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Over the decades, several attempts have been made to develop new fatigue analysis methods for welded joints since most of the incidents in automotive structures are joints related. Therefore, a reliable and effective fatigue damage parameter is needed to properly predict the failure location and fatigue life of these welded structures to reduce the hardware testing, time, and the associated cost. The nodal force-based structural stress approach is becoming widely used in fatigue life assessment of welded structures. In this paper, a new nodal force-based structural stress recovery procedure is proposed that uses the least squares method to linearly smooth the stresses in elements along the weld line. Weight function is introduced to give flexibility in choosing different weighting schemes between elements. Two typical weighting schemes are discussed and compared.

A method is presented to process random vibration data from a complete road durability test environment as stationary segments and then develop test profiles based on fatigue content of their power spectral densities. Background is provided on existing techniques for estimating fatigue damage in the frequency domain. A general model for stress response to acceleration is offered to address the vibration test's requirement for acceleration data and the fatigue prediction method's requirement for stress data. With these tools, the engineer can extend test correlation beyond failure modes to include retention of estimated fatigue damage. Recommendations allow for test time compression from editing and improve existing exaggeration methods.

In the North American automotive industry, various advanced high strength steels (AHSS) are used to lighten vehicle structures, improve safety performance and fuel economy, and reduce harmful emissions. Relatively thick gages of AHSS are commonly joined to conventional high strength steels and/or mild steels using Gas Metal Arc Welding (GMAW) in the current generation body-in-white structures. Additionally, fatigue failures are most likely to occur at joints subjected to a variety of different loadings. It is therefore critical that automotive engineers need to understand the fatigue characteristics of welded joints. The Sheet Steel Fatigue Committee of the Auto/Steel Partnership (A/S-P) completed a comprehensive fatigue study on GMAW joints of both AHSS and conventional sheet steels including: DP590 GA, SAE 1008, HSLA HR 420, DP 600 HR, Boron, DQSK, TRIP 780 GI, and DP780 GI steels.

Corrosion-fatigue (CF) and stress corrosion cracking (SCC) have long been recognized as the major degradation and failure mechanisms of engineering materials under combined mechanical loading and corrosive environments. How to model and characterize these failure phenomena and how to screen, rank, and select materials in corrosion-fatigue and stress corrosion cracking resistance is a significant challenge in the automotive industry and many engineering applications. In this paper, the mathematical structure of a superposition-theory based corrosion-fatigue model is investigated and possible closed-form and approximate solutions are sought. Based on the model and the associated solutions and test results, screening and ranking of the materials in fatigue, corrosion-fatigue are discussed.

Recent stringent government regulations on emission control and fuel economy drive the vehicles and their associated components and systems to the direction of lighter weight. However, the achieved lightweight must not be obtained by sacrificing other important performance requirements such as manufacturability, strength, durability, reliability, safety, noise, vibration and harshness (NVH). Additionally, cost is always a dominating factor in the lightweight design of automotive products. Therefore, a successful lightweight design can only be accomplished by better understanding the performance requirements, the potentials and limitations of the designed products, and by balancing many conflicting design parameters. The combined knowledge-based design optimization procedures and, inevitably, some trial-and-error design iterations are the practical approaches that should be adopted in the lightweight design for the automotive applications.

This paper is targeted to engineers who are involved in predicting fatigue life using either the strain-life approach or the stress-life approach. However, more emphasis is given to the strain-life approach, which is commonly used for fatigue life analysis in the ground vehicle industry. It attempts to discuss, modify and extend approaches in fatigue analysis, so they are best suited for structural durability engineers. Fatigue analysis requires the use of material fatigue properties, stress or strain results obtained from finite element analyses or measurements, and load data obtained from multi-body dynamic analysis or road load data acquisition. This paper examines the effects of these variables in predicting fatigue life. Various mean stress corrections, along with their advantages and disadvantages are discussed. Different stress/strain combinations such as signed von Mises, and signed Tresca are examined. Also, advanced methods such as Fatemi-Socie and Bannantine are discussed.

In the automotive industry, vehicle durability analysis is based on test schedule encompassing multiple road surfaces (events) including rough roads, potholes, etc. Traditionally, in the Computer Aided Engineering (CAE) world, road load data for various road surfaces are measured/predicted and fatigue life is predicted for each individual road surface. Fatigue life for the complete test schedule is then calculated with Miner’s rule by summing fatigue damage for each road surface with an appropriate number of repetitions. A major pitfall of this approach is that it does not consider the effect of the largest rainflow range across the entire test schedule. The method described in this paper was developed to perform fatigue analysis of structures subjected to diverse road surfaces and also consider the case in which the maximum overall peak and minimum overall valley do not occur over the same road surface.