Evaluation of Human and Anthropomorphic Test Device Finite Element Models under Spaceflight Loading Conditions

In an effort to develop occupant protection standards for future multipurpose crew vehicles, the National Aeronautics and Space Administration (NASA) has looked to evaluate the test device for human occupant restraint with the modification kit (THORK) anthropomorphic test device (ATD) in relevant impact test scenarios. With the allowance and support of the National Highway Traffic Safety Administration, NASA has performed a series of sled impact tests on the latest developed THORK ATD. These tests were performed to match test conditions from human volunteer data previously collected by the U.S. Air Force. The objective of this study was to evaluate the THORK finite element (FE) model and the Total HUman Model for Safety (THUMS) FE model with respect to the tests performed. These models were evaluated in spinal and frontal impacts against kinematic and kinetic data recorded in ATD and human testing. Methods: The FE simulations were developed based on recorded pretest ATD/human position and sled acceleration pulses measured during testing. Predicted responses by both human and ATD models were compared to test data recorded under the same impact conditions. The kinematic responses of the models were quantitatively evaluated using the ISOmetric curve rating system. In addition, ATD injury criteria and human stress/strain data were calculated to evaluate the risk of injury predicted by the ATD and human model, respectively. Results: Preliminary results show wellcorrelated response between both FE models and their physical counterparts. In addition, predicted ATD injury criteria and human model stress/strain values are shown to positively relate. Kinematic comparison between human and ATD models indicates promising biofidelic response, although a slightly stiffer response is observed within the ATD. Conclusion: As a compliment to ATD testing, numerical simulation provides efficient means to assess vehicle safety throughout the design process and further improve the design of physical ATDs. The assessment of the THORK and THUMS FE models in a spaceflight testing condition is an essential first step to implementing these models in the computational evaluation of spacecraft occupant safety. Promising results suggest future use of these models in the aerospace field

The Influence of the Specimen Shape and Loading Conditions on the Parameter Identification of a Viscoelastic Brain Model

The mechanical properties of brain under various loadings have been reported in the literature over the past 50 years. Step-and-hold tests have often been employed to characterize viscoelastic and nonlinear behavior of brain under high-rate shear deformation; however, the identification of brain material parameters is typically performed by neglecting the initial strain ramp and/or by assuming a uniform strain distribution in the brain samples. Using finite element (FE) simulations of shear tests, this study shows that these simplifications have a significant effect on the identified material properties in the case of cylindrical human brain specimens. Material models optimized using only the stress relaxation curve under predict the shear force during the strain ramp, mainly due to lower values of their instantaneous shear moduli. Similarly, material models optimized using an analytical approach, which assumes a uniform strain distribution, under predict peak shear forces in FE simulations. Reducing the specimen height showed to improve the model prediction, but no improvements were observed for cubic samples with heights similar to cylindrical samples. Models optimized using FE simulations show the closest response to the test data, so a FE-based optimization approach is recommended in future parameter identification studies of brain

A Finite Element Model of the THOR-K Dummy for Aerospace and Aircraft Impact Simulations

1) Update and Improve the THOR Finite Element (FE) model to specifications of the latest mod kit (THOR-K). 2) Evaluate the kinematic and kinetic response of the FE model in frontal, spinal, and lateral impact loading conditions

Multivariate Modelling of Pedestrian Fatality Risk Through on the Spot Accident Investigation

Pedestrians are the most vulnerable users of public roads and represent one of the largest groups of road casualties; their death rate around the world due to vehicle-pedestrian collisions is high and tending to rise. In Spain, as in other countries of the European Union, steps have been taken to reduce the number and consequences of such accidents, with encouraging results in recent years. A key to countering this concern is the accident research activity that has obtained remarkable achievements in different fields, especially when multidisciplinary approaches are taken. This paper describes the development of a multivariate model that is able to detect the most influential parameters on the consequences of vehicle-pedestrian collision and to quantify their impact on pedestrian fatality risk. First, an accident database containing detailed information and parameters of vehicle-pedestrian collisions in Madrid has been developed. The accidents were investigated on the spot by INSIA accident investigation teams and analyzed using advanced reconstruction techniques. The model was then developed with two components: (1) a classification tree that characterizes and selects the explanatory variables, identifying their interactions, and (2) a binary logistic regression to quantify the influence of each variable and interaction resulting from the classification tree. The whole model represents an important tool for identifying, quantifying and predicting the potential impact of measures aimed at reducing injuries in vehicle-pedestrian collisions

Real-time biomechanical modeling of the liver using Machine Learning models trained on Finite Element Method simulations

[EN] The development of accurate real-time models of the biomechanical behavior of different organs and tissues still poses a challenge in the field of biomechanical engineering. In the case of the liver, specifically, such a model would constitute a great leap forward in the implementation of complex applications such as surgical simulators, computed-assisted surgery or guided tumor irradiation. In this work, a relatively novel approach for developing such a model is presented. It consists in the use of a machine learning algorithm, which provides real-time inference, trained on tens of thousands of simulations of the biomechanical behavior of the liver carried out by the finite element method on more than 100 different liver geometries. Considering a target accuracy threshold of 3 mm for the Euclidean Error, four different scenarios were modeled and assessed: a single liver with an arbitrary force applied (99.96% of samples within the accepted error range), a single liver with two simultaneous forces applied (99.84% samples in range), a single liver with different material properties and an arbitrary force applied (98.46% samples in range), and a much more general model capable of modeling the behavior of any liver with an arbitrary force applied (99.01% samples in range for the median liver). The results show that the Machine Learning models perform extremely well on all the scenarios, managing to keep the Mean Euclidean Error under 1 mm in all cases. Furthermore, the proposed model achieves working frequencies above 100Hz on modest hardware (with frequencies above 1000Hz being easily achievable on more powerful GPUs) thus fulfilling the real-time requirements. 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Aerodynamic investigation of the start-up process of H-type vertical axis wind turbines using CFD

In this study, a CFD start-up model has been built after conducting the sensitivity studies to evaluate the self-starting behaviour of the H-type vertical axis wind turbines (VAWTs). The self-starting behaviour of a well-investigated VAWT is used for the model validation, and then the details of aerodynamics of the start-up process have been examined. Finally, the effect of the moment of inertia and the blade number on the aerodynamic behaviour of the self-starting and power performance of the H-type VAWT are analysed. It has been found that in the critical region, where TSR<1, the contribution of the drag to the torque generation plays a significant role in the second and third quarters of the rotor revolution, where the azimuthal position varies between 100° and 253°. The results also show that increasing the turbine inertia did not show a noticeable effect on the start-up behaviour of the turbine and final rotational speed. However, an increase in the instantaneous turbine power during the start-up process after the optimum TSR is observed with decreasing the turbine inertia. The current findings also show that an increase in the blade number makes the turbine easier to start-up; however, this may reduce the turbine power coefficient