development of this front in the coming five to ten years involves quantitative risk assessment, intelligent monitoring and early warning, advanced prevention and control, intelligent construction, intelligent emergency rescue.

2.2.2 Riverway ecological environment conservation and restoration

Protecting the ecological security of territorial space is a basic national policy in many countries including China, and conserving riverway is the core artery of ecological

《Table 2.2.1》

Table 2.2.1 Countries with the greatest output of core patents on “active prevention and control technology of geohazards along the Sichuan-Tibet Railway”

No. Country Published patents Percentage of published patents/% Citations Percentage of citations/% Citations
per patent
1 China 255 91.4 674 78.37 2.64
2 South Korea 10 3.58 6 0.7 0.6
3 USA 9 3.23 163 18.95 18.11
4 Japan 2 0.72 4 0.47 2

《Table 2.2.2》

Table 2.2.2 Institutions with the greatest output of core patents on the “active prevention and control technology of geohazards along the Sichuan-Tibet Railway”

No. Institution Published patents Percentage of published patents/% Citations Percentage of citations/% Citations
per patent
1  Gansu Province Academy of Sciences Institute of Geological and Natural Disasters Prevention 29 10.39 27 3.14 0.93
2  China Institute of Geoenvironment Monitoring 21 7.53 74 8.6 3.52
3  Chongqing Geological Bureau of Geology and Minerals Exploration 15 5.38 17 1.98 1.13
4 Shandong Geological Environment Monitoring Station 14 5.02 21 2.44 1.5
5  Kunming University of Science and Technology 9 3.23 25 2.91 2.78
6 Chengdu University of Technology 7 2.51 33 3.84 4.71
7 Sichuan College of Architectural Technology 7 2.51 30 3.49 4.29
8  Gansu Geological Disaster Prevention Engineering Exploration and Design Institute 7 2.51 3 0.35 0.43
9  Shandong University 5 1.79 39 4.53 7.8
10 China Chemical Geology and Mine Bureau Shandong Geological Prospecting Institute 5 1.79 1 0.12 0.2

《Figure 2.2.1》

Figure 2.2.1 Collaboration network among major institutions in the engineering development front of “active prevention and control technology of geohazards along the Sichuan-Tibet Railway”

《Figure 2.2.2》

Figure 2.2.2 Roadmap of the engineering development front of “active prevention and control technology of geohazards along the Sichuan-Tibet Railway”

security of the life community of mountains, rivers, forests, fields, lakes, plants and sediments. The global research and practice on river ecological management dates back to 1960s, while the principle and strategy for sustainable riverway ecological conservation and restoration considering regional variation has been developed in China since 21st century by learning lessons from traditional riverway governance. Nowadays it has become an international consensus to fundamentally reversing and changing traditional modes of river development and governance that damage the health of river ecosystems. Identifying the scientific and technological frontiers in this field, and solving the bottleneck problems of river ecological governance are important supports for ensuring the ecological security of territorial space.

It is a scientific goal and a national strategic need to protect or restore the resilience of river ecosystem to facilitate the sustainable development of beautiful territorial space. The frontiers of river ecological environment conservation and restoration technology mainly focus on the following directions:

1) The intelligent integration technology of riverway monitoring, evaluation and smart collaborative watershed management system, which includes high-precision and rapid monitoring and evaluation, river ecological model construction and simulation based on big data and digital twins, water control projects and systematic collaborative technology, efficient and intelligent collaborative integration technology of watershed management.

2)  Riverway green low-carbon and naturalization restoration technology, which includes restoration technology based on hydrological rhythm and spatial heterogeneity of geomo- rphology, riverside wetland conservation and restoration technology based on green and low-carbon concept, ecological conservation and restoration technology based on three-dimensional connectivity.

3)  Riverway ecosystem function and biodiversity of conser- vation and restoration technology, which includes river habitat identification and conservation, aquatic food chain structure evaluation, food chain conservation and restoration technology, retroactive fish habitat conservation and restoration, natural simulation and efficient fish facilities construction with ecological flow precision regulation technology.

As listed in Table 2.1.1, 296 patents related to this front were registered between 2016 and 2021, with each patent being cited 4.3 times on average. The three countries that registered the most patents were China, the USA, and South Korea (Table 2.2.3). Among these countries, China was at the forefront of development, contributing 95.27% of the patents. The average citation frequency of Chinese patents was 3.91. Cooperation is rare among major countries.

The five organizations that produced the most patents were China Institute of Water Resources and Hydropower Research, Hohai University, Sinohydro Bureau 11 Co., Ltd., North China University of Water Resources and Electric Power, and Nanjing University (Table 2.2.4). From the above

《Table 2.2.3》

Table 2.2.3 Countries with the greatest output of core patents on “riverway ecological environment conservation and restoration”

No. Country Published patents Percentage of published patents/% Citations Percentage of citations/% Citations
per patent
1 China 282 95.27 1 102 86.57 3.91
2 USA 6 2.03 150 11.78 25
3 South Korea 4 1.35 4 0.31 1
4 Australia 2 0.68 5 0.39 2.5
5 India 1 0.34 10 0.79 10
6 Netherlands 1 0.34 2 0.16 2

《Table 2.2.4》

Table 2.2.4 Institutions with the greatest output of core patents on “riverway ecological environment conservation and restoration”

No. Institution Published patents Percentage of published patents/% Citations Percentage of citations/% Citations
per patent
1 China Institute of Water Resources and Hydropower Research 7 2.36 19 1.49 2.71
2 Hohai University 6 2.03 30 2.36 5
3 Sinohydro Bureau 11 Co., Ltd. 6 2.03 22 1.73 3.67
4 North China University of Water Resources and Electric Power 3 1.01 18 1.41 6
5 Nanjing University 3 1.01 14 1.1 4.67
6 China First Metallurgical Group Co., Ltd. 3 1.01 13 1.02 4.33
7 Chinese Academy of Fishery Sciences 3 1.01 9 0.71 3
8  Shandong Jianzhu University 2 0.68 30 2.36 15
9  Institute of Hydroecology, MWR & CAS 2 0.68 19 1.49 9.5
10  Research Institute of Forest Ecology Environment and Protection, Chinese Academy of Forestry 2 0.68 18 1.41 9

ranking of core patent output institutions, China Institute of Water Resources and Hydropower Research focuses on river ecological corridor and ecological slope protection, riverway habitat feature identification using remote sensing, and habitat biodiversity restoration,Hohai University focuses on the real-time diagnosis and self-restoration of riverway health, riverway ecological slope protection, ecological flow and river ecological connectivity related technical products. Cooperation among major institutions is rare.

In the next five to ten years, the key development directions involved in this front are the intelligent integration technology of riverway monitoring, evaluation and smart collaborative watershed management system, riverway green low-carbon and naturalization restoration technology, riverway ecosystem function and biodiversity of conservation and restoration technology. In terms of application, it is expected that the intelligent integration technology of riverway monitoring, evaluation and smart collaborative watershed management system will gradually reach maturity by 2027, and achieve large-scale applications afterwards. It is expected that riverway green low-carbon and naturalization restoration technology and riverway ecosystem function and biodiversity of conservation and restoration technology will be advanced from concept design to technology development until 2030, and receive large- scale applications afterwards (Figure 2.2.3).

《Figure 2.2.3》

Figure 2.2.3 Roadmap of the engineering development front of “riverway ecological environment conservation and restoration”

2.2.3 Modeling and optimization of urban building energy consumption and carbon emission

Energy saving and emission reduction in buildings is crucial to achieve the carbon peaking and carbon neutrality goals. Modeling and optimization of urban building energy consumption and carbon emission is to establish physically- based models of energy consumption of buildings, and optimize design and operation of buildings through quantitative analyses of the impact of different factors on energy consumption and carbon emission of buildings. The ultimate goal of this development front is to achieve energy saving and emission reduction at urban scale, promote green, low-carbon and high-quality regional development, and technically support government to formulate policies and measures for energy saving and emission reduction. The current regional scale simulation is characterized by massive input data, complex model, and intensive computation. Thus, automation in model generation, light-weight model, “one model for multiple uses”, and new energy systems (such as electric vehicles, photovoltaic, energy storage, and microgrid) are the hot issues in this front.

The main topics involved in this front include the following:

1)  Buildings big data acquisition and digital city construction. The relevant work is intended to ① acquire image data through remote sensing from unmanned aerial vehicle (UAV), satellite images, or street view images, ② automatically extract building information (e.g., building geometry, building type, and construction age) from the image data in combination with GIS-based buildings big data (e.g., city information points and building outlines) by using artificial intelligence technologies such as machine learning, deep learning, and computer vision, and ③ ultimately establish a digital twin city.

2)  Automatic modeling of energy consumption of buildings at regional scale. Regional building energy consumption and carbon emission models are automatically generated from based on the extracted building information and relevant standards with GIS and building energy simulation tools for rapid modeling at regional scale and automating model calibration with actual measurement data.

3)  Regional energy system design and operation optimization. The energy demand of building groups is obtained through building regional energy consumption simulation, and optimization is made in the design of photovoltaic power generation system, energy storage system, electric vehicle charging and discharging system, and combined heat and power supply system. Ultimately, building energy consumption regulation is optimized according to electrovalence and demand response to achieve intelligent response and intelligent matching of building energy consumption and power supply.

4)   Carbon emission prediction and optimization of urban building clusters. Regional building operation carbon emissions is calculated based on building energy consumption simulation and carbon emission factor database, and meanwhile the emission reduction potential brought by different energy-saving technologies is analyzed.

As listed in Table 2.1.1, 13 patents related to this front were registered between 2016 and 2021, with each patent being cited 21.15 times on average. The three countries that registered the most patents were China, the USA, and South Korea (Table 2.2.5). Among these countries, China was at the forefront of development, contributing 61.54% of the patents. Cooperation is rare among major countries.

The five institutions that produced the most patents were Southeast University, Xi’an University of Architecture and Technology, Anguleris Technologies Limited Liability Company, Cenergistic Incorporation, and Johnson Controls Technology Company (Table 2.2.6). Cooperation is rare among major institutions.

The development frontier of the “modeling and optimization of urban building energy consumption and carbon emission” for the next 5–10 years are: building big data acquisition and digital city construction, automated urban building energy modeling, community scale energy system design and operation optimization, and carbon emission prediction and optimization of urban buildings. To be more specific, on the data side, the research and application frontiers are twofold. First, how to introduce new data sources such as drone-aided remote sensing, satellite image, street view into building energy modeling and how to extract useful information from those new data sources using rapid evolving technologies such as deep learning, computer vision etc. Second, how to

《Table 2.2.5》

Table 2.2.5 Countries with the greatest output of core patents on “modeling and optimization of urban building energy consumption and carbon emission”

No. Country Published patents Percentage of published patents/% Citations Percentage of citations/% Citations
per patent
1 China 8 61.54 48 17.45 6
2 USA 4 30.77 227 82.55 56.75
3 South Korea 1 7.69 0 0 0

《Table 2.2.6》

Table 2.2.6 Institutions with the greatest output of core patents on “modeling and optimization of urban building energy consumption and carbon emission”

No. Institution Published patents Percentage of published patents/% Citations Percentage of citations/% Citations
per patent
1 Southeast University 3 23.08 5 1.82 1.67
2 Xi’an University of Architecture and Technology 2 15.38 2 0.73 1
3 Anguleris Technologies Limited Liability Company 1 7.69 107 38.91 107
4 Cenergistic Incorporation 1 7.69 61 22.18 61
5  Johnson Controls Technology Company 1 7.69 58 21.09 58
6 Jiangsu Emap Geographic Information Technology Company Limited 1 7.69 32 11.64 32
7 Harbin Institute of Technology 1 7.69 9 3.27 9
8  Research Foundation of the City University of New York 1 7.69 1 0.36 1
9  Beijing Institute of Technology 1 7.69 0 0 0
10  Korea Advanced Institute of Science and Technology 1 7.69 0 0 0

better leverage data from multiple sources for data fusion and calibration. The research frontier of modeling is how to automate the model development and calibration process. In terms of optimization, the frontiers are twofold. First, how to leverage BIM technology to co-optimize the energy system design and operation. Second, how to more efficiently integrate the electrical vehicle, and distributed renewable generations into building energy system. As for the carbon emission reduction, the emerging trend is how to accurately audit and predict carbon emission from building energy consumption at the urban scale, based on which to design a feasible and effective roadmap to achieve carbon peaking and carbon neutrality goal. For details, please refer to the Figure 2.2.4.

《Figure 2.2.4》

Figure 2.2.4 Roadmap of the engineering development front of “modeling and optimization of urban building energy consumption and carbon emission”

 

 

 

 

Participants of the Field Group

Leaders

CUI Junzhi, ZHANG Jianyun, GU Xianglin

Members of the expert group

Academicians

CUI Junzhi, OU Jinping, YANG Yongbin, ZHANG Jianyun, LIU Jiaping1, MIAO Changwen, LI Jiancheng, DU Yanliang, GUO Renzhong, HU

Chunhong, PENG Yongzhen, ZHENG Jianlong, WANG Fuming, ZHANG Jianmin, WU Zhiqiang, YUE Qingrui, LYU Xilin, CHEN Jun, MA Jun,

FENG Xiating, ZHU Hehua, DU Xiuli, LIU Jiaping2

Experts

AI Jianliang, CAI Chunsheng, CAI Yi, CAI Yongli, CHEN Jun, CHEN Peng, CHEN Qing, CHEN Qiuwen, CHEN Xin, CHEN Yanling, CHEN Yiyi,

CHEN Yonggui, CHENG Yuning, DONG Biqin, DONG Wei, FAN Jiansheng, FAN Lingyun, FENG Dianlei, GAO Liang, GE Yaojun, GONG Jian,

GU Chongshi, GUO Jinsong, GUO Ronghuan, HAN Jie, HE Pengfei, HE Ruimin, HUANG Jiesheng, HUANG Tinglin, HUANG Yaping, JIA

Liangjiu, JIANG Jinyang, JIANG Zhengwu, JIN Junliang, LI Angui, LI Chen, LI Jianbin, LI Xiangfeng, LI Zhengrong, LI Zhigang, LIN Borong,

LING Jianming, LIU Chao, LIU Cuishan, LIU Fang, LIU Jing, LIU Renyi, LIU Shuguang, LIU Tingxi, NIU Xinyi, PANG Lei, QIAN Feng, REN

Weixin, SHAO Yisheng, SHI Tiemao, SHI Xing, SHI Peiling, SHI Caijun, SHU Zhangkang, SUN Jian, SUN Lijun, SUN Zhi, TAN Yiqiu, TIAN Li,

TONG Xiaohua, WANG Fang, WANG Jieqiong, WANG Shuangjie, WANG Aijie, WANG Benjin, WANG Fazhou, WANG Huaning, WANG

Jianhua, WANG Wei, WANG Yayi, WANG Yuanzhan, WANG Zhiwei, WU Faquan, XIA Shengyi, XIAO Feipeng, XIAO Yiqiang, XIE Hui, XU Bin,

XU Feng, XU Xiangdong, YAN Jinxiu, YANG Dawen, YANG Junyan, YANG Liu, YANG Qingshan, YANG Ting, YANG Zhongxuan, YAO Junlan,

YE Wei, YE Yu, YU Haitao, YUAN Feng, ZHANG Chen, ZHANG Feng, ZHANG Xu, ZHAO Miaoxi, ZHEN Feng, ZHENG Bailin, ZHENG Gang,

ZHONG Zhen, ZHOU Suhong, ZHOU Xiang, ZHOU Zhengzheng, ZHU Neng, ZHU Xingyi, ZHUANG Xiaoying, ZHUO Jian

Report writers

DU Yanliang, ZHENG Jianlong, MA Jun, CAI Yongli, CHEN Peng, CHEN Yixing, DONG Biqin, HAO Luoxi, JIA Liangjiu, JIN Junliang, LI Jianhua,

LIN Borong, LING Jianming, LIU Fang, LIU Song, LIU Wanzeng, PENG Wanting, SUN Zhi, WANG Jieqiong, WANG Benjin, WANG Zhe,

Warren Julian, WU Chengzhao, WU Wei, XIANG Yan, YAN Qixiang, YANG Changwei, YANG Junyan, YAO Junlan, YE Yu, ZHANG Chen,

ZHANG Dongming, ZHAO Yong, ZHOU Zhengzheng

1 Xi’an University of Architecture and Technology

2 Southeast University