Applications for SURE/SROP 2017 are now open and the deadline is January 15, 2017. Please review the criteria for SURE and SROP, and consider all of the projects in this list carefully before applying. You are welcome to contact faculty if you have additional, specific questions regarding these projects. If you have any SURE/SROP application questions, please contact, Angela Jeon (firstname.lastname@example.org).
2017 CEE Projects
CEE Project 1: Fire Forecasting
Faculty Advisor: Ann Jeffers (email@example.com)
This project explores the potential for applying forecasting techniques to the simulation of fires in order to predict how a fire might grow or spread within a building. An inverse model has already been created to determine heat release rates from measurements of fire signatures, such as the temperature and oxygen concentrations. Forecasting techniques will be applied to extrapolate the fire growth rate in order to generate a predictive model that can tell firefighters how a fire is evolving within a building. The model will be updated with new “measurements” of temperature and oxygen concentration taken from a simulated building fire. No prior experience in fire modeling is necessary.
CEE Project 2: Incorporating Non-Traditional Materials in Structures for Earthquake Response Reduction
Faculty Advisor: Jason McCormick (firstname.lastname@example.org)
Graduate Student Mentor: Malcolm Ammons (email@example.com)
Seismic activity each year leads to injury, loss of life, property damage and significant economic impacts to the affected areas. One solution is to improve the performance of buildings through passive control systems. The goal of this project is to address this problem through integration of non-traditional materials such as metal foams, polymer foams, and rubber into structural members to enhance their performance during a seismic event. These materials provide a unique means of adding energy dissipation capacity and inhibiting local buckling in steel members with minimal added weight. Specifically, this research will focus on the evaluation of the energy dissipation characteristics of these materials and their use in steel members. The student working on this project will determine the properties and energy dissipation capacity of these non-traditional materials through experimental tension, compression, and shear tests. Larger member tests of steel section incorporating these materials also will be conducted under cyclic and non-cyclic loadings. Experience will be gained in designing and running experimental tests, working with instrumentation to gather data, and analyzing the resulting data from experimental tests.
CEE Project 3: Nanoengineered Thin Films for Distributed Structural Sensing
Faculty Advisor: Jerome P. Lynch (firstname.lastname@example.org)
Graduate Student Mentor: Andrew Burton (email@example.com)
Nanotechnology has the potential to transform current approaches to structural sensing. Specifically, nano-engineered thin films can be created with both mechanical strength and electro-mechanical properties suitable for sensing. This project will explore carbon nanotube-polymeric thin films for distributed sensing using flexible substrates bonded to a structure. A lithographically-assisted patterning process will be developed to pattern thin films for sensing specific structural responses. The student selected will be required to perform bench-top fabrication of the thin films, model their electro-mechanical behavior using equivalent circuit analyses, and experimentally verify film performance in small- and large-scale structural tests. A detailed report at the end of the project will be required.
CEE Project 4: Rethinking Mainstream Domestic Wastewater Treatment: Novel Biological Processes for Nitrogen Removal from Wastewater
Faculty Advisor: Nancy Love (firstname.lastname@example.org)
Graduate Student Mentors: Zerihun Alemayehu (email@example.com), Brett Wagner (firstname.lastname@example.org) and Jeseth Delgado-Vela (email@example.com)
Prerequisite: Must be at least a junior with a focus in environmental engineering
Using anaerobic technologies to treat domestic wastewater can significantly decrease energy use and increase biogas production when compared to conventional treatment schemes. However, there has been little research on the treatment of nitrogen from anaerobic effluents, which have a notably different composition than effluents treated using conventional technologies. In addition, nitrogen can be removed from aerobic effluents using low-energy technologies. Through this research project, we are evaluating novel treatment approaches that remove nitrogen and greenhouse gases from wastewater. The technologies rely upon microorganisms that are grown in biofilms (both attached to surfaces and self-immobilized aerobic granules) to convert nitrogen and residual carbon into less harmful forms. Two laboratory-scale biofilm reactors are currently being operated to evaluate the novel treatment technologies. A range of standard and advanced chemical and biological methods, including DNA sequencing methods and mass spectrometry, are being used to evaluate the performance of the systems. The student will be expected to help operate the reactors, will become skilled in chemical methods to evaluate water and gas quality, and will learn selected microbial techniques.
CEE Project 5: Applying Physiological Sensors and Activity Trackers to Understand Workers’ Physical Status
Faculty Advisor: SangHyun Lee (firstname.lastname@example.org)
Recent advancement made in physiological sensors and activity trackers allow us to access unprecedented information about construction workers’ physical status (e.g., fatigue). Construction poses a great challenge to workers’ health. However, there has been no systemic and economic tool that can be used to monitor and analyze their physical activities. We aim to monitor workers’ physical status with light-weight, non-intrusive (i.e., non-intervening), and in-expensive sensors so that useful feedback to improve workers’ health can be given. Enthusiasm on construction safety and health is the only prerequisite.
CEE Project 6: Nutrient Recovery through Urine Separation
Faculty Advisors: Krista Wigginton (email@example.com) and Nancy Love (firstname.lastname@example.org)
Graduate Student Mentor: Heather Goetsch (email@example.com)
Prerequisites: Must be at least a junior with a focus in environmental engineering, environmental engineering, chemical engineering or microbiology.
Human urine contains the bulk of the nitrogen and phosphorus that passes through municipal wastewater treatment plants, while comprising only 1% of the total volume. Separating urine at the beginning of the waste stream and producing urine-derived fertilizer from that urine could help supplement fertilizer demands and simultaneously reduce excess nutrient release to water bodies. Environmental and human health implications of human urine used as fertilizer must first be assessed. Bacteria, viruses, antibiotic resistance genes, and nutrients will be characterized in collected urine, urine processed through pasteurization, struvite precipitation and other methods, lysimeter water and vegetables. Student will learn wet chemistry water quality analyses to characterize nutrients and biological methods to track bacteria, viruses, and antibiotic resistance genes. Depending on interest, the student may also learn analytical chemistry methods to measure trace organic chemicals in the above mentioned constituents.
CEE Project 7: Sustainably Unlocking Energy from Municipal Solid Waste Landfills
Faculty Advisor: Dimitrios Zekkos (firstname.lastname@example.org) and Jerome Lynch (email@example.com)
Graduate Student Mentor: Sampurna Datta (firstname.lastname@example.org)
Current municipal solid waste management practices are unsustainable. A coordinated plan that involves experimental testing in the laboratory, sensing and field measurements using a wireless sensors network and land-based as well as unmanned aerial vehicles at modern landfills and numerical modeling is undertaken with the intent to revolutionize the way we manage solid waste in landfills and lead to a new technology that will not be geared towards waste containments, but towards energy harvesting of MSW through the process of anaerobic biodegradation. This project involves monitoring of actively biodegrading municipal solid waste in the laboratory and the field. A more broad description of the project can be found here: http://www.nsf.gov/awardsearch/showAward?AWD_ID=1442773
CEE Project 8: Investigating the Use of Drones for Post-Disaster Reconnaissance
Faculty Advisors: Dimitrios Zekkos (email@example.com), Jerome Lynch (firstname.lastname@example.org) and Vineet Kamat (email@example.com)
Graduate Student Mentor: Will Greenwood (firstname.lastname@example.org)
Recent disastrous earthquakes are reminders that many lessons are yet to be learned to ensure we can engineer truly resilient communities. Post-earthquake reconnaissance missions are absolutely vital to the experience-based learning process required to advance our understanding of natural hazards and their impact on geotechnical systems. Unmanned Autonomous Aerial Vehicles (UAAVs), using the latest technological and computational tools available, will enable engineers to collect higher quality, more objective, and more extensive perishable datasets on the performance of geotechnical systems during reconnaissance missions. A transformative framework for post-event reconnaissance and decision making is planned based on the use of highly-mobile and sensor-rich UAAVs. Students engaged in this research will explore the abilities of drones to collect and analyze images as well as execute dynamic testing following natural disasters. A more broad description of the project can be found here: http://www.nsf.gov/awardsearch/showAward?AWD_ID=1362975
CEE Project 9: Experimental Assessment of the Seismic Properties of Non-Textbook Earth Materials
Faculty Advisors: Dimitrios Zekkos (email@example.com) and Athanasopoulos-Zekkos (firstname.lastname@example.org)
Recent disastrous earthquakes are reminders that many lessons are yet to be learned to ensure that we can engineer truly resilient communities. Characterization of the seismic properties of earth materials is key to assess the expected performance of infrastructure during an earthquake. A unique large-size device has been developed at the University of Michigan to test earth materials with large particles in simple shear. Tests will be conducted to evaluate the properties of more challenging, and less studied, materials such as gravelly soils and Municipal Solid Waste that can only be tested with a large experimental setup. The results of this study are expected to impact the engineering practice and affect assessment of critical infrastructure such as dams, levees, and landfills during earthquake loading.
CEE Project 10: Novel anaerobic membrane bioreactor configurations for domestic wastewater treatment at low temperatures
Faculty advisors: Steve Skerlos (email@example.com) and Lut Raskin (firstname.lastname@example.org)
Graduate Student Mentor: Caroline Van Steendam (email@example.com)
The objective of this project is to research Anaerobic Membrane Bioreactor (AnMBR) configurations that can treat domestic wastewater (DWW) at low cost while producing net energy and reducing greenhouse gas emissions. AnMBRs combine the benefits of anaerobic biological treatment (energy production) and membrane separation (excellent effluent quality). However, previous research has shown that changes to the design of AnMBR systems will be needed to achieve net energy recovery at DWW temperatures typically found in the Upper Midwest of the United States (yearly average of 15⁰C). This project's focus will be on enhancing the activity of biofilms within AnMBR systems to achieve excellent environmental and economic sustainability characteristics in the treatment of DWW. The student working on this project will gain experience with operating laboratory-scale AnMBRs and bioreactor monitoring methods. If interested, the student can also study the microbial community in the AnMBR using advanced molecular biology tools.
CEE Project 11: Design, manufacturing and evaluation of deployable arches
Faculty Advisor: Evgueni Filipov (firstname.lastname@example.org)
Deployable structures that use the principles of origami could lead to applications in multiple scales and disciplines from biomedicine to space exploration. In architecture and civil engineering reconfigurable facades could adapt to the environment, and rapidly deployable shelters and bridges could be used for disaster relief efforts. This project will first involve the use of analytical models to evaluate and design the geometry for a deployable arch structure. The main objective of the research will be aimed at exploring and developing new fabrication techniques for origami inspired systems. The student will use 3D printing, mechanical cutters, and integrated fabrication methods to create prototype deployable arches. The arches will be constructed to minimize the stowed volume, while allowing for a reliable deployment that requires minimum force input. Time permitting, the student will conduct experimental testing to quantify the stiffness of different deployable systems.
CEE Project 12: Evaluation of Permeability-Reducing Admixtures for Improving Concrete Durability
Faculty Advisor: Will Hansen (email@example.com)
The purpose of this study is to provide an initial performance evaluation of selected samples of permeability-reducing admixtures (PRAs) and to establish a protocol for evaluating other PRAs for their suitability in highway concrete applications. The approach will be to evaluate mortar and concrete mixtures using a combination of physical tests coupled with a detailed material characterization.
CEE Project 13: Fermentation of solid organic waste streams within a novel anaerobic bioreactor with dynamic membrane
Faculty advisors: Lut Raskin (firstname.lastname@example.org)
Post-Doc Mentor: Xavier Fonoll Almansa (email@example.com)
Anaerobic digestion (AD) fits well in the framework of sustainability since it treats organic waste while generating energy in the form of methane and producing a solid digestate with fertilizing properties. Nevertheless, hydrolysis is usually slow due to the presence of lignocellulosic materials in solid wastes. In previous work, the use of rumen content, which contains microbes able to efficiently digest plant material, led to an improvement in the hydrolysis rate and a high production of volatile fatty acids (VFA), which can be used later for the generation of methane, hydrogen or platform chemicals. The objective of this project is to enhance the rate of hydrolysis and the fermentation yield when solid organic wastes like sewage sludge, food waste or agricultural wastes are used in an anaerobic system. To accomplish this, a novel anaerobic dynamic membrane bioreactor has been designed based on the rumen as a model. The student working on this project will gain experience with operating laboratory-scale anaerobic digesters and bioreactor monitoring methods. If interested, the student can also study the microbial community in the reactor using advanced molecular biology tools.
CEE Project 14: Inactivation of Airborne Pathogens by Non-thermal Plasma Exposure
Faculty mentor: Herek L. Clack (firstname.lastname@example.org)
Graduate Student Mentor: Tian Xia
Environmental engineering addresses the control of contaminants in soil, water and air. Small inert particles suspended in air, aerosols, can be a challenge to remove from air streams; bioaerosols include airborne pathogens such as viruses and bacteria that can transmit disease (e.g., influenza) or stimulate allergic responses (e.g., pollen) in humans and animals. This project focuses on an advanced method of both removing such infectious aerosols and rendering them inactive through their precise exposure a non-thermal plasma. A student is sought who is both interested in and capable of making contributions to this project in any capacity, including design and construction of electronic controls; supporting cultivation of the (harmless) viruses to be aerosolized; or developing numerical simulations and/or optimization algorithms.
CEE Project 15: Leveraging Connected Vehicle Data to Devise Individualized Driver Alert Systems
Faculty Advisor: Neda Masoud (email@example.com)
With rapid advancements of automobile manufacturers toward building Autonomous Vehicles (AVs), it is no stretch to imagine the future of surface transportation with cars that are fully or partially autonomous. One of the appealing features of AVs is the promise of a safer road network by eliminating the cause of over 90% of motor vehicle crashes: human error. Although there may be individuals who will appreciate the enhanced driver assistance levels introduced by AVs, the sub-population of drivers who enjoy the driving task and the excitement of engaging in thrill-seeking behaviors might not look forward to having the control of their vehicles taken away from them at the slightest deviation from the deemed-safe behavior. Such concerns are not limited to extreme drivers, as individuals who have had the chance to ride autonomous cars typically describe their experience as “boring”, “mundane”, and “unexciting”, rendering the initial excitement over the concept of an autonomous car insufficient to create demand. This research aims to address these issues of diversity in the driving population by proposing a general framework to appeal to all drivers, regardless of their propensity for thrill-seeking behavior, by devising individualized driver alert systems for them through using connected vehicle data collected during the Safety Pilot Model Deployment at U-M and machine learning techniques.
CEE Project 16: Optimization of Multi-Modal Transportation Systems
Faculty Advisor: Neda Masoud (firstname.lastname@example.org) & Pascal Van Hentenryck (email@example.com)
Note: Joint project with IOE
Congestion is one of the main current issues faced by major cities in the US. In addition to increasing travel time and negatively affecting travel time reliability, congestion leads to higher levels of emissions which has negative health and the environmental implications. Single-occupancy vehicles are one of the major contributors to congestion. In order to encourage individuals to leave their vehicles behind, on-demand, flexible, and affordable transport options should be introduced.
The two major modes of transport available today, namely private vehicles and transit systems, are at the opposite ends of the spectrum in terms of flexibility and cost: private vehicle ownership increases one’s flexibility, but at the higher cost to the owner, the transportation system, and the environment. Transit systems, on the other hand, are inexpensive and could be environmentally friendly, but lack flexibility and often reliability. Between these two extreme ends, however, there exist an entire range of transportation options that have not been used, or even investigated. This research aims at tapping into this unused potential by introducing multi-modal on-demand transportation options. In a multi-modal system, riders make their trips by combining multiple modes of transportation, including walking, biking, private vehicles, transit, ridesharing, carsharing, bikesharing, etc. The research question is how to route riders in such a complex multi-modal network, and how to redistribute the supply (e.g., cars and bikes) in the system to guarantee fast, easy and seamless trips for individuals.
CEE Project 17: Mode Choice Analysis for Benton Harbor, MI
Faculty Advisor: Tierra Bills
Mode choice models are used to analyze the travel choices of individuals, as a function of their individual characteristics and the attributes of the alternatives they are choosing from. There are a number of data types necessary for mode choice estimation, including travel survey data, individual and household demographics, transportation network data, and land-use related data. Reliable samples of these data can be difficult to collect and compile, especially for small cities, making mobility improvements particularly challenging. This project aims to develop a reliable mode choice model for the City of Benton Harbor, Michigan. The student will need to compile existing data and collect new data samples, necessary for model estimation. This will also involve developing and implementing a survey instrument for collecting travel survey data.
CEE Project 18: Sensors in a Shoebox: Ubiquitous Citizen-based Wireless Sensing in Smart Cities
Faculty Advisor: Jerome P. Lynch (firstname.lastname@example.org)
Graduate Student Mentor: Katherine Flanigan (email@example.com)
In recent years, smart cities have emerged based on exciting new sensing technologies including connected vehicles, wireless sensor networks, and citizen’s cell phones. However, cities adopting such technologies continue to struggle with how best to utilize them. However, one place where there is an immediate need to to provide city residents with means to sense their own cities to acquire data they can use to inform them. Our project, Sensors in a Shoebox, aims to empower citizens to collect and analyze their own smart city data (as opposed to city governments and/or city businesses). Students selected for this project will work on the design and deployment of wireless sensor arrays with various collaborative partners throughout Detroit and Benton Harbor, MI.