Estimation of uncertainty bounds on unmeasured variables via nonlinear finite element model updating.

Doebling, S. W. ; Schultze, J. F. ; Hemez, F. M.

Technical Information Center Oak Ridge Tennessee

关键词: Dynamic structural analysis;    Finite element analysis;    Accuracy;    Distribution;    Monitors;   

RP-ID  :  DE2001780368

学科分类：工程和技术（综合）

美国|英语

来源: National Technical Reports Library

【 摘 要 】

Finite element model validation is a topic of current interest to many researchers in the field of linear and nonlinear structural dynamics. Model validation refers to substantiation that a model, within its domain of applicability, possesses a satisfactory range of accuracy consistent with the intended application of the model. (1). Validation is accomplished primarily by comparison of simulation results to experimental results to confirm the accuracy of the mechanics models in the simulation and the values of the parameters employed in the simulation, and to explore how the simulation might be improved. The assessment of uncertainties in the simulation mechanics models and their associated parameters plays a critical role in the credible validation of nonlinear structural dynamics models. The study of the effects that these uncertainties produce is termed uncertainty quantification (UQ). A major issue in UQ is the determination of how the distributions of the model parameters (which essentially form a set of inputs to the simulation) should be represented in order to accurately reflect the real-world response of the structure. In the case of repeated experiments, it is sometimes adequate to monitor the values of the input variables (e.g. forces, temperatures, velocities, etc.) and estimate a distribution from these observations. However, in many structural dynamics experiments, there can be significant input variables that are either unmeasurable (such as the actual orientation of parts during an impact event) or unmeasured (such as the level of torque applied to an interface during assembly). In these cases, it is necessary to estimate the distributions of the key input variables by indirect means. In this paper, a previously developed model updating technique for nonlinear structural dynamics models is applied to data from repeated experimental trials to estimate the distributions of four key input parameters for a transient impact event. The model updating technique itself, along with the selection of the key simulation parameters, is not the focus of this paper, and so these issues are only addressed in summary form.