Congratulations to Dr. Wangda Zuo! An Assistant Professor in the Civil, Architectural, and Environmental Engineering Department at the University of Miami College of Engineering, Dr. Zuo runs the Sustainable Building Systems Laboratory (SBS Lab), which focuses on developing cutting edge modeling and simulation technology and applying them to reduce building energy and water consumption while improving indoor environment quality. The SBS Lab is funded by various agencies, including National Science Foundation (NSF); U.S. Department of Energy ( DOE); U.S. Department of Defense; U.S. Department of Homeland Security; American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE); and JPMorgan Chase & Co. Dr. Zuo is currently working on three important grant projects.
On August 30, 2016, Dr. Zuo (PI) received a $443,867 research award from NSF (Award No 1633338) for his proposed research titled: “BIG DATA: Collaborative Research: IA: Big Data Analytics for Optimized Planning of Smart, Sustainable, and Connected Communities” (a joint research project with Virginia Tech).
Transforming villages, towns, and cities into smart, connected, and sustainable communities is one of the most critical technological challenges of the coming decade. Realizing this vision is contingent upon enabling existing community infrastructure such as transportation, communications, and energy systems, to seamlessly integrate sustainable components such as renewable sources, smart sensors, and electric vehicles. Such an integration will ensure that tomorrow’s communities are truly sustainable and connected by exhibiting desirable qualities that include:
a) zero energy, in that they are self-sufficient in their energy production,
b) zero outage, in that communication links across the community are ultra-reliable and experience significantly low interruption, and
c) zero congestion, in that the traffic congestion is minimized across the community.
With this overarching vision, the goal of this project is to develop a new planning framework for smart, connected and sustainable communities that allows meeting such zero-energy, zero-outage, and zero-congestions goals by optimally deciding on how, when, and where to deploy or upgrade a community’s infrastructure. These decisions will be driven by massive volumes of community data, stemming from multiple sources that can include mobility, energy, traffic, communication demands, and other socio-technological information, to make informed decisions on how to gradually and organically transform a community into a fully sustainable and truly connected environment.
The scale and heterogeneity of this problem necessitates the need for innovation in the tools used to process, analyze, and visualize heterogeneous data, as well as the data-aware metrics used to monitor the performance of this community infrastructure. One key element of this research is creation of a virtual testbed that can accurately reconstruct, simulate, and evaluate the theoretical framework by leveraging real-world big data sets from Virginia Tech and a zero-energy community in Florida as well as other sources, such as the DOE. The testbed is intended to be open access and will be able to support both research at host institution as well as other users requiring non-proprietary multi-domain open-data sets. The holistic nature of this research is thus expected to catalyze the global deployment of sustainable and connected communities. The proposed research will be complemented by a smart community big data challenge event that will enable broad community participation. The educational plan includes new big data-centric courses, as well as a large-scale involvement of graduate and undergraduate students in big data and smart communities research. Broad dissemination is ensured via open-source software and periodic workshops and tutorials. K-12 outreach events will be organized to attract under-represented student groups to big data research.
This transformative research will lay the theoretical and practical foundations of smart, connected, and sustainable communities by developing the first big data-driven holistic approach to joint planning, optimization, and deployment of community infrastructure for systems of critical importance, such as communication, energy, and transportation networks. By bringing together interdisciplinary domain experts from data science, electrical engineering, and civil and architectural engineering, this research will yield several innovations:
1) Novel big data techniques for faithfully creating spatio-temporal models for smart communities that integrate data from heterogeneous sources and shed light on the composition and operation of a given smart community,
2) Novel, data-driven performance metrics that advance powerful mathematical tools from stochastic geometry to explicitly quantify the health of smart communities via tractable notions of zero energy, zero outage, and zero congestion,
3) Advanced analytical tools that bring forward novel ideas from optimization theory to devise the most effective strategies for deploying, upgrading, and operating various community infrastructure nodes, given the scale, dynamics, and structure of both the data and the community, and
4) A virtual smart community testbed that can accurately reconstruct, simulate, and evaluate the theoretical framework by leveraging open non-proprietary real-world big data sets.
Additionally, a team of University of Miami researchers including Dr. Zuo (Co-PI), Landolf Rhode-Barbarigos (PI), and Sonia R. Chao (Co-PI), also recently received a $299,579 award from the NSF (Award No 1638336) for their proposed research titled: “CRISP Type 1/Collaborative Research: A Human-Centered Computational Framework for Urban and Community Design of Resilient Coastal Cities” (another joint research project with Virginia Tech).
Coastal cities play a critical role in the global economy. However, they are being increasingly exposed to natural hazards and disasters, such as hurricanes, and recurrent flooding due to the rise of sea-levels caused by climate change. These disasters directly impact critical coastal infrastructure such as the energy, transportation, water, and sewer systems as well as streets, buildings and houses of coastal cities, thus adversely affecting the safety and well-being of their residents. The goal of this research is to create new paradigms for the resilient design of urban communities, and uniquely tailored toward the design of coastal cities, thus contributing to NSF’s science and engineering mission. Results from this research will help make critical coastal infrastructures more tolerant to damage. The in turn will foster socio-economic resilience by enabling anticipatory interventions. The developed techniques and simulation models will redefine traditional urban design strategies through the integration of architecture, urban design, land-use planning, civil engineering, and advanced computational methods that explicitly consider socio-economic drivers. This project will be conducted in close collaboration with the cities of Miami and Miami Beach.
In addition to these collaborations serving as as case studies for the proposed research, the research will directly and tangibly benefit high-risk coastal urban centers by providing them with clear, context-specific recommendations with respect to implementing resiliency. Broad dissemination efforts will be undertaken via a series of seminars for decision-makers and practitioners within the cities of Miami and Miami Beach. An exposition at the Miami Museum of Science will be organized to raise awareness and promote research on resiliency. The project will involve students via direct engagement in the research as well as via new learning modules that will integrate research findings into the existing curriculum. The proposed educational plan will thus help train a new workforce that is skilled in STEM disciplines, in general, and adept in resiliency planning of coastal cities, in particular. In addition to serving NSF’s science mission, therefore, this project also serves its education mission.
This transformative research will introduce a novel methodological approach that symbiotically integrates urban design and socio-economic considerations into an advanced simulation and optimization framework to enhance the resilience of a coastal city’s critical infrastructure. This human-centered computational framework will help identify key resilient infrastructures, and design and land use patterns that will increase the damage tolerance of coastal cities while reducing the socio-economic impacts of coastal hazards and disasters. The proposed approach will bring together an interdisciplinary set of collaborators from engineering, architecture, and social sciences, to yield several key innovations:
1) a holistic human-centered computational framework for the design of resilient cities;
2) identification of key typologies, morphologies and their interdependencies by analyzing the urban design and its infrastructure networks;
3) an innovative flexible modeling and computational framework that integrate socio-economic characteristics for simulation and resilience optimization (damage tolerance) of the critical infrastructure;
4) a novel optimization framework that will facilitate making damage tolerance decisions that can achieve anticipatory resilience in face of disaster uncertainty; and
5) new identified interdependencies, trends, and typologies of socio-economic system of highly-urbanized coastal communities based on the cities of Miami and Miami Beach in Florida.
In summary, the proposed research will lay the scientific foundation for envisioning and redesigning resilient coastal cities making them ready to meet anticipated future challenges.
Dr. Zuo is also the PI working on “1771-TRP, Energy Modeling of Typical Commercial Buildings in Support of ASHRAE Building Energy Quotient Energy Rating Program” a $199,395 grant funded by ASHRAE (the American Society of Heating, Refrigerating, and Air-Conditioning Engineers) (04/2016-04/2018). Co-PI is Gang Wang, PhD (pictured at right) also with UM’s College of Engineering’s Department of Civil, Architectural, and Environmental Engineering. In this project, Dr. Zuo and Dr. Wang we will use CCS’s supercomputer Pegasus to perform millions of building energy simulations that would take 16 years if they were using a desktop computer. This research outcome will be used by the development of ASHARE’s building energy quotient energy rating program, which is aimed to improve building energy efficiency of the world.
Dr. Zuo currently has multiple openings for Ph.D. students in two areas. Both are fully supported and expected to start no later than 8/2017 (preferably 1/2017) .
- Area 1: Computational Fluid Dynamics
- Area 2: Modeling of Infrastructure Systems for Smart and Resilient Cities.
Please send your applications to Dr. Zuo: email@example.com.