A study on the potential risk of traumatic brain injury due to ground impact in a vehicle-pedestrian collision using full-scale finite element models

2011 ◽  
Vol 5 (2) ◽  
pp. 117 ◽  
Author(s):  
Atsutaka Tamura ◽  
Stefan Duma
Keyword(s):  
Traumatic Brain Injury ◽  
Finite Element ◽  
Brain Injury ◽  
Potential Risk ◽  
Full Scale ◽  
Finite Element Models ◽  
Ground Impact

A Numerical Study of Traumatic Brain Injury Due to Ground Impact in an SUV-Pedestrian Crash Using Full-Scale Finite Element Models

2010 ◽  
Author(s):  
Atsutaka Tamura
Keyword(s):  
Traumatic Brain Injury ◽  
Finite Element ◽  
Brain Injury ◽  
Numerical Study ◽  
Element Model ◽  
Whole Body ◽  
Impact Speed ◽  
Intrinsic Complexity ◽  
Pedestrian Crashes ◽  
Ground Impact

A number of studies have worked on traffic injuries or traumas related to pedestrian impacts. However, most of them placed more focuses on traumatic injuries due to primary impact with a striking vehicle rather than those involved in secondary impact with the ground. In this study, a validated, human whole-body, pedestrian finite element model was utilized to investigate the potential risk of traumatic brain injury (TBI) relevant to the ground impact as well as primary head strike in an SUV-to-pedestrian collision. By conducting a set of numerical experiments at impact speed of 25 and 40 km/h with pedestrian’s pre-impact, transverse, traveling speed of 1.3 m/s, it was found that ground impact is likely to cause serious TBI even in a low impact speed level. Although the post-impact kinematics and subsequent kinetics were considerably unpredictable due to the intrinsic complexity of pedestrian impact, this finding also suggests that impact speed does not necessarily contribute to the severity of pedestrian TBI involving vehicle with a higher profile. In the future, an effective countermeasure for ground impact should be taken into account to reduce the risk of sustaining serious TBIs in pedestrian crashes.

Comparing Experimental Data to Traumatic Brain Injury Finite Element Models

1999 ◽  
Author(s):  
Reid T. Miller ◽  
Douglas H. Smith ◽  
Xiaohan Chen ◽  
Bai-Nan Xu ◽  
Matt Leoni ◽  
...  
Keyword(s):  
Experimental Data ◽  
Traumatic Brain Injury ◽  
Finite Element ◽  
Brain Injury ◽  
Finite Element Models

Blast Traumatic Brain Injury Mechanisms

Neurotrauma ◽  
2018 ◽  
pp. 111-122
Author(s):  
Elizabeth McNeil ◽  
Zachary Bailey ◽  
Allison Guettler ◽  
Pamela VandeVord
Keyword(s):  
Traumatic Brain Injury ◽  
Finite Element ◽  
Brain Injury ◽  
Head Injury ◽  
Mechanism Of Injury ◽  
Primary Blast ◽  
Blast Traumatic Brain Injury ◽  
Injury Mechanisms ◽  
Biomechanical Investigation

Blast traumatic brain injury (bTBI) is a leading cause of head injury in soldiers returning from the battlefield. Primary blast brain injury remains controversial with little evidence to support a primary mechanism of injury. The four main theories described herein include blast wave transmission through skull orifices, direct cranial transmission, thoracic surge, and skull flexure dynamics. It is possible that these mechanisms do not occur exclusively from each other, but rather that several of them lead to primary blast brain injury. Biomechanical investigation with in-vivo, cadaver, and finite element models would greatly increase our understanding of bTBI mechanisms.

Investigating the fire performance of LSF wall systems using finite element analyses

2017 ◽  
Vol 8 (4) ◽  
pp. 354-376 ◽  
Author(s):  
Mohamed Rusthi ◽  
Poologanathan Keerthan ◽  
Mahen Mahendran ◽  
Anthony Ariyanayagam
Keyword(s):  
Heat Transfer ◽  
Finite Element ◽  
Full Scale ◽  
Finite Element Models ◽  
Fire Tests ◽  
Fire Performance ◽  
Load Bearing ◽  
Content Type ◽  
System Configurations ◽  
Wall System

Purpose This research was aimed at investigating the fire performance of LSF wall systems by using 3-D heat transfer FE models of existing LSF wall system configurations. Design/methodology/approach This research was focused on investigating the fire performance of LSF wall systems by using 3-D heat transfer finite element models of existing LSF wall system configurations. The analysis results were validated by using the available fire test results of five different LSF wall configurations. Findings The validated finite element models were used to conduct a parametric study on a range of non-load bearing and load bearing LSF wall configurations to predict their fire resistance levels (FRLs) for varying load ratios. Originality/value Fire performance of LSF wall systems with different configurations can be understood by performing full-scale fire tests. However, these full-scale fire tests are time consuming, labour intensive and expensive. On the other hand, finite element analysis (FEA) provides a simple method of investigating the fire performance of LSF wall systems to understand their thermal-mechanical behaviour. Recent numerical research studies have focused on investigating the fire performances of LSF wall systems by using finite element (FE) models. Most of these FE models were developed based on 2-D FE platform capable of performing either heat transfer or structural analysis separately. Therefore, this paper presents the details of a 3-D FEA methodology to develop the capabilities to perform fully-coupled thermal-mechanical analyses of LSF walls exposed to fire in future.

scholarly journals Embedded axonal fiber tracts improve finite element model predictions of traumatic brain injury

2019 ◽  
Vol 19 (3) ◽  
pp. 1109-1130 ◽  
Author(s):  
Marzieh Hajiaghamemar ◽  
Taotao Wu ◽  
Matthew B. Panzer ◽  
Susan S. Margulies
Keyword(s):  
Traumatic Brain Injury ◽  
Finite Element ◽  
Brain Injury ◽  
Strain Rate ◽  
Brain Tissue ◽  
Brain Injuries ◽  
Characteristic Curve ◽  
Strain And Strain Rate

AbstractWith the growing rate of traumatic brain injury (TBI), there is an increasing interest in validated tools to predict and prevent brain injuries. Finite element models (FEM) are valuable tools to estimate tissue responses, predict probability of TBI, and guide the development of safety equipment. In this study, we developed and validated an anisotropic pig brain multi-scale FEM by explicitly embedding the axonal tract structures and utilized the model to simulate experimental TBI in piglets undergoing dynamic head rotations. Binary logistic regression, survival analysis with Weibull distribution, and receiver operating characteristic curve analysis, coupled with repeated k-fold cross-validation technique, were used to examine 12 FEM-derived metrics related to axonal/brain tissue strain and strain rate for predicting the presence or absence of traumatic axonal injury (TAI). All 12 metrics performed well in predicting of TAI with prediction accuracy rate of 73–90%. The axonal-based metrics outperformed their rival brain tissue-based metrics in predicting TAI. The best predictors of TAI were maximum axonal strain times strain rate (MASxSR) and its corresponding optimal fraction-based metric (AF-MASxSR7.5) that represents the fraction of axonal fibers exceeding MASxSR of 7.5 s−1. The thresholds compare favorably with tissue tolerances found in in–vitro/in–vivo measurements in the literature. In addition, the damaged volume fractions (DVF) predicted using the axonal-based metrics, especially MASxSR (DVF = 0.05–4.5%), were closer to the actual DVF obtained from histopathology (AIV = 0.02–1.65%) in comparison with the DVF predicted using the brain-related metrics (DVF = 0.11–41.2%). The methods and the results from this study can be used to improve model prediction of TBI in humans.

Investigation of Cross-Species Scaling Methods for Traumatic Brain Injury Using Finite Element Analysis

2020 ◽  
Vol 37 (2) ◽  
pp. 410-422 ◽  
Author(s):  
Taotao Wu ◽  
Jacobo Antona-Makoshi ◽  
Ahmed Alshareef ◽  
J. Sebastian Giudice ◽  
Matthew B. Panzer
Keyword(s):  
Traumatic Brain Injury ◽  
Finite Element Analysis ◽  
Finite Element ◽  
Brain Injury ◽  
Element Analysis ◽  
Scaling Methods
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