APPLICATION OF HUMAN COMPUTER MODELS IN MODELLING MARITIME CRASHES.

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APPLICATION OF HUMAN COMPUTER MODELS IN MODELLING MARITIME CRASHES. M. Orlowski 1, C. Bastien 1, O. Razmkhah 1, S. McCartan 1 1 Centre for Mobility and Transport Coventry University (UK) 1

Strange 2

Content Background Cabin model Injuries probability using Hybrid III Analysis with human model Conclusions 3

Crash on the sea? RMS Titanic 15.04.1912 crash with an iceberg, max speed 24 knots, 1517 fatalities RMS Empress of Ireland 28.05.1914 crash with another ship, max speed 18 knots, 1024 fatalities 9 ships of US Navy crash into the shore 8.09.1923 crash with rock at 20 knots, 23 fatalities SS Andrea Doria and MS Stockholm 26.07.1956 two ships crash, 40 knots crash, 51 fatalities MV Dona Paz 20.12.1987, collision with an oil tanker, max speed 18 knots, 4386 fatalities Costa Concordia 13.01.2012 crash with a rock, max speed 23 knots, 32 fatalities 4

Cruise Logistics Ferry Mix of aluminium and steel Cruise speed of 40 knots (~20 m/s) Similarities with automotive crash Occupant Pedestrian Automotive solutions can be utilised Finite Element analysis Safety solutions airbags, crash test dummies, restrain systems 5

Cruise Logistics Ferry Crash Crash with a rigid target at 40 knots Impact energy of 316 MJ Peak displacement Ds=14 m Average deceleration of 2g acting on the occupant Peak deceleration of 8g 6

What this Research will answer 1. Cabin safety assessment methodology 2. A safe bracing position 7

Hybrid III Dummy 50 th Percentile Male Crash Test Dummy Frontal crash applications Calibrated to record forces and accelerations acting on the joints Injuries criteria determined for head, chest and neck Determination of injury probability based on the injury criteria 8

Injury prediction of the CLF cabin occupant Cabin model Modelling approach and assumptions Wall design Acceleration pulse 9

Impact scenarios 18 DIFFERENT IMPACT CASES 6 P 7 P 8 P 9 P 11 P 10 P 7 N 6 N 1 P 2 P a P 1 N 2 N 3 N 4 N 5 N a N 3 P 4 P 5 P Positive acceleration Negative acceleration 10

Results impact scenario 8P Crash with a rigid target at 40 knots 11

Results impact scenario 4N 12

Injury Results 14 impact cases with probability of serious injury higher or equal to 50% 9 impact cases with probability of serious injury higher or equal to 80% Clear dependency between the injury probability and distance to obstacle Case AIS 2+ head (probability) (%) AIS 3+ Neck (probability) (%) AIS 3+ Chest (probability) (%) 1P >90 100 27 2P >90 100 13 3P 13 55 40 4P 4 33 23 5P 1 11 21 6P >90 94 25 7P 48 34 60 8P 78 52 11 9P >90 87 9 10P >90 97 53 11P 17 82 11 1N 11 15 18 2N 50 52 27 3N 81 97 58 4N 88 100 25 5N >90 100 19 6N 76 99 37 7N 1 20 7 13

Safe (bracing) position Frontal position Posterior position 14

THUMS Model Analysis a N Total Human Model for Safety (THUMS) The most injurious case analysed with THUMS model posterior impact 15

Results impact scenario 4N 16

THUMS Injuries Diffuse axon Injury (DAI) Brain Contusion Heart Rupture Bone fracture 17

Bracing Position Validation 18

Safe position Diffuse axon Injury (DAI) Brain Contusion Heart Rupture Bone fracture 19

Conclusions A process to analyse cabin design under crash event has been developed Numerical investigation shown very high probability of serious injury in case of the CLF crash Dependency between the distance to the obstacle and the probability of an injury THUMS model also predicts severe injuries of the internal organs (brain, heart and bone structure) high risk of death or life changing injury THUMS and Hybrid III safe position was found to be as closed to the wall as possible and it enables for reduction of the injury probability or its severity THUMS human model very useful to evaluate future evacuation plans 20

Questions? 21