《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 ten most-researched engineering topics in the field of mechanical and vehicle engineering (hereafter referred to as mechanical field) include mechanical, transportation, ship and marine engineering; weapon science and technology; aeronautical and astronautical science and technology, and power and electrical equipment engineering and technology (as listed in Table 1.1.1). Among these, “high-energy density solid-state lithium batteries,” “drag/heat reduction in supersonic flow,” “high-performance nano-biosensors,” “information security and privacy protection in the Internet of Vehicles (IoV),” “self-adaptive target capture by tethered space robots,” and “hybrid power systems with renewable energy and fuel cells” are extensively studied traditional topics. “Intelligent manufacturing based on the industrial Internet of Things (IIoT),” “cooperative control of multirobot systems,” “integration of design and manufacturing based on topology optimization and additive manufacturing,” and “resource scheduling and risk assessment of smart grids” are considered as emerging topics. The annual publication of papers during the years 2013–2018 is listed in Table 1.1.2.

“Hybrid power systems with renewable energy and fuel cells” and “cooperative control of multirobot systems” are the most rapidly growing topics in terms of paper publications in recent years.

(1)  Intelligent manufacturing based on the industrial IIoT

The IIoT can achieve rational allocation of manufacturing resources, on-demand execution and continuous optimization of manufacturing processes, and rapid adaptation of manufacturing environments through network interconnections, data exchange, and system interoperation of manufacturing systems. As a result, intelligent manufacturing systems driven by innovative manufacturing services are developed. Relevant studies are currently categorized in three main areas: 1) intellisense (i.e., intelligent perception) and iterative optimization of smart products in their entire life cycle that includes the perception and handling of large amounts of data in the industrial value chains of design, production, logistics, sales, and services; 2) universal interconnection and accurate control of manufacturing systems that include sensing devices, distributed control systems, manufacturing execution systems, enterprise resource planning systems, and supply chain management systems at the equipment, control, shop floor, enterprise, and enterprise collaboration layers; 3) modeling, simulation, and real-time analysis of intelligent functions of manufacturing systems including entity coordination, system

《Table 1.1.1》

Table 1.1.1 Top 10 engineering research fronts in mechanical and vehicle engineering

《Table 1.1.2》

Table 1.1.2 Annual number of core papers published for the top 10 engineering research fronts in mechanical and vehicle engineering

integration, information fusion, and new business patterns such as customization and predictive maintenance of smart products. Research in these areas faces the challenges of the complexity and diversity of interconnection technologies and protocols, a wide range of applications, numerous hidden issues of cyber security and data safety. Therefore, new 5G mobile networks, human–cyber–physical systems (HCPSs), software-defined networks, edge computing, digital twins, and so on have emerged as frontiers in the research and development trends of intelligent manufacturing based on the industrial Internet of Things.

(2) High-energy density solid-state lithium batteries

Liquid-state lithium batteries are in widespread use, but they have already reached their theoretical or engineering limits in the key metrics of energy density and safety. Therefore, new methods of energy storage must be developed to satisfy future needs. Solid-state batteries use solid instead of liquid electrolytes containing small organic molecules. Thus, these batteries possess advantages over liquid batteries in terms of energy density, safety, and life cycle and are believed to be the next-generation electrochemical power sources. Surface/interface mass transfer, key materials compatibility, low interfacial impedance technology, evolution mechanism during the entire life cycle, and other frontier science challenges are mainly addressed in the emerging technology of solid-state batteries. In future, in situ analysis and characterization techniques will be developed for interface impedance problems such as the following. 1) Matching of key materials with high specific energy include cathode materials with high capacity/high voltage, high- performance solid electrolytes, and high capacity lithium anodes with high capacity metals. These challenges require considerable attention at present. 2) Preparation techniques for low impedance micro-interfaces that include design and material matching are vital for mass production. 3) The attenuation in the battery performance and the evolutionary route of the materials in the system during the entire life cycle are key factors in the assessment and prediction of health status of solid-state batteries. Further development of solid- state metal–air batteries based on solid electrolytes with long lifetimes will become the ultimate goal of research on electrochemical power components.

(3) Drag/heat reduction in supersonic flow

Drag/heat reduction in supersonic flow studies the flow of gas or plasma on solid surfaces with a relative speed above Mach 3. Such a supersonic flow occurs in nozzles on hypersonic vehicles, around spacecrafts re-entering the atmosphere, and in high-altitude, high-speed scouting planes or nozzle internal flow in jet engines. Strong aerodynamic heating, air ionization, impact waves, burning, and other problems accompany such rapid motion. Theoretically, problems in plasma flow, impact wave, rarefied air dynamics, and heat transfer under complex flow can be barely simulated through the currently applied Navier–Stokes equation-based numerical simulation method. The direct Monte Carlo simulation and Fokker–Planck equation methods must be improved. Real experimental methods should further develop sensors that are resistant to the high temperatures and impact forces found in supersonic systems and wind tunnels. Drag/heat reduction techniques under investigation include the use of needles, reverse and internal jets, plasma boundary layer control, laser energy deposition, bottomward direction of aircraft exhaust, sacrificial surface layers for ablation, and internal insulation at the front end of an aircraft. The manufacture of jet orifices and gas supply systems, experimental techniques, and numerical simulation techniques for complex curved surfaces should have increased capabilities.

(4)  Cooperative control of multirobot systems

As the cross development in artificial intelligence (AI), automation, and computer science, the interactions of multiple robots have become an important subject of study in engineering control. Communication, coordination, scheduling, cooperation, and control among robots have all been studied, and highly coordinated collective dynamic actions have been observed; multirobot cooperation can be applied to accomplishing substantial complex work that no single robot can complete. Multirobot control methods are known to be robust and can reliably solve actual problems. Traditional multirobot production systems employ a centralized control structure and ignore the possibility of cooperative behavior. Such systems cannot adjust to production patterns involving small quantities and numerous varieties of products, and lack smart manufacturing ability. As the manufacturing industry develops toward ever larger and more complex operations, there is a pressing need for cooperative multirobot systems with improved compliance, consistency, and optimization performance.

(5)  High-performance nano-biosensors

Nano-biosensors are very important for modern biotechnology. The trend in this area is toward small, portable, fast, highly sensitive, integrated, and inexpensive devices. High- performance nano-biosensors of current interest include immunosensors, surface plasma resonance biosensors, mycotoxin ultratrace sensors, and tumor biomarker sensors. Ultratrace and highly selective nano-biosensors are an imminent requirement because conventional biosensors lack sensitivity and selectivity in the detection of mycotoxins and tumor cells. Such devices, based on novel biocompatible nanomaterials such as metal sulfide quantum dots, nanocomposites, graphene oxide, and two-dimensional nanomaterials, could greatly improve the sensitivity, response rate, and selectivity of biosensors, and is likely to become a dominant research topic in the field.

(6)  Information security and privacy protection in the IoV

The IoV is a new intelligent system that integrates wireless communication technology into the modern automobile industry. It incorporates advanced technologies, such as big data, cloud computing, and AI, substantially contributing to road planning, resource scheduling, and traffic improvement. However, because of its large network scale, open communication environment, and predictable mobile track, the IoV is extremely vulnerable to attacks, system crashes, and privacy leaks. Safeguarding the IoV is therefore a major goal of academics and automotive industry researchers. Proposed secure communication methods, such as aggregate signatures and periodic certificate ignoring, have improved verification and communication efficiency, which can solve the problem of the high communication overhead of digital signature communication based on Public Key Infrastructure (PKI). Privacy protection proposals such as anonymous authentication, shared certificates, and group signatures can reduce the number of vehicles using unique certificates, thereby enhancing user privacy. Location privacy protection schemes such as k-anonymity, mixed zones, and group navigation can prevent the location server from knowing the actual place from which a location request originates. Such research can effectively improve the communication efficiency and safety of the IoV. However, as driverless technology rapidly develops, the IoV will face an increasingly complex network environment and ever greater data-processing demands. IoV information security and privacy protection will be a long and arduous task.

(7)    Integration of design and manufacturing based on topology optimization and additive manufacturing

Both topology optimization and additive manufacturing are major innovations in design and manufacturing. The integration of the two has become a leading priority in the development of China’s high-end equipment industry. Currently, it is mostly implemented by a serial method that attempts to fabricate the optimized designs through additive manufacturing. Research on more sophisticated topology optimization methods for additive manufacturing remains limited. On the one hand, many additive manufacturing components must still meet the requirements of traditional processes, such as casting, sheet metal, and machining. Consequently, the advantages and potentials of additive manufacturing are difficult to maximize. On the other hand, existing topology optimization methods do not consider the design of the structure from the perspective of multi- material, multi-scale, and multi-component integration, and the special constraints of the additive manufacturing process are hardly considered at all. Such circumstances inevitably result in structural performance being sacrificed, given the current serial mode of design and manufacturing. Although existing research has achieved initial results, it cannot reveal its design principles from the depth of material–structure– process integration. Structural models of mechanical behavior, influencing mechanisms of process constraints, topology optimization design with a complex overall structure, design tool development, and material applications of additive manufacturing constitute a bottleneck for additive manufacturing and structural innovation design.

(8) Self-adaptive target capture by tethered space robots

As human activity in space increases, the number of lost or retired spacecraft and the amount of orbital debris increase as well. The use of robots to remove unwanted materials in space is thus gradually becoming a prevalent research topic in the aerospace industry. Tethered robots are an effective solution for capturing and dragging large targets with complex motion, but they can easily collide, oscillate, or roll in microgravity or vacuum environments. Tethered space-robot technology requires advances in attitude measurement techniques and coordinated control systems based on vision. Collision analysis, real-time dynamics, and control design should be improved to ensure the reliability of tethered space robots in the target-capture process.

(9) Hybrid power systems with renewable energy and fuel cells

Internal combustion vehicles bring people convenience and comfort, but also cause serious environmental pollution and consume fossil fuels. Almost all countries are therefore researching green and renewable energy. Hybrid power systems based on renewable energy and fuel cells have become attractive particularly to the automotive industry due to their lack of emissions. Hybrid systems also have high power density, high stability, and a wide range of operating temperature. These advantages make them preferred power sources for solving energy and environmental problems in the future. Currently, the main and auxiliary energy sources are commonly used to simultaneously supply energy to the multi- energy power system structure. Research on the structure and optimization of hybrid systems, and selection of reasonable control strategies for the proper distribution of power between the various energy sources, are the core issues of current hybrid power system research, which is complicated by the diversity of hybrid power systems, the complexity of their control systems, and their weak dynamic performance.

(10) Resource scheduling and risk assessment for smart grids

Smart grids are grids of a new type closely integrating modern sensing, communication, information, and control technologies into the traditional framework. Seamless connection and real-time interaction between the elements of a smart grid can be ensured through the application of distributed intelligence, broadband communication, and automatic control, resulting in a more reliable, safer, cheaper, and more environmentally friendly grid. The keys to building a smart grid are the establishment of a strong and flexible grid structure, access to renewable and distributed energy, integration of open power–information communication systems, and construction of an efficient network of emergency centers. Because the scale of power systems is continually expanding, the risks of grid operation are increasing, and resource scheduling tasks are becoming increasingly complicated and arduous. Thus the development of new resource-scheduling and risk-assessment methods for smart grids is necessary to improve the flexibility, security, and reliability of power systems.

《1.2 Interpretations for three key engineering research fronts》

1.2 Interpretations for three key engineering research fronts

1.2.1 Intelligent manufacturing based on the IIoT

We are currently in an era of intense global competition, sometimes called a new industrial revolution. In the national development strategies of many countries, including German Industry 4.0, American Advanced Manufacturing, Made in China 2025, British Industry 2050, and the Japan Revitalization Strategy, intelligent manufacturing is ranked as an important direction for the future development of industry. Research on the IIoT, a crucial enabling technology for intelligent manufacturing, has become widespread. This includes research on the interconnection of entities in the manufacturing field; information modeling and fusion; innovative application modes; and optimization of manufacturing resources allocation. Current research and development in intelligent manufacturing based on the IIoT proceeds in three dimensions (life cycle, system level, and intelligence) and six directions (intellisense, ubiquitous connectivity, precision control, digital modeling, real-time analysis, and iterative optimization).

The life cycle dimension includes the application of the IIoT to chained sets of interrelated activities (such as design, production, logistics, sales, and services) that focus on collaboration and interconnection between enterprises. The system level dimension focuses on the application of the IIoT at the equipment, control, shop floor, enterprise, and supply chain coordination levels, that is, on interconnections mostly within a single enterprise. The intelligence dimension concentrates on entity collaboration, system integration, information fusion, and emerging business patterns including the transformation from manufacturing to services and product predictive maintenance. Intellisense research explores the effective use of sensors, including radio- frequency identification (RFID) systems, as a means to obtain information on different aspects of a product’s life cycle. Ubiquitous connectivity research investigates methods of interconnecting machines with each other, with people, and with the environment. Digital modeling studies the mapping of manufacturing resources to digital spaces, including the abstract modeling of the full elements of the production. Real-time analysis studies visualization and conducts visual analysis of manufacturing resource data, exploring the intrinsic link between industrial resource states in virtual and real spaces. Precision control studies the precise information interaction and seamless cooperation of manufacturing resources in the IIoT. Iterative optimization studies self- learning and improvement methods, and explores the optimal configuration of manufacturing resources, processes, and environments in the IIoT.

Although some important progress has been made in the three dimensions and six directions of intelligent manufacturing research based on the Internet of Things, such research faces the usual problems posed by the complexity and diversity of interconnected technologies and protocols, different depths and widths of applications, cyber security and data safety, as well as other issues. In recent years, HCPS, new 5G mobile networks, software-defined networks, edge computing, and digital twins have attracted a lot of attention. Ternary systems and frameworks, large-bandwidth communication, low latency and superior connection, automated and programmable networks, device-side edge computing, and virtual digital and physical device spaces mapping are all important topics in this field.

The four countries/regions producing the most core papers in intelligent manufacturing based on the IIoT are China (7), Germany (6), Sweden (6), and Italy (6). The three countries/ regions with the greatest average number of citations are Germany (38), Brazil (28), and France (23.75), as shown in Table 1.2.1. Among the 10 countries/regions with the most core papers, substantial collaboration is initiated between China, Switzerland, and Sweden, as shown in Figure 1.2.1. The four institutions with the most core papers are ABB Corporate Research Center (4), Beijing University of Posts and Telecommunications (3), Tsinghua University (3), and University of Padua (3). The three institutions with the highest average number of citations are Asea Brown Boveri Corporate Research Center (34), Cisco Systems (34), and Center Communication Systems Research (34), as shown in Table 1.2.2. Among the ten institutions with the most core papers, substantial collaboration is initiated between the ABB Corporate Research Center, Beijing University of Posts and Telecommunications, and Tsinghua University, as shown in Figure 1.2.2. The three countries or regions with the most citing papers are China (71), Italy (61), and the USA (52), as shown in Table 1.2.3. The institutions with the greatest number of citing papers are ABB Corporate Research Center (12), National Research Council (Italy) (11), Federal University of Santa Catarina (7), and University of Padua (7), as shown in Table 1.2.4.

1.2.2 High-energy density solid-state lithium batteries

Liquid electrolyte lithium batteries, limited by material and device structure constraints, have reached their theoretical engineering limits for several key indicators, including energy density, safety, and cycle life. Further improvements in materials or processes cannot easily be translated into major improvements in performance. Therefore, new energy-storage materials and matching device structures must be developed to meet the future need for high specific energy. Liquid electrolyte batteries use a small-molecule organic solvent, which is flammable and easily degraded, initiating a series of chain reactions that reduce battery performance. Solid-state batteries use solid electrolytes instead of liquid, and possess potential advantages in energy density, safety, and cycle life.

《Table 1.2.1》

Table 1.2.1 Countries or regions with the greatest output of core papers on “intelligent manufacturing based on the IIoT

《Table 1.2.2》

Table 1.2.2 Institutions with the greatest output of core papers on “intelligent manufacturing based on the IIoT”

《Figure 1.2.1》

Figure 1.2.1  Collaboration network among major countries  or regions in the engineering research front of “intelligent manufacturing based on the IIoT”

《Figure 1.2.2》

Figure 1.2.2 Collaboration network among major institutions in the engineering research front of “intelligent manufacturing based on the IIoT”

《Table 1.2.3》

Table 1.2.3 Countries or regions with the greatest output of citing papers on “intelligent manufacturing based on the IIoT”

《Table 1.2.4》

Table 1.2.4 Institutions with the greatest output of citing papers on “intelligent manufacturing based on the IIoT”

By matching the high-voltage positive electrodes and selecting compact structure modes, they effectively avoid the side reactions caused by small organic molecules. Therefore, solid- state batteries are believed to be the most promising generation of high-specific-energy electrochemical power sources.

Despite the great advantages that solid-state batteries potentially afford, several major challenges hinder their adoption for large-scale usage. The first is that of exploring a practical high-performance solid electrolyte exhibiting high ionic conductivity under the condition of various rates and establishing suitable manufactory processes to avoid damaging the desired interface microstructures. Materials genomics, which uses cutting-edge technology such as AI and machine learning to discover and optimize new materials, provides a more efficient way to design and develop high-performance solid electrolyte materials than the traditional trial-and-error method. This emerging approach will undoubtedly accelerate the evolution of solid- state batteries. Another challenge involves material-matched preparation technology and techniques that are based on surface/interface mass transfer and interface impedance. Material systems and structural processes certainly need to be changed systematically to match the changing manufacturing processes. Integrated roll-to-roll preparation is currently considered a promising direction for research. Another bottleneck is that the performance life cycle of solid-state batteries remains unclear. Life cycle monitoring can take as long as ten years; understanding changes in performance over such a long time is very challenging. Big data analysis, including AI and deep learning, will be required to address the performance attenuation of batteries over their entire life cycle.

Solid-state batteries can meet the need for high energy density to a certain extent, but the ultimate goal of research on electrochemical power devices is to match that of conventional fuels. Metal–air batteries based on solid electrolyte materials can, in theory, come close to achieving this, with specific energy densities near 11 430 W·h/kg. Such batteries are currently the focus of intense research and development, but there are serious challenges yet to be overcome on ways to deal with side effects caused by air anodes, stabilization of metal cathodes, and improvement in cyclic performance. Important science and engineering topics will involve research on catalytic mechanisms, structural design, and module packing and power management. In the future, research will give way to development, and the focus will shift to material systems, engineering, and processes.

The four countries or regions that have produced the most core papers on high-energy density solid-state lithium battery engineering are India (20), Slovenia (5), the USA (2), and Hungary (2). The countries or regions producing the highest average number of citations are Slovenia (39.2), India (30.35), and the USA (28), as shown in Table 1.2.5. There is extensive research cooperation between India and Hungary, as shown in Figure 1.2.3. The institutions with the most core papers are Institute of Chemical Technology (17), University of Ljubljana (5), and Jozef Stefan Institute (3). The institutions with the highest average citation numbers are Jozef Stefan International Postgraduate School (55.5), Jozef Stefan Institute (49.67), and University of Ljubljana (39.2), as shown in Table 1.2.6. More cooperation transpires between the University of Ljubljana, the Jozef Stefan Institute, and the Jozef Stefan International Postgraduate School than with other institutions, as shown in Figure 1.2.4.

The countries or regions with the most citing papers are China (113), India (100), Malaysia (30), and Italy (30), as shown in Table 1.2.7. The institutions that have produced the most citing papers are Institute of Chemical Technology (50), University of Ljubljana (16), Chinese Academy of Sciences (13), and University of Malaya (13), as shown in Table 1.2.8.

《Table 1.2.5》

Table 1.2.5 Countries or regions with the greatest output of core papers on “high-energy density solid-state lithium batteries”

《Table 1.2.6》

Table 1.2.6 Institutions with the greatest output of core papers on “high-energy density solid-state lithium batteries”

《Figure 1.2.3》

Figure 1.2.3 Collaboration network among major countries or regions in the engineering research front of “high-energy density solid-state lithium batteries”

《Figure 1.2.4》

Figure 1.2.4 Collaboration network among major institutions in the engineering research front of “high-energy density solid-state lithium batteries”

《Table 1.2.7》

Table 1.2.7 Countries or regions with the greatest output of citing papers on “high-energy density solid-state lithium batteries”

《Table 1.2.8》

Table 1.2.8 Institutions with the greatest output of citing papers on “high-energy density solid-state lithium batteries”

1.2.3 Drag/heat reduction in supersonic flow

At present, most of the problems in supersonic flow are theoretically studied by numerical simulations based on the Navier–Stokes equations. The Monte Carlo direct simulation method and the Fokker–Planck equation, which can simulate thin air conditions, shock waves, and plasma, are rarely used, due to a lack of sophisticated software. Existing hypersonic wind tunnels can be used to perform experiments in this area, and provide mature noncontact testing techniques. However, the lack of sensors that can withstand temperatures of 1000 °C and high impact forces leads to difficulties in effectively contact testing many heat flow and heat transfer details. Research on high-temperature-resistant sensors based on silicon nitride, sapphire, platinum alloys, and other materials is expected to solve such problems, although substantial requirements will still be placed on the insulation and refrigeration technologies of sensing systems.

When hypersonic vehicles and spacecraft re-enter the atmosphere, the airflow can reach speeds in excess of Mach 6 and be accompanied by strong aerodynamic heating, air ionization, and aerodynamic load. Moreover, the air is thin at high altitudes and in near-earth space. Therefore, using the Navier–Stokes equations for numerical simulations is inherently difficult. The once-promising idea of adding a needle to the front end of the hypersonic aircraft has largely been abandoned because of the ease of ablation. At present, heat insulation for a spacecraft is mainly achieved by optimizing the aerodynamic shape, preparing a sacrificial layer on the outer surface that will be lost to ablation, and preparing a heat insulation layer on the inner surface. Research has been conducted on drag reduction (or even incidental heat reduction) achievable by the use of reverse jets, plasma boundary-layer control, laser energy deposition, and direction of aircraft exhaust at the bottom of an aircraft.

For high-altitude and high-speed scouting planes, the airflow speed is generally between Mach 2.5 and 6 that leads to strong aerodynamic heating, but generally not to an extensive ionization of the air. These planes ordinarily fly at altitudes of less than 30 000 m in an environment satisfying the conditions of a continuous medium, and therefore they can be analyzed by numerical simulation methods based on the Navier–Stokes equations. The drag can be reduced by adding a needle at the front end of the aircraft, and the heat can be reduced by preparing an insulating layer on the inner surface.

When the problem of nozzle internal flow occurs in jet engines, especially in turbojets and ramjets, the airflow velocity after nozzle expansion is generally above Mach 2.5, and the temperature is often above 1400 °C so that the air is largely a plasma, and the heat exchange is intense. Theoretical analysis based on the Fokker–Planck equation is needed in these circumstances. Research addressing this situation has mainly focused on heat reduction, whether by an ablation sacrificial layer on the outer surface, thermal insulation on the inner surface, or thermally protective jet flow in the boundary layer. A few studies have also explored drag reduction and improvements in engine efficiency, using surface microstructures and jet flow control.

The countries or regions producing the most core papers in engineering development focusing on drag/heat reduction in supersonic flow are China (34), Iran (10), the UK (3), and Azerbaijan (3). The countries or regions with the greatest average number of citations are Iran (29.5), Australia (20), and China (19.15), as shown in Table 1.2.9. Among the top 10 countries or regions, China, the UK, and Azerbaijan display the most cooperation, as shown in Figure 1.2.5. The institutions producing the most core papers are National University of Defence Technology (29), Babol University of Technology (5), and Islamic Azad University (5). The institutions with the highest average number of citations are Babol University of Technology (40), Islamic Azad University (35.8), and Isfahan University of Technology (35.5), as shown in Table 1.2.10. Among the top 10 institutions, Islamic Azad University and Babol Noshirvani University of Technology display the most cooperation, as shown in Figure 1.2.6. The countries or regions with the most citing papers are China (174), Iran (36), and India (22), as shown in Table 1.2.11. The institutions producing the most citing papers are National University of Defence Technology (89), Harbin Institute of Technology (27), and Khazar University (15), as shown in Table 1.2.12.

《Table 1.2.9》

Table 1.2.9 Countries or regions with the greatest output of core papers on “drag/heat reduction in supersonic flow”

《Table 1.2.10》

Table 1.2.10 Institutions with the greatest output of core papers on “drag/heat reduction in supersonic flow”

《Figure 1.2.5》

Figure 1.2.5 Collaboration network among major countries or regions in the engineering research front of “drag/heat reduction in supersonic flow”

《Figure 1.2.6》

Figure 1.2.6 Collaboration network among major institutions  in the engineering research front of “drag/heat reduction in supersonic flow”

《Table 1.2.11》

Table 1.2.11 Countries or regions with the greatest output of citing papers on “drag/heat reduction in supersonic flow”

《Table 1.2.12》

Table 1.2.12 Institutions with the greatest output of citing papers on “drag/heat reduction in supersonic flow”

《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

In the previous section, we examined the top ten engineering research fronts in mechanical engineering (broadly defined). In this section, we will examine the top ten development (as opposed to research) fronts in the field (Table 2.1.1). Six of these fronts are characterized by in-depth traditional research: “propulsion systems for near-space hypersonic vehicles,” “design and manufacturing technology of high-efficiency gas turbine engines,” “wave-energy power generation and collection,” “novel high-efficiency hydrogen fuel cells,” “marine electric propulsion systems,” and “development and application of electromagnetic stealth metamaterials for aircraft”. There are also four other fronts that are newly emerging: “human–computer interaction systems based on deep learning,” “3D bio-printing technology,” “visual sensing and recognition for driverless vehicles, and “interception of unmanned aerial vehicles (UAVs).” Table 2.1.2 shows the annual number of core patents published from 2013 to 2018. “Human–computer interaction systems based on deep learning” and “visual sensing and recognition for driverless vehicles” are the most significant directions of patent disclosure in recent years.

(1) Propulsion systems for near-space hypersonic vehicles

A near-space hypersonic vehicle is a high-speed aircraft that is intended to be flown mainly at altitudes in the range of 20–100 km and at speeds above Mach 5. In addition, this

《Table 2.1.1》

Table 2.1.1 Top 10 engineering development fronts in mechanical and vehicle engineering

《Table 2.1.2》

Table 2.1.2 Annual number of core patents published for the top 10 engineering development fronts in mechanical and vehicle engineering