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This paper presents a methodology to evaluate life safety risk of coastal communities vulnerable to seismic and tsunami hazards. The work explicitly incorporates two important aspects in tsunami evacuation modeling: (1) the effect of earthquake-induced damage to buildings on building egress time, (2) the effect of earthquake-induced debris on horizontal evacuation time. The city of Seaside, Oregon, is selected as a testbed community. The hazard is based on a megathrust earthquake and tsunami from the Cascadia Subduction Zone that was defined in a previous study. The built environment consists of buildings and the transportation network for the city. Fragility analysis is used to estimate the seismic damage to buildings and resulting debris that covers portions of the road network. The horizontal evacuation time is determined based on the shortest path to shelters, including the increased travel time due to the earthquake-generated debris. The effects of different mitigation strategies are quantified. Results indicate the fatality and life safety risk of a near-field tsunami increases by 4.2–8.3 times when the effects of building egress and earthquake-induced debris are considered. The choice of population layer affects the life safety risk and thus the maximum risk is obtained when daytime populations are considered. Use of mitigation strategies result in a significant decrease in the number of fatalities. For hazards with recurrence intervals larger than 500- to 1000-years, the seismic retrofit is comparable to vertical evacuation and an effective strategy in reducing fatalities and associated risks. Implementing all mitigation strategies reduces the life safety risk by 90%. [ABSTRACT FROM AUTHOR]

Probabilistic seismic risk is affected by several sources of uncertainty. Investigating their influence on loss analysis results is essential to obtain reliable quantitative estimations of seismic performance. Within the framework developed by the Pacific Earthquake Engineering Research (PEER) Center for probabilistic seismic loss analysis, this study incorporates the effect of seismic demand model class uncertainty on seismic risk performance metric estimation. The extended formulation is illustrated with an application example code-designed reinforced concrete moment resisting frame building with unreinforced masonry (URM) infill walls, where model class uncertainty related to URM infill walls modeling is propagated to the estimation of seismic financial losses. Model class uncertainty accounts for the variability arising from the use of different modeling solutions, such as the ones associated with the adoption of three equivalent strut macro-models and their modeling parameters. Probabilistic distributions are assigned to selected infill strut model parameters, and a large set of finite element models (FEMs) are generated for each infill strut model class by sampling the model parameter distributions through Latin Hypercube Sampling (LHS). Expected values of repair cost and life-cycle annualized loss are evaluated and compared for two sets of three building performance models. The first set considers the original (median) values of infill strut backbone parameters, while the second set includes model parameter uncertainty. The uncertainty propagation from structural response results to repair costs is also reported for the six performance models. Finally, the contribution of different structural and non-structural element categories to the financial losses is presented. [ABSTRACT FROM AUTHOR]

In this paper, unreinforced masonry (URM) and retrofitted masonry walls are modeled experimentally and computationally. The walls were subjected to in-plane loading to assess on the effectiveness of a retrofit solution that makes use of near surface mounted (NSM) reinforcing steel bars. A laboratory testing campaign was performed that included pull-out tests, diagonal compression tests, and in-plane cyclic tests of URM and NSM retrofitted physical models. The experimental results indicate that the NSM reinforcing steel bars are effective in improving the deformation capacity of the URM walls. A computational modeling approach that makes use of the applied element method is proposed and the computational results are validated using the experimental tests presented. Results from computational models indicate that a good correlation with the test results is achieved in terms of load-displacement response as well as failure mechanisms observed. [ABSTRACT FROM AUTHOR]

Probabilistic Tsunami Hazard Analysis (PTHA) can be used to evaluate and quantify tsunami hazards for planning of integrated community-level preparedness, including mitigation of casualties and dollar losses, and to study resilient solutions for coastal communities. PTHA can provide several outputs such as the intensity measures (IMs) of the hazard quantified as a function of the recurrence interval of a tsunami event. In this paper, PTHA is developed using a logic tree approach based on numerical modeling for tsunami generated along the Cascadia Subduction Zone. The PTHA is applied to a community on the US Pacific Northwest Coast located in Newport, Oregon. Results of the PTHA are provided for five IMs: inundation depth, flow speed, specific momentum flux, arrival time, and duration of inundation. The first three IMs are predictors of tsunami impact on the natural and built environment, and the last two are useful for tsunami evacuation and immediate response planning. Results for the five IMs are presented as annual exceedance probability for sites within the community along several transects with varying bathymetric and topographic features. Community-level characteristics of spatial distribution of each IM for three recurrence intervals (500, 1000, 2500 year) are provided. Results highlight the different pattern of IMs between land and river transects, and significant magnitude variation of IMs due to complex bathymetry and topographic conditions at the various recurrence intervals. IMs show relatively higher magnitudes near the coastline, at the low elevation regions, and at the harbor channel. In addition, results indicate a positive correlation between inundation depth and other IMs near the coastline, but a weaker correlation at inland locations. Values of the Froude number ranged 0.1-1.0 over the inland inundation area. In general, the results in this study highlight the spatial differences in IMs and suggest the need to include multiple IMs for resilience planning for a coastal community subjected to tsunami hazards. [ABSTRACT FROM AUTHOR]