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Decision support for biomass feedstock production enabled by concurrent science, engineering and technology (ConSEnT)

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Title: Decision support for biomass feedstock production enabled by concurrent science, engineering and technology (ConSEnT)
Author(s): Liao, Yung-Chen
Advisor(s): Ting, K.C.; Rodríguez, Luis F.
Department / Program: Engineering Administration
Discipline: Agricultural & Biological Engr
Degree Granting Institution: University of Illinois at Urbana-Champaign
Degree: M.S.
Genre: Thesis
Subject(s): Decision Support System Biomass Feedstock Production Concurrent Science and Engineering
Abstract: In the U.S., more than half of all energy comes from fossil fuels (59.99 of 108.41 quintillion joules) and close to 50% of annual fossil fuel (26.55 of 59.99 quintillion joules) is imported. Fossil fuels accounted for almost all carbon dioxide emissions (5814.4 of 5839.3 million metric tons) in 2008, which caused significant contributions to the accumulation of greenhouse gasses in the atmosphere. There is, thus, an urgent need to develop viable alternative energy options to address these concerns. It is because of this need that alternative energies have drawn such significant attention in the recent years. There are several potential alternative energy resources under consideration, but biomass-based energy is of particular importance given that it is currently available in large quantities. Specifically, lignocellulosic ethanol is considered among one of the leading alternative energy options in terms of sustainability and availability, and it is expected to replace a significant amount of fossil fuels in transportation sector. The supply chain of biomass-based biofuels is generally comprised of three major steps: (1) biomass feedstock production, (2) biofuel production, and (3) biofuel distribution. The goal of the biomass feedstock production system is the preparation of stable, affordable, and continuous biomass dry matter supply to satisfy the targeted displacement of 30% of petroleum used in transportation sector. In order to achieve this goal, an array of scientific discoveries and engineering developments must occur. The research described in this thesis seeks to ensure that an efficient pathway is utilized for the research and technology development of biomass feedstock production systems, such that science and engineering research can occur in concert with one another, supporting progress in both endeavors. This has been termed a Concurrent Science, Engineering, and Technology approach. A web-based environment for decision support has been designed and implemented for the planning, design, and management of biomass feedstock production. Concurrent Science, Engineering, and Technology is suitable for studying the complexity of biomass feedstock production because it integrates a systems model directly with an informatics platform, which assembles the latest information generated by research teams, and a web-based interface for integrating and utilizing these two resources in a real-time fashion. This web-based decision support system (DSS) has been named BPSys. It is programmed in the JavaTM (Oracle Corporation, Redwood Shores, CA) and integrates the functions of various software packages including: Apache HTTP Server (Apache Software Foundation, Forest Hill, MD), Apache Tomcat (Apache Software Foundation, Forest Hill, MD), Drupal (Drupal Association, Kortrijk, Belgium), MySQL (Oracle Corporation, Redwood Shores, CA) and JFreeChart (Object Refinery Limited, Harpenden, United Kingdom). The DSS is divided into in two parts: (1) the graphical user interface (GUI) of BPSys, a JavaTM applet, that will run on the user’s local machine and enables the user to work with the analytical model; and (2) an array of server side supporting programs, JavaTM servlets, that respond to requests from the graphical user interface and deliver information to the users. Through this platform, users can access the system via web browsers and design biomass feedstock production scenarios for analysis, retrieve the latest attributes describing the scenario, modify attributes, execute models, and save results. With the aid of the system, users can leverage the power of the simulation and analysis tools but are not bothered by how to build and run the models. By utilizing this platform, the latest knowledge and information regarding the biomass feedstock production system can be leveraged more effectively at the system level, allowing for seamless development of new innovative systems.
Issue Date: 2011-08-26
URI: http://hdl.handle.net/2142/26333
Rights Information: Copyright 2011 Yung-Chen Liao
Date Available in IDEALS: 2013-08-27
Date Deposited: 2011-08
 

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