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...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.展开更多
The infiltration of water into soil is one of the most important soil physical properties that affect soil erosion and the eco-environment, especially in the Pisha sandstone area on the Chinese Loess Plateau. We studi...The infiltration of water into soil is one of the most important soil physical properties that affect soil erosion and the eco-environment, especially in the Pisha sandstone area on the Chinese Loess Plateau. We studied the one-dimensional vertical infiltration of water in three experimental soils, created by mixing Pisha sandstone with sandy soil, irrigation-silted soil, and loessial soil, at mass ratios of 1：1, 1：2, 1：3, 1：4, and 1：5. Our objective was to compare water infiltration in the experimental soils and to evaluate the effect of Pisha sandstone on water infiltration. We assessed the effect by measuring soil bulk density（BD）, porosity, cumulative infiltration, infiltration rate and saturated hydraulic conductivity（Ks）. The results showed that Pisha sandstone decreased the infiltration rate and saturated hydraulic conductivity in the three experimental soils. Cumulative infiltration over time was well described by the Philip equation. Sandy soil mixed with the Pisha sandstone at a ratio of 1：3 had the best water-holding capacity. The results provided experimental evidence for the movement of soil water and a technical support for the reconstruction and reclamation of mining soils in the Pisha sandstone area.展开更多
通过对黑土坡耕地免耕、少耕与传统耕作土壤物理性状全生育期观测，比较研究土壤结构和导水性状季节变化差异及其与水土流失的关系。结果表明，表层0～20 cm土壤，免耕土壤容重全生育期维持在1.20～1.30 g cm^-3，变化小，大于0.25 mm...通过对黑土坡耕地免耕、少耕与传统耕作土壤物理性状全生育期观测，比较研究土壤结构和导水性状季节变化差异及其与水土流失的关系。结果表明，表层0～20 cm土壤，免耕土壤容重全生育期维持在1.20～1.30 g cm^-3，变化小，大于0.25 mm的水稳性团聚体含量（WR0.25）和平均重量直径（MWD）高于传统耕作，初始和稳定入渗速率均高于少耕和传统耕作，土壤含水量分别较少耕和传统耕作高4.7和4.4个百分点，较传统耕作分别减少地表径流和土壤流失量86%和100%；少耕除夏季各项性状均介于免耕和传统耕作之间，夏季垄沟深松后，垄沟土壤容重显著降低，较免耕和传统耕作降低0.15 g cm^-3以上，提高土壤初始入渗速率30%以上，较传统耕作减少水和土壤流失量20%和40%。传统耕作土壤容重，垄台由播种时的0.91 g cm^-3增加至收获时的1.23 g cm^-3，垄沟一直维持在1.30 g cm^-3左右，WR0.25、MWD、土壤稳定入渗速率、含水量均较低，全生育期10%的雨水流失，土壤流失量615 t km^-2 a^-1。免耕土壤结构稳定，蓄水保水最佳，为效果显著的水土保持耕作措施，少耕也有一定的保水保土作用；免耕和少耕均能够改善土壤物理性状。展开更多
文摘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.
基金supported by the Key Technology and Demonstration of Damaged Ecosystem Restoration and Reconstruction in Shanxi–Shaanxi–Inner Mongolia Energy Base Location (KZCX2-XB3-13-02)
文摘The infiltration of water into soil is one of the most important soil physical properties that affect soil erosion and the eco-environment, especially in the Pisha sandstone area on the Chinese Loess Plateau. We studied the one-dimensional vertical infiltration of water in three experimental soils, created by mixing Pisha sandstone with sandy soil, irrigation-silted soil, and loessial soil, at mass ratios of 1：1, 1：2, 1：3, 1：4, and 1：5. Our objective was to compare water infiltration in the experimental soils and to evaluate the effect of Pisha sandstone on water infiltration. We assessed the effect by measuring soil bulk density（BD）, porosity, cumulative infiltration, infiltration rate and saturated hydraulic conductivity（Ks）. The results showed that Pisha sandstone decreased the infiltration rate and saturated hydraulic conductivity in the three experimental soils. Cumulative infiltration over time was well described by the Philip equation. Sandy soil mixed with the Pisha sandstone at a ratio of 1：3 had the best water-holding capacity. The results provided experimental evidence for the movement of soil water and a technical support for the reconstruction and reclamation of mining soils in the Pisha sandstone area.
文摘通过对黑土坡耕地免耕、少耕与传统耕作土壤物理性状全生育期观测，比较研究土壤结构和导水性状季节变化差异及其与水土流失的关系。结果表明，表层0～20 cm土壤，免耕土壤容重全生育期维持在1.20～1.30 g cm^-3，变化小，大于0.25 mm的水稳性团聚体含量（WR0.25）和平均重量直径（MWD）高于传统耕作，初始和稳定入渗速率均高于少耕和传统耕作，土壤含水量分别较少耕和传统耕作高4.7和4.4个百分点，较传统耕作分别减少地表径流和土壤流失量86%和100%；少耕除夏季各项性状均介于免耕和传统耕作之间，夏季垄沟深松后，垄沟土壤容重显著降低，较免耕和传统耕作降低0.15 g cm^-3以上，提高土壤初始入渗速率30%以上，较传统耕作减少水和土壤流失量20%和40%。传统耕作土壤容重，垄台由播种时的0.91 g cm^-3增加至收获时的1.23 g cm^-3，垄沟一直维持在1.30 g cm^-3左右，WR0.25、MWD、土壤稳定入渗速率、含水量均较低，全生育期10%的雨水流失，土壤流失量615 t km^-2 a^-1。免耕土壤结构稳定，蓄水保水最佳，为效果显著的水土保持耕作措施，少耕也有一定的保水保土作用；免耕和少耕均能够改善土壤物理性状。
