Optimization of condensed stiffness matrices for structural health monitoring

This chapter aims to develop a system identification methodology for determining structural parameters of linear dynamic systems, taking into consideration practical constraints such as insufficient sensors. Based on numerical analysis of measured responses (output) due to known excitations (input), structural parameters such as stiffness values are identified. If the values at the damaged state are compared with the identified values at the undamaged state, damage detection and quantification can be carried out. To retrieve second-order parameters from the identified state space model, various methodologies developed thus far impose different restrictions on the number of sensors and actuators employed. The restrictions are relaxed in this study by a proposed method called the condensed model identification and recovery (CMIR) method. To estimate individual stiffness coefficient from the condensed stiffness matrices, the genetic algorithms approach is presented to accomplish the required optimization problem

Complexities of Coordinating Service-Learning Experiences in Rural Communities

Explored from the viewpoint of the faculty member, nonprofit director, and service-learning staff, this chapter provides insight into the complexity of the service-learning relationship in rural communities. Specifically, it provides perspectives that highlight the cultivation and maintenance of a relationship with a local nonprofit, challenges of incorporating and implementing a e-service-learning project in a hybrid format, and the outcome of the e-service-learning project between a graduate level public health course and a free medical clinic that serves the medically uninsured. These highlights will be discussed through sections detailing the geographical location of the area, through an overview of the local nonprofit community partner, which is a free medical clinic, a review of the community partners various university partnerships, an overview of e-service-learning within the graduate level course, the faculty member perspective, the community partner perspective, and the service-learning staff member perspective