Multivariate anomaly detection plays a critical role in maintaining the stable operation of information systems.However,in existing research,multivariate data are often influenced by various factors during the data co...Multivariate anomaly detection plays a critical role in maintaining the stable operation of information systems.However,in existing research,multivariate data are often influenced by various factors during the data collection process,resulting in temporal misalignment or displacement.Due to these factors,the node representations carry substantial noise,which reduces the adaptability of the multivariate coupled network structure and subsequently degrades anomaly detection performance.Accordingly,this study proposes a novel multivariate anomaly detection model grounded in graph structure learning.Firstly,a recommendation strategy is employed to identify strongly coupled variable pairs,which are then used to construct a recommendation-driven multivariate coupling network.Secondly,a multi-channel graph encoding layer is used to dynamically optimize the structural properties of the multivariate coupling network,while a multi-head attention mechanism enhances the spatial characteristics of the multivariate data.Finally,unsupervised anomaly detection is conducted using a dynamic threshold selection algorithm.Experimental results demonstrate that effectively integrating the structural and spatial features of multivariate data significantly mitigates anomalies caused by temporal dependency misalignment.展开更多
Enterprise applications utilize relational databases and structured business processes, requiring slow and expensive conversion of inputs and outputs, from business documents such as invoices, purchase orders, and rec...Enterprise applications utilize relational databases and structured business processes, requiring slow and expensive conversion of inputs and outputs, from business documents such as invoices, purchase orders, and receipts, into known templates and schemas before processing. We propose a new LLM Agent-based intelligent data extraction, transformation, and load (IntelligentETL) pipeline that not only ingests PDFs and detects inputs within it but also addresses the extraction of structured and unstructured data by developing tools that most efficiently and securely deal with respective data types. We study the efficiency of our proposed pipeline and compare it with enterprise solutions that also utilize LLMs. We establish the supremacy in timely and accurate data extraction and transformation capabilities of our approach for analyzing the data from varied sources based on nested and/or interlinked input constraints.展开更多
The local overheating issue is a serious threat to the safe operation of data centers(DCs).The chip level liquid cooling with pool boiling is expected to solve this problem.The effect of nano configuration and surface...The local overheating issue is a serious threat to the safe operation of data centers(DCs).The chip level liquid cooling with pool boiling is expected to solve this problem.The effect of nano configuration and surface wettability on the boiling characteristics of copper surfaces is studied using molecular dynamics(MD)simulation.The argon is chosen as the coolant,and the wall temperature is 300 K.The main findings and innovations are as follows.(1)Compared to the smooth surface and fin surface,the cylindrical nano cavity obtains the superior boiling performance with earlier onset of nucleate boiling(ONB),larger heat flux because of the higher heat transport rate.(2)The nano cavity with hydrophilicity can improve the response speed and heat dissipation efficiency.Compared to the contact angleθ=121°,the formation times of nucleate bubble and film boiling for theθ=0°are reduced by 90.84%and 93.57%,respectively.(3)A deeper cavity of 3.3 nm is beneficial for triggering boiling and improving the heat dissipation rate.The highest heat flux can be achieved at 21.86 x 10°W/m2,which can meet the cooling requirements of the micro devices with ultra-high heat flux(107-108 W/m2).The coupling effect of nano configuration and surface wettability is illustrated,and the essential reasons for the enhanced heat transport are revealed.The findings can guide the optimization of cooling systems and promote the practical application of phase change liquid cooling in DCs.展开更多
The boundary layer structure and related heavy rainfall of Typhoon Fitow(2013), which made landfall in Zhejiang Province, China, are studied using the Advanced Research version of the Weather Research and Forecasting ...The boundary layer structure and related heavy rainfall of Typhoon Fitow(2013), which made landfall in Zhejiang Province, China, are studied using the Advanced Research version of the Weather Research and Forecasting model, with a focus on the sensitivity of the simulation to the planetary boundary layer parameterization. Two groups of experiments—one with the same surface layer scheme and including the Yonsei University(YSU), Mellor–Yamada–Nakanishi–Niino Level 2.5,and Bougeault and Lacarrere schemes; and the other with different surface layer schemes and including the Mellor–Yamada–Janjic′ and Quasi-Normal Scale Elimination schemes—are investigated. For the convenience of comparative analysis, the simulation with the YSU scheme is chosen as the control run because this scheme successfully reproduces the track, intensity and rainfall as a whole. The maximum deviations in the peak tangential and peak radial winds may account for 11% and 33%of those produced in the control run, respectively. Further diagnosis indicates that the vertical diffusivity is much larger in the first group, resulting in weaker vertical shear of the tangential and radial winds in the boundary layer and a deeper inflow layer therein. The precipitation discrepancies are related to the simulated track deflection and the differences in the simulated low-level convergent flow among all tests. Furthermore, the first group more efficiently transfers moisture and energy and produces a stronger ascending motion than the second, contributing to a deeper moist layer, stronger convection and greater precipitation.展开更多
Addressing the current challenges in transforming pixel displacement into physical displacement in visual monitoring technologies,as well as the inability to achieve precise full-field monitoring,this paper proposes a...Addressing the current challenges in transforming pixel displacement into physical displacement in visual monitoring technologies,as well as the inability to achieve precise full-field monitoring,this paper proposes a method for identifying the structural dynamic characteristics of wind turbines based on visual monitoring data fusion.Firstly,the Lucas-Kanade Tomasi(LKT)optical flow method and a multi-region of interest(ROI)monitoring structure are employed to track pixel displacements,which are subsequently subjected to band pass filtering and resampling operations.Secondly,the actual displacement time history is derived through double integration of the acquired acceleration data and subsequent band pass filtering.The scale factor is obtained by applying the least squares method to compare the visual displacement with the displacement derived from double integration of the acceleration data.Based on this,the multi-point displacement time histories under physical coordinates are obtained using the vision data and the scale factor.Subsequently,when visual monitoring of displacements becomes impossible due to issues such as image blurring or lens occlusion,the structural vibration equation and boundary condition constraints,among other key parameters,are employed to predict the displacements at unknown monitoring points,thereby enabling full-field displacement monitoring and dynamic characteristic testing of the structure.Finally,a small-scale shaking table test was conducted on a simulated wind turbine structure undergoing shutdown to validate the dynamic characteristics of the proposed method through test verification.The research results indicate that the proposed method achieves a time-domain error within the submillimeter range and a frequency-domain accuracy of over 99%,effectively monitoring the full-field structural dynamic characteristics of wind turbines and providing a basis for the condition assessment of wind turbine structures.展开更多
Multi-source data fusion provides high-precision spatial situational awareness essential for analyzing granular urban social activities.This study used Shanghai’s catering industry as a case study,leveraging electron...Multi-source data fusion provides high-precision spatial situational awareness essential for analyzing granular urban social activities.This study used Shanghai’s catering industry as a case study,leveraging electronic reviews and consumer data sourced from third-party restaurant platforms collected in 2021.By performing weighted processing on two-dimensional point-of-interest(POI)data,clustering hotspots of high-dimensional restaurant data were identified.A hierarchical network of restaurant hotspots was constructed following the Central Place Theory(CPT)framework,while the Geo-Informatic Tupu method was employed to resolve the challenges posed by network deformation in multi-scale processes.These findings suggest the necessity of enhancing the spatial balance of Shanghai’s urban centers by moderately increasing the number and service capacity of suburban centers at the urban periphery.Such measures would contribute to a more optimized urban structure and facilitate the outward dispersion of comfort-oriented facilities such as the restaurant industry.At a finer spatial scale,the distribution of restaurant hotspots demonstrates a polycentric and symmetric spatial pattern,with a developmental trend radiating outward along the city’s ring roads.This trend can be attributed to the efforts of restaurants to establish connections with other urban functional spaces,leading to the reconfiguration of urban spaces,expansion of restaurant-dedicated land use,and the reorganization of associated commercial activities.The results validate the existence of a polycentric urban structure in Shanghai but also highlight the instability of the restaurant hotspot network during cross-scale transitions.展开更多
Stope mining design is a very important and complicated task in daily production design and technical management of an underground mine.Based on workface technology and human-computer interaction technology,this study...Stope mining design is a very important and complicated task in daily production design and technical management of an underground mine.Based on workface technology and human-computer interaction technology,this study introduces a method of 3D parametric design for the irregular structure of stope bottoms,and focuses on solving technical problems in surface modeling of stope bottom structure.Optimization of the minimum span length algorithm(MSLA) and the shortest path search algorithm(SPSA) is conducted to solve the problem of contour-line based instant modeling of stope bottom structures,which makes possible the 3D parametric design for irregular structure of stope bottom.Implementation process and relevant methods of the proposed algorithms are also presented.Feasibility and reliability of the proposed modeling method are testified in a case study.In practice,the proposed 3 D parameterization design method for irregular structure stope bottom proves to be very helpful to precise 3D parametric design.This method is capable of contributing to improved efficiency and precision of stope design,and is worthy of promotion.展开更多
To identify the model structure parameters in shaking table tests from seismic response, especially from time- varying response records, this paper presents a new methodology by combining the online recursive Adaptive...To identify the model structure parameters in shaking table tests from seismic response, especially from time- varying response records, this paper presents a new methodology by combining the online recursive Adaptive Forgetting through Multiple Models （AFMM） and offtine Auto-Regression with eXogenous variables （ARX） model. First, the AFMM is employed to detect whether the response of model structure is time-invariant or time-varying when subjected to strong motions. Second, if the response is time-invariant, the modal parameters are identified from the entire response record, such as the acceleration time-history using the ARX model. If the response is time-varying, the acceleration record is divided into three segments according to the accurate time-varying points detected by AFMM, and parameters are identified by only using the tail segment data, which is time-invariant and suited for analysis by the ARX model. Finally, the changes in dynamic properties due to various strong motions are obtained using the presented methodology. The feasibility and advantages of the method are demonstrated by identifying the modal parameters of a 12-story reinforced concrete （RC） frame structure in a shaking table test.展开更多
Lattice structures with excellent physical properties have attracted great research interest.In this paper,a novel volume parametric modeling method based on the skeleton model is proposed for the construction of thre...Lattice structures with excellent physical properties have attracted great research interest.In this paper,a novel volume parametric modeling method based on the skeleton model is proposed for the construction of threedimensional lattice structures.The skeleton model is divided into three types of nodes.And the corresponding algorithms are utilized to construct diverse types of volume parametric nodes.The unit-cell is assembled with distinct nodes according to the geometric features.The final lattice structure is created by the periodic arrangement of unit-cells.Several different types of volume parametric lattice structures are constructed to prove the stability and applicability of the proposed method.The quality is assessed in terms of the value of the Jacobian matrix.Moreover,the volume parametric lattice structures are tested with the isogeometric analysis to verify the feasibility of integration of modeling and simulation.展开更多
By using the high spatial and temporal resolution Jinan Doppler Weather Radar data and Jinan,Xingtai sounding data,the radar signature and mesocyclone parameters of 54 supercells during 2003-2008 were analyzed.The res...By using the high spatial and temporal resolution Jinan Doppler Weather Radar data and Jinan,Xingtai sounding data,the radar signature and mesocyclone parameters of 54 supercells during 2003-2008 were analyzed.The results showed that the probability of a supercell forming would be higher when SI (showalter index) ≤ -2℃,K (K index) ≥ 30℃ and 0-6 km wind shear>15 m/s.The supercell storms can generally be divided into two categories,namely,type of isolation and mosaic type.To the type of isolation,the max reflectivity,cell-based VIL,max reflectivity height,cell top,mesocyclone base and top were significantly higher than the mosaic type.Isolation-type supercells had significantly higher probability of hail,lower probability of gale than the mosaic category.The mesocyclone attribute differences between isolation-type and mosaic type supercells determined the differences of storm structures and severe weather phenomenon.展开更多
A robust and efficient algorithm is presented to build multiresolution models (MRMs) of arbitrary meshes without requirement of subdivision connectivity. To overcome the sampling difficulty of arbitrary meshes, edge c...A robust and efficient algorithm is presented to build multiresolution models (MRMs) of arbitrary meshes without requirement of subdivision connectivity. To overcome the sampling difficulty of arbitrary meshes, edge contraction and vertex expansion are used as downsampling and upsampling methods. Our MRMs of a mesh are composed of a base mesh and a series of edge split operations, which are organized as a directed graph. Each split operation encodes two parts of information. One is the modification to the mesh, and the other is the dependency relation among splits. Such organization ensures the efficiency and robustness of our MRM algorithm. Examples demonstrate the functionality of our method.展开更多
With a more complex pore structure system compared with clastic rocks, carbonate rocks have not yet been well described by existing conventional rock physical models concerning the pore structure vagary as well as the...With a more complex pore structure system compared with clastic rocks, carbonate rocks have not yet been well described by existing conventional rock physical models concerning the pore structure vagary as well as the influence on elastic rock properties. We start with a discussion and an analysis about carbonate rock pore structure utilizing rock slices. Then, given appropriate assumptions, we introduce a new approach to modeling carbonate rocks and construct a pore structure algorithm to identify pore structure mutation with a basis on the Gassmann equation and the Eshelby-Walsh ellipsoid inclusion crack theory. Finally, we compute a single well＇s porosity using this new approach with full wave log data and make a comparison with the predicted result of traditional method and simultaneously invert for reservoir parameters. The study results reveal that the rock pore structure can significantly influence the rocks＇ elastic properties and the predicted porosity error of the new modeling approach is merely 0.74%. Therefore, the approach we introduce can effectively decrease the predicted error of reservoir parameters.展开更多
Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters accordi...Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring(SHM)system,so as to provide a scientific basis for structural damage identification and dynamic model modification.In view of this,this paper reviews methods for identifying structural modal parameters under environmental excitation and briefly describes how to identify structural damages based on the derived modal parameters.The paper primarily introduces data-driven modal parameter recognition methods(e.g.,time-domain,frequency-domain,and time-frequency-domain methods,etc.),briefly describes damage identification methods based on the variations of modal parameters(e.g.,natural frequency,modal shapes,and curvature modal shapes,etc.)and modal validation methods(e.g.,Stability Diagram and Modal Assurance Criterion,etc.).The current status of the application of artificial intelligence(AI)methods in the direction of modal parameter recognition and damage identification is further discussed.Based on the pre-vious analysis,the main development trends of structural modal parameter recognition and damage identification methods are given to provide scientific references for the optimized design and functional upgrading of SHM systems.展开更多
More web pages are widely applying AJAX （Asynchronous JavaScript XML） due to the rich interactivity and incremental communication. By observing, it is found that the AJAX contents, which could not be seen by traditi...More web pages are widely applying AJAX （Asynchronous JavaScript XML） due to the rich interactivity and incremental communication. By observing, it is found that the AJAX contents, which could not be seen by traditional crawler, are well-structured and belong to one specific domain generally. Extracting the structured data from AJAX contents and annotating its semantic are very significant for further applications. In this paper, a structured AJAX data extraction method for agricultural domain based on agricultural ontology was proposed. Firstly, Crawljax, an open AJAX crawling tool, was overridden to explore and retrieve the AJAX contents; secondly, the retrieved contents were partitioned into items and then classified by combining with agricultural ontology. HTML tags and punctuations were used to segment the retrieved contents into entity items. Finally, the entity items were clustered and the semantic annotation was assigned to clustering results according to agricultural ontology. By experimental evaluation, the proposed approach was proved effectively in resource exploring, entity extraction, and semantic annotation.展开更多
In this paper, a new concept called numerical structure of seismic data is introduced and the difference between numerical structure and numerical value of seismic data is explained. Our study shows that the numerical...In this paper, a new concept called numerical structure of seismic data is introduced and the difference between numerical structure and numerical value of seismic data is explained. Our study shows that the numerical seismic structure is closely related to oil and gas-bearing reservoir, so it is very useful for a geologist or a geophysicist to precisely interpret the oil-bearing layers from the seismic data. This technology can be applied to any exploration or production stage. The new method has been tested on a series of exploratory or development wells and proved to be reliable in China. Hydrocarbon-detection with this new method for 39 exploration wells on 25 structures indi- cates a success ratio of over 80 percent. The new method of hydrocarbon prediction can be applied for: (1) depositional environment of reservoirs with marine fades, delta, or non-marine fades (including fluvial facies, lacustrine fades); (2) sedimentary rocks of reservoirs that are non-marine clastic rocks and carbonate rock; and (3) burial depths range from 300 m to 7000 m, and the minimum thickness of these reservoirs is over 8 m (main frequency is about 50 Hz).展开更多
In order to improve the quality of web search,a new query expansion method by choosing meaningful structure data from a domain database is proposed.It categories attributes into three different classes,named as concep...In order to improve the quality of web search,a new query expansion method by choosing meaningful structure data from a domain database is proposed.It categories attributes into three different classes,named as concept attribute,context attribute and meaningless attribute,according to their semantic features which are document frequency features and distinguishing capability features.It also defines the semantic relevance between two attributes when they have correlations in the database.Then it proposes trie-bitmap structure and pair pointer tables to implement efficient algorithms for discovering attribute semantic feature and detecting their semantic relevances.By using semantic attributes and their semantic relevances,expansion words can be generated and embedded into a vector space model with interpolation parameters.The experiments use an IMDB movie database and real texts collections to evaluate the proposed method by comparing its performance with a classical vector space model.The results show that the proposed method can improve text search efficiently and also improve both semantic features and semantic relevances with good separation capabilities.展开更多
By analyzing the optical spectra and electron paramagnetic resonance parameter D, the local structure distortion of （NiF6）4- clusters in AMF3 （A=K, Rb; M=Zn, Cd, Ca） and K2ZnF4 series are studied using the complet...By analyzing the optical spectra and electron paramagnetic resonance parameter D, the local structure distortion of （NiF6）4- clusters in AMF3 （A=K, Rb; M=Zn, Cd, Ca） and K2ZnF4 series are studied using the complete energy matrix based on the double spin-orbit coupling parameter model for configuration ions in a tetragonal ligand field. The results indicate that the contribution of ligand to spin-orbit coupling interaction should be considered for our studied systems. Moreover, the relationships between D and the spin-obit coupling coefficients as well as the average parameter and the divergent parameter are discussed.展开更多
Seismic data structure characteristics means the waveform character arranged in the time sequence at discrete data points in each 2-D or 3-D seismic trace. Hydrocarbon prediction using seismic data structure character...Seismic data structure characteristics means the waveform character arranged in the time sequence at discrete data points in each 2-D or 3-D seismic trace. Hydrocarbon prediction using seismic data structure characteristics is a new reservoir prediction technique. When the main pay interval is in carbonate fracture and fissure-cavern type reservoirs with very strong inhomogeneity, there are some difficulties with hydrocarbon prediction. Because of the special geological conditions of the eighth zone in the Tahe oil field, we apply seismic data structure characteristics to hydrocarbon prediction for the Ordovician reservoir in this zone. We divide the area oil zone into favorable and unfavorable blocks. Eighteen well locations were proposed in the favorable oil block, drilled, and recovered higher output of oil and gas.展开更多
To design a power source system and mold for electromagnetic soft-contact continuous casting process and to theoretically estimate the heat losses from the charges and the system power, the effect of structure paramet...To design a power source system and mold for electromagnetic soft-contact continuous casting process and to theoretically estimate the heat losses from the charges and the system power, the effect of structure parameters on system power and magnetic flux density distribution was calculated using finite element method. The results show that as for electromagnetic soft-contact continuous casting system with partial-segment type mold, the power consumption is much more than that with a full-segment type mold; about 62% of electric power is dissipated in the mold, and the effective acting range of magnetic field is relatively narrow. Optimizing mold structure is a crucial measure of remarkably reducing mold power consumption and saving electric energy. Increasing slit number, width, and length can remarkably increase the magnetic flux density in the mold and can reduce the electric energy consumption. Among structure parameters, slit number and slit width are relatively more effective to reduce energy consumption. For a round billet electromagnetic continuous casting system with diameter of 178 ram, the reasonable slit number, width, and length are about 24--32, 0. 5--1.0 mm, and 160 mm, respectively.展开更多
Mg–3Nd–0.2Zn–0.4Zr(NZ30K,wt.%)alloy is a new kind of high-performance metallic biomaterial.The combination of the NZ30K Magnesium(Mg)alloy and selective laser melting(SLM)process seems to be an ideal solution to pr...Mg–3Nd–0.2Zn–0.4Zr(NZ30K,wt.%)alloy is a new kind of high-performance metallic biomaterial.The combination of the NZ30K Magnesium(Mg)alloy and selective laser melting(SLM)process seems to be an ideal solution to produce porous Mg degradable implants.However,the microstructure evolution and mechanical properties of the SLMed NZ30K Mg alloy were not yet studied systematically.Therefore,the fabrication defects,microstructure,and mechanical properties of the SLMed NZ30K alloy under different processing parameters were investigated.The results show that there are two types of fabrication defects in the SLMed NZ30K alloy,gas pores and unfused defects.With the increase of the laser energy density,the porosity sharply decreases to the minimum first and then slightly increases.The minimum porosity is 0.49±0.18%.While the microstructure varies from the large grains with lamellar structure inside under low laser energy density,to the large grains with lamellar structure inside&the equiaxed grains&the columnar grains under middle laser energy density,and further to the fine equiaxed grains&the columnar grains under high laser energy density.The lamellar structure in the large grain is a newly observed microstructure for the NZ30K Mg alloy.Higher laser energy density leads to finer grains,which enhance all the yield strength(YS),ultimate tensile strength(UTS)and elongation,and the best comprehensive mechanical properties obtained are YS of 266±2.1 MPa,UTS of 296±5.2 MPa,with an elongation of 4.9±0.68%.The SLMed NZ30K Mg alloy with a bimodal-grained structure consisting of fine equiaxed grains and coarser columnar grains has better elongation and a yield drop phenomenon.展开更多
基金supported by Natural Science Foundation of Qinghai Province(2025-ZJ-994M)Scientific Research Innovation Capability Support Project for Young Faculty(SRICSPYF-BS2025007)National Natural Science Foundation of China(62566050).
文摘Multivariate anomaly detection plays a critical role in maintaining the stable operation of information systems.However,in existing research,multivariate data are often influenced by various factors during the data collection process,resulting in temporal misalignment or displacement.Due to these factors,the node representations carry substantial noise,which reduces the adaptability of the multivariate coupled network structure and subsequently degrades anomaly detection performance.Accordingly,this study proposes a novel multivariate anomaly detection model grounded in graph structure learning.Firstly,a recommendation strategy is employed to identify strongly coupled variable pairs,which are then used to construct a recommendation-driven multivariate coupling network.Secondly,a multi-channel graph encoding layer is used to dynamically optimize the structural properties of the multivariate coupling network,while a multi-head attention mechanism enhances the spatial characteristics of the multivariate data.Finally,unsupervised anomaly detection is conducted using a dynamic threshold selection algorithm.Experimental results demonstrate that effectively integrating the structural and spatial features of multivariate data significantly mitigates anomalies caused by temporal dependency misalignment.
文摘Enterprise applications utilize relational databases and structured business processes, requiring slow and expensive conversion of inputs and outputs, from business documents such as invoices, purchase orders, and receipts, into known templates and schemas before processing. We propose a new LLM Agent-based intelligent data extraction, transformation, and load (IntelligentETL) pipeline that not only ingests PDFs and detects inputs within it but also addresses the extraction of structured and unstructured data by developing tools that most efficiently and securely deal with respective data types. We study the efficiency of our proposed pipeline and compare it with enterprise solutions that also utilize LLMs. We establish the supremacy in timely and accurate data extraction and transformation capabilities of our approach for analyzing the data from varied sources based on nested and/or interlinked input constraints.
基金the National Natural Science Foundation of China (No. 52406191, No. 52408123)the Science and Technology Project of Tianjin (No. 24YDTPJC00680).
文摘The local overheating issue is a serious threat to the safe operation of data centers(DCs).The chip level liquid cooling with pool boiling is expected to solve this problem.The effect of nano configuration and surface wettability on the boiling characteristics of copper surfaces is studied using molecular dynamics(MD)simulation.The argon is chosen as the coolant,and the wall temperature is 300 K.The main findings and innovations are as follows.(1)Compared to the smooth surface and fin surface,the cylindrical nano cavity obtains the superior boiling performance with earlier onset of nucleate boiling(ONB),larger heat flux because of the higher heat transport rate.(2)The nano cavity with hydrophilicity can improve the response speed and heat dissipation efficiency.Compared to the contact angleθ=121°,the formation times of nucleate bubble and film boiling for theθ=0°are reduced by 90.84%and 93.57%,respectively.(3)A deeper cavity of 3.3 nm is beneficial for triggering boiling and improving the heat dissipation rate.The highest heat flux can be achieved at 21.86 x 10°W/m2,which can meet the cooling requirements of the micro devices with ultra-high heat flux(107-108 W/m2).The coupling effect of nano configuration and surface wettability is illustrated,and the essential reasons for the enhanced heat transport are revealed.The findings can guide the optimization of cooling systems and promote the practical application of phase change liquid cooling in DCs.
基金supported by the National Natural Science Foundation of China (Grant No. 41375056)the National Basic Research and Development Project (973 program) of China under contract no. 2015CB452805+2 种基金the National Key Technology R&D Program (Grant No. 2012BAC03)the Social Welfare Technology Development Projects of the Science and Technology Department of Zhejiang Province (Grant No. 2014C33056)the Key Project of Science and Technology Plan of Zhejiang Meteorological Provincial Bureau (2017ZD04)
文摘The boundary layer structure and related heavy rainfall of Typhoon Fitow(2013), which made landfall in Zhejiang Province, China, are studied using the Advanced Research version of the Weather Research and Forecasting model, with a focus on the sensitivity of the simulation to the planetary boundary layer parameterization. Two groups of experiments—one with the same surface layer scheme and including the Yonsei University(YSU), Mellor–Yamada–Nakanishi–Niino Level 2.5,and Bougeault and Lacarrere schemes; and the other with different surface layer schemes and including the Mellor–Yamada–Janjic′ and Quasi-Normal Scale Elimination schemes—are investigated. For the convenience of comparative analysis, the simulation with the YSU scheme is chosen as the control run because this scheme successfully reproduces the track, intensity and rainfall as a whole. The maximum deviations in the peak tangential and peak radial winds may account for 11% and 33%of those produced in the control run, respectively. Further diagnosis indicates that the vertical diffusivity is much larger in the first group, resulting in weaker vertical shear of the tangential and radial winds in the boundary layer and a deeper inflow layer therein. The precipitation discrepancies are related to the simulated track deflection and the differences in the simulated low-level convergent flow among all tests. Furthermore, the first group more efficiently transfers moisture and energy and produces a stronger ascending motion than the second, contributing to a deeper moist layer, stronger convection and greater precipitation.
基金supported by the National Science Foundation of China(Grant Nos.52068049 and 51908266)the Science Fund for Distinguished Young Scholars of Gansu Province(No.21JR7RA267)Hongliu Outstanding Young Talents Program of Lanzhou University of Technology.
文摘Addressing the current challenges in transforming pixel displacement into physical displacement in visual monitoring technologies,as well as the inability to achieve precise full-field monitoring,this paper proposes a method for identifying the structural dynamic characteristics of wind turbines based on visual monitoring data fusion.Firstly,the Lucas-Kanade Tomasi(LKT)optical flow method and a multi-region of interest(ROI)monitoring structure are employed to track pixel displacements,which are subsequently subjected to band pass filtering and resampling operations.Secondly,the actual displacement time history is derived through double integration of the acquired acceleration data and subsequent band pass filtering.The scale factor is obtained by applying the least squares method to compare the visual displacement with the displacement derived from double integration of the acceleration data.Based on this,the multi-point displacement time histories under physical coordinates are obtained using the vision data and the scale factor.Subsequently,when visual monitoring of displacements becomes impossible due to issues such as image blurring or lens occlusion,the structural vibration equation and boundary condition constraints,among other key parameters,are employed to predict the displacements at unknown monitoring points,thereby enabling full-field displacement monitoring and dynamic characteristic testing of the structure.Finally,a small-scale shaking table test was conducted on a simulated wind turbine structure undergoing shutdown to validate the dynamic characteristics of the proposed method through test verification.The research results indicate that the proposed method achieves a time-domain error within the submillimeter range and a frequency-domain accuracy of over 99%,effectively monitoring the full-field structural dynamic characteristics of wind turbines and providing a basis for the condition assessment of wind turbine structures.
基金Under the auspices of the Key Program of National Natural Science Foundation of China(No.42030409)。
文摘Multi-source data fusion provides high-precision spatial situational awareness essential for analyzing granular urban social activities.This study used Shanghai’s catering industry as a case study,leveraging electronic reviews and consumer data sourced from third-party restaurant platforms collected in 2021.By performing weighted processing on two-dimensional point-of-interest(POI)data,clustering hotspots of high-dimensional restaurant data were identified.A hierarchical network of restaurant hotspots was constructed following the Central Place Theory(CPT)framework,while the Geo-Informatic Tupu method was employed to resolve the challenges posed by network deformation in multi-scale processes.These findings suggest the necessity of enhancing the spatial balance of Shanghai’s urban centers by moderately increasing the number and service capacity of suburban centers at the urban periphery.Such measures would contribute to a more optimized urban structure and facilitate the outward dispersion of comfort-oriented facilities such as the restaurant industry.At a finer spatial scale,the distribution of restaurant hotspots demonstrates a polycentric and symmetric spatial pattern,with a developmental trend radiating outward along the city’s ring roads.This trend can be attributed to the efforts of restaurants to establish connections with other urban functional spaces,leading to the reconfiguration of urban spaces,expansion of restaurant-dedicated land use,and the reorganization of associated commercial activities.The results validate the existence of a polycentric urban structure in Shanghai but also highlight the instability of the restaurant hotspot network during cross-scale transitions.
基金Supported by the National High Technology Research and Development Programme of China(No.2011AA060407)Yunnan Province Science and Technology Innovation Platform Construction Plans,China(No.2010DH005)
文摘Stope mining design is a very important and complicated task in daily production design and technical management of an underground mine.Based on workface technology and human-computer interaction technology,this study introduces a method of 3D parametric design for the irregular structure of stope bottoms,and focuses on solving technical problems in surface modeling of stope bottom structure.Optimization of the minimum span length algorithm(MSLA) and the shortest path search algorithm(SPSA) is conducted to solve the problem of contour-line based instant modeling of stope bottom structures,which makes possible the 3D parametric design for irregular structure of stope bottom.Implementation process and relevant methods of the proposed algorithms are also presented.Feasibility and reliability of the proposed modeling method are testified in a case study.In practice,the proposed 3 D parameterization design method for irregular structure stope bottom proves to be very helpful to precise 3D parametric design.This method is capable of contributing to improved efficiency and precision of stope design,and is worthy of promotion.
基金Basic Science&Research Foundation of IEM,CEA under Grant No.2013B07International Science&Technology Cooperation Program of China under Grant No.2012DFA70810Natural Science Foundation of China under Grant No.50908216
文摘To identify the model structure parameters in shaking table tests from seismic response, especially from time- varying response records, this paper presents a new methodology by combining the online recursive Adaptive Forgetting through Multiple Models （AFMM） and offtine Auto-Regression with eXogenous variables （ARX） model. First, the AFMM is employed to detect whether the response of model structure is time-invariant or time-varying when subjected to strong motions. Second, if the response is time-invariant, the modal parameters are identified from the entire response record, such as the acceleration time-history using the ARX model. If the response is time-varying, the acceleration record is divided into three segments according to the accurate time-varying points detected by AFMM, and parameters are identified by only using the tail segment data, which is time-invariant and suited for analysis by the ARX model. Finally, the changes in dynamic properties due to various strong motions are obtained using the presented methodology. The feasibility and advantages of the method are demonstrated by identifying the modal parameters of a 12-story reinforced concrete （RC） frame structure in a shaking table test.
基金supported by the National Nature Science Foundation of China under Grant No.52075340.
文摘Lattice structures with excellent physical properties have attracted great research interest.In this paper,a novel volume parametric modeling method based on the skeleton model is proposed for the construction of threedimensional lattice structures.The skeleton model is divided into three types of nodes.And the corresponding algorithms are utilized to construct diverse types of volume parametric nodes.The unit-cell is assembled with distinct nodes according to the geometric features.The final lattice structure is created by the periodic arrangement of unit-cells.Several different types of volume parametric lattice structures are constructed to prove the stability and applicability of the proposed method.The quality is assessed in terms of the value of the Jacobian matrix.Moreover,the volume parametric lattice structures are tested with the isogeometric analysis to verify the feasibility of integration of modeling and simulation.
基金Supported by The Project from Department of Science and Technology of Shandong Province Under Grant No. 2007GG20008001 and 2010GSF10805
文摘By using the high spatial and temporal resolution Jinan Doppler Weather Radar data and Jinan,Xingtai sounding data,the radar signature and mesocyclone parameters of 54 supercells during 2003-2008 were analyzed.The results showed that the probability of a supercell forming would be higher when SI (showalter index) ≤ -2℃,K (K index) ≥ 30℃ and 0-6 km wind shear>15 m/s.The supercell storms can generally be divided into two categories,namely,type of isolation and mosaic type.To the type of isolation,the max reflectivity,cell-based VIL,max reflectivity height,cell top,mesocyclone base and top were significantly higher than the mosaic type.Isolation-type supercells had significantly higher probability of hail,lower probability of gale than the mosaic category.The mesocyclone attribute differences between isolation-type and mosaic type supercells determined the differences of storm structures and severe weather phenomenon.
文摘A robust and efficient algorithm is presented to build multiresolution models (MRMs) of arbitrary meshes without requirement of subdivision connectivity. To overcome the sampling difficulty of arbitrary meshes, edge contraction and vertex expansion are used as downsampling and upsampling methods. Our MRMs of a mesh are composed of a base mesh and a series of edge split operations, which are organized as a directed graph. Each split operation encodes two parts of information. One is the modification to the mesh, and the other is the dependency relation among splits. Such organization ensures the efficiency and robustness of our MRM algorithm. Examples demonstrate the functionality of our method.
基金sponsored by the National Nature Science Foundation of China (Grant No.40904034 and 40839905)
文摘With a more complex pore structure system compared with clastic rocks, carbonate rocks have not yet been well described by existing conventional rock physical models concerning the pore structure vagary as well as the influence on elastic rock properties. We start with a discussion and an analysis about carbonate rock pore structure utilizing rock slices. Then, given appropriate assumptions, we introduce a new approach to modeling carbonate rocks and construct a pore structure algorithm to identify pore structure mutation with a basis on the Gassmann equation and the Eshelby-Walsh ellipsoid inclusion crack theory. Finally, we compute a single well＇s porosity using this new approach with full wave log data and make a comparison with the predicted result of traditional method and simultaneously invert for reservoir parameters. The study results reveal that the rock pore structure can significantly influence the rocks＇ elastic properties and the predicted porosity error of the new modeling approach is merely 0.74%. Therefore, the approach we introduce can effectively decrease the predicted error of reservoir parameters.
基金supported by the Innovation Foundation of Provincial Education Department of Gansu(2024B-005)the Gansu Province National Science Foundation(22YF7GA182)the Fundamental Research Funds for the Central Universities(No.lzujbky2022-kb01)。
文摘Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring(SHM)system,so as to provide a scientific basis for structural damage identification and dynamic model modification.In view of this,this paper reviews methods for identifying structural modal parameters under environmental excitation and briefly describes how to identify structural damages based on the derived modal parameters.The paper primarily introduces data-driven modal parameter recognition methods(e.g.,time-domain,frequency-domain,and time-frequency-domain methods,etc.),briefly describes damage identification methods based on the variations of modal parameters(e.g.,natural frequency,modal shapes,and curvature modal shapes,etc.)and modal validation methods(e.g.,Stability Diagram and Modal Assurance Criterion,etc.).The current status of the application of artificial intelligence(AI)methods in the direction of modal parameter recognition and damage identification is further discussed.Based on the pre-vious analysis,the main development trends of structural modal parameter recognition and damage identification methods are given to provide scientific references for the optimized design and functional upgrading of SHM systems.
基金supported by the Knowledge Innovation Program of the Chinese Academy of Sciencesthe National High-Tech R&D Program of China(2008BAK49B05)
文摘More web pages are widely applying AJAX （Asynchronous JavaScript XML） due to the rich interactivity and incremental communication. By observing, it is found that the AJAX contents, which could not be seen by traditional crawler, are well-structured and belong to one specific domain generally. Extracting the structured data from AJAX contents and annotating its semantic are very significant for further applications. In this paper, a structured AJAX data extraction method for agricultural domain based on agricultural ontology was proposed. Firstly, Crawljax, an open AJAX crawling tool, was overridden to explore and retrieve the AJAX contents; secondly, the retrieved contents were partitioned into items and then classified by combining with agricultural ontology. HTML tags and punctuations were used to segment the retrieved contents into entity items. Finally, the entity items were clustered and the semantic annotation was assigned to clustering results according to agricultural ontology. By experimental evaluation, the proposed approach was proved effectively in resource exploring, entity extraction, and semantic annotation.
基金Mainly presented at the 6-th international meeting of acoustics in Aug. 2003, and The 1999 SPE Asia Pacific Oil and GasConference and Exhibition held in Jakarta, Indonesia, 20-22 April 1999, SPE 54274.
文摘In this paper, a new concept called numerical structure of seismic data is introduced and the difference between numerical structure and numerical value of seismic data is explained. Our study shows that the numerical seismic structure is closely related to oil and gas-bearing reservoir, so it is very useful for a geologist or a geophysicist to precisely interpret the oil-bearing layers from the seismic data. This technology can be applied to any exploration or production stage. The new method has been tested on a series of exploratory or development wells and proved to be reliable in China. Hydrocarbon-detection with this new method for 39 exploration wells on 25 structures indi- cates a success ratio of over 80 percent. The new method of hydrocarbon prediction can be applied for: (1) depositional environment of reservoirs with marine fades, delta, or non-marine fades (including fluvial facies, lacustrine fades); (2) sedimentary rocks of reservoirs that are non-marine clastic rocks and carbonate rock; and (3) burial depths range from 300 m to 7000 m, and the minimum thickness of these reservoirs is over 8 m (main frequency is about 50 Hz).
基金Program for New Century Excellent Talents in University(No.NCET-06-0290)the National Natural Science Foundation of China(No.60503036)the Fok Ying Tong Education Foundation Award(No.104027)
文摘In order to improve the quality of web search,a new query expansion method by choosing meaningful structure data from a domain database is proposed.It categories attributes into three different classes,named as concept attribute,context attribute and meaningless attribute,according to their semantic features which are document frequency features and distinguishing capability features.It also defines the semantic relevance between two attributes when they have correlations in the database.Then it proposes trie-bitmap structure and pair pointer tables to implement efficient algorithms for discovering attribute semantic feature and detecting their semantic relevances.By using semantic attributes and their semantic relevances,expansion words can be generated and embedded into a vector space model with interpolation parameters.The experiments use an IMDB movie database and real texts collections to evaluate the proposed method by comparing its performance with a classical vector space model.The results show that the proposed method can improve text search efficiently and also improve both semantic features and semantic relevances with good separation capabilities.
文摘By analyzing the optical spectra and electron paramagnetic resonance parameter D, the local structure distortion of （NiF6）4- clusters in AMF3 （A=K, Rb; M=Zn, Cd, Ca） and K2ZnF4 series are studied using the complete energy matrix based on the double spin-orbit coupling parameter model for configuration ions in a tetragonal ligand field. The results indicate that the contribution of ligand to spin-orbit coupling interaction should be considered for our studied systems. Moreover, the relationships between D and the spin-obit coupling coefficients as well as the average parameter and the divergent parameter are discussed.
基金This reservoir research is sponsored by the National 973 Subject Project (No. 2001CB209).
文摘Seismic data structure characteristics means the waveform character arranged in the time sequence at discrete data points in each 2-D or 3-D seismic trace. Hydrocarbon prediction using seismic data structure characteristics is a new reservoir prediction technique. When the main pay interval is in carbonate fracture and fissure-cavern type reservoirs with very strong inhomogeneity, there are some difficulties with hydrocarbon prediction. Because of the special geological conditions of the eighth zone in the Tahe oil field, we apply seismic data structure characteristics to hydrocarbon prediction for the Ordovician reservoir in this zone. We divide the area oil zone into favorable and unfavorable blocks. Eighteen well locations were proposed in the favorable oil block, drilled, and recovered higher output of oil and gas.
基金Item Sponsored by National Natural Science Foundation of China(50274203)National High Technology Research and Development Program of China(2001AA337040)
文摘To design a power source system and mold for electromagnetic soft-contact continuous casting process and to theoretically estimate the heat losses from the charges and the system power, the effect of structure parameters on system power and magnetic flux density distribution was calculated using finite element method. The results show that as for electromagnetic soft-contact continuous casting system with partial-segment type mold, the power consumption is much more than that with a full-segment type mold; about 62% of electric power is dissipated in the mold, and the effective acting range of magnetic field is relatively narrow. Optimizing mold structure is a crucial measure of remarkably reducing mold power consumption and saving electric energy. Increasing slit number, width, and length can remarkably increase the magnetic flux density in the mold and can reduce the electric energy consumption. Among structure parameters, slit number and slit width are relatively more effective to reduce energy consumption. For a round billet electromagnetic continuous casting system with diameter of 178 ram, the reasonable slit number, width, and length are about 24--32, 0. 5--1.0 mm, and 160 mm, respectively.
基金financial supports from the National Natural Science Foundation of China(52130104,51821001)High Technology and Key Development Project of Ningbo,China(2019B10102)。
文摘Mg–3Nd–0.2Zn–0.4Zr(NZ30K,wt.%)alloy is a new kind of high-performance metallic biomaterial.The combination of the NZ30K Magnesium(Mg)alloy and selective laser melting(SLM)process seems to be an ideal solution to produce porous Mg degradable implants.However,the microstructure evolution and mechanical properties of the SLMed NZ30K Mg alloy were not yet studied systematically.Therefore,the fabrication defects,microstructure,and mechanical properties of the SLMed NZ30K alloy under different processing parameters were investigated.The results show that there are two types of fabrication defects in the SLMed NZ30K alloy,gas pores and unfused defects.With the increase of the laser energy density,the porosity sharply decreases to the minimum first and then slightly increases.The minimum porosity is 0.49±0.18%.While the microstructure varies from the large grains with lamellar structure inside under low laser energy density,to the large grains with lamellar structure inside&the equiaxed grains&the columnar grains under middle laser energy density,and further to the fine equiaxed grains&the columnar grains under high laser energy density.The lamellar structure in the large grain is a newly observed microstructure for the NZ30K Mg alloy.Higher laser energy density leads to finer grains,which enhance all the yield strength(YS),ultimate tensile strength(UTS)and elongation,and the best comprehensive mechanical properties obtained are YS of 266±2.1 MPa,UTS of 296±5.2 MPa,with an elongation of 4.9±0.68%.The SLMed NZ30K Mg alloy with a bimodal-grained structure consisting of fine equiaxed grains and coarser columnar grains has better elongation and a yield drop phenomenon.
