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Hydraulic structures are typically subjected to long-term hydraulic loading, and concrete—the main material of structures—may suffer from cracking damage and seepage failure, which can threaten the safety of hydraulic structures. In order to assess the safety of hydraulic concrete structures and realize the accurate analysis of the whole failure process of hydraulic concrete structures under the coupling effect of seepage and stress, it is vital to comprehend the variation law of concrete permeability coefficients under complex stress states. In this paper, several concrete samples were prepared, designed for loading conditions of confining pressures and seepage pressures in the first stage, and axial pressures in the later stage, to carry out the permeability experiment of concrete materials under multi-axial loading, followed by the relationships between the permeability coefficients and axial strain, and the confining and seepage pressures were revealed accordingly. In addition, during the application of axial pressure, the whole process of seepage–stress coupling was divided into four stages, describing the permeability variation law of each stage and analyzing the causes of its formation. The exponential relationship between the permeability coefficient and volume strain was established, which can serve as a scientific basis for the determination of permeability coefficients in the analysis of the whole failure process of concrete seepage–stress coupling. Finally, this relationship formula was applied to numerical simulation to verify the applicability of the above experimental results in the numerical simulation analysis of concrete seepage–stress coupling.

The deformation instability of surrounding rock and the collapse of rock blocks are two common failure modes observed during the construction of underground caverns. Therefore, a comprehensive safety evaluation method (CSEM) of surrounding rock for application during underground cavern construction is presented in this paper. The method can be used to evaluate the deformation stability of surrounding rock and predict the collapse of rock blocks, rapidly. First, a deformation stability prediction and evaluation method (DSPEM) for rock mass is established. It combines the safety evaluation method based on a deformation statistical analysis and an inverse deformation prediction method using measured deformation data of surrounding rock. This approach possesses the unique characteristics of complementary and mutual verification. In addition, a comprehensive early-warning index system (CWIS) for assessing the deformation stability of surrounding rock is presented. It consists of three types of warning indicators and three levels of warning values. The early-warning values can be adjusted reasonably by the prediction correction method according to the measured displacements. For the collapse of rock blocks controlled by structural surfaces, a rapid prediction method of rock block collapse (RPMBC) based on the block theory is then presented. Finally, combining the DSPEM, RPMBC, and CWIS, the CSEM of surrounding rock for assessing the safety of cavern construction is established. It can provide technical support for decision making on the safety of surrounding rock during the construction of underground caverns.

The 300 m-level high arch dams built in China have different degrees of valley-narrowing deformation in the initial impoundment. This unexpected phenomenon may increase the long-term safety risk of high arch dams. There are several explanations for the valley-narrowing deformation phenomenon, and one of the explanations—that it is caused by a drop in bedrock temperature—is still under debate. In this paper, coupled thermo-hydromechanical (THM) simulations of the temporal and spatial evolutions of the bedrock temperature and seepage fields of the Xiluodu arch dam site were performed. The results showed that the mechanism of the bedrock temperature drop after impoundment can be divided into two types: short-term type and long-term. For the short-term type, the maximum temperature drop of 9 °C is caused by the heat exchange between the bedrock surface layer and the reservoir water during the initial impoundment. For the long-term type, the maximum temperature drop of 15 °C in front of the grouted curtain is caused by the long-term infiltration of cold water from upstream to downstream bypassing the grout curtain. The monitoring data showed that the valley-narrowing deformation mainly occurred in the initial impoundment, which corresponds to the short-term type. Notably, the valley-narrowing deformation may be overestimated if the long-term type of bedrock temperature drop is considered. Taken together, these findings demonstrate that the bedrock temperature change due to impoundment is dominated by the short-term type and can be applied to study the effect of temperature on valley-narrowing deformation after impounding.

The key to the dam damage assessment is analyzing the remaining seismic carrying capacity after an earthquake occurs. In this paper, taking Koyna concrete gravity dam as the object of study, the dynamic response and damage distribution of the dam are obtained based on the concrete damage plastic constitutive model. By using time-frequency localization performance of wavelet transform, the distribution characteristics of wavelet energy for gravity dam dynamic response signal are revealed under the action of different amplitude earthquakes. It is concluded by numerical study that the wavelet energy is concentrated in low-frequency range with the improving of seismic amplitude. The ultimate peak seismic acceleration is obtained according to the concentration degree of low-frequency energy. The earthquake damage of the dam under the moderate-intensity earthquake is simulated and its residual seismic bearing capacity is further analyzed. The new global damage index of the dam is proposed and the overall damage degree of the dam can be distinguished using defined formula under given earthquake actions. The seismic bearing capacity of the intact Koyna dam is 591 gal considering the dam-water interaction and its residual seismic bearing capacity after simulating earthquake can be calculated.

Context: Individuals with type 2 diabetes mellitus (DM) have an increased risk of pneumonia and septic shock. Traditional glucose-lowering drugs have recently been found to be associated with a higher risk of infections. It remains unclear whether sodium-glucose cotransporter 2 inhibitors (SGLT2is), which have pleiotropic/anti-inflammatory effects, may reduce the risk of pneumonia and septic shock in DM. Methods: MEDLINE, Embase, and ClinicalTrials.gov were searched from inception up to May 19, 2022, for randomized, placebo-controlled trials of SGLT2i that included patients with DM and reported outcomes of interest (pneumonia and/or septic shock). Study selection, data extraction, and quality assessment (using the Cochrane Risk of Bias Assessment Tool) were conducted by independent authors. A fixed-effects model was used to pool the relative risk (RRs) and 95% CI across trials. Results: Out of 4568 citations, 26 trials with a total of 59 264 patients (1.9% developed pneumonia and 0.2% developed septic shock) were included. Compared with placebo, SGLT2is significantly reduced the risk of pneumonia (pooled RR 0.87, 95% CI 0.78-0.98) and septic shock (pooled RR 0.65, 95% CI 0.44-0.95). There was no significant heterogeneity of effect size among trials. Subgroup analyses according to the type of SGLT2i used, baseline comorbidities, glycemic control, duration of DM, and trial follow-up showed consistent results without evidence of significant treatment-by-subgroup heterogeneity (all Pheterogeneity>.10). Conclusion: Among DM patients, SGLT2is reduced the risk of pneumonia and septic shock compared with placebo. Our findings should be viewed as hypothesis generating, with concepts requiring validation in future studies. [ABSTRACT FROM AUTHOR]

Soil-rock mixture (SRM) filling in fault zone is an inhomogeneous geomaterial, which is composed of soil and rock block. It controls the deformation and stability of the abutment and dam foundation, and threatens the long-term safety of high arch dams. To study the macroscopic and mesoscopic mechanical properties of SRM, the development of a viable mesoscopic numerical simulation method with a mesoscopic model generation technology, and a reasonable parametric model is crucially desired to overcome the limitations of experimental conditions, specimen dimensions, and experiment fund. To this end, this study presents a mesoscopic numerical method for simulating the mechanical behavior of SRM by proposing mesoscopic model generation technology based on its mesostructure features, and a rock parameter model considering size effect. The validity and rationality of the presented mesoscopic numerical method is experimentally verified by the triaxial compression tests with different rock block contents (RBC). The results indicate that the rock block can increase the strength of SRM, and it is proved that the random generation technique and the rock parameter model considering size effect are validated. Furthermore, there are multiple failure surfaces for inhomogeneous geomaterial of SRM, and the angle of the failure zone is no longer 45°. The yielding zones of the specimen are more likely to occur in thin sections of soil matrix isolated by blocks with the failure path avoiding the rock block. The proposed numerical method is effective to investigate the meso-damage mechanism of SRM. [ABSTRACT FROM AUTHOR]

The Impact Echo (IE) method is a widely used method for the detection of concrete structures. The signal has non-stationary characteristics. Empirical mode decomposition (EMD) is one of the typical ways of dealing with non-stationary signals. Due to EMD having mode overlap and a breakpoint effect, Variational Mode Decomposition (VMD) has been proposed to overcome these problems. In this study, VMD is introduced into the analysis of the concrete component detection signals, and the impact echo analysis method based on VMD and marginal spectrum is established. The proposed method to solve the marginal spectrum is used in order to analyze the numerical simulation model's IE signal. This method is able to correctly obtain the main frequency. When compared with the traditional Fourier spectrum, the marginal spectrum that is based on the VMD method shows that the band width that is present in the main frequency is narrow. Even in the presence of a highly noisy background, the method is able to correctly obtain the main frequency. At last, through the detection signal analysis of the non-defective concrete specimen and the concrete specimen with the circular hole, the results show that the proposed method can distinguish the signal in the different defective states of the concrete structures, which has obvious advantages compared with the Fourier spectrum. [ABSTRACT FROM AUTHOR]

This study proposes a sensitivity analysis method for slope stability based on the least squares support vector machine (LS-SVM) to examine tire influencing factors of slope stability. The method uses LS-SVM as an algorithm for machine learning. An appropriate training dataset is established according to the slope characteristics, and a testing dataset is designed orthogonally. Results of the testing data in the experiment design are calculated after training using tire LS-SVM model. The sensitivity of the slope stability of each factor is examined via gray con-elation analysis. The results are consistent with those of the traditional Bishop analysis and can be used as a reference for optimizing slope design. [ABSTRACT FROM AUTHOR]

Low strain dynamic testing is an important nondestructive testing method in the engineering. However, the pile foundation material is usually assumed as having a uniform elastic modulus in low strain simulations. In this paper, we consider the elastic modulus of concrete as having an inhomogeneous elastic modulus that is described by the Weibull distribution model. An explicit algorithm was adopted in order to solve the model. The finite element method (FEM) was used to simulate the low strain dynamic test of a 3D pile. The response velocity characteristics of different shape parameters were obtained using this method, and the Daubechies wavelet transform was used to analyze the characteristics of the wavelet modulus. The result shows that simulation response velocity has a correlation with the different homogeneity of the elastic modulus. [ABSTRACT FROM AUTHOR]

Low strain detection, an indirect and nondestructive testing method, is one of the main pile integrity testing methods. We propose low strain testing analysis based on a synchrosqueezing wavelet transformation (SST). Through a typical model pile test, the SST is applied to identify pile bottom signal reflection time and to separate signal from noise. It is also compared with the conventional wavelet de-noising and the empirical mode decomposition (EMD) de-noising method. Results show that the SST technique can be used to identify the reflected signal of the pile bottom, achieve signal and noise separation, and improve signal-to-noise ratio. The method has significant advantage in low strain detection signal processing compared to other methods. [ABSTRACT FROM AUTHOR]

Compared with conventional time-frequency analysis method, synchrosqueezing wavelet transformation (SST) exhibits high resolution capability and good application effect. In this study, SST is introduced to ground-penetrating radar (GPR) processing. This method is applied to analyze a continuous electromagnetic signal. SST can obtain a higher resolution and a better processing effect than conventional wavelet transform and short-time Fourier analysis. In the application of GPR forward analysis data, the transform can correctly distinguish different interfaces and objects. Its resolution increases as frequency increases. However, compression wavelet modulus gradually decays as frequency increases. The proposed method is applied to detect tunnel lining under actual conditions and in a strong noise background. Indeed, the method can efficiently identify interfaces and abnormalities. [ABSTRACT FROM AUTHOR]

The numerical evaluation of high-order modes of a uniform Euler-Bernoulli beam has been studied by reformatting the classical expression of mode shapes. That method, however, is inapplicable to a stepped beam due to the nonuniform expressions of the mode shape for each beam segment. Given that concern, this study develops an alternative method for the numerical evaluation of high-order modes for stepped beams. This method effectively expands the space of high-order modal solutions by introducing local coordinate systems to replace the conventional global coordinate system. This set of local coordinate systems can significantly simplify the frequency determinant of vibration equations of a stepped beam, in turn, largely eliminating numerical round-off errors and conducive to high-order mode evaluation. The efficacy of the proposed scheme is validated using various models of Euler-Bernoulli stepped beams. The principle of the method has the potential for extension to other types of Euler-Bernoulli beams with discontinuities in material and geometry. (The Matlab code for the numerical evaluation of high-order modes for stepped beams can be provided by the corresponding author upon request.) [ABSTRACT FROM AUTHOR]

An improved neuro-wavelet modeling (NWM) methodology is presented, and it aims at improving prediction precision of time-varying behavior of engineering structures. The proposed methodology distinguishes from the existing NWM methodology by featuring the distinctive capabilities of constructing optimally uncoupled dynamic subsystems in light of the redundant Haar wavelet transform (RHWT) and optimizing neural network. In particular, two techniques of imitating wavelet packet transform of RHWT and reconstructing the major crests of power spectrum of analyzed data are developed with the aim of constructing the optimally uncoupled dynamic subsystems from time-varying data. The resulting uncoupled dynamic subsystems make the underlying dynamic law of time-varying behavior more tractable than the raw scale subwaves arose from the RHWT, and they provide a platform for multiscale modeling via individual modeling at the uncoupled dynamic subsystem level. Furthermore, on each uncoupled dynamic subsystem, the technique of optimal brain surgeon in conjunction with a new dynamic mechanism refreshing is employed to optimize the neural network, and the recombination of the modeling outcomes on every subsystem constitutes the overall modeling of time-varying behavior. The improved NMW methodology offers a feasible framework of multiscale modeling due to its flexibility, adaptability and rationality, and it is particularly useful for prediction applications of time-varying behavior of engineering structures. As an illustrative example, the improved NWM methodology is applied to model and forecast dam deformation, and the results show that the methodology possesses positive advantages over the existing multiscale and single scale modeling techniques. The improved NMW methodology is promising and valuable for the safety monitoring and extreme event warning of engineering structures. [ABSTRACT FROM AUTHOR]