Zhongmei Wang

The presence of fluorine and phosphorus in phosphogypsum leachate directly affects the local ecological environment and groundwater quality. This paper examined the adsorption characteristics of fluorine and phosphorus by red clay near a phosphogypsum landfill in Guizhou Province, China, under different pH values, initial concentrations, soil dosages, and particle sizes of the soil. Response surface methodology (RSM) was employed to optimize the three factors (pH, initial concentration, and soil dosage) selected by Box-Behnken design that have a great influence on single-factor adsorption. The optimum condition for the adsorption of fluorine by red clay was identified as pH = 3, initial concentration of 91.08 mg/L, and soil dosage of 5.31 g, while that for the adsorption of phosphorus by red clay was pH = 4.17, initial concentration of 99.49 mg/L, and soil dosage of 5.82 g. The Langmuir equation, the quasi-secondary kinetic model, and the Elovich model were used for fitting, which demonstrated good fitting. Finally, comparing the characterization results of scanning electron microscopy (SEM-EDX), X-ray diffraction (XRD), and infrared spectroscopy (FTIR), the adsorption process of red clay on fluorine and phosphorus was accompanied by electrostatic adsorption in addition to chemical adsorption and ligand exchange, which was the result of multiple adsorption effects. The findings of this study will provide a reference for the prevention, control, and management of fluoro-phosphorus pollution in phosphogypsum dumps.

This paper proposes a new prediction method for damages such as spalling and wear of heavy haul railways caused and deteriorated easily by the continuous rail-wheel contact during the high intensity and heavy load transportation. Based on the combined model of PCA and TCN-Attention, it is capable of accurately predicting the deterioration trend of spalling damage for heavy haul railways. Firstly, a feature set with high dimension is constructed with the features of time domain and frequency domain extracted from the original vibration signal of rail damage. Secondly, PCA is used to reduce the dimension of the high-dimensional feature set of rail damages. The first principal component is used as the health indicator of rail damages. Further, the TCN-Attention model is adopted to predict the deterioration trend of the rail spalling damage. Finally, the feasibility of the proposed method is verified by using the vibration data of the life cycle of a rail track, from normal working to damaged to failure, collected from a railway depot. The results of the proposed method are also compared with those of prediction models constructed by TCN, LSTM and GRU networks. The comparison shows that the proposed method has better performance and higher prediction accuracy. The proposed method can more accurately predict the deterioration trend of the rail spalling damage.

The surface nuclear magnetic resonance (SNMR) method is widely used in groundwater detection because of its sensitivity to hydrogen in water and direct water detection. However, low signal‐to‐noise ratios (SNR) restrict the development of this technique. An optimum pulse sequence is designed according to correspondence between the pulse moment strength and its best detection depth. Because only selection of the pulse intensity distribution according to the target aquifer depth is required and the “on‐resonance” pulse pattern is still employed, this pulse sequence emission can be easily achieved using existing SNMR instrumentation. Numerical simulation results and field experiments show that, compared with traditional exponential growth pulses, the optimum pulse sequence effectively improves the SNR of the SNMR method. The aquifer boundary, water content, and pore characteristics of the inversion result are thus more consistent with characteristics of underground structures. Additionally, because the optimum pulse sequence focuses most of the pulse moments in the target depth range, in situations where two aquifers are separated by a relatively narrow aquitard, it is better able to resolve the individual aquifers than the traditional pulses. Optimum pulse moments improve the SNR by enhancing the signal amplitude, compared with various filtering methods, and obtain a better detection effect. This kind of pulse sequence can be used as an alternative pulse sequence form of the SNMR method.

Expansive sulfate-bearing soils are frequently encountered in transportation and construction practices. These soils are often treated with a lime or cement stabilizer to improve the relevant qualities. However, the reaction between sulfate and alumina in soils and calcium of lime or cement can lead to the formation of ettringite, an expansive sulfate mineral resulting in soil swelling or heaving. The underlying mechanisms often involve intricate interactions between chemical processes and mechanical responses. The present study explores a chemo–mechanical approach in an attempt to quantify several mechanisms potentially responsible for the volume expansion, including the geochemical formation of ettringite, crystallization pressure, and osmosis-induced swelling. The geochemical reaction leading to ettringite formation is examined with a specific focus on the circumstances under which it may lead to volume change. The crystallization pressure developed during the ettringite formation may also play a significant role in the soil expansion and is investigated in the present study based on thermodynamic formulations, and the resulting volume expansion is simulated. The osmosis-induced swelling is studied within the context of the chemo–mechanical framework, and its kinetics is also explored. Numerical simulations are performed in the present study to examine different scenarios driven by distinct predominant mechanisms. In particular, the interplay between ettringite formation and osmosis swelling as interpreted from some recently-reported experimental studies shows that these mechanisms can all contribute to the observed expansion processes, and overall, the modeling results are consistent with the experimental findings.

Sinkholes are a devastating and widespread geo-hazard which poses a significant threat to the environment, infrastructure, and human lives. Many practices involved in the sinkhole assessment are generally of a qualitative nature and largely based on geological characteristics of the karst terrains. This paper aims to present a quantitative analysis of the deformation involving the various behaviors of the geo-materials and interplay of multiple mechanisms involved during the development of sinkholes. It is primarily focused on the influence of rapid and slow drawdown of water scenarios, studied via a coupled hydromechanical model. Rapid drawdown at a higher rate of head drop causes much higher deformation than the slower drawdown which may lead to fast creation of sinkhole. A parametric study of various properties responsible for the sinkhole development is undertaken which involves influence of cohesion, permeability and ground water flow time. The results shows that the higher permeability and higher ground water flow time causes rapid formation of sinkhole. The resistance to the sinkhole formation in the limestone zone is a function of the tensile strength of the rock while the cohesion and friction angle are responsible for the resistance in the clay soil.

Sinkhole is a hazardous geological phenomenon which in recent years has occurred with an alarmingly increased frequency around the world. Although the conceptual nature of the involved key mechanisms of formation of the sinkhole is well-known and is believed to be related to the interaction between the underlying limestone rock layer and the groundwater subsequently leading to the accumulated deformation in the soil overlaying the weakened rocks, there has not been an adequate amount of geomechanical research devoted to the study of sinkholes in a quantitative manner. This paper presents some of the preliminary results of an ongoing research aimed to explore a geo-mechanical modelling approach and to understand the behavior of geo-materials around sinkholes. The finite difference program, FLAC, is used to model the behavior of geo-materials involved and simulate the deformation and stress characteristics of sinkholes. A parametric study is conducted to examine the results with different sizes of cavity, overburden thickness and pressure. The potential scenario of water drawdown is also examined. The results demonstrate some key characteristics of sinkhole subsidence and the feasibility of a geomechanical approach manifested in numerical modelling to improve the understanding of the process of sinkhole development.