Joel Ducoste

The proposed Annual Support Package is designed to build the foundation needed to develop the KEEN EM program at NC State. It includes a mix of faculty support to conferences and workshops provided by the KEEN network, the development of a Wolf Pack KEEN EM website, the development of the CEMENT (Creating Entrepreneurial Mindset in Engineering Teaching at NC State) Workshop , and finally, the development of a certificate program that documents the level of faculty training in EM.

In North America, temperatures nearing 100 ���������������� have been reported in a few municipal solid waste landfills. Elevated temperature landfills (ETLFs) have unique characteristics and challenges including substantial changes in the composition and quantity of landfill gas (LFG) and leachate, rapid waste subsidence, and, in some cases, elevated liquid and gas pressures. In an effort to understand the key chemical and microbial processes that lead to heat accumulation, we developed a batch reactor model (BRM) which describes all sources of heat input, generation and loss in a typical Subtitle D landfill. While the BRM can generate temperature predictions in a matter of seconds, it cannot predict spatial variations in temperatures that would be essential in assessing disposal strategies that mitigate heat accumulation. Recently, we developed a transient 3-dimensional finite element model to incorporate spatially-dependent waste composition, heat generation and transfer processes, waste disposal strategy, landfill geometry and operating conditions to address the limitations of the BRM. Although this 3D model was effective in demonstrating the propagation of heat through a landfill, the model������������������s solution time is ~4 days on desktop computers using a licensed software (COMSOL) and it is impractical for use on portable devices. To facilitate the need for landfill owners to predict waste temperatures as a function of waste composition and operating strategies, a simplified 3D modeling tool is needed that can rapidly generate results on multiple computing devices. The objectives of the proposed research are to (1) develop an open source compartmental landfill reactor heat (CLRHeat) model to describe spatial heat generation, transfer and accumulation, (2) verify the CLRHeat model using field and/or 3D finite element model data, and (3) develop a graphical user interface (GUI) to simplify the required data to describe a landfill and ease of use of a 3D predictive tool.

TSA: UV Modeling of work space to simulate COVID virus reduction using Computational Fluid Dynamics

Recently, there have been reports of municipal solid waste (MSW) landfills that have been experiencing temperatures in excess of 80 ���������C. Elevated temperatures have a number of deleterious effects that are well known to landfill owners. Consequently, elevated temperature landfills often require increased monitoring and management. In recent work supported by the EREF, we developed a model of heat accumulation in a landfill. The objective of the model was to help identify and mathematically describe all sources of heat input, generation and loss in a typical Subtitle D landfill. The model simulations identified several reactions that contribute significant heat to landfills including the hydration and carbonation of calcium-containing wastes (e.g., ash) and aluminum corrosion. Model predictions however, were based on information adopted from the literature for systems other than landfills. In addition to MSW, many landfills receive non-hazardous industrial wastes including ash from both coal and MSW combustion, ash used to solidify liquid wastes, auto shredder residue (ASR) that contains Al and Fe, and perhaps other Al-containing wastes. Methods are needed to measure the heat production potential of such wastes under landfill-relevant conditions and to use the resulting heat production data to evaluate the quantity of a given waste that can be disposed without the accumulation of unacceptable heat. The objectives of the proposed research are to (1) develop laboratory methods to measure heat evolution from special wastes under landfill-relevant conditions and (2) measure rates of heat production to parameterize our heat accumulation model. The model will then be used to estimate acceptable quantities of specific heat-producing wastes for disposal. The proposal emphasizes heat release from ash and metal corrosion. However, methods will be generalized to assess the heat generation of other wastes.

In the continuing quest to relate microbial communities in bioreactors to function and environmental and operational conditions, engineers and biotechnologists have adopted the latest molecular and ���������������omic methods. Despite the large amounts of data generated, gaining mechanistic insights and using the data for predictive and practical purposes is still a huge challenge. This project will use a methodological framework to guide experimental design to improve the operation, start-up, and resilience and resistance of anaerobic bioreactors co-digesting food and FOG wastes. This research represents leading edge work to combine molecular microbial methods, bioreactor experiments, and modeling to identify and exploit the underlying factors that govern microbial community assembly in anaerobic co-digestion systems.

According to the US Environmental Protection Agency (USEPA), around 23,000 to 75,000 Sanitary Sewer Overflows (SSOs) occur annually and approximately 25% of these SSOs are due to sewer line blockages related to the deposition of insoluble calcium salts of fat, oil and grease (FOG). Prior research studies have quantified the chemical and rheological properties of the FOG deposits along with its formation mechanism (Keener et al. 2008; He et al. 2011, 2013; Williams et al. 2012; Gross et al. 2017). Research performed by the PI and Co-PI on the project entitled ����������������Evaluation of Alternative Binder Material to Reduce Sewer Collection System Infrastructure Maintenance and Enhance Sustainability��������������� funded by WRRI, investigated the substitution of Fly Ash (FA) in concrete to reduce the formation and adhesion of FOG deposit on sewer line surfaces. Although exciting results from this project revealed a significant reduction in FOG formation and adhesion on FA replaced concrete surfaces, its mechanism for reduced FOG deposition at the interface is unknown. An interesting observation from these prior adhesion studies is that FOG deposits do not form or adhere on the concrete coarse aggregate (granite) surface. Understanding this unique and previously unknown phenomenon could lead to new strategies on treating pipe surfaces that would not allow any FOG deposit adhesion. The objectives of this proposed research are to: 1) understand the FOG adhesion mechanism on different sewer pipe surfaces and 2) evaluate the factors affecting FOG adhesion on different sewer surfaces. Successful completion of this project will help to determine the adhesion mechanism of FOG deposits on sewer collection system and develop new strategies during construction or the maintenance of sewer pipes that will change the surface characteristics to reduce the adhesion of FOG deposits. We anticipate that results will eliminate or significantly retard the accumulation of FOG deposits in sewer lines leading to a reduction in the maintenance cost and the occurrence of FOG related SSOs especially in ����������������Hot Spot��������������� regions known for the persistent accumulation of these solids.

The North Carolina Louis Stokes Alliance for Minority Participation (NC-LSAMP), requests a supplement to implement Cohort VII of the ����������������Bridge to the Doctorate��������������� program with North Carolina State University (NC State) serving as the institutional site. NC State University is a member since the beginning of the North Carolina Louis Stokes Alliance for Minority Participation. As one of the two flagship research universities in the University of North Carolina Education System, NC State������������������s world leadership in research and education makes it an ideal site for this phase of the NC-LSAMP Bridge to the Doctorate program. NC State university proposes to support a critical mass of 12 Bridge to the Doctorate fellows in each of the two years of this program. We have a firm written commitments from senior NC State University leadership in the College of Engineering and College of Science, to guarantee funding for BD Fellows through completion of their Ph.D. degree. We plan to develop new initiatives that will increase the percentage of BD fellows that complete their doctorate. Our proposed initiatives will help recruit, retain, and prepare researchers of the future in STEM beyond the timeline of this BD program and change the culture at NCSU for underrepresented graduate students in STEM. At NC State University, our goals are 1) to broaden participation of underrepresented students pursuing a graduate degree, 2) to improve graduate student mentoring and develop a Presidential style advisory panel structure for each student, and 3) to provide workshops on research methods and transition from undergraduate to graduate school for graduate students.

Myo-inositol phosphates (InsPs) are signaling molecules that are critically important in a number of developmental, metabolic and signaling processes in eukaryotes. The fully phosphorylated form, inositol hexakisphosphate or InsP6, plays important roles in many eukaryotes. A new frontier for InsP signaling is the study of unique signaling roles for a novel group of InsPs containing diphospho- or triphospho- moieties (PPx) at one or more positions on the Ins ring. In some ways, these PPx-InsPs are analogous to ATP in that they contain high-energy pyrophosphate bonds, and in addition, have been linked to communicating the energy status of the cell in other organisms. In this collaborative project, we previously developed analytical methods to detect and quantify PPx-InsPs in plant tissues, identified and cloned genes encoding the VIP kinases that are responsible for inositol pyrophosphate production in plants, and developed genetic resources to examine function of the Vip genes. Our preliminary data using mutants lacking both Vip genes reveal these genes are key in signaling the energy status of the plant cell. Further, we have identified a possible mechanistic link between inositol pyrophosphate signaling and a major regulator of eukaryotic metabolism, the Sucrose non-fermenting related kinase 1 (SnRK1). Given the immediate need to understand and manipulate plant bioenergy, the long-term goal of this project is to understand how InsP6, InsP7 and InsP8 convey signaling information within the cell. We focus on these molecules in plants, but point out that our model and findings are applicable to understanding the InsP6 signaling hub in other eukaryotes. During the proposed project, we plan to address several unresolved questions pertaining to PPx-InsPs and energy by first adding to a preliminary kinetic model of this signaling pathway.

NC State's EFRI PSBR program will model, develop, implement, and evaluate a scalable photosynthetic biorefinery (PSBR) that uses transformational nutrient recycle processes and supports efficient conversion of CO2 to lipid (oil) in a marine microalgae-based system. Algal oils are an ideal feedstock for biofuels production, offering high production density and the ability to use marginal water (municipal wastewater, brackish water, etc.) and reuse CO2 in flue gases. However, there are a number of technical challenges associated with culturing algae in current generation PSBRs. Using a tightly coupled synergistic approach employing both Engineers and Biologists, the team will: a) genetically engineer a marine microalgae species (Dunaliella spp.) with enhanced CO2 uptake/fixation and the capability to recycle N and P from microalgal biomass; b) design a small-scale PSBR informed by our kinetic model which will be used to develop a scalable dynamic reactor model based on computational fluids dynamic simulation of the PSBR; c) develop innovative, scalable approaches for algal harvesting and lipid extraction; and d) develop an analytical framework for the LCA of our microalgal PSBR system to include creation of flexible and scalable cost and LCI process models that will ultimately lead to generation of a robust PSBR life-cycle decision tool that can be applied to this and other PSBR systems. Intellectual Merit New technologies developed as a result of this project for scalable, sustainable culturing of phototrophic marine microalgae for optimized algal oil production will broaden scientific discovery and create the framework, synergy and momentum for biologists and engineers to further explore rational design and operation of PSBRs. Genetic enhancement, reactor modeling, and LCA will be used to optimize production of algal biomass and lipids in our PSBR. Exploration of innovative and efficient means for algal CO2 uptake/fixation, cell harvesting, lipid extraction, and nutrient and water recycle, will transform the scientific development of algae-based biorefineries. Demonstration of novel Lagrangian microsensors that can assess accumulation of light radiation in proportion to its exposure during transport through the reactor will significantly aid in the modeling and testing of PSBR operation in response to light. PSBR design optimization enabled by our experiment-informed kinetic and CFD modeling and LCA will advance knowledge in rational microalgal-based PSBR design and operation, ultimately leading to development of fully scalable and sustainable biofuel feedstock production systems. Broader Impacts The development of truly scalable and sustainable PSBRs offers tremendous economic and environmental impact by reducing the transportation sector?s reliance on fossil fuels. This increases the prospect of finally being able to fully exploit the promise of algae as a biofuels feedstock, given that production of algal-oil derived biofuels that are fully compatible with all existing infrastructure has been demonstrated. Innovative and transformative enabling-technologies that will permit robust production of marine microalgae biomass and lipids in scalable and sustainable PSBRs will bring significant environmental and economic benefits to the nation through the development of an efficient, high-yield alternative energy feedstock production platform. This interdisciplinary research among engineers, microbiologists, molecular biologists and plant physiologists provides unique training opportunities for high school, undergraduate, graduate and postdoctoral scholars to bridge traditional disciplines and become the new generation of scientists and engineers to develop renewable energy for future generations.

In this proposal, we present a novel paradigm for identifying putative cis-regulatory promoter targets that control the regulation of stress responses in plants. This paradigm will also be used to identify critical regulatory components that differentiate the regulatory stress response across different cell types. We first develop the computational and analytical infrastructure needed to build a dynamic model of the gene regulatory network from time-course transcription profile data that quantifies the stress response. Novel analytical model refinement techniques are proposed to reduce the space of feasible solutions, generate specifications for model validation experiments, and test functional redundancy in the response. Parallel computing architectures will be used to scale the implementation of these model refinement approaches to the size and complexity associated with gene regulatory networks. The dynamic model of the gene regulatory network will be used to identify relationships between genes, build corresponding functional modules, and identify putative cis-regulatory promoter targets and regulatory components that can be used to alter responses to biotic and abiotic stresses in plants. Previous cell-specific transcription profiling has indicated that cell types have distinct expression profiles and respond differently to stress. We will generate cell-specific time-course transcription profiles using experiment specifications derived from the dynamic gene regulatory network. These data will be used to create a cell-specific dynamic gene regulatory network for identifying regulators that are key in differentiating the stress response between cell types.