This article provides an outline of the issues to consider in performing a probabilistic life assessment. It begins with an historical background and introduces the most common methods. The article then describes those methods covering subjects such as the required random variable definitions, how uncertainty is quantified, and input for the associated random variables, as well as the characterization of the response uncertainty. Next, it focuses on specific and generic uncertainty propagation techniques: first- and second-order reliability methods, the response surface method, and the most frequently used simulation methods, standard Monte Carlo sampling, Latin hypercube sampling, and discrete probability distribution sampling. Further, the article discusses methods developed to analyze the results of probabilistic methods and covers the use of epistemic and aleatory sampling as well as several statistical techniques. Finally, it illustrates some of the techniques with application problems for which probabilistic analysis is an essential element.

This article discusses statistical concepts that form the basis of most of the following articles on specific areas of applied statistics and data analysis. It reviews some of the basic concepts that must be understood to successfully apply the statistical procedures, including probability, random variables, degrees of freedom, confidence limits and intervals, and reliability. Descriptive statistics, measures of central tendency, confidence limits and intervals, and degrees of freedom are also discussed.

The six types of statistical distributions are normal distribution, log normal distribution, Weibull distribution, exponential distribution, binomial distribution, and Poisson distribution. This article discusses the applicability of each distribution, providing information on the probability density function, cumulative distribution function, population mean and variance, and parameter and percentile estimation.

This article presents definitions, equations, and notational conventions that are used widely in statistical analysis. It provides information on a basic framework for the selection of a statistical test. The article outlines the basic elements common to all statistical tests. Illustrations of specific statistical tests and the concept of confidence limits are introduced. The article provides an overview of sampling issues, with guidance on both selecting a sampling method and determining the number of units to sample. One-way analysis of the variance, correlation, and simple regression are also illustrated.

This article discusses some of the statistical aspects of design from an engineer's perspective. It reviews the commonly used statistical terms and distributions for providing some guidance on the practical engineering applications of these distributions. The article describes the basic statistical procedures that can be used to address variability and uncertainty in an engineering analysis. It contains a table that lists the relevant statistics standards published by the American Society of Testing and Materials.

This article describes the historical background, uncertainties in structural parameters, classifications, and application areas of probabilistic analysis. It provides a discussion on the basic definition of random variables, some common distribution functions used in engineering, selection of a probability distribution, the failure model definition, and a definition of the probability of failure. The article also explains the solution techniques for special cases and general solution techniques, such as first-second-order reliability methods, the advanced mean value method, the response surface method, and Monte Carlo sampling. A brief introduction to importance sampling, time-variant reliability, system reliability, and risk analysis and target reliabilities is also provided. The article examines the various application problems for which probabilistic analysis is an essential element. Examples of the use of probabilistic analysis are presented. The article concludes with an overview of some of the commercially available software programs for performing probabilistic analysis.

Brittle materials, such as ceramics, intermetallics, and graphites, are increasingly being used in the fabrication of lightweight components. This article focuses on the design methodologies and characterization of certain material properties. It describes the fundamental concepts and models associated with performing time-independent and time-dependent reliability analyses for brittle materials exhibiting scatter in ultimate strength. The article discusses the two-parameter and three-parameter Weibull distribution for representing the underlying probability density function for tensile strength. It reviews life prediction reliability models used for predicting the life of a component with complex geometry and loading. The article outlines reliability algorithms and presents several applications to illustrate the utilization of these reliability algorithms in structural applications.

This article describes design factors for products used in engineering applications. The article groups these factors into three categories: functional requirements, analysis of total life cycle, and other major factors. These categories intersect and overlap, constituting a major challenge in engineering design. Performance specifications, risk and hazard analysis, design process, design for manufacture and assembly, design for quality, reliability in design, and redesign are considered for functional requirements. Life-cycle analysis considers raw-material extraction from the earth and product manufacture, use, recycling (including design for recycling), and disposal. The other major factors considered include evaluation of the current state of the art for a given design, designing to codes and standards, and human factors/ergonomics.

The misorientation of a boundary of a growing grain is defined not only by its crystallography but also by the crystallography of the grain into which it is growing. This article focuses on the Monte Carlo Potts model that is typically used to model grain growth, Zener-Smith pinning, abnormal grain growth, and recrystallization. It introduces the basics of the model, providing details of the dynamics, simulation variables, boundary energy, boundary mobility, pinning systems, and stored energy. The article explains how to incorporate experimental parameters and how to validate the model by comparing the observed behavior quantitatively with theory. The industrial applications of the model are also discussed. The article also provides a wide selection of the algorithms for implementing the Potts model, such as boundary-site models, n -fold way models, and parallel models, which are needed to simulate large-scale industrial applications.

Reliability is a measure of the capacity of equipment or systems to operate without failure in the service environment. This article focuses on reliability in design and presents equations governing the instantaneous failure rate, general reliability function, mean time to failure, mean time between failures, and useful life period. The article describes the calculation of reliabilities for series and parallel arrangements of a complex system. It provides a comparison of probabilistic and deterministic design and concludes with a discussion on reliability growth.

The process of optimization involves choosing the best solution from a pool of potential candidate solutions. This article provides a description of some classes of problems and the optimization methods that solve them. These problems include the deterministic single-objective problem, the deterministic multiobjective problem, and the nondeterministic, stochastic optimization problem. The article presents several complementary approaches to solve a wide variety of single-objective and multiobjective mechanical engineering applications. Multiobjective optimization study and stochastic optimization studies are also discussed.

This article examines how cellular automaton (CA) can be applied to the simulation of static and dynamic recrystallization. It describes the steps involved in the CA simulation of recrystallization. These include defining the CA framework, generating the initial microstructure, distributing nuclei of recrystallized grains, growing the recrystallized grains, and updating the dislocation density. The article concludes with information on the developments in CA simulations.

Vibroacoustic analysis of mechanical systems has an important role in the engineering discipline. This can be used as a monitoring tool to obtain insights about the condition of a system, identify its probable defects, and determine the time window that the maintenance should happen. This article introduces the basics of signal processing in time, frequency, and time-frequency domains. It focuses on statistical analysis of the time-domain data. Various measures of data distribution and variability are pointed out. Important signal-processing functions in the frequency domain are presented and explained with examples. The article discusses and clarifies the benefits of time-frequency domain based on short-time Fourier transform with some practical applications. The article presents the most frequently used statistical functions. It concludes with information on some real-world applications of vibroacoustic analysis.

Crystallographic texture measurement and analysis is an important tool for correlating material properties with microstructural features. This article describes the general approach to quantifying crystallographic texture, namely, the collection of statistical data from grain measurements and subsequent analysis based on Euler plots (i.e., pole figures), orientation distribution functions, and stereographic projections. Using detailed illustrations and examples, it explains the significance of preferred crystallographic orientations and their influence on properties and material behavior. The article also discusses sample selection and preparation as well as the challenges and limitations of various methods.

This article provides information on life assessment strategies and conceptually illustrates the interplay of nondestructive evaluation (NDE) and fracture mechanics in the damage tolerant approach. It presents information on probability of detection (POD) and probability of false alarm (PFA). The article describes the damage tolerance approach to life management of cyclic-limited engine components and lists the commonly used nondestructive evaluation methods. It concludes with an illustration on the role of NDE, as quantified by POD, in fully probabilistic life management.

This article describes the mechanisms involved in creating texture for various metal-fabrication processes, namely, solidification, deformation, recrystallization and grain growth, thin-film deposition, and imposition of external magnetic fields. It discusses two experimental and analytical approaches for experimental determination of texture: one using classical diffraction and pole figure measurement techniques and the other using individual orientation measurements. The article also provides information on microtexture, grain-boundary character, and texture gradients. It concludes with information on texture evolution through modeling.

This article presents an approach to manage the uncertainty present in materials design. It describes inductive and deductive approaches to deal with uncertainty. The article focuses on providing an understanding of the opportunities for managing uncertainty and the decisions that influence the accuracy of the results. A design of experiments (DOE) represents a sequence of experiments to be performed, expressed in terms of factors set at specified levels. The article discusses the two types of DOEs: the full factorial design and the fractional factorial design. It explains the factors to be considered when selecting a procedure for propagating uncertainty. The article lists the categories of the popular types of uncertainty propagation methods, including simulation-based methods, local expansion methods, and numerical integration-based methods.

Both nondestructive testing (NDT) and nondestructive evaluation (NDE) use noninvasive measurement techniques to gain information about defects and various properties of materials, components, and structures. This article begins with a discussion on the historical development of quantitative measurement techniques, evaluation reliability, and quantitative interpretation of nondestructive inspection methods. The common nondestructive evaluation methods, along with their uses and limitations, are summarized in a table. The article conceptually illustrates the interplay of NDE and fracture mechanics in the damage tolerant approach. It concludes with information on pressure vessel applications that can be separated into three protocols used by military nuclear power, commercial nuclear power, and non-nuclear pressure vessels and/or fired boilers.

This article primarily considers the problem of sampling bulk materials, including minerals, metals, environmentally important substances, and industrial raw materials and waste products. It provides useful information on sample types, sampling plan, optimizing sampling resources, practical aspects of sampling, and how to ensure the quality of sampling.

This article reviews the planning of fatigue experiments, including the structure of a test plan, randomization, and nuisance variables. The statistical characterization of the S/N (stress/life) or e/N (strain/life) response of a single material tested under a single condition is discussed. The techniques for defining a mean fatigue curve and evaluating scatter or variability about that mean are explained. The article presents the standard techniques for statistical characterization of the fatigue strength or fatigue limit of a single material by use of the Probit method, the up-and-down (staircase) method, and two-point procedures. Stress-level selection methods are also presented. The article discusses the comparison of the fatigue behavior of two or more materials for data generated at a single stress or strain level. Treatments to compare data generated over a range of stress or strain levels are included. The article also summarizes the consolidation of fatigue data generated at different conditions.