Search Results for data normalization

This article provides a summary of the concepts discussed in the articles under the Section “Introduction to Testing and Certification” in ASM Handbook, Volume 21: Composites. The Section covers the basics of what to test, how to test, and how many to test to obtain specific properties of common advanced composite materials.

Composites are complex engineered materials that often behave differently than common isotropic materials. Before testing a composite material, or before ordering or supervising such testing, the responsible party should review certain considerations. This article provides an overview of such considerations, namely, the differences between the testing of composites and testing of isotropic materials, role of certification agencies and importance of their involvement, building-block approach to composites testing, determining the purpose of testing, normalizing results, and statistical data reduction.

This article discusses the basic approach for predicting the corrosion-fatigue life of structural components. It describes two types of tests that are normally used in combination: cycles-to-failure tests, which focus on crack initiation, and crack propagation tests, which focus on crack growth rates under cyclic load. The article examines corrosion-fatigue cracking along with the effects of cracking due to stress corrosion and hydrogen embrittlement, which often occur together. It explains how test parameters such as loading and environmental conditions impact crack growth mechanisms and data interpretation.

Statistical analysis of mechanical property data is the most reliable method for determination of minimum design allowables. This article describes the general procedures used to determine design allowables. It provides information on the determination of a distribution form. The article presents statistical methods which help in determining design allowables. These methods include direct computation for normal distribution, direct computation for an unknown distribution, computation of derived properties, and regression analysis. The article concludes with information on low- and elevated-temperature design properties.

Properties of an engineering material have a characteristic range of values that are conveniently displayed on materials selection charts. This article describes the plotting of data on these charts. It discusses the features of various types of material property charts, namely, modulus-density, strength-density, fracture toughness-density, modulus-strength, specific stiffness-specific strength, fracture toughness-modulus, fracture toughness-strength, loss coefficient-modulus, thermal conductivity-thermal diffusivity, thermal expansion-thermal conductivity, thermal expansion-modulus, and normalized strength-thermal expansion charts. The article examines the use of material property charts in presenting information in a compact and easily accessible manner.

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 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 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.

This article discusses the need for design allowables, development of design allowables, and important factors that affect the selection of the allowable. It provides a comparison between lamina and laminate allowables. The article discusses laminate results and specific techniques used in the statistical development of allowable values.