The importance analysis of expert diagnosis indexes in the safety evaluation of concrete dam

The influencing factors on the evaluation of concrete dam safety are rather complex, which can be divided into quantitative indexes and qualitative indexes and has the characteristic of fuzziness and uncertainty. Expert diagnosis provides positive effect in the comprehensive evaluation of concrete dam safety, and the evaluation result rely on the experiences and wisdom of experts. The importance analysis of experts in the safety evaluation of concrete dams was performed to have fine evaluation result. Subjective expert important analysis model and objective expert importance model were established, and then the interactive objectivity and subjectivity importance analysis model was established. In the end, there proposed models were performed in the safety evaluation of a concrete dam, and the models were verified to be effective in the importance analysis of experts in the evaluation of concrete dam safety

The Analysis of the Concrete Gravity Dam’s Foundation Uplift Pressure under the Function of Typhoon

How to evaluate the seepage safety status of the concrete gravity dam under the function of short-period heavy rainfall and the possible historical extreme reservoir water level during typhoon is an important issue considering the dam safety-monitoring. Based on analysis of the monitoring series of the foundation uplift pressure, this paper assumed the influential process of antecedent reservoir water level and rainfall as a process of normal distribution and introduced the mutation factor to reflect the uprush feature of uplift pressure under the function of high-influential typhoon. Moreover, the corresponding hysteresis days and influential days of the model are optimized with quantum genetic algorithm (QGA) to raise the fitting and prediction accuracy. It is verified that the new statistical model for fitting can obtain higher multiple correlation coefficient (0.972) compared with the traditional statistical model (0.925) and could also perfectly predict the uprush feature of the pressure during the typhoon, which is of certain theoretical and practical application value in the future

Seepage Monitoring Models Study of Earth-Rock Dams Influenced by Rainstorms

For earth-rock dams influenced by rainstorms, seepage status monitoring is very important and provides the basis for the safe and effective operation of earth-rock dams. The most influential factors concerning the seepage of earth-rock dams are the reservoir water level, precipitation, temperature, and timeliness, and the influence of the reservoir water level and precipitation on the seepage of an earth-rock dam exhibits hysteretic effects. The reservoir water level of an earth-rock dam abruptly increases and may exceed the historically highest water level, therein causing new deformations of the earth-rock dam or even plastic deformation. Thus, the permeability coefficient for parts of an earth-rock dam changes, and we present the exceeded water level factor. Considering the complexity of the seepage monitoring of earth-rock dams, based on the hysteretic reservoir water level and precipitation, temperature, timeliness, and the exceeded water level factor, a statistical model based on an explicit function and an artificial wavelet neural network model based on an implicit function are established. Based on these two models, an integrated monitoring model based on maximum entropy theory is established. At the end of this paper, three monitoring models are used for the seepage monitoring of a measuring point of an earth-rock dam influenced by rainstorms, and the results show that the three monitoring models obtain satisfactory predication accuracy

Study on SO42−/Cl− Erosion Resistance and Mechanism of Recycled Concrete Containing Municipal Solid Waste Incineration (MSWI) Powder

In this paper, the strength characteristics and erosion resistance of solid waste incineration (MSWI) powder were studied. Firstly, the optimum process for the preparation of regenerated powder from MSWI bottom slag by ball milling was determined as follows: rotational speed 350 r/min, time 45 min. The strength activity index of regenerated powder reached the maximum when the substitute content of powder was 30%. Secondly, the semi-erosion method was used to study the strength variation rule of mortar with different content of MSWI powder in semi-immersion of salt solution. It was found that the higher the content of MSWI powder, the greater the anti-erosion coefficient of mortar specimen. Finally, the capillary rise test, crystallization test and capillary pore water absorption test were used to study the total porosity, coarse capillary-pore porosity and fine-capillary pore porosity of concrete containing MSWI powder. The results showed that, with the increase in MSWI powder content, the above pore structure properties were improved. The results revealed the transport and crystallization process of salt solution in concrete mixed with MSWI powder and the mechanism of corrosion resistance

Study on Impermeability of Foamed Concrete Containing Municipal Solid Waste Incineration Powder

In this paper, the effects of dry density, w/c ratio, and municipal solid waste incineration (MSWI) powder on the multi-scale properties and internal pore structure of foamed concrete were studied by using a single-factor controlled experiment. It was found that an increase in the dry density of foamed concrete could effectively reduce the porosity, leading to the improvement of compressive strength and impermeability and to the reduction of water absorption. The compressive strength, water absorption, and impermeability were mainly affected by the porosity when the w/c ratio changed. With the increase in porosity, the water absorption rate increased, and the compressive strength and impermeability decreased. The addition of MSWI powder caused no obvious change in the overall pore size distribution of the foamed concrete, and there was no significant change in the water absorption and impermeability of the structure. However, because the hydration activity of MSWI powder was lower than that of ordinary Portland cement, the compressive strength of foamed concrete decreased with the increase in MSWI powder

RNA Interference Targeting GRP75 Decreases Cisplatin Resistance in Human Lung Adenocarcinoma Cell

Background and objective GRP75, a member of HSPs which is overexpressed in some resistant cancer cells, is a molecular chaperone mainly located in mitochondrial membrane. The aim of this study is to investigate the role of GRP75 on the resistant mechanisms of cancer cells by downregulating GRP75 expreesion via RNAi approach. Methods Cisplatin-resistant cell A549/CDDP was established from their parental human lung adenocarcinoma cell line A549 by combining gradually increasing concentrations of cisplatin with high dosage impact. The shRNA for GRP75 was transfected into A549 and A549/CDDP cells by lentivirus. Western blot and methyl thiazolyl tetrazolium (MTT) assay were applied to detect the influence of silencing GRP75 expression on sensitivity of the cells to cisplatin. Results The infection rate of six groups were all over 90%. After infection, the level of expression of GRP75 in both A549 and A549/CDDP were down-regulated (P < 0.05); the level of expression of p53 in A549/CDDP was up-regulated (P < 0.05) and the level of expression of bcl-2 of A549/CDDP was down-regulated (P < 0.05). The resistance index of A549/CDDP before and after infection were 21.52 and 4.14 respectively. Conclusion Cisplatin resistance of lung cancer cells is associated with overexpression of GRP75 gene, which could regulate the expressions of p53 and bcl-2

Optical Fiber Sensor Experimental Research Based on the Theory of Bending Loss Applied to Monitoring Differential Settlement at the Earth-Rock Junction

Considering the differential settlement in the junction between the structure perpendicular to the dike and the body and foundation of dike (called the earth-rock junction in this paper) during runtime, an experimental investigation of optical fiber sensor monitoring was conducted. Based on the sensing mechanism of single-mode optical fiber bending loss, the experiment focused on the influence of the bending radius of an optical fiber on the bending loss. In view of the characteristics of the differential settlement in the earth-rock junction, we designed a butterfly-type optical fiber sensor and composite optical fiber sensor for monitoring device in monitoring the differential settlement to enlarge the monitoring range and improve the sensibility of optical fiber sensor. Based on the research on the working principle and bending properties of the composite optical fiber monitoring device, we conducted experiments on the bending of the composite optical fiber sensor monitoring device and the use of the device for monitoring the differential settlement. These experiments verified the feasibility of the composite optical fiber sensor monitoring device at monitoring the differential settlement in the earth-rock junction

Determining the Optimal Placement of Sensors on a Concrete Arch Dam Using a Quantum Genetic Algorithm

Structural modal identification has become increasingly important in health monitoring, fault diagnosis, vibration control, and dynamic analysis of engineering structures in recent years. Based on an analysis of traditional optimization algorithms, this paper proposes a novel sensor optimization criterion that combines the effective independence (EFI) method with the modal strain energy (MSE) method. Considering the complex structure and enormous degrees of freedom (DOFs) of modern concrete arch dam, a quantum genetic algorithm (QGA) is used to optimize the corresponding sensor network on the upstream surface of a dam. Finally, this study uses a specific concrete arch dam as an example and determines the optimal sensor placement using the proposed method. By comparing the results with the traditional optimization methods, the proposed method is shown to maximize the spatial intersection angle among the modal vectors of sensor network and can effectively resist ambient perturbations, which will make the identified modal parameters more precise

Multiaxial Strength Criterion Model of Concrete Based on Random Forest

The concrete strength criterion is the basis of strength analysis and evaluation under a complex stress state. In this paper, a large number of multiaxial strength tests were carried out, and many mathematical expressions of strength criteria were proposed based on the geometric characteristics and the assumption of a convex function. However, the rationality of the assumption of a convex function limits the use of these strength criteria. In particular, misjudgment will occur near the failure curve surface. Therefore, this paper does not assume the shape function of the criterion in advance. By collecting experimental data and using a machine learning method, it proposes a method of hidden function of failure curve surface. Based on 777 groups of experimental data, the random forest (RF), the back propagation neural network (BP) and the radial basis neural network (RBF) models were used to analyze and verify the feasibility and effectiveness of the method. Subsequently, the results were compared with the Ottosen strength criterion, the Guo Wang strength criterion and the Drucker–Prager (DP) strength criterion. The results show that the consistency between the strength criterion model established by the machine learning algorithm (especially random forest) and the experimental data is higher than the convex function multiaxis strength criterion of the preset failure surface shape. Moreover, the physical significance is clearer, the deficiency of the convex function failure surface hypothesis is avoided and the established multiaxial strength criterion of concrete is more universal