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Road vibrations cause fatigue failures in vehicle components and systems. Therefore, reliable and accurate damage and life assessment is crucial to the durability and reliability performances of vehicles, especially at early design stages. However, durability and reliability assessment is difficult not only because of the unknown underlying damage mechanisms, such as crack initiation and crack growth, but also due to the large uncertainties introduced by many factors during operation. How to effectively and accurately assess the damage status and quantitatively measure the uncertainties in a damage evolution process is an important but still unsolved task in engineering probabilistic analysis. In this paper, a new procedure is developed to assess the durability and reliability performance, and characterize the uncertainties of damage evolution of components under constant amplitude loadings.

Active regeneration systems for cleaning diesel exhaust can operate at extremely high temperatures up to 1000°C. The extremely high temperatures create a unique challenge for the design of regeneration structural components near their melting temperatures. In this paper, the preparation of the sheet specimens and the test set-up based on induction heating for sheet specimens are first presented. Tensile test data at room temperature, 500, 700, 900 and 1100°C are then presented. The yield strength and tensile strength were observed to decrease with decreasing strain rate in tests conducted at 900 and 1100°C but no strain rate dependence was observed in the elastic properties for tests conducted below 900°C. The stress-life relations for under cyclic loading at 700 and 1100°C with and without hold time are then investigated. The fatigue test data show that the hold time at the maximum stress strongly affects the stress-life relation at high temperatures.

Strength and fatigue life prediction is very difficult for stamped structural steel parts because the manufacturing process alters the localized material properties. Traditional tensile tests cannot be used to obtain material properties due to size limitations. Because of this, FEA predictions are most often “directional” at best. In this paper an improved prediction methodology is suggested. With a material library developed from standard homogenous test specimens, or even textbook material property tables, localized strength and plastic strain numbers can be inferred from localized hardness tests(1). The new method, using standard ABAQUS static analysis (not commercial fatigue analysis software with many unknowns), is shown to be very accurate. This paper compares the new process FEA strength and fatigue life predictions to laboratory test results using statistical confidence intervals.

This study presents a probabilistic life (failure) and damage assessment approach for components under general fatigue loadings, including constant amplitude loading, step-stress loading, and variable amplitude loading. The approach consists of two parts: (1) an empirical probabilistic distribution obtained by fitting the fatigue failure data at various stress range levels, and (2) an inverse technique, which transforms the probabilistic life distribution to the probabilistic damage distribution at any applied cycle. With this approach, closed-form solutions of damage as function of the applied cycle can be obtained for constant amplitude loading. Under step-stress and variable amplitude loadings, the damage distribution at any cycle can be calculated based on the accumulative damage model in a cycle-by-cycle manner. For Gaussian-type random loading, a cycle-by-cycle equivalent, but a much simpler closed-form solution can be derived.

Vehicle exhaust components and systems under fatigue loading often show multiple failure modes, which should be treated, at least theoretically, with rigorous advanced bi-modal and multi-modal statistical theories and approaches. These advanced methods are usually applied to mission-critical engineering applications such as nuclear and aerospace, in which large amounts of test data are often available. In the automotive industry, however, the sample size adopted in the product validation is usually small, thus the bi-modal and multi-modal phenomena cannot be distinguished with certainty.

In the Big Data era, the capability in statistical and probabilistic data characterization, data pattern identification, data modeling and analysis is critical to understand the data, to find the trends in the data, and to make better use of the data. In this paper the fundamental probability concepts and several commonly used probabilistic distribution functions, such as the Weibull for spectrum events and the Pareto for extreme/rare events, are described first. An event quadrant is subsequently established based on the commonality/rarity and impact/effect of the probabilistic events. Level of measurement, which is the key for quantitative measurement of the data, is also discussed based on the framework of probability. The damage density function, which is a measure of the relative damage contribution of each constituent is proposed. The new measure demonstrates its capability in distinguishing between the extreme/rare events and the spectrum events.

A new passive muffler valve has been developed that offers the advantages of both the current passive and active valves without their major drawbacks. Like current passive valves this new valve provides high restriction at low to medium engine speeds for improved noise control. But with a near over-center spring action and unique flap shape, this high performance valve has minimal pressure drop at high engine speeds, closer to the active valve pressure drop performance. The in-line design of the valve makes it ideal for low restriction OE mufflers, resonators, and aftermarket performance mufflers. The new valve design is uncomplicated, with few components and has been tested extensively for durability utilizing both bench and vehicle level testing.

In order to satisfy tightening global emissions regulations, diesel truck manufacturers are striving to meet increasingly stringent Oxides of Nitrogen (NOx) reduction standards. The majority of heavy duty diesel trucks have integrated urea SCR NOx abatement strategies. To this end, aftertreatment systems need to be properly engineered to achieve high conversion efficiencies. A EuroV intent urea SCR system is evaluated and failed to meet NOx conversion targets with severe urea deposit formation. Systematic enhancements of the design have been performed to enable it to meet targets, including emission reduction efficiency via improved reagent mixing, evaporation, distribution, back pressure, and removing of urea deposits. Multiple urea mixers, injector mounting positions and various system layouts are developed and evaluated, including both CFD analysis and full scale laboratory tests.

Durability life is one of the major concerns in the automotive industry. Road Load Data Acquisition (RLDA) is one of the most important steps to verify exhaust system durability performance. RLDA will not only provide data for system level rig testing drive file development but also for exhaust components validation (computing safety factors). Modal transient FEA can be utilized to simulate either vehicle durability testing or sub-system level rig testing. How to simulate correctly is critical in the simulation. One of the most challenging portions in the full exhaust system simulation is isolator modeling due to its non-linear characteristics. However, we have to use linear modeling to simulate isolator in modal transient analysis, which induces errors.

A probabilistic distribution function roughly consists of two parts: the middle part and the tails. The fatigue life distribution at a stress/load level is often described with two-parameter lognormal or Weibull distribution functions, which are more suitable for modeling the mean (middle) behaviors. The domains of the conventional probabilistic distribution functions are often unbounded, either infinite small (0 for the two-parameter Weibull) or infinite large or both. For most materials in low- and medium-cycle fatigue regimes, the domains of fatigue lives are usually bounded, and the inclusion of the bounds in a probabilistic model is often critical in some applications, such as product validation and life management. In this paper, four- and five-parameter Weibull distribution functions for the probabilistic distributions with bounds are developed. Finally, the applications of these new models in fatigue data analysis and damage assessment are provided and discussed.

Life testing or test-to-failure method and binomial testing method are the two most commonly used methods in product validation and reliability demonstration. The two-parameter Weibull distribution function is often used in the life testing and almost exclusively used in the extended time testing, which can be considered as an accelerated testing method by appropriately extending the testing time but with significantly reduced testing samples. However, the fatigue data from a wide variety of sources indicate that the three-parameter Weibull distribution function with a threshold parameter at the left tail is more appropriate for fatigue life data with large sample sizes. The uncertainties introduced from the assumptions about the underlying probabilistic distribution would significantly affect the interpretation of the test data and the assessment of the performance of the accelerated binomial testing methods, therefore, the selection of a probabilistic model is critically important.

Fatigue life prediction of elastomer NVH suspension products has become an operating norm for OEMs and suppliers during the product quoting process and subsequent technical reviews. This paper reviews a critical plane analysis based fatigue simulation methodology for a front lower control arm. Filled natural rubber behaviors were measured and defined for the analysis, including: stress-strain, fatigue crack growth, strain crystallization, fatigue threshold and initial crack precursor size. A series of four distinct single and dual axis bench durability tests were derived from OEM block cycle specifications, and run to end-of-life as determined via a stiffness loss criterion. The tested parts were then sectioned in order to compare developed failure modes with predicted locations of crack initiation. In all cases, failure mode was accurately predicted by the simulation, and predicted fatigue life preceded actual end-of-life by not more than a factor of 1.4 in life.

Automotive exhaust system experiences vibratory and thermal loads. Bogey test had been the major validation method until recent years when the strain-life approach was adopted to evaluate component's fatigue life. In practice, when using the strain-life model to evaluate a component subjected to elevated temperature, temperature effect on component fatigue life is considered by introducing a temperature scale factor KC that is used to scale up the measured nominal strain, hence the mechanical load. This paper intends to propose a method to estimate KC by designing component bench tests at room temperature and at elevated temperature, respectively. Two major failure modes in the exhaust system are investigated and different temperature effects on the base metal fatigue and on the weld or heat-affected zone are analyzed.

The approaches of obtaining both fatigue strength distribution and fatigue life distribution for a given set of fatigue S-N data are reviewed in this paper. A new fatigue S-N curve transformation technique, which is based on the fundamental statistics definition and some reasonable assumptions, is specifically developed in this paper to transform a fatigue life distribution to a fatigue strength distribution. The procedures of applying the technique to multiple-stress level, two-stress level, and one-stress level fatigue S-N data are presented.

Driven by diesel engine emission regulation, more emission aftertretment products have been under development by Tenneco to address the Particular Matter (PM) and NOx reduction needs. The T.R.U.E. (Thermal Regeneration Unit for Exhaust) Clean active thermal management system is one of the examples to reduce PM. The system is designed to increase exhaust temperatures for DPF (Diesel Particulate Filter) regeneration. This product is exposed to high temperature and high oxidation. Therefore, thermal fatigue, creep, oxidation and the interaction become critical mechanism to be considered for its durability. One of the key challenges to validate this product is to find a way of accelerated testing for thermal, creep, and oxidation as well as for vibration. In this paper, accelerated durability test strategy for high temperature device like T.R.U.E Clean is addressed.

Component bench testing is a basic method to validate the component fatigue life. However, the component bench testing takes long time and is costly. With the development of more powerful computer and CAE simulation techniques, virtual CAE simulation method becomes more important in the component design, optimization, and validation due to its efficiency and low cost. Fatigue life of components of exhaust system is a critical characteristic and it is not deterministic but statistical phenomenon. Thus, a probabilistic approach is necessary. Variations and reliability of fatigue life can be considered in physical testing by testing more samples. However, how to account variations from manufacturing and testing in virtual CAE simulation is a big challenge. In this paper, a virtual CAE fatigue life prediction of components of exhaust system by probabilistic approach is studied and proposed.

The purpose of this work was to initiate a comparative evaluation of the aqueous corrosion resistance of ferritic stainless steels currently used to fabricate automotive exhaust systems. Both acid condensate and double loop electrochemical potentiokinetic reactivation (DL-EPR) testing using both as-received and heat treated test coupons prepared from Types 409, 409Al, 436 and 439 stainless steel was conducted for this purpose. A truncated version of an in-house acid condensate testing protocol revealed that Type 409Al stainless steel was the most resistant to corrosion of the four ferritic stainless steels examined, whereas Type 409 stainless steel was the least resistance to corrosion.

Product validation and reliability demonstration require testing of limited samples and probabilistic analyses of the test data. The uncertainties introduced from the tests with limited sample sizes and the assumptions made about the underlying probabilistic distribution will significantly impact the results and the results interpretation. Therefore, understanding the nature of these uncertainties is critical to test method development, uncertainty reduction, data interpretation, and the effectiveness of the validation and reliability demonstration procedures. In this paper, these uncertainties are investigated with the focuses on the following two aspects: (1) fundamentals of the RxxCyy criterion used in both the life testing and the binomial testing methods, (2) issues and benefits of using the two-parameter Weibull probabilistic distribution function.

Fatigue life assessment is an integral part of the durability and reliability evaluation process of vehicle exhaust components and systems. The probabilistic life assessment approaches, including analytical, experimental, and simulation, CAE implementation in particular, are attracting significant attentions in recent years. In this paper, the state-of-the-art probabilistic life assessment methods for vehicle exhausts under combined thermal and mechanical loadings are reviewed and investigated. The loading cases as experienced by the vehicle exhausts are first categorized into isothermal fatigue, anisothermal fatigue, and high-temperature thermomechanical fatigue (TMF) based on the failure mechanisms. Subsequently, the probabilistic life assessment procedures for each category are delineated, with emphasis on product validation.

Fatigue testing and related fatigue life assessment are essential parts of the design and validation processes of vehicle components and systems. Fatigue bench test is one of the most important testing methods for durability and reliability assessment, and its primary function is to construct design curves based on a certain amount of repeated tests, with which recommendations on product design can be advised. How to increase the accuracy of predictions from test results, the associated life assessment, and to reduce the cost through reducing test sample size is an active and continuous effort. In this paper the current engineering practices on constructing design curves for fatigue test data are reviewed first.