GNSS time series analysis provides an effective method for research on the earth's surface deformation,and it can be divided into two parts,deterministic models and stochastic models.The former part can be achieve...GNSS time series analysis provides an effective method for research on the earth's surface deformation,and it can be divided into two parts,deterministic models and stochastic models.The former part can be achieved by several parameters,such as polynomial terms,periodic terms,offsets,and post-seismic models.The latter contains some stochastic noises,which can be affected by detecting the former parameters.If there are not enough parameters assumed,modeling errors will occur and adversely affect the analysis results.In this study,we propose a processing strategy in which the commonly-used 1-order of the polynomial term can be replaced with different orders for better fitting GNSS time series of the Crustal Movement Network of China(CMONOC)stations.Initially,we use the Bayesian Information Criterion(BIC)to identify the best order within the range of 1-4 during the fitting process using the white noise plus power-law noise(WN+PL)model.Then,we compare the 1-order and the optimal order on the effect of deterministic models in GNSS time series,including the velocity and its uncertainty,amplitudes,and initial phases of the annual signals.The results indicate that the first-order polynomial in the GNSS time series is not the primary factor.The root mean square(RMS)reduction rates of almost all station components are positive,which means the new fitting of optimal-order polynomial helps to reduce the RMS of residual series.Most stations maintain the velocity difference(VD)within ±1 mm/yr,with percentages of 85.6%,81.9%and 63.4%in the North,East,and Up components,respectively.As for annual signals,the numbers of amplitude difference(AD)remained at ±0.2 mm are 242,239,and 200 in three components,accounting for 99.6%,98.4%,and 82.3%,respectively.This finding reminds us that the detection of the optimal-order polynomial is necessary when we aim to acquire an accurate understanding of the crustal movement features.展开更多
In this article,the post-peak softening stage of the constitutive relation and the elastic stiffness degradation of concrete are investigated,and a highly reasonable constitutive relation curve is proposed.At the mate...In this article,the post-peak softening stage of the constitutive relation and the elastic stiffness degradation of concrete are investigated,and a highly reasonable constitutive relation curve is proposed.At the material level,the energy change in the concrete failure process is studied based on the different stress-strain curves of concrete under uniaxial tension and compression.The concrete failure criterion based on elastic strain energy density is deemed suitable and consistent with the experimental phenomena.The hysteresis phenomenon(lags behind the peak strength)is also discussed.At the structure level,the strength reduction method is employed for the stability analysis,the energy change in the failure process of the Long Xi-Kou Dam is examined,and the results show that the dam failure criterion based on elastic strain energy shows a greater significance in practical applications compared with other conventional structural failure criteria in engineering.This criterion is objective and can avoid subjective arbitrariness.展开更多
As autonomous vehicles and the other supporting infrastructures(e.g.,smart cities and intelligent transportation systems)become more commonplace,the Internet of Vehicles(IoV)is getting increasingly prevalent.There hav...As autonomous vehicles and the other supporting infrastructures(e.g.,smart cities and intelligent transportation systems)become more commonplace,the Internet of Vehicles(IoV)is getting increasingly prevalent.There have been attempts to utilize Digital Twins(DTs)to facilitate the design,evaluation,and deployment of IoV-based systems,for example by supporting high-fidelity modeling,real-time monitoring,and advanced predictive capabilities.However,the literature review undertaken in this paper suggests that integrating DTs into IoV-based system design and deployment remains an understudied topic.In addition,this paper explains how DTs can benefit IoV system designers and implementers,as well as describes several challenges and opportunities for future researchers.展开更多
Azole fungicides(AFs)play an important role in the prevention and treatment of fungal diseases in agricultural crops.However,limited studies are addressing the fate and ecological risk of AFs in the urban water cycle ...Azole fungicides(AFs)play an important role in the prevention and treatment of fungal diseases in agricultural crops.However,limited studies are addressing the fate and ecological risk of AFs in the urban water cycle at a large watershed scale.To address this gap,we investigated the spatiotemporal distribution and ecological risk of twenty AFs in the lower reaches of the Yangtze River across four seasons.Carbendazim(CBA),tebuconazole(TBA),tricyclazole(TCA),and propiconazole(PPA)were found to be the dominant compounds.Their highest concentrations were measured in January(188.3 ng/L),and November(2197.1 ng/L),July(162.0 ng/L),and November(1801.9 ng/L),respectively.The comparison between wastewater treatment plants(WWTPs)effluents and surface water suggested that industrial WWTPs are major sources of AFs in the Yangtze River.In particular,TBA and PPA were found to be the most recalcitrant AFs in industrial WWTPs,while difenoconazole(DFA)was found to be the most potent pollutant in municipal WWTPs,with an average removal rate of less than60%.The average risk quotient(RQ)for the entire AFs was 6.45 in the fall,which was higher than in January(0.98),April(0.61),and July(0.40).This indicates that AFs in surface water posed higher environmental risks during the dry season.Additionally,the exposure risk of AFs via drinking water for sensitive populations deserves more attention.This study provides benchmark data on the occurrence of AFs in the lower reaches of the Yangtze River,and offers suggestions for better reduction of AFs.展开更多
Accurate monitoring of bridge deformation under environmental and operational loads is critical for ensuring structural safety and serviceability.This paper presents an integrated displacement and attitude determinati...Accurate monitoring of bridge deformation under environmental and operational loads is critical for ensuring structural safety and serviceability.This paper presents an integrated displacement and attitude determination approach for bridge health monitoring,leveraging Global Navigation Satellite System(GNSS)technology to simultaneously capture displacement and attitude variations,such as pitch and heading angles.This method combines the GNSS observations at multiple antennas located on the bridge,utilizes a unit quaternion to express the attitude,and parameterizes the displacement,attitude,and carrier-phase ambiguities in one unifed measurement model.Then,the unscented Kalman flter is adapted to achieve the optimal estimation of the quaternion-based nonlinear systems.Finally,the double-diferenced ambiguities between the stations are resolved to integers to improve the accuracy of estimated displacement and attitude.The proposed method was evaluated using the data collected in the Forth Road Bridge,a long-span suspension bridge with a main span of 1.006 km and a total length exceeding 2.5 km.Using GNSS baselines ranging from 1.2 to 2.0 km,the method achieved horizontal and vertical displacement accuracies of 0.004-0.006 m and 0.008-0.010 m,respectively.For a 263 m baseline between the quarter-and mid-span points,pitch and heading accuracies reached 0.0013°and 0.0004°,respectively.Furthermore,the method is capable of determining the roll angle by utilizing monitoring stations located on the opposite side of the bridge.It reveals that this method can sensitively detect subtle attitude changes,ofering insights into bridge behaviour from a new perspective beyond displacement data.This work establishes the full cross-correlation between displacement and attitude parameters,which is benefcial for developing tightly coupled GNSS and inertial measurement unit in terms of both displacement and attitude parameters for structural health monitoring.The fndings underscore the potential of this approach in the establishment of the next-generation structure health monitoring systems,with a focus on robustness,reliability,and scalability for broader applications.展开更多
This paper aims to explore the coupling mechanism between flow movement, sediment transport and riverbed evolution in currently widely used mathematical models for sediment transport. Based on characteristic theory, a...This paper aims to explore the coupling mechanism between flow movement, sediment transport and riverbed evolution in currently widely used mathematical models for sediment transport. Based on characteristic theory, analytic forms of eigenvalues,eigenvectors and characteristic relationships of total-sediment transport model, bed-load transport model and suspenedload transport model were derived, respectively. The singular perturbation technology was implemented to obtain the asymptotic solutions to different families of eigenvalues. The results indicate that, interactions between motion variables were explicitly coupled in the characteristics of total-sediment transport model and bed-load transport model. Further qualitative and quantitative analysis demonstrates that high sediment transport intensity and significant riverbed change will inevitably affect the property of flow movement. In the process of deposition, sediment-laden flow will move faster when sediment transport intensity becomes stronger. In contrast, the wave of flow will propagate at slower speed as erosion intensity becomes stronger.For most existing suspended-load transport models, however, the characteristics are decoupled as the interactions between motion variables cannot be integrally illustrated in eigenvalues, eigenvectors and characteristic relationship.展开更多
Evaluating the health of river surface water is essential,as rivers support significant biological resources and serve as vital drinking water sources.While the Water Quality Index(WQI)is commonly employed to evaluate...Evaluating the health of river surface water is essential,as rivers support significant biological resources and serve as vital drinking water sources.While the Water Quality Index(WQI)is commonly employed to evaluate surface water quality,it fails to consider biodiversity and does not fully capture the ecological health of rivers.Here we show a comprehensive assessment of the ecological health of surface water in the lower Yangtze River(LYR),integrating chemical and biological metrics.According to traditional WQI metrics,the LYR's surface water generally meets China's Class II standards.However,it also contains 43 high-risk emerging contaminants;nitrobenzenes are found at the highest concentrations,representing 25e90%of total detections,while polycyclic aromatic hydrocarbons present the most substantial environmental risks,accounting for 81e93%of the total risk quotient.Notably,the plankton-based index of biological integrity(P-IBI)rates the ecological health of the majority of LYR water samples(59.7%)as‘fair’,with significantly better health observed in autumn compared to other seasons(p<0.01).Our findings suggest that including emerging contaminants and P-IBI as additional metrics can enhance the traditional WQI analysis in evaluating surface water's ecological health.These results highlight the need for a multidimensional assessment approach and call for improvements to LYR's ecological health,focusing on emerging contaminants and biodiversity rather than solely on reducing conventional indicators.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.42404017,42122025 and 42174030).
文摘GNSS time series analysis provides an effective method for research on the earth's surface deformation,and it can be divided into two parts,deterministic models and stochastic models.The former part can be achieved by several parameters,such as polynomial terms,periodic terms,offsets,and post-seismic models.The latter contains some stochastic noises,which can be affected by detecting the former parameters.If there are not enough parameters assumed,modeling errors will occur and adversely affect the analysis results.In this study,we propose a processing strategy in which the commonly-used 1-order of the polynomial term can be replaced with different orders for better fitting GNSS time series of the Crustal Movement Network of China(CMONOC)stations.Initially,we use the Bayesian Information Criterion(BIC)to identify the best order within the range of 1-4 during the fitting process using the white noise plus power-law noise(WN+PL)model.Then,we compare the 1-order and the optimal order on the effect of deterministic models in GNSS time series,including the velocity and its uncertainty,amplitudes,and initial phases of the annual signals.The results indicate that the first-order polynomial in the GNSS time series is not the primary factor.The root mean square(RMS)reduction rates of almost all station components are positive,which means the new fitting of optimal-order polynomial helps to reduce the RMS of residual series.Most stations maintain the velocity difference(VD)within ±1 mm/yr,with percentages of 85.6%,81.9%and 63.4%in the North,East,and Up components,respectively.As for annual signals,the numbers of amplitude difference(AD)remained at ±0.2 mm are 242,239,and 200 in three components,accounting for 99.6%,98.4%,and 82.3%,respectively.This finding reminds us that the detection of the optimal-order polynomial is necessary when we aim to acquire an accurate understanding of the crustal movement features.
基金supported by The National Natural Science Foundation of China(No.51739006,11132003).
文摘In this article,the post-peak softening stage of the constitutive relation and the elastic stiffness degradation of concrete are investigated,and a highly reasonable constitutive relation curve is proposed.At the material level,the energy change in the concrete failure process is studied based on the different stress-strain curves of concrete under uniaxial tension and compression.The concrete failure criterion based on elastic strain energy density is deemed suitable and consistent with the experimental phenomena.The hysteresis phenomenon(lags behind the peak strength)is also discussed.At the structure level,the strength reduction method is employed for the stability analysis,the energy change in the failure process of the Long Xi-Kou Dam is examined,and the results show that the dam failure criterion based on elastic strain energy shows a greater significance in practical applications compared with other conventional structural failure criteria in engineering.This criterion is objective and can avoid subjective arbitrariness.
基金supported by the Natural Science Foundation of Jiangsu Province of China under grant no.BK20211284the Financial and Science Technology Plan Project of Xinjiang Production and Construction Corps under grant no.2020DB005.
文摘As autonomous vehicles and the other supporting infrastructures(e.g.,smart cities and intelligent transportation systems)become more commonplace,the Internet of Vehicles(IoV)is getting increasingly prevalent.There have been attempts to utilize Digital Twins(DTs)to facilitate the design,evaluation,and deployment of IoV-based systems,for example by supporting high-fidelity modeling,real-time monitoring,and advanced predictive capabilities.However,the literature review undertaken in this paper suggests that integrating DTs into IoV-based system design and deployment remains an understudied topic.In addition,this paper explains how DTs can benefit IoV system designers and implementers,as well as describes several challenges and opportunities for future researchers.
基金supported by the National Natural Science Foundation of China(Nos.52270072,4222780043)。
文摘Azole fungicides(AFs)play an important role in the prevention and treatment of fungal diseases in agricultural crops.However,limited studies are addressing the fate and ecological risk of AFs in the urban water cycle at a large watershed scale.To address this gap,we investigated the spatiotemporal distribution and ecological risk of twenty AFs in the lower reaches of the Yangtze River across four seasons.Carbendazim(CBA),tebuconazole(TBA),tricyclazole(TCA),and propiconazole(PPA)were found to be the dominant compounds.Their highest concentrations were measured in January(188.3 ng/L),and November(2197.1 ng/L),July(162.0 ng/L),and November(1801.9 ng/L),respectively.The comparison between wastewater treatment plants(WWTPs)effluents and surface water suggested that industrial WWTPs are major sources of AFs in the Yangtze River.In particular,TBA and PPA were found to be the most recalcitrant AFs in industrial WWTPs,while difenoconazole(DFA)was found to be the most potent pollutant in municipal WWTPs,with an average removal rate of less than60%.The average risk quotient(RQ)for the entire AFs was 6.45 in the fall,which was higher than in January(0.98),April(0.61),and July(0.40).This indicates that AFs in surface water posed higher environmental risks during the dry season.Additionally,the exposure risk of AFs via drinking water for sensitive populations deserves more attention.This study provides benchmark data on the occurrence of AFs in the lower reaches of the Yangtze River,and offers suggestions for better reduction of AFs.
基金This research is funded by the project“BeiDou/GNSS Multi-Sourced Data Fusion Theory and Digital Twinning Method for Real-Time and Condition Diagnosis of Large-Span Bridges”from the National Natural Science Foundation of China(No.42430711)supported by“the Fundamental Research Funds for the Central Universities”(No.2242025K20010).
文摘Accurate monitoring of bridge deformation under environmental and operational loads is critical for ensuring structural safety and serviceability.This paper presents an integrated displacement and attitude determination approach for bridge health monitoring,leveraging Global Navigation Satellite System(GNSS)technology to simultaneously capture displacement and attitude variations,such as pitch and heading angles.This method combines the GNSS observations at multiple antennas located on the bridge,utilizes a unit quaternion to express the attitude,and parameterizes the displacement,attitude,and carrier-phase ambiguities in one unifed measurement model.Then,the unscented Kalman flter is adapted to achieve the optimal estimation of the quaternion-based nonlinear systems.Finally,the double-diferenced ambiguities between the stations are resolved to integers to improve the accuracy of estimated displacement and attitude.The proposed method was evaluated using the data collected in the Forth Road Bridge,a long-span suspension bridge with a main span of 1.006 km and a total length exceeding 2.5 km.Using GNSS baselines ranging from 1.2 to 2.0 km,the method achieved horizontal and vertical displacement accuracies of 0.004-0.006 m and 0.008-0.010 m,respectively.For a 263 m baseline between the quarter-and mid-span points,pitch and heading accuracies reached 0.0013°and 0.0004°,respectively.Furthermore,the method is capable of determining the roll angle by utilizing monitoring stations located on the opposite side of the bridge.It reveals that this method can sensitively detect subtle attitude changes,ofering insights into bridge behaviour from a new perspective beyond displacement data.This work establishes the full cross-correlation between displacement and attitude parameters,which is benefcial for developing tightly coupled GNSS and inertial measurement unit in terms of both displacement and attitude parameters for structural health monitoring.The fndings underscore the potential of this approach in the establishment of the next-generation structure health monitoring systems,with a focus on robustness,reliability,and scalability for broader applications.
基金supported by the National Key Research and Development Program of China(Grant No.2016YFC0402503)the National Basic Research Program of China(“973” Project)(Grant No.2011CB403303)the National Natural Science Foundation of China(Grant Nos.51109064&51479071)
文摘This paper aims to explore the coupling mechanism between flow movement, sediment transport and riverbed evolution in currently widely used mathematical models for sediment transport. Based on characteristic theory, analytic forms of eigenvalues,eigenvectors and characteristic relationships of total-sediment transport model, bed-load transport model and suspenedload transport model were derived, respectively. The singular perturbation technology was implemented to obtain the asymptotic solutions to different families of eigenvalues. The results indicate that, interactions between motion variables were explicitly coupled in the characteristics of total-sediment transport model and bed-load transport model. Further qualitative and quantitative analysis demonstrates that high sediment transport intensity and significant riverbed change will inevitably affect the property of flow movement. In the process of deposition, sediment-laden flow will move faster when sediment transport intensity becomes stronger. In contrast, the wave of flow will propagate at slower speed as erosion intensity becomes stronger.For most existing suspended-load transport models, however, the characteristics are decoupled as the interactions between motion variables cannot be integrally illustrated in eigenvalues, eigenvectors and characteristic relationship.
基金supported by the National Key Research and Development Project(No.2020YFC1808200).
文摘Evaluating the health of river surface water is essential,as rivers support significant biological resources and serve as vital drinking water sources.While the Water Quality Index(WQI)is commonly employed to evaluate surface water quality,it fails to consider biodiversity and does not fully capture the ecological health of rivers.Here we show a comprehensive assessment of the ecological health of surface water in the lower Yangtze River(LYR),integrating chemical and biological metrics.According to traditional WQI metrics,the LYR's surface water generally meets China's Class II standards.However,it also contains 43 high-risk emerging contaminants;nitrobenzenes are found at the highest concentrations,representing 25e90%of total detections,while polycyclic aromatic hydrocarbons present the most substantial environmental risks,accounting for 81e93%of the total risk quotient.Notably,the plankton-based index of biological integrity(P-IBI)rates the ecological health of the majority of LYR water samples(59.7%)as‘fair’,with significantly better health observed in autumn compared to other seasons(p<0.01).Our findings suggest that including emerging contaminants and P-IBI as additional metrics can enhance the traditional WQI analysis in evaluating surface water's ecological health.These results highlight the need for a multidimensional assessment approach and call for improvements to LYR's ecological health,focusing on emerging contaminants and biodiversity rather than solely on reducing conventional indicators.
