New Grants

Development of WRRF Influent and Plant-Wide Simulation Tool

Great Lakes Water Authority (GLWA); PI – Glen Daigger

The Great Lakes Water Authority (GLWA) Water Resource Recovery Facility (WRRF) provides primary and secondary treatment, chemical and biological phosphorus removal, and disinfection of municipal, industrial, and combined sewer flows using conventional primary treatment, with ferric chloride addition followed by high purity oxygen (HPO) activated sludge process. Primary and secondary sludge is thickened in separate gravity thickener complexes, combined, and either processed into pellets by centrifuge dewatering and thermal drying or dewatered and incinerated. University of Michigan (U-M) researchers have been assisting GLWA with analysis of the functional treatment mechanisms and performance of the WRRF since 2017, including investigations of chemical and biological phosphorus removal, the fate of phosphorus through the WRRF, opportunities for phosphorus recovery, and development of a whole plant model in SUMO. GLWA wishes to continue to receive assistance from U-M researchers and to provide research opportunities for U-M students. The purpose of this project is to provide the basis for continuing this collaboration and to conduct research, as agreed to by GLWA, to further assist with understanding and optimizing the performance of the WRRF.

Deposited smoke in urban areas; surface grime and emissions of volatile products

Commerce, Department of-National Oceanic and Atmospheric Administration; PI – Rachel O’Brien

This project will look at the impact of wildland fires on the air quality in urban areas. We will carry out a laboratory study that probes the aging of biomass-burning organic aerosol particles (BBOA) and we will explore the products formed in the condensed phase as well as look at the volatile fraction. This project is looking at aerosol particles as well as BBOA materials deposited on surfaces indoors and outdoors. The majority of the work will take place at the University of Michigan with some travel to Aerodyne for experimental measurements. We will also be collaborating with a team at UC Davis that will be sending us surface samples to look at deposited real-world smoke samples. The major deliverables will include multiple papers and a portion of a Ph.D. thesis. This project will involve a graduate student from UM as well as undergraduate student researchers to assist with preparation, aging, and some data analysis.

FY24-Project M (SEWRB-UM): ELC SEWER Network Project-Wigginton/Eisenberg

State of Michigan, Health and Human Services Department ; PI – Krista Wigginton

This project provides the State of Michigan with data on wastewater SARS-CoV-2 levels in wastewater treatment plants. Samples will be collected regularly and SARS-CoV-2 genes will be quantified with digital droplet PCR.

NSF Convergence Accelerator Track K: Advancing equitable and circular water systems through source separation

National Science Foundation; PI – Nancy G. Love

Water in modern society is inherently complex; its management, use, value, and accessibility are all defined through a complex “system-of-systems” web of technology, regulations, policy, economics, public health, social history, and human perceptions. Furthermore, every type of water in water systems (e.g., source and receiving waters, treated drinking water, the various forms of water containing waste materials from human use, stormwater, groundwater, irrigation water, industrial water) is connected to and impacts multiple other types of water the flows through our communities. This proposal is grounded in the premise of One Water. Among the many features of this approach is the acknowledgement that waste management is the first step in effective water treatment for both potable and non-potable uses. Our vision for this proposal is to normalize source separation as a strategy to create sustainable, resilient, and equitable water systems.

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Grants Awarded for 2023

Assistance Optimizing the Great Lakes Water Authority (GLWA) Water Resource Recovery Facility

Great Lakes Water Authority (GLWA); PI- Glen Daigger

The Great Lakes Water Authority (GLWA) Water Resource Recovery Facility (WRRF) provides primary and secondary treatment, chemical and biological phosphorus removal, and disinfection of municipal, industrial, and combined sewer flows using conventional primary treatment, with ferric chloride addition followed by high purity oxygen (HPO) activated sludge process. Primary and secondary sludge is thickened in separate gravity thickener complexes, combined, and either processed into pellets by centrifuge dewatering and thermal drying or dewatered and incinerated. University of Michigan (U-M) researchers have been assisting GLWA with analysis of the functional treatment mechanisms and performance of the WRRF since 2017, including investigations of chemical and biological phosphorus removal, the fate of phosphorus through the WRRF, opportunities for phosphorus recovery, and development of a whole plant model in SUMO. GLWA wishes to continue to receive assistance from U-M researchers and to provide research opportunities for U-M students. The purpose of this project is to provide the basis for continuing this collaboration and to conduct research, as agreed to by GLWA, to further assist with understanding and optimizing the performance of the WRRF.

Transforming Equilibrium Analysis Paradigm for Modeling Transportation Networks with Intelligent Traveling Agents

National Science Foundation; PI- Yafeng Yin

Transportation network equilibrium modeling paradigm plays an important role in planning and operations of transportation networks. The paradigm has been established via a “bottom-up” approach over the past 66 years. The proposed research aims to transform this “bottom-up approach” by developing an end-to-end learning and optimization framework. Our research is also motivated by observing that, assisted by advanced decision-support technologies, future traveling agents (connected drivers or automated vehicles) will possess strong learning and computation capability, and their travel decisions can be algorithmic, strategic and adaptive. The presence of these intelligent agents cast doubt on whether the equilibrium modeling paradigm is adequate for planning future urban transportation networks, and whether the notion of equilibrium remains relevant for capturing the interactions of intelligent traveling agents. The proposed research consists of two thrusts. The first thrust focuses on developing dynamical systems by explicitly modeling day-to-day travel choices of intelligent traveling agents and examining the convergence and stability properties of the dynamical systems. By demonstrating Wardropian user equilibrium can still emerge in the day-to-day evolution of network traffic dynamics with intelligent traveling agents, we hope to provide certain justification for the premise of equilibrium or establish some behavioral basis for the equilibrium modeling paradigm. The second thrust aims to integrate implicit deep learning with network equilibrium analysis to develop an end-to-end framework that directly learns the behaviors of traveling agent, the equilibrium state, and other modeling components, if needed, from empirical data. This end-to-end framework can not only support a much richer representation of travel behaviors but also describe the outcome of strategic interactions among intelligent traveling agents. Once trained, it can be used to conduct “what-if” analyses. In addition, the same modeling framework can be further tweaked to prescribes optimal plans for improving the network performance.

Performance-Based Financing Models for Sustainable Water Management in the Great Lakes Basin

Foundation For Food and Agriculture Research; PI- Peter Adriaens

This implementation project focuses on an innovative financial markets approach to address soil health, nutrient leakage and water quality issues in the Great Lakes Basin. While conventional farming operations are often singled out as the direct cause of fertilizer runoff, the role of the capital markets using green farming financing to influence sustainable farming practices has received little attention until recently. There is an increasing demand in the farm credit and lending market for sustainability-linked financial products, to catalyze the change from traditional to sustainable on-farm practices resulting in improvements in soil health from measurement to adoption. This implementation project focuses on demonstrating the leveraging power of the capital markets to affect behavioral change in corporate supply chains and their agricultural partners (producers) on a use case in the Saginaw Bay area. The premise underlying this theory of change is that environmental externalities from agricultural pollution are not priced in the market because of market and definitional frictions that could capture this sustainability risk in (i) financial transactions; (ii) land and commodity valuation; and (iii) a risk and return framework. The key implementation objective of the project is to demonstrate the feasibility of new financing (lending) instruments to accelerate sustainable land stewardship and mitigate impacts from fertilizers in the Great Lakes ecosystem. 

Performance-Based Financing Models for Sustainable Agriculture in the Great Lakes Basin 

Great Lakes Protection Fund; PI- Peter Adriaens

This implementation project focuses on an innovative financial markets approach to address soil health, nutrient leakage and water quality issues in the Great Lakes Basin.  While conventional farming operations are often singled out as the direct cause of fertilizer runoff, the role of the capital markets using green farming financing to influence sustainable farming practices has received little attention until recently.  There is an increasing demand in the farm credit and lending market for sustainability-linked financial products, to catalyze the change from traditional to sustainable on-farm practices resulting in improvements in soil health from measurement to adoption.  This implementation project focuses on demonstrating the leveraging power of the capital markets to affect behavioral change in corporate supply chains and their agricultural partners (producers) on a use case in the Saginaw Bay area. The premise underlying this theory of change is that environmental externalities from agricultural pollution are not priced in the market because of market and definitional frictions that could capture this sustainability risk in (i) financial transactions; (ii) land and commodity valuation; and (iii) a risk and return framework. The key implementation objective of the project is to demonstrate the feasibility of new financing (lending) instruments to accelerate sustainable land stewardship and mitigate impacts from fertilizers in the Great Lakes ecosystem.  

Feasibility of single-stage softening during water treatment: a pilot scale assessment

City of Ann Arbor; PI- Aleksandra Szczuka

The pilot study is conducted to address the following treatment needs:
1.        Hardness removal with single-stage softening using lime and sodium hydroxide (or soda ash).
2.      Organic carbon removal with single-stage softening including potential coagulants and their impact on the settleability and filterability of the organics.
3.       Sustainability of filter operations to meet water quality objectives with single-stage softening.
4.        1,4-dioxane removal.
5. Evaluation of disinfection byproduct (DBP) formation (at pilot scale) and formation potential (at lab scale) during treatment
6.    Evaluation of the behavior of per- and poly- fluoroalkyl substances (PFAS) during treatment
7.     Evaluation of the behavior of optional additional contaminants. These contaminants would be assessed if time and budget allow, and are not included within this scope of work. 

Personalizing stormwater investments using digital tools

Fred A. & Barbara M. Erb Family Foundation; PI- Branko Kerkez

Project Goals: 1. Democratize access to the latest generation of digital tools, which will allow residents, community groups, and municipal managers to personalize stormwater solutions and maximize the likelihood of positive outcomes. We envision an easy-to-use web app, accessible to anyone in the region. 2. Empower residents to easily answer questions such as “if I place a rain garden on my property, how will flooding in my neighborhood change?” Community groups will be able to evaluate scenarios, such as “how will water quality in the Detroit River improve if our neighborhood switched to permeable pavement?”  3. Support Municipal managers to quickly optimize and compare green and gray solutions across large scales through recommendations made by the latest generation of Artificial Intelligence and Data Analytics.

“FISH’N’CHIPS”:  Forecasting and Identifying Supply-and-demand Hindrances aNd Correlated Hazards In Procurement Systems 

Stealth Software Technologies, Inc.; PI- Peter Adriaens

Stealth Software Technologies, Inc. (Stealth) proposes a new supply chain management system for DARPA RSDN TA2. At a high level, our proposed effort involves three components. The first component is (a) applying cutting-edge graph, network, and learning algorithms to SDN data using cutting edge ideas from graph clustering, streaming and multicommodity flow algorithms from theoretical computer science. Next, we have a novel approach to (b) data and function connectors with APIs that are expressive and flexible. These can interface with TA1 systems in a robust way that will produce novel graph analyses and utilize secure multiparty computation and/or differential privacy, and can also be connected to TA3 solutions that heavily rely on automated stress testing. The final component is (c) a revolutionary visualization engine tied into the APIs, enabling easy-to-understand, reactive depictions of the complex underlying analysis. We further elaborate on these tasks in the Technical Plan section.

Regional Coordination to Optimize Wastewater and Stormwater System Operations

Fred A. & Barbara M. Erb Family Foundation; PI- Glen Daigger

The primary goals of the project are to identify barriers to regional stormwater cooperation and then to work towards solutions to these barriers so that the region can better manage the impacts of larger storm events and variability of precipitation driven primarily by climate change. The benefit for the region could be hundreds of millions of dollars in capital savings. This project will focus on the GLWA wastewater service area in SE Michigan which includes portions of Wayne, Oakland and Macomb counties. There are a number of technologies and concepts that currently exist to more effectively manage stormwater flows from a regional perspective. In addition, new approaches can be developed based on new operating parameters which could benefit the region significantly. These approaches have the potential to save hundreds of millions of dollars of capital investment and operations costs.

BRITE Relaunch: A Physics-Based Simulation Model for Exploring Community Resilience to Wildfires

National Science Foundation.; PI- Ann Jeffers

Wildfires pose a substantial threat to civilians living at the wildland-urban interface (WUI). The damage to most structures is caused by ignition from firebrands, which are fragments of flaming and smoldering materials that are carried by the wind and may impinge on structures. While a single firebrand is enough to ignite a home, a greater danger is faced when accumulations of firebrands gather at certain locations on the structure (e.g., in corners, cracks, and crevices). At present, the only way to study how firebrands accumulate around structures is to perform an experimental test. However, such tests are expensive and do not necessarily scale to full-sized structures. Furthermore, the lack of a model for firebrand transport and ignition prohibits advances that seek to understand how policy and data science can inform decision-making for communities at the WUI. This work proposes the formulation and validation of a physics-based simulation model for firebrand transport around structures. The simulation will use computational fluid dynamics (CFD) to simulate the flow of air around a structure due to wind using a multiphase Eulerian approach, and firebrands coming in contact with the structure will be modeled using the Discrete Element Method (DEM). Due to the high level of uncertainty, a stochastic model is proposed that takes into account the variability in firebrand properties, which have been measured from experiments and are published in the literature. Once validated, the simulation model will be used to study how policy decisions affect community resiliency to wildfires.

Grants Awarded for 2022

Impact of UV treatment on microbial communities in a full-scale drinking water distribution system

City of Ann Arbor; PI- Lutgarde Raskin

The proposed research will investigate the effect of UV treatment within a full-scale water treatment plant (AA-WTP) on microbial communities in the distribution system, with a focus on opportunistic pathogens and nitrifying bacteria. Experiments will be conducted to characterize microbial communities within A) a full-scale water treatment plant and distribution system 1) while the UV system is off/operated only intermittently and 2) during a one-year period of continuous operation. Samples will be collected before and after theUV system to characterize the impact of UV on the overall microbial community and target populations. Additionally, sampling will be conducted in the distribution system to determine how continuous UV treatment changes distribution system water quality. The results of this research will provide guidance to the utility regarding the potential benefits and costs of continuous operation of the UV disinfection system, including how the system may influence microbial communities, microorganisms of concern, and general water quality.

Leveraging Vehicle Telemetry Data to Reduce Congestion in Urban Traffic Networks

General Motors Company; PI- Yafeng Yin

Utilizing GM’s high speed vehicle telemetry (HSVT) data, the University of Michigan (UM) team, in collaboration with General Motors LLC Global R&D, aims to develop novel computational techniques that prescribe strategies to better manage and operate existing traffic networks to reduce traffic congestion. This project contributes to GM’s efforts of achieving the “zero congestion” for future transportation. It leverages recent advancements in machine learning to develop an end-to-end modeling framework that would transform the way how metropolitan planning organizations model, plan and manage their traffic networks.

Multidisciplinary InvesTIGAtion of Transmission to Ease inFLUenza (MITIGATE FLU)

National Philanthropic Trust; PI- Krista Wigginton

The overall goals of this project are to innovate influenza virus detection and quantification and to probe mechanisms of virus inactivation in air and on surfaces. These goals will be achieved by systematically and simultaneously optimizing both sampling and detection. The final products of this effort will be accurate and rapid platforms for influenza virus detection within indoor air and on fomites, as well as mechanistic descriptions of influenza virus fate in the indoor environment. Our cross-disciplinary team of experts in environmental virus surveillance, influenza virology, protein mass spectrometry, pathogen sensors, and aerosol science is uniquely positioned to address this persistent issue.

Collaborative Research: NNA Research: Interactions of natural and social systemAnalysis and Characterizing Sludging in Flat Sheet Membranes

Fibracast; PI- Glen Daigger

The objectives of the research to be conducted in accordance with the scope of work are as follows:
1.To characterize the fluid flow characteristics of Fibracast commercial membrane cassettes tobetter understand how to optimize membrane system performance.
2.To verify computational fluid dynamic (CFD) model experimentally.
3.To investigate and verify potential improvements to commercial membrane cassette.
4.To investigate potential additional applications for Fibracast membrane products.
This project emphasizes two types of stressors: (a) changes in summer and winter heating regimes that have led to growth of tall vegetation in the tundra, and an increased frequency of winter warm spells that change snowpack structure and seasonality and (b) growing presence of industrial activities/infrastructure as well as increasing social complexity of reindeer herding economy. Building on state-of-the-science understandings of impact paths of these stressors, we propose a set of hypotheses to be tested via a transdisciplinary approach, and synthesis of traditional and scientific knowledge. The project addresses all six focus areas of the NNA solicitation. Based on Track 2 team development activities, our group (22 scientists) has developed a comprehensive management and integration plan for effective coordination and integration of
disciplinary research tracks.

FW-HTF-R: Collaborative Research: Partnering Workers with Interactive Robot Assistants to Usher Transformation in Future Construction Work

National Science Foundation; PI- Seymour Spence

Extreme windstorms cause massive economic loss and societal disruption each year. According to the National Oceanic and Atmospheric Administration, in 2020 the United States was subject to 22 weather events that caused more than one billion dollars of losses, with Hurricane Laura the costliest causing 19 billion dollars of losses and leaving more than a million people without power. To increase the resilience of the built environment against extreme winds there is huge interest from the civil engineering
community to radically change how buildings, a key part of the built environment, are designed to resist extreme winds through the application of methodologies based on the concepts of performance-based engineering. This new paradigm, referred to as performance-based wind design (PBWD), centers on the explicit evaluation of performance at all hazard intensities, including at ultimate load levels where significant damage is expected, while systematically treating uncertainty through reliability. This industry-led drive for PBWD has resulted in the recent publication of a first-of-its-kind Pre-standard on PBWD by the American Society of Civil Engineers and created a fundamental need for technologies that can assist practicing engineers in carrying out PBWD of structural systems through advanced reliability-based analysis procedures. The technology of this project fills this critical gap through providing an initial software tool for reliability-based PBWD that leverages the basic research breakthroughs in probabilistic dynamic shakedown of wind excited structural systems that were spawned by the NSF lineage award: CMMI-1462084: Collaborative Research: Performance-Based Framework for Wind-Excited Multi-Story Buildings. The target market for the technology are the thousands of civil and structural engineers tasked with designing structural systems that possess greater resilience to extreme wind events, while meeting the stakeholder’s need for cost effectiveness. It is estimated that there are over 300,000 civil engineers in the United States, with over 50,000 specifically working in the space of structural engineering and therefore the design of systems to resist the actions of natural hazards.  

MS2 enumeration in samples

MagPlasma, Inc.; PI- Alexsandra Szczuka

The purpose of these trials is to inform system optimization and to determine disinfection efficacy of the final system prior to field trials.

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Integrated biochemical and electrochemical technologies (IBET) to convert organic wastes to biopower via North American research and educational partnerships

Department of Energy; PI- Lutgarde Raskin

We propose to develop an integrated biochemical and electrochemical technologies (IBET) system to convert mixed urban and suburban organic waste streams to pipeline-ready biomethane. The IBET system consists of three synergistic components. A first-stage anaerobic dynamic membrane bioreactor (AnDMBR), modeled after the stomach of ruminants, will be used to enhance hydrolysis and achieve rapid short chain carboxylic acids (SCCAs) generation (expected organic loading rate is 24 g volatile solids (VS)/L reactor/day at a 12-h hydraulic retention time (HRT)). A second novel AnDMBR with enhanced biofilm surface area and recirculation (MagnaTree bioreactor) will convert the SCCAs produced in the first-stage AnDMBR to biogas with an expected yield of 0.4 L CH4/g VSfed at a 5-day HRT. In the final stage, an electrochemical separation system, called the Electrochemical Reactor for CO2 and H2 Delivery (ERCHD), electrolyzes water into H2 and captures biogas CO2 as aqueous HCO3-. The produced H2 and captured HCO3- serve as substrates for a second MagnaTree bioreactor focused on hydrogenotrophic methanogenesis, which produces an extra ~38% of high-purity (98%) CH4. The project aims to evaluate the performance of this IBET system at the pilot-scale level at the Great Lakes Water Authority water resource recovery facility (WRRF), perform a techno-economic analysis and a life-cycle assessment, and develop industry recommendation. We anticipate greater than 25% more biomethane production and 25% less operating cost compared to the State of Technology. We propose to integrate our research with innovative educational efforts to advance both waste-to-energy (W2E) technology and next-generation workforce development. We will create an educational consortium to connect the leading institutions and collaborating partners. Collaborations among five North American universities will expand our research potential and promote an understanding of the North American W2E context. Involving a WRRF, three engineering companies, and a national lab partner will be especially effective taking into account real-world complexities from the start. These partnerships also allow the sharing of educational resources and create meaningful training opportunities for diverse students at different levels. The consortium will achieve its goals through three major activities: Ph.D. student research rotations, co-op-based master student training, and research experiences for undergraduates. We will recruit students from partner and collaborating universities and community colleges. Diverse students will be recruited through our existing networks with Minority Serving Institutions.

Collaborative Research: Cascade “Ecohydronomics” in the Amazonian Headwater System

National Science Foundation; PI- Valeriy Ivanov

Tropical forests yield a third of global evapotranspiration from land surface. Nearly half of the water that falls on the Amazon rainforest, the world’s largest contiguous tropical forest, passes through stem xylem and leaf stomata on its way back to the atmosphere. There has been progress in quantifying large-scale water fluxes in Amazonia, however, ecophysiological and soil-water processes controlling landscape variability in transpiration, and the unilateral, cascading impact of forests residing in groundwater recharge (GW-R) areas on hydrology and tree function in discharge (GW-D) zones remains poorly understood. We hypothesize that (H1) there is a strong landscape variation in forest
transpiration capacity due to distinct ecophysiological traits of trees residing in GW-R and GW-D regions; (H2) previously unquantified “hybrid” hydraulic behavior of tropical soils governs flux quantity and the transit time scales of soil water transport connecting GW-R and GW-D areas; and (H3) the composition and ecophysiology of forests in topographic highs control the one-way cascade GW-R→GW-D connection and shape its sensitivity to climate variations, determining the distribution of ecophysiological traits and
transpiration in topographic lows. The specific objectives are (O1) to estimate forest transpiration capacities in GW-R and GW-D areas based on physiological trait measurements and mechanistic modeling for two locations in the Amazon of distinct climate seasonality; (O2) to inversely estimate properties of the hybrid soil hydraulic system based on deep soil water observations using novel tools in
probabilistic learning and models of soil hydraulics; (O3) to infer effective soil hydraulic properties governing GW-R→GW-D connection in a case study tropical watershed in central Amazonia; (O4) Integrate ecophysiological and hydrological models to estimate the spatial distributions of GW-R→GW-D water transit times; and (O5) to quantify watershed-scale GW-RGW-D flux sensitivities to climatic perturbations at seasonal and interannual scales, including long-term change of vegetation traits.

Next-generation performance-based wind engineering: knowledge and computational modeling advances for collapse characterization

National Science Foundation; PI- Seymour M.J. Spence

Each year extreme windstorms cause massive economic and societal loss around the world. Estimates put the losses to the United States to hurricanes alone, over the past five years, to be in excess of $300 billion. This has led to intense interest from both wind engineering researchers and practitioners to transition from traditional prescriptive approaches in favor of performance-based engineering (PBE) methodologies. A direct consequence of these efforts has been the development of state-of-the-art frameworks and guidelines for the application of what has become known as performance-based wind engineering (PBWE). Despite these efforts, a fundamental lack of knowledge still exists on the behavior at collapse of integrated structural and envelope systems of typical wind excited buildings that adhere to current codes and standards. This lack of knowledge is coupled with an absence of efficient and practical computational modeling approaches that are capable of not only assessing such an integrated collapse scenario, but also accounting for the inevitable uncertainty that exists in estimating collapse. These essential gaps in knowledge and modeling severely limit the benefits of current PBWE methodologies. The main goal of this project is to provide the necessary advances in knowledge and modeling to overcome these fundamental hurdles. This will be achieved through the creation of a comprehensive knowledge base concerning the probability of collapse of typical structural systems subject to extreme winds and how this correlates to the performance of typical building envelope solutions. This knowledge base will enable the introduction of a new generation of probabilistic computational modeling frameworks for the rapid and integrated structural and envelope collapse assessment. These advances will arm engineers with the necessary tools for reaping the maximum benefits offered by PBWE during the integrated design of building systems against extreme winds. This will lead to transformative innovation in design, while providing the fundamental knowledge advances necessary for the development of next generation PBWE guidelines and standards.

Collaborative Research: NNA Research: Interactions of natural and social systems with climate change, globalization, and infrastructure development in Yamal (Russian Arctic)

National Science Foundation; PI- Valeriy Ivanov

The Arctic warming has triggered seasonality shifts, permafrost warming, and the occurrence of extreme weather conditions. Terrestrial ecosystems have already responded with phenology changes, lower-latitude plants moving into the tundra, and cascading northward displacement of mammalian and bird populations. These changes have put increased pressure on livelihoods of peoples of the North, who depend on flora and fauna tied inextricably to weather and seasonality. The Arctic is also being impacted by globalization: the emergence of industrial and urban “hot spots” and centers of hydrocarbon extraction, the development of tourism, and the growing influ-ence of “newcomers” are impacting the tundra and livelihoods of indigenous peoples as
never before. Multi-system responses of Arctic systems to both climate change and globalization is urgently needed.
Following our Track 2 project team integration and synthesis activities, we propose to study natural, social, and built environment systems of the Yamal region of Russia – a tightly bound, circum-scribed “microcosm” of the Arctic. The region spans four of the five Arctic bioclimatic subzones; it bears signatures of the tightly woven processes linking climate, weather, landscapes with permafrost, plants, animals and the increasingly interacting worlds of the Nenets (the indigenous pastoralists subsistent on reindeer) and global economy bringing to the region reindeer product businesses and the hydrocarbon industry. Understanding how these abiotic, biotic, social, and built environment systems are linked in their responses to stressors of the “new Arctic” is our primary objective.
This project emphasizes two types of stressors: (a) changes in summer and winter heating regimes that have led to growth of tall vegetation in the tundra, and an increased frequency of winter warm spells that change snowpack structure and seasonality and (b) growing presence of industrial activities/infrastructure as well as increasing social complexity of reindeer herding economy. Building on state-of-the-science understandings of impact paths of these stressors, we propose a set of hypotheses to be tested via a transdisciplinary approach, and synthesis of traditional and scientific knowledge. The project addresses all six focus areas of the NNA solicitation. Based on Track 2 team development activities, our group (22 scientists) has developed a comprehensive management and integration plan for effective coordination and integration of
disciplinary research tracks.

FW-HTF-R: Collaborative Research: Partnering Workers with Interactive Robot Assistants to Usher Transformation in Future Construction Work

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. This FW-HTF project envisions that 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 this research, human workers will use interactive task learning technology to teach co-robots to perform construction work tasks resulting in symbiotic human-robot teams that can be widely deployed in the construction industry. The future human construction worker will be responsible for high-level work planning and will transition to the role of teacher and supervisor of the co-robot. The co-robot, on the other hand, will perform physically strenuous work tasks and collaborate with the human supervisor to improvise when unforeseen work conditions are
encountered. This envisioned approach parallels the classical Master-Apprentice vocational model prevalent in today’s construction industry, wherein novice human workers develop skills by completing apprenticeships under the tutelage of skilled workers and accumulating experience in diverse work conditions. This transition will be achieved through innovation in the construction vocational curriculum, where, in addition to learning fundamentals of construction work, human workers will learn and use new interaction, visualization and trust-development methods to collaborate with co-robots. These new skills will enable workers to advance their work roles, encourage upward mobility, and open avenues for people of diverse physical abilities to be productive members of the construction workforce, a prospect that is impossible today. This will result in improved productivity and reduced costs associated with re-work and safety in construction work. A tight knit partnership with industry collaborators will inform the research activities and provide access to interactions with a broad range of construction workers.

AI-Based EHS Management

VelocityEHS; PI- SangHyun Lee

Recent advancements in Artificial Intelligence (AI) techniques have enabled Environment,
Health, and Safety (EHS) practices to be smarter and more automated. We aim to define the next generation of EHS management by fully utilizing the potential of AI through a 5-year project with multiple objectives (described below) that can be directly translated into todays’ EHS practices. This project requires significant field trips to collect the data and validate our
developed techniques.

Grants Awarded for 2021

User-driven refinement and improvement of first-generation tools for performance-based wind engineering

Magnusson Klemencic Associates Foundation; PI- Seymour M.J. Spence

The American Society of Civil Engineers (ASCE) Prestandard on Performance-based Wind Design (PBWD) has the promise to revolutionize the way in which structural systems are designed to resist extreme winds. Inelastic design of the Main Wind Force Resisting System (MWFRS) is now contemplated and opens the door to design innovations that have the potential to both significantly reduce the costs associated with the MWFRS as well as increase the sustainability of the MWFRS through reduced material use. With the continued development of the Prestandard, there is a fundamental industry need for validated and user-friendly tools that enable the implementation of the Prestandard procedures following the analysis paths that promise to provide the greatest benefits to designers. This project will respond to these needs by 1) continued user-driven development and refinement of the software tools recently developed in partnership with the Magnusson Klemencic Associates Foundation, and 2) expansion of the software for the explicit evaluation of the incipient collapse limit states associated considered in the ASCE Prestandard on PBWD.

CAREER: Peer-to-peer models and mechanisms for the next generation of transportation systems

National Science Foundation; PI- Neda Masoud

Sharing economy, also known as collaborative consumption, is a fairly old concept that leverages the benefits obtained from sharing resources (products or services) that would otherwise go under-utilized. Although communities have been using the concept of the sharing economy locally for decades, advent of internet has led to its spread in global markets and has highlighted its benefits. Today, the advent of high-performing computational architectures, the promise of a future connected and automated transportation system, and the proliferation of smart personal devices bring a plethora of opportunities to transform the way people and goods move by integrating the sharing economy into the core of transportation systems. In the next generation of transportation systems, peer travelers can interact with each other and create value. This CAREER proposal seeks to identify several major ways through which P2P interactions can significantly enhance mobility and sustainability in the next generation of transportation systems, identify the current knowledge gaps that hinder adoption of P2P systems, and lay out a research plan to address them.

Traffic signal evaluation and optimization using vehicle trajectory data

Denso International America; PI- Henry Liu.

In this project, we will leverage our previous research experience on performance measure and optimization for traffic signals on the Melrose Dr., Vista, California. We will first use traffic signal data from RSU, and trajectory data collected from floating vehicles to develop traffic signal performance measures. Then, volume estimation algorithm with floating vehicle data will be used for traffic state estimation. For signal timing optimization, a hierarchical optimization process will be developed to optimize traffic signal timing plan schedule, and signal settings of cycle length, green split, and offset. A traffic simulation model will be developed to visualize and evaluate signal optimization algorithms. Finally, we will closely work with Denso and local traffic management agencies to implement the new traffic signal timing plan and conduct a field experiment to test the performance of the optimized plan. Evaluation of experiment will also be conducted accordingly.

Enhancing the benefits of community parks using computer vision to map community uses: application to Campus Martius and Cadillac Square Parks

Downtown Detroit Partnership; PI- Jerome Lynch

This project continuously assess the public use of Campus Martius and Cadillac Square Parks. To accomplish this goal, the objectives of the project include: creation of high-performance object detectors based on computer vision methodologies that can identify in real-time patrons in public open spaces and classify their activities while protecting their identities;
creation an automated approach to spatially mapping and labeling trajectories of patrons within public open spaces using camera networks of varying spatial sparsity; study the spatial-temporal dynamics of patron use of public space to understand the interrelationship between design of the space and patron utilization to inform understanding of which aspects of the park offer the most benefit to community users; and, demonstration of the impact of the developed tools and methods working with park managers. The work will be performed in partnership with the Downtown Detroit Partnership (DDP) and with other community stakeholders.

Financial mechanisms and the conditioning of lending and capital flows in agriculture supply chains for farm-based nutrient performance

Great Lakes Protection Fund; PI-Peter Adriaens

We propose a design study to explore the development and pilot-testing of performance-based and market-driven financing mechanisms, including but not limited to, syndicated loans and green bonds, that individually or collectively help reduce nutrient loss from agricultural fields and support the accounting of performance related-benefits from regenerative agriculture. We will detail how the supply chain, and more specifically conditioned, purposeful capital applied along the supply chain, can accelerate the demand for crops that are produced in a manner that creates less environmental damage and that serves to protect the Great Lakes waters from deleterious nutrient enrichment. Recent financial innovations have focused on the conditioning of capital across financial asset classes for sustainable agriculture and are creating an opening to explore their applicability to a place-based testbed, such as the Great Lakes system.

Rapid assembly of continuous surfaces by adhesion of curved-crease origami

Department of Defense; PI- Evgueni Filipov

Assembly of hulls and other surfaces with curvature is often slow and inefficient because multiple flat sheets need to be connected by riveting/welding, or the fabrication requires a complex casting approach. In contrast, origami principles can allow for rapid and easy fabrication from flat sheets. Curved-crease origami allow for smooth surface topologies with the added benefit that the curvature is controlled by the geometry of the crease and the amount of folding. Additional advantages of curved-creasing include reduced stress concentrations, improved resistance to buckling, and enhanced global stiffness. However, to achieve advanced surface geometries, such as non-zero Gaussian curvatures for ship hulls, it will be necessary to connect multiple curved-crease sheets together. To that end, the objective of this project is to establish methods for geometric design, surface optimization, and physical fabrication of hull-type surfaces assembled by adhesion of curved-crease origami.

Our work will establish methods for designing the flat origami crease patterns that when folded and subsequently assembled, will produce a desired three-dimensional hull-type surface. New analytical tools will give insight to the mechanical properties of the final system, and the process for folding and assembly of the separate sheets with adhesion. The curved crease geometries will be rendered to allow for computational fluid dynamics (CFD) simulations of the hulls. We will create an iterative process through which the surface designs will be optimized to improve hydrodynamic characteristics including resistance and seakeeping. Our work will then explore the fabrication processes where we fold the curved-crease origami from flat sheets and adhere them to assemble a desired surface. A large-scale hull-type prototype will be created as a proof-of-concept, and will be used for preliminary testing of stiffness and stability, and if time/resources permit for more advanced hydrostatic and hydrodynamic properties.

If successful, this research will enable a paradigm shift for the fabrication and assembly of complex surface geometries. The adhered curved-crease origami can enable rapid, cost effective, and on-demand fabrication when starting from simple flat sheets or rolls of material. The surfaces will have high stiffness and improved hydrodynamic performance allowing for the rapid creation of small hulls and other naval structures.

Grants Awarded for 2020

PFAS destruction technology investigation for RACER Trust’s Willow Run site – phase 1

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- Smart Infrastructure Finance Center partnership fixed income products ESG strategy

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).

Assessing the integration of Real Time Control (RTC) water management systems into GLWA’s long term control plan

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.

COVID: Wastewater based epidemiology focused on wastewater treatment plants in Michigan

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.

Redesigning the future of construction work by replicating the master-apprentice learning model in human-robot worker teams

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 on-site workers. 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 Future of Work at the Human-Technology Frontier (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.

Predictive models for determining the fate of nonculturable and difficult-to-culture viruses in disinfection processes

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.

Lake St. Clair and Clinton River Watershed decision support system – University of Michigan

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.

Policies and strategies for evolving and managing automated mobility

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 provide guidance on their development and deployment. Related: How self-driving car subsidies could carry us through the ‘dark age’ of deployment.

CO2 utilization for geothermal energy production and renewable energy storage

Alfred P. Sloan 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.

Development of localized ECC for durable infrastructure in the KSA region

Saudi Aramco Technologies Company dba AramcoTech; PI- Victor Li

The objectives of this research is to establish (1) engineered cementitious composite (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.

CAREER: carbon negative subsurface energy technologies

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.

CAREER: large, deployable and adaptable structures through origami engineering

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.

Collaborative research: RAPID: Coronavirus persistence, transmission, and circulation in the environment COVID-19

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.

DPR- 3 “Feasibility of collecting pathogens in wastewater during outbreaks”

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.