Development of an optimization model for biofuel facility size and location and a simulation model for design of a biofuel supply chain

To mitigate greenhouse gas (GHG) emissions and reduce U.S. dependence on imported oil, the United States (U.S.) is pursuing several options to create biofuels from renewable woody biomass (hereafter referred to as “biomass”). Because of the distributed nature of biomass feedstock, the cost and complexity of biomass recovery operations has significant challenges that hinder increased biomass utilization for energy production. To facilitate the exploration of a wide variety of conditions that promise profitable biomass utilization and tapping unused forest residues, it is proposed to develop biofuel supply chain models based on optimization and simulation approaches. The biofuel supply chain is structured around four components: biofuel facility locations and sizes, biomass harvesting/forwarding, transportation, and storage. A Geographic Information System (GIS) based approach is proposed as a first step for selecting potential facility locations for biofuel production from forest biomass based on a set of evaluation criteria, such as accessibility to biomass, railway/road transportation network, water body and workforce. The development of optimization and simulation models is also proposed. The results of the models will be used to determine (1) the number, location, and size of the biofuel facilities, and (2) the amounts of biomass to be transported between the harvesting areas and the biofuel facilities over a 20-year timeframe. The multi-criteria objective is to minimize the weighted sum of the delivered feedstock cost, energy consumption, and GHG emissions simultaneously. Finally, a series of sensitivity analyses will be conducted to identify the sensitivity of the decisions, such as the optimal site selected for the biofuel facility, to changes in influential parameters, such as biomass availability and transportation fuel price. Intellectual Merit The proposed research will facilitate the exploration of a wide variety of conditions that promise profitable biomass utilization in the renewable biofuel industry. The GIS-based facility location analysis considers a series of factors which have not been considered simultaneously in previous research. Location analysis is critical to the financial success of producing biofuel. The modeling of woody biomass supply chains using both optimization and simulation, combing with the GIS-based approach as a precursor, have not been done to date. The optimization and simulation models can help to ensure the economic and environmental viability and sustainability of the entire biofuel supply chain at both the strategic design level and the operational planning level. Broader Impacts The proposed models for biorefineries can be applied to other types of manufacturing or processing operations using biomass. This is because the biomass feedstock supply chain is similar, if not the same, for biorefineries, biomass fired or co-fired power plants, or torrefaction/pelletization operations. Additionally, the research results of this research will continue to be disseminated internationally through publications in journals, such as Biomass and Bioenergy, and Renewable Energy, and presentations at conferences, such as the 2011 Industrial Engineering Research Conference. For example, part of the research work related to biofuel facility identification has been published: Zhang, Johnson and Sutherland [2011] (see Appendix A). There will also be opportunities for the Michigan Tech campus community to learn about the research through the Sustainable Future Institute

Digital Modeling Phenomenon Of Surface Ground Movement

With the development of specialized software applications it was possible to approach and resolve complex problems concerning automating and process optimization for which are being used field data. Computerized representation of the shape and dimensions of the Earth requires a detailed mathematical modeling, known as "digital terrain model". The paper aims to present the digital terrain model of Vulcan mining, Hunedoara County, Romania. Modeling consists of a set of mathematical equations that define in detail the surface of Earth and has an approximate surface rigorously and mathematical, that calculated the land area. Therefore, the digital terrain model means a digital representation of the earth's surface through a mathematical model that approximates the land surface modeling, which can be used in various civil and industrial applications in. To achieve the digital terrain model of data recorded using linear and nonlinear interpolation method based on point survey which highlights the natural surface studied. Given the complexity of this work it is absolutely necessary to know in detail of all topographic elements of work area, without the actions to be undertaken to project and manipulate would not be possible. To achieve digital terrain model, within a specialized software were set appropriate parameters required to achieve this case study. After performing all steps we obtained digital terrain model of Vulcan Mine. Digital terrain model is the complex product, which has characteristics that are equivalent to the specialists that use satellite images and information stored in a digital model, this is easier to use

Using Simulation to Estimate Vehicle Emissions in Response to Urban Sprawl within Geauga County, Ohio

Author Institution: Division of Mathematics & Natural Sciences, Penn State University--Altoona CollegeUrban sprawl often leads to rapid expansion and haphazard developments of low density residential land uses that are spatially disjoined. Populations occupying these new developments are expected to contribute to increased traffic volumes and vehicle emissions through increased home-work journeys. Computer simulation is one of few feasible approaches to model projected trends of local communities to understand how they evolve and better plan their future courses. The VERTUS model was developed as a planning tool to estimate vehicle emissions in response to urban sprawl. The model is specific towards estimating vehicle emissions at the local and highway levels during the home-work journey. The model was applied to Geauga County, Ohio to estimate how an increase in housing over a 20-year period from 2000-2020 will influence vehicle emissions generated. Results indicate that emissions are currently highest in the western part of the county where the greatest number of households is located. This geographic distribution remains when emissions are estimated for growth in housing. While additional housing translates to more vehicle emissions, this research found that differences exist among the county’s individual municipalities in terms of emissions generated. In several instances, municipalities with a smaller growth in housing generate a greater amount of emissions than a municipality with a larger growth in housing. These differences result from variations in the commuting characteristics of each municipality’s residents and provide insight into how household travel patterns relate to vehicle emissions

Design of Low Impact Development and Green Infrastructure at Flood Prone Areas in the City of Miami Beach, FLORIDA, USA

This thesis investigates the effectiveness of Low Impact Development Infrastructure (LIDI) and Green Infrastructure (GI) in reducing flooding resulting from heavy rainfall events and sea-level rise, and in improving stormwater quality in the City of Miami Beach (CMB). InfoSWMM was used to simulate the 5, 10, and 100-year, 24-hour storm events, total suspended solids (TSS), biochemical oxygen demand (BOD), and chemical oxygen demand (COD) loadings, and in evaluating the potential of selected LIDI and GI solutions in North Shore neighborhood. Post-development results revealed a decrease of 48%, 46%, and 39% in runoff, a decrease of 57%, 60%, and 62% in TSS, a decrease of 82%, 82%, and 84% in BOD, and a decrease of 69%, 69%, and 70% in COD loadings. SWMM 5.1 was also used to simulate the king tide effect in a cross section in Indian Creek Drive. The proposed design simulations successfully demonstrated the potential to control flooding, showing that innovative technologies offer the city opportunities to cope with climate impacts. This study should be most helpful to the CMB to support its management of flooding under any adaptation scenarios that may possibly result from climate changes. Flooding could be again caused as a result of changes in inland flooding from precipitation patterns or from sea-level rise or both

Earth Observations in Social Science Research for Management of Natural Resources and the Environment: Identifying the Contribution of the U.S. Land Remote Sensing (Landsat) Program

This paper surveys and describes the peer-reviewed social science literature in which data from the U.S. land remote sensing program, Landsat, inform public policy in managing natural resources and the environment. The Landsat program has provided the longest collection of observations of Earth from the vantage point of space. The paper differentiates two classes of research: methodology exploring how to use the data (for example, designing and testing algorithms or verifying the accuracy of the data) and applications of data to decisionmaking or policy implementation in managing land, air quality, water, and other natural and environmental resources. Selection of the studies uses social science-oriented bibliographic search indices and expands results of previous surveys that target only researchers specializing in remote sensing or photogrammetry. The usefulness of Landsat as a basis for informing public investment in the Landsat program will be underestimated if this body of research goes unrecognized.natural resources policy, environmental policy, Landsat, social science, environmental management