A new spectral representation of seismic demand is described for use in the seismic design of new structures and in the evaluation and rehabilitation of existing structures. Yield Point Spectra (YPS) retain the intuitive appeal of the Capacity Spectrum Method (Freeman 1978) and join the Nonlinear Static Procedures of FEMA 273/274 (1997) and ATC 40 (1996) for use in estimating displacement demands. YPS also may be used to establish admissible combinations of strength and stiffness for the design of new structures to limit system ductility and drift to arbitrary values. Graphical procedures allow admissible design regions to be established to satisfy multiple performance objectives. YPS computed for 15 ground motions classified as Short Duration, Long Duration, or as containing near-fault Forward Directivity pulses are presented for bilinear and stiffness-degrading hysteretic models.
A systematic study involving over 20,000 single-degree-of-freedom (SDOF) analyses was made to assess the effects of prior earthquake damage on the peak displacement response of simple oscillators. Principal variables were oscillator strength, period of vibration, degree of prior damage, and load-deformation relation. Base input was provided by 18 recorded ground motions, representing different frequency content, duration, and the presence or absence of near-field forward directivity effects. Prior damage was modeled as a reduction in initial stiffness under the assumption that residual displacements are negligible. The study is restricted to cases in which prior demands are less than those that would result if the structure were initially undamaged. For these conditions, prior damage usually has a minor effect on peak displacement response. This was observed for SDOF oscillators having the Takeda load-deformation relation with positive post-yield stiffness and for a modified Takeda relation incorporating pinched hysteresis and strength degradation. Takeda oscillators with negative post-yield stiffness were prone to collapse, whether or not they had experienced prior damage.
We present Brown Dog, two highly extensible services that aim to leverage any existing pieces of code, libraries, services, or standalone software (past or present) towards providing users with a simple to use and programmable means of automated aid in the curation and indexing of distributed collections of uncurated and/or unstructured data. Data collections such as these encompassing large varieties of data, in addition to large amounts of data, pose a significant challenge within modern day "Big Data" efforts. The two services, the Data Access Proxy (DAP) and the Data Tilling Service (DTS), focusing on format conversions and content based analysis/extraction respectively, wrap relevant conversion and extraction operations within arbitrary software, manages their deployment in an elastic manner, and manages job execution from behind a deliberately compact REST API. We describe both the motivation and need/scientific drivers for such services, the constituent components that allow for arbitrary software/code to be used and managed, and lastly an evaluation of the systems capabilities and scalability.
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