Instituto Superior Técnico

About: Instituto Superior Técnico is a based out in . It is known for research contribution in the topics: Catalysis & Finite element method. The organization has 10085 authors who have published 30226 publications receiving 667524 citations. The organization is also known as: IST & Instituto Superior Tecnico.

Environmental benefits of substituting talc by sugarcane bagasse fibers as reinforcement in polypropylene composites: Ecodesign and LCA as strategy for automotive components

Abstract: The auto industry is compelled to improve its environmental performance, namely by making use of renewable materials and cleaner manufacturing processes with lower energy intensity, and at the end-of-life of the auto, recyclable products and materials are desirable specifications that need to be considered at an earlier design stage, i.e., promoting the ecodesign. This paper provides an analysis of such a strategy for a material that is used extensively in the auto industry, namely polypropylene composites, as we have quantified the environmental impacts when sugarcane bagasse-reinforced polypropylene substitutes for talc-filled polypropylene (PP). To achieve these goals, a comparative Life Cycle Assessment (LCA) was performed for the two alternatives, from raw extractions to the end-of-life (EOL) phase of sugarcane bagasse-PP and talc-PP composite, where data gathered in different industries in Brazil were included in the LCA GaBi software. Our analysis shows that in addition to similar mechanical performance, natural fiber composites showed superior environmental performance throughout the entire life cycle. This superior performance is because: (1) in the cultivation phase, sugarcane absorbs carbon through the photosynthesis process while growing, thus reducing the global warming impact of the materials used; (2) the production process is cleaner; (3) sugarcane bagasse-reinforced composites are lighter for equivalent performance, which reduces the amount of polypropylene used; and (4) the economic reuse proposed for the EOL sugarcane bagasse-PP composite was the best alternative to minimize environmental impacts.

An Augmented Lagrangian Approach to Constrained MAP Inference

Abstract: We propose a new algorithm for approximate MAP inference on factor graphs, by combining augmented Lagrangian optimization with the dual decomposition method. Each slave subproblem is given a quadratic penalty, which pushes toward faster consensus than in previous subgradient approaches. Our algorithm is provably convergent, parallelizable, and suitable for fine decompositions of the graph. We show how it can efficiently handle problems with (possibly global) structural constraints via simple sort operations. Experiments on synthetic and real-world data show that our approach compares favorably with the state-of-the-art.