- Exploring alternative solid waste management strategies for achieving policy goals , Engineering Optimization (2020)
- Metamodels to assess the thermal performance of naturally ventilated, low-cost houses in Brazil , ENERGY AND BUILDINGS (2019)
- Solid Waste Management Policy Implications on Waste Process Choices and Systemwide Cost and Greenhouse Gas Performance , Environmental Science & Technology (2019)
- Battle of Water Networks DMAs: Multistage Design Approach , JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT (2017)
- Construction and setup of a bench-scale algal photosynthetic bioreactor with temperature, light, and ph monitoring for kinetic growth tests , Jove-Journal of Visualized Experiments (2017)
- An enhanced linear regression-based building energy model (LRBEM plus ) for early design , JOURNAL OF BUILDING PERFORMANCE SIMULATION (2016)
- A framework for incorporating ecological releases in single reservoir operation , Advances in Water Resources (2015)
- Role of multimodel combination and data assimilation in improving streamflow prediction over multiple time scales , Stochastic Environmental Research and Risk Assessment (2015)
- Understanding the low-frequency variability in hydroclimatic attributes over the southeastern US , JOURNAL OF HYDROLOGY (2015)
- A Monitoring Network Design Procedure for Three-Dimensional (3D) Groundwater Contaminant Source Identification , ENVIRONMENTAL FORENSICS (2014)
Per- and polyfluoroalkyl substances (PFAS) are emerging as a major public health problem in North Carolina and across the United States. PFAS comprise a class of over 5,000 compounds. Their unique chemical properties have been harnessed to make consumer and industrial products more water, stain, and grease resistant; they are found in products as diverse as cosmetics and flame-retardants. PFAS are resistant to degradation, move easily through the environment, and accumulate in living organisms. Exposure to PFAS has been associated with health effects including cancer and toxicity to the liver, reproductive development, and thyroid and immune systems. Despite widespread detection in the environment and evidence of increasing human exposure, understanding about PFAS toxicity, its bioaccumulative potential in dietary sources such as aquatic organisms, and effective remediation remain notably understudied. The recent discovery by this proposed CenterÃƒÂ¢Ã¢â€šÂ¬Ã¢â€žÂ¢s Deputy Director, Dr. Detlef Knappe, of widespread PFAS contamination in the Cape Fear River watershed in NC underscores that these compounds are in need of immediate investigation.. The goal of our Center is to advance understanding about the environmental and health impacts of PFAS. To meet this goal we are employing a highly trans-disciplinary approach that will integrate leaders in diverse fields (epidemiology, environmental science and engineering, biology, toxicology, immunology, data science, and advanced analytics); all levels of biological organization (biomolecule, pathway, cell, tissue, organ, model organism, human, and human population); state-of-the-art analytical technologies; cutting-edge data science approaches; a recognized track record in interdisciplinary, environmental health science (EHS) training; and well-established partnerships with government and community stakeholders.
Bridge girder cross-sections continue to become regional in nature, with many state DOTs adopting their own unique sections at either the state or regional level. Typically, girders are developed without consideration of a formal ÃƒÂ¢Ã¢â€šÂ¬Ã‹Å“optimizationÃƒÂ¢Ã¢â€šÂ¬Ã¢â€žÂ¢ of cross-section shape, or when any optimization was employed, the process of optimization and hence its outcome posed several limitations. For example, in many cases, the optimization focused on a single girder without considering any deck on it, whereas the lateral spacing of girders and thickness of the overhead deck are design variables which should be considered while optimizing the girder. Also, such optimization was often based on local search algorithms that do not guarantee global optimality, especially when the solution space is multi-dimensional and highly nonlinear. In most instances, optimization process only included ÃƒÂ¢Ã¢â€šÂ¬Ã‹Å“quantifiableÃƒÂ¢Ã¢â€šÂ¬Ã¢â€žÂ¢ factors like material cost, volume or weight, labor cost, and formwork cost, etc. But solutions that are mathematically optimal with respect to the quantified factors are not necessarily and readily acceptable when considering non-quantifiable factors and preferences pertaining to practical and field implementation issues. Hence, it is important to extend the optimization procedure to enable outcomes from a formal optimization to be integrated with important subjective considerations. The objective of this research is to develop and apply contemporary meta-heuristic global search procedures for optimizing pre-tensioned decked bulb-tee girders for systematically identifying new optimized cross-section shapes. It is envisioned that, for a specific girder span length and a number of lateral girders, several maximally different alternative cross-sections with competitive structural and cost performance will be first identified; this will be repeated for different combinations of girder spans and numbers of girders to analyze and develop structural and cost performance characteristics variation with girder span length. Then in consultation with AKDOT and precast manufacturers, the alternative optimized cross-section shapes will be screened and fine-tuned based on practical considerations to identify a small set of ÃƒÂ¢Ã¢â€šÂ¬Ã‹Å“best feasibleÃƒÂ¢Ã¢â€šÂ¬Ã¢â€žÂ¢ cross-section shapes. The cross sections to be explored here will be compared for structural performance and material savings against existing ÃƒÂ¢Ã¢â€šÂ¬Ã‹Å“optimizedÃƒÂ¢Ã¢â€šÂ¬Ã¢â€žÂ¢ sections as well as various legacy sections used by Alaska DOT (existing decked-bulb-tee section), and sections employed elsewhere around the US (i.e., AASHTO girders, PCI Bulb-Tees). Preliminary exploratory analysis will be conducted to study the effects of optimized cross-section shapes on extending the girder spans and reducing the number of spans, and therefore the approximate (empirically estimated) net life-cycle cost savings of the bridge system considering the number of piers, foundations, abutments, etc. We expect the outcomes of this project will potentially benefit the AKDOT in improving the ability to span longer distances, reducing overall bridge construction cost, and using resources more efficiently.
The overall objective of the proposed project is to evaluate the environmental impacts (including greenhouse gas emissions) for three options for managing Montgomery Countyâ€™s residual municipal solid waste (MSW). Option 1: Disposal at an out-of-state landfill, with transportation by truck, rail, or both. Option 2: Disposal at a new in-county landfill to be constructed on the Countyâ€™s Site 2 properties in Dickerson, MD with transportation by rail, truck, or both. Option 3: Management at the Countyâ€™s existing mass burn waste-to-energy (WtE) facility in Dickerson, Montgomery Count, Maryland with transport by rail.
Floods impact a series of interconnected urban systems (referred to in this project as the Urban Multiplex) that include the power grid and transportation networks, surface water and groundwater, sewerage and drinking water systems, inland navigation and dams, and other system, all of which are intertwined with the socioeconomic and public health sectors. This project uses a convergent approach to integrate these multiple interconnected systems and merges state-of-the-art practices in hydrologic and hydraulic engineering; systems analysis, optimization and control; machine learning, data and computer science; epidemiology; socioeconomics; and transportation and electrical engineering to develop an Urban Flood Open Knowledge Network (UF-OKN). The UF-OKN will be built by bringing together academic and non-academic researchers from engineering, computer science, social science, and economics. The UF-OKN is envisioned to empower decision makers and the general public by providing information not just on how much flooding may occur from a future event, but also to show the cascading impact of a flood event on natural and engineered infrastructure of an urban area, so that more effective planning and decision-making can occur.
Leakage in bulk water pipelines is a major problem for many water utilities as it leads to significant economic losses and cause service disruptions threatening public safety. Most utilities currently employ intrusive methods based on acoustic or infrared signals that can be expensive, time consuming, and require trained personnel. Non-intrusive methods that currently exist require significant computational resources and are not suitable for real-time application. We have developed extremely fast leakage detection algorithms that are suitable for real-time application. These methods rely on a hydraulic model and routine pressure measurements and were developed as part of an NSF project funded from 2011-2016. In partnership with DC Water, Lakewood City (CA), TAGO (an Internet of Things (IoT) company based in Raleigh, NC), and Citilogics (a smart water analytics company based in Cincinnati, OH) we will conduct a proof-of-concept study for isolated sections of each utilitiesÃƒÂ¢Ã¢â€šÂ¬Ã¢â€žÂ¢ water networks. Data from existing pressure sensors as well as new sensors installed at strategic locations in the network will be used to validate our algorithms using experimentally simulated leakage scenarios. Citilogics will provide necessary expertise and software for processing the real time data suitable for inputs into the hydraulic model from AMI, SCADA, and CMMS systems. TAGO will build an IoT framework for acquiring the pressure data (from sensors) in real-time and for integrating our algorithms and associated filters on cloud resources. Partner utilities will install the pressure sensors as needed and execute the experiment. NCSU will design the experiment, build the hydraulic model and the leak detection analytics, test the IoT architecture, and evaluate the potential for commercialization.
Recent surveys of the national water industry warn of looming costs for capital improvements for drinking water systems in the coming decades [1,2]. One AWWA report estimates that over $1 trillion are needed over the next 25 years, and $1.7 trillion over the next 40 years; about half of this investment would cover the renewal and replacement of aging pipes, and half would pay for system expansions to accommodate population changes . At the same time, SCADA and sensor systems, monitoring and modeling software are facilitating real-time operational decision making in water utilities as never before. These short-term operational decisions, as well as capital improvements such as system expansions, equipment or technology upgrades, and price structures, affect system performance with respect to long-term master planning goals such as system resilience, cost and resource sustainability. Currently, no systematic decision support methodologies exist to optimize the timing of the needed investments over the 25 or 40 year horizon, assessing the criticality of these decisions for overall system vulnerability and resource optimization. The proposed project aims to build a resilience modeling framework using a water utilityÃƒÂ¢Ã¢â€šÂ¬Ã¢â€žÂ¢s in-house data and models to bridge the gap between short-term operations and the medium- and long-term decisions that influence master planning objectives such as system resilience. The objectives of this research are: develop a general purpose resilience modeling framework that integrates computational tools and data to expand the optimization capacity of available data and infrastructure component models from short-term operational to long-term planning horizons; build, demonstrate and test the modeling framework using a case study water utilityÃƒÂ¢Ã¢â€šÂ¬Ã¢â€žÂ¢s data and models to provide in-house decision support for optimal timing and balance between short-term performance and long-term objectives; and develop an open-source water system resilience library that is compatible with a standard resilience modeling language and water infrastructure system modeling tools.
The last decade saw a series of catastrophic floods due to hurricanes and storms of increased intensity, and news headlines like Cities Swimming in Raw Sewage After Storm Expose Flaws in System became commonplace. These events exposed the fault lines in flood management. Perhaps more importantly, they also revealed the complex and interconnected nature of engineered, natural and social systems that form the fabric of modern cities. These systems can be conceptualized as a network of networks, or a multiplex, that includes the power grid and transportation network, surface water and groundwater, sewerage and drinking water systems, inland navigation and dams, intertwined with the socioeconomic and public health sectors. Under external pressures and improper management, failures propagating across the Urban Multiplex became obvious - as if viewed under a magnifying glass. Extreme weather is a primary driver of flooding. Its consequences however depend on the interconnectedness of the multiplex components that are, unfortunately, typically designed and/or analyzed independently of one another. For example, a power outage may lead to failure of a storm water network designed to carry the maximum flow during floods, resulting in raw sewage overflow into streets and exposing humans to pathogens. At the same time, storm water overflows could flood critical segments of road networks designed to meet traffic needs, preventing timely evacuation of vulnerable populations. Thus, it is impossible to effectively handle increasingly frequent urban floods by managing these components independently from one another, and ignoring the inherent interconnections of the urban multiplex. Rather, a convergent approach that integrates all interconnected systems and merges state-of-the-art in hydrological and hydraulic engineering; systems analysis, optimization and control; artificial intelligence, data and computer science; epidemiology; socioeconomics; transportation and electrical engineering is proposed in this research.
The primary goal of this proposed Science Across Virtual Institutes (SAVI) effort is to establish a self-sustaining virtual institute to enhance research, education, and outreach related to life-cycle assessment (LCA) of solid waste management (SWM) systems.
The US EPA is interested in developing a next generation tool for sustainable materials management as an update to the current Municipal Solid Waste Decision Support Tool (MSW DST). As part of this task, RTI International (RTI) will conduct a review the current SWOLF software tool being developed at North Carolina State University (NCSU) and assess the work required to convert the tool into a stand-alone desktop application, similar to the MSW DST.
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.