Although energy consumption during use can cause a majority of a product’s environmental impact, the relationship between a product’s usage context and its environmental performance is rarely considered in design evaluations. Probabilistic graphical models (PGMs) provide the capability of evaluating uncertainty and variability of product use in addition to correlating the results with aspects of the usage context. This research demonstrates a method for representing the usage context as a PGM through the use of a lightweight vehicle design example. The demonstration PGM is constructed from factors such as driver behavior, alternative driving schedules, and residential density, which are related to local conditional probability distributions derived from publicly available data sources. Unique scenarios are then assembled from sets of conditions on these factors to provide insight into sources of variance in lifetime energy use. The vehicle example demonstrates that implementation of realistic usage scenarios via a PGM can provide a much higher fidelity investigation of energy savings during use than commonly found in the literature and that distinct scenarios can have significantly different implications for the effectiveness of lightweight vehicle designs.

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