Bedding slope is a typical heterogeneous slope consisting of different soil/rock layers and is likely to slide along the weakest interface.Conventional slope protection methods for bedding slopes,such as retaining wal...Bedding slope is a typical heterogeneous slope consisting of different soil/rock layers and is likely to slide along the weakest interface.Conventional slope protection methods for bedding slopes,such as retaining walls,stabilizing piles,and anchors,are time-consuming and labor-and energy-intensive.This study proposes an innovative polymer grout method to improve the bearing capacity and reduce the displacement of bedding slopes.A series of large-scale model tests were carried out to verify the effectiveness of polymer grout in protecting bedding slopes.Specifically,load-displacement relationships and failure patterns were analyzed for different testing slopes with various dosages of polymer.Results show the great potential of polymer grout in improving bearing capacity,reducing settlement,and protecting slopes from being crushed under shearing.The polymer-treated slopes remained structurally intact,while the untreated slope exhibited considerable damage when subjected to loads surpassing the bearing capacity.It is also found that polymer-cemented soils concentrate around the injection pipe,forming a fan-shaped sheet-like structure.This study proves the improvement of polymer grouting for bedding slope treatment and will contribute to the development of a fast method to protect bedding slopes from landslides.展开更多
Eye diagnosis is a method for inspecting systemic diseases and syndromes by observing the eyes.With the development of intelligent diagnosis in traditional Chinese medicine(TCM);artificial intelligence(AI)can improve ...Eye diagnosis is a method for inspecting systemic diseases and syndromes by observing the eyes.With the development of intelligent diagnosis in traditional Chinese medicine(TCM);artificial intelligence(AI)can improve the accuracy and efficiency of eye diagnosis.However;the research on intelligent eye diagnosis still faces many challenges;including the lack of standardized and precisely labeled data;multi-modal information analysis;and artificial in-telligence models for syndrome differentiation.The widespread application of AI models in medicine provides new insights and opportunities for the research of eye diagnosis intelli-gence.This study elaborates on the three key technologies of AI models in the intelligent ap-plication of TCM eye diagnosis;and explores the implications for the research of eye diagno-sis intelligence.First;a database concerning eye diagnosis was established based on self-su-pervised learning so as to solve the issues related to the lack of standardized and precisely la-beled data.Next;the cross-modal understanding and generation of deep neural network models to address the problem of lacking multi-modal information analysis.Last;the build-ing of data-driven models for eye diagnosis to tackle the issue of the absence of syndrome dif-ferentiation models.In summary;research on intelligent eye diagnosis has great potential to be applied the surge of AI model applications.展开更多
This study introduced at first the background of numerous highway widening projects that have been developed in recent years in China.Using a large ground settlement simulator and a fiber Bragg grating (FBG) strain se...This study introduced at first the background of numerous highway widening projects that have been developed in recent years in China.Using a large ground settlement simulator and a fiber Bragg grating (FBG) strain sensor network system,a large-scale model test,with a similarity ratio of 1:2,was performed to analyze the influence of differential settlement between new and old subgrades on pavement structure under loading condition.The result shows that excessive differential settlement can cause considerable tensile strain in the pavement structure of a widened road,for which a maximum value (S) of 6 cm is recommended.Under the repetitive load,the top layers of pavement structure are subjected to the alternate action of tensile and compressive strains,which would eventually lead to a fatigue failure of the pavement.However,application of geogrid to the splice between the new and the old roads can reduce differential settlement to a limited extent.The new subgrade of a widened road is vulnerable to the influence of dynamic load transferred from the above pavement structures.While for the old subgrade,due to its comparatively high stiffness,it can well spread the load on the pavement statically or dynamically.The test also shows that application of geogrid can effectively prevent or defer the failure of pavement structure.With geogrid,the modulus of resilience of the subgrade is increased and inhomogeneous deformation can be reduced;therefore,the stress/strain distribution in pavement structure under loading condition becomes uniform.The results obtained in this context are expected to provide a helpful reference for structural design and maintenance strategy for future highway widening projects.展开更多
Physical testing of large-scale ship models at sea is a new experimental method.It is a cheap and reliable way to research the environment adaptability of a ship in complex and extreme wave conditions.It is necessary ...Physical testing of large-scale ship models at sea is a new experimental method.It is a cheap and reliable way to research the environment adaptability of a ship in complex and extreme wave conditions.It is necessary to have a stable experimental system for the test.Since the experimental area is large, a remote control system and a telemetry system are essential, and were designed by the authors.An experiment was conducted on the Songhuajiang River to test the systems.The relationship between the model's speed and its electromotor's revolutions was also measured during the model test.The results showed that the two systems make it possible to carry out large-scale model tests at sea.展开更多
The design and application of morphing systems are ongoing issues compelling the aviation industry.The Clean Sky-program represents the most significant aeronautical research ever launched in Europe on advanced techno...The design and application of morphing systems are ongoing issues compelling the aviation industry.The Clean Sky-program represents the most significant aeronautical research ever launched in Europe on advanced technologies for greening next-generation aircraft.The primary purpose of the program is to develop new concepts aimed at decreasing the effects of aviation on the environment,increasing reliability,and promoting eco-friendly mobility.These ambitions are pursued through research on enabling technologies fostering noise and gas emissions reduction,mainly by improving aircraft aerodynamic performances.Within the Clean Sky framework,a multimodal morphing flap device was designed based on tight industrial requirements and tailored for large civil aircraft applications.The flap is deployed in one unique setting,and its cross section is morphed differently in take-off and landing to get the necessary extra lift for the specific flight phase.Moreover,during the cruise,the tip of the flap is deflected for load control and induced drag reduction.Before manufacturing the first flap prototype,a high-speed(Ma=0.3),large-scale test campaign(geometric scale factor 1:3)was deemed necessary to validate the performance improvements brought by this novel system at the aircraft level.On the other hand,the geometrical scaling of the flap prototype was considered impracticable due to the unscalability of the embedded mechanisms and actuators for shape transition.Therefore,a new architecture was conceived for the flap model to comply with the scaled dimensions requirements,withstand the relevant loads expected during the wind tunnel tests and emulate the shape transition capabilities of the true-scale flap.Simplified strategies were developed to effectively morph the model during wind tunnel tests while ensuring the robustness of each morphed configuration and maintaining adequate stiffness levels to prevent undesirable deviations from the intended aerodynamic shapes.Additionally,a simplified design was conceived for the flap-wing interface,allowing for quick adjustments of the flap setting and enabling load transmission paths like those arising between the full-scale flap and the wing.The design process followed for the definition of this challenging wind tunnel model has been addressed in this work,covering the definition of the conceptual layout,the numerical evaluation of the most severe loads expected during the test,and the verification of the structural layout by means of advanced finite element analyses.展开更多
The excavation of deep tunnels crossing faults is highly prone to triggering rockburst disasters,which has become a significant engineering issue.In this study,taking the fault-slip rockbursts from a deep tunnel in so...The excavation of deep tunnels crossing faults is highly prone to triggering rockburst disasters,which has become a significant engineering issue.In this study,taking the fault-slip rockbursts from a deep tunnel in southwestern China as the engineering prototype,large-scale three-dimensional(3D)physical model tests were conducted on a 3D-printed complex geological model containing two faults.Based on the selfdeveloped 3D loading system and excavation device,the macroscopic failure of fault-slip rockbursts was simulated indoors.The stress,strain,and fracturing characteristics of the surrounding rock near the two faults were systematically evaluated during excavation and multistage loading.The test results effectively revealed the evolution and triggering mechanism of fault-slip rockbursts.After the excavation of a highstress tunnel,stress readjustment occurred.Owing to the presence of these two faults,stress continued to accumulate in the rock mass between them,leading to the accumulation of fractures.When the shear stress on a fault surface exceeded its shear strength,sudden fault slip and dislocation occurred,thus triggering rockbursts.Rockbursts occurred twice in the vault between the two faults,showing obvious intermittent characteristics.The rockburst pit was controlled by two faults.When the faults remained stable,tensile failure predominated in the surrounding rock.However,when the fault slip was triggered,shear failure in the surrounding rock increased.These findings provide valuable insights for enhancing the comprehension of fault-slip rockbursts.展开更多
Extremely large-scale array(XL-array)communications can significantly improve the transmission rate,spectral efficiency,and spatial resolution,and has great potential in next-generation mobile communication networks.A...Extremely large-scale array(XL-array)communications can significantly improve the transmission rate,spectral efficiency,and spatial resolution,and has great potential in next-generation mobile communication networks.A crucial problem in XLarray communications is to determine the boundary of applicable regions of the plane wave model(PWM)and spherical wave model(SWM).In this paper,we propose new PWM/SWM demarcations for XL-arrays from the viewpoint of channel gain and rank.Four sets of results are derived for four different array setups.First,an equi-power line is derived for a point-touniform linear array(ULA)scenario,where an inflection point is found at±π6 central incident angles.Second,an equi-power surface is derived for a point-touniform planar array(UPA)scenario,and it is proved that cos2(ϕ)cos2(φ)=12 is a dividing curve,where ϕ andφdenote the elevation and azimuth angles,respectively.Third,an accurate and explicit expression of the equi-rank surface is obtained for a ULA-to-ULA scenario.Finally,an approximated expression of the equirank surface is obtained for a ULA-to-UPA scenario.With the obtained closed-form expressions,the equirank surface for any antenna structure and any angle can be well estimated.Furthermore,the effect of scatterers is also investigated,from which some insights are drawn.展开更多
This research pioneers the integration of geographic information systems(GIS)and 3D modeling within a virtual reality(VR)framework to assess the viability and planning of a 20 MW hybrid wind-solarphotovoltaic(PV)syste...This research pioneers the integration of geographic information systems(GIS)and 3D modeling within a virtual reality(VR)framework to assess the viability and planning of a 20 MW hybrid wind-solarphotovoltaic(PV)system connected to the local grid.The study focuses on Dakhla,Morocco,a region with vast untapped renewable energy potential.By leveraging GIS,we are innovatively analyzing geographical and environmental factors that influence optimal site selection and system design.The incorporation of VR technologies offers an unprecedented level of realism and immersion,allowing stakeholders to virtually experience the project's impact and design in a dynamic,interactive environment.This novel methodology includes extensive data collection,advanced modeling,and simulations,ensuring that the hybrid system is precisely tailored to the unique climatic and environmental conditions of Dakhla.Our analysis reveals that the region possesses a photovoltaic solar potential of approximately2400 k Wh/m^(2) per year,with an average annual wind power density of about 434 W/m^(2) at an 80-meter hub height.Productivity simulations indicate that the 20 MW hybrid system could generate approximately 60 GWh of energy per year and 1369 GWh over its 25-year lifespan.To validate these findings,we employed the System Advisor Model(SAM)software and the Global Solar Photovoltaic Atlas platform.This comprehensive and interdisciplinary approach not only provides a robust assessment of the system's feasibility but also offers valuable insights into its potential socio-economic and environmental impact.展开更多
The rapid advancement of artificial intelligence technology is driving transformative changes in medical diagnosis,treatment,and management systems through large-scale deep learning models-a process that brings both g...The rapid advancement of artificial intelligence technology is driving transformative changes in medical diagnosis,treatment,and management systems through large-scale deep learning models-a process that brings both groundbreaking opportunities and multifaceted challenges.This study focuses on the medical and healthcare applications of large-scale deep learning architectures,conducting a comprehensive survey to categorize and analyze their diverse uses.The survey results reveal that current applications of large models in healthcare encompass medical data management,healthcare services,medical devices,and preventive medicine,among others.Concurrently,large models demonstrate significant advantages in the medical domain,especially in high-precision diagnosis and prediction,data analysis and knowledge discovery,and enhancing operational efficiency.Nevertheless,we identify several challenges that need urgent attention,including improving the interpretability of large models,strengthening privacy protection,and addressing issues related to handling incomplete data.This research is dedicated to systematically elucidating the deep collaborative mechanisms between artificial intelligence and the healthcare field,providing theoretical references and practical guidance for both academia and industry.展开更多
The management of large-scale architectural engineering projects(e.g.,airports,hospitals)is plagued by information silos,cost overruns,and scheduling delays.While building information modeling(BIM)has improved 3D desi...The management of large-scale architectural engineering projects(e.g.,airports,hospitals)is plagued by information silos,cost overruns,and scheduling delays.While building information modeling(BIM)has improved 3D design coordination,its static nature limits its utility in real-time construction management and operational phases.This paper proposes a novel synergistic framework that integrates the static,deep data of BIM with the dynamic,real-time capabilities of digital twin(DT)technology.The framework establishes a closed-loop data flow from design(BIM)to construction(IoT,drones,BIM 360)to operation(DT platform).We detail the technological stack required,including IoT sensors,cloud computing,and AI-driven analytics.The application of this framework is illustrated through a simulated case study of a mega-terminal airport construction project,demonstrating potential reductions in rework by 15%,improvement in labor productivity by 10%,and enhanced predictive maintenance capabilities.This research contributes to the field of construction engineering by providing a practical model for achieving full lifecycle digitalization and intelligent project management.展开更多
Large-scale and heavily jointed rocks have inherent planes of anisotropy and secondary structural planes,such as dominant joint sets and random fractures,which result in significant differences in their failure mechan...Large-scale and heavily jointed rocks have inherent planes of anisotropy and secondary structural planes,such as dominant joint sets and random fractures,which result in significant differences in their failure mechanism and deformation behavior compared to other rock types.To address this issue,inherent anisotropic rocks with large-scale and dense joints are considered to be composed of the rock matrix,inherent planes of anisotropy,and secondary structural planes.Then a new implicit continuum model called LayerDFN is developed based on the crack tensor and damage tensor theories to characterize the mechanical properties of inherent anisotropic rocks.Furthermore,the LayerDFN model is implemented in the FLAC3D software,and a series of numerical results for typical example problems is compared with those obtained from the 3DEC,the analytical solutions,similar classical models,laboratory uniaxial compression tests,and field rigid bearing plate tests.The results demonstrate that the LayerDFN model can effectively capture the anisotropic mechanical properties of inherent anisotropic rocks,and can quantitatively characterize the damaging effect of the secondary structural planes.Overall,the numerical method based on the LayerDFN model provides a comprehensive and reliable approach for describing and analyzing the behavior of inherent anisotropic rocks,which will provide valuable insights for engineering design and decision-making processes.展开更多
Large-scale 3D physical models of complex structures can be used to simulate hydrocarbon exploration areas. The high-fidelity simulation of actual structures poses challenges to model building and quality control. Suc...Large-scale 3D physical models of complex structures can be used to simulate hydrocarbon exploration areas. The high-fidelity simulation of actual structures poses challenges to model building and quality control. Such models can be used to collect wideazimuth, multi-azimuth, and full-azimuth seismic data that can be used to verify various 3D processing and interpretation methods. Faced with nonideal imaging problems owing to the extensive complex surface conditions and subsurface structures in the oil-rich foreland basins of western China, we designed and built the KS physical model based on the complex subsurface structure. This is the largest and most complex 3D physical model built to date. The physical modeling technology advancements mainly involve 1） the model design method, 2） the model casting flow, and 3） data acquisition. A 3D velocity model of the physical model was obtained for the first time, and the model building precision was quantitatively analyzed. The absolute error was less than 3 mm, which satisfies the experimental requirements. The 3D velocity model obtained from 3D measurements of the model layers is the basis for testing various imaging methods. Furthermore, the model is considered a standard in seismic physical modeling technology.展开更多
Model tests and numerical calculations were adopted based on the New Yuanliangshan tunnel project to investigate the water pressure resistance of lining construction joints in high-pressure and water-rich karst tunnel...Model tests and numerical calculations were adopted based on the New Yuanliangshan tunnel project to investigate the water pressure resistance of lining construction joints in high-pressure and water-rich karst tunnels.A large-scale model test was designed and conducted,innovatively transforming the external water pressure of the lining construction joint into internal water pressure.The effects of the embedded position and waterstop type on the water pressure resistance of the construction joint were analyzed,and the reliability of the model test was verified via numerical calculations.The results show that using waterstops can significantly improve the water pressure resistance of lining construction joints.The water pressure resistance of the lining construction joint is positively correlated with the lining thickness and embedded depth of the waterstop.In addition,the type of waterstop significantly influences the water pressure resistance of lining construction joints.The test results show that the water pressure resistance of the embedded transverse reinforced waterstop is similar to that of the steel plate waterstop,and both have more advantages than the rubber waterstop.The water pressure resistance of the construction joint determined via numerical calculations is similar to the model test results,indicating that the model test results have high accuracy and reliability.This study provides a reference for similar projects and has wide applications.展开更多
The large-scale model(LSM)can handle large-scale data and complex problems,effectively improving the intelligence level of urban intersections.However,the traffic conditions at intersections are becoming increasingly ...The large-scale model(LSM)can handle large-scale data and complex problems,effectively improving the intelligence level of urban intersections.However,the traffic conditions at intersections are becoming increasingly complex,so the intelligent intersection LSMs(I2LSMs)also need to be continuously learned and updated.The traditional cloud-based training method incurs a significant amount of computational and storage overhead,and there is a risk of data leakage.The combination of edge artificial intelligence and federated learning provides an efficient and highly privacy protected computing mode.Therefore,we propose a hierarchical hybrid distributed training mechanism for I2LSM.Firstly,relying on the intelligent intersection system for cloud-network-terminal integration,we constructed an I2LSM hierarchical hybrid distributed training architecture.Then,we propose a hierarchical hybrid federated learning(H2Fed)algorithm that combines the advantages of centralized federated learning and decentralized federated learning.Further,we propose an adaptive compressed sensing algorithm to reduce the communication overhead.Finally,we analyze the convergence of the H2Fed algorithm.Experimental results show that the H2Fed algorithm reduces the communication overhead by 21.6%while ensuring the accuracy of the model.展开更多
The streamflow over the Yellow River basin is simulated using the PRECIS （Providing REgional Climates for Impacts Studies） regional climate model driven by 15-year （1979-1993） ECMWF reanalysis data as the initial ...The streamflow over the Yellow River basin is simulated using the PRECIS （Providing REgional Climates for Impacts Studies） regional climate model driven by 15-year （1979-1993） ECMWF reanalysis data as the initial and lateral boundary conditions and an off-line large-scale routing model （LRM）. The LRM uses physical catchment and river channel information and allows streamflow to be predicted for large continental rivers with a 1°×1° spatial resolution. The results show that the PRECIS model can reproduce the general southeast to northwest gradient distribution of the precipitation over the Yellow River basin, The PRECIS- LRM model combination has the capability to simulate the seasonal and annual streamflow over the Yellow River basin. The simulated streamflow is generally coincident with the naturalized streamflow both in timing and in magnitude.展开更多
A Long Short-Term Memory(LSTM) Recurrent Neural Network(RNN) has driven tremendous improvements on an acoustic model based on Gaussian Mixture Model(GMM). However, these models based on a hybrid method require a force...A Long Short-Term Memory(LSTM) Recurrent Neural Network(RNN) has driven tremendous improvements on an acoustic model based on Gaussian Mixture Model(GMM). However, these models based on a hybrid method require a forced aligned Hidden Markov Model(HMM) state sequence obtained from the GMM-based acoustic model. Therefore, it requires a long computation time for training both the GMM-based acoustic model and a deep learning-based acoustic model. In order to solve this problem, an acoustic model using CTC algorithm is proposed. CTC algorithm does not require the GMM-based acoustic model because it does not use the forced aligned HMM state sequence. However, previous works on a LSTM RNN-based acoustic model using CTC used a small-scale training corpus. In this paper, the LSTM RNN-based acoustic model using CTC is trained on a large-scale training corpus and its performance is evaluated. The implemented acoustic model has a performance of 6.18% and 15.01% in terms of Word Error Rate(WER) for clean speech and noisy speech, respectively. This is similar to a performance of the acoustic model based on the hybrid method.展开更多
The regional hydrological system is extremely complex because it is affected not only by physical factors but also by human dimensions.And the hydrological models play a very important role in simulating the complex s...The regional hydrological system is extremely complex because it is affected not only by physical factors but also by human dimensions.And the hydrological models play a very important role in simulating the complex system.However,there have not been effective methods for the model reliability and uncertainty analysis due to its complexity and difficulty.The uncertainties in hydrological modeling come from four important aspects：uncertainties in input data and parameters,uncertainties in model structure,uncertainties in analysis method and the initial and boundary conditions.This paper systematically reviewed the recent advances in the study of the uncertainty analysis approaches in the large-scale complex hydrological model on the basis of uncertainty sources.Also,the shortcomings and insufficiencies in the uncertainty analysis for complex hydrological models are pointed out.And then a new uncertainty quantification platform PSUADE and its uncertainty quantification methods were introduced,which will be a powerful tool and platform for uncertainty analysis of large-scale complex hydrological models.Finally,some future perspectives on uncertainty quantification are put forward.展开更多
1.Introduction Climate change mitigation pathways aimed at limiting global anthropogenic carbon dioxide(CO_(2))emissions while striving to constrain the global temperature increase to below 2℃—as outlined by the Int...1.Introduction Climate change mitigation pathways aimed at limiting global anthropogenic carbon dioxide(CO_(2))emissions while striving to constrain the global temperature increase to below 2℃—as outlined by the Intergovernmental Panel on Climate Change(IPCC)—consistently predict the widespread implementation of CO_(2)geological storage on a global scale.展开更多
Considering the large diameter effect of piles,the influence of different pile-soil analysis methods on the design of monopile foundations for offshore wind turbines has become an urgent problem to be solved.Three dif...Considering the large diameter effect of piles,the influence of different pile-soil analysis methods on the design of monopile foundations for offshore wind turbines has become an urgent problem to be solved.Three different pile-soil models were used to study a large 10 MW monopile wind turbine.By modeling the three models in the SACS software,this paper analyzed the motion response of the overall structure under the conditions of wind and waves.According to the given working conditions,this paper concludes that under the condition of independent wind,the average value of the tower top x-displacement of the rigid connection method is the smalle st,and the standard deviation is the smallest under the condition of independent wave.The results obtained by the p-y curve method are the most conservative.展开更多
This paper investigates the wireless communication with a novel architecture of antenna arrays,termed modular extremely large-scale array(XLarray),where array elements of an extremely large number/size are regularly m...This paper investigates the wireless communication with a novel architecture of antenna arrays,termed modular extremely large-scale array(XLarray),where array elements of an extremely large number/size are regularly mounted on a shared platform with both horizontally and vertically interlaced modules.Each module consists of a moderate/flexible number of array elements with the inter-element distance typically in the order of the signal wavelength,while different modules are separated by the relatively large inter-module distance for convenience of practical deployment.By accurately modelling the signal amplitudes and phases,as well as projected apertures across all modular elements,we analyse the near-field signal-to-noise ratio(SNR)performance for modular XL-array communications.Based on the non-uniform spherical wave(NUSW)modelling,the closed-form SNR expression is derived in terms of key system parameters,such as the overall modular array size,distances of adjacent modules along all dimensions,and the user's three-dimensional(3D)location.In addition,with the number of modules in different dimensions increasing infinitely,the asymptotic SNR scaling laws are revealed.Furthermore,we show that our proposed near-field modelling and performance analysis include the results for existing array architectures/modelling as special cases,e.g.,the collocated XL-array architecture,the uniform plane wave(UPW)based far-field modelling,and the modular extremely large-scale uniform linear array(XL-ULA)of onedimension.Extensive simulation results are presented to validate our findings.展开更多
基金supported by the Fujian Science Foundation for Outstanding Youth(Grant No.2023J06039)the National Natural Science Foundation of China(Grant No.41977259 and No.U2005205)Fujian Province natural resources science and technology innovation project(Grant No.KY-090000-04-2022-019)。
文摘Bedding slope is a typical heterogeneous slope consisting of different soil/rock layers and is likely to slide along the weakest interface.Conventional slope protection methods for bedding slopes,such as retaining walls,stabilizing piles,and anchors,are time-consuming and labor-and energy-intensive.This study proposes an innovative polymer grout method to improve the bearing capacity and reduce the displacement of bedding slopes.A series of large-scale model tests were carried out to verify the effectiveness of polymer grout in protecting bedding slopes.Specifically,load-displacement relationships and failure patterns were analyzed for different testing slopes with various dosages of polymer.Results show the great potential of polymer grout in improving bearing capacity,reducing settlement,and protecting slopes from being crushed under shearing.The polymer-treated slopes remained structurally intact,while the untreated slope exhibited considerable damage when subjected to loads surpassing the bearing capacity.It is also found that polymer-cemented soils concentrate around the injection pipe,forming a fan-shaped sheet-like structure.This study proves the improvement of polymer grouting for bedding slope treatment and will contribute to the development of a fast method to protect bedding slopes from landslides.
基金National Natural Science Foundation of China(82274265 and 82274588)Hunan University of Traditional Chinese Medicine Research Unveiled Marshal Programs(2022XJJB003).
文摘Eye diagnosis is a method for inspecting systemic diseases and syndromes by observing the eyes.With the development of intelligent diagnosis in traditional Chinese medicine(TCM);artificial intelligence(AI)can improve the accuracy and efficiency of eye diagnosis.However;the research on intelligent eye diagnosis still faces many challenges;including the lack of standardized and precisely labeled data;multi-modal information analysis;and artificial in-telligence models for syndrome differentiation.The widespread application of AI models in medicine provides new insights and opportunities for the research of eye diagnosis intelli-gence.This study elaborates on the three key technologies of AI models in the intelligent ap-plication of TCM eye diagnosis;and explores the implications for the research of eye diagno-sis intelligence.First;a database concerning eye diagnosis was established based on self-su-pervised learning so as to solve the issues related to the lack of standardized and precisely la-beled data.Next;the cross-modal understanding and generation of deep neural network models to address the problem of lacking multi-modal information analysis.Last;the build-ing of data-driven models for eye diagnosis to tackle the issue of the absence of syndrome dif-ferentiation models.In summary;research on intelligent eye diagnosis has great potential to be applied the surge of AI model applications.
文摘This study introduced at first the background of numerous highway widening projects that have been developed in recent years in China.Using a large ground settlement simulator and a fiber Bragg grating (FBG) strain sensor network system,a large-scale model test,with a similarity ratio of 1:2,was performed to analyze the influence of differential settlement between new and old subgrades on pavement structure under loading condition.The result shows that excessive differential settlement can cause considerable tensile strain in the pavement structure of a widened road,for which a maximum value (S) of 6 cm is recommended.Under the repetitive load,the top layers of pavement structure are subjected to the alternate action of tensile and compressive strains,which would eventually lead to a fatigue failure of the pavement.However,application of geogrid to the splice between the new and the old roads can reduce differential settlement to a limited extent.The new subgrade of a widened road is vulnerable to the influence of dynamic load transferred from the above pavement structures.While for the old subgrade,due to its comparatively high stiffness,it can well spread the load on the pavement statically or dynamically.The test also shows that application of geogrid can effectively prevent or defer the failure of pavement structure.With geogrid,the modulus of resilience of the subgrade is increased and inhomogeneous deformation can be reduced;therefore,the stress/strain distribution in pavement structure under loading condition becomes uniform.The results obtained in this context are expected to provide a helpful reference for structural design and maintenance strategy for future highway widening projects.
基金Supported by the National Defense Foundation under Grant No.51414030204CB0109
文摘Physical testing of large-scale ship models at sea is a new experimental method.It is a cheap and reliable way to research the environment adaptability of a ship in complex and extreme wave conditions.It is necessary to have a stable experimental system for the test.Since the experimental area is large, a remote control system and a telemetry system are essential, and were designed by the authors.An experiment was conducted on the Songhuajiang River to test the systems.The relationship between the model's speed and its electromotor's revolutions was also measured during the model test.The results showed that the two systems make it possible to carry out large-scale model tests at sea.
基金carried out in the framework of AIRGREEN2 Project,which gratefully received funding from the Clean Sky 2 Joint Undertaking,under the European’s Union Horizon 2020 Research and Innovation Program,Grant Agreement(No.807089—REG GAM 4822018—H2020-IBA-CS2-GAMS-2017)funded by TUBITAK 2214-A-International Research Fellowship Programme for Ph.D.Students。
文摘The design and application of morphing systems are ongoing issues compelling the aviation industry.The Clean Sky-program represents the most significant aeronautical research ever launched in Europe on advanced technologies for greening next-generation aircraft.The primary purpose of the program is to develop new concepts aimed at decreasing the effects of aviation on the environment,increasing reliability,and promoting eco-friendly mobility.These ambitions are pursued through research on enabling technologies fostering noise and gas emissions reduction,mainly by improving aircraft aerodynamic performances.Within the Clean Sky framework,a multimodal morphing flap device was designed based on tight industrial requirements and tailored for large civil aircraft applications.The flap is deployed in one unique setting,and its cross section is morphed differently in take-off and landing to get the necessary extra lift for the specific flight phase.Moreover,during the cruise,the tip of the flap is deflected for load control and induced drag reduction.Before manufacturing the first flap prototype,a high-speed(Ma=0.3),large-scale test campaign(geometric scale factor 1:3)was deemed necessary to validate the performance improvements brought by this novel system at the aircraft level.On the other hand,the geometrical scaling of the flap prototype was considered impracticable due to the unscalability of the embedded mechanisms and actuators for shape transition.Therefore,a new architecture was conceived for the flap model to comply with the scaled dimensions requirements,withstand the relevant loads expected during the wind tunnel tests and emulate the shape transition capabilities of the true-scale flap.Simplified strategies were developed to effectively morph the model during wind tunnel tests while ensuring the robustness of each morphed configuration and maintaining adequate stiffness levels to prevent undesirable deviations from the intended aerodynamic shapes.Additionally,a simplified design was conceived for the flap-wing interface,allowing for quick adjustments of the flap setting and enabling load transmission paths like those arising between the full-scale flap and the wing.The design process followed for the definition of this challenging wind tunnel model has been addressed in this work,covering the definition of the conceptual layout,the numerical evaluation of the most severe loads expected during the test,and the verification of the structural layout by means of advanced finite element analyses.
基金funding support from the National Natural Science Foundation of China(Grant Nos.42177136 and 52309126).
文摘The excavation of deep tunnels crossing faults is highly prone to triggering rockburst disasters,which has become a significant engineering issue.In this study,taking the fault-slip rockbursts from a deep tunnel in southwestern China as the engineering prototype,large-scale three-dimensional(3D)physical model tests were conducted on a 3D-printed complex geological model containing two faults.Based on the selfdeveloped 3D loading system and excavation device,the macroscopic failure of fault-slip rockbursts was simulated indoors.The stress,strain,and fracturing characteristics of the surrounding rock near the two faults were systematically evaluated during excavation and multistage loading.The test results effectively revealed the evolution and triggering mechanism of fault-slip rockbursts.After the excavation of a highstress tunnel,stress readjustment occurred.Owing to the presence of these two faults,stress continued to accumulate in the rock mass between them,leading to the accumulation of fractures.When the shear stress on a fault surface exceeded its shear strength,sudden fault slip and dislocation occurred,thus triggering rockbursts.Rockbursts occurred twice in the vault between the two faults,showing obvious intermittent characteristics.The rockburst pit was controlled by two faults.When the faults remained stable,tensile failure predominated in the surrounding rock.However,when the fault slip was triggered,shear failure in the surrounding rock increased.These findings provide valuable insights for enhancing the comprehension of fault-slip rockbursts.
基金supported in part by the National Natural Science Foundation of China (NSFC) under Grants 62271310 and 62125108in part by the Fundamental Research Funds for the Central Universities of Chinain part by the NSFC under Grant 62431014
文摘Extremely large-scale array(XL-array)communications can significantly improve the transmission rate,spectral efficiency,and spatial resolution,and has great potential in next-generation mobile communication networks.A crucial problem in XLarray communications is to determine the boundary of applicable regions of the plane wave model(PWM)and spherical wave model(SWM).In this paper,we propose new PWM/SWM demarcations for XL-arrays from the viewpoint of channel gain and rank.Four sets of results are derived for four different array setups.First,an equi-power line is derived for a point-touniform linear array(ULA)scenario,where an inflection point is found at±π6 central incident angles.Second,an equi-power surface is derived for a point-touniform planar array(UPA)scenario,and it is proved that cos2(ϕ)cos2(φ)=12 is a dividing curve,where ϕ andφdenote the elevation and azimuth angles,respectively.Third,an accurate and explicit expression of the equi-rank surface is obtained for a ULA-to-ULA scenario.Finally,an approximated expression of the equirank surface is obtained for a ULA-to-UPA scenario.With the obtained closed-form expressions,the equirank surface for any antenna structure and any angle can be well estimated.Furthermore,the effect of scatterers is also investigated,from which some insights are drawn.
文摘This research pioneers the integration of geographic information systems(GIS)and 3D modeling within a virtual reality(VR)framework to assess the viability and planning of a 20 MW hybrid wind-solarphotovoltaic(PV)system connected to the local grid.The study focuses on Dakhla,Morocco,a region with vast untapped renewable energy potential.By leveraging GIS,we are innovatively analyzing geographical and environmental factors that influence optimal site selection and system design.The incorporation of VR technologies offers an unprecedented level of realism and immersion,allowing stakeholders to virtually experience the project's impact and design in a dynamic,interactive environment.This novel methodology includes extensive data collection,advanced modeling,and simulations,ensuring that the hybrid system is precisely tailored to the unique climatic and environmental conditions of Dakhla.Our analysis reveals that the region possesses a photovoltaic solar potential of approximately2400 k Wh/m^(2) per year,with an average annual wind power density of about 434 W/m^(2) at an 80-meter hub height.Productivity simulations indicate that the 20 MW hybrid system could generate approximately 60 GWh of energy per year and 1369 GWh over its 25-year lifespan.To validate these findings,we employed the System Advisor Model(SAM)software and the Global Solar Photovoltaic Atlas platform.This comprehensive and interdisciplinary approach not only provides a robust assessment of the system's feasibility but also offers valuable insights into its potential socio-economic and environmental impact.
基金funded by the National Natural Science Foundation of China(Grant No.62272236)the Natural Science Foundation of Jiangsu Province(Grant No.BK20201136).
文摘The rapid advancement of artificial intelligence technology is driving transformative changes in medical diagnosis,treatment,and management systems through large-scale deep learning models-a process that brings both groundbreaking opportunities and multifaceted challenges.This study focuses on the medical and healthcare applications of large-scale deep learning architectures,conducting a comprehensive survey to categorize and analyze their diverse uses.The survey results reveal that current applications of large models in healthcare encompass medical data management,healthcare services,medical devices,and preventive medicine,among others.Concurrently,large models demonstrate significant advantages in the medical domain,especially in high-precision diagnosis and prediction,data analysis and knowledge discovery,and enhancing operational efficiency.Nevertheless,we identify several challenges that need urgent attention,including improving the interpretability of large models,strengthening privacy protection,and addressing issues related to handling incomplete data.This research is dedicated to systematically elucidating the deep collaborative mechanisms between artificial intelligence and the healthcare field,providing theoretical references and practical guidance for both academia and industry.
文摘The management of large-scale architectural engineering projects(e.g.,airports,hospitals)is plagued by information silos,cost overruns,and scheduling delays.While building information modeling(BIM)has improved 3D design coordination,its static nature limits its utility in real-time construction management and operational phases.This paper proposes a novel synergistic framework that integrates the static,deep data of BIM with the dynamic,real-time capabilities of digital twin(DT)technology.The framework establishes a closed-loop data flow from design(BIM)to construction(IoT,drones,BIM 360)to operation(DT platform).We detail the technological stack required,including IoT sensors,cloud computing,and AI-driven analytics.The application of this framework is illustrated through a simulated case study of a mega-terminal airport construction project,demonstrating potential reductions in rework by 15%,improvement in labor productivity by 10%,and enhanced predictive maintenance capabilities.This research contributes to the field of construction engineering by providing a practical model for achieving full lifecycle digitalization and intelligent project management.
基金supported by financial support from the National Natural Science Foundation of China(Grant Nos.52309122 and U2340229)the Innovation Team of Changjiang River Scientific Research Institute(Grant No.CKSF2024329/YT).
文摘Large-scale and heavily jointed rocks have inherent planes of anisotropy and secondary structural planes,such as dominant joint sets and random fractures,which result in significant differences in their failure mechanism and deformation behavior compared to other rock types.To address this issue,inherent anisotropic rocks with large-scale and dense joints are considered to be composed of the rock matrix,inherent planes of anisotropy,and secondary structural planes.Then a new implicit continuum model called LayerDFN is developed based on the crack tensor and damage tensor theories to characterize the mechanical properties of inherent anisotropic rocks.Furthermore,the LayerDFN model is implemented in the FLAC3D software,and a series of numerical results for typical example problems is compared with those obtained from the 3DEC,the analytical solutions,similar classical models,laboratory uniaxial compression tests,and field rigid bearing plate tests.The results demonstrate that the LayerDFN model can effectively capture the anisotropic mechanical properties of inherent anisotropic rocks,and can quantitatively characterize the damaging effect of the secondary structural planes.Overall,the numerical method based on the LayerDFN model provides a comprehensive and reliable approach for describing and analyzing the behavior of inherent anisotropic rocks,which will provide valuable insights for engineering design and decision-making processes.
基金sponsored by National Science and Technology Major Project(2011ZX05046-001)
文摘Large-scale 3D physical models of complex structures can be used to simulate hydrocarbon exploration areas. The high-fidelity simulation of actual structures poses challenges to model building and quality control. Such models can be used to collect wideazimuth, multi-azimuth, and full-azimuth seismic data that can be used to verify various 3D processing and interpretation methods. Faced with nonideal imaging problems owing to the extensive complex surface conditions and subsurface structures in the oil-rich foreland basins of western China, we designed and built the KS physical model based on the complex subsurface structure. This is the largest and most complex 3D physical model built to date. The physical modeling technology advancements mainly involve 1） the model design method, 2） the model casting flow, and 3） data acquisition. A 3D velocity model of the physical model was obtained for the first time, and the model building precision was quantitatively analyzed. The absolute error was less than 3 mm, which satisfies the experimental requirements. The 3D velocity model obtained from 3D measurements of the model layers is the basis for testing various imaging methods. Furthermore, the model is considered a standard in seismic physical modeling technology.
基金the General Program of the National Natural Science Foundation of China(Grant No.51878037).
文摘Model tests and numerical calculations were adopted based on the New Yuanliangshan tunnel project to investigate the water pressure resistance of lining construction joints in high-pressure and water-rich karst tunnels.A large-scale model test was designed and conducted,innovatively transforming the external water pressure of the lining construction joint into internal water pressure.The effects of the embedded position and waterstop type on the water pressure resistance of the construction joint were analyzed,and the reliability of the model test was verified via numerical calculations.The results show that using waterstops can significantly improve the water pressure resistance of lining construction joints.The water pressure resistance of the lining construction joint is positively correlated with the lining thickness and embedded depth of the waterstop.In addition,the type of waterstop significantly influences the water pressure resistance of lining construction joints.The test results show that the water pressure resistance of the embedded transverse reinforced waterstop is similar to that of the steel plate waterstop,and both have more advantages than the rubber waterstop.The water pressure resistance of the construction joint determined via numerical calculations is similar to the model test results,indicating that the model test results have high accuracy and reliability.This study provides a reference for similar projects and has wide applications.
基金supported by the National Natural Science Foundation of China(No.62322103)the BUPT Excellent PhD Students Foundation(No.CX2022218).
文摘The large-scale model(LSM)can handle large-scale data and complex problems,effectively improving the intelligence level of urban intersections.However,the traffic conditions at intersections are becoming increasingly complex,so the intelligent intersection LSMs(I2LSMs)also need to be continuously learned and updated.The traditional cloud-based training method incurs a significant amount of computational and storage overhead,and there is a risk of data leakage.The combination of edge artificial intelligence and federated learning provides an efficient and highly privacy protected computing mode.Therefore,we propose a hierarchical hybrid distributed training mechanism for I2LSM.Firstly,relying on the intelligent intersection system for cloud-network-terminal integration,we constructed an I2LSM hierarchical hybrid distributed training architecture.Then,we propose a hierarchical hybrid federated learning(H2Fed)algorithm that combines the advantages of centralized federated learning and decentralized federated learning.Further,we propose an adaptive compressed sensing algorithm to reduce the communication overhead.Finally,we analyze the convergence of the H2Fed algorithm.Experimental results show that the H2Fed algorithm reduces the communication overhead by 21.6%while ensuring the accuracy of the model.
文摘The streamflow over the Yellow River basin is simulated using the PRECIS （Providing REgional Climates for Impacts Studies） regional climate model driven by 15-year （1979-1993） ECMWF reanalysis data as the initial and lateral boundary conditions and an off-line large-scale routing model （LRM）. The LRM uses physical catchment and river channel information and allows streamflow to be predicted for large continental rivers with a 1°×1° spatial resolution. The results show that the PRECIS model can reproduce the general southeast to northwest gradient distribution of the precipitation over the Yellow River basin, The PRECIS- LRM model combination has the capability to simulate the seasonal and annual streamflow over the Yellow River basin. The simulated streamflow is generally coincident with the naturalized streamflow both in timing and in magnitude.
基金supported by the Ministry of Trade,Industry & Energy(MOTIE,Korea) under Industrial Technology Innovation Program (No.10063424,'development of distant speech recognition and multi-task dialog processing technologies for in-door conversational robots')
文摘A Long Short-Term Memory(LSTM) Recurrent Neural Network(RNN) has driven tremendous improvements on an acoustic model based on Gaussian Mixture Model(GMM). However, these models based on a hybrid method require a forced aligned Hidden Markov Model(HMM) state sequence obtained from the GMM-based acoustic model. Therefore, it requires a long computation time for training both the GMM-based acoustic model and a deep learning-based acoustic model. In order to solve this problem, an acoustic model using CTC algorithm is proposed. CTC algorithm does not require the GMM-based acoustic model because it does not use the forced aligned HMM state sequence. However, previous works on a LSTM RNN-based acoustic model using CTC used a small-scale training corpus. In this paper, the LSTM RNN-based acoustic model using CTC is trained on a large-scale training corpus and its performance is evaluated. The implemented acoustic model has a performance of 6.18% and 15.01% in terms of Word Error Rate(WER) for clean speech and noisy speech, respectively. This is similar to a performance of the acoustic model based on the hybrid method.
基金National Key Basic Research Program of China,No.2010CB428403National Grand Science and Technology Special Project of Water Pollution Control and Improvement,No.2009ZX07210-006
文摘The regional hydrological system is extremely complex because it is affected not only by physical factors but also by human dimensions.And the hydrological models play a very important role in simulating the complex system.However,there have not been effective methods for the model reliability and uncertainty analysis due to its complexity and difficulty.The uncertainties in hydrological modeling come from four important aspects：uncertainties in input data and parameters,uncertainties in model structure,uncertainties in analysis method and the initial and boundary conditions.This paper systematically reviewed the recent advances in the study of the uncertainty analysis approaches in the large-scale complex hydrological model on the basis of uncertainty sources.Also,the shortcomings and insufficiencies in the uncertainty analysis for complex hydrological models are pointed out.And then a new uncertainty quantification platform PSUADE and its uncertainty quantification methods were introduced,which will be a powerful tool and platform for uncertainty analysis of large-scale complex hydrological models.Finally,some future perspectives on uncertainty quantification are put forward.
基金supported by the National Key Research and Development Program of China(2022YFE0206700)。
文摘1.Introduction Climate change mitigation pathways aimed at limiting global anthropogenic carbon dioxide(CO_(2))emissions while striving to constrain the global temperature increase to below 2℃—as outlined by the Intergovernmental Panel on Climate Change(IPCC)—consistently predict the widespread implementation of CO_(2)geological storage on a global scale.
基金financially supported by the Open Research Fund of Hunan Provincial Key Laboratory of Key Technology on Hydropower Development (Grant No.PKLHD202003)the National Natural Science Foundation of China (Grant Nos.52071058 and 51939002)+1 种基金the National Natural Science Foundation of Liaoning Province (Grant No.2022-KF-18-01)Fundamental Research Funds for the Central University (Grant No.DUT20ZD219)。
文摘Considering the large diameter effect of piles,the influence of different pile-soil analysis methods on the design of monopile foundations for offshore wind turbines has become an urgent problem to be solved.Three different pile-soil models were used to study a large 10 MW monopile wind turbine.By modeling the three models in the SACS software,this paper analyzed the motion response of the overall structure under the conditions of wind and waves.According to the given working conditions,this paper concludes that under the condition of independent wind,the average value of the tower top x-displacement of the rigid connection method is the smalle st,and the standard deviation is the smallest under the condition of independent wave.The results obtained by the p-y curve method are the most conservative.
基金supported by the National Key R&D Program of China with Grant number 2019YFB1803400the National Natural Science Foundation of China under Grant number 62071114the Fundamental Research Funds for the Central Universities of China under grant numbers 3204002004A2 and 2242022k30005。
文摘This paper investigates the wireless communication with a novel architecture of antenna arrays,termed modular extremely large-scale array(XLarray),where array elements of an extremely large number/size are regularly mounted on a shared platform with both horizontally and vertically interlaced modules.Each module consists of a moderate/flexible number of array elements with the inter-element distance typically in the order of the signal wavelength,while different modules are separated by the relatively large inter-module distance for convenience of practical deployment.By accurately modelling the signal amplitudes and phases,as well as projected apertures across all modular elements,we analyse the near-field signal-to-noise ratio(SNR)performance for modular XL-array communications.Based on the non-uniform spherical wave(NUSW)modelling,the closed-form SNR expression is derived in terms of key system parameters,such as the overall modular array size,distances of adjacent modules along all dimensions,and the user's three-dimensional(3D)location.In addition,with the number of modules in different dimensions increasing infinitely,the asymptotic SNR scaling laws are revealed.Furthermore,we show that our proposed near-field modelling and performance analysis include the results for existing array architectures/modelling as special cases,e.g.,the collocated XL-array architecture,the uniform plane wave(UPW)based far-field modelling,and the modular extremely large-scale uniform linear array(XL-ULA)of onedimension.Extensive simulation results are presented to validate our findings.
