Intelligent manufacturing is a general concept that is under continuous development. It can be categorized into three basic paradigms: digital manufacturing, digital-networked manufacturing, and newgeneration intelligent manufacturing. New-generation intelligent manufacturing represents an indepth integration of new-generation artificial intelligence (AI) technology and advanced manufacturing technology. It runs through every link in the full life-cycle of design, production, product, and service. The concept also relates to the optimization and integration of corresponding systems; the continuous improvement of enterprises’ product quality, performance, and service levels; and reduction in resources consumption. New-generation intelligent manufacturing acts as the core driving force of the new industrial revolution and will continue to be the main pathway for the transformation and upgrading of the manufacturing industry in the decades to come. Human-cyber-physical systems (HCPSs) reveal the technological mechanisms of new-generation intelligent manufacturing and can effectively guide related theoretical research and engineering practice. Given the sequential development, cross interaction, and iterative upgrading characteristics of the three basic paradigms of intelligent manufacturing, a technology roadmap for ‘‘parallel promotion and integrated development” should be developed in order to drive forward the intelligent transformation of the manufacturing industry in China.
Bio-syncretic robots consisting of both living biological materials and non-living systems possess desirable attributes such as high energy efficiency, intrinsic safety, high sensitivity, and self-repairing capabilities. Compared with living biological materials or non-living traditional robots based on electromechanical systems, the combined system of a bio-syncretic robot holds many advantages. Therefore, developing bio-syncretic robots has been a topic of great interest, and significant progress has been achieved in this area over the past decade. This review systematically summarizes the development of bio-syncretic robots. First, potential trends in the development of bio-syncretic robots are discussed. Next, the current performance of bio-syncretic robots, including simple movement and controllability of velocity and direction, is reviewed. The living biological materials and non-living materials that are used in bio-syncretic robots, and the corresponding fabrication methods, are then discussed. In addition, recently developed control methods for bio-syncretic robots, including physical and chemical control methods, are described. Finally, challenges in the development of bio-syncretic robots are discussed from multiple viewpoints, including sensing and intelligence, living and non-living materials, control approaches, and information technology.
As resource scarcity, extreme climate change, and pollution levels increase, economic growth must rely on more environmentally friendly and efficient production processes. Fuel cells are an ideal alternative to internal combustion (IC) engines and boilers on the path to greener industries because of their high efficiency and environmentally friendly operation. However, as a new energy technology, significant market penetration of fuel cells has not yet been achieved. In this paper, we perform a techno-economic and environmental analysis of fuel cell systems using life cycle and value chain activities. First, we investigate the procedure of fuel cell development and identify what activities should be undertaken according to fuel cell life cycle activities, value chain activities, and end-user acceptance criteria. Next, we present a unified learning of the institutional barriers in fuel cell commercialization. The primary end-user acceptance criteria are function, cost, and reliability; a fuel cell should outperform these criteria compared with its competitors, such as IC engines and batteries, to achieve a competitive advantage. The repair and maintenance costs of fuel cells (due to low reliability) can lead to a substantial cost increase and decrease in availability, which are the major factors for end-user acceptance. The fuel cell industry must face the challenge of how to overcome this reliability barrier. This paper provides a deeper insight into our work over the years on the main barriers to fuel cell commercialization, and discusses the potential pivotal role of fuel cells in a future low-carbon green economy. It also identifies the needs and points out some directions for this future low-carbon economy. Green energy, supplied with fuel cells, is truly the business mode of the future. Striving for a more sustainable development of economic growth by adopting green public investments and implementing policy initiatives encourages environmentally responsible industrial investments.
This study provides a definition for urban big data while exploring its features and applications of China’s city intelligence. The differences between city intelligence in China and the “smart city” concept in other countries are compared to highlight and contrast the unique definition and model for China’s city intelligence in this paper. Furthermore, this paper examines the role of urban big data in city intelligence by showing that it not only serves as the cornerstone of this trend as it also plays a core role in the diffusion of city intelligence technology and serves as an inexhaustible resource for the sustained development of city intelligence. This study also points out the challenges of shaping and developing of China’s urban big data. Considering the supporting and core role that urban big data plays in city intelligence, the study then expounds on the key points of urban big data, including infrastructure support, urban governance, public services, and economic and industrial development. Finally, this study points out that the utility of city intelligence as an ideal policy tool for advancing the goals of China’s urban development. In conclusion, it is imperative that China make full use of its unique advantages—including using the nation’s current state of development and resources, geographical advantages, and good human relations—in subjective and objective conditions to promote the development of city intelligence through the proper application of urban big data.
The application of high pressure favors many chemical processes, providing higher yields or improved rates in chemical reactions and improved solvent power in separation processes, and allowing activation barriers to be overcome through the increase in molecular energy and molecular collision rates. High pressures—up to millions of bars using diamond anvil cells—can be achieved in the laboratory, and lead to many new routes for chemical synthesis and the synthesis of new materials with desirable thermodynamic, transport, and electronic properties. On the industrial scale, however, high-pressure processing is currently limited by the cost of compression and by materials limitations, so that few industrial processes are carried out at pressures above 25 MPa. An alternative approach to high-pressure processing is proposed here, in which very high local pressures are generated using the surface-driven interactions from a solid substrate. Recent experiments and molecular simulations show that such interactions can lead to local pressures as high as tens of thousands of bars (1 bar= 1 _ 105 Pa), and even millions of bars in some cases. Since the active high-pressure processing zone is inhomogeneous, the pressure is different in different directions. In many cases, it is the pressure in the direction parallel to the surface of the substrate (the tangential pressure) that is most greatly enhanced. This pressure is exerted on the molecules to be processed, but not on the solid substrate or the containing vessel. Current knowledge of such pressure enhancement is reviewed, and the possibility of an alternative route to high-pressure processing based on surface-driven forces is discussed. Such surface-driven high-pressure processing would have the advantage of achieving much higher pressures than are possible with traditional bulk-phase processing, since it eliminates the need for mechanical compression. Moreover, no increased pressure is exerted on the containing vessel for the process, thus eliminating concerns about materials failure.
Given the increasingly notable segmentation of underground space by existing subway tunnels, it is difficult to effectively and adequately develop and utilize underground space in busy parts of a city. This study presents a combined construction technology that has been developed for use in underground spaces; it includes a deformation buffer layer, a special grouting technique, jump excavation by compartment, back-pressure portal frame technology, a reinforcement technique, and the technology of a steel portioning drum or plate. These technologies have been successfully used in practical engineering. The combined construction technology presented in this paper provides a new method of solving key technical problems in underground spaces in effectively used cross-subway tunnels. As this technology has achieved significant economic and social benefits, it has valuable future applications.
Failures are very common during the online real-time monitoring of large quantities of complex liquids in industrial processes, and can result in excessive resource consumption and pollution. In this study, we introduce a monitoring method capable of non-contact original-state online real-time monitoring for strongly coated, high-salinity, and multi-component liquids. The principle of the method is to establish the relationship among the concentration of the target substance in the liquid (C), the color space coordinates of the target substance at different concentrations (L*, a*, b*), and the maximum absorption wavelength (λmax); subsequently, the optimum wavelength λT of the liquid is determined by a high-precision scanning-type monitoring system that is used to detect the instantaneous concentration of the target substance in the flowing liquid. Unlike traditional monitoring methods and existing online monitoring methods, the proposed method does not require any pretreatment of the samples (i.e., filtration, dilution, oxidation/reduction, addition of chromogenic agent, constant volume, etc.), and it is capable of originalstate online real-time monitoring. This method is employed at a large electrolytic manganese plant to monitor the Fe3+ concentration in the colloidal process of the plant’s aging liquid (where the concentrations of Fe3+, Mn2+, and (NH4)2SO4are 0.5–18 mg·L1, 35–39 g·L1, and 90–110 g·L1, respectively). The relative error of this monitoring method compared with an off-line laboratory monitoring is less than 2%.
With the popularization of the Internet, permeation of sensor networks, emergence of big data, increase in size of the information community, and interlinking and fusion of data and information throughout human society, physical space, and cyberspace, the information environment related to the current development of artificial intelligence (AI) has profoundly changed. AI faces important adjustments, and scientific foundations are confronted with new breakthroughs, as AI enters a new stage: AI 2.0. This paper briefly reviews the 60-year developmental history of AI, analyzes the external environment promoting the formation of AI 2.0 along with changes in goals, and describes both the beginning of the technology and the core idea behind AI 2.0 development. Furthermore, based on combined social demands and the information environment that exists in relation to Chinese development, suggestions on the development of AI 2.0 are given.
Cyberattack forms are complex and varied, and the detection and prediction of dynamic types of attack are always challenging tasks. Research on knowledge graphs is becoming increasingly mature in many fields. At present, it is very significant that certain scholars have combined the concept of the knowledge graph with cybersecurity in order to construct a cybersecurity knowledge base. This paper presents a cybersecurity knowledge base and deduction rules based on a quintuple model. Using machine learning, we extract entities and build ontology to obtain a cybersecurity knowledge base. New rules are then deduced by calculating formulas and using the path-ranking algorithm. The Stanford named entity recognizer (NER) is also used to train an extractor to extract useful information. Experimental results show that the Stanford NER provides many features and the useGazettes parameter may be used to train a recognizer in the cybersecurity domain in preparation for future work.
The type, model, quantity, and location of sensors installed on the intelligent vehicle test platform are different, resulting in different sensor information processing modules. The driving map used in intelligent vehicle test platform has no uniform standard, which leads to different granularity of driving map information. The sensor information processing module is directly associated with the driving map information and decision-making module, which leads to the interface of intelligent driving system software module has no uniform standard. Based on the software and hardware architecture of intelligent vehicle, the sensor information and driving map information are processed by using the formal language of driving cognition to form a driving situation graph cluster and output to a decision-making module, and the output result of the decision-making module is shown as a cognitive arrow cluster, so that the whole process of intelligent driving from perception to decision-making is completed. The formalization of driving cognition reduces the influence of sensor type, model, quantity, and location on the whole software architecture, which makes the software architecture portable on different intelligent driving hardware platforms.
This article provides in-depth insights into the necessary technologies for automated driving in future cities. State of science is reflected from different perspectives such as in-car computing and data management, road side infrastructure, and cloud solutions. Especially the challenges for the application of HD maps as core technology for automated driving are depicted in this article.
Enhanced oil recovery (EOR) via carbon dioxide (CO2) flooding has received a considerable amount of attention as an economically feasible method for carbon sequestration, with many recent studies focusing on developing enhanced CO2 foaming additives. However, the potential long-term environmental effects of these additives in the event of leakage are poorly understood and, given the amount of additives injected in a typical CO2 EOR operation, could be far-reaching. This paper presents a summary of recent developments in surfactant and surfactant/nanoparticle-based CO2 foaming systems, with an emphasis on the possible environmental impacts of CO2 foam leakage. Most of the surfactants studied are unlikely to degrade under reservoir conditions, and their release can cause major negative impacts on wildlife. With recent advances in the use of additives (e.g., nonionic surfactants, nanoparticles, and other chemicals) the use of harsh anionic surfactants may no longer be warranted. This paper discusses recent advances in producing foaming systems, and highlights possible strategies to develop environmentally friendly CO2 EOR methods.
This article analyzes the current research status and development trend of intelligent technologies for underground metal mines in China, where such technologies are under development for use to develop mineral resources in a safe, efficient, and environmentally friendly manner. We analyze and summarize the research status of underground metal mining technology at home and abroad, including some specific examples of equipment, technology, and applications. We introduce the latest equipment and technologies with independent intellectual property rights for unmanned mining, including intelligent and unmanned control technologies for rock-drilling jumbos, down-the-hole (DTH) drills, underground scrapers, underground mining trucks, and underground charging vehicles. Three basic platforms are used for intelligent and unmanned mining: the positioning and navigation platform, information-acquisition and communication platform, and scheduling and control platform. Unmanned equipment was tested in the Fankou Lead-Zinc Mine in China, and industrial tests on the basic platforms of intelligent and unmanned mining were carried out in the mine. The experiment focused on the intelligent scraper, which can achieve autonomous intelligent driving by relying on a wireless communication system, location and navigation system, and data-acquisition system. These industrial experiments indicate that the technology is feasible. The results show that unmanned mining can promote mining technology in China to an intelligent level and can enhance the core competitive ability of China’s mining industry.
The emerging prototype for a Smart City is one of an urban environment with a new generation of innovative services for transportation, energy distribution, healthcare, environmental monitoring, business, commerce, emergency response, and social activities. Enabling the technology for such a setting requires a viewpoint of Smart Cities as cyber-physical systems (CPSs) that include new software platforms and strict requirements for mobility, security, safety, privacy, and the processing of massive amounts of information. This paper identifies some key defining characteristics of a Smart City, discusses some lessons learned from viewing them as CPSs, and outlines some fundamental research issues that remain largely open.
Goethite is a metals-rich residue that occurs during zinc production. The feasibility of metal recovery from goethite has been demonstrated, but is not economically viable on an industrial scale. Therefore, goethite is landfilled with considerable economic costs and environmental risks. The goal of this study is to evaluate the environmental performance of a new valorization strategy for goethite residues from zinc production, with the aims of: ① recovering the valuable zinc contained in the goethite and ② avoiding the landfilling of goethite by producing a clean byproduct. The presented goethite valorization strategy consists of a sequence of two processes: ① plasma fuming and ② inorganic polymerization of the fumed slag. Plasma fuming recovers the valuable metals by fuming the goethite. The metals-free fumed slag undergoes a process of inorganic polymerization to form inorganic polymers, that can be used as a novel building material, as an alternative to ordinary Portland cement (OPC)-based concrete. Lifecycle assessment (LCA) is used to compare the environmental performance of the inorganic polymer with the environmental performances of equivalent OPC-based concrete. The LCA results show the tradeoff between the environmental burdens of the fuming process and inorganic polymerization versus the environmental benefits of metal recovery, OPC concrete substitution, and the avoidance of goethite landfilling. The goethite-based inorganic polymers production shows better performances in several environmental impact categories, thanks to the avoided landfilling of goethite. However, in other environmental impact categories, such as global warming, the goethite valorization is strongly affected by the high-energy requirements of the plasma-fuming process, which represent the environmental hotspots of the proposed goethite recycling scheme. The key elements toward the sustainability of goethite valorization have been identified, and include the use of a clean electric mix, more effective control of the fumed gas emissions, and a reduced use of fumed slag through increased efficiency of the inorganic polymerization process.
Gas hydrates are solid inclusion compounds that are composed of a three-dimensional hydrogen-bonded network of water cages that can trap small gas molecules, such as methane and carbon dioxide. Understanding the rheological properties of gas hydrate crystals in solution can be critical in a number of energy applications, including the transportation of natural gas in subsea and onshore operations, as well as technological applications for gas separation, desalination, or sequestration. A number of experimental and modeling studies have been done on hydrate slurry rheology; however, the link between theory and experiment is not well-defined. This article provides a review on the current state of the art of hydrate slurry viscosity measurements from high- and low-pressure rheometer studies and high-pressure flowloops over a range of different sub-cooling (ΔTsub=Tequil−Texp) and fluid conditions, including for water and oil continuous systems. The theoretical models that have been developed to describe the gas hydrate slurry relative viscosity are also reviewed. Perspectives’ linkage between the experiments and theory is also discussed.
Organic solid and liquid wastes contain large amounts of energy, nutrients, and water, and should not be perceived as merely waste. Recycling, composting, and combustion of non-recyclables have been practiced for decades to capture the energy and values from municipal solid wastes. Treatment and disposal have been the primary management strategy for wastewater. As new technologies are emerging, alternative options for the utilization of both solid wastes and wastewater have become available. Considering the complexity of the chemical, physical, and biological properties of these wastes, multiple technologies may be required to maximize the energy and value recovery from the wastes. For this purpose, biorefining tends to be an appropriate approach to completely utilize the energy and value available in wastes. Research has demonstrated that non-recyclable waste materials and bio-solids can be converted into usable heat, electricity, fuel, and chemicals through a variety of processes, and the liquid waste streams have the potential to support crop and algae growth and provide other energy recovery and food production options. In this paper, we propose new biorefining schemes aimed at organic solid and liquid wastes from municipal sources, food and biological processing plants, and animal production facilities. Four new breakthrough technologies—namely, vacuum-assisted thermophilic anaerobic digestion, extended aquaponics, oily wastes to biodiesel via glycerolysis, and microwave-assisted thermochemical conversion—can be incorporated into the biorefining schemes, thereby enabling the complete utilization of those wastes for the production of chemicals, fertilizer, energy (biogas, syngas, biodiesel, and bio-oil), foods, and feeds, and resulting in clean water and a significant reduction in pollutant emissions.
After a systematic review of 38 current intelligent city evaluation systems (ICESs) from around the world, this research analyzes the secondary and tertiary indicators of these 38 ICESs from the perspectives of scale structuring, approaches and indicator selection, and determines their common base. From this base, the fundamentals of the City Intelligence Quotient (City IQ) Evaluation System are developed and five dimensions are selected after a clustering analysis. The basic version, City IQ Evaluation System 1.0, involves 275 experts from 14 high-end research institutions, which include the Chinese Academy of Engineering, the National Academy of Science and Engineering (Germany), the Royal Swedish Academy of Engineering Sciences, the Planning Management Center of the Ministry of Housing and Urban-Rural Development of China, and the Development Research Center of the State Council of China. City IQ Evaluation System 2.0 is further developed, with improvements in its universality, openness, and dynamic adjustment capability. After employing deviation evaluation methods in the IQ assessment, City IQ Evaluation System 3.0 was conceived. The research team has conducted a repeated assessment of 41 intelligent cities around the world using City IQ Evaluation System 3.0. The results have proved that the City IQ Evaluation System, developed on the basis of intelligent life, features more rational indicators selected from data sources that can offer better universality, openness, and dynamics, and is more sensitive and precise.