Metasurfaces provide a potent platform for the dynamic manipulation of electromagnetic waves.Coupled with phase-change materials,they facilitate the creation of versatile metadevices,showcasing various tunable functio...Metasurfaces provide a potent platform for the dynamic manipulation of electromagnetic waves.Coupled with phase-change materials,they facilitate the creation of versatile metadevices,showcasing various tunable functions based on the transition between amorphous and crystalline states.However,the inherent limitation in tunable states imposes constraints on the multiplexing channels of metadevices.Here,this paper introduces a novel approach-a multi-functional metadevice achieved through the two-level control of the encoding phasechange metaatoms.Utilizing the phase-change material Ge_(2)Sb_(2)Se_(4)Te1(GSST)and high refractive-index liquid diiodomethane(CH_(2)I_(2)),this paper showcases precise control over electromagnetic wave manipulation.The GSST state governs the tunable function,switching it ON and OFF,while the presence of liquid in the hole dictates the deflection angle when the tunable function is active.Importantly,our tunable coding metasurface exhibits robust performance across a broad wavelength spectrum.The incorporation of high refractive-index liquid extends the regulatory dimension of the metadevice,enabling dynamic switching of encoding bit levels.This two-level tunable metadevice,rooted in phase-change materials,presents a promising avenue for the dynamic control of functions.展开更多
One of the most important reasons for the serious damage of embankment dams is their impermissible settlement.Therefore,it can be stated that the prediction of settlement of a dam is of paramount importance.This study...One of the most important reasons for the serious damage of embankment dams is their impermissible settlement.Therefore,it can be stated that the prediction of settlement of a dam is of paramount importance.This study aims to apply intelligent methods to predict settlement after constructing central core rockfill dams.Attempts were made in this research to prepare models for predicting settlement of these dams using the information of 35 different central core rockfill dams all over the world and Adaptive Neuro-Fuzzy Interface System(ANFIS) and Gene Expression Programming(GEP) methods.Parameters such as height of dam(H) and compressibility index(Ci) were considered as the input parameters.Finally,a form was designed using visual basic software for predicting dam settlement.With respect to the accuracy of the results obtained from the intelligent methods,they can be recommended for predicting settlement after constructing central core rockfill dams for the future plans.展开更多
The main purpose of current study is development of an intelligent model for estimation of shear wave velocity in limestone. Shear wave velocity is one of the most important rock dynamic parameters. Because rocks have...The main purpose of current study is development of an intelligent model for estimation of shear wave velocity in limestone. Shear wave velocity is one of the most important rock dynamic parameters. Because rocks have complicated structure, direct determination of this parameter takes time, spends expenditure and requires accuracy. On the other hand, there are no precise equations for indirect determination of it; most of them are empirical. By using data sets of several dams of Iran and neuro-genetic, adaptive neuro-fuzzy inference system （ANFIS）, and gene expression programming （GEP） methods, models are rendered for prediction of shear wave velocity in limestone. Totally, 516 sets of data has been used for modeling. From these data sets, 413 ones have been utilized for building the intelligent model, and 103 have been used for their performance evaluation. Compressional wave velocity （Vp）, density （7） and porosity （.n）, were considered as input parameters. Respectively, the amount of R for neuro-genetic and ANFIS networks was 0.959 and 0.963. In addition, by using GEP, three equations are obtained; the best of them has 0.958R. ANFIS shows the best prediction results, whereas GEP indicates proper equations. Because these equations have accuracy, they could be used for prediction of shear wave velocity for limestone in the future.展开更多
基金Supported by the Strategic Priority Research Program(B)of Chinese Academy of Sciences(XDB0580000,XDB43010200)National Natural Science Foundation of China(62222514,62350073,U2341226,61991440)+6 种基金National Key Research and Development Program of China(2023YFA1406900)Shanghai Science and Technology Committee(23ZR1482000,22JC1402900,22ZR1472700)Natural Science Foundation of Zhejiang Province(LR22F050004)Shanghai Municipal Science and Technology Major Project(2019SHZDZX01)Youth Innovation Promotion Association(Y2021070)and International Partnership Program(112GJHZ2022002FN)of Chinese Academy of SciencesShanghai Human Resources and Social Security Bureau(2022670)China Postdoctoral Science Foundation(2023T160661,2022TQ0353 and 2022M713261).
文摘Metasurfaces provide a potent platform for the dynamic manipulation of electromagnetic waves.Coupled with phase-change materials,they facilitate the creation of versatile metadevices,showcasing various tunable functions based on the transition between amorphous and crystalline states.However,the inherent limitation in tunable states imposes constraints on the multiplexing channels of metadevices.Here,this paper introduces a novel approach-a multi-functional metadevice achieved through the two-level control of the encoding phasechange metaatoms.Utilizing the phase-change material Ge_(2)Sb_(2)Se_(4)Te1(GSST)and high refractive-index liquid diiodomethane(CH_(2)I_(2)),this paper showcases precise control over electromagnetic wave manipulation.The GSST state governs the tunable function,switching it ON and OFF,while the presence of liquid in the hole dictates the deflection angle when the tunable function is active.Importantly,our tunable coding metasurface exhibits robust performance across a broad wavelength spectrum.The incorporation of high refractive-index liquid extends the regulatory dimension of the metadevice,enabling dynamic switching of encoding bit levels.This two-level tunable metadevice,rooted in phase-change materials,presents a promising avenue for the dynamic control of functions.
文摘One of the most important reasons for the serious damage of embankment dams is their impermissible settlement.Therefore,it can be stated that the prediction of settlement of a dam is of paramount importance.This study aims to apply intelligent methods to predict settlement after constructing central core rockfill dams.Attempts were made in this research to prepare models for predicting settlement of these dams using the information of 35 different central core rockfill dams all over the world and Adaptive Neuro-Fuzzy Interface System(ANFIS) and Gene Expression Programming(GEP) methods.Parameters such as height of dam(H) and compressibility index(Ci) were considered as the input parameters.Finally,a form was designed using visual basic software for predicting dam settlement.With respect to the accuracy of the results obtained from the intelligent methods,they can be recommended for predicting settlement after constructing central core rockfill dams for the future plans.
文摘The main purpose of current study is development of an intelligent model for estimation of shear wave velocity in limestone. Shear wave velocity is one of the most important rock dynamic parameters. Because rocks have complicated structure, direct determination of this parameter takes time, spends expenditure and requires accuracy. On the other hand, there are no precise equations for indirect determination of it; most of them are empirical. By using data sets of several dams of Iran and neuro-genetic, adaptive neuro-fuzzy inference system （ANFIS）, and gene expression programming （GEP） methods, models are rendered for prediction of shear wave velocity in limestone. Totally, 516 sets of data has been used for modeling. From these data sets, 413 ones have been utilized for building the intelligent model, and 103 have been used for their performance evaluation. Compressional wave velocity （Vp）, density （7） and porosity （.n）, were considered as input parameters. Respectively, the amount of R for neuro-genetic and ANFIS networks was 0.959 and 0.963. In addition, by using GEP, three equations are obtained; the best of them has 0.958R. ANFIS shows the best prediction results, whereas GEP indicates proper equations. Because these equations have accuracy, they could be used for prediction of shear wave velocity for limestone in the future.
