Research > New Grants
RACER Trust; PI-Terese M. Olson
The Revitalization Auto Communities Environmental Response (RACER) Trust seeks to address perfluoroalkyl substance (PFAS) contamination that was recently discovered in groundwater at the former General Motors Corporation Willow Run site in Ypsilanti, Michigan. RACER seeks a cost effective, reliable, and sustainable solution to the problem. Previous bench scale studies conducted by RACER have involved treatment by granular activated carbon, ion exchange resins, UV and ozone based advanced oxidation, and plasma-based destruction. None of these options, however, yielded a cost effective, sustainable solution. Reviews of these technologies to mitigate PFAS in the literature reaffirm the stiff challenges experienced by RACER (1-3 ).
Many of the challenges associated with PFAS arise due to their exceptional persistence, the large number of different PFAS that exist, and the low regulatory health advisory levels that have been adopted for human health protection. Adsorption technologies have been effective in removing PFAS from water, but they produce residuals that must be disposed of as a hazardous waste or further treated. Destruction technologies for aqueous wastes such as advanced oxidation or reduction, electrochemical methods, and plasma-based treatment have shown promise for PFAS, but these processes are difficult to scale up for dilute, large volume waste streams. As a result, destruction processes are unlikely to be cost effective by themselves for many applications.
Plasma-based treatment relies on the production of reactive radicals, UV light, electrons, ions and excited species which form when a gas breaks down. Breakdown typically occurs through the application of a sufficiently high voltage such that the sparking potential is reached, thereby facilitating the formation of an ionization wave. The ionization wave produces the plasma activated gas which chemically reacts with its surroundings. In contact with water, the plasma activated gas drives both advanced oxidation through the introduction of reactive species such as the hydroxyl radical and reduction through the introduction of solvated electrons and negative ions into solution.
Nuveen; PI-Peter Adriaens
Nuveen is the third largest municipal fund manager with a long and rich experience in the social and environmental investment space, aiming to establish ESG as a pillar of mainstream investing. Due to client demand for ESG muni customization, Nuveen has developed an in-house capability to rate muni issuers, aligned with the UN Sustainable Development Goals. The rating is based on an evaluation at the issuer (state, county, city) level, and leverages unconventional public datasets along multiple thematic areas. The long-term goal of the ratings strategy is to develop multiple use cases including integration of ESG factors in its muni-investment process and product innovation such as ESG muni indexing.
The UM Finance Center seeks to work with Nuveen to help facilitate this strategy by advising on its methodology, addressing coverage gaps in existing models using data science tools, and expanding ESG scoring factors for its scoring models, including for additional sectors (e.g. transportation, other).
Department of Defense; PI-Jerome Lynch
This project advances a unifying cyber-physical system (CPS) architecture that integrate the sensing of warfighter operational environments and data streams from wearable biometric sensors worn by warfighters. The CPS architecture provides a comprehensive approach to assessing the performance and health of warfighters in relevant Navy and Marine Corp operational applications. A key element of the proposed CPS is the integration of computer vision and deep learning methods that can track warfighters in their environments using cameras. Automated detection and classification of warfighter performance based on convolutional neural networks processing images will provide a means of spatiotemporal tracking of warfighters performance. Discrete sensor measurements from sensors embedded in the environment and biometric wearable sensors will augment the CPS architecture offering a complete view of how the operational environment influences the warfighter. Combinations of warfighter location, behavior and biometric data with environmental data will offer unprecedented insights leading to better understanding of warfighter health when operating in complex and harsh environments. The project will validate the proposed framework using lab-based experimental testing and will seek collaborations with military laboratories (USARIEM, NHRC, CCD) as additional validation partners.
Great Lakes Water Authority (GLWA); PI- Branko Kerkez
This proposed effort builds upon our prior success — this time with a particular focus on a vision for long term adoption and scale. We intend to scale up our modeling analyses to include the broader GLWA system. The full-scale modeling component, developed using historical flow and rain event data, is necessary in order to determine a benchmark for assessing control system alternatives. We will assist GLWA with a variety of tasks associated with the implementation of its LTCP with a goal of realizing a smart and dynamically controlled system.
Outcomes and benefits to GLWA: Application of our real-time control approach offers the potential to significantly improve the existing GLWA wastewater and CSO management system by reducing both the occurrence of CSOs and peak flows going to the treatment facility. These benefits can be achieved without new construction, rather by relying entirely on existing infrastructure, which promises to free up significant capital savings for future investments. The potential results include significantly more benefit achieved using existing infrastructure, along with significant capital savings for future infrastructure additions.
State of Michigan; PI- Krista Wigginton
We will measure SARS-CoV-2 RNA concentrations in wastewater influent and primary settled solids from multiple wastewater treatment plants (WWTPs) in the Ann Arbor vicinity. Viral RNA will be measured using analytical methods our team has developed and rigorously tested. We will also compare the SARS-CoV-2 RNA concentrations in solids relative to liquid influent in Ann Arbor wastewater; this is important to determine the preferred approach for measuring SARS-CoV-2 to get the more sensitive and representative data. Our team will collect high-resolution samples as our early work in COVID highlighted the necessity of high-resolution measurements to convey COVID-19 dynamics in communities.
Samples will be collected from the WWTPs by our team on a regular basis. We have been collecting samples from the Ann Arbor WWTP since early September and we will begin sampling at two additional plants immediately. At Ann Arbor, the samples are currently collected by WWTP staff according to our instructions in falcon tubes provided by Krista Wigginton and Kevin Bakker. Kevin Bakker is currently responsible for retrieving these samples from the WWTP and transporting them to the lab; however he will be replaced by a technician once they are hired and trained. We will start sampling at Ypsilanti and a third plant (possibly Flint) as soon as the project is initiated. The analysis will be split between the Environmental Engineering labs on UMich’s North Campus and the School of Public Health. Preanalytical methods will be performed by current graduate student Kaitlyn Chin and a TBD technician funded by this grant. These steps will take place in Prof. Wigginton’s lab in the EWRE building. The ddPCR analyses will take place in the SPH building in Kevin Bakker’s lab. The ddPCR analysis will be performed by Kevin Baker and the a TBD lab technician hired through this grant. Data analysis will be carried out by Kevin Bakker and the TBD Epidemiology technician. Raw and interpreted results will be submitted to EGLE and local health departments if they are interested in these data. The collection of WWTP and environmental data will be collected by Kevin and Krista Wigginton.
National Science Foundation; PI-Carol Menassa
The construction industry is ill-famed for its stagnant productivity, use of antiquated work processes, adversarial relationships among stakeholders, and safety and health issues among construction workers. Over time, this has led to a chronic shortage of skilled workers, largely due to an aging and retiring workforce and the reluctance of younger generations or people of different abilities to pursue such careers. More recently, the outbreak of COVID-19 has caused serious economic impact and schedule delays on construction projects, since it is hard to maintain social-distancing between workers on construction sites. This emphasizes the need for construction techniques that can allow workers to perform tasks remotely, allowing for reduction in the number of on-site workers in close proximity to ensure worker health and safety. This FW-HTF planning grant will investigate whether intelligent human-robot teams have the potential to transform future construction work and the profile of future construction workers resulting in new career opportunities and significant benefits to the industry. In these teams, we envision that human workers will use technology to teach co-robots to perform construction work tasks remotely resulting in symbiotic human-robot teams that can be widely deployed in the construction industry. This envisioned approach parallels the classical MasterApprentice vocational model prevalent in today’s construction industry.
The overarching goal of this research planning grant is to explore the feasibility and potential of the outlined vision through engagement with a wide range of stakeholders. The proposed activities for this planning project include: 1) Fact-finding surveys distributed to representatives of construction firms, current construction workers and potential future construction workers (high school students); 2) Technology pilot presentation and feedback from representatives of construction firms and workers; and 3) A comprehensive research program development workshop with expert stakeholder participants from academia and industry. These activities will allow the research team to set the foundation for developing a convergent research agenda that reshapes the future of construction work into a human-robot partnership that supports a self-sustaining cycle of lifelong learning, knowledge-transfer, and effective teamwork. Ultimately, the results of this project will inform the opportunities and challenges of incorporating co-robots on construction sites without replacing the current workforce or adversely impacting the construction work process.
National Science Foundation; PI- Krista Wigginton
Viruses are difficult to remove from water with physical purification processes due to their small size and surface charge. As a result, waterborne virus removal relies heavily on disinfection processes. The number and diversity of human viruses with published, high-quality disinfection kinetics is extremely limited due to the fact that most are non-culturable or difficult to culture. Surrogate viruses are commonly used to shed light on the fate of human viruses in the environment and through water treatment; however, we lack a consistent framework for selecting effective surrogates. Meanwhile, the environmental virology field has gained an increasing understanding of the mechanisms that drive virus inactivation through disinfection processes. We propose to harness the collective understanding of virus structure, biology, and disinfection mechanisms to develop predictive frameworks that accurately estimate the inactivation kinetics of nonculturable and difficult-to-culture viruses with UV254, free chlorine, and chlorine dioxide disinfectants. To achieve this vision, we will apply concepts from environmental engineering, chemistry, virology, and data science to undertake three major research objectives, namely 1) expand the virus disinfection kinetics dataset in the literature to capture a broader and systematic range of virus physico-chemical and biological characteristics and thus better represent the diversity of human viruses in the environment; 2) develop computational models that predict virus inactivation kinetics based on virus particle chemistry, structure, and biology, and 3) use the vastly broadened disinfection kinetics dataset and predictive models obtained with Objectives 1 and 2 to design more effective bacteriophage process surrogates for the water quality engineering industry.
Department of Environment, Great Lakes, and Energy (State of Michigan); PI- Branko Kerkez
Our goal is to enable adaptive environmental management and highly target restoration initiatives in the Clinton River Basin. To that end, our interdisciplinary team of researchers and scientists will build a first-of-its-kind water information system, which will process massive quantities of streaming sensor data to inform a new generation of water models and scenario planning tools. This proposal presents the second phase of a project, which began through the support of the Office of the Great Lakes in 2018.
The specific objectives of this proposal will be:
The expansion and maintenance of an existing 50-node wireless sensor network for measuring hydrology and water quality. A major contribution will be the development of a real-time decision support dashboard, which will be used by community members to control lake levels and flows in channels and streams.
The development and calibration of a regional, watershed-scale hydrologic model, which will use data collected by sensors to drive realistic-scenario planning for the region.
Providing supportive capacity and skills to assure project integration among investigators, and knowledge translation to end-users.
National Science Foundation; PI- Yafeng Yin
The deployment of automated vehicles (AVs) is rapidly approaching with a push from governments who are relaxing laws to allow AVs to operate on highways, and industry, both manufacturers and mobility service providers, who are heavily investing in the development of the technology and its applications. AVs are expected to tremendously enhance the efficiency, safety and convenience of existing transportation systems. However, all these benefits hinge on the level of market penetration of AVs being sufficiently high. At low market shares, AVs exert little impact on enhancing transportation system efficiency. Worse yet, early deployment of AVs may even compromise the efficiency. The transition period is expected to be lengthy. If we can shorten it, the tremendous benefits promised by AVs can be realized sooner. This grant thus sets out to investigate incentivizing policies and innovative traffic management strategies to promote the development and deployment of AVs to maximize the social benefit over the entire duration of the AV deployment. Specifically, incentivizing policies will nurture the AV market and accelerate their adoption while innovative traffic management schemes aim to better utilize AVs in the traffic stream and promote high-occupancy mobility services to maximize the benefits of AVs at a given market share. The synergies between incentivizing policies and traffic management schemes may create an upward spiral for the AV deployment and particularly reduce the duration of initial deployment where AVs exert little or even negative impact on enhancing efficiency. This grant will provide timely support for government agencies to better understand the impacts and implications of AVs and provides guidance on their development and deployment.
Sloan, Alfred P., Foundation; PI- Brian R. Ellis
The University of Michigan and partners at North Carolina State University and Ohio State University propose the research project “CO2 Utilization for Geothermal Energy Production and Renewable Energy Storage” to address the need to develop and deploy carbon negative energy technologies. The research team led by Brian Ellis (PI) includes Co-PIs Jeffrey Bielicki (Ohio State University) and Jeremiah Johnson (North Carolina State University), and industrial collaborator, TerraCOH. The PIs will combine their complementary expertise in the geochemistry of geologic carbon dioxide (CO2) storage (GCS), geothermal reservoir engineering, systems-scale techno-economic modeling and optimization, and power systems modeling to provide technical advancements that will enable the deployment of novel CO2-based geo-energy systems.
Saudi Aramco Technologies Company dba AramcoTech; PI- Victor Li
The objectives of this research is to establish (1) ECC technology for applications in the Saudi Arabia and surrounding regions, using as much as possible local materials especially dune sand; (2) the durability of ECC and R/ECC structures in the Saudi Arabia environment; and (3) the range of polymer materials suitable for use in or with ECC as a material in the large volume construction industry, with respect to potential extension of Aramco businesses in the future. The potential of deploying KSA localized ECC in civil infrastructure, blast resistant structures, and in pipelines will also be identified. It is recognized that at the present, less than seven percent of the materials used in the construction industry belongs to polymer. ECC has the potential to greatly expand this percentage by using polymers as essential ingredients of localized ECC.
National Science Foundation; PI-Brian R. Ellis
The proposed CAREER research program seeks to transform our understanding of and ability to control feedbacks between mineral reactivity and fluid flow in geologic reservoirs. The two primary research objectives of this project are to (1) enhance predictive capability for estimating permeability evolution in reservoirs used for CO2-based energy storage or production based on measures of core-scale heterogeneity and (2) evaluate permeability reduction strategies designed to control subsurface fluid migration. The principal application to benefit from this research is the utilization of CO2 for production of geothermal energy and grid energy storage from intermittent renewable power generation. Examining CO2-water-rock interactions within the context of these emerging energy technologies presents an opportunity to advance our fundamental scientific understanding of the role that mineral heterogeneity plays in determining reservoir permeability evolution during flow of reactive fluids. Simultaneously, it supports broader deployment of energy technologies that are potentially carbon negative by improving our confidence in modeling the fate of injected CO2 in heterogeneous geologic reservoirs.
This research program will be integrated with the educational mission of raising student literacy of subsurface processes related to energy production, carbon mitigation, and sustainable groundwater management. The educational program will build upon the PI’s experience interfacing with middle school students on the topic of the energy-water nexus and leverage the UM Wolverine Pathways program to develop a series of educational modules for students in the greater metro-Detroit area. The Wolverine Pathways program follows a cohort of students from 7th through 12th grade, allowing the PI to develop and refine the teaching modules through rigorous evaluation of student learning objectives over the span of the five-year project period. Once fully developed, these modules will be made freely available to educators through an online resource catalog coupled with companion video teaching tutorials.
National Science Foundation; PI-Evgueni Fillipov
The overarching goal for my career is to introduce large-scale adaptable structures that are cost-efficient, safe and functional for everyday use. Such systems would be transformative by allowing fully reconfigurable structural components, and infrastructure that can be deployed, repackaged, and reused. Because large structures are difficult to actuate, the research objective of this proposal is to establish and formalize a new genre of low to zero stiffness origami that can move and reconfigure effortlessly, but can also gain stiffness and rigidity as needed for functional use. First, the fundamental mechanics of pre-stress and counter-balancing (zero-stiffness) will be explored in systems made of thin folded sheets (origami). These principles will be built into new computational tools that can discover origami surfaces, which are capable of switching between multiple stable states with the least amount of applied force. Additionally, these surfaces will be optimized to deploy into dome-like shapes, in which their non-zero Gaussian curvature will give structural stiffness for externally applied loads. The new origami structures will be prototyped, instrumented, and experimentally tested to examine their motions, stability, and performance under different loading scenarios. Through close interactions with a collaborator in practice this project will use the new innovations in geometric mechanics to conceive and devise large-scale systems that are adaptable, functional, and structurally sound.
The educational objective is to improve learning outcomes and promote scientific curiosity through the use of Hands-On, and Do-It-Yourself modules. The vision for these active learning efforts will be directly integrated with the research on low/zero stiffness origami, and will be implemented in several settings to engage learners with different levels of academic training. First, students in a low-income Detroit high-school, and a group of middle-school girls will learn geometry and basic engineering by making a deployable tent, a lamp-shade, and other devices they can take home. Second, students in a first-year graduate course on Deployable Structures, and several undergraduate researchers, will learn kinematics, structural analysis, and experimental testing by exploring new origami geometries. Third, the public, as well as the broad community of structural engineers will be engaged through different online modules tailored to teach about the benefits and application of deployable and adaptable structures. All learning modules will be tested, critiqued, evaluated, and continuously improved over the course of the project.
National Science Foundation; PI-Krista Wigginton
A novel coronavirus (2019-nCoV) recently emerged from Wuhan China and its spread is causing international concern. Although peer-reviewed reports are only beginning to be published, early reports suggest it is closely related to SARS and transfer from human to human can take place before symptoms are observed. This outbreak follows two other coronavirus outbreaks in recent years, namely SARS and MERS. In 2003, the initial cases of the SARS coronavirus outbreak spread via aerosolized fecal particles through the air ducts of the apartment complex. Highly unusual for enveloped human respiratory viruses, infective SARS particles were excreted at high concentrations in feces. Early reports of 2019-nCoV suggest it too is excreted in feces.
Despite these outbreaks of enveloped viruses that can be transmitted through the environment (e.g., SARS, MERS, 2019-nCoV), we still lack an understanding of how these particles are transferred between hands and surfaces, how they are inactivated with solar and UVC radiation, and whether wastewater monitoring can relay outbreak dynamics within a community. This information is critical to control transmission by surfaces, to predict persistence in water treatment and the natural environment, and to catch virus circulation early in community outbreaks. We will address these remaining knowledge gaps by characterizing how enveloped viruses are transferred from surfaces to skin, how coronaviruses are inactivated by solar and UV radiation, and by monitoring coronavirus dynamics in wastewater treatment plants in the Bay Area. The project team is uniquely prepared to address these questions. Building on past research by Co-I Boehm on non-enveloped virus transfer from skin to surfaces and their photoinactivation, and by Co-I Wigginton on coronavirus detection methods and environmental persistence, we can
immediately begin probing how infective coronavirus particles are transferred to and from skin and how they are inactivated by UV and solar radiation. With Co-I Criddle’s current effort to monitor bacterial and viral pathogen dynamics in untreated wastewater at the Codiga Resource Recovery Center on Stanford’s campus, we are posed to immediately begin monitoring coronaviruses in wastewater. We note that Santa Clara County has two of the initial 2019-nCoV cases in the country. This research captures the spirit of the NSF RAPID funding mechanism because of the need to contain the rapidly expanding 2019-nCoV outbreak and to be prepared for its spread in the United States.
The Water Research Foundation; PI-Krista Wigginton
DPR-3 Feasibility of Collecting Pathogens in Wastewater During Outbreaks is focused on determining the feasibility of measuring pathogen concentrations in CA wastewater during a community outbreak event. Further investigation of this question may be critical to characterizing the highest levels of pathogens expected in untreated wastewater in CA. The effort will involve both an in-depth literature review of sewage monitoring studies and of the seasonal and spatial trends of enteric pathogen outbreaks in CA. It is expected that the sampling location, sampling technique, time of year, and specific pathogen are critical aspects to consider when assessing the feasibility of a sewer monitoring campaign in CA that detects outbreak levels in untreated wastewater. As this project is closely related to DPR-2: Measure of Pathogens in Wastewater, DPR-3 team members will regularly consult with DPR-2 team members. Results from DPR-2 will be incorporated in DPR-3 as they become available.
Magnusson Klemencic Associates Foundation; PI-Seymour Spence
This research project will focus on the advancement of the strain-based dynamic shakedown framework recently developed during the MKA Foundation sponsored project “Methods for the efficient estimation of the reliability of post-elastic high-rise wind-excited structures within a performance-based design setting”, denominated “Shakedown 1” in the following, for the rapid system-level inelastic performance assessment of wind-excited high-rise structures. To this end, specific goals will be to: 1) Include P-Delta
effects in the shakedown approach; 2) Continue the development of the path-following algorithms for estimation of the strains and deformations not only at shakedown but also post-shakedown; 3) House the approach in a smart stochastic simulation framework that will allow small failure probabilities (e.g. 10-6 ) to be estimated with confidence without having to consider huge sample sets; 4) Apply and validate the new models on a set of 3D architype buildings. The models developed in this study will be directly related to the evaluation of reliability necessary for following Path Three of the recently published ASCE PreStandard for Performance-Based Wind Design (PBWD).
Department of Energy; PI-Victor Li
Significant degradation of our physical infrastructure has important implications on economic and energy security of the United States. An extremely durable concrete (EDC), say with at least five times the service life of current concrete materials, is urgently needed for civil and energy infrastructure. This research project aims at developing a novel ductile EDC that is resistant to chemical attacks and possesses built-in crack width control not feasible with current concrete. When EDC is overloaded, the tighter than hairline crack width will stop penetration of aggressive agents into the structure and it will automatically heal under rain and sunshine. An integrated micromechanical, nano-micro analytic, chemical, computational material science, and life-cycle analysis approach will be deployed for the design of this material. The objective of this research is to drive down lifecycle cost of infrastructure by minimizing O&M expenses, while at the same time reduce energy and emissions, particularly in the cost of reconstruction and repair. This new concrete is targeted at meeting everyday construction requirements and will have tensile resistance that dramatically enables efficient additive manufacturing and the construction of resilient energy facilities. The ingredients of the EDC will be deliberately selected to ensure broad geographic availability within the US and worldwide.
Department of Energy; PI-Jeremy Semrau
It has been previously shown that some methanotrophs (methane-oxidizing bacteria) produce a copper chelator termed methanobactin (MB) that binds copper with extremely high affinity. As a result, MB provides these methanotrophs a “copper monopoly” where other microbes can no longer collect copper. Specifically, in defined laboratory systems, we have found that MB prevents many denitrifiers from completely converting NO3- to N2. Rather N2O is the terminal product as the nitrous oxide reductase (NosZ) is also copper-dependent and the ability of denitrifiers to collect copper substantially decreases in the presence of either MB or MB-producing methanotrophs. Given that methanotrophs constitute a substantial portion of the active microbial community in soils and MB is highly expressed, it is quite possible that methanotrophs inhibit denitrifier activity in situ by exerting a “copper monopoly”. Not all methanotrophs, however, produce MB. Rather, other methanotrophs produce an alternative copper uptake system called MopE/MopE*, and the ability of MB to “steal” copper from MopE/MopE-producing methanotrophs is unknown, i.e., copper competition may not only exist between methanotrophs and denitrifying bacteria, but also between different methanotrophs, affecting overall methanotrophic community activity. Hence, it is the goal of this proposal to extend the initial work to determine how significant microbial competition for copper is, particularly how such competition affects net greenhouse gas emissions in different environments.
The proposed research will have three general phases. First, Semrau will examine copper competition between methanotrophs that synthesize either MB or MopE/MopE*. At this time, it is unknown if methanotrophs that express MB have a competitive advantage over those that express MopE/MopE* for copper sequestration or vice-versa. To resolve this uncertainty, his team will initially perform simple two component experiments to characterize the impact of MopE/MopE* on copper uptake and activity of MB-producing methanotrophs, as well as the impact of MB on copper uptake and activity of MopE/MopE*-producing methanotrophs. Second, Semrau will characterize copper uptake and activity of denitrifiers in the presence of MopE/MopE*-producing methanotrophs. Third, the team will quantify copper competition in soil microcosms and examine its impact on greenhouse gas emissions. In this phase, they will use a tiered approach to characterize the microbial community and activity via metagenomics and metatranscriptomics.
National Science Foundation/Georgia Institute of Technology; PI-Yafeng Yin
The goal of this proposal is to develop the data and decision science to engineer ODMTS for large, congested cities. This requires a step change in ability to plan, operate, and optimize ODMTS, which are complex socio-technical systems deployed over a sophisticated infrastructure. To achieve this objective, the proposal explores five research threads that address the following high-level questions:
1. How to design scalable optimization and machine learning algorithms for designing the multimodal networks at the core of ODMTS?
2. How to forecast the ridership demand in ODMTS and how to integrate the resulting forecasting models into optimization model for network design?
3. How to generalize the network design optimization to take into account and mitigate congestion?
4. How to co-design ODMTS and infrastructure improvements to maximize the performance of transit system, using concepts such as complete streets and context-sensitive solutions?
5. How to incrementally integrate autonomous vehicles in ODMTS as they become available and their capabilities improve?
Each of these threads addresses a fundamental challenge in realizing the promise of ODMTS for large cities. Thread 1 tackles the computational challenges of planning and optimizing ODMTS for cities with millions of inhabitants. Thread 2 recognizes the need for predicting ridership accurately to design and size ODMTS appropriately. Thread 3 acknowledges that, in large cities, the design of ODMTS must model network capacity and congestion with high fidelity. Thread 4 recognizes the potential synergies between transit systems and the transportation infrastructure and envisions infrastructure improvements that support the operations of ODMTS. Thread 5 acknowledges that autonomous vehicles may fundamentally impact the design of ODMTs and studies how autonomous vehicles can be incrementally integrated in the design and operations of ODMTS and the consequences and benefits of their integration.
University of Michigan will participate in Threads 2, 3 and 5. Specifically, the team of University of Michigan will develop network design model that encapsulate travelers’ response to the design (Thread 2); investigate ways to consider congestion in the network design (Thread 3), and integrate autonomous vehicles in the design and operations of ODMTS (Thread 4).
Hampton Roads Sanitation District; PI-Nancy Love
The objective of this work is to add to HRSD’s water quality assessment protocols to assess the quality of the water produced by the carbon-based demonstration plant system as it pertains to biotoxicity. In the first year of this grant, Love worked with HRSD to identify appropriate toxicity bioassays to use, and to resolve protocols for both sample preparation, processing and bioassay implementation. Love and her team are tasked with evaluating biotoxicity levels across 9 points of the treatment process, in the effluent stream, and in the groundwater flow from the discharge point. These toxicity measures provide information that can be fed into an effect-directed analysis to assess overall toxicity risk.
National Science Foundation; PI-Shawn McElmurry, Co-PIs–Matthew Seeger, Nancy Love, Branko Kerkez, Jacqueline MacDonald Gibson
The long term objective of this study is to replace theoretical frameworks for how water and health systems adapt to risk associated with, and learn from, water system-based disruptions to enhance resiliency. The first aim in support of this long term objective is to identify the range of risks and disruptions in water and public health systems in urban areas and assess the extent to which the systems possess characteristics of resilience. The second aim is to evaluate how the public engages with drinking water and public health systems. The third aim is to model how water and public health systems respond to water based disruptions. To achieve these aims, we first will conduct case studies of a range of recent disruptions (e.g., routine water main breaks, large-scale disasters) in cities (Detroit, Flint, Benton Harbor, MI; Toledo, OH; Raleigh, NC) and tribal communities (Robeson County, NC). Results from these cases will be used to replace existing resilience frameworks with a coupled model of these two interdependent systems of how these systems jointly function and adapt to risks and hazards. Bayesian network modeling and machine-learning approaches will be used to predict system characteristics associated with disruptions and the interdependent system responses. Next, the case study results will inform a national survey of drinking water and public health systems to both test and refine the coupled model to support each aim including the long-term objective.
NASA; PI-Dalia Kirshbaum, Co-PIs–Marin Clark and Dimitrios Zekkos
Landslides are a global hazard that causes loss of life and lasting damage to critical infrastructure. A major rainfall or earthquake can cause tens of thousands of landslides, compounding losses from damage to transportation networks that inhibits disaster response and resulting in cascading effects such as flooding and debris hazards. Despite the ubiquitous nature of landslides, there is little integration of the pervasive impacts of landslides throughout the complete landslide disaster life cycle, including preparation, recovery and mitigation.
Zekkos, Kirshbaum, and Clark propose to advance landslide forecasting using predictive models, satellite data and ground observation, including evaluation of landslide risk based on the hazard model outputs combined with exposure and vulnerability data. They will address the impact of widespread landsliding triggered by disaster events, including tropical cyclones and earthquakes, where landslides are a significant secondary hazard interrelated with the effects of strong ground shaking and flooding. Given the dynamic nature of the proposed suite of tools, Zekkos, Kirshbaum and Clark anticipate that engagement in Disaster Project teams will provide new opportunities to integrate their efforts with other teams during natural disaster events that include multiple types of hazards, of which landslide play a pivotal role.
Zekkos, Kirshbaum and Clark rely significantly on NASA data and directly incorporate multiple sensor types, platforms and spatiotemporal scales to model susceptibility, hazard and risk, and also incorporate cascading effects of landslides on other disaster phenomenon. Currently, the Landslide Hazard Assessment for Situational Awareness (LHASA) model represents the only known global dynamic landslide model running routinely and accessible to the public. The proposed work seeks to advance the current system to include dynamic triggering variables, including forest fires, snowfall and seismicity. Advancement of geomechanical regional models applicable at smaller scales of 10s-100s of km provide a critical link between ground observations and remote sensing data with satellite-based methods and will be benchmarked using data from several recent past events.
Over the duration of this $695,103 award, Zekkos, Kirshbaum and Clark will contribute forecasts, real-time updates on evolving hazards, and post-event data collection in support of rescue and recovery efforts and longer-term model improvement/validation. The stakeholder partners participating in this effort will directly contribute and co-develop these models, products and tools to ensure seamless transferability and uptake within their decision making systems. These efforts will provide improved situational awareness, disaster risk reduction, response and resilience of landslide hazards relevant to both scientific and stakeholder communities.
National Science Foundation; PI-SangHyun Lee
Labor intensive construction accounts for a significant portion of the U.S. economy. However, construction suffers from significant occupational injuries/deaths, stagnant productivity, lack of skilled labors, and aging workforces. To address these issues, the construction industry is gradually gearing up for robotic automation, particularly for human robot collaboration. However, many research and development efforts to date have been focusing on improving the functionality and capability of robots and thus, fundamental questions in human robot collaboration in construction remain unanswered: how can a robot work with a human worker building and maintaining his/her trust? What are the best strategies to design future working construction environments for human robot collaboration? How can the construction industry retrain existing workers and attract new ones in this new working environment? To answer these questions, Lee proposes anthropocentric robot collaboration in construction. In essence, he will make a human robot collaboration human-centric to better understand how he/she responds to co-work with construction robots. He aims to learn his/her response to different scenarios of human robot collaboration in construction, which will be used to maximize the overall performance of human robot collaboration Further, such learning can provide a firm foundation to answer the aforementioned fundamental questions on future construction tasks/operation/work environment/workforce training. With such vision, we propose three activities for this planning grant: 1) Wearable Biosensor-based Emotional Response Measurement in Human Robot Collaboration; 2) Virtual Reality as an Alternative to Real/Lab Tests with Wearable Biosensors; and 3) Workshops to Build a Multidisciplinary Research Team. The success of these proposed activities will validate the overarching vision for anthropocentric robot collaboration in construction and allow Lee to create a cohesive and multidisciplinary FW-HWP research proposal.
National Science Foundation; PI-Valeriy Ivanov
The Arctic is today warming at a rate unprecedented in historic times. Changing climate has amplified seasonal redistribution of heat budgets, accelerated permafrost warming, and affected extreme weather conditions. Terrestrial ecosystems have responded, resulting in lower latitude plants moving into the tundra and cascading northward displacement of mammalian and bird populations up to the Arctic Ocean coastline. Rain-on-snow events and timing changes in plant phenology are imperiling herbivore populations. Biotic communities at the northern fringes face increased competition from southern species and changing conditions threaten extinction, given that the Arctic Ocean prevents migration to yet higher latitudes. These changes have put increased pressure on livelihoods of peoples of the North, who rely on its fauna. Studies of causes and consequences of climate change in the Arctic associated with biotic, abiotic, and socio- cultural systems abound in the literature, but there are few that focus all components on a single area to understand the nature and strengths of underlying interactions and coupling mechanisms. In this Track 2 proposal, Ivanov designs activities to develop a Track 1 proposal for the study of the Yamal region of northern Russia, which presents an ideal natural laboratory for transdisciplinary work to facilitate comprehensive understandings of effects of climate change on environmental, social, and built environment systems of the Arctic. Yamal is ideal for developing a large-scale transdisciplinary project because (along with abutting Belyi Island) it spans four of the five Arctic bioclimatic subzones along a uniform south-north radient and has the research and transportation infrastructure necessary to support this work. The main objectives of research resulting from the proposed planning activities are to understand 1) the complexity and adaptation of Arctic biotic and abiotic systems to climate, 2) society’s role and response to the dynamics of these systems, and 3) the significance of feed-forward and feedback mechanisms modulating their mutual co-evolution in the Yamal region. In this planning project, Ivanov outlines two sets of processes that span natural and built environment systems as well as social systems. He aims to carry out comprehensive synthesis activities identifying knowledge gaps, critical science questions, and specific research objectives as well as tools, data, models, and research capacity gaps required for transdisciplinary integration. His specific planned activities include (a) two workshops with stakeholder and indigenous community engagement, (b) monthly virtual conferences, (c) international research capacity-building, (d) synthesis activities and a talk-team course, and (e) the submission of Track 1 proposal at the conclusion of these activities.
National Science Foundation; PI-Jeremy Semrau
Methanotrophs, or methane-oxidizing bacteria, are a group of microbes with great industrial importance. Specifically, methanotrophs oxidize methane under ambient temperatures and pressures, and thus are attractive platforms for the valorization of methane to products such as bioplastics and biofuels. Interest in commercial application of methanotrophy has dramatically accelerated in recent years as methane prices have become quite low, with the industrial price of natural gas dropping from $13.06 per 1000 ft3 in July 2008 to $3.73 per 1000 ft3 in August 2018.
Methanotrophic activity, however, is strongly affected by a number of environmental parameters, especially the bioavailability of copper and rare earth elements. That is, methanotrophs have a well known “copper-switch” where the form and activity of methane monooxygenase responsible for the initial oxidation of methane to methanol responds significantly to the availability of copper. More recently, it has been shown that rare earth elements (REE) also have a major effect on methanotrophs, i.e., REEs strongly regulate the expression of alternative methanol dehydrogenases that oxidize methanol, signifying that a “REE-switch” also exists. This is particularly interesting as this is the first example of rare earth elements regulating prokaryotic gene expression.
Given that methanotrophs respond quite strongly to copper and rare earth elements, the industrial significance of methanotrophy is highly dependent on culture conditions. Herein, Semrau propose to determine how to manipulate methanotrophs for the enhanced valorization of methane to products such as methanol (as an example of biofuels) as well as polyhydroxybutyrate (as a precursor to bioplastics). To achieve these goals, however, more information is required as how copper and rare earth elements affect methanotrophic physiology and gene expression such that these microbes can be best genetically modified for enhanced methane valorization. Specifically, a suite of molecular techniques will be pursued to delineate the basis of the copper and REE-switches in methanotrophs, and then targeted genes will be knocked out to enhance the re-direction of carbon to desired end products.
National Science Foundation; PI-Radoslaw Michalowski
The time-dependent behavior of granular geomaterials is among the least understood of their characteristics, and arching in granular materials is an elusive phenomenon that has been considered only intuitively in engineering, without a definitive mathematical framework needed for engineering analyses. This proposal addresses both time-dependent evolution of contacts between grains with its consequences for contact shear strength and influence of the contact evolution on formation of soil arches in silica sand. This proposal has three objectives: (a) gathering experimental evidence for an increase in shear resistance of contacts between grains of silica sand and seek explanation for time-dependency of grain-to-grain contact interaction, (b) development of models for time-dependent behavior of individual contacts between silica sand grains, and (c) development of predictive tools and computational capabilities for predicting arching in granular materials. A new, custom-designed grain-scale testing apparatus will be constructed to gain insight into shear behavior of contacts between silica sand grains. Scanning electron microscopy and atomic force microscopy will be employed to characterize the surface texture of grains. Experimental evidence will be collected for the evolution of the contact shear strength. Numerical models of this behavior will be developed, which will be used in computational analyses of arching development in soil masses. These analyses are expected to shed light on dependence of soil arch formation on the behavior of contacts between grains in granular materials.
Great Lakes Water Authority (GLWA); PI-Jerome Lynch
The project will develop a first-order reliability framework to assess the probability of failure in the GLWA drinking water transmission system. The approach will take an analytical strategy to model service load demands on system pipe infrastructure with service pipe structural capacity estimated based on GLWA inspection, maintenance and failure reports of the network. Coupled with the consequence of failure, a prototype risk assessment framework will be provided to GLWA decision makers at the end of the project.
Great Lakes Water Authority (GLWA); PI-Glen Daigger
Discontinuing or reducing ferric chloride addition for phosphorus removal for flows receiving secondary treatment represents a significant opportunity for the GLWA WRRF. Potential advantages include reduced chemical costs, reduced sludge production, and the potential for phosphorus recovery which will also reduce the phosphorus content of the biosolids product produced by the facility. While the GLWA HPO secondary treatment system exhibits bio-P capacity, it is not possible to assess the true extent of bio-P capability due to the addition of ferric chloride to the full-scale system. Thus, bench-scale testing using GLWA primary effluent without ferric chloride added is required to assess the full bio-P capacity potentially available. GLWA is also running pilot tests on anaerobic digestion of waste sludges (primary, WAS, and imported organic matter), and conversion to full bio-P would significantly affect such a system. A process model of the GLWA liquid treatment process as part of the previous U-M research can be extended to include solids processing options, including the current system and various anaerobic digestion options including phosphorus recovery, to assist GLWA to understand the impacts of potential process modifications.
The Water Research Foundation; PI-Krista Wigginton
Human viruses are linked to a number of important illnesses associated with contaminated water. Interestingly, despite their impact on public health, human viruses are only a small fraction of those found in wastewater and drinking water. The vast majority are viruses that infect bacteria, algae, plants, and other organisms. These “dark” viruses likely play significant roles in shaping microorganism functions in biological processes, in the formation of biofilms in distribution systems, and in the populations of opportunistic bacteria that sometimes flourish in household plumbing. Despite the impact they have on the water quality industry, we know much less about waterborne viruses than other groups of aquatic microorganisms. This is driven by the difficulty in detecting viruses. Virus particles are extremely small, measuring only 20-200 nm in diameter, which makes them difficult to capture from water samples and nearly impossible to visualize with common microscopy techniques. Furthermore, only select viruses can be grown in the lab and molecular methods require well-equipped labs.
The lack of methods to rapidly count virus particles makes it difficult to demonstrate the efficacy of water treatment processes at removing viruses in real-time. Wigginton will develop a new approach to tracking virus particle removal. Her team will develop empty virus particles that are noninfective and behave just like real viruses in water treatment processes. The empty particles will be tagged so that they can readily counted in pilot and full-scale systems with common flow cytometers.
Fast and accurate methods for detecting specific environmental pathogens are critical in outbreak events, but most available virus detection methods are not field deployable. Wigginton proposes to translate a new biotechnology called CRISPR-Cas into a fast and quantitative method for virus detection. Already demonstrated for virus detection in human samples, the method will transform environmental monitoring because it does not require expensive equipment, and is thus easily field-deployable. Ultimately, the method could be expanded to monitor bacteria and protozoa in the same samples.
The water quality field lacks a thorough understanding of how the overall virus community fluctuates in wastewater, through water treatment processes, and in drinking water distribution systems. Presently, methods that quantify viruses tend to detect only one or a few strains at a time. Alternative methods that screen for many viruses tend to provide qualitative results. To address this, her team will develop a sensitive virus sequencing method that measures the concentrations of all viruses in a sample, and thus can show how virus concentrations vary from plant to plant, how certain viruses are resistant to treatment, or how viruses that infect bacteria and other microorganisms are influencing biological unit processes. This method will ultimately help protect public health and also facilitate the development of virus-based methods for treating water.