An alternative single-step algorithm for dynamic problems

In this paper we consider a one-step form of the weighted residual method for solving equations of motion for discrete structural problems. The resulting time integration algorithm is equivalent to the Newmark method for a restricted but important range of the parameters. The weighted residual treatment of the forcing function permits use of time increments based solely on the expected periods of the structural response, instead of the usual additional restrictions based on the periods of the forcing function. A numerical example is included to illustrate the behaviour of the algorithm for a forced ground motion with both low- and high-frequency components.     

地球物理问题的自适应模拟退火方法求解

对应用模拟退火方法来处理具有多参数性和非线性特点的地球物理问题时，温度参数和退火过程难以选取，需通过反复试验，不便于应用的缺陷，通过对晶体生长过程的分析，提出了温度参数的确定方法，不同的参数退火速度可以调节．使得本文所述算法具有自适应的特点，便于实际应用，通过理论和实际试算，证明了该方法的正确有效性．     

Optimal control algorithm and neural network for dynamic groundwater management

Researchers have found that obtaining optimal solutions for groundwater resource‐planning problems, while simultaneously considering time‐varying pumping rates, is a challenging task. This study integrates an artificial neural network (ANN) and constrained differential dynamic programming (CDDP) as simulation‐optimization model, called ANN‐CDDP. Optimal solutions for a groundwater resource‐planning problem are determined while simultaneously considering time‐varying pumping rates. A trained ANN is used as the transition function to predict ground water table under variable pumping conditions. The results show that the ANN‐CDDP reduces computational time by as much as 94·5% when compared to the time required by the conventional model. The proposed optimization model saves a considerable amount of computational time for solving large‐scale problems. Copyright © 2009 John Wiley & Sons, Ltd.     

单自由度系统地震动力反应的实时计算方法

本文对计算单自由度系统地震动力反应的频域方法和时域方法进行了分析比较。说明了目前时域方法所存在的问题,指出寻找一种在计算精度上与频域方法等价的时域算法是一个值得研究的重要课题。据此,本文提出了一套能较精确模拟单自由度系统传递函数的时域方法。其计算格式采用具有较高计算效率的递归格式。理论分析与数值试验表明,该方法具有精度优于其他时域算法、速度快的特点,可应用于强震观测台网中强地震动参数的实时计算。     

Use of a Lanczos algorithm in dynamic analysis of structures

In this paper the Choleski factorization of the mass or the stiffness matrix and its use in reduction of the general free vibration equation to a standard eigenproblem prior to the application of the Lanczos method is described, and their effects on the necessary computing time in determination of the frequencies are discussed.     

Performance of a transparent Flexible Shear Beam container for geotechnical centrifuge modeling of dynamic problems

A transparent Flexible Shear Beam (FSB) container was designed and constructed to simulate the dynamic response of a stratum of soil under horizontal, one-dimensional (1-D) earthquake shaking in a geotechnical centrifuge. A stack of four rectangular, acrylic frames separated by layers of flexible, high-strength rubber was used to form the transparent container. The fundamental natural frequency of the container was estimated to be similar to a layer of sand in its softened or liquefied state. The suitability of the container in simulating 1-D site response with minimal boundary effects was evaluated by monitoring the uniformity of the induced accelerations and settlements across the soil specimen. Further, the measured lateral displacements were compared with equivalent-linear site response analyses. The new FSB container was found to provide satisfactory boundary conditions for studying complex Soil–Structure-Interaction problems, while simultaneously enabling researchers to visualize deformations of the soil and buried structures during shaking.     

A parallel dynamic programming algorithm for multi-reservoir system optimization

This paper develops a parallel dynamic programming algorithm to optimize the joint operation of a multi-reservoir system. First, a multi-dimensional dynamic programming (DP) model is formulated for a multi-reservoir system. Second, the DP algorithm is parallelized using a peer-to-peer parallel paradigm. The parallelization is based on the distributed memory architecture and the message passing interface (MPI) protocol. We consider both the distributed computing and distributed computer memory in the parallelization. The parallel paradigm aims at reducing the computation time as well as alleviating the computer memory requirement associated with running a multi-dimensional DP model. Next, we test the parallel DP algorithm on the classic, benchmark four-reservoir problem on a high-performance computing (HPC) system with up to 350 cores. Results indicate that the parallel DP algorithm exhibits good performance in parallel efficiency; the parallel DP algorithm is scalable and will not be restricted by the number of cores. Finally, the parallel DP algorithm is applied to a real-world, five-reservoir system in China. The results demonstrate the parallel efficiency and practical utility of the proposed methodology.     

Hydrological modeling using a dynamic neuro-fuzzy system with on-line and local learning algorithm

This paper introduces the dynamic neuro-fuzzy local modeling system (DNFLMS) that is based on a dynamic Takagi–Sugeno (TS) type fuzzy inference system with on-line and local learning algorithm for complex dynamic hydrological modeling tasks. Our DNFLMS is aimed to implement a fast training speed with the capability of on-line simulation where model adaptation occurs at the arrival of each new item of hydrological data. The DNFLMS applies an on-line, one-pass, training procedure to create and update fuzzy local models dynamically. The extended Kalman filtering algorithm is then implemented to optimize the parameters of the consequence part of each fuzzy model during the training phase. Local generalization in the DNFLMS is employed to optimize the parameters of each fuzzy model separately, region-by-region, using subsets of training data rather than all training data.     

A methodology for quantifying the value of spatial information for dynamic Earth problems

We develop a methodology for assessing the value of information (VOI) from spatial data for groundwater decisions. Two sources of uncertainty are the focus of this VOI methodology: the spatial heterogeneity (how it influences the hydrogeologic response of interest) and the reliability of geophysical data (how they provide information about the spatial heterogeneity). An existing groundwater situation motivates and in turn determines the scope of this research. The objectives of this work are to (1) represent the uncertainty of the dynamic hydrogeologic response due to spatial heterogeneity, (2) provide a quantitative measure for how well a particular information reveals this heterogeneity (the uncertainty of the information) and (3) use both of these to propose a VOI workflow for spatial decisions and spatial data. The uncertainty of the hydraulic response is calculated using many Earth models that are consistent with the a priori geologic information. The information uncertainty is achieved quantitatively through Monte Carlo integration and geostatistical simulation. Two VOI results are calculated which demonstrate that a higher VOI occurs when the geophysical attribute (the data) better discriminates between geological indicators. Although geophysical data can only indirectly measure static properties that may influence the dynamic response, this transferable methodology provides a framework to estimate the value of spatial data given a particular decision scenario.     

Directional interpolation infinite element for dynamic problems in saturated porous media

In this study, a directional interpolation infinite element suited to a saturated porous medium is presented to account for dynamic problems with semi-infi     

Model updating for real time dynamic substructures based on UKF algorithm

Combining the advantages of numerical simulation with experimental testing, real-time dynamic substructure (RTDS) testing provides a new experimental method for the investigation of engineered structures. However, not all unmodeled parts can be physically tested, as testing is often limited by the capacity of the test facility. Model updating is a good option to improve the modeling accuracy for numerical substructures in RTDS. In this study, a model updating method is introduced, which has great performance in describing this nonlinearity. In order to determine the optimal parameters in this model, an Unscented Kalman Filter (UKF)-based algorithm was applied to extract the knowledge contained in the sensors data. All the parameters that need to be identified are listed as the extended state variables, and the identification was achieved via the step-by-step state prediction and state update process. Effectiveness of the proposed method was verified through a group of experimental data, and results showed good agreement. Furthermore, the proposed method was compared with the Extended Kalman Filter (EKF)-based method, and better accuracy was easily found. The proposed parameter identification method has great applicability for structural objects with nonlinear behaviors and could be extended to research in other engineering fields.     

欧拉梁动力反应初边值问题的微分求积解

动荷载作用下欧拉梁动响应的计算是一个初边值问题,通常很难得到解析解,传统数值方法一般是把空间和时间分别离散进行求解,计算相对复杂,效率也不高.针对分布动荷载作用下欧拉梁的振动偏微分方程,采用传统微分求积法,在空间和时间上同时进行离散;对于所有非0阶的初/边值条件,采用嵌入法在权系数计算中予以考虑.算例的数值结果与精确解的对比证明采用传统微分求积法处理此问题是可行的,而且是高效的.对于实际工程中的其他类似问题,该方法同样适用.     

动力机器基础振动与设计若干问题的讨论

讨论了《动力机器基础设计规范》(GB 50040-96)中的若干问题,包括质-弹-阻模型、地基动力参数、荷载组合和基础的构造要求等几个方面。对动力响应,基于弹性半空间理论定义质-弹-阻模型中引入的各个参数(频变),基于该模型计算稳态荷载或暂态荷载作用下基础的动力响应;引入承载力、变形和稳定性等的验算,并在基础的形状尺寸、埋深、材料、配筋等构造方面为设计人员提供指导;对基础的重要程度进行分类,对重要基础,特殊场地条件下的基础,建造时宜考虑沉降等观测手段,及可改变基础固有特性和加固维修等相关的措施。     

A least-squares penalty method algorithm for inverse problems of steady-state aquifer models

Based on the generalized Gauss–Newton method, a new algorithm to minimize the objective function of the penalty method in (Bentley LR. Adv Wat Res 1993;14:137–48) for inverse problems of steady-state aquifer models is proposed. Through detailed analysis of the “built-in” but irregular weighting effects of the coefficient matrix on the residuals on the discrete governing equations, a so-called scaling matrix is introduced to improve the great irregular weighting effects of these residuals adaptively in every Gauss–Newton iteration. Numerical results demonstrate that if the scaling matrix equals the identity matrix (i.e., the irregular weighting effects of the coefficient matrix are not balanced), our algorithm does not perform well, e.g., the computation cost is higher than that of the traditional method, and what is worse is the calculations fail to converge for some initial values of the unknown parameters. This poor situation takes a favourable turn dramatically if the scaling matrix is slightly improved and a simple preconditioning technique is adopted: For naturally chosen simple diagonal forms of the scaling matrix and the preconditioner, the method performs well and gives accurate results with low computational cost just like the traditional methods, and improvements are obtained on: (1) widening the range of the initial values of the unknown parameters within which the minimizing iterations can converge, (2) reducing the computational cost in every Gauss–Newton iteration, (3) improving the irregular weighting effects of the coefficient matrix of the discrete governing equations. Consequently, the example inverse problem in Bentley (loc. cit.) is solved with the same accuracy, less computational effort and without the regularization term containing prior information on the unknown parameters. Moreover, numerical example shows that this method can solve the inverse problem of the quasilinear Boussinesq equation almost as fast as the linear one.In every Gauss–Newton iteration of our algorithm, one needs to solve a linear least-squares system about the corrections of both the parameters and the groundwater heads on all the discrete nodes only once. In comparison, every Gauss–Newton iteration of the traditional method has to solve the discrete governing equations as many times as one plus the number of unknown parameters or head observation wells (Yeh WW-G. Wat Resour Res 1986;22:95–108).All these facts demonstrate the potential of the algorithm to solve inverse problems of more complicated non-linear aquifer models naturally and quickly on the basis of finding suitable forms of the scaling matrix and the preconditioner.     

A fuzzy logic based dynamic wave model inversion algorithm for canal regulation

A fuzzy logic based centralized control algorithm for irrigation canals is presented. Purpose of the algorithm is to control downstream discharge and water level of pools in the canal, by adjusting discharge release from the upstream end and gates settings. The algorithm is based on the dynamic wave model (Saint‐Venant equations) inversion in space, wherein the momentum equation is replaced by a fuzzy rule based model, while retaining the continuity equation in its complete form. The fuzzy rule based model is developed on fuzzification of a new mathematical model for wave velocity, the derivational details of which are given. The advantages of the fuzzy control algorithm, over other conventional control algorithms, are described. It is transparent and intuitive, and no linearizations of the governing equations are involved. Tuning of the algorithm and method of computation are explained. It is shown that the tuning is easy and the computations are straightforward. The algorithm provides stable, realistic and robust outputs. The disadvantage of the algorithm is reduced precision in its outputs due to the approximation inherent in the fuzzy logic. Feed back control logic is adopted to eliminate error caused by the system disturbances as well as error caused by the reduced precision in the outputs. The algorithm is tested by applying it to water level control problem in a fictitious canal with a single pool and also in a real canal with a series of pools. It is found that results obtained from the algorithm are comparable to those obtained from conventional control algorithms. Copyright © 2009 John Wiley & Sons, Ltd.     

Optimal design of soil dynamic compaction using genetic algorithm and fuzzy system

Computational intelligent techniques, such as fuzzy and genetic algorithm, have proven to be useful in modeling of complex nonlinear phenomena such as dynamic compaction. Dynamic compaction method is used to improve the mechanical behavior of underlying soil layers especially loose granular materials. The method involves the repeated impart of high-energy impacts to the soil surface using steel or concrete tampers with weights ranging 10–40 ton and with drop heights ranging 10–40 m. A relatively exact estimation of dynamic compaction level is of major concern to geotechnical engineers. This paper develops a fuzzy set base method for the analysis of dynamic compaction phenomenon. In this model, the input variables are tamper weight, height of tamper drop, print spacing, tamper radius, number of impact and soil layer geotechnical properties. The main shortcoming of this technique is uncertainty to locate the best sketch of dynamic compaction to gain maximum effect of this method of soil improvement. Therefore, this paper describes the incorporation of genetic algorithm methodology using fuzzy system for determining the optimum design of dynamic compaction. Subsequently, it will be shown that the genetic algorithm has some abilities in the optimization of dynamic compaction design. Also different manners of this algorithm are compared and then the optimized structure of genetic algorithm will be suggested for dynamic compaction.     

Tangential‐projection algorithm for manifold representation in unidentifiable model updating problems

The problem of updating a structural model and its associated uncertainties by utilizing structural response data is addressed. In an identifiable case, the posterior probability density function (PDF) of the uncertain model parameters for given measured data can be approximated by a weighted sum of Gaussian distributions centered at a number of discrete optimal values of the parameters at which some positive measure‐of‐fit function is minimized. The present paper focuses on the problem of model updating in the general unidentifiable case for which certain simplifying assumptions available for identifiable cases are not valid. In this case, the PDF is distributed in the neighbourhood of an extended and usually highly complex manifold of the parameter space that cannot be calculated explicitly. The computational difficulties associated with calculating the highly complex posterior PDF are discussed and a new adaptive algorithm, referred to as the tangential‐projection (TP) algorithm, allowing for an efficient approximate representation of the above manifold and the posterior PDF is presented. Using this approximation, expressions for calculating the uncertain predictive response are established. A numerical example involving noisy data is presented to demonstrate the proposed method. Copyright © 2002 John Wiley & Sons, Ltd.     

On enhancement of accuracy in direct integration dynamic response problems

Enhancement of accuracy of the direct integration methods used in structural dynamic response analysis is presented. The accuracy achieved is obtained at the same time as the cost of the problem solution is reduced. The method presented is based on Richardson's extrapolation technique.