This article studies a class of nonlinear Kirchhoff equations with exponential critical growth,trapping potential,and perturbation.Under appropriate assumptions about f and h,the article obtained the existence of norm...This article studies a class of nonlinear Kirchhoff equations with exponential critical growth,trapping potential,and perturbation.Under appropriate assumptions about f and h,the article obtained the existence of normalized positive solutions for this equation via the Trudinger-Moser inequality and variational methods.Moreover,these solutions are also ground state solutions.Additionally,the article also characterized the asymptotic behavior of solutions.The results of this article expand the research of relevant literature.展开更多
[Objective]Implementation of the Ten-Year Fishing Ban policy may alter fish diversity and niche characteristics of dominant species in spawning grounds within the National Nature Reserve for Rare and Endemic Fish in t...[Objective]Implementation of the Ten-Year Fishing Ban policy may alter fish diversity and niche characteristics of dominant species in spawning grounds within the National Nature Reserve for Rare and Endemic Fish in the Upper Yangtze River.This study initiated continuous monitoring of natural spawning habitats from February 2022 to assess these ecological changes.[Methods]Environmental DNA(eDNA)metabarcoding was employed to analyze fish species composition,biodiversity patterns,and niche parameters of dominant species.Water sampling followed the CEN/TS 19461 standard across five monitoring transects(ZT1-ZT5).[Results]The eDNA analysis detected 45 species of fish belonging to 38 genera,13 families,and 3 orders were detected through environmental DNA(eDNA)in this survey,including 10 species endemic to the upper reaches of the Yangtze River,such as Procypris rabaudi and Myxocyprinus asiaticus.The fish community was mainly composed of bottom-dwelling,settling ovum-producing,omnivorous fish.The variation ranges of the Chao1 index,ACE index,Shannon index,and Simpson index are 736~996,719~965,1.58~3.23,and 0.83~0.99,respectively,indicating that fish species in spawning sites are abundant and community distribution uniformity is high.All indexes are highest at ZT1 monitoring points.Cluster analysis showed that,at a certain similarity level,fish community types in spawning sites could be basically divided into two groups:ZT1,ZT3,and ZT5 clustered together,and ZT2 and ZT4 clustered together,indicating similar fish community habitats.There are 9 dominant fish species in typical deep pool habitats in the reserve,with niche widths(Bi)ranging from 1.13 to 3.87.The dominant fish species are broad and medium niche fish,such as Cyprinus carpio and Hemiculter tchangi,with the niche overlap index(Oik)of some dominant fish species reaching more than 0.95.This indicates fierce competition for resources among the fish in this spawning ground.[Conclusion]The Zhutuo spawning ground demonstrates high species richness with homogeneous community structure and intense resource competition.This study establishes an eDNA-based monitoring framework that enhances conventional survey method,providing critical baseline data for adaptive management under the fishing moratorium regime.展开更多
Ground reinforcement is crucial for tunnel construction, especially in soft rock tunnels. Existing analytical models are inadequate for predicting the ground reaction curves (GRCs) for reinforced tunnels in strain-sof...Ground reinforcement is crucial for tunnel construction, especially in soft rock tunnels. Existing analytical models are inadequate for predicting the ground reaction curves (GRCs) for reinforced tunnels in strain-softening (SS) rock masses. This study proposes a novel analytical model to determine the GRCs of SS rock masses, incorporating ground reinforcement and intermediate principal stress (IPS). The SS constitutive model captures the progressive post- peak failure, while the elastic-brittle model simulates reinforced rock masses. Nine combined states are innovatively investigated to analyze plastic zone development in natural and reinforced regions. Each region is analyzed separately, and coupled through boundary conditions at interface. Comparison with three types of existing models indicates that these models overestimate reinforcement effects. The deformation prediction errors of single geological material models may exceed 75%. Furthermore, neglecting softening and residual zones in natural regions could lead to errors over 50%. Considering the IPS can effectively utilize the rock strength to reduce tunnel deformation by at least 30%, thereby saving on reinforcement and support costs. The computational results show a satisfactory agreement with the monitoring data from a model test and two tunnel projects. The proposed model may offer valuable insights into the design and construction of reinforced tunnel engineering.展开更多
Blast-induced ground vibration,quantified by peak particle velocity(PPV),is a crucial factor in mitigating environmental and structural risks in mining and geotechnical engineering.Accurate PPV prediction facilitates ...Blast-induced ground vibration,quantified by peak particle velocity(PPV),is a crucial factor in mitigating environmental and structural risks in mining and geotechnical engineering.Accurate PPV prediction facilitates safer and more sustainable blasting operations by minimizing adverse impacts and ensuring regulatory compliance.This study presents an advanced predictive framework integrating Cat Boost(CB)with nature-inspired optimization algorithms,including the Bat Algorithm(BAT),Sparrow Search Algorithm(SSA),Butterfly Optimization Algorithm(BOA),and Grasshopper Optimization Algorithm(GOA).A comprehensive dataset from the Sarcheshmeh Copper Mine in Iran was utilized to develop and evaluate these models using key performance metrics such as the Index of Agreement(IoA),Nash-Sutcliffe Efficiency(NSE),and the coefficient of determination(R^(2)).The hybrid CB-BOA model outperformed other approaches,achieving the highest accuracy(R^(2)=0.989)and the lowest prediction errors.SHAP analysis identified Distance(Di)as the most influential variable affecting PPV,while uncertainty analysis confirmed CB-BOA as the most reliable model,featuring the narrowest prediction interval.These findings highlight the effectiveness of hybrid machine learning models in refining PPV predictions,contributing to improved blast design strategies,enhanced structural safety,and reduced environmental impacts in mining and geotechnical engineering.展开更多
Ferrite-rich calcium sulfoaluminate(FCSA)cement is often used in special projects such as marine engineering due to its excellent resistance of seawater attack although the cost is a little high.Ground granulated blas...Ferrite-rich calcium sulfoaluminate(FCSA)cement is often used in special projects such as marine engineering due to its excellent resistance of seawater attack although the cost is a little high.Ground granulated blast furnace slag(GGBS),a byproduct of industrial production,is used as a mineral admixture to reduce concrete costs and provide excellent performance.This study aimed to investigate the impact of GGBS on the hydration properties of FCSA cement in seawater.Tests were conducted on heat of hydration,compressive strength,mass change,and pH value of pore solution of FCSA cement paste with a water-to-binder ratio of 0.45.X-ray diffraction(XRD)analysis and thermogravimetric analysis were used to determine the hydration products,while mercury intrusion porosimetry(MIP)was used to measure pore structure.The results indicated that the FCSA cement hydration showed a concentrated heat release at early age.The compressive strength of specimens consistently increased over time,where seawater curing enhanced the compressive strength of control samples.The pH value of pore solution decreased to 10.7−10.9 at 90 d when cured in seawater.The primary hydration products of FCSA cement included ettringite,iron hydroxide gel(FH_(3)),and aluminum hydroxide gel(AH_(3)).Moreover,when cured in seawater,Friedel’s salt was formed,which enhanced the compressive strength of the specimen and increased its coefficient of corrosion.Seawater curing gradually increased sample mass,and GGBS refined pore structure while reducing harmful pore proportions.These results suggest that while GGBS can refine pore structure and improve certain aspects of performance,its inclusion may also reduce compressive strength,highlighting the need for a balanced approach in its use for marine applications.展开更多
The process of ground vehicle dynamic gravimetry is inevitably affected by the carrier’s maneuvering acceleration,which makes the result contain a large amount of dynamic error.In this paper,we propose a dynamic erro...The process of ground vehicle dynamic gravimetry is inevitably affected by the carrier’s maneuvering acceleration,which makes the result contain a large amount of dynamic error.In this paper,we propose a dynamic error suppression method of gravimetry based on the high-precision acquisition of external velocity for compensating the horizontal error of the inertial plat-form.On the basis of platform gravity measurement,firstly,the dynamic performance of the system is enhanced by optimizing the horizontal damping network of the inertial platform and selecting its parameter.Secondly,an improved federal Kalman filtering algorithm and a fault diagnosis method are designed using strapdown inertial navigation system(SINS),odometer(OD),and laser Doppler velocimeter(LDV).Simulation validates that these methods can improve the accuracy and robustness of the external velocity acquisition.Three survey lines are selected in Tianjin,China,for the gravimetry experiments with different maneuvering levels,and the results demonstrate that after dynamic error suppression,the internal coincidence accuracies of smooth and uniform operation,obvious acceleration and deceleration operation,and high-dynamic operation are improved by 70.2%,73.6%,and 77.9%to reach 0.81 mGal,1.30 mGal,and 1.94 mGal,respectively,and the external coinci-dence accuracies during smooth and uniform operation are improved by 48.6%up to 1.66 mGal.It is shown that the pro-posed method can effectively suppress the dynamic error,and that the accuracy improvement increases with carrier maneuver-ability.However,the amount of residual error that can not be entirely eliminated increases as well,so the ground vehicle dynamic gravimetry should be maintained in the carrier for smooth and uniform operation.展开更多
Ground penetrating radar(GPR),as a fast,efficient,and non-destructive detection device,holds great potential for the detection of shallow subsurface environments,such as urban road subsurface monitoring.However,the in...Ground penetrating radar(GPR),as a fast,efficient,and non-destructive detection device,holds great potential for the detection of shallow subsurface environments,such as urban road subsurface monitoring.However,the interpretation of GPR echo images often relies on manual recognition by experienced engineers.In order to address the automatic interpretation of cavity targets in GPR echo images,a recognition-algorithm based on Gaussian mixed model-hidden Markov model(GMM-HMM)is proposed,which can recognize three dimensional(3D)underground voids automatically.First,energy detection on the echo images is performed,whereby the data is preprocessed and pre-filtered.Then,edge histogram descriptor(EHD),histogram of oriented gradient(HOG),and Log-Gabor filters are used to extract features from the images.The traditional method can only be applied to 2D images and pre-processing is required for C-scan images.Finally,the aggregated features are fed into the GMM-HMM for classification and compared with two other methods,long short-term memory(LSTM)and gate recurrent unit(GRU).By testing on a simulated dataset,an accuracy rate of 90%is obtained,demonstrating the effectiveness and efficiency of our proposed method.展开更多
Unmanned autonomous helicopter(UAH)path planning problem is an important component of the UAH mission planning system.Aiming to reduce the influence of non-complete ground threat information on UAH path planning,a gro...Unmanned autonomous helicopter(UAH)path planning problem is an important component of the UAH mission planning system.Aiming to reduce the influence of non-complete ground threat information on UAH path planning,a ground threat prediction-based path planning method is proposed based on artificial bee colony(ABC)algorithm by collaborative thinking strategy.Firstly,a dynamic threat distribution probability model is developed based on the characteristics of typical ground threats.The dynamic no-fly zone of the UAH is simulated and established by calculating the distribution probability of ground threats in real time.Then,a dynamic path planning method for UAH is designed in complex environment based on the real-time prediction of ground threats.By adding the collision warning mechanism to the path planning model,the flight path could be dynamically adjusted according to changing no-fly zones.Furthermore,a hybrid enhanced ABC algorithm is proposed based on collaborative thinking strategy.The proposed algorithm applies the leader-member thinking mechanism to guide the direction of population evolution,and reduces the negative impact of local optimal solutions caused by collaborative learning update strategy,which makes the optimization performance of ABC algorithm more controllable and efficient.Finally,simulation results verify the feasibility and effectiveness of the proposed ground threat prediction path planning method.展开更多
This study is the result of long-term efforts of the authors’team to assess ground response of gob-side entry by roof cutting(GSERC)with hard main roof,aiming at scientific control for GSERC deformation.A comprehensi...This study is the result of long-term efforts of the authors’team to assess ground response of gob-side entry by roof cutting(GSERC)with hard main roof,aiming at scientific control for GSERC deformation.A comprehensive field measurement program was conducted to determine entry deformation,roof fracture zone,and anchor bolt(cable)loading.The results indicate that GSERC deformation presents asymmetric characteristics.The maximum convergence near roof cutting side is 458 mm during the primary use process and 1120 mm during the secondary reuse process.The entry deformation is closely associated with the primary development stage,primary use stage,and secondary reuse stage.The key block movement of roof cutting structure,a complex stress environment,and a mismatch in the supporting design scheme are the failure mechanism of GSERC.A controlling ideology for mining states,including regional and stage divisions,was proposed.Both dynamic and permanent support schemes have been implemented in the field.Engineering practice results indicate that the new support scheme can efficiently ensure long-term entry safety and could be a reliable approach for other engineering practices.展开更多
基金Supported by National Natural Science Foundation of China(11671403,11671236)Henan Provincial General Natural Science Foundation Project(232300420113)。
文摘This article studies a class of nonlinear Kirchhoff equations with exponential critical growth,trapping potential,and perturbation.Under appropriate assumptions about f and h,the article obtained the existence of normalized positive solutions for this equation via the Trudinger-Moser inequality and variational methods.Moreover,these solutions are also ground state solutions.Additionally,the article also characterized the asymptotic behavior of solutions.The results of this article expand the research of relevant literature.
文摘[Objective]Implementation of the Ten-Year Fishing Ban policy may alter fish diversity and niche characteristics of dominant species in spawning grounds within the National Nature Reserve for Rare and Endemic Fish in the Upper Yangtze River.This study initiated continuous monitoring of natural spawning habitats from February 2022 to assess these ecological changes.[Methods]Environmental DNA(eDNA)metabarcoding was employed to analyze fish species composition,biodiversity patterns,and niche parameters of dominant species.Water sampling followed the CEN/TS 19461 standard across five monitoring transects(ZT1-ZT5).[Results]The eDNA analysis detected 45 species of fish belonging to 38 genera,13 families,and 3 orders were detected through environmental DNA(eDNA)in this survey,including 10 species endemic to the upper reaches of the Yangtze River,such as Procypris rabaudi and Myxocyprinus asiaticus.The fish community was mainly composed of bottom-dwelling,settling ovum-producing,omnivorous fish.The variation ranges of the Chao1 index,ACE index,Shannon index,and Simpson index are 736~996,719~965,1.58~3.23,and 0.83~0.99,respectively,indicating that fish species in spawning sites are abundant and community distribution uniformity is high.All indexes are highest at ZT1 monitoring points.Cluster analysis showed that,at a certain similarity level,fish community types in spawning sites could be basically divided into two groups:ZT1,ZT3,and ZT5 clustered together,and ZT2 and ZT4 clustered together,indicating similar fish community habitats.There are 9 dominant fish species in typical deep pool habitats in the reserve,with niche widths(Bi)ranging from 1.13 to 3.87.The dominant fish species are broad and medium niche fish,such as Cyprinus carpio and Hemiculter tchangi,with the niche overlap index(Oik)of some dominant fish species reaching more than 0.95.This indicates fierce competition for resources among the fish in this spawning ground.[Conclusion]The Zhutuo spawning ground demonstrates high species richness with homogeneous community structure and intense resource competition.This study establishes an eDNA-based monitoring framework that enhances conventional survey method,providing critical baseline data for adaptive management under the fishing moratorium regime.
基金Projects(52208382, 52278387, 51738002) supported by the National Natural Science Foundation of ChinaProject(2022YJS072) supported by the Fundamental Research Funds for the Central Universities,China。
文摘Ground reinforcement is crucial for tunnel construction, especially in soft rock tunnels. Existing analytical models are inadequate for predicting the ground reaction curves (GRCs) for reinforced tunnels in strain-softening (SS) rock masses. This study proposes a novel analytical model to determine the GRCs of SS rock masses, incorporating ground reinforcement and intermediate principal stress (IPS). The SS constitutive model captures the progressive post- peak failure, while the elastic-brittle model simulates reinforced rock masses. Nine combined states are innovatively investigated to analyze plastic zone development in natural and reinforced regions. Each region is analyzed separately, and coupled through boundary conditions at interface. Comparison with three types of existing models indicates that these models overestimate reinforcement effects. The deformation prediction errors of single geological material models may exceed 75%. Furthermore, neglecting softening and residual zones in natural regions could lead to errors over 50%. Considering the IPS can effectively utilize the rock strength to reduce tunnel deformation by at least 30%, thereby saving on reinforcement and support costs. The computational results show a satisfactory agreement with the monitoring data from a model test and two tunnel projects. The proposed model may offer valuable insights into the design and construction of reinforced tunnel engineering.
基金the Deanship of Scientific Research at Northern Border University,Arar,KSA for funding this research work through the project number"NBUFFMRA-2025-2461-09"。
文摘Blast-induced ground vibration,quantified by peak particle velocity(PPV),is a crucial factor in mitigating environmental and structural risks in mining and geotechnical engineering.Accurate PPV prediction facilitates safer and more sustainable blasting operations by minimizing adverse impacts and ensuring regulatory compliance.This study presents an advanced predictive framework integrating Cat Boost(CB)with nature-inspired optimization algorithms,including the Bat Algorithm(BAT),Sparrow Search Algorithm(SSA),Butterfly Optimization Algorithm(BOA),and Grasshopper Optimization Algorithm(GOA).A comprehensive dataset from the Sarcheshmeh Copper Mine in Iran was utilized to develop and evaluate these models using key performance metrics such as the Index of Agreement(IoA),Nash-Sutcliffe Efficiency(NSE),and the coefficient of determination(R^(2)).The hybrid CB-BOA model outperformed other approaches,achieving the highest accuracy(R^(2)=0.989)and the lowest prediction errors.SHAP analysis identified Distance(Di)as the most influential variable affecting PPV,while uncertainty analysis confirmed CB-BOA as the most reliable model,featuring the narrowest prediction interval.These findings highlight the effectiveness of hybrid machine learning models in refining PPV predictions,contributing to improved blast design strategies,enhanced structural safety,and reduced environmental impacts in mining and geotechnical engineering.
基金Project(2023DJC182)supported by the Department of Science and Technology of Hubei Province,ChinaProjects(51608402,51602229)supported by the National Natural Science Foundation of ChinaProject(2021-2075-38)supported by the Department of Housing and Urban-Rural Development of Hubei Province,China。
文摘Ferrite-rich calcium sulfoaluminate(FCSA)cement is often used in special projects such as marine engineering due to its excellent resistance of seawater attack although the cost is a little high.Ground granulated blast furnace slag(GGBS),a byproduct of industrial production,is used as a mineral admixture to reduce concrete costs and provide excellent performance.This study aimed to investigate the impact of GGBS on the hydration properties of FCSA cement in seawater.Tests were conducted on heat of hydration,compressive strength,mass change,and pH value of pore solution of FCSA cement paste with a water-to-binder ratio of 0.45.X-ray diffraction(XRD)analysis and thermogravimetric analysis were used to determine the hydration products,while mercury intrusion porosimetry(MIP)was used to measure pore structure.The results indicated that the FCSA cement hydration showed a concentrated heat release at early age.The compressive strength of specimens consistently increased over time,where seawater curing enhanced the compressive strength of control samples.The pH value of pore solution decreased to 10.7−10.9 at 90 d when cured in seawater.The primary hydration products of FCSA cement included ettringite,iron hydroxide gel(FH_(3)),and aluminum hydroxide gel(AH_(3)).Moreover,when cured in seawater,Friedel’s salt was formed,which enhanced the compressive strength of the specimen and increased its coefficient of corrosion.Seawater curing gradually increased sample mass,and GGBS refined pore structure while reducing harmful pore proportions.These results suggest that while GGBS can refine pore structure and improve certain aspects of performance,its inclusion may also reduce compressive strength,highlighting the need for a balanced approach in its use for marine applications.
基金supported by the Shanxi Provincial Natural Science Basic Research Program Young Talent Project(S2019-JC-QN-2408).
文摘The process of ground vehicle dynamic gravimetry is inevitably affected by the carrier’s maneuvering acceleration,which makes the result contain a large amount of dynamic error.In this paper,we propose a dynamic error suppression method of gravimetry based on the high-precision acquisition of external velocity for compensating the horizontal error of the inertial plat-form.On the basis of platform gravity measurement,firstly,the dynamic performance of the system is enhanced by optimizing the horizontal damping network of the inertial platform and selecting its parameter.Secondly,an improved federal Kalman filtering algorithm and a fault diagnosis method are designed using strapdown inertial navigation system(SINS),odometer(OD),and laser Doppler velocimeter(LDV).Simulation validates that these methods can improve the accuracy and robustness of the external velocity acquisition.Three survey lines are selected in Tianjin,China,for the gravimetry experiments with different maneuvering levels,and the results demonstrate that after dynamic error suppression,the internal coincidence accuracies of smooth and uniform operation,obvious acceleration and deceleration operation,and high-dynamic operation are improved by 70.2%,73.6%,and 77.9%to reach 0.81 mGal,1.30 mGal,and 1.94 mGal,respectively,and the external coinci-dence accuracies during smooth and uniform operation are improved by 48.6%up to 1.66 mGal.It is shown that the pro-posed method can effectively suppress the dynamic error,and that the accuracy improvement increases with carrier maneuver-ability.However,the amount of residual error that can not be entirely eliminated increases as well,so the ground vehicle dynamic gravimetry should be maintained in the carrier for smooth and uniform operation.
基金National Natural Science Foundation of China(62071147)。
文摘Ground penetrating radar(GPR),as a fast,efficient,and non-destructive detection device,holds great potential for the detection of shallow subsurface environments,such as urban road subsurface monitoring.However,the interpretation of GPR echo images often relies on manual recognition by experienced engineers.In order to address the automatic interpretation of cavity targets in GPR echo images,a recognition-algorithm based on Gaussian mixed model-hidden Markov model(GMM-HMM)is proposed,which can recognize three dimensional(3D)underground voids automatically.First,energy detection on the echo images is performed,whereby the data is preprocessed and pre-filtered.Then,edge histogram descriptor(EHD),histogram of oriented gradient(HOG),and Log-Gabor filters are used to extract features from the images.The traditional method can only be applied to 2D images and pre-processing is required for C-scan images.Finally,the aggregated features are fed into the GMM-HMM for classification and compared with two other methods,long short-term memory(LSTM)and gate recurrent unit(GRU).By testing on a simulated dataset,an accuracy rate of 90%is obtained,demonstrating the effectiveness and efficiency of our proposed method.
文摘Unmanned autonomous helicopter(UAH)path planning problem is an important component of the UAH mission planning system.Aiming to reduce the influence of non-complete ground threat information on UAH path planning,a ground threat prediction-based path planning method is proposed based on artificial bee colony(ABC)algorithm by collaborative thinking strategy.Firstly,a dynamic threat distribution probability model is developed based on the characteristics of typical ground threats.The dynamic no-fly zone of the UAH is simulated and established by calculating the distribution probability of ground threats in real time.Then,a dynamic path planning method for UAH is designed in complex environment based on the real-time prediction of ground threats.By adding the collision warning mechanism to the path planning model,the flight path could be dynamically adjusted according to changing no-fly zones.Furthermore,a hybrid enhanced ABC algorithm is proposed based on collaborative thinking strategy.The proposed algorithm applies the leader-member thinking mechanism to guide the direction of population evolution,and reduces the negative impact of local optimal solutions caused by collaborative learning update strategy,which makes the optimization performance of ABC algorithm more controllable and efficient.Finally,simulation results verify the feasibility and effectiveness of the proposed ground threat prediction path planning method.
基金Project(WPUKFJJ2019-19)supported by the Open Fund of State Key Laboratory of Water Resource Protection and Utilization in Coal Mining,ChinaProject(51974317)supported by the National Natural Science Foundation of China。
文摘This study is the result of long-term efforts of the authors’team to assess ground response of gob-side entry by roof cutting(GSERC)with hard main roof,aiming at scientific control for GSERC deformation.A comprehensive field measurement program was conducted to determine entry deformation,roof fracture zone,and anchor bolt(cable)loading.The results indicate that GSERC deformation presents asymmetric characteristics.The maximum convergence near roof cutting side is 458 mm during the primary use process and 1120 mm during the secondary reuse process.The entry deformation is closely associated with the primary development stage,primary use stage,and secondary reuse stage.The key block movement of roof cutting structure,a complex stress environment,and a mismatch in the supporting design scheme are the failure mechanism of GSERC.A controlling ideology for mining states,including regional and stage divisions,was proposed.Both dynamic and permanent support schemes have been implemented in the field.Engineering practice results indicate that the new support scheme can efficiently ensure long-term entry safety and could be a reliable approach for other engineering practices.
