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Research Activities

Overview

Integration of systems analytic methods and high performance computing paradigms to model, analyze and solve complex engineering problems involving design, planning, management, and decision making.

Research Topics

  • Water Supply Sustainability and Adaptive Watershed Management
    Flow alteration-driven ecological impacts in watersheds due to land-use and climate change effects are being modeled and studied, using multi disciplinary research in Computing & Systems/Water Resources, to develop contemporary data and modeling tools in integration with optimization methods to support water sustainability and adaptive watershed management.

    The focus of this research is to model and analyze integrated water supply systems for identifying ways to best meet the demand with the available supply aided by streamflow forecasting and pro-active conservation measures. This research attempts to address questions such as: What are climate change & land use development impacts on hydrologic flows?; How to identify sustainable watershed management strategies?
    (Collaborators: Arumugam, Brill)

  • Leak Detection in Water Distribution Infrastructure
    Computing & Systems/Water Resources research investigations are playing a key role in helping to detect leaks in water distribution networks by integrating hydraulic simulation models and infrastructure data with contemporary analytical methods that are enabled by high performance computing technologies.

    This research attempts to address questions such as: What pipe network infrastructure data and what types of measurements help to assess leaks? How to use these information bases to identify leak locations and related characteristics?; What analytical and computational techniques are needed to reliably and robustly detect the leaks?
    (Collaborators: Brill, Mahinthakumar)

  • Water Distribution Contamination Threat Management
    Computational and analytical procedures in sync with modern search algorithms developed by this Computing & Systems/Water Resources research team have resulted in efficient and effective decision-support tools to identify sources of contamination in groundwater aquifer systems and water distribution networks.

    This research attempts to address questions such as: How to use sensor information to identify contamination source location and mass loading history?; How does the accuracy and precision of source characterization depend on design choices, including the number and type of sensors, error and uncertainty in data and measurements?
    (Collaborators: Brill, Mahinthakumar)

  • Integrated Water Supply Infrastructure Systems Planning and Design
    (Collaborator: Knappe)

  • Energy and Environmental Sustainability of Buildings
    Computing & Systems/Energy/Architecture researchers are innovating a sustainable building design approach by coupling simulation and building information models with analytical and optimization methods to integrate architectural and engineering design processes such that the energy efficiency of buildings can be enhanced at every stage of building design.

    This research attempts to address questions such as: How can the current building design process be improved to consider energy and environmental performance at all levels of design?; How best to couple Building Information Models (BIMs) with building performance models to inform throughout the design process about the overall performance of a building while enhancing the creative as well as the performance aspects?
    (Collaborators: DeCarolis, Hill (Architecture), Cho (Architecture), Chvatal (U of Sao Paulo, Brazil))

  • Resilient Civil Infrastructure and Natural Systems Considering Natural Hazards
    The activities of this research focus on understanding the effects of natural disasters on built and natural environments, and identifying engineering solutions to advance the resilience of civil infrastructure and natural systems. Mathematical modeling and computational procedures are being developed and used by Computing & Systems researchers to quantify the resilience of a civil infrastructure system (CIS) in supporting lifeline services that are collectively enabled by the components of that CIS. Founded on these research results, the system-wide resilience metrics are combined with decision models and search algorithms to prioritize infrastructure investments to improve lifeline service resilience considering storm hazards and their impacts on the civil infrastructure systems.
    (Collaborators: Baugh, Brill)

  • Integrated Solid Waste Management (ISWM) and Environmental Sustainability
    SWOLF
    Through development and innovative interfacing of data, measurements, analytical and decision models, and search algorithms for optimization, a multi disciplinary Computing & Systems/Environmental Engineering research team has developed, tested and applied one-of-a-kind life-cycle-based municipal solid waste management decision-support tool for generating integrated waste management plans that consider cost, energy and material consumption, environmental impacts and potential carbon prices. Recent work extends this approach to investigate effectiveness of e-waste management considering their implications on the supply chains for electronics manufacturing.

    This research attempts to address questions such as: What are life cycle cost and emissions implications of alternative ISWM strategies?; How to identify effective ISWM strategies to meet budget and environmental targets?; How will potential greenhouse gas mitigation policies affect technological choices and ISWM strategies?
    (Collaborators: Barlaz, DeCarolis, Levis, Kemahlioglu Ziya (Poole College of Management))

  • Design and Life-Cycle Analysis of Photo Synthetic Bio Reactors (PSBRs) for Microalgae-based Biofuels
    (Collaborators: de los Reyes, Ducoste, Levis, Grunden (Plant & Microbial Biology), Sederoff (Plant & Microbial Biology))

  • Development of Heuristic Search Methods for System Optimization and Analysis
    • Algorithms for Design Innovation
      Investigation of search algorithms to identify alternatives that consist of unusual combinations of design choices but with similar design performance, potentially creating innovative solutions to engineering design problems.
    • Asynchronous Hierarchical Parallel Evolutionary Algorithms
      Development of evolutionary algorithms that are not only designed for decentralized distributed search while maintaining solution diversity, but also structured for computationally parallel implementations considering memory and communication arrangements in modern high performance computing architectures.
    • Multi Objective Evolutionary Algorithms
      Development and testing of evolutionary algorithms for identifying the Pareto optimal solutions for multiobjective problems.
    • Model Error Correction Procedures
      Development and testing of quantitative methods to improve the predictability of simulation models by accounting for automatic parameter calibration and model error correction.

 

List of Projects and Abstracts

SAVI: International Institute for Solid Waste Management Life-Cycle Modeling
Barlaz, DeCarolis, Levis, Ranjithan
NSF
08/2014-08/2017

EFRI-PSBR: Closing the Loop -- Towards a PSBR Design Framework for Self-Sustained Marine Microalgal-Based Fuel Production
Grunden, Sederoff, de los Reyes, Ducoste, Ranjithan
NSF
09/2013-09/2017

An Adaptive Leak Detection And Risk Analysis Framework For Urban Water Distribution Systems
Mahinthakumar, Brill, Ranjithan
NSF
08/2011-08/2015
Abstract:
The primary goal of this project is to understand how routine measurements of pressure, flow and water quality data could be used to characterize leaks and contaminant intrusion in urban water distribution systems and illustrate how this information could be used to aid in the risk assessment of these systems.

The Environmental Sustainability of Integrated Solid Waste Management in a Carbon Constrained World
DeCarolis, Barlaz, Ranjithan
NSF
08/2010-08/2015
Abstract:
Given the complexity of climate change mitigation, there is significant potential for unintended consequences. This is particularly true in regard to SWM, which consists of complex relationships among a multitude of individual processes as well as competing management objectives. We hypothesize that as the cost of energy and GHG emissions increase in response to GHG policy, the relative cost-effectiveness of SWM options will change, consequently altering the optimal waste material flows as well as technology and process selections in future SWM programs. This proposal aims to answer the following: Given that future SWM is likely to be driven by the price effects of a GHG policy, how will GHG emissions and other pollutant discharges be affected and what are the key tradeoffs among them? Rigorous analysis of SWM system response under a GHG mitigation policy requires a modeling framework that links detailed process-level operations to an aggregate SWM strategy and to the larger energy system. The proposed framework will include an integrated life-cycle optimization model to estimate the costs, energy use, emissions, and environmental impacts associated with SWM processes. The framework will be used to achieve the following objectives: analyze technology choices at the process level, evaluate changes in integrated SWM strategies (i.e., waste flows and process choices) that most effectively respond to different GHG policies, characterize the effects of specific SWM policies (e.g., recycling targets, landfill bans) on management alternatives in a GHG-regulated environment, quantify effects of these policies on other SWM-related environmental impacts, and quantify tradeoffs among different environmental impacts. The effects of uncertainty in model parameters and inputs will be systematically considered.

Integrated Solid Waste Management and Its Environmental Sustainability in a Carbon Constrained Environment
Barlaz, DeCarolis, Ranjithan
Environmental Research & Education Foundation
01/2010-12/2014
Abstract:
The goal of the proposed research is to develop a life-cycle assessment (LCA) model capable of analyzing solid waste management (SWM) performance, at both the individual process and integrated system levels, taking into account implications of greenhouse gas (GHG) mitigation policies and competing SWM objectives (e.g., costs, emissions, and diversion targets). An integrated life-cycle optimization model will be developed to estimate the costs, energy use, emissions, and environmental impacts associated with the processes (e.g., collection, separation, waste-to-energy [WTE], composting, anaerobic digestion, landfilling) that constitute the SWM system. The model will be used to meet the following objectives: 1. Quantify the increased costs associated with various SWM processes due to different GHG mitigation policies including anticipated energy price changes induced by these policies; 2. Evaluate changes in integrated SWM strategies (i.e., waste flows and process choices) that most effectively respond to different GHG mitigation policies; 3. Quantify the effects of GHG mitigation policies and related energy price changes on other SWM-related environmental impacts (e.g., smog formation and acidification).

DHS Homeland Security HS-STEM Career Development Grants (CDG)
Ranjithan, Baugh, Brill, Gabr, List, Overton, Seracino
DHS
09/2009-09/2013
Abstract:
The purpose of this proposal is to establish a graduate research fellowship program to train students to be future leaders in the area of engineering of resilient civil infrastructure systems for coastal regions considering natural hazards. This program will be conducted in coordination with the ongoing DHS Center of Excellence on Natural Disasters, Coastal Infrastructure and Emergency Management.

Improving Water Resources Sustainability Utilizing Multi-time Scale Streamflow Forecasts
Arumugam, Ranjithan
NSF
03/2008-02/2012
Abstract:
This project has three major objectives. The first is to develop an integrated approach to promote sustainable management of water supply systems through combined application of both weather information-based near-term streamflow forecasts and climate-based short-term streamflow forecasts. For this first objective, water management measures will be invoked that include water conservation and hedging, water contracts for improving water-use efficiency, in-stream and ecological flow protection and alternative water management plans including wastewater reuse. The second major objective is to apply and demonstrate the approach for two water supply systems, one serving an area experiencing rapid increase in water demand in North Carolina, and another aimed at maximizing hydropower production and preserving ecological flows in Virginia. The third major objective is to develop an instructional tool for assessing the role of proactive water management measures and multitime scale forecasts to promote sustainable water management and to incorporate it in undergraduate/graduate curricula at several universities. An educational outreach effort will inculcate dynamic risk management and sustainability concepts in water and environmental curricula at two major historically black colleges in North Carolina.

Building Design Process Innovation for Enhancing Energy and Environmental Sustainability
DeCarolis, Hill (Architecture), Ranjithan
NCSU Strategic Research Initiative
05/2010-08/2011
Abstract:
Current design process is typically driven by informed trial-and-error rather than quantitative building-specific performance data, which makes design for sustainability difficult. We hypothesize that the availability of targeted building performance data through the full breadth of the architectural design process will lead to innovative designs that improve the use of energy, water, and materials during both building construction and operation. The goal of this research is to evaluate a human-computer joint cognitive design process, allowing architects to couple building information models (BIM) with building performance analysis to create a progressive decision-making framework for building design. An approach to find good configurations of building options to meet performance objectives specified at any stage of the design process will be investigated. This search will explore an array of alternatives that underscore the multiplicity of design possibilities available to match the design objectives.

Engineering the Civil Infrastructure For Enhanced Resilience of the Built and Natural Environments
Baugh, Brill, Gabr, List, Overton, Ranjithan, Seracino
DHS
07/2008-06/2011
Abstract:
The dynamic evolution of landforms under stress can lead to catastrophic loss of either functionality or of mass itself. This project will examine the dynamics of landforms undergoing a transition from one state to another (e.g., barrier island collapse, wetland loss, dune erosion) in order to determine critical defining features of the resilient natural and developed landforms. This descriptive dynamic will be translated into design parameters for restoration of protective or beneficial landforms (e.g., beaches, dunes, barrier islands, wetlands). In addition, this analysis will be used to provide improved metrics for communicating hazard and risk as well as incorporating hazard and risk into land use plans. This project lies at the interface between Coastal Hazards Science and Planning for Resilience focus areas and has the potential to provide insights to the Hazards, Human Behavior and Economic Resilience focus area.

DDDAS-TMRP (COLLABORATIVE RESEARCH): An Adaptive Cyberinfrastructure for Threat Management in Urban Water Distribution Systems
Brill, Mahinthakumar, Ranjithan, Harrison (Univ of SC), Uber (Univ of Cincinnati), von Laszewski (Univ Chicago/Argonne Natl Lab)
NSF
01/2006-12/2009
Abstract:
The goal of this multi-disciplinary research is to develop a cyberinfrastructure system for water distribution system threat management that will both adapt to and control changing needs in data, models, computer resources and management choices facilitated by a dynamic workflow design. Using virtual simulation and a field study, this cyberinfrastructure will be tested on illustrative scenarios for adaptive management of contamination events in water distribution systems.

Application of Municipal Solid Waste Decision Support Tool to Wake County, North Carolina
Barlaz, Ranjithan
US EPA
01/2005-08/2009
Abstract:
This project intends to conduct an integrated solid waste management study for Wake County, NC. Working in coordination with the county solid waste staff, this study would be conducted to obtain as much site-specific data as possible for input to NCSUÂ’s SWM-LCI (Solid Waste Management Life Cycle Inventory) model. This information will be processed for input data and strategy development to represent Wake County in the SWM-LCI model. This will take advantage of the existing model's flexibility to represent a site-specific scenario.

Assessment of Environmental Emissions associated with the Beneficial Reuse of Industrial, Commercial and Agricultural Wastes
Barlaz, Ranjithan
Delaware Solid Waste Authority
06/2006-08/2009
Abstract:
The objective of this research is to estimate the environmental benefits of the recycling and reuse of commercial, industrial and agricultural wastes generated in the State of Delaware.

ITR: A Prototype to Enable Near Real-time Environmental Characterization on the Grid
Mahinthakumar, Ranjithan, Karonis (NIU)
NSF
09/2003-08/2006
Abstract:
The overall goal of this project is to investigate formal computational approaches that can readily harness grid computing for the solution of environmental characterization problems. To this end, we will develop a grid-enabled software framework. Two alternative paradigms, based on the grid-enabled version of MPI and Java, respectively, will be explored. The framework will be applied to groundwater and air pollution problems, both of which are of prime societal importance. Acknowledging that, even within a grid environment, inverse problems are computationally challenging, model surrogates will be explored. Further, modeling to generate alternatives (MGA), a technique that identifies a set of good yet very different solutions, will be investigated for dynamically steering the search process through human-computer interaction. Alternatives generated via MGA will be used also to address the commonly encountered non-uniqueness issue in inverse problems.

Solid Waste Management Planning for the State of Delaware
Barlaz, Ranjithan
Delaware Solid Waste Authority
10/2003-12/2005
Abstract:
The objective of this project is to assist Delaware Solid Waste Authority (DSWA) identify long-term solid waste management (SWM) alternatives. Using a Life-cycle inventory (LCI) based SWM model that was developed at NC State University, a series of alternate SWM strategies will be analyzed with respect to cost, waste diversion from landfills, energy consumption and environmental emissions. Tradeoff information will be generated to examine the incremental cost of increased recycling, decreased dependence on landfills and reduced emissions. A variety of options, including curbside recycling, composting, combustion, and in-state disposal or out-of-state landfill disposal, for managing waste will be considered. The results from this research are expected to provide valuable input to the DSWA staff as they develop and evaluate future SWM plans for the State of Delaware.

Urban Watershed Management Tools
Ranjithan
US EPA/MCNC
10/2001-9/2004
Abstract:
U.S. EPA's Multimedia Integrated Modeling System (MIMS) provides a unified computing framework to simulate the cycling of environmental pollutants within and across all media. The processes associated with urban storm water runoff and wastewater discharge are to be available for simulation in MIMS. The simulation models are to be coupled with systems analytic methods (including uncertainty analysis and optimization-based search procedures) to explore and identify efficient strategies to manage the urban runoff related problems. In addition, decision-makers require cost/benefit tradeoffs and reliability associated with different strategies. The objective of this project is to integrate urban watershed decisions support tools into MIMS, and demonstrate their use. Related goals include integration of an appropriate urban storm water model into MIMS, and testing the broader applicability of the decision support tools for use with other process simulation models, including US EPA's Storm Water Management Model (version 5).

NSF CAREER Award: Development of a Computer-Based Methodology to Assist in Environmental Systems Analysis and Decision Making and Its Applications in Watershed Management
Ranjithan
National Science Foundation
5/1998-4/2003
Abstract:
This project will: 1) investigate ways to enhance the capabilities of genetic algorithms (GAs) for complex environmental systems analysis, 2) develop and integrate into existing courses an interactive training module to assist in teaching the fundamentals of GAs and their uses in environmental systems analysis, 3) explore applications of the methodology in watershed management and 4) integrate the applications and their findings in courses related to environmental systems analysis. The academic plans include the development of teaching modules and interactive techniques for both students and practitioners. To demonstrate the practical applicability, an array of realistic watershed management applications will be investigated, including a case study of the Neuse River Basin in North Carolina.
Key Words watershed management, BASINS, modeling, evolutionary computation, genetic algorithms, uncertainty, decision support, TMDL, planning and management

Enhancements to the Strategy Development Tool to Support Regulatory Analysis
Baugh, Brill, Loughlin, Ranjithan
North Carolina Department of Environment and Natural Resources - Division of Air Quality
9/1998-12/2001
Abstract:
The Strategy Development Tool (SDT) is a prototype decision support system for air quality management. Components of the SDT include tools for: 1) visualizing emissions inventories, 2) designing and testing control strategies, 3) modeling the costs and impacts of incentive-based control approaches such as emissions trading programs, and 4)identifying low-cost management alternatives through optimization. The goal of this project is to upgrade the features of the SDT so that it can be used by the State of North Carolina in developing state implementation plans towards meeting the Federal air quality standards.
Key Words air quality management, modeling, evolutionary computation, genetic algorithms, optimization/search procedures, uncertainty, decision support, planning and management, control strategy development

Development of an integrated systems model to explore environmentally beneficial alternatives for product manufacturing and waste management
Barlaz, Ranjithan
National Science Foundation
10/1998-10/2001
Abstract:
As societies become more focused on minimizing the impact of human activity on the environment, many industries are trying to move towards environmentally responsible manufacturing practices. The objective of this work is to develop a model, integrating a product life-cycle inventory (LCI) with a newly developed life-cycle model of waste management alternatives to examine how the combined LCIs are important and can be influential in product decision making. An integrated systems model will be developed to represent life cycle considerations of products from manufacturing through waste management. The model will then be illustrated through a series of case studies.
Key Words solid waste management, modeling, life cycle analysis, mathematical programming, optimization, uncertainty, planning and management

Advancement of Environmental Decision Support Systems through HPCC
Baugh, Brill, Ranjithan
US EPA
9/1996-9/1999
Abstract:
The goal of the proposed research is to overcome the current computational resource limitations by developing Decision Support System (DSS) tools for use within a high performance distributed computing and communications (HPCC) environment. There are four research objectives: 1) to explore the role of optimization techniques in a DSS framework for complex environmental problems; 2) to examine ways of making better use of existing and expected future computational power to increase performance, 3) to continue the development of better DSS prototypes as true joint-congnitive systems, and 4) to evaluate each prototype's performance and user interface with respect to user needs.
Key Words air quality management, modeling, evolutionary computation, genetic algorithms, optimization/search procedures, uncertainty, decision support, planning and management, control strategy development, high performance computing

Models for Evacuation Planning and Network Analysis System
Ranjithan, Rouphail
Lockheed Martin Energy Systems, Inc./Oak Ridge National Laboratory
6/1996-5/1999
Abstract:
This research is directed at developing network-specific evacuation plans for dynamic incidents. The focus is on the development of algorithm that can produce minimum evacuation times over a highway network subject to constraints on shelter locations and capacity, and link capacity. Models will be developed which consider the priority status of evacuation subzones, and selection of link reversals to expedite the evacuation process.
Key Words evacuation management, transportation planning and management, mathematical programming, network optimization

Assessing Pavement Layer Condition Using Deflection Data
Kim, Ranjithan
National Cooperative Highway Research Program, TRB
2/1997-4/2000
Abstract:
The objective of the research is to develop procedures to assess the condition of pavement layers based on deflection measurements. This research is concerned with all layers of rigid and flexible pavements that include an asphalt concrete surface layer. The proposed research approach describes a mechanistic-empirical method of developing a simple, practical deflection interpretation procedure for condition assessment of distressed pavement layers. Validation and implementation of this procedure will be conducted using data collected from distressed pavement sections in various locations in the United States.
Key Words nondestructive evaluation, artificial neural networks, pavement management

Nondestructive Evaluation of Structural Condition of Timber Piles
Kim, Ranjithan
North Carolina Department of Transportation
7/1997-12/1999
Abstract:
The principal objective of the proposed research is to develop a nondestructive test and analysis method, that can be readily implemented, for determining structural condition of installed timber piles using the stress wave test method currently used by NCDOT for the evaluation of in-place length of timber piles. The outcome of this research will be a comprehensive stress wave testing system that can quantitatively evaluate the structural condition of installed timber piles. Test results obtained from this system will enable NCDOT calculating the load bearing capacity of deteriorated timber piles. The resulting system will be a user-friendly analysis program that can be used for routine inspection of timber piles.
Key Words nondestructive evaluation, artificial neural networks, transportation infrastructure management

An Environmental Assessment of Management Alternatives for Municipal Solid Waste
Barlaz, Brill, Ranjithan
Research Triangle Institute
8/1995-4/2000
Abstract:
Research is in progress to evaluate the cost and life-cycle inventory (LCI) of municipal solid waste management alternatives. The overall objective of the research is to develop a user-friendly decision support system prototype to identify efficient alternatives for solid waste management (SWM) in consideration of the cost and LCI parameters. The decision support tool will utilize a combination of a site-specific user input data and default data to identify SWM strategies that are optimal with respect to a given objective such as cost, energy consumption, or the emissions of a number of air pollutants including NOx, Sox, CO and particulates. Components of the decision support system include process models for each solid waste unit operation included in the management system, a mathematical model of the SWM system, an optimization routine and a graphical user interface. The SWM system includes waste collection and transfer, recycling, composting, waste-to-energy, refuse derived fuel, anaerobic digestion and landfills. In addition, an offset analysis is used to include manufacturing processes associated with the conversion of recycled materials to new products.
Key Words solid waste management, modeling, life cycle analysis, mathematical programming, optimization, planning and management

Interpretation of FWD Data When Pavement Layers Are Not Intact
Kim, Ranjithan
North Carolina Department of Transportation
7/1995-7/1997
Abstract:
The falling weight deflectometer (FWD) is a principal means of evaluating the structural condition of pavements. Effort has been made to interpret FWD deflection basins for determining rehabilitation strategies and overlay thickness. This research interprets FWD information for condition evaluation of flexible pavements. The objectives are: 1) to determine the effects of cracked or broken layers in flexible pavement systems based on FWD deflection basins; 2) to develop a method for determining the layers in the existing pavement structure at which rehabilitation must be directed; and 3) to verify the recommended procedure using the deflection measured from cracked pavements with known conditions.
Key Words nondestructive evaluation, artificial neural networks, pavement management

A Decision Support System for Highway Construction Considering Environmental Impacts
Ranjithan, Rouphail
Center for Transportation and the Environment
8/1995-12/1997
Abstract:
This project represents a collaborative research with the Technical University of Lisbon, with support from the Portuguese-American Foundation (FLAD) and the Center for Transportation and Environment (CTE). The project is designed to develop a decision support system (DSS) for scheduling highway construction projects in a metro area, subject to annual budget, resource and precedence constraints. The Lisbon Metropolitan Area will be the case study for the development and application of the DSS.
Key Words transportation planning and management, mathematical programming, optimization

Decision Support Systems for Air Pollution Management
Baugh, Brill, Ranjithan
US EPA via MCNC-North Carolina Supercomputing Center and Industrial Extension Service
9/1993-9/1996
Abstract:
The capabilities of high-performance computing systems are often used to build analysis models with increasing detail and realism. However, these computing resources also provide a key technological component for interactive decision support systems. This project explores the design and development issues necessary to create computer systems that support open ended, iterative decision making processes. A wide range of support system tools will be considered for use in such a system, including mathematical optimization, genetic algorithms, neural networks, and formal methods to examine tradeoffs among multiple objectives and to generate alternative solutions.
Key Words air quality management, control strategy development, mathematical programming, evolutionary computation, optimization, high performance computing, decision support

Design of Animal Waste Management Strategies to Achieve Regional Environmental Objectives
Classes, Liehr, Ranjithan
Abstract:
The replacement of anaerobic lagoons that are currently used for swine waste management in North Carolina is expected to be expensive. Recent initiatives calling for such actions have increased the need for characterization of the cost and treatment effectiveness of each alternative, which potentially depends on the location and size of the farm. Thus, identification of the most effective solution to achieve collective target reductions in discharge levels needs an integrated approach that examines and searches among these technology alternatives at all farms simultaneously. The objective of this research is to develop collective or regional management strategies that will aid policy makers, planners, and farmers in making cost effective lagoon replacement decisions to achieve desired treatment and public protection goals. A major component of this activity is the implementation of a cost and treatment efficiency assessment tool (CAWSST) to evaluate alternative animal waste treatment technologies. Building upon the outputs of CAWSST and existing databases, formal optimization techniques to search for good solutions with respect to different goals are being developed. This procedure is presented. In an illustrative example that is used to describe the application of this approach, GIS based data for the farms within the Lower Neuse River Watershed are used. Farm sizes are inputted to CAWSST, and the outputs, together with additional GIS data such as farm locations, are then used in a mixed-integer programming model that helps us examine different management scenarios for the region. We optimized for cost while meeting constraints such as pollutant discharge targets, farm proximity to floodplains, risk levels, or the effect of odor on the area. Example scenarios include the least cost solution, uniform treatment for the whole watershed area, and uniform treatment within certain zones defined by such factors as political boundaries, farm size, type of farming operation or proximity to floodplains.
Key Words animal waste management, treatment technology modeling, mathematical programming, optimization, planning and management

Improving Performance of Water Treatment Plant Operations through Optimization
Knappe, Ranjithan
Abstract:
The primary focus of this research is to develop and test computer-based decision support tools to assist in improving the performance of drinking water treatment plants in the presence of variability and uncertainty. Two aspects of the plant operations are targeted. One, the unit process choices at the plant design stage, and two, the process control settings during daily operations. This investigation attempts to identify, based on pilot studies, these choices such that the overall reliability in meeting effluent conditions is increased. The first phase of this research implemented a procedure based on artificial neural network (ANN) models of unit process trains. Data from a pilot plant was used to test and validate this modeling approach. This ANN-based model was then coupled with a systematic search procedure to identify effective process control choices for controlling turbidity. This procedure is then applied to identify effective process controls to achieve the desired effluent targets assuming deterministic conditions. The performance of these controls, however, is unpredictable in the presence of variable or uncertain influent conditions, measurement errors, and uncertainty in process performance. Applying excessive treatment to build in a safety factor is an option to avoid potential failure to meet effluent targets, but at a significant increase in cost. A systematic consideration of uncertainty is needed to address this problem. Ongoing work investigates ways to characterize the uncertainty in the plant performance, and to identify cost-effective operational controls that improve the robustness in the performance of water treatment plant operations.
Key Words water treatment, artificial neural networks, mathematical programming, optimization, uncertainty

Decision-making under uncertainty: A New Quantitative Method-Bayesian Programming
Harrison, Ranjithan
Abstract:
Our understanding of environmental processes is fraught with uncertainty. Nevertheless, environmental decision-makers must decide a course of action to follow. Often, the question of what to do is falsely framed as having to decide between taking immediate action or to gather more data before addressing the problem. In fact, of course, both actions can be pursued simultaneously. Surprisingly, however, there are few numerical approaches available to explore such options. Of the methods for decision-making under uncertainty that are available, nearly all are either not theoretically sound or are applicable only to the simplest of problems. This poster introduces a new method for decision-making under uncertainty that addresses many of the limitations of existing approaches. In addition to uncertainty, the methodology can be used to address a range of related issues typically encountered in environmental modeling, including the stochastic behavior of environmental systems, and irreversibility. The method, Bayesian Programming (BP), utilizes optimization techniques for an efficient search of the alternatives and incorporates Bayesian methods to model uncertainty reduction as data is collected. The methodology is illustrated with a simple example. Finally, the strengths and limitations of the method are discussed. The technique is expected to increase the decision-maker's ability to address uncertainty.
Key Words uncertainty, decision analysis, optimization, Bayesian methods, heuristic search procedures