Anders T Johansson

Spread in Modal Data Obtained from Wind Turbine Blade Testing

This paper presents a pre-study for an on-going research project in experimental dynamic substructuring, initiated by the SEM Substructuring Focus Group. The focus group has selected a small wind turbine, the Ampair 600W, to serve as test bed for the studies. The turbine blades are considered in this study. A total of 12 blades have been tested for modal properties in a free-free configuration. The data has been acquired and analysed by students participating in the undergraduate course “Structural Dynamics – Model Validation” at Chalmers University of Technology. Each blade was tested by different students as part of their required course work to account for spread in modal properties between the blades. A subset of the blades were tested independently multiple times to account for variability in the test setup. Furthermore, correlation analysis of test data was made with Finite Element model eigensolution data of the blade.

Modeling and Calibration of Small-Scale Wind Turbine Blade

The SEM Substructuring Focus Group has chosen an Ampair 600W wind turbine to be used as a test bed in the continued efforts to further experimental and experimental-analytical substructure coupling techniques. To assess such coupling techniques, validated models of the parts, the substructures considered, play a crucial role. This paper describes the modeling, calibration and validation of a Finite Element (FE) model of a blade for the test bed turbine. Orthotropic composite material modeling is used to set up the model, which is calibrated and validated based on results from an ambitious measurement campaign including both non-destructive testing for dynamic properties and dedicated destructive tests for deduction of material properties. The measurement campaign is carefully described in the paper.

Model Calibration and Uncertainty of A600 Wind Turbine Blades

Recently, a lot of work has been done on modeling, testing and calibrating Ampair 600 W wind turbine blades, owing to the use of that turbine as a test bed structure for the Dynamic Substructuring Focus Group within the Society of Experimental Mechanics. In Sweden alone, more than 20 blades have been tested for dynamical properties, geometrical differences and material properties as was presented in several papers at IMAC XXXI. The quantity of blades, originating from different manufacturing batches, makes them ideal for investigations of component variability.

Towards an Automatic Modal Parameter Estimation Framework: Mode Clustering

The estimation of modal parameters from a set of measured data is a highly judgmental task, with user expertise playing a significant role for distinguishing between physical and spurious modes. However, it can be very tedious especially in situations when the data is difficult to analyze. This study presents a new algorithm for mode clustering as a preliminary step in a multi-step algorithm for performing physical mode selection with little or no user interaction. The algorithm commences by identification of a high-order model from estimated frequency response functions to collect all the important characteristics of the structure in a so-called library of modes. This often results in the presence of spurious modes which can be detected on the basis of the hypothesis that spurious modes are estimated with a higher level of uncertainty comparing to physical modes. Therefore, we construct a series of data using a simple random sampling technique in order to obtain a set of linear systems using subspace identification. Then, their similar modes are grouped together using a new correlation criterion, which is called Modal Observability Correlation (MOC). An illustrative example shows the efficiency of the proposed clustering technique and also demonstrates its capability to dealing with inconsistent data.

Development of Simplified Models for Wind Turbine Blades with Application to NREL 5 MW Offshore Research Wind Turbine

Integration of complex models of wind turbine blades in aeroelastic simulations places an untenable demand on computational resources and, hence, means of speed-up become necessary. This paper considers the process of producing simplified rotor blade models which accurately approximate the dynamics of interest. The novelty, besides applying an efficient model updating procedure to the wind turbine blade, is to challenge the conventional beam element formulation utilized in the majority of aeroelastic codes. First, a 61.5 m blade, previously reported by the National Renewable Energy Laboratory, is selected as a case study and a verified industry-standard three dimensional shell model is developed based on its actual geometry. Next, given the reported spanwise cross sectional properties of the blade, a calibrated beam model is developed, using an efficient model updating process, that shows an excellent agreement to the low frequency dynamics of the baseline model in terms of mode shapes, resonance frequency and frequency response function. The simulation study provides evidence that a beam model cannot capture all the important features found in a large-scale 3D blade. This motivates a departure from conventional beam element formulation and suggests addressing the problem of producing simplified models in the framework of model reduction techniques. A modified modal truncation algorithm is applied to the baseline model to produce a simpler model which accurately approximates its input–output behavior in a given frequency range. It is concluded that besides the computational efficiency of the reduction algorithm, the resulting approximation error is guaranteed to be bounded and the yielded low-order model can, in turn, be served in wind turbine design codes.

Improving Test Rig Performance Using Passive Components

The Time Waveform Replication (TWR) algorithm is presently used in industry for calculating the input force needed to replicate reference sensor outputs in a dynamic test rig. The feasible range of that input force is restricted by power supply and forcing rate limitations. If the force transfer paths of the reference test cannot be replicated in the test rig, lack of state controllability may cause unnecessarily large input forces and an increased remaining output error. We advocate the use of passive components to improve output tracking and limit input force demands of dynamic test rigs in the case that controllability is lacking. A method for introducing such passive components is described in this paper. It uses a virtual testing model of the test system with genetic algorithm optimization and TWR in the loop to calculate the position and dynamic properties of the proposed passive component.

Stochastic Finite Element Model Updating by Bootstrapping

This paper presents a new stochastic finite element model calibration framework for estimation of the uncertainty in model parameters, which combines the principles of bootstrapping with the technique of FE model calibration with damping equalization. The bootstrapping allows to quantify the uncertainty bounds on the model parameters by constructing a number of resamples, with replacement, of the experimental data and solving the FE model calibration problem on the resampled datasets. To a great extent, the success of the calibration problem depends on the starting value for the parameters. The formulation of FE model calibration with damping equalization gives a smooth metric with a large radius of convergence to the global minimum and its solution can be viewed as the initial estimate for the model parameters. In this study, practical suggestions are made to improve the performance of this algorithm in dealing with noisy measurements. The performance of the proposed stochastic calibration algorithm is illustrated using simulated data for a six degree-of-freedom mass-spring model.

State-Space Substructuring with Transmission Simulator

The dynamic substructuring focus group of SEM organizes sessions on experimental substructuring each IMAC conference and has been doing so for a number of years. Over the last decade, the use of so-called transmission simulators has trended within the community. Transmission simulators are well-modeled parts that fit to the interface of the substructures to be coupled to allow distributed interfaces and relaxation of the coupling conditions by the transmission simulator’s analytical modes at the cost of adding a decoupling step to the substructuring problem. In this paper, the transmission simulator concept is adapted to state-space substructuring. Experimental-analytical substructuring of the focus group benchmark structure, the Ampair A600 wind turbine, is used to verify the methodology.

Sequential Gauss-Newton MCMC Algorithm for High-Dimensional Bayesian Model Updating

Bayesian model updating provides a rigorous framework to account for uncertainty induced by lack of knowledge about engineering systems in their respective mathematical models through updates of the joint probability density function (PDF), the so-called posterior PDF, of the unknown model parameters. The Markov chain Monte Carlo (MCMC) methods are currently the most popular approaches for generating samples from the posterior PDF. However, these methods often found wanting when sampling from difficult distributions (e.g., high-dimensional PDFs, PDFs with flat manifolds, multimodal PDFs, and very peaked PDFs). This paper introduces a new multi-level sampling approach for Bayesian model updating, called Sequential Gauss-Newton algorithm, which is inspired by the Transitional Markov chain Monte Carlo (TMCMC) algorithm. The Sequential Gauss-Newton algorithm improves two aspects of TMCMC to make an efficient and effective MCMC algorithm for drawing samples from difficult posterior PDFs. First, the statistical efficiency of the algorithm is enhanced by use of the systematic resampling scheme. Second, a new MCMC algorithm, called Gauss-Newton MCMC algorithm, is proposed which is essentially an M-H algorithm with a Gaussian proposal PDF tailored to the posterior PDF using the gradient and Hessian information of the negative log posterior. The effectiveness of the proposed algorithm for solving the Bayesian model updating problem is illustrated using three examples with irregularly shaped posterior PDFs.

A Comparison of the Dynamic Behavior of Three Sets of the Ampair 600 Wind Turbine

© The Society for Experimental Mechanics, Inc. 2015. The Ampair 600 wind turbine assembly has been modified to suit as a benchmark structure in the pursuit of finding best practices for experimental substructure coupling of structural dynamic systems. Seven such systems have been assembled in test laboratories in Europe and in the USA. We scrutinize the dynamic behavior of the total assembly of three of those by vibration testing and compare the test outcome from seemingly identical assemblies. The aim is to support future component synthesis activities with high fidelity data and support future model validation. Comparisons are made by evaluating deviations of measured frequency response functions, the differences of identified structural eigenfrequencies and the correlation between eigenvector estimates. The testing is made in two parts. First, a partly assembled system, not including the hub and blades, is tested. This constitutes one possible and logical subsystem splitting that is likely to appear in future substructure synthesis efforts. In the second part, the full system assembly is tested. The test procedure, the test setup, the obtained test data and test data statistics are presented.