Real-time monitoring of civil infrastructure provides valuable information to assess the health and condition of the associated systems. This paper presents the recently developed shape acceleration array (SAA) and local system identification (SI) technique, which constitute a major step toward long-term effective health monitoring and analysis of soil and soil-structure systems. The SAA is based on triaxial micro-electro-mechanical system (MEMS) sensors to measure in situ deformation (angles relative to gravity) and dynamic accelerations up to a depth of one hundred meters. This paper provides an assessment of this array's performance for geotechnical instrumentation applications by reviewing the recorded field data from a bridge replacement site and a full-scale levee test facility. The SI technique capitalizes on the abundance of static and dynamic measurements from the SAA. The geotechnical properties and constitutive response of soil contained within a locally instrumented zone are analyzed and identified independently of adjacent soil strata. 1. Introduction The health and state of the aging and overburdened civil infrastructure in the United States has been subjected to renewed scrutiny over the last few years. The American Society of Civil Engineers reports that this state threatens the economy and quality of life in every state, city and town in the nation. As one example, the United States Army Corps of Engineers noted in early 2007 that nearly 150 United States levees pose an unacceptable risk of failing during a major flood [1]. Additionally, losses associated with failures of soil systems continue to grow in the United States and elsewhere in view of increased development in hazard-prone areas. The control and mitigation of the effects of these failures requires a better understanding of the field response of soil systems. In order to overcome these problems, the performance of these systems needs to be reliably predicted, and such predictions can be used to improve design and develop efficient remediation measures. The use of advanced in situ monitoring devices of soil systems, such as the shape acceleration array (SAA) system described in this paper, and the development of effective system identification and model calibration is essential to achieve these goals. Soil and soil-structure systems are massive semi-infinite systems that have spatially varying parameters and state variables. These systems exhibit a broad range of complex response patterns when subjected to extreme loading conditions [2–4]. Accurate prediction of site response
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