Research

Bayesian methods for the data-driven recovery of networks: measuring impact and building resilience in infrastructures and communities

Funding agency: National Science Foundation

The objective of this work is to develop a new data-driven optimization framework to improve (i) the ability to model the performance of infrastructure networks, and (ii) the ability to plan for the recovery of these networks after a disruption, with an emphasis on community resilience and economic productivity.

The research approach is composed of three components. The first component develops a new statistical technique, the hierarchical Bayesian kernel method, which integrates the Bayesian property of improving predictive accuracy as data are dynamically obtained, the kernel function that adds specificity to the model and can make nonlinear data more manageable, and the hierarchical property of borrowing information from different sources in sparse and diverse data situations which are common in disruptive events scenarios. The second component develops an infrastructure network recovery optimization formulation that minimizes the larger impact of infrastructure network performance with data-driven (and dynamically updated) hierarchical Bayesian kernel parameters of infrastructure recovery, along with solution techniques that account for the size and dynamic nature of model parameters. The application of the first two integrated components to electric power networks (where impact is measured on the safety and resilience of the community) and inland waterways (where impact is measured on economic productivity across multiple industries), constitutes the third component, offering two application perspectives on the impact of infrastructure network resilience and recovery.

Mississippi river supply chain management

Funding agency: U.S. Department of Housing and Urban Development through the Tennessee Department of Economic and Community Development

The project focus is primarily on the port development project in Lake County, where significant investments have been made to create an attractive port and economic development infrastructure. The Cates Landing Port is Tennessee’s newest port and sits in the center of a multistate agricultural and industrial development region, located not just in a protected harbor along the Mississippi River but near the Canadian national mainline between Chicago and New Orleans, the intersection of several interstate highways and adjacent to the designated I-69 “North American Corridor.”

The objective of this project is to help stakeholders in the affected region understand how their actions and behaviors can impact the resilience of the prospective waterborne commerce that might be attracted to this region and the new port developments that have been implemented in recent years.  Extreme weather impacts the overall economic vitality of the target region and the resulting competitiveness in attracting development that can take advantage of the natural locational advantages.

A cradle to grave approach to supply chain modeling will establish the barriers to shippers locating proximate to the port footprint. A mode choice analysis will focus particularly on the inland maritime service options that are available as a result of the infrastructure buildout at Cates Landing. And finally, an all hazards analysis including use of Hazus developed by FEMA that can look particularly at how vulnerabilities in the region may affect the relative attractiveness of development and what opportunities for mitigation may be possible.

Maritime Transportation Research and Education Center (MarTREC)

Funding agency: U.S. Department of Transportation

The Maritime Transportation Reseach and Education Center (MarTREC) is a consortium led by the University of Arkansas in which Vanderbilt is a member. MarTREC is a USDOT Tier 1 University Transportation Center.

Vanderbilt University, specifically the Vanderbilt Center for Transportation and Operational Resiliency (VECTOR), is involved in research areas focused on (i) improving understanding of the impacts to inland marine transportation due to the shift in domestic energy production, (ii) the potential impacts of climate change and extreme weather on the inland marine transportation systems and operations, and (iii) improving decision support using advanced data analytics including agent-based modeling, river information services, simulations, among other methodologies.

Multi-scale modeling and observations of landscape dynamics, mass balance, and network connectivity for a sustainable Ganges-Brahmaputra delta

Funding agency: National Science Foundation

River deltas around the world are in a state of modest to severe decline, primarily in response to anthropogenic activities. These settings are also among the world’s most physically dynamic, being impacted by sea-level rise and subsidence, river flooding, channel erosion, and storms. Such vulnerabilities are further magnified in highly populated delta systems, notably the large mega-deltas that rim Asian coasts in politically sensitive regions from Pakistan to China. These environments suffer not only from having more humans, infrastructure, and livelihoods in peril, but also from the anthropogenic strain that large populations place on physical and ecological support systems. In Bangladesh and West Bengal, India, the Ganges-Brahmaputra-Meghna delta (GBMD) may well be the prime example as the world’s largest and most densely populated delta system, hosting 150 million people in an area the size of Louisiana. In this Coastal SEES project, a diverse group of scholars with expertise across several earth-science and engineering disciplines are brought together to answer questions about the fate and future sustainability of the GBMD and its human population.

Specifically, our group wants to understand how are human activities affecting this channel-network system, and what are the subsequent repercussions on the infrastructure network and the economy. We are developing network models integrated with Bayesian approaches to assess the risk and resilience of the inland transportation network governed by the GBMD. Interdependency economic models will help understand the regional and national impact of changes in river deltas.

Bayesian methods for the data-driven recovery of networks: measuring impact and building resilience in infrastructures and communities

Funding agency: National Science Foundation

The objective of this work is to develop a new data-driven optimization framework to improve (i) the ability to model the performance of infrastructure networks, and (ii) the ability to plan for the recovery of these networks after a disruption, with an emphasis on community resilience and economic productivity.

The research approach is composed of three components. The first component develops a new statistical technique, the hierarchical Bayesian kernel method, which integrates the Bayesian property of improving predictive accuracy as data are dynamically obtained, the kernel function that adds specificity to the model and can make nonlinear data more manageable, and the hierarchical property of borrowing information from different sources in sparse and diverse data situations which are common in disruptive events scenarios. The second component develops an infrastructure network recovery optimization formulation that minimizes the larger impact of infrastructure network performance with data-driven (and dynamically updated) hierarchical Bayesian kernel parameters of infrastructure recovery, along with solution techniques that account for the size and dynamic nature of model parameters. The application of the first two integrated components to electric power networks (where impact is measured on the safety and resilience of the community) and inland waterways (where impact is measured on economic productivity across multiple industries), constitutes the third component, offering two application perspectives on the impact of infrastructure network resilience and recovery.

Mississippi river supply chain management

Funding agency: U.S. Department of Housing and Urban Development through the Tennessee Department of Economic and Community Development

The project focus is primarily on the port development project in Lake County, where significant investments have been made to create an attractive port and economic development infrastructure. The Cates Landing Port is Tennessee’s newest port and sits in the center of a multistate agricultural and industrial development region, located not just in a protected harbor along the Mississippi River but near the Canadian national mainline between Chicago and New Orleans, the intersection of several interstate highways and adjacent to the designated I-69 “North American Corridor.”

The objective of this project is to help stakeholders in the affected region understand how their actions and behaviors can impact the resilience of the prospective waterborne commerce that might be attracted to this region and the new port developments that have been implemented in recent years.  Extreme weather impacts the overall economic vitality of the target region and the resulting competitiveness in attracting development that can take advantage of the natural locational advantages.

A cradle to grave approach to supply chain modeling will establish the barriers to shippers locating proximate to the port footprint. A mode choice analysis will focus particularly on the inland maritime service options that are available as a result of the infrastructure buildout at Cates Landing. And finally, an all hazards analysis including use of Hazus developed by FEMA that can look particularly at how vulnerabilities in the region may affect the relative attractiveness of development and what opportunities for mitigation may be possible.

Maritime Transportation Research and Education Center (MarTREC)

Funding agency: U.S. Department of Transportation

The Maritime Transportation Reseach and Education Center (MarTREC) is a consortium led by the University of Arkansas in which Vanderbilt is a member. MarTREC is a USDOT Tier 1 University Transportation Center.

Vanderbilt University, specifically the Vanderbilt Center for Transportation and Operational Resiliency (VECTOR), is involved in research areas focused on (i) improving understanding of the impacts to inland marine transportation due to the shift in domestic energy production, (ii) the potential impacts of climate change and extreme weather on the inland marine transportation systems and operations, and (iii) improving decision support using advanced data analytics including agent-based modeling, river information services, simulations, among other methodologies.

Multi-scale modeling and observations of landscape dynamics, mass balance, and network connectivity for a sustainable Ganges-Brahmaputra delta

Funding agency: National Science Foundation

River deltas around the world are in a state of modest to severe decline, primarily in response to anthropogenic activities. These settings are also among the world’s most physically dynamic, being impacted by sea-level rise and subsidence, river flooding, channel erosion, and storms. Such vulnerabilities are further magnified in highly populated delta systems, notably the large mega-deltas that rim Asian coasts in politically sensitive regions from Pakistan to China. These environments suffer not only from having more humans, infrastructure, and livelihoods in peril, but also from the anthropogenic strain that large populations place on physical and ecological support systems. In Bangladesh and West Bengal, India, the Ganges-Brahmaputra-Meghna delta (GBMD) may well be the prime example as the world’s largest and most densely populated delta system, hosting 150 million people in an area the size of Louisiana. In this Coastal SEES project, a diverse group of scholars with expertise across several earth-science and engineering disciplines are brought together to answer questions about the fate and future sustainability of the GBMD and its human population.

Specifically, our group wants to understand how are human activities affecting this channel-network system, and what are the subsequent repercussions on the infrastructure network and the economy. We are developing network models integrated with Bayesian approaches to assess the risk and resilience of the inland transportation network governed by the GBMD. Interdependency economic models will help understand the regional and national impact of changes in river deltas.