Hirotaka Shiozaki

Joint stiffness analysis and optimization as a mechanism for improving the structural design and performance of a vehicle

An approach is presented to evaluate the structural performance of a vehicle model in terms of the joint stiffness. Seven major joints on the left and right sides of the vehicle body are identified, and each joint is decomposed in the finite element model and assigned a separate set of material properties. By adjusting the elastic modulus of each structural member, the effects of the joint stiffness on the full and offset frontal impacts as well as the vibration characteristics are examined. Latin hypercube sampling is used in the design of experiments to approximate the acceleration, the intrusion distance, and the fundamental vibration frequencies using full quadratic polynomial response surface models. Through direct differentiation, the sensitivities of the crash responses and the vibration responses to the joint stiffness are calculated. A constrained multi-objective optimization problem is formulated and solved to improve the structural responses by adjusting the stiffness at each joint. Evaluation of the car body structure based on the optimum joint stiffness showed a superior performance relative to the baseline model without a weight penalty. The results of both the sensitivity analysis and the design optimization are presented and discussed.

Using Experimental Data to Improve Crash Modeling for Composite Materials

Accurate simulation of the composite material crash tubes subjected to axial impact is a challenging field of study in automotive or aerospace industry; however, analytical prediction of the crashworthiness behavior in composite materials is limited. In this paper, three different analytical approaches are presented which have been used to study the crashworthiness of a pultruded glass-polyester tube. The first model is established based on the single shell elements. This approach is very effective, when composite part is assembled in the full structure. However, this technique can be used when the experimental result is available. In the second approach, the crash tube is modeled by using multi-layered shell element (delamination model). Relying on coupon test information of the composite material, this modeling technique can provide reasonable result for the energy absorption of the tube. The third modeling approach is looking for crashworthiness prediction of the discussed tube by using the first model which its parameters are tuned based on the result of the second model. Finally, the sensitivity of the result is studied by changing the major parameters in the first model. This paper is looking for finding a method to reasonably estimate the crashworthiness behavior in the composite materials.

Identification of acoustic wavenumber component of fluctuating surface pressure for flow noise analysis

The importance of flow noise is increasing with the increasing popularity of quiet electric vehicles. In general, flow noise covers a wide frequency range and usually the high frequency flow noise is important for the vehicle quality because of the increased sensitivity of human perception to high frequency noise. For predicting high frequency noise, statistical energy analysis (SEA) is often used in the prediction of acoustic insulation and absorption. Some of SEA modeling for flow noise transmission has been reported in the literature. However, most of the SEA modeling needs CFD results which require huge computation time. In vehicle design, sometimes the time required for improvements does not permit time for development of CFD models. In such situations, easy and fast diagnostic method like energy transmission contribution analysis is required. In this paper, the mechanism of the flow noise transmission is reviewed especially in the case of low speed flow of around 80 km/h. The acoustic wavenumber component of fluctuating surface pressure is dominant source of flow noise transmission for low speed flow. Therefore, the acoustic wavenumber component identification using conventional acoustic SEA model and the wind tunnel test results is presented. The identified acoustic wavenumber component is validated by comparing with the acoustic wavenumber component identified from the wavenumber-frequency spectrum to that computed using a CFD model.