This study investigates the influence of unsymmetrical surcharge on the piles of a bridge located in a coastal soft soil area, aiming to elucidate the deformation characteristics of the piles. The impact of some key parameters, including soft soil properties and unsymmetrical surcharge, on pile deformations is evaluated through 3D finite element numerical analysis and parameter sensitivity analysis. The results show that unsymmetrical surcharge significantly influences the displacement of both the piles and the surrounding soil, with both being affected by the soil arching effect. The parameter sensitivity analysis reveals that Poisson's ratio of the soft soil, and the stiffness of the piles have minimal impact on horizontal displacement. In contrast, the elastic modulus, cohesion, and internal friction angle of the soft soil, as well as the height and slope of the unsymmetrical surcharge, have significant effects on the piles. When the unsymmetrical surcharge is applied parallel or perpendicular to the bridge, the parallel surcharge has a relatively minor impact on the pile. The horizontal displacement of the pile follows an exponential relationship with L/B, D/h, and B/d. A functional relationship can be established between these parameters to predict the pile's horizontal displacement.

Ambient seismic noise and microseismicity analyses are increasingly applied for the monitoring of landslides and natural hazards. These methodologies can offer a valuable monitoring tool also for glacial and periglacial bodies, to understand the internal processes driven by external modifications in air temperature and rainfall/snowfall regimes and to forecast possible melting-related hazards in the light of climate change adaptation. We applied the methods to an almost continuous year of data recorded by a network of four passive seismic stations deployed in the frontal portion of the Gran Sometta rock glacier (Aosta Valley, NW Italian Alps). The spectral analysis of ambient seismic noise revealed frequency peaks related to stratigraphic resonances inside the rock glacier. Although the resonance frequency related to the bedrock interface was constant over time, a second higher resonance frequency was identified as the effect of variations in the active layer thickness driven by external air temperature modifications at the daily and seasonal scales. Ambient seismic noise cross-correlation highlighted coherent shear wave velocity modifications inside the periglacial body. The microseismicity dataset extracted from the continuous ambient noise recordings was analyzed and clustered to further investigate the ongoing internal processes and gain insight into their source mechanism and location. The first cluster of events was found to be likely related to the basal movements of the rock glacier and to falls and slides of the debris material. The second cluster was possibly related to shallow ice and rock fracturing processes. The validation of the seismic results through simple models of the rock glacier physical and mechanical layering, the internal thermal regime and the surface displacements allowed for a comprehensive understanding of the rock glacier's reaction to the external conditions.

The influences of NO3- concentration and AC density on corrosion resistance of FeCoNi high entropy alloy in simulated saline-alkali soil solution were studied via a series of measurements. Related results imply that the anticorrosion property of the HEA is significantly improved with the increase in NO3- concentration, particularly at high concentration of 0.1 mol/L, and the passive film covering the HEA becomes dense, intact and uniform. NO3- as a protective barrier is absorbed on the film surface, significantly inhibiting the pitting corrosion of the HEA. As AC density rises, the HEA surface status evolves from passivation to activated state, presenting a serious overall corrosion feature. The AC application facilitates the damage of passivation film grown on the HEA, resulting in a rapid increase in the number of flaws, which remarkedly decreases its resistance capacity against corrosion. Furthermore, under the combined influence of the two factors, the adverse effect of AC interference is obviously larger than the positive impact of NO3- on the corrosion resistance of the HEA at i(AC) of 50 A/m(2), causing plentiful defects within the passive film and severe corrosion of FeCoNi HEA.

Waterfront and submarine retaining structures are normally exposed to catastrophic seepage conditions under the effect of tidal and occasionally heavy rainfall effect, resulting in a decreased passive earth thrust and thus the higher risk of instability of retaining structures. To examine the effect of seepage flow on the magnitude and distribution of passive earth thrust, this paper assumes a composite curved-planar failure surface and presents a modified method of passive earth pressure considering the seepage flow effect. The flow field and pore pressure are firstly solved by the two-dimensional (2D) Laplace equation using the Fourier series expansion. The effective reaction force acting on the composite failure surface is then obtained using a modified K & ouml;tter equation. Compared to conventional methods based on limit equilibrium, the present method facilitates a straightforward assessment of both the magnitude and distribution of passive earth thrust without the prior assumption of the application point. The outcomes highlight that the passive earth thrust decreases with the ratios of permeability coefficients. The greater effective friction angle and a smaller ratio of permeability coefficients result in the lower application point of the passive earth thrust.

The relevance between microstructure and anti-corrosion performance of FeCoNi HEA prepared with different cooling methods was studied in simulated Golmud salinized soil solution. The results reveal that the corrosion rate reduces with increasing cooling rate, and the water-cooling HEA has the best anti-corrosion performance, followed by the air-cooling and furnace-cooled samples, which mainly depends on the grain size and the protectiveness of passivation film. An increase in grain size weakens the micro-galvanic corrosion effect between the grain boundary and the internal grain. Moreover, compact and uniform passive film markedly improves the anti-corrosion performance of water-cooled HEA. Combined with electrochemical tests, the water-cooling HEA exhibits the lowest sensitivity of metastable and stable pitting, as well as its surface passive film possesses excellent self-repairing ability. In addition, the HEA substrate occurs the preferential dissolution of Ni element.

The freeze-thaw cycle of near-surface soils significantly affects energy and water exchanges between the atmosphere and land surface. Passive microwave remote sensing is commonly used to observe the freeze-thaw state. However, existing algorithms face challenges in accurately monitoring near-surface soil freeze/thaw in alpine zones. This article proposes a framework for enhancing freeze/thaw detection capability in alpine zones, focusing on band combination selection and parameterization. The proposed framework was tested in the three river source region (TRSR) of the Qinghai-Tibetan Plateau. Results indicate that the framework effectively monitors the freeze/thaw state, identifying horizontal polarization brightness temperature at 18.7 GHz (TB18.7H) and 23.8 GHz (TB23.8H) as the optimal band combinations for freeze/thaw discrimination in the TRSR. The framework enhances the accuracy of the freeze/thaw discrimination for both 0 and 5-cm soil depths. In particular, the monitoring accuracy for 0-cm soil shows a more significant improvement, with an overall discrimination accuracy of 90.02%, and discrimination accuracies of 93.52% for frozen soil and 84.68% for thawed soil, respectively. Furthermore, the framework outperformed traditional methods in monitoring the freeze-thaw cycle, reducing root mean square errors for the number of freezing days, initial freezing date, and thawing date by 16.75, 6.35, and 12.56 days, respectively. The estimated frozen days correlate well with both the permafrost distribution map and the annual mean ground temperature distribution map. This study offers a practical solution for monitoring the freeze/thaw cycle in alpine zones, providing crucial technical support for studies on regional climate change and land surface processes.

Accurately determining the freeze/thaw state (FT) is crucial for understanding land-atmosphere interactions, with significant implications for climate change, ecological systems, agriculture, and water resource management. This article introduces a novel approach to assess FT dynamics by comparing the new diurnal amplitude variations (DAV) algorithm with the traditional seasonal threshold algorithm (STA) based on the soil moisture active passive (SMAP) brightness temperature data. Utilizing soil temperature profiles from 44 sites recorded by the National Ecological Observatory Network between July 2019 and June 2022. The results reveal that the DAV algorithm demonstrates a remarkable potential for capturing FT signals, achieving an average accuracy of 0.82 (0.89 for the SMAP-FT product) across all sites and a median accuracy of 0.94 (0.92 for the SMAP-FT product) referring to soil temperature at 0.02 m. Notably, the DAV algorithm outperforms the SMAP-adopted STA in 25 out of 44 sites. The accuracy of the DAV algorithm is affected by daily temperature fluctuations and geographical latitudes, while the STA exhibits limitations in certain regions, particularly those with complex terrains or variable climatic patterns. This article's innovative contribution lies in systematically comparing the performance of the DAV and STA algorithms, providing valuable insights into their respective strengths and weaknesses.

Estimating the landscape and soil freeze-thaw (FT) dynamics in the Northern Hemisphere (NH) is crucial for understanding permafrost response to global warming and changes in regional and global carbon budgets. A new framework for surface FT-cycle retrievals using L-band microwave radiometry based on a deep convolutional autoencoder neural network is presented. This framework defines the landscape FT-cycle retrieval as a time-series anomaly detection problem, considering the frozen states as normal and the thawed states as anomalies. The autoencoder retrieves the FT-cycle probabilistically through supervised reconstruction of the brightness temperature (TB) time series using a contrastive loss function that minimizes (maximizes) the reconstruction error for the peak winter (summer). Using the data provided by the Soil Moisture Active Passive (SMAP) satellite, it is demonstrated that the framework learns to isolate the landscape FT states over different land surface types with varying complexities related to the radiometric characteristics of snow cover, lake-ice phenology, and vegetation canopy. The consistency of the retrievals is assessed over Alaska using in situ observations, demonstrating an 11% improvement in accuracy and reduced uncertainties compared to traditional methods that rely on thresholding the normalized polarization ratio (NPR).

The adjacent surcharge caused by improper soil dumping and irregular backfilling poses a huge threat to the safe service of high-speed railway bridge pile foundations in soft soils. In this study, multiple-case field prototype tests including different surcharge distances and loading values and a numerical model embedded with a soft soil material subroutine were carried out to investigate the time-dependent lateral behavior of bridge piles. The timedependent mechanism of pile-soil interaction was revealed by characterizing the variations of the additional lateral load acting on the pile shaft, the soil-arching stress between piles, and the plastic deformation in the soil around piles. The results show that with increasing load duration, the bending moment and deflection of the pile increase gradually, and their distribution is closely related to the thickness and location of the soft soil layer. Furthermore, the horizontal soil-arching between piles underwent the stages of stabilization, local damage, and plastic flow, in which the passive load acting on the pile side continued to increase until it stabilized, resulting in time-dependent lateral deflection of the pile foundation. Consolidation parameters and pile-soil stiffness ratios also have a significant effect on the time-dependent behavior of pile responses. The conclusions obtained can provide a valuable reference for engineering applications to predict the long-term behavior of bridge piles.

The soil moisture active passive (SMAP) satellite mission distributes a product of CO2 flux estimates (SPL4CMDL) derived from a terrestrial carbon flux model, in which SMAP brightness temperatures are assimilated to update soil moisture (SM) and constrain the carbon cyclemodeling. While the SPL4CMDL product has demonstrated promising performance across the continental USA and Australia, a detailed assessment over the arctic and subarctic zones (ASZ) is still missing. In this study, SPL4CMDL net ecosystem exchange (NEE), gross primary production (GPP), and ecosystem respiration (R-E) are evaluated against measurements from 37 eddy covariance towers deployed over the ASZ, spanning from 2015 to 2022. The assessment indicates that the NEE unbiased root-mean-square error falls within the targeted accuracy of 1.6 gC.m(-2).d(-1), as defined for the SPL4CMDL product. However, modeled GPP and R-E are overestimated at the beginning of the growing season over evergreen needleleaf forests and shrublands, while being underestimated over grasslands. Discrepancies are also found in the annual net CO2 budgets. SM appears to have a minimal influence on the GPP and R-E modeling, suggesting that ASZ vegetation is rarely subjected to hydric stress, which contradicts some recent studies. These results highlight the need for further carbon cycle process understanding and model refinements to improve the SPL4CMDL CO2 flux estimatesover the ASZ.