基于Monte Carlo法的结构动力学模型确认

提出一种蒙特卡洛模拟(MCS)与多元回归分析相结合的有限元模型确认方法。采用基于动态响应面法生成的代理模型改进直接MCS,用一种逐步迭代的方式改进代理模型保证模型确认的精度。传统欧氏距离/马氏距离从不同方面描述了两点间距离,然而如果在距离准则中能够同时考虑两者则会更全面。在相关性分析过程中,综合欧氏/马氏距离的特点,采用了一种欧氏/马氏距离相结合的不确定量化方法(距离判别方法),并给出了基于此指标的迭代收敛判断准则。算例仿真结果表明:所提出的有限元模型确认方法和此距离判别方法的使用,能比较大地降低MCS的计算量并能得到满意的模型确认结果,迭代收敛的稳定性和精度都有了提高。     

基于模型修正的钢管焊接结构焊缝损伤识别

摘要：本文提出了一种基于模型修正的钢管焊接结构焊缝损伤识别方法。利用从发射台骨架试验模型获取的模态参数,选择识别结果中精度较好的模态频率作为模型修正的基准频率。通过对待修正参数的灵敏度分析,运用ANSYS和MATLAB软件对有限元模型进行了修正。以实测模态和计算模态之间的误差建立一个带约束边界非线性最小二乘目标函数,将损伤识别问题转化为优化问题,并采用信赖域方法求解该优化问题。以有限元模型焊接结点单元组弹性模量的降低模拟焊缝损伤,并假定了两种损伤工况,通过对发射台骨架模型的数值仿真及试验研究,结果表明本文提出的损伤识别方法识别效果较为理想,为解决这种复杂焊接结构焊缝损伤识别问题提供了新的思路。     

基于最优复Morlet小波的结构密集模态参数识别

针对结构密集模态参数识别精度不高的问题,提出了一种小波Shannon熵与最小标准差相结合来优化复Morlet小波参数的方法。首先理论推导了中心频率与带宽参数的取值范围,其次采用两个最小原则对中心频率与带宽参数同时进行优化,通过仿真算例和模型实验的参数识别,验证了参数优化后的Morlet小波可准确地识别结构的密集模态参数,并且具有一定的抗噪性能。     

基于不完备实测模态数据的结构损伤识别方法研究

在传统的基于模型修正的损伤识别中,由于实测模态信息有限而待识别参数过多,往往导致损伤识别方程出现较大误差,从而限制了该方法在复杂结构中的应用。为解决这一问题,对结构的自由度进行了分解,将损伤结构中模态振型的未测量部分表达为已测量到的模态振型、模态频率以及结构其它参数的函数。将损伤视为结构单元刚度的减小,利用完好结构的计算模态数据以及损伤结构扩充后的实测模态数据,建立了结构的损伤识别方程。运用信赖域优化算法对具有双重约束条件的目标函数进行最小化,识别出了结构各单元的刚度损伤参数。通过两个损伤识别数值仿真算例及实验验证,结果表明,在测点数量有限及测试噪声等不利因素影响下,所提方法只需运用少量的实测模态信息,即可实现结构损伤位置及程度的准确识别,同时算法具有较好的鲁棒性。     

离合器波形片轴向非线性特性分析与优化

建立了用于计算波形片轴向非线性特性的有限元模型,并对模型精细化以提高仿真曲线与试验曲线的吻合程度。分析了波形片各结构参数对其轴向非线性特性的灵敏度,选取了除厚度外的三个主要结构参数作为波形片轴向非线性特性优化的参数。基于正交试验获得主要结构参数的设计空间,采用响应面法构建系统的代理模型,利用遗传算法求解代理模型,获得主要结构参数取值的最优组合。通过实例验证了波形片结构参数优化设计方法的正确性。     

结构损伤识别中噪声的模拟

在有限元仿真的结构振动信号上施加不同水平的噪声,采用随机子空间法,分别从各种噪声水平的信号中提取结构的模态参数。以无噪声信号得到的模态参数为标准值,计算了各信号噪声水平下模态参数的误差,得到了信号噪声水平与模态参数噪声水平的对应关系,给出了模拟模态参数噪声的方式。通过损伤识别算例,考察了识别效果对信号信噪比的要求。     

一种基于奇异值分解技术的模型定阶方法

摘要：模态参数识别中模型阶次的确定非常重要。基于奇异值分解技术,探讨模型阶次的确定方法,提出了利用奇异值的相对变化率来确定模型的阶次。该方法利用结构的量测脉冲响应信号构造Hankel矩阵,对其进行奇异值分解后计算奇异值的相对变化率,变化率最大的地方对应着模型的阶次。通过数值算例研究了噪声因素对模型阶次确定的影响,并利用模型实验数据验证了本方法的有效性。     

聚乙烯缓冲材料多自由度跌落包装系统优化设计

在测试基础上,依据粘弹性力学理论,建立发泡聚乙烯缓冲材料动态非线性本构模型,并成功识别了模型参数;应用此模型在一定高度跌落冲击下,建立了多自由度包装系统动力学方程;依据物品响应加速度小于许用值及材料用量最小化两个原则,进行多自由度系统缓冲包装优化设计并获得最优解;基于最优解结构尺寸,测试了发泡聚乙烯缓冲系统的加速度响应值,数值算例及试验的结果表明理论值与试验值的平均相对误差都在0.8%以内。利用此设计方法可有效地避免欠包装和过度包装,克服了最大加速度-静应力曲线不能设计多自由度缓冲包装设计的弊端     

非粘滞阻尼系统阻尼系数识别的拉普拉斯域方法

在结构动力响应的分析中,阻尼模型的选取对得到的分析结果具有相当的制约性,因此,结构的阻尼值机理及阻尼参数的识别研究一直倍受关注。由于结构实际阻尼机理的复杂性,目前常用的粘滞阻尼模型具有一定的局限性。首先介绍一种更一般的非粘滞阻尼模型,该模型的阻尼力与质点速度的时间历程相关;通过拉普拉斯变换对具有该阻尼的系统进行复模态分析,推导得到了结构阻尼系数的识别方法。对算例的数值仿真表明,该方法能有效地识别这种非粘滞阻尼模型的阻尼系数;当阻尼的非粘滞性不强时,其得出的结果与已有方法对粘滞阻尼参数识别的结果一致。     

带挠性附件卫星转动惯量的在轨辨识

针对大型卫星的挠性附件振动会影响质量特性参数辨识精度和准确性的问题,提出了带挠性附件卫星转动惯量参数在轨辨识的递推算法。基于带挠性附件卫星动力学模型,导出了转动惯量参数辨识的最小二乘描述形式;与挠性附件振动模态估计的卡尔曼滤波算法相结合,提出了一种适用于带挠性附件卫星转动惯量参数辨识的并发递推算法。通过仿真算例验证了卫星挠性附件振动对转动惯量参数辨识的影响和文中递推算法的有效性。     

一种基于正交试验设计的土中爆炸数值模型确认方法

提出了一种基于正交试验设计的土中爆炸数值模型确认方法。结合相应物理实验数据,该方法将数值模型确认问题转化为确定影响数值计算结果的各因素及其水平最佳搭配的优化问题。采用正交试验设计作为优化手段,达到了用较少的试验次数获得各因素及其水平最佳搭配的目的。通过极差分析,研究了在不同确认准则条件下,各因素及其水平对土中爆炸数值模拟结果的影响。计算结果表明：分别以最小计算耗时和最高计算精度为确认准则时,网格尺寸是影响数值结果的主要因素;以两者综合评估为确认准则时,计算方法是影响数值结果的主要因素。该文提出的这种方法为复杂数值模型确认问题的研究提供了新的思路。     

Entwicklung eines neuen Meridionalverfahrens für mehrstufige kompakte Axialverdichter und Validierung durch Experimente und CFD-Berechnungen

Development and validation of a universal through flow method applicable to design and analysis of compact multi-stage axial compressors will be described. Our method is based on correlations of the open literature which had been evaluated, selected and improved for this purpose. It contains a span wise mixing model to represent the 3D flow structure. For code validation various test cases are considered covering a wide range of application. Finally, the application of the method to analyse a newly-developed 11-stage gas turbine compressor will be demonstrated. The computed results have been compared with detailed test rig experiments. In addition, multi-stage steady-state computations were executed using a calibrated Navier-Stokes solver for 3D turbulent flows. Very good agreements of computed and measured results were achieved. In particular the through flow solver proves to be very accurate and fast in the prediction of compressor characteristics and has been directly used for optimisation of variable guide vane settings during the compressor test.     

Computational methods for model reliability assessment

This paper investigates various statistical approaches for the validation of computational models when both model prediction and experimental observation have uncertainties, and proposes two new methods for this purpose. The first method utilizes hypothesis testing to accept or reject a model at a desired significance level. Interval-based hypothesis testing is found to be more practically useful for model validation than the commonly used point null hypothesis testing. Both classical and Bayesian approaches are investigated. The second and more direct method formulates model validation as a limit state-based reliability estimation problem. Both simulation-based and analytical methods are presented to compute the model reliability for single or multiple comparisons of the model output and observed data. The proposed methods are illustrated and compared using numerical examples.     

Real-time validation of mechanical models coupling PGD and constitutive relation error

In this work, we introduce a general framework that enables to perform real-time validation of mechanical models. This framework is based on two main ingredients: (i) the constitutive relation error which constitutes a convenient and mechanically sound tool for model validation; (ii) a powerful method for model reduction, the proper generalized decomposition, which is used to compute a solution with separated representations and thus to run the validation process quickly. Performances of the proposed approach are illustrated on machining applications.     

Bayesian risk-based decision method for model validation under uncertainty

This paper develops a decision-making methodology for computational model validation, considering the risk of using the current model, data support for the current model, and cost of acquiring new information to improve the model. A Bayesian decision theory-based method is developed for this purpose, using a likelihood ratio as the validation metric for model assessment. An expected risk or cost function is defined as a function of the decision costs, and the likelihood and prior of each hypothesis. The risk is minimized through correctly assigning experimental data to two decision regions based on the comparison of the likelihood ratio with a decision threshold. A Bayesian validation metric is derived based on the risk minimization criterion. Two types of validation tests are considered: pass/fail tests and system response value measurement tests. The methodology is illustrated for the validation of reliability prediction models in a tension bar and an engine blade subjected to high cycle fatigue. The proposed method can effectively integrate optimal experimental design into model validation to simultaneously reduce the cost and improve the accuracy of reliability model assessment.     

非对称船体梁弯扭耦合振动试验及分析

为了验证一种基于薄壁结构力学理论，考虑了翘曲，剪切，剖面转动以及结构不连续性影响的薄壁梁有限元模型的适用性，针对航空空母舰这种具有不对称结构的船型进行了弯扭耦合振动试验，并就试验结果和计算结果作了分析和比较。     

基于CV-SVM方法的手术时间估计

手术时间估计是进行科学手术排程的前提和依据,为了能够准确地估计手术时间从而为手术排程提供有效信息,采用交叉验证（CV）方法优化支持向量机(SVM)参数,构建基于交叉验证的支持向量机模型对手术时间进行估计。为了验证模型的性能,将CV SVM模型与径向基（RBF）神经网络模型相对比,通过某医院眼科角膜移植手术时间估计进行实例验证。结果表明,相比RBF模型,基于CV SVM模型的手术时间估计结果平均绝对百分误差在11%以内,相对误差在23%以内,验证了模型的有效性,为手术时间估计提供了一种有效的方法。     

A case study in engineering model validation using new wavelet‐based methods

Simulation model validation is an important part of simulation development and use. An emerging challenge is the examination of functional data systems and the validation of the simulations built to represent them. While validation methods do exist, there is a gap in the engineering and statistical approaches used for functional model validation. This case study demonstrates the use of recently developed methods based on the use of wavelets to bridge the engineering‐statistical gap in functional simulation model validation. Two methods are used to provide insight regarding model validity, and a third method is used to identify areas of system‐simulation disagreement when model validity fails to hold.