Filtern
Dokumenttyp
- Zeitschriftenartikel (4) (entfernen)
Sprache
- Englisch (4)
Referierte Publikation
- ja (4)
Schlagworte
- Inverse problem (4) (entfernen)
In this contribution, we present an efficient approach for the transient and time-causal modeling of guided waves in viscoelastic cylindrical waveguides in the context of ultrasonic material characterization. We use the scaled boundary finite element method (SBFEM) for efficient computation of the phase velocity dispersion. Regarding the viscoelastic behavior of the materials under consideration, we propose a decomposition approach that considers the real-valued frequency dependence of the (visco-)elastic moduli and, separately, of their attenuation. The modal expansion approach is utilized to take the transmitting and receiving transducers into account and to propagate the excited waveguide modes through a waveguide of finite length. The effectiveness of the proposed simulation model is shown by comparison with a standard transient FEM simulation as well as simulation results based on the exact solution of the complex-valued viscoelastic guided wave problem. Two material models are discussed, namely the fractional Zener model and the anti-Zener model; we re-interpret the latter in terms of the Rayleigh damping model. Measurements are taken on a polypropylene sample and the proposed transient simulation model is used for inverse material characterization. The extracted material properties may then be used in computer-aided design of ultrasonic systems.
This paper deals with the system identification of a mechanical structure supported by nonlinear springs subjected to an external load. If all mechanical parameters of the system were known, the displacement of the system subjected to this load could be easily calculated. However, the monitoring applications often deal with the inverse problem. The loads and displacements of the system are known and certain mechanical Parameters of the system are sought. The solution of such inverse problems can be difficult, especially when they have a nonlinear and multimodal character, which often makes them appear intractable at first sight. However, evolutionary computing can be applied to solve this inverse, nonlinear and multimodal problem. Sometimes a prior knowledge exists on certain system properties, which is difficult to implement into analytical or numerical solvers. This knowledge can play a decisive role in identifying the System properties and it can be easily included as a boundary condition when applying evolutionary algorithms.
This article discusses how and under what conditions the unknown spring resistances can be identified. The practical application of this procedure is exemplified here with the mechanical system of a pile foundation.
Micro-cracks in a magnetized ferromagnetic material cause stray fields that can be observed using giant magnetoresistive (GMR) sensors. This work investigates the applicability of GMR sensors to the non-destructive evaluation of micro-cracks via the observation of stray fields. For this purpose, our measurement setup is assessed using a fast new sensitivity analysis based on adjoint states, employing the finite-element method. A model for the GMR sensor is developed and verified. We are able to resolve micro-cracks with an opening of 3 µm and a depth of 30 µm. GMR positioning inaccuracies are analyzed.
The determination of material parameters from displacement field measurement is being examined for linear elastic solid. A frequently used approach to compute material constants can be found in many studies. Even though they presented the approach in many different variations, but in the end they are essentially based on the same algorithm: Parameters are iteratively tuned until the computed results are in accordance with the measurements. The main drawback of this approach is that mainly commercial software is used that hinders us to investigate its inner evaluation process. This leads to the question, how the results from this commercial software can be trusted. On the contrary to these debatable approaches, we present a method that inverts the procedure of finite element method by using the most general model for a least-squares adjustment – the GAUSS-HELMERT Model.