Technology Impact Forecasting for Multi-Functional Composites
Abstract
New aircraft are being required to meet increasingly stringent requirements, demanding that they be lighter, stronger, faster, and more environmentally friendly and sustainable, all at reduced operating costs. Multi-functional composites offer a possible solution to these conflicting design goals, and, through custom design and manufacturing techniques, could result in new materials that offer higher strength at lower weight. In addition, potential exists for bespoke capabilities, such as self-healing and damage detection, increased lightning strike protection, morphing wing shapes, and ice detection and prevention. The key challenge, and thus the novelty, of the research, is the extraction of meaningful data for a technology that is in its embryonic stage, and then being able to statistically extrapolate that data into a form that enables decision-making. Key gaps include how to mathematically extrapolate statistically meaningful data from small experimental data sets, corresponding to low TRL technology research, and how to meaningfully and usefully conduct knowledge extraction from technology experts. Technology impact forecasting (TIF) as a science is still in its infancy, particularly in the engineering disciplines, such as aerospace. Simultaneously, the world is experiencing a dramatic increase in technology innovation. In an age where engineering designers are being asked to do more with less, a framework that enables the assessment of the system level impact of a low TRL technology would be invaluable as a means for enabling superior engineering design, as well as directing critical resource allocation. Specific gaps in the state of the art of TIF methods include how to mathematically represent combinations of impacts from several different or multi-functional technologies, how to merge probability distributions for different technologies while maintaining traceability, and how to propagate impact effects through a multi-scale model.
Document Details
- Document Type
- Technical Report
- Publication Date
- Apr 17, 2019
- Accession Number
- AD1077582
Entities
People
- Danielle Soban
- Ying Huang
Organizations
- Queen's University