Accurately and efficiently predicting the permeability of porous media is essential for addressing a wide range of hydrogeological issues.However,the complexity of porous media often limits the effectiveness of indivi...Accurately and efficiently predicting the permeability of porous media is essential for addressing a wide range of hydrogeological issues.However,the complexity of porous media often limits the effectiveness of individual prediction methods.This study introduces a novel Particle Swarm Optimization-based Permeability Integrated Prediction model(PSO-PIP),which incorporates a particle swarm optimization algorithm enhanced with dy-namic clustering and adaptive parameter tuning(KGPSO).The model integrates multi-source data from the Lattice Boltzmann Method(LBM),Pore Network Modeling(PNM),and Finite Difference Method(FDM).By assigning optimal weight coefficients to the outputs of these methods,the model minimizes deviations from actual values and enhances permeability prediction performance.Initially,the computational performances of the LBM,PNM,and FDM are comparatively analyzed on datasets consisting of sphere packings and real rock samples.It is observed that these methods exhibit computational biases in certain permeability ranges.The PSOPIP model is proposed to combine the strengths of each computational approach and mitigate their limitations.The PSO-PIP model consistently produces predictions that are highly congruent with actual permeability values across all prediction intervals,significantly enhancing prediction accuracy.The outcomes of this study provide a new tool and perspective for the comprehensive,rapid,and accurate prediction of permeability in porous media.展开更多
One of the core developments in geomathematics in now days is the use of digital data processing in mineral prospecting and assessment. The information discovery is based on multidisciplinary geoscientific data and an...One of the core developments in geomathematics in now days is the use of digital data processing in mineral prospecting and assessment. The information discovery is based on multidisciplinary geoscientific data and an integrated management approach is crucial. The lack of a standard description hinders interoperations in database search and discovery. Metadata hierarchy aims to provide a standard view of the geoscientific data, and facilitate data description and discovery. In the research of integrated geoscientific database, the metadata hierarchy used a standardized description for each collection in the content structure and realized in semantic structure. It recorded both dataset identification and inner structures and relationships of objects, thus differed from many other applications. There were four tiers in the content structure and three levels in the semantic structure. With its help, database users could determine how applicable a dataset is to a project, and improve their queries to the database. Effectiveness of data accessing is significantly enhanced through the rich, consistent metadata.展开更多
This paper analyzes the status of existing resources through extensive research and international cooperation on the basis of four typical global monthly surface temperature datasets including the climate research dat...This paper analyzes the status of existing resources through extensive research and international cooperation on the basis of four typical global monthly surface temperature datasets including the climate research dataset of the University of East Anglia(CRUTEM3), the dataset of the U.S. National Climatic Data Center(GHCN-V3), the dataset of the U.S. National Aeronautics and Space Administration(GISSTMP), and the Berkeley Earth surface temperature dataset(Berkeley). China's first global monthly temperature dataset over land was developed by integrating the four aforementioned global temperature datasets and several regional datasets from major countries or regions. This dataset contains information from 9,519 stations worldwide of at least 20 years for monthly mean temperature, 7,073 for maximum temperature, and 6,587 for minimum temperature. Compared with CRUTEM3 and GHCN-V3, the station density is much higher particularly for South America, Africa,and Asia. Moreover, data from significantly more stations were available after the year 1990 which dramatically reduced the uncertainty of the estimated global temperature trend during 1990e2011. The integrated dataset can serve as a reliable data source for global climate change research.展开更多
The space-air-ground integrated network(SAGIN)combines the superiority of the satellite,aerial,and ground communications,which is envisioned to provide high-precision positioning ability as well as seamless connectivi...The space-air-ground integrated network(SAGIN)combines the superiority of the satellite,aerial,and ground communications,which is envisioned to provide high-precision positioning ability as well as seamless connectivity in the 5G and Beyond 5G(B5G)systems.In this paper,we propose a three-dimensional SAGIN localization scheme for ground agents utilizing multi-source information from satellites,base stations and unmanned aerial vehicles(UAVs).Based on the designed scheme,we derive the positioning performance bound and establish a distributed maximum likelihood algorithm to jointly estimate the positions and clock offsets of ground agents.Simulation results demonstrate the validity of the SAGIN localization scheme and reveal the effects of the number of satellites,the number of base stations,the number of UAVs and clock noise on positioning performance.展开更多
The good estimation consistency of Invariant Extended Kalman Filter(InEKF)is mainly attributed to its excellent trajectory-independent property.However,when the InEKF is applied to multi-source inertial-based navigati...The good estimation consistency of Invariant Extended Kalman Filter(InEKF)is mainly attributed to its excellent trajectory-independent property.However,when the InEKF is applied to multi-source inertial-based navigation that coexists left-invariant and right-invariant observations,the observation matrix would be unavoidably trajectory-dependent and might lead to the degradation of estimation performance.This paper for the first time performs theoretical analyses on the covariance switch between the left error and the right error in multi-source inertial-based navigation.Furthermore,detailed realizations of the covariance switch-based InEKF are formulated in this work,which are lacked in previous works.Numerical simulations and experiments demonstrate that the covariance switch significantly reduces the attitude errors during the transient phase in contrast with the original method using the incompatible error definition.展开更多
With extensive application of building information modeling(BIM),vast BIM model resources have accumulated from both new and existing projects.Digital twins,a key application of these models,face two main challenges:e...With extensive application of building information modeling(BIM),vast BIM model resources have accumulated from both new and existing projects.Digital twins,a key application of these models,face two main challenges:exponential growth in geometric and attribute data,risking data explosion,and low data utilization due to insufficient semantic association among multi-source data across projects and domains.This paper addresses the challenge of reducing system complexity via scenario-driven methods while achieving deep semantic integration of cross-domain BIM data.It proposes an ontology-based“Digital Theater”framework that defines data boundaries based on scenario requirements and employs dynamic trimming strategies to reduce complexity.By combining a simplified data standard with a multi-domain fusion ontology model,the framework constructs scenario-based data integration rules for semantic alignment.An adaptive relational database with object storage design further supports efficient engineering data storage and utilization.The proposed method significantly reduces the complexity of data processing,enabling the integrated application of multi-domain data at a lower cost while enhancing the decision-support capabilities of BIM data.This framework demonstrates potential for application in diverse scenarios,supporting engineering digitalization and smart city development.展开更多
For the integrity monitoring of a multi-source PNT(Positioning,Navigation,and Timing)resilient fusion navigation system,a theoretical framework of multi-level autonomous integrity monitoring is proposed.According to t...For the integrity monitoring of a multi-source PNT(Positioning,Navigation,and Timing)resilient fusion navigation system,a theoretical framework of multi-level autonomous integrity monitoring is proposed.According to the mode of multi-source fusion navigation,the framework adopts the top-down logic structure and establishes the navigation source fault detection model based on the multi-combination separation residual method to detect and isolate the fault source at the system level and subsystem level.For isolated non-redundant navigation sources,the system level recovery verification model is used.For the isolated multi-redundant navigation sources,the sensor fault detection model optimized with the dimension-expanding matrix is used to detect and isolate the fault sensors,and the isolated fault sensors are verified in real-time.Finally,according to the fault detection and verification results at each level,the observed information in the fusion navigation solution is dynamically adjusted.On this basis,the integrity risk dynamic monitoring tree is established to calculate the Protection Level(PL)and evaluate the integrity of the multi-source integrated navigation system.The autonomous integrity monitoring method proposed in this paper is tested using a multi-source navigation system integrated with Inertial Navigation System(INS),Global Navigation Satellite System(GNSS),Long Baseline Location(LBL),and Ultra Short Baseline Location(USBL).The test results show that the proposed method can effectively isolate the fault source within 5 s,and can quickly detect multiple faulty sensors,ensuring that the positioning accuracy of the fusion navigation system is within 5 m,effectively improving the resilience and reliability of the multi-source fusion navigation system.展开更多
A brand new design of integrated corrosion information system is introduced to meet the constantly increasing demands of material corrosion information. Two concepts, "general-purpose corrosion data model" a...A brand new design of integrated corrosion information system is introduced to meet the constantly increasing demands of material corrosion information. Two concepts, "general-purpose corrosion data model" and "public corrosion data ex-changing interface", are suggested to integrate a wide variety of corrosion data sources based on detailed analysis on characteristics of each source in order to promote the information sharing and data mining. The architecture of integrated corrosion information environment is blueprinted. The insight analysis is focused on 1) architecture of the system; 2) data flow and information sharing; 3) roles of system players and their interactions; 4) approaches to data integration. Several key issues are addressed in detail including coverage of data model, data source integration and mitigation, and data granularity from system performance and model acceptance points of view. At the end, the design and implementation ap-proach of general corrosion data model is presented based on cutting edge IT techniques.展开更多
基金supported by the National Key Research and Devel-opment Program of China (Grant No.2022YFC3005503)the National Natural Science Foundation of China (Grant Nos.52322907,52179141,U23B20149,U2340232)+1 种基金the Fundamental Research Funds for the Central Universities (Grant Nos.2042024kf1031,2042024kf0031)the Key Program of Science and Technology of Yunnan Province (Grant Nos.202202AF080004,202203AA080009).
文摘Accurately and efficiently predicting the permeability of porous media is essential for addressing a wide range of hydrogeological issues.However,the complexity of porous media often limits the effectiveness of individual prediction methods.This study introduces a novel Particle Swarm Optimization-based Permeability Integrated Prediction model(PSO-PIP),which incorporates a particle swarm optimization algorithm enhanced with dy-namic clustering and adaptive parameter tuning(KGPSO).The model integrates multi-source data from the Lattice Boltzmann Method(LBM),Pore Network Modeling(PNM),and Finite Difference Method(FDM).By assigning optimal weight coefficients to the outputs of these methods,the model minimizes deviations from actual values and enhances permeability prediction performance.Initially,the computational performances of the LBM,PNM,and FDM are comparatively analyzed on datasets consisting of sphere packings and real rock samples.It is observed that these methods exhibit computational biases in certain permeability ranges.The PSOPIP model is proposed to combine the strengths of each computational approach and mitigate their limitations.The PSO-PIP model consistently produces predictions that are highly congruent with actual permeability values across all prediction intervals,significantly enhancing prediction accuracy.The outcomes of this study provide a new tool and perspective for the comprehensive,rapid,and accurate prediction of permeability in porous media.
基金Funded by the National 863 Program of China (No.2002AA130406)the Key Project of China Geological Survey (No.200218310077).
文摘One of the core developments in geomathematics in now days is the use of digital data processing in mineral prospecting and assessment. The information discovery is based on multidisciplinary geoscientific data and an integrated management approach is crucial. The lack of a standard description hinders interoperations in database search and discovery. Metadata hierarchy aims to provide a standard view of the geoscientific data, and facilitate data description and discovery. In the research of integrated geoscientific database, the metadata hierarchy used a standardized description for each collection in the content structure and realized in semantic structure. It recorded both dataset identification and inner structures and relationships of objects, thus differed from many other applications. There were four tiers in the content structure and three levels in the semantic structure. With its help, database users could determine how applicable a dataset is to a project, and improve their queries to the database. Effectiveness of data accessing is significantly enhanced through the rich, consistent metadata.
基金supported by the China Meteorological Administration Special Public Welfare Research Fund (GYHY201206012, GYHY201406016)the Climate Change Foundation of the China Meteorological Administration (CCSF201338)
文摘This paper analyzes the status of existing resources through extensive research and international cooperation on the basis of four typical global monthly surface temperature datasets including the climate research dataset of the University of East Anglia(CRUTEM3), the dataset of the U.S. National Climatic Data Center(GHCN-V3), the dataset of the U.S. National Aeronautics and Space Administration(GISSTMP), and the Berkeley Earth surface temperature dataset(Berkeley). China's first global monthly temperature dataset over land was developed by integrating the four aforementioned global temperature datasets and several regional datasets from major countries or regions. This dataset contains information from 9,519 stations worldwide of at least 20 years for monthly mean temperature, 7,073 for maximum temperature, and 6,587 for minimum temperature. Compared with CRUTEM3 and GHCN-V3, the station density is much higher particularly for South America, Africa,and Asia. Moreover, data from significantly more stations were available after the year 1990 which dramatically reduced the uncertainty of the estimated global temperature trend during 1990e2011. The integrated dataset can serve as a reliable data source for global climate change research.
文摘The space-air-ground integrated network(SAGIN)combines the superiority of the satellite,aerial,and ground communications,which is envisioned to provide high-precision positioning ability as well as seamless connectivity in the 5G and Beyond 5G(B5G)systems.In this paper,we propose a three-dimensional SAGIN localization scheme for ground agents utilizing multi-source information from satellites,base stations and unmanned aerial vehicles(UAVs).Based on the designed scheme,we derive the positioning performance bound and establish a distributed maximum likelihood algorithm to jointly estimate the positions and clock offsets of ground agents.Simulation results demonstrate the validity of the SAGIN localization scheme and reveal the effects of the number of satellites,the number of base stations,the number of UAVs and clock noise on positioning performance.
基金supported by National Key R&D Program(2022YFB3903802)National Natural Science Foundation(62303310,62273228)
文摘The good estimation consistency of Invariant Extended Kalman Filter(InEKF)is mainly attributed to its excellent trajectory-independent property.However,when the InEKF is applied to multi-source inertial-based navigation that coexists left-invariant and right-invariant observations,the observation matrix would be unavoidably trajectory-dependent and might lead to the degradation of estimation performance.This paper for the first time performs theoretical analyses on the covariance switch between the left error and the right error in multi-source inertial-based navigation.Furthermore,detailed realizations of the covariance switch-based InEKF are formulated in this work,which are lacked in previous works.Numerical simulations and experiments demonstrate that the covariance switch significantly reduces the attitude errors during the transient phase in contrast with the original method using the incompatible error definition.
基金supported by the National Key Research and Development Program of China“Comprehensive Application Demonstration of Self-developed BIM Platform in the Full Life Cycle of Engineering Construction”(Grant No.2024YFC3809700)。
文摘With extensive application of building information modeling(BIM),vast BIM model resources have accumulated from both new and existing projects.Digital twins,a key application of these models,face two main challenges:exponential growth in geometric and attribute data,risking data explosion,and low data utilization due to insufficient semantic association among multi-source data across projects and domains.This paper addresses the challenge of reducing system complexity via scenario-driven methods while achieving deep semantic integration of cross-domain BIM data.It proposes an ontology-based“Digital Theater”framework that defines data boundaries based on scenario requirements and employs dynamic trimming strategies to reduce complexity.By combining a simplified data standard with a multi-domain fusion ontology model,the framework constructs scenario-based data integration rules for semantic alignment.An adaptive relational database with object storage design further supports efficient engineering data storage and utilization.The proposed method significantly reduces the complexity of data processing,enabling the integrated application of multi-domain data at a lower cost while enhancing the decision-support capabilities of BIM data.This framework demonstrates potential for application in diverse scenarios,supporting engineering digitalization and smart city development.
基金The project is supported by the National key research and development program of China(Grant No.2020YFB0505804)the National Natural Science Foundation of China(Grant No.42274037,41874034)the Beijing Natural Science Foundation(Grant No.4202041).
文摘For the integrity monitoring of a multi-source PNT(Positioning,Navigation,and Timing)resilient fusion navigation system,a theoretical framework of multi-level autonomous integrity monitoring is proposed.According to the mode of multi-source fusion navigation,the framework adopts the top-down logic structure and establishes the navigation source fault detection model based on the multi-combination separation residual method to detect and isolate the fault source at the system level and subsystem level.For isolated non-redundant navigation sources,the system level recovery verification model is used.For the isolated multi-redundant navigation sources,the sensor fault detection model optimized with the dimension-expanding matrix is used to detect and isolate the fault sensors,and the isolated fault sensors are verified in real-time.Finally,according to the fault detection and verification results at each level,the observed information in the fusion navigation solution is dynamically adjusted.On this basis,the integrity risk dynamic monitoring tree is established to calculate the Protection Level(PL)and evaluate the integrity of the multi-source integrated navigation system.The autonomous integrity monitoring method proposed in this paper is tested using a multi-source navigation system integrated with Inertial Navigation System(INS),Global Navigation Satellite System(GNSS),Long Baseline Location(LBL),and Ultra Short Baseline Location(USBL).The test results show that the proposed method can effectively isolate the fault source within 5 s,and can quickly detect multiple faulty sensors,ensuring that the positioning accuracy of the fusion navigation system is within 5 m,effectively improving the resilience and reliability of the multi-source fusion navigation system.
文摘A brand new design of integrated corrosion information system is introduced to meet the constantly increasing demands of material corrosion information. Two concepts, "general-purpose corrosion data model" and "public corrosion data ex-changing interface", are suggested to integrate a wide variety of corrosion data sources based on detailed analysis on characteristics of each source in order to promote the information sharing and data mining. The architecture of integrated corrosion information environment is blueprinted. The insight analysis is focused on 1) architecture of the system; 2) data flow and information sharing; 3) roles of system players and their interactions; 4) approaches to data integration. Several key issues are addressed in detail including coverage of data model, data source integration and mitigation, and data granularity from system performance and model acceptance points of view. At the end, the design and implementation ap-proach of general corrosion data model is presented based on cutting edge IT techniques.
