Spatial and temporal variation process of seabed dynamic response induced by the internal solitary wave

Internal solitary wave(ISW)is often accompanied by huge energy transport,which will change the pore water pressure in the seabed.Based on the two-dimensional Biot consolidation theory,the excess pore water pressure in seabed was simulated,and the spatiotemporal distribution characteristics of excess pore water pressure was studied.As the parameters of both ISW and seabed can affect the excess pore water pressure,the distribution of pore water pressure showed both dissipation and phase lag.And parametric studies were done on these two phenomena.Due to influenced by the phase lag of excess pore water pressure,the penetration depth under the site of northern South China Sea with total water depth 327 m,induced by typical internal solitary wave increased by 26.19%,53.27%and 149.86%from T_(0)to T_(0.5)in sand silt,clayey silt and fine sand seabed,respectively.That means the effect of ISW on seabed will be underestimated if we only take into accout the penetration depth under ISW trough,especially for fine sand seabed.In addition,the concept of“amplitude-depth ratio”had been introduced to describe the influence of ISW on seabed dynamic response in the actual marine environment.In present study,it is negatively correlated with the excess pore water pressure,and an ISW with smaller amplitude-depth ratio can wide the range of lateral impacts.Our study results help understand the seabed damage induced by the interaction between ISW and seabed.

Fine-Grained Classification of Remote Sensing Ship Images Based on Improved VAN

The remote sensing ships’fine-grained classification technology makes it possible to identify certain ship types in remote sensing images,and it has broad application prospects in civil and military fields.However,the current model does not examine the properties of ship targets in remote sensing images with mixed multi-granularity features and a complicated backdrop.There is still an opportunity for future enhancement of the classification impact.To solve the challenges brought by the above characteristics,this paper proposes a Metaformer and Residual fusion network based on Visual Attention Network(VAN-MR)for fine-grained classification tasks.For the complex background of remote sensing images,the VAN-MR model adopts the parallel structure of large kernel attention and spatial attention to enhance the model’s feature extraction ability of interest targets and improve the classification performance of remote sensing ship targets.For the problem of multi-grained feature mixing in remote sensing images,the VAN-MR model uses a Metaformer structure and a parallel network of residual modules to extract ship features.The parallel network has different depths,considering both high-level and lowlevel semantic information.The model achieves better classification performance in remote sensing ship images with multi-granularity mixing.Finally,the model achieves 88.73%and 94.56%accuracy on the public fine-grained ship collection-23(FGSC-23)and FGSCR-42 datasets,respectively,while the parameter size is only 53.47 M,the floating point operations is 9.9 G.The experimental results show that the classification effect of VAN-MR is superior to that of traditional CNNs model and visual model with Transformer structure under the same parameter quantity.

Preparation and characterization of a specialized lunar regolith simulant for use in lunar low gravity simulation

Lunar in-situ resource utilization(ISRU)has been put on the agenda by many countries.Due to the special material nature and low gravity environment,the lunar regolith demonstrates significantly different behavior from terrestrial geomaterials.However,the systematic understanding of its geotechnical behavior is now seriously restricted by the scarcity of lunar regolith and the difficulty in simulating lunar gravity.A new lunar regolith simulant,termed as China University of Mining and Technology Number One(CUMT-1),has been developed to recover properties of the lunar regolith and simulate the lunar gravity by adopting the recently advanced geotechnical magnetic-similitude-gravity model testing(GMMT)method.The CUMT-1 simulant was prepared by reproducing the in-situ formation and fragmentation of the lunar matrix,which plays a key role in the irregular particle morphology.The mineralogical compositions,particle morphology and gradation,specific gravity,bulk density,void ratio,shear strength,and compressibility were determined.After quantifying the magnetization and magnetic-similitude-gravity characteristics,an application of the cone penetration resistance under low gravity was further given.The obtained results are compared to the values known for lunar regolith samples and other simulants,which demonstrates promising characteristics for use in geotechnical engineering-based and scientificbased applications,especially considering the influence of lunar gravity.

Empirical formulae for electric double-layer repulsion between two arbitrarily inclined clay particles

To understand the mesoscopic mechanism of clayey soil in view of macroscopic behavior, it is essential to quantitatively calculate the electric double-layer repulsion between arbitrarily inclined clay particles.However, suitable calculation methods with high efficiency and accuracy are still rare at present in literature. Based on a great number of numerical calculations of the repulsion between two inclined platy clay particles, explicit empirical formulae for estimating electric double-layer repulsion between clay particles are put forward. Comparison between the empirical solutions and corresponding numerical results shows that the proposed formulae have a reasonable accuracy, and application of the presented formula is easy and efficient.

Behaviour of granular matter under gravity-induced stress gradient:A two-dimensional numerical investigation

Gravity is the most important load source in mining and geotechnical engineering,which causes both the stress level and stress gradient inside geomaterials.Different from the stress level,the influence of gravity-induced stress gradient on the behaviour of the material is still unknown.An in-deep study on it will help to promote the understanding of material behaviour,especially for those cases related to unconventional gravity such as terrestrial ng physical modelling and extraterrestrial resource exploitation(g is the terrestrial gravitational acceleration).In this study,a high-order homogenization for granular materials is proposed at first,in which the stress gradient is drawn into the constitutive representation by adopting a representative volume element(RVE).The consolidation and shear strength behaviour of RVE are then investigated by performing numerical biaxial tests.The results show that all the compressibility,shear strength,shear stiffness,volumetric deformation,and critical state behaviour show a stress gradient dependence.A coupling between stress gradient,stress level,and material properties is also observed.These observations suggest that,besides the stress level,extra attention needs to be paid to material responses related to stress gradient during engineering practices.

Neumann stochastic finite element method for calculating temperature field of frozen soil based on random field theory

To study the effect of uncertain factors on the temperature field of frozen soil, we propose a method to calculate the spatial average variance from just the point variance based on the local average theory of random fields. We model the heat transfer coefficient and specific heat capacity as spatially random fields instead of traditional random variables. An analysis for calculating the random temperature field of seasonal frozen soil is suggested by the Neumann stochastic finite element method, and here we provide the computational formulae of mathematical expectation, variance and variable coefficient. As shown in the calculation flow chart, the stochastic finite element calculation program for solving the random temperature field, as compiled by Matrix Laboratory （MATLAB） sottware, can directly output the statistical results of the temperature field of frozen soil. An example is presented to demonstrate the random effects from random field parameters, and the feasibility of the proposed approach is proven by compar- ing these results with the results derived when the random parameters are only modeled as random variables. The results show that the Neumann stochastic finite element method can efficiently solve the problem of random temperature fields of frozen soil based on random field theory, and it can reduce the variability of calculation results when the random parameters are modeled as spatial- ly random fields.

Bearing capacity of surface circular footings on granular material under low gravity fields

Low gravity fields have been simulated through magnetic acceleration to conduct experimental study on bearing capacity of circular footings on a type of crushable planetary regolith simulant,which has comparable density and particle size distribution of lunar soil.The loadesettlement responses of surface spread footings are obtained by investigating the relative density,footing size and gravity effects.Applying the hyperbolic asymptote method,normalised foundation stiffness and ultimate bearing capacity are obtained by curve fitting and predicted by power functions using multivariate nonlinear regression.The results show that the nonlinear gravity effect is not negligible,related to stress condition,soil dilatancy and mobilised friction angle.A cone penetration test(CPT)-based method for prediction of bearing capacity is proposed with correlations between ultimate bearing capacity of footings and shallow penetration stiffness of CPTs,avoiding the uncertainties of soil property estimations.Analyses of allowable bearing capacity and footing influence zone in consideration of footing size and gravity effects could therefore improve the design of shallow foundations on the Moon and Mars,and provide new understandings and potential implications to the bearing capacity of shallow foundations on crushable granular material in both terrestrial and extraterrestrial geotechnical engineering.

Uncertainties of thermal boundaries and soil properties on permafrost table of frozen ground in Qinghai-Tibet Plateau

In the permafrost regions of the Qinghai-Tibet Plateau(QTP),the permafrost table has a significant effect on the stability of geotechnical engineering.The thermal boundaries and soil properties are the key factors affecting the permafrost table.Complex geological environments and human activities can lead to the uncertainties of thermal boundaries and soil properties.In this paper,an array of field experiments and Monte Carlo(MC)simulations of thermal boundaries and soil properties are carried out.The coefficient of variation(COV),scale of fluctuation(SOF),and autocorrelation distance(ACD)of uncertainties of thermal boundaries and soil properties are investigated.A stochastic analysis method of the probabilistic permafrost table is then proposed,and the statistical properties of permafrost table on the QTP are computed by self-compiled program.The proposed stochastic analysis method is verified with the calculated and measured temperature observations.According to the relationship between ACD and SOF for the five theoretical autocorrelation functions(ACFs),the effects of ACF,COV,and ACD of soil properties and the COV of thermal boundaries on the permafrost tables are analyzed.The results show that the effects of different ACFs of soil properties on the standard deviation(SD)of permafrost table depth are not obvious.The SD of permafrost table depth increases with time,and the larger the COVs of thermal boundaries and soil properties,the deeper the SD of permafrost table;the longer the ACD of soil properties,the shallower the SD of permafrost table.This study can provide a reference for the stability analysis of geotechnical engineering on the QTP considering the uncertainties of thermal boundaries and soil properties.

Strength of undisturbed and reconstituted frozen soil at temperatures close to 0 ℃

The strength of warm frozen soils in permafrost is fundamentally significant to estimate and predict the ground settlements from construction activities. A study was therefore initiated to assess the strength and its behaviors of undisturbed and reconstituted frozen soils at temperatures close to 0 ℃. A series of triaxial compression tests(TCT) were performed by using a developed testing apparatus and a matching specimen-preparation method. The confinement was applied from air pressure, the temperature in the specimen was maintained using two-end refrigeration, and multi-stage loading on a single specimen was adopted to determine the strength. The test results showed that the strength, both for the undisturbed and reconstituted frozen-soil specimens, was significantly dependent on the temperatures and independent of the applied confining pressures. Additionally, the strength of undisturbed frozen soils was about 1.6 times more than that for reconstituted frozen soils. These observations were closely associated with the structures existing between pore-ice and gravels with large diameters.

Finite element analysis on deformation of high embankment in heavy-haul railway subjected to freeze-thaw cycles

Finite element simulations are increasingly providing a versatile environment for this topic. In this study, a two-dimensional finite element analysis is conducted to predict the deformation of high embankment in Bazhun heavy-haul railway, China. A recently developed nonlinear softening-type constitutive model is utilized to model the be- havior of subgrade filling materials subjected to freeze-thaw cycles. For the convenience of practical application, the dynamic loading induced by a vehicle is treated as a quasi-static axle load. The deformation of this embankment with different moisture content under freeze-thaw cycles is compared. The results show that when subjected to the first freeze-thaw cycle, the embankment experienced significant deformation variations. Maximum deformation was usually achieved after the embankment with optimum moisture content experienced six freeze-thaw cycles, however, the em- bankment with moisre content of 8.0% and 9.5% deforms continuously even after experiencing almost ten freeze-thaw cycles. Overall, this study provides a simple nonlinear finite element approach for calculating the deformation of the embankment in changing climate conditions.

Purification of heavy metal chromium in saturated sand by artificial freezing:Mechanism and method optimization

Heavy metal pollution of soil has become one of the most common hazards in human development.The artificial freezing method,especially the progressive freezing method,can reduce heavy metal pollutants in the soil and promises to be an effective in-situ treatment of contaminated sites.This study analyzes the freezing purification mechanism of heavy metal contaminants in saturated sand and identifies three main factors that impact the effects of purification:freezing rate,initial concentration,and diffusion coefficient.Moreover,one-dimensional freezing tests are carried out by different freezing modes.The experimental results show that the heavy metal chromium could only be removed effectively with a slow freezing rate.By optimizing the freezing mode and freezing rate,a long section of soil was frozen and purified,with the maximum purification rate reaching 65.8%.This study shows that it is feasible to treat contaminated saturated sand by a gradual-cooling freezing method.

Combination of super-resolution reconstruction and SGA-Net for marsh vegetation mapping using multi-resolution multispectral and hyperspectral images

Vegetation is crucial for wetland ecosystems.Human activities and climate changes are increasingly threatening wetland ecosystems.Combining satellite images and deep learning for classifying marsh vegetation communities has faced great challenges because of its coarse spatial resolution and limited spectral bands.This study aimed to propose a method to classify marsh vegetation using multi-resolution multispectral and hyperspectral images,combining super-resolution techniques and a novel self-constructing graph attention neural network(SGA-Net)algorithm.The SGA-Net algorithm includes a decoding layer(SCE-Net)to preciselyfine marsh vegetation classification in Honghe National Nature Reserve,Northeast China.The results indicated that the hyperspectral reconstruction images based on the super-resolution convolutional neural network(SRCNN)obtained higher accuracy with a peak signal-to-noise ratio(PSNR)of 28.87 and structural similarity(SSIM)of 0.76 in spatial quality and root mean squared error(RMSE)of 0.11 and R^(2) of 0.63 in spectral quality.The improvement of classification accuracy(MIoU)by enhanced super-resolution generative adversarial network(ESRGAN)(6.19%)was greater than that of SRCNN(4.33%)and super-resolution generative adversarial network(SRGAN)(3.64%).In most classification schemes,the SGA-Net outperformed DeepLabV3+and SegFormer algorithms for marsh vegetation and achieved the highest F1-score(78.47%).This study demonstrated that collaborative use of super-resolution reconstruction and deep learning is an effective approach for marsh vegetation mapping.

Fatigue of asphalt binder,mastic and mixture at low temperature

The fatigue damage is one of the most common distresses observed on the asphalt concrete pavement.To thoroughly understand the fatigue of asphalt concrete,the behaviors of the major components of asphalt concrete under cyclic loading are investigated respectively in this study.A new experiment method is developed to evaluate the performances of asphalt binder,mastic and fine aggregates mixture under cyclic tensile loading.The fatigue test results of asphalt binder show that the fatigue performance of asphalt binder is closely related with loading magnitude,temperature and loading rate.Mastic specimens with different filler content are tested and the results indicate that mastic specimens with 30%filler content show better fatigue resistance and higher permanent strain.The micro-structure analysis of mastic and mixture indicates that the fatigue resistance is closely related with the air void content of specimen.3D digital specimens are developed to model the fatigue of the asphalt binder,mastic and mixture specimens based on the finite element method(FEM).Fatigue damage of asphalt concrete is simplified by a damage model.With proper selection of damage parameters,the simulation results agree well with laboratory test results and can be used as a basis for future fatigue research.

Quantitative Evaluation of Leaf Inclination Angle Distribution on Leaf Area Index Retrieval of Coniferous Canopies

Both leaf inclination angle distribution(LAD)and leaf area index(LAI)dominate optical remote sensing signals.The G-function,which is a function of LAD and remote sensing geometry,is often set to 0.5 in the LAI retrieval of coniferous canopies even though this assumption is only valid for spherical LAD.Large uncertainties are thus introduced.However,because numerous tiny leaves grow on conifers,it is nearly impossible to quantitatively evaluate such uncertainties in LAI retrieval.In this study,we proposed a method to characterize the possible change of G-function of coniferous canopies as well as its effect on LAI retrieval.Specifically,a Multi-Directional Imager(MDI)was developed to capture stereo images of the branches,and the needles were reconstructed.The accuracy of the inclination angles calculated from the reconstructed needles was high.Moreover,we analyzed whether a spherical distribution is a valid assumption for coniferous canopies by calculating the possible range of the G-function from the measured LADs of branches of Larch and Spruce and the true G-functions of other species from some existing inventory data and threedimensional(3D)tree models.Results show that the constant G assumption introduces large errors in LAI retrieval,which could be as large as 53%in the zenithal viewing direction used by spaceborne LiDAR.As a result,accurate LAD estimation is recommended.In the absence of such data,our results show that a viewing zenith angle between 45 and 65 degrees is a good choice,at which the errors of LAI retrieval caused by the spherical assumption will be less than 10%for coniferous canopies.

Synthetic Jet Control on the Propulsion Behavior of a Foil in Plunge-pitch Motion

The Synthetic Jet(S J)control on the propulsion behavior of a foil in plunge-pitch motion is examined in this work by numerical simulations.An elliptic foil with ratio of 8 performs the plunge and pitch motions synchronously.A pair of SJs with the same frequency and strength is integrated into the upper and lower surfaces of the foil.As a result,the local flow field around the foil could be obviously modified by the SJs.At the Reynolds number of 200,the effects of the inclined angle between the jet direction and the chord line,the phase angle between the SJs and the flapping motion as well as the location of SJ on the propulsion performance are systematically investigated.Compared with the pure plunging and pitching foil,it is indicated that the enhancement of mean thrust and propulsive efficiency can be obtained by the SJs with suitable working parameters.Based on the numerical analysis,it is found that the jet flow on the foil surfaces,which changes the local pressure distribution to increase the pressure difference between upper and lower surfaces,can benefit the propulsion behavior of the flapping foil.

Evaluation of county-level poverty alleviation progress by deep learning and satellite observations

Poverty alleviation is one of the greatest challenges faced by low-income and middle-income countries.China,which had the largest rural poverty-stricken population,has made tremendous efforts in alleviating poverty especially since the implementation of the targeted poverty alleviation(TPA)policy in 2014,and by 2020,all national poverty-stricken counties(NPCs)have been out of poverty.This study combines deep learning with multiple satellite datasets to estimate county-level economic develop-ment from 2008 to 2019 and assess the effect of the TPA policy for 592 national poverty-stricken counties(NPCs)at country,provincial and county levels.Per capita gross domestic product(GDP)is used to measure the affluence level.From 2014 through 2019,the 592 NPCs experience an average growth rate of per capita GDP at 7.6%±0.4%,higher than the average growth rate of 310 adjacent non-NPC counties(7.3%±0.4%)and of the whole country(6.3%).We also reveal 42 counties with weak growth recently and that the average affluence level of the NPCs in 2019 is still much lower than the national or provincial averages.The inexpensive,timely and accurate method proposed here can be applied to other low-income and middle-income countries for affluence assessment.