Structural Health Monitoring(SHM)systems have become a crucial tool for the operational management of long tunnels.For immersed tunnels exposed to both traffic loads and the effects of the marine environment,efficient...Structural Health Monitoring(SHM)systems have become a crucial tool for the operational management of long tunnels.For immersed tunnels exposed to both traffic loads and the effects of the marine environment,efficiently identifying abnormal conditions from the extensive unannotated SHM data presents a significant challenge.This study proposed amodel-based approach for anomaly detection and conducted validation and comparative analysis of two distinct temporal predictive models using SHM data from a real immersed tunnel.Firstly,a dynamic predictive model-based anomaly detectionmethod is proposed,which utilizes a rolling time window for modeling to achieve dynamic prediction.Leveraging the assumption of temporal data similarity,an interval prediction value deviation was employed to determine the abnormality of the data.Subsequently,dynamic predictive models were constructed based on the Autoregressive Integrated Moving Average(ARIMA)and Long Short-Term Memory(LSTM)models.The hyperparameters of these models were optimized and selected using monitoring data from the immersed tunnel,yielding viable static and dynamic predictive models.Finally,the models were applied within the same segment of SHM data,to validate the effectiveness of the anomaly detection approach based on dynamic predictive modeling.A detailed comparative analysis discusses the discrepancies in temporal anomaly detection between the ARIMA-and LSTM-based models.The results demonstrated that the dynamic predictive modelbased anomaly detection approach was effective for dealing with unannotated SHM data.In a comparison between ARIMA and LSTM,it was found that ARIMA demonstrated higher modeling efficiency,rendering it suitable for short-term predictions.In contrast,the LSTM model exhibited greater capacity to capture long-term performance trends and enhanced early warning capabilities,thereby resulting in superior overall performance.展开更多
In general,acid aggregates are not used in combination with asphalt concrete because of their poor compatibility with the asphalt binder,which typically results in a scarce water stability of the concrete.In the prese...In general,acid aggregates are not used in combination with asphalt concrete because of their poor compatibility with the asphalt binder,which typically results in a scarce water stability of the concrete.In the present study,the feasibility of a new approach based on the combination of acid granite fine aggregate with alkaline limestone coarse aggregate and Portland cement filler has been assessed.The mineral and chemical compositions of these three materials have first been analyzed and compared.Then,the effect of different amounts of Portland cement(0%,25%,50%,75%and 100%of the total filler by weight)on the mechanical performance and water stability of the asphalt concrete has been considered.Asphalt concrete has been designed by using the Marshall method,and the mechanical performance indexes of this material,including the Marshall stability and indirect tensile strength(ITS),have been measured together with the related water stability indexes(namely the Marshall stability(RMS)and tensile strength ratio(TSR)).The results indicate that the alkaline limestone coarse aggregate and Portland cement filler can balance the drawback caused by the acid granite fine aggregate.The asphalt concrete has good mechanical performances and water stability when the amount of common limestone powder filler replaced by cement is not less than 75%.展开更多
Titanium dioxide(TiO_(2))was recently employed to apply onto road surfaces to degrade the harmful compounds from vehicle emissions.However,it remains a challenging task to find a highly compatible pavement type for Ti...Titanium dioxide(TiO_(2))was recently employed to apply onto road surfaces to degrade the harmful compounds from vehicle emissions.However,it remains a challenging task to find a highly compatible pavement type for TiO_(2)application to achieve durable and efficient air-purifying performance.This study proposed to coat TiO_(2)particles onto semi-flexible pavement surface and tried to investigate an optimum coating method.Three coating methods,including direct mixing TiO_(2)(MT)with asphalt mixture,spraying dry TiO_(2)(ST)coating and watersolution-based TiO_(2)(WT)coating on semi-flexible pavement surface.To achieve this objective,semi-flexible samples were prepared to evaluate and compare the performances of three coating methods by employing resistance to wearing,NO removal efficiency tests and residual texture depth tests.It was found that the ST method not only provided better NO degrading efficiency but also improved the resistance to wearing than the other two methods.展开更多
In the paper,the analytic static deflection solutions of uniform cantilever beams resting on nonlinear elastic rotational boundary are developed by the Modified Adomian Decomposition Method(MADM).If the applied force ...In the paper,the analytic static deflection solutions of uniform cantilever beams resting on nonlinear elastic rotational boundary are developed by the Modified Adomian Decomposition Method(MADM).If the applied force function is an analytic function,then the deflection function can be derived and expressed in Maclaurin series.A recurrence relation for the coefficients of the Maclaurin series is derived.It is shown that the proposed solution method is accurate and efficient.The solution method can be successfully applied to the uniform cantilever beam and non-linear elastic rotational boundary problem.展开更多
Signal reconstruction is a significantly important theoretical issue for compressed sensing.Considering the situation of signal reconstruction with unknown sparsity,the conventional signal reconstruction algorithms us...Signal reconstruction is a significantly important theoretical issue for compressed sensing.Considering the situation of signal reconstruction with unknown sparsity,the conventional signal reconstruction algorithms usually perform low accuracy.In this work,a sparsity adaptive signal reconstruction algorithm using sensing dictionary is proposed to achieve a lower reconstruction error.The sparsity estimation method is combined with the construction of the support set based on sensing dictionary.Using the adaptive sparsity method,an iterative signal reconstruction algorithm is proposed.The sufficient conditions for the exact signal reconstruction of the algorithm also is proved by theory.According to a series of simulations,the results show that the proposed method has higher precision compared with other state-of-the-art signal reconstruction algorithms especially in a high compression ratio scenarios.展开更多
In current work,Ni-Ti-CeO_(2) nanocomposite coatings were achieved by co-adding Ti microparticles and CeO_(2) nanoparticles.Designed experiments and COMSOL computer simulation were applied to reveal the synergistic ro...In current work,Ni-Ti-CeO_(2) nanocomposite coatings were achieved by co-adding Ti microparticles and CeO_(2) nanoparticles.Designed experiments and COMSOL computer simulation were applied to reveal the synergistic role of Ti microparticles and CeO_(2) nanoparticles in tailoring the spatial microstructures and properties of Ni-Ti-CeO_(2) nanocomposite coating.Unilaterally,the conductive Ti microparticles conducted the growth behavior of Ni grains by current density concentration,distorting electronic feld lines and heterogeneous nucleation.Individual domains consisting of inner nanograins and outer radial columnar grains surrounded Ti microparticles,where Ti microparticles acted as seeds.Ti microparticles tended to be aggregated,leading to spatial heterogeneity of microstructures.Ni deposits buried the Ti microparticles in forms of“covering model”,contributing to the formation of inside voids and rough surface and aggregation of Ti microparticles;on the other hand,the non-conductive CeO_(2)microparticles hardly changed the distribution of current density and electronic feld lines on the cathode surface.Ni deposits buried the CeO_(2)microparticle in forms of“stacking model”,avoiding the inside voids and aggregation of particles.The incorporation of CeO_(2)microparticle brought in microstructure evolutions only on its top side without disturbing the growth behavior of Ni grains on its lateral side or bottom,suggesting the limited effects.This was correlated with the presence of current concentration above the CeO_(2) microparticle at the last stage of burying CeO_(2) microparticle.The co-addition of Ti microparticles and CeO_(2) nanoparticles into Ni deposits exploited the complementary action of the two particles,which gave birth to satisfed spatial microstructures and improved hardness.Ti microparticles took major responsibility for microstructure evolutions,while the CeO_(2) nanoparticles were mainly in charge of the microstructure homogeneity.展开更多
基金supported by the Research and Development Center of Transport Industry of New Generation of Artificial Intelligence Technology(Grant No.202202H)the National Key R&D Program of China(Grant No.2019YFB1600702)the National Natural Science Foundation of China(Grant Nos.51978600&51808336).
文摘Structural Health Monitoring(SHM)systems have become a crucial tool for the operational management of long tunnels.For immersed tunnels exposed to both traffic loads and the effects of the marine environment,efficiently identifying abnormal conditions from the extensive unannotated SHM data presents a significant challenge.This study proposed amodel-based approach for anomaly detection and conducted validation and comparative analysis of two distinct temporal predictive models using SHM data from a real immersed tunnel.Firstly,a dynamic predictive model-based anomaly detectionmethod is proposed,which utilizes a rolling time window for modeling to achieve dynamic prediction.Leveraging the assumption of temporal data similarity,an interval prediction value deviation was employed to determine the abnormality of the data.Subsequently,dynamic predictive models were constructed based on the Autoregressive Integrated Moving Average(ARIMA)and Long Short-Term Memory(LSTM)models.The hyperparameters of these models were optimized and selected using monitoring data from the immersed tunnel,yielding viable static and dynamic predictive models.Finally,the models were applied within the same segment of SHM data,to validate the effectiveness of the anomaly detection approach based on dynamic predictive modeling.A detailed comparative analysis discusses the discrepancies in temporal anomaly detection between the ARIMA-and LSTM-based models.The results demonstrated that the dynamic predictive modelbased anomaly detection approach was effective for dealing with unannotated SHM data.In a comparison between ARIMA and LSTM,it was found that ARIMA demonstrated higher modeling efficiency,rendering it suitable for short-term predictions.In contrast,the LSTM model exhibited greater capacity to capture long-term performance trends and enhanced early warning capabilities,thereby resulting in superior overall performance.
基金supported by the Science and Technology Planning Project of Zhejiang Provincial Department of Transportation(2021012)Zhejiang Provincial Natural Science Foundation of China under Grant(No.LGG21E080002).
文摘In general,acid aggregates are not used in combination with asphalt concrete because of their poor compatibility with the asphalt binder,which typically results in a scarce water stability of the concrete.In the present study,the feasibility of a new approach based on the combination of acid granite fine aggregate with alkaline limestone coarse aggregate and Portland cement filler has been assessed.The mineral and chemical compositions of these three materials have first been analyzed and compared.Then,the effect of different amounts of Portland cement(0%,25%,50%,75%and 100%of the total filler by weight)on the mechanical performance and water stability of the asphalt concrete has been considered.Asphalt concrete has been designed by using the Marshall method,and the mechanical performance indexes of this material,including the Marshall stability and indirect tensile strength(ITS),have been measured together with the related water stability indexes(namely the Marshall stability(RMS)and tensile strength ratio(TSR)).The results indicate that the alkaline limestone coarse aggregate and Portland cement filler can balance the drawback caused by the acid granite fine aggregate.The asphalt concrete has good mechanical performances and water stability when the amount of common limestone powder filler replaced by cement is not less than 75%.
基金The authors would like to acknowledge the Science Technology Department of Zhejiang Province(Grant Nos.2018F10045 and 2021C01106)for the funding support and the technical guidance in 3D laser scanning by Dr.Fengxia Chi from the Institute of Road Engineering of Zhejiang Scientific Research Institute of TransportThe constant of this paper reflects the views of authors,who are responsible for the facts and the accuracy of the data shown herein.The authors gratefully acknowledge their financial and technical supporting.
文摘Titanium dioxide(TiO_(2))was recently employed to apply onto road surfaces to degrade the harmful compounds from vehicle emissions.However,it remains a challenging task to find a highly compatible pavement type for TiO_(2)application to achieve durable and efficient air-purifying performance.This study proposed to coat TiO_(2)particles onto semi-flexible pavement surface and tried to investigate an optimum coating method.Three coating methods,including direct mixing TiO_(2)(MT)with asphalt mixture,spraying dry TiO_(2)(ST)coating and watersolution-based TiO_(2)(WT)coating on semi-flexible pavement surface.To achieve this objective,semi-flexible samples were prepared to evaluate and compare the performances of three coating methods by employing resistance to wearing,NO removal efficiency tests and residual texture depth tests.It was found that the ST method not only provided better NO degrading efficiency but also improved the resistance to wearing than the other two methods.
文摘In the paper,the analytic static deflection solutions of uniform cantilever beams resting on nonlinear elastic rotational boundary are developed by the Modified Adomian Decomposition Method(MADM).If the applied force function is an analytic function,then the deflection function can be derived and expressed in Maclaurin series.A recurrence relation for the coefficients of the Maclaurin series is derived.It is shown that the proposed solution method is accurate and efficient.The solution method can be successfully applied to the uniform cantilever beam and non-linear elastic rotational boundary problem.
基金supported by the National Natural Science Foundation of China(61773202,71874081)the Special Financial Grant from China Postdoctoral Science Foundation(2017T100366)+2 种基金the Key Laboratory of Avionics System Integrated Technology for National Defense Science and Technology,China Institute of Avionics Radio Electronics(6142505180407)the Open Fund of CAAC Key laboratory of General Aviation Operation,Civil Aviation Management Institute of China(CAMICKFJJ-2019-04)the Innovation Project of the Civil Aviation Administration of China(EAB19001)。
文摘Signal reconstruction is a significantly important theoretical issue for compressed sensing.Considering the situation of signal reconstruction with unknown sparsity,the conventional signal reconstruction algorithms usually perform low accuracy.In this work,a sparsity adaptive signal reconstruction algorithm using sensing dictionary is proposed to achieve a lower reconstruction error.The sparsity estimation method is combined with the construction of the support set based on sensing dictionary.Using the adaptive sparsity method,an iterative signal reconstruction algorithm is proposed.The sufficient conditions for the exact signal reconstruction of the algorithm also is proved by theory.According to a series of simulations,the results show that the proposed method has higher precision compared with other state-of-the-art signal reconstruction algorithms especially in a high compression ratio scenarios.
文摘In current work,Ni-Ti-CeO_(2) nanocomposite coatings were achieved by co-adding Ti microparticles and CeO_(2) nanoparticles.Designed experiments and COMSOL computer simulation were applied to reveal the synergistic role of Ti microparticles and CeO_(2) nanoparticles in tailoring the spatial microstructures and properties of Ni-Ti-CeO_(2) nanocomposite coating.Unilaterally,the conductive Ti microparticles conducted the growth behavior of Ni grains by current density concentration,distorting electronic feld lines and heterogeneous nucleation.Individual domains consisting of inner nanograins and outer radial columnar grains surrounded Ti microparticles,where Ti microparticles acted as seeds.Ti microparticles tended to be aggregated,leading to spatial heterogeneity of microstructures.Ni deposits buried the Ti microparticles in forms of“covering model”,contributing to the formation of inside voids and rough surface and aggregation of Ti microparticles;on the other hand,the non-conductive CeO_(2)microparticles hardly changed the distribution of current density and electronic feld lines on the cathode surface.Ni deposits buried the CeO_(2)microparticle in forms of“stacking model”,avoiding the inside voids and aggregation of particles.The incorporation of CeO_(2)microparticle brought in microstructure evolutions only on its top side without disturbing the growth behavior of Ni grains on its lateral side or bottom,suggesting the limited effects.This was correlated with the presence of current concentration above the CeO_(2) microparticle at the last stage of burying CeO_(2) microparticle.The co-addition of Ti microparticles and CeO_(2) nanoparticles into Ni deposits exploited the complementary action of the two particles,which gave birth to satisfed spatial microstructures and improved hardness.Ti microparticles took major responsibility for microstructure evolutions,while the CeO_(2) nanoparticles were mainly in charge of the microstructure homogeneity.
