基于Elman型神经网络的金川二矿地表岩移时序预测 模型

建立于煤矿开采基础之上的矿山开采沉陷理论和预测方法并不适用于象金川这样厚大、陡倾的金属矿床开采的岩移问题,因此,本文探讨利用神经网络来对地表岩移进行预测。根据Elman神经网络能够逼近任意非线性函数的特点和具有反映系统动态特性的能力,提出了利用Elman神经网络建立地表岩移时序预报模型的方法。利用金川二矿区GPS监测所得到的时间序列数据,通过对Elman神经网络模型预测值与GPS实测值之间的比较,结果表明模型预测显示了良好的准确性,特别是在时间步长较短情况下,应用于实际预测一定程度上可以弥补金属矿山岩移预测方法不足的缺憾。     

A novel analytical model based on arc tangent velocity field for prediction of rolling force in strip rolling

Accurate prediction of rolling force is an effective method to improve strip quality in rolling process. To achieve this goal, a novel arc tangent velocity field model based on the upper bound method is proposed to evaluate the rolling force. The mathematical expression of rolling force is derived from the virtual work principle and maximum plastic work principle. Comparing the experimental results with the proposed analytical model prediction, it has been found that this model is good for estimation of rolling force. Meanwhile, the finite element method is also used to simulate the rolling process to verify the validity of the analytical model. It is shown that this model can be used for prediction of rolling force in practice.

     

基于多模型的参数空间预测推断

当建立多个模型对工程结构进行数值仿真时,为了得到更可靠的预测结果,需要综合考虑模型选择不确定性和模型形式不确定性对预测结果的影响. 联合贝叶斯方法与实验数据计算不同模型的可信度,采用调节因子方法传播模型选择不确定性得到系统响应置信区间,并叠加模型形式不确定性的影响获得综合模型计算结果的置信区间,再通过插值得到关心量在预测点的置信区间. 最后通过某飞行器气动力系数的预测推断检验了该方法的可行性.     

阵风谱载下疲劳寿命可靠性预测

基于维概率ＭＩＮＥＲ准则,建立了在阵风谱载下对结构构件疲劳寿命进行可靠性预测的方法。根据一组ＬＹ１２－ＣＺ铝合金中心孔试件的疲劳试验数据对上述方法进行了较为成功的验证,验证结果表明本方法的预测值与试验值吻合良好,具有较好的工程实用价值     

A computer method for simulating service loads

A recently presented study addressed the problem of analyzing field data that are best characterized as nonstationary stochastic signais. The analysis method hypothesizes that the nonstationary signal consists of two stationary signals, which belong to different populations, occurring consecutively according to a suitable probabilistic model. The analysis procedure involves the following: segmenting the time history, estimating the population of each segment, estimating the power spectrum of each segment, averaging the power spectra which belong to each population, presenting the power spectra via parameters of digital filters (which shape white noise sequences into sequences with the measured power spectra), and measuring the parameters of the probabilistic model. In this paper a simulation method is presented that uses the results of the analysis method mentioned above to create a sequence that simulates the statistical characteristics of the nonstationary field data. This simulation method is designed to be efficiently implemented on a general-purpose computer of any size, including micros. First, a review of the stochastic model is given. Then the steps of simulation are presented: generating a white sequence on the digital computer, generating the probabilistic model, and developing an algorithm for using digital filters in shaping the power spectra. Sample results are shown to reflect the soundness of the procedure. This simulation method can prove useful in computer studies of the fatigue of mechanical components under field loading. Since it is exactly reproducible in different laboratories, this method can also serve in comparison studies of fatigue-life prediction procedures. Paper was presented at V International Congress on Experimental Mechanics held in Montreal, Quebec, Canada on June 10–15, 1984.     

Prediction of leaching rate in heap leaching process by grey dynamic model GDM（1,1）

The method of developing GM（1,1） model is extended on the basis of grey system theory. Conditions for the transfer function that improve smoothness of original data sequence and decrease the revert error are given. The grey dynamic model is first combined with the transfer function to predict the leaching rate in heap leaching process. The results show that high prediction accuracy can be expected by using the proposed method. This provides a new approach to realize prediction and control of the future behavior of leaching kinetics.     

Prediction of incipient shear band trajectories in a thick wall cylinder explosion test

A simple but precise and physical mechanism-based mathematical expression is proposed to predict shear band trajectories in thick wall cylinders subject to external surrounding pressure. The expression is based on the Coulomb-Mohr fracture criterion and can be applied to various compression-sensitive materials, especially ceramics. The predicted result closely matches the experimental observations, which makes this method quite useful in testing material behavior. This expression also permits the extraction of the parameter μ in the Coulomb-Mohr criterion from experimental observations. Furthermore, no pre-assumptions or after-test measurement are necessary in order to carry out the prediction. The only two values needed to conduct the prediction are the initial inner radius and the friction coefficient μ. A comparison between the newly proposed model and existing theory is made to reveal their relations and demonstrate the effectiveness of the newly derived mathematical expression.     

巴西圆盘试样中心斜裂纹疲劳扩展轨迹的边界元模拟

提出了一个平面弹性体多裂纹疲劳扩展模型. 它主要涉及到复合型加载情况下多裂纹尖端疲劳扩展的数学模型及杂交位移不连续法(一种边界元法). 在数值模拟中, 对每一裂纹扩展增量分析时,在其先前的边界上增添裂纹扩展增量, 且只对新增添的裂纹扩展增量划分单元, 同时, 按照这种边界元法的实施方法对一些单元特征进行调整, 就可以方便地模拟裂纹扩展. 用这种数值方法模拟了巴西圆盘试样中心斜裂纹疲劳扩展轨迹,数值结果说明了预报模型的有效性, 揭示了裂纹体几何对疲劳扩展的影响.      

Experiment and evaluation of wrinkling strain in a corner tensioned square membrane

Prediction of wrinkling characteristics is strongly correlated with the strain perpendicular to wrinkling direc- tion. In this paper, the strain field of wrinkled membrane is tested by VIC-3D system based on the digital image correlation technique. Experimental results are validated by the tension wrinkling simulation. The experimental strain perpendicular to wrinkling direction is analyzed in depth. The wrinkling strain of a square wrinkled membrane under corner tension is extracted from experimental strain perpendicular to wrinkling direction. A quantitative characterization format of the experimental wrinkling strain is proposed. A modified prediction method of wrinkling amplitude is presented based on the experimental wrinkling strain. The re- sults show that the precision of modified prediction model has improved 13.2% compared with the classical prediction model. The results reveal that the modified model can give an accurate prediction of the wrinkling amplitude.     

加权函数组合预测边坡变形模型的研究

边坡变形监测是边坡监测的主要内容之一,其变形预测问题是边坡工程中主要技术难题之一。考虑边坡位移变形预测模型的局限性,如神经网络预测方法需要大量的实测数据作为学习样本,灰色系统模型要求原始数据序列必须满足指数规律,且数据序列变化速度不能太快等。建立了边坡变形反向传播神经网络预测模型,同时给出了灰色GM(1,1)边坡预测模型。提出边坡的神经网络与灰色系统加权函数组合预测模型,采用动态规划解法,将原模型转化为多阶段决策问题,使组合预测误差的平方和最小,得到组合权重,这样得到的变形预测结果的精度将大大提高,弥补了单一方法的局限性,满足工程预测的需要。通过边坡实例加以验证,加权函数组合预测模型的预测结果精度有一定提高,能够与实际监测数据相吻合,达到准确预测的目的。     

Characterizing complex flows using adaptive sparse dynamic mode decomposition with error approximation

Dynamic mode decomposition (DMD) is a powerful data-driven method for analyzing the coherent structures of dynamical systems. This work develops an adaptive sparse DMD with error approximation for the sparse reconstruction of complex flow fields. First, we propose a new sparse DMD model by redefining the penalty function, where adaptive weights are assigned to penalize different DMD modes. With the adaptive weights, the sparse DMD model is more capable of extracting important DMD modes and discarding unimportant ones. Second, we develop a novel error prediction model for the proposed sparse DMD. The key idea is to construct a multiple regression model between the sparse model and its error by employing the partial least squares regression. The error of the sparse DMD model can be reduced by integrating the error prediction model. Finally, we assess the proposed method by means of test cases, including a nonlinear parameterized function, a cylinder bundle flow, and the transient state of square cylinder flow. The results show that the proposed method can be used to capture the dominant modes and substantially increase the accuracy of flow reconstruction.     

Spurious counts in gas volume flow measurements by means of turbine meters

Acoustical oscillations can induce a rotation of a turbine flow meter in the absence of main flow, which leads to spurious counts. A simplified model is presented which explains the occurrence of spurious counts in the limit of very thin turbine blades and high Strouhal numbers. The predicted threshold for the occurrence of spurious counts is compared to experimentally obtained data at various gas pressures in the range from 1 to 8 bar. The simplified model provides a reasonable prediction of the occurrence of spurious counts and can be used as an useful engineering tool in the prediction of the occurrence of spurious counts.     

Analysis of a horizontal solid-liquid pipe flow by a cross correlation method

The transit time distribution has been demonstrated to be a most useful measure of the behaviour of two phases mixtures but the measurement of it with tracers is difficult. The authors have tested a method based on the correlation of fluctuations in the mixture concentration as measured by gamma ray density meters at two sections. This method is shown to give accurate results and allows continuous monitoring of conditions in a pipeline. It is shown how such monitoring can allow the onset of critical conditions such as deposition or the formation of a mobile bed to be detected. This approach can lead to non-dimensional analysis and therefore prediction of mixture behaviour from laboratory tests.     

Parametric study of the influence of compression on the acoustical absorption coefficient of automotive felts

The present note describes some work related to the modelization of acoustical absorption properties of compressed porous materials. An `equivalent fluid' model with five parameters is used. This prediction technique is validated with some industrial materials being 1-D compressed along their thickness, starting from a felt mat having a given basic weight. The obtained results tend to indicate that an adequate prediction of the decrease in the coefficient of absorption is possible with this method.     

Data assimilation and pollution forecasting in Burgers' equation with model error function

This article presents a correction method for a better resolution of the problem of estimating and predicting pollution, governed by Burgers' equations. The originality of the method consists in the introduction of an error function into the system's equations of state to model uncertainty in the model. The initial conditions and diffusion coefficients, present in the equations for pollution and concentration, and also those in the model error equations, are estimated by solving a data assimilation problem. The efficiency of the correction method is compared with that produced by the traditional method without introduction of an error function.Three test cases are presented in this study in order to compare the performances of the proposed methods. In the first two tests, the reference is the analytical solution and the last test is formulated as part of the “twin experiment”.The numerical results obtained confirm the important role of the model error equation for improving the prediction capability of the system, in terms of both accuracy and speed of convergence.     

A note of hybrid GR-SVM for prediction of surface roughness in abrasive water jet machining

The paper attempts at reviewing a previous research entitled “Hybrid GR-SVM for prediction of surface roughness in abrasive water jet (AWJ) machining” and some problems were found in its reducing parameters process and prediction model. The authors presented a hybrid of grey relation analysis (GRA) and support vector machine (SVM) to estimate the roughness surface in a certain dataset of AWJ machining. Their proposed method may not work in real case of AWJ machining as it is claimed. This paper gives a counter model in order to illustrate these remarks.     

Identification of the plastic behavior of aluminum plates under free air explosions using inverse methods and full-field measurements

This article describes an inverse method for the identification of the plastic behavior of aluminum plates subjected to sudden blast loads. The method uses full-field optical measurements taken during the first milliseconds of a free air explosion and the finite element method for the numerical prediction of the blast response. The identification is based on a damped least-squares solution according to the Levenberg–Marquardt formulation. Three different rate-dependent plasticity models are examined. First, a combined model based on linear strain hardening and the strain rate term of the Cowper–Symonds model, secondly, the Johnson–Cook model and finally, a combined model based on a bi-exponential relation for the strain hardening term and the strain rate term of the Cowper–Symonds model. A validation of the method and its sensitivity to measurement uncertainties is first provided according to virtual measurements generated with the finite element method. Next, the plastic behavior of aluminum is identified using measurements from real free air explosions obtained from a controlled detonation of C4. The results show that inverse methods can be successfully applied for the identification of the plastic behavior of metals subjected to blast waves. In addition, the material parameters identified with inverse methods enable the numerical prediction of the material’s response with increased accuracy.     

基于LS-DYNA的汽车安全带固定点强度研究

以交叉型乘用车的安全带固定点强度分析为例,将分析置于整个白车身模型中,采用LS-DYNA的显式求解方法,按照标准设置规定的载荷,可以更准确地评估结构通过标准的可能性,为结构优化提供明确的指导信息.该方法可以推广到其他准静态强度分析中,在产品开发中有很强的实用性.     

An analysis of perturbation based methods for the treatment of parameter uncertainty in numerical groundwater models

Monte Carlo methods are robust approaches for the estimation of prediction uncertainty in groundwater flow and transport modelling under uncertain model parameters. However Monte Carlo procedures estimate the prediction statistics by generating a population of solutions from random realisations of the model parameters which are consistent with the parameter statistics, and as a result are computationally demanding. Taylor series based procedures offer an alternative to Monte Carlo methods for calculating the prediction statistics. Two such approaches, the first-order second moment and McLaughlin and Wood's perturbation method, are based on using a Taylor series to derive approximate expressions for the model predictions first and second statistical moments. In this paper the perturbation method presented by McLaughlin and Wood is rederived using Vetter matrix notation. This is compared with the first-order second moment (FOSM) method and while the steady state expressions for these two approaches are shown to be equivalent, the transient forms are considerably different. A new form of the FOSM is derived, which is simpler and has a lower computational burden. However, the transient McLaughlin and Wood expression is found to have a significantly lower computational overhead than either of the FOSM methods presented.