Studies on knot placement techniques for the geometry construction and the accurate simulation of isogeometric spatial curved beams

The present paper investigates the use of different knot placement techniques for isogeometric analysis of spatial curved beams, to enhance analysis results in cases when geometries are given in terms of data points. Focusing on analysis-aware modeling for structural static and vibration simulations of spatial free-form curved beams, the knot placement techniques based on uniformly spaced knots as well as on De Boor’s and Piegl and Tiller’s algorithms are studied. For this purpose, an isogeometric formulation for linear Euler–Bernoulli beams based on the Euler–Rodriguez transformation rule is implemented. Different case studies and numerical examples are presented and the results are validated against “overkill” solutions computed with a commercial finite element software. The results show that the De Boor’s knot placement algorithm typically leads to better approximation errors and is therefore the suggested strategy for this kind of problems

Use of Graded Laser Scanning to Generate Efficient Boundary Element Meshes

This thesis presents an approach which combines a reverse engineering technique with boundary element stress analysis, by generating a graded mesh to improve the simulation efficiency. A rectangular metal plate, a bar of a circular cross section, a gas turbine blade and a steam turbine blade were scanned at different resolutions using a (non-contact) laser scanner measurement to obtain the point clouds. Meshes of each object were generated in Rapidform and directly used in a boundary element stress analysis. In addition, the steam turbine blade was scanned using different scanning resolutions. From this, a graded mesh model of the blade was generated and then efficient boundary element stress analyses were performed. An application of a freeform surface reconstruction of a blade surface is also given. Also, several Matlab programs were written to repair the edges and the cylindrical surface of the meshes

Multiple Crack Detection using Wavelet Transforms and Energy Signal Techniques

Wavelet transforms are efficient tools for structural health monitoring (SHM) and damage detection. However, these methods are encountered with some limitations in practice. Thus, signal energy analysis is used as an alternative technique for damage detection. In this paper, discrete wavelet transforms (DWT) and Teager energy operator (TEO) is applied to the curvature of the mode shapes of the beams, and the locations of the damages are identified. The results show that in comparison with the discrete wavelet transform, the signal energy operator has better performance. This superiority in detecting the damages, especially near the supports of the beam, is obvious and has enough sensitivities in low damage intensities. Additionally, the damage detection in the cases that the response data are noisy is investigated. For this purpose, by adding low-intensity noises to the curvature of the mode shapes, the abilities of the mentioned methods are evaluated. The results indicate that each method is not individually efficient in the detection of damages in noisy conditions, but the combination of them under noisy conditions is more reliabl

Smart FRP Composite Sandwich Bridge Decks in Cold Regions

INE/AUTC 12.0

Automated parameter extraction of ScAlN MEMS devices using an extended Euler-Bernoulli beam theory

Magnetoelectric sensors provide the ability to measure magnetic fields down to the pico tesla range and are currently the subject of intense research. Such sensors usually combine a piezoelectric and a magnetostrictive material, so that magnetically induced stresses can be measured electrically. Scandium aluminium nitride gained a lot of attraction in the last few years due to its enhanced piezoelectric properties. Its usage as resonantly driven microelectromechanical system (MEMS) in such sensors is accompanied by a manifold of influences from crystal growth leading to impacts on the electrical and mechanical parameters. Usual investigations via nanoindentation allow a fast determination of mechanical properties with the disadvantage of lacking the access to the anisotropy of specific properties. Such anisotropy effects are investigated in this work in terms of the Young’s modulus and the strain on basis of a MEMS structures through a newly developed fully automated procedure of eigenfrequency fitting based on a new non-Lorentzian fit function and subsequent analysis using an extended Euler–Bernoulli theory. The introduced procedure is able to increase the resolution of the derived parameters compared to the common nanoindentation technique and hence allows detailed investigations of the behavior of magnetoelectric sensors, especially of the magnetic field dependent Young‘s modulus of the magnetostrictive layer

A quadrilateral inverse-shell element with drilling degrees of freedom for shape sensing and structural health monitoring

The inverse Finite Element Method (iFEM) is a state-of-the-art methodology originally introduced by Tessler and Spangler for real-time reconstruction of full-field structural displacements in plate and shell structures that are instrumented by strain sensors. This inverse problem is commonly known as shape sensing. In this effort, a new four-node quadrilateral inverse-shell element, iQS4, is developed that expands the library of existing iFEM-based elements. This new element includes hierarchical drilling rotation degrees-of-freedom (DOF) and further extends the practical usefulness of iFEM for shape sensing analysis of large-scale structures. The iFEM/iQS4 formulation is derived from a weighted-least-squares functional that has Mindlin theory as its kinematic framework. Two validation problems, (1) a cantilevered plate under static transverse force near the free tip, and (2) a short cantilever beam under shear loading, are solved and discussed in detail. Following the validation cases, the applicability of the iQS4 element to more complex structures is demonstrated by the analysis of a thin-walled cylinder. For this problem, the effects of noisy strain measurements on the accuracy of the iFEM solution are examined using strain measurements that involve five and ten percent random noise, respectively. Finally, the effect of sensor locations, number of sensors, the discretization of the geometry, and the influence of noise on the strain measurements are assessed with respect to the solution accuracy

Ambient Excitation Based Model Updating for Structural Health Monitoring via Dynamic Strain Measurements

Structural health monitoring (SHM) technologies continue to be pursued for aerospace structures in the interests of increased safety and, when combined with prognosis, efficiency in life-cycle management. The current work is focused on developing and validating a method for in-situ health monitoring of aerospace structures. In particular, the current framework has been developed for use with response only vibration data using natural operating turbulence to provide the means of excitation. While the framework is general so as to work with a wide suite of sensor options, particular emphasis has been placed on fiber optic strain sensors as a lightweight, low cost, non-intrusive means of monitoring the vibration response. At its core, the developed SHM system actively monitors a network of fiber optic strain sensors and utilizes the transient response data to calculate their associated power spectral densities (PSD). These PSD serve as the fundamental input to the developed SHM algorithm presented in the dissertation whereby comparisons between previously correlated model PSD and the current measured PSD are made. If anomalies between the correlated model and the measured data sets are detected, the developed SHM algorithm seeks to minimize the difference via updating of structural parameters underlying the structural model of interest (in the case of the presented work, a finite element model of the structure). The SHM algorithm itself is an adaption of a statistical least-squares minimization based in concepts of non-linear parameter estimation and model correlation. The algorithm developed uses power spectra based residual error vectors derived from distributed vibration measurements to update a structural model through statistically weighted least-squares minimization. The output of the algorithm is a correlated finite element model which inherently produces estimates of the location, type, and severity of any detected damage as well as the uncertainty associated with these estimates. Throughout the dissertation the developed algorithm was shown, both analytically and experimentally, to successfully detect, locate, and quantify damage present in a structural system

The calculation of noise from railway bridges and viaducts

Pandrol Rail Fastenings Limited are a designer and manufacturer of railway rail-fastening systems. As an organisation they have the capability to reduce the noise impact of bridges using resilient track components. They also have a commercial interest in providing such technology. Knowledge of the processes behind bridge noise is important to Pandrol in two ways; to aid the engineers within the organisation in the design of fastening systems and to demonstrate a state-of-the-art understanding of the problem of railway bridge noise to customers, as this will aid in the sale of Pandrol products. The fitting of new rail components to an existing track form, or failure to meet noise regulations with a new track form, can be costly. It is important to be able to predict accurately the effectiveness of noise reduction techniques. Currently, Pandrol’s knowledge of the problem consists almost entirely of experience gained and data gathered while working on existing bridge projects. To expand their knowledge base, Pandrol perform noise and vibration measurements on railway bridges and viaducts and then use the measured data to predict the performance of their systems on other bridges. This completely empirical approach to predicting bridge noise is both costly and situation specific results cannot be provided before the installation of the fastening system. Another approach to predicting bridge noise is through the application of analytical models. Limited analytical modelling in the context of bridge noise is currently conducted within the organisation. For these reasons, Pandrol are sponsoring research into bridge noise in the form of this EngD project. Here an existing rapid calculation approach is identified that relies less on the exact geometry of the bridge and more on its general characteristics. In this approach an analytical model of the track is coupled to a statistical energy analysis (SEA) model of the bridge. This approach forms a suitable basis from which to develop a better model here by concentrating on its weaknesses. A mid-frequency calculation for the power input to the bridge via a resilient track system has been developed by modelling the track-bridge system as two finite Timoshenko beams continuously connected by a resilient layer. This has resulted in a power input calculation which includes the important effects of coupling between the rail and bridge and the resonance effects of the finite length of a bridge. In addition, a detailed study of the frequency characteristics of deep I-section beams has been performed using Finite Element, Boundary Element and Dynamic stiffness models. It is shown that, at high frequencies, the behaviour of the beam is characterised by in-plane motion of the beam web and bending motion in the flange. This knowledge has resulted in an improved calculation for the mobility of a bridge at high frequencies. The above improvements are included in an improved model for use by Pandrol in their general activities. Data from real bridges is compared to predictions from the improved model in order to validate different aspects of the model. The model is then used to study the effect on noise of varying many bridge design parameters. It is shown that the parameter that has most influence on the noise performance of a bridge is the dynamic stiffness of the resilient rail fastening system. Additionally it is demonstrated that for a given bridge and noise receiver location, an optimum fastener stiffness exists where the noise radiated by the bridge and track is at a minimum