For brevity, the class of “composite materials” in this paper is intended to refer to one of its subclasses, namely, the fiber-reinforced composite materials. In developing composite material property databases, three categories of data are needed. Category 1 consists of all raw test data with detailed information on specimen preparation, test machine description, specimen size and number per test, test loading history including temperature and humidity, etc., test configuration such as strain gage type and location, grip description, etc. Category 2 is the design allowable derived from information contained in Category 1 without making further experimental tests. Category 3 is the same design allowable for applications such that new experiments prescribed by user to obtain more reliable properties for the purpose on hand. At present, most handbook-based composite material property databases contain incomplete information in Category 1 (raw data), where a user is given only the test average values of properties such as longitudinal, transverse, and shear moduli, major and out-of-plane Poisson’s ratios, longitudinal tensile and compressive, transverse tensile and compressive, and shear strengths, inter-laminar shear strength, ply thickness, hygrothermal expansion coefficients, specific gravity, fiber volume fraction, etc. The presentation in Category 1 ignores the inclusion of the entire test environment description necessary for a user to assess the uncertainty of the raw data. Furthermore, the design allowable listed in Category 2 is deterministically obtained from Category 1 and the user is given average design allowable without uncertainty estimation. In this paper, it is presented a case study where average design allowable failure envelopes of open hole specimens were obtained numerically for two different quasi-isotropic carbon fiber-epoxy laminates using the appropriate Category 1 data. Using the method of statistical design of experiments, it is then showed how the average design allowable can be supplemented with uncertainty estimates if the Category 1 database is complete. Application of this methodology to predicting reliability of composite structures is discussed.
