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Time-history deformation analyses of upstream-raised tailings dams useseismic records as input data. Such records must be representative of thein-situ seismicity in terms of a wide range of intensity measures (IMs)including peak ground acceleration (PGA), Arias intensity (AI), cumulativeabsolute velocity (CAV), source-to-site distance, duration, among others. Nosingle IM is a sufficient descriptor of a given seismic demand (e.g. crestsettlement) because different records, all of them compliant with any IM, canproduce a very wide range of results from insignificant damage to globalfailure. The use of brute force, where hundreds of seismic records compliantwith a set of IMs are employed, has proven to be a reasonable workaround ofthis limitation, at least able to produce a probabilistic density function ofdemand indicators. This procedure, however, requires a large number of runs,and is therefore expensive and time-consuming. Analyses can be optimized if ana priori simple tool is used to predict which seismic records would yield agiven demand, thus obtaining estimations with much fewer runs. In order toperform a more precise selection, a semi-analytical screening procedure ispresented in this paper. The procedure makes use of the spectral properties ofthe seismic record, considering only the intensity of the frequency contentwhich is not filtered by the dam to obtain an a priori estimate of demand,expressed in this case in terms of displacements. The tool is validated usinganalytical and numerical models that prove insensitivity to the constitutivemodel used in the analysis, and is applied to a large tailings dam subjected tostrong earthquakes.

Screening of seismic records to perform time-history dynamic analyses of tailings dams: a power-spectral based approach