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Technical Paper

Fatigue Life Prediction of an Automotive Chassis System with Combined Hardening Material Model

2016-04-05
2016-01-0378
The choice of an appropriate material model with parameters derived from testing and proper modeling of stress-strain response during cyclic loading are the critical steps for accurate fatigue-life prediction of complex automotive subsystems. Most materials used in an automotive substructure, like a chassis system, exhibit combined hardening behavior and it is essential to capture this behavior in the CAE model in order to accurately predict the fatigue life. This study illustrates, with examples, the strain-controlled testing of material coupons, and the calculations of material parameters from test data for the combined hardening material model used in the Abaqus solver. Stress-strain response curves and fatigue results from other simpler material models like the isotropic hardening model and the linear material model with Neuber correction are also discussed in light of the respective fatigue theories.
Journal Article

Ductile Fracture Prediction of Automotive Suspension Components

2017-03-28
2017-01-0318
Characterization of the plastic and ductile fracture behavior of a ferrous casting commonly used for the steering knuckle of an automotive suspension system is presented in this work. Ductile fracture testing for various coupon geometries was conducted to simulate a wide range of stress states. Failure data for the higher stress triaxiality were obtained from tension tests conducted on thin flat specimens, wide flat specimens and axisymmetric specimens with varying notch radii. The data for the lower triaxiality were generated from thin-walled tube specimens subjected to torsional loading and compression tests on cylindrical specimens. The failure envelopes for the material were developed utilizing the test data and finite element (FE) simulations of the corresponding test specimens. Experiments provided the load-displacement response and the location of fracture initiation.
Technical Paper

Application of MC Method-Based H2 Fueling

2012-04-16
2012-01-1223
To address challenges related to refueling with compressed hydrogen, a simple, analytical method has been developed that allows a hydrogen station to directly and accurately calculate an end-of-fill temperature in a hydrogen tank and thereby maximize the fill quantity and minimize the refueling time. This is referred to as the MC Fueling Method, where MC represents total heat capacity. The MC Method incorporates a set of thermodynamic parameters for the tank system that are used by the station in a simple analytical equation along with measured values of dispensed hydrogen temperature and pressure at the station. These parameters can be communicated to the hydrogen station either directly from the vehicle or from a database that is accessible by the station. Because the MC Method is based on direct measurements of actual thermodynamic conditions at the station, and quantified thermodynamic behavior of the tank system, highly accurate tank filling results can be achieved.
Technical Paper

Actual Recyclability of Selected Honda Vehicles

2004-03-08
2004-01-0246
The purpose of the recyclability pilot project was to evaluate and confirm the reality of reuse, material recycling and landfill potential of parts and components over a range of Honda vehicles by model and year. A total of 18 vehicles, model years ranging from 1982 to 2001, were selected for study and processed at two automotive recycling centers and a scrap metal processing facility with an automotive shredder. The automotive dismantlers identified which parts and components were removed for reuse or remained with the hulk for further processing at an automotive shredder facility. Dismantling times and part weights were recorded and dismantling procedures were videotaped. The remaining hulks were delivered to the scrap metal processing facility for further processing. After shredding, the ferrous, nonferrous and landfill materials were separately collected for determining weights of these different process outputs.
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