Validation of a Football Helmet Finite Element Model and Quantification of Impact Energy Distribution

Corrales, Miguel A.; Gierczycka, Donata; Barker, JA; Bruneau, David; Bustamante, Michael; Cronin, Duane S.

doi:10.1007/s10439-019-02359-1

Cited by 19 publications

(11 citation statements)

References 23 publications

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“…Both producers and NOC-SAE indicate that football helmets may not fully protect the player. Other research communities have made similar conclusions in the literature [58,[84][85][86][87][88][89][90][91][92].…”

Section: Discussionsupporting

confidence: 64%

Design and Virtual Testing of American Football Helmets–A Review

Dymek

Ptak

Fernandes

2021

Arch Computat Methods Eng

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This paper aims to review the recent progress in the research carried out by scientists worldwide regarding American Footballers' head injuries and head protective equipment, focusing on the role of computation methods, mainly finite element method application to American Football helmet design and testing as well as head injury biomechanics. The helmet technology has been constantly improved, and it is driven by market competition, medical records, coaches and athletes' self-awareness. With finite element analysis and computational resources development, it is possible to develop more accurate brain models to recreate American Footballers' head impacts. This method seems to be an excellent simulation tool to verify the helmet's ability to absorb energy and enable the researchers to have an insight into head kinematics and tissue-level injuries. The work is focused on head injuries in American Football as the sport becomes more popular across the globe. Additionally, a reference to the development and newest technology is presented. The review's proposed approach gathers studies presented within the last decade regarding the coupling of finite element brain models with helmets in standardised or on-field conditions. The synthesis of the existing state of the art may enhance the researchers to continue investigating the athlete's trauma and improve the protective gear technology to minimise head injuries. The authors presented numerous studies regarding concussions and the newest findings from the last decade, including Finite Element Head models (FEHm) with American Football helmet simulations. All the studies were searched through Google Scholar, Scopus and ResearchGate databases.

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Section: Discussionsupporting

confidence: 64%

Design and Virtual Testing of American Football Helmets–A Review

Dymek

Ptak

Fernandes

2021

Arch Computat Methods Eng

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“…35,40 Three studies in the literature performed initial work in this area by validating individual components of a football helmet model prior to implementation in a holistic headgear simulation. 35,43,44 The faceguard validation procedures discussed in the studies compressed a faceguard similarly to Bina et al 27 ; however, the validation metric reported was lateral faceguard structural stiffness. The current study has validated the structural stiffness of the faceguard when compressed in the anterior-posterior direction, similar to common, on-field impacts.…”

Section: Discussionmentioning

confidence: 99%

Finite element validation of 3D American football faceguard structural stiffness models

Ferriell

Batt

DesJardins

2020

Proceedings of the Institution of Mechanical Engineers, Part P:

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Despite continued efforts to improve American football headgear technology, minimal structural changes have been made to faceguard design in the past 20 years. Although each new helmet system has its own compatible faceguard series, the primary design components have changed little between helmet systems. Additionally, little is known about specific parameters that influence faceguard performance, largely due to the variation inherent in laboratory impact testing. The goal of this study was two-fold: to validate a reverse engineering method for developing a library of faceguard models; and to validate the finite element simulation of three common American football faceguards subject to a quasi-static structural stiffness test. Three common Riddell® Speedflex™ (Des Plaines, IL) faceguard styles were modeled using a novel reverse engineering approach. Within ANSYS® Mechanical™ (ANSYS, Inc., Canonsburg, PA), the faceguards were modeled as stainless steel (elastic modulus = 193 GPa, Poisson’s ratio = 0.31). A displacement of 5 mm was prescribed in the posterior (z) direction. Boundary conditions were applied to accommodate the coronal plane (x, y) translation at clip attachment locations. The computational results correlated to the experimental results with statistical significance ( p value = 0.001). The Nose location was the most reliable with an average percent difference from experimental results of 2.7%, compared to 10.8% and 9.9% at the Mouth and Chin locations, respectively. Many studies utilizing computational models of protective headgear lack reported validation of headgear components. This study has validated the structural stiffness of three common faceguards to be used in future computational analyses. Furthermore, advancements in additive manufacturing technologies have opened the door to increasingly complex faceguard design capabilities; however, little is known about specific parameters that influence faceguard performance. With the models validated in this study, parameterized faceguard models should be used to iterate between design variables and assess the contribution of each variable on faceguard structural stiffness.

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“…The detail of this geometry depends on the type of methodology implored and the material properties assigned to the head and proposed helmet design. Corrales et al, addressed these limitations by developing a numerical model of a modern football helmet by integrating two headforms and assessing a range of impact conditions [ 301 ].…”

Section: Review Of Hvm Applications Of Ibsimmentioning

confidence: 99%

A Review of Image-Based Simulation Applications in High-Value Manufacturing

Evans

Sozumert

Keenan

et al. 2023

Arch Computat Methods Eng

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Image-Based Simulation (IBSim) is the process by which a digital representation of a real geometry is generated from image data for the purpose of performing a simulation with greater accuracy than with idealised Computer Aided Design (CAD) based simulations. Whilst IBSim originates in the biomedical field, the wider adoption of imaging for non-destructive testing and evaluation (NDT/NDE) within the High-Value Manufacturing (HVM) sector has allowed wider use of IBSim in recent years. IBSim is invaluable in scenarios where there exists a non-negligible variation between the ‘as designed’ and ‘as manufactured’ state of parts. It has also been used for characterisation of geometries too complex to accurately draw with CAD. IBSim simulations are unique to the geometry being imaged, therefore it is possible to perform part-specific virtual testing within batches of manufactured parts. This novel review presents the applications of IBSim within HVM, whereby HVM is the value provided by a manufactured part (or conversely the potential cost should the part fail) rather than the actual cost of manufacturing the part itself. Examples include fibre and aggregate composite materials, additive manufacturing, foams, and interface bonding such as welding. This review is divided into the following sections: Material Characterisation; Characterisation of Manufacturing Techniques; Impact of Deviations from Idealised Design Geometry on Product Design and Performance; Customisation and Personalisation of Products; IBSim in Biomimicry. Finally, conclusions are drawn, and observations made on future trends based on the current state of the literature.

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Validation of a Football Helmet Finite Element Model and Quantification of Impact Energy Distribution

Cited by 19 publications

References 23 publications

Design and Virtual Testing of American Football Helmets–A Review

Design and Virtual Testing of American Football Helmets–A Review

Finite element validation of 3D American football faceguard structural stiffness models

A Review of Image-Based Simulation Applications in High-Value Manufacturing

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