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.

Overview: This project is centered on enhancing interaction and coordination between autonomous vehicles (AVs). It aims to develop algorithms and systems that enable AVs to share information and make joint decisions, improving traffic flow and navigation efficiency. Students will explore the integration of advanced sensor technologies and machine learning techniques to facilitate distributed intelligence for AVs. Students participating in this project will have a unique opportunity for hands-on experience, involving programming multiple Raspberry Pi Cars, each equipped with a camera, to work in unison for efficient and accurate object detection and decisions. This hands-on approach provides a direct insight into the challenges and potential solutions for collaborative decision-making in autonomous vehicle systems, allowing students to apply theoretical concepts to real-world scenarios. 

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Suggested coursework: N/A

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.

Overview: With the expansion of the STAR campus (south), and the reconfiguration of the Laird campus (north), there is a growing need to have a safe, efficient, effective people mover that can be used by students, staff, faculty, visitors, and the residents of Newark to connect these locations.  It would be ideal if such a people mover would utilize clean energy and be net zero.  This project involves establishing the demand for such a people mover, setting project design criteria, researching analogous solutions around the country and the world, consulting with appropriate state agencies, and proposing conceptual people mover designs that will address the growing need and become an icon for UD and the City of Newark.

Suggested coursework: Knowledge of engineering design, structures, transportation, public policy, and sustainability is helpful.

Overview: Daily operation of our society heavily relies on the effective functioning of the infrastructure system. However, disaster poses a severe threat to the coupled human-infrastructure system. And climate change can exacerbate the risk by amplifying both physical and societal disruptions and potentially introducing new failure modes. To prepare our society to quickly recover after a disaster, we need to first understand how the coupled human-infrastructure system responds to disruptions. This research aims to utilize mobility data to map the intricate interactions between human and infrastructure systems, developing models to characterize this interdependent system. This project employs data science techniques and a complex network modeling approach to elucidate the resilience of the coupled human-infrastructure system in facing disaster disruption.

 

Suggested coursework: Probability and Statistics for Engineers, Mathematical modeling and simulation, Strong programming skills in Python.

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.

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Suggested coursework: Organic Chemistry and/or Introduction to Polymers are helpful, but not required. 

Overview: Silicon anodes are a promising replacement for Lithium-Ion battery anodes displaying a capacity tenfold greater than current graphite anodes with superior manufacturing cost profile. However, current silicon anodes experience rapid failure due mechanical expansion and contraction of silicon during battery cycling and a reactive surface. The reactive surface in particular causes the evolution of gases in the battery assembly which may result in catastrophic rupture of the cell assembly and ancillary parasitic deposits on both the cathode and anode. This project will study the gas evolution profile of various sourced silicon anode materials using a differential electrochemical mass spectrometer and a custom-made electrochemical cell. A good candidate to perform this research is a mechanical of chemical engineering student with an inclination for both reactor system design and materials/battery chemistry investigation.

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Suggested coursework: Introductory electrochemistry, Mechanical design, or Reactor design.

Overview: Sea level rise has the potential to greatly increase the volume and rate of saltwater intrusion in natural and built systems.  One specific concern caused by this is saltwater intrusion in concrete infrastructure (e.g., bridges, culverts, storm water management systems, etc.), which can cause premature and / or unexpected corrosion and structural failures.  This is a particular concern in Delaware, which has the 4th highest coast-to-area ratio in the United States, but also affects the 40% of the US population that lives along a coastline.  The project will consider causes and / or effects of sea level rise and saltwater intrusion.  Possible avenues of research include quantification of the airborne and groundwater salinity in different locations, sampling of concrete near the coastline to assess the depth to which chlorides have been absorbed in concrete members, and investigation of concrete mix designs that are more resistant to chloride permeation.

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Suggested coursework: Civil engineering materials, chemistry

Overview: The surge in autonomous vehicle research has shown the importance of accurate localization systems. The critical component of these systems is the Simultaneous Localization and Mapping (SLAM) technology, which enables vehicles to map their environment and position themselves within it. However, the dynamic nature of urban environments, characterized by frequent changes such as construction, weather conditions, and varying traffic patterns, poses a significant challenge to the reliability of SLAM maps. The conventional approach to updating SLAM maps, primarily through data gathered by the vehicles themselves, is limited in scope and often lags real-time changes in the environment. This limitation not only affects the efficiency of autonomous vehicles but also raises safety concerns. This project proposes the use of drones as a novel solution to this problem. Drones can offer a broader and more flexible perspective, capturing real-time changes in the environment from an aerial viewpoint. By incorporating drone-assisted updates into the SLAM mapping process, this project aims to enhance the accuracy and reliability of the maps, thereby improving the overall performance of autonomous vehicles.

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Suggested coursework: N/A