Anthropometric test devices (ATDs), commonly referred to as crash test dummies, are tools used to conduct aerospace and spaceflight safety evaluations. Finite element (FE) analysis provides an effective complement to these evaluations. In this work a FE model of the Test Device for Human Occupant Restraint (THOR) dummy was developed, calibrated, and validated for use in aerospace and spaceflight impact analysis. A previously developed THOR FE model was first evaluated under spinal loading. The FE model was then updated to reflect recent updates made to the THOR dummy. A novel calibration methodology was developed to improve both kinematic and kinetic responses of the updated model in various THOR dummy certification tests. The updated THOR FE model was then calibrated and validated under spaceflight loading conditions and used to asses THOR dummy biofidelity. Results demonstrate that the FE model performs well under spinal loading and predicts injury criteria values close to those recorded in testing. Material parameter optimization of the updated model was shown to greatly improve its response. The validated THOR-FE model indicated good dummy biofidelity relative to human volunteer data under spinal loading, but limited biofidelity under frontal loading. The calibration methodology developed in this work is proven as an effective tool for improving dummy model response. Results shown by the dummy model developed in this study recommends its use in future aerospace and spaceflight impact simulations. In addition the biofidelity analysis suggests future improvements to the THOR dummy for spaceflight and aerospace analysis. / Master of Science

No description available.

In this paper, market participants’ tendency to form investor herds in the stocks listed on Nasdaq First North Growth Market of Sweden is examined for the period from 2018 to 2023. The models used in this study to detect herd behavior in stocks consist of two measures of dispersions, Cross-Sectional Standard Deviation of returns (CSSD) and Cross-Sectional Absolute Deviation of returns (CSAD), which were proposed by Christie and Huang (1995) and Chang, et al. (2000), respectively. An equally-weighted index consisting of all of the stocks that have traded on this market during the period is created and a quantitative analysis is conducted. Evidence showed absence of herd behavior when using both models, as well as when accounting for robustness tests consisting of small, mid-and large cap portfolios. Our results also support the prediction of rational asset pricing models, which suggest that stock return dispersions around the market returns increase during periods of market stress.