Research > New Grants
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.
Argonne National Labs / Department of Energy; PI-Lutgarde Raskin
Argonne National Laboratory (Argonne) and the University of Michigan (U of Michigan) will develop innovative, scalable anaerobic membrane biotechnology that converts organic waste streams into renewable methane using a two-stage novel anaerobic membrane bioreactor (AnMBR) system. U of Michigan is a part of the project team led by Argonne, with BETO-DOE providing funds.
U of Michigan will help Argonne perform bench-scale lab experiments for 12 months. The bench-scale demonstration will be conducted in U of Michigan labs. U of Michigan will also conduct a technoeconomic analysis and assist Argonne in lifecycle analysis of new AnMBR technology.
National Science Foundation; PI-Roman Hryciw
The objective of this project is to advance the state of the knowledge and practice in evaluating the liquefaction response of challenging soil sites. The need for this research is highlighted by several recent liquefaction studies and identified as a high priority issue by participants in the 2016 US-New Zealand-Japan International Workshop on Liquefaction-Induced Ground Movement Effects. The proposed approached that will be used to develop the procedure fully integrates knowledge of the geologic and geomorphic constraints on liquefaction triggering and manifestations and novel in-situ tests (e.g., VisCPT and geo-slicing), which is directly aligned with recommendations made in the recently published National Research Council report on liquefaction and its consequences.