共查询到20条相似文献，搜索用时 15 毫秒
1.
Selection of sand models and identification of parameters using an enhanced genetic algorithm 
下载免费PDF全文
下载免费PDF全文 Numerous constitutive models of granular soils have been developed during the last few decades. As a consequence, how to select an appropriate model with the necessary features based on conventional tests and with an easy way of identifying parameters for geotechnical applications has become a major issue. This paper aims to discuss the selection of sand models and parameters identification by using genetic algorithm. A real‐coded genetic algorithm is enhanced for the optimization with high efficiency. Models with gradually varying features (elastic‐perfectly plastic modelling, nonlinear stress–strain hardening, critical state concept and two‐surface concept) are selected from numerous sand models as examples for optimization. Conventional triaxial tests on Hostun sand are selected as the objectives in the optimization. Four key points are then discussed in turn: (i) which features are necessary to be accounted for in constitutive modelling of sand; (ii) which type of tests (drained and/or undrained) should be selected for an optimal identification of parameters; (iii) what is the minimum number of tests that should be selected for parameter identification; and (iv) what is the suitable and least strain level of objective tests to obtain reliable and reasonable parameters. Finally, a useful guide, based on all comparisons, is provided at the end of the discussion. Copyright © 2015 John Wiley & Sons, Ltd. 相似文献
2.
This paper discusses the quality of the procedure employed in identifying soil parameters by inverse analysis. This procedure includes a FEM‐simulation for which two constitutive models—a linear elastic perfectly plastic Mohr–Coulomb model and a strain‐hardening elasto‐plastic model—are successively considered. Two kinds of optimization algorithms have been used: a deterministic simplex method and a stochastic genetic method. The soil data come from the results of two pressuremeter tests, complemented by triaxial and resonant column testing. First, the inverse analysis has been performed separately on each pressuremeter test. The genetic method presents the advantage of providing a collection of satisfactory solutions, among which a geotechnical engineer has to choose the optimal one based on his scientific background and/or additional analyses based on further experimental test results. This advantage is enhanced when all the constitutive parameters sensitive to the considered problem have to be identified without restrictions in the search space. Second, the experimental values of the two pressuremeter tests have been processed simultaneously, so that the inverse analysis becomes a multi‐objective optimization problem. The genetic method allows the user to choose the most suitable parameter set according to the Pareto frontier and to guarantee the coherence between the tests. The sets of optimized parameters obtained from inverse analyses are then used to calculate the response of a spread footing, which is part of a predictive benchmark. The numerical results with respect to both the constitutive models and the inverse analysis procedure are discussed. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
3.
Current studies have focused on selecting constitutive models using optimization methods or selecting simple formulas or models using Bayesian methods. In contrast, this paper deals with the challenge to propose an effective Bayesian-based selection method for advanced soil models accounting for the soil uncertainty. Four representative critical state-based advanced sand models are chosen as database of constitutive model. Triaxial tests on Hostun sand are selected as training and testing data. The Bayesian method is enhanced based on transitional Markov chain Monte Carlo method, whereby the generalization ability for each model is simultaneously evaluated, for the model selection. The most plausible/suitable model in terms of predictive ability, generalization ability, and model complexity is selected using training data. The performance of the method is then validated by testing data. Finally, a series of drained triaxial tests on Karlsruhe sand is used for further evaluating the performance. 相似文献
4.
Optimization techniques for identifying soil parameters in geotechnical engineering: Comparative study and enhancement 下载免费PDF全文
下载免费PDF全文 A comparative study of optimization techniques for identifying soil parameters in geotechnical engineering was first presented. The identification methodology with its 3 main parts, error function, search strategy, and identification procedure, was introduced and summarized. Then, current optimization methods were reviewed and classified into 3 categories with an introduction to their basic principles and applications in geotechnical engineering. A comparative study on the identification of model parameters from a synthetic pressuremeter and an excavation tests was then performed by using 5 among the mostly common optimization methods, including genetic algorithms, particle swarm optimization, simulated annealing, the differential evolution algorithm and the artificial bee colony algorithm. The results demonstrated that the differential evolution had the strongest search ability but the slowest convergence speed. All the selected methods could reach approximate solutions with very small objective errors, but these solutions were different from the preset parameters. To improve the identification performance, an enhanced algorithm was developed by implementing the Nelder‐Mead simplex method in a differential algorithm to accelerate the convergence speed with strong reliable search ability. The performance of the enhanced optimization algorithm was finally highlighted by identifying the Mohr‐Coulomb parameters from the 2 same synthetic cases and from 2 real pressuremeter tests in sand, and ANICREEP parameters from 2 real pressuremeter tests in soft clay. 相似文献
5.
Soft structured clays usually exhibit complex behaviors, which can lead to difficulties in the determination of parameters and high testing costs. This paper aims to propose an efficient optimization method for identifying the parameters of advanced constitutive model for soft structured clays from only limited conventional triaxial tests. First, a new real-coded genetic algorithm (RCGA) is proposed by combining two new crossover and mutation operators for improving the performance of optimization. A newly developed elastic–viscoplastic model accounting for anisotropy, destructuration and creep features is enhanced with the cross-anisotropy of elasticity and is adopted for test simulations during optimization. Laboratory tests on soft Wenzhou marine clay are selected, with three of them being used as objectives for optimization and others for validation. The optimization process, using the new RCGA with a uniform sampling initialization method, is carried out to obtain the soil parameters. A classic genetic algorithm (NSGA-II)-based optimization is also conducted and compared to the RCGA for estimating the performance of the new RCGA. Finally, the optimal parameters are validated by comparing with other measurements and test simulations on the same clay. All comparisons demonstrate that a reliable solution can be obtained by the new RCGA optimization combined with the appropriate soil model, which is practically useful with a reduction in testing costs. 相似文献
6.
This paper describes the numerical simulation of two dynamic centrifuge tests on reduced scale models of shallow tunnels in dry sand, carried out using both an advanced bounding surface plasticity constitutive soil model and a simple Mohr–Coulomb elastic-perfectly plastic model with embedded nonlinear and hysteretic behaviour. The predictive capabilities of the two constitutive models are assessed by comparing numerical predictions and experimental data in terms of accelerations at several positions in the model, and bending moment and hoop forces in the lining. Computed and recorded accelerations match well, and a quite good agreement is achieved also in terms of dynamic bending moments in the lining, while numerical and experimental values of the hoop force differ significantly with one another. The influence of the contact assumption between the tunnel and the soil is investigated by comparing the experimental data and the numerical results obtained with different interface conditions with the analytical solutions. The overall performance of the two models is very similar indicating that at least for dry sand, where shear-volumetric coupling is less relevant, even a simple model can provide an adequate representation of soil behaviour under dynamic conditions. 相似文献
7.
SEYYED MOHAMMAD MOUSAVI AMIR HOSSEIN ALAVI AMIR HOSSEIN GANDOMI ALI MOLLAHASANI 《Journal of Earth System Science》2011,120(6):1001-1022
New nonlinear solutions were developed to estimate the soil shear strength parameters utilizing linear genetic programming
(LGP). The soil cohesion intercept (c) and angle of shearing resistance (ϕ) were formulated in terms of the basic soil physical properties. The best models were selected after developing and controlling
several models with different combinations of influencing parameters. Comprehensive experimental database used for developing
the models was established upon a series of unconsolidated, undrained, and unsaturated triaxial tests conducted in this study.
Further, sensitivity and parametric analyses were carried out. c and ϕ were found to be mostly influenced by the soil unit weight and liquid limit. In order to benchmark the proposed models, a
multiple least squares regression (MLSR) analysis was performed. The validity of the models was proved on portions of laboratory
results that were not included in the modelling process. The developed models are able to effectively learn the complex relationship
between the soil strength parameters and their contributing factors. The LGP models provide a significantly better prediction
performance than the regression models. 相似文献
8.
Arsalan Ghorbanian Mahmod Reza Sahebi Ali Mohammadzadeh 《Comptes Rendus Geoscience》2019,351(4):332-339
This study suggests a novel approach to the retrieval of soil surface parameters using a single-acquisition single-configuration synthetic-aperture radar (SAR) system. Soil surface parameters such as soil moisture and surface roughness are key elements for many environmental studies, including Earth surface water cycles, energy exchange, agriculture, and geology. Remote sensing techniques, especially SAR data, are commonly used to retrieve such soil surface parameters over large areas. Several backscattering models have been proposed for soil surface parameters retrieval from SAR data. However, commonly, these backscattering models require multi configuration SAR data, including multi-polarization, multi-frequency, and multi-incidence angle. Here we propose a methodology that employs single-acquisition single-configuration SAR data for the retrieval of soil surface parameters. The originality is to use single-acquisition single-configuration SAR data to retrieve the soil surface parameters using an optimization approach by the genetic algorithm (GA); we have used the modified Dubois model (MDM) in HH polarization as the backscattering model. Three HH polarization and C band data sets from Quebec (Radarsat-1), Ontario (SIR-C), and Oklahoma (AIRSAR) were analyzed. The retrieved values of soil moisture and soil surface roughness were then compared to ground truth measurements with corresponding parameters. We employed diverse criteria, including the mean absolute error (MAE), the root mean square error (RMSE), the coefficient of performance (CP), and the correlation coefficient to investigate the performance of the proposed methodology. This analysis suggests the capability of the GA for the retrieval of soil surface parameters. Based on our findings, this method presents a viable alternative approach to the retrieval of soil surface parameters when only single-acquisition single-configuration SAR data is available. 相似文献
9.
基于Yang和Ahmed[1－5]等提出的砂土液化大变形本构模型,对该模型的硬化规则和弹塑性模量确定方法作了改进,把该本构模型扩展应用到三维液化大变形的数值分析中,实现了基于ABAQUS大型商用软件计算平台上砂土液化大变形的计算子程序开发。基于该计算平台,对该模型的主要参数在描述砂土液化动孔隙水压力增长和动应力-应变关系曲线等方面的可靠性和敏感性进行了研究。给出了模型全过程参数、剪胀过程参数、剪缩与剪胀状态转换点流动变形量控制参数对试样的应力-应变关系曲线的影响程度及其规律,并对模型的主要参数的敏感性进行了分析,所得结论为通过动三轴试验获得相关模型参数提供了有效的指导和帮助,同时也发展了砂土液化大变形新的数值计算方法。 相似文献
10.
The paper at hand investigates a strategy to calibrate different constitutive models for soils via back analysis. The efficiency and reliability of the parameter identification for soil models is worked out. In order to demonstrate of how to utilise identification procedures, results from optimisation against conventional oedometer and drained triaxial compression tests on natural Pappadai clay are presented and discussed. The aim of geotechnical optimisation problems is to obtain a set of model parameter values that provide the best match between soil model simulations and appropriate measurements. For the parameter identification process, a constrained population-based algorithm is chosen, namely the Particle Swarm Optimiser. The identification is carried out in an initial step separately on each test and then simultaneously on oedometer and triaxial tests. The evaluation is performed employing three different constitutive models of varying complexity and number of constitutive parameters.A subsequent residual analysis and the computation of confidence intervals for the parameters provide valuable results to assess the quality of the identified parameters in correlation with the evaluated data. Therefore, criteria of the utility and reliability of the mathematical models for further prognosis computations can be estimated. 相似文献
11.
马露 《水文地质工程地质》2021,48(4):72-77
我国南海神狐海域海底沉积物主要由钙质砂与无黏性土组成,其力学性质对海洋工程的稳定性具有显著影响。无黏性土的压缩特性是研究其力学性能的重要内容之一,为分析不同荷载作用下土样的压缩特性,利用高压三轴仪试验系统,开展了不同砂含量及不同初始孔隙比下无黏性土样的等向压缩试验。试验结果表明:在试验采用的高有效应力下,无黏性土具有显著的过渡土性质,初始组构难以被改变;随多孔易碎钙质砂含量的增加,土样可压缩性和压缩曲线的收敛度均增加,钙质砂的破碎显著改变了初始组构。提出可以描述含砂无黏性土压缩特性的数学模型,所含参数物理意义明确且易于确定。与不同砂土压缩试验数据对比发现,该模型对其他种类土同样具有较好的拟合度,验证了本模型的广泛适用性。与已有压缩模型的对比,验证了本模型的实用性,为无黏性土应力-应变关系的理论研究提供基础。 相似文献
12.
In this paper, an enhanced backtracking search algorithm (so-called MBSA-LS) for parameter identification is proposed with two modifications: (a) modifying the mutation of original backtracking search algorithm (BSA) considering the contribution of current best individual for accelerating convergence speed and (b) novelly incorporating an efficient differential evolution (DE) as local search for improving the quality of population. The proposed MBSA-LS is first validated with better performance than the original BSA and some other typical state-of-the-art optimization algorithms on a benchmark of soil parameter identification in terms of effectiveness, efficiency, and robustness. Then, the efficiency of the MBSA-LS is further illustrated by two representative cases: identifying soil parameters from both laboratory tests and field measurements. All comparisons demonstrate that the proposed MBSA-LS algorithm can give accurate results in a short time. Finally, to conveniently solve the problems of parameter identification, a practical tool ErosOpt for parameter identification is developed by integrating the proposed MBSA-LS and some other efficient algorithms for readers to conduct the parameter identification using optimisation algorithms. 相似文献
13.
分别开展砂土和粉质黏土两种典型土质条件下基坑悬臂式开挖离心模型试验,详细叙述试验过程中所要解决的关键问题,并提出合理的解决方案。通过对比分析两组试验结果,得到以下结论：非饱和土地基制备中参数控制困难,分层夯实法有待进一步改进,而砂雨法制备的砂土地基参数可控性更好;两组试验的结果有差异,砂土地基试验所呈现的土压力、地基变形、支护弯矩的变化规律更好,因此,岩土离心试验可适当考虑以砂土代替非饱和土;对于采用悬臂式支护结构的基坑,开挖引起的地表沉降曲线在砂土中呈指数型,而在粉质黏土中呈直线型;开挖引起的粉质黏土地基土体位移范围较砂土地基更大;开挖引起的砂土中挡墙弯矩较粉质黏土更大,砂土和粉质黏土中最大弯矩位置都随开挖逐渐下移;在砂土试验中开挖引起主动区土压力各处均减小,而在粉质黏土试验中开挖引起土压力在挡墙底有增大趋势。该基坑工程离心模型试验过程及数据处理方法可为进一步试验提供参考。 相似文献
14.
This paper investigates the numerical performance of the generalized trapezoidal integration rule by using an advanced soil model. The generalized trapezoidal integration rule can include many other integration algorithms by adjusting a single parameter α ranging from 1 to 0. The soil model used is the recently developed middle surface concept (MSC) sand model which simulates different soil response characteristics by using different pseudo‐yield functions. The generalized trapezoidal rule and MSC sand model are used to simulate the responses of sand samples with different relative densities under various initial and loading conditions. Instead of a single step, multiple loading steps bring the sample to the vicinity of failure. These comprehensive investigations examine and compare the influences of various values of α on the numerical solution of integrated constitutive equations, the convergence of Newton's iterative scheme, and the integration accuracy. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
15.
Li Yunkai Tian Yingjie Ouyang Zhiyun Wang Lingyan Xu Tingwu Yang Peiling Zhao Huanxun 《Environmental Earth Sciences》2010,60(7):1559-1568
Sand production by soil erosion in small watershed is a complex physical process. There are few physical models suitable to
describe the characteristics of the intense erosion in domestic loess plateau. Introducing support vector machine (SVM) oriented
to small sample data and possessing good extension property can be an effective approach to predict soil erosion because SVM
has been applied in hydrological prediction to some extent. But there are no effective methods to select the rational parameters
for SVM, which seriously limited the practical application of SVM. This paper explored the application of intelligence-based
particle swarm optimization (PSO) algorithm in automatic selection of parameters for SVM, and proposed a prediction model
by linking PSO and SVM for small sample data analysis. This method utilized the high efficiency optimization property and
swarm paralleling property of PSO algorithm and the relatively strong learning and extending capacity of SVM. For an example
of Huangfuchuan small watershed, its intensive fragmentation and intense erosion earn itself the name of “worst erosion in
the world”. Using four characteristics selection algorithms of correlation feature selection, the primary affecting factors
for soil erosion in this small watershed were determined to be the channel density, ravine area, sand rock proportion, and
the total vegetation coverage. Based on the proposed PSO–SVM algorithm, the soil erosion modulus in the small watershed was
predicted. The accuracy of the simulation and prediction was good, and the average error was 3.85%. The SVM predicting model
was based on the monitoring data of sand production. The construction of the SVM erosion modulus prediction model for the
small watershed comprehensively reflected the complex mechanism of soil erosion and sand production. It had certain advantage
and relatively high practical value in small sample prediction in the discipline of soil erosion. 相似文献
16.
冻土的蠕变特性对深井冻结法施工至关重要。针对某矿区人工冻土在-5℃、-10℃、-15℃和-20℃下进行单轴抗压强度试验,发现冻土的抗压强度受冻结温度变化影响,两者间为线性反比例关系。通过小生境原理对传统的遗传算法作模糊随机改进,给出模糊遗传算法的步骤思路,进而运用该算法反演冻土蠕变模型中的参数值,获得各温度下的蠕变模型。试验结果表明：蠕变模型计算值在蠕变各阶段与试验值吻合较好,准确反映了冻土蠕变的整体规律。可见,模糊遗传算法能有效反演蠕变参数,较传统方法更符合工程实际。 相似文献
17.
Large sets of soil experimental data (field and laboratory) are becoming increasingly available for calibration of soil constitutive models. A challenging task is to calibrate a potentially large number of model parameters to satisfactorily match many data sets simultaneously. This calibration effort can be facilitated by optimization techniques. The current study aims to explore systematic approaches for exercising optimization and sensitivity analysis in the area of soil constitutive modelling. Analytical, semi‐analytical and numerical optimization techniques are employed to calibrate a multi‐surface‐plasticity sand model. Calibration is based on results from a number of drained triaxial sample tests and a dynamic centrifuge liquefaction test. The analytical and semi‐analytical approaches and associated sensitivity analysis are applied to calibrate the model non‐linear shear stress–strain response. Thereafter, model parameters controlling shear–volume coupling effects (dilatancy) are calibrated using a solid–fluid fully coupled finite element program in conjunction with an advanced numerical optimization code. A related sensitivity study reveals the challenges often encountered in optimizing highly non‐linear functions. Overall, this study demonstrates applicability and limitations of optimization techniques for constitutive model calibration. Copyright © 2003 John Wiley & Sons, Ltd. 相似文献
18.
This study back analyzed deformation parameters of in situ sand through two excavation case histories in Kaohsiung, Taiwan. Two main features are highlighted; deformation prediction based on monitoring data at the first excavation stage and in situ Young’s modulus evaluation for sand considering monitoring data at the overall excavation stages. The former tends to establish a reliable method to predict the wall deflection at the critical stage based on the data at the first stage and the latter to enrich the limited database of Young’s modulus correlation for sand, specifically applicable for deep excavations analysis. The two constitutive models, linear elastic perfectly plastic and non-linear stress–strain constitutive models, were selected. The stiffness parameters of the models were discretely distributed along the subdivided soil body mesh to reflect the effect of overburden pressure on the in situ soil. In addition, relationship between Standard Penetration Test value (SPT-N value) and Young’s modulus and relationships for estimating the in situ Young’s modulus of the Kaohsiung sand as a function of depth were evaluated. The results greatly enhanced a framework for estimating the in situ Young’s modulus of sand. 相似文献
19.
SHARAFUTDINOV Rafael 《岩土力学》2022,43(10):2873-2886
砂土的密度和应力状态对其刚度有很大的影响。计算岩土工程中许多硬化土体模型都是基于邓肯−张模型得出的,没有考虑到密度对砂土刚度的影响。而在极致密或松散的砂土的三轴压缩过程中,剪切应变的上升会引起密度的显著变化。为了评估粒径分布、密度及应力状态对砂土刚度的影响,使用统计和回归方法对来自莫斯科和明斯克的15个建筑工地的962个土壤样本的各向同性三轴试验数据进行分析。基于密度和应力状态参数的影响,提出了评估不同粒径砂土刚度的经验方程。对来自欧洲、印度和美国的冲积土和陆地土试验的比较分析表明,其砂土的刚度与莫斯科和明斯克的砂土在同一范围。所提出的方程可用于初步估计有限元法计算里的刚度参数,也可应用于岩土工程模型（允许考虑刚度的变化、水平和垂直分布）。此外,还提出了基于邓肯−张模型的半经验关系。当密度的变化影响土的刚度时,该半经验关系可为受到大变形和（或）复杂加载路径影响的松散和非常致密的砂土提供更为真实的结果。一般来说,岩土工程师可将获得的结果应用于更为复杂的土体模型设计中。 相似文献
20.
Various constitutive models have been proposed, and previous studies focused on identifying parameters of specified models. To develop the smart construction, this paper proposes a novel optimization-based intelligent model selection procedure in which parameter identification is also performed during staged excavation. To conduct the model selection, a database of seven constitutive models accounting for isotropic or anisotropic yield surface, isotropic or anisotropic elasticity, or small strain stiffness for clayey soils is established, with each model numbered and deemed as one additional parameter for optimization. A newly developed real-coded genetic algorithm is adopted to evaluate the performance of simulation against field measurement. As the process of optimization goes on, the soil model exhibiting good performance during simulation survives from the database and model parameters are also optimized. For each excavation stage, with the selected model and optimized parameters, wall deflection and ground surface settlement of the subsequent unexcavated stage are predicted. The proposed procedure is repeated until the entire excavation is finished. This proposed procedure is applied to a real staged excavation with field data, which demonstrates its effectiveness and efficiency in engineering practice with highlighting the importance of anisotropic elasticity and small strain stiffness in simulating excavation. All results demonstrate that the current study has both academic significance and practical significance in providing an efficient and effective approach of adaptive optimization-based model selection with parameters updating in engineering applications.
相似文献