Search Results

Efficient brain strain estimation is critical for routine application of a head injury model. Lately, a convolutional neural network (CNN) has been successfully developed to estimate spatially detailed brain strains instantly and accurately in contact sports. Here, we extend its application to automotive head impacts, where impact profiles are typically more complex with longer durations. Head impact kinematics (N=458) from two public databases were used to generate augmented impacts (N=2694). They were simulated using the anisotropic Worcester Head Injury Model (WHIM) V1.0, which provided baseline elementwise peak maximum principal strain (MPS). For each augmented impact, rotational velocity (vrot) and the corresponding rotational acceleration (arot) profiles were concatenated as static images to serve as CNN input.

On December 2015, The National Highway Traffic Safety Administration (NHTSA) published its proposal to implement U.S New Car Assessment Program (NCAP) changes covering three categories of crashworthiness, crash avoidance and pedestrian protection, beginning with the 2019 model year. The crashworthiness category included a new frontal oblique impact (OI) test protocol. The test compromises of a new Oblique Moving Deformable Barrier (OMDB), new THOR 50th percentile male (THOR-50M) anthropomorphic test device (ATD), and a new test configuration. An OMDB of 2,486 kg (5,480 lb) impacts a stationary target vehicle at a speed of 90 kph (56 mph) at an angle of 15 degrees with a 35% barrier overlap with the front end of the target vehicle. In vehicle-to-vehicle collisions, the lighter weight vehicle experience higher velocity change and higher acceleration levels, thereby, occupants in the lighter vehicle experience higher injury risk.

The objective of this study is to develop a method that uses a combination of field data analysis, naturalistic driving data analysis, and computational simulations to explore the potential injury reduction capabilities of integrating passive and active safety systems in frontal impact conditions. For the purposes of this study, the active safety system is actually a driver assist (DA) feature that has the potential to reduce delta-V prior to a crash, in frontal or other crash scenarios. A field data analysis was first conducted to estimate the delta-V distribution change based on an assumption of 20% crash avoidance resulting from a pre-crash braking DA feature. Analysis of changes in driver head location during 470 hard braking events in a naturalistic driving study found that drivers’ head positions were mostly in the center position before the braking onset, while the percentage of time drivers leaning forward or backward increased significantly after the braking onset.

The objective of this paper focused on the modeling of an adaptive energy absorbing steering column which is the first phase of a study to develop a modeling methodology for an advanced steering wheel and column assembly. Early steering column designs often consisted of a simple long steel rod connecting the steering wheel to the steering gear box. In frontal collisions, a single-piece design steering column would often be displaced toward the driver as a result of front-end crush. Over time, engineers recognized the need to reduce the chance that a steering column would be displaced toward the driver in a frontal crash. As a result, collapsible, detachable, and other energy absorbing steering columns emerged as safer steering column designs. The safety-enhanced construction of the steering columns, whether collapsible, detachable, or other types, absorb rather than transfer frontal impact energy.

This paper presents the final phase of a study to develop the modeling methodology for an advanced steering assembly with a safety-enhanced steering wheel and an adaptive energy absorbing steering column. For passenger cars built before the 1960s, the steering column was designed to control vehicle direction with a simple rigid rod. In severe frontal crashes, this type of design would often be displaced rearward toward the driver due to front-end crush of the vehicle. Consequently, collapsible, detachable, and other energy absorbing steering columns emerged to address this type of kinematics. These safety-enhanced steering columns allow frontal impact energy to be absorbed by collapsing or breaking the steering columns, thus reducing the potential for rearward column movement in severe crashes. Recently, more advanced steering column designs have been developed that can adapt to different crash conditions including crash severity, occupant mass/size, seat position, and seatbelt usage.

With a goal to help develop pressure sensor calibration and deployment algorithms using computer simulations, an Arbitrary Lagrangian Eulerian (ALE) approach was adopted in this research to predict the responses of side crash pressure sensors for unitized vehicles. For occupant protection, acceleration-based crash sensors have been used in the automotive industry to deploy restraint devices when vehicle crashes occur. With improvements in the crash sensor technology, pressure sensors that detect pressure changes in door cavities have been developed recently for vehicle crash safety applications. Instead of using acceleration (or deceleration) in the acceleration-based crash sensors, the pressure sensors utilize pressure change in a door structure to determine the deployment of restraint devices. The crash pulses recorded by the acceleration-based crash sensors usually exhibit high frequency and noisy responses.

In an attempt to assist pressure sensor algorithm and calibration development using computer simulations, an Arbitrary Lagrangian Eulerian (ALE) approach was adopted in this study to predict the responses of side crash pressure sensors for body-on-frame vehicles. Acceleration based, also called G-based, crash sensors have been used extensively to deploy restraint devices, such as airbags, curtain airbags, seatbelt pre-tensioners, and inflatable seatbelts, in vehicle crashes. With advancements in crash sensor technologies, pressure sensors that measure pressure changes in vehicle side doors have been developed recently and their applications in vehicle crash safety are increasing. The pressure sensors are able to detect and record the dynamic pressure change when the volume of a vehicle door changes as a result of a crash.

This paper reports a study undertaken by the Crash Safety Working Group (CSWG) of the United States Council for Automotive Research (USCAR) to determine generic acceleration pulses for testing and evaluating advanced batteries subjected to inertial loading for application in electric passenger vehicles. These pulses were based on characterizing vehicle acceleration time histories from standard laboratory vehicle crash tests. Crash tested passenger vehicles in the United States vehicle fleet of the model years 2005-2009 were used in this study. Crash test data, in terms of acceleration time histories, were collected from various crash modes conducted by the National Highway Traffic Safety Administration (NHTSA) during their New Car Assessment Program (NCAP) and Federal Motor Vehicle Safety Standards (FMVSS) evaluations, and the Insurance Institute for Highway Safety (IIHS).

This paper reports a 2010 study undertaken to determine generic acceleration pulses for testing and evaluating advanced batteries for application in electric passenger vehicles. These were based on characterizing vehicle acceleration time histories from standard laboratory vehicle crash tests. Crash tested passenger vehicles in the United States vehicle fleet of the model years 2005-2009 were used. The crash test data were gathered from the following test modes and sources: 1 Frontal rigid flat barrier test at 35 mph (NHTSA NCAP) 2 Frontal 40% offset deformable barrier test at 40 mph (IIHS) 3 Side moving deformable barrier test at 38 mph (NHTSA side NCAP) 4 Side oblique pole test at 20 mph (US FMVSS 214/NHTSA side NCAP) 5 Rear 70% offset moving deformable barrier impact at 50 mph (US FMVSS 301). The accelerometers used were from locations in the vehicle where deformation is minor or non-existent, so that the acceleration represents the “rigid-body” motion of the vehicle.

Changes in vehicle safety design technology and the increasing use of seat-belts and airbag restraint systems have gradually changed the relative proportion of lower extremity injuries. These changes in real world injuries have renewed interest and the need of further investigation into occupant injury mechanisms and biomechanical impact responses of the knee-thigh-hip complex during frontal impacts. This study uses a detailed finite element model of the human body to simulate occupant knee impacts experienced in frontal crashes. The human body model includes detailed anatomical features of the head, neck, shoulder, chest, thoracic and lumbar spine, abdomen, pelvis, and lower and upper extremities. The material properties used in the model for each anatomic part of the human body were obtained from test data reported in the literature. The human body model used in the current study has been previously validated in frontal and side impacts.

This study applies a detailed finite element model of the human body to simulate occupant knee impacts experienced in vehicular frontal crashes. The human body model includes detailed anatomical features of the head, neck, chest, thoracic and lumbar spine, abdomen, and lower and upper extremities. The material properties used in the model for each anatomic part of the human body were obtained from test data reported in the literature. The total human body model used in the current study has been previously validated in frontal and side impacts. Several cadaver knee impact tests representing occupants in a frontal impact condition were simulated using the previously validated human body model. Model impact responses in terms of force-time and acceleration-time histories were compared with test results. In addition, stress distributions of the patella, femur, and pelvis were reported for the simulated test conditions.

The biofidelity of the Ford Motor Company human body finite element (FE) model in side impact simulations was analyzed and evaluated following the procedures outlined in ISO technical report TR9790. This FE model, representing a 50th percentile adult male, was used to simulate the biomechanical impact tests described in ISO-TR9790. These laboratory tests were considered as suitable for assessing the lateral impact biofidelity of the head, neck, shoulder, thorax, abdomen, and pelvis of crash test dummies, subcomponent test devices, and math models that are used to represent a 50th percentile adult male. The simulated impact responses of the head, neck, shoulder, thorax, abdomen, and pelvis of the FE model were compared with the PMHS (Post Mortem Human Subject) data upon which the response requirements for side impact surrogates was based. An overall biofidelity rating of the human body FE model was determined using the ISO-TR9790 rating method.

Human abdominal response and injury in blunt impacts was investigated through finite element simulations of cadaver tests using a full human body model of an average-sized adult male. The model was validated at various impact speeds by comparing model responses with available experimental cadaver test data in pendulum side impacts and frontal rigid bar impacts from various sources. Results of various abdominal impact simulations are presented in this paper. Model-predicted abdominal dynamic responses such as force-time and force-deflection characteristics, and injury severities, measured by organ pressures, for the simulated impact conditions are presented. Quantitative results such as impact forces, abdominal deflections, internal organ stresses have shown that the abdomen responded differently to left and right side impacts, especially in low speed impact.

Human thoracic dynamic responses and injuries associated with frontal impact, side impact, and belt loading were investigated and predicted using a complete human body finite element model for an average adult male. The human body model was developed to study the impact biomechanics of a vehicular occupant. Its geometry was based on the Visible Human Project (National Library of Medicine) and the topographies from human body anatomical texts. The data was then scaled to an average adult male according to available biomechanical data from the literature. The model includes details of the head, neck, ribcage, abdomen, thoracic and lumbar spine, internal organs of the chest and abdomen, pelvis, and the upper and lower extremities. The present study is focused on the dynamic response and injuries of the thorax.

This paper describes a CAE-based methodology used to identity major factors influencing vehicle structural performance and crash energy management in full-frontal vehicle-to-vehicle collisions. Finite element models of an “average” SUV and an “average” full-size passenger vehicle were used in this study. The determining factors of vehicle compatibility in multi-vehicle collisions are relative mass, relative stiffness and relative geometry. Four parameters of the average SUV, mass, fore rail length, fore rail thickness, and fore rail height were selected as design variables. A uniformly spaced Optimal Latin Hypercube sampling technique was employed to probe the design space of these variables using thirteen simulation runs. Dash intrusions in the passenger vehicle and the absorbed collision energy in both vehicles were selected as response variables.

The relationship between designing for both rigid fixed barrier (RFB) and vehicle-to-vehicle tests is a topical area of research. Specifically, vehicle-to-vehicle compatibility has been a topic of keen interest to many researchers, and the interplay between the two aspects of design is presently addressed. In this paper, the studied vehicles for potential vehicle-to-vehicle impacts included: sport utility vehicles (SUVs), Pickups (PUs), and passenger cars. The SUV/PU-to-Car frontal impact tests were compared to those obtained from vehicle-to-rigid fixed barrier frontal impacts. Acceleration pulses at the B-pillar/rocker as well as dash and cabin intrusions were monitored and compared. Additionally, the energy distributions in SUV/PU-to-Car crash tests were compared to those of single vehicle-to-RFB tests. It was concluded from the analysis that vehicle weight and front-end stiffness were not always the overriding factors dictating performance.

Light truck vehicles (LTVs), sport utility vehicles (SUVs), and vans collectively make up a growing segment of the total automotive fleet sales, particularly in the United States. The National Highway Traffic Safety Administration (NHTSA) has identified this trend and has increased the extent of its research in vehicle-to-vehicle compatibility. Additionally, vehicle compatibility concerns have also been emphasized by International Harmonization Research Activity (IHRA). Accordingly, with intention to further enhance road safety, research in the area of crash compatibility between cars and LTVs in different crash configurations is of significant importance. This paper describes a part of ongoing research at Ford Motor Company to further investigate the effect of compatibility in SUV/LTV-to-Car crashes.

This paper describes the development and validation of a finite element model of the SID-IIs beta+-prototype dummy using a nonlinear explicit finite element code. The geometry of the SID-IIs dummy is modeled with shell and solid elements from digital scans. The material properties are derived from dynamic tests and the model validation is conducted on component, subassembly and full assembly levels. Component level validation of the head/neck, arm, ribs, and lumbar spine is presented. The model validation of the thorax and pelvis subassemblies as well as pendulum calibration tests (shoulder, thorax, abdomen, and pelvis) and rigid-wall sled tests of the fully assembled dummy mode is also presented. The model response compares favorably with experimental data and provides a reasonable level of confidence in the model biofidelity.