Parameters inversion of high central core rockfill dams based on a novel genetic algorithm

Zhou, Wei; Li, Shaolin; Ma, Gang; Chang, Xiaolin; Ma, Xiaotong; Zhang, Chao

doi:10.1007/s11431-016-6017-2

Cited by 33 publications

(10 citation statements)

References 16 publications

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“…Under high stresses, grain breakage alters the grain size distribution and is usually accompanied by a reduction of the permeability and an increase in compressibility of the grain skeleton [1][2][3][4]. These complex microscale processes play a critical role in the performance and serviceability of many engineering applications, such as embankments [5], rockfill dams [6,7], railway tracks and geotechnical engineering [8]. The mechanisms of grain crushing are complex and depend closely on the stresses transmitted through particle contacts.…”

Section: Introductionmentioning

confidence: 99%

DEM Modeling of Crushable Grain Material under Different Loading Conditions

Benmebarek

Rad

2021

Period. Polytech. Civil Eng.

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This paper deals with the effect of contact conditions on the crushing mechanisms and the strength of granular materials. The computation of crushable grain material under different loading conditions is performed using 3D model of discrete element method (DEM). The crushable macro-grain is generated from a large number of identical spherical micro-grains which are connected according to the bonded particle model. First, the parameters of the proposed DEM model are calibrated to match the force-displacement curve obtained from Brazilian Tests performed on cylinders made of artificially crushable material. The damage profile right at the point when the force-displacement curve reaches its maximum is seen to replicate the same crack patterns observed in Brazilian test experiments. Then, parametric investigations are performed by varying the coordination number, the contact location distribution, and the contact area. The results show that these parameters play a significant role in determining the critical contact force and fracture mechanism of crushable particles compared to a traditional macro-grain crushing test. Increasing distribution and coordination number of the macro-grain increases particle strength when large area contact is permitted. However, for linear contact area, the effect of increasing coordination number on particle strength is marginal.

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Section: Introductionmentioning

confidence: 99%

DEM Modeling of Crushable Grain Material under Different Loading Conditions

Benmebarek

Rad

2021

Period. Polytech. Civil Eng.

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“…e traditional methods for parametric inversion are clear, but there are still shortcomings like inefficient calculation and poor accuracy. With the development of artificial intelligence, various intelligent algorithms have been introduced into the engineering reverse analysis and fruitful achievements have been presented [13][14][15][19][20][21][22]. Guo et al [15] performed deformation back analysis based on the response surface method and genetic optimization theory to sequentially calculate parameters of the creep and Duncan-Chang models for the Pubugou gravelly soil core rockfill dam.…”

Section: Introductionmentioning

confidence: 99%

“…Gan et al [20] proposed a new deformation back analysis method called MPSO-BP, which integrates a modified particle swarm optimization algorithm and neural network simulator, to reverse the creep model parameters of Jiudianxia CFRD. Zhou et al [21] modified the genetic algorithm to solve the high-dimension multimodal and nonlinear optimal parameters inversion problem and validated this method in parametric analysis of E-B and Merchant creep model. e back-propagation neutral network (BPNN), with strong nonlinear capability, is employed to express the complicated relationship between the model parameters and simulated displacement.…”

Section: Introductionmentioning

confidence: 99%

Parameter Sensitivity and Inversion Analysis for a Concrete Face Rockfill Dam Based on CS‐BPNN

Chen

Shao

et al. 2019

Advances in Civil Engineering

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The deformation behavior of rockfill is significant to the normal operation of concrete face rockfill dam. Considering both the nonlinear mechanical behavior and long-term rheological deformation, the E-ν model and modified Burgers model are coupled to describe the deformation behavior of the rockfill materials. The coupled E-ν and Burgers model contains numerous parameters with complex relationship, and an efficient and accurate inversion analysis is in demand. The sensitivity of the parameters in the coupled E-ν and modified Burgers is analyzed using the modified Morris method initially. Then, a new approach of parameter back analysis is proposed by combining back-propagation neutral network (BPNN) and Cuckoo Search (CS) algorithm. The numerical example shows that parameters K, Rf, and φ0 as well as G are more sensitive to the deformation of the rockfill body. The inversion analysis for these four parameters and η2, E2, and A as well as B in modified Burgers model is performed by the CS-BPNN algorithm. The numerical results demonstrate that the parameters obtained with the proposed method are reasonable and its feasibility is validated.

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“…The traditional inversion methods often integrate the forward analysis with an optimization method, and an inversion problem is simplified as a minimization problem of the sum of squares function. With the development of artificial intelligence technology, numerous artificial intelligent algorithms have been introduced to the inversion analysis: the genetic algorithm (Zhou et al , 2016), the particle swarm optimization algorithm (Jia and Chi, 2015), the bat algorithm (Yang and Gandomi, 2012), the neural network algorithm (Yang et al , 2018) and so on. Among them, the neural network algorithm has become quite popular as it separates the forward analysis and the inversion analysis with training strategy and multiple parameters can be quickly obtained once the training is finished.…”

Section: Introductionmentioning

confidence: 99%

The forward and inversion analysis of high rock-fill dam during construction period using the node-based smoothed point interpolation method

Pan

Cheng

2019

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Purpose The meshfree node-based smoothed point interpolation method (NS-PIM) is extended to the forward and inversion analysis of a high gravelly soil core rock-fill dam during construction periods. Design/methodology/approach As one member of the meshfree methods, the NS-PIM has the advantages of “softer” stiffness and adaptability to large deformations which is quite indispensable for the stability analysis of rock-fill dams. In this work, the present method contains a reconstruction procedure to deal with the existence or nonexistence of the construction layers. After verifying the validity of the NS-PIM method for nonlinear elastic model during construction period, the convergence features of the NS-PIM and FEM methods are further investigated with different mesh schemes. Furthermore, the NS-PIM and FEM methods are applied for the forward analysis of a high gravelly soil core rock-fill dam and the convergence features under complex stress conditions are also studied using the rock-fill dam model. Finally, the NS-PIM method is used to calculate the Duncan–Chang parameters of the deep overburden under the high gravelly soil core rock-fill dam based on the back-propagation neural network method. Findings The results show that: the NS-PIM solution for construction analysis still possesses the property of upper bound solution even under complex stress conditions and can provide comparatively more conservative results for safety evaluation. Furthermore, it can be used to evaluate the accuracy of results and mesh quality together with the FEM solution which has the property of lower bound solution; the inversion analysis in this work provides a set of material parameters for the deep overburden under high rock-fill dam during construction period and the calculated results show good agreement with the measured displacement values and it is feasible to apply the NS-PIM to the forward and inversion analysis of high rock-fill dams on deep overburden during construction periods. Research limitations/implications In further study, the feasibility of three-dimensional problems, elastic–plastic problems, contact problems and multipoint inversion can still be probed in the NS-PIM solution for the forward and inversion analysis of high rock-fill dams on deep overburden. Practical implications This paper introduced a method for the forward and inversion analysis of high rock-fill dams during construction period using the NS-PIM solution. The property of upper bound solution ensures that the NS-PIM can provide more conservative results for safety evaluation. The inversion analysis in this work provides a set of material parameters for the deep overburden under high rock-fill dam during construction periods. Originality/value First, the analysis from forward to inversion for high rock-fill dams during construction period using the NS-PIM solution is accomplished in this work. A procedure dealing with the existence or nonexistence of the construction layers is also developed for the construction analysis. Second, it is confirmed in this work that the NS-PIM still possesses the property of upper bound solution even under complex stress conditions (the forward analysis of high rock-fill dams during construction period). Thus, more conservative results can be provided for safety evaluation. Furthermore, it can be used to evaluate the accuracy of results and mesh quality together with the FEM solution which has the property of lower bound solution. Third, the calculated material parameters of the deep overburden in this work can be used for further studies of the high rock-fill dam.

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Parameters inversion of high central core rockfill dams based on a novel genetic algorithm

Cited by 33 publications

References 16 publications

DEM Modeling of Crushable Grain Material under Different Loading Conditions

DEM Modeling of Crushable Grain Material under Different Loading Conditions

Parameter Sensitivity and Inversion Analysis for a Concrete Face Rockfill Dam Based on CS‐BPNN

The forward and inversion analysis of high rock-fill dam during construction period using the node-based smoothed point interpolation method

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