Search results

The complexity of atmospheric corrosion, further compounded by the effects of climate change, makes existing models inappropriate for corrosion prediction. The commonly used kinetic model and dose-response functions are restricted in their capacity to represent the non-linear behaviour of corrosion phenomena. The application of artificial intelligence (AI)-driven machine learning algorithms to corrosion data can better represent the corrosion mechanism by considering the dynamic behaviour due to changing climatic conditions. Effective use of materials, coating systems and maintenance strategies can then be made with such a corrosivity model. Accurate corrosion prediction will help to improve climate change resilience of the social, economic and energy infrastructure in line with the UN Sustainable Development Goals (SDGs) 7 (Affordable and Clean Energy), 9 (Industry, Innovation and Infrastructure) and 13 (Climate Action). This chapter discusses atmospheric corrosion prediction in relation to the SDGs and the influence of AI in overcoming the challenges.

New mindsets and innovative thinking (ABIS, 2017; Moon, 2013, 2014, 2015; Moon, Walmsley, & Apostolopoulos, 2018) are needed to deliver on everything from good health and well-being to affordable and clean energy. This chapter reviews the latest trends globally to tackling pressing social and environmental problems (2016–2018), focuses on a sample of 100 projects, mapped against the UN SDGs and evaluated on their ‘innovation’ and scalability and selects 25 projects related to ‘circular economy’ solutions for a more in-depth consideration. The projects cover a range of applications including Buildings, Food, Energy, Transportation, Resources and Education. The key research question is: what strategic policy support is needed for enterprise & entrepreneurship education to develop the necessary multi collaborative and cross disciplinary mindsets and skills that such projects require? Reference is made to global risks and sustainability solutions, skills needed for the green economy and implications for enterprise development and entrepreneurship education. Findings reveal the need for new measures of eco and social mindset that will support the development of the creative and innovative solutions necessary for tackling the UN SDGs.