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Abstract A probabilistic limit equilibrium framework combining empirical load transfer factor and anisotropy of soil cohesion is developed to conduct pile‐reinforced slope reliability analysis. The anisotropy of soil cohesion is determined conditioned on that the thrust force direction is parallel to the major principal direction and it is easily combined with load transfer factor, which are related with soil parameters, and pile parameters. The proposed method is illustrated against a homogeneous soil slope. The sensitivity studies of pile parameters on factor of safety (FS; calculated at respective means of soil parameters) and β demonstrated that the anisotropy of soil cohesion tends to pose significant effect on reliability index β than on FS. The effect of anisotropy of soil cohesion on FS is found to be slightly different under different pile locations, whereas its effect on β is observed to be least if piles are drilled at the middle part of slope and more significant effect is observed when piles are drilled at the lower and upper part of slope. The plots from the sensitivity studies provide an alternative tool for pile designs aiming at the target reliability index β. The proposed method contributes to the pile‐reinforced slope stability within limit equilibrium framework.

The Qianchuiliu Gold Deposit on the northeastern margin of the Jiaolai Basin is a newly discoverd altered rock type gold deposit, and is a medium-sized gold deposit hosted in the structural alteration zone between Muniushan, Jingshan Group and Queshan monzonitic granites. However, the source of ore-forming materials and the ore genesis are not clear. Based on previous field and analytical studies, the authors conducted sulfur and lead isotopic analyses on gold-bearing pyrite from typical ores as the research target. The δ34S values are high and homogeneous ranging from 10.13‰-12.39‰, with an average of 10.98‰ and polar odds of 2.26‰. These sulfur isotopic results reveal a mixing process of sulfur in the Jingshan Group during the upwelling of deep ore-forming fluid. The ratios of 206Pb/204Pb, 207Pb/204Pb, and 208Pb/204Pb vary from 17.149-18.886, 15.482-15.677, and 37.860-40.073, respectively, suggesting a crust-mantle mixed source. In conclusion, sulfur and lead isotope analysis results of the Qianchuiliu Gold Deposit show a crust-mantle mixed source and are similar to those of typical gold deposits in this region. The gold deposits on the northeastern margin of the Jiaolai Basin formed at the large-scale Yanshanian metallogenic event, indicating great prospecting potential in this area.

Abstract This paper presents a framework combining Monte Carlo Simulation (MCS) and the Newmark sliding block model with representative slip surfaces (RSS) (model II) and multiple response surfaces method (MRSM) to conduct seismic reliability analysis and risk assessment of soil slopes. An empirical threshold is introduced to define the limit state function to identify the failure samples in MCS and the sliding area and Newmark sliding displacement are multiplied to quantify the failure consequence. The proposed methodology is illustrated through a soil slope with multiple layers. The calculation results demonstrate that traditional Newmark sliding block model (model I) tend to underestimate the variations of yield acceleration. Both the failure probability and landslide risk exhibit decreasing trends with the increase of threshold. Significant discrepancy in failure probability and landslide risk between two models is found even for a small threshold. Therefore, the proposed methodology is highly recommended in seismic reliability analysis and risk assessment. The contributions of RSSs to the failure probability and landslide risk are insensitive to the variation of displacement thresholds.

In the context of global warming, the sustainability of farmland ecosystems is increasingly impacted by multiple disturbances from both natural and human-induced sources. This study constructed a conceptual model and indicator system of farmland ecosystem resilience (FER) based on the disturbance-response processes of farmland ecosystems. FER assessment, supported by 30 specific indicators, was tested in Ethiopia, one of the most food-insecure countries in the world and the factors impending farmland ecosystem sustainability were discussed based on the obstacle degree values (ODVs). The results showed that the FER change rate in Ethiopia was 0.3 %/year during 2003–2018, indicating positive sustainability on the whole. However, in the five years of 2004, 2007, 2008, 2011, and 2017, the FER decreased, among which the largest decline was −0.017 in 2017. Natural comprehensive disturbance (ND), human activity disturbance (HD), resilience of farmland supply (RFS), and resilience of social support (RS) were the key constraints of FER, while the ODVs of ND and RFS showed increasing trends. We also found that there were general antagonistic and synergistic effects among the response factors and the synergistic enhancement between disturbance factors was more pronounced than the antagonistic buffering effect. This study provides a fresh perspective for farmland ecosystem managers and stakeholders to examine disturbance risks and assess the sustainability of farmland ecosystems.

For deep resource exploitation and engineering construction, the mechanical properties of soft and hard interbedded rock masses are important factors impacting engineering stability. Simultaneously, the influence of temperature on the strength of deep rock masses poses a significant obstacle to the exploitation of deep resources and the utilization of underground space. In this paper, the particle flow code (PFC2D) is utilized to establish the thermal-mechanical coupling numerical model of soft and hard interbedded rock masses, and then the uniaxial compression response of soft and hard interbedded rock masses following thermal damage is studied. The displacement and contact force produced by applying temperature, as well as the failure strength, strain, and crack development of the specimen after uniaxial compression is analyzed. The findings reveal that: 1) The peak displacement caused by applied temperature increases first and subsequently decreases with the increase of soft rock thickness ratio (Hs/H), whereas the peak displacement increases linearly with increasing temperature. The peak contact force varies in two stages with the increase of the soft rock thickness ratio (Hs/H), and with the same trends. 2) As the soft rock thickness ratio increases (Hs/H), the number of cracks decreases steadily. When the soft rock thickness ratio Hs/H < 0.5, the relationship curve between vertical strain and crack changes in two stages: the stage of crack development along with the stage of vertical strain gradually increases with crack development. When the thickness ratio of soft rock Hs/H > 0.5, the relationship curve changes in three stages: crack development stage, vertical strain increase stage, and vertical strain increase stage with crack development. 3) When the soft rock thickness ratio Hs/H < 0.5, the failure strength gradually decreases as soft rock thickness increases at T = 100°C, 200°C. The failure strength gradually increases as the soft rock thickness increases in general at T = 400°C. Soft rock thickness ratio Hs/H > 0.5, the failure strength increases with the increase of soft rock thickness at T = 300°C, 400°C. At T = 100°C, 200°C, the tendency of the failure strength changes less.

With the shortage of land resources, there has been a trend toward increasingly deep foundation pit engineering in urban areas. It is extremely important to reflect on the behavior and safety of deep foundation pits and conduct risk assessments in time. A nonhomologous and multi-indicator deep foundation pit risk assessment model was studied for nine types of nonhomologous on-site data monitored in the deep foundation pit. Based on the BIM (Building Information Modeling) technology, a family of monitored points was created that reflects the information on site from a deep foundation pit. The data visualization module was redeveloped by using Visual Studio 2019 to map the on-site data monitored to the components in the BIM model, which can visualize the data monitored in the BIM model of deep foundation pits. On this basis, the assessment of the safety level of deep foundation pits was realized in combination with a risk assessment model. Through the instance of the deep foundation pit of Zibo light rail, the analysis shows that the new visualization and risk assessment method can help construction workers locate dangerous units and formulate corresponding prevention and control measures better and faster.

The movement of the ground caused by the excavation of subway tunnels and the sinking of the earth's surface inevitably affect above-ground buildings, with the impact on historical and cultural buildings, which are already in disrepair, being more prominent. In existing research, the impact of the stiffness of a building itself is often neglected when assessing the influence of the displacement of the stratum caused by tunnel excavation on the building. However, as the settlement and deformation of the building are related to the structural characteristics of the building itself, the effect of the building stiffness should not be completely ignored. This study analyzed the case of the national key protected cultural relics (Red House Hotel) located near the tunnel of the Qingdao Metro (Line 3). Based on the factors affecting the stiffness of the building structure, the Peck empirical formula was modified to predict the effect on the building in the stratum. Subsequently, a three-dimensional finite element model was established and force analysis conducted. Considering the results of the finite element analysis, which determined the stress condition of the cultural relic buildings, a reinforcement design was carried out and implemented in the project.

In this paper, the sensitivity factors of CO2 huff-n-puff for multifractured horizontal wells (MFHWs) in tight oil reservoirs were investigated through an experimental test and numerical simulation. The pressure-volume-temperature (PVT) experiment and the slim tube experiment are used to understand the interaction mechanism between CO2 and crude oil, and the minimum miscibility pressure (MMP) of the CO2-crude oil system is 17 MPa. The single-well model was firstly established to analyze the sensitivity factors on production performance of MFHWs by using CO2 huff-n-puff. The controlling factors of CO2 huff-n-puff for MFHWs in tight oil reservoirs were divided into three categories (i.e., reservoir parameters, well parameters, and injection-production parameters), and the impact of individual parameter on well performance was discussed in detail. The range of reservoir parameters suitable for CO2 huff-n-puff of MFHWs is obtained. The reservoir permeability is from 0.1 mD to 1 mD, the reservoir thickness changes from 10 m to 30 m, and the reservoir porosity is from 7% to 12%. Based on the reservoir parameters of the target reservoir, the reasonable well and fracture parameters are obtained. The sensitivity intensity was followed by the horizontal well length, fracture conductivity, fracture spacing, and fracture half-length. CO2 injection-production parameters are further optimized, and the sensitivity intensity was followed by the single-cycle cumulative CO2 injection rate, the soaking time, the injection rates, and the production rates. It provides a reference for parameter optimization of CO2 huff-n-puff for MFHWs in tight oil reservoirs.

The electric power distribution grid directly serves the ordinary users, the stability and reliability of which are crucial to production and life. The traditional operation and maintenance of the distribution grid is based on experience and cannot scientifically predict the state of line faults. In this paper, stepwise regression is used to screen out 8 key influencing factors of line faults, and principal component analysis is performed to find the risk value of each line; so that establishes multiple linear and exponential regression equations for the line risk value. According to the existing data, the risk of the line is predicted, and the GABP neural network model is built so as to accurately predict the risk value of the line.

The electric power distribution grid is directly oriented to the majority of the ordinary users. Traditional operation and maintenance are performed mainly based on experience, which disable to rationally evaluate the status of the line and predict faults. Based on big data, the risk of the line is evaluated through principal component analysis in this paper, so that a machine learning algorithm is carried out to calculate the risk value of the distribution grid line unit. Finally, GA-BP neural network is used to build a line risk value prediction model for improvement.

Land Use/Cover Change (LUCC) has gradually became an important direction in the research of global changes. LUCC is a complex system, and entropy is a measure of the degree of disorder of a system. According to land use information entropy, this paper analyzes changes in land use from the perspective of the system. Research on the entropy of LUCC structures has a certain “guiding role” for the optimization and adjustment of regional land use structure. Based on the five periods of LUCC data from the year of 1990 to 2010, this paper focuses on analyzing three types of LUCC entropies among counties in China—namely, Shannon, Renyi, and Tsallis entropies. The findings suggest that: (1) Shannon entropy can reflect the volatility of the LUCC, that Renyi and Tsallis entropies also have this function when their parameter has a positive value, and that Renyi and Tsallis entropies can reflect the extreme case of the LUCC when their parameter has a negative value.; (2) The entropy of China’s LUCC is uneven in time and space distributions, and that there is a large trend during 1990–2010, the central region generally has high entropy in space.

Abstract As the size of wind turbine blades increases, the flexibility of the blades increases. In actual operation, airflow flow can cause aerodynamic elastic instability of the blade structure. Long blades may experience coupled mode flutter due to the bending torsion coupling effect, leading to blade failure. Based on Euler Bernoulli beam theory combined with Theodorsen non directional aerodynamic loads, a blade flutter characteristic equation is established through finite element method. Taking NREL 5 MW wind turbine blades as an example, analyze the influence of parameter changes in different regions of the blades on flutter characteristics. Research has found that paramter changes in the tip region of blade have the greatest impact on flutter characteristics. The vibration frequency shows an overall upward trend with the increase of waving stiffness and torsional stiffness. The flutter velocity of the three regions tends to stabilize as the bending stiffness decreases. The blade flutter speed increases with the increase of torsional stiffness. The radius of gyration is inversely proportional to the flutter frequency and flutter velocity. The impact of centroid offset on blade structure flutter frequency is minimal, but the centroid offset in the tip region has a greater impact on flutter velocity. Increasing the torsional frequency can prevent coupled mode flutter and provide a theoretical basis for blade flutter prevention design.