Holistic Approach to Decision Making in the Formulation and Selection of Anti-Icing Products

Abstract

To effectively fight snow storms in the challenging funding environment, many maintenance agencies in North America have started to produce their own anti-icing liquids, instead of procuring commercial anti-icers. This work demonstrates a systematic approach to collaborative, data-driven, and multicriteria decision making by conducting a set of laboratory tests to assess twenty blended chloride-based anti-icing formulations. The laboratory data were then used to establish predictive models correlating the multiple design parameters with the anti-icer performance and effects or with an anti-icer composite index. The authors used artificial neural networks for modeling and examined anti-icer performance (characteristic temperature and ice-melting capacity at 30 and 15°F (