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Predicting gas reservoir of Puguang Gas Field by applying seismic data structure characteristics abnormality method

Zeng Daqian,Lin Changrong,Zhang Shimin,Peng Xinling

Strategic Study of CAE 2010, Volume 12, Issue 10,   Pages 91-96

Abstract:

The reserve space of carbonate reservoir is complex and various in Puguang Gas Field, so the traditional hydrocarbon prediction methods can not get better results. The paper used the structural characteristics of seismic data volume to predict hydrocarbon reservoir, which took relationship between seismic data components on each seismic trace (that is structural characteristics of data volume) as study object to research the characteristics of composition and range of various parameters and their relationship with hydrocarbon bearing ability by detecting the amplitude value of each seismic trace, achieving the goal of predicting the hydrocarbon reservoir. Finally, the method was used to predict reservoir of Puguang Gas Field. The applied results demonstrated that the method can overcome the influence of reservoir nature and can get better results in the prediction of strong nonhomogeneous carbonate reservoir.

Keywords： seismic data volume     structural characteristics     Puguang Gas Field     hydrocarbon reservoir    

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GPU-based multi-slice per pass algorithm in interactive volume illumination rendering Research Articles

Dening Luo, Yi Lin, Jianwei Zhang,onexinoneyi@hotmail.com,Yilin@scu.edu.cn,zhangjianwei@scu.edu.cn

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 8,   Pages 1092-1103 doi: 10.1631/FITEE.2000214

Abstract: plays a significant role in medical imaging and engineering applications. To obtain an improved three-dimensional shape perception of , realistic has been considerably studied in recent years. However, the calculation overhead associated with interactive is unusually high, and the solvability of the problem is adversely affected when the data size and algorithm complexity are increased. In this study, a scalable and GPU-based (MSPP) algorithm is proposed which can quickly generate global volume shadow and achieve a translucent effect based on the transfer function, so as to improve perception of the shape and depth of . In our real-world data tests, MSPP significantly outperforms some complex volume shadow algorithms without losing the illumination effects, for example, half-angle slicing. Furthermore, the MSPP can be easily integrated into the parallel rendering frameworks based on sort-first or sort-last algorithms to accelerate . In addition, its scalable slice-based framework can be combined with several traditional frameworks.

Keywords： 体绘制；体积光照；体数据；单绘制遍多切片    

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A GIS Open-Data Co-Simulation Platform for Photovoltaic Integration in Residential Urban Areas Article

Marco Massano, Enrico Macii, Andrea Lanzini, Edoardo Patti, Lorenzo Bottaccioli

Engineering 2023, Volume 26, Issue 7,   Pages 198-213 doi: 10.1016/j.eng.2022.06.020

Abstract:

The rising awareness of environmental issues and the increase of renewable energy sources (RES) has led to a shift in energy production toward RES, such as photovoltaic (PV) systems, and toward a distributed generation (DG) model of energy production that requires systems in which energy is generated, stored, and consumed locally. In this work, we present a methodology that integrates geographic information system (GIS)-based PV potential assessment procedures with models for the estimation of both energy generation and consumption profiles. In particular, we have created an innovative infrastructure that co-simulates PV integration on building rooftops together with an analysis of households’ electricity demand. Our model relies on high spatiotemporal resolution and considers both shadowing effects and real-sky conditions for solar radiation estimation. It integrates methodologies to estimate energy demand with a high temporal resolution, accounting for realistic populations with realistic consumption profiles. Such a solution enables concrete recommendations to be drawn in order to promote an understanding of urban energy systems and the integration of RES in the context of future smart cities. The proposed methodology is tested and validated within the municipality of Turin, Italy. For the whole municipality, we estimate both the electricity absorbed from the residential sector (simulating a realistic population) and the electrical energy that could be produced by installing PV systems on buildings' rooftops (considering two different scenarios, with the former using only the rooftops of residential buildings and the latter using all available rooftops). The capabilities of the platform are explored through an in-depth analysis of the obtained results. Generated power and energy profiles are presented, emphasizing the flexibility of the resolution of the spatial and temporal results. Additional energy indicators are presented for the self-consumption of produced energy and the avoidance of CO2 emissions.

Keywords： Energy informatics     Geographic information system     Load estimation     Open data     Photovoltaic     Residential     Urban planning     Co-simulation    

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Multi-agent differential game based cooperative synchronization control using a data-driven method Research Article

Yu SHI, Yongzhao HUA, Jianglong YU, Xiwang DONG, Zhang REN

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 7,   Pages 1043-1056 doi: 10.1631/FITEE.2200001

Abstract: This paper studies the multi-agent based problem and its application to cooperative . A systematized formulation and analysis method for the multi-agent is proposed and a methodology based on the (RL) technique is given. First, it is pointed out that typical distributed controllers may not necessarily lead to global Nash equilibrium of the in general cases because of the coupling of networked interactions. Second, to this end, an alternative local Nash solution is derived by defining the best response concept, while the problem is decomposed into local s. An off-policy RL algorithm using neighboring interactive data is constructed to update the controller without requiring a system model, while the stability and robustness properties are proved. Third, to further tackle the dilemma, another configuration is investigated based on modified coupling index functions. The distributed solution can achieve global Nash equilibrium in contrast to the previous case while guaranteeing the stability. An equivalent parallel RL method is constructed corresponding to this Nash solution. Finally, the effectiveness of the learning process and the stability of are illustrated in simulation results.

Keywords： Multi-agent system     Differential game     Synchronization control     Data-driven     Reinforcement learning    

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The Formation of Tetraploid Hybrids of Common Carp with Red Crucian Carp and the Evolutionary Significance of Tetraploidization in Vertebrate

Liu Shaojun,Cao Yunzhang,He Xiaoxiao,Li Jianzhong,Liu Yun

Strategic Study of CAE 2001, Volume 3, Issue 12,   Pages 33-41

Abstract:

In this paper, the number and karyotype of chromosomes, DNA content, the mean nuclear erythrocyte volume, gonads and gametes, embryo development, the mechanism of the tetraploid formation, and the appearance in tetraploid hybrid stocks of the red crucian carp (♀）× common carp (♂）were described. The tetraploid hybrids with stable genetic characteristics were inherited from F3 to F11 and a large population of tetraploid fish had been formed. The tetraploid hybrids were essentially different from their parents-red crucian carp and common carp in chromosome number, reproduction and appearance. Based on the genetic characteristics, the bisexual fertility and reproductive isolation, the tetraploid stocks had possessed the good base to form a new tetraploid species in the future. The formation of the new tetraploid stocks had great significance both in the evolutionary theory of vertebrate and in the production application.

Keywords： allotetraploid     triploid     diploid gamete     evolution    

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Overall Conception and Development Suggestions for the Systematic Construction of Smart Society

Lei Bin, Lan Yushi, Li Maolin, Pan Jianqun, Zhou Zhongyuan, Zhang Chunhui

Strategic Study of CAE 2023, Volume 25, Issue 3,   Pages 219-229 doi: 10.15302/J-SSCAE-2023.07.025

Abstract:

A smart society is an important component of the digital China strategy; however, the construction of the smart society currently faces practical challenges. Studying a systematic construction method for the smart society will cultivate new competitive advantages for China, promote Chinese path to modernization, and realize the digital China strategy. This study aims to explore methods for building a new type of smart society and maximizing the benefits of social resources. It analyzes the current status and development trends of smart society construction and summarizes the prominent problems including large investment in decentralized construction, low operational efficiency, and uneven development. Following a systems engineering method, an overall architecture for the systematic construction of the smart society is proposed. The architecture adopts a new “1+N+X” model that focuses on coordinating information infrastructure resources of the entire society to build a smart society system capability support platform, thus to expand various business applications accordingly. Moreover, we propose the following suggestions: (1) strengthening top-level design to build a system capability support platform that integrates network, cloud, data, control, and intelligence, thereby forming a basic digital base for the smart society; (2) adopting a new model of systematic construction to promote the sustainable development of smart society construction through efficient operation; (3) establishing  a comprehensive standards and regulations system for the smart society; and (4) providing solid theoretical, technical, and talent support for  the systematic construction of the smart society by building a national laboratory for digital systems engineering of the smart society.

Keywords： smart society     systematic construction     capability support platform     integrated data     unified resource control    

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The Mechanics of 3D Multi-body Contact System of Long Shell and Tyres

Liang Xiaoling,Xiao Yougang,Li Xuejun

Strategic Study of CAE 2005, Volume 7, Issue 12,   Pages 41-44

Abstract:

According to the high iterative feature of shell and tyre structure, the multi-level substructure technique is adopted to set up the multi-body contact model between tyres and long shell. Applying parametric quadratic programming method, the multi-body contact FEM analysis of the No.2 rotary kiln in Henan Branch of China Aluminum Company is done, and the conclusions are as follows： The equivalent stress of shell at supports changes 5 times, and at other parts changes 4 times; the strength of shell at supports is weak, and at other parts is affluent; the strength of shell at the supports 2 and 3 is the weakest.

Keywords： shell     multi-body contact     multi-level substructure     mechanical property    

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Magmatic Ore Deposits in Small Rockbody in China

Tang Zhongli

Strategic Study of CAE 2002, Volume 4, Issue 6,   Pages 9-12

Abstract:

There is not any large deposit associated with giant layered igneous complex in China. But superlarge and large magmatic deposits have been discovered in many small intrusions. Therefore, research and exploration direction having great potentialities for the magmatic deposits of small intrusions is defined. The Jinchuan and Panzhihua deposits represent two important types of the magmatic deposits in China.

Keywords： small rockbody     magmatic deposits     exploration    

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Ionic Elastomers for Electric Actuators and Sensors Review

Chenrun Feng, C.P. Hemantha Rajapaksha, Antal Jákli

Engineering 2021, Volume 7, Issue 5,   Pages 581-602 doi: 10.1016/j.eng.2021.02.014

Abstract:

In the past decades, ion conductive polymers and elastomers have drawn worldwide attention for their advanced functions in batteries, electroactive soft robotics, and sensors. Stretchable ionic elastomers with dispersed soft ionic moieties such as ionic liquids have gained remarkable attention as soft sensors, in applications such as the wearable devices that are often called electric skins. A considerable amount of research has been done on ionic-elastomer-based strain, pressure, and shear sensors; however, to the best of our knowledge, this research has not yet been reviewed. In this review, we summarize the materials and performance properties of engineered ionic elastomer actuators and sensors. First, we review three classes of ionic elastomer actuators—namely, ionic polymer metal composites, ionic conducting polymers, and ionic polymer/carbon nanocomposites—and provide perspectives for future actuators, such as adaptive four-dimensional (4D) printed systems and ionic liquid crystal elastomers (iLCEs). Next, we review the state of the art of ionic elastomeric strain and pressure sensors. We also discuss future wearable strain sensors for biomechanical applications and sports performance tracking. Finally, we present the preliminary results of iLCE sensors based on flexoelectric signals and their amplification by integrating them with organic electrochemical transistors.

Keywords： Soft robots     Ionic electroactive elastomer     Ionic elastomer sensor     Programmable deformation     Liquid crystal elastomer    

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The Research of Discovery Feature Sub-space Model (DFSSM) Based on Complex Type Data

Yang Bingru,Tang Qing

Strategic Study of CAE 2003, Volume 5, Issue 1,   Pages 56-61

Abstract:

This paper discusses the macroscopic and important problem in the field of KDD. First, it is very difficult to describe the complex type data by general knowledge representation method. So the authors use pattern, which is defined as the vector in Hilbert Space, to represent the characteristic of complex type data. It also can be used to describe the rule of knowledge discovery. Second, the general structure model is constructed based on complex type data—DFSSM (discovery feature sub-space model ) following by the research on inner mechanism of knowledge discovery system. At last, the authors prove the practicability and validity of this general structure model i. e. DFSSM which can guide the knowledge discovery of textual data and image data (meteorological echogram data). It will beapplied in other complex type data in future.

Keywords： complex type data     data mining     text mining    

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Big data storage technologies: a survey Review

Aisha SIDDIQA, Ahmad KARIM, Abdullah GANI

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 8,   Pages 1040-1070 doi: 10.1631/FITEE.1500441

Abstract: There is a great thrust in industry toward the development of more feasible and viable tools for storing fast-growing volume, velocity, and diversity of data, termed ‘big data’. The structural shift of the storage mechanism from traditional data management systems to NoSQL technology is due to the intention of fulfilling big data storage requirements. However, the available big data storage technologies are inefficient to provide consistent, scalable, and available solutions for continuously growing heterogeneous data. Storage is the preliminary process of big data analytics for real-world applications such as scientific experiments, healthcare, social networks, and e-business. So far, Amazon, Google, and Apache are some of the industry standards in providing big data storage solutions, yet the literature does not report an in-depth survey of storage technologies available for big data, investigating the performance and magnitude gains of these technologies. The primary objective of this paper is to conduct a comprehensive investigation of state-of-the-art storage technologies available for big data. A well-defined taxonomy of big data storage technologies is presented to assist data analysts and researchers in understanding and selecting a storage mechanism that better fits their needs. To evaluate the performance of different storage architectures, we compare and analyze the existing approaches using Brewer’s CAP theorem. The significance and applications of storage technologies and support to other categories are discussed. Several future research challenges are highlighted with the intention to expedite the deployment of a reliable and scalable storage system.

Keywords： Big data     Big data storage     NoSQL databases     Distributed databases     CAP theorem     Scalability     Consistency- partition resilience     Availability-partition resilience    

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Prompting the construction of national land observation data center and improving data sharing

Guo Jianning,Lu Shuning,Zhao Xiang

Strategic Study of CAE 2008, Volume 10, Issue 6,   Pages 70-75

Abstract:

This paper discussed the developing trend of the foreign land observation data processing center and the problems of our country land observation data management. The developing trend of the foreign land observation data processing center are: building up the concentrative data processing center and providing comprehensive service;building up the data sharing mechanism, improving the data sharing and servicing;reforming and integrating data resources. In order to improve the land observation data sharing and applications, it is necessary to build up the national land observation data center. The construction of the national land observation data center includes the facility of comprehensive data processing, archiving, distributing and service and so on. The national land observation data center will improve the land observation data sharing and application; satisfy the requirement of land observation data.

Keywords： satellite of remote sensing     land observation     data sharing     data center    

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View and Comments on the Data Ecosystem: “Ocean of Data”

Zi-Kui Liu

Engineering 2020, Volume 6, Issue 6,   Pages 604-608 doi: 10.1016/j.eng.2020.04.009

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Conception and Exploration of Using Data as a Service in Tunnel Construction with the NATM Article

Bowen Du, Yanliang Du, Fei Xu, Peng He

Engineering 2018, Volume 4, Issue 1,   Pages 123-130 doi: 10.1016/j.eng.2017.07.002

Abstract:

The New Austrian Tunneling Method (NATM) has been widely used in the construction of mountain tunnels, urban metro lines, underground storage tanks, underground power houses, mining roadways, and so on. The variation patterns of advance geological prediction data, stress–strain data of supporting structures, and deformation data of the surrounding rock are vitally important in assessing the rationality and reliability of construction schemes, and provide essential information to ensure the safety and scheduling of tunnel construction. However, as the quantity of these data increases significantly, the uncertainty and discreteness of the mass data make it extremely difficult to produce a reasonable construction scheme; they also reduce the forecast accuracy of accidents and dangerous situations, creating huge challenges in tunnel construction safety. In order to solve this problem, a novel data service system is proposed that uses data-association technology and the NATM, with the support of a big data environment. This system can integrate data resources from distributed monitoring sensors during the construction process, and then identify associations and build relations among data resources under the same construction conditions. These data associations and relations are then stored in a data pool. With the development and supplementation of the data pool, similar relations can then be used under similar conditions, in order to provide data references for construction schematic designs and resource allocation. The proposed data service system also provides valuable guidance for the construction of similar projects

Keywords： New Austrian Tunneling Method     Big data environments     Data as a service     Tunnel construction    

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Data-Driven Learning for Data Rights, Data Pricing, and Privacy Computing Review

Jimin Xu, Nuanxin Hong, Zhening Xu, Zhou Zhao, Chao Wu, Kun Kuang, Jiaping Wang, Mingjie Zhu, Jingren Zhou, Kui Ren, Xiaohu Yang, Cewu Lu, Jian Pei, Harry Shum

Engineering 2023, Volume 25, Issue 6,   Pages 66-76 doi: 10.1016/j.eng.2022.12.008

Abstract:


In recent years, data has become one of the most important resources in the digital economy. Unlike traditional resources, the digital nature of data makes it difficult to value and contract. Therefore, establishing an efficient and standard data-transaction market system would be beneficial for lowering cost and improving productivity among the parties in this industry. Although numerous studies have been dedicated to the issue of complying with data regulations and other data-transaction issues such as privacy and pricing, little work has been done to provide a comprehensive review of these studies in the fields of machine learning and data science. To provide a complete and up-to-date understanding of this topic, this review covers the three key issues of data transaction: data rights, data pricing, and privacy computing. By connecting these topics, this paper provides a big picture of a data ecosystem in which data is generated by data subjects such as individuals, research agencies, and governments, while data processors acquire data for innovational or operational purposes, and benefits are allocated according to the data’s respective ownership via an appropriate price. With the long-term goal of making artificial intelligence (AI) beneficial to human society, AI algorithms will then be assessed by data protection regulations (i.e., privacy protection regulations) to help build trustworthy AI systems for daily life.

Keywords： Data science     Artificial intelligence     Data rights     Data pricing     Privacy computing    

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Title Author Date Type Operation

Predicting gas reservoir of Puguang Gas Field by applying seismic data structure characteristics abnormality method

Zeng Daqian,Lin Changrong,Zhang Shimin,Peng Xinling

Journal Article

GPU-based multi-slice per pass algorithm in interactive volume illumination rendering

Dening Luo, Yi Lin, Jianwei Zhang,onexinoneyi@hotmail.com,Yilin@scu.edu.cn,zhangjianwei@scu.edu.cn

Journal Article

A GIS Open-Data Co-Simulation Platform for Photovoltaic Integration in Residential Urban Areas

Marco Massano, Enrico Macii, Andrea Lanzini, Edoardo Patti, Lorenzo Bottaccioli

Journal Article

Multi-agent differential game based cooperative synchronization control using a data-driven method

Yu SHI, Yongzhao HUA, Jianglong YU, Xiwang DONG, Zhang REN

Journal Article

The Formation of Tetraploid Hybrids of Common Carp with Red Crucian Carp and the Evolutionary Significance of Tetraploidization in Vertebrate

Liu Shaojun,Cao Yunzhang,He Xiaoxiao,Li Jianzhong,Liu Yun

Journal Article

Overall Conception and Development Suggestions for the Systematic Construction of Smart Society

Lei Bin, Lan Yushi, Li Maolin, Pan Jianqun, Zhou Zhongyuan, Zhang Chunhui

Journal Article

The Mechanics of 3D Multi-body Contact System of Long Shell and Tyres

Liang Xiaoling,Xiao Yougang,Li Xuejun

Journal Article

Magmatic Ore Deposits in Small Rockbody in China

Tang Zhongli

Journal Article

Ionic Elastomers for Electric Actuators and Sensors

Chenrun Feng, C.P. Hemantha Rajapaksha, Antal Jákli

Journal Article

The Research of Discovery Feature Sub-space Model (DFSSM) Based on Complex Type Data

Yang Bingru,Tang Qing

Journal Article

Big data storage technologies: a survey

Aisha SIDDIQA, Ahmad KARIM, Abdullah GANI

Journal Article

Prompting the construction of national land observation data center and improving data sharing

Guo Jianning,Lu Shuning,Zhao Xiang

Journal Article

View and Comments on the Data Ecosystem: “Ocean of Data”

Zi-Kui Liu

Journal Article

Conception and Exploration of Using Data as a Service in Tunnel Construction with the NATM

Bowen Du, Yanliang Du, Fei Xu, Peng He

Journal Article

Data-Driven Learning for Data Rights, Data Pricing, and Privacy Computing

Jimin Xu, Nuanxin Hong, Zhening Xu, Zhou Zhao, Chao Wu, Kun Kuang, Jiaping Wang, Mingjie Zhu, Jingren Zhou, Kui Ren, Xiaohu Yang, Cewu Lu, Jian Pei, Harry Shum

Journal Article