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Complex systems, such as modern advanced driver assistance systems (ADAS), consist of many interacting components. The number of options promises considerable flexibility for configuring systems with many cost-performance-value tradeoffs; however the potential unique configurations are exponentially many prohibiting a build-test-fix approach. Instead, engineering analysis tools for rapid design-space navigation and analysis can be applied to find feasible options and evaluate their potential for correct system behavior and performance subject to functional requirements. The OpenMETA toolchain is a component-based, design space creation and analysis tool for rapidly defining and analyzing systems with large variability and cross-domain requirements. The tool supports the creation of compositional, multi-domain components, based on a user-defined ontology, which captures the behavior and structure of components and the allowable interfaces.

Autonomous vehicles (AVs) have already driven millions of miles on public roads, but even the simplest scenarios have not been certified for safety. Current methodologies for the verification of AV’s decision and control systems attempt to divorce the lower level, short-term trajectory planning and trajectory tracking functions from the behavioral rules-based framework that governs mid-term actions. Such analysis is typically predicated on the discretization of the state space and has several limitations. First, it requires that a conservative buffer be added around obstacles such that many feasible plans are classified as unsafe. Second, the discretized controllers modeled in this analysis require several refinement steps before being implementable on an actual AV, and typically do not allow the specification of comfort-related properties on the trajectories. Consumer-ready AVs use motion planning algorithms that generate smooth trajectories.

This IC engine improvement addresses ICE’s inherent efficiency limit through innovative mechanical design of a consolidated system encompassing intake bypass and coordinating injection mechanism. In principle, the exhaust energy is recuperated to modulate intake temperature, in the meantime, multi-staged injection control is proposed that enhances in-cylinder thermal efficiency. To be specific, a CFD-optimized bypass is constructed alongside the intake and injection design which utilizes multi-stage variable mixing precisely, taking full advantage of exhaust temperature elevation. Regenerative heat gained through exhaust system gives rise to flexible amount of thermal dynamics adjustment to the intake, which consequently delivers more robust combustion efficiency as well as lower emission metrics. A flow control valve is developed at intake interface enables modular variable intake routing supporting engine efficiency promotion.

To meet the increasing electrical power demands for advanced internal combustion engine (ICE) vehicles, auxiliary power units (APUs) are of growing interest. Fuel cell based APUs offer the potential for high chemical-to-electrical conversion efficiency with low noise and low emissions. It has recently been shown that solid oxide fuel cells (SOFCs) can be used to directly convert the chemical energy of liquid hydrocarbon fuels to electricity. Because the combustion reaction takes place by direct oxidation of vaporized fuel at the fuel cell anode, the expectation exists for development of compact, reformerless APUs that can operate on the same fuel that the ICE uses for vehicle propulsion. Critical issues for the transportation SOFC-APU applications are fast start-up and the need to survive extensive thermal cycling.

The principle of maximum entropy is used to obtain the prior probability distribution functions for critical creep-strain and creep-rupture characteristics of engineering materials, operating at known high temperatures and uniaxial stresses. From the prior distribution function obtained, reliability function which is simply the probability of successful operation of the material, can be derived for specified critical creep-strain and creep-rupture modes of failure. An attempt is made to derive the reliability functions from prior considerations of the mechanics of failure, and the mechanical and physical characteristics of engineering materials. This work assumes that mechanical creep design reliability functions for creep-rupture and critical creep-strain modes of structural elements can have values such that the failure of the elements can occur either by any of the modes of failure or by the assumed combined modes of failure.

Simulating human reach is still challenging when considering complex interactions with the environment. Standard approaches involve inverse kinematics (IK) methods and usually require a complete but exponential cost search in configuration space. In ergonomic applications, both “naturalness” and interactive performance are important. We describe a real-time, collision-free, sternum-rooted IK solution for an articulated human figure based on motion capture data, human strength models, and multi-joint coordination functions. Movement paths are discovered through spatial search in a partitioned workspace. The system generates natural collision-free reach motions in real-time. The resulting animations and statistics demonstrate the efficacy of this approach.

Computational ergonomic analyses are often laboriously tested one task at a time. As digital human models improve, we can partially automate the entire analysis process of checking human factors requirements or regulations against a given design. We are extending our Parameterized Action Representation (PAR) to store requirements and its execution system to drive human models through required tasks. Databases of actions, objects, regulations, and digital humans are instantiated into PARs and executed by analyzers that simulate the actions on digital humans and monitor the actions to report successes and failures. These extensions will allow quantitative but localized design assessment relative to specific human factors requirements

Finite element (FE) models are commonly used for automotive crashworthiness design. However, even with increasing speed of computers, the FE-based simulation is still too time-consuming when simulating the complex dynamic process such as vehicle crashworthiness. To improve the computational efficiency, the response surface model, as the surrogate of FE model, has been widely used for crashworthiness optimization design. Before introducing the surrogate model into the design optimization, the surrogate should satisfy the accuracy requirements. However, the bias of surrogate model is introduced inevitably. Meanwhile, it is also very difficult to decide how many samples are needed when building the high fidelity surrogate model for the system with strong nonlinearity. In order to solve the aforementioned problems, the application of a kind of surrogate optimization method called Efficient Global Optimization (EGO) is proposed to conduct the crashworthiness design optimization.

Motor vehicle crashes remain the leading cause of death for children. Traditionally, restraint design has focused on the crash phase of the impact with an optimally seated occupant. In order to optimize restrain design for real-world scenarios, research has recently expanded its focus to non-traditional loading conditions including pre-crash positioning and lower speed impacts. The goal of this study was to evaluate the biofidelity of the large omni-directional child (LODC) ATD in non-traditional loading conditions by comparing its response to pediatric volunteer data in low-speed sled tests. Low-speed (2-4 g, 1.9-3.0 m/s) frontal (0°), far-side oblique (60°), and far-side lateral (90°) sled tests, as well as lateral swerving (0.72 g, 0.5 Hz) tests, were conducted using the LODC. The LODC was restrained using a 3-point-belt with an electromechanical motorized seat belt retractor, or pre-pretensioner. Motion capture markers were placed on the head, torso, and belt.

Experimental tests using porcine brainstem samples were performed on a custom designed stress relaxation shear device. Tests were performed dynamically at strain rates >1 s−1, to three levels of peak strain (2.5%-7.5%). The directional dependence of the material properties was investigated by shearing both parallel and transverse to the predominant direction of the axonal fibers. Quasi-linear viscoelastic theory was used to describe the reduced relaxation response and the instantaneous elastic function. The time constants of the reduced relaxation function demonstrate no directional dependence; however, the relative magnitude of the exponential functions and the parameter representing the final limiting value are significantly different for each direction. The elastic function qualitatively demonstrates a dependence on direction. These results suggest that the brainstem is an anisotropic material.

This report discusses the development of brain injury tolerance criteria based on the study of three model systems: the primate, inanimate physical surrogates, and isolated tissue elements. Although we are equally concerned with the neural and neurovascular tissue components of the brain, the report will focus on the former and, in particular, the axonal elements. Under conditions of distributed, impulsive, angularacceleration loading, the primate model exhibits a pathophysiological response ranging from mild cerebral concussion to massive, diffuse white matter damage with prolonged coma. When physical models are subjected to identical loading conditions it becomes possible to map the displacements and calculate the associated strains and stresses within the field simulating the brain. Correlating these experimental models leads to predictive levels of tissue element deformation that may be considered as a threshold for specific mechanisms of injury.

The use of cerium oxide as an oxygen storage component in automotive three-way catalysis has been well established. More recently the need to thermally stabilize these materials against deactivation at higher temperatures has focused attention on doping of the ceria with a wide range of metal oxides. The role of these dopants in the stabilization mechanisms for ceria is not completely understood as they must perform the complex role of sintering inhibitor while promoting oxygen storage and release. The scattering of pulsed neutrons produced by a spallation source coupled with the Fourier analysis provides a powerful method to characterize the local atomic structure of complex systems such as mixed oxides. We demonstrate that by using this method it is possible to obtain valuable information on the local atomic structure of the CeO2/ZrO2 catalyst support that cannot be attained by the conventional diffraction methods.

Validating a traumatic brain injury finite element model is often limited by a lack of extensive animal injury data that may be used to examine the conditions under which the model is accurate. Given that most published reports specify only general descriptions of injury, this study examined potential evaluation strategies and assessed the ability of a finite element model to simulate the general descriptions of injury in an animal model. The results of this study showed that 1) the results from a simplified finite element model could estimate trends that were similar to the injury patterns observed in a set of animal experiments, 2) a parameter (Z parameter), which quantified the comparison process between computational and animal data, estimated trends that would help in the model evaluation process, and 3) a more complete evaluation process would occur if multiple testing methods were included in the evaluation procedure.

Cervical nerve roots are susceptible to compression injuries of various durations. The duration of an applied compression has been shown to contribute to both the onset of persistent pain and also the degree of spinal cellular and molecular responses related to nociception. This study investigated the relationship between peripherally evoked activity in spinal cord neurons during a root compression and the resulting development of axonal damage. Electrically evoked spikes were measured in the spinal cord as a function of time during and after (post-compression) a 15 minute compression of the C7 nerve root. Compression to the root significantly (p=0.035) reduced the number of spikes that were evoked over time relative to sham. The critical time for compression to maximally reduce evoked spikes was 6.6±3.0 minutes. A second study measured the post-compression evoked neuronal activity following compression applied for a shorter, sub-threshold time (three minutes).

Frontal and temporal lobe contusions that were caused by a single sagittal plane angular acceleration impulse were analyzed. At neuropathological exam the depth, extent, and location of contusions were mapped and described according to a classification previously developed for human use. Of 30 rhesus monkeys subjected to a single angular acceleration impulse, 13 had no frontal or temporal contusion (Group 1), 8 had only frontal contusion (Group 2) and 9 had temporal contusions (Group 3). Correlation with angular acceleration, tangential acceleration and tangential force showed that the three groups were statistically different. The mean peak positive tangential force for Groups 1-3 was 541, 659 and 766 newtons respectively (p<0.10). This suggested that as mechanical imput increased, frontal contusions occur before temporal contusions and that the threshold for frontal contusion is less than that for temporal contusion.

Digital human modeling (DHM) progress worldwide will be much faster and cohesive if the diverse community now developing simulations has a global blueprint for DHM, and is able to work together efficiently. DHM developers and users can save time by building on each other's work. This paper highlights a panel discussion on DHM goals and strategic plans for the next decade to begin formulating the international blueprint. Four subjects are chosen as the starting points: (1) moving DHM into the public safety and internet arenas, (2) role of DHM in computer assisted surgery and automotive safety, (3) DHM in defense applications, and (4) DHM to improve workplace ergonomics.

Autonomous and/or automated vehicles offer a host of future opportunities but leave many questions unanswered regarding their impact on crash avoidance or the ability of drivers to effectively scan and re-engage from self-driving mode when necessary to avoid crash scenarios. Considering a 16-year-old is several times more likely to die in an automobile crash than other licensed drivers, it was crucial to test both teenage drivers and adults to determine head-on collision avoidance abilities when subjected to a failing autopilot in a simulated autonomous vehicle. In this study, eight teenagers ages 16-19 and four experienced adults underwent four simulated drives (one manual practice drive and three simulated autonomous drives) using a hi-fidelity, Real Time Technologies SimDriver Simulator to represent being in a self-driving vehicle.

Driving simulators offer a safe alternative to on-road driving for the evaluation of performance. In addition, simulated drives allow for controlled manipulations of traffic situations producing a more consistent and objective assessment experience and outcome measure of crash risk. Yet, few simulator protocols have been validated for their ability to assess driving performance under conditions that result in actual collisions. This paper presents results from a new Simulated Driving Assessment (SDA), a 35- to-40-minute simulated assessment delivered on a Real-Time® simulator. The SDA was developed to represent typical scenarios in which teens crash, based on analyses from the National Motor Vehicle Crash Causation Survey (NMVCCS). A new metric, failure to brake, was calculated for the 7 potential rear-end scenarios included in the SDA and examined according two constructs: experience and skill.

In this paper, we consider smart charging and vehicle-to-home (V2H) technologies for plugin electric vehicles coordinated with home energy management systems (HEMS) for automated demand response. In this system, plugin electric vehicles automatically react to demand response events with or without HEMS’s coordination, while vehicles are charged and discharged (i.e., V2H) in appropriate time slots by taking into account demand response events, time-ofuse rate information, and users’ vehicle usage plan. We introduce three approaches on home energy management: centralized energy control, distributed energy control, and coordinated energy control. We implemented smart charging and V2H systems by employing two sets of standardized communication protocols: one using OpenADR 2.0b, SEP 2.0, and SAE standards and the other using OpenADR 2.0b, ECHONET Lite, and ISO/IEC 15118.

Traumatic brain injury finite element analyses have evolved from crude geometric representations of the skull and brain system into sophisticated models which take into account distinct anatomical features. However, two distinct finite element modeling approaches have evolved to account for the relative motion that occurs between the skull and cerebral cortex during traumatic brain injury. The first and most common approach assumes that the relative motion can be estimated by representing the cerebrospinal fluid inside the subarachnoid space as a low shear modulus, virtually incompressible solid. The second approach assumes that the relative motion can be approximated by defining a frictional interface between the cerebral cortex and dura mater. This study presents data from an experimental model of traumatic brain injury coupled with finite element analyses to evaluate the modeling approach's ability to predict specific forms of traumatic brain injury.