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Latches are generally used to lock/unlock a component against each other. In the automotive industry, latches are widely used in doors and seats. Seat latches have to secure the seat safely to the body in the event of a crash and at the same time they have to be locked/unlocked with easy efforts. Seat latches are mostly supplier designed parts. Supplier latch effort calculations involve only latch components. Actual latch effort calculations should be done with seat structures, foams, trims and body environments. Hence OEMs are responsible to provide easily lockable/unlockable seats to their customers. Customers nowadays, are raising complaints regarding latching issues to respective automotive industry which in turn costs more due to after sales services/warranty claims. Therefore, automotive industries must spend a significant amount of time and capital on physical test and method development for calculating the latch efforts.

Considerable research has been conducted in terms of attempting to reduce lower leg injury risk in full frontal impacts, in some cases by the use of a knee airbag (KAB). However, there has been limited research into the performance of KAB systems during a crash test with increased oblique loading, such as the IIHS small overlap frontal test, an oblique moving deformable barrier test (OI) being researched by NHTSA, and a mobile progressive deformable barrier test (MPDB) that is expected to be implemented by Euro NCAP in the next few years. The objective of the current numerical study was concentrated on the evaluation of an innovative KAB concept design intended to reduce ATD right inboard lower leg/foot responses under small overlap and oblique loading conditions. A novel appendage KAB concept design was developed with the help of morphing and computational studies which were performed with different ATD sizes.

Vehicle restraint systems are optimized to maximize occupant safety and achieve high safety ratings. The optimization formulation often involves the inclusion or exclusion of restraint features as discrete design variables, as well as continuous restraint design variables such as airbag firing time, airbag vent size, inflator power level, etc. The optimization problem is constrained by injury criteria such as Head Injury Criterion (HIC), chest deflection, chest acceleration, neck tension/compression, etc., which ensures the vehicle meets or exceeds all Federal Motor Vehicle Safety Standard (FMVSS) requirements. Typically, Genetic Algorithms (GA) optimizations are applied because of their capability to handle discrete and continuous variables simultaneously and their ability to jump out of regions with multiple local optima, particularly for this type of highly non-linear problems.