Comparative study on damage identification from lso-Eigen-Value-Change contours and smeared damage model

The paper proposes two methodologies for damage identification from measured natural frequencies of a contiguously damaged reinforced concrete beam, idealised with distributed damage model. The first method identifies damage from Iso-Eigen-Value-Change contours, plotted between pairs of different frequencies. The performance of the method is checked for a wide variation of damage positions and extents. The method is also extended to a discrete structure in the form of a five-storied shear building and the simplicity of the method is demonstrated. The second method is through smeared damage model, where the damage is assumed constant for different segments of the beam and the lengths and centres of these segments are the known inputs. First-order perturbation method is used to derive the relevant expressions. Both these methods are based on distributed damage models and have been checked with experimental program on simply supported reinforced concrete beams, subjected to different stages of symmetric and un-symmetric damages. The results of the experiments are encouraging and show that both the methods can be adopted together in a damage identification scenario.

Reliability models for existing structures based on dynamic state estimation and data based asymptotic extreme value analysis

The problem of time variant reliability analysis of existing structures subjected to stationary random dynamic excitations is considered. The study assumes that samples of dynamic response of the structure, under the action of external excitations, have been measured at a set of sparse points on the structure. The utilization of these measurements m in updating reliability models, postulated prior to making any measurements, is considered. This is achieved by using dynamic state estimation methods which combine results from Markov process theory and Bayes' theorem. The uncertainties present in measurements as well as in the postulated model for the structural behaviour are accounted for. The samples of external excitations are taken to emanate from known stochastic models and allowance is made for ability (or lack of it) to measure the applied excitations. The future reliability of the structure is modeled using expected structural response conditioned on all the measurements made. This expected response is shown to have a time varying mean and a random component that can be treated as being weakly stationary. For linear systems, an approximate analytical solution for the problem of reliability model updating is obtained by combining theories of discrete Kalman filter and level crossing statistics. For the case of nonlinear systems, the problem is tackled by combining particle filtering strategies with data based extreme value analysis. In all these studies, the governing stochastic differential equations are discretized using the strong forms of Ito-Taylor's discretization schemes. The possibility of using conditional simulation strategies, when applied external actions are measured, is also considered. The proposed procedures are exemplifiedmby considering the reliability analysis of a few low-dimensional dynamical systems based on synthetically generated measurement data. The performance of the procedures developed is also assessed based on a limited amount of pertinent Monte Carlo simulations. (C) 2010 Elsevier Ltd. All rights reserved.

Dimensionality of quality from a customer perspective in the wood industry

The research analyzes product quality from a customer perspective in the case of the wood products industry. Of specific interest is to understand better how environmental quality is perceived from a customer perspective. The empirical material used comprises four data-sets from Finland, Germany and the UK, collected during 1992 2004. The methods consist of a set of quantitative statistical analyses. The results indicate that perceived quality from a customer perspective can be presented using a multidimensional and hierarchical construct with tangible and intangible dimensions, that is common to different markets and products. This applies in the case of wood products but also more generally at least for some other construction materials. For wood products, tangible product quality has two main sub-dimensions: technical quality and appearance. For product intangibles, a few main quality dimensions seem be detectable: Quality of intangibles related to the physical product, such as environmental issues and product-related information, supplier-related characteristics, and service and sales personnel behavior. Environmental quality and information are often perceived as being inter-related. Technical performance and appearance are the most important considerations for customers in the case of wood products. Organizational customers in particular also clearly consider certain intangible quality dimensions to be important, such as service and supplier reliability. The high technical quality may be considered as a license to operate , but product appearance and intangible quality provide potential for differentiation for attracting certain market segments. Intangible quality issues are those where Nordic suppliers underperform in comparison to their Central-European competitors on the important German markets. Environmental quality may not have been used to its full extent to attract customers. One possibility is to increase the availability of the environment-related information, or to develop environment-related product characteristics to also provide some individual benefits. Information technology provides clear potential to facilitate information-based quality improvements, which was clearly recognized by Finnish forest industry already in the early 1990s. The results indeed indicate that wood products markets are segmented with regard to quality demands