A child dies in road traffic crashes every fourth minute. Totally were 186 300 children under the age of 18 killed in vehicle accidents in 2012, even more were severely injured [1]. The World Health Organisation (WHO) could conclude that fatalities in traffic accidents are more likely to occur in low- to middle income countries compared to high income countries [1]. Finite element based human body models has enabled the increased understanding of kinematics and injury mechanisms of child occupants. These models sustain higher biofidelity than the previously used crash test dummies. The European project PIPER [6] had the aim to develop a model that, combined with a framework, would simplify positioning and also to offer a scalable HBM child model. The PIPER framework software and the scalable PIPER model offers child HBM:s within the ages 1.5-6-years old and is an useful tool for the analysis of child occupants.    The present study evaluates the kinematics and dummy responses of the 4- and 6-year old PIPER model evaluated. The objective of this master thesis is to evaluate the PIPER model with respect to its sensitivity to seat belt geometries, child restraint system, load cases and child anthropometrics. The aim of the master thesis is to get an increased comprehension of the PIPER model and its capability to evaluate occupant kinematics relevant for safety developments, with a special focus on seat belt geometry and interaction in frontal impacts.   The PIPER model showed good sensitivity to different seatbelt geometries regarding the abdominal part of the shoulder belt and to different CRS. The PIPER framework was perceived as hard to use and with the presence of errors. The kinematic response showed good accuracy compared to other previous studies with other crash test dummies however, reoccurring error termination could not be neglectable.    The PIPER model is limited to its ease to positioning in desired sitting postures within the PIPER framework. It is regardless of its disadvantages believed to be a suitable tool to further understand occupant kinematics, as for different belt routings, child anthropometrics and dummy responses are further studies needed to validate the outputs that the model offers and to conclude its robustness in crashworthiness tests.

<p>Human body models (HBMs) have been present in the automotive industry for simulating automotive related injury since the turn of the century and have in recent years found a place in assessment of soldier and sports related injury prediction and assessment. This issue is the lack of models that lie outside of the 50th percentile. By a simple application of physics, it is evident that acceleration or force will affect people of varying weights differently. To this end, having the ability to scale a 50th percentile HBM to targets for weight and stature would allow for better characterization on how an impact or acceleration event will affect people of differing size, especially when ~90% of males can fall outside the 50th percentile for weight and stature and HBMs models from vendors exist in only a few variations outside the 50th percentile [1]. Using Corvid Technologies’ 50th percentile model CAVEMAN (capable of being repositioned) as a base, scaled model from the 5th to 95th percentiles of stature and weight were generated based on ANSURII metrics, using a combination of 1D and 3D scaling transformations. These models met their stature and weight metrics when standing and weight metrics when positioned. </p> <p>After creation of a framework to scale the CAVEMAN HMB, creation of a digital twin to the HIRRT Lab helmet testing model commenced. With the HIRRT Lab’s history of experimental testing of football helmets, a natural turn of events was to bring helmet performance testing into the computational space. This digital twin was a natural evolution and addition to the HIRRT Lab’s helmet testing as it would enable manipulation of helmets that would be infeasible experimentally. After calibration of the barehead using experimental data, helmeted simulation began. Angle of impact, while it was found to effect peak translational acceleration, was found to profoundly effect peak rotational acceleration. With this in mind, various angles of impact were simulated to produce curves similar to experimental results. Helmeted simulations were qualitatively dissimilar to experimental data, prompting a modification of the padding material used by the models. Following various modifications of the padding material model, these inconsistencies between simulated helmets and experimentally tested helmets persisted. These inconsistencies highlight a need for better characterization of material, such as foam, and more thorough validation of simulated helmet models. The results of the helmeted simulations are difficult to quantify, as the evaluation criteria used for the BioCore model did not include rotational acceleration, indicating a need for further research and simulation is necessary. </p>

Master of Science / Department of Electrical Engineering / William Kuhn / When enough charges accumulate on two objects, the air dielectric between them breaks down to create a phenomenon known as electrostatic discharge (ESD). ESD is of great concern in the integrated circuit industry because of the damage it can cause to ICs. The problem will only become worse as process components become smaller. The three main types of ESD experienced by an IC are the human body model (HBM), the charged device model (CDM), and the machine model (MM). HBM ESD has the highest voltage while CDM ESD has the highest bandwidth and current of the three ESD types. Integrated circuits generally include ESD protection circuitry connected to their pads. Pads are the connection between the IC and the outside world, making them the required location for circuitry designed to route ESD events away from the IC's internal circuitry. The most basic protection pads use diodes connected from I/O to VDD and I/O to ground. A voltage clamp between VDD and ground is also necessary to protect against CDM and MM event types where the device may not yet have a low impedance supply path connected. The purpose of this research is to investigate the performance of ESD circuits and to develop a method for detecting the occurrence of an ESD event in an integrated circuit by utilizing IC fuses. The combination of IC fuses and detection circuitry designed to sense a broken fuse allows the IC to perform a built-in self-test (BIST) for ESD to identify compromised ICs, preventing manufacturers from shipping damaged circuits. Simulations are used to design an optimized protection circuit to complement the proposed ESD detection circuit. Optimization of an ESD pad circuit increases the turn-on speed of its voltage clamps and decreases the series resistance of its protection diodes. These improvements minimize the stress voltage placed on internal circuitry due to an ESD event. An ESD measurement setup is established and used to verify voltage clamp operation. This research also proposes an ESD detection circuit based on IC fuses, which fail during an ESD event. A variety of IC fuses are tested using the ESD measurement setup as well as a TLP setup in order to determine the time and current needed for them to break. Suitable IC fuses have a resistance less than 5 Ω and consistently break during the first trial.

Although there have been tremendous improvements in crash safety there has been an increasing trend in side impact fatalities, rising from 30% to 37% of total fatalities from 1975 to 2004 (NHTSA, 2004). Between 1979 and 2004, 63% of AIS≥4 injuries in side impact resulted from thoracic trauma (NHTSA, 2004). Lateral impact fatalities, although decreasing in absolute numbers, now comprise a larger percentage of total fatalities. Safety features are typically more effective in frontal collisions compared to side impact due to the reduced distance between the occupant and intruding vehicle in side impact collisions. Therefore, an increased understanding of the mechanisms governing side impact injury is necessary in order to improve occupant safety in side impact auto crash. This study builds on an advanced numerical human body model with focus on a detailed thoracic model, which has been validated using available post mortem human subject (PMHS) test data for pendulum and side sled impact tests (Forbes, 2005). Crash conditions were investigated through use of a modified side sled model used to reproduce the key conditions present in full scale crash tests. The model accounts for several important factors that contribute to occupant response based on the literature. These factors are; the relative velocities between the seat and door, the occupant to door distance, the door shape and compliance. The side sled model was validated by reproducing the crash conditions present in FMVSS 214 and IIHS side impact tests and comparing the thoracic compression, velocity, and Viscous Criterion (VC) response determined by the model to the response of the ES-2 dummy used in the crash tests. Injury was predicted by evaluating VCmax, selected for its ability to predict rate-sensitive soft tissue injury during thoracic compression (Lau & Viano, 1986). The Ford Taurus FMVSS 214 and Nissan Maxima IIHS tests were selected from side impact crash test data found in the NHTSA database because they included factors not present in standard side impact test procedures. These factors were; the presence of door accelerometers used to provide input velocities to the side impact model and the use of a ES-2 (rather than the SID) to facilitate comparison of VC response to the human body model. Also, the two crash test procedures (FMVSS 214 & IIHS) were selected to ensure accurate side impact model response to different impact scenarios. The side impact model was shown to closely reproduce the timing and injury response of the full-scale FMVSS 214 side impact test of a Ford Taurus, as well as the IIHS side impact test of a Nissan Maxima. The side impact model was then used to investigate the effects of door to occupant spacing, door velocity profile, armrest height, seat foam, restraint system, and arm position. It was found that the VCmax was controlled by both the first and second peaks typically found in door velocity profiles, but the effect of each varies depending on the situation. This study found that VCmax was reduced by 73-88% when door intrusion was eliminated compared to the VC response incurred by an intruding door. Also, the presence of a deformable door based on physical geometry and material characteristics rather than a simplified rigid door reduced VCmax by 16% in this study. The study on seat foam determined that significant effects on VC response can be made by modest adjustments in foam properties. Low stiffness seat foam was found to increase VCmax by 41% when compared to the VC response when using high stiffness foam. Arm position has been proven to be a relevant factor in side impact crash. Positioning the arms parallel to the thorax, in the “down” position, caused a 42% increase in VCmax when compared to the VC response determined with the arms positioned at 45 degrees. Finally, although restraint systems have limited influence on side impact crash safety compared to front and rear impacts, this study found that the presence of a pre-tensioning restraint system reduced VCmax by 13% when compared to the VC response of an un-belted occupant. It should be noted that the current study was limited to velocity profiles obtained from a specific FMVSS 214 test and therefore results and observations are restricted to the confines of the input conditions used. However, the side impact model developed is a useful tool for evaluating factors influencing side impact and can be used to determine occupant response in any side impact crash scenario when the appropriate input conditions are provided.

Thoracic injury is the most dominant segment of automotive side impact traumas. A numerical model that can predict such injuries in crash simulation is essential to the process of designing a safer motor vehicle. The focus of this study was to develop a numerical model to predict lung response and injury in side impact car crash scenarios. A biofidelic human body model was further developed. The geometry, material properties and boundary condition of the organs and soft tissues within the thorax were improved with the intent to ensure stress transmission continuity and model accuracy. The thoracic region of the human body model was revalidated against three pendulum and two sled impact scenarios at different velocities. Other body regions such as the shoulder, abdomen, and pelvis were revalidated. The latest model demonstrated improvements in every response category relative to the previous version of the human body model. The development of the lung model involved advancements in the material properties, and boundary conditions. An analytical approach was presented to correct the lung properties to the in-situ condition. Several injury metric predictor candidates of pulmonary contusion were investigated and compared based on the validated pendulum and sled impact scenarios. The results of this study confirmed the importance of stress wave focusing, reflection, and concentration within the lungs. The bulk modulus of the lung had considerable influence on injury metric outcomes. Despite the viscous criterion yielded similar response for different loading conditions, this study demonstrated that the level of contusion volume varied with the size of the impact surface area. In conclusion, the human body model could be used for the analysis of thoracic response in automotive impact scenarios. The overall model is capable of predicting thoracic response and lung contusion. Future development on the heart and aorta can expand the model capacity to investigate all vital organ injury mechanisms.

Although there have been tremendous improvements in crash safety there has been an increasing trend in side impact fatalities, rising from 30% to 37% of total fatalities from 1975 to 2004 (NHTSA, 2004). Between 1979 and 2004, 63% of AIS≥4 injuries in side impact resulted from thoracic trauma (NHTSA, 2004). Lateral impact fatalities, although decreasing in absolute numbers, now comprise a larger percentage of total fatalities. Safety features are typically more effective in frontal collisions compared to side impact due to the reduced distance between the occupant and intruding vehicle in side impact collisions. Therefore, an increased understanding of the mechanisms governing side impact injury is necessary in order to improve occupant safety in side impact auto crash. This study builds on an advanced numerical human body model with focus on a detailed thoracic model, which has been validated using available post mortem human subject (PMHS) test data for pendulum and side sled impact tests (Forbes, 2005). Crash conditions were investigated through use of a modified side sled model used to reproduce the key conditions present in full scale crash tests. The model accounts for several important factors that contribute to occupant response based on the literature. These factors are; the relative velocities between the seat and door, the occupant to door distance, the door shape and compliance. The side sled model was validated by reproducing the crash conditions present in FMVSS 214 and IIHS side impact tests and comparing the thoracic compression, velocity, and Viscous Criterion (VC) response determined by the model to the response of the ES-2 dummy used in the crash tests. Injury was predicted by evaluating VCmax, selected for its ability to predict rate-sensitive soft tissue injury during thoracic compression (Lau & Viano, 1986). The Ford Taurus FMVSS 214 and Nissan Maxima IIHS tests were selected from side impact crash test data found in the NHTSA database because they included factors not present in standard side impact test procedures. These factors were; the presence of door accelerometers used to provide input velocities to the side impact model and the use of a ES-2 (rather than the SID) to facilitate comparison of VC response to the human body model. Also, the two crash test procedures (FMVSS 214 & IIHS) were selected to ensure accurate side impact model response to different impact scenarios. The side impact model was shown to closely reproduce the timing and injury response of the full-scale FMVSS 214 side impact test of a Ford Taurus, as well as the IIHS side impact test of a Nissan Maxima. The side impact model was then used to investigate the effects of door to occupant spacing, door velocity profile, armrest height, seat foam, restraint system, and arm position. It was found that the VCmax was controlled by both the first and second peaks typically found in door velocity profiles, but the effect of each varies depending on the situation. This study found that VCmax was reduced by 73-88% when door intrusion was eliminated compared to the VC response incurred by an intruding door. Also, the presence of a deformable door based on physical geometry and material characteristics rather than a simplified rigid door reduced VCmax by 16% in this study. The study on seat foam determined that significant effects on VC response can be made by modest adjustments in foam properties. Low stiffness seat foam was found to increase VCmax by 41% when compared to the VC response when using high stiffness foam. Arm position has been proven to be a relevant factor in side impact crash. Positioning the arms parallel to the thorax, in the “down” position, caused a 42% increase in VCmax when compared to the VC response determined with the arms positioned at 45 degrees. Finally, although restraint systems have limited influence on side impact crash safety compared to front and rear impacts, this study found that the presence of a pre-tensioning restraint system reduced VCmax by 13% when compared to the VC response of an un-belted occupant. It should be noted that the current study was limited to velocity profiles obtained from a specific FMVSS 214 test and therefore results and observations are restricted to the confines of the input conditions used. However, the side impact model developed is a useful tool for evaluating factors influencing side impact and can be used to determine occupant response in any side impact crash scenario when the appropriate input conditions are provided.

Thoracic injury is the most dominant segment of automotive side impact traumas. A numerical model that can predict such injuries in crash simulation is essential to the process of designing a safer motor vehicle. The focus of this study was to develop a numerical model to predict lung response and injury in side impact car crash scenarios. A biofidelic human body model was further developed. The geometry, material properties and boundary condition of the organs and soft tissues within the thorax were improved with the intent to ensure stress transmission continuity and model accuracy. The thoracic region of the human body model was revalidated against three pendulum and two sled impact scenarios at different velocities. Other body regions such as the shoulder, abdomen, and pelvis were revalidated. The latest model demonstrated improvements in every response category relative to the previous version of the human body model. The development of the lung model involved advancements in the material properties, and boundary conditions. An analytical approach was presented to correct the lung properties to the in-situ condition. Several injury metric predictor candidates of pulmonary contusion were investigated and compared based on the validated pendulum and sled impact scenarios. The results of this study confirmed the importance of stress wave focusing, reflection, and concentration within the lungs. The bulk modulus of the lung had considerable influence on injury metric outcomes. Despite the viscous criterion yielded similar response for different loading conditions, this study demonstrated that the level of contusion volume varied with the size of the impact surface area. In conclusion, the human body model could be used for the analysis of thoracic response in automotive impact scenarios. The overall model is capable of predicting thoracic response and lung contusion. Future development on the heart and aorta can expand the model capacity to investigate all vital organ injury mechanisms.

In this master thesis it have been investigated how the stiffness of a seat affect the risk of neck injuries, e.g whiplash associated disorders, in a rear end low velocity car collision using a female human body model, HBM, and if dividing the seat into several sections with different stiffnesses. The project is performed in collaboration with CEVT, China Euro Vehicle Technology, a innovation center of the Geely Holding Group. The HBM used is the VIVA open source HBM developed by Chalmers University of Technology together with Volvo Cars, The Swedish National Road and Transport ResearchInstitute (VTI) and Folksams forskningsstiftelse. Two different seats were investigated, a generic seat and the seat of the existing Lynk&amp;Co 01. The stiffness of the seat had a significant impact on the risk of neck injuries, but does not seem to be a good idea to divide the seat into several sections since the height of the individual in the seat influence what stiffness is optimal for each section. It was also discovered that the relative distance between the head and the headrest at the moment of impact has a great affect on the risk of neck injuries.

The increased prevalence of crash avoidance technologies like autonomous emergency braking necessitates understanding of occupant responses during low-speed frontal pre-crash braking and low-severity crash events. Active human body models (HBMs) have emerged as valuable tools to evaluate occupant safety during these events, but must be validated with relevant volunteer data to accurately represent the responses of live occupants. The objective of this dissertation was to quantify the occupant responses of relaxed and braced 5th percentile female and 50th percentile male volunteers during low-speed frontal and frontal-oblique sled tests designed to simulate pre-crash braking and low-severity crash events. A study comprised of 160 low-speed sled tests was performed with 20 volunteers. The volunteers' kinematics, kinetics, and muscle responses were compared to determine how altering impact direction (frontal and frontal-oblique), impact severity (1 g and 2.5 g), demographic group (mid-size male and small female), and muscle state (relaxed and braced) affected occupant responses. The volunteers' occupant responses were significantly affected by impact direction, impact severity, demographic group, and muscle state. The frontal-oblique tests resulted in greater leftward excursions compared to the frontal tests. Increasing the pulse severity resulted in greater forward excursions, reaction forces, and muscle activation. The male volunteers exhibited greater forward excursions and reaction forces compared to the female volunteers. However, the two demographic groups exhibited similar muscle activation during the sled tests. Bracing increased the volunteers' initial joint angles, muscle activation, and reaction forces prior to the sled tests. Bracing decreased forward excursions and increased reaction forces during the sled tests. The relaxed volunteers exhibited greater relative changes in occupant responses compared to the braced volunteers. Overall, this study demonstrated that muscle activation significantly affected the volunteers' kinematics, kinetics, and muscle responses for both mid-size males and small females during low-speed events. Observed differences between demographic groups were more prominent when relaxed and more diminished when braced. These results underscore the importance of validating active HBMs with relevant volunteer data in order to be more representative of live occupants for a wider range of demographic groups in varying muscle states. Finally, this dissertation provides a large, comprehensive, and novel biomechanical dataset that can be used to develop and validate active HBMs for use in assessing occupant response during frontal pre-crash braking and low-severity crash events. These models will help improve the understanding of potential injury risk and development of effective vehicle safety systems for use during low-speed events. / Doctor of Philosophy / Computer models, known as active human body models (HBMs), have emerged as tools that can be used to assess occupant safety during low-speed vehicle crashes. In these types of events, occupants have enough time to react and potentially brace before the crash, which could in turn affect their responses during the crash. It is important to understand how occupants respond during crashes so that effective vehicle safety systems can be developed. Active HBMs are particularly valuable because they can simulate muscle activation to reflect the response of live occupants. However, data are needed from live occupants to ensure that these models are accurate. To gather this data, a study was performed where volunteers experienced low-speed frontal sled tests when they were relaxed and braced. The sled tests were designed to simulate pre-crash braking and low-severity vehicle crashes. Mid-size male and small female volunteers were recruited to participate to represent the standard adult occupant populations used in current frontal impact vehicle safety standards. A motion capture system was used to measure the volunteers' forward motion, load cells were used to measure the volunteers' exerted reaction forces on the test buck, and electrodes were used to measure the volunteers' muscle activity. The volunteers' responses were significantly different between the relaxed and braced muscle states, and between the males and females. Comparing between males and females, the males moved farther forward and exerted larger reaction forces, but both demographic groups exhibited similar muscle responses. Comparing between muscle states, bracing increased the volunteers' muscle activation and reaction forces before the sled tests. Bracing also increased the volunteers' reaction forces during the sled tests, but decreased forward movement. Overall, the volunteers exhibited greater relative changes in response when they were relaxed compared to when they were braced. Overall, this study demonstrated that muscle activation significantly affected the volunteers' responses for both mid-size males and small females during low-speed events. These results highlight the importance of developing active HBMs with relevant volunteer data in order to be more representative of live occupants. Finally, the data from this study can be used to develop active HBMs to improve their accuracy, so that the models can be used to assess occupant safety during low-speed frontal vehicle crashes. This will help improve the understanding of potential injury risk and development of effective vehicle safety systems, to reduce the number of injuries caused by vehicle crashes.

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