Para Weerappuli
Ford Motor Company
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Publication
Featured researches published by Para Weerappuli.
SAE International journal of transportation safety | 2014
Raed E. El-Jawahri; Tony R. Laituri; Agnes S. Kim; Stephen W. Rouhana; Para Weerappuli
In the present study, transfer equations relating the responses of post-mortem human subjects (PMHS) to the mid-sized male Hybrid III test dummy (HIII50) under matched, or nearly-identical, loading conditions were developed via math modeling. Specifically, validated finite element (FE) models of the Ford Human Body Model (FHBM) and the HIII50 were used to generate sets of matched cases (i.e., 256 frontal impact cases involving different impact speeds, severities, and PMHS age). Regression analyses were subsequently performed on the resulting age-dependent FHBM- and HIII50-based responses. This approach was conducted for five different body regions: head, neck, chest, femur, and tibia. All of the resulting regression equations, correlation coefficients, and response ratios (PHMS relative to HIII50) were consistent with the limited available test-based results. Language: en
International Journal of Vehicle Safety | 2005
Para Weerappuli; Priya Prasad; Saeed David Barbat
Results of a CAE (Madymo) analysis probing effectiveness of the HANS device in reducing injuries to open-wheel racecar drivers in frontal impacts are presented. The model utilised a typical impact pulse used in sled tests. Results show that the HANS device significantly reduces upper-neck shear, tension, and extension moment. These results agree with published test data. Upper-neck loads remain lower than the no-HANS case for a wide range of tether stiffness. The same is true for upper-neck shear and tension for increasing tether slack. Results are more sensitive to changes in slack than stiffness. The predicted head injury criterion is higher for drivers with the HANS device. This is attributable to tether forces at the time of engagement, the magnitude and duration of which depend on contact-interaction between head and helmet-inside. Further tests are needed to better estimate this interaction. Results also show that lowering friction on HANS surfaces reduces head-neck injury potential.
ASME 2002 International Mechanical Engineering Congress and Exposition | 2002
Para Weerappuli; Edwin Chiu; Saeed David Barbat; Priya Prasad
This paper presents acceleration data of seventy-eight open-wheel, Indy car type, racecar impacts. These data were collected by the “Impact Sensor Program” conducted jointly by the Ford Motor Company and the Championship Auto Racing Teams (CART), Inc. The seventy-eight impacts consisted of forty-two side impacts, thirty rear impacts, three frontal impacts, and three rollover/flipping of cars. Related crash data were used as input to a CAE model of a racecar driver in a typical CART car to perform computer simulations of the impacts. This model was developed using MADYMO software, and was an enhanced version of one previously published. Enhancements to the model included accurate geometrical representations of the cockpit interior, the seat, and the energy-absorbing collar; a more realistic geometry of the driver’s head and an improved representation of the neck; a highly detailed model of the driver’s helmet; and improved contact algorithms to define the head-helmet, helmet-collar, and head-chin strap interactions. Additionally, data collected from twenty-six drivers were used to improve the seating posture of the driver in the model. Results of simulations performed established the validity of the model in predicting the potential injury risk to the drivers in the head and neck areas. Model predictions of injuries based on the “Head Injury Criterion” (HIC), the Injury Assessment Reference Values (IARVs) of upper neck forces and moments, and a biomechanical neck injury predictor compared well with the actual injuries sustained by the drivers. The model predictions of reversible concussions also compared well with results of recent brain injury risk studies. The present study shows that CAE modeling can be effectively used to predict potential injuries to racecar drivers involved in high “G” impacts, and that the model can be used to evaluate countermeasures to improve safety of CART cars.© 2002 ASME
SAE International Journal of Materials and Manufacturing | 2009
Xiaomo Jiang; Ren-Jye Yang; Saeed David Barbat; Para Weerappuli
SAE International journal of transportation safety | 2013
Saeed David Barbat; Mark Mehall; Raviraj Nayak; Guy S. Nusholtz; Natalie Olds; Yibing Shi; William L. Stanko; Jenne-Tai Wang; Para Weerappuli; Lan Xu; Krishnarao V. Yalamanchili
Archive | 2018
Para Weerappuli
WCX™ 17: SAE World Congress Experience | 2017
Raed E. El-Jawahri; Agnes S. Kim; Dean M. Jaradi; Rich Ruthinowski; Kevin Siasoco; Cortney Stancato; Para Weerappuli
Stapp car crash journal | 2016
Tony R. Laituri; Scott Henry; Kevin Pline; Guosong Q Li; Michael Frankstein; Para Weerappuli
Archive | 2015
Mangala A. Jayasuriya; Para Weerappuli; Saeed David Barbat
Archive | 2015
Guosong Li; Yan Fu; Para Weerappuli; Kevin Pline