Today’s cities inflict a mostly adverse impact on our natural environment. Our challenge is to re-imagine future urban environments to improve sustainability, resiliency, and the urban quality of life.
We integrate analytical, experimental, and computational methods with analysis of large urban data sets to understand and predict urban phenomena, and promote social, environmental, and economic sustainability of the cities across future several disciplines:
- water quality and infrastructure
- air quality and wind engineering
- earthquake engineering and structural design
- construction management
- renewable energy
- urban infrastructure, material and energy flows
Wind Engineering for Sustainable Urban Environments
Improving health in slum homes
The objective of this project is to develop and validate a modeling framework that can predict the ventilation rate for different window configurations in a variety of single-room homes and weather conditions. Currently, we are validating a model of a representative single-room slum home in Dhaka, Bangladesh by comparing model predictions with uncertainty quantification to field measurements. The validated model will be leveraged to inform research that investigates the relationship between the ventilation of a home and the occurrence of pneumonia in the household. Learn more >
Infrastructure & Cities
Urban Planning and Integrated Infrastructure Design and Optimization for Sustainability and Resilience
Cities, covering only 3% of the Earth's land, account for 60-80% of global primary energy consumption and roughly 75% of the world's carbon emissions . Besides, 55% of the world's population live in urban areas, a figure expected to reach 68% by 2050 . Hence, urban areas offer a great potential for reducing the global energy consumption and emissions as well as improving the quality of life for a large portion of the human population.
Stanford Urban Resilience Initiative
Compound Flood Risk in the South San Francisco Bay
Projected increases in the frequency of wet winters pose challenges for the future management of infrastructure built under historic climate conditions. We evaluate the risk of downstream compound flooding at the Anderson Dam due to multivariate hazards: extreme and sequential rainfall and hazardous ground shaking driving subsequent dam failure. In a collaborative effort with local city and emergency managers, our research works towards developing management alternatives that can be directly integrated as recommendations into operation plans.
Visit the Stanford Urban Resilience Website for more projects including:
- Use of corridors to support bridge management strategies focused in resilient transportation networks
- Flood risk transfer under changing management strategies and climate conditions
- G-DIF: Geospatial data integration framework to rapidly estimate post-earthquake damage
- Post-earthquake downtime induced by safety cordons
- Quantifying resilience performance objectives of urban systems under the stress of disasters
- Flood risk analysis for valuating ecosystem services
- Crowd sourcing post-earthquake building damage
- Resilient Oakland Initiative
- Linking building damage to organizational disruption
The new GPC Digital Cities research initiative creates a focused research effort bringing together cross-discipline expertise including data analytics, institutional investment on urban sustainability, and exploration of how emerging technologies will change the way we think about business model development for government and enterprises engaged in digital cities. Collaboration with corporate affiliates will ensure market connection, validation, and new ways of transforming disruption into competitive advantage.
Stanford is developing a ground-breaking new visual modeling platform - making it possible to visualize and ask "What If" questions of an entire city. The platform accurately depicts the entire city infrastructure including buildings, roads, infrastructure and transportation. But in addition to this, it is possible to attach physical data to the model including earthquake, flooding, energy flow, financial transactions, commuting data, sensors information, demographics, and a wide range of other information. When this data is applied to the model, the model will display the impact of the data on the city environment and commercial markets.
We address sustainability problems facing the urban built environment by studying socio-technical dynamics at three scales: building, community and urban. Our interdisciplinary research lies at the intersection of civil engineering, data analytics and social science.