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Due to the high center of gravity of medium-duty vehicles, rollover accidents can easily occur during high-speed cornering and lane changes. In order to prevent the deformation of the body structure, which would restrict the survival space and cause compression injuries to occupants, it is necessary to investigate methods for mitigating these incidents.

The ranges of powertrain uncertain responses are obtained through the perturbation center difference method (PCDM) and are validated using the Monte Carlo method (MCM). The optimized upper and lower bounds of powertrain responses are also given.

Deregulation without aircraft-reliability improvement increases the risk of accidents. However, demanding high reliability for all aircraft leads to an increase in the price of the aircraft.

In addition to this, car door handles also play a critical role in ensuring passenger safety by keeping the door closed during accidents or when there is a significant amount of G-force acting on the vehicle. A typical car door handle comprises several components including the structure, cover, bowden lever, bracket, pins and other child parts. ...The position of the Bowden lever is crucial for the unlatching process and for keeping the door closed during the accidents and unauthorized entry. Therefore, design of the car door handle must work under optimize force to ensure that the handle performs it’s function effectively.

The Mobile Progressive Deformable Barrier (MPDB) is a standardized automotive crash scenario that comprehensively evaluates the safety of battery-electric vehicles (BEVs) in a crash. In an accident, the deformation pattern of the Front of Battery Electric Vehicle (FOBEV) structure, the efficiency of energy absorption, the acceleration pulse, and the degree of intrusion into the passenger compartment combine to affect the safety of the driver and passengers. ...Taking a BEV under development as an example, the application of the accident damage prediction method based on the FOBEV equivalent model in the optimal design of BEV crashworthiness is illustrated.

When an accident occurs, energy absorption and deformation play a vital role in the Automobile safety aspects, and also grooves and triggers are the ones included in the crash box for axial folding and uniform deformation.

For optimization, the following three key relationships were chosen: wheel bearing specification and geometry for design variables, weight for cost function, and stiffness for constraint. A Monte Carlo simulation considering the probability distribution of the geometric uncertainties was performed to identify the effect of variations in dimensions. ...A Monte Carlo simulation considering the probability distribution of the geometric uncertainties was performed to identify the effect of variations in dimensions. Since Monte Carlo simulation to analyze the stiffness of the bearings takes a very high computational cost, a regression analysis was performed, followed by running Monte Carlo simulation based on this regression. ...Since Monte Carlo simulation to analyze the stiffness of the bearings takes a very high computational cost, a regression analysis was performed, followed by running Monte Carlo simulation based on this regression. Based on the simulation results, the design variations for the automotive wheel bearings were evaluated using the results of the Monte Carlo simulation.

It was found that the best approach for detecting a temperature hot spot depends on several factors such as the current injection (stimulation) patterns, the measurement patterns, and the reconstruction algorithms. For well-performing combinations of these factors, customized baseline conductivities were assessed and compared to the baseline uniform conductivity. ...Overall, the results at hand suggest that improved 2D surface temperature measurement are best served by continued development of measurements and reconstruction algorithms rather than the use of sensing skins with tailored baseline conductivity distributions.

Partial discharge (PD) detection has been always a fundamental tool, potentially, for the design, quality control, commissioning, and reliability monitoring for the of insulation systems. The word “potentially” stems from the objective consideration of the intrinsic limitations suffered by the existing partial discharge, PD, measurement technologies, especially the need of experts to interpret results and the lack of clear correlation between PD-related quantities, and the condition-based maintenance approach. On the whole, a thorough revision of insulation systems design procedures and of the tools to evaluate aging and failure risk is needed, especially in components of electrical assets which are critical in terms of reliability, resilience, and safety.

The methodology employed in this study includes outlining the theoretical development of a fully automated condition monitoring system and describing data cleansing steps to account for environmental effects on system performance. A Monte Carlo simulation is used to evaluate the sensitivity of the remaining useful life prediction to varying measurement frequencies, prediction models, and parameter settings, leading to an estimate of the optimal measurement frequency for the system.

A forward uncertainty propagation analysis is carried out using a Monte Carlo approach. The optimization framework relies on a gradient-free algorithm (Mesh Adaptive Direct Search) and three different problem formulations are considered in this work.

The driver monitoring system (DMS) plays an essential role in reducing traffic accidents caused by human errors due to driver distraction and fatigue. The vision-based DMS has been the most widely used because of its advantages of non-contact and high recognition accuracy.

To further improve the reliability of the optimization result, a six-sigma level robust design optimization is carried out based on the Monte Carlo sampling method and the archive-based Micro Genetic Algorithm (AMGA) method. The minimum fatigue times of the optimized bolted T-joint increased by 60.80% compared with that before optimization.

Lithium-ion battery has advantages of high energy density and cost effectiveness than other types of batteries. However due to the low mechanical stability, their performance is strongly influenced by environmental conditions. Especially, external pressure on a cell surface is a crucial factor because an appropriate force can improve battery cycle life, but excessive force may cause structural failure. In addition, battery pack is composed of various components so that uncertainties in dimension and material properties of each component can cause a wide variance in initial pressure. Therefore, it is important to optimize structural design of battery pack to ensure initial pressure in an effective range. In this paper, target stiffness of module structure was determined based on cell level cycle life test, then structural design has been optimized for weight reduction. Cell cycling tests were performed under different stiffness conditions and analyzed with regression model.

In the last few years, the number of Advanced Driver Assistance Systems (ADAS) on road vehicles has been increased with the aim of dramatically reducing road accidents. Therefore, the OEMs need to integrate and test these systems, to comply with the safety regulations.

Therefore, attention should be paid to the protection of vulnerable road users in traffic accidents, such as pedestrians. In order to reduce the pedestrians’ head injury in collision accidents, in this study, the vehicle engine hood which responds significantly to head injuries was taken as the design object, so as to put forward a new optimization design process.

We then propose a Markov chain Monte Carlo method for solving the bi-level optimization problem, and construct a system for automatic generation of evaluation courses.

The forthcoming introduction of the EURO VII regulation requires urgent strategies and solutions for the reduction of sub-23 nm particle emissions. Although they have been historically considered as particulate matter-free, the high interest for Natural Gas (NG) Heavy-Duty engines in the transport sector, demands their compliance with the new proposed regulations. In order to obtain high conversion of gas pollutants and a strong abatement of the emitted particles, the use of Particle Filters in NG aftertreatment (CPF) in conjunction with the Three-Way Catalyst (TWC) may represent an attractive and feasible solution. Performances of a cordierite filter were explored through an extensive experimental campaign both in Steady-State conditions and during transient engine maneuvers that involved a whole analysis of the emitted particles in terms of number and mass.

Uncertainty probabilistic study depends on Monte Carlo (MC) method applied. From the experimental results, the most impactful processing variable for force is cutting depth, surface roughness, and chip-tool interface indices are feed rate while cutting velocity for tool wear.

The specific scenarios used for testing, outline incidences of accidents or near-miss events. In order to simulate these scenarios, specific values for all the above parameters are required including the ego vehicle model.