• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.5
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• pp.201-209
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• 2003

Virtual human models are widely used to save time and expense in vehicle safety studies. A human model is an essential tool to visualize and simulate a vehicle driver in virtual environments. This research is focused on creation and application of a human model fer virtual reality. The Korean anthropometric data published are selected to determine basic human model dimensions. These data are applied to GEBOD, a human body data generation program, which computes the body segment geometry, mass properties, joints locations and mechanical properties. The human model was constituted using MADYMO based on data from GEBOD. Frontal crash and bump passing test were simulated and the driver's motion data calculated were transmitted into the virtual environment. The human model was organized into scene graphs and its motion was visualized by virtual reality techniques including OpenGL Performer. The human model can be controlled by an arm master to test driver's behavior in the virtual environment.

• Transactions of the Korean Society of Automotive Engineers
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• v.18 no.3
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• pp.149-155
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• 2010

Currently various safety tests are being performed in many countries with growing interest in vehicle safety. However the vehicles which have good safety performance in these tests could not secure the good performance in real car to car accident. So new test protocol using progressive deformable barrier (PDB) was proposed by EEVC in Europe, NHTSA in USA and some vehicle manufacturers, etc. The target of PDB test is to control partner protection in addition to self-protection on the same test. The proposal is to update current ECE R.94 frontal ODB test. So barrier, impact speed, overlap are changed to avoid bottoming-out in the test configuration. In this paper 3 different tests (R.94, EuroNCAP and PDB test) were carried out using current production vehicles with same structure. The results of these tests were compared to understand PDB test. As a result PDB test shows the highest vehicle deceleration and dummy injury because PDB offers a progressive increase in stiffness in depth and height. However vehicle intrusion was affected with rather test velocity than stiffness of deformable barrier. PDB deformation data is used for partner protection assessment using PDB software and it shows that the test vehicle is rather not aggressive.

• Transactions of the Korean Society of Automotive Engineers
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• v.18 no.4
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• pp.18-30
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• 2010

As the automobile industry is developing, the number of deaths and injuries has increased. To reduce the damages from automobile accidents, the government of each country proposes experimental conditions for reproducing the accident and establishes the vehicle safety regulations. Automotive manufacturers are trying to make safer vehicles by satisfying the requirements. The Hybrid III crash test dummy is a standard Anthropomorphic Test Device (ATD) used for measuring the occupant's injuries in a frontal impact test. Since a real crash test using a vehicle is fairly expensive, a computer simulation using the Finite Element Method (F.E.M.) is widely used. Therefore, a detailed and robust F.E. dummy model is needed to acquire more accurate occupant injury data and behavior during the crash test. To achieve this goal, a detailed F.E. model of the Hybrid III 5th percentile female dummy is constructed by using the reverse engineering technique in this research. A modeling process is proposed to construct the F.E. model. The proposed modeling process starts from disassembling the physical dummy. Computer Aided Design (CAD) geometry data is constructed by three-dimensional (3-D) scanning of the disassembled physical dummy model. Based on the geometry data, finite elements of each part are generated. After mesh generation, each part is assembled with other parts using the joints and rigid connection elements. The developed F.E. model of dummy is simulated based on the FMVSS 572 validation regulations. The results of simulation are compared with the results of physical tests.

• Journal of Auto-vehicle Safety Association
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• v.8 no.4
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• pp.12-17
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• 2016

NHTSA (National Highway Traffic Safety Administration) has offered consumers the vehicle safety information on their car since 1978. NHTSA believes that they contribute auto makers to develop safer vehicle for customers, which will result in even lower numbers of deaths and injuries resulting from motor vehicle crashes. NHTSA has been studied why people are still dying in frontal test despite of the use of many restraints system and they understand that current test does not reflect real world crash data such as oblique and corner impact test. As a result, NHTSA announced that a new test method will be introduced to use of enhanced biofidelic dummy and new crash avoidance technology evaluation from 2019. New and refined injury criteria will be applied to Head / Neck / Chest / Lower Leg. BrIC(Brain Injury Criterion)value in NHTSA test results using THOR dummy from 2014 to 2015 was average 0.91 and 1.24 in driver and passenger dummies. IIHS 64kph SOF test is the most likely to new frontal oblique test in an aspect of offset impact which is being studied by NHTSA. In this paper, we focused on head injury, especially brain injury - BrIC and conducted IIHS 64kph SOF (Small Offset Front) test with Hybrid III dummy to evaluate the injury for BrIC. Based on the test results, these data can be predicted BrIC level and US NCAP rating with current vehicle.

• Journal of Auto-vehicle Safety Association
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• v.15 no.1
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• pp.55-62
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• 2023

In this study, a chest deflection is predicted by introducing a deep learning technique with the results of the frontal impact of the USNCAP conducted for 110 car models from MY2018 to MY2020. The 120 data are divided into training data and test data, and the training data is divided into training data and validation data to determine the hyperparameters. In this process, the deceleration data of each vehicle is averaged in units of 10 ms from crash pulses measured up to 100 ms. The performance of the deep learning model is measured by the indices of the mean squared error and the mean absolute error on the test data. A DNN (Deep Neural Network) model can give different predictions for the same hyperparameter values at every run. Considering this, the mean and standard deviation of the MSE (Mean Squared Error) and the MAE (Mean Absolute Error) are calculated. In addition, the deep learning model performance according to the inclusion of CVW (Curb Vehicle Weight) is also reviewed.

• Journal of the korean Society of Automotive Engineers
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• v.14 no.2
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• pp.88-98
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• 1992

Real automobiles have been utilized to study the occupant behaviors and the response of the structures in the crash environment. Since various parameters are involved in the automobile crashworthiness, a number of experiments must be conducted. The experiments have been contributed to increasing the cost due to the fact that the test is quite expensive. Therefore, computer simulation is adopted to reduce the number of experiments. A few computer programs have been developed specifically to solve the occupant responses in the crash environment. In this research, a software is used to study the occupant dynamic analysis. A modeling of occupant analysis is established for a passenger car and the results are verified through comparisons with real experiments. In the modeling, data are tuned very carefully so that simulated results such as HIC(Head Injury Criterion) and acceleration of each body may approximate to the experimental results. The compared experiment is a barrier test which is carried out by frontal impact. A feedback to the design process is suggested from the result of this research.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1035-1040
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• 2004

In the proto design stage of a new car, the performance of an occupant protection system is often evaluated by CAE instead of the real test. CAE predicts and recommends the appropriate design values hence reducing the number of the real tests. However, the existing researches using CAE in predicting the performances do not consider the uncertainties of parameters, in which inconsistency between the actual test results and CAE exists. In this research, the optimization procedure of a protection system such as airbag and load limiter is suggested for the frontal collision. The DACE modeling known as Kriging interpolation is introduced to obtain the meta model of the system followed by the tabu search method to determine a global optimum. Finally, the distribution of a suggested design is determined through the Monte-Carlo Simulation.

• Journal of the Korean Society of Safety
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• v.26 no.5
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• pp.7-12
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• 2011

The crash cushion has drawn a great attention because of its versatility, efficiency and simplicity in reducing the mortality and damages from traffic accidents. However, the existing cushion systems are high priced or have limited functions. The purpose of the study was to devise an improved crash cushion which can offer higher safety compared to the available ones at present. In addition, the conformity of the cushion with the facility standards was assessed through computer simulation for collision with vehicles. The novel cushion system adopts the used tires as shock absorber, which can not only secure cushioning effect but also reduce the production cost. Moreover, it is highly durable and easy to maintain and repair the damaged parts. According to the simulation using BARRIER VII program, the novel cushion system showed PHD of 17.4 g and 10.1 g for a frontal collision and a side collision, respectively. Based on the results, it could be concluded that the novel cushion system met the test standards in the guideline for road safety facility installation and management.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.6
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• pp.1-8
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• 2014

Safety performance of a new car is evaluated through USNCAP and their results in the star rating are provided to the consumers. It is very important to obtain high score of USNCAP to appeal their performance to consumers. Therefore the car companies have made the effort to improve their car safety performance. These efforts should satisfy the demand not only to get high score but also to pass the FMVSS, NHTSA regulations on safety. Huge numbers of car crash tests have been conducted on these bases by car companies. However physical tests spend too much cost and time, as an alternative way, the simulation on the car crash could be a solution to reduce the cost and time. Therefore the simulations have been widely conducted in car industry and various researches on this have been reported. In this study, restraint system had been optimized to minimize the injury of female passenger. Belted $5^{th}%ile$ female frontal crash test was selected from various test methods of USNCAP for the study. Initial velocity of the test was 56km/h. The combination injury probability of USNCAP was selected as an objective function and the injury limit value, which was defined in FMVSS, was set to an optimization constraint. Many researches that were similar to this study had been conducted, however most of them had limitation that interaction between airbag and safety belt had not been considered. Contrary to these researches, the interaction was considered in this study.

• Proceedings of the KSME Conference
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• 2000.04a
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• pp.224-229
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• 2000

This paper describe a (mite element computer simulation of a absorption system using full scale car crash test. The full scale test selected for this study is a 80kmh frontal, side and 25% offset impact of a 1993 Ford Taurus vehicle into a absorption system. This absorption system has external rubber and internal steel pannel. This simulation has completed for decision of these components energy absorption performance. Dynamical performance of this system and movement are obtained from this simulation. and then We can appreciate the safety of passenger from measure the vehicle C.G's acceleration.