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Technical Paper

CAE Modeling Static and Fatigue Performance of Short Glass Fiber Reinforced Polypropylene Coupons and Components

2020-04-14
2020-01-1309
One approach of reducing weight of vehicles is using composite materials, and short glass fiber reinforced polypropylene is one of most popular composite materials. To more accurately predict durability performance of structures made of this kind of composite material, static and fatigue performance of coupons and components made of a short glass fiber reinforced polypropylene has been physically studied. CAE simulations have been conducted accordingly. This paper described details of CAE model setup, procedures, analysis results and correlations to test results for static, fiber orientation flow and fatigue of coupons and a battery tray component. The material configurations include fiber orientations (0, 20 and 90 degrees), and mean stress effect (R = -1.0, -0.5, -0.2, 0.1 and 0.4). The battery tray component samples experience block cycle loading with loading ratio of R = -0.3 and 0.3. The CAE predictions have reasonable correlations to the test results.
Technical Paper

A Study on Bolted Joint Finite Element Modeling for Vehicle Level Durability Analysis

2020-04-14
2020-01-0178
This paper describes a study on identifying a suitable thickness for finite element modeling a “deformable washer” to simulate bolted joints for vehicle level durability analysis based on experimental results. First, a test matrix table is introduced, which is based on representative vehicle structures for different bolt/nut sizes, bolt grades, sheet gages, and sheet materials etc. Then coupon tests, both static and fatigue, are illustrated. Next, the corresponding finite element model with different thickness of “deformable washers” and results are presented. Following that, the optimal “deformable washer” thickness is recommended based on statistical parameters (mean and standard deviation) of the relative differences between finite element analysis results and physical test results. Lastly, a case study is demonstrated for the proposed strategy.
Technical Paper

Fatigue Life Prediction for Adaptable Insert Welds between Sheet Steel and Cast Magnesium Alloy

2016-04-05
2016-01-0392
Joining technology is a key factor to utilize dissimilar materials in vehicle structures. Adaptable insert weld (AIW) technology is developed to join sheet steel (HSLA350) to cast magnesium alloy (AM60) and is constructed by combining riveting technology and electrical resistance spot welding technology. In this project, the AIW joint technology is applied to construct front shock tower structures composed with HSLA350, AM60, and Al6082 and a method is developed to predict the fatigue life of the AIW joints. Lap-shear and cross-tension specimens were constructed and tested to develop the fatigue parameters (load-life curves) of AIW joint. Two FEA modeling techniques for AIW joints were used to model the specimen geometry. These modeling approaches are area contact method (ACM) and TIE contact method.
Journal Article

Development of a CAE Modeling Technique for Heavy Duty Cargo Weight using a DFSS Methodology

2022-03-29
2022-01-0774
Cargo box is one of the indispensable structures of a pickup truck which makes it capable of transporting heavy cargo weights. This heavy cargo weight plays an important role in durability performance of the box structure when subjected to road load inputs. Finite element representation for huge cargo weight is always challenging, especially in a linear model under dynamic proving ground road load durability analysis using a superposition approach. Any gap in virtual modeling technique can lead to absurd cargo box modes and hence durability results. With the existing computer aided engineering (CAE) approach, durability results could not correlate much with physical testing results. It was crucial to have the right and robust CAE modeling technique to represent the heavy cargo weight to provide the right torsional and cargo modes of the box structure and in turn good durability results.
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