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Optimal Impact Isolation for Minimal Head Injury Criterion (HIC) Using Effective Operating Region (EOR)

Resource type
Thesis type
(Thesis) M.A.Sc.
Date created
The high incidence of human impact-induced injuries is a serious public health issue that can reduce the quality of life, often leading to chronic pain, dependence on others for daily activities, disability, and even death. The medical and recovery expenses of these injuries impose significant economic and social burdens on the patient and the healthcare system. Such injuries may occur in different groups of people who are most vulnerable and require more attention than others in society, including children, the elderly wheelchair users, and those who are involved in high-risk activities such as construction, transportation and sports. As a result, there is an urgent need for the design and development of an effective impact protection safety device. Injury criteria, such as head injury criterion (HIC) and neck injury criterion (NIC), are metrics by which to identify, compare, and improve the effectiveness of impact isolators. Head Injury Criterion (HIC) is one of the most globally adapted measures of injury analysis. In recent years, many researchers have investigated HIC Optimization by applying both traditional and novel methodologies and algorithms. In this thesis, the concept of "Effective Operating Region (EOR)" is introduced as a potential element in impact isolator. The concept has been analytically established and then applied in order to show the feasibility of generating near-square waveform impact impulse using linear springs and dampers. The functionality of the proposed approach has been examined by conducting properly designed experiments and by applying the approach in tangible examples of impact isolators such as airbags. A novel self-inflated foam airbag was eventually developed and experimentally verified. The tests results for this airbag have shown that the proposed EOR concept is effective in practice.
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Scholarly level
Supervisor or Senior Supervisor
Thesis advisor: Arzanpour, Siamak
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