Jingwen Hu

A statistical human rib cage geometry model accounting for variations by age, sex, stature and body mass index

In this study, we developed a statistical rib cage geometry model accounting for variations by age, sex, stature and body mass index (BMI). Thorax CT scans were obtained from 89 subjects approximately evenly distributed among 8 age groups and both sexes. Threshold-based CT image segmentation was performed to extract the rib geometries, and a total of 464 landmarks on the left side of each subject׳s ribcage were collected to describe the size and shape of the rib cage as well as the cross-sectional geometry of each rib. Principal component analysis and multivariate regression analysis were conducted to predict rib cage geometry as a function of age, sex, stature, and BMI, all of which showed strong effects on rib cage geometry. Except for BMI, all parameters also showed significant effects on rib cross-sectional area using a linear mixed model. This statistical rib cage geometry model can serve as a geometric basis for developing a parametric human thorax finite element model for quantifying effects from different human attributes on thoracic injury risks.

A numerical investigation of factors affecting cervical spine injuries during rollover crashes.

Study Design. Factors affecting the risk of cervical spine injury in rollover crashes were investigated using a detailed finite element human head-neck model. Objective. Analyze systematically neck responses and associated injury predictors under complex loading conditions similar to real-world rollover scenarios and use the findings to identify potential design improvements. Summary of Background Data. Although many previous experimental and numerical studies have focused on cervical spine injury mechanisms and tolerance, none of them have investigated the risk of cervical spine injuries under loading condition similar to that in rollovers. Methods. The effects of changing the coefficient of friction (COF), impact velocity, padding material thickness and stiffness, and muscle force on the risk of neck injuries were analyzed in 16 different impact orientations based on a Taguchi array of design of experiments. Results. Impact velocity is the most important factor in determining the risk of cervical spine fracture (P = 0.000). Decreases in the COF between the head and impact surface can effectively reduce the risk of cervical spine fracture (P = 0.038). If the COF is not 0, an impact with lateral force component could sometimes increase the risk of cervical spine fracture; and the larger the oriented angle of the impact surface, the more important it becomes to reduce the COF to protect the neck. Soft (P = 0.033) and thick (P = 0.137) padding can actually decrease the neck fracture risk, which is in contrast to previous experimental data. Conclusion. A careful selection of proper padding stiffness and thickness, along with a minimized COF between the head and impact surface or between the padding and its supporting structure, may simultaneously decrease the risk of head and neck injuries during rollover crashes. A seatbelt design to effectively reduce/eliminate the head-to-roof impact velocity is also very crucial to enhance the neck protection in rollovers.

Quantifying dynamic mechanical properties of human placenta tissue using optimization techniques with specimen-specific finite-element models

Motor-vehicle crashes are the leading cause of fetal deaths resulting from maternal trauma in the United States, and placental abruption is the most common cause of these deaths. To minimize this injury, new assessment tools, such as crash-test dummies and computational models of pregnant women, are needed to evaluate vehicle restraint systems with respect to reducing the risk of placental abruption. Developing these models requires accurate material properties for tissues in the pregnant abdomen under dynamic loading conditions that can occur in crashes. A method has been developed for determining dynamic material properties of human soft tissues that combines results from uniaxial tensile tests, specimen-specific finite-element models based on laser scans that accurately capture non-uniform tissue-specimen geometry, and optimization techniques. The current study applies this method to characterizing material properties of placental tissue. For 21 placenta specimens tested at a strain rate of 12/s, the mean failure strain is 0.472+/-0.097 and the mean failure stress is 34.80+/-12.62 kPa. A first-order Ogden material model with ground-state shear modulus (mu) of 23.97+/-5.52 kPa and exponent (alpha(1)) of 3.66+/-1.90 best fits the test results. The new method provides a nearly 40% error reduction (p<0.001) compared to traditional curve-fitting methods by considering detailed specimen geometry, loading conditions, and dynamic effects from high-speed loading. The proposed method can be applied to determine mechanical properties of other soft biological tissues.

A Stochastic Visco-hyperelastic Model of Human Placenta Tissue for Finite Element Crash Simulations

Placental abruption is the most common cause of fetal deaths in motor-vehicle crashes, but studies on the mechanical properties of human placenta are rare. This study presents a new method of developing a stochastic visco-hyperelastic material model of human placenta tissue using a combination of uniaxial tensile testing, specimen-specific finite element (FE) modeling, and stochastic optimization techniques. In our previous study, uniaxial tensile tests of 21 placenta specimens have been performed using a strain rate of 12/s. In this study, additional uniaxial tensile tests were performed using strain rates of 1/s and 0.1/s on 25 placenta specimens. Response corridors for the three loading rates were developed based on the normalized data achieved by test reconstructions of each specimen using specimen-specific FE models. Material parameters of a visco-hyperelastic model and their associated standard deviations were tuned to match both the means and standard deviations of all three response corridors using a stochastic optimization method. The results show a very good agreement between the tested and simulated response corridors, indicating that stochastic analysis can improve estimation of variability in material model parameters. The proposed method can be applied to develop stochastic material models of other biological soft tissues.

Effects of obesity on occupant responses in frontal crashes: a simulation analysis using human body models.

The objective of this study is to investigate the effects of obesity on occupant responses in frontal crashes using whole-body human finite element (FE) models representing occupants with different obesity levels. In this study, the geometry of THUMS 4 midsize male model was varied using mesh morphing techniques with target geometries defined by statistical models of external body contour and exterior ribcage geometry. Models with different body mass indices (BMIs) were calibrated against cadaver test data under high-speed abdomen loading and frontal crash conditions. A parametric analysis was performed to investigate the effects of BMI on occupant injuries in frontal crashes based on the Taguchi method while controlling for several vehicle design parameters. Simulations of obese occupants predicted significantly higher risks of injuries to the thorax and lower extremities in frontal crashes compared with non-obese occupants, which is consistent with previous field data analyses. These higher injury risks are mainly due to the increased body mass and relatively poor belt fit caused by soft tissues for obese occupants. This study demonstrated the feasibility of using a parametric human FE model to investigate the obesity effects on occupant responses in frontal crashes.

A parametric ribcage geometry model accounting for variations among the adult population

The objective of this study is to develop a parametric ribcage model that can account for morphological variations among the adult population. Ribcage geometries, including 12 pair of ribs, sternum, and thoracic spine, were collected from CT scans of 101 adult subjects through image segmentation, landmark identification (1016 for each subject), symmetry adjustment, and template mesh mapping (26,180 elements for each subject). Generalized procrustes analysis (GPA), principal component analysis (PCA), and regression analysis were used to develop a parametric ribcage model, which can predict nodal locations of the template mesh according to age, sex, height, and body mass index (BMI). Two regression models, a quadratic model for estimating the ribcage size and a linear model for estimating the ribcage shape, were developed. The results showed that the ribcage size was dominated by the height (p=0.000) and age-sex-interaction (p=0.007) and the ribcage shape was significantly affected by the age (p=0.0005), sex (p=0.0002), height (p=0.0064) and BMI (p=0.0000). Along with proper assignment of cortical bone thickness, material properties and failure properties, this parametric ribcage model can directly serve as the mesh of finite element ribcage models for quantifying effects of human characteristics on thoracic injury risks.

Rear Seat Restraint System Optimization for Older Children in Frontal Crashes

Objective: Analyses of crash injury data have shown that injury risk increases when children transition from belt-positioning boosters to the vehicle seat belt alone. The objective of this study is to investigate how to improve the restraint environment for these children. Methods: A parametric analysis was conducted to investigate the effects of body size, seat belt anchorage locations, and rear seat design parameters on the injury risks in frontal crashes of children aged 6 to 12 years old using a newly developed parametric child anthropomorphic test dummy (ATD) model. Restraint design optimizations were also conducted to obtain ranges of optimal restraint system configurations that provide best protections for 6-, 9-, and 12-year-old children. Results: Simulation results showed that child body size was the dominant factor affecting outcome measures. In general, lower and more rearward D-rings (upper belt anchorages), higher and more forward lap belt anchorages, and shorter, stiffer, and thinner seat cushions were associated with improved restraint performance. In these simulations, children with smaller body sizes require more-forward D-rings, inboard anchors, and outboard anchor locations to avoid submarining. However, these anchorage locations increase head excursions relative to more-rearward anchorages. Conclusions: The balance of reducing head and knee excursions and preventing submarining indicates that an optimization approach is necessary to improve protection for 6- to 12-year-old child occupants. The findings of this study provided design guidelines for future rear seat restraint system. Supplemental materials are available for this article. Go to the publishers online edition of Traffic Injury Prevention to view the supplemental file.

A Statistical Skull Geometry Model for Children 0-3 Years Old

Head injury is the leading cause of fatality and long-term disability for children. Pediatric heads change rapidly in both size and shape during growth, especially for children under 3 years old (YO). To accurately assess the head injury risks for children, it is necessary to understand the geometry of the pediatric head and how morphologic features influence injury causation within the 0–3 YO population. In this study, head CT scans from fifty-six 0–3 YO children were used to develop a statistical model of pediatric skull geometry. Geometric features important for injury prediction, including skull size and shape, skull thickness and suture width, along with their variations among the sample population, were quantified through a series of image and statistical analyses. The size and shape of the pediatric skull change significantly with age and head circumference. The skull thickness and suture width vary with age, head circumference and location, which will have important effects on skull stiffness and injury prediction. The statistical geometry model developed in this study can provide a geometrical basis for future development of child anthropomorphic test devices and pediatric head finite element models.

TOWARD DESIGNING PEDESTRIAN-FRIENDLY VEHICLES

In this study, we present a literature review and provide insights into vehicle designs to improve pedestrian safety. Field data show that pedestrian injuries are highly correlated with impact speed, pedestrian age, and vehicle type. The increased proportion of older pedestrians and SUVs will likely result in more pedestrian injuries, especially those involving the torso. Adding energy–absorbing materials to the vehicle front–end structures is cost–effective, but often conflicts with other design considerations. Deployable passive safety designs and active safety designs have demonstrated considerable benefits for reducing pedestrian injuries. Integrated passive and active systems are recommended for a further enhancement of pedestrian protection. However, the benefits from different pedestrian–safety designs vary with different types of vehicles and pedestrians with different statures and ages. Consequently, it is important to consider vehicle–specific safety designs, and population–age profile may also play an important role in selecting the pedestrian safety features.

Development of a finite element model for simulation of rollover crashes

Rollover crashes are complex by their very nature, and have stimulated many researches aimed at improved occupant safety. In order to investigate the vehicle crashworthiness during rollovers, several test modes are generally used to replicate different real world rollover scenarios. However, such tests are very expensive, especially during the development stage of a new car line. Computer modeling is a cost-effective way to study rollover crashes. However, a survey of literature showed that only rigid-body dynamics based models have been used for rollover simulations. It is well known that this class of models cannot be used to simulate component deformation and structural collapses. Finite element (FE) method, which has been widely used to simulate frontal and side crashes, was rarely used for simulating rollover crashes, due mainly to the relative long duration of a rollover crash. The objective of this study was to develop an FE model for investigating vehicle crashworthiness during three commonly used rollover tests. An FE model of an SUV was developed in this study. Several sub-models, namely the vehicle structure sub-model, the tire sub-model, the suspension system sub-model, the restraint system sub-model, and the dummy model were generated and integrated together. The structure model was first used to simulate the roof crush test as prescribed in FMVSS 216. The resulting load versus roof crush curve matched well against test results. The integrated model was then used to simulate three laboratory-based rollover test modes, namely the SAE J2114 dolly test, curb-trip test, and corkscrew test. For each test mode, up to 1.5 seconds of simulation time (about 1 full vehicle roll) were computed. The vehicle kinematics, including the angular velocity, lateral acceleration, and vertical acceleration during these three test modes were computed and compared with experimental data. The simulated dummy head accelerations, timing and location of the most severe impact to the dummy’s head were also compared with the experimental results. Results showed very good agreement between the tests and simulations. In order to reduce the computational time, multiple CPUs were used. Approximately ten hours were required to run a 1.5 second rollover simulation on eight CPUs. Thus, simulating rollovers using FE method is quickly becoming a reality.Copyright