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UTC-UTI Final Research Report 006: "FUNCTIONAL RESILIENCE EVALUATION OF ROAD TUNNELS THROUGH STOCHASTIC EVENT SIMULATION AND DATA ANALYSIS"

Accurate prediction of bridge component condition over time is critical for determining a reliable maintenance, repair, and rehabilitation (MRR) strategy for highway bridges. Based on bridge inspection data, regression models are the most-widely adopted tools used by researchers and state agencies to predict future bridge condition (FHWA 2007). Various regression models can produce quite different results because of the differences in modeling assumptions. The evaluation of model quality can be challenging and sometimes subjective. In this study, an external validation procedure was developed to quantitatively compare the forecasting power of different regression models for highway bridge component deterioration. Several regression models for highway bridge component rating over time were compared using the proposed procedure and a traditional apparent model evaluation method based on the goodness-of-fit to data. The results obtained by applying the two methods are compared and discussed in this paper.

With the increased usage of Cross Laminated Timber (CLT) in the United States, research efforts have been focused on demonstrating CLT as an effective Seismic Force Resisting System (SFRS). Presented in this paper are the findings of full-scale shake table tests of a two-story 223 m2 (2400 ft2) building with two sets of CLT shear walls on the first and second story. The testing consisted of three phases, each with a unique wall configuration, but only the first phase is presented herein, which consisted of a shear wall with 4:1 aspect ratio CLT panels. The structure was subjected to ground motions scaled to intensities that correspond to a Service Level Earthquake (SLE), Design Base Earthquake (DBE), and Maximum Considered Earthquake (MCE) respectively. In all phases and motions the structure performed well and was in accordance with FEMA collapse prevention requirements for each motion intensity.