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1.
Optimization techniques for identifying soil parameters in geotechnical engineering: Comparative study and enhancement 
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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
2.
The Barcelona basic model (BBM) successfully explained many key features of unsaturated soils and received extensive acceptance. It is also one of the few elastoplastic constitutive models for unsaturated soils that have been implemented within finite element codes and applied to the analysis of real boundary value problems. The BBM was proposed in incremental forms according to theories of soil plasticity in which individual aspects of the isotropic virgin behavior are controlled by multiple parameters, whereas at the same time, a single parameter controls more than one aspect of soil behavior. Although a variety of methods have been recently developed for calibrating model parameters for elastoplastic soil models, at present, there are no well‐established, simple, and objective methods for selecting parameter values in the BBM from laboratory tests. This has been one of the major obstacles to the dissemination of this constitutive model beyond the research context. This article presents an optimization approach especially developed for simple and objective identification of material parameters in the BBM. This is achieved by combining a modified state surface approach, recently proposed to model the elastoplastic behavior of unsaturated soils under isotropic stress conditions, with the Newton or quasi‐Newton method to simultaneously determine the five parameters governing isotropic virgin behavior in the BBM. The comparison between results using the proposed method and an existing method for the same laboratory tests was discussed from which the simplicity and objectivity of the proposed method were evaluated. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
3.
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
4.
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
5.
Simulation-based optimization methods have been recently proposed for calibrating geotechnical models from laboratory and field tests. In these methods, geotechnical parameters are identified by matching model predictions to experimental data, i.e. by minimizing an objective function that measures the difference between the two. Expensive computational models, such as finite difference or finite element models are often required to simulate laboratory or field geotechnical tests. In such cases, simulation-based optimization might prove demanding since every evaluation of the objective function requires a new model simulation until the optimum set of parameter values is achieved. This paper introduces a novel simulation-based “hybrid moving boundary particle swarm optimization” (hmPSO) algorithm that enables calibration of geotechnical models from laboratory or field data. The hmPSO has proven effective in searching for model parameter values and, unlike other optimization methods, does not require information about the gradient of the objective function. Serial and parallel implementations of hmPSO have been validated in this work against a number of benchmarks, including numerical tests, and a challenging geotechnical problem consisting of the calibration of a water infiltration model for unsaturated soils. The latter application demonstrates the potential of hmPSO for interpreting laboratory and field tests as well as a tool for general back-analysis of geotechnical case studies. 相似文献
6.
临界滑动面的获得是土质边坡稳定性分析中一个必要的过程,然而现有分析方法难以保证该临界滑面的准确性,而且部分分析方法在计算过程中会陷入局部最小值陷阱。基于单变量方法和最速梯度法,提出了交替变量局部梯度法,该方法能够突破最优化方法应用在边坡稳定性分析上的瓶颈。首先,通过斯宾塞极限平衡方法和网格搜索法（或者其他确定临界滑面的方法）,获得边坡初始椭球状临界滑面;其次,在该滑面上布置若干节点作为变量,目标函数为安全系数Fs关于空间节点坐标Zi的方程,为了使目标函数快速降低,沿负梯度方向循环优化每个节点,当满足一定精度要求时,即可获得三维土质边坡非圆弧状临界滑动面;最后,通过算例证明该方法可行,计算结果可靠。 相似文献
7.
水文地质参数的正确与否是构建地下水数值模型的根本,而参数寻优结果很大程度上取决于优化算法的选择。禁忌搜索算法是一种广泛应用于组合优化问题的启发式全局寻优算法,但在连续函数优化领域应用比较少。基于上述考虑,本文首先引入求解连续函数优化问题的连续禁忌搜索算法并对其进行改进,进而提出一种连续禁忌搜索改进算法(ICTS),最后将其与地下水模型耦合进行水文地质参数识别。算例研究表明,ICTS算法较其他算法(CTS,SGA,Micro-GA,PSO)求解效率提高1.87～4.64倍,求解精度提高1.08～12.86倍。因此ICTS算法在参数反演计算中求解精度高、收敛速度快、寻优性能强,是一种值得推广的水文地质参数识别方法。 相似文献
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水文地质参数寻优结果的好坏会直接影响到地下水数值模拟的精度,而参数寻优结果很大程度上取决于寻优方法的选择。粒子群算法是一种基于群智能的随机全局寻优方法,算法的缺陷是后期搜索效率低劣。基于随机寻优算法的混合策略,引入有效的约束处理手段和粒子群算法惯性因子的动态非线性调整技术,有机融合粒子群算法与Hooke-Jeeves方法,提出一种适用于水文地质参数反演的HJPSO混合算法。应用研究表明,HJPSO混合算法在参数反演计算中求解精度高、收敛速度快、寻优性能强,是一种值得推广的水文地质参数识别方法。 相似文献
9.
This paper presents a two-surface plasticity constitutive model based on critical-state soil mechanics and describes a practical process for the determination of its parameters. Determination of the constitutive model parameters can be done in a hierarchical manner, starting with the model parameters that have the most bearing on sand behavior and that can be determined using routine experimental procedures. Most parameters can be determined through simple curve fitting through experimental data points. The constitutive model is calibrated against experimental data for Toyoura sand, clean Ottawa sand and mixtures of Ottawa sand with non-plastic silt. The model simulates closely the mechanical response of sands under various loading conditions and predicts both drained and undrained behavior of sands at small and large strains using the actual small-strain shear modulus, as measured in resonant column or bender elements tests, along with realistic values of Poisson’s ratio. Performance of the model in simulating sand response is demonstrated for a variety of initial states and loading conditions. 相似文献
10.
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
11.
The development of a coupled damage‐plasticity constitutive model for concrete is presented. Emphasis is put on thermodynamic admissibility, rigour and consistency both in the formulation of the model, and in the identification of model parameters based on experimental tests. The key feature of the thermodynamic framework used in this study is that all behaviour of the model can be derived from two specified energy potentials, following procedures established beforehand. Based on this framework, a constitutive model featuring full coupling between damage and plasticity in both tension and compression is developed. Tensile and compressive responses of the material are captured using two separate damage criteria, and a yield criterion with a multiple hardening rule. A crucial part of this study is the identification of model parameters, with these all being shown to be identifiable and computable based on standard tests on concrete. Behaviour of the model is assessed against experimental data on concrete. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
12.
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
13.
A five-step procedure involving mathematical formulation, identification and determination of parameters and verification is presented for development and selection of appropriate and reliable constitutive law(s) for geologic media. Comprehensive analyses are performed toward determination of an appropriate law for a (artificial) soil. The most suitable model is obtained by critical evaluation of four different plasticity models; here verification and comparisons of predictions with observations from laboratory tests, and with those from two boundary value problems are used as the basis of the selection. The model thus selected is found to be appropriate for applications to relevant practical problems. 相似文献
14.
为了得到三维边坡的临界滑裂面,提出了6个参数控制的三维滑裂面构造方法,基于边坡三维最小势能稳定性分析方法建立目标函数,采用遗传算法实现了临界滑裂面的搜索,并开发了相应的搜索程序。为检验文中搜索方法的合理性,将其与其他方法得到的临界滑裂面以及最小安全系数进行比较,并且将室内模型试验得到的临界滑面与理论搜索的结果进行对比。研究表明：搜索方法可实现稳步收敛;针对算例进行多变量同时变化的搜索验算,得到了与极限平衡法较为接近的结果,表明提出的搜索方法是合理的;理论计算结果与室内模型试验坡面加载得到的边坡临界滑面较为接近,再次验证三维边坡临界滑面搜索方法是可行的。 相似文献
15.
从最优化数学理论角度对大气廓线物理反演以及卫星辐射率资料直接同化中的最优化算法进行了回顾。分析了各种方法的优点和缺点、联系和差别。总结了卫星大气遥感反演问题的求解思路。对大气廓线反演研究中几种主要的目标函数和寻优策略进行了分析,着重分析了目前作为各数值预报中心和卫星数据处理中心业务数值产品核心算法的牛顿非线性迭代法的不足之处,并对其改进途径进行了探讨。引入了Levenberg-Marquardt方法及信赖域方法用于大气廓线反演,使反演算法的收敛性质得到改善。 相似文献
16.
A non-linear optimization technique based on the quasi-Newton approach is employed to back-calculate certain model parameters of a simple, bounding surface, soil plasticity model from in situ pressuremeter data. The theoretical response corresponding to a given set of parameters is generated by finite element analysis. A semi-analytical procedure is developed for the accurate and efficient evaluation of the gradient of objective function with respect to the model parameters of interest. The BFGS update is used to update the Hessian. Results of a series of numerical experimentation using artificial pressuremeter responses is first reported and discussed. A set of laboratory cavity expansion data is then used to calibrate the constitutive model. 相似文献
17.
S. W. Sloan 《国际地质力学数值与分析法杂志》1988,12(1):61-77
This paper describes a technique for computing lower bound limit loads in soil mechanics under conditions of plane strain. In order to invoke the lower bound theorem of classical plasticity theory, a perfectly plastic soil model is assumed, which may be either purely cohesive or cohesive-frictional, together with an associated flow rule. Using a suitable linear approximation of the yield surface, the procedure computes a statically admissible stress field via finite elements and linear programming. The stress field is modelled using linear 3-noded traingles and statically admissible stress discontinuities may occur at the edges of each triangle. Imposition of the stress-boundary, equilibrium and yield conditions leads to an expression for the collapse load which is maximized subject to a set of linear constraints on the nodal stresses. Since all of the requirements for a statically admissible solution are satisfied exactly (except for small round-off errors in the optimization computations), the solution obtained is a strict lower bound on the true collapse load and is therefore ‘safe’. A major drawback of the technique, as first described by Lysmer,1 is the large amount of computer time required to solve the linear programming problem. This paper shows that this limitation may be avoided by using an active set algorithm, rather than the traditional simplex or revised simplex strategies, to solve the resulting optimization problem. This is due to the nature of the constraint matrix, which is always very sparse and typically has many more rows that columns. It also proved that the procedure can, without modification, be used to derive strict lower bounds for a purely cohesive soil which has increasing strength with depth. This important class of problem is difficult to tackle using conventional methods. A number of examples are given to illustrate the effectiveness of the procedure. 相似文献
18.
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
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20.
Youssef M.A. Hashash Séverine Levasseur Abdolreza Osouli Richard Finno Yann Malecot 《Computers and Geotechnics》2010
Performance observation is a necessary part of the design and construction process in geotechnical engineering. For deep urban excavations, empirical and numerical methods are used to predict potential deformations and their impacts on surrounding structures. Two inverse analysis approaches are described and compared for an excavation project in downtown Chicago. The first approach is a parameter optimization approach based on genetic algorithm (GA). GA is a stochastic global search technique for optimizing an objective function with linear or non-linear constraints. The second approach, self-learning simulations (SelfSim), is an inverse analysis technique that combines finite element method, continuously evolving material models, and field measurements. The optimization based on genetic algorithm approach identifies material properties of an existing soil model, and SelfSim approach extracts the underlying soil behavior unconstrained by a specific assumption on soil constitutive behavior. The two inverse analysis approaches capture well lateral wall deflections and maximum surface settlements. The GA optimization approach tends to overpredict surface settlements at some distance from the excavation as it is constrained by a specific form of the material constitutive model (i.e. hardening soil model); while the surface settlements computed using SelfSim approach match the observed ones due to its ability to learn small strain non-linearity of soil implied in the measured settlements. 相似文献