Research On Concrete Facing Rockfill Dam Construction Time-quality-cost Comprehensive Optimization Based On Real-time Monitoring

Concrete facing rockfill dam has been widely recognized as a relatively economical type of dam. With the rapid development of pumped-storage power station in China, concrete facing rockfill dam is increasingly applied in these hydropower stations. Nevertheless, the construction of face rockfill dams,which are used in pumped-storage power station, faces some key issues such as tight construction schedule, large numbers of uncertain factors, complexity of construction technology, how to comprehensively evaluate the quality of roller compaction, how to equilibrate and optimize three targets of time limit, quality and cost, etc. It is a challenge for the current construction management of face rockfill dam to solve above problems. This paper has a in-depth study on the problems mentioned above and obtains the researching results as follows:1. Aiming at the problems of complicated construction process of face rockfill dam and the difficulty in acquiring its construction dynamic parameter in real time, this paper bases on the construction parameters sensitivity analysis method and puts forward the construction dynamic simulation model and method of face rockfill dam on the basis of real-time monitoring.There are great randomness and uncertainty in the construction process of face rockfill dam. However, the methods of expert experience and engineering analogy are mostly adopted for the selection of the current construction simulation parameters of face rockfill dam for construction phase, which influences the reliability of simulation results. Also the simulation lacks real-time performance, and it is hard to predict the future construction schedule in real time on the basis of current construction condition and latest machinery allocation. Aiming at the problems mentioned above, this paper adopts orthogonal test method to have a sensitivity analysis for construction parameters and determine the key parameters and key construction links in the process of construction. On this basis, this paper also puts forward the construction dynamic simulation model of face rockfill dam based on real-time monitoring. Simulation parameters can be obtained and updated according to the actual construction information. Then through dynamic simulation, construction schedule is able to be predicted and analyzed, which ensures the realization of progress aim.2. Having comprehensive consideration of the key influencing factors of dam body’s roller compaction quality of face rockfill dam, the paper bases on the coupling analysis of porosity-reliability and proposes the bivariate analysis model and method of the dam’s filling quality of face rockfill dam, which couples with porosity-reliability.In the past, the control of face rockfill dam’s filling quality mainly depends on random sampling test at the construction site. Therefore, the analysis results can only reflect defects such as the filling quality of test points themselves on the dam storehouse surface. In order to solve the above problems, combining with the rolling real-time monitoring technology of face rockfill dam, this paper bases on the sensitivity analysis of rolling parameters on porosity and establishes the genetic neural network porosity prediction model on the basis of elites to keep the tactics. Additionally, considering the condition that porosity will affect parameter variability, the paper also proposes bivariate analysis method of the dam body’s filling quality of face rockfill dam, which couples with porosity-reliability. When compared with the traditional random sampling test evaluation method at the construction field, the analysis model and method of dam filling quality, which are put forward in this paper, comprehensively reflect the quality of the whole dam body. Their evaluation results are more comprehensive and reasonable, and also provide a more reliable basis for subsequent dam construction.3. Aiming at the uncertainty of construction period and quality, this paper sets up the equilibrium optimization model of time-quality-cost on the basis of quality cost and decision preference.The current study on the multi-objective optimization of dam construction duration, quality and cost always ignores restrictive relation between time limit, quality and cost. Furthermore, current study neglects the great influence of actual construction parameters on quality cost, construction control and management decisions. Combining with the real-time monitoring system, the paper takes the fuzziness of quality and schedule into account and sets up the equilibrium optimization model of time limit-quality-cost on the basis of quality cost and decision preference. When compared with the existing multi-objective optimization model, the model established in this paper comprehensively reflects the benefits in terms of accurate dynamic prediction of construction progress, control of quality level and control of quality cost, which are brought about by real-time monitoring system, and provide effective way to solve construction optimization problem.4. With the use of analysis algorithms such as data sensitivity analysis method, construction dynamic simulation approach, genetic neural network algorithm based on elites to keep the tactics, non-dominated sorting genetic algorithm on the basis of fuzzy time limit and fuzzy quality, etc., the paper analyzes and solves the model mentioned above.Current research lacks analysis of the importance of real-time monitoring parameter, leading to situation that the control of construction parameters at the site has no pertinence. What’s more, with the adoption of traditional mathematical method, the way to solve models of construction dynamic simulation, quality analysis, equilibrium and optimization, etc., which are based on real-time monitoring, is not satisfying. It is due to the complicated operations and low-solving efficiency. In order to solve the above problems, this paper proposes some methods as follows: first, adopting rang method of orthogonal test as well as neural network to respectively make sensitivity analysis of construction simulation parameter and rolling quality parameter, giving quantitative evaluation of effect degree which the change of real-time monitoring makes on the variability of model output, and determining key influencing parameters; second, with the combination of queuing theory, computer simulation technology, network planning technique and real-time monitoring technology, proposing construction dynamic simulation method-CYCLONE(Cycle Operation Network), which provides favorable analysis tool for mastering construction process of face rockfill dam comprehensively and quickly; third, using genetic neural network algorithm based on elites to keep the tactics to obtain the model of porosity prediction, which overcomes the problems that former genetic algorithm loses the best individual and is slow in convergence of calculation; fourth, adopting non-dominated sorting genetic algorithm based on fuzzy time limit and fuzzy quality to obtain equilibrium optimization model of time limit-quality-cost, which takes uncertainty of construction period and quality into account, improves the computational efficiency and robustness, and has good convergence when compared with traditional equilibrium optimization method.5. In this paper, a face rockfill dam of pumped storage power station is chosen to study the application of the model, which proves the feasibility of above theory and methodTaking a face rockfill dam project of pumped storage power station in China as a case study, the theory, method and technology of above research results are applied to practical engineering.(1) The projet adopted orthogonal test method to have a sensitivity analysis of construction parameters and determined key parameters as well as key construction links. It also used single sample K-S(Kolmogorov Smirnov) test and P-P probability graph test to have a statistical analysis of monitoring data of key parameters, according to which subsequent construction progress simulation parameters could be updated and construction dynamic simulation method- CYCLONE was adopted to realize the dynamic simulation of construction schedule. Additionally, the project had staging analysis of a key construction link-the heavy transport of dump truck and provided construction guidance for the link of staging heavy transport with pertinence.(2) The project adopted the method of neural network sensitivity analysis to determine effect degree that dam stone’s uneven coefficient, curvature coefficient, moisture content, fine aggregate content as well as characteristic parameters obtained through real-time monitoring, including compactor pass, rolling thickness, status of excitation force,etc. have made on porosity. Combining with the parameters mentioned above, the project used elites to keep the tactics genetic neural network algorithm to predict porosity of dam surface. Furthermore, considering the situation that porosity will affect variety of parameters, the project used quality bivariate analysis method,which couples with porosity-reliability, to have comprehensive analysis of filling quality of each area of face rockfill dam, and provided basis for the equilibrium and optimization of time limit-quality-cost and quality control of site construction.(3) Combining with engineering background, the project respectively adopted analytic hierarchy process, entropy weight method and combination weighting method to calculate weights of three targets of time limit, quality as well as cost. During construction process, the project combined with current analysis results of quality, considered quality cost under real-time monitoring and put forward subsequent construction scheme. Through non-dominated sorting genetic algorithm based on fuzzy time limit and fuzzy quality, the construction period, quality as well as cost of schemes were able to be balanced and optimized. Then with the combination of TOPSIS method, the project made further comparison of optimized schemes, which provided reasonable construction scheme for the subsequent filling construction of the dam.