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The traditional representative volume element (RVE) is usually obtained through an iterative procedure based on the convergence of a selected material property. Although RVEs produced in this manner are generally presumed to automatically capture the salient features of the underlying microstructure, they typically do not achieve this requirement. Alternatively, one can identify a weighted set of statistical volume elements (WSVEs) that captures selected dominant components of n-point spatial correlations of the microstructure to prescribed accuracy. The main advantage of using WSVEs is that the key microstructural features are captured within sets of computationally manageable models ensuring reliable calculation of the material behavior and its variance in an efficient manner. In this paper, this concept of WSVEs is applied and validated for a nearly randomly oriented body-centered cubic β-Ti alloy …