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Agricultural crop residues (e.g., straw and stover) are a current focus for bioenergy feedstocks, with new technologies being developed to improve the economics of bioenergy production. Among the emerging technologies focused on feedstock engineering is the selective harvest concept. Due to the complexity of the biomass separations required for addressing the challenges and requirements of selective harvest, high fidelity models and advanced experimental methods that allow observation and measurement of the physical system are needed. These models and methods were developed and include computational fluid dynamics (CFD) modeling to simulate the cleaning shoe of a grain combine and a particle image velocimetry (PIV) technique to quantitatively and qualitatively characterize the cleaning shoe performance. While these techniques alone can be sufficient engineering and analysis tools for developing selective harvest technologies, this paper presents a new methodology, Virtual Engineering (VE), that integrates the CFD and PIV data into a virtual environment, where the data is coupled with the geometric model of a grain combine to provide a virtual representation of the cleaning shoe performance. Using VE visualization capabilities, the CFD and PIV data can be viewed in the context of the physical system for an interactive evaluation of characteristics and performance. This paper also discusses the concepts of additional VE tools that are being developed to provide necessary visualization, simulation and integration functionality.