Biological Systems Engineering
DEVELOPING AN INTEGRATED MODEL FOR THE CORN, ETHANOL, AND BEEF SYSTEMS USING A LOOSELY COUPLED WEB FRAMEWORK
Date of this Version
Anderson, Ryan (2018). Developing and integrated model for the corn, ethanol, and beef systems using a loosely coupled web framework (Masters Thesis). Retrieved from Digital Commons.
With the global population approaching 9 billion people by the year 2050, the world’s food, energy, and water (FEW) resources must be used more intelligently to provide for everyone. While we understand how individual FEW systems behave using modeling, we cannot understand the full environmental and production impacts of decisions in each system without understanding how they are all linked together. An approach to coupling these systems is starting with identifying a few highly interconnected FEW systems. The corn, ethanol, and beef systems are large economic and agricultural drivers in the Midwest United States and are highly linked. Many individual models exist for each system and are wrapped in software to be used for decision support. This thesis explores the integration of the corn, ethanol, and beef systems by connecting existing models using a loosely coupled web framework. Each model is wrapped in Python code and linked, also in Python, using connections that reflect the real world system. Environmental impact of the full integrated system is done using life cycle assessment that accounts for inputs and outputs for each model. Simulations done with the models predict the resource production of the integrated system given user inputs and the full environmental impacts in water use, energy use, and greenhouse gas emissions. The objectives of this thesis are: (1) to review literature of FEW nexus integration by coupling models, (2) integrating the crop and biofuel systems with service-oriented architecture, and (3) integrating the corn, ethanol, and beef systems with service-oriented architecture. Scenario analyses are done to test the models’ responses to different management, climate, and resource demand scenarios.
Advisors: Jeyamkondan Subbiah and Deepak Keshwani
Bioresource and Agricultural Engineering Commons, Operations Research, Systems Engineering and Industrial Engineering Commons
A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Master of Science, Major: Agricultural and Biological Systems Engineering, Under the Supervision of Professor Jeyamkondan Subbiah and Professor Deepak Keshwani. Lincoln, Nebraska: June 15th, 2018
Copyright (c) 2018 Ryan Anderson