Novel geometric metric for uncertainty accumulation in life cycle assessment

Arvind Shankar Raman

doi:10.7273/000004297

Life-Cycle Assessment (LCA) is a technique used to estimate the environmental impact of any product from its inception to disposal. Quantification of environmental impact is accompanied by a certain level of uncertainty with it; the objective of this research is to create a geometric metrics of uncertainty on parameters that contribute to environmental impact. In mechanical design, LCA is performed at end of design stage, implying that the product is not yet manufactured, used or disposed off. Therefore, data utilized in LCA is estimated from similar products all across the board. Data utilized in such LCA study is from different processes, products, technologies, different geographic locations, areas of application and time frame. Therefore, there is large uncertainty in data utilized in LCA. There are multiple factors that contribute to uncertainty in LCA. The four environmental impacts included in this study are Air Acidification, Water Eutrophication, Carbon emission and Energy. Individual uncertainties of these parameters play a huge role on consolidated uncertainty in LCA. Consolidation of these individual uncertainties can be linear or non-linear based on multiple factors and parameters. This research focuses on creating a metrics for these linear or non-linear effects on uncertainty between the parameters that contribute to environmental impact. A visual representation of impacts of these four parameters on uncertainty will provide a much better understanding on the design flaws and its improvement. This research is creating a Novel geometric metric for the uncertainty in the process parameters is developed using Barycentric co-ordinates and mapped onto a hypothetical space called S-Map (Sustainability Map). S-Map, a bounded space for multiple process parameters can be accumulated using a mathematical technique called, convolution for multiple convex multi-dimensional shapes. The accumulated S-map is the total uncertainty of all environmental impacts of a product life-cycle. This research focuses on creating an effective algorithm for non-convex to non-convex or non-convex to convex accumulation of multi-dimensional shapes for uncertainty accumulation in LCA. The research also calculates the effect of statistical distribution on each parameter, which governs the uncertainty quantification. Resulting S-map created using this research is a geometric metric of uncertainty accumulation.

Novel geometric metric for uncertainty accumulation in life cycle assessment

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