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DesignSafe addresses the challenges of supporting integrative data-driven research in natural hazards engineering. It is an end-to-end data management, communications, and analysis platform where users collect, generate, analyze, curate, and publish large data sets from a variety of sources, including experiments, simulations, field research, and post-disaster reconnaissance. DesignSafe achieves key objectives through: (1) integration with high performance and cloud-computing resources to support the computational needs of the regional risk assessment community; (2) the possibility to curate and publish diverse data structures emphasizing relationships and understandability; and (3) facilitation of real time communications during natural hazards events and disasters for data and information sharing. The resultant services and tools shorten data cycles for resiliency evaluation, risk modeling validation, and forensic studies. This article illustrates salient features of the cyberinfrastructure. It summarizes its design principles, architecture, and functionalities. The focus is on case studies to show the impact of DesignSafe on the disaster risk community. The Next Generation Liquefaction project collects and standardizes case histories of earthquake-induced soil liquefaction into a relational database—DesignSafe—to permit users to interact with the data. Researchers can correlate in DesignSafe building dynamic characteristics based on data from building sensors, with observed damage based on ground motion measurements. Reconnaissance groups upload, curate, and publish wind, seismic, and coastal damage data they gather during field reconnaissance missions, so these datasets are available shortly after a disaster. As a part of the education and community outreach efforts of DesignSafe, training materials and collaboration space are also offered to the disaster risk management community.

Tornado and straight-line wind events are often discussed and compared in terms of their intensity, e.g., maximum wind speed, however, it is unclear to what extent tornadoinduced and straight-line wind-induced wind loads are equivalent even for the same nominal intensity. This lack of understanding inhibits both tornado design philosophies and policies, and communication of tornado risk to the public. This study directly compares existing wind tunnel databases of tornado-induced and straight-line windinduced pressures, for a similar building model, to evaluate to what extent the induced surface pressures on a typical building differ. The existing datasets used in the study are enhanced with a numerical internal pressure model to facilitate the comparison across a range of opening configurations that would be common in typical buildings. The analysis finds that differences are most pronounced in the overall distribution of pressures across the building surface, and in the magnitudes of pressures in regions of strong flow separation. However, overall the magnitudes of the peak tornado-induced pressures are reasonably similar to straight-line wind-induced pressures, with tornadoinduced pressures on average 13% higher than equivalent straight-line wind-induced pressures. Ultimately, this study demonstrates a framework for such comparisons, while recognizing key sources of uncertainty and further research needs.