Critical Infrastructure Sustainability and Security
Critical Infrastructure Sustainability and Security will promote the development of fundamental engineering to embed resilience into the design strategies, standards and regulatory frameworks of critical infrastructure systems through predictive understanding of climate and security hazards with geospatial Big Data and computational solutions. It will develop a framework for establishing translational solutions in collaboration with academic partners, industry leaders and startups, as well as national laboratories and federal agencies.
Critical infrastructure sectors ranging from water/wastewater, transportation, energy, and communication systems to commercial, government sector, and critical response facilities need to embed resilience and sustainability into design strategies, standards, and regulatory frameworks. Homeland security may be a direct function of enhanced resilience since less vulnerable facilities are less attractive targets for asymmetric threats. The ability to develop a predictive understanding of risks, vulnerabilities, and threats remain important, which calls for solutions in geospatial knowledge discovery from data and models. In addition, climate change and associated extremes ranging from heat waves, cold snaps and heavy rain to floods, droughts, water scarcity, and hurricanes, have significant impacts on critical infrastructures sectors and provide important opportunities for coupling sustainable and resilient design strategies.
As a recent U.S. presidential directive suggests, and as has been demonstrated through reports of the IPCC and the U.S. National Assessments, a key national challenge is to develop solutions for resilient communities that minimize energy, materials, pollution and waste and that can incorporate credible projections of climate change and extremes at resolutions and time horizons relevant to stakeholders. The problem grows challenging owing to the massive size of climate data and the complexity of dependence structures and generation processes. This requires Big Data solutions for physics-guided data mining, intelligent diagnostics of sensors, predictability studies based on nonlinear dynamics, and regional simulation models that are geospatially aware.
Northeastern University in general, and the College of Engineering is particular, is well suited to develop and lead such an initiative. The theme of the proposed initiative fits within the university thrusts in sustainability, security, along with health and with Big Data solutions. While the impacts are not limited to urban or coastal areas, the nature of the threats and change are likely to have disproportionate consequences on urban and populated regions, and for certain kind of threats, on coastal communities.