Coupling dynamic response of saturated soil with anisotropic thermal conductivity under fractional order thermoelastic theory.

In this paper, a two-dimensional (2D) thermo-hydro-mechanical dynamic (THMD) coupling analysis in the presence of a half-space medium is studied using Ezzat's fractional order generalized theory of thermoelasticity. Using normal mode analysis (NMA), the influence of the anisotropy of the thermal conduction coefficient, fractional derivatives, and frequency on the THMD response of anisotropy, fully saturated, and poroelastic subgrade is then analyzed with a time-harmonic load including mechanical load and thermal source subjected to the surface. The general relationships among the dimensionless physical variables such as the vertical displacement, excess pore water pressure, vertical stress, and temperature distribution are graphically illustrated. The NMA method does not require the integration and inverse transformation, increases the decoupling speed, and eliminates the limitation of numerical inverse transformation. The obtained results can guide the geotechnical engineering construction according to different values of load frequency, fractional order coefficient, and anisotropy of thermal conduction coefficient. This improves the subgrade stability and enriches the theoretical studies on thermo-hydro-mechanical coupling.

Coupled processes of groundwater dynamics and land subsidence in the context of active human intervention, a case in Tianjin, China.

To address the crisis of water shortage in the North China Plain, the Chinese government implemented the South-to-North Water Transfer Project (SNWTP). In this context, Tianjin, one of the main beneficiaries of this project, has been relieved from water shortages and begun to implement Groundwater Management Plans (GMP) since 2018, which undoubtedly have a significant effect on the groundwater recovery. Meanwhile, this provides a good case for studying the coupled process of ground settlement and groundwater dynamics, especially the soil deformation pattern driven by groundwater level (GWL) rebound. To analyze these issues in detail, field well data was collected to depict groundwater flow field. Moreover, geodetic data was also collated, including leveling, GPS, and InSAR, so that a vertical deformation field with high spatiotemporal resolution could be generated. The results reveal that the GWL of the third confined aquifer which is the main exploitation layer in Tianjin recovered significantly since 2018 with a rate of 2.1 m/yr. The dynamic deformation patterns indicate that the area of land subsidence cones in Tianjin has reduced significantly, accompanied by a sharply declining subsidence rate (decreased from -32.2 mm/yr to -4.5 mm/yr.). Particularly, a significant poroelastic rebound has occurred in the Wuqing and Beichen districts since 2020. Furthermore, due to the delayed pore pressure dissipation in the aquitard, we find a time delay of 0.3-5.5 years between land subsidence and GWL time series, which is far less than that estimated by hydrogeological parameters, as the latter ignored the recharge and recovery capacity of the aquifer system. Finally, an evolution models in Tianjin was presented to illustrate interactive process among the deformation, pore pressure, and hydraulic head. In general, the SNWDP and the GMP has restored the pore pressure of aquifer, reduced the land subsidence, and alleviated the groundwater storage depletion of Tianjin.

Operational Modal Analysis of Bridge Structures with Data from GNSS/Accelerometer Measurements.

Real-time dynamic displacement and acceleration responses of the main span section of the Tianjin Fumin Bridge in China under ambient excitation were tested using a Global Navigation Satellite System (GNSS) dynamic deformation monitoring system and an acceleration sensor vibration test system. Considering the close relationship between the GNSS multipath errors and measurement environment in combination with the noise reduction characteristics of different filtering algorithms, the researchers proposed an AFEC mixed filtering algorithm, which is an combination of autocorrelation function-based empirical mode decomposition (EMD) and Chebyshev mixed filtering to extract the real vibration displacement of the bridge structure after system error correction and filtering de-noising of signals collected by the GNSS. The proposed AFEC mixed filtering algorithm had high accuracy (1 mm) of real displacement at the elevation direction. Next, the traditional random decrement technique (used mainly for stationary random processes) was expanded to non-stationary random processes. Combining the expanded random decrement technique (RDT) and autoregressive moving average model (ARMA), the modal frequency of the bridge structural system was extracted using an expanded ARMA_RDT modal identification method, which was compared with the power spectrum analysis results of the acceleration signal and finite element analysis results. Identification results demonstrated that the proposed algorithm is applicable to analyze the dynamic displacement monitoring data of real bridge structures under ambient excitation and could identify the first five orders of the inherent frequencies of the structural system accurately. The identification error of the inherent frequency was smaller than 6%, indicating the high identification accuracy of the proposed algorithm. Furthermore, the GNSS dynamic deformation monitoring method can be used to monitor dynamic displacement and identify the modal parameters of bridge structures. The GNSS can monitor the working state of bridges effectively and accurately. Research results can provide references to evaluate the bearing capacity, safety performance, and durability of bridge structures during operation.