Low technology readiness level (TRL) technologies are attractive to the aerospace industry because their maturation cycles can happen simultaneously with the development lifecycle of the aircraft. However, due to the limited knowledge about a new technology in system evaluation, a low TRL technology’s high potential is counterbalanced by its inherent high risk and high uncertainty. As a result, the assessment of the potential impact of low TRL technologies on a new system is exceedingly difficult. In this paper, a modified technology impact forecasting (TIF) methodology has been proposed that incorporates the novel use of possibility distributions to more accurately quantify the potential of a low TRL technology on a baseline system. The proposed method has been demonstrated through a case study that considers composite self-healing technologies (i.e., microcapsule-based and one-dimensional vascular-based self-healing materials) as a representative low TRL technology, and quantifies the impact of infusing this set of technology onto a notional commercial aircraft system. The results show that, compared with evaluation using a traditional TIF framework, the variability using possibility distributions is significantly reduced for the same system responses. This reduced variability decreases uncertainty, which implies further reduced risk.

低技术准备水平（TRL）技术对航空航天业具有吸引力，因为它们的成熟周期可以与飞机的开发生命周期同时发生。但是，由于对系统评估中的新技术的了解有限，因此低TRL技术的高潜力被其固有的高风险和高不确定性所抵消。结果，很难评估低TRL技术对新系统的潜在影响。在本文中，提出了一种改进的技术影响预测（TIF）方法，该方法结合了可能性分布的新颖用法，可以更准确地量化低TRL技术在基准系统上的潜力。通过案例研究证明了所提出的方法，该案例考虑了复合自我修复技术（即基于微胶囊和基于一维血管的自我修复材料）作为代表性的低TRL技术，并量化了注入该组合的影响技术应用于名义上的商用飞机系统。结果表明，与使用传统TIF框架进行评估相比，对于相同的系统响应，使用可能性分布的变异性显着降低。这种降低的可变性降低了不确定性，这意味着进一步降低了风险。结果表明，与使用传统TIF框架进行评估相比，对于相同的系统响应，使用可能性分布的变异性显着降低。这种降低的可变性降低了不确定性，这意味着进一步降低了风险。结果表明，与使用传统TIF框架进行评估相比，对于相同的系统响应，使用可能性分布的变异性显着降低。这种减少的可变性减少了不确定性，这意味着进一步降低了风险。