Towards identification of a general model of damping

Characterization of damping forces in a vibrating structure has long been an active area of research in structural dynamics. In spite of a large amount of research, understanding of damping mechanisms is not well developed. A major reason for this is that unlike inertia and stiffness forces it is not in general clear what are the state variables that govern the damping forces. The most common approach is to use `viscous damping' where the instantaneous generalized velocities are the only relevant state variables. However, viscous damping by no means the only damping model within the scope of linear analysis. Any model which makes the energy dissipation functional non-negative is a possible candidate for a valid damping model. This paper is devoted to develop methodologies for identification of such general damping models responsible for energy dissipation in a vibrating structure. The method uses experimentally identified complex modes and complex natural frequencies and does not a-priori assume any fixed damping model (eg., viscous damping) but seeks to determine parameters of a general damping model described by the so called `relaxation function'. The proposed method and several related issues are discussed by considering a numerical example of a linear array of damped spring-mass oscillators.

Active learning of model evidence using Bayesian quadrature

Numerical integration is a key component of many problems in scientific computing, statistical modelling, and machine learning. Bayesian Quadrature is a modelbased method for numerical integration which, relative to standard Monte Carlo methods, offers increased sample efficiency and a more robust estimate of the uncertainty in the estimated integral. We propose a novel Bayesian Quadrature approach for numerical integration when the integrand is non-negative, such as the case of computing the marginal likelihood, predictive distribution, or normalising constant of a probabilistic model. Our approach approximately marginalises the quadrature model's hyperparameters in closed form, and introduces an active learning scheme to optimally select function evaluations, as opposed to using Monte Carlo samples. We demonstrate our method on both a number of synthetic benchmarks and a real scientific problem from astronomy.

A thermalization energy analysis of the threshold voltage shift in amorphous indium gallium zinc oxide thin film transistors under simultaneous negative gate bias and illumination

It has been previously observed that thin film transistors (TFTs) utilizing an amorphous indium gallium zinc oxide (a-IGZO) semiconducting channel suffer from a threshold voltage shift when subjected to a negative gate bias and light illumination simultaneously. In this work, a thermalization energy analysis has been applied to previously published data on negative bias under illumination stress (NBIS) in a-IGZO TFTs. A barrier to defect conversion of 0.65-0.75 eV is extracted, which is consistent with reported energies of oxygen vacancy migration. The attempt-to-escape frequency is extracted to be 10 6-107 s-1, which suggests a weak localization of carriers in band tail states over a 20-40 nm distance. Models for the NBIS mechanism based on charge trapping are reviewed and a defect pool model is proposed in which two distinct distributions of defect states exist in the a-IGZO band gap: these are associated with states that are formed as neutrally charged and 2+ charged oxygen vacancies at the time of film formation. In this model, threshold voltage shift is not due to a defect creation process, but to a change in the energy distribution of states in the band gap upon defect migration as this allows a state formed as a neutrally charged vacancy to be converted into one formed as a 2+ charged vacancy and vice versa. Carrier localization close to the defect migration site is necessary for the conversion process to take place, and such defect migration sites are associated with conduction and valence band tail states. Under negative gate bias stressing, the conduction band tail is depleted of carriers, but the bias is insufficient to accumulate holes in the valence band tail states, and so no threshold voltage shift results. It is only under illumination that the quasi Fermi level for holes is sufficiently lowered to allow occupation of valence band tail states. The resulting charge localization then allows a negative threshold voltage shift, but only under conditions of simultaneous negative gate bias and illumination, as observed experimentally as the NBIS effect. © 2014 AIP Publishing LLC.