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 the present study,high-quality apatite-type La_(9.33)Ge_6O_(26) powders are successfully synthesized by a facile moltensalt synthesis method(MSSM) at low temperatures,using Li Cl,Li Cl/Na Cl mixture(mass ratio 1:1)...In the present study,high-quality apatite-type La_(9.33)Ge_6O_(26) powders are successfully synthesized by a facile moltensalt synthesis method(MSSM) at low temperatures,using Li Cl,Li Cl/Na Cl mixture(mass ratio 1:1) as molten salt,respectively.Experimental results indicate that the optimal mass ratio between reactant and molten salt is 1:2,and Li Cl/Na Cl mixed molten-salt is more beneficial for forming high-quality La_(9.33)Ge_6O_(26) powders than Li Cl individual molten-salt.Comparing with the conventional solid-state reaction method(SSRM),the synthesis temperature of apatitetype La_(9.33)Ge_6O_(26) powders using the MSSM decreases more than 350?C,which can effectively avoid Ge loss in the preparation process of precursor powders.Furthermore,the powders obtained by the MSSM are homogeneous,nonagglomerated and well crystallized,which are very favorable for gaining dense pellets in the premise of avoiding Ge loss.On the basis of high-quality precursor powders,the dense and pure ceramic pellets of La_(9.33)Ge_6O_(26) are gained at a low temperature of 1100?C for 2 h,which exhibit higher conductivities(σ850?C(Li Cl)= 2.3 × 10^(-2) S·cm^(-1),σ850 ?C(Li Cl/Na Cl) = 4.9 × 10^(-2) S·cm^(-1)) and lower activation energies(Ea(Li Cl)= 1.02 e V,Ea(Li Cl/Na Cl)= 0.99 e V) than that synthesized by the SSRM.展开更多
Using high-resolution angle-resolved and time-resolved photoemission spectroscopy,we have studied the low-energy band structures in occupied and unoccupied states of three ternary compounds GeBi_(2)Te_(4),SnBi_(2)Te_(...Using high-resolution angle-resolved and time-resolved photoemission spectroscopy,we have studied the low-energy band structures in occupied and unoccupied states of three ternary compounds GeBi_(2)Te_(4),SnBi_(2)Te_(4) and Sn_(0.571)Bi_(2.286)Se_(4) near the Fermi level.In previously confirmed topological insulator GeBi_(2)Te_(4) compounds,we confirmed the existence of the Dirac surface state and found that the bulk energy gap is much larger than that in the first-principles calculations.In SnBi_(2)Te_(4) compounds,the Dirac surface state was observed,consistent with the first-principles calculations,indicating that it is a topological insulator.The experimental detected bulk gap is a little bit larger than that in calculations.In Sn_(0.571)Bi_(2.286)Se_(4) compounds,our measurements suggest that this nonstoichiometric compound is a topological insulator although the stoichiometric SnBi_(2)Se_(4) compound was proposed to be topological trivial.展开更多
We report the superconductivity of a new quaternary compound ThMo_(2)Si_(2)C, synthesized with the arc-melting technique. The compound crystallizes in a tetragonal CeCr_(2)Si_(2)C-type structure with cell parameters o...We report the superconductivity of a new quaternary compound ThMo_(2)Si_(2)C, synthesized with the arc-melting technique. The compound crystallizes in a tetragonal CeCr_(2)Si_(2)C-type structure with cell parameters of a = 4.2296A and c = 5.3571 A. An interlayer Si–Si covalent bonding is suggested by the atomic distance. The electrical resistivity and magnetic susceptibility measurements indicate a Pauli-paramagnetic metal with dominant electron-electron scattering in the normal-state. Bulk superconductivity at 2.2 K is demonstrated with a dimensionless specific-heat jump of △C/γnT = 0.98. The superconducting parameters of the critical magnetic fields, coherence length, penetration depth, and superconducting energy gap are given.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Project supported by the Natural Science Foundation of Shandong Province,China(Grant Nos.ZR2016FB16,ZR2015AQ010,and ZR2016AQ08)the Shandong University of Technology at Zibo and Zibo City Integration Development Project,China(Grant No.2016ZBXC205)
文摘In the present study,high-quality apatite-type La_(9.33)Ge_6O_(26) powders are successfully synthesized by a facile moltensalt synthesis method(MSSM) at low temperatures,using Li Cl,Li Cl/Na Cl mixture(mass ratio 1:1) as molten salt,respectively.Experimental results indicate that the optimal mass ratio between reactant and molten salt is 1:2,and Li Cl/Na Cl mixed molten-salt is more beneficial for forming high-quality La_(9.33)Ge_6O_(26) powders than Li Cl individual molten-salt.Comparing with the conventional solid-state reaction method(SSRM),the synthesis temperature of apatitetype La_(9.33)Ge_6O_(26) powders using the MSSM decreases more than 350?C,which can effectively avoid Ge loss in the preparation process of precursor powders.Furthermore,the powders obtained by the MSSM are homogeneous,nonagglomerated and well crystallized,which are very favorable for gaining dense pellets in the premise of avoiding Ge loss.On the basis of high-quality precursor powders,the dense and pure ceramic pellets of La_(9.33)Ge_6O_(26) are gained at a low temperature of 1100?C for 2 h,which exhibit higher conductivities(σ850?C(Li Cl)= 2.3 × 10^(-2) S·cm^(-1),σ850 ?C(Li Cl/Na Cl) = 4.9 × 10^(-2) S·cm^(-1)) and lower activation energies(Ea(Li Cl)= 1.02 e V,Ea(Li Cl/Na Cl)= 0.99 e V) than that synthesized by the SSRM.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11521404,12074248,11974243,and 11804194)additional support from a Shanghai talent program。
文摘Using high-resolution angle-resolved and time-resolved photoemission spectroscopy,we have studied the low-energy band structures in occupied and unoccupied states of three ternary compounds GeBi_(2)Te_(4),SnBi_(2)Te_(4) and Sn_(0.571)Bi_(2.286)Se_(4) near the Fermi level.In previously confirmed topological insulator GeBi_(2)Te_(4) compounds,we confirmed the existence of the Dirac surface state and found that the bulk energy gap is much larger than that in the first-principles calculations.In SnBi_(2)Te_(4) compounds,the Dirac surface state was observed,consistent with the first-principles calculations,indicating that it is a topological insulator.The experimental detected bulk gap is a little bit larger than that in calculations.In Sn_(0.571)Bi_(2.286)Se_(4) compounds,our measurements suggest that this nonstoichiometric compound is a topological insulator although the stoichiometric SnBi_(2)Se_(4) compound was proposed to be topological trivial.
基金supported by the National Key Research and Development Program of China (Grant No. 2017YFA0303002)the Natural Science Foundation of Shandong Province (Grant Nos. ZR2019MA036, and ZR2016AQ08)。
文摘We report the superconductivity of a new quaternary compound ThMo_(2)Si_(2)C, synthesized with the arc-melting technique. The compound crystallizes in a tetragonal CeCr_(2)Si_(2)C-type structure with cell parameters of a = 4.2296A and c = 5.3571 A. An interlayer Si–Si covalent bonding is suggested by the atomic distance. The electrical resistivity and magnetic susceptibility measurements indicate a Pauli-paramagnetic metal with dominant electron-electron scattering in the normal-state. Bulk superconductivity at 2.2 K is demonstrated with a dimensionless specific-heat jump of △C/γnT = 0.98. The superconducting parameters of the critical magnetic fields, coherence length, penetration depth, and superconducting energy gap are given.
