The aerospace industry and TU Delft have set stringent climate goals for themselves and with each passing year, these goals seem all the more implausible. While sustainability in the aerospace industry is envisioned as futuristic, circular, net-zero aircraft, the change rarely comes from the grassroots. Although these technological solutions are undoubtedly our liberators from long-term climate change, there is relatively less focus on the education of engineers who grow up to design these machines. This thesis follows a bottom-up approach which can stimulate pro-environmental attitudes among future aerospace engineers to give ourselves a fighting chance to mitigate climate change.

Unmanned aircraft system (UAS) is an emerging technology that is now gaining traction around the world. UAS operations are expected to be integrated into very-low-level rural and urban airspace via the enabling of the novel concept of unmanned traffic system (UTM). For such operations to become a reality, one of the major challenges that needs to be overcome is the assessment and, subsequently, mitigation of safety risk posed to third parties on the ground.
Third parties on the ground refer to people or pedestrians that resides within the area of operation but are not involved with the operation. To assess this risk, an approach called third-party risk (TPR) assessment has been developed in many research. Prediction of TPR of UAS operations will allow operators, authorities and stakeholders make well-informed decision on the deployment of UAS operations. If the TPR risk level of the designed operational concept exceeds the acceptable risk level, then risk mitigation can then be applied.
In a typical TPR model, one of the important sub-models is the collision consequence model used to predict probability of fatality (PoF) of human subjected to UAS collision. This sub-component requires a good understanding of human fatality due to inflicted injury by UAS collision which is, at this time of writing, still under-studied.
This thesis addresses the key component of the TPR framework that is the quantification of UAS collision consequence on human on the ground. The central aim of this thesis is to develop a quantitative, model-based collision consequence model of UAS collision on human. To achieve this main aim, a series of interrelated research studies was performed in a systematic way.

Due to an exponential growth in the number of shipments of Unmanned Aerial Systems (UAS), the amount of these devices operating in the sky has increased remarkably over the last few years. This led to an increasing number of proximity incidents with manned aircraft. Since these devices share certain airspace with rotorcraft, the question arises how much damage a helicopter could sustain after an impact with a UAS. Within this thesis, a risk assessment was completed initially to determine which collision in terms of type of UAS and helicopter impact location poses the highest risk to the operator of the helicopter. Subsequently a validated model of a DJI Phantom III was developed and impacted onto a rotorcraft windshield in explicit Finite Element software. The sustained damage was compared with a simulated bird strike event to determine whether the prevailing certification requirements would suffice to guarantee safety of the crew.

Using a data-driven approach, a heterogeneous populated agent-based model of an airport security checkpoint is calibrated and validated. It is found that average performance using the model can be replicated to a sufficient degree. The heterogenous population could become useful when different passenger fractions - with different performance per passenger type - are analysed for different security checkpoint configurations. Furthermore, time-dependent agent performance could improve the models validity.