Application of regularization methods to damage detection in large scale plane frame structures using incomplete noisy modal data

This paper presents an approach for detecting local damage in large scale frame structures by utilizing regularization methods for ill-posed problems. A direct relationship between the change in stiffness caused by local damage and the measured modal data for the damaged structure is developed, based on the perturbation method for structural dynamic systems. Thus, the measured incomplete modal data can be directly adopted in damage identification without requiring model reduction techniques, and common regularization methods could be effectively employed to solve the developed equations. Damage indicators are appropriately chosen to reflect both the location and severity of local damage in individual components of frame structures such as in brace members and at beam-column joints. The Truncated Singular Value Decomposition solution incorporating the Generalized Cross Validation method is introduced to evaluate the damage indicators for the cases when realistic errors exist in modal data measurements. Results for a 16-story building model structure show that structural damage can be correctly identified at detailed level using only limited information on the measured noisy modal data for the damaged structure.

A modelling approach for coupling numerical analytical techniques applied in microsystems

In this paper, a method for the integration of several numerical analytical techniques that are used in microsystems design and failure analysis is presented. The analytical techniques are categorized into four groups in the discussion, namely the high-fidelity analytical tools, i.e. finite element (FE) method, the fast analytical tools referring to reduced order modeling (ROM); the optimization tools, and probability based analytical tools. The characteristics of these four tools are investigated. The interactions between the four tools are discussed and a methodology for the coupling of these four tools is offered. This methodology consists of three stages, namely reduced order modeling, deterministic optimization and probabilistic optimization. Using this methodology, a case study for optimization of a solder joint is conducted. It is shown that these analysis techniques have mutual relationship of interaction and complementation. Synthetic application of these techniques can fully utilize the advantages of these techniques and satisfy various design requirements. The case study shows that the coupling method of different tools provided by this paper is effective and efficient and it is highly relevant in the design and reliability analysis of microsystems