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Numerous test data have been generated in many testing institutions over the years and the historical information from previous similar designs and operating conditions can shed light on the current and future designs since they would share some common features when the changes are not drastic. To effectively utilize the historical information for current and future designs, two steps are necessary: (1) finding an approach to consistently correlate the test data; (2) utilizing Bayesian statistics, which can provide a rigorous mathematical tool for extracting useful information from the historical data. In this paper, a procedure for test sample size reduction is proposed based on historical fatigue S-N test data and Bayesian statistics. First, the statistical information is extracted from a large amount of fatigue test data collected over the years.

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.

Durability and reliability performance is one of the most important concerns of a recently developed Thermal Regeneration Unit for Exhaust (T.R.U.E-Clean®) for exhaust emission control. Like other ground vehicle systems, the T.R.U.E-Clean® system experiences cyclic loadings due to road vibrations leading to fatigue failure over time. Creep and oxidation cause damage at high temperature conditions which further shortens the life of the system and makes fatigue life assessment even more complex. Great efforts have been made to develop the ability to accurately and quickly assess the durability/reliability of the system in the early development stage. However, reliable and validated simplified engineering methods with rigorous mathematical and physical bases are still urgently needed to accurately manage the margin of safety and decrease the cost, whereas iterative testing is expensive and time consuming.

Fatigue, creep, oxidation, or their combinations have long been recognized as the principal failure mechanisms in many high-temperature applications such as exhaust manifolds and thermal regeneration units used in commercial vehicle aftertreatment systems. Depending on the specific materials, loading, and temperature levels, the role of each damage mechanism may change significantly, ranging from independent development to competing and combined creep-fatigue, fatigue-oxidation, creep-fatigue-oxidation. Several multiple failure mechanisms based material damage models have been developed, and products to resist these failure mechanisms have been designed and produced. However, one of the key challenges posed to design engineers is to find a way to accelerate the durability and reliability tests of auto exhaust in component and system levels and to validate the product design within development cycle to satisfy customer and market's requirements.

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.

It is important to quantitatively characterize the automotive events in order to not only accurately interpret their past but also to reliably predict and forecast their short-term, medium-term, and even long-term future. In this paper, several automotive industry related events, i.e. vehicle safety, vehicle weight/HP ratio, the emissions of CO2, HC, CO, and NOx, are analyzed to find their general trends. Exponential and power law functions are used to empirically fit and quantitatively characterize these data with an emphasis on the two functions’ effectiveness in predictability. Finally, three empirical emission laws based on the historical HC, CO, and NOx data are proposed and the impact of these laws on emission control is discussed.

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.

High-temperature thermal-mechanical systems are considered as an indispensable solution to modern vehicle emission control. Such systems include advanced engines, manifolds, thermal regeneration systems, and many other systems. Creep, fatigue, oxidation, or their combinations are the fundamental underlying material degradation and failure mechanisms in these systems subjected to combined thermal and mechanical loadings. Therefore, the basic understanding and modeling of these mechanisms are crucial in engineering designs. In this paper, the state-of-the-art methods of damage/failure modeling and life assessment for components under thermal-fatigue loading, are reviewed first. Subsequently, a new general life assessment procedure is developed for components subjected to variable amplitude thermal- and mechanical- loadings, with an emphasis on hold-time effect and cycle counting.

In this paper, the uncertainty of the estimated parameters of lognormal and Weibull distributions for test data with small sample size is investigated. The confidence intervals of the estimated parameters are determined by solving available analytical equations, and the scatters of the estimated parameters with respect to the true values are estimated by using Monte Carlo simulation approaches. Important parameters such as mean, standard deviation, and design curve are considered. The emphasis is on the interpretation and the implication of the obtained shape parameter β of the Weibull distribution function and the design curve obtained from a lognormal distribution function. Finally, the possible impact of this study on the current engineering practice is discussed.

Creep, fatigue, oxidation, or their combinations are usually the fundamental underlying material degradation and failure mechanisms in advanced engines, manifolds, thermal regeneration systems, and other systems. Therefore, the basic understanding and appropriate mathematical modeling of these mechanisms are crucial in engineering designs. Several numerical simulation strategies are being pursued to achieve a long-term goal of virtual simulation of high-temperature degradation and failure of such components and systems. In this paper, as the first step of the effort in virtual high-temperature material failure simulation, the numerical simulation of the recently developed crack growth models, i.e. creep-fatigue, fatigue-oxidation, and creep-fatigue-oxidation models, are conducted. It is demonstrated that the models developed can be implemented in an efficient way for virtual life assessment and engineering design applications.

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.

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.

Engineering components and systems are usually subjected to mixed-mode and multiaxial fatigue loadings, and these conditions should be considered in product durability and reliability design and the maintenance of aging equipment, especially mission-critical components and systems. However, modeling the damage and degradation processes under these complex loading conditions is difficult and challenging task because not only the concepts, such as range, mean, peak, valley etc., developed for uniaxial loading usually cannot be directly transferred to mixed-mode and multiaxial loadings, but also some very unique phenomena related to these complex loading conditions. One such a phenomenon is the loading path effect that can be simply described as: out-of-phase loading is more damaging than in-phase loading for some ductile materials.

A modern definition of quality control and improvement is the reduction of variability in processes and products. The reduced variability can be directly translated into lower costs, better functions and fewer repairs. However, the final quality of processes and products is sometimes derived from other measured variables through some implicit or explicit functional relationships. Sometimes, a tiny uncertainty in a variable can produce a huge uncertainty in a derived quantity. Therefore, the propagation of uncertainty needs to be understood and the individual variables need to be well controlled. More importantly, the critical factors that affect quality the most should be identified and thoroughly investigated. Design of experiments and statistical control plays central roles in finding root cause of failure, reduction of variability and quality improvement.

Corrosion resistance is an extremely important technical issue for long-term durability and reliability performance of exhaust components and systems. Failure mechanisms, such as corrosion, fatigue, corrosion-fatigue and stress corrosion cracking, have long been recognized as the principal degradation and failure mechanisms of vehicle components and systems under combined mechanical and corrosive environmental conditions. The combination of fluid flow, introduced by components such as advanced injectors, and corrosive environment leads to corrosion-erosion failure mechanism. These failure mechanisms are strongly material, environment, and loading dependent. How to characterize, screen, rank and select the materials in corrosion resistance is a big challenge posed to materials scientists and engineers. In this paper, the common corrosion related failure mechanisms appearing in auto exhaust systems are reviewed first.