Browse Topic: Head injuries
Industries are following a tedious product development cycle for developing their product. In product development major steps includes design ideas, Drawings, CAD, CAE, Testing and design improvement cycle. This is a monotonous process and takes time which impacts on its time to deliver product and cost on development. Now a days industries are fast growing and targeting to reduce development cycle time and cost. AI&ML is impacting almost all areas in the industry and significantly reducing efforts time and cost. To make use of AI&ML in CAE, Altair Physics AI is an effective tool. To ensure the design of product traditional way is to develop a CAD of the product, develop, perform CAE and analyze performance. If we consider CAE procedure it is time consuming process which includes FEA model build, applying boundary conditions, running simulation and analyzing results which could take minutes to hours. By using ML with Physics AI we can make predictions on new design of the product in seconds and significantly save time and cost. To demonstrate the CAE acceleration process with physic AI we have solved two case studies. The first case study is head impact on hood where ML tool will predict deformation contour of the hood, acceleration and displacement curve of the impactor. The second case study is Tube crush analysis where prediction of tube deformation pattern, force and energy curve for different tube length and impact velocity is carried out. For both Case studies we have used TCS inhouse data to train test and prediction of the ML model. For Head impact case study, it gives lower training loss with more than 90 percent prediction accuracy. Similarly for tube crush study it gives good accuracy and predicts comparable behavior patten with CAE results. Physic AI ML tool accelerates the design and development cycle and can be utilized in different product development. Implementation of ML accelerates the CAE process in design and development of products. It saves a lot of time in multiple design iteration study. Similar method can be implemented for different CAE cases.
Rear-facing infant seats that are positioned behind front outboard vehicle seats are at risk of being compromised by the rearward yielding of occupied front seat seatbacks during rear-impact collisions. This movement can cause the plastic shell of the infant seat to collapse and deform, increasing the risk of head injuries to the infant. Current designs of rear-facing infant seats typically do not consider the loading effects from the front seatback during rear-impact situations, which results in weak and collapsible shell structures. Moreover, regulatory compliance tests, such as FMVSS 213, do not include assessments of rear-facing infant seats under realistic rear-impact conditions. as the bench used for the regulatory test lacks realistic vehicle interior components. This study emphasizes the need for revised testing methodologies that employ sled tests with realistic seatback intrusion conditions to facilitate the development of improved infant seat designs. Research shows that rear-facing infant seats designed for real-world loading conditions can improve safety and injury outcomes for infants in severe rear-impact collisions in the presence of front-occupied seats.
Innovators at the NASA Johnson Space Center have developed a soft, wearable, robotic upper limb exoskeleton garment designed to actively control the shoulder and elbow, both positioning the limb in specific orientations and commanding the limb through desired motions. The invention was developed to provide effective upper extremity motor rehabilitation for patients with neurological impairments (e.g., traumatic brain injury, stroke).
This study presents an analysis of 364 motorcycle helmet impact tests, including standard certified full-face, open-face, and half-helmets, as well as non-certified (novelty) helmet designs. Two advanced motorcycle helmet designs that incorporate technologies intended to mitigate the risk of rotational brain injuries (rTBI) were included in this study. Results were compared to 80 unprotected tests using an instrumented 50th percentile Hybrid III head form and neck at impact speeds ranging from 6 to 18 m/s (13 to 40 mph). Results show that, on average, the Head Injury Criterion (HIC) was reduced by 92 percent across certified helmets, compared to the unhelmeted condition, indicating substantial protection against focal head and brain injuries. However, findings indicate that standard motorcycle helmets increase the risk of AIS 2 to 5 rotational brain injuries (rTBI) by an average of 30 percent compared to the unprotected condition, due to the increased rotational inertia generated by the added size and weight of the helmet. Advanced helmets performed, on average, about 5 percent better than standard certified helmets. Non-certified or novelty helmets offer inadequate protection against focal head and brain injuries, though they may offer some insight into rTBI protection. The findings of this study also indicate a critical methodological deficiency in the oblique impact tests utilized in revised motorcycle helmet standards, including ECE 22.06, Snell M2025, and FRHPe-02, which fail to correctly assess rTBI risk. This paper provides recommendations for enhancing motorcycle helmet design to improve protection against rotational traumatic brain injuries.
Head injuries from interior impacts during vehicle accidents are a significant cause of fatalities in India. Data from the National Crime Records Bureau (NCRB) for 2023 reveals that approximately 15% of the total 150,000 road fatalities were due to head impacts on vehicle interiors, resulting in about 22,500 deaths. Thus, head impact protection in a car crash is key during the design of vehicle interiors. IS 15223 and ECE-R21 provide specific guidelines for head impact testing of instrument panels and consoles in vehicles to ensure compliance with safety standards and minimize the risk of head injury during collisions. By systematically addressing each aspect of IS 15223 and ECE- R21 in the design, testing, and documentation phases, manufacturers can ensure that console armrests are optimized for safety. This approach not only helps meet regulatory standards but also enhances overall occupant protection in vehicles during collisions. The objective of this paper is to design a console armrest that meets stringent head impact testing requirements and thereby enhances occupant safety in automotive applications. The research focuses on optimizing the armrest’s structural integrity to withstand dynamic loads and to transfer or dissipate that impact energy effectively.
Communicating when traumatic brain injury, stroke, or disease has made speech impossible can be daunting. But specialized eye-tracking technology uses eye movement to enable people living with disabilities to connect one-on-one, over the phone, or via the internet.
With the current trend of including the evaluation of the risk of brain injuries in vehicle crashes due to rotational kinematics of the head, two injury criteria have been introduced since 2013 – BrIC and DAMAGE. BrIC was developed by NHTSA in 2013 and was suggested for inclusion in the US NCAP for frontal and side crashes. DAMAGE has been developed by UVa under the sponsorship of JAMA and JARI and has been accepted tentatively by the EuroNCAP. Although BrIC in US crash testing is known and reported, DAMAGE in tests of the US fleet is relatively unknown. The current paper will report on DAMAGE in NCAP-like tests and potential future frontal crash tests involving substantial rotation about the three axes of occupant heads. Distribution of DAMAGE of three-point belted occupants without airbags will also be discussed. Prediction of brain injury risks from the tests have been compared to the risks in the real world. Although DAMAGE correlates well with MPS in the human brain model across several test scenarios, the predicted risk of AIS2+ brain injuries are too high compared to real-world experience. The prediction of AIS4+ brain injury risk in lower velocity crashes is good, but too high in NCAP-like and high speed angular frontal crashes.
Hood insulators are widely used in automotive industry to improve noise insulation, pedestrian impact protection and to provide aesthetic appeal. They are attached below the hood panel and are often complex in shape and size. Pedestrian head impacts are highly dynamic events with a compressive strain rate experienced by the insulator exceeding 300/s. The energy generated by the impact is partly absorbed by the hood insulators thus reducing the head injury to the pedestrian. During this process, the insulator experiences multi-axial stress states. The insulators are usually made of soft multi-layered materials, such as polyurethane or fiberglass, and have a thin scrim layer on either side. These materials are foamed to their nominal thickness and are compression molded to take the required shape of the hood. During this process they undergo thickness reduction, thereby increasing their density. Hence, the material properties vary greatly based on the thickness and strain rate experienced by the material. This paper presents a methodology for characterization of hood insulator materials at strain rates ranging from 0.01/s to 300/s for use in finite element (FE) simulations. A rate dependent material model is validated against the results of hemispherical punch tests. Unique tensile response of the hood insulator materials at high strain rates and the challenges it poses for material modeling is discussed in detail. In addition, challenges with specimen extraction and tensile testing of soft multilayer materials are presented, and the improved tensile testing procedure is proposed.
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