Existing sequential parameter estimation methods use the acoustic pressure of a line array as observations. The modal dispersion curves are employed to estimate the sound speed profile(SSP) and geoacoustic parameter...Existing sequential parameter estimation methods use the acoustic pressure of a line array as observations. The modal dispersion curves are employed to estimate the sound speed profile(SSP) and geoacoustic parameters based on the ensemble Kalman filter. The warping transform is implemented to the signals received by a single hydrophone to obtain the dispersion curves. The experimental data are collected at a range-independent shallow water site in the South China Sea. The results indicate that the SSPs are well estimated and the geoacoustic parameters are also well determined. Comparisons of the observed and estimated modal dispersion curves show good agreement.展开更多
This paper reports a new approach to estimate kinetic parameters for the thermal decomposition of the solid state from TG-DTG or DSC curve.Reduced equations are derived for the first tlme.The validity of these equatio...This paper reports a new approach to estimate kinetic parameters for the thermal decomposition of the solid state from TG-DTG or DSC curve.Reduced equations are derived for the first tlme.The validity of these equations was demonstrated employing data obtained from the dehydration process of calcium oxalate monohydrate.展开更多
For the plane curves Γ,the maximal operator associated to it is defined by Mf(x)=sup|∫f(x-Γ(t))(r^(-1)t)r^(-1)dt| where is a Schwartz function.For a certain class of curves in R^2,M is shown to bounded on (H(R^2)...For the plane curves Γ,the maximal operator associated to it is defined by Mf(x)=sup|∫f(x-Γ(t))(r^(-1)t)r^(-1)dt| where is a Schwartz function.For a certain class of curves in R^2,M is shown to bounded on (H(R^2),Weak L^1(R^2).This extends the theorem of Stein & Wainger and the theo- rem of Weinberg.展开更多
ABSTRACT This paper discusses the adoption of Artificial Intelligence-based techniques to estimate seismic damage,not with the goal of replacing existing approaches,but as a mean to improve the precision of empirical ...ABSTRACT This paper discusses the adoption of Artificial Intelligence-based techniques to estimate seismic damage,not with the goal of replacing existing approaches,but as a mean to improve the precision of empirical methods.For such,damage data collected in the aftermath of the 1998 Azores earthquake(Portugal)is used to develop a comparative analysis between damage grades obtained resorting to a classic damage formulation and an innovative approach based on Artificial Neural Networks(ANNs).The analysis is carried out on the basis of a vulnerability index computed with a hybrid seismic vulnerability asssment methodology,which is subsequently used as input to both approaches.The results obtained are then compared with real post-earthquake damage observation and critically discussed taking into account the level of adjustment achieved by each approach.Finally,a computer routine that uses the ANN as an approximation function is developed and applied to derive a new vulnerability curve expression.In general terms,the ANN developed in this study allowed to obtain much better approximations than those achieved with the original vulnerability approach,which has revealed to be quite non-conservative.Similarly,the proposed vulnerability curve expression was found to provide a more accurate damage prediction than the traditional analytical expressions.展开更多
基金Supported by the National Natural Science Foundation of China under Grant Nos 11434012,11774374,11404366 and41561144006
文摘Existing sequential parameter estimation methods use the acoustic pressure of a line array as observations. The modal dispersion curves are employed to estimate the sound speed profile(SSP) and geoacoustic parameters based on the ensemble Kalman filter. The warping transform is implemented to the signals received by a single hydrophone to obtain the dispersion curves. The experimental data are collected at a range-independent shallow water site in the South China Sea. The results indicate that the SSPs are well estimated and the geoacoustic parameters are also well determined. Comparisons of the observed and estimated modal dispersion curves show good agreement.
文摘This paper reports a new approach to estimate kinetic parameters for the thermal decomposition of the solid state from TG-DTG or DSC curve.Reduced equations are derived for the first tlme.The validity of these equations was demonstrated employing data obtained from the dehydration process of calcium oxalate monohydrate.
文摘For the plane curves Γ,the maximal operator associated to it is defined by Mf(x)=sup|∫f(x-Γ(t))(r^(-1)t)r^(-1)dt| where is a Schwartz function.For a certain class of curves in R^2,M is shown to bounded on (H(R^2),Weak L^1(R^2).This extends the theorem of Stein & Wainger and the theo- rem of Weinberg.
基金This work was funded by the Portuguese Foundation for Science and Technology(FCT)through the postdoctoral Grant SFRH/BPD/122598/2016The authors acknowledge to the Society of Promotion for Housing and Infrastructures Rehabilitation(SPRHI)the Regional Secretariat for Housing and Equipment(SRHE)of Faial for their support and contribution to the development of this work
文摘ABSTRACT This paper discusses the adoption of Artificial Intelligence-based techniques to estimate seismic damage,not with the goal of replacing existing approaches,but as a mean to improve the precision of empirical methods.For such,damage data collected in the aftermath of the 1998 Azores earthquake(Portugal)is used to develop a comparative analysis between damage grades obtained resorting to a classic damage formulation and an innovative approach based on Artificial Neural Networks(ANNs).The analysis is carried out on the basis of a vulnerability index computed with a hybrid seismic vulnerability asssment methodology,which is subsequently used as input to both approaches.The results obtained are then compared with real post-earthquake damage observation and critically discussed taking into account the level of adjustment achieved by each approach.Finally,a computer routine that uses the ANN as an approximation function is developed and applied to derive a new vulnerability curve expression.In general terms,the ANN developed in this study allowed to obtain much better approximations than those achieved with the original vulnerability approach,which has revealed to be quite non-conservative.Similarly,the proposed vulnerability curve expression was found to provide a more accurate damage prediction than the traditional analytical expressions.