The duplicate form of the generalized Gould-Hsu inversions has been obtained by Shi and Zhang. In this paper, we present a simple proof of this duplicate form. With the same method, we construct the duplicate form of ...The duplicate form of the generalized Gould-Hsu inversions has been obtained by Shi and Zhang. In this paper, we present a simple proof of this duplicate form. With the same method, we construct the duplicate form of the generalized Carlitz inversions. Using this duplicate form, we obtain several terminating basic hypergeometric identities and some limiting cases.展开更多
The presence of temperature inversions (TI), concentration of air pollutants (AP) and meteorological variables (MV) affect the welfare of the population, creating public health problems (acute respiratory diseases ARD...The presence of temperature inversions (TI), concentration of air pollutants (AP) and meteorological variables (MV) affect the welfare of the population, creating public health problems (acute respiratory diseases ARDs, among others). The Guadalajara Metropolitan Zone (GMZ) experiences high levels of air pollution, which associated with the presence of temperature inversions and meteorological variations is conducive to the incidence of ARDs in children. The aim of this work is to evaluate the TI, MV, AP and their influence on the ARDs in children under five years in the GMZ from 2003 to 2007. In this period, the moderate and strong TI are the most frequent presenting from November to May. The AP shows a variable behavior during the year and between years, with the highest concentration of particles less than 10 microns (PM10), followed by ozone (O3), nitrogen dioxide (NO2), nitrogen oxides (NOX), carbon monoxide (CO) and sulfur dioxide (SO2), the most affected areas are the southeast of the GMZ. Annual arithmetic mean is 213,510 ± 41,209 ARDs consultations. The most important diseases are acute respiratory infections (98.0%), followed by pneumonia and bronchopneumonia (1.1%), asthma and status asthmaticus (0.5%) and streptococcal pharyngitis and tonsillitis (0.4%). Months with most inquiries were from October to March, mainly in the southeast, south and center of the city, coinciding with high levels of AP. Statistical analysis shows that the TI have significant correlation with ARDs in three years, temperature (Temp) in two, relative humidity (RH) in two, wind speed (WS) in three, wind direction (WD) in two, while that air pollutants NOX and NO2 showed significant correlation with ARDs throughout the period. CO and SO2 showed significance in two years, while the PM10 and O3 in one.展开更多
Knowledge of the statistical characteristics of inversions and their effects on aerosols under different large-scale synoptic circulations is important for studying and modeling the diffusion of pollutants in the boun...Knowledge of the statistical characteristics of inversions and their effects on aerosols under different large-scale synoptic circulations is important for studying and modeling the diffusion of pollutants in the boundary layer. Based on results gen- erated using the self-organizing map （SOM） weather classification method, this study compares the statistical characteristics of surface-based inversions （SBIs） and elevated inversions （EIs）, and quantitatively evaluates the effect of SBIs on aerosol condensation nuclei （CN） concentrations and the relationship between temperature gradients and aerosols for six prevailing synoptic patterns over the the Southern Great Plains （SGP） site during 2001-10. Large-scale synoptic patterns strongly influ- ence the statistical characteristics of inversions and the accumulation of aerosols in the low-level atmosphere. The activity, frequency, intensity, and vertical distribution of inversions are significantly different among these synoptic patterns. The verti- cal distribution of inversions varies diurnally and is significantly different among the different synoptic patterns. Anticyclonic patterns affect the accumulation of aerosols near the ground more strongly than cyclonic patterns. Mean aerosol CN con- centrations increase during SBIs compared to no inversion cases by 16.1%, 22.6%, 24.5%, 58.7%, 29.8% and 23.7% for the six synoptic patterns. This study confirms that there is a positive correlation between temperature gradients and aerosol CN concentrations near the ground at night under similar large-scale synoptic patterns. The relationship is different for different synoptic patterns and can be described by linear functions. These findings suggest that large-scale synoptic patterns change the static stability of the atmosphere and inversions in the lower atmosphere, thereby influencing the diffusion of aerosols near the ground.展开更多
Traditional 3D Magnetotelluric(MT) forward modeling and inversions are mostly based on structured meshes that have limited accuracy when modeling undulating surfaces and arbitrary structures. By contrast, unstructured...Traditional 3D Magnetotelluric(MT) forward modeling and inversions are mostly based on structured meshes that have limited accuracy when modeling undulating surfaces and arbitrary structures. By contrast, unstructured-grid-based methods can model complex underground structures with high accuracy and overcome the defects of traditional methods, such as the high computational cost for improving model accuracy and the difficulty of inverting with topography. In this paper, we used the limited-memory quasi-Newton(L-BFGS) method with an unstructured finite-element grid to perform 3D MT inversions. This method avoids explicitly calculating Hessian matrices, which greatly reduces the memory requirements. After the first iteration, the approximate inverse Hessian matrix well approximates the true one, and the Newton step(set to 1) can meet the sufficient descent condition. Only one calculation of the objective function and its gradient are needed for each iteration, which greatly improves its computational efficiency. This approach is well-suited for large-scale 3D MT inversions. We have tested our algorithm on data with and without topography, and the results matched the real models well. We can recommend performing inversions based on an unstructured finite-element method and the L-BFGS method for situations with topography and complex underground structures.展开更多
We conducted rapid inversions of rupture process for the 2023 earthquake doublet occurred in SE Türkiye,the first with a magnitude of M_(W)7.8 and the second with a magnitude of M_(W)7.6,using teleseismic and str...We conducted rapid inversions of rupture process for the 2023 earthquake doublet occurred in SE Türkiye,the first with a magnitude of M_(W)7.8 and the second with a magnitude of M_(W)7.6,using teleseismic and strong-motion data.The teleseismic rupture models of the both events were obtained approximately 88 and 55 minutes after their occurrences,respectively.The rupture models indicated that the first event was an asymmetric bilateral event with ruptures mainly propagating to the northeast,while the second one was a unilateral event with ruptures propagating to the west.This information could be useful in locating the meizoseismal areas.Compared with teleseismic models,the strong-motion models showed relatively higher resolution.A noticeable difference was found for the M_(W)7.6 earthquake,for which the strong-motion models shows a bilateral event,rather than a unilateral event,but the dominant rupture direction is still westward.Nevertheless,all strong-motion models are consistent with the teleseismic models in terms of magnitudes,durations,and dominant rupture directions.This suggests that both teleseismic and strong-motion data can be used for fast determination of major source characteristics.In contrast,the strong-motion data would be preferable in future emergency responses since they are recorded earlier and have a better resolution ability on the source ruptures.展开更多
High-quality and continuous radiosonde, aerosol and surface meteorology datasets are used to investigate the statistical characteristics of meteorological parameters and their effects on aerosols. The data were collec...High-quality and continuous radiosonde, aerosol and surface meteorology datasets are used to investigate the statistical characteristics of meteorological parameters and their effects on aerosols. The data were collected at the Atmospheric Radiation Measurement Southern Great Plains climate research facility during 2000–15. The parameters and vertical distribution of temperature inversion layers were found to have strong diurnal and seasonal changes. For surface-based temperature inversion (SBI), the mean frequency and depth of temperature inversion layers were 39.4% and 198 m, respectively. The temperature difference between the top and bottom of SBI was 4.8℃, and so the temperature gradient was 2.4℃(100 m)^-1. The detailed vertical distributions of temperature inversion had been determined, and only the temperature inversion layers below 1000 m showed diurnal and seasonal variations. Mean surface aerosol number concentrations increased by 43.0%, 21.9% and 49.2% when SBIs were present at 0530, 1730 and 2330 LST, respectively. The effect of SBI on surface aerosol concentration was weakest in summer (18.1%) and strongest in winter (58.4%). During elevated temperature inversion events, there was no noticeable difference in surface aerosol number concentrations. Temperature differences and temperature gradients across SBIs correlated fairly well with aerosol number concentrations, especially for temperature gradients. The vertical distribution of aerosol optical properties with and without temperature inversions was different. Surface aerosol measurements were representative of the air within (below), but not above, SBIs and EIs. These results provide a basis for developing a boundary layer aerosol accumulation model and for improving radiative transfer models in the lower atmosphere.展开更多
It is now common practice to perform simultaneous traveltime inversion for the velocity field and the reflector geometry in reflection/refraction tomography, or the velocity field and the hypocenter locations in regio...It is now common practice to perform simultaneous traveltime inversion for the velocity field and the reflector geometry in reflection/refraction tomography, or the velocity field and the hypocenter locations in regional earthquake tomography, but seldom are all three classes of model parameters updated simultaneously. This is mainly due to the trade-off between the different types of model parameters and the lack of different seismic phases to constrain the model parameters. Using a spherical-coordinate ray tracing algorithm for first and later（primary reflected） arrival tracing algorithm in combination with a popular linearized inversion solver, it is possible to simultaneously recover the three classes of model parameters in regional or global tomographic studies. In this paper we incorporate the multistage irregular shortest-path ray tracing algorithm（in a spherical coordinate system） with a subspace inversion solver to formulate a simultaneous inversion algorithm for triple model parameters updating using direct and later arrival time information.Comparison tests for two sets of data（noise free and added noise） indicate that the new triple-class parameter inversion algorithm is capable of obtaining nearly the same results as the double-class parameter inversion scheme. Furthermore,the proposed multi-parameter type inversion method is not sensitive to a modest level of picking error in the traveltime data, and also performs well with a relatively large uncertainty in earthquake hypocentral locations. This shows it to be a feasible and promising approach in regional or global tomographic applications.展开更多
In the paper, a 2D symmetrical anisotropic medium whose strike agrees with one of the horizontal principal axes is considered to develop a corresponding inversion technique. In the specified conditions, if we assume a...In the paper, a 2D symmetrical anisotropic medium whose strike agrees with one of the horizontal principal axes is considered to develop a corresponding inversion technique. In the specified conditions, if we assume an equivalent conductivity anisotropy in both the vertical and dipping directions, i.e., σzz=σyy, the differential equations obtained are formally the same as that for TE and TM modes in the 2D isotropic geoelectrical media. The same inversion technique as that in the 2D isotropic media can be employed to obtain the anisotropic conductivities. It means that the TE and TM inversion results in the isotropic media can be respectively thought as the resistivities in the two principal directions of the symmetrically anisotropic media, which has offered a new approach and a theoretical guidance for interpreting magnetotelluric data. And the inversion technique developed here is used to test the magnetotelluric data in the area of Tianzhu and Yongdeng in Gansu Province, so that the crust anisotropic geoelectrical structures in this region can be obtained.展开更多
Variations in incoming shortwave radiation influence the net surface heat flux,contributing to the formation of a temperature inversion.The effects of shortwave radiation on the temperature inversions in the Bay of Be...Variations in incoming shortwave radiation influence the net surface heat flux,contributing to the formation of a temperature inversion.The effects of shortwave radiation on the temperature inversions in the Bay of Bengal and eastern equatorial Indian Ocean have never been investigated.Thus,a high-resolution(horizontal resolution of 0.07°×0.07° with 50 vertical layers) Regional Ocean Modeling System(ROMS) model is utilized to quantify the contributions of shortwave radiation to the temperature inversions in the study domain.Analyses of the mixed layer heat and salt budgets are performed,and different model simulations are compared.The model results suggest that a 30% change in shortwave radiation can change approximately 3% of the temperature inversion area in the Bay of Bengal.Low shortwave radiation reduces the net surface heat flux and cools the mixed layer substantially;it also reduces the evaporation rate,causing less evaporative water vapor losses from the ocean than the typical situation,and ultimately enhances haline stratification.Thus,the rudimentary outcome of this research is that a decrease in shortwave radiation produces more temperature inversion in the study region,which is primarily driven by the net surface cooling and supported by the intensive haline stratification.Moreover,low shortwave radiation eventually intensifies the temperature inversion layer by thickening the barrier layer.This study could be an important reference for predicting how the Indian Ocean climate will respond to future changes in shortwave radiation.展开更多
The Bayesian inversion method is a stochastic approach based on the Bayesian theory.With the development of sampling algorithms and computer technologies,the Bayesian inversion method has been widely used in geophysic...The Bayesian inversion method is a stochastic approach based on the Bayesian theory.With the development of sampling algorithms and computer technologies,the Bayesian inversion method has been widely used in geophysical inversion problems.In this study,we conduct inversion experiments using crosshole seismic travel-time data to examine the characteristics and performance of the stochastic Bayesian inversion based on the Markov chain Monte Carlo sampling scheme and the traditional deterministic inversion with Tikhonov regularization.Velocity structures with two different spatial variations are considered,one with a chessboard pattern and the other with an interface mimicking the Mohorovicicdiscontinuity(Moho).Inversions are carried out with different scenarios of model discretization and source–receiver configurations.Results show that the Bayesian method yields more robust single-model estimations than the deterministic method,with smaller model errors.In addition,the Bayesian method provides the posterior probabilistic distribution function of the model space,which can help us evaluate the quality of the inversion result.展开更多
HF (high frequency) radar sounder technology has been developed for several missions of Mars surface/subsurface exploration. This paper presents a model of rough surface and stratified sub-surfaces to describe the mul...HF (high frequency) radar sounder technology has been developed for several missions of Mars surface/subsurface exploration. This paper presents a model of rough surface and stratified sub-surfaces to describe the multi-layer structure of Mars polar deposits. Based on numerical simulation of radar echoes from rough surface/stratified interfaces, an inversion approach is developed to obtain the parameters of Polar Layered Deposits, i.e. layers thickness and dielectric constants. As a validation example, the SHARAD radar sounder data of the Promethei Lingula of Mars South Polar region is adopted for parameters inversion. The result of stratification is also analyzed and compared with the optical photo of the deep cliff of Chasma Australe canyon. Dielectric inversions show that the deposit media are not uniform, and the dielectric constants of the Promethei Lingula surfaces are large, and become reduced around the depth of 20 m - 30 m, below where most of the deposits are nearly pure ice, except a few thin layers with a lot of dust.展开更多
As is well known, Greece has a significant number of earthquakes each year. Ιn recent years, several earthquakes have occurred in Greece. For this scope, a methodology was used to determine the source parameters. Thi...As is well known, Greece has a significant number of earthquakes each year. Ιn recent years, several earthquakes have occurred in Greece. For this scope, a methodology was used to determine the source parameters. This methodology is based on minimizing the difference between the observed and the synthetic waveforms, using the method Source Parameters Calculation—SPCa <a href="#ref1" target="_blank">[1]</a>. The source parameters, using the proposed methodology, are calculated by comparing observed seismograms and synthetic by inverting data. The synthetics are calculated using the reflectivity method (Kennett, 1983) as implemented by Randall et al. (1994) for a given earth structure. This study includes inversion results for the strongest events that occurred in Greece from 2008 to 2014. For the same events calculated the main fault plane, using the method of Hypocenter Centroid-plot (HC-plot) <a href="#ref2" target="_blank">[2]</a> <a href="#ref3" target="_blank">[3]</a>. This methodology is a simple geometrical method based on the combination between the hypocentral position and the two possible fault planes.展开更多
Four exotic chiral organocatalysts, 9-amino-（9-deoxy） cinchona alkaloids with （8S, 9R） and （8R, 9S）- configurations, were conveniently synthesized for the first time in 27-72% total yields through two conversion...Four exotic chiral organocatalysts, 9-amino-（9-deoxy） cinchona alkaloids with （8S, 9R） and （8R, 9S）- configurations, were conveniently synthesized for the first time in 27-72% total yields through two conversions of configuration at the 9-stereogenic centers of commercially available cinchona alkaloids.展开更多
We shall give natural generalized solutions of Hadamard and tensor products equations for matrices by the concept of the Tikhonov regularization combined with the theory of reproducing kernels.
In order to obtain large broadband, a novel travelling-wave modulator with nonperiodic domain inversions and ridge structure is proposed. The composite structure is designed to achieve velocity matching between the op...In order to obtain large broadband, a novel travelling-wave modulator with nonperiodic domain inversions and ridge structure is proposed. The composite structure is designed to achieve velocity matching between the optical wave and the microwave, to get a 50 characteristic impedance and to reduce the loss of the microwave electrodes with finite element method (FEM). The calculation results show that the frequency response of the new device is flat up to 350 GHz with interaction length of 1 cm, characteristic impedance of 49 , and microwave refractive index of 2.5.展开更多
Accurate assessment of snowpack volumetric liquid water content and bulk density is essential for understanding snow hydrology,avalanche risk management,and monitoring cryosphere changes.This study presents a novel du...Accurate assessment of snowpack volumetric liquid water content and bulk density is essential for understanding snow hydrology,avalanche risk management,and monitoring cryosphere changes.This study presents a novel dual-parameter inversion framework that integrates synthetic electromagnetic modelling,dimensionality reduction,and machine learning algorithms to extract relative permittivity and log-resistivity from ground-penetrating radar(GPR)data.Traditional snowpack measurements are invasive,labor-intensive,and limited to point observations.To overcome these limitations,we developed a non-invasive,scalable,and data-driven framework that uses synthetic GPR datasets representing diverse snowpack conditions with variable moisture and density profiles.Synthetic 1D time series reflections(A-scans)are generated using finite-difference time-domain simulations in the state-of-the-art electromagnetic simulator gprMax.Principal component analysis(PCA)is applied to compress each A-scan while preserving key features,which significantly improved and enhanced the model training efficiency.Four machine learning models,including random forest,neural network,support vector machine,and eXtreme gradient boosting,are trained on PCA-reduced features.Among these,the neural network model achieved the best performance,with R^(2)>0.97 for permittivity and R 2>0.92 for resistivity.Gaussian noise(signal-to-noise ratio of 6 dB)is introduced to the synthetic data,and then targeted domain adaptation is employed to enhance generalization to field data.The framework is validated on two contrasting GPR transects in the Altay Mountains of the Chinese mainland,representing moist(T750)and wet(G125)snowpack conditions.The neural network model predictions are most consistent with the GPR derived estimates,Snowfork measurements,and snow pit data,achieving volumetric liquid water content deviation of≤1.5% and bulk density error within the range of 30-84 kg m^(-3).The results demonstrate that machine learning-based inversion,supported by realistic simulations and data augmentation enables scalable,non-invasive snowpack characterization with significant applications in hydrological forecasting,snow monitoring,and water resource management.展开更多
Wetting deformation in earth-rockfill dams is a critical factor influencingdam safety.Although numerous mathematical models have been developed to describe this phenomenon,most of them rely on empirical formulations a...Wetting deformation in earth-rockfill dams is a critical factor influencingdam safety.Although numerous mathematical models have been developed to describe this phenomenon,most of them rely on empirical formulations and lack prior knowledge of model parameters,which is essential for Bayesian parameter inversion to enhance accuracy and reduce uncertainty.This study introduces a datadriven approach to establishing prior knowledge of earth-rockfill dams.Driving factors are utilized to determine the potential range of model parameters,and settlement changes within this range are calculated.The results are iteratively compared with actual monitoring data until the calculated range encompasses the observed data,thereby providing prior knowledge of the model parameters.The proposed method is applied to the right-bank earth-rockfilldam of Danjiangkou.Employing a Gibbs sample size of 30,000,the proposed method effectively calibrates the prior knowledge of the wetting model parameters,achieving a root mean square error(RMSE)of 5.18 mm for the settlement predictions.By comparison,the use of non-informative priors with sample sizes of 30,000 and 50,000 results in significantly larger RMSE values of 11.97 mm and 16.07 mm,respectively.Furthermore,the computational efficiencyof the proposed method is demonstrated by an inversion computation time of 902 s for 30,000 samples,which is notably shorter than the 1026 s and 1558 s required for noninformative priors with 30,000 and 50,000 samples,respectively.These findingsunderscore the superior performance of the proposed approach in terms of both prediction accuracy and computational efficiency.These results demonstrate that the proposed method not only improves the predictive accuracy but also enhances the computational efficiency,enabling optimal parameter identificationwith reduced computational effort.This approach provides a robust and efficientframework for advancing dam safety assessments.展开更多
Machine learning(ML)is recognized as a potent tool for the inverse design of environmental functional material,particularly for complex entities like biochar-based catalysts(BCs).Thus,the tailored BCs can have a disti...Machine learning(ML)is recognized as a potent tool for the inverse design of environmental functional material,particularly for complex entities like biochar-based catalysts(BCs).Thus,the tailored BCs can have a distinct ability to trigger the nonradical pathway in advance oxidation processes(AOPs),promising a stable,rapid and selective degradation of persistent contaminants.However,due to the inherent“black box”nature and limitations of input features,results and conclusions derived from ML may not always be intuitively understood or comprehensively validated.To tackle this challenge,we linked the front-point interpretable analysis approaches with back-point density functional theory(DFT)calculations to form a chained learning strategy for deeper sight into the intrinsic activation mechanism of BCs in AOPs.At the front point,we conducted an easy-to-interpret meta-analysis to validate two strategies for enhancing nonradical pathways by increasing oxygen content and specific surface area(SSA),and prepared oxidized biochar(OBC500)and SSA-increased biochar(SBC900)by controlling pyrolysis conditions and modification methods.Subsequently,experimental results showed that OBC500 and SBC900 had distinct dominant degradation pathways for 1O2 generation and electron transfer,respectively.Finally,at the end point,DFT calculations revealed their active sites and degradation mechanisms.This chained learning strategy elucidates fundamental principles for BC inverse design and showcases the exceptional capacity to integrate computational techniques to accelerate catalyst inverse design.展开更多
文摘The duplicate form of the generalized Gould-Hsu inversions has been obtained by Shi and Zhang. In this paper, we present a simple proof of this duplicate form. With the same method, we construct the duplicate form of the generalized Carlitz inversions. Using this duplicate form, we obtain several terminating basic hypergeometric identities and some limiting cases.
文摘The presence of temperature inversions (TI), concentration of air pollutants (AP) and meteorological variables (MV) affect the welfare of the population, creating public health problems (acute respiratory diseases ARDs, among others). The Guadalajara Metropolitan Zone (GMZ) experiences high levels of air pollution, which associated with the presence of temperature inversions and meteorological variations is conducive to the incidence of ARDs in children. The aim of this work is to evaluate the TI, MV, AP and their influence on the ARDs in children under five years in the GMZ from 2003 to 2007. In this period, the moderate and strong TI are the most frequent presenting from November to May. The AP shows a variable behavior during the year and between years, with the highest concentration of particles less than 10 microns (PM10), followed by ozone (O3), nitrogen dioxide (NO2), nitrogen oxides (NOX), carbon monoxide (CO) and sulfur dioxide (SO2), the most affected areas are the southeast of the GMZ. Annual arithmetic mean is 213,510 ± 41,209 ARDs consultations. The most important diseases are acute respiratory infections (98.0%), followed by pneumonia and bronchopneumonia (1.1%), asthma and status asthmaticus (0.5%) and streptococcal pharyngitis and tonsillitis (0.4%). Months with most inquiries were from October to March, mainly in the southeast, south and center of the city, coinciding with high levels of AP. Statistical analysis shows that the TI have significant correlation with ARDs in three years, temperature (Temp) in two, relative humidity (RH) in two, wind speed (WS) in three, wind direction (WD) in two, while that air pollutants NOX and NO2 showed significant correlation with ARDs throughout the period. CO and SO2 showed significance in two years, while the PM10 and O3 in one.
基金sponsored by the U.S. Department of Energy (DOE)supported by the Ministry of Science and Technology of China (Grant Nos. 2010CB950804 and 2013CB955801)+1 种基金the "Strategic Priority Research Program" of the Chinese Academy of Sciences (Grant No. XDA05100300)the National Natural Science Foundation of China (Grant No. 41305011)
文摘Knowledge of the statistical characteristics of inversions and their effects on aerosols under different large-scale synoptic circulations is important for studying and modeling the diffusion of pollutants in the boundary layer. Based on results gen- erated using the self-organizing map （SOM） weather classification method, this study compares the statistical characteristics of surface-based inversions （SBIs） and elevated inversions （EIs）, and quantitatively evaluates the effect of SBIs on aerosol condensation nuclei （CN） concentrations and the relationship between temperature gradients and aerosols for six prevailing synoptic patterns over the the Southern Great Plains （SGP） site during 2001-10. Large-scale synoptic patterns strongly influ- ence the statistical characteristics of inversions and the accumulation of aerosols in the low-level atmosphere. The activity, frequency, intensity, and vertical distribution of inversions are significantly different among these synoptic patterns. The verti- cal distribution of inversions varies diurnally and is significantly different among the different synoptic patterns. Anticyclonic patterns affect the accumulation of aerosols near the ground more strongly than cyclonic patterns. Mean aerosol CN con- centrations increase during SBIs compared to no inversion cases by 16.1%, 22.6%, 24.5%, 58.7%, 29.8% and 23.7% for the six synoptic patterns. This study confirms that there is a positive correlation between temperature gradients and aerosol CN concentrations near the ground at night under similar large-scale synoptic patterns. The relationship is different for different synoptic patterns and can be described by linear functions. These findings suggest that large-scale synoptic patterns change the static stability of the atmosphere and inversions in the lower atmosphere, thereby influencing the diffusion of aerosols near the ground.
基金financially supported by the National Natural Science Foundation of China(No.41774125)Key Program of National Natural Science Foundation of China(No.41530320)+1 种基金the Key National Research Project of China(Nos.2016YFC0303100 and 2017YFC0601900)the Strategic Priority Research Program of Chinese Academy of Sciences Pilot Special(No.XDA 14020102)
文摘Traditional 3D Magnetotelluric(MT) forward modeling and inversions are mostly based on structured meshes that have limited accuracy when modeling undulating surfaces and arbitrary structures. By contrast, unstructured-grid-based methods can model complex underground structures with high accuracy and overcome the defects of traditional methods, such as the high computational cost for improving model accuracy and the difficulty of inverting with topography. In this paper, we used the limited-memory quasi-Newton(L-BFGS) method with an unstructured finite-element grid to perform 3D MT inversions. This method avoids explicitly calculating Hessian matrices, which greatly reduces the memory requirements. After the first iteration, the approximate inverse Hessian matrix well approximates the true one, and the Newton step(set to 1) can meet the sufficient descent condition. Only one calculation of the objective function and its gradient are needed for each iteration, which greatly improves its computational efficiency. This approach is well-suited for large-scale 3D MT inversions. We have tested our algorithm on data with and without topography, and the results matched the real models well. We can recommend performing inversions based on an unstructured finite-element method and the L-BFGS method for situations with topography and complex underground structures.
基金supported by the National Key Research and Development Program of China(2022YFF0800603).
文摘We conducted rapid inversions of rupture process for the 2023 earthquake doublet occurred in SE Türkiye,the first with a magnitude of M_(W)7.8 and the second with a magnitude of M_(W)7.6,using teleseismic and strong-motion data.The teleseismic rupture models of the both events were obtained approximately 88 and 55 minutes after their occurrences,respectively.The rupture models indicated that the first event was an asymmetric bilateral event with ruptures mainly propagating to the northeast,while the second one was a unilateral event with ruptures propagating to the west.This information could be useful in locating the meizoseismal areas.Compared with teleseismic models,the strong-motion models showed relatively higher resolution.A noticeable difference was found for the M_(W)7.6 earthquake,for which the strong-motion models shows a bilateral event,rather than a unilateral event,but the dominant rupture direction is still westward.Nevertheless,all strong-motion models are consistent with the teleseismic models in terms of magnitudes,durations,and dominant rupture directions.This suggests that both teleseismic and strong-motion data can be used for fast determination of major source characteristics.In contrast,the strong-motion data would be preferable in future emergency responses since they are recorded earlier and have a better resolution ability on the source ruptures.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDA17010101)the National Natural Science Foundation of China (Grant Nos. 41305011, 41775033, 41575033 and 41675034)+1 种基金the China Postdoctoral Science Foundation (Grant No.2014M550797)the National Key R&D Program of China (Grant No. 2017YFA0603504)
文摘High-quality and continuous radiosonde, aerosol and surface meteorology datasets are used to investigate the statistical characteristics of meteorological parameters and their effects on aerosols. The data were collected at the Atmospheric Radiation Measurement Southern Great Plains climate research facility during 2000–15. The parameters and vertical distribution of temperature inversion layers were found to have strong diurnal and seasonal changes. For surface-based temperature inversion (SBI), the mean frequency and depth of temperature inversion layers were 39.4% and 198 m, respectively. The temperature difference between the top and bottom of SBI was 4.8℃, and so the temperature gradient was 2.4℃(100 m)^-1. The detailed vertical distributions of temperature inversion had been determined, and only the temperature inversion layers below 1000 m showed diurnal and seasonal variations. Mean surface aerosol number concentrations increased by 43.0%, 21.9% and 49.2% when SBIs were present at 0530, 1730 and 2330 LST, respectively. The effect of SBI on surface aerosol concentration was weakest in summer (18.1%) and strongest in winter (58.4%). During elevated temperature inversion events, there was no noticeable difference in surface aerosol number concentrations. Temperature differences and temperature gradients across SBIs correlated fairly well with aerosol number concentrations, especially for temperature gradients. The vertical distribution of aerosol optical properties with and without temperature inversions was different. Surface aerosol measurements were representative of the air within (below), but not above, SBIs and EIs. These results provide a basis for developing a boundary layer aerosol accumulation model and for improving radiative transfer models in the lower atmosphere.
基金partially supported by the Doctoral Programming Research Fund of Higher Education, Chinese Ministry of Education (No. 20110205110010)
文摘It is now common practice to perform simultaneous traveltime inversion for the velocity field and the reflector geometry in reflection/refraction tomography, or the velocity field and the hypocenter locations in regional earthquake tomography, but seldom are all three classes of model parameters updated simultaneously. This is mainly due to the trade-off between the different types of model parameters and the lack of different seismic phases to constrain the model parameters. Using a spherical-coordinate ray tracing algorithm for first and later（primary reflected） arrival tracing algorithm in combination with a popular linearized inversion solver, it is possible to simultaneously recover the three classes of model parameters in regional or global tomographic studies. In this paper we incorporate the multistage irregular shortest-path ray tracing algorithm（in a spherical coordinate system） with a subspace inversion solver to formulate a simultaneous inversion algorithm for triple model parameters updating using direct and later arrival time information.Comparison tests for two sets of data（noise free and added noise） indicate that the new triple-class parameter inversion algorithm is capable of obtaining nearly the same results as the double-class parameter inversion scheme. Furthermore,the proposed multi-parameter type inversion method is not sensitive to a modest level of picking error in the traveltime data, and also performs well with a relatively large uncertainty in earthquake hypocentral locations. This shows it to be a feasible and promising approach in regional or global tomographic applications.
基金National Natural Science Foundation of China (40074010).
文摘In the paper, a 2D symmetrical anisotropic medium whose strike agrees with one of the horizontal principal axes is considered to develop a corresponding inversion technique. In the specified conditions, if we assume an equivalent conductivity anisotropy in both the vertical and dipping directions, i.e., σzz=σyy, the differential equations obtained are formally the same as that for TE and TM modes in the 2D isotropic geoelectrical media. The same inversion technique as that in the 2D isotropic media can be employed to obtain the anisotropic conductivities. It means that the TE and TM inversion results in the isotropic media can be respectively thought as the resistivities in the two principal directions of the symmetrically anisotropic media, which has offered a new approach and a theoretical guidance for interpreting magnetotelluric data. And the inversion technique developed here is used to test the magnetotelluric data in the area of Tianzhu and Yongdeng in Gansu Province, so that the crust anisotropic geoelectrical structures in this region can be obtained.
基金The Marine Scholarship of ChinaChina Scholarship Council for International Doctoral Students under contract No.2017SOA016552the National Natural Science Foundation of China under contract Nos U2106204 and 41676003。
文摘Variations in incoming shortwave radiation influence the net surface heat flux,contributing to the formation of a temperature inversion.The effects of shortwave radiation on the temperature inversions in the Bay of Bengal and eastern equatorial Indian Ocean have never been investigated.Thus,a high-resolution(horizontal resolution of 0.07°×0.07° with 50 vertical layers) Regional Ocean Modeling System(ROMS) model is utilized to quantify the contributions of shortwave radiation to the temperature inversions in the study domain.Analyses of the mixed layer heat and salt budgets are performed,and different model simulations are compared.The model results suggest that a 30% change in shortwave radiation can change approximately 3% of the temperature inversion area in the Bay of Bengal.Low shortwave radiation reduces the net surface heat flux and cools the mixed layer substantially;it also reduces the evaporation rate,causing less evaporative water vapor losses from the ocean than the typical situation,and ultimately enhances haline stratification.Thus,the rudimentary outcome of this research is that a decrease in shortwave radiation produces more temperature inversion in the study region,which is primarily driven by the net surface cooling and supported by the intensive haline stratification.Moreover,low shortwave radiation eventually intensifies the temperature inversion layer by thickening the barrier layer.This study could be an important reference for predicting how the Indian Ocean climate will respond to future changes in shortwave radiation.
基金supported by the National Natural Science Foundation of China (grant nos. 41930103 and 41674052)
文摘The Bayesian inversion method is a stochastic approach based on the Bayesian theory.With the development of sampling algorithms and computer technologies,the Bayesian inversion method has been widely used in geophysical inversion problems.In this study,we conduct inversion experiments using crosshole seismic travel-time data to examine the characteristics and performance of the stochastic Bayesian inversion based on the Markov chain Monte Carlo sampling scheme and the traditional deterministic inversion with Tikhonov regularization.Velocity structures with two different spatial variations are considered,one with a chessboard pattern and the other with an interface mimicking the Mohorovicicdiscontinuity(Moho).Inversions are carried out with different scenarios of model discretization and source–receiver configurations.Results show that the Bayesian method yields more robust single-model estimations than the deterministic method,with smaller model errors.In addition,the Bayesian method provides the posterior probabilistic distribution function of the model space,which can help us evaluate the quality of the inversion result.
文摘HF (high frequency) radar sounder technology has been developed for several missions of Mars surface/subsurface exploration. This paper presents a model of rough surface and stratified sub-surfaces to describe the multi-layer structure of Mars polar deposits. Based on numerical simulation of radar echoes from rough surface/stratified interfaces, an inversion approach is developed to obtain the parameters of Polar Layered Deposits, i.e. layers thickness and dielectric constants. As a validation example, the SHARAD radar sounder data of the Promethei Lingula of Mars South Polar region is adopted for parameters inversion. The result of stratification is also analyzed and compared with the optical photo of the deep cliff of Chasma Australe canyon. Dielectric inversions show that the deposit media are not uniform, and the dielectric constants of the Promethei Lingula surfaces are large, and become reduced around the depth of 20 m - 30 m, below where most of the deposits are nearly pure ice, except a few thin layers with a lot of dust.
文摘As is well known, Greece has a significant number of earthquakes each year. Ιn recent years, several earthquakes have occurred in Greece. For this scope, a methodology was used to determine the source parameters. This methodology is based on minimizing the difference between the observed and the synthetic waveforms, using the method Source Parameters Calculation—SPCa <a href="#ref1" target="_blank">[1]</a>. The source parameters, using the proposed methodology, are calculated by comparing observed seismograms and synthetic by inverting data. The synthetics are calculated using the reflectivity method (Kennett, 1983) as implemented by Randall et al. (1994) for a given earth structure. This study includes inversion results for the strongest events that occurred in Greece from 2008 to 2014. For the same events calculated the main fault plane, using the method of Hypocenter Centroid-plot (HC-plot) <a href="#ref2" target="_blank">[2]</a> <a href="#ref3" target="_blank">[3]</a>. This methodology is a simple geometrical method based on the combination between the hypocentral position and the two possible fault planes.
基金Research support from the National Science Foundation ofChina(No.21071116)Chongqing Scientific Foundation,China(No.2010BB4126)
文摘Four exotic chiral organocatalysts, 9-amino-（9-deoxy） cinchona alkaloids with （8S, 9R） and （8R, 9S）- configurations, were conveniently synthesized for the first time in 27-72% total yields through two conversions of configuration at the 9-stereogenic centers of commercially available cinchona alkaloids.
文摘We shall give natural generalized solutions of Hadamard and tensor products equations for matrices by the concept of the Tikhonov regularization combined with the theory of reproducing kernels.
文摘We exploit the theory of reproducing kernels to deduce a matrix inequality for the inverse of the restriction of a positive definite Hermitian matrix.
基金This work was supported by the National Natural Science Foundation of China(No.60077030)
文摘In order to obtain large broadband, a novel travelling-wave modulator with nonperiodic domain inversions and ridge structure is proposed. The composite structure is designed to achieve velocity matching between the optical wave and the microwave, to get a 50 characteristic impedance and to reduce the loss of the microwave electrodes with finite element method (FEM). The calculation results show that the frequency response of the new device is flat up to 350 GHz with interaction length of 1 cm, characteristic impedance of 49 , and microwave refractive index of 2.5.
基金supported by the National Key R&D Program of China(Grant Nos.2023YFC3008300&2023YFC3008305)the National Natural Science Foundation of China(Grant No.42172320)+1 种基金the Key Laboratory of Mountain Hazards and Engineering Resilience,Institute of Mountain Hazards and Environment,Chinese Academy of Sciences(Grant Nos.KLMHER-Z06&KLMHER-T07)the Science and Technology Research Program of Institute of Mountain Hazards and Environment,Chinese Academy of Sciences(Grant No.IMHE-CXTD.04).
文摘Accurate assessment of snowpack volumetric liquid water content and bulk density is essential for understanding snow hydrology,avalanche risk management,and monitoring cryosphere changes.This study presents a novel dual-parameter inversion framework that integrates synthetic electromagnetic modelling,dimensionality reduction,and machine learning algorithms to extract relative permittivity and log-resistivity from ground-penetrating radar(GPR)data.Traditional snowpack measurements are invasive,labor-intensive,and limited to point observations.To overcome these limitations,we developed a non-invasive,scalable,and data-driven framework that uses synthetic GPR datasets representing diverse snowpack conditions with variable moisture and density profiles.Synthetic 1D time series reflections(A-scans)are generated using finite-difference time-domain simulations in the state-of-the-art electromagnetic simulator gprMax.Principal component analysis(PCA)is applied to compress each A-scan while preserving key features,which significantly improved and enhanced the model training efficiency.Four machine learning models,including random forest,neural network,support vector machine,and eXtreme gradient boosting,are trained on PCA-reduced features.Among these,the neural network model achieved the best performance,with R^(2)>0.97 for permittivity and R 2>0.92 for resistivity.Gaussian noise(signal-to-noise ratio of 6 dB)is introduced to the synthetic data,and then targeted domain adaptation is employed to enhance generalization to field data.The framework is validated on two contrasting GPR transects in the Altay Mountains of the Chinese mainland,representing moist(T750)and wet(G125)snowpack conditions.The neural network model predictions are most consistent with the GPR derived estimates,Snowfork measurements,and snow pit data,achieving volumetric liquid water content deviation of≤1.5% and bulk density error within the range of 30-84 kg m^(-3).The results demonstrate that machine learning-based inversion,supported by realistic simulations and data augmentation enables scalable,non-invasive snowpack characterization with significant applications in hydrological forecasting,snow monitoring,and water resource management.
基金supported by the National Key R&D Program of China(Grant No.2023YFC3209504)Natural Science Foundation of Wuhan(Grant No.2024040801020271)the Fundamental Research Funds for Central Public Welfare Research Institutes(Grant No.CKSF2025718/YT).
文摘Wetting deformation in earth-rockfill dams is a critical factor influencingdam safety.Although numerous mathematical models have been developed to describe this phenomenon,most of them rely on empirical formulations and lack prior knowledge of model parameters,which is essential for Bayesian parameter inversion to enhance accuracy and reduce uncertainty.This study introduces a datadriven approach to establishing prior knowledge of earth-rockfill dams.Driving factors are utilized to determine the potential range of model parameters,and settlement changes within this range are calculated.The results are iteratively compared with actual monitoring data until the calculated range encompasses the observed data,thereby providing prior knowledge of the model parameters.The proposed method is applied to the right-bank earth-rockfilldam of Danjiangkou.Employing a Gibbs sample size of 30,000,the proposed method effectively calibrates the prior knowledge of the wetting model parameters,achieving a root mean square error(RMSE)of 5.18 mm for the settlement predictions.By comparison,the use of non-informative priors with sample sizes of 30,000 and 50,000 results in significantly larger RMSE values of 11.97 mm and 16.07 mm,respectively.Furthermore,the computational efficiencyof the proposed method is demonstrated by an inversion computation time of 902 s for 30,000 samples,which is notably shorter than the 1026 s and 1558 s required for noninformative priors with 30,000 and 50,000 samples,respectively.These findingsunderscore the superior performance of the proposed approach in terms of both prediction accuracy and computational efficiency.These results demonstrate that the proposed method not only improves the predictive accuracy but also enhances the computational efficiency,enabling optimal parameter identificationwith reduced computational effort.This approach provides a robust and efficientframework for advancing dam safety assessments.
基金supported by Project of National and Local Joint Engineering Research Center for Biomass Energy Development and Utilization(Harbin Institute of Technology,No.2021A004).
文摘Machine learning(ML)is recognized as a potent tool for the inverse design of environmental functional material,particularly for complex entities like biochar-based catalysts(BCs).Thus,the tailored BCs can have a distinct ability to trigger the nonradical pathway in advance oxidation processes(AOPs),promising a stable,rapid and selective degradation of persistent contaminants.However,due to the inherent“black box”nature and limitations of input features,results and conclusions derived from ML may not always be intuitively understood or comprehensively validated.To tackle this challenge,we linked the front-point interpretable analysis approaches with back-point density functional theory(DFT)calculations to form a chained learning strategy for deeper sight into the intrinsic activation mechanism of BCs in AOPs.At the front point,we conducted an easy-to-interpret meta-analysis to validate two strategies for enhancing nonradical pathways by increasing oxygen content and specific surface area(SSA),and prepared oxidized biochar(OBC500)and SSA-increased biochar(SBC900)by controlling pyrolysis conditions and modification methods.Subsequently,experimental results showed that OBC500 and SBC900 had distinct dominant degradation pathways for 1O2 generation and electron transfer,respectively.Finally,at the end point,DFT calculations revealed their active sites and degradation mechanisms.This chained learning strategy elucidates fundamental principles for BC inverse design and showcases the exceptional capacity to integrate computational techniques to accelerate catalyst inverse design.
