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.

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.

There are two parts to deal with uncertainty in fatigue design: determining the distributions of possible values for all uncertain inputs and calculating the probability of failure due to all the uncertain inputs. This article discusses the sources of uncertainty in a fatigue analysis, such as the material properties, distribution of applied stress levels within a given environment, environments or loading intensities, and modeling or prediction. It presents a probabilistic approach for analyzing the uncertainties and determining the level of reliability (probability of failure).

Risk and hazard analysis can be effectively used during design reviews to provide valuable feedback to the design to avoid failures. This article discusses the types of risks, namely, real risk, statistical risk, predicted risk, and perceived risk. It describes the principle and technical methods of risk/hazard analysis practiced in the industry to identify possible hazards and the resources necessary to avoid or reduce risks. These methods include the failure mode and effect analysis, fault tree analysis, event tree analysis, risk/benefit analysis, safety analysis, and probabilistic estimates.

This article describes concepts and tools that can be used by the failure analyst to understand and address deformation, cracking, or fracture after a stress-related failure has occurred. Issues related to the determination and use of stress are detailed. Stress is defined, and a procedure to deal with stress by determining maximum values through stress transformation is described. The article provides the stress analysis equations of typical component geometries and discusses some of the implications of the stress analysis relative to failure in components. It focuses on linear elastic fracture mechanics analysis, with some mention of elastic-plastic fracture mechanics analysis. The article describes the probabilistic aspects of fatigue and fracture. Information on crack-growth simulation of the material is also provided.

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.

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 provides an overview of the structural design process and discusses the life-limiting factors, including material defects, fabrication practices, and stress. It details the role of a failure investigator in performing nondestructive inspection. The article provides information on fatigue life assessment, elevated-temperature life assessment, and fitness-for-service life assessment.

Life assessment of structural components is used to avoid catastrophic failures and to maintain safe and reliable functioning of equipment. The failure investigator's input is essential for the meaningful life assessment of structural components. This article provides an overview of the structural design process, the failure analysis process, the failure investigator's role, and how failure analysis of structural components integrates into the determination of remaining life, fitness-for-service, and other life assessment concerns. The topics discussed include industry perspectives on failure and life assessment of components, structural design philosophies, the role of the failure analyst in life assessment, and the role of nondestructive inspection. They also cover fatigue life assessment, elevated-temperature life assessment, fitness-for-service life assessment, brittle fracture assessments, corrosion assessments, and blast, fire, and heat damage assessments.

The goals of modeling diffusion bonding can be regarded as twofold: to optimize the selection of the process variables for a given material and to provide an understanding of the mechanisms by which bonding is achieved. This article describes the existing models of diffusion bonding with an assumption that the surfaces to be joined are free of contaminants and oxide, that bonding occurs between similar materials, and that the materials are single-phase metals. It discusses the mechanisms considered for diffusion bonding and limitations of existing models.

Particle size and size distribution have a significant effect on the behavior of metal powders during their processing. This article provides an overview of the sample preparation process for particle size measurement, which is a key step in the measurement of particle size distributions. Common particle size measuring techniques discussed in this article include sieve analysis, quantitative image analysis, laser diffraction, sedimentation methods, aerodynamic time-of-flight method, electrical zone sensing, and photon correlation spectroscopy. The advantages and disadvantages of these methods are reviewed.

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.

Fatigue crack growth rate testing and data analysis are performed to characterize the crack propagation resistance of material environment combinations in order to predict crack growth life under anticipated stress histories. This article presents analyses performed on the numerical output of crack growth rate tests, including the analysis framework for modeling fatigue crack growth rate data. It describes the numerical methods for calculating da/dN as a function of stress intensity factor. The article discusses the principles in fatigue crack growth damage analysis.

This article details factors that have been used for evaluating the susceptibility of alloys to stress-corrosion cracking. Many considerations impacting the validity and accuracy of information gathered from laboratory testing programs are reviewed. The article highlights the main characteristics of probability distributions, such as normal distribution, log-normal distribution, exponential distribution, Poisson distribution, and extreme-value distribution. It also provides information on the statistical concepts to produce effective test programs.

The design process for ceramic materials is more complex than that of metals because of low-strain tolerance, low fracture toughness and brittleness. The application of structural ceramics to engineering systems hinges on the functional benefits to be derived and is manifested in the conceptual design for acceptable reliability. This article discusses the design considerations for the use of structural ceramics for engineering applications. It describes the conceptual design and deals with fast fracture reliability, lifetime reliability, joints, attachments, interfaces, and thermal shock in detailed design procedure. The article provides information on the proof testing of ceramics, and presents a short note on public domain software that helps determine the reliability of a loaded ceramic component. The article concludes with several design scenarios for gas turbine components, turbine wheels, ceramic valves, and sliding parts.

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 aviation industry has been driving the use of additive manufacturing (AM), moving from one-off demonstrator or pathfinder components toward higher-volume serial production applications. This article presents an introduction to AM in aviation, explaining how aviation requirements apply to AM. It also presents advancements, standards, and future expectations of aviation.