Abstract
This paper reviews several recently-developed techniques for the minimum-cost optimal design of water-retaining structures (WRSs), which integrate the effects of seepage. These include the incorporation of uncertainty in heterogeneous soil parameter estimates and quantification of reliability. This review is limited to methods based on coupled simulation-optimization (S-O) models. In this context, the design of WRSs is mainly affected by hydraulic design variables such as seepage quantities, which are difficult to determine from closed-form solutions or approximation theories. An S-O model is built by integrating numerical seepage modeling responses to an optimization algorithm based on efficient surrogate models. The surrogate models (meta-models) are trained on simulated data obtained from finite element numerical code solutions. The proposed methodology is applied using several machine learning techniques and optimization solvers to optimize the design of WRS by incorporating different design variables and boundary conditions. Additionally, the effects of several scenarios of flow domain hydraulic conductivity are integrated into the S-O model. Also, reliability based optimum design concepts are incorporated in the S-O model to quantify uncertainty in seepage quantities due to uncertainty in hydraulic conductivity estimates. We can conclude that the S-O model can efficiently optimize WRS designs. The ANN, SVM, and GPR machine learning technique-based surrogate models are efficiently and expeditiously incorporated into the S-O models to imitate the numerical responses of simulations of various problems.
Highlights
Construction of water-retaining structures (WRSs) [1] [2], such as dams, barrages, regulators and weirs, is essential for stable and safe water management and to generate clean energy
The percentage of reliability only reflects the uncertainty of seepage quantities under WRS due to uncertainty associated with heterogeneous hydraulic conductivity
The multi-objective multi-realization optimization (MOMRO) technique was applied to hypothetical design scenarios/cases to evaluate the performance of the reliability based optimum design (RBOD)-based MOMRO technique
Summary
Construction of water-retaining structures (WRSs) [1] [2], such as dams, barrages, regulators and weirs, is essential for stable and safe water management and to generate clean energy. This study presents a coupled simulation-optimization (S-O) approach to identifying minimum-cost WRS designs while incorporating numerical seepage analysis, uncertainty in seepage quantities, and hydraulic design safety factors. Numerical techniques only provide solutions when certain parameters of the hydraulic structure are known, including the boundary conditions and geometry of the flow domain. There is limited potential to apply S-O models to the hydraulic design of WRSs. no studies have yet considered the effects of uncertainty in some of the design parameters related to seepage analysis. Uncertainty in seepage characteristic estimates due to uncertainty in hydraulic conductivity is integrated into the reliability based optimum design using S-O model. Application of the S-O Approach to a Simple Conceptual Seepage Model Related to WRS Design
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