Chongshi Gu

Study on Semi-Parametric Statistical Model of Safety Monitoring of Cracks in Concrete Dams

Cracks are one of the hidden dangers in concrete dams. The study on safety monitoring models of concrete dam cracks has always been difficult. Using the parametric statistical model of safety monitoring of cracks in concrete dams, with the help of the semi-parametric statistical theory, and considering the abnormal behaviors of these cracks, the semi-parametric statistical model of safety monitoring of concrete dam cracks is established to overcome the limitation of the parametric model in expressing the objective model. Previous projects show that the semi-parametric statistical model has a stronger fitting effect and has a better explanation for cracks in concrete dams than the parametric statistical model. However, when used for forecast, the forecast capability of the semi-parametric statistical model is equivalent to that of the parametric statistical model. The modeling of the semi-parametric statistical model is simple, has a reasonable principle, and has a strong practicality, with a good application prospect in the actual project.

Dam's risk identification under interval-valued intuitionistic fuzzy environment

This paper uses both fuzzy analytic hierarchy process (FAHP) and the cross entropy of interval-valued intuitionistic fuzzy sets on risk identification of dams. The problem of risk identification can be transformed into a multi-criteria decision-making problem under fuzzy environment. Based on the weight of criteria calculated by the FAHP method and the interval-valued intuitionistic fuzzy information of risk aggregated by geometric average operator, the weight of each alternative can be obtained. The proposed method is used to identify the main risk factors of an earth–rock dam and to rank potential failure modes of the dam. The proposed method takes into account the interval unknown degree (hesitancy degree) in dam safety assessment and it is more effective and accurate in real conditions of dam operation.

Zoned elasticity modulus inversion analysis method of a high arch dam based on unconstrained Lagrange support vector regression (support vector regression arch dam)

An inverse modeling process is proposed to estimate the actual elasticity modulus of a high arch dam based on unconstrained Lagrange support vector regression (ULSVR) and monitoring data. The proposed ULSVR eliminates the inequality and equality constraints to improve the iteration speed, especially for large repeated calculations, and the process takes advantage of the culture genetic algorithm (CGA) by importing the belief space, which utilizes social knowledge to guide the generations to accelerate the evolution speed. Then, CGA is used to optimize the parameters of ULSVR and seek the optimal elasticity modulus combination. The inverse modeling procedure is successfully applied to optimize the zoned elasticity modulus of the Jinping high arch dam and foundation in its initial impound period. The inversion analysis shows that the actual modulus is larger than the experimental results, showing that the actual situation is safer than the design condition.

Variable-intercept panel model for deformation zoning of a super-high arch dam

This study determines dam deformation similarity indexes based on an analysis of deformation zoning features and panel data clustering theory, with comprehensive consideration to the actual deformation law of super-high arch dams and the spatial–temporal features of dam deformation. Measurement methods of these indexes are studied. Based on the established deformation similarity criteria, the principle used to determine the number of dam deformation zones is constructed through entropy weight method. This study proposes the deformation zoning method for super-high arch dams and the implementation steps, analyzes the effect of special influencing factors of different dam zones on the deformation, introduces dummy variables that represent the special effect of dam deformation, and establishes a variable-intercept panel model for deformation zoning of super-high arch dams. Based on different patterns of the special effect in the variable-intercept panel model, two panel analysis models were established to monitor fixed and random effects of dam deformation. Hausman test method of model selection and model effectiveness assessment method are discussed. Finally, the effectiveness of established models is verified through a case study.

Risk Analysis of Earth-Rock Dam Failures Based on Fuzzy Event Tree Method

Earth-rock dams make up a large proportion of the dams in China, and their failures can induce great risks. In this paper, the risks associated with earth-rock dam failure are analyzed from two aspects: the probability of a dam failure and the resulting life loss. An event tree analysis method based on fuzzy set theory is proposed to calculate the dam failure probability. The life loss associated with dam failure is summarized and refined to be suitable for Chinese dams from previous studies. The proposed method and model are applied to one reservoir dam in Jiangxi province. Both engineering and non-engineering measures are proposed to reduce the risk. The risk analysis of the dam failure has essential significance for reducing dam failure probability and improving dam risk management level.

Research on early-warning index of the spatial temperature field in concrete dams

Warning indicators of the dam body’s temperature are required for the real-time monitoring of the service conditions of concrete dams to ensure safety and normal operations. Warnings theories are traditionally targeted at a single point which have limitations, and the scientific warning theories on global behavior of the temperature field are non-existent. In this paper, first, in 3D space, the behavior of temperature field has regional dissimilarity. Through the Ward spatial clustering method, the temperature field was divided into regions. Second, the degree of order and degree of disorder of the temperature monitoring points were defined by the probability method. Third, the weight values of monitoring points of each regions were explored via projection pursuit. Forth, a temperature entropy expression that can describe degree of order of the spatial temperature field in concrete dams was established. Fifth, the early-warning index of temperature entropy was set up according to the calculated sequential value of temperature entropy. Finally, project cases verified the feasibility of the proposed theories. The early-warning index of temperature entropy is conducive to the improvement of early-warning ability and safety management levels during the operation of high concrete dams.

Bootstrap-typed criterion studies of online diagnostic to cracks abnormality of concrete dam

Crack is one of the major manifestations of damages on concrete dam, and studies on the safe-monitoring model of concrete dam cracks have always been a focus in dam safety monitoring field. Currently, the corresponding diagnostic methods and the criteria belong to post hoc test (diagnosis) category. But in practice, it is also concerned in the cracking abnormality diagnosis of concrete dam that whether the cracking abnormality will occur in its current state, and whether the original crack safety monitoring model is still appropriate in its current state. This chapter focuses on reflecting different states of cracks abnormality by studying the structural stability of the linear regression model in concrete dam cracks; the main idea is based on the steady state of the regression coefficients in the model to reflect crack abnormal states. Thus, online diagnostic of the concrete dam cracks abnormality corresponds statistically to the model of structural stability (changeable points) or to the problem of online monitoring sequential detection problem. In this paper, the author does different considerations on the concrete dam cracks transformation characteristic, constructs the appropriate online diagnostic methods and criteria, and takes a project as an example to analyse and to verify its established criteria and methods.