Search scope:
排序： Display mode:
Guo Shuren, Jiang Kun, Li Xing, Liu Gang, Li Ping, Li Linze, Guo Siyuan
Strategic Study of Chinese Academy of Engineering doi: 10.15302/J-SSCAE-2023.02.006
Satellite navigation has all-weather, all-time, and low-cost advantages and has become the most widely used means of positioning, navigation, and timing (PNT) service since its inception. However, to avoid excessive reliance on the single means of satellite navigation at the application level, the concept of satellite-independent navigation technology has been proposed and received attention. How to accurately understand the relationship between satellite and satellite-independent navigation technologies has become a realistic and urgent issue. The technological characteristics and system positioning of satellite navigation are summarized in this study. The performances, costs, and application scenarios of typical satellite independent navigation technologies such as inertial navigation, matching navigation, and radio navigation (except for satellite navigation) are comparatively analyzed from a PNT system perspective. The relationship between satellite and satellite-independent navigation technologies is comprehensively analyzed. The overall positioning of satellite navigation as the most common demand satisfied and the core and cornerstone of the PNT system is further clarified. Additionally, the fusion efficiency is quantitatively analyzed. The scientific development of China’s PNT system requires the innovative development of satellite-independent navigation technologies, and the deep integration of satellite and satellite-independent navigation technologies should be promoted. Moreover, the construction of low-orbit navigation systems should be accelerated to improve satellite navigation performance and maximizing system contribution.
Keywords： positioning navigation and timing system satellite navigation satellite-independent navigation technology integration system development
Technology System of Offshore Carbon Capture, Utilization, and Storage
Li Jianghui, Li Pengchun, Li Yanzun, Tong Feng
Strategic Study of Chinese Academy of Engineering doi: 10.15302/J-SSCAE-2023.07.015
Offshore carbon capture, utilization, and storage (CCUS) is an engineering solution and technical system developed by coastal countries or regions to reduce carbon dioxide (CO2) emissions. Compared with onshore CCUS, offshore CCUS has multiple significant advantages, such as higher storage potential and safer storage environment. Offshore CCUS comprises capturing CO2 from large coastal or offshore carbon emission sources, compressing and transporting it to offshore storage platforms, and injecting it into sub-seabed geological reservoirs, to achieve permanent isolation from the atmosphere or use it to produce valuable products. This study reviews the development demand and industry status quo of offshore CCUS in China and worldwide and analyzes the technical and social values of offshore CCUS development. The development routes and trends of representative offshore CCUS technologies are summarized, including CO2 plant capture, CO2 pipeline transportation, CO2 storage in the deep saline aquifer and for petroleum displacement, CO2 chemical utilization, and several other technical frameworks. Focusing on the common problems faced by different technology systems, we propose the following suggestions for the future development of China’s offshore CCUS: strengthening the land-sea overall planning and layout, cultivating high-level research teams, and enhancing fundamental research, key technology research and development, cost control, scale expansion, and policy incentives at all stages of development.
Keywords： offshore carbon capture utilization and storage CO2 capture CO2 transport CO2 storage CO2 utilization coastal areas offshore sedimentary basin
A Smart Metasurface for Electromagnetic Manipulation Based on Speech Recognition Article
Lin Bai, Yuan Ke Liu, Liang Xu, Zheng Zhang, Qiang Wang, Wei Xiang Jiang, Cheng-Wei Qiu, Tie Jun Cui
Engineering 2023, Volume 22, Issue 3, Pages 185-190 doi: 10.1016/j.eng.2022.06.026
In this work, we propose and realize a smart metasurface for programming electromagnetic (EM) manipulations based on human speech recognition. The smart metasurface platform is composed of a digital coding metasurface, a speech-recognition module, a single-chip computer, and a digital-to-analog converter (DAC) circuit, and can control EM waves according to pre-stored voice commands in a smart way. The constructed digital metasurface contains 6 × 6 super unit cells, each of which consists of 4 × 4 active elements with embedded varactor diodes. Together with the DAC and single-chip computer, the speech-recognition module can recognize voice commands and generate corresponding voltage sequences to control the metasurface. In addition, a genetic algorithm (GA) is adopted in the design of the metasurface for efficiently optimizing the phase distributions. To verify the performance of the smart metasurface platform, three typical functions are demonstrated: radar cross-section reduction, vortex beam generation, and beam splitting. The proposed strategy may offer a new avenue for controlling EM waves and establishing a link between EM and acoustic communications.
Keywords： Speech recognition Programmable metasurface Genetic algorithm Smart electromagnetic manipulation
The Future of Smart Process Manufacturing
Feng Qian
Engineering 2023, Volume 22, Issue 3, Pages 20-22 doi: 10.1016/j.eng.2022.04.029
Cheng Runting, Zhang Yongjun, Li Licheng, Ding Maosheng, Deng Wenyang,Chen Haoyong, Lin Jingchun
Strategic Study of Chinese Academy of Engineering doi: 10.15302/J-SSCAE-2023.02.011
A complete electricity market plays a decisive role in the allocation of electricity resources and is key to ensuring active supply-demand interactions between market players and promoting the consumption of renewable energies. Currently, a targeted,comprehensive analysis on factors that affect renewable energy consumption is urgently required. Focusing on trading mechanisms that can promote renewable energy consumption at a full time scale, this study summarizes the structures and mechanisms of typical electricity markets abroad and sorts out the key factors that can promote renewable energy consumption. Based on this, the study explores the current structures and mechanisms of China’s electricity market and examines the challenges faced during the electricitymarket construction. Moreover, the research progress of China’s electricity market for high-proportion renewable energy consumption is reviewed from the aspects of market mechanism, trading mode, and new consumption pattern. Furthermore, we propose that key measures should be taken in terms of multiple-market collaborative cooperation, linking of medium- and long-term spot trading,ancillary services market construction, and establishment of a demand-side response mechanism.
Keywords： renewable energy consumption green certificate market carbon market ancillary services market demand-side response
Shibao Pang, Shunsheng Guo, Xi Vincent Wang, Lei Wanga, Lihui Wang
Engineering 2023, Volume 22, Issue 3, Pages 34-48 doi: 10.1016/j.eng.2022.07.020
An Industrial Internet platform is acknowledged to be a requisite promoter for smart manufacturing, enabling physical manufacturing resources to be virtualized and permitting resources to collaborate in the form of services. As a central function of the platform, manufacturing service collaboration optimization is dedicated to establishing high-quality service collaboration solutions for manufacturing tasks. Such optimization is inseparable from the functional and amount requirements of a task, which must be satisfied when orchestrating services. However, existing manufacturing service collaboration optimization methods mainly focus on horizontal collaboration among services for functional demands and rarely consider vertical collaboration to cover the needed amounts. To address this gap, this paper proposes a dual-dimensional service collaboration methodology that combines functional and amount collaboration. First, a multi-granularity manufacturing service modeling method is presented to describe services. On this basis, a dual-dimensional manufacturing service collaboration optimization (DMSCO) model is formulated. In the vertical dimension, multiple functionally equivalent services form a service cluster to fulfill a subtask; in the horizontal dimension, complementary service clusters collaborate for the entire task. Service selection and amount distribution to the selected services are critical issues in the model. To solve the problem, a multi-objective memetic algorithm with multiple local search operators is tailored. The algorithm embeds a competition mechanism to dynamically adjust the selection probabilities of the local search operators. The experimental results demonstrate the superiority of the algorithm in terms of convergence, solution quality, and comprehensive metrics, in comparison with commonly used algorithms.
Keywords： Manufacturing service collaboration Service optimal selection Service granularity Industrial Internet platform
Editorial for the Special Issue on Intelligent Manufacturing
Peigen Li, Xinyu Li, Liang Gao, Akhil Garg, Weiming Shen
Engineering 2023, Volume 22, Issue 3, Pages 1-2 doi: 10.1016/j.eng.2022.11.001
Webb Space Telescope Hits Its Stride, Dazzling Astronomers
Mitch Leslie
Engineering 2023, Volume 22, Issue 3, Pages 3-6 doi: 10.1016/j.eng.2023.01.003
Fengle Zhu, Zhenzhu Su, Alireza Sanaeifar, Anand Babu Perumal, Mostafa Gouda, Ruiqing Zhou, Xiaoli Li, Yong He
Engineering 2023, Volume 22, Issue 3, Pages 171-184 doi: 10.1016/j.eng.2022.10.006
Plant pathogens continuously impair agricultural yields and food security. Therefore, the dynamic characterization of early pathogen progression is crucial for disease monitoring and presymptomatic diagnosis. Hyperspectral imaging (HSI) has great potential for tracking the dynamics of initial infected sites for presymptomatic diagnosis; however, no related studies have extracted fingerprint spectral signatures (FSSs) that can capture diseased lesions on leaves during the early infection stage in vivo or investigated the detection mechanism of HSI relating to the host biochemical responses. The FSSs denote unique and representative spectral signatures that characterize a specific plant disease. In this study, the FSSs of spot blotch on barley leaves inoculated with Bipolaris sorokiniana were discovered to characterize symptom development for presymptomatic diagnosis based on time-series HSI data analysis. The early spectral and biochemical responses of barley leaves to spot blotch progression were also investigated. The fullspectrum FSSs were physically interpretable and could capture the unique characteristics of chlorotic and necrotic tissues along with lesion progression, enabling the in situ visualization of the spatiotemporal dynamics of early plant–pathogen interactions at the pixel level. Presymptomatic diagnosis of spot blotch was achieved 24 h after inoculation—12 h earlier than the traditional polymerase chain reaction (PCR) assay or biochemical measurements. To uncover the mechanism of HSI presymptomatic diagnosis, quantitative relationships between the mean spectral responses of leaves and their biochemical indicators (chlorophylls, carotenoids, malondialdehyde (MDA), ascorbic acid (AsA), and reduced glutathione (GSH)) were developed, achieving determination coefficient of prediction set (Rp2) > 0.84 for regression models. The overall results demonstrated that, based on the association between HSI and in vivo planttrait alterations, the extracted FSSs successfully tracked the spatiotemporal dynamics of bipolaris spot blotch progression for presymptomatic diagnosis. Tests of this methodology on other plant diseases demonstrated its remarkable generalization potential for the early control of plant diseases.
Keywords： Hyperspectral imaging Fingerprint spectral signatures Spot blotch Leaf lesion progression Presymptomatic diagnosis Biochemical indicators
Funding Bonanza Lifts CO2 Removal Technology to Demonstration Phase
Sarah C.P. Williams
Engineering 2023, Volume 22, Issue 3, Pages 7-9 doi: 10.1016/j.eng.2023.01.002
Expanding Fleet of Autonomous Floating Robots Targets Deeper Understanding of Global Ocean Dynamics
Chris Palmer
Engineering 2023, Volume 22, Issue 3, Pages 10-13 doi: 10.1016/j.eng.2023.01.001
Diling Yang,Xuwen Peng,Qiongyao Peng,Tao Wang,Chenyu Qiao,Ziqian Zhao,Lu Gong,Yueliang Liu,Hao Zhang,Hongbo Zeng
Engineering 2023, Volume 22, Issue 3, Pages 233-233 doi: 10.1016/j.eng.2023.02.001
Digital-Twin-Enhanced Quality Prediction for the Composite Materials Article
Yucheng Wang, Fei Tao, Ying Zuo, Meng Zhang, Qinglin Qi
Engineering 2023, Volume 22, Issue 3, Pages 23-33 doi: 10.1016/j.eng.2022.08.019
Composite materials are widely used in many fields due to their excellent properties. Quality defects in composite materials can lead to lower quality components, creating potential risk of accidents. Experimental and simulation methods are commonly used to predict the quality of composite materials. However, it is difficult to predict the quality of composite materials accurately due to the uncertain curing environment and incomplete feature space. To address this problem, a digital twin (DT) visual model of a composite material is first constructed. Then, a static autoclave DT virtual model is coupled with a variable composite material DT virtual model to construct a model of the curing process. Features are added to the proposed model by generating simulated data to enhance the quality prediction. An extreme learning machine (ELM) for quality prediction is trained with the generated data. Finally, the effectiveness of the proposed method is verified through result analysis.
Keywords： Digital twin Quality prediction Composites Coupling models
Zhou-Zheng Tu, Qi Lu, Yan-Bo Zhang, Zhe Shu, Yu-Wei Lai, Meng-Nan Ma, Peng-Fei Xia, Ting-Ting Geng, Jun-Xiang Chen, Yue Li, Lin-Jing Wu, Jing Ouyang, Zhi Rong, Xiong Ding, Xu Han, Shuo-Hua Chen, Mei-An He, Xiao-Min Zhang, Lie-Gang Liu, Tang-Chun Wu, Shou-Ling Wu, Gang Liu, An Pan
Engineering 2023, Volume 22, Issue 3, Pages 141-148 doi: 10.1016/j.eng.2022.04.010
Lifestyle modification is an effective measure for diabetes prevention in people with prediabetes, but its associations with the long-term risks of cardiovascular disease (CVD), cancer, and mortality remain largely uncertain. We aimed to investigate the associations of combined healthy lifestyle factors with these health outcomes among participants with prediabetes. The study included 121 254 people with prediabetes from four prospective cohorts: the Dongfeng-Tongji (DFTJ) cohort and Kailuan study, both from China; the UK Biobank; and the US National Health and Nutrition Examination Survey (NHANES; for mortality analysis only). We documented a total of 18 333 incident diabetes, 10 829 incident CVD, 6926 incident cancer, and 9877 deaths during follow-up. Combined healthy lifestyle scores (scored from 0 to 5) were constructed based on never smoking or quitting smoking for ≥ 10 years, low-to-moderate alcohol drinking, optimal physical activity, healthy diet, and optimal waist circumference. First, Cox proportional-hazards regression models were used to quantify the associations of combined lifestyle score with health outcomes in each cohort; then, multivariable-adjusted hazard ratios (HRs) were pooled via a random-effects model of meta-analysis. Compared with participants with the least healthy lifestyle (a score of 0–1), participants with the healthiest lifestyle (a score of 4–5) had significantly reduced risks of all outcomes. The HRs (95% confidence interval (CI)) were 0.57 (0.48–0.69) for diabetes, 0.67 (0.62– 0.73) for CVD, 0.80 (0.73–0.88) for cancer, and 0.54 (0.42–0.70) for mortality. Significant associations were consistently found across subgroups of baseline demographic characteristics and metabolic health status. In conclusion, our pooled analyses of four cohorts from three countries reveal that greater adherence to a healthy lifestyle is associated with considerably lower risks of diabetes and its major complications among adults with prediabetes. These findings provide informative and compelling evidence for establishing clinical guidelines and public health policies.
Keywords： Prediabetes Lifestyle Diabetes Cardiovascular disease Cancer Mortality
Ma Hongmei, Jin Bijun, Luo Tao, Ding Long, Song Baoan
Strategic Study of Chinese Academy of Engineering doi: 10.15302/J-SSCAE-2023.07.011
Digital technology is an important driving force for agricultural modernization in China. Developing modern agriculture in China's southwest mountainous areas using digital technologies is crucial for rural revitalization and common prosperity and is an inevitable requirement for realizing Chinese path to modernization. This study expounds the concept connotation and operation logic of digital agriculture in southwest mountainous areas. Based on public statistics and field survey data, it analyzes the current status of digital agriculture development in southwest mountainous areas from the aspects of coordination of relevant subjects, infrastructure construction, production and sales link application, and population structure, and further clarifies the practical difficulties faced by the development. Furthermore, the study suggests that we should improve the multi-party cooperation mechanism, strengthen the construction of digital infrastructure, broaden the application scenarios of digital agriculture, and promote digital personnel training in rural areas, thus to deepen the development of digital agriculture in the southwest mountainous areas.
Keywords： southwest mountainous area digital agriculture digital technology infrastructure Chinese path to modernization
Title Author Date Type Operation
Integrated Development of Satellite and Satellite-Independent Navigation Technologies from the Perspective of PNT System
Guo Shuren, Jiang Kun, Li Xing, Liu Gang, Li Ping, Li Linze, Guo Siyuan
Journal Article
Technology System of Offshore Carbon Capture, Utilization, and Storage
Li Jianghui, Li Pengchun, Li Yanzun, Tong Feng
Journal Article
A Smart Metasurface for Electromagnetic Manipulation Based on Speech Recognition
Lin Bai, Yuan Ke Liu, Liang Xu, Zheng Zhang, Qiang Wang, Wei Xiang Jiang, Cheng-Wei Qiu, Tie Jun Cui
Journal Article
Construction and Research Progress of Electricity Market for High-Proportion Renewable Energy Consumption
Cheng Runting, Zhang Yongjun, Li Licheng, Ding Maosheng, Deng Wenyang,Chen Haoyong, Lin Jingchun
Journal Article
Dual-Dimensional Manufacturing Service Collaboration Optimization Toward Industrial Internet Platforms
Shibao Pang, Shunsheng Guo, Xi Vincent Wang, Lei Wanga, Lihui Wang
Journal Article
Editorial for the Special Issue on Intelligent Manufacturing
Peigen Li, Xinyu Li, Liang Gao, Akhil Garg, Weiming Shen
Journal Article
Fingerprint Spectral Signatures Revealing the Spatiotemporal Dynamics of Bipolaris Spot Blotch Progression for Presymptomatic Diagnosis
Fengle Zhu, Zhenzhu Su, Alireza Sanaeifar, Anand Babu Perumal, Mostafa Gouda, Ruiqing Zhou, Xiaoli Li, Yong He
Journal Article
Funding Bonanza Lifts CO2 Removal Technology to Demonstration Phase
Sarah C.P. Williams
Journal Article
Expanding Fleet of Autonomous Floating Robots Targets Deeper Understanding of Global Ocean Dynamics
Chris Palmer
Journal Article
Erratum to "Probing the Interfacial Forces and Surface Interaction Mechanisms in Petroleum Production Processes" [Engineering 18 (2022) 49–61]
Diling Yang,Xuwen Peng,Qiongyao Peng,Tao Wang,Chenyu Qiao,Ziqian Zhao,Lu Gong,Yueliang Liu,Hao Zhang,Hongbo Zeng
Journal Article
Digital-Twin-Enhanced Quality Prediction for the Composite Materials
Yucheng Wang, Fei Tao, Ying Zuo, Meng Zhang, Qinglin Qi
Journal Article
Associations of Combined Healthy Lifestyle Factors with Risks of Diabetes, Cardiovascular Disease, Cancer, and Mortality Among Adults with Prediabetes: Four Prospective Cohort Studies in China, the United Kingdom, and the United States
Zhou-Zheng Tu, Qi Lu, Yan-Bo Zhang, Zhe Shu, Yu-Wei Lai, Meng-Nan Ma, Peng-Fei Xia, Ting-Ting Geng, Jun-Xiang Chen, Yue Li, Lin-Jing Wu, Jing Ouyang, Zhi Rong, Xiong Ding, Xu Han, Shuo-Hua Chen, Mei-An He, Xiao-Min Zhang, Lie-Gang Liu, Tang-Chun Wu, Shou-Ling Wu, Gang Liu, An Pan
Journal Article
京公网安备 11010502051620号