Dr. Jovan Tatar
Durability of Composites Derived from Renewable Resources
Overview: Fiber-reinforced polymer (FRP) composites have become an essential and widely used construction material. While FRP composites offer significant advantages over concrete and steel—such as higher strength-to-weight ratio, improved durability and faster construction—these materials are produced from non-renewable fossil fuel feedstocks with a substantial carbon footprint. This research examines novel recyclable composite materials manufactured from renewable sources, like natural fibers and biomass-derived epoxy. The specific objective is to investigate the fundamental degradation mechanisms of bio-based composites when exposed to outdoor environments typical for transportation infrastructure (e.g., wet/dry cycles, freeze/thaw, UV, etc.) The project employs sensitive materials characterization techniques and mechanical testing of aged composite samples to elucidate the environmental effects on the material performance.
Suggested coursework: Construction Materials, Construction Materials Lab, Mechanics of Materials, Mechanics of Materials Lab. Equivalent courses are acceptable.
Dr. Andreas Malikopoulos
Understanding Travel Behavior in Emerging Mobility Systems
Overview: How can we design an efficient mobility system with emerging new technologies (self-driving cars and smart public transit all accessible via a phone)? A first step is to understand travel behavior and the tendencies of passengers and drivers. We want to create a “test virtual environment,” and simulate “travel decision instances” for human users to engage with and make decisions. This will enable us to test different incentive schemes (e.g., tolls) and find out which incentives are effective and efficient. Further reading: https://arxiv.org/abs/2011.14399
The game must consist of a player on a virtual map of a generic campus (divided to residential, academic, extracurricular, or social areas). The player must be personalized with a series of questions, setting the player's wants and needs regarding mobility, type of commute, and travel behavior. The human user takes control of the player and plays the game with the objective to reach the final destination safely, affordably, and timely. Based on the personalization, if the player reaches their final destination with a bus but they prefer a taxicab, then the player is unhappy, so the human user loses points in the game (in other words, create a reward happiness mechanism). The game can start at any time of a typical day (weekday morning or weekend night), and the human user will take control of the player and will need to make a decision based on a set of available information. The game decision will be: which mode of transportation to use, whether to use multiple modes, how many stops, how much to invest or to pay for the services. It can definitely be a multiple rounds game, for example, take your player to work in the morning and then bring the player back home while making a stop for shopping groceries (especially if the human user has personalized their player as one having family).
Suggested coursework: Game Theory, Transportation Analysis.
Dr. Mark Nejad
Electric Vehicle Charging Mechanisms Compatible with Dynamic Renewable Energy Production
Overview: Vehicle electrification and automation has the potential to transform transportation into a low-carbon-footprint mode. The objective of this project is to investigate energy-aware charging mechanisms for Electric Automated Vehicles (EAVs). The potential reduction of CO2e emissions of EAVs cannot be fully exploited unless a large part of its charging electricity is produced by renewable energy sources. Given that electricity is perishable, and its storage has limitations, coping with fluctuations in renewable energy production is highly critical. This project will result in a new approach to optimal charging decisions for EAVs. Optimizing charging decisions while considering factors such as renewable energy production, cost, amount and rate of charging, and charging stations availability, brings about new classes of network flow and mechanism design problems. We will contribute to the state-of-the-art by developing new mathematical modeling frameworks and solution methods to address the emerging problems in energy-aware EAV charging.
Suggested coursework: N/A.
Dr. Michael Chajes
Newark’s Sustainability Plan: Implementation and Monitoring Measures
Overview: In November of 2019, the City of Newark finalized an ambitious sustainability plan. The plan was based on significant public input and is organized around four interrelated themes which are: (1) Respond to Climate Change, (2) Plan and Develop for All, (3) Build Better, Waste Less, and (4) Preserve Nature, Reduce Impacts. Among these themes, the concepts of building better using sustainable design strategies and reducing the city’s transportation GHG footprint are both important goals. The project will involve reviewing the plan and its current status, and then conducting research aimed at helping the design, implement, and monitor sustainability strategies that will speed up the city’s electrification and reduce its GHG emissions.
Suggested coursework: Knowledge of sustainability is helpful.
Dr. Shangjia Dong
Critical Facility Access Equity in Facing Disaster Disruption
Overview: Different communities have different levels of access to critical facilities for services that are shaped by their geographic location and socio-economic background. Such access disparity is further exacerbated by natural hazards disruption such as flooding, as communities are exposed to varying flooding risks and people have different capacities to cope with the access disruption. This research aims to assess the network-wide critical facility access equity in facing disaster disruptions. The specific objective is to (1) utilize network modeling tools to analyze the impact of critical facility access disruption in different flooding and human behavioral scenarios and (2) identify critical communities/facilities for targeted hazards mitigation and infrastructure protection.
Suggested coursework: Probability and Statistics for Engineers, Basic programming skills in Python is needed.
Dr. Chris Kloxin
Recyclable Covalent Adaptable Networks
Overview: Thermosetting polymers are used a wide variety of structural applications but are fundamentally incapable of being remelted, remolded, or recycled owing the permanent covalent crosslinking. In contrast, covalent adaptable networks (CANs) implements reversible covalent crosslinkings, enabling bond breaking and reforming to impart non-destructive flow on the macroscopic scale. This new class of materials have the potential to be recycled towards the creation the next generation of sustainable construction materials. This project will consider different CAN formulations and examine the effects on dynamic properties, such as creep and stress relaxation. Through formulation optimization of the mechanical properties, we will tailor these materials for a range of applications that have, to date, had limited potential for recovery or repair.
Suggested coursework: Organic Chemistry and/or Introduction to Polymers are helpful, but not required.
Dr. Koffi Pierre Yao
Factors Affecting Battery Degradation During Fast Charging
Overview: Electrochemical energy storage such as lithium-ion batteries are pivotal to enabling vehicle electrification. While common batteries such as those based on graphite and NCA are currently applied in commercial electric vehicles, their intrinsic energy storage capacities are limited. This results in limited specific range which must be addressed by the use of large number of cells that incur high cost. Extra fast charging (XFC) is a technological pathway that may enable the use of shorter-range batteries in EVs while retaining consumer confidence in their ability to complete long trips through rapid “refueling”. However, fast charging of batteries faces issues of reduced cell life and limited capacities. The project will investigate factors limiting the lifecycle of batteries under fast charging using tools such as battery cyclers, temperature monitoring, and post-mortem FTIR and TEM of electrode to reveal degradation pathways.
Suggested coursework: prior electrochemistry knowledge (best but optional), working knowledge of Thermodynamics and Heat transfer will help.
Dr. Nii Attoh Okine
Digital Twin and Critical Infrastructure
Overview: A digital twin is a computational model (or set of coupled) that evolves over time to persistently represent the critical structure, its components, system or process. Digital twin underpins intelligent automation by supporting data-driven decision making and enabling asset specific analysis and system behavior. Within the contexts of critical Infrastructure Systems, the digital twins represent the flow of information among connected platforms and it does become the central clearinghouse for data and visualization. The digital twin can be used to run “what-if” scenarios, predict and prevent failures, provide early alerts of anomalies and conduct predictive analysis. The strength of digital twin is the interconnectivity of data and models. Hence any model can use any combination of inputs (e.g. operator owned data sets and sensors, third party data bases or weather data, threat modeling or risk modeling. This creates a platform whereby one model may become the input to another. The aim of discuss the formulation and solution of Digital Twin application in critical infrastructure systems.
Suggested coursework: Statistics and Probability; Civil Infrastructure Systems; Systems Engineering.
Dr. Rachel Davidson
Hurricane Evacuation Behavior and the Transportation Network
Overview: When hurricanes occur, thousands or even hundreds of thousands of people may evacuate. At the same time, the road network that many of them rely on to travel to safety and then return may be damaged, temporarily flooded, or otherwise impassable. In Hurricane Florence in 2018, for example, more than 2500 road closure incidents were recorded in North Carolina September 12-29, 91% of which blocked traffic in both directions. In this project, we will use a variety of data types to better understand evacuation movements, and in particular, route choice, the effect of road closures, and timing of the return home. The data will include that from a previously deployed survey of people affected by recent hurricanes, smartphone location data, and data describing the hurricane hazard and effects on the transportation system.
Suggested coursework: Probability and statistics. Equivalent courses are acceptable.